Malawi - Demographic and Health Survey - 2001

Publication date: 2001

2000Demographic andHealth Survey M alaw i 2000 D em ographic and H ealth Survey Malawi Malawi Demographic and Health Survey 2000 National Statistical Office Zomba, Malawi ORC Macro Calverton, Maryland, USA August 2001 This report presents findings from the 2000 Malawi Dem ographic and Health Survey (2000 MDHS), which was implemented by the National Statistical Office. ORC Macro (DHS) furnished technical assistance in the design and implementation of the survey. Funding for the 2000 MDHS survey was provided by the United States Agency for International Development (USAID/Malawi), the Department for International Development (DfID/Malawi), and the United Nations Children’s Fund (UNICEF/Malawi). The 2000 MDHS is part of a worldwide MEASURE Demographic and Health Surveys (DHS+) Project, which is designed to collect, analyse, and disseminate data on fertility, family planning, maternal and child health, HIV/AIDS, and other topics in health and population. Additional information about the Malawi DHS may be obtained from: National Statistical Office P.O. 333 Zomba, Malawi Telephone: 524-377 Fax 525-130 E-mail: demography@statis tics.gov.mw Internet: www.nso.malawi.net Information about the MEASURE DHS+ project may be obtained from: ORC Macro 11785 Beltsville Drive Suite 300 Calverton, MD 20705 Telephone: 301-572-0200 Fax: 301-572-0999 E-mail: reports@macroint.com Internet: www.measuredhs.com Suggested citation: National Statistica l Office [Malawi] and ORC Macro. 2001. Malawi Demographic and Health Survey 2000. Zomba, Malawi and Calverton, Maryland, USA: National Statistical Office and ORC Macro. Contents * iii CONTENTS Page TABLES AND FIGURES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . vii FOREWORD . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xv SUMMARY OF FINDINGS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xvii MAP OF MALAWI . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xxii CHAPTER 1 INTRODUCTION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 1.1 Geography, History, and the Economy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 Geography . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 History . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 Economy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 1.2 Population . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 1.3 Objectives of the Survey . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 1.4 Organisation of the Survey . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 1.5 Sample Design . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 1.6 Questionnaires . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 1.7 Training . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 1.8 Data Collection and Data Processing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 CHAPTER 2 CHARACTERISTICS OF HOUSEHOLDS AND HOUSEHOLD MEMBERS . . . 9 2.1 Household Population by Age, Sex, and Residence . . . . . . . . . . . . . . . . . . . . . . . 9 2.2 Household Composition . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9 2.3 Fosterhood and Orphanhood . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11 2.4 Educational Level of Household Population . . . . . . . . . . . . . . . . . . . . . . . . . . . 12 2.5 School Attendance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14 2.6 Child Labour . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16 2.7 Housing Characteristics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17 CHAPTER 3 CHARACTERISTICS OF RESPONDENTS AND WOMEN’S STATUS . . . . . . 21 3.1 Characteristics of Survey Respondents . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21 3.2 Educational Attainment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23 3.3 Literacy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24 3.4 Access to Mass Media . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24 3.5 Women’s Employment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27 3.6 Form of Women’s Earnings . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29 3.7 Control over Women’s Earnings and Women’s Contribution to Household Expenditures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30 3.8 Measures of Women’s Empowerment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32 3.9 Use of Tobacco . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37 3.10 Birth Registration . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38 iv * Contents Page CHAPTER 4 FERTILITY LEVELS AND TRENDS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39 4.1 Current Fertility Levels and Trends . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39 4.2 Children Ever Born . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 44 4.3 Birth Intervals . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45 4.4 Age of Mothers at First Birth . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 46 4.4.1 Adolescent Fertility . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 47 CHAPTER 5 FERTILITY REGULATION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49 5.1 Knowledge of Contraceptive Methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49 5.2 Knowledge of Contraceptive Methods by Background Characteristics . . . . . . . . 50 5.3 Ever Use of Contraception . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 52 5.4 Current Use of Contraceptive Methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 52 5.5 Current Use of Contraception by Background Characteristics . . . . . . . . . . . . . . 57 5.6 Current Use of Contraceptives by Women’s Status . . . . . . . . . . . . . . . . . . . . . . 60 5.7 Number of Children at First Use of Contraception . . . . . . . . . . . . . . . . . . . . . . 60 5.8 Timing of Female Sterilisation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 62 5.9 Source of Supply . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 62 5.10 Informed Choice . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 63 5.11 Future Use of Contraception . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 65 5.12 Reasons for Not Intending to Use Contraception . . . . . . . . . . . . . . . . . . . . . . . 65 5.13 Preferred Method of Contraception for Future Use . . . . . . . . . . . . . . . . . . . . . . 65 5.14 Exposure to Family Planning Messages on Radio and Television . . . . . . . . . . . 66 5.15 Exposure to Family Planning Messages in Print Media or Drama . . . . . . . . . . . 69 5.16 Exposure to Specific Health and Family Planning Radio Programmes . . . . . . . . 69 5.17 Contact of Nonusers with Family Planning Providers . . . . . . . . . . . . . . . . . . . . 69 5.18 Discussion about Family Planning with Husband . . . . . . . . . . . . . . . . . . . . . . . 73 5.19 Attitudes of Couples toward Family Planning . . . . . . . . . . . . . . . . . . . . . . . . . . 73 CHAPTER 6 OTHER PROXIMATE DETERMINANTS OF FERTILITY . . . . . . . . . . . . . . . . 75 6.1 Marital Status . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 75 6.2 Polygyny . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 76 6.3 Age at First Marriage . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 78 6.4 Age at First Sexual Intercourse . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 80 6.5 Recent Sexual Activity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 81 6.6 Postpartum Amenorrhoea, Abstinence, and Insusceptibility . . . . . . . . . . . . . . . 83 CHAPTER 7 FERTILITY PREFERENCES AND UNMET NEED FOR FAMILY PLANNING . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 87 7.1 Desire for More Children . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 87 7.2 Desire to Limit Childbearing by Background Characteristics . . . . . . . . . . . . . . . 88 7.3 Unmet Need for Family Planning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 89 7.4 Ideal Family Size . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 92 7.5 Wanted and Unwanted Fertility . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 94 Contents * v Page CHAPTER 8 INFANT AND CHILD MORTALITY . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 97 8.1 Definitions, Methodology, and Assessment of Data Quality . . . . . . . . . . . . . . . 97 8.2 Early Childhood Mortality Rates: Levels and Trends . . . . . . . . . . . . . . . . . . . . . 98 8.3 Socioeconomic Differentials in Childhood Mortality . . . . . . . . . . . . . . . . . . . . 100 8.4 Biodemographic Differentials in Childhood Mortality . . . . . . . . . . . . . . . . . . . 101 8.5 Perinatal Mortality . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 103 CHAPTER 9 MATERNAL AND CHILD HEALTH . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 105 9.1 Antenatal Care . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 105 9.2 Assistance and Medical Care at Delivery . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 109 9.3 Caesarean Section and Small Size at Birth . . . . . . . . . . . . . . . . . . . . . . . . . . . 112 9.4 Postnatal Care . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 113 9.5 Vaccinations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 114 9.6 Acute Respiratory Infection . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 117 9.7 Diarrhoeal Disease and Related Findings . . . . . . . . . . . . . . . . . . . . . . . . . . . . 119 9.8 Women’s Perceptions of Problems in Accessing Health Care . . . . . . . . . . . . . . 122 CHAPTER 10 INFANT FEEDING, NUTRITIONAL PRACTISES, AND NUTRITIONAL STATUS AMONG YOUNG CHILDREN AND WOMEN . . . . . . . . . . . . . . 125 10.1 Breastfeeding and Supplementation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 125 10.1.1 Initiation of Breastfeeding . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 125 10.1.2 Age Pattern of Breastfeeding . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 126 10.1.3 Types of Complementary Foods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 129 10.1.4 Frequency of Foods Consumed by Children . . . . . . . . . . . . . . . . . . . . 130 10.1.5 Micronutrients . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 132 10.2 Nutritional Status of Children under Age Five . . . . . . . . . . . . . . . . . . . . . . . . 136 10.2.1 Measures of Nutritional Status in Childhood . . . . . . . . . . . . . . . . . . . 136 10.2.2 Levels of Child Malnutrition . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 137 10.3 Nutritional Status of Women . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 140 CHAPTER 11 AIDS AND OTHER SEXUALLY TRANSMITTED INFECTIONS . . . . . . . . . . 143 11.1 Knowledge of Ways to Prevent HIV/AIDS . . . . . . . . . . . . . . . . . . . . . . . . . . . 144 11.2 Knowledge of Other AIDS-related Issues . . . . . . . . . . . . . . . . . . . . . . . . . . . . 150 11.3 Stigma Associated with AIDS and Acceptability of AIDS-related Messages in the Media . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 151 11.4 Testing for HIV . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 156 11.5 Reports on Recent Sexually Transmitted Infections . . . . . . . . . . . . . . . . . . . . 159 11.6 Treatment-seeking and Other Behaviours in Response to STIs . . . . . . . . . . . . 162 11.7 Number of Sexual Partners . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 165 11.7.1 Married Men and Women . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 166 11.7.2 Unmarried Men and Women . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 167 vi * Contents Page 11.8 Payment for Sexual Relations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 168 11.9 Knowledge of a Source for Condoms . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 168 11.10 Chishango Condoms . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 169 11.11 Use of Condoms . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 172 Condom Use during Commercial Sex . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 174 CHAPTER 12 ADULT AND MATERNAL MORTALITY . . . . . . . . . . . . . . . . . . . . . . . . . . 177 12.1 The Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 177 12.2 Adult Mortality . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 179 12.3 Maternal Mortality . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 181 CHAPTER 13 MALARIA . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 185 13.1 Bednets . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 185 13.1.1 Possession of Bednets . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 186 13.1.2 Use of Bednets . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 187 13.1.3 Insecticide Treatment of Bednets . . . . . . . . . . . . . . . . . . . . . . . . . . . . 188 13.2 Intermittent Treatment During Pregnancy . . . . . . . . . . . . . . . . . . . . . . . . . . . 189 13.3 Treatment of Children with Fever . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 190 13.4 Timing of Antimalarial Response to Child’s Fever . . . . . . . . . . . . . . . . . . . . . . 192 13.5 Initial Response to Child’s Fever . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 193 REFERENCES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 195 APPENDIX A SAMPLE DESIGN . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 197 APPENDIX B SAMPLING ERRORS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 203 APPENDIX C DATA QUALITY TABLES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 225 APPENDIX D SURVEY STAFF . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 231 APPENDIX E QUESTIONNAIRES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 235 APPENDIX F UNICEF WORLD SUMMIT FOR CHILDREN: END-DECADE INDICATORS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 325 Tables and Figures * vii TABLES AND FIGURES Page CHAPTER 1 INTRODUCTION Table 1.1 Demographic indicators . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 Table 1.2 Results of the household and individual interviews . . . . . . . . . . . . . . . . . 6 CHAPTER 2 CHARACTERISTICS OF HOUSEHOLDS AND HOUSEHOLD MEMBERS Table 2.1 Household population by age, sex, and residence . . . . . . . . . . . . . . . . . 10 Table 2.2 Household composition . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11 Table 2.3 Children’s living arrangements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11 Table 2.4 Educational attainment of household population . . . . . . . . . . . . . . . . . 13 Table 2.5 School attendance ratios . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14 Table 2.6 Grade repetition and dropout rates . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15 Table 2.7 Child labour . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17 Table 2.8 Housing characteristics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18 Table 2.9 Household durable goods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19 Figure 2.1 Population pyramid . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10 CHAPTER 3 CHARACTERISTICS OF RESPONDENTS AND WOMEN’S STATUS Table 3.1 Background characteristics of respondents . . . . . . . . . . . . . . . . . . . . . . 22 Table 3.2 Educational attainment by background characteristics . . . . . . . . . . . . . 23 Table 3.3 Literacy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25 Table 3.4 Exposure to mass media . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26 Table 3.5 Employment of women . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28 Table 3.6 Employer and form of earnings . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29 Table 3.7 Decision on use of earnings and contribution of earnings to household expenditures . . . . . . . . . . . . . . . . . . . . . . . . . 31 Table 3.8 Women’s participation in decisionmaking . . . . . . . . . . . . . . . . . . . . . . . 33 Table 3.9 Women’s participation in decisionmaking by background characteristics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34 Table 3.10 Women’s attitude toward wife beating . . . . . . . . . . . . . . . . . . . . . . . . . 35 Table 3.11 Women’s attitude toward refusing sexual relations with husband . . . . . 36 Table 3.12 Use of smoking tobacco . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38 Table 3.13 Knowledge of birth registration . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38 Figure 3.1 Percentage of Men and Women Who Have Had Any Exposure to Mass Media, by Background Characteristics . . . . . . . . . . . . . . . . . . . 27 Figure 3.2 Percent Distribution of Women Age 15-49 Employed in Agricultural Work and in Non-agricultural Work by Type of Earnings . . 30 viii * Tables and Figures Page CHAPTER 4 FERTILITY LEVELS AND TRENDS Table 4.1 Current fertility . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 40 Table 4.2 Fertility by background characteristics . . . . . . . . . . . . . . . . . . . . . . . . . 41 Table 4.3 Trends in fertility . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 42 Table 4.4 Trends in age-specific fertility rates . . . . . . . . . . . . . . . . . . . . . . . . . . . 43 Table 4.5 Children ever born and living . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 44 Table 4.6 Birth intervals . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45 Table 4.7 Age at first birth . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 46 Table 4.8 Median age at first birth by background characteristics . . . . . . . . . . . . 47 Table 4.9 Teenage pregnancy and motherhood . . . . . . . . . . . . . . . . . . . . . . . . . . 48 Figure 4.1 Total Fertility Rates, by Background Characteristics . . . . . . . . . . . . . . . 42 Figure 4.2 Trends in Age-specific Fertility Rates, 1984 FFS, 1992 MDHS, and 2000 MDHS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43 Figure 4.3 Percentage of Women Age 15-49 Who Are Mothers or Are Pregnant with Their First Child, by Level of Education . . . . . . . . . . . . . 48 CHAPTER 5 FERTILITY REGULATION Table 5.1 Knowledge of contraceptive methods . . . . . . . . . . . . . . . . . . . . . . . . . . 50 Table 5.2 Knowledge of contraceptive methods by background characteristics . . . 51 Table 5.3.1 Ever use of contraception: women . . . . . . . . . . . . . . . . . . . . . . . . . . . . 53 Table 5.3.2 Ever use of contraception: men . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 54 Table 5.4.1 Current use of contraception: women . . . . . . . . . . . . . . . . . . . . . . . . . . 55 Table 5.4.2 Current use of contraception: men . . . . . . . . . . . . . . . . . . . . . . . . . . . . 56 Table 5.5.1 Current use of contraception by background characteristics: women . . 58 Table 5.5.2 Current use of contraception by background characteristics: men . . . . 59 Table 5.6 Current use of contraception by women’s status . . . . . . . . . . . . . . . . . . 61 Table 5.7 Number of children at first use of contraception . . . . . . . . . . . . . . . . . . 61 Table 5.8 Timing of sterilisation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 62 Table 5.9 Source of contraception . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 63 Table 5.10 Informed choice . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 64 Table 5.11 Future use of contraception . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 65 Table 5.12 Reason for not intending to use contraception . . . . . . . . . . . . . . . . . . . 66 Table 5.13 Preferred method of contraception for future use . . . . . . . . . . . . . . . . . 66 Table 5.14.1 Exposure to family planning messages on radio and television: women 67 Table 5.14.2 Exposure to family planning messages on radio and television: men . . 68 Table 5.15 Exposure to family planning messages in print media . . . . . . . . . . . . . . 70 Table 5.16.1 Exposure to radio programs on health and family planning: women . . . 71 Table 5.16.2 Exposure to radio programs on health and family planning: men . . . . . 71 Table 5.17 Contact of nonusers with family planning providers . . . . . . . . . . . . . . . 72 Table 5.18 Discussion of family planning with husband . . . . . . . . . . . . . . . . . . . . . 73 Table 5.19 Attitudes of couples toward family planning . . . . . . . . . . . . . . . . . . . . . 74 Figure 5.1 Percentage of Currently Married Women Using Contraception, by Method Type, 1992 MDHS, 1996 MKAPH, 2000 MDHS . . . . . . . . . . 57 Tables and Figures * ix Page CHAPTER 6 OTHER PROXIMATE DETERMINANTS OF FERTILITY Table 6.1 Current marital status . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 75 Table 6.2 Number of co-wives and wives . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 77 Table 6.3 Age at first marriage . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 78 Table 6.4 Median age at first marriage . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 79 Table 6.5 Age at first sexual intercourse . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 80 Table 6.6 Median age at first sexual intercourse . . . . . . . . . . . . . . . . . . . . . . . . . . 81 Table 6.7 Recent sexual activity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 82 Table 6.8 Postpartum amenorrhoea, abstinence, and insusceptibility . . . . . . . . . . 84 Table 6.9 Median duration of postpartum insusceptibility by background characteristics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 85 Figure 6.1 Percentage of Currently Married Men in a Polygynous Marriage, by Background Characteristics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 77 CHAPTER 7 FERTILITY PREFERENCES AND UNMET NEED FOR FAMILY PLANNING Table 7.1 Fertility preferences by number of living children . . . . . . . . . . . . . . . . . 88 Table 7.2 Desire to limit childbearing by background characteristics . . . . . . . . . . 90 Table 7.3 Need for family planning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 91 Table 7.4 Ideal and actual number of children . . . . . . . . . . . . . . . . . . . . . . . . . . . 93 Table 7.5 Mean ideal number of children by background characteristics . . . . . . . 94 Table 7.6 Fertility planning status . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 94 Table 7.7 Wanted fertility rates . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 95 Figure 7.1 Percentage of Currently Married Men and Women Who Have Had Two Children Who Want to End Childbearing . . . . . . . . . . . 89 CHAPTER 8 INFANT AND CHILD MORTALITY Table 8.1 Early childhood mortality rates . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 98 Table 8.2 Early childhood mortality by socioeconomic characteristics . . . . . . . . 100 Table 8.3 Early childhood mortality by demographic characteristics . . . . . . . . . 102 Table 8.4 Perinatal mortality . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 104 Figure 8.1 Trends in Infant and Under-five Mortality, 1992 MDHS and 2000 MDHS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 99 Figure 8.2 Under-five Mortality by Biodemographic Characteristics . . . . . . . . . . . 102 CHAPTER 9 MATERNAL AND CHILD HEALTH Table 9.1 Antenatal care . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 106 Table 9.2 Number of antenatal care visits and stage of pregnancy . . . . . . . . . . . 107 Table 9.3 Antenatal care content . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 108 x * Tables and Figures Page Table 9.4 Place of delivery . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 109 Table 9.5 Assistance during delivery . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 111 Table 9.6 Delivery characteristics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 113 Table 9.7 Vaccinations by source of information . . . . . . . . . . . . . . . . . . . . . . . . 115 Table 9.8 Vaccinations by background characteristics . . . . . . . . . . . . . . . . . . . . 116 Table 9.9 Prevalence and treatment of acute respiratory infection . . . . . . . . . . 118 Table 9.10 Disposal of children’s stools . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 119 Table 9.11 Prevalence of diarrhoea . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 120 Table 9.12 Knowledge of ORS packets . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 120 Table 9.13 Diarrhoea treatment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 121 Table 9.14 Feeding practices during diarrhoea . . . . . . . . . . . . . . . . . . . . . . . . . . . 122 Table 9.15 Perceived problems in accessing women’s health care by background characteristics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 123 Figure 9.1 Percentage of Births for Which Women Received Medical Assistance at Delivery, by Urban-rural Residence and Selected Districts . . . . . . . 112 Figure 9.2 Percentage of Children Age 12-23 Months Who Are Fully Vaccinated, by Background Characteristics . . . . . . . . . . . . . . . . . . . . . 117 CHAPTER 10 INFANT FEEDING, NUTRITIONAL PRACTISES, AND NUTRITIONAL STATUS AMONG YOUNG CHILDREN AND WOMEN Table 10.1 Initial breastfeeding . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 126 Table 10.2 Breastfeeding status by child’s age . . . . . . . . . . . . . . . . . . . . . . . . . . . 127 Table 10.3 Median duration and frequency of breastfeeding . . . . . . . . . . . . . . . . 128 Table 10.4 Foods consumed by children in preceding 24 hours . . . . . . . . . . . . . . 129 Table 10.5 Frequency of foods consumed by children in preceding 24 hours . . . . 131 Table 10.6 Micronutrient intake of children . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 133 Table 10.7 Micronutrient intake among mothers . . . . . . . . . . . . . . . . . . . . . . . . . 135 Table 10.8 Nutritional status of children by demographic characteristics . . . . . . . 138 Table 10.9 Nutritional status of women by background characteristics . . . . . . . . 141 Figure 10.1 Percentage of Children under Age 5 Who Live in Households That Use Adequately Iodised Salt . . . . . . . . . . . . . . . . . . . 134 Figure 10.2 Percentage of Children with Low Height-for-Age, Low Weight-for-Height, Low Weight-for-Age, by Age of Child . . . . . . . . . . 139 Figure 10.3 Prevalence of Chronic Energy Deficiency (Percent with BMI < 18.5) among Women Age 15-49, for Selected Districts . . . . . . 142 CHAPTER 11 AIDS AND OTHER SEXUALLY TRANSMITTED INFECTIONS Table 11.1 Knowledge of AIDS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 145 Table 11.2.1 Knowledge of ways to avoid HIV/AIDS: women . . . . . . . . . . . . . . . . . 146 Table 11.2.2 Knowledge of ways to avoid HIV/AIDS: men . . . . . . . . . . . . . . . . . . . 146 Table 11.3.1 Knowledge of programmatically important ways to avoid HIV/AIDS: women . . . . . . . . . . . . . . . . . . . . . . . . . . . . 148 Tables and Figures * xi Page Table 11.3.2 Knowledge of programmatically important ways to avoid HIV/AIDS: men . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 149 Table 11.4 Knowledge of HIV/AIDS-related issues . . . . . . . . . . . . . . . . . . . . . . . . 150 Table 11.5 Discussion of HIV/AIDS with spouse/partner . . . . . . . . . . . . . . . . . . . 151 Table 11.6.1 Social aspects of HIV/AIDS prevention and mitigation: women . . . . . 152 Table 11.6.2 Social aspects of HIV/AIDS prevention and mitigation: men . . . . . . . . 153 Table 11.7 Discussion of HIV/AIDS in the media . . . . . . . . . . . . . . . . . . . . . . . . . 155 Table 11.8.1 Testing for HIV: women . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 157 Table 11.8.2 Testing for HIV: men . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 158 Table 11.9.1 Self-reporting of sexually transmitted infections and STI symptoms: women . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 160 Table 11.9.2 Self-reporting of sexually transmitted infections and STI symptoms: men . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 161 Table 11.10.1 Source of treatment of STIs: women . . . . . . . . . . . . . . . . . . . . . . . . . . 162 Table 11.10.2 Source of treatment of STIs: men . . . . . . . . . . . . . . . . . . . . . . . . . . . . 163 Table 11.11.1 Efforts to protect partners from infection: women with STIs . . . . . . . . 164 Table 11.11.2 Efforts to protect partners from infection: men with STIs . . . . . . . . . . 165 Table 11.12 Number of sexual partners: married women and men . . . . . . . . . . . . 166 Table 11.13 Number of sexual partners: unmarried women and men . . . . . . . . . . 167 Table 11.14 Payment for sexual relations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 169 Table 11.15 Knowledge of male condoms . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 170 Table 11.16 Knowledge of Chishango brand condom . . . . . . . . . . . . . . . . . . . . . . . 171 Table 11.17.1 Use of condoms: women . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 172 Table 11.17.2 Use of condoms: men . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 173 Table 11.18 Use of condoms during commercial sex . . . . . . . . . . . . . . . . . . . . . . . 175 Figure 11.1 Percentage of Women and Men Who Think That An HIV-positive Individual Who Works with Others in a Shop, Office, or Farm Should be Allowed to Continue Working, by Level of Education . . . . . 154 Figure 11.2 Percentage of Respondents with a Need (Met and Unmet) for HIV-Testing Services, by Sex and (among Women) by Level of Education . . . . . . . . . . . . . . 159 Figure 11.3 Percentage of Men and Women Who Could “Get a Condom If They Wanted To,” by Level of Education . . . . . . . . . . . . . . . . . . . . . 171 Figure 11.4 Percentage of Women and Men Who Used a Condom at Last Sex with a Noncohabitating (High Risk) Partner, by Urban-rural Residence . . . . . . . . . . . . . . . . . . . . . . . . . . . 174 CHAPTER 12 ADULT AND MATERNAL MORTALITY Table 12.1 Data on siblings: completeness of reported data . . . . . . . . . . . . . . . . . 178 Table 12.2 Adult mortality rates . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 179 Table 12.3 Direct estimates of maternal mortality . . . . . . . . . . . . . . . . . . . . . . . . 181 Figure 12.1 Trends in Age-specific Mortality among Women 15-49 . . . . . . . . . . . . 180 Figure 12.2 Trends in Age-specific Mortality among Men 15-49 . . . . . . . . . . . . . . 180 xii * Tables and Figures Page CHAPTER 13 MALARIA Table 13.1 Possession and use of bednets . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 186 Table 13.2 Bednet age and insecticide treatment for bednets . . . . . . . . . . . . . . . . 188 Table 13.3 Intermittent treatment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 190 Table 13.4 Treatment of children with fever . . . . . . . . . . . . . . . . . . . . . . . . . . . . 191 Table 13.5 Promptness of treatment of children with fever . . . . . . . . . . . . . . . . . 193 Table 13.6 Initial response to fever . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 194 Figure 13.1 Percentage of Children Under Age 5 and Women Age 15-49 Who Slept under a Bednet on the Night Before the Survey . . . . . . . . . 187 Figure 13.2 Among Children under Age 5 with Fever in 2 Weeks Preceding Survey, the Percentage Who Were Treated with an Antimalarial Drug and the Percentage Who Were Taken to a Health Facility . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 192 APPENDIX A SAMPLE DESIGN Table A.1 Sample implementation: women . . . . . . . . . . . . . . . . . . . . . . . . . . . . 201 Table A.1 Sample implementation: men . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 202 Figure A.1 Malawi GPS Data Points . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 200 APPENDIX B SAMPLING ERRORS Table B.1 List of selected variables for sampling errors, Malawi 2000 . . . . . . . . 206 Table B.2 Sampling errors: Total sample, Malawi 2000 . . . . . . . . . . . . . . . . . . . 207 Table B.3 Sampling errors: Urban sample, Malawi 2000 . . . . . . . . . . . . . . . . . . 208 Table B.4 Sampling errors: Rural sample, Malawi 2000 . . . . . . . . . . . . . . . . . . 209 Table B.5 Sampling errors: Northern sample, Malawi 2000 . . . . . . . . . . . . . . . . 210 Table B.6 Sampling errors: Central sample, Malawi 2000 . . . . . . . . . . . . . . . . . 211 Table B.7 Sampling errors: Southern sample, Malawi 2000 . . . . . . . . . . . . . . . . 212 Table B.8 Sampling errors: Blantyre sample, Malawi 2000 . . . . . . . . . . . . . . . . 213 Table B.9 Sampling errors: Karonga sample, Malawi 2000 . . . . . . . . . . . . . . . . 214 Table B.10 Sampling errors: Kasungu sample, Malawi 2000 . . . . . . . . . . . . . . . . 215 Table B.11 Sampling errors: Lilongwe sample, Malawi 2000 . . . . . . . . . . . . . . . . 216 Table B.12 Sampling errors: Machinga sample, Malawi 2000 . . . . . . . . . . . . . . . 217 Table B.13 Sampling errors: Mangochi sample, Malawi 2000 . . . . . . . . . . . . . . . 218 Table B.14 Sampling errors: Mulanje sample, Malawi 2000 . . . . . . . . . . . . . . . . 219 Table B.15 Sampling errors: Mzimba sample, Malawi 2000 . . . . . . . . . . . . . . . . 220 Table B.16 Sampling errors: Salima sample, Malawi 2000 . . . . . . . . . . . . . . . . . 221 Table B.17 Sampling errors: Thyolo sample, Malawi 2000 . . . . . . . . . . . . . . . . . 222 Table B.18 Sampling errors: Zomba sample, Malawi 2000 . . . . . . . . . . . . . . . . . 223 Tables and Figures * xiii Page APPENDIX C DATA QUALITY TABLES Table C.1 Household age distribution . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 225 Table C.2.1 Age distribution of eligible and interviewed women . . . . . . . . . . . . . . 226 Table C.2.2 Age distribution of eligible and interviewed men . . . . . . . . . . . . . . . . 226 Table C.3 Completeness of reporting . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 227 Table C.4 Births by calendar years . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 228 Table C.5 Reporting of age at death in days . . . . . . . . . . . . . . . . . . . . . . . . . . . . 229 Table C.6 Reporting of age at death in months . . . . . . . . . . . . . . . . . . . . . . . . . . 230 APPENDIX F UNICEF WORLD SUMMIT FOR CHILDREN: END-DECADE INDICATORS Table F.1 World Summit for Children: End-decade Indicators . . . . . . . . . . . . . . 327 Foreword * xv FOREWORD This final report presents the major findings of the 2000 Malawi Demographic and Health Survey (MDHS). The 2000 MDHS survey is the second survey of its kind to be conducted in Malawi; the first MDHS was in 1992. The fieldwork was carried out by the National Statistical Office (NSO) from July to November 2000. In 1996, a similar survey on Knowledge, Attitudes, and Practices in Health (MKAPH) was conducted. All three surveys were designed to provide information on indicators of maternal and child health in Malawi. The primary objective of the 2000 MDHS survey was to provide up-to-date information for policymakers, planners, researchers, and programme managers that would allow guidance in the development, monitoring, and evaluation of health programmes in Malawi. Specifically, the 2000 MDHS collected information on fertility levels, nuptiality, fertility preferences, knowledge and use of family planning methods, breastfeeding practices, nutritional status of mothers and children, childhood illnesses and mortality, use of maternal and child health services, malaria, maternal mortality, and HIV/AIDS-related knowledge and behaviours. The 2000 MDHS results present evidence of a decline in fertility, an increase in the use of family planning methods, a decline in infant and under-five mortality, and an increase in adult and maternal mortality since the 1992 MDHS survey. However, the disparity between knowledge and use of family planning remains high. Some of these are critical issues and need to be addressed without delay. I would like to acknowledge the efforts of a number of organisations and individuals who contributed immensely to the success of the survey. First, I would like to acknowledge the financial assistance from the United States Agency for International Development (USAID), the Department for International Development (DfID), United Kingdom, and the United Nations Children’s Fund (UNICEF/Malawi). I would also like to acknowledge ORC Macro for technical backstopping, and the assistance of the staff of the National Statistical Office and the Ministry of Health and Population. Finally, I am grateful to the survey respondents who generously gave their time to provide the information that forms the basis of this report. Charles Machinjili Commissioner for Census and Statistics xvi * Summary of Findings SUMMARY OF FINDINGS The 2000 Malawi Demographic and Health Survey (MDHS) is a nationally represen- tative sample survey covering 14,213 house- holds, 13,220 women age 15-49, and 3,092 men age 15-54. The 2000 MDHS is similar, but much expanded in size and scope, to the 1992 MDHS. The survey was designed to provide information on fertility trends, family planning knowledge and use, early childhood mortality, various indicators of maternal and child health and nutrition, HIV/AIDS, adult and maternal mortality, and malaria control programme indicators. Unlike earlier surveys in Malawi, the 2000 MDHS sample was sufficiently large to allow for estimates of certain indicators to be produced for 11 districts in addition to esti- mates for national, regional, and urban-rural domains. Twenty-two mobile survey teams, trained and supervised by the National Statisti- cal Office, conducted the survey from July to November 2000. FERTILITY Fertility Decline. The 2000 MDHS data indicate that there has been a modest decline in fertility since the 1992 MDHS. The total fertil- ity rate has dropped from 6.7 births per woman, in the period 1990-1992 to 6.3 births in the period 1998-2000. The fertility decline is concentrated amongst older women (age 30 and above); no decline was observed in women under age 30. Large Fertility Differentials. Fertility levels remain high in Malawi, especially in rural parts of the country. The total fertility rate among rural women is 6.7 births per woman compared with 4.5 births in urban areas. Fertil- ity levels are closely related to the socio-eco- nomic status of women. For example, women with no formal education give birth to an average of 7.3 children in their lifetime, com- pared with 3.0 for women who attended sec- ondary school or higher. Among districts over- sampled in the survey, fertility ranges from 4.3 births per woman in Blantyre District to 7.0 or more births in Kasungu, Machinga, and Mangochi districts. Unplanned Fertility. One reason for the persistently high fertility levels is that unplanned pregnancies are still common. Overall, 40 percent of births in the five years prior to the survey were reported to be un- planned; 18 percent were mistimed (wanted later) and 22 percent were unwanted. Un- wanted births are disproportionately high among older women who already have several children. If births associated with mistimed and unwanted pregnancies were avoided alto- gether, the total fertility rate in Malawi would be 5.2 births per woman instead of the actual level of 6.3. Ideal Family Size. Although a reduction in the number of unplanned births would reduce fertility substantially, the average mar- ried Malawian woman age 15-49 or man age 15-54 reports that they would like to have more than five children. Even among those who have yet to start family formation, the reported ideal family size exceeds four children. Childbearing at Young Ages. One-third of adolescent females (age 15-19) have either already had a child or are currently pregnant. This proportion has not changed significantly since the 1992 MDHS. The median age of women at first birth is 19.1 years, meaning that more than half of women have had a child by the time they reach age 20. FAMILY PLANNING Increasing Use of Contraception. A principle cause of the fertility decline in Malawi is the steady increase in contraceptive use over the last decade. The contraceptive prevalence rate (current use of a modern family planning method) has more than tripled since 1992, from 7 to 26 percent of all married women. Summary of Findings * xvii Less effective, traditional methods have become less frequently used during the 1990s. Changing Method Mix. Currently, the most widely used methods among married women are injectable contraceptives (16 per- cent), female sterilisation (5 percent), and the pill (3 percent). This method mix represents a shift in contraceptive use among Malawian women. The rapid increase in use of injectables (from 2 percent in 1992) has made it the predominant method. This, combined with small rises in the use of condoms and female sterilisation, have more than offset small drops in pill and IUD use. Thus, acceptance of new methods of contraception, as well as some method switching, have characterised the 1992- 2000 intersurvey period. Differentials in Family Planning Use. Differentials in current use of family planning are large. Urban women are nearly 60 percent more likely than rural women to be using a modern contraceptive method (38 versus 24 percent). Among districts oversampled in the 2000 MDHS, use of modern contraception is highest in Blantyre District (38 percent) and lowest in Salima District (16 percent). Source of Family Planning Methods. The survey results show that government-run facilities remain the major source for contra- ceptives in Malawi—providing family planning methods to 68 percent of the current users. This represents an increase from 59 percent based on the 1996 MKAPH survey results. The increase in public-sector participation is due in large part to the rapid increase in use of inject- ables, which are provided mostly at govern- ment health centres. Twenty-eight percent of users get their methods from private medical sources, and 4 percent get their methods from other private sources (mostly shops). Community-based distribution agents are involved in providing contraceptives to 2 per- cent of current users. Unmet Need for Family Planning. Women who are exposed to the risk of preg- nancy but who say they would like to delay or limit childbearing and are not using contracep- tion are considered to have an unmet need for family planning services. Unmet need for family planning services has declined from 36 to 30 percent of married women since 1992. Fifty- eight percent of the unmet need is composed of women who want to space their next birth, while the remainder is made up of women who do not want any more children. Although much progress has been made in satisfying women’s need for family planning, half of the total “demand” for contraception remains unmet. CHILD HEALTH AND SURVIVAL Progress in Reducing Early Childhood Mortality. The 2000 MDHS data indicate that mortality of children under age 5 has declined since the early 1990s. During the period 1988- 1992, the under-five mortality rate was 234 deaths per 1,000 live births, compared with 189 per 1,000 for the period 1996-2000. Al- though this represents important progress, the rate of the downward trend is modest and childhood mortality remains at a very high level. Factors discussed as potentially associ- ated with the improved child survival picture are better access to clean water sources, ma- laria control activities, and progress in the education of women (primary caregivers). The risk of child death is not spread evenly across Malawi’s geographic and social landscape. Low educational attainment, young age of mother at birth, and residence in a rural area are factors associated with higher child mortality. Childhood Vaccination Coverage Declines. The 2000 MDHS results show that 70 percent of children age 12-23 months are fully vaccinated. This represents a decline in coverage from 82 percent based on the 1992 MDHS. More detailed examination of the data indicates that the level of vaccination card retention has fallen from 86 to 81 percent suggesting lower levels of contact with child health care providers generally. Furthermore, dropout rates in the polio and DPT multi-dose schedules have worsened. Last, measles vaccine and BCG coverage have declined slightly from levels in the early 1990s. xviii * Summary of Findings Childhood Illnesses. The survey also provides data on some of the more common childhood illnesses and their treatment. A little more than 1 in 4 children under age five had a cough with short, rapid breathing, signs of acute respiratory infection (ARI), in the two weeks before the survey. Of these, 27 percent were taken to a health facility for treatment. In the 1992 MDHS, only 15 percent of children under five were reported to have had ARI in the preceding 2 weeks, and 49 percent of these were taken to health facilities for treatment. One explanation for the rise in reported mor- bidity and decline in use of health facilities for treatment is that caregivers (mostly mothers) are increasingly recognising and reporting less severe cases of ARI in their young children. Further in-depth study is required. Eighteen percent of children under age five were reported to have had diarrhoea in the two weeks preceding the survey, and of these, 62 percent received oral rehydration therapy (either solution prepared from oral rehydration salts (ORS) or increased fluids of some other kind). Most mothers (86 percent) know about the use of ORS packets. Improved Breastfeeding Practices. The 2000 MDHS results show that exclusive breast- feeding of children under 4 months of age has increased to 63 percent from only 3 percent in the 1992 MDHS. Further, the overall median duration of breastfeeding has risen from 21 to 24 months during the same period. Patterns of Feeding in Early Child- hood. After a child is weaned from the breast, which occurs for most children between 18 and 24 months of age, the daily diet tends to stabi- lize at the following pattern: virtually all chil- dren receive grain or cereal-based foods regu- larly; 80 to 85 percent of children receive some fruits or vegetables; 85 to 90 percent get foods rich in vitamin A; about 50 percent receive meats, poultry, fish or eggs; one-third of chil- dren receive beans or other legumes; and 50 to 55 percent get tubers, roots, or plantains. Only 10 to 15 percent of children get some oils or fats added to their daily diet. Micronutrient Supplements. The im- portance of adequate intake of vitamin A in mitigating the severity of childhood illnesses, and thereby reducing mortality, is well docu- mented. Supplementing young children and postpartum women with a capsule containing a high dose of vitamin A is an easy way to ensure adequate intake. The 2000 MDHS data show that 65 percent of children under age five received a vitamin A supplement in the six months preceding the survey, and 42 percent of women delivering a baby in the past five years received a vitamin A supplement within two months after the last birth. The iodine content of salt used in the household was measured in the 2000 MDHS. The results show that 49 percent of children under age five live in households that use salt containing an adequate level of iodine, but this varies from only 22 percent in Machinga District to over 62 percent in Kasungu, Blantyre and Thyolo districts. Nutritional Status of Children. The results show no appreciable change in the nutritional status of children in Malawi since 1992; still, nearly half (49 percent) of the children under age five are chronically mal- nourished or stunted in their growth. Malawi’s Central Region has especially high levels of stunting. Acute malnutrition or wasting re- mains at 5 to 6 percent of children under age five in Malawi. MALARIA CONTROL PROGRAMM E INDICATORS Bednets. The use of insecticide-treated bednets (mosquito nets) is a primary health intervention proven to reduce malaria transmis- sion. The 2000 MDHS found that 13 percent of households own at least 1 bednet, and among these households, the average number of bed- nets owned is 1.6. Bednet possession is more common in the Northern Region and in house- holds of higher socioeconomic status. The data also show that 8 percent of women age 15-49, 7 percent of pregnant Summary of Findings * xix women, 8 percent of children under age five, and 6 percent of men age 15-54 slept under a bednet on the night before the survey. (Note: Most of the survey was conducted during the dry season, when bednet use was probably lower than average.) Intermittent Antimalarial Treatment during Pregnancy. In Malawi, as a protective measure against various adverse outcomes of pregnancy, it is recommended that pregnant women receive a dose of sulpha-pyrimethamine (SP or Fansidar) in the second trimester and then again in the third trimester. The 2000 MDHS findings show that among women who recently gave birth, 68 percent received at least one dose of SP and 29 percent received two doses of SP during the last pregnancy. Treatment of Fever in Children Under Age Five. The survey found that 42 percent of children under age five had a fever in the two weeks preceding the survey. Among febrile children, 35 percent were reported to have been taken to a health facility for treatment and 27 percent of children were given an antimalarial, mostly SP (23 percent). Of those given an antimalarial, 83 percent were given the treatment within zero to one day of the onset of fever. WOMEN’S HEALTH Maternal Health Care. The survey findings indicate that use of antenatal services remains high in Malawi. Ninety-one percent of mothers with births in the last five years re- ceived antenatal care from a health profes- sional (doctor, trained nurse or midwife) at least once. In the 1992 MDHS, the figure was 90 percent. For 56 percent of births, mothers visited antenatal services four or more times. Antenatal care can be more effective in avoid- ing adverse pregnancy outcomes when it is sought early in pregnancy. By the start of the sixth month of pregnancy, 50 percent of preg- nant women have not had a single antenatal care visit. The 2000 MDHS also points to a wide disparity in the quality of antenatal ser- vices among Malawi’s districts and socioeco- nomic strata. Delivery under hygienic conditions and where medical assistance is available decreases the risk of maternal morbidity and mortality. At the national level, 55 percent of births in the five years before the survey were delivered in a health facility. This figure is identical to that reported from the 1992 data. For 7 percent of births occurring outside of a health facility, mothers received a postnatal check on their health. The survey results indicate that 3 percent of births were delivered by caesarean section (C-section). A C-section rate below 5 percent is generally thought to be a reflection of limited access to maternal health services and poten- tially life-saving emergency obstetrical care. Constraints to Use of Health Services. Women in the 2000 MDHS were asked whether certain circumstances constrain their access to and use of health services for themselves. By far, the most serious problems women face regarding use of health services involve trans- portation and cost. Nutritional Status of Women. The 2000 MDHS collected information on the height and weight of all women age 15-49, which allows assessment of the body mass index (BMI), a measure of a woman’s weight relative to her height. The findings point to two important issues in women’s health. First, about 1 in 11 women have a low BMI (too thin), indicating chronic energy (calorie) deficiency, with rural women and women in the Southern Region having the highest prevalence of low BMI. Second, about 1 in 8 women have a very high BMI level, indicating these woman are over- weight or obese. Nearly 1 in 4 urban women are overweight or obese, which places them at increased risk of cardiovascular disease, pregnancy-related complications, and other health problems. Rising Maternal Mortality. The survey collected data allowing measurement of mater- xx * Summary of Findings nal mortality. For the period 1994-2000, the maternal mortality ratio was estimated at 1,120 maternal deaths per 100,000 live births. This represents a rise from 620 maternal deaths per 100,000 estimated from the 1992 MDHS for the period 1986-1992. HIV/AIDS Impact of the Epidemic on Adult Mortality. All-cause mortality has risen by 76 percent among men and 74 percent among women age 15-49 during the 1990s. The age patterns of the increase are consistent with causes related to HIV/AIDS. Improved Knowledge of AIDS Preven- tion Methods. The 2000 MDHS results indi- cate that practical AIDS prevention knowledge has improved since the 1996 MKAPH survey. For example, unprompted awareness that use of condoms prevents HIV transmission has risen from 23 to 55 percent among women and from 47 to 71 percent among men. Generally, knowl- edge of means to prevent HIV/AIDS is lowest in the young, sexually inexperienced, and rural population. Sexual Activity Outside of Marriage. Among married men, 18 percent reported having had sex with someone other than their wives in the last 12 months. Only 1 percent of married women reported having extramarital sex. Among unmarried men who have had sex in the last 12 months, about 1 in 4 reported two or more partners. In contrast, only 1 in 20 unmarried women who have had sex in the last 12 months reported more than 1 partner. First sexual activity continues to occur at a young age. The median age of girls at first sex is 17 years; for boys, first sex occurs at 18 years of age. Patterns in the MDHS data suggest that age at first sex is unchanged or slightly rising for girls but falling for boys. Men in the 2000 MDHS were asked whether they had paid for sex in the last 12 months. The findings indicate that 21 percent of men engage in this high-risk activity, with married men as likely as unmarried men to be involved. Condom Use. One of the main objectives of the National AIDS Control Programme is to encourage consistent and correct use of con- doms, especially in high-risk sexual encounters. The 2000 MDHS data show that condom use with extramarital partners has increased slight- ly since 1996, but that use within marriage has actually declined by a small margin. Among men reporting having had commercial sex (for cash) in the last 12 months, only 35 percent reported using a condom on the last occasion. HIV-testing Experience. The 2000 MDHS data show that 9 percent of women and 15 percent of men have been tested for HIV. However, more than 70 percent of both men and women, while not yet tested, said that they would like to be tested. This represents a very large pool of men and women with an unmet need for HIV-testing services. Knowledge of one’s own HIV status is considered crucial to the adoption of AIDS prevention behaviours and the appropriate responses to mitigate the impact of the epidemic. Map of Malawi * xxi Introduction * 1 INTRODUCTION 1 Louis M. Magombo 1.1 GEOGRAPHY, HISTORY, AND THE ECONOMY GEOGRAPHY Malawi is a landlocked country south of the equator in sub-Saharan Africa. It is bordered to the north and northeast by the United Republic of Tanzania; to the east, south, and southwest by the People’s Republic of Mozambique; and to the west and northwest by the Republic of Zambia. The country is 901 kilometres long and ranges in width from 80 to 161 kilometres. It has a total area of 118,484 square kilometres of which 94,276 square kilometres is land area. The remaining area is mostly composed of Lake Malawi, which is about 475 kilometres long and runs down Malawi’s eastern boundary with Mozambique. Malawi’s most striking topographic feature is the Rift Valley that runs the entire length of the country, passing through Lake Malawi in the Northern and Central regions to the Shire Valley in the south. The Shire River drains the water from Lake Malawi into the Zambezi River in Mozambique. To the west and south of Lake Malawi lie fertile plains and mountain ranges whose peaks range from 1,700 to 3,000 metres above sea level. The country is divided into three regions: the Northern, Central, and Southern regions. There are 27 districts in the country. Six districts are in the Northern Region, nine are in the Central Region, and 12 are in the Southern Region. Administratively, the districts are subdivided into Traditional Authorities (TAs), presided over by chiefs. Traditional Authorities are composed of villages, which are the smallest administrative units and are presided over by village headmen. Malawi has a tropical, continental climate with maritime influences. Rainfall and temperature vary depending on altitude and proximity to the lake. From May to August, the weather is cool and dry. From September to November, the weather becomes hot. The rainy season begins in October or November and continues until April. HISTORY Malawi was under British rule from 1891 until July 1964 under the name of the Nyasaland Protectorate. In 1953, the Federation of Rhodesia and Nyasaland was created, which was composed of three countries, namely, Zimbabwe (then Southern Rhodesia), Zambia (then Northern Rhodesia) and Malawi (then Nyasaland). In July1964, the country became the independent state of Malawi, and it gained republic status in 1966. In 1994, the country became a multiparty state and adopted a strategy to eradicate poverty. Since then the following have been introduced: free primary school education, a free market economy, a bill of rights, and a parliament with three main parties. Over the past ten years, the country has experienced a considerable increase of migrants from rural to urban areas. 2 * Introduction Table 1.1 Demographic indicators Selected demographic indicators, Malawi, 1977, 1987 and 1998 national censuses_______________________________________________________________ Census year____________________________ Index 1977 1987 1998________________________________________________________________ Population Intercensal growth rate Total area (sq km) Land area (sq km) Density (population per sq km) Percentage of urban population Women of child bearing age as a percentage of female population Sex ratio Crude birth rate Total fertility rate Crude death rate Infant mortality rate Life expectancy: Male Female 5,547,460 7,988,507 9,933,868 2.9 3.2 2.0 118,484 118,484 118,484 94,276 94,276 94,276 59 85 105 8.5 10.7 14.0 45.1 44.2 47.2 93 94 96 48.3 41.2 37.9 7.6 7.4 6.2 25.0 14.1 21.1 165 159 121 39.2 41.4 40.0 42.4 44.6 44.0 ECONOMY Malawi has a predominantly agricultural economy. Agricultural produce accounted for 61 percent of Malawi’s exports in 1999: tobacco, tea, and sugar being the major export commodities. The country is largely self-sufficient for food. 1.2 POPULATION The major source of historical demographic data comes from the population censuses. Population censuses have been taken in Malawi during the years 1891, 1901, 1911, 1921, 1926, 1931, 1945, 1956, 1966, 1977, 1987, and 1998. Other sources of population data include nationwide surveys: 1968/69, 1980/81, and 1992/93 National Sample Surveys of Agriculture; the 1970-72 Malawi Population Change Survey; the 1982 Malawi Demographic Survey; the 1983 Malawi Labour Force Survey and Survey of Handicapped Persons; the 1984 Family Formation Survey; the 1992 Malawi Demographic and Health Survey (MDHS); the 1996 Malawi Knowledge, Attitudes, and Practises in Health Survey (MKAPH); and the 1997/98 Integrated Household Survey. Table 1.1 provides some demographic indicators for Malawi based on the previous three censuses. The 1998 Population and Housing Census enumerated a total population of 9.9 million. The population grew from 8.0 million in 1987 representing an increase of 24 percent or an intercensal population growth rate of 2.0 percent per year. Along with population growth has come increasing Introduction * 3 population density from 85 persons per square kilometre in 1987 to 105 persons per square kilometre in 1998. To address problems associated with rapid population growth, the Malawi government adopted a National Population Policy in 1994, which was designed to reduce population growth to a level compatible with Malawi’s social and economic goals (OPC, 1994). The policy’s objectives include the following: to improve family planning and health care programmes, to increase school enrolment with an emphasis on raising the proportion of female students to 50 percent of total enrolment, and to increase employment opportunities—particularly in the private sector. 1.3 OBJECTIVES OF THE SURVEY The principal aim of the 2000 MDHS project is to provide up-to-date information on fertility and childhood mortality levels, nuptiality, fertility preferences, awareness and use of family planning methods, use of maternal and child health services, and knowledge and behaviours related to HIV/AIDS and other sexually transmitted infections. It was designed as a follow-on to the 1992 MDHS survey, a national-level survey of similar scope. The 2000 MDHS survey also strived to collect data that would be comparable to those collected under the international Multiple Indicator Cluster Survey (MICS), sponsored by UNICEF. In broad terms, the 2000 MDHS survey aimed to— C Assess trends in Malawi’s demographic indicators—principally, fertility and mortality C Assist in the evaluation of Malawi’s health, population, and nutrition programmes C Advance survey methodology in Malawi and contribute to national and international databases. In more specific terms, the 2000 MDHS survey was designed to— C Provide data on the family planning and fertility behaviour of the Malawian population and to thereby enable policymakers to evaluate and enhance family planning initiatives in the country. C Measure changes in fertility and contraceptive prevalence and at the same time, study the factors that affect these changes, such as marriage patterns, desire for children, availability of contraception, breastfeeding habits, and important social and economic factors. C Examine basic indicators of maternal and child health and welfare in Malawi, including nutritional status, use of antenatal and maternity services, treatment of recent episodes of childhood illness, and use of immunisation services. A particular emphasis was placed on the area of malaria programmes, including prevention activities and treatment of episodes of fever. C Describe levels and patterns of knowledge and behaviour related to the prevention of HIV/AIDS and other sexually transmitted infections. C Measure the level of adult and maternal mortality at the national level. C Assess the status of women in the country. 4 * Introduction 1.4 ORGANISATION OF THE SURVEY The 2000 MDHS survey was a comprehensive survey that involved several agencies. The National Statistical Office (NSO) had the major responsibility for conducting the survey. The Ministry of Health and Population, the National AIDS Secretariat, the National Economic Council, and the Ministry of Gender also contributed to the development of the questionnaires for the survey. Financial support for the survey was provided by the United States Agency for International Development (USAID), the United Kingdom’s Department for International Development (DfID), and the United Nations Children’s Fund (UNICEF/Malawi). Technical assistance was provided by Macro International Inc., USAID-funded MEASURE DHS+ project (USA). 1.5 SAMPLE DESIGN The 2000 MDHS survey was designed to provide estimates of health and demographic indicators at the national and regional levels, for rural and urban areas, and for some districts that were designated for oversampling. The 2000 MDHS sample points (clusters) were systematically sampled from a list of enumeration areas (EAs) defined in the 1998 Malawi Census of Population and Housing. A total of 560 clusters were drawn from the census sample frame: 449 in rural areas and 111 in urban areas. Eleven districts were oversampled in the 2000 MDHS survey in order to produce reliable estimates for certain variables at the district level. The oversampled districts are: Lilongwe, Blantyre, Zomba, Mzimba, Mangochi, Kasungu, Salima, Machinga, Mulanje, Thyolo, and Karonga. Upon selecting the 560 clusters, NSO trained teams of personnel in MDHS procedures for the comprehensive listing of households and updating of maps in the selected clusters. Nine listing teams were deployed; each team was composed of ten members including a team leader and driver. Each team was provided with a Global Positioning System (GPS) unit to obtain geographic coordinates for the locality of each selected cluster. The listing of households was conducted from early April until early May 2000. After the listing operation was complete, households to be included in the MDHS survey were selected, with the number of households selected per cluster being inversely proportional to the size of the cluster. Within each selected household, all women age 15-49 were eligible for interview. Further, a one-in-four systematic subsample of households was drawn, within which all men age 15-54 were eligible for interview. 1.6 QUESTIONNAIRES Three types of questionnaires were used in the 2000 MDHS survey: the Household Questionnaire, the Women’s Questionnaire, and the Men’s Questionnaire. The contents of the questionnaires were based on the MEASURE DHS+ model. A series of meetings were held with policy experts, programme managers, and other professionals in Malawi to review, adapt, and revise the questionnaires. This process culminated in English-version questionnaires that were then translated into Chichewa and Tumbuka. 1 A household is defined as one or more persons, related or unrelated, who live together, make common provisions for food, regularly take their food from the same pot or same grainstore (Nkhokwe), or pool their income for the purpose of purchasing food. Introduction * 5 The Household Questionnaire was used to list all of the usual members and visitors in the selected households1. Basic information on each person listed was collected, including age, sex, education, and relationship to the head of the household. The main purpose of the Household Questionnaire was to identify all of the eligible women (age 15-49) and men (age 15-54) for individual interviews. In addition, information was collected about characteristics of the household, such as the source of water, type of toilet facilities, materials used to construct the household’s dwelling, and ownership of various consumer goods. Data on child labour practises, use of bednets (mosquito nets), and nutritional status of children and women were also collected in the Household Questionnaire. The Women’s Questionnaire was used to collect information from women age 15-49 and included questions on the following topics: C Background characteristics (age, education, religion, etc.) C Reproductive history (to arrive at fertility and childhood mortality rates) C Knowledge and use of family planning methods C Antenatal and delivery care C Infant feeding practises, including patterns of breastfeeding C Childhood vaccinations C Recent episodes of childhood illness and responses to illness, especially recent fevers C Marriage and sexual activity C Fertility preferences C Woman’s status and decisionmaking C Mortality of adults, including maternal mortality C AIDS-related knowledge, attitudes, and behaviour The Men’s Questionnaire covered many of the same topics but excluded the detailed reproductive history and sections dealing with maternal and child health and adult and maternal mortality. The Men’s questionnaire is consequently much shorter than the Women’s Questionnaire. The questionnaires were pretested in February 2000 in Mzimba, Ntcheu, and Blantyre City. More than 200 interviews were conducted over a one-week period. The questionnaires were produced in three language versions: Chichewa, Tumbuka, and English. However, interviews could be conducted in any of the languages spoken in Malawi if the respondent was not fluent in one of these three languages. Adjustments in language and content were made to the questionnaires based on the lessons drawn from the pretest interviews. 1.7 TRAINING Training of field staff for the main survey was conducted over a three-week period in June and July 2000. The training took place at Chilema Ecumenical Lay Training Centre outside Zomba Municipality. A total of 200 field staff were trained. The training course consisted of instruction in general interviewing techniques, and field procedures, a detailed review of items on the questionnaires, instruction and practise in weighing and measuring children and women, mock interviews between participants, and practical interviews 6 * Introduction Table 1.2 Results of the household and individual interviews Number of households, number of interviews and response rates, according to urban-rural residence, Malawi 2000 _____________________________________________________ Residence _____________ Result Urban Rural Total _______________________________________________________ Household interviews Households sampled Households occupied Households interviewed Household response rate Individual interviews: women Number of eligible women Number of eligible women interviewed Eligible woman response rate 2,868 2,714 2,680 98.7 2,929 2,871 98.0 12,553 11,638 11,533 99.1 10,609 10,349 97.5 15,421 14,352 14,213 99.0 13,538 13,220 97.7 Individual interviews: men Number of eligible men Number of eligible men interviewed Eligible man response rate 812 721 88.8 2,566 2,371 92.4 3,377 3,092 91.6 in surrounding villages. In-depth discussions of the translations were an important part of the training programme. The trainees included 26 medically trained personnel who worked on the survey as health technicians. Of the trainees, 183 who performed satisfactorily in the training programme were selected to form the 22 teams for the fieldwork. The rest, if qualified, were employed as MDHS data entry and registry staff. 1.8 DATA COLLECTION AND DATA PROCESSING Twenty-two interviewing teams carried out the fieldwork for the MDHS survey, with each team consisting of one team leader, one field editor, four female interviewers, one health technician, one male interviewer, and one driver. On a few teams, an additional male interviewer was added. Additionally, six senior staff from NSO coordinated and supervised field activities. Data collection began on July 12 and was completed in early November 2000. Complete, field-edited questionnaires were brought to the NSO headquarters in Zomba after collection during supervisory visits by NSO senior staff. Data entry began one week after data collection started and was completed in December 2000. Office editing, coding of open-ended questions, and editing based on computer identified inconsistencies in the data continued into January 2001. The questionnaires were entered, verified, and edited using a new version of ISSA (Integrated System for Survey Analysis) adapted by ORC Macro and the U.S. Bureau of Census for integrated use in censuses and surveys. Table 1.2 shows the results of household and individual interviews for Malawi as a whole, and for urban and rural areas. A total of 15,421 households were selected in the MDHS sample, of which 14,352 were occupied. Of the occupied households, 14,213 were interviewed, yielding a household response rate of 99 percent. The household response rate was slightly higher in rural areas. Introduction * 7 Within the interviewed households, 13,538 eligible women age 15-49 were identified, of which 13,220 were interviewed. The individual women’s response rate to the 2000 MDHS survey was 98 percent. In the one-in-four subsample of households, 3,377 men age 15-54 were identified, of which 3,092 men were interviewed, giving a response rate of 92 percent. The main reason for nonresponse among both eligible men and women was the failure to find them at home despite repeated visits to the household. It is typical for male response rates to be lower than female response rates because men are more frequently absent from the household. Response rates for women were not influenced by urban-rural residence, but men’s response rates were significantly better in rural areas than in urban areas. In comparing response rates from the 1992 MDHS survey and the 2000 MDHS survey, the more recent survey performed slightly better. The women’s response rate rose from 97 to 98 percent, and the men’s response rate increased from 89 to 92 percent. Characteristics of Households * 9 CHARACTERISTICS OF HOUSEHOLDS AND HOUSEHOLD MEMBERS Richmond C. Chinula The purpose of this chapter is to provide a descriptive summary of some demographic and socioeconomic characteristics of the population in the sampled households. Also examined are environmental conditions, such as housing facilities and physical features of dwelling units. This information on the characteristics of the surveyed population is essential for the interpretation of survey findings and can provide an approximate indication of the representativeness of the MDHS survey. For the purpose of the 2000 MDHS survey, a household was defined as a person or a group of persons, related or unrelated, who live together in the same dwelling unit, who make common provisions for food and regularly take their food from the same pot or share the same grain store (nkhokwe), or who pool their income for the purpose of purchasing food. The Household Questionnaire was used to collect information on all usual residents and visitors who spent the night preceding the survey in the household. This allows the analysis of either de jure (usual residents) or de facto (those who are there at the time of the survey) populations. 2.1 HOUSEHOLD POPULATION BY AGE, SEX, AND RESIDENCE The distribution of the household population in the 2000 MDHS survey is shown in Table 2.1 by five-year age groups, according to sex and urban-rural residence. The 2000 MDHS households constitute a population of 61,725 persons. Fifty-one percent of the population is females, and 49 percent is males. Because of relatively high levels of fertility in the past, Malawi has a larger proportion of its population in the younger age groups than in the older age groups for each sex in both rural and urban areas. This pattern mirrors those observed in the 1992 MDHS survey and the 1998 Population and Housing Census. Figure 2.1 shows that the population structure is much wider at the younger ages than at the older ages. There is no evidence of a tapering at the younger ages, which would be expected in a population with declining fertility rates (see Chapter 4). This indicates that Malawi’s fertility decline is very recent and is not yet evident in the population structure. 2.2 HOUSEHOLD COMPOSITION Information about the composition of households by sex of the head of the household and size of the household is presented in Table 2.2. The data show that men head 73 percent of households in Malawi, similar to the level observed in the 1992 MDHS survey (75 percent). Female-headed households are more common in rural areas (28 percent) than in urban areas (16 percent). The average household size in Malawi is 4.4 persons. The household size is roughly the same in rural (4.4) and urban (4.5) areas. 2 10 * Characteristics of Households Table 2.1 Household population by age, sex, and residence Percent distribution of the de facto household population by five-year age group, according to sex and residence, Malawi 2000____________________________________________________________________________________________________ Urban Rural Total_______________________ _______________________ _______________________ Age group Male Female Total Male Female Total Male Female Total____________________________________________________________________________________________________ 0-4 5-9 10-14 15-19 20-24 25-29 30-34 35-39 40-44 45-49 50-54 55-59 60-64 65-69 70-74 75-79 80 + Total Number 16.1 16.5 16.3 18.5 17.8 18.1 18.1 17.6 17.9 13.8 14.0 13.9 16.3 15.3 15.8 15.9 15.2 15.5 11.0 14.3 12.6 13.8 13.5 13.6 13.4 13.6 13.5 11.6 11.7 11.7 10.0 9.0 9.5 10.3 9.3 9.8 12.4 13.3 12.8 8.2 8.9 8.6 8.8 9.5 9.2 10.2 9.2 9.7 7.0 7.4 7.2 7.5 7.6 7.5 7.2 5.7 6.5 5.0 4.8 4.9 5.4 5.0 5.1 5.8 4.5 5.2 4.6 4.5 4.5 4.7 4.5 4.6 3.4 2.9 3.2 3.6 3.4 3.5 3.5 3.3 3.4 3.1 2.5 2.8 2.8 3.0 2.9 2.8 3.0 2.9 2.2 2.0 2.1 2.7 3.6 3.2 2.6 3.4 3.0 1.3 1.1 1.2 2.2 2.5 2.4 2.0 2.3 2.2 0.8 0.7 0.8 1.8 2.2 2.0 1.6 2.0 1.8 0.4 0.8 0.6 1.5 1.6 1.5 1.3 1.5 1.4 0.2 0.4 0.3 1.1 1.1 1.1 0.9 1.0 1.0 0.1 0.1 0.1 0.6 0.6 0.6 0.5 0.6 0.6 0.2 0.3 0.2 0.6 0.6 0.6 0.5 0.6 0.6 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 4,483 4,326 8,809 25,507 27,409 52,917 29,990 31,735 61,725 ____________________________________________________________________________________________________ Note: Table is based on the de facto population; i.e., persons who stayed in the household the night before the interview. Characteristics of Households * 11 Table 2.2 Household composition Percent distribution of households by sex of head of household and by household size, according to residence, Malawi 2000________________________________________ Residence_____________ Characteristic Urban Rural Total________________________________________ Sex of head of household Male Female Total Number of usual members 1 2 3 4 5 6 7 8 9+ Total Mean size 84.1 71.7 73.4 15.9 28.3 26.6 100.0 100.0 100.0 8.1 8.0 8.0 12.6 13.5 13.4 18.2 18.7 18.6 17.2 17.0 17.0 14.2 14.5 14.5 10.5 11.4 11.3 7.8 7.3 7.4 4.6 4.3 4.3 6.7 5.2 5.4 100.0 100.0 100.0 4.5 4.4 4.4 _______________________________________ Note: Table is based on de jure members; i.e., usual residents. Table 2.3 Children’s living arrangements Percent distribution of de jure children under age 15 by survival status of parents and children's living arrangements, according to background characteristics, Malawi 2000______________________________________________________________________________________________________ Living Living with mother with father but not father but not mother Not living with either parent Missing Living ____________ _____________ ________________________ informa- with Only Only tion on Background both Father Father Mother Mother Both father mother Both father/ characteristic parents alive dead alive dead alive alive alive dead mother Total Number______________________________________________________________________________________________________ Age <2 2-4 5-9 10-14 Sex Male Female Residence Urban Rural Region Northern Central Southern Total 75.1 21.6 1.5 0.0 0.0 1.0 0.3 0.0 0.0 0.4 100.0 4,872 68.4 18.3 2.9 0.6 0.4 7.4 0.6 0.5 0.4 0.5 100.0 6,176 58.3 15.0 5.2 1.6 0.9 12.1 2.4 2.0 1.7 0.8 100.0 9,650 48.0 13.3 7.0 2.3 1.5 14.7 4.1 3.7 4.2 1.3 100.0 8,417 61.7 16.2 4.8 1.4 0.8 8.8 1.9 1.7 1.8 0.8 100.0 14,308 . 58.9 16.4 4.4 1.2 0.8 11.2 2.5 1.9 1.9 0.8 100.0 14,806 . 63.3 9.2 5.4 2.7 1.7 10.1 1.7 2.7 2.4 0.8 100.0 3,763 59.8 17.4 4.5 1.1 0.7 10.0 2.2 1.7 1.8 0.8 100.0 25,352 . 61.3 12.6 4.0 2.1 1.7 11.7 1.3 2.4 2.0 0.7 100.0 3,349 64.6 15.2 3.7 1.2 0.8 8.9 2.0 1.5 1.3 0.6 100.0 12,524 . 55.9 18.3 5.7 1.2 0.6 10.5 2.5 2.0 2.3 1.0 100.0 13,242 60.3 16.3 4.6 1.3 0.8 10.0 2.2 1.8 1.9 0.8 100.0 29,114 2.3 FOSTERHOOD AND ORPHANHOOD Information on fosterhood and orphanhood of children under age 15 is presented in Table 2.3. The MDHS survey shows that only 60 percent of children under age 15 currently live with both of their biological parents. Twenty-one percent of children under 15 are living with their mother (but not with their father), 2 percent are living with their father (but not with their mother), and 16 percent are living with neither of their natural parents. The table also provides data on the extent of orphanhood, that is, the proportion of children who have lost one or both parents. Of children under 15 years, 8 percent have lost their father and 5 percent have lost their mother. Two percent of children have lost both their natural parents. Eleven percent have lost one or both parents. With the rates of adult illness and mortality related to HIV/AIDS rising in Malawi (see Chapter 12), the percentage of households with orphaned and foster children is expected to rise in the near term. 12 * Characteristics of Households Differentials by background characteristics in fosterhood and orphanhood are not large. As expected, older children are more likely than younger children to be fostered and orphaned. A slightly larger proportion of urban children than rural children have lost their father or both parents. 2.4 EDUCATIONAL LEVEL OF HOUSEHOLD POPULATION Education is a key determinant of the lifestyle and status an individual enjoys in a society. It affects many aspects of life, including demographic and health behaviour. Studies have consistently shown that educational attainment has strong effects on reproductive behaviour, contraceptive use, fertility, infant and child mortality, morbidity, and attitudes and awareness related to family health and hygiene. In the 2000 MDHS survey, information on educational attainment was collected for every member of the household. Table 2.4 shows the percent distribution of the de facto male and female population age 6 and over, by the highest level of education attained, according to selected background characteristics. There is a strong differential in educational attainment between the sexes, especially as age increases. Twenty-eight percent of female household members in Malawi have never been to school, compared with 16 percent of males. The proportion with no education increases with age. For example, the proportion of women who have never attended any formal schooling increases from 19 percent at age group 20-24 to 70 percent among those age 65 and over. For men, the proportion increases from 9 percent at age group 20-24 to 38 percent at age group 65 and over. About 6 percent of women and 12 percent of men have attended some secondary school. The median number of years of schooling is 1.4 for women and 2.7 for men. Overall, educational attainment is higher in urban areas than in rural areas. The proportion of women and men with secondary education is much higher in urban than in rural areas. Conversely, the proportion with no education in urban areas is one-third that in rural areas. The proportion of the population age 6 and over that has achieved any education varies among Malawi’s regions and districts. The Northern Region has the highest proportions with some education for both males (92 percent) and females (85 percent). For females, the proportion is lowest in the Southern Region (68 percent); for males, it is lowest in the Central Region (82 percent). Of the oversampled districts, Blantyre has the highest median years of education at 6.1 years for men and 4.2 years for women. Mzimba and Karonga follow at 4.5 years for men and 3.1 and 2.8, respectively, for women. The lowest educational attainment for both men and women is observed in Mangochi, where the median years of education is 1 year for men and 0 years for women. Rates of school attendance have improved since the 1992 MDHS survey, especially among females. The percentages of girls and boys age 10-14 who had never been to school were 27 and 22 percent, respectively, based on the 1992 MDHS survey. The 2000 MDHS survey indicates that these figures have improved greatly, to just 7 percent for both girls and boys. This trend can be attributed at least in part to the government’s introduction in 1994 of tuition-free primary education. Characteristics of Households * 13 Table 2.4 Educational attainment of household population Percent distribution of the de facto female and male household populations age six and over by highest level of education attended, according to background characteristics, Malawi 2000_____________________________________________________________________________________________________ Level of education___________________________________________________ No 0-4 5-8 More Don't Median Background educa- years of years of Secon- than know/ number characteristic tion primary primary dary secondary missing Total Number of years_____________________________________________________________________________________________________ FEMALE____________________________________________________________________________________________________ Age 6-9 10-14 15-19 20-24 25-29 30-34 35-39 40-44 45-49 50-54 55-59 60-64 65+ Residence Urban Rural Region Northern Central Southern Districts Blantyre Karonga Kasungu Lilongwe Machinga Mangochi Mulanje Mzimba Salima Thyolo Zomba Other districts Total 25.7 73.6 0.2 0.0 0.0 0.5 100.0 4,029 0.0 6.8 76.3 15.9 0.8 0.0 0.3 100.0 4,311 2.1 8.0 33.7 44.4 13.9 0.0 0.0 100.0 2,961 4.6 18.8 32.8 30.5 17.7 0.1 0.0 100.0 3,013 3.8 30.2 28.9 30.4 10.1 0.3 0.1 100.0 2,417 2.7 34.5 29.0 29.5 7.0 0.1 0.0 100.0 1,572 2.1 39.5 28.9 25.1 6.4 0.1 0.0 100.0 1,439 1.6 46.9 27.2 20.9 4.8 0.1 0.0 100.0 1,057 0.4 48.9 30.5 16.6 3.8 0.1 0.0 100.0 939 0.0 55.0 30.1 11.5 2.4 0.1 1.0 100.0 1,082 0.0 60.4 30.7 6.6 1.3 0.0 0.9 100.0 742 0.0 65.0 31.5 2.9 0.3 0.0 0.4 100.0 644 0.0 70.0 25.8 3.5 0.2 0.0 0.5 100.0 1,158 0.0 11.7 33.3 31.1 23.3 0.4 0.2 100.0 3,519 4.7 31.1 47.0 18.3 3.3 0.0 0.2 100.0 21,843 1.0 14.9 39.9 36.7 8.1 0.0 0.3 100.0 2,843 3.4 27.7 48.8 18.3 5.0 0.1 0.2 100.0 10,368 1.3 32.2 43.2 17.7 6.6 0.1 0.2 100.0 12,152 1.1 11.2 37.5 28.6 22.3 0.4 0.1 100.0 2,169 4.2 18.0 42.7 33.2 5.7 0.0 0.3 100.0 500 2.8 19.8 49.0 25.9 5.2 0.1 0.0 100.0 928 2.1 25.5 48.5 18.3 7.3 0.1 0.2 100.0 3,595 1.4 41.8 43.6 11.8 2.3 0.0 0.3 100.0 952 0.3 48.0 39.5 9.6 2.6 0.0 0.3 100.0 1,335 0.0 29.2 52.2 15.3 2.7 0.0 0.6 100.0 1,201 1.0 16.1 40.9 35.9 6.8 0.1 0.3 100.0 1,190 3.1 37.9 43.1 14.3 4.5 0.1 0.1 100.0 607 0.6 31.0 47.7 18.2 3.1 0.0 0.1 100.0 1,340 1.0 31.8 44.7 19.7 3.6 0.0 0.2 100.0 1,547 1.3 30.5 45.7 19.2 4.3 0.0 0.2 100.0 9,999 1.2 28.4 45.1 20.1 6.1 0.1 0.2 100.0 25,363 1.4 ___________________________________________________________________________________________________ MALE____________________________________________________________________________________________________ Age 6-9 10-14 15-19 20-24 25-29 30-34 35-39 40-44 45-49 50-54 55-59 60-64 65+ Residence Urban Rural Region Northern Central Southern Districts Blantyre Karonga Kasungu Lilongwe Machinga Mangochi Mulanje Mzimba Salima Thyolo Zomba Other districts Total 28.5 70.8 0.2 0.0 0.0 0.5 100.0 3,952 0.0 7.4 78.5 13.4 0.6 0.0 0.2 100.0 4,011 1.8 5.4 35.0 46.9 12.6 0.0 0.1 100.0 3,080 4.7 9.4 23.7 34.3 32.0 0.5 0.1 100.0 2,645 6.3 12.4 24.5 35.9 26.3 0.7 0.1 100.0 2,242 5.6 16.5 22.3 40.5 19.5 1.0 0.1 100.0 1,606 5.5 18.3 22.3 40.9 17.3 1.0 0.3 100.0 1,424 5.4 17.9 22.3 43.3 14.5 1.2 0.8 100.0 1,064 5.0 20.3 27.8 38.8 11.6 1.0 0.3 100.0 849 4.2 22.1 33.2 34.0 9.5 0.7 0.4 100.0 782 3.4 27.1 32.8 30.6 7.3 1.0 1.2 100.0 609 2.6 34.6 41.7 17.6 5.0 0.5 0.6 100.0 486 1.6 38.3 42.6 16.1 2.3 0.2 0.6 100.0 998 1.2 5.5 27.8 31.8 32.8 2.0 0.2 100.0 3,642 6.8 18.4 46.9 26.2 8.1 0.1 0.3 100.0 20,104 2.3 8.0 36.7 37.9 16.7 0.6 0.1 100.0 2,656 4.7 18.2 45.9 25.2 10.2 0.2 0.3 100.0 10,143 2.4 16.8 43.9 26.1 12.3 0.5 0.4 100.0 10,947 2.6 5.9 30.4 30.2 31.1 2.2 0.1 100.0 2,181 6.1 8.2 38.1 38.6 14.6 0.1 0.5 100.0 475 4.5 13.1 42.7 32.3 11.5 0.2 0.1 100.0 957 3.3 16.4 44.5 24.6 13.9 0.4 0.2 100.0 3,705 2.7 24.7 47.2 20.8 6.6 0.3 0.5 100.0 792 1.8 29.3 45.3 18.8 5.9 0.1 0.6 100.0 1,172 1.0 15.5 50.4 26.9 6.3 0.2 0.6 100.0 991 2.3 8.4 37.4 39.4 14.1 0.7 0.1 100.0 1,076 4.5 25.2 41.6 22.4 10.4 0.1 0.3 100.0 540 1.8 15.4 47.0 28.9 8.4 0.1 0.3 100.0 1,089 2.6 16.5 44.6 29.0 9.5 0.1 0.3 100.0 1,396 2.6 17.9 46.6 26.1 9.0 0.2 0.3 100.0 9,372 2.3 16.4 44.0 27.0 11.9 0.4 0.3 100.0 23,747 2.7 ____________________________________________________________________________________________________ Note: Totals include 3 women and 6 men for whom information on age is not available. 14 * Characteristics of Households Table 2.5 School attendance ratios Net attendance ratios (NAR) and gross attendance ratios (GAR) for the de jure household population by level of schooling and sex, according to background characteristics, Malawi 2000 ________________________________________________________________________________________ Net attendance ratio (NAR)1 Gross attendance ratio (GAR)2 Background ____________________________ ___________________________ characteristic Male Female Total Male Female Total ________________________________________________________________________________________ PRIMARY SCHOOL ________________________________________________________________________________________ Residence Urban Rural Region Northern Central Southern Total 90.1 87.5 88.7 123.9 107.8 115.4 75.2 77.9 76.6 109.6 101.5 105.5 86.3 89.9 88.2 128.5 116.4 122.2 74.7 78.5 76.6 107.0 100.9 103.9 77.0 77.2 77.1 111.3 100.1 105.6 77.0 79.2 78.2 111.4 102.4 106.8 ________________________________________________________________________________________ SECONDARY SCHOOL ________________________________________________________________________________________ Residence Urban Rural Region Northern Central Southern Total 23.4 30.0 26.6 75.5 61.8 69.0 3.7 5.0 4.3 24.9 13.0 19.2 8.0 15.0 11.6 46.1 25.3 35.5 5.8 7.0 6.4 30.8 17.4 24.5 7.3 8.5 7.8 30.9 21.6 26.4 6.7 8.8 7.7 32.6 20.4 26.8 ________________________________________________________________________________________ 1 The NAR for primary school is the percentage of the primary-school-age (6-13 years) population that is attending primary school. The NAR for secondary school is the percentage of the secondary-school-age (14-17 years) population that is attending secondary school. By definition the NAR cannot exceed 100 percent. 2 The GAR for primary school is the total number of primary school students, among those of any age, expressed as the percentage of the official primary-school-age population. The GAR for secondary school is the total number of secondary school students (up to age 24), expressed as the percentage of the official secondary-school-age population. If there are significant numbers of overage and underage students at a given level of schooling, the GAR can exceed 100 percent. 2.5 SCHOOL ATTENDANCE The 2000 MDHS collected information that allows calculation of net attendance ratios (NARs) and gross attendance ratios (GARs). The NAR for primary school is the percentage of the primary-school-age (6-13 years) population that is attending primary school. The NAR for secondary school is the percentage of the secondary-school-age (14-17 years) population that is attending secondary school. By definition, the NAR cannot exceed 100 percent. The GAR for primary school is the total number of primary school students, of any age, expressed as the percentage of the official primary-school-age population. The GAR for secondary school is the total number of secondary school students up to an age limit of 24 years, expressed as the percentage of the official secondary-school-age population. If there are significant numbers of overage and underage students at a given level of schooling, the GAR can exceed 100 percent. Table 2.5 presents the NARs and GARs by urban-rural residence and region, according to sex for primary school and secondary school. Findings indicate that among children within the official age range for primary school, slightly more girls are attending school than boys (79 versus Characteristics of Households * 15 Table 2.6 Grade repetition and dropout rates Repetition and dropout rates for the de jure household population age 5-24 years by school standard, sex, residence, and region, Malawi 2000___________________________________________________________________________________________ Primary school standard______________________________________________________________________ Characteristic 1 2 3 4 5 6 7 8_________________________________________________________________________________________ REPETITION RATE1_________________________________________________________________________________________ Sex Male Female Residence Urban Rural Region Northern Central Southern Total 43.9 23.6 28.5 17.8 16.1 14.3 11.3 40.2 46.7 24.9 25.7 16.5 14.2 10.4 11.4 35.9 29.1 16.4 24.7 9.2 12.4 12.0 12.4 27.2 47.1 25.3 27.6 18.5 15.8 12.6 11.0 43.3 42.7 17.2 22.4 19.7 14.3 12.4 18.1 49.8 46.7 24.5 28.3 15.2 12.9 10.9 8.0 34.9 44.6 25.9 27.5 18.0 17.4 13.8 10.7 35.5 45.3 24.2 27.2 17.2 15.2 12.5 11.4 38.6 ___________________________________________________________________________________________ DROPOUT RATE2_________________________________________________________________________________________ Sex Male Female Residence Urban Rural Region Northern Central Southern Total 3.3 3.1 4.7 4.8 6.9 4.9 6.2 9.9 2.2 3.5 4.0 6.2 6.5 9.0 9.7 14.1 1.0 0.6 1.7 1.1 2.5 4.6 2.7 5.4 2.9 3.7 4.8 6.3 7.6 7.4 9.5 14.0 1.1 1.1 1.5 1.8 3.0 4.7 8.3 11.4 2.0 2.3 4.3 4.0 6.5 6.6 6.9 10.5 3.9 4.8 5.1 7.8 8.2 7.8 7.9 12.4 2.7 3.3 4.3 5.5 6.7 6.9 7.7 11.5 ___________________________________________________________________________________________ 1 The repetition rate is the percentage of students in a given standard who are repeating that standard. 2 The dropout rate is the percentage of students in a given standard in the previous school year who are not currently attending school. 77 percent). However the GAR shows that, overall, more boys are attending than girls. It is also shown that the primary net attendance ratio is highest for children in the Northern Region (88 percent), followed by the Central and Southern regions (both 77 percent). The NAR for primary school is also higher in urban areas (89 percent) than in rural areas (77 percent). Secondary school attendance ratios are much lower and differ substantially by background characteristics. The NAR in urban areas is six times higher than the NAR in rural areas. The same regional patterns exist for secondary school attendance ratios as for educational attainment: the Northern Region has the highest attendance ratios with the Central and Southern regions being slightly lower. Overall, the net attendance ratio is 8, indicating only 8 percent of secondary-school- age children are attending school at roughly the correct ages. The gross attendance ratio of 27 percent (secondary school) indicates that a substantial proportion of secondary school students are outside the official age range. By asking about the grade or standard that children were attending during the previous school year, it is possible to calculate dropout rates and repetition rates. Table 2.6 indicates that repetition rates are high in Standard 1 (45 percent), which may be related to the teachers’ decision 16 * Characteristics of Households to ensure a more uniform preparedness before promoting children to Standard 2. Repetition rates decline at higher standards, but increase at Standard 8, due to failed attempts at getting into a secondary school. The second panel of Table 2.6 shows a pattern of increasing dropout rates with increasing year in school. Only 3 percent of children drop out of school after having attended Standard 1 compared with a dropout rate of 12 percent at Standard 8. Notable is that the dropout rate at Standard 8 is higher for girls than for boys, while the repetition rate at Standard 8 is higher for boys than for girls (first panel of Table 2.6). This suggests that, despite initiatives to promote continuation of girls’ schooling, boys are still able (to a greater extent than girls) to persist in moving on past a primary education. Boys are more likely to repeat Standard 8, which allows repeat attempts at entry to secondary schools, while girls are more likely to leave school. Rural children are more likely to drop out at all standards than their urban counterparts. Children from the Southern Region are more likely to dropout than children in the Northern or Central regions, except in Standards 7 and 8. 2.6 CHILD LABOUR In the 2000 MDHS survey, information was collected on the work activities of children age 5-14. Working children have less opportunity to attend school and are more susceptible than adults to unfair working environments, including low or no pay, poor working conditions, and physical abuse. Despite policies and laws designed to curtail exploitative child labour, the practise continues in many settings. The 2000 MDHS survey asked a series of questions about whether children age 5-14 were doing any kind of work for pay, whether children regularly did unpaid family work on the farm or in a family business, and whether and to what extent (number of hours) children helped with household chores. Table 2.7 shows that 9 percent of children age 5-14 are doing work for nonrelatives, about two-thirds of these without pay. Sixty-two percent are working in the family business or on the family farm, and 19 percent of children are doing four or more hours of domestic work per day. Overall, 27 percent of children are either working for a nonrelative (paid or unpaid) or spending four or more hours a day doing household chores. Older children are much more likely to be working than younger children. Although boys are more likely to be involved in four or more hours of domestic work per day, there is little difference in the overall percentage engaged in work (26 to 28 percent). Urban children are much less likely to be involved in work than urban children. Children in the Northern Region (13 percent) are more likely than those in the Central Region (5 percent) and Southern Region (4 percent) to be working without pay for nonrelatives. Children in the Northern Region are also more likely to be employed on the family farm or in the family business. Characteristics of Households * 17 2.7 HOUSING CHARACTERISTICS MDHS respondents were asked about their household environment, including questions on access to electricity, sources of drinking water, time to water sources, type of toilet facilities and floor materials, and possession of various durable goods. This information is summarised in Table 2.8. About 5 percent of households in Malawi have electricity. Electricity is much more common in urban areas (29 percent) than in rural areas (1 percent). A household’s source of drinking water is important because potentially fatal diseases, including typhoid, cholera, and dysentery, are prevalent in unprotected sources. Sources of water expected to be relatively free of these diseases are piped water and water drawn from protected wells and deep boreholes. Other sources, like unprotected wells and surface water (rivers, streams, ponds, and lakes), are more likely to carry disease-causing agents. Table 2.8 shows that overall, 65 percent of Malawian households have access to clean water sources (23 percent from piped water plus 42 percent from protected wells or boreholes). This represents a substantial increase since the 1992 MDHS survey when just 47 percent of households had access to similar water sources. Most of this gain is the result of a doubling in the percentage of rural households that now have access to water from protected wells or boreholes from 24 percent in 1992 to 47 percent in 2000. These findings describe one of the most important public health advances in Malawi during the 1990s and may be an important reason for the declines in mortality among young children (see Chapter 8). Table 2.7 Child labour Percentage of children age 5-14 years who are currently working, by type of work and background characteristics, Malawi 2000 _________________________________________________________________________________ Currently Currently doing doing domestic work for: work on _________________ Working for family Less 4 or non-relatives farm or than more Number Background ______________ family 4 hours hours Currently of characteristic Paid Unpaid business per day per day working1 children __________________________________________________________________________________ Age 5-9 1.3 4.2 49.2 1.7 8.1 13.8 9,573 10-14 5.1 7.3 76.6 6.3 30.6 42.1 8,321 Gender Male 3.2 4.4 53.8 2.6 21.1 27.6 8,775 Female 3.0 6.8 69.7 5.1 16.1 26.4 9,120 Residence Urban 1.6 3.7 63.2 4.4 10.6 17.7 2,334 Rural 3.3 6.0 61.8 3.8 19.8 28.4 15,560 Region Northern 2.2 12.9 70.8 4.0 20.2 31.8 2,099 Central 3.7 5.3 61.6 3.8 16.8 25.4 7,686 Southern 2.8 4.1 60.0 3.9 19.9 27.2 8,110 Total 3.1 5.7 61.9 3.9 18.6 27.0 17,894 __________________________________________________________________________________ 1Working means doing paid or unpaid work or doing domestic work for four or more hours a day. 18 * Characteristics of Households Table 2.8 Housing characteristics Percent distribution of households by housing characteristics, according to residence, Malawi 2000_____________________________________________________ Residence Housing ______________ characteristic Urban Rural Total_____________________________________________________ Electricity Yes No Missing Total Source of drinking water Piped into dwelling Piped into yard/plot Community stand pipe Protected well Borehole Unprotected well Surface water Total Time to water source (in minutes) Percentage <15 minutes Median time to source Sanitation facility Own flush toilet Pit latrine No facility/bush Missing Total Main floor material Earth/sand/dung Cement or other modern material Total Number 28.7 1.0 4.8 71.2 98.8 95.0 0.1 0.2 0.2 100.0 100.0 100.0 17.1 0.6 2.8 24.6 1.1 4.3 41.8 12.1 16.2 3.0 6.6 6.1 8.3 40.1 35.8 3.9 27.0 23.8 1.3 12.5 10.9 100.0 100.0 100.0 65.4 28.3 33.4 4.8 19.9 19.6 16.4 0.7 2.9 81.8 78.0 78.5 1.8 21.2 18.5 0.0 0.1 0.1 100.0 100.0 100.0 31.5 89.1 81.2 68.5 10.9 18.8 100.0 100.0 100.0 1,949 12,264 14,213 As expected, a far greater propor- tion of urban than rural households have access to piped water (84 versus 14 per- cent). In urban areas, 65 percent of the households have access to water within 15 minutes, compared with 28 percent of rural households. Modern sanitation facilities are not yet available to large proportions of Malawian households. The use of tradi- tional pit latrines is still common in both urban and rural areas, accounting for 79 percent of all households. Overall, about 19 percent of the households in Malawi have no toilet facilities. This problem is more common in rural areas, where 21 percent of the households have no toilet facilities, compared with 2 percent of households in urban areas. The type of material used for flooring is an indicator of the economic standing of the household as well as an indicator of potential exposure to disease-causing agents. Overall, 81 per- cent of all households in Malawi live in residences with floors made of earth, sand, or dung, while 19 percent live in houses with finished floors like those made of cement or wooden panels. Earth flooring is almost universal in rural areas (89 percent). Respondents were also asked about their household’s ownership of particular durable goods. In addition to providing an indicator of economic status, ownership of these goods provides measures of other aspects of life. Ownership of a radio and a television is a measure of access to mass media; ownership of a refrigerator indicates a capacity for more hygienic food storage; and ownership of a bicycle, motorcycle, or car reflects means of transport and thus employment opportunities available to households. Information on ownership of these items is presented in Table 2.9. Possession of the specific durable goods referenced in the MDHS survey is not common in Malawi, since many households simply cannot afford them. Nationally, 55 percent of households own a radio and only 2 percent of households own a television. Bicycles are the most common type of vehicle owned by households; 43 percent of households have a bicycle. Ownership of motorised transport is rare. Only 2 percent of households have cars and even fewer (only 1 percent) have motorcycles. As expected, urban households are more likely than rural households to own the items listed, except for bicycles, which are more commonly owned in rural areas. For example, 80 percent of urban households have radios, compared with 51 percent of rural households. Most households (91 percent) own a paraffin lamp. Characteristics of Households * 19 Table 2.9 Household durable goods Percentage of households possessing various durable consumer goods and means of transport, by residence, Malawi 2000 ____________________________________________________ Residence Durable ______________ consumer goods Urban Rural Total ____________________________________________________ Household possessions Radio Television Paraffin lamp Means of transport Bicycle Motorcycle/scooter Car/truck None of the above Number of households 79.5 50.8 54.8 13.7 0.5 2.3 83.6 91.9 90.7 28.4 45.8 43.4 1.3 0.9 1.0 6.4 0.8 1.6 1.8 5.9 5.3 1,949 12,264 14,213 Ownership of radios, televisions, and bicycles has increased substantially since 1992. For example, the proportion of households with radios has increased from 33 to 55 percent and the proportion with bicycles has increased from 21 to 43 percent. Characteristics of Respondents * 21 CHARACTERISTICS OF RESPONDENTS AND WOMEN’S STATUS Sophie Kang’oma This chapter provides a demographic and socioeconomic profile of the 2000 Malawi DHS sample of individual female and male respondents. The chapter begins by describing basic background characteristics of men and women, including age, martial status, educational level, and residential characteristics. Next, more detailed information on education, literacy, and exposure to mass media among men and women are provided. Last, data on the employment and earnings of women, decisionmaking in the household, and attitudes on women’s position in relation to others in the household are presented. 3.1 CHARACTERISTICS OF SURVEY RESPONDENTS Background characteristics of women age 15-49 and men age 15-54 interviewed in the 2000 MDHS survey are presented in Table 3.1. Generally, the proportion of respondents in each age group declines as age increases. Seventy percent of women and 59 percent of men were currently married as of the survey date. An additional 1 percent of women and nearly 3 percent of men reported being in an informal marriage or living together. For purposes of the 2000 MDHS survey and in presentation of findings throughout later chapters of this report, informal marriages are typically grouped together with formalised marriages to form the group “currently married” or “in union”. Because men get married later in life than women, more than one-third (35 percent) of the surveyed men have never married, compared with just 17 percent of women. Women were three times more likely than men to be divorced, widowed, or separated. As expected, most of the interviewed women and men reside in rural areas (82 percent of males and 84 percent of females). The largest proportion of the male and female respondents live in the Southern Region (47 and 49 percent, respectively), while 42 and 40 percent of men and women live in the Central Region. Only 11 percent of both men and women live in the Northern Region. Table 3.1 also shows the distribution of men and women by district, including those districts that were oversampled to allow for the estimation of certain indicators presented later in the report. Notable is the large difference between the weighted number of men and women and the unweighted number in some districts. The unweighted number represents the number that were actually interviewed in the 2000 MDHS survey; whereas the weighted number represents that district’s proportional representation in the population based on the 1998 census population distribution. For instance, Karonga District has only 2 percent of the national population of women age 15-49 (as represented by 266 weighted cases), but 941 women were actually interviewed (or 7 percent of the total number of interviewed women). This is mentioned so that the reader will understand that while weighted numbers are presented throughout the report, the district estimates may be based on a significantly large number of unweighted male or female individual interviews. 3 22 * Characteristics of Respondents Table 3.1 Background characteristics of respondents Percent distribution of women and men by background characteristics, Malawi 2000__________________________________________________________________________________ Women Men__________________________ ___________________________ Un- Un- Background Weighted Weighted weighted Weighted Weighted weighted characteristic percent number number percent number number__________________________________________________________________________________ Age 15-19 20-24 25-29 30-34 35-39 40-44 45-49 50-54 Marital status Never married Married Living together Divorced/separated/widowed Residence Urban Rural Region Northern Central Southern Education No education Primary 1-4 Primary 5-8 Secondary Higher District Blantyre Karonga Kasungu Lilongwe Machinga Mangochi Mulanje Mzimba Salima Thyolo Zomba Other districts Total 21.7 2,867 2,914 21.4 660 674 22.4 2,957 2,998 19.4 598 584 18.2 2,401 2,358 17.4 539 544 11.8 1,566 1,574 10.7 330 335 10.8 1,424 1,410 11.0 340 333 8.0 1,053 1,052 7.8 240 240 7.2 951 914 6.7 207 209 na na na 5.7 177 173 17.0 2,243 2,284 34.7 1,073 1,064 70.2 9,282 9,155 59.2 1,830 1,807 1.3 170 206 2.5 76 96 11.5 1,525 1,575 3.7 113 125 15.9 2,106 2,871 18.2 564 721 84.1 11,114 10,349 81.8 2,528 2,371 11.0 1,453 2,187 11.3 351 544 40.3 5,321 4,508 41.9 1,296 1,116 48.8 6,446 6,525 46.8 1,446 1,432 27.0 3,574 3,372 10.4 322 301 30.4 4,025 3,829 29.0 898 822 31.4 4,152 4,390 40.2 1,243 1,269 11.0 1,452 1,608 19.9 614 682 0.1 16 21 0.5 15 18 10.0 1,324 1,023 10.4 321 252 2.0 266 941 2.1 64 245 3.7 484 728 4.6 142 215 14.1 1,864 871 15.7 487 217 3.6 481 798 3.8 119 173 4.8 637 654 5.0 154 154 4.7 624 905 3.8 117 171 4.6 603 781 4.6 142 199 2.3 301 784 2.1 65 174 5.2 687 882 4.5 141 179 6.4 846 899 5.7 177 213 38.6 5,103 3,954 37.6 1,163 900 100.0 13,220 13,220 100.0 3,092 3,092 ___________________________________________________________________________________ Note: Education refers to the highest level ever attended whether or not that level was completed. na = Not applicable Characteristics of Respondents * 23 Table 3.2 Educational attainment by background characteristics Percent distribution of women and men by highest level of schooling attended, and median number of years of schooling completed, according to background characteristics, Malawi 2000 ____________________________________________________________________________________________ Highest level of schooling attended Median ________________________________________________________ years of Background No edu- Primary Primary Secon- More than schooling characteristic cation 1-4 5-8 dary secondary Total Number completed ____________________________________________________________________________________________ WOMEN ____________________________________________________________________________________________ Age 15-19 20-24 25-29 30-34 35-39 40-44 45-49 Residence Urban Rural Region Northern Central Southern Total 7.7 32.9 45.2 14.2 0.0 100.0 2,867 4.7 18.5 32.5 31.1 17.7 0.1 100.0 2,957 3.9 30.0 29.1 30.6 9.9 0.3 100.0 2,401 2.8 34.9 28.3 29.8 6.9 0.1 100.0 1,566 2.2 40.1 28.7 24.8 6.3 0.1 100.0 1,424 1.5 47.0 26.8 21.2 4.9 0.1 100.0 1,053 0.4 49.6 30.3 16.4 3.6 0.1 100.0 951 0.0 10.3 14.2 39.1 35.7 0.6 100.0 2,106 7.0 30.2 33.5 29.9 6.3 0.0 100.0 11,114 2.5 11.1 18.0 56.4 14.4 0.0 100.0 1,453 5.6 26.9 34.0 29.7 9.2 0.1 100.0 5,321 2.8 30.7 30.3 27.2 11.7 0.1 100.0 6,446 2.7 27.0 30.4 31.4 11.0 0.1 100.0 13,220 3.1 ___________________________________________________________________________________________ MEN ___________________________________________________________________________________________ Age 15-19 20-24 25-29 30-34 35-39 40-44 45-49 50-54 Residence Urban Rural Region Northern Central Southern Total 3.3 32.9 51.6 12.1 0.0 100.0 660 5.0 5.4 26.8 35.6 32.1 0.1 100.0 598 6.4 7.5 31.6 33.9 26.1 0.9 100.0 539 5.6 15.9 23.3 37.4 22.9 0.5 100.0 330 5.8 15.9 27.6 40.0 15.1 1.4 100.0 340 4.8 17.2 24.5 44.0 14.0 0.3 100.0 240 4.9 21.7 30.2 36.9 11.1 0.1 100.0 207 3.8 19.0 32.6 36.7 10.2 1.5 100.0 177 3.8 3.4 10.4 39.3 45.0 1.9 100.0 564 7.7 12.0 33.2 40.4 14.3 0.2 100.0 2,528 4.5 2.7 12.6 58.8 25.5 0.3 100.0 351 7.2 11.8 32.0 39.1 16.5 0.7 100.0 1,296 4.6 11.1 30.4 36.7 21.5 0.4 100.0 1,446 4.9 10.4 29.0 40.2 19.9 0.5 100.0 3,092 5.1 3.2 EDUCATIONAL ATTAINMENT Table 3.2 shows the percent distribution of respondents by highest level of schooling attained according to their age and place of residence. Young women and men are more likely to have attended school than the older generation. The distribution of respondents who have never attended school rises with increasing age. For example, 8 percent of women and 3 percent of men age 15-19 have no formal education, compared with 50 percent of women and 22 percent of men 24 * Characteristics of Respondents age 45-49. Similarly, 18 percent of women age 20-24 attended secondary school, compared with only 4 percent of women age 45-49. For the male respondents, 32 percent of men age 20-24 attended secondary school, compared with just 10 percent of men age 50-54. The MDHS data indicate that educational opportunities vary among the respondents according to their areas of residence. Urban women and men are more likely to go to school than their rural counterparts. Only 10 percent of urban women and 3 percent of urban men have not attended school, compared with 30 percent and 12 percent in rural areas, respectively. Comparing the median completed years of education shows a similar differential, with urban women having a median of seven years of schooling and rural respondents having only three years. At the regional level, the proportion of women who have no formal education is lower in the Northern Region (11 percent), compared with to the Central Region (27 percent) and the Southern Region (31 percent). Secondary education (or higher) is most common for men (26 percent) and women (14 percent) who reside in the Northern Region and is least common for men (17 percent) and women (9 percent) residing in the Central Region. 3.3 LITERACY The ability to read is an important personal asset allowing women and men increased opportunities in life. In the 2000 MDHS survey, persons were defined as literate based on the UNICEF definition: persons who are able to read a complete sentence or those with some secondary education. Knowing the distribution of the literate population can help planners, especially for health and family planning, know how to reach women and men with their messages. Table 3.3 shows that especially for women, there has been a marked increase in the percent literate over time. Only 25 percent of women age 45-49 are literate compared with 67 percent of women age 15-19. The level of literacy is higher among men (72 percent) than women (49 percent). Urban respondents have a higher level of literacy (75 percent for women and 88 percent for men) than rural respondents (44 and 69 percent, respectively). For both women and men, the Northern Region has the highest literacy rate: almost 15 percentage points higher than the other two regions. 3.4 ACCESS TO MASS MEDIA The 2000 MDHS survey collected information on the exposure of respondents to the various common print and electronic media. Respondents were asked how often they read a newspaper, listened to the radio, or watched television in a week. This information is useful to family planning and health programmers to enable them to know how to reach targeted groups. Although more than one-half of the women and men listen to the radio at least once a week, a much smaller proportion read newspapers or watch television. Data in Table 3.4 show that 52 percent of interviewed women and 70 percent of interviewed men listen to the radio at least once a week. Only 4 percent of women and 9 percent of men watch television at least once a week. About one in five men and one in ten women read a newspaper at least once a week. Less than half of the interviewed women (46 percent) and one-quarter of men (26 percent) have no access to any type of mass media. Characteristics of Respondents * 25 Table 3.3 Literacy Percent distribution of women and men by level of schooling attended, level of literacy, and percent literate, according to background characteristics, Malawi 2000_______________________________________________________________________________________________ No schooling or primary school ______________________________________ No card in Cannot Can read Can read respon- Secondary Background read part of a a whole dent’s school or Percent characteristic at all sentence sentence language1 higher Total Number literate_______________________________________________________________________________________________ WOMEN_______________________________________________________________________________________________ Age 15-19 20-24 25-29 30-34 35-39 40-44 45-49 Residence Urban Rural Region Northern Central Southern Total 24.2 8.4 52.9 0.2 14.2 100.0 2,867 67.2 36.5 7.8 37.8 0.1 17.8 100.0 2,957 55.7 46.4 7.7 35.6 0.1 10.2 100.0 2,401 45.8 49.8 8.9 34.2 0.2 6.9 100.0 1,566 41.1 53.1 7.7 32.8 0.0 6.4 100.0 1,424 39.2 63.3 6.4 25.2 0.1 5.0 100.0 1,053 30.2 68.1 7.1 21.0 0.1 3.7 100.0 951 24.5 17.5 7.1 38.8 0.2 36.4 100.0 2,106 75.1 48.3 8.0 37.3 0.1 6.3 100.0 11,114 43.6 28.7 8.5 47.8 0.5 14.5 100.0 1,453 62.5 43.5 7.9 39.1 0.1 9.4 100.0 5,321 48.5 46.6 7.7 33.9 0.0 11.8 100.0 6,446 45.7 43.4 7.9 37.5 0.1 11.1 100.0 13,220 48.6 _______________________________________________________________________________________________ MEN_______________________________________________________________________________________________ Age 15-19 20-24 25-29 30-34 35-39 40-44 45-49 50-54 Residence Urban Rural Region Northern Central Southern Total 17.2 8.5 61.6 0.6 12.1 100.0 660 73.5 15.9 7.5 44.3 0.1 32.2 100.0 598 76.5 20.5 5.5 46.9 0.2 26.9 100.0 539 74.0 21.8 5.1 49.7 0.0 23.4 100.0 330 73.1 25.9 4.4 53.3 0.0 16.5 100.0 340 69.7 23.9 11.6 50.1 0.1 14.3 100.0 240 64.5 28.3 5.6 54.1 0.7 11.2 100.0 207 65.5 22.8 8.4 57.2 0.0 11.7 100.0 177 68.9 5.4 6.3 40.9 0.4 46.9 100.0 564 87.6 23.9 7.1 54.3 0.2 14.4 100.0 2,528 68.6 9.5 3.6 60.5 0.5 25.8 100.0 351 86.5 24.4 6.5 51.7 0.3 17.2 100.0 1,296 68.6 19.7 8.3 49.9 0.1 21.9 100.0 1,446 71.7 20.5 7.0 51.9 0.2 20.4 100.0 3,092 72.1 _________________________________________________________________________________________________ Note: Percent literate includes those who have attended secondary school and those who can read a whole sentence. 1 Literacy cards for reading a sentence were available only in the major languages. Urban residents and in general younger respondents have more access to all three types of media than their rural or older counterparts. In the Northern Region, where the literacy rate is high, both women and men are more likely to read a newspaper weekly than in the Central or Southern regions. Respondents of both sexes in the Southern Region and urban areas have greater exposure to televisions and radios. Accessibility to all mass media is lower among the Central Region residents. 26 * Characteristics of Respondents Table 3.4 Exposure to mass media Percentage of women and men who usually read a newspaper at least once a week, watch television at least once a week, and listen to the radio at least once a week, by background characteristics, Malawi 2000 ___________________________________________________________________________________________ Reads a Watches Listens to newspaper television the radio No at least at least at least All Background mass once a once a once a three characteristic media week week week media Number ___________________________________________________________________________________________ WOMEN ___________________________________________________________________________________________ Age 15-19 20-24 25-29 30-34 35-39 40-44 45-49 Residence Urban Rural Region Northern Central Southern Education No education Primary 1-4 Primary 5-8 Secondary+ Total 44.1 14.6 4.7 52.4 2.5 2,867 43.6 10.8 4.2 54.3 2.7 2,957 45.5 9.6 3.5 53.6 2.3 2,401 46.4 8.1 3.5 52.3 2.0 1,566 45.9 6.8 3.2 53.2 2.0 1,424 51.6 5.2 3.1 47.3 1.2 1,053 52.4 4.6 2.4 46.5 1.0 951 20.7 28.4 18.0 76.2 11.2 2,106 50.7 6.2 1.1 47.8 0.5 11,114 43.7 23.4 3.6 50.7 2.6 1,453 49.5 7.6 2.7 49.0 1.3 5,321 43.4 8.5 4.7 55.4 2.8 6,446 59.7 0.2 0.5 40.1 0.0 3,574 52.0 2.7 0.9 47.1 0.1 4,025 38.8 12.7 2.8 58.2 1.1 4,152 15.7 44.4 22.2 79.9 16.4 1,468 45.9 9.8 3.8 52.3 2.2 13,220 ___________________________________________________________________________________________ MEN ___________________________________________________________________________________________ Age 15-19 20-24 25-29 30-34 35-39 40-44 45-49 50-54 Residence Urban Rural Region Northern Central Southern Education No education Primary 1-4 Primary 5-8 Secondary+ Total 24.8 22.2 10.9 69.0 3.8 660 28.2 24.0 13.1 66.8 7.2 598 26.4 21.9 10.3 70.5 5.8 539 20.4 26.3 6.5 75.2 3.9 330 31.2 18.2 5.8 65.4 3.5 340 23.7 18.5 2.4 74.6 2.0 240 25.4 20.6 3.6 72.9 2.2 207 29.2 11.2 1.4 67.3 0.6 177 10.4 53.8 25.6 82.8 17.2 564 29.7 14.3 4.7 66.7 1.5 2,528 33.2 34.7 6.4 54.5 3.3 351 29.0 16.1 6.1 67.8 2.3 1,296 21.9 23.1 11.1 75.0 6.5 1,446 44.4 1.6 1.8 53.1 0.0 322 34.2 5.6 3.4 64.3 0.9 898 23.9 21.7 6.8 70.3 1.9 1,243 9.9 54.0 22.4 84.6 16.5 629 26.2 21.5 8.5 69.7 4.4 3,092 Characteristics of Respondents * 27 Education is strongly associated with mass media exposure. For instance, about 16 percent of women and men with secondary or more education were likely to have access to all three types of media versus less than 2 percent for the other education categories. Men have greater exposure to the mass media than women. As Figure 3.1 presents, this differential applies within every population subgroup. 3.5 WOMEN’S EMPLOYMENT Respondents were asked a number of questions to elicit their employment status at the time of the survey and the continuity of their employment in the 12 months prior to the survey. The measurement of women’s employment is difficult because some of the activities that women do, especially work on family farms, family businesses, or in the informal sector are often not perceived by women themselves as employment and hence are not reported as such. To avoid underestimating women’s employment, the MDHS survey asked women several questions to ascertain their employment status. First women were asked, “Aside from your own housework, are you currently working?” Women who answered “no” to this question were then asked, “As you know, some women take up jobs for which they are paid in cash or kind. Others sell things, have a small business, or work on the family farm or in the family business. Are your currently doing any of these things or any other work?” Women who answered “no” to this question were asked,“Have you done any work in the last 12 months?” Women are currently employed if they answered “yes” to either of the first two questions. Women who answered “yes” to the third question are not currently employed but have worked in the past 12 months. All employed women were asked their occupation; whether they were paid in cash, in kind, or not at all; and for whom they worked. 28 * Characteristics of Respondents Table 3.5 Employment of women Percent distribution of women by employment status and continuity of employment, according to background characteristics, Malawi 2000 ____________________________________________________________________________________ Not currently employed __________________ Did not Worked work in the in the Currently employed 12 mos. 12 mos. ______________________ preced- preced- Background ing the ing the All Season- Occasion- characteristic survey survey year ally ally Total Number ____________________________________________________________________________________ Age 15-19 20-24 25-29 30-34 35-39 40-44 45-49 Current marital status Never married Currently married/ living together Divorced, separated, widowed Number of living children 0 1-2 3-4 5+ Residence Urban Rural Region Northern Central Southern Education No education Primary 1-4 Primary 5-8 Secondary+ Total 54.7 5.5 10.7 24.6 4.4 100.0 2,867 42.0 4.4 16.7 31.8 5.1 100.0 2,957 37.0 3.7 20.8 33.6 4.8 100.0 2,401 31.0 4.4 23.7 34.8 6.2 100.0 1,566 28.8 4.6 23.7 38.0 4.8 100.0 1,424 28.2 4.4 24.4 38.2 4.9 100.0 1,053 27.8 5.3 21.4 40.0 5.6 100.0 951 58.2 4.9 12.7 19.8 4.4 100.0 2,243 36.7 4.5 18.8 35.4 4.6 100.0 9,452 25.2 5.1 26.9 34.6 8.2 100.0 1,525 52.7 4.7 14.0 24.0 4.6 100.0 3,216 38.4 4.6 19.4 32.7 4.9 100.0 4,628 33.4 3.8 20.7 36.7 5.2 100.0 2,877 28.9 5.3 21.0 39.3 5.6 100.0 2,499 55.1 2.3 27.3 10.5 4.8 100.0 2,106 35.9 5.0 17.0 36.9 5.1 100.0 11,114 27.1 8.1 20.5 38.4 5.7 100.0 1,453 39.1 5.3 19.1 31.8 4.7 100.0 5,321 41.6 3.2 17.9 32.1 5.1 100.0 6,446 36.3 4.0 16.7 38.6 4.4 100.0 3,574 35.9 4.7 17.1 37.0 5.3 100.0 4,025 41.5 5.2 17.2 30.4 5.6 100.0 4,152 47.0 4.1 32.1 13.0 3.9 100.0 1,468 39.0 4.6 18.7 32.7 5.0 100.0 13,220 Table 3.5 shows the percent distribution of female respondents by employment status and continuity of employment, according to background characteristics. Fifty-six percent of women reported being currently employed: 19 percent all year, 33 percent seasonally, and 5 percent occasionally. Forty-four percent of women are not currently working, but 5 percent did work at some time during the past 12 months. Characteristics of Respondents * 29 Table 3.6 Employer and form of earnings Percent distribution of currently employed women by employer and type of earnings (cash, in kind, no payment), according to background characteristics, Malawi 2000 _____________________________________________________________________________________________________ Employed by a Employed by Self-employed non-family member a family member _______________ ______________ _______________ Does Does Does Background Earns not earn Earns not earn Earns not earn characteristic cash1 cash2 cash1 cash2 cash1 cash2 Missing3 Total Number _____________________________________________________________________________________________________ Age 15-19 20-24 25-29 30-34 35-39 40-44 45-49 Residence Urban Rural Region Northern Central Southern Education No education Primary 1-4 Primary 5-8 Secondary+ Occupation Agriculture Non-agriculture Total 18.0 32.9 6.2 2.9 7.7 32.0 0.3 100.0 1,139 27.0 43.1 8.1 0.6 5.6 15.2 0.4 100.0 1,585 25.7 40.8 10.3 0.5 8.0 14.3 0.4 100.0 1,424 30.7 39.3 12.8 0.3 4.8 11.8 0.3 100.0 1,012 25.5 43.2 10.3 0.9 5.6 14.4 0.0 100.0 948 27.1 46.2 9.6 0.2 4.4 12.3 0.3 100.0 710 28.6 47.1 4.9 0.4 3.3 15.6 0.0 100.0 636 38.1 16.1 35.3 0.3 4.8 5.3 0.1 100.0 898 24.2 44.7 5.4 1.0 6.1 18.4 0.3 100.0 6,557 30.6 38.0 6.6 0.5 9.3 14.8 0.1 100.0 940 26.9 38.6 7.4 1.1 9.4 16.4 0.2 100.0 2,958 23.7 44.3 11.0 0.8 2.2 17.7 0.4 100.0 3,558 23.2 49.5 4.9 0.5 4.6 17.1 0.3 100.0 2,133 23.9 45.4 5.0 0.8 6.5 18.1 0.3 100.0 2,390 29.2 37.6 6.1 1.5 7.2 18.2 0.2 100.0 2,215 29.7 14.1 43.7 0.6 4.4 7.1 0.4 100.0 718 15.1 52.1 3.3 0.9 5.9 22.6 0.1 100.0 4,962 47.1 19.6 20.5 0.9 6.1 5.2 0.6 100.0 2,494 25.8 41.2 9.0 0.9 6.0 16.8 0.3 100.0 7,455 __________________________________________________________________________________________________ 1 Includes both women who receive only cash and those who receive cash and in-kind payment. 2 Includes both women who receive only in-kind payment and those who receive no payment. 3 Missing information on employer or type of earnings. All-year current employment is highest in the urban, more educated population, whereas seasonal work is more prevalent among the rural, less educated women. Women who have more children are more likely to be currently employed. Respondents from the Northern Region were more likely to be currently employed than those from Southern and Central regions. 3.6 FORM OF WOMEN’S EARNINGS Table 3.6 shows the percent distribution of employed women by type of employer and the type of earnings according to background characteristics. Sixty-seven percent of the employed women are self-employed, 23 percent work for a family member, and only 10 percent work for a nonrelative. The majority of the working women in rural areas are either self-employed or work for a family member. Similarly, less educated women and women engaged in agricultural work are more likely to be self-employed or to work for a family member. Self-employment and work for family members in these less advantaged settings usually involves work without cash payment. 30 * Characteristics of Respondents Figure 3.2 presents data on the type of earnings for employed women in the agricultural sector versus the non-agricultural sector. The majority of agricultural workers (72 percent) reported they receive no pay. For those women in non-agricultural professions, only 24 percent reported no pay. 3.7 CONTROL OVER WOMEN’S EARNINGS AND WOMEN’S CONTRIBUTION TO HOUSEHOLD EXPENDITURES To assess women’s autonomy, MDHS respondents were asked who decided how their earnings were used. Further, the survey asked employed women who earned cash, “On average, how much of your household’s expenditure do your earnings pay for: Almost none, less than half, about half, more than half, or all?” This information not only allows an evaluation of the relative importance of women’s earnings in the household economy but also has implications for the empowerment of women. It is expected that employment and earnings are more likely to empower women if they perceive their earnings as important for meeting the needs of their household. Table 3.7 shows that 51 percent of women report that they alone decide how their earnings are used, while 32 percent do not take part in household expenditure decisions, and 18 percent decide jointly with someone else (mostly husbands). The data also indicate that 75 percent of women report that one-half to all of their household’s expenditures are covered by their earnings. Although women with more education are more likely to report having a role in deciding how their earnings are spent, these same women are not more likely to contribute in a major way to the household expenditures. As a woman ages and has more children, her decisionmaking influence and contribution to meeting household expenditures increase. Characteristics of Respondents * 31 Table 3.7 Decision on use of earnings and contribution of earnings to household expenditures Percent distribution of women receiving cash earnings by person who decides how earnings are used, and by proportion of household expenditures met by earnings, according to background characteristics, Malawi 2000 ____________________________________________________________________________________________________ Person who decides Proportion of household how earnings are used expenditures met by earnings __________________________ ________________________________ Some- Less Half/ Background Self one Almost than more characteristic only Jointly1 else2 Missing Total none half than half All Missing Total Number ____________________________________________________________________________________________________ Age 15-19 20-24 25-29 30-34 35-39 40-44 45-49 Current marital status Never married Currently married/ living together Divorced, separated, widowed Number of living children 0 1-2 3-4 5+ Residence Urban Rural Region Northern Central Southern Education No education Primary 1-4 Primary 5-8 Secondary+ Total 45.4 13.2 41.4 0.0 100.0 12.6 24.8 41.1 21.1 0.4 100.0 365 48.2 14.7 37.1 0.0 100.0 4.5 24.8 48.2 22.5 0.0 100.0 649 43.8 23.9 32.2 0.0 100.0 2.5 20.9 43.5 33.1 0.0 100.0 629 55.4 17.5 26.6 0.6 100.0 2.3 18.6 45.4 33.3 0.3 100.0 489 52.9 18.4 28.7 0.0 100.0 1.0 18.4 49.9 30.7 0.0 100.0 393 56.5 19.1 24.2 0.3 100.0 2.4 18.2 43.8 35.4 0.3 100.0 292 62.7 13.8 23.5 0.0 100.0 3.0 14.5 44.5 37.9 0.0 100.0 234 62.3 6.4 31.3 0.0 100.0 15.9 26.2 37.9 19.5 0.5 100.0 312 37.5 23.5 38.8 0.1 100.0 2.3 22.0 49.4 26.3 0.0 100.0 2,186 95.7 1.0 3.1 0.3 100.0 3.7 12.7 34.3 49.1 0.3 100.0 554 49.8 13.9 36.3 0.0 100.0 11.7 23.1 41.1 23.8 0.3 100.0 503 50.1 18.5 31.4 0.1 100.0 3.3 22.0 46.1 28.5 0.1 100.0 1,132 50.3 18.6 30.9 0.2 100.0 1.7 17.4 48.0 32.7 0.2 100.0 739 52.5 18.2 29.1 0.2 100.0 1.7 20.7 44.7 32.9 0.0 100.0 678 69.1 20.1 10.9 0.0 100.0 9.0 18.5 46.1 26.5 0.0 100.0 703 45.1 17.0 37.8 0.2 100.0 2.4 21.5 45.3 30.7 0.2 100.0 2,349 45.3 16.3 38.1 0.3 100.0 5.3 29.0 49.4 16.2 0.0 100.0 439 42.3 16.2 41.4 0.0 100.0 2.1 19.7 50.5 27.8 0.0 100.0 1,293 60.5 19.6 19.7 0.2 100.0 5.2 19.1 39.2 36.2 0.3 100.0 1,320 44.6 18.1 37.3 0.0 100.0 2.2 18.2 42.6 36.9 0.0 100.0 697 46.6 14.9 38.4 0.1 100.0 3.5 20.0 44.6 31.7 0.3 100.0 851 50.0 18.1 31.5 0.3 100.0 4.7 22.5 46.4 26.2 0.2 100.0 945 65.3 20.7 14.0 0.0 100.0 5.5 22.0 48.7 23.8 0.0 100.0 558 50.6 17.7 31.6 0.1 100.0 3.9 20.8 45.4 29.7 0.1 100.0 3,052 ____________________________________________________________________________________________________ 1 With husband or someone else 2 Includes predominantly the husband The proportion of women who make decisions on their own is higher among those who are divorced, separated, or widowed (96 percent); never-married women (62 percent); urban residents (69 percent); women with a secondary education (65 percent); and Southern Region residents (61 percent). 32 * Characteristics of Respondents 3.8 MEASURES OF WOMEN’S EMPOWERMENT In addition to information on women’s education, employment status, and earnings control, the 2000 MDHS survey also obtained information on some other measures of women’s status and empowerment. In particular, questions were asked on women’s participation in specific household decisions, on their degree of acceptance of wife beating, and on their opinions about when a wife should be able to refuse sex with her husband. These data provide insight into women’s control over their lives and their environment and their attitudes toward traditional gender roles, which are important aspects of women’s empowerment relevant for understanding demographic and health behaviours. These questions are used to define three different indicators of women’s empowerment: women’s participation in decisionmaking, women’s degree of acceptance of wife beating, and their degree of acceptance of a wife’s right to refuse sex with her husband. The first measure requires little explanation since the ability to make decisions about one’s own life is of obvious importance to practical empowerment. The other two measures derive from the notion that gender equity is essential to empowerment. Responses that indicate a view that the beating of wives by husbands is justified reflect a sanction in favour of lower women’s status, both absolutely and relative to men. Although such attitudes do not necessarily signify approval of men beating their wives, they do signify women’s acceptance of norms that give men the right, in this case, to discipline women with force. Similarly, beliefs about whether and when a woman can refuse sex with her husband, reflect issues of gender equity regarding sexual rights and bodily integrity. Besides yielding an important measure of empowerment, the information about women’s attitudes toward sexual rights will be useful for improving and monitoring reproductive health programmes that depend on women’s willingness and ability to control their own sexual lives. Table 3.8 shows the percent distribution of women by the person who makes specific decisions, according to current marital status. The data show that more than 65 percent of currently married women reported that they have no say in their own health care, large household purchases, and daily household purchases. The majority of unmarried women make these decisions jointly with someone else. Table 3.9 displays the percentage of women who report that they, alone or jointly, have the final say in specific household decisions according to background characteristics. Women who are urban residents; have secondary or higher education; earn cash; or are divorced, separated, or widowed are more likely to have a final say in all given decisions. To assess women’s degree of acceptance of wife beating, the MDHS survey asked ever- married women, “Sometimes a husband is annoyed or angered by things which his wife does. In your opinion, is a husband justified in hitting or beating his wife in the following situations?” The five situations presented to women for their opinion were: if she burns the food, if she argues with him, if she goes out without telling him, if she neglects the children, and if she refuses to have sex with him. The first five columns in Table 3.10 show how acceptance of wife beating varies for each reason. The last column gives the percentages of women who feel that a husband beating his wife is justified for at least one of the given reasons. Note that empowerment decreases as the value of this indicator increases. That is to say, the more reasons with which a respondent agrees, the more “disempowered” she is according to this indicator. Characteristics of Respondents * 33 Table 3.8 Women's participation in decisionmaking Percent distribution of women by person who makes specific household decisions, according to marital status and type of decision, Malawi 2000 ___________________________________________________________________________________ Jointly with Some- Jointly some- one Household Self with one Husband else decision only husband else only only Nobody Total ____________________________________________________________________________________ CURRENTLY MARRIED OR LIVING WITH A MAN____________________________________________________________________________________ Own health care 20.5 7.1 1.6 70.6 0.2 0.1 100.0 Large household purchases 6.1 10.8 1.5 81.3 0.2 0.0 100.0 Daily household purchases 20.3 12.1 1.6 65.7 0.3 0.0 100.0 Visits to family or relatives 17.7 44.4 1.2 36.2 0.3 0.1 100.0 What food to cook each day 44.9 10.9 1.6 42.2 0.2 0.0 100.0 Number of children to bear 8.3 45.1 0.2 42.4 0.4 3.6 100.0 ___________________________________________________________________________________ NOT CURRENTLY MARRIED___________________________________________________________________________________ Own health care 38.4 na 53.6 na 6.4 1.6 100.0 Large household purchases 31.6 na 60.2 na 5.2 3.0 100.0 Daily household purchases 32.1 na 60.1 na 5.5 2.2 100.0 Visits to family or relatives 40.1 na 48.8 na 9.0 2.1 100.0 What food to cook each day 33.8 na 58.1 na 6.1 2.0 100.0 Number of children to bear 42.0 na 4.2 na 17.6 36.0 100.0 ______________________________________________________________________________________ Note: Not currently married refers to never-married, divorced, separated, or widowed women. na = Not applicable Thirty-six percent of women agree with at least one of the selected reasons for wife beating. Differentials across respondents’ background characteristics are small although rural women, women with less than secondary education, and younger women tend to be more likely to accept justifications for beating wives. Thirty-eight percent of rural women agree with at least one reason for justifying wife beating, compared with only 22 percent of urban women. The extent of control women have over when and with whom they have sex has important implications for demographic and health outcomes. To measure women’s agreement with the idea that a woman has the right to refuse to have sex with her husband, the MDHS survey asked respondents whether a wife is justified in refusing to have sex with her husband under four circumstances: she is tired or not in the mood, she has recently given birth, she knows her husband has had sex with other women, and she knows her husband has a sexually transmitted disease. Table 3.11 shows the percentage of ever-married women who say that women are justified in refusing to have sex with their husband for specific reasons, by background characteristics. The table also shows how this indicator of women’s empowerment varies with the other two indicators, namely with women’s participation in decisionmaking and women’s attitudes toward wife beating. It is worth noting that, unlike the previous indicator of empowerment, this indicator is positively related to empowerment: the more reasons women agree with, the higher is their empowerment in terms of the belief in women’s sexual rights. 34 * Characteristics of Respondents Table 3.9 Women’s participation in decisionmaking by background characteristics Percentage of women who say that they alone or jointly have the final say in specific household decisions, by background characteristics, Malawi 2000 _____________________________________________________________________________________________________ Alone or jointly have final say in: __________________________________________________ Has Has no Visits to What Number final say final say Own Making Making family food of in all in all Background health large daily relatives/ to cook children specified specified characteristic care purchases purchases friends daily to bear decisions decisions Number _____________________________________________________________________________________________________ Age 15-19 20-24 25-29 30-34 35-39 40-44 45-49 Current marital status Never married Currently married/ living together Divorced, separated, widowed Number of living children 0 1-2 3-4 5+ Residence Urban Rural Region Northern Central Southern Education No education Primary 1-4 Primary 5-8 Secondary+ Current employment Work for cash Not work for cash Not employed Total 70.2 65.6 71.4 77.1 78.7 32.1 16.0 9.6 2,867 42.7 32.9 44.4 69.3 61.8 54.1 16.0 14.8 2,957 35.3 26.0 39.2 65.1 60.4 55.8 15.3 16.6 2,401 40.3 31.1 45.1 72.1 67.3 58.8 19.1 13.4 1,566 39.2 33.1 46.7 68.0 66.4 61.0 21.3 13.4 1,424 45.1 36.7 50.3 70.3 66.5 55.9 23.7 15.3 1,053 46.0 40.1 51.1 71.6 69.5 59.4 26.5 13.6 951 89.8 90.2 91.0 85.6 90.1 27.2 22.1 4.2 2,243 29.2 18.5 34.0 63.4 57.5 53.5 9.2 17.9 9,452 95.2 94.1 94.0 93.7 94.4 74.3 68.1 1.1 1,525 70.7 67.6 72.9 78.2 79.5 34.3 17.9 8.8 3,216 41.4 31.5 43.6 68.9 62.3 56.4 18.2 15.3 4,628 37.5 28.4 42.4 66.6 63.5 57.3 18.4 15.6 2,877 38.2 30.2 44.3 68.7 65.2 57.7 18.3 14.5 2,499 57.4 51.8 65.9 81.9 75.2 63.1 24.1 5.4 2,106 45.1 37.0 47.7 68.5 65.8 49.2 17.1 15.2 11,114 51.0 35.3 55.5 75.4 87.7 53.8 16.4 4.9 1,453 42.0 36.9 46.6 70.4 66.4 50.7 15.1 14.2 5,321 50.4 42.3 52.9 69.8 63.4 51.6 21.1 15.1 6,446 37.6 28.4 37.7 62.0 56.8 51.0 16.3 19.4 3,574 43.6 35.7 47.5 68.9 64.9 49.0 15.9 15.4 4,025 50.9 42.5 55.4 74.5 72.8 51.7 17.7 10.4 4,152 69.0 67.0 77.0 85.5 84.1 58.6 30.5 3.8 1,468 53.9 47.5 60.6 77.3 75.5 60.0 27.9 9.2 3,052 42.5 32.8 45.0 65.1 64.5 51.2 15.5 15.5 4,401 46.9 40.0 49.5 71.4 65.1 47.2 15.1 14.6 5,762 47.1 39.4 50.6 70.7 67.3 51.5 18.2 13.6 13,220 __________________________________________________________________________________________________ Note: Six respondents had missing values for current employment status. Characteristics of Respondents * 35 Table 3.10 Women's attitude toward wife beating Percentage of women who agree with specific reasons justifying a husband hitting or beating his wife and percentage who agree with at least one of the reasons, by background characteristics, Malawi 2000 __________________________________________________________________________________________ Reasons justifying a husband hitting or beating his wife ________________________________________________ Agrees Goes out with at Burns Argues without Neglects Refuses least one Background the with telling the sexual specified characteristic food him him children relations reason Number __________________________________________________________________________________________ Age 15-19 20-24 25-29 30-34 35-39 40-44 45-49 Current marital status Never married Married or living together Divorced, separated, widowed Number of living children 0 1-2 3-4 5+ Residence Urban Rural Region Northern Central Southern Education No education Primary 1-4 Primary 5-8 Secondary+ Employment1 Employed for cash Employed not for cash Not employed Number of decisions in which woman has final say2 0-1 2-3 4-5 6 All women 18.9 20.7 19.2 25.2 16.9 38.5 2,867 18.9 20.9 17.1 23.9 19.0 38.4 2,957 15.3 17.1 15.9 20.4 17.7 33.7 2,401 14.5 17.7 15.8 21.0 18.1 36.1 1,566 12.9 14.9 12.8 18.0 16.6 29.7 1,424 15.8 17.7 16.1 19.7 17.6 34.4 1,053 14.9 17.1 15.9 17.5 19.3 33.1 951 17.5 18.6 16.2 23.5 15.1 35.3 2,243 16.6 18.8 16.8 21.6 18.2 36.0 9,452 15.0 17.2 15.4 19.9 19.6 34.2 1,525 18.1 19.6 17.9 23.5 16.8 37.0 3,216 17.2 19.6 16.8 22.7 19.2 37.2 4,628 15.5 17.6 16.2 20.9 17.9 34.5 2,877 14.5 16.7 14.8 18.6 16.5 32.4 2,499 7.9 10.8 11.4 13.7 11.0 22.4 2,106 18.2 20.1 17.5 23.3 19.1 38.2 11,114 19.3 25.8 22.9 28.9 23.2 43.7 1,453 18.5 18.9 16.5 22.4 20.6 37.9 5,321 14.3 16.8 15.2 19.6 14.4 32.0 6,446 15.7 17.2 15.3 19.3 18.9 34.3 3,574 19.7 20.5 17.5 23.7 19.3 38.9 4,025 16.8 20.4 18.8 23.8 18.2 37.5 4,152 9.2 11.7 10.5 16.4 10.3 25.0 1,468 17.0 19.2 15.6 22.6 19.7 36.8 3,052 17.1 19.6 19.3 23.3 18.5 38.1 4,401 15.9 17.6 15.0 20.1 16.3 33.1 5,762 18.2 18.7 16.7 21.9 18.5 34.6 3,271 17.3 20.5 17.7 22.6 19.4 39.2 3,596 15.8 18.0 16.5 22.5 16.8 35.6 3,949 14.3 16.8 14.7 19.1 16.3 32.0 2,405 16.5 18.6 16.6 21.8 17.8 35.7 13,220 ____________________________________________________________________________________________ 1 Six respondents had missing values for employment status. 2 Refers to decisions made by the woman alone or jointly with others (Table 3.9). 36 * Characteristics of Respondents Table 3.11 Women's attitude toward refusing sexual relations with husband Percentage of women who have ever been in union who agree with specific reasons justifying a wife refusing to have sexual relations with her husband and percentage who agree with all and with none of the reasons, by background characteristics, Malawi 2000 _______________________________________________________________________________________________ Reasons justifying a wife refusing sex with husband _________________________________________ Knows husband has sexual Agrees Agrees Gave relations Knows with all with no Background Tired, not birth with other husband specified specified characteristic in mood recently women has STI1 reasons reason Number ________________________________________________________________________________________________ Age 15-19 20-24 25-29 30-34 35-39 40-44 45-49 Current marital status Married or living together Divorced, separated, widowed Number of living children 0 1-2 3-4 5+ Residence Urban Rural Region Northern Central Southern Education No education Primary 1-4 Primary 5-8 Secondary+ Employment Employed for cash Employed not for cash Not employed Number of decisions in which women have final say2 0-1 2-3 4-5 6 Number of reasons for which wife beating is justified 0 1-3 4-5 Total 61.5 74.4 66.8 70.9 50.2 18.8 1,054 60.3 76.7 68.6 73.7 50.1 16.8 2,594 62.9 79.3 71.2 73.8 53.0 15.4 2,357 61.0 78.8 68.1 73.4 48.9 15.6 1,551 59.4 78.9 68.9 74.0 49.9 16.3 1,420 56.8 77.8 65.3 73.9 45.9 16.8 1,049 58.8 75.8 64.1 72.3 45.2 18.1 951 62.5 80.0 70.2 75.3 51.0 13.9 9,452 47.9 63.3 56.3 61.3 41.7 33.2 1,525 57.1 71.8 64.3 69.9 45.2 19.6 1,173 61.7 77.0 68.2 73.1 50.7 17.1 4,431 59.5 78.0 68.1 72.8 49.2 16.6 2,875 61.2 81.2 70.3 76.0 50.6 14.1 2,497 55.3 74.0 65.8 72.5 47.2 21.0 1,585 61.4 78.3 68.6 73.5 50.1 15.8 9,392 73.4 89.5 77.8 84.0 60.1 6.1 1,228 56.2 78.7 67.6 72.6 45.8 16.0 4,373 61.0 74.1 66.5 71.5 50.5 19.4 5,376 58.2 76.5 65.5 70.9 47.3 18.1 3,468 58.3 77.1 67.9 71.6 47.7 16.6 3,434 64.6 79.7 71.0 77.0 53.0 14.2 3,200 62.8 77.0 70.4 76.3 54.8 18.9 876 63.8 80.1 72.5 77.1 54.9 15.4 2,740 59.2 80.2 69.6 75.6 48.0 13.8 3,885 59.6 73.9 64.3 68.9 47.9 19.8 4,347 65.6 79.5 69.3 72.6 53.0 14.1 3,128 63.2 82.2 72.3 78.5 52.5 12.1 3,487 57.1 77.7 67.5 74.6 46.3 17.0 2,453 51.5 66.4 60.0 63.5 43.5 28.1 1,908 60.1 75.9 67.5 71.9 50.8 19.2 7,055 59.1 79.6 68.0 75.3 45.7 12.4 2,826 66.7 84.1 74.0 77.6 53.1 10.1 1,095 60.5 77.7 68.2 73.3 49.7 16.6 10,977 _______________________________________________________________________________________________ 1 Sexually transmitted infection 2 Refers to decisions made by the woman alone or jointly with others (Table 3.9). Characteristics of Respondents * 37 Fifty percent of women agree with all selected reasons and only 17 percent agree with no selected reasons. Women are most likely to agree with the right of women to refuse sex if the woman recently gave birth (78 percent). It is a cultural taboo in Malawi to have sex right after birth so this finding may not be so much a sign of empowerment as a sign of adherence to an important traditional belief. Women are least likely to agree with the right to refuse sex if the woman is tired or not in the mood (61 percent). There is little variation in this index by background characteristics. Married women are slightly more likely to agree with reasons to refuse sex than women who are divorced, separated, or widowed. Sixty percent of the women in the Northern Region agree with all reasons for a woman to refuse to have sex with her husband. This is higher than the national average of 50 percent. There is evidence for a small negative correlation between the number of decisions in which a woman has a final say and her likelihood of agreeing with the reasons for refusing sex. (i.e., women with the most decisionmaking influence are less likely to agree with justifications for refusing sex). If a woman believes in none of the mentioned justifications for wife beating, she is more likely to respond that there is no reason to refuse sex. These findings are contrary to expectations and suggest that the particular dimensions of sexual empowerment captured in the MDHS survey may not be suitable in the Malawian context. More in-depth, qualitative research would perhaps be more illuminating. 3.9 USE OF TOBACCO The use of tobacco in the household adversely affects the health status of all household members, including individuals who are not smoking. In the 2000 MDHS survey, questions were asked on whether the respondent smoked regularly and how much he or she smoked in the last 24 hours. The results revealed that the number of Malawian women age 15-49 who smoke is small, just 2 percent of those surveyed, one-half of whom are cigarette smokers. On the other hand, smoking is common among men. Table 3.12 shows that nearly one in five men age 15-54 are tobacco smokers; 19 percent smoke (pre-rolled) cigarettes and 6 percent smoke “other” types of tobacco including locally grown and rolled tobacco “cigarettes” and pipe tobacco. Smoking of pre- rolled cigarettes does not vary much by region or urban-rural residence, but smoking of “other” forms of tobacco is limited largely to rural areas of the country. Smoking is much more prevalent among men with less education. Among cigarette smokers, 31 percent smoke six or more cigarettes per day, 41 percent smoke three to five per day, 23 percent smoke one or two, and 5 percent had not smoked any cigarettes in the last 24 hours. 38 * Characteristics of Respondents Table 3.12 Use of smoking tobacco Percentage of men who smoke tobacco and percent distribution of cigarette smokers by number of cigarettes in preceding 24 hours, according to background characteristics, Malawi 2000 ___________________________________________________________________________________________________________ Number Does Number Number of cigarettes Don’t of Background not use Cigar- Other of __________________________ know/ cigarette characteristic tobacco ettes tobacco men 0 1-2 3-5 6+ missing Total smokers ___________________________________________________________________________________________________________ Residence Urban Rural Region Northern Central Southern Education No education Primary 1-4 Primary 5-8 Secondary+ Total 80.6 18.5 0.9 564 7.4 18.6 42.1 31.6 0.3 100.0 104 75.0 18.8 6.8 2,528 3.9 24.2 41.0 30.6 0.3 100.0 475 78.8 19.0 2.6 351 3.7 17.9 51.2 27.2 0.0 100.0 67 73.5 20.3 6.3 1,296 1.6 22.0 46.0 29.9 0.5 100.0 263 77.6 17.3 5.9 1,446 7.8 25.8 33.5 32.7 0.1 100.0 250 54.4 31.8 14.8 322 6.4 23.2 36.1 34.3 0.0 100.0 102 68.7 23.4 8.4 897 3.7 24.0 46.2 25.6 0.6 100.0 210 80.6 15.7 4.0 1,243 3.4 20.6 43.7 32.3 0.0 100.0 196 88.3 11.4 0.5 629 7.2 28.1 27.4 36.8 0.4 100.0 72 76.0 18.7 5.6 3,092 4.5 23.2 41.2 30.8 0.3 100.0 580 Table 3.13 Knowledge of birth registration Percentage of women age 15-49 and men age 15-54 who have heard that when a child is born they can register that child with the government and receive a birth certificate, by background characteristics, Malawi 2000 ___________________________________________ Heard that a child may be registered and receive a birth certificate Background ______________________ characteristic Women Men ____________________________________________ Residence Urban Rural Region Northern Central Southern Education No education Primary 1-4 Primary 5-8 Secondary+ Total 27.3 42.5 17.4 29.6 27.3 39.3 16.5 28.8 19.0 33.0 13.2 28.0 16.2 31.4 18.8 32.6 40.9 41.0 18.9 32.0 3.10 BIRTH REGISTRATION The Malawian government has recently launched a birth registration programme, where- by parents are urged to register all live births and obtain a birth certificate for their children. This is an important step in ensuring health care and education for all of Malawi’s children. Men and women in the MDHS survey were asked whether they knew that a child’s birth could be registered. As shown in Table 3.13, 19 percent of women and 32 percent of men know of the birth registra- tion programme. There are slight regional differ- ences in knowledge of the birth registration programme. Urban respondents and Northern respondents are more likely to know about the programme than other respondents. Similarly women and men with more education are more likely to know that a child’s birth can be regis- tered. Fertility Levels and Trends * 39 FERTILITY LEVELS AND TRENDS 4 Ladislas R. S. Mpando The assessment of the levels, trends, and differentials in fertility in Malawi is especially relevant at this time for two reasons. First, the national population policy is currently being reviewed and reevaluated for the first time since its adoption in 1994. Second, the last time a DHS survey was conducted was in 1992 and the demographic profile of the nation can no longer rely on outdated data. The 2000 Malawi Demographic and Health Survey findings will facilitate evaluation of the demographic impact of successes in the uptake of family planning in the country over the last decade. This chapter presents the 2000 MDHS results on levels, trends, and differentials in fertility based on the analysis of the reported birth histories of women age 15-49 who were interviewed during the survey. This information was collected by asking each woman to report the number of her own children living with her, the number living elsewhere, and the number who had died. She was then asked a complete history of each of her live births. The detailed information collected on each of her children included sex; year and month of birth; and if dead, age at death, or if alive, whether the child was living with the respondent. Current fertility (age-specific and total fertility) and completed fertility (number of children ever born alive to the woman) are examined in relation to various background characteristics such as urban-rural residence, educational level of the woman, and region and district of residence. 4.1 CURRENT FERTILITY LEVELS AND TRENDS The most widely used measures of current fertility are the total fertility rate (TFR) and its component age-specific fertility rates (ASFRs). The TFR is defined as the total number of births a woman would have by the end of her childbearing period if she were to pass through those years bearing children at the currently observed rates of age-specific fertility. To obtain the most recent estimates of fertility without compromising the statistical precision of estimates and also as an attempt to avoid possible displacement of births from five to six years before the survey, the three- year period just prior to the survey is used, which roughly corresponds to the calendar period 1998- 2000. Current total fertility and age-specific fertility rates for Malawi, by urban and rural area are presented in Table 4.1. The results indicate that if fertility were to remain constant at the current age-specific rates measured in the survey (within 36 months before the survey), a woman in Malawi would, on average, bear 6.3 children in her lifetime. The corresponding total fertility rates for urban and rural areas are 4.5 and 6.7 children per woman, respectively. The TFR measured in the 2000 MDHS survey is lower than the corresponding rate of 6.7 obtained in the 1992 MDHS survey (for the 1989-1992 period). The current TFR indicates that fertility in Malawi has declined by 6 percent during the past decade or so. Fertility has declined more rapidly in urban areas (18 percent) than in rural areas (3 percent) during this period. 40 * Fertility Levels and Trends Table 4.1 Current fertility Age-specific and cumulative fertility rates and the crude birth rate for the three years preceding the survey, by residence, Malawi 2000___________________________________________ Residence______________ Age group Urban Rural Total___________________________________________ 15-19 20-24 25-29 30-34 35-39 40-44 45-49 TFR 15-49 TFR 15-44 GFR CBR 134 180 172 243 319 305 223 282 272 145 232 219 104 176 167 51 100 94 1 45 41 4.5 6.7 6.3 4.5 6.4 6.1 173 233 223 40.8 46.2 45.5 ___________________________________________ Note: Rates are for the period 1-36 months preceding the survey. Rates for age group 45-49 may be slightly biased due to truncation. TFR: Total fertility rate for ages 15-49 expressed per woman GFR: General fertility rate (births ÷ no. of women 15-44) expressed per 1,000 women CBR: Crude birth rate expressed per 1,000 population A further examination of the patterns of fertility in urban and rural areas reveals that rural fertility is higher than urban fertility at every age. The peak of childbearing among women in both urban and rural areas is 20-24 as was also observed in past censuses and demographic surveys. How- ever, elevated childbearing in urban areas is rather limited to the peak at age 20-24, unlike in the rural areas where childbearing is elevated over the age range 20-34. Urban women thus tend to start limit- ing their family size (or spacing births) at an earlier age than rural women. Table 4.2 and Figure 4.1 show fertility differentials by background characteristics. In addi- tion to the urban-rural difference, there exist notable geographic and education-related variations in the TFR. Women with no formal education have a TFR of 7.3 children per woman, compared with 6.7 for those with one to four years of primary education, 6.0 for those with five to eight years of primary education, and 3.0 for those with secondary educa- tion or higher. Fertility variations across regions are not very large: women in the Southern Region have a TFR of 6.0 children per woman, about one child less than women from the Central Region who have the highest total fertility rate of 6.8. Women in the Northern Region have a TFR of 6.2 children per woman. District variation is more substantial, with TFRs ranging from 4.3 children per woman in Blantyre District to more than 7 children per woman in Mangochi, Machinga, and Kasungu districts. At the time of the survey, about 12 percent of the women interviewed reported that they were pregnant. This proportion is probably an underestimate because some women who are early in their pregnancy do not yet know that they are pregnant, and some women may not want to declare that they are pregnant. The proportions of pregnant women in urban areas (10 percent) and those with secondary education or higher (8 percent) are lower than those for the other populations subgroups. As expected, levels of current pregnancy prevalence correlate with the levels of current fertility in population subgroups. Table 4.2 also allows a crude assessment of differential trends in fertility over time among population subgroups. The mean number of children ever born alive to a women age 40-49 years is a measure of past completed fertility. A comparison of current fertility (total fertility rate) with past fertility (completed) shows, for example, that there has been a substantial decline (40 percent) in fertility in Malawi among women with secondary education or higher. There have been modest declines in fertility among women with five to eight years of primary education (9 percent), urban women (24 percent), and women in the Southern Region (8 percent). Fertility in the Northern Region and in rural areas has remained virtually constant, but fertility for women with no formal education may have actually increased by about 6 percent. Differential trends among districts are Fertility Levels and Trends * 41 Table 4.2 Fertility by background characteristics Total fertility rate for the three years preceding the survey, percentage currently pregnant, and mean number of children ever born to women age 40-49 years, by background charac- teristics, Malawi 2000___________________________________________________ Mean number of children Total Percentage ever born Background fertility currently to women characteristic rate1 pregnant age 40-49___________________________________________________ Residence Urban Rural Region Northern Central Southern Education No education Primary 1-4 Primary 5-8 Secondary and higher Districts Blantyre Karonga Kasungu Lilongwe Machinga Mangochi Mulanje Mzimba Salima Thyolo Zomba Other districts Total 4.5 9.8 5.9 6.7 12.3 6.9 6.2 11.8 6.4 6.8 12.8 7.3 6.0 11.1 6.5 7.3 11.9 6.9 6.7 12.9 7.0 6.0 12.4 6.6 3.0 7.5 5.0 4.3 9.6 6.3 5.6 11.7 6.1 7.0 14.1 7.6 6.5 13.3 6.8 7.0 14.6 6.7 7.4 10.8 6.9 5.5 9.0 6.3 6.7 10.9 6.7 6.7 14.0 7.1 5.3 10.2 6.0 6.2 11.2 6.1 6.8 12.3 7.2 6.3 11.9 6.8 ___________________________________________________ 1 Rate for women age 15-49 years. notable. In Blantyre, fertility has declined by about 2 children per woman and in Thyolo and Mulanje, declines of 0.7 to 0.8 children per women occurred. On the other hand, the data indicates that little decrease in fertility has taken place in Zomba, Lilongwe, Salima, and Mzimba. In the districts of Mangochi and Machinga, fertility levels may have risen slightly. More direct evidence of the declining trend in fertility is obtained by looking at changes in age-specific fertility rates across three surveys that were conducted in Malawi since the early 1980s: the 1984 Family Formation Survey, the 1992 MDHS survey, and the 2000 MDHS survey (Table 4.3 and Figure 4.2). The results show that fertility declined in all groups between the 1984 and 1992 surveys. Between the 1992 and 2000 surveys, fairly dramatic downturns in fertility were seen at age 30 and above, but under age 25, fertility may have slightly increased. Over the whole period covered by the surveys (early 1980s to late 1990s), the TFR decreased by 17 percent. 42 * Fertility Levels and Trends Table 4.3 Trends in fertility Age-specific fertility rates (per 1,000 women) and total fertility rates for the three years preceding the survey, Malawi 1984, 1992, and 2000____________________________________________ 1984 1992 2000 Age group FFS1 MDHS MDHS____________________________________________ 15-19 202 161 172 20-24 319 287 305 25-29 309 269 272 30-34 273 254 219 35-39 201 197 167 40-44 129 120 94 45-49 83 58 41 Total fertility rate 7.6 6.7 6.3 ____________________________________________ 1 Family Formation Survey. Based on four years prior to survey. Further evidence of a recent modest de- cline in fertility in Malawi comes from analysis of the fertility of age cohorts of women in the 2000 MDHS survey (i.e., by examining trends within age groups). Table 4.4 shows age-specific fertility rates for four-year periods preceding the survey. Because women age 50 and above were not interviewed in the survey, the rates for calendar periods preceding the survey will be increasingly truncated by the exclusion of the fertility experi- ence of older women. The table shows that, again, the reduction in total fertility rates is due principally to declines in the older age groups. There has been little or no change in fertility among women age 20-24, and a small recent rise in women age15-19. The rise in contraceptive use occurring over the last decade (see next chapter) is likely to explain, at least in part, the fertility trends documented here. Fertility Levels and Trends * 43 Table 4.4 Trends in age-specific fertility rates Age-specific fertility rates for four-year periods preceding the survey, by mother's age at the time of the birth, Malawi 2000 ______________________________________________________ Number of years preceding survey Mother's __________________________________________ age at birth 0-3 4-7 8-11 12-15 16-19 ______________________________________________________ 15-19 20-24 25-29 30-34 35-39 40-44 45-49 167 151 161 180 188 307 304 305 308 302 276 275 286 308 [294] 219 237 264 [272] - 169 179 [209] - - 99 [116] - - - [50] - - - - _______________________________________________________ Note: Age-specific fertility rates are per 1,000 women. Estimates in brackets are truncated. Figure 4.2 Trends in Age-Specific Fertility Rates 1984 FFS, 1992 MDHS, and 2000 MDHS , , , , , , , % % % % % % % ! ! ! ! ! ! ! 15-19 20-24 25-29 30-34 35-39 40-44 45-49 . Age Group (years) 0 50 100 150 200 250 300 350 Births per 1,000 Women MDHS 2000 MDHS 1992 FFS 1984! % , Note: FFS is the Family Formation Survey 44 * Fertility Levels and Trends Table 4.5 Children ever born and living Percent distribution of all women and currently married women by number of children ever born (CEB), and mean number of children ever born and mean number of living children, according to age group, Malawi 2000_____________________________________________________________________________________________________________ Mean Mean number Number of children ever born number of ___________________________________________________________________ of living Age 0 1 2 3 4 5 6 7 8 9 10+ Total Number CEB children _____________________________________________________________________________________________________________ ALL WOMEN____________________________________________________________________________________________________________ 15-19 20-24 25-29 30-34 35-39 40-44 45-49 Total 74.6 20.9 4.0 0.4 0.1 0.0 0.0 0.0 0.0 0.0 0.0 100.0 2,867 0.30 0.26 16.7 33.3 31.8 14.5 3.2 0.4 0.1 0.0 0.0 0.0 0.0 100.0 2,957 1.56 1.29 4.0 9.9 19.1 30.0 20.5 11.5 4.0 0.7 0.1 0.1 0.0 100.0 2,401 3.09 2.46 3.0 5.5 7.5 11.5 21.1 21.9 15.8 9.6 2.7 0.8 0.5 100.0 1,566 4.46 3.56 2.2 4.4 6.3 7.6 10.3 12.4 19.9 15.5 12.9 5.6 2.9 100.0 1,424 5.55 4.30 1.8 3.0 3.8 7.2 8.2 7.6 12.7 14.8 14.9 11.3 14.9 100.0 1,053 6.63 4.97 2.0 3.2 4.3 5.7 5.5 9.6 12.1 11.3 13.5 12.0 20.8 100.0 951 6.99 4.89 21.5 15.4 13.6 11.9 9.1 7.4 6.6 4.9 3.9 2.5 3.1 100.0 13,220 3.13 2.42 ___________________________________________________________________________________________________________ CURRENTLY MARRIED WOMEN____________________________________________________________________________________________________________ 15-19 20-24 25-29 30-34 35-39 40-44 45-49 Total 39.8 48.3 10.7 0.9 0.3 0.0 0.0 0.0 0.0 0.0 0.0 100.0 934 0.74 0.62 8.8 34.0 35.6 17.3 3.7 0.5 0.1 0.0 0.0 0.0 0.0 100.0 2,324 1.75 1.44 2.4 9.0 18.7 31.0 21.1 12.3 4.3 0.8 0.2 0.1 0.0 100.0 2,102 3.19 2.56 2.8 4.5 6.1 10.0 21.4 23.2 17.0 10.7 2.8 0.9 0.5 100.0 1,312 4.62 3.69 2.2 3.8 5.6 7.1 9.9 12.4 20.1 15.7 13.5 6.5 3.3 100.0 1,192 5.69 4.42 1.6 2.7 3.2 6.9 8.0 6.4 12.0 14.8 15.2 12.8 16.5 100.0 848 6.84 5.16 2.0 3.6 3.5 6.0 5.5 8.6 10.4 10.5 14.5 13.0 22.4 100.0 739 7.11 4.98 7.6 16.8 16.1 14.6 11.0 8.9 7.8 5.8 4.6 3.1 3.7 100.0 9,452 3.74 2.91 4.2 CHILDREN EVER BORN The distribution of women by number of children ever born is presented in Table 4.5 for all women and currently married women. The table also shows the mean number of children ever born (CEB) to women in each five-year age group. On average, women have given birth to three children by their late twenties, six children by their late thirties, and seven children by age 45-49. Of the 7 children ever born to women age 45-49, only 4.9, or about 70 percent, have survived. The distribution of women by children ever born indicates that about one-quarter of the women age 15-19 have already given birth to at least one child, and about one fifth of the women age 45-49 have had ten or more children. The results for younger women who are currently married differ from those for the sample as a whole because of the large number of young unmarried women with minimal fertility. Differences at older ages, though modest, generally reflect the impact of marital dissolution althrough divorce or widowhood. The desire for children is nearly universal in Malawi and so the proportion of married women at 45-49 years who are still childless is a rough indicator of primary infertility, or the inability to bear children. The survey results suggest that primary infertility is low in Malawi, with only 2 percent of Malawian women unable to bear children. It should be pointed out here that this estimate of primary infertility does not include women who may have had one or more births but who are unable to have more children, or secondary infertility. Fertility Levels and Trends * 45 Table 4.6 Birth intervals Percent distribution of non-first births in the five years preceding the survey by number of months since preceding birth, according to demographic and background characteristics, Malawi 2000____________________________________________________________________________________________________ Median number of months Months since preceding birth since Background ____________________________________________ preceding characteristic 7-17 18-23 24-35 36-47 48+ Total birth Number____________________________________________________________________________________________________ Age 15-19 20-29 30-39 40-49 Birth order 2-3 4-6 7 + Sex of preceding birth Male Female Survival of preceding birth Living Dead Residence Urban Rural Region Northern Central Southern Education No education Primary 1-4 Primary 5-8 Secondary+ Total 13.9 26.6 44.4 12.1 3.0 100.0 25.7 128 6.3 13.6 45.2 21.5 13.4 100.0 31.6 5,047 3.8 9.6 33.5 25.9 27.2 100.0 36.8 3,188 5.5 6.7 29.0 23.9 35.0 100.0 39.7 967 5.7 13.3 43.6 21.1 16.3 100.0 32.1 4,247 4.9 10.6 37.2 25.3 22.1 100.0 35.2 3,401 6.0 9.8 33.8 24.0 26.4 100.0 36.1 1,681 5.1 11.8 39.5 23.5 20.1 100.0 34.0 4,633 5.9 11.6 39.5 22.7 20.3 100.0 33.7 4,697 3.0 9.8 41.1 24.8 21.3 100.0 34.8 7,468 15.3 19.2 33.1 16.4 16.0 100.0 28.2 1,862 3.5 10.1 35.8 24.8 25.9 100.0 36.2 1,018 5.7 11.9 40.0 22.9 19.5 100.0 33.6 8,312 3.6 8.7 38.6 26.2 22.8 100.0 35.7 1,050 6.1 11.8 40.4 23.1 18.6 100.0 33.3 4,140 5.4 12.3 38.8 22.4 21.2 100.0 33.7 4,141 5.5 12.0 38.0 22.9 21.5 100.0 34.3 3,408 6.0 12.4 40.5 21.9 19.2 100.0 32.9 2,943 4.9 10.9 41.0 24.3 18.9 100.0 33.8 2,614 4.7 8.2 34.6 26.4 26.1 100.0 36.9 365 5.5 11.7 39.5 23.1 20.2 100.0 33.8 9,330 ____________________________________________________________________________________________________ Note: First-order births are excluded. The interval for multiple births is the number of months since the preceding pregnancy that ended in a live birth. 4.3 BIRTH INTERVALS Information on the length of birth intervals provides insight into birth spacing patterns. Research has shown that children born too soon after a previous birth are at an increased risk of poor health and consequently an increased risk of dying, particularly when the interval between births is less than 24 months. Maternal health is also jeopardised when births are closely spaced. Table 4.6 shows the distribution of births in the five-year period preceding the survey by the number of months since the previous birth, according to various selected demographic and socioeconomic variables. First births are excluded from the table. The survey results indicate that about one in every six births (17 percent) in Malawi occurs less than 24 months after the birth of the previous child. The overall median birth interval length is 33.8 months, which is about one month longer than it was in the 1992 MDHS survey. 46 * Fertility Levels and Trends Table 4.7 Age at first birth Percentage of women who had their first birth by specific exact ages and median age at first birth, by current age, Malawi 2000 ___________________________________________________________________________________ Percentage who have Median Percentage who had first birth by exact age: never age at ____________________________________ given first Current age 15 18 20 22 25 birth Number birth ___________________________________________________________________________________ 15-19 20-24 25-29 30-34 35-39 40-44 45-49 1.3 na na na na 74.6 2,867 a 4.2 30.3 61.7 na na 16.7 2,957 19.3 5.8 32.7 60.9 82.0 92.9 4.0 2,401 19.2 7.8 38.5 65.3 83.2 92.7 3.0 1,566 18.8 7.4 36.5 62.4 78.1 90.1 2.2 1,424 19.0 10.6 39.6 62.6 79.8 91.6 1.8 1,053 19.0 7.0 33.6 60.0 73.2 85.1 2.0 951 19.2 ____________________________________________________________________________________ na = Not applicable a Omitted in populations where less than 50 percent of the women in the age group × to × + 4 have had a birth by age × In Malawi, birth intervals tend to be shorter for younger mothers and for births occurring after the preceding sibling has died. The latter relationship is the result largely of replacement fertility, whereby a mother will get pregnant again soon after the death of a child. The median birth interval length is shortened by about seven months when the preceding sibling dies. The results also show that only 13 percent of the births to women with secondary education or higher were born after less than 24 months, compared to 18 percent of the births to women with less than 5 years of primary education. 4.4 AGE OF MOTHERS AT FIRST BIRTH One of the factors that determines the level of current fertility in a population is the average age at first birth. Early childbearing generally leads to a large family size and is often associated with increased health risks for the mother and potential health hazards for the children. A rise in the median age at first birth is typically a sign of transition to lower fertility levels. Table 4.7 presents the percentage of women who have given birth by specified ages and the median age at first birth, according to current age. The results show that the median age at first birth for the youngest cohort of women is 19.3 years, a modest increase of 0.4 years over the median age measured in the 1992 MDHS survey. However, there is also evidence of a modest increase in the median age at first birth for all the women age 20-49. In the 1992 MDHS survey, the median age at first birth was 18.9 years, 0.2 years lower than the median age of 19.1 observed in 2000 MDHS survey. This interpretation is supported by the decrease in the percentage of births that occurred at a very young age (less than 15 years) from 8 percent among women currently age 30-34 to only 1 percent among the women now age 15-19. Further, the percentage of births occurring at very young ages has declined from about 3 percent as observed in the 1992 MDHS survey to the current level of 1 percent. Fertility Levels and Trends * 47 Table 4.8 Median age at first birth by background characteristics Median age at first birth among women age 20-49 years, by current age and background characteristics, Malawi 2000__________________________________________________________________________________________________ Current age Women Women Background _____________________________________________________ age age characteristic 20-24 25-29 30-34 35-39 40-44 45-49 20-49 25-49__________________________________________________________________________________________________ Residence Urban Rural Region Northern Central Southern Education No education Primary 1-4 Primary 5-8 Secondary+ All women 20.1 19.8 19.0 19.5 19.3 18.9 19.7 19.4 19.1 19.2 18.8 18.9 18.9 19.3 19.0 19.0 19.0 18.6 18.9 18.4 18.6 18.4 18.7 18.6 19.6 19.4 19.0 19.3 19.4 19.4 19.4 19.3 19.0 19.2 18.6 18.9 18.7 19.3 19.0 18.9 18.4 18.9 18.3 19.3 18.8 19.6 18.8 18.9 18.9 19.1 18.7 18.3 18.3 19.1 18.8 18.8 19.1 19.1 19.1 19.1 19.3 18.5 19.1 19.1 20+a 22.3 21.3 21.1 21.3 19.6 20+a 21.6 19.3 19.2 18.8 19.0 19.0 19.2 19.1 19.1 _________________________________________________________________________________________________ a Less than 50 percent of respondents have had a birth by age 20; median is at least 20 years. Table 4.8 shows the median age at first birth for different age cohorts of women across urban-rural residence, regional, and educational subgroups. There is a small difference in the median age at first birth between urban women (19.7 years) and rural women (19.0 years). At the regional level, first births occur later, on average, in the Central Region than in the Northern and Southern regions. Age at first birth varies significantly with a woman’s level of education, ranging from 19 years for women with no education or primary education to 22 years among women with secondary education or higher. 4.4.1 ADOLESCENT FERTILITY The issue of adolescent fertility is important for both health and social reasons. Children born to very young mothers face an increased risk of illness and death. Adolescent mothers themselves are more likely to experience adverse pregnancy outcomes and maternity-related mortality than more mature women, and they are more constrained in their ability to pursue educational opportunities than their counterparts who delay childbearing. Table 4.9 shows the percentage of adolescent women (age 15-19) who were mothers or pregnant with their first child by selected background characteristics. About one-quarter of adolescent women in Malawi are already mothers with at least one child, and a further 8 percent are currently pregnant. The proportion of teenagers already on the family formation pathway rises very rapidly with age. Only about 4 percent of women age 15 have started childbearing, but by age 19, about two-thirds are pregnant or have had a baby. Overall, 33 percent of adolescents have begun childbearing, compared with 35 percent based on the 1992 MDHS survey. In rural areas, 34 percent of the adolescents have already begun childbearing, compared with 27 percent in urban areas. Regional variations also exist: 36 percent of the adolescents in the Southern Region are either mothers or are pregnant with their first child, compared with 33 percent and 30 percent of their counterparts in the Northern and Central regions, respectively. 48 * Fertility Levels and Trends Table 4.9 Teenage pregnancy and motherhood Percentage of women age 15-19 who are mothers or pregnant with their first child, by background characteristics, Malawi 2000_______________________________________________________________ Percentage who are: Percentage_________________ who have Pregnant begun Background with first child- characteristic Mothers child bearing Number_______________________________________________________________ Age 15 16 17 18 19 Residence Urban Rural Region Northern Central Southern Education No education Primary 1-4 Primary 5-8 Secondary+ Total 2.0 2.3 4.2 541 7.6 5.6 13.2 577 21.5 8.0 29.5 501 37.0 11.5 48.5 723 56.6 9.8 66.4 524 20.1 7.0 27.1 490 26.4 7.8 34.2 2,377 23.8 9.0 32.8 332 22.3 7.4 29.7 1,122 28.1 7.5 35.7 1,413 46.6 9.4 56.1 219 27.5 7.6 35.1 943 23.5 8.2 31.7 1,297 14.8 4.9 19.7 408 25.4 7.6 33.0 2,867 A strong link between continuing education and early motherhood is clear from the survey results (Figure 4.3). Whereas 56 percent of adolescents with no formal education have started childbearing, only 20 percent of their counterparts with secondary education or higher have done so. Fertility Regulation * 49 FERTILITY REGULATION 5 George J. Mandere This chapter presents the 2000 MDHS results on contraceptive knowledge, attitudes, and behaviour. Although the focus is on women, some results from the male survey will also be presented since men play an important role in the realisation of reproductive goals. Comparisons are also made, where feasible, with findings from previous surveys in order to evaluate trends occurring in Malawi over the last decade. 5.1 KNOWLEDGE OF CONTRACEPTIVE METHODS Acquiring knowledge about fertility control is an important step toward gaining access to and then using a suitable contraceptive method in a timely and effective manner. Information on knowledge of contraception was collected by asking the respondent to name ways or methods by which a couple could delay or avoid pregnancy. If the respondent failed to mention a particular method spontaneously, the interviewer described the method and asked whether the respondent recognised it. Modern family planning methods—the pill, the IUD, injectables, vaginal methods (jelly, sponge, and diaphragm), male and female condoms, female and male sterilisation, the lactational amenorrhoea method (LAM), implants, and emergency contraception—were described, as well as two methods categorised as traditional (periodic abstinence and withdrawal). All other traditional or “folk” methods mentioned by the respondent, such as using herbs and tying strings around the waist, were recorded as well. In Table 5.1, knowledge of contraceptive methods is presented for all women and men, for currently married women and men, for sexually active unmarried women and men, for sexually inactive unmarried women and men, and for women and men with no sexual experience, by specific method. The 2000 MDHS survey finds that 97 percent of all women age 15-49 know at least one method of family planning. Knowledge of a modern method is higher for currently married women and sexually active unmarried women than among women with no sexual experience. The most widely known modern contraceptive methods among all women are injection (92 percent), pill (91 percent), male condom (90 percent), and female sterilisation (83 percent). Nearly all currently married men and sexually actively unmarried men know about fertility regulation. Even among men with no sexual experience, knowledge of any method is high (88 percent). The male condom (96 percent), female sterilisation (88 percent), injectables (87 percent), the pill (87 percent), and male sterilisation (68 percent) were the most widely known modern contraceptive methods among men. It is important to note that both unmarried male and female respondents who have never had sex possess a much more limited base of contraceptive knowledge than their sexually active counterparts. Programmes aimed at reducing adolescent pregnancy may see this as a challenge to improve educational interventions on knowledge and appropriate use of family planning methods. 50 * Fertility Regulation Table 5.1 Knowledge of contraceptive methods Percentage of all women and men, of currently married women and men, of sexually active unmarried women and men, of sexually inactive unmarried women and men, and of women and men with no sexual experience who know any contraceptive method, by specific method, Malawi 2000 ______________________________________________________________________________________________________________ Women Men ________________________________________ _______________________________________ Unmarried women: Unmarried men: ever had sex Un- ever had sex Un- Cur- ______________ married Cur- ______________ married rently Not women: rently Not men: Contraceptive All married Sexually sexually never All married Sexually sexually never method women women active1 active2 had sex men men active1 active2 had sex _____________________________________________________________________________________________________________ Any method Any modern method Pill IUD Injectables Diaphragm/Foam/Jelly Female condom Male condom Female sterilisation Male sterilisation Implants Emergency contraception Lactational amenorrhoea (LAM) Any traditional method Periodic abstinence Withdrawal Other methods3 Mean no. of methods known Number 96.8 98.6 98.2 97.2 82.9 98.3 99.7 99.0 98.7 88.2 96.5 98.4 98.2 96.7 82.7 98.2 99.5 99.0 98.7 88.2 91.0 94.9 91.2 90.7 65.1 86.8 93.0 82.6 81.8 61.7 64.7 70.4 64.2 61.7 30.3 49.9 60.4 38.7 37.7 18.9 92.2 95.5 93.0 91.6 69.6 86.6 93.0 84.2 80.5 61.2 35.8 39.9 34.3 34.7 9.8 26.7 31.2 24.2 21.9 10.5 47.7 51.6 53.1 48.0 19.7 52.3 57.2 49.8 47.6 33.3 89.8 92.2 94.3 89.7 71.9 96.3 97.7 96.9 96.2 86.5 82.8 87.5 78.7 82.2 52.6 87.7 92.5 88.0 85.7 61.5 55.4 60.2 54.4 51.7 28.2 67.8 72.9 64.0 65.7 43.8 48.0 52.4 48.4 45.8 20.9 27.8 32.9 22.9 21.3 13.1 20.4 22.2 28.9 20.4 6.1 19.8 22.7 16.8 17.9 7.9 38.7 43.2 37.8 35.7 11.9 37.3 45.4 31.2 28.2 10.1 65.5 73.0 65.2 63.0 17.3 74.2 86.8 67.5 60.9 27.7 42.0 46.4 48.1 41.0 12.3 57.3 68.7 50.6 45.3 15.7 40.4 46.0 42.2 37.5 6.2 51.8 61.1 48.4 41.5 17.4 35.2 39.9 37.4 33.2 4.6 23.1 32.3 11.2 9.8 2.7 8.4 9.0 8.6 8.1 4.2 8.0 9.0 7.3 7.0 4.5 13,220 9,452 317 2,076 1,375 3,092 1,906 281 599 306 ______________________________________________________________________________________________________________ 1 Unmarried women/men who have had sexual intercourse in the month preceding the survey 2 Unmarried women/men who have ever had sexual intercourse but have not had sexual intercourse in the month preceding the survey 3 Includes mostly folk methods such as tying strings around waist and taking herbs. 5.2 KNOWLEDGE OF CONTRACEPTIVE METHODS BY BACKGROUND CHARACTERISTICS Table 5.2 shows that knowledge of at least one modern family planning method is universally high (95 percent or more) among all subgroups of the currently married women and men in Malawi. Women age 15-19 and 45-49 and women with no education had slightly lower awareness levels. Also, women from Salima, Karonga, and Machinga were less likely to know of modern methods than women from other districts. The pattern of results for men is similar, with knowledge of contraceptive methods being uniformly high in all population subgroups. The youngest married men, however, do possess a more limited knowledge of contraception than both older men and their same-age female counterparts. Fertility Regulation * 51 Table 5.2 Knowledge of contraceptive methods by background characteristics Percentage of currently married women and men who know at least one contraceptive method and who know at least one modern method, by background characteristics, Malawi 2000 _____________________________________________________________________________________________________ Women Men ____________________________________ _______________________________________ Knows Knows Knows three Knows three Knows any or more Knows any or more Background any modern modern any modern modern characteristic method method1 methods1 Number method method1 methods1 Number _____________________________________________________________________________________________________ Age 15-19 20-24 25-29 30-34 35-39 40-44 45-49 50-54 Residence Urban Rural Region Northern Central Southern Districts Blantyre Karonga Kasungu Lilongwe Machinga Mangochi Mulanje Mzimba Salima Thyolo Zomba Other districts Education No education Primary 1-4 Primary 5-8 Secondary+ Total 96.4 96.3 89.7 934 (100.0) (94.9) (74.8) 23 99.1 98.9 95.9 2,324 100.0 99.9 94.2 236 98.9 98.7 96.3 2,102 99.7 99.7 98.9 441 99.1 99.1 97.2 1,312 100.0 100.0 98.7 308 99.3 99.2 95.4 1,192 100.0 100.0 98.2 314 98.6 98.3 95.5 848 99.0 99.0 96.1 228 97.4 96.8 93.1 739 98.8 98.8 97.1 195 na na na na 100.0 99.1 94.3 161 99.9 99.8 99.2 1,362 100.0 99.9 99.0 307 98.4 98.2 94.6 8,089 99.6 99.5 96.6 1,599 98.1 97.7 95.2 1,075 100.0 99.9 94.4 217 98.5 98.3 94.7 3,919 99.8 99.8 97.3 775 98.9 98.7 95.7 4,458 99.5 99.2 97.3 914 100.0 100.0 98.0 837 100.0 100.0 99.4 184 95.1 94.8 90.0 191 100.0 99.3 92.9 40 99.3 99.1 96.4 367 100.0 100.0 98.1 84 99.7 99.7 97.2 1,402 100.0 100.0 97.3 279 96.4 96.2 91.1 374 98.9 98.9 97.7 75 98.6 98.3 93.9 467 98.6 98.6 97.2 92 100.0 100.0 99.1 429 100.0 100.0 99.0 75 98.8 98.6 96.3 458 100.0 100.0 94.3 95 95.4 95.2 89.0 223 100.0 100.0 94.1 43 100.0 99.8 97.2 456 100.0 100.0 99.1 94 98.9 98.5 95.8 564 100.0 99.7 98.3 105 98.1 97.8 94.1 3,683 99.5 99.2 96.1 739 97.7 97.4 92.6 2,975 99.2 99.2 94.5 265 98.7 98.4 95.0 2,980 99.5 99.2 96.0 565 99.2 99.2 97.2 2,784 99.8 99.6 97.4 737 100.0 100.0 99.7 713 100.0 100.0 99.7 338 98.6 98.4 95.2 9,452.0 99.7 99.5 97.0 1,906 ______________________________________________________________________________________________________ na = Not applicable 1 Pill, IUD, injectables, diaphragm/foam/jelly, condom, female sterilisation, male sterilisation, implants, LAM or emergency contraception. ( ) Estimate based on 25-49 unweighted cases. 52 * Fertility Regulation 5.3 EVER USE OF CONTRACEPTION All women and men interviewed in the survey who said they had heard of a method of family planning were asked whether they had ever used that method. Tables 5.3.1 and 5.3.2 show the percent distribution of women and men who have ever used family planning by specific method and age. Forty-five percent of women and 65 percent of men reported having used a method at some time. Thirty-nine percent of women and 56 percent of men reported having used a modern method at some time. Of those currently married, 52 percent of women and 79 percent of men had used a method in the past; 45 percent of women and 66 percent of men used a modern method. Among currently married women, the most commonly used modern methods were injectables (30 percent), the pill (11 percent), male condoms (8 percent), and LAM (6 percent). For currently married men, use of the male condom (35 percent) was highest, followed by injectables (28 percent), the pill (20 percent), LAM (18 percent), and female sterilisation (6 percent). The large difference between men and women in ever use of contraception is due to the greater use of the male condom among men. For the sexually active unmarried population, ever use of any contraceptive method was 49 percent for women and 62 percent for men; modern method use was 44 percent for women and 59 percent for men. The most commonly used methods among women were the male condom (22 percent) and injectables (16 percent); among men, the male condom (57 percent) was by far the predominant method, with much lower use of the pill (5 percent) and injectables (3 percent). 5.4 CURRENT USE OF CONTRACEPTIVE METHODS In the 2000 MDHS, women and men were asked about the contraceptive method they were currently using. For women, current use was elicited from the question, “Are you currently doing something or using any method to delay or avoid getting pregnant?” However, for men the question was asked slightly differently. Men were first asked, “When was the last time you had sex?”—then they were asked, “On that occasion, did you or your partner do something to avoid pregnancy?” This means that for men, the current contraceptive method refers to the method employed at last sexual encounter. Table 5.4 shows the percent distribution of women and men who are currently using specific family planning methods by age. The 2000 MDHS indicates that 31 percent of currently married women are using a method of family planning. The 26 percent using a modern method represents a dramatic increase in the use of modern methods from 7 percent in the 1992 MDHS and 14 percent in the 1996 MKAPH—an approximate doubling of use every four years (see Figure 5.1). The increase in the use of modern contraceptive methods is due to a sharp rise in use of injectables and a small increase in female sterilisation. The use of injectables has more than doubled in four years, from 6 percent in 1996 to 16 percent in 2000, while the percentage of currently married women who have been sterilised grew from 3 to 5 percent. Use of other modern methods is lower: the pill (3 percent), the condom (2 percent), and the IUD, male sterilisation, implants, and LAM (each less than 0.5 percent). Contraceptive use varies by age. Current use of a modern contraceptive method is 13 percent for married women age 15-19, rises to 32 percent among women age 35-44, and then drops sharply to 20 percent at age 45-49. Most of the women who are sterilised are age 35 and over; injectables are predominant in the peak childbearing ages (20-39); and under age 20, condoms are favoured (i.e., especially among the unmarried). Fertility Regulation * 53 Ta bl e 5. 3. 1 E ve r u se o f c on tra ce pt io n: w om en Pe rc en ta ge o f a ll w om en , o f c ur re nt ly m ar rie d w om en , a nd o f s ex ua lly a ct iv e un m ar rie d w om en w ho h av e ev er u se d a co nt ra ce pt iv e m et ho d, b y sp ec ifi c m et ho d an d ag e, M al aw i 2 00 0 __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ _ M od er n m et ho d Tr ad iti on al m et ho d __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ _ An y An y D ia ph ra gm / Fe m al e M al e Em er ge nc y tra di - Pe rio di c An y m od er n In je ct - Fo am / Fe m al e M al e st er ili - st er ili - Im - co nt ra - tio na l ab st i- W ith - Ag e m et ho d m et ho d Pi ll IU D ab le s Je lly co nd om co nd om sa tio n sa tio n pl an t ce pt io n LA M m et ho d ne nc e dr aw al O th er 1 N um be r __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ _ AL L W O M EN __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ 15 -1 9 20 -2 4 25 -2 9 30 -3 4 35 -3 9 40 -4 4 45 -4 9 Al l a ge s 15 .1 13 .5 1 .7 0. 0 4 .5 0. 1 0. 1 7 .2 0 .0 0. 0 0. 0 0. 3 1 .5 3 .9 2 .5 1 .7 0 .6 2, 86 7 45 .4 39 .4 7 .7 0. 2 24 .9 0. 4 0. 2 11 .4 0 .5 0. 0 0. 2 0. 7 5 .5 14 .5 6 .2 6 .7 4 .8 2, 95 7 59 .1 52 .3 12 .1 0. 9 35 .4 0. 4 0. 1 11 .5 1 .9 0. 1 0. 3 0. 4 7 .3 19 .6 7 .6 8 .4 7 .6 2, 40 1 59 .4 51 .0 16 .7 1. 1 36 .2 0. 3 0. 2 8 .1 4 .6 0. 3 0. 6 0. 4 6 .5 22 .6 7 .4 10 .5 9 .9 1, 56 6 56 .2 49 .4 15 .0 1. 3 31 .1 0. 8 0. 1 6 .0 10 .0 0. 0 0. 4 0. 2 6 .1 19 .1 6 .0 8 .4 8 .4 1, 42 4 55 .4 45 .5 13 .8 1. 2 28 .6 0. 7 0. 3 5 .2 13 .0 0. 0 0. 2 0. 2 5 .3 21 .6 7 .5 7 .8 12 .2 1, 05 3 44 .7 32 .5 9 .2 1. 4 17 .2 0. 4 0. 0 2 .6 9 .6 0. 3 0. 2 0. 9 4 .7 22 .0 6 .7 6 .4 13 .5 9 51 44 .9 38 .6 9 .7 0. 7 24 .1 0. 4 0. 2 8 .4 3 .8 0. 1 0. 2 0. 4 5 .1 15 .7 5 .9 6 .6 6 .6 13 ,2 20 __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ C U RR EN TL Y M AR RI ED W O M EN __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ 15 -1 9 20 -2 4 25 -2 9 30 -3 4 35 -3 9 40 -4 4 45 -4 9 Al l a ge s 28 .1 24 .1 2 .8 0. 0 11 .6 0. 2 0. 3 8 .7 0 .0 0. 0 0. 2 0. 6 3 .6 8 .8 5 .7 3 .9 1 .5 9 34 47 .9 41 .3 8 .0 0. 2 27 .4 0. 5 0. 3 10 .7 0 .6 0. 0 0. 2 0. 8 6 .2 16 .3 7 .1 7 .5 5 .5 2, 32 4 59 .6 52 .8 12 .1 1. 0 36 .2 0. 5 0. 1 10 .8 2 .0 0. 1 0. 3 0. 4 7 .5 19 .4 7 .6 8 .3 7 .8 2, 10 2 60 .6 52 .2 16 .9 1. 2 37 .8 0. 1 0. 1 7 .5 5 .1 0. 2 0. 7 0. 4 6 .8 23 .6 7 .3 11 .1 10 .4 1, 31 2 57 .8 50 .9 15 .7 1. 4 32 .5 0. 9 0. 2 5 .5 10 .7 0. 0 0. 4 0. 2 6 .6 19 .7 6 .1 9 .0 8 .6 1, 19 2 57 .3 47 .6 13 .8 1. 3 30 .7 0. 4 0. 2 5 .8 13 .9 0. 0 0. 0 0. 3 5 .5 22 .9 7 .1 8 .2 13 .2 8 48 47 .3 35 .1 9 .9 1. 5 18 .7 0. 4 0. 0 2 .8 10 .8 0. 4 0. 2 1. 2 4 .1 21 .7 5 .3 6 .4 14 .4 7 39 5 2. 4 45 .0 11 .3 0. 8 29 .5 0. 4 0. 2 8 .4 4 .7 0. 1 0. 3 0. 5 6 .1 18 .7 6 .8 8 .0 8 .1 9, 45 2 __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ _ SE XU AL LY A C TI VE U N M AR RI ED W O M EN 2 __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ 15 -2 9 30 -4 9 Al l a ge s 44 .3 41 .0 4 .0 0. 1 6 .2 0. 0 0. 0 13 .3 0 .3 0. 0 0. 0 0. 0 0 .6 10 .4 0 .4 0 .0 0 .8 25 0 67 .7 53 .1 0 .0 0. 0 13 .1 0. 0 0. 0 1 .7 13 .2 0. 0 2. 2 0. 0 0 .0 31 .5 0 .0 0 .0 1 .3 6 7 49 .2 43 .6 11 .4 1. 0 16 .3 0. 1 0. 0 22 .3 3 .0 0. 0 0. 5 0. 4 4 .8 14 .8 5 .9 7 .3 5 .3 31 7 __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ _ 1 In cl ud es m os tly fo lk m et ho ds s uc h as ty in g st rin g ar ou nd w ai st a nd ta ki ng h er bs . 2 Se xu al ly a ct iv e un m ar rie d w om en a re th os e w ho h av e ha d se xu al in te rc ou rs e in th e on e m on th p re ce di ng th e su rv ey . 54 * Fertility Regulation Ta bl e 5. 3. 2 E ve r u se o f c on tra ce pt io n: m en Pe rc en ta ge o f a ll m en , o f c ur re nt ly m ar rie d m en , a nd o f s ex ua lly a ct iv e un m ar rie d m en w ho h av e ev er u se d a co nt ra ce pt iv e m et ho d, b y sp ec ifi c m et ho d an d ag e, M al aw i 2 00 0 __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ _ M od er n m et ho d Tr ad iti on al m et ho d _ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ _ An y An y D ia ph ra gm / Fe m al e M al e Em er ge nc y tra di - Pe rio di c An y m od er n In je ct - Fo am / Fe m al e M al e st er ili - st er ili - Im - co nt ra - tio na l ab st i- W ith - Ag e m et ho d m et ho d Pi ll IU D ab le s Je lly co nd om co nd om sa tio n sa tio n pl an t ce pt io n LA M m et ho d ne nc e dr aw al O th er 1 N um be r __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ _ AL L M EN __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ 15 -1 9 20 -2 4 25 -2 9 30 -3 4 35 -3 9 40 -4 4 45 -4 9 50 -5 4 Al l a ge s 26 .5 23 .6 1 .5 0. 1 0 .7 0. 1 0. 2 23 .1 0 .0 0. 0 0. 0 0. 1 0 .6 8 .2 3 .6 5 .5 0 .9 66 0 62 .7 56 .7 7 .3 0. 2 7 .2 0. 2 0. 8 49 .2 0 .3 0. 0 0. 0 1. 2 7 .5 29 .3 21 .3 16 .3 1 .1 59 8 76 .7 64 .9 13 .3 0. 1 24 .4 0. 3 0. 6 45 .6 1 .0 0. 2 0. 7 1. 9 14 .0 43 .9 29 .8 17 .9 9 .6 53 9 84 .2 70 .4 24 .0 0. 9 34 .3 0. 6 0. 9 42 .1 3 .1 0. 0 0. 7 2. 4 14 .7 53 .3 38 .3 26 .6 9 .5 33 0 79 .5 70 .2 25 .4 2. 3 31 .4 0. 9 0. 2 34 .4 7 .1 0. 0 0. 1 1. 5 18 .7 49 .1 35 .2 22 .5 11 .2 34 0 80 .3 68 .9 23 .5 1. 2 26 .6 1. 6 0. 0 31 .6 15 .8 0. 0 0. 1 0. 0 16 .7 52 .5 36 .0 21 .6 14 .5 24 0 76 .1 58 .0 19 .1 2. 2 25 .8 1. 3 0. 5 22 .8 10 .6 0. 0 1. 4 0. 8 20 .0 60 .5 40 .8 25 .0 18 .9 20 7 79 .0 63 .9 16 .4 0. 8 18 .1 0. 9 0. 5 14 .1 11 .3 0. 6 0. 0 1. 2 28 .7 57 .3 43 .0 25 .5 20 .0 17 7 64 .7 55 .5 13 .4 0. 7 17 .7 0. 5 0. 5 35 .4 3 .9 0. 1 0. 3 1. 1 11 .9 37 .6 26 .0 17 .6 7 .9 3, 09 2 __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ C U RR EN TL Y M AR RI ED M EN __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ 15 -1 9 20 -2 4 25 -2 9 30 -3 4 35 -3 9 40 -4 4 45 -4 9 50 -5 4 Al l a ge s 47 .0 41 .9 11 .5 0. 0 10 .0 0. 0 0. 0 41 .9 0 .0 0. 0 0. 0 0. 0 6 .2 38 .5 15 .8 29 .1 0 .0 2 3 68 .6 57 .6 9 .1 0. 4 16 .8 0. 5 0. 5 41 .3 0 .6 0. 0 0. 0 2. 3 18 .0 42 .0 34 .1 21 .9 2 .1 23 6 78 .7 64 .6 14 .9 0. 1 28 .2 0. 2 0. 2 41 .7 0 .9 0. 1 0. 5 2. 0 16 .7 50 .2 34 .6 19 .7 11 .7 44 1 85 .6 70 .9 25 .4 1. 0 36 .4 0. 7 0. 8 40 .9 3 .3 0. 0 0. 8 2. 4 15 .4 54 .3 38 .4 27 .7 10 .2 30 8 79 .8 69 .9 26 .4 2. 1 32 .5 0. 9 0. 3 32 .7 7 .4 0. 0 0. 1 1. 6 20 .0 50 .5 36 .3 23 .2 12 .2 31 4 81 .5 70 .9 24 .5 1. 3 28 .0 1. 6 0. 0 32 .5 16 .7 0. 0 0. 1 0. 0 16 .6 52 .8 35 .4 22 .7 15 .3 22 8 76 .7 58 .7 19 .0 2. 4 26 .3 1. 3 0. 6 22 .4 10 .9 0. 0 1. 5 0. 9 21 .1 61 .1 40 .8 25 .7 19 .0 19 5 81 .3 64 .8 17 .3 0. 9 19 .2 1. 0 0. 5 13 .5 11 .9 0. 7 0. 0 1. 3 27 .3 58 .6 43 .2 27 .1 20 .0 16 1 78 .7 65 .5 19 .5 1. 0 27 .6 0. 8 0. 4 34 .6 6 .2 0. 1 0. 4 1. 6 18 .4 51 .9 36 .7 23 .6 12 .1 1, 90 6 __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ _ SE XU AL LY A C TI VE U N M AR RI ED M EN 2 __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ Al l a ge s 62 .4 59 .1 4 .9 0. 0 2 .5 0. 1 1. 0 56 .5 0 .8 0. 0 0. 0 1. 0 0 .9 20 .1 8 .7 13 .5 2 .4 28 1 __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ _ 1 In cl ud es m os tly fo lk m et ho ds s uc h as ty in g st rin g ar ou nd w ai st a nd ta ki ng h er bs . 2 Se xu al ly a ct iv e un m ar rie d m en a re th os e w ho h av e ha d se xu al in te rc ou rs e in th e on e m on th p re ce di ng th e su rv ey . Fertility Regulation * 55 Ta bl e 5. 4. 1 C ur re nt u se o f c on tra ce pt io n: w om en Pe rc en t d ist rib ut io n of a ll w om en , c ur re nt ly m ar rie d w om en , a nd s ex ua lly a ct iv e un m ar rie d w om en b y co nt ra ce pt iv e m et ho d cu rr en tly u se d, a cc or di ng to a ge , M al aw i 2 00 0 __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ M od er n m et ho d Tr ad iti on al m et ho d __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ An y An y Fe m al e M al e tra di - Pe rio di c N ot An y m od er n In je ct - st er ili - st er ili - Im - tio na l ab st i- W ith - cu rr en tly Ag e m et ho d m et ho d Pi ll IU D ab le s C on do m sa tio n sa tio n pl an t LA M m et ho d ne nc e dr aw al O th er 1 us in g To ta l N um be r __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ _ AL L W O M EN __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ _ 15 -1 9 20 -2 4 25 -2 9 30 -3 4 35 -3 9 40 -4 4 45 -4 9 Al l a ge s 7 .9 6 .9 0. 8 0. 0 3 .0 2 .8 0 .0 0. 0 0. 0 0. 3 1. 0 0. 5 0. 2 0. 2 92 .1 10 0. 0 2, 86 7 24 .5 21 .5 2. 3 0. 0 15 .3 2 .9 0 .5 0. 0 0. 0 0. 4 3. 0 0. 5 1. 1 1. 4 75 .5 10 0. 0 2, 95 7 32 .9 28 .5 3. 6 0. 3 20 .3 1 .8 1 .9 0. 0 0. 1 0. 5 4. 5 0. 9 1. 5 2. 1 67 .1 10 0. 0 2, 40 1 32 .9 28 .1 3. 2 0. 1 18 .6 0 .9 4 .6 0. 2 0. 3 0. 3 4. 7 0. 8 1. 9 2. 0 67 .1 10 0. 0 1, 56 6 34 .0 29 .6 3. 0 0. 3 14 .6 0 .9 10 .0 0. 0 0. 1 0. 5 4. 4 1. 0 1. 7 1. 6 66 .0 10 0. 0 1, 42 4 33 .4 28 .5 2. 4 0. 0 12 .5 0 .6 13 .0 0. 0 0. 0 0. 1 4. 9 0. 8 0. 8 3. 3 66 .6 10 0. 0 1, 05 3 21 .9 17 .3 0. 7 0. 0 6 .5 0 .3 9 .6 0. 2 0. 0 0. 0 4. 6 0. 9 0. 9 2. 8 78 .1 10 0. 0 9 51 25 .0 21 .5 2. 3 0. 1 13 .0 1 .9 3 .8 0. 0 0. 1 0. 3 3. 4 0. 7 1. 1 1. 6 75 .0 10 0. 0 13 ,2 20 __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ _ C U RR EN TL Y M AR RI ED W O M EN __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ _ 15 -1 9 20 -2 4 25 -2 9 30 -3 4 35 -3 9 40 -4 4 45 -4 9 Al l a ge s 15 .2 12 .9 1. 2 0. 0 8 .1 2 .8 0 .0 0. 0 0. 0 0. 8 2. 3 1. 0 0. 7 0. 6 84 .8 10 0. 0 9 34 26 .3 22 .7 2. 3 0. 0 17 .2 2 .3 0 .6 0. 0 0. 0 0. 3 3. 6 0. 6 1. 4 1. 6 73 .7 10 0. 0 2, 32 4 34 .6 29 .9 3. 8 0. 3 21 .3 1 .9 2 .0 0. 0 0. 0 0. 6 4. 7 0. 9 1. 6 2. 2 65 .4 10 0. 0 2, 10 2 35 .8 30 .2 3. 5 0. 1 19 .8 0 .8 5 .1 0. 2 0. 4 0. 3 5. 5 1. 0 2. 2 2. 3 64 .2 10 0. 0 1, 31 2 36 .7 31 .5 3. 2 0. 3 15 .7 0 .9 10 .7 0. 0 0. 0 0. 5 5. 2 1. 2 2. 1 1. 9 63 .3 10 0. 0 1, 19 2 37 .7 31 .6 2. 7 0. 0 14 .2 0 .7 13 .9 0. 0 0. 0 0. 1 6. 0 1. 0 1. 0 4. 1 62 .3 10 0. 0 8 48 25 .7 20 .4 0. 9 0. 0 8 .1 0 .3 10 .8 0. 2 0. 0 0. 0 5. 3 1. 2 1. 2 2. 9 74 .3 10 0. 0 7 39 30 .6 26 .1 2. 7 0. 1 16 .4 1 .6 4 .7 0. 1 0. 1 0. 4 4. 5 0. 9 1. 5 2. 1 69 .4 10 0. 0 9, 45 2 __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ SE XU AL LY A C TI VE U N M AR RI ED W O M EN 2 __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ _ 15 -2 9 30 -4 9 Al l a ge s 25 .6 24 .4 4. 0 0. 1 6. 2 13 .3 0. 3 0. 0 0. 0 0. 6 1. 2 0. 4 0. 0 0. 8 74 .4 10 0. 0 25 0 31 .5 30 .2 0. 0 0. 0 13 .1 1. 7 13 .2 0. 0 2. 2 0. 0 1. 3 0. 0 0. 0 1. 3 68 .5 10 0. 0 67 26 .9 25 .6 3. 1 0. 0 7. 7 10 .8 3. 0 0. 0 0. 5 0. 5 1. 2 0. 3 0. 0 0. 9 73 .1 10 0. 0 31 7 __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ N ot e: If m or e th an o ne m et ho d is us ed , o nl y th e m os t e ffe ct iv e m et ho d is co ns id er ed in th is ta bl e. 1 In cl ud es m os tly fo lk m et ho ds s uc h as ty in g st rin g ar ou nd w ai st a nd ta ki ng h er bs . 2 Se xu al ly a ct iv e un m ar rie d w om en a re th os e w ho h av e ha d se xu al in te rc ou rs e in th e on e m on th p re ce di ng th e su rv ey . 56 * Fertility Regulation Ta bl e 5. 4. 2 C ur re nt u se o f c on tra ce pt io n: m en Pe rc en t d ist rib ut io n of a ll w om en , c ur re nt ly m ar rie d m en , a nd se xu al ly a ct iv e un m ar rie d m en w ho a re c ur re nt ly u sin g a co nt ra ce pt iv e m et ho d, b y sp ec ifi c m et ho d an d fo r m en , b y ag e, M al aw i 2 00 0 __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ M od er n m et ho d Tr ad iti on al m et ho d __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ _ An y An y Fe m al e M al e tra di - Pe rio di c N ot An y m od er n In je ct - st er ili - st er ili - Im - tio na l ab st i- W ith - cu rr en tly Ag e m et ho d m et ho d Pi ll IU D ab le s C on do m sa tio n sa tio n pl an t LA M m et ho d ne nc e dr aw al O th er 1 us in g To ta l N um be r __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ AL L M EN __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ 15 -1 9 20 -2 4 25 -2 9 30 -3 4 35 -3 9 40 -4 4 45 -4 9 50 -5 4 Al l a ge s 14 .1 13 .4 0. 5 0. 0 0 .0 12 .8 0 .0 0. 0 0. 0 0. 0 0 .7 0. 0 0 .3 0. 3 85 .9 10 0. 0 66 0 28 .5 25 .7 1. 7 0. 0 2 .3 21 .2 0 .0 0. 0 0. 0 0. 5 2 .8 1. 2 1 .4 0. 2 71 .5 10 0. 0 59 8 30 .7 27 .5 2. 4 0. 0 11 .6 12 .7 0 .5 0. 2 0. 0 0. 1 3 .2 0. 3 1 .4 1. 4 69 .3 10 0. 0 53 9 34 .7 32 .2 5. 1 0. 0 15 .0 10 .4 1 .5 0. 0 0. 2 0. 0 2 .4 0. 4 0 .8 1. 3 65 .3 10 0. 0 33 0 32 .1 26 .2 5. 5 0. 0 11 .6 4 .8 4 .4 0. 0 0. 0 0. 0 5 .9 1. 6 1 .9 2. 4 67 .9 10 0. 0 34 0 37 .1 31 .6 2. 4 0. 4 10 .0 5 .9 13 .0 0. 0 0. 0 0. 0 5 .6 2. 1 1 .1 2. 3 62 .9 10 0. 0 24 0 28 .1 25 .1 3. 8 0. 2 9 .9 2 .3 8 .8 0. 0 0. 1 0. 0 3 .0 0. 0 0 .3 2. 8 71 .9 10 0. 0 20 7 26 .9 20 .1 2. 2 0. 0 5 .8 1 .5 9 .9 0. 6 0. 0 0. 0 6 .8 0. 6 4 .3 1. 9 73 .1 10 0. 0 17 7 27 .4 24 .2 2. 6 0. 0 7 .1 11 .4 2 .9 0. 1 0. 0 0. 1 3 .2 0. 7 1 .2 1. 2 72 .6 10 0. 0 3, 09 2 __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ C U RR EN TL Y M AR RI ED M EN __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ 15 -1 9 20 -2 4 25 -2 9 30 -3 4 35 -3 9 40 -4 4 45 -4 9 50 -5 4 Al l a ge s 27 .8 27 .8 0. 0 0. 0 0 .0 27 .8 0 .0 0. 0 0. 0 0. 0 0 .0 0. 0 0 .0 0. 0 72 .2 10 0. 0 2 3 22 .8 19 .5 2. 5 0. 0 5 .5 10 .2 0 .0 0. 0 0. 0 1. 3 3 .3 0. 4 2 .4 0. 6 77 .2 10 0. 0 23 6 29 .2 25 .3 2. 7 0. 0 13 .9 8 .0 0 .6 0. 1 0. 0 0. 1 3 .9 0. 4 1 .7 1. 8 70 .8 10 0. 0 44 1 35 .0 32 .4 5. 4 0. 0 15 .8 9 .3 1 .6 0. 0 0. 3 0. 0 2 .6 0. 4 0 .9 1. 3 65 .0 10 0. 0 30 8 33 .9 27 .9 5. 9 0. 0 12 .5 4 .7 4 .8 0. 0 0. 0 0. 0 6 .0 1. 8 1 .7 2. 6 66 .1 10 0. 0 31 4 39 .1 33 .3 2. 5 0. 4 10 .6 6 .2 13 .7 0. 0 0. 0 0. 0 5 .9 2. 2 1 .2 2. 4 60 .9 10 0. 0 22 8 28 .7 25 .5 3. 3 0. 2 10 .5 2 .1 9 .4 0. 0 0. 1 0. 0 3 .2 0. 0 0 .3 2. 9 71 .3 10 0. 0 19 5 29 .1 21 .6 2. 5 0. 0 6 .4 1 .2 10 .9 0. 7 0. 0 0. 0 7 .4 0. 6 4 .7 2. 1 70 .9 10 0. 0 16 1 31 .2 26 .8 3. 6 0. 1 11 .4 6 .8 4 .7 0. 1 0. 1 0. 2 4 .4 0. 8 1 .7 1. 9 68 .8 10 0. 0 1, 90 6 __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ SE XU AL LY A C TI VE U N M AR RI ED M EN 2 __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ _ Al l a ge s 35 .6 33 .6 1. 2 0. 0 0 .0 32 .4 0 .0 0. 0 0. 0 0. 0 2 .0 0. 1 1 .2 0. 8 64 .4 10 0. 0 28 1 __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ _ N ot e: If m or e th an o ne m et ho d is us ed , o nl y th e m os t e ffe ct iv e m et ho d is co ns id er ed in th is ta bl e. 1 In cl ud es m os tly fo lk m et ho ds s uc h as ty in g st rin g ar ou nd w ai st a nd ta ki ng h er bs . 2 Se xu al ly a ct iv e un m ar rie d m en a re th os e w ho h av e ha d se xu al in te rc ou rs e in th e on e m on th p re ce di ng th e su rv ey . Fertility Regulation * 57 Among currently married men, current use of modern methods fluctuates from one age group to another. Among currently married men, the pattern of current use by age for male condoms, female sterilisation, and injectables is similar to that of currently married women. Condom use is concentrated in the youngest age groups and among the sexually active, unmarried individuals. 5.5 CURRENT USE OF CONTRACEPTION BY BACKGROUND CHARACTERISTICS Table 5.5 presents the percent distribution of currently married women and men by their current use of family planning methods, according to background characteristics. There are substantial differences in the use of contraceptive methods among subgroups of currently married women and men. Women in urban areas are more likely to use a family planning method than their rural counterparts. Use of any method is 41 percent in urban areas, compared with 29 percent in rural areas. The difference is largely due to more women in the urban areas using modern contraception (38 percent) than in the rural areas (24 percent). Traditional methods are, on the other hand, more likely to be used in the rural areas (5 percent) than in urban areas (3 percent). Contraceptive use varies minimally by region of residence, but greatly by district of residence. At the regional level, use of a modern method among married women is slightly higher in the Central Region (27 percent) than in the Northern and Southern regions (25 percent each). As in previous surveys, the 2000 MDHS survey finds that among both men and women, withdrawal (a traditional method) is commonly used in the Northern Region but not much elsewhere. This causes use of any method (as opposed to modern methods) to be highest in the Northern Region. Among currently married men, current use of any method and any modern method is highest in the Northern Region, followed by the Central Region and the Southern Region. 58 * Fertility Regulation Ta bl e 5. 5. 1 C ur re nt u se o f c on tra ce pt io n by b ac kg ro un d ch ar ac te ris tic s: w om en Pe rc en t d ist rib ut io n of c ur re nt ly m ar rie d w om en b y co nt ra ce pt iv e m et ho d cu rr en tly u se d, a cc or di ng to b ac kg ro un d ch ar ac te ris tic s, M al aw i 2 00 0 __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ _ M od er n m et ho d Tr ad iti on al m et ho d __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ _ __ __ __ __ __ __ __ __ __ __ __ _ An y An y Fe m al e M al e tra di - Pe rio di c N ot Ba ck gr ou nd An y m od er n In je ct - st er ili - st er ili - Im - tio na l ab st i- W ith - cu rr en tly ch ar ac te ris tic m et ho d m et ho d Pi ll IU D ab le s C on do m sa tio n sa tio n pl an t LA M m et ho d ne nc e dr aw al O th er 1 us in g To ta l N um be r __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ _ Re si de nc e U rb an R ur al Re gi on N or th er n C en tra l S ou th er n D is tr ic ts B la nt yr e K ar on ga K as un gu L ilo ng w e M ac hi ng a M an go ch i M ul an je M zi m ba S al im a T hy ol o Z om ba O th er d ist ric ts Ed uc at io n N o ed uc at io n P rim ar y 1- 4 P rim ar y 5- 8 S ec on da ry a nd hi gh er N o. o f l iv in g c hi ld re n 0 1 2 3 4 + To ta l 41 .2 38 .2 4. 2 0. 3 22 .9 2. 6 7 .6 0. 1 0. 3 0. 2 3 .0 0. 7 1 .0 1. 3 58 .8 10 0. 0 1, 36 2 28 .9 24 .1 2. 5 0. 1 15 .3 1. 4 4 .3 0. 0 0. 0 0. 4 4 .8 1. 0 1 .6 2. 2 71 .1 10 0. 0 8, 08 9 35 .4 25 .4 4. 4 0. 0 10 .9 4. 7 4 .9 0. 1 0. 0 0. 3 10 .0 0. 7 7 .7 1. 6 64 .6 10 0. 0 1, 07 5 31 .4 27 .2 2. 1 0. 1 18 .2 1. 1 5 .2 0. 0 0. 1 0. 5 4 .2 1. 2 0 .9 2. 1 68 .6 10 0. 0 3, 91 9 28 .8 25 .3 2. 9 0. 2 16 .1 1. 2 4 .3 0. 1 0. 1 0. 4 3 .5 0. 7 0 .5 2. 2 71 .2 10 0. 0 4, 45 8 40 .8 38 .4 3. 8 0. 5 22 .6 2. 0 8 .3 0. 2 0. 4 0. 5 2 .4 0. 5 0 .7 1. 2 59 .2 10 0. 0 83 7 28 .5 16 .8 1. 8 0. 2 6 .4 3. 7 4 .5 0. 0 0. 0 0. 2 11 .7 0. 6 9 .1 2. 0 71 .5 10 0. 0 19 1 36 .1 26 .3 4. 2 0. 0 14 .2 3. 3 3 .2 0. 0 0. 3 1. 2 9 .8 2. 7 2 .9 4. 2 63 .9 10 0. 0 36 7 36 .1 32 .8 2. 4 0. 0 22 .1 1. 2 6 .6 0. 0 0. 0 0. 4 3 .3 0. 7 0 .6 2. 0 63 .9 10 0. 0 1, 40 2 26 .6 22 .6 2. 5 0. 0 16 .0 1. 5 2 .0 0. 2 0. 0 0. 2 4 .0 0. 4 0 .4 3. 2 73 .4 10 0. 0 37 4 21 .6 16 .7 3. 0 0. 3 8 .0 1. 1 3 .4 0. 0 0. 0 0. 9 4 .9 0. 0 0 .5 4. 3 78 .4 10 0. 0 46 7 30 .6 26 .3 3. 8 0. 0 16 .7 0. 6 5 .1 0. 0 0. 0 0. 0 4 .3 0. 5 0 .4 3. 4 69 .4 10 0. 0 42 9 34 .5 21 .6 4. 3 0. 0 8 .8 3. 2 4 .6 0. 2 0. 1 0. 4 12 .8 0. 9 10 .2 1. 8 65 .5 10 0. 0 45 8 18 .5 15 .5 1. 3 0. 0 9 .6 0. 4 4 .1 0. 0 0. 0 0. 0 3 .0 0. 5 0 .7 1. 9 81 .5 10 0. 0 22 3 25 .9 24 .4 1. 5 0. 2 16 .3 1. 1 4 .9 0. 2 0. 0 0. 2 1 .5 0. 1 0 .2 1. 2 74 .1 10 0. 0 45 6 26 .3 22 .0 1. 4 0. 0 16 .8 1. 1 2 .6 0. 0 0. 1 0. 0 4 .3 1. 0 0 .4 2. 9 73 .7 10 0. 0 56 4 28 .9 24 .9 2. 7 0. 1 15 .9 1. 5 4 .2 0. 0 0. 0 0. 4 4 .1 1. 3 1 .2 1. 7 71 .1 10 0. 0 3, 68 3 26 .0 21 .7 1. 4 0. 1 14 .5 0. 9 4 .2 0. 1 0. 0 0. 5 4 .2 0. 8 0 .8 2. 6 74 .0 10 0. 0 2, 97 5 28 .1 23 .6 2. 1 0. 0 15 .6 0. 7 4 .6 0. 0 0. 0 0. 4 4 .5 1. 2 1 .3 1. 9 71 .9 10 0. 0 2, 98 0 34 .7 29 .5 4. 1 0. 0 17 .7 2. 4 4 .7 0. 1 0. 0 0. 3 5 .2 0. 6 2 .4 2. 1 65 .3 10 0. 0 2, 78 4 45 .1 41 .6 5. 3 0. 9 22 .1 4. 6 7 .6 0. 0 0. 6 0. 2 3 .5 1. 2 1 .5 0. 7 54 .9 10 0. 0 71 3 3. 6 2 .6 0. 4 0. 0 0 .6 0. 4 1 .2 0. 0 0. 0 0. 0 1 .1 0. 4 0 .4 0. 3 96 .4 10 0. 0 1, 00 5 22 .8 20 .1 2. 2 0. 1 12 .9 3. 4 0 .8 0. 0 0. 0 0. 6 2 .7 0. 8 0 .8 1. 0 77 .2 10 0. 0 1, 98 4 28 .6 24 .3 3. 3 0. 2 17 .1 1. 7 1 .4 0. 1 0. 0 0. 5 4 .3 0. 9 1 .5 1. 9 71 .4 10 0. 0 1, 82 2 34 .4 30 .1 3. 1 0. 4 20 .9 1. 3 3 .2 0. 1 0. 3 0. 6 4 .3 0. 8 1 .6 1. 9 65 .6 10 0. 0 1, 37 9 43 .3 36 .4 3. 3 0. 0 21 .0 0. 8 10 .7 0. 1 0. 0 0. 3 6 .9 1. 2 2 .2 3. 6 56 .7 10 0. 0 3, 26 2 30 .6 26 .1 2. 7 0. 1 16 .4 1. 6 4 .7 0. 1 0. 1 0. 4 4 .5 0. 9 1 .5 2. 1 69 .4 10 0. 0 9, 45 2 __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ N ot e: If m or e th an o ne m et ho d is us ed , o nl y th e m os t e ffe ct iv e m et ho d is co ns id er ed in th is ta bl e. 1 In cl ud es m os tly fo lk m et ho ds s uc h as ty in g st rin g ar ou nd w ai st a nd ta ki ng h er bs . Fertility Regulation * 59 Ta bl e 5. 5. 2 C ur re nt u se o f c on tra ce pt io n by b ac kg ro un d ch ar ac te ris tic s: m en Pe rc en t d ist rib ut io n of c ur re nt ly m ar rie d m en b y co nt ra ce pt iv e m et ho d cu rr en tly u se d, a cc or di ng to b ac kg ro un d ch ar ac te ris tic s, M al aw i 2 00 0 __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ _ M od er n m et ho d Tr ad iti on al m et ho d __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ _ __ __ __ __ __ __ __ __ __ __ __ _ An y An y Fe m al e M al e tra di - Pe rio di c N ot Ba ck gr ou nd An y m od er n In je ct - st er ili - st er ili - Im - tio na l ab st i- W ith - cu rr en tly ch ar ac te ris tic m et ho d m et ho d Pi ll IU D ab le s C on do m sa tio n sa tio n pl an t LA M m et ho d ne nc e dr aw al O th er 1 us in g To ta l N um be r __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ Re si de nc e U rb an R ur al Re gi on N or th er n C en tra l S ou th er n D is tr ic ts B la nt yr e K ar on ga K as un gu L ilo ng w e M ac hi ng a M an go ch i M ul an je M zi m ba S al im a T hy ol o Z om ba O th er d ist ric ts Ed uc at io n N o ed uc at io n P rim ar y 1- 4 P rim ar y 5- 8 S ec on da ry a nd hi gh er N o. o f l iv in g c hi ld re n 0 1 2 3 4 + To ta l 37 .9 35 .2 6. 9 0. 1 13 .5 7 .6 6. 9 0. 1 0. 0 0. 0 2 .7 0. 5 2 .0 0. 2 62 .1 10 0. 0 30 7 29 .9 25 .2 3. 0 0. 1 11 .0 6 .6 4. 3 0. 1 0. 1 0. 2 4 .7 0. 9 1 .6 2. 2 70 .1 10 0. 0 1, 59 9 38 .5 29 .1 8. 0 0. 0 4 .9 11 .1 4. 5 0. 5 0. 1 0. 0 9 .4 0. 0 8 .0 1. 4 61 .5 10 0. 0 21 7 33 .6 28 .2 2. 4 0. 0 12 .7 7 .2 5. 3 0. 0 0. 1 0. 4 5 .4 1. 3 1 .3 2. 7 66 .4 10 0. 0 77 5 27 .5 25 .2 3. 6 0. 1 11 .8 5 .4 4. 2 0. 0 0. 0 0. 0 2 .3 0. 5 0 .5 1. 3 72 .5 10 0. 0 91 4 36 .1 33 .1 5. 3 0. 0 14 .9 5 .2 7. 6 0. 0 0. 0 0. 0 3 .0 0. 0 1 .3 1. 7 63 .9 10 0. 0 18 4 43 .7 28 .0 2. 5 0. 0 5 .7 13 .5 5. 7 0. 0 0. 7 0. 0 15 .7 0. 0 12 .5 3. 2 56 .3 10 0. 0 4 0 33 .1 29 .7 4. 3 0. 0 7 .0 15 .7 1. 8 0. 0 1. 0 0. 0 3 .5 0. 0 3 .3 0. 2 66 .9 10 0. 0 8 4 33 .6 28 .8 2. 7 0. 0 13 .5 6 .6 4. 9 0. 0 0. 0 1. 1 4 .9 1. 6 1 .1 2. 1 66 .4 10 0. 0 27 9 30 .9 26 .1 4. 5 0. 0 8 .3 7 .4 5. 9 0. 0 0. 0 0. 0 4 .7 0. 0 0 .0 4. 7 69 .1 10 0. 0 7 5 17 .2 14 .4 3. 1 0. 0 4 .5 4 .8 1. 7 0. 3 0. 0 0. 0 2 .8 0. 0 1 .4 1. 4 82 .8 10 0. 0 9 2 31 .2 30 .2 4. 9 0. 0 15 .3 2 .9 7. 1 0. 0 0. 0 0. 0 1 .0 0. 0 1 .0 0. 0 68 .8 10 0. 0 7 5 34 .3 24 .5 2. 6 0. 0 4 .9 11 .3 4. 5 1. 1 0. 0 0. 0 9 .8 0. 0 8 .7 1. 1 65 .7 10 0. 0 9 5 22 .0 19 .6 0. 4 0. 0 8 .7 3 .5 5. 9 0. 0 0. 0 1. 0 2 .4 0. 0 0 .4 2. 1 78 .0 10 0. 0 4 3 21 .6 19 .8 2. 7 0. 9 8 .6 4 .1 3. 6 0. 0 0. 0 0. 0 1 .8 0. 9 0 .0 0. 9 78 .4 10 0. 0 9 4 33 .5 32 .4 2. 5 0. 3 22 .9 5 .7 1. 1 0. 0 0. 0 0. 0 1 .1 1. 1 0 .0 0. 0 66 .5 10 0. 0 10 5 31 .0 26 .3 4. 0 0. 0 11 .0 6 .6 4. 7 0. 0 0. 0 0. 0 4 .7 1. 2 1 .1 2. 4 69 .0 10 0. 0 73 9 24 .3 21 .2 3. 5 0. 0 8 .3 4 .8 4. 7 0. 0 0. 0 0. 0 3 .0 0. 4 0 .8 1. 9 75 .7 10 0. 0 26 5 25 .8 20 .3 2. 3 0. 0 9 .5 4 .9 3. 6 0. 0 0. 0 0. 0 5 .4 1. 4 1 .1 2. 9 74 .2 10 0. 0 56 5 31 .6 27 .3 2. 4 0. 0 12 .1 7 .5 5. 0 0. 2 0. 0 0. 0 4 .3 0. 5 2 .3 1. 6 68 .4 10 0. 0 73 7 45 .0 41 .2 8. 6 0. 3 15 .4 9 .8 5. 8 0. 0 0. 2 1. 0 3 .8 0. 8 2 .1 1. 0 55 .0 10 0. 0 33 8 7 .5 6 .8 0. 8 0. 0 0 .0 5 .9 0. 0 0. 0 0. 0 0. 0 0 .7 0. 7 0 .0 0. 0 92 .5 10 0. 0 17 0 30 .6 26 .9 3. 8 0. 0 8 .9 13 .1 0. 3 0. 0 0. 0 0. 8 3 .7 0. 7 1 .9 1. 1 69 .4 10 0. 0 35 1 29 .5 24 .6 4. 0 0. 0 11 .1 5 .0 4. 1 0. 3 0. 0 0. 0 4 .9 0. 7 1 .8 2. 4 70 .5 10 0. 0 31 0 39 .0 35 .4 5. 7 0. 3 17 .8 7 .5 3. 5 0. 0 0. 3 0. 2 3 .6 1. 1 2 .0 0. 5 61 .0 10 0. 0 26 0 34 .6 29 .2 3. 3 0. 0 12 .9 4 .7 8. 1 0. 0 0. 0 0. 0 5 .5 0. 8 1 .8 2. 8 65 .4 10 0. 0 81 6 31 .2 26 .8 3. 6 0. 1 11 .4 6 .8 4. 7 0. 1 0. 1 0. 2 4 .4 0. 8 1 .7 1. 9 68 .8 10 0. 0 1, 90 6 __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ _ N ot e: If m or e th an o ne m et ho d is us ed , o nl y th e m os t e ffe ct iv e m et ho d is co ns id er ed in th is ta bl e. 1 In cl ud es m os tly fo lk m et ho ds s uc h as ty in g st rin g ar ou nd w ai st a nd ta ki ng h er bs . 60 * Fertility Regulation The highest level of modern method use (married women) is found in the Blantyre (38 percent) and Lilongwe (33 percent) districts, and the lowest is found in the Salima (16 percent), Mangochi (17 percent), and Karonga (17 percent) districts. Differentials among the districts are driven in large part by differences in the use of injectables and, to a lesser extent, female sterilisation. For example, the use of modern methods is almost twice as high in Lilongwe District as in Mangochi District; use of contraceptive injectables is just 8 percent in Mangochi District, compared with 22 percent in Lilongwe District. Higher educational attainment is positively correlated with current use of family planning. Use of modern methods increases from 22 percent among currently married women with no education to 42 percent among women with secondary education or above. A similar pattern of results was obtained when looking at information collected from men. There is a direct association between use of modern family planning and number of living children for women. Only 3 percent of women with no living children use modern contraception; the percentage increases to 36 percent among women with four or more children. For men, this relationship is similar but less pronounced. Use of sterilisation to end childbearing altogether rises expectedly with the number of living children a woman has. One in nine married women with four or more living children has chosen this option. 5.6 CURRENT USE OF CONTRACEPTIVES BY WOMEN’S STATUS A woman’s desire and ability to control her fertility and her choice of contraceptive method are in part affected by her status and self-image. A woman who feels that she is unable to control her life may be less likely to feel she can make and carry out decisions about her fertility. Table 5.6 shows the distribution of currently married women by contraceptive use, according to women’s status indicators. Use of modern methods was reported by 23 percent of women who had a final say in 0-1 decisions, 25 percent of women with final say in 2-3 decisions, and 30 percent of women with final say in more than 4 decisions. There were no significant differences in the percentages of women using modern methods relative to the number of reported reasons to refuse sexual relations with their husband or reported reasons to justify wife beating. In sum, the dimensions of women’s status used here are not important factors in determining contraceptive use in Malawi. 5.7 NUMBER OF CHILDREN AT FIRST USE OF CONTRACEPTION Family planning may be used to either limit family size or delay the next birth. Couples using family planning as a means to control family size (i.e., to stop having children) adopt contraception when they have already had the desired number of children they want. When contraception is used to space births, couples may start to use family planning earlier with an intention to delay a possible pregnancy. This may be done even before a couple has had their desired number of children. In a culture where smaller family size is becoming a norm, young women adopt family planning at an earlier age than their older counterparts. Women interviewed in the 2000 MDHS survey were asked how many children they had at the time they first used a method of family planning. The results (Table 5.7) indicate that 9 percent of young women (15-19 years) started to use contraception before they had their first birth, compared with 1 percent of older women (35 years and over). The table also shows that the median number of children at first use has declined rapidly from more than four children among the cohort age 40-49 to less than one child among the cohort age 15-24. This trend is consistent with the rapid rise in contraceptive use and the decline in fertility levels over the past decade or so. Fertility Regulation * 61 Table 5.6 Current use of contraception by women's status Percent distribution of currently married women by contraceptive method currently used, according to selected indicators of women's status, Malawi, 2000 __________________________________________________________________________________ Type of method __________________________________ Any Any Not Women’s Any modern traditional using any status method method method method Total Number _________________________________________________________________________________ Number of decisions with woman having final say 0-1 27.2 23.2 4.0 72.8 100.0 3,087 2-3 29.9 25.1 4.8 70.1 100.0 3,440 4-5 35.3 30.4 4.9 64.7 100.0 2,055 6 34.8 30.5 4.3 65.2 100.0 870 Number of reasons to refuse sexual relations 0 30.0 26.4 3.6 70.0 100.0 1,311 1-2 28.9 25.1 3.7 71.1 100.0 1,447 3-4 31.2 26.3 4.9 68.8 100.0 6,694 Number of reasons to justify wife beating 0 31.6 27.1 4.5 68.4 100.0 6,051 1-3 28.6 24.2 4.4 71.4 100.0 2,443 4-5 30.0 24.6 5.4 70.0 100.0 958 Total 30.6 26.1 4.5 69.4 100.0 9,452 __________________________________________________________________________________ Note: If more than one method is used, only the most effective method is considered in this table. Table 5.7 Number of children at first use of contraception Percent distribution of ever-married women by number of living children at the time of first use of contraception and median number of children at first use, according to current age, Malawi 2000 ___________________________________________________________________________________________ Median number of Never Number of living children at time children at used of first use of contraception first use contra- _________________________________________ of contra- Current age ception 0 1 2 3 4+ Total ception Number _________________________________________________________________________________________ 15-19 20-24 25-29 30-34 35-39 40-44 45-49 Total 71.7 9.0 16.9 2.2 0.0 0.0 100.0 0.3 1,054 51.9 3.8 29.8 11.3 2.9 0.2 100.0 0.7 2,594 40.4 2.0 20.4 20.1 11.1 5.8 100.0 1.4 2,357 40.2 1.6 11.2 13.1 12.1 21.6 100.0 2.3 1,551 43.9 0.6 6.7 6.9 10.0 31.9 100.0 3.4 1,420 44.5 0.2 5.4 6.4 6.4 36.9 100.0 4.2 1,049 55.2 1.3 5.1 3.9 5.6 28.9 100.0 4.1 951 48.3 2.6 16.5 10.9 7.2 14.5 100.0 1.6 10,977 62 * Fertility Regulation Table 5.8 Timing of sterilisation Percent distribution of sterilised women by age at the time of sterilisation, according to the number of years since the operation, Malawi 2000 _____________________________________________________________________________________________ Age at time of sterilisation Years since ____________________________________________________ Median operation <25 25-29 30-34 35-39 40-44 45-49 Total Number age1 ______________________________________________________________________________________________ <2 6.4 17.8 21.2 27.9 15.0 11.6 100.0 230 33.5 2-3 1.9 11.3 27.2 34.2 18.8 6.6 100.0 102 34.8 4-5 4.9 17.2 23.3 33.2 18.7 2.7 100.0 46 33.9 6-7 11.8 15.6 39.3 28.0 5.2 0.0 100.0 39 32.4 8-9 3.3 28.7 29.1 31.3 7.5 0.0 100.0 32 33.4 10+ 19.8 29.7 34.4 16.0 0.0 0.0 100.0 54 a Total 7.0 18.2 25.9 28.6 13.3 6.9 100.0 504 33.2 ______________________________________________________________________________________________ 1 Median ages are calculated only for women sterilised at less than 40 years of age to avoid problems of censoring a Not calculated due to censoring. 5.8 TIMING OF FEMALE STERILISATION Table 5.8 shows the distribution of sterilised women by the age at which they had the procedure, according to the number of years since the operation was done. The results indicate that most women (68 percent) who were sterilised had the operation at age 30-44. Seven percent of women reported to have been sterilised before reaching age 25. The median age at sterilisation (for women sterilised before age 40) is 33 years, which has remained roughly constant over the last 10 years. 5.9 SOURCE OF SUPPLY Information on where women obtain their contraceptive methods is important for family planning programme managers. All current users of modern contraceptive methods were asked the most recent source of their methods. The results in Table 5.9 indicate that the public sector remains the major source of contraceptive methods in Malawi—providing methods to 68 percent of the current users, representing an increase from 59 percent in 1996. The increase in public-sector participation is due in large part to the rapid increase in the use of injectables, which are being provided predominantly at government health centres. Twenty-eight percent of users get their methods from the private medical sector, and 4 percent from other private sources, mostly shops. In the public sector, 23 percent of the users obtain their contraceptive methods from government hospitals, and 39 percent from government health centres. Community-based distribution agents (CBDAs) are the source for only 2 percent of current users. In the private medical sector, Banja La Mtsogola (BLM) is the most commonly used source, providing contraceptive methods to 12 percent of all users of modern methods. One in ten current users obtain their family planning methods at mission hospitals and clinics. Injectables were supplied primarily in government health centres (54 percent) and government hospitals (20 percent). Female sterilisations were conducted mostly in government hospitals (41 percent) and BLM centres (40 percent). Male condoms were obtained primarily from Fertility Regulation * 63 Table 5.9 Source of contraception Percent distribution of women currently using modern contraceptive methods by most recent source of supply, according to specific method, Malawi, 2000 __________________________________________________________________ Female Inject- sterili- Source of supply Pill ables Condom sation Total1 __________________________________________________________________ Public sector Government hospital Government health centre Family planning clinic Mobile clinic CBDA/Field worker Private medical sector Private clinic/hospital Private mobile clinic CBDA/Field worker Mission hospital Mission health clinic Mission mobile clinic BLM (Banja la Mtsogolo) Other private Shop Church Friends/relatives Other Don’t know/Missing Total Number 67.3 79.7 42.4 42.5 68.0 17.4 19.6 10.8 41.2 22.7 37.4 53.8 22.5 1.3 39.3 1.1 0.5 0.4 0.0 0.5 3.4 4.9 5.2 0.0 3.8 8.0 0.8 3.5 0.0 1.6 31.7 20.0 12.8 57.2 27.6 7.3 5.3 1.4 0.8 4.3 0.4 0.4 0.5 0.0 0.3 2.6 0.2 1.0 0.0 0.5 2.8 4.5 1.5 16.4 6.3 5.1 4.3 1.3 0.0 3.3 0.9 0.7 0.0 0.0 0.5 12.5 4.6 7.0 40.1 12.3 1.0 0.0 43.8 0.0 4.0 0.0 0.0 41.8 0.0 3.7 0.0 0.0 0.7 0.0 0.1 1.0 0.0 1.3 0.0 0.2 0.0 0.0 0.1 0.3 0.1 0.0 0.3 0.9 0.0 0.4 100.0 100.0 100.0 100.0 100.0 303 1,717 247 504 2,799 ___________________________________________________________________ 1 Includes 3 users of diaphragm/foam/jelly, 9 users of implants, 5 users of male sterilisation, and 12 users of IUDs who are not shown separately. shops (42 percent), government health centres (23 percent), and government hospitals (11 percent). Pills were obtained primarily from government health centres (37 percent), government hospitals (17 percent), and BLM centres (13 percent). These findings point up the reliance on government facilities along with the important complementary services of BLM. 5.10 INFORMED CHOICE Informed choice is an important aspect of the delivery of family planning services. All providers of sterilisation must inform potential users that the operation is a permanent, irreversible method; potential users must also be informed of other methods that could be used. Family planning providers should also inform all method users of potential side effects and what they should do if they encounter signs of a problem. This information assists users in coping with side effects and decreases unnecessary discontinuation of temporary methods. 64 * Fertility Regulation Table 5.10 Informed choice Among women currently using a modern contraceptive method, percentage who were informed that sterilisation is permanent, percentage who were informed at first use about the side effects of the method used, percentage who were informed at first use what to do if side effects were experienced, and percentage who were informed at first use of other methods that could be used for contraception, by specific method and background characteristics, Malawi 2000 __________________________________________________________________________________ Informed what Informed of Method/ Informed that Informed about to do if other methods background sterilisation side effects experience that could be characteristic is permanent1 of method used2 side effects2 used3 _________________________________________________________________________________ Method Pill na 81.9 79.6 84.7 IUD na 89.4 89.4 87.3 Injectables na 85.7 83.4 86.2 Female sterilisation 90.1 52.0 49.2 45.2 Other na na na 60.0 Residence Urban 96.9 80.3 77.1 78.4 Rural 87.4 78.1 76.0 77.3 Region Northern 94.3 80.1 78.0 83.9 Central 84.8 77.2 74.8 74.3 Southern 93.2 79.4 77.2 79.2 Education No education 87.1 77.6 74.2 74.8 Primary 1-4 86.1 78.6 76.5 75.8 Primary 5-8 92.4 79.5 77.5 81.1 Secondary+ 97.2 78.0 76.5 78.2 Total 89.64 78.6 76.2 77.5 Number of women 509 2,544 2,544 2,591 __________________________________________________________________________________ na = Not applicable 1 Among users of female or male sterilisation 2 Among users of female sterilisation, pill, IUD, injectables, and implants 3 Among users of female sterilisation, pill, IUD, injectables, implants, diaphragm, foam, jelly, and LAM. 4 Total includes 5 users of male sterilisation. Table 5.10 presents the percentage of users of modern contraceptives who were informed that sterilisation is an irreversible method, that there are other family planning method options, that there are potential side effects of their current method, and what to do if they experience any of the side effects. The results indicate that 90 percent of sterilisation users were informed that sterilisation is permanent. Of women using female sterilisation, the pill, the IUD, injectables, and implants, 79 percent reported that they were informed of side effects of the method they use, and 76 percent reported that they were told what they should do in case of a side effect. Of women using female sterilisation, the pill, the IUD, injectables, implants, LAM, and vaginal methods, 78 percent said that they were told about other contraceptive options. Fertility Regulation * 65 Table 5.11 Future use of contraception Percent distribution of currently married women who are not using a contraceptive method by intention to use in the future, according to number of living children, Malawi 2000 _______________________________________________________________________________ Number of living children1 _________________________________________ Intention 0 1 2 3 4+ Total _______________________________________________________________________________ Intends to use Does not intend to use Unsure Missing Total Number 70.3 78.2 75.2 74.3 70.6 73.9 24.1 18.8 22.1 23.3 27.1 23.3 5.6 2.9 2.5 2.3 2.3 2.8 0.0 0.1 0.1 0.1 0.1 0.1 100.0 100.0 100.0 100.0 100.0 100.0 617 1,489 1,449 952 2,048 6,555 _______________________________________________________________________________ 1 Includes current pregnancy 5.11 FUTURE USE OF CONTRACEPTION Intention to use family planning is an important indicator of the potential demand for services. Currently married women who were not using contraceptives at the time of the survey were asked about their intention to use family planning in the future. The results are shown in Table 5.11. Among married women who are not using contraception, 74 percent reported that they intend to adopt a family planning method in the future, 23 percent said that they did not intend to use a method, and 3 percent were unsure of their intention. There are no major differences in the percentage of women who intend to use family planning according to the number of living children. 5.12 REASONS FOR NOT INTENDING TO USE CONTRACEPTION Table 5.12 presents the main reasons for not intending to use contraception given by noncontracepting, married women who do not intend to use a contraceptive method in the future. Among women under 30 years, side effects and health concerns (26 percent), women’s own opposition to family planning (15 percent), spouse’s opposition (14 percent), and difficulties with getting pregnant (11 percent) are the main reasons reported for not intending to use a contraceptive method. For women age 30 and over, the main reasons for not intending to adopt family planning are difficulties in getting pregnant (27 percent), side effects and health concerns (24 percent), menopause/hysterectomy (13 percent), and the woman’s own opposition to family planning (9 percent). 5.13 PREFERRED METHOD OF CONTRACEPTION FOR FUTURE USE Currently married women who reported that they intend to adopt family planning methods, were asked about contraceptive methods they intend to use in the future. The results in Table 5.13 indicate that most women intend to use injectables (59 percent), followed by the pill (18 percent) and female sterilisation (10 percent), to limit or space births in the future. This represents a major change in method preference from the 1992 MDHS survey, in which most women said they intended to use the pill (51 percent) and injectables (16 percent). 66 * Fertility Regulation Table 5.13 Preferred method of contra- ception for future use Percent distribution of currently married women who are not using a contracep- tive method but who intend to use in the future by preferred method, Malawi 2000 _________________________________ Intend to use Preferred method later _________________________________ Pill IUD Injectables Condom Female sterilisation Male sterilisation Periodic abstinence Withdrawal Implants Lactational amenorrhoea Female condom Other Missing Total Number of women 17.9 1.4 59.2 4.9 9.9 0.1 0.6 0.5 1.4 0.2 0.1 2.6 1.3 100 4,841 Table 5.12 Reason for not intending to use contraception Percent distribution of currently married women who are not using a contraceptive method and who do not intend to use in the future by main reason for not intending to use, according to age, Malawi 2000 ___________________________________________________ Age ______________ All Reason 15-29 30-49 ages ___________________________________________________ Wants children Side effects Health concerns Lack of knowledge Access/availability Cost Religious prohibition Opposed to family planning Husband opposed Others opposed Infrequent sex/no sex Difficult to get pregnant Menopausal/hysterectomy Inconvenient Other reasons Don't know Total Number 9.4 7.1 7.9 17.2 9.2 12.1 8.8 14.4 12.4 4.5 1.9 2.8 2.9 0.7 1.5 0.3 0.3 0.3 7.3 4.3 5.4 14.9 9.2 11.3 14.2 5.1 8.3 3.1 0.3 1.3 4.1 7.0 5.9 10.8 27.2 21.3 0.2 12.7 8.2 0.4 0.1 0.2 0.1 0.1 0.1 1.8 0.5 1.0 100.0 100.0 100.0 548 978 1,526 5.14 EXPOSURE TO FAMILY PLANNING MESSAGES ON RADIO AND TELEVISION Radio and television are potential media for disseminating family planning messages, al- though televisions are still relatively rare in Malawi. To assess the extent to which these media serve as sources of family planning messages, respondents were asked whether they heard or saw a message about family planning on the radio or television “in the last few months”. The results are shown in Table 5.14. The majority of women (69 percent) and men (82 percent) had heard a family planning message recently on the radio. Only 5 percent of women and 6 percent of men were reached by both radio and television sources. Women and men in the youngest (15-19) and oldest (45 and older) age groups were least likely to have heard a family planning messages on radio and television. As expected, women in rural areas are much more likely to have not been exposed to family planning messages through the electronic media (35 percent) than their urban counterparts (12 percent). Regional differentials are minimal, but large variations exist between districts. Just 12 percent of women in Blantyre District have had no exposure to family planning promotion in the electronic media, compared with 44 percent in Salima and Thyolo districts and 52 percent in Fertility Regulation * 67 Table 5.14.1 Exposure to family planning messages on radio and television: women Percent distribution of women by whether they had heard a radio or television message about family planning in the few months preceding the survey, according to background characteristics, Malawi 2000 _____________________________________________________________________________ Heard family planning message on radio/television __________________________________ Tele- Background Radio vision characteristic Both only only Neither Total Number _____________________________________________________________________________ Age 15-19 20-24 25-29 30-34 35-39 40-44 45-49 Residence Urban Rural Region Northern Central Southern Districts Blantyre Karonga Kasungu Lilongwe Machinga Mangochi Mulanje Mzimba Salima Thyolo Zomba Other districts Education No education Primary 1-4 Primary 5-8 Secondary+ Total 5.8 59.3 0.2 34.8 100.0 2,867 5.6 66.5 0.1 27.8 100.0 2,957 5.3 66.9 0.1 27.7 100.0 2,401 4.9 65.0 0.3 29.8 100.0 1,566 5.3 63.3 0.0 31.4 100.0 1,424 4.4 61.1 0.1 34.4 100.0 1,053 5.2 57.1 0.2 37.5 100.0 951 16.2 71.2 0.5 12.1 100.0 2,106 3.3 61.9 0.1 34.7 100.0 11,114 5.9 62.0 0.2 31.8 100.0 1,453 4.3 60.9 0.1 34.6 100.0 5,321 6.0 65.7 0.2 28.1 100.0 6,446 13.0 74.3 0.3 12.4 100.0 1,324 3.1 44.7 0.0 52.2 100.0 266 2.1 72.9 0.2 24.9 100.0 484 7.4 61.1 0.2 31.2 100.0 1,864 4.1 62.7 0.2 33.1 100.0 481 2.7 63.4 0.0 33.9 100.0 637 3.0 72.9 0.0 24.1 100.0 624 8.2 63.7 0.4 27.6 100.0 603 3.4 52.5 0.2 44.0 100.0 301 1.8 53.8 0.2 44.2 100.0 687 10.2 67.2 0.2 22.4 100.0 846 3.2 61.6 0.1 35.1 100.0 5,103 2.1 55.1 0.0 42.8 100.0 3,574 3.0 60.6 0.1 36.3 100.0 4,025 4.9 70.8 0.1 24.2 100.0 4,152 20.9 70.3 0.8 8.0 100.0 1,468 5.3 63.4 0.2 31.1 100.0 13,220 Karonga District. A woman’s level of education is positively related to her exposure to family planning messages on the radio or television. For example, 43 percent of the women with no education had no exposure to family planning information on radio or television versus 8 percent of women with secondary or higher education. Among men, the same patterns of differentials in exposure to family planning messages exist but are less pronounced. 68 * Fertility Regulation Table 5.14.2 Exposure to family planning messages on radio and television: men Percent distribution of men by whether they had heard a radio or television message about family planning in the few months preceding the survey, according to background characteristics, Malawi 2000 _____________________________________________________________________________ Heard family planning message on radio/television __________________________________ Tele- Background Radio vision characteristic Both only only Neither Total Number _____________________________________________________________________________ Age 15-19 20-24 25-29 30-34 35-39 40-44 45-49 50-54 Residence Urban Rural Region Northern Central Southern Districts Blantyre Karonga Kasungu Lilongwe Machinga Mangochi Mulanje Mzimba Salima Thyolo Zomba Other districts Education No education Primary 1-4 Primary 5-8 Secondary+ Total 5.7 66.5 0.6 27.2 100.0 660 9.1 72.0 0.2 18.6 100.0 598 6.5 79.3 0.5 13.7 100.0 539 7.6 78.8 0.6 13.0 100.0 330 4.3 82.5 0.0 13.2 100.0 340 6.4 78.6 0.5 14.5 100.0 240 3.0 82.4 0.0 14.6 100.0 207 4.1 79.5 0.0 16.3 100.0 177 15.9 73.4 0.9 9.8 100.0 564 4.2 76.1 0.3 19.4 100.0 2,528 6.5 74.0 0.6 18.8 100.0 351 6.0 76.1 0.4 17.6 100.0 1,296 6.6 75.5 0.3 17.5 100.0 1,446 14.2 75.4 0.4 10.0 100.0 321 5.8 69.2 0.8 24.2 100.0 64 2.0 84.2 0.0 13.8 100.0 142 7.3 77.8 0.6 14.2 100.0 487 8.4 68.3 0.7 22.6 100.0 119 6.0 78.1 0.0 15.8 100.0 154 3.3 79.8 0.0 16.8 100.0 117 10.8 79.3 0.3 9.6 100.0 142 6.1 62.8 0.7 30.4 100.0 65 7.6 77.6 0.1 14.7 100.0 141 4.8 80.8 1.3 13.1 100.0 177 4.0 73.2 0.2 22.5 100.0 1,163 3.5 68.2 0.0 28.4 100.0 322 3.4 72.7 0.7 23.3 100.0 898 4.9 79.3 0.0 15.8 100.0 1,243 14.9 76.3 0.9 7.9 100.0 629 6.3 75.6 0.4 17.7 100.0 3,092 Fertility Regulation * 69 5.15 EXPOSURE TO FAMILY PLANNING MESSAGES IN PRINT MEDIA OR DRAMA Aside from radio and television, other channels can assist in disseminating family planning messages, including the print media and drama. In the 2000 MDHS survey, women were asked whether they saw a family planning message in the newspaper, on a poster, on clothing, or in a drama during the few months before the interview. Table 5.15 shows that 37 percent of women saw a family planning message on a poster, 36 percent saw a message in a drama, 31 percent on clothing, and 18 percent saw a family planning message in a newspaper. Women in urban areas were much more likely than their rural counterparts to have these types of exposure to family planning messages. A smaller proportion of women in the Central and Southern regions saw family planning messages in newspapers, on posters, on clothing, and in dramas than women in the Northern Region. Exposure to family planning messages in all of these media types, but especially in newspapers, increases sharply with a woman’s level of education. 5.16 EXPOSURE TO SPECIFIC HEALTH AND FAMILY PLANNING RADIO PROGRAMMES The 2000 MDHS survey collected information from women and men about whether they had listened to specific radio programmes that promote health and family planning in the last few months. Table 5.16 shows that the overall level of listening to the cited radio programmes is higher among men than women, which is consistent with the more widespread access among men to radios. The most popular programmes, among both men and women, are “Tinkanena” and “Kulera,” both reaching more than two-thirds of women and 85 percent or more of men. Overall, the English- language programmes were much less likely to have been heard (approximately 20 percent of women and 30 percent of men), compared with the programmes in local languages (about 50 to 65 percent of women and 75 to 85 percent of men). 5.17 CONTACT OF NONUSERS WITH FAMILY PLANNING PROVIDERS In the 2000 MDHS survey, women who were not using contraception were asked whether a family planning worker had visited them in the last 12 months. They were also asked whether they had attended a health facility in the last year and, if so, whether a staff person at that facility spoke to them about family planning methods. This information is important for determining whether family planning initiatives in Malawi are reaching nonusers of family planning. Table 5.17 indicates that 66 percent of women who were not using family planning reported that they were neither visited by a family planning worker nor discussed family planning at a health facility with staff personnel in the past year. Most of these women (45 percent of the total) neither received a visit from a family planning worker nor visited a health facility where family planning information or services could potentially have been provided. The remaining 21 percent of women were not visited by a family planning worker, did attend a health facility, but did not speak with a staff member about family planning. This is a missed opportunity and may indicate that family planning has not been fully integrated into the health services delivery system for women. It should be noted that, in this regard, it is among adolescent women (age 15-19) that both community-level and facility-level access to family planning information and services are most limited. Not only are these young women less likely to attend a health facility but when they do attend a facility they are less likely to have family planning discussed with them. 70 * Fertility Regulation Table 5.15 Exposure to family planning messages in print media Percentage of women who saw a message about family planning in various print and artistic media in the few months preceding the survey, by background characteristics, Malawi 2000 _____________________________________________________________________ Saw family planning message in: Background _______________________________________ characteristic Newspaper Poster Clothing Drama Number ____________________________________________________________________ Age 15-19 20-24 25-29 30-34 35-39 40-44 45-49 Residence Urban Rural Region Northern Central Southern Education No education Primary 1-4 Primary 5-8 Secondary+ Total 21.4 37.0 33.5 39.9 2,867 19.7 40.4 34.3 40.4 2,957 20.1 40.0 32.6 36.9 2,401 16.1 38.4 29.2 32.5 1,566 15.9 36.7 29.6 31.8 1,424 13.2 33.0 24.8 30.0 1,053 12.3 27.8 22.1 28.2 951 41.0 59.0 57.6 67.0 2,106 14.0 33.4 26.1 30.2 11,114 32.1 48.4 42.0 40.0 1,453 16.1 40.2 28.6 34.3 5,321 17.0 32.7 30.7 36.7 6,446 4.8 21.8 14.9 19.5 3,574 9.8 32.7 24.4 30.2 4,025 23.4 44.4 38.6 43.7 4,152 59.9 69.0 67.3 71.1 1,468 18.3 37.4 31.1 36.1 13,220 Differentials across Malawi’s districts in contact with family planning providers are substantial. In Salima and Lilongwe districts, more than 70 percent of noncontracepting women were not contacted by a family planning provider, compared with 48 percent in Mulanje District. The results also show that 12 percent of noncontracepting women were visited by a family planning worker in the last 12 months. Women living in rural areas are more likely to have contact with a community-based family planning worker (12 percent) than urban women (8 percent). Contact with a family planning worker was highest in the Southern Region (14 percent) and lowest in the Northern Region (8 percent). Women in Mulanje District were three times more likely (24 percent) to be visited by a family planning worker than their counterparts in Lilongwe District (7 percent) and Mzimba District (8 percent). Fertility Regulation * 71 Table 5.16.1 Exposure to radio programs on health and family planning: women Percentage of women who reported having listened to specific health and family planning radio programmes in the few months preceding the survey, by background characteristics, Malawi 2000 Phukusi Women’s Window Background Uchembere la Pa Talking Through Umoyo Tinka- Radio Chitukuku Women's characteristic Wabwino Moyo Mtondo Point Health M'Malawi nena Doctor M'Malawi Forum Tichitenji Kulera Number Age 15-19 20-24 25-29 30-34 35-39 40-44 45-49 Residence Urban Rural Region Northern Central Southern Education No education Primary 1-4 Primary 5-8 Secondary+ Total 54.1 52.6 53.9 19.9 18.7 52.1 70.4 41.7 57.6 21.8 44.7 64.2 2,867 63.0 62.2 63.8 24.6 22.2 58.9 71.0 48.9 62.4 26.3 48.3 71.9 2,957 63.7 62.4 64.9 23.1 20.9 56.3 69.4 46.7 60.3 25.6 49.8 71.0 2,401 60.6 59.6 60.4 21.1 20.3 55.2 67.5 45.4 59.3 23.3 49.1 68.9 1,566 60.0 58.6 58.6 22.1 20.2 55.3 65.4 44.3 60.1 25.3 48.3 67.2 1,424 55.0 55.2 58.6 21.4 18.2 50.0 61.0 41.3 54.5 23.2 44.9 64.2 1,053 50.8 48.4 55.6 14.1 14.5 50.9 57.0 36.5 54.1 18.3 44.7 61.3 951 75.2 76.4 76.1 38.7 35.1 71.0 85.7 64.8 74.1 42.8 61.0 83.7 2,106 56.0 54.4 56.8 18.4 17.0 51.8 64.4 40.7 56.3 20.3 44.8 64.9 11,114 57.2 54.3 56.5 24.0 23.2 53.9 63.8 45.8 57.8 24.0 43.2 69.4 1,453 56.1 55.2 57.8 19.1 17.5 51.0 65.4 42.9 55.6 21.2 43.7 64.7 5,321 61.9 60.9 62.4 23.1 21.1 58.2 70.6 45.6 62.3 26.1 51.3 70.1 6,446 47.0 44.5 48.5 10.2 9.7 42.0 54.2 29.4 46.4 13.5 38.1 56.0 3,574 53.9 52.5 55.0 14.3 13.4 49.1 63.3 37.8 55.2 16.3 42.9 63.5 4,025 66.4 65.5 67.0 25.2 23.1 62.3 75.7 51.5 65.8 26.2 53.0 74.9 4,152 81.9 83.7 81.2 59.6 53.7 80.8 90.4 80.2 81.9 63.4 66.1 88.5 1,468 59.0 57.9 59.9 21.6 19.9 54.8 67.8 44.5 59.1 23.9 47.3 67.8 13,220 Table 5.16.2 Exposure to radio programs on health and family planning: men Percentage of men who reported having listened to specific health and family planning radio programmes in the few months preceding the survey, by background characteristics, Malawi 2000 Phukusi Women’s Window Background Uchembere la Pa Talking Through Umoyo Tinka- Radio Chitukuku Women's characteristic Wabwino Moyo Mtondo Point Health M'Malawi nena Doctor M'Malawi Forum Tichitenji Kulera Number Age 15-19 20-24 25-29 30-34 35-39 40-44 45-49 50-54 Residence Urban Rural Region Northern Central Southern Education No education Primary 1-4 Primary 5-8 Secondary+ Total 66.2 70.0 66.2 20.5 18.6 73.3 86.0 52.9 76.2 24.3 54.2 76.3 660 75.9 79.7 76.1 29.7 31.1 79.6 91.8 68.8 79.6 35.1 55.0 83.8 598 78.3 84.1 78.3 34.6 31.0 82.3 92.5 68.4 82.0 42.0 61.9 88.9 539 79.4 85.2 80.2 40.4 39.2 82.7 90.2 74.8 86.3 44.4 61.3 91.5 330 78.6 83.4 80.7 34.2 31.8 81.8 88.5 68.1 79.8 38.8 63.2 89.0 340 77.0 83.0 76.8 37.0 30.0 81.3 87.5 72.5 83.8 42.9 68.7 87.4 240 78.5 80.7 79.5 39.0 33.2 81.7 85.6 66.9 82.1 42.3 70.2 85.0 207 80.8 80.2 81.8 37.1 34.0 81.8 86.3 68.4 86.6 39.6 74.8 86.1 177 73.4 83.0 74.6 38.0 34.5 77.8 94.4 82.0 75.7 49.1 53.8 87.6 564 75.9 79.0 76.2 30.5 28.5 80.1 87.9 62.5 82.1 34.0 62.4 84.4 2,528 74.3 76.7 75.5 42.7 46.3 80.2 82.3 69.2 84.4 41.4 66.8 84.5 351 74.9 80.9 77.5 28.1 25.5 81.3 90.0 66.3 81.2 33.3 56.7 85.9 1,296 76.3 79.4 74.6 32.6 29.2 78.1 89.9 65.0 79.7 38.7 63.0 84.3 1,446 69.7 75.3 75.3 12.8 9.8 76.3 83.3 52.2 72.8 15.9 59.2 78.7 322 68.4 72.6 71.9 16.8 15.8 74.0 84.4 54.1 76.5 20.9 58.0 80.3 898 78.9 83.2 80.0 36.3 32.4 83.1 91.4 69.4 86.1 38.0 63.5 88.3 1,243 81.6 85.4 73.9 54.3 53.8 83.0 94.3 83.4 81.2 67.5 60.4 88.3 629 75.5 79.8 75.9 31.8 29.6 79.7 89.1 66.0 80.9 36.7 60.8 85.0 3,092 Fertility Regulation * 73 Table 5.17 Contact of nonusers with family planning providers Percent distribution of women who are not using contraception by whether they were visited by a family planning (FP) worker or spoke to a health facility (HF) staff person about family planning methods in the 12 months preceding the survey, according to background characteristics, Malawi 2000 __________________________________________________________________________________________________________ Visited by FP worker Not visited by a FP worker Neither __________________________ __________________________ visited by Attended Attended Did not Attended Attended Did not FP worker HF and HF but attend HF and HF but attend nor Number Background discussed did not health discussed did not health discussed of characteristic FP1 discuss FP1 facility FP1 discuss FP1 facility Total FP at HF women ____________________________________________________________________________________________________________ Age 15-19 20-24 25-29 30-34 35-39 40-44 45-49 Residence Urban Rural Region Northern Central Southern Districts Blantyre Karonga Kasungu Lilongwe Machinga Mangochi Mulanje Mzimba Salima Thyolo Zomba Other districts Education No education Primary 1-4 Primary 5-8 Secondary+ Total 2.2 1.7 3.2 9.6 21.6 61.7 100.0 83.3 2,642 5.9 2.3 3.5 29.2 22.4 36.6 100.0 58.9 2,233 10.2 2.6 3.2 31.6 20.5 31.9 100.0 52.4 1,610 8.3 2.9 4.4 32.6 18.6 33.1 100.0 51.7 1,051 6.5 1.6 3.9 25.1 21.3 41.6 100.0 62.9 941 5.3 2.7 5.7 17.6 18.9 49.8 100.0 68.7 702 4.0 2.3 5.7 12.3 21.4 54.3 100.0 75.7 743 3.7 1.8 2.6 24.3 22.2 45.5 100.0 67.7 1,430 6.1 2.3 4.0 21.9 20.9 44.8 100.0 65.6 8,491 4.0 0.9 2.7 27.7 17.6 47.1 100.0 64.7 1,046 4.7 2.2 3.1 19.9 22.3 47.8 100.0 70.1 3,963 7.0 2.5 4.6 23.0 20.8 42.0 100.0 62.8 4,913 4.5 3.1 1.7 24.5 26.8 39.3 100.0 66.1 913 4.4 1.7 2.8 22.6 19.7 48.8 100.0 68.5 206 7.6 2.9 4.0 28.5 22.5 34.6 100.0 57.1 337 2.9 1.4 3.0 19.9 19.1 53.8 100.0 72.8 1,304 6.8 1.4 4.8 17.1 19.8 50.1 100.0 69.9 371 7.5 2.4 6.6 21.9 17.5 44.2 100.0 61.7 531 10.9 5.0 7.8 28.1 16.0 32.3 100.0 48.3 461 3.7 0.7 3.8 27.2 19.0 45.7 100.0 64.7 432 3.7 1.6 3.8 14.5 24.0 52.4 100.0 76.4 252 6.5 4.0 4.2 24.8 22.1 38.5 100.0 60.6 522 7.3 2.1 5.5 24.6 19.6 40.6 100.0 60.2 670 6.0 2.0 3.4 21.0 21.7 46.0 100.0 67.6 3,923 5.7 1.9 4.9 19.2 21.4 46.9 100.0 68.2 2,736 6.0 2.5 3.7 21.8 19.9 46.1 100.0 66.0 3,100 6.1 1.8 3.6 25.0 20.4 43.0 100.0 63.5 3,066 4.3 3.3 1.9 23.8 25.4 41.3 100.0 66.7 1,019 5.7 2.2 3.8 22.3 21.1 44.9 100.0 65.9 9,921 __________________________________________________________________________________________________________ Note: The total includes 3 respondents who were missing information on whether they were visited by a family planning provider. 1 Spoke with health facility staff about family planning methods 74 * Fertility Regulation Table 5.18 Discussion of family planning with husband Percent distribution of currently married women who know a contraceptive method by the number of times family planning was discussed with their husband in the past year, according to current age, Malawi 2000 _____________________________________________________________________________________________ Number of times family planning was discussed with husband _____________________________________________ Three Once or or more Age Never twice times Missing Total Number _____________________________________________________________________________________________ 15-19 20-24 25-29 30-34 35-39 40-44 45-49 Total 31.1 43.3 25.2 0.4 100.0 900 23.5 40.7 35.6 0.1 100.0 2,304 23.7 37.9 38.4 0.1 100.0 2,079 27.4 35.7 36.8 0.1 100.0 1,301 29.3 32.1 38.6 0.0 100.0 1,183 37.5 27.6 34.9 0.0 100.0 836 44.6 28.7 26.7 0.0 100.0 720 28.5 36.4 35.0 0.1 100.0 9,323 5.18 DISCUSSION ABOUT FAMILY PLANNING WITH HUSBAND Although discussion between husband and wife about contraceptive use is not a precondition for adoption of contraception, its absence may be an impediment to use. Interspousal communication is thus an important intermediate step along the path to eventual adoption and especially continuation of contraceptive use. Lack of discussion may reflect a lack of personal interest, hostility to the subject, or customary reticence in talking about sex-related matters. To explore this subject, women interviewed in the 2000 MDHS survey were asked about the number of times family planning was discussed with their husband in the 12 months preceding the survey. Table 5.18 shows the percent distribution of married women who know about family planning by the number of times they reported having discussed family planning with their husband in the 12 months before the survey. The results indicate that 29 percent of the women did not discuss family planning at all with their husband in the past year, while 36 percent and 35 percent had discussed family planning once or twice or three or more times, respectively. Interspousal communication was more frequent among younger women (except age 15-19), compared with older women. These results represent an improved environment for communication between spouses since the 1992 MDHS survey, when 43 percent of women reported that they had not spoken to their husband about family planning in the past year. 5.19 ATTITUDES OF COUPLES TOWARD FAMILY PLANNING When couples have a positive attitude toward family planning, they are more likely to adopt a family planning method. In the 2000 MDHS survey, married women were asked whether they approved of couples using family planning and what they perceived as their husband’s attitude toward family planning. This information is important in the formulation of family planning policies since it indicates the extent to which further education and publicity are needed to increase acceptance of family planning. Fertility Regulation * 75 Table 5.19 Attitudes of couples toward family planning Percent distribution of currently married women who know of a method of family planning (FP) by approval of family planning and their perception of their husband's attitude toward family planning, according to background characteristics, Malawi 2000 _________________________________________________________________________________________________________________ Respondent Respondent approves of disapproves of Percentage Percent- family planning family planning of respon- age of _________________ ________________ dents husbands Husband Husband’s Husband’s Both Respon- who who Background Both dis- attitude Husband attitude disap- dent approve approve characteristic approve approves unknown approves unknown prove unsure Total of FP of FP Number ________________________________________________________________________________________________________________ Age 15-19 20-24 25-29 30-34 35-39 40-44 45-49 Residence Urban Rural Region Northern Central Southern Education No education Primary 1-4 Primary 5-8 Secondary+ Total 71.2 10.1 10.1 1.7 0.9 4.4 1.6 100.0 91.4 73.1 900 75.7 11.3 7.0 0.9 0.7 3.5 0.8 100.0 94.1 76.7 2,304 74.6 13.1 6.5 0.7 0.8 3.7 0.4 100.0 94.3 75.4 2,079 77.2 11.8 6.4 0.1 0.6 3.4 0.4 100.0 95.4 77.5 1,301 70.3 15.8 7.3 1.5 0.8 3.7 0.7 100.0 93.3 71.7 1,183 72.1 12.5 7.1 2.0 0.7 4.8 0.8 100.0 91.7 74.2 836 66.5 11.6 11.8 2.3 0.7 5.7 1.4 100.0 89.9 69.0 720 81.0 9.6 6.0 0.6 0.7 1.7 0.5 100.0 96.6 81.7 1,360 72.2 12.8 7.8 1.2 0.8 4.3 0.8 100.0 92.9 73.5 7,963 71.3 11.8 7.3 1.5 2.2 4.4 1.7 100.0 90.4 72.9 1,055 74.3 12.1 6.3 1.8 0.6 4.5 0.4 100.0 92.7 76.1 3,859 73.3 12.8 8.7 0.5 0.5 3.3 0.9 100.0 94.8 74.0 4,409 65.9 14.3 10.3 1.7 0.8 5.7 1.2 100.0 90.5 67.7 2,907 72.6 13.3 8.0 0.8 0.8 3.8 0.8 100.0 93.9 73.4 2,942 78.8 10.7 5.3 1.0 0.8 2.9 0.4 100.0 94.9 79.9 2,762 87.8 6.9 3.2 0.7 0.0 1.2 0.2 100.0 97.9 88.7 713 73.5 12.4 7.5 1.1 0.8 3.9 0.8 100.0 93.4 74.7 9,323 Table 5.19 shows that 93 percent of currently married, nonsterilised women who know a contraceptive method approve of couples using contraception. There are small differences in approval in the use of family planning between women in the three regions of the country and women in the rural and urban areas. Women from the Northern Region were slightly less likely to approve of family planning than women from other regions. Age appears not to have a big influence on a woman’s attitude toward family planning. The results suggest that better educated women are more receptive to the idea of family planning than less educated women. Seventy-four percent of women reported that both they and their husband approved of family planning; only 4 percent reported that both they and their husband disapproved. Eight percent of women did not know whether their husband disapproved of family planning or not. When the wife perceived a conflicting opinion between herself and her husband, it was more likely that the husband disapproved and the wife approved (12 percent) than that the wife disapproved and the husband approved (1 percent). Among subgroups of the population, discrepancies between the woman’s and man’s view of family planning as well as uncertainty about the man’s view were most common when the respondent had never been to school. Other Proximate Determinants of Fertility * 75 Table 6.1 Current marital status Percent distribution of women and men by current marital status, according to age, Malawi 2000____________________________________________________________________________________________ Marital status_______________________________________________________ Never Living Not living Age married Married together Widowed Divorced together Total Number____________________________________________________________________________________________ WOMEN____________________________________________________________________________________________ 15-19 20-24 25-29 30-34 35-39 40-44 45-49 All ages 63.2 31.1 1.4 0.1 1.6 2.5 100.0 2,867 12.3 77.3 1.3 1.0 3.9 4.2 100.0 2,957 1.8 86.2 1.4 2.3 4.8 3.4 100.0 2,401 0.9 82.6 1.3 5.1 5.2 5.0 100.0 1,566 0.3 82.7 1.0 6.5 5.9 3.6 100.0 1,424 0.4 79.6 0.9 8.9 7.3 2.9 100.0 1,053 0.0 76.2 1.5 11.4 7.0 3.9 100.0 951 17.0 70.2 1.3 3.5 4.4 3.6 100.0 13,220 ____________________________________________________________________________________________ MEN____________________________________________________________________________________________ 15-19 20-24 25-29 30-34 35-39 40-44 45-49 50-54 All ages 96.0 3.3 0.2 0.0 0.4 0.1 100.0 660 58.2 37.4 2.0 0.0 1.1 1.2 100.0 598 13.6 79.3 2.4 0.5 2.0 2.2 100.0 539 3.0 90.7 2.7 0.5 2.1 0.9 100.0 330 1.3 88.4 4.0 2.3 2.6 1.5 100.0 340 0.6 90.8 4.1 0.8 3.7 0.1 100.0 240 0.0 89.6 4.7 1.0 2.9 1.8 100.0 207 0.9 86.8 4.1 1.4 3.2 3.6 100.0 177 34.7 59.2 2.5 0.6 1.8 1.2 100.0 3,092 OTHER PROXIMATE DETERMINANTS OF FERTILITY 6 Martin Palamuleni This chapter focuses on the principal factors, other than contraception, that affect a woman’s risk of becoming pregnant. These factors include nuptiality and sexual intercourse, postpartum amenorrhoea, abstinence from sexual relations, and onset of menopause. Sexual initiation and marriage signal the onset of women’s exposure to the risk of childbearing, postpartum amenorrhoea and abstinence affect the length of intervals between births, and the onset of menopause marks the end of a woman’s reproductive life. Collectively, these factors determine the length and pace of reproductive activity and are therefore important for understanding fertility levels and trends. 6.1 MARITAL STATUS The demographic significance of marriage patterns derives from the fact that formal or informal unions are primary indicators of exposure to the risk of pregnancy. The percentage distribution of women and men by marital status is shown in Table 6.1. The data indicate that 17 percent of women of reproductive age in Malawi have never married; 70 percent are currently married; 1 percent are living with a man; and 12 percent are widowed, divorced, or no longer living with a man. 76 * Other Proximate Determinants of Fertility There has been a slight increase in the percentage of women currently in a union (married or living together) over the past eight years, from 72 percent based on the 1992 MDHS survey to 75 percent in 2000. The proportion of women age 15-49 who have never married declines sharply from 63 percent for women age 15-19 to less than 1 percent for women age 30 and over. This confirms that marriage is essentially universal in Malawi. As expected, most of the single (never married) women are under 25 years old. The proportion of women who are currently married increases to a peak at age 25-29 (86 percent) and then declines slowly because of increasing levels of widowhood and divorce with age. Thirty-five percent of the men interviewed have never been married; 59 percent are currently married; 3 percent are living with a woman; and 4 percent are widowed, divorced, or no longer living with a woman. Compared with women, a much greater proportion of men (twice as many as women) have never been married. This is, as we will see in later sections, due to later age at marriage among men. Widowhood is rare among men, indicating that they are more likely than women to die before their spouse and more likely to remarry upon the death of a spouse. 6.2 POLYGYNY The extent of polygyny in Malawi was measured in the 2000 MDHS survey by asking married women whether their husband has other wives and, if so, how many. Married men were asked whether they have more than one wife and, if so, how many other wives. Table 6.2 shows the percentage of currently married women by the number of co-wives they have, according to background characteristics. Overall, 17 percent of currently married women in Malawi are in a polygynous union (that is, one or more co-wives). Older women are more likely to be in polygynous unions than younger women. Polygyny is more common in rural areas (19 percent) than in urban areas (9 percent). Polygyny exists in all regions of the country but is most prevalent in the Northern Region, followed by the Central and Southern regions (26, 18, and 14 percent, respectively). Nearly 21 percent of women with no education are in polygynous unions, compared with 8 percent of those with secondary and higher education. Based on comparisons with previous surveys, polygyny is on the decline in Malawi. The proportion of married women in polygynous unions has fallen from 21 percent in the 1992 MDHS survey to 17 percent in the 2000 MDHS survey. Data on polygynous unions among currently married men are also given in Table 6.2. Nine percent of married men report being in a polygynous union, but this varies greatly by age, place of residence, region, and level of education. Whereas only 11 percent of married men age 30-34 are in a polygynous union, the corresponding proportion for those age 50-54 is 21 percent. Differentials in urban-rural residence, region, and level of education for men parallel those observed for women (Figure 6.1). Other Proximate Determinants of Fertility * 77 Table 6.2 Number of co-wives and wives Percent distribution of currently married women by number of co-wives and percent distribution of currently married men by number of wives, according to background characteristics, Malawi 2000________________________________________________________________________________________________ WOMEN MEN_________________________________________ ____________________________ Number of co-wives Number of wives__________________________________ ___________________ Background Don’t characteristic 0 1 2+ know Total Number 1 2+ Total Number________________________________________________________________________________________________ Age 15-19 20-24 25-29 30-34 35-39 40-44 45-49 50-54 Residence Urban Rural Region Northern Central Southern Education No education Primary 1-4 Primary 5-8 Secondary+ Total 92.5 7.1 0.2 0.2 100.0 934 100.0 0.0 100.0 23 88.7 9.5 1.6 0.2 100.0 2,324 96.9 3.1 100.0 236 81.9 16.1 1.8 0.1 100.0 2,102 95.0 5.0 100.0 441 77.8 19.4 2.8 0.0 100.0 1,312 89.4 10.6 100.0 308 78.3 17.3 4.0 0.4 100.0 1,192 91.4 8.6 100.0 314 78.5 16.6 4.9 0.0 100.0 848 90.5 9.5 100.0 228 75.7 20.5 3.8 0.0 100.0 739 82.8 17.2 100.0 195 na na na na na na 78.6 21.4 100.0 161 91.3 7.7 0.8 0.2 100.0 1,362 96.5 3.5 100.0 307 81.4 15.8 2.7 0.1 100.0 8,089 89.5 10.5 100.0 1,599 74.0 20.7 5.2 0.2 100.0 1,075 81.3 18.7 100.0 217 81.6 15.2 2.9 0.2 100.0 3,919 91.4 8.6 100.0 775 86.0 12.6 1.4 0.1 100.0 4,458 92.2 7.8 100.0 914 79.1 18.2 2.7 0.1 100.0 2,975 89.1 10.9 100.0 265 83.0 14.5 2.2 0.2 100.0 2,980 91.3 8.7 100.0 565 84.4 12.6 2.9 0.1 100.0 2,784 88.7 11.3 100.0 737 91.2 7.6 0.8 0.4 100.0 713 94.6 5.4 100.0 338 82.8 14.6 2.4 0.2 100.0 9,452 90.6 9.4 100.0 1,906 ________________________________________________________________________________________________ na = Not applicable 1 The median for the age group 45-49 years is probably overestimated, since previous survey research indicates that older women tend to (retrospectively) overestimate their age at first marriage. Hence, this estimate is not considered in looking at the trend in median age at first marriage. 78 * Other Proximate Determinants of Fertility Table 6.3 Age at first marriage Percentage of women and men who were first married by specific exact ages and median age at first marriage, according to current age, Malawi 2000____________________________________________________________________________________________ WOMEN____________________________________________________________________________________________ Percentage Median Percentage who were first married by exact age: who had age at_________________________________________ never first Current age 15 18 20 22 25 married Number marriage____________________________________________________________________________________________ 15-19 20-24 25-29 30-34 35-39 40-44 45-49 Women 20-49 5.6 na na na na 63.2 2,867 a 10.2 46.9 72.9 na na 12.3 2,957 18.2 12.9 48.5 76.0 88.7 96.1 1.8 2,401 18.1 17.0 53.9 75.8 87.9 94.7 0.9 1,566 17.7 15.2 54.3 74.4 86.0 93.1 0.3 1,424 17.7 18.9 55.7 77.0 86.9 93.7 0.4 1,053 17.5 15.4 51.9 72.4 81.9 91.7 0.0 951 17.9 13.9 50.7 74.6 86.3 92.5 4.2 10,353 17.9 ____________________________________________________________________________________________ MEN____________________________________________________________________________________________ Percentage Median Percentage who were first married by exact age: who had age at_________________________________________ never first Current age 20 22 25 28 30 married Number marriage____________________________________________________________________________________________ 25-29 30-34 35-39 40-44 45-49 50-54 Men 25-54 19.0 40.1 72.9 na na 13.6 539 22.7 23.3 42.3 69.1 86.0 94.1 3.0 330 22.9 23.1 41.8 70.2 82.2 89.0 1.3 340 22.9 26.7 47.4 72.6 87.8 93.5 0.6 240 22.3 16.9 40.2 70.9 87.4 91.1 0.0 207 22.7 17.5 37.3 66.5 84.5 89.9 0.9 177 23.3 21.2 41.5 70.8 85.2 90.1 4.9 1,833 22.8 ____________________________________________________________________________________________ na = Not applicablea Less than 50 percent of respondents in the age group x to x+4 have married by age x. 6.3 AGE AT FIRST MARRIAGE For most societies, marriage marks the point in a woman’s life when childbearing first becomes socially acceptable. Women who marry early will have, on average, longer exposure to the risk of pregnancy; therefore, early age at first marriage usually implies higher fertility levels for a society. In the 2000 MDHS survey, information on age at first marriage was obtained by asking all ever-married respondents for the month and year that they started living together with their first husband. Table 6.3 shows that the median age at first marriage for women age 20-49 is about 18 years. The median age at first marriage has risen slowly over the last generation, from around 17.5 years among women age 40-44 to around 18.2 years for women age 20-24 years1. This is consistent with a rise of about the same magnitude between the 1992 MDHS and 2000 MDHS estimates in the 20-24 age group from 17.7 years and 18.2 years. Other Proximate Determinants of Fertility * 79 Table 6.4 Median age at first marriage Median age at first marriage among women age 20-49 years and men age 25-54, by current age and background characteristics, Malawi 2000____________________________________________________________________________________ Current age Women Background __________________________________________________ age characteristic 20-24 25-29 30-34 35-39 40-44 45-49 20-49____________________________________________________________________________________ WOMEN____________________________________________________________________________________ Residence Urban Rural Region Northern Central Southern Education No education Primary 1-4 Primary 5-8 Secondary+ All women 19.6 18.8 18.0 18.0 18.0 18.4 18.7 18.0 18.0 17.7 17.6 17.5 17.8 17.8 17.8 17.6 17.9 17.4 17.6 17.5 17.7 18.7 18.4 18.1 17.9 17.8 18.1 18.3 17.9 17.8 17.4 17.6 17.1 17.8 17.7 17.0 17.6 17.0 17.8 17.3 18.1 17.4 17.6 17.8 17.6 17.1 16.8 17.8 17.5 18.2 18.0 18.0 17.9 17.9 17.4 18.0 20+a 21.9 20.9 20.1 20.2 18.9 20+a 18.2 18.1 17.7 17.7 17.5 17.9 17.9 ___________________________________________________________________________________ Current age Men Background __________________________________________________ age characteristic 25-29 30-34 35-39 40-44 45-49 50-54 25-54___________________________________________________________________________________ MEN___________________________________________________________________________________ Residence Urban Rural Region Northern Central Southern Education No education Primary 1-4 Primary 5-8 Secondary+ All men 24.4 25.1 24.6 23.8 22.8 24.7 24.4 22.4 22.3 22.5 21.9 22.7 23.0 22.4 22.3 22.7 23.8 23.9 22.8 24.1 23.0 22.8 23.2 23.0 21.6 22.9 22.8 22.7 22.7 22.4 22.7 22.5 22.6 23.3 22.7 23.1 22.4 24.5 21.9 23.0 24.0 23.2 22.2 21.6 22.5 20.0 22.2 21.6 21.9 22.0 22.2 22.0 23.0 22.7 22.9 22.4 24.8 25.8 25.0 24.5 24.0 25.5 25.0 22.7 22.9 22.9 22.3 22.7 23.3 22.8 _____________________________________________________________________________________ a Less than 50 percent of respondents have been married by age 20. Median is at least 20 years. There is further evidence of increasing age at marriage observed in the proportion of women married before age 15. For example, the proportion of women married by age 15 has dropped from about 15 percent among women age 30 and over to 6 percent among women age 15-19. The male data suggest that men enter into first union about 5 years later than women; the median age at first marriage for men age 25-54 is 23 years. Only 21 percent of men were married by age 20, compared with 75 percent of women. Table 6.4 examines the median age at first marriage for women age 20-49 by background characteristics. The overall median age at first marriage observed for women age 20-49 is 17.9 years. Urban women marry, on average, nearly one year later than rural women. Regional variations indicate that women in the Central Region marry at a slightly older age than women in 80 * Other Proximate Determinants of Fertility Table 6.5 Age at first sexual intercourse Percentage of women and men who had first sexual intercourse by specified exact ages and median age at first intercourse, according to current age, Malawi 2000_____________________________________________________________________________________________ Percentage who had first Percentage Median sexual intercourse by exact age: never age at_________________________________________ having first Current age 15 18 20 22 25 intercourse Number intercourse____________________________________________________________________________________________ WOMEN____________________________________________________________________________________________ 15-19 20-24 25-29 30-34 35-39 40-44 45-49 20-49 25-49 16.5 na na na na 42.7 2,867 a 17.8 62.1 83.2 na na 4.3 2,957 17.1 21.8 62.9 83.7 91.6 95.2 0.8 2,401 16.9 21.7 66.0 83.4 91.2 94.2 0.2 1,566 16.7 20.4 65.4 82.4 90.3 94.5 0.0 1,424 16.8 23.4 64.4 83.0 88.6 93.0 0.3 1,053 16.7 21.4 63.2 80.8 87.2 92.7 0.0 951 16.9 20.6 63.7 83.0 na na 1.5 10,353 16.9 21.7 64.3 82.9 90.3 94.2 0.3 7,396 16.8 ____________________________________________________________________________________________ MEN____________________________________________________________________________________________ 15-19 20-24 25-29 30-34 35-39 40-44 45-49 50-54 20-54 25-54 29.1 na na na na 38.9 660 a 19.5 53.1 77.1 na na 6.8 598 17.7 14.5 47.0 68.7 83.4 95.9 1.0 539 18.2 13.8 44.8 69.5 83.0 92.4 0.4 330 18.3 15.2 49.3 69.7 83.1 95.0 0.1 340 18.1 9.2 44.4 64.9 78.9 91.3 0.6 240 18.5 6.2 36.7 56.0 75.0 91.2 0.0 207 19.5 10.9 32.9 52.2 68.1 90.8 0.0 177 19.6 14.2 46.4 68.4 na na 2.0 2,432 18.3 12.5 44.2 65.5 80.3 93.5 0.5 1,833 18.4 _____________________________________________________________________________________________ na = Not applicable a Less than 50 percent of respondents in age group x to x + 4 have had intercourse by age x. the Southern and Northern regions. The median age at first marriage for women with no formal education is 17.4 years, compared with 17.5 for women with one to four years of primary school and 18.0 for women with five to eight years of primary school. Women with secondary or higher education have a median age of marriage of over 20 years. 6.4 AGE AT FIRST SEXUAL INTERCOURSE Age at first marriage is often used as a proxy for exposure to sexual intercourse and hence the onset of a woman’s exposure to the risk of pregnancy. However, since some women are sexually active before marriage, the age at which women initiate sexual intercourse more directly marks the beginning of exposure to the risk of pregnancy. Table 6.5 presents the percentage of women and men who have ever had intercourse by specific ages. The findings indicate that the median age at first sex is, on average, about one year earlier than the median age at first marriage. Looking at age cohorts, the median age at first intercourse has remained roughly constant at just under 17 years. Virtually all women initiate sexual activity before their early twenties. More than one-half of adolescents (age 15-19) have already started sexual activity. Other Proximate Determinants of Fertility * 81 Table 6.6 Median age at first sexual intercourse Median age at first sexual intercourse among women age 20-49 years, by current age and background characteristics, Malawi 2000 _________________________________________________________________________________ Current age Women Background ___________________________________________________ age characteristic 20-24 25-29 30-34 35-39 40-44 45-49 20-49 _________________________________________________________________________________ Residence Urban Rural Region Northern Central Southern Education No education Primary 1-4 Primary 5-8 Secondary+ All women 17.8 17.6 17.3 17.2 16.9 17.8 17.5 17.0 16.7 16.6 16.8 16.6 16.8 16.8 17.1 17.1 17.2 16.7 17.1 17.0 17.0 17.7 17.4 17.2 17.3 17.1 17.4 17.4 16.7 16.4 16.1 16.4 16.3 16.6 16.5 16.1 16.3 16.0 16.5 16.2 16.6 16.3 16.6 16.5 16.3 16.5 16.4 17.0 16.5 17.3 17.2 17.5 17.0 17.6 17.2 17.3 18.9 19.7 19.8 19.5 18.5 18.9 19.2 17.1 16.9 16.7 16.8 16.7 16.9 16.9 The data from male respondents show a different picture. Whereas for women, average age at first sex precedes first marriage by just a year, men start having sex about five years before first marriage. Moreover, this gap may be lengthening because age at first sex seems to be declining in men, from about 19.6 years for the cohort currently age 50-54 to about 17.7 years for the cohort age 20-24. The median age at first sex for men (20-54) is 18.3 years, compared with 16.9 years for women. Table 6.6 shows differentials in the median age at first sexual intercourse by background characteristics for women age 20-49. Overall, there are limited geographical differences in the age at which women become sexually active. On average, rural women start sexual relations earlier than urban women. At the regional level, sexual activity begins earliest in the Southern Region (16.5 years), followed by the Northern Region (17.0 years), and latest in the Central Region (17.4 years). Women with at least some secondary education initiate sexual relations, on average, almost three years later than those with no education or one to four years of primary education. 6.5 RECENT SEXUAL ACTIVITY Although few women age 20-49 have never had sexual intercourse, not all those who have ever had sex are currently sexually active. In the absence of effective contraception, the probability of becoming pregnant is related to the frequency of intercourse. Information on recent sexual activity, therefore, can be used to refine measures of exposure to pregnancy. Women who had ever had sex were asked how long ago their last sexual activity occurred; this allows assessment of whether they had a recent sexual encounter. Table 6.7 shows the percent distribution of women, according to their sexual activity and background characteristics. Women are considered to be sexually active if they had sexual intercourse at least once in the four weeks prior to the survey. Women who are not sexually active may be abstaining for various reasons, such as having recently given birth (i.e., postpartum abstinence). 82 * Other Proximate Determinants of Fertility Table 6.7 Recent sexual activity Percent distribution of women by sexual activity in the four weeks preceding the survey, and among those not sexually active, the duration of abstinence and whether postpartum or not postpartum abstaining, according to background characteristics, Malawi 2000 ____________________________________________________________________________________________________ Not sexually active in last four weeks _________________________________ Never Background Sexually Postpartum Not postpartum had characteristic/ active abstaining abstaining sexual contraceptive in last _________________ _________________ inter- method 4 weeks 0-1 years 2+ years 0-1 years 2+ years Missing course Total Number ____________________________________________________________________________________________________ Current age 15-19 20-24 25-29 30-34 35-39 40-44 45-49 Marriage duration (years) Never married 0-4 5-9 10-14 15-19 20-24 25+ Residence Urban Rural Region Northern Central Southern Education No education Primary 1-4 Primary 5-8 Secondary+ Current contraceptive method No method Pill Female sterilisation Injectables Condom Other Total 28.0 10.0 0.5 15.7 2.6 0.5 42.7 100.0 2,867 58.2 18.7 1.8 14.0 1.6 1.4 4.3 100.0 2,957 66.8 15.6 1.7 12.5 1.6 1.1 0.8 100.0 2,401 63.9 13.0 1.7 15.9 3.9 1.4 0.2 100.0 1,566 67.4 9.6 2.6 13.4 5.5 1.5 0.0 100.0 1,424 64.9 6.3 2.0 15.6 9.4 1.5 0.3 100.0 1,053 61.8 2.3 1.6 16.8 16.1 1.3 0.0 100.0 951 7.7 5.2 1.0 19.6 4.8 0.4 61.3 100.0 2,243 64.7 20.0 1.3 12.5 0.5 0.9 0.0 100.0 2,837 66.2 17.1 1.7 11.8 1.7 1.7 0.0 100.0 2,351 65.6 13.8 1.4 14.6 3.2 1.5 0.0 100.0 1,835 66.0 11.7 2.8 14.2 4.0 1.3 0.0 100.0 1,428 67.7 8.1 1.7 13.8 7.2 1.6 0.0 100.0 1,150 63.4 2.8 1.9 16.7 14.0 1.2 0.0 100.0 1,375 55.0 9.5 1.3 14.9 5.2 1.2 13.0 100.0 2,106 55.8 13.0 1.6 14.5 4.0 1.2 9.9 100.0 11,114 49.5 16.7 2.8 12.9 5.2 1.2 11.7 100.0 1,453 61.3 8.7 1.6 12.3 3.6 0.9 11.6 100.0 5,321 52.5 14.5 1.2 16.9 4.4 1.4 9.2 100.0 6,446 62.1 13.9 2.0 14.6 4.0 1.4 1.9 100.0 3,574 58.5 12.0 1.3 13.3 3.7 1.1 10.2 100.0 4,025 52.9 12.3 1.5 13.6 3.7 1.2 14.9 100.0 4,152 40.1 10.3 1.8 20.8 7.1 0.9 19.0 100.0 1,468 49.1 14.0 1.8 15.0 5.2 1.1 13.9 100.0 9,921 71.3 11.5 1.8 14.4 0.5 0.5 0.0 100.0 303 78.2 5.2 1.4 11.0 2.8 1.4 0.0 100.0 504 78.6 7.3 0.5 10.8 1.2 1.7 0.0 100.0 1,717 63.4 5.5 0.0 29.9 0.1 1.2 0.0 100.0 247 71.2 10.1 1.4 15.7 0.8 0.9 0.0 100.0 528 55.7 12.4 1.6 14.6 4.2 1.2 10.4 100.0 13,220 Other Proximate Determinants of Fertility * 83 Fifty-six percent of women were sexually active in the four weeks preceding the survey, 14 percent were in postpartum abstinence, 19 percent were abstaining for reasons other than recent childbirth, and 10 percent had never had sex. With the exception of lower levels of sexual activity among women age 15-19, the proportion of women who are sexually active varies little by age of the woman and marital duration. Urban-rural residence is not closely associated with recent sexual activity in women. Women in the Central Region are more likely to be sexually active (61 percent) than counterparts in the Southern Region (53 percent) and the Northern Region (50 percent). The proportion sexually active decreases with increasing education. Women with secondary or higher education had markedly higher levels of abstinence for reasons other than giving birth. This may be due to the fact that the better educated women are likely to be younger and unmarried. Women who are using contraception are more likely to be sexually active than those who are not using a family planning method. This is not surprising, since many women do not use a method because they are having little or no sex. Among users of a family planning method, the proportion of women who are sexually active varies according to the method used: the highest level of sexual activity was found among users of injectables and female sterilisation, followed by the pill, other methods, and condoms. The proportion of women abstaining postpartum for less than two years declines with increasing age and with increasing marital duration. Women in rural areas and those who are not using any form of contraception are more likely to be postpartum abstaining. Long-term abstinence (more than two years) unrelated to childbirth rises with increasing age and duration of marriage. 6.6 POSTPARTUM AMENORRHOEA, ABSTINENCE, AND INSUSCEPTIBILITY Postpartum amenorrhoea refers to the interval between childbirth and the return of menstruation. During this time without menses, a woman is unlikely to ovulate, and the risk of pregnancy is much reduced. How long after childbirth this protection from conception lasts depends on the length and intensity of breastfeeding and on how long it takes the woman to resume sexual intercourse. Postpartum abstinence refers to the period of voluntary sexual inactivity after childbirth. Women are considered insusceptible if they are not exposed to the risk of pregnancy, either because they are amenorrhoeic or because they are abstaining from sexual intercourse after a birth. Table 6.8 shows the percentage of recent births for which mothers are postpartum amenorrhoeic, abstaining, and insusceptible at the time of the survey, by number of months since birth. The period of postpartum amenorrhoea is considerably longer than the period of postpartum abstinence and is therefore the principal determinant of the length of postpartum insusceptibility to pregnancy in Malawi. The median duration of amenorrhea is 13 months, the median duration of abstinence is 6 months, and the median duration of the period of insusceptibility is 15 months. Virtually all women are insusceptible to pregnancy within the first two months after a birth and both amenorrhea and abstinence are important factors in their insusceptibility. However, starting from the second month after birth, the contribution of abstinence to the insusceptible period is greatly reduced as more and more women resume sexual relations. At about 12-13 months postpartum, one-half of mothers are still amenorrheic, while only 16 percent are still abstaining. From 14-23 months postpartum, however, the proportion of mothers who are amenorrhoeic also drops sharply so that by 24 months after a birth, less than 12 percent of mothers are still insusceptible to the risk of pregnancy. 84 * Other Proximate Determinants of Fertility Table 6.8 Postpartum amenorrhoea, abstinence, and insusceptibility Percentage of births in the three years preceding the survey for which mothers are postpartum amenorrhoeic, abstaining, and insusceptible, by number of months since birth, and median and mean durations, Malawi 2000________________________________________________________________ Percentage of births for which the mother is:_________________________________ Months Amenor- Insus- since birth rhoeic Abstaining ceptible Number________________________________________________________________ <2 2-3 4-5 6-7 8-9 10-11 12-13 14-15 16-17 18-19 20-21 22-23 24-25 26-27 28-29 30-31 32-33 34-35 Total Median Mean 91.6 94.1 98.8 371 90.0 80.6 96.0 477 82.7 56.2 89.8 487 76.9 44.4 84.3 445 69.8 32.0 77.9 434 59.2 20.9 64.4 469 47.9 16.3 54.0 479 44.2 19.1 52.4 405 34.4 13.6 41.7 374 29.3 10.8 35.1 426 17.3 9.8 23.3 407 13.2 7.4 18.8 400 7.5 5.5 11.3 420 8.1 6.7 13.5 416 7.0 6.1 11.6 398 6.3 4.0 9.5 390 3.0 3.5 5.9 386 1.8 3.8 4.3 407 39.7 24.8 45.5 7,590 12.7 5.8 14.5 - 14.1 9.0 16.1 - Table 6.9 shows the median durations of postpartum amenorrhoea, abstinence, and insusceptibility by various background characteristics of the mother. Young mothers (less than 30 years) tend to have a shorter duration of postpartum insusceptibility than older mothers (more than 30 years) due to their shorter period of amenorrhoea. This is associated with shorter breastfeeding durations in younger women (who are more likely to be employed in the formal sector). Urban women also have shorter periods of amenorrhoea and insusceptibility than rural women for the same reason. Regional differences, although small, are worth highlighting. Women in the Central Region have the longest duration of amenorrhoea (14 months), followed by women in the Southern Region (12 months) and the Northern Region (11 months). Women from the Central Region abstain from sex after birth for a considerably shorter duration (3 months) than women in the Southern Region (7 months) and Northern Region (8 months). There is an inverse relationship between education and women’s insusceptibility to the risk of pregnancy. Insusceptibility lasts for about 17 months postpartum among women with no education, 14 months among those with a primary education, and 13 months among women with at least some secondary education. These differentials are due to sharp education-related differences in the duration of amenorrhoea. Other Proximate Determinants of Fertility * 85 Table 6.9 Median duration of postpartum insusceptibility by background characteristics Median number of months of postpartum amenorrhoea, postpartum absti- nence, and postpartum insusceptibility, by background characteristics, Malawi 2000____________________________________________________________ Median duration of postpartum:__________________________ Background Amenor- Absti- Insuscep- characteristic rhoea nence tibility Number____________________________________________________________ Age 15-29 30-49 Residence Urban Rural Region Northern Central Southern Education No education Primary 1-4 Primary 5-8 Secondary+ Total 11.9 5.8 13.8 5,284 14.4 6.0 16.0 2,306 10.4 5.8 12.1 951 13.0 5.8 14.9 6,640 11.2 7.9 14.1 836 13.7 3.3 15.3 3,270 12.4 7.4 13.7 3,484 14.4 6.3 16.7 2,323 12.7 4.9 14.4 2,432 11.5 6.2 13.9 2,310 9.1 6.2 13.1 525 12.7 5.8 14.5 7,590 ____________________________________________________________ Note: Medians are based on current status. Fertility Preferences and Family Planning * 87 FERTILITY PREFERENCES AND UNMET NEED FOR FAMILY PLANNING A.J. Claudio-Jeke Information on the fertility preferences of men and women provides family planning programs with an assessment of trends in ideals about family size, the prevailing need for contraception, and the extent of unwanted and mistimed pregnancies. Data on fertility preferences can also be useful as an indicator of future fertility trends. In the 2000 MDHS survey, women and men were asked a series of questions to ascertain their fertility preferences including their desire to have another child, the length of time they would like to wait before having another child, and what they consider to be the ideal number of children. These data make it possible to quantify fertility preferences and, in combination with data on contraceptive use, allow estimation of the unmet need for family planning, both for spacing and limiting births. Interpretation of results on fertility preferences is the subject of controversy since it is understood that respondents’ reported preferences are, in most cases, hypothetical and thus subject to change and rationalisation. 7.1 DESIRE FOR MORE CHILDREN Men and women in the MDHS survey were asked, “Would you like to have (a/another) child or would you prefer not to have any (more) children?” Women who said they wanted to have another child were then asked how long they would like to wait before the birth of the next child. Table 7.1 shows fertility desires among women by the number of living children. Although more than one-half (53 percent) of women wanted another child, only 16 percent wanted a child soon. Forty-two percent of the women indicated either that they wanted no more children or that they had already been sterilised and therefore want to limit the family size at its current level. The majority of women (79 percent) want to space their next birth or end childbearing altogether. These women are potentially in need of either a reversible or permanent method of family planning. As expected, the desire to end childbearing increases with the number of living children, from about 5 percent among married women with no children to 84 percent among women with six or more children. A comparison of these results with data from the 1992 MDHS survey indicates that there has been a decline in the proportion of women who desire more children and an increase in the proportion of women who want to limit childbearing. The proportion of married women who want to end childbearing has risen from 25 percent in 1992 to 42 percent in 2000. The proportion of women desiring a large family has also changed over the last decade. Among married women with six or more children, the proportion who want to have another child declined from 20 percent in 1992 to 10 percent in 2000. 7 88 * Fertility Preferences and Family Planning Table 7.1 Fertility preferences by number of living children Percent distribution of currently married women by desire for more children, according to number of living children, Malawi 2000______________________________________________________________________________________________________ Number of living children1___________________________________________________________ Desire for children 0 1 2 3 4 5 6+ Total______________________________________________________________________________________________________ Have another soon2 Have another later3 Have another, undecided when Undecided Want no more Sterilised4 Declared infecund5 Missing Total Number of women 80.5 22.0 12.8 10.4 6.8 4.4 1.1 15.7 9.4 59.5 53.6 41.8 28.5 19.2 9.3 37.1 1.8 0.7 0.8 0.3 0.3 0.2 0.4 0.6 1.1 0.8 2.0 1.4 2.6 1.4 1.2 1.5 3.2 15.0 26.8 40.0 51.8 62.9 69.4 37.5 1.8 0.9 1.4 3.2 7.1 7.4 14.5 4.8 2.3 1.1 2.7 2.8 2.9 4.6 4.1 2.8 0.0 0.0 0.0 0.1 0.0 0.0 0.0 0.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 654 1,941 1,970 1,426 1,192 853 1,415 9,452 ______________________________________________________________________________________________________ 1 Includes current pregnancy2 Wants next birth within two years3 Wants to delay next birth for two or more years4 Includes both male and female sterilisation5 Woman reports that she is infecund. 7.2 DESIRE TO LIMIT CHILDBEARING BY BACKGROUND CHARACTERISTICS Table 7.2 shows the percentage of currently married men and women who want no more children by number of living children and background characteristics. Larger proportions of urban women want to stop childbearing (47 percent) than rural women (42 percent). This pattern is most pronounced for women at higher parity levels. Regional differentials are also notable. Among currently married women, women from the Central Region (irrespective of parity) are more likely to want to stop childbearing (49 percent) than women from the Northern or Southern regions (41 and 37 percent, respectively). The desire to limit childbearing appears to decrease as the respondent’s education increases; this is because more educated women have, on average, much lower fertility (i.e., lower average parity). As such, interpretation of the relationship between education level and fertility preferences needs to be based on comparisons within parity categories. For example, for women with no or one child, there are minimal educational differentials, but at higher parity, women with more education are much more likely to want to limit their family size. No clear patterns emerge when looking at the data for men except that at higher numbers of living children, urban men are more likely than rural men to want to have no more children. Figure 7.1 shows the percentage of women and men with two living children who want no additional children, according to urban-rural residence, region, and education level. Education and urban-rural differentials are smaller among men than among women. Women and men who never went to school have the same level of preference for limiting their family size at two children (about 20 percent). Women with secondary education, on the other hand, are nearly twice as likely to want to stop having children as men with the same level of education. 1 For an exact description of the calculation, see footnote 1, Table 7.3 Fertility Preferences and Family Planning * 89 7.3 UNMET NEED FOR FAMILY PLANNING Women who say either that they do not want any more children or that they want to wait two or more years before having another child, but are not using contraception, are considered to have an unmet need for family planning.1 Women who are using family planning methods are said to have a met need for family planning. Women with unmet need and met need together constitute the total demand for family planning, which can be categorised based on whether the need is for spacing or limiting births. Table 7.3 presents estimates of currently married women with unmet need, met need, and total demand for family planning services by background characteristics, according to intention to space or limit births. Based on the 2000 MDHS survey, 30 percent of married women have an unmet need for family planning services, 17 percent for spacing and 13 percent for limiting. Combined with the 31 percent of married women who are currently using a contraceptive method, the total demand for family planning comprises 60 percent of married women. At present, 51 percent of the potential demand for family planning is being met (i.e., satisfied demand). Although much remains to be accomplished to meet the need for family planning in Malawi, the survey findings point to considerable progress since the 1992 MDHS survey, when unmet need was estimated at 36 percent and the percentage of demand satisfied was just 26 percent. 90 * Fertility Preferences and Family Planning Table 7.2 Desire to limit childbearing by background characteristics Percentage of currently married women and men who want no more children, by number of living children and background characteristics, Malawi 2000________________________________________________________________________________ Number of living children1 Background _________________________________________________ characteristic 0 1 2 3 4 5 6+ Total_________________________________________________________________________________ WOMEN_________________________________________________________________________________ Residence Urban Rural Region Northern Central Southern Education No education Primary 1-4 Primary 5-8 Secondary+ Total 3.3 15.9 38.8 59.9 71.0 85.8 95.9 46.6 5.3 15.8 26.2 40.2 57.2 68.2 82.6 41.6 5.9 9.4 18.5 40.8 49.5 72.2 89.2 41.2 8.2 17.4 29.2 48.4 67.5 74.7 89.5 48.5 3.2 15.9 29.2 38.7 52.4 64.6 76.7 37.2 8.7 18.4 24.5 36.6 54.1 65.3 80.7 45.8 2.8 14.7 25.1 42.7 58.4 70.6 85.3 40.1 4.2 15.3 28.9 47.6 62.8 74.1 86.4 41.5 6.2 16.0 47.6 63.3 79.7 95.6 100.0 40.2 5.0 15.8 28.2 43.2 58.9 70.2 84.0 42.3 _________________________________________________________________________________ MEN_________________________________________________________________________________ Residence Urban Rural Region Northern Central Southern Education No education Primary 1-4 Primary 5-8 Secondary+ Total 6.5 10.2 25.1 42.4 65.7 71.9 71.0 36.6 7.9 7.7 22.9 36.8 44.3 56.7 70.2 37.4 8.2 2.8 11.9 38.6 37.7 45.9 56.2 31.2 6.0 6.2 16.3 38.0 53.9 64.2 77.8 39.9 8.7 11.1 31.4 37.4 44.4 56.2 67.5 36.5 * * * * * * * 37.7 1.5 6.2 17.8 39.2 39.5 64.0 65.4 33.5 8.9 11.7 25.8 32.6 55.3 62.5 70.5 41.1 5.9 8.5 27.0 50.8 34.5 76.3 78.3 34.8 7.7 8.3 23.2 37.8 47.5 58.5 70.3 37.3 _________________________________________________________________________________ Note: Women and men who have been sterilised are considered to want no more children. 1 Includes current pregnancy * Based on fewer than 25 cases; estimate has been suppressed As expected, unmet need for spacing is higher among younger women, while unmet need for limiting is higher among older women. Although the overall demand for contraception is lowest among adolescent women, the percentage of demand that is satisfied is also lowest in this age group (just 35 percent). This shows that young women are relatively underserved in Malawi. Total unmet need is greater among rural women (31 percent) than among urban women (23 percent) and is higher in the Central Region (33 percent) than in the Northern and Southern regions (28 percent). Unmet need is lower among women with some secondary education than among women with less education, despite greater overall demand among the more educated women. This is primarily because a larger proportion of women with secondary or higher education is currently using family planning, leading to a larger proportion being satisfied (i.e., met need). Two-thirds of demand is satisfied among women with secondary education, compared with just 46 percent among women who have never been to school. Fertility Preferences and Family Planning * 91 Table 7.3 Need for family planning Percentage of currently married women with unmet need for family planning, and with met need for family planning, and the total demand for family planning, by background characteristics, Malawi 2000 ____________________________________________________________________________________________________________ Met need for Unmet need for family planning Total demand for Percentage family planning1 (currently using)2 family planning3 of ______________________ ______________________ _____________________ demand Background For For For For For For satis- characteristic spacing limiting Total spacing limiting Total spacing limiting Total fied Number ___________________________________________________________________________________________________________ Age 15-19 20-24 25-29 30-34 35-39 40-44 45-49 Residence Urban Rural Region Northern Central Southern Education No education Primary 1-4 Primary 5-8 Secondary+ Districts Blantyre Karonga Kasungu Lilongwe Machinga Mangochi Mulanje Mzimba Salima Thyolo Zomba Other districts Currently married women Unmarried women 24.3 4.5 28.8 12.8 2.4 15.2 37.1 6.9 43.9 34.5 934 25.1 6.4 31.6 19.8 6.5 26.3 44.9 13.0 57.9 45.5 2,324 19.8 10.4 30.2 18.9 15.7 34.6 38.7 26.1 64.9 53.4 2,102 16.1 16.6 32.7 9.8 25.9 35.8 25.9 42.5 68.4 52.3 1,312 10.8 20.2 31.0 5.0 31.7 36.7 15.8 51.9 67.7 54.2 1,192 5.1 20.9 26.0 2.9 34.8 37.7 7.9 55.7 63.7 59.1 848 2.3 17.5 19.8 1.5 24.2 25.7 3.7 41.8 45.5 56.5 739 13.5 9.7 23.2 16.4 24.8 41.2 29.9 34.6 64.4 64.0 1,362 17.8 12.9 30.7 12.1 16.8 28.9 29.9 29.7 59.6 48.4 8,089 16.6 11.4 28.1 17.0 18.4 35.4 33.6 29.8 63.4 55.8 1,075 17.7 14.9 32.6 11.0 20.5 31.4 28.7 35.4 64.0 49.1 3,919 16.9 10.6 27.5 13.2 15.6 28.8 30.1 26.2 56.3 51.2 4,458 16.8 14.0 30.8 9.3 16.7 26.0 26.1 30.7 56.8 45.7 2,975 17.1 12.8 30.0 11.9 16.2 28.1 29.0 29.1 58.1 48.4 2,980 18.1 11.3 29.5 14.7 20.0 34.7 32.8 31.4 64.1 54.0 2,784 15.4 8.9 24.3 22.8 22.3 45.1 38.2 31.2 69.4 64.9 713 13.9 8.3 22.2 17.4 23.4 40.8 31.2 31.7 62.9 64.8 837 17.2 10.0 27.2 18.2 10.3 28.5 35.4 20.3 55.7 51.2 191 17.4 14.7 32.1 16.2 19.9 36.1 33.6 34.6 68.2 53.0 367 14.6 13.7 28.2 11.4 24.7 36.1 25.9 38.4 64.3 56.1 1,402 15.8 11.0 26.8 12.9 13.7 26.6 28.7 24.7 53.4 49.8 374 18.0 5.8 23.8 9.4 12.2 21.6 27.4 18.0 45.4 47.5 467 18.8 9.4 28.2 13.7 16.8 30.6 32.6 26.3 58.8 52.0 429 17.8 13.7 31.5 16.2 18.2 34.5 34.1 31.9 66.0 52.2 458 17.6 17.1 34.7 6.2 12.3 18.5 23.8 29.4 53.2 34.8 223 20.1 8.7 28.8 11.7 14.2 25.9 31.8 22.8 54.7 47.3 456 16.5 13.2 29.7 10.4 15.9 26.3 26.9 29.1 56.0 47.0 564 18.4 14.1 32.6 12.2 16.7 28.9 30.7 30.8 61.5 47.1 3,683 17.2 12.5 29.7 12.7 17.9 30.6 29.9 30.4 60.3 50.8 9,452 2.9 1.0 3.9 5.4 5.3 10.7 8.3 6.3 14.6 73.2 3,768 ___________________________________________________________________________________________________________ 1 Unmet need for spacing includes pregnant women whose pregnancy was mistimed, amenorrhoeic women whose last birth was mistimed, and women who are neither pregnant nor amenorrhoeic and who are not using any method of family planning and say they want to wait two or more years for their next birth. Also included in unmet need for spacing are women who are unsure whether they want another child or who want another child but are unsure when to have the birth. Unmet need for limiting refers to pregnant women whose pregnancy was unwanted, amenorrhoeic women whose last child was unwanted, and women who are neither pregnant nor amenorrhoeic and who are not using any method of family planning and who want no more children. 2 Using for spacing is defined as women who are using some method of family planning and say they want to have another child or are undecided whether to have another. Using for limiting is defined as women who are using and who want no more children. Note that the specific methods used are not taken into account here. 3 Pregnant and amenorrhoeic women whose pregnancy was the result of a contraceptive failure are not included in the category of unmet need (they need a better method of contraception), but are included in total demand for contraception (since they would have been using had their method not failed). 92 * Fertility Preferences and Family Planning Amongst the districts, Salima has the highest rate of unmet need (35 percent) and the lowest percentage of demand that has been satisfied through contraceptive use (35 percent). On the other hand, Blantyre has the lowest level of unmet need (22 percent) and the highest level of demand satisfied (65 percent). Unmarried women have much lower rates of unmet need (4 percent), met need (11 percent), and total need or demand (15 percent) for family planning services than married women. Among the unmarried, 73 percent of the total demand for contraception is being satisfied. 7.4 IDEAL FAMILY SIZE Information on what men and women believe to be their ideal family size was elicited through two questions. Respondents who had no children were asked, “If you could choose exactly the number of children to have in your whole life, how many would that be?” For respondents who had children, the question was rephrased as follows: “If you could go back to the time when you did not have any children and could choose exactly the number of children to have in your whole life, how many would that be?” Some respondents, especially those for whom fertility control is an unfamiliar concept, would have some difficulty in answering this hypothetical question. The results in Table 7.4 indicate that nearly all respondents were able to give a numeric response to this question; less than 1 percent of men and women responded “up to God” or “any number”. This is in itself a rather large and important change in the way individuals think about family size since the 1992 MDHS survey when 13 percent of women and 8 percent of men gave non- numeric responses to the same question. The 2000 MDHS findings indicate that about one-third of both men and women (33 percent) said they would choose to have four children, with an average response of about five children. Sixty-four percent of women and 69 percent of men in Malawi want four or fewer children. The findings show that women’s actual and ideal number of children are correlated. The average ideal family size is 3.8 among women with 1 child, compared with an ideal of 7.5 children among women with 6 or more children. There are two principal reasons for this pattern. First, to the extent that women are able to implement their fertility desires, women who want smaller families will tend to achieve smaller families. Second, some women may have difficulty admitting that they would have had fewer children if they could begin childbearing again. Such women are likely to report their actual number of children as their preferred number. Despite this tendency to rationalise, the data do provide evidence of unwanted fertility: close to half (46 percent) of the women with six or more children said that ideally they would have liked fewer than six children. In general, men and women want families of a similar size. Currently married women want on average 5.3 children, while currently married men want 5.4 children. Married men prefer larger families (5.4 children) than all men (4.8 children). For both men and women, there was a small change in the ideal family size between the 1992 MDHS survey and the 2000 MDHS survey. The average ideal family size for women in 1992 was 5.1 children, decreasing to 5.0 in 2000. For men, a more important change occurred: from an ideal family size of 5.2 in 1992 to 4.8 in 2000. Fertility Preferences and Family Planning * 93 Table 7.4 Ideal and actual number of children Percent distribution of all women and men by ideal number of children and mean ideal number of children for all women and men and for currently married women and men, according to number of living children, Malawi 2000__________________________________________________________________________________________ Number of living children1 Ideal number ___________________________________________________ of children 0 1 2 3 4 5 6+ Total__________________________________________________________________________________________ WOMEN__________________________________________________________________________________________ 0 1 2 3 4 5 6+ Non-numeric response Total Number Mean ideal number for:2 All women Number Currently married women Number 0.4 0.1 0.0 0.0 0.2 0.0 0.0 0.1 3.4 3.9 0.6 0.4 0.7 0.4 0.7 1.8 27.2 19.9 13.0 4.5 6.2 3.8 4.0 13.8 19.7 24.0 17.4 15.2 7.6 6.1 6.5 15.7 30.8 33.8 42.1 37.4 36.1 20.8 22.7 32.9 9.5 10.3 14.8 21.9 18.3 24.8 12.5 14.5 7.8 7.8 12.1 20.4 30.5 43.6 52.7 20.6 1.1 0.2 0.1 0.3 0.3 0.4 0.9 0.5 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 2,814 2,481 2,296 1,645 1,365 1,006 1,612 13,220 3.9 3.8 4.5 5.2 5.7 6.8 7.5 5.0 2,782 2,476 2,293 1,641 1,360 1,002 1,597 13,152 4.4 3.9 4.5 5.1 5.6 6.7 7.5 5.3 652 1,940 1,967 1,421 1,189 851 1,402 9,422 __________________________________________________________________________________________ MEN__________________________________________________________________________________________ 0 1 2 3 4 5 6+ Non-numeric response Total Number of men Mean ideal number for:2 All men Number Mean ideal number for: Currently married men Number 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.6 0.1 0.0 0.0 0.0 2.2 0.0 0.8 19.6 16.4 9.9 7.3 5.9 3.9 5.8 13.2 30.2 31.9 21.2 13.4 7.3 7.6 10.5 22.2 32.1 37.0 39.7 38.2 34.0 19.4 25.8 32.6 9.3 8.9 17.1 19.7 21.6 23.1 8.4 12.7 5.9 5.8 11.8 21.4 31.2 43.4 49.1 17.8 1.3 0.0 0.3 0.0 0.0 0.4 0.3 0.6 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 1,240 414 329 270 245 190 405 3,092 3.8 3.9 4.2 5.3 5.6 7.0 7.4 4.8 1,224 414 328 270 245 189 403 3,073 4.3 3.9 4.2 5.2 5.6 7.0 7.5 5.4 167 351 309 260 237 179 397 1,901 __________________________________________________________________________________________ 1 Includes current pregnancy 2 Means are calculated excluding the women and men giving non-numeric responses. Table 7.5 shows the mean ideal number of children for all women by age according to background characteristics. The mean ideal family size increases with age of the respondents from 3.7 children for women age 15-19 to 7.6 children for women age 45-49. At every age, rural women have larger family size norms than urban women, with the average ideal number of children being a full child more in the rural areas (5.2 children) than in urban areas (4.1 children). Few regional variations are observed in ideal family size. However, ideal family size is strongly related to level of education attained: as the level of education of a woman increases, her desired family size sharply decreases. 94 * Fertility Preferences and Family Planning Table 7.5 Mean ideal number of children by background characteristics Mean ideal number of children for all women, by age and background characteristics, Malawi 2000____________________________________________________________________________________________ Current age Background _____________________________________________________ Total characteristic 15-19 20-24 25-29 30-34 35-39 40-44 45-49 women___________________________________________________________________________________________ Residence Urban Rural Region Northern Central Southern Education No education Primary 1-4 Primary 5-8 Secondary+ All women 3.4 3.3 4.2 4.8 5.5 5.9 5.6 4.1 3.8 4.1 5.0 5.5 6.3 7.5 7.8 5.2 3.7 4.5 4.9 5.5 5.8 7.6 7.4 5.1 3.7 3.9 5.0 5.3 6.4 7.9 8.1 5.1 3.8 3.9 4.7 5.4 6.1 6.8 7.3 4.9 4.2 4.6 5.2 5.8 6.7 7.8 7.7 6.1 3.9 4.2 5.4 5.4 6.5 7.6 8.5 5.3 3.7 3.8 4.5 5.1 5.3 6.4 6.0 4.4 3.1 3.1 3.4 3.9 4.8 4.6 5.2 3.4 3.7 3.9 4.8 5.4 6.2 7.3 7.6 5.0 Table 7.6 Fertility planning status Percent distribution of births (including current pregnancy) in the five years preceding the survey by fertility planning status, according to birth order and mother's age at birth, Malawi 2000_______________________________________________________________________ Planning status of birth Birth order _____________________________________ and mother's Wanted Wanted Not age at birth then later wanted Missing Total Number_______________________________________________________________________ Birth order 1 2 3 4+ Age at birth <20 20-24 25-29 30-34 35-39 40-44 45-49 Total 70.9 11.6 17.2 0.4 100.0 3,157 65.8 20.6 13.3 0.2 100.0 2,722 62.3 20.9 16.4 0.4 100.0 2,150 49.5 19.9 30.3 0.3 100.0 5,739 65.8 15.2 18.8 0.2 100.0 2,705 66.0 19.2 14.5 0.3 100.0 4,525 58.2 22.1 19.2 0.4 100.0 2,995 51.6 17.5 30.6 0.3 100.0 1,773 45.1 15.4 39.0 0.5 100.0 1,135 44.0 15.9 39.9 0.2 100.0 493 38.0 12.2 49.2 0.5 100.0 143 59.6 18.3 21.7 0.3 100.0 13,769 7.5 WANTED AND UNWANTED FERTILITY There are two main ways of looking at the issue of unwanted fertility. In the first approach, responses to a question about children born in the five years preceding the survey (and any current pregnancy) are used to determine whether the pregnancy was planned (wanted then), wanted but at a later time (mistimed), or unwanted (not wanted at all). The answers to these questions provide some insight into the degree to which couples are able to control fertility. Table 7.6 shows the percent distribution of births (including current pregnancy) in the five years preceding the survey by fertility planning status, according to birth order and mother’s age at birth. Sixty percent of the births in the five years preceding the survey were wanted at the time Fertility Preferences and Family Planning * 95 Table 7.7 Wanted fertility rates Total wanted fertility rates and total fertility rates for the three years preceding the survey, by background characteristics, Malawi 2000____________________________________________ Total wanted Total Background fertility fertility characteristic rates rates____________________________________________ Residence Urban Rural Region Northern Central Southern Mother's education No education Primary 1-4 Primary 5-8 Secondary+ Districts Blantyre Karonga Kasungu Lilongwe Machinga Mangochi Mulanje Mzimba Salima Thyolo Zomba Other districts Total 3.5 4.5 5.5 6.7 5.3 6.2 5.5 6.8 5.0 6.0 6.1 7.3 5.5 6.7 4.8 6.0 2.8 3.0 3.3 4.3 4.9 5.6 5.8 7.0 5.2 6.5 5.9 7.0 6.7 7.4 4.7 5.5 5.6 6.7 5.4 6.7 4.6 5.3 5.0 6.2 5.5 6.8 5.2 6.3 ____________________________________________ Note: Rates are calculated based on births to women age 15-49 in the period 1-36 months preceding the survey. The total fertility rates are the same as those presented in Table 4.2. of conception, while 18 percent were not wanted then (wanted later) and 22 percent were not wanted at all. The percentage of births that were unwanted or mistimed increases from 29 percent for first order births to 50 percent of fourth or higher order births. The proportion of births that were not wanted at all tends to increase with increasing age of women. Given that contraceptive use has increased dramatically since 1992 from 7 to 26 percent, it might be assumed that the number and percentage of unwanted births would be reduced. This is not the case: the percentage of recent births that were not wanted has risen from 14 percent based on the 1992 MDHS data to 22 percent based on the 2000 MDHS data. Table 7.7 shows the total wanted fertility rates and total actual fertility rates for the three years preceding the survey, by selected back- ground characteristics. The wanted fertility is calculated in the same manner as the total fertility rate, but unwanted births are excluded from the numerator. For this purpose, un- wanted births are defined as those that exceed the number considered ideal by the respondent. (Women who did not report a numeric ideal family size were assumed to want all their births). The rate represents the level of fertility that would have prevailed in the three years preceding the survey if all unwanted births were prevented. A comparison of the total wanted fertility and actual total fertility rate suggests the potential demographic impact of the elimi- nation of unwanted births. The total wanted fertility rate is 5.2 for Malawi as a whole, more than 1 child lower than the actual total fertility rate (6.3). The difference between wanted and actual total fertility is greatest among those subgroups of women who, as we saw earlier, have the great- est unmet need for fertility control: rural women, less educated women, and women in the Central Region. In the Salima and Lilongwe districts, the gap between wanted and actual total fertility is 1.4 and 1.3 children, respec- tively. Infant and Child Mortality * 97 INFANT AND CHILD MORTALITY 8 Jameson S. Ndawala This chapter presents levels, trends, and differentials in mortality among children under five years of age in Malawi. This information is relevant both for the demographic assessment of the population and for assessing the impact of child-survival-related programmes. Understanding patterns in mortality during early childhood also assists in the design of health interventions by identifying sectors of the population that are at high risk. The information is thus essential for planning and evaluating current policies. Unlike earlier demographic surveys in Malawi, the 2000 MDHS survey also collected information that allows assessment of perinatal mortality, which includes stillbirths (late foetal deaths) and early neonatal deaths. 8.1 DEFINITIONS, METHODOLOGY, AND ASSESSMENT OF DATA QUALITY Estimates of childhood mortality are based on information from the birth history section of the questionnaire administered to individual women. The section begins with questions about the aggregate childbearing experience of respondents (i.e., the number of sons and daughters who live with the mother, the number who live elsewhere, and the number who have died). For each of these births, more detailed information was then collected on the sex, the month and year of birth, survivorship status, and current age, or if the child had died, the age at death. In this report, mortality in early childhood is measured using the following five rates: Neonatal mortality: the probability of dying within the first month of life Postneonatal mortality: the difference between infant and neonatal mortality Infant mortality: the probability of dying before the first birthday Child mortality: the probability of dying between the first and fifth birthday Under-five mortality: the probability of dying between birth and fifth birthday. All rates are expressed per 1,000 live births, except for child mortality, which is expressed per 1,000 children surviving to 12 months of age. In developing countries like Malawi, population censuses and demographic surveys are the major sources of mortality data. Vital registration is another potential source of mortality data, but in Malawi unfortunately, the information is incomplete in coverage and unrepresentative of the population. Mortality information from the Health Management Information System (HMIS) does not provide a suitable basis for calculation of mortality rates from a population perspective because the system is facility-based and thus does not include data on deaths that occur outside the facilities. Given this prevailing reality, birth history data from surveys continue to provide for the most robust estimates of infant and child mortality. 98 * Infant and Child Mortality Table 8.1 Early childhood mortality rates Neonatal, postneonatal, infant, child, and under-five mortality for five-year periods preceding the survey, Malawi 2000 ____________________________________________________________________ Years Neonatal Postneonatal Infant Child Under-five preceding mortality mortality1 mortality mortality mortality the survey (NN) (PNN) (1q0) (4q1) (5q0)____________________________________________________________________ 0-4 41.8 62.0 103.8 94.6 188.6 5-9 50.4 72.3 122.7 110.5 219.7 10-14 51.9 83.6 135.5 129.4 247.4 ___________________________________________________________________ 1 Computed as the difference between the infant and the neonatal mortality rates. The quality of mortality estimates calculated from retrospective birth histories depends upon the completeness with which births and deaths are reported and recorded. The most potentially serious data quality problem is the selective omission from the birth histories of births that did not survive, which will lead to underestimation of mortality rates. Other potential problems include displacement of birth dates, which may cause a distortion of mortality trends, and misreporting of the age at death, which may distort the age pattern of mortality. When selective omission of childhood deaths occurs, it is usually most severe for deaths that occur very early in infancy. If early neonatal deaths were selectively underreported, the result would be an unusually low ratio of deaths under seven days to all neonatal deaths and an unusually low ratio of neonatal to infant mortality. Underreporting of early infant deaths is more commonly observed for births that occurred longer before the survey; hence, it is useful to examine the ratios over time. Inspection of these ratios (shown in Appendix Tables C.5 and C.6) indicates that significant numbers of early infant deaths have not been omitted in the 2000 MDHS survey. First, the proportion of neonatal deaths that occur in the first week of life is high (67 percent) and is roughly constant over the 20 years before the survey (between 66 and 71 percent). Second, the proportion of infant deaths that occur during the first month of life is entirely plausible in level (42 percent) and is stable over the 20 years before the survey (varying between 38 and 44 percent). This inspection of the mortality data reveals no evidence of selective underreporting or age at death misreporting that would significantly compromise the quality of the MDHS rates of childhood mortality. It is important to recognize that any method of measuring childhood mortality that relies on mothers’ reports (e.g., full or abbreviated birth histories like those used in censuses and sample surveys) rests on the assumption that adult female mortality is not high or if it is high, that there is little or no correlation between the mortality risks of mothers and their children. In countries with high rates of adult female mortality, these assumptions will seldom hold, and the resulting childhood mortality rates will be underestimated to some degree. 8.2 EARLY CHILDHOOD MORTALITY RATES: LEVELS AND TRENDS Neonatal, postneonatal, infant, child, and under-five mortality rates, by five-year periods preceding the survey, are shown in Table 8.1. Examining the most recent five-year period (0-4 years preceding the survey, or mid-1996 to mid-2000), under-five mortality is estimated at 189 per 1,000 live births, and infant mortality is estimated at 104 per 1,000 live births. This means that one in five children born in Malawi dies before reaching the fifth birthday. The age pattern of mortality shows that 22 percent of deaths under five occur during the neonatal period, while 33 percent occur during the postneonatal period, and 45 percent of deaths occur at age 1-4 years. Infant and Child Mortality * 99 There are two main ways of evaluating trends in under-five mortality. Both are represented in Figure 8.1. In the first approach, the 2000 MDHS data are used to construct mortality rates for successive periods prior to the survey. This approach indicates that under-five mortality has declined by 14 percent, from 220 deaths per 1,000 births in the period 5-9 years before the survey (i.e., 1991-1995) to 189 for the period 0-4 years before the survey (i.e., 1996-2000). This represents a rate of mortality decline of 2.8 percent per year during the 1990s. In the second method of estimating trends in mortality, estimates of mortality from two successive surveys are compared—in this case, the 1992 MDHS survey and the 2000 MDHS survey. The strength of this comparison derives from the fact the surveys used identical data collection instruments and sample design approaches. The estimate calculated from the 1992 MDHS data (for the period 1988-1992) is 234 deaths per 1,000, compared with 189 per 1,000 from the 2000 MDHS data (for the period 1996-2000). This represents a 19 percent decline, or 2.4 percent per year during the late 1980s and 1990s. Thus, the two approaches yield essentially the same picture, one of slowly declining under-five mortality over the last decade or so. By looking at changes in neonatal mortality, postneonatal mortality, and child mortality (1- 4 years), one can assess whether there has been a change in the age pattern of under-five mortality. This examination indicates that mortality at all ages under five years is undergoing a downward trend of roughly the same magnitude: about 20 percent over the past decade. In other words, the age pattern of under-five mortality has not changed substantially. The causes of childhood mortality in the developing world are many and varied. Similarly, the causes of increases and decreases in under-five mortality are typically multifactoral. The decline in mortality at all ages, as described above, suggests that any explanation of the overall decline in under-five mortality will need to involve detailed examination of trends in numerous child-survival- related variables. This type of analysis of the causes of mortality decline in Malawi is beyond the 100 * Infant and Child Mortality Table 8.2 Early childhood mortality by socioeconomic characteristics Neonatal, postneonatal, infant, child, and under-five mortality for the ten-year period preceding the survey, by socioeconomic characteristics, Malawi 2000__________________________________________________________________________ Post- Neonatal neonatal Infant Child Under-five Socioeconomic mortality mortality1 mortality mortality mortality characteristic (NN) (PNN) (1q0) (4q1) (5q0)__________________________________________________________________________ Residence Urban Rural Region Northern Central Southern Mother's education No education Primary 1-4 Primary 5-8 Secondary+ Districts Blantyre Karonga Kasungu Lilongwe Machinga Mangochi Mulanje Mzimba Salima Thyolo Zomba Other districts Total2 29.8 52.7 82.5 71.3 147.9 47.9 68.8 116.7 106.0 210.4 40.9 60.7 101.5 76.5 170.3 42.0 55.6 97.6 114.6 201.0 50.5 79.1 129.6 95.2 212.5 46.2 70.4 116.6 110.8 214.5 56.2 72.1 128.3 110.7 224.8 36.6 62.5 99.1 87.9 178.3 30.9 34.5 65.4 56.3 118.0 37.8 68.3 106.1 94.7 190.7 37.6 55.6 93.2 57.9 145.7 37.5 55.6 93.1 125.7 207.1 42.4 56.1 98.5 105.0 193.2 56.3 62.0 118.2 98.8 205.4 51.7 63.9 115.6 95.5 200.1 61.6 68.7 130.3 111.7 227.4 52.6 52.6 105.2 84.7 181.0 55.0 76.8 131.9 123.9 239.5 58.2 87.3 145.5 93.6 225.4 42.6 108.4 151.0 76.7 216.1 43.8 65.5 109.3 106.2 203.9 45.7 66.8 112.5 101.7 202.7 ____________________________________________________________________________ 1 Computed as the difference between the infant and the neonatal mortality rates 2 Note that these rates are for the 10 years before the survey and thus differ from Table 8.1 which is based on the five years before the survey scope of this descriptive report. Still, some child-survival-related factors can be posited as potentially involved in the observed trends. Among those that would be expected to enhance child survival, researchers may look to improvements that reduce exposure to disease-causing agents. One important example of this would be the impressive gains made in the provision of clean water supplies to Malawi’s rural population (Chapter 2). Increases in the percentage of mothers who have received formal education may also be examined in light of evidence linking education to improved recognition and response to disease symptoms, as well as improved disease prevention behaviours, including adoption of hygienic practices in the household and improved infant feeding. Of course, an important 1990s trend that would be expected to counterbalance, at least in part, these improvements are the direct and indirect effects of the HIV/AIDS epidemic. These issues, and others, will need to be addressed in the context of in-depth further analysis of the MDHS data and other data. 8.3 SOCIOECONOMIC DIFFERENTIALS IN CHILDHOOD MORTALITY Table 8.2 presents mortality differentials by background characteristics such as urban-rural residence, region, district, and level of education of mothers. A ten-year period (1991-2000) is used to calculate the mortality estimates in order to have a sufficient number of cases in each category. Infant and Child Mortality * 101 As expected, urban mortality rates are generally lower than rural rates. The under-five mortality rate is 148 per 1,000 in urban parts of the country, compared with 210 per 1,000 in rural areas. The urban-rural difference is proportionately larger during the neonatal period than during the postneonatal and 1-4 age periods. Comparing the three regions, the Northern Region has the lowest under-five mortality (170 per 1,000 live births), followed by the Central Region (201 per 1,000) and the Southern Region (212 per 1,000). On the other hand, the infant mortality rate is lowest in the Central Region (98 per 1,000 live births), followed by the Northern Region (102), and is highest in the Southern Region (130). The lower infant mortality rate in the Central Region is due to a lower postneonatal mortality compared with the Northern and Southern regions. These regional differences in the age pattern of under-five mortality was also observed in the 1992 MDHS survey; however, since that time, mortality in the Southern Region has declined at a slower pace, at all ages, than mortality in the other two regions. Table 8.2 also presents childhood mortality rates in the 11 oversampled districts. Under-five mortality was lowest in the Northern districts of Karonga (146 per 1,000) and Mzimba (181 per 1,000) and was highest in Salima District (239 per 1,000), Mulanje District (227 per 1,000), and Thyolo District (225 per 1,000). For infant mortality, Karonga and Kasungu districts had the lowest rates (93 per, 1,000) while the highest rates were observed in Zomba (151 per 1,000), Thyolo (146 per 1,000), Salima (132 per 1,000), and Mulanje (130 per 1,000). Mother’s education is strongly linked to child survival. At all ages under five, higher levels of education are generally associated with lower mortality risks. As an exception to this pattern, children of women with no formal schooling have slightly lower mortality rates than children of women with one to four years of primary education. Children of women with a secondary education have much lower under-five mortality than children of other women. Strong education- related differentials are apparent during every age period. 8.4 BIODEMOGRAPHIC DIFFERENTIALS IN CHILDHOOD MORTALITY Studies have shown that biodemographic factors impact survival chances of young children. These factors include sex of the child, age of the mother at birth, birth order, length of previous birth interval, and the size of the child at birth. Table 8.3 presents mortality rates for the ten years preceding the survey by selected demographic characteristics. The MDHS results show that male children experience slightly higher mortality than female children, with under-five mortality rates of 207 and 199 deaths per 1,000 live births for males and females, respectively. This differential is apparent during the first year of life, but does not extend beyond the first birthday, suggesting that heritable, nonbehavioural factors are the cause of the difference. Children born to younger mothers (under 20 years of age) and older mothers (over 40 years) had higher mortality than children born to mothers age 20-39 years (Figure 8.2). Children of mothers under age 20 are especially vulnerable, particularly in the first month of life. Neonatal mortality is 68 deaths per 1,000 among children of teenage mothers, compared with 38 per 1,000 among children of women age 20-29. The relationship between birth order and mortality shows the same U-shaped pattern, with first births and higher order births experiencing the highest mortality rates. 102 * Infant and Child Mortality Table 8.3 Early childhood mortality by demographic characteristics Neonatal, postneonatal, infant, child, and under-five mortality for the ten-year period preceding the survey, by demographic characteristics, Malawi 2000_________________________________________________________________________________ Post- Neonatal neonatal Infant Child Under-five Demographic mortality mortality1 mortality mortality mortality characteristic (NN) (PNN) (1q0) (4q1) (5q0)__________________________________________________________________________________ Sex of child Male Female Mother's age at birth < 20 20-29 30-39 40-49 Birth order 1 2-3 4-6 7+ Previous birth interval2 < 2 years 2 years 3 years 4 or more years Birth size3 Small or very small Average or large 50.4 66.8 117.1 101.4 206.6 41.1 66.8 107.9 102.0 198.9 67.6 80.6 148.2 125.6 255.2 37.7 66.6 104.3 99.2 193.1 40.5 55.6 96.1 88.6 176.1 67.4 61.3 128.7 82.6 200.6 59.9 80.0 139.9 114.4 238.3 41.6 67.6 109.2 103.7 201.6 36.1 59.2 95.3 91.8 178.4 51.8 59.4 111.2 98.5 198.7 72.9 93.4 166.3 144.3 286.7 36.5 58.4 94.9 97.2 182.9 27.5 45.7 73.1 79.3 146.6 25.6 52.1 77.7 57.6 130.8 82.7 71.0 153.7 na na 32.1 58.7 90.8 na na _________________________________________________________________________________ na = Not applicable 1 Computed as the difference between the infant and the neonatal mortality rates. 2 Excludes first-order births 3 Rates for the five-year period before the survey. Infant and Child Mortality * 103 The most potent variable explaining variation in under-five mortality is the length of the interval between births. As the birth interval gets shorter, the risk of child death increases sharply. This pattern is most pronounced in the neonatal period, when a threefold difference in risk is observed between children with an interval less than 24 months (73 per 1,000) and those with a interval of 4 years or more (26 per 1,000). The findings suggest the potential for reducing the mortality risks of Malawian children by promoting family planning use and traditional practices (such as long durations of breastfeeding) to space children farther apart. The size of a child at birth provides an important predictor of survival during early infancy. In the 2000 MDHS survey, mothers were asked whether their young children were very small, small, average, large, or very large at birth. A mother’s perception of “size” is broadly correlated to her child’s actual weight at birth. Newly born babies perceived by their mothers to be small or very small are much more likely to die in the first year of life (154 per 1,000 live births) than those perceived as average or larger in size (91 per 1,000 live births). The excess mortality associated with small size at birth is especially evident during the neonatal period. 8.5 PERINATAL MORTALITY The 2000 MDHS survey asked women to report on pregnancy losses and the duration of the pregnancy for each loss, for all such pregnancies ending in the five years before the survey. Pregnancy losses occurring after seven completed months of gestation (stillbirths) plus deaths to live births within the first seven days of life (early neonatal deaths) constitute perinatal deaths. When the total number of perinatal deaths is divided by the total number of pregnancies reaching seven months gestation, the perinatal mortality rate is derived. The routine collection of data to estimate rates of perinatal mortality is new to sample survey research in sub-Saharan Africa. An important consideration in the evaluation of the results of this new initiative is the quality or completeness of reports on stillbirths, which are susceptible to omission, underreporting, or misclassification (as early neonatal deaths). The distinction between a stillbirth and an early neonatal death may be a fine one, depending often on the observed presence or absence of some faint signs of life after delivery. The causes of stillbirths and early neonatal deaths are overlapping, and examining just one or the other can understate the true level of mortality around delivery. For this reason, it is suggested that both event types be combined and examined together. Table 8.4 shows perinatal mortality rates, according to demographic and socioeconomic characteristics. At the national level, the perinatal mortality rate is estimated to be 46 perinatal deaths per 1,000. Perinatal mortality displays the expected U-shaped pattern in relation to age of the mother, with the youngest and oldest women having the highest rates. First pregnancies and pregnancies with a short preceding interpregnancy interval are also at high perinatal risk. First pregnancies have a perinatal risk of 63 perinatal deaths per 1,000, and pregnancies with a interpregnancy interval of less than 15 months carry a risk of 80 perinatal deaths per 1,000, compared with a risk of just 34 per 1,000 for pregnancies with an interpregnancy interval of 39 months or more. Perinatal mortality is higher in rural areas (48 per 1,000) than in urban areas (35 per 1,000). At the regional level, the differences in perinatal mortality rates are minimal: 42 per 1,000 in the Northern Region, 46 per 1,000 in the Central Region, and 47 per 1000 in the Southern Region. It is, however, worth noting that perinatal mortality is higher for women with one to four years of primary education (52 per 1,000) than for those with no education (44 per 1,000) and those with secondary or higher education (42 per 1,000). These differentials are similar to those observed for under-five mortality. 104 * Infant and Child Mortality Table 8.4 Perinatal mortality Number of stillbirths and early neonatal deaths, and perinatal mortality rate for the five-year period preceding the survey, by background characteristics, Malawi 2000________________________________________________________________________________ Number Number of of early Perinatal pregnancies Background Number of neonatal mortality of 7 or more characteristic stillbirths1 deaths2 rate3 months duration_______________________________________________________________________________ Mother's age at birth <20 20-29 30-39 40-49 Previous pregnancy interval No previous pregnancy <15 months 15-26 months 27-38 months 39+ months Residence Urban Rural Region Northern Central Southern Mother's education No education Primary 1-4 Primary 5-8 Secondary+ Total 39 125 65.9 2,484 78 178 38.2 6,718 36 68 39.8 2,599 10 34 78.2 563 43 130 62.5 2,779 9 28 79.8 456 30 102 49.7 2,653 32 91 35.9 3,432 49 53 33.7 3,044 21 32 34.9 1,524 142 373 47.5 10,840 18 39 42.4 1,352 78 168 45.9 5,365 67 197 46.8 5,647 48 125 43.8 3,945 51 154 51.7 3,961 55 103 42.9 3,666 10 23 41.7 791 163 405 45.9 12,364 ________________________________________________________________________________ 1 Stillbirths are fetal deaths among pregnancies lasting seven or more months. 2 Early neonatal deaths are deaths at age 0 to 6 days among live-born children. 3 Perinatal mortality rate is the sum of the number of stillbirths and early neonatal deaths divided by the number of pregnancies of seven or more months duration. Maternal and Child Health * 105 MATERNAL AND CHILD HEALTH 9 Habib Somanje and Jameson Ndawala This chapter presents the MDHS findings in the following areas of importance to maternal and child health: health services use during and after pregnancy, characteristics of the newborn, childhood vaccinations, and common childhood illnesses and their treatment. Combined with information on childhood mortality, this information can be used to identify women and children who are at risk because of nonuse of health services and to provide information to assist in the planning of appropriate improvements in service access and delivery. The results presented in the following sections are based on data collected from mothers on all live births that occurred in the five years preceding the survey. Given the importance of malaria in Malawi, a special malaria data collection “module” was implemented in the 2000 MDHS survey. The survey results pertaining to reported fevers, treatment of febrile episodes, and other malaria control programme activities, including possession and use of bednets, are presented in a separate chapter (Chapter 13). 9.1 ANTENATAL CARE Table 9.1 shows the percent distribution of women who had a live birth in the five years preceding the survey by source of antenatal care (ANC) received during pregnancy, according to maternal and background characteristics. Although interviewers were instructed to record all persons a woman had consulted for care, only the provider with the highest qualifications is considered here (if more than one person was seen). Ninety-one percent of mothers received antenatal care from a doctor or trained nurse or midwife. This compares with 90 percent of births based on the 1992 MDHS data. Women received antenatal care from a traditional birth attendant (TBA) for only 3 percent of births and no antenatal care at all for 5 percent of births. Thus, most women receive some antenatal care, relying largely on a nurse or trained midwife (83 percent) or a doctor (8 percent). It should be considered, however, that the type and quality of antenatal services is not reflected in these figures. Maternal age at birth, the birth order of the child, and urban-rural residence are not strongly related to use of antenatal care. Older, higher parity women and women living in rural areas are, however, more likely to have seen no one for antenatal services than younger, lower parity women and women living in urban areas. The use of antenatal services is strongly associated with level of education. Women with no education are eight times more likely than women with some secondary education to have received no antenatal care and 23 percent less likely to have received care from a doctor. Access and use of antenatal services varies among Malawi’s districts. Lack of any antenatal care is as high as 7 percent in Lilongwe District and as low as 1 percent in Blantyre District. Variation among districts in the use of doctors for antenatal care should be viewed with caution because the definition among respondents of what constitutes a “doctor” is rather loose and may vary by locality. 106 * Maternal and Child Health Table 9.1 Antenatal care Percent distribution of women who had a live birth in the five years preceding the survey by source of antenatal care (ANC) during pregnancy, according to maternal and background characteristics, Malawi 2000 ____________________________________________________________________________________________________ Traditional Background Nurse/ Ward birth Other/ characteristic Doctor midwife attendant attendant No one Missing Total Number _____________________________________________________________________________________________________ Mother's age at birth <20 20-34 35-49 Birth order 1 2-3 4-5 6+ Residence Urban Rural Region Northern Central Southern Education No education Primary 1-4 Primary 5-8 Secondary+ Districts Blantyre Karonga Kasungu Lilongwe Machinga Mangochi Mulanje Mzimba Salima Thyolo Zomba Other districts Total 7.7 85.7 1.1 2.1 3.4 0.0 100.0 1,487 8.5 83.4 1.0 2.5 4.3 0.3 100.0 5,342 7.6 79.4 1.5 3.9 7.2 0.4 100.0 1,228 8.3 86.1 0.6 1.9 3.1 0.0 100.0 1,703 8.8 83.1 1.2 2.5 4.1 0.2 100.0 2,780 8.2 84.0 0.7 2.5 4.4 0.3 100.0 1,664 7.3 80.3 1.7 3.7 6.7 0.4 100.0 1,909 9.0 88.3 0.4 0.5 1.5 0.2 100.0 1,075 8.1 82.5 1.2 3.0 5.0 0.2 100.0 6,982 4.2 87.7 0.7 4.3 2.9 0.3 100.0 894 9.1 81.1 0.9 2.6 6.1 0.3 100.0 3,407 8.4 84.1 1.4 2.3 3.6 0.2 100.0 3,757 7.9 78.0 1.6 4.0 8.3 0.2 100.0 2,477 8.7 83.2 1.0 2.6 4.3 0.2 100.0 2,531 7.6 87.5 0.8 1.9 1.9 0.3 100.0 2,434 10.2 87.8 0.4 0.6 1.0 0.0 100.0 615 4.7 93.2 0.6 0.2 1.2 0.0 100.0 638 2.8 85.2 0.5 9.1 2.4 0.0 100.0 157 5.5 86.3 1.6 1.3 5.0 0.3 100.0 316 8.5 81.3 0.2 2.7 6.9 0.4 100.0 1,173 14.0 78.6 1.5 3.3 2.6 0.0 100.0 314 9.8 80.2 5.0 2.8 1.9 0.3 100.0 412 2.1 91.7 0.5 2.7 2.7 0.4 100.0 368 3.5 89.6 0.8 2.5 3.2 0.5 100.0 382 18.7 73.0 1.2 2.7 3.9 0.6 100.0 189 3.7 91.1 0.6 2.4 2.0 0.2 100.0 397 5.8 87.8 1.0 3.5 1.9 0.0 100.0 469 10.1 79.7 1.1 2.8 6.1 0.2 100.0 3,242 8.2 83.2 1.1 2.7 4.6 0.2 100.0 8,057 _____________________________________________________________________________________________________ Note: For women with two or more live births in the five-year period, data refer to the most recent birth. If more than one source of ANC care was mentioned, only the provider with the highest qualifications is considered in this tabulation. Antenatal care can be more effective in avoiding adverse pregnancy outcomes when it is sought early in the pregnancy and continues through to delivery. It is recommended in Malawi that women first attend an antenatal clinic in the first trimester of pregnancy and, barring signs of heightened risk, at least three more times during the pregnancy (i.e., a minimum of four times total). Information about the number and timing of visits made by pregnant women is presented in Table 9.2. For 56 percent of births, mothers made four or more antenatal care visits, indicating that many women are aware of the importance of regular attendance. Yet, the median number of antenatal care visits was 3.4, fewer than the 4.8 visits found in the 1992 MDHS survey. The median Maternal and Child Health * 107 Table 9.2 Number of antenatal care visits and stage of pregnancy Percent distribution of women who had a live birth in the five years preceding the survey by number of antenatal care (ANC) visits, and by the stage of pregnancy at the time of the first visit, according to urban-rural residence, Malawi 2000 _______________________________________________ Number and timing of ANC visits Urban Rural Total _______________________________________________ Number of ANC visits None 1 2-3 4+ Don't know/missing Total Median number of visits (for those with ANC) Number of months pregnant at time of first ANC visit No antenatal care <4 months 4-5 months 6-7 months 8+ months Don't know/missing Total Median months pregnant at first visit (for those with ANC) Number of live births 1.5 5.0 4.6 1.9 4.0 3.8 27.6 35.7 34.6 68.3 54.1 56.0 0.7 1.2 1.1 100.0 100.0 100.0 3.8 3.3 3.4 1.5 5.0 4.6 7.5 6.4 6.5 50.6 41.3 42.6 37.9 43.3 42.6 2.2 3.6 3.4 0.3 0.3 0.3 100.0 100.0 100.0 5.7 6.0 5.9 1,075 6,982 8,057 _______________________________________________ Note: For women with two or more live births in the five- year period, data refer to the most recent birth. number of antenatal visits per pregnancy is slightly higher in urban areas (3.8 times) than in rural areas (3.3 times) By the start of the sixth month of preg- nancy, 50 percent of Malawian women have not made a single antenatal visit—the median dura- tion of gestation at which the first antenatal care visit was made was 5.9 months. This de- layed use of services, whether because of moth- ers’ poor access or poor knowledge, makes it difficult for the optimum benefits of antenatal care to be realised. Urban women tend to attend their first antenatal care (ANC) visit at a slightly earlier gestational age than rural women. Unlike earlier DHS surveys, the 2000 MDHS survey asked questions about particular services that were received during pregnancy at the ANC provider. These include whether infor- mation about signs of pregnancy complications were provided, whether the woman’s blood pressure was measured, whether urine and blood samples were taken, whether the woman received tetanus toxoid injections, and whether iron supplements and antimalarial (intermittent treatment) tablets were provided. Table 9.3 shows that among the births in the last five years that involved some type of antenatal care during pregnancy, 71 percent of mothers were told about the signs of pregnancy complications. For 83 percent of births, the mother’s blood pressure was measured during antenatal care. A urine sample was taken from women for 23 percent of births, and a blood sample was taken for 43 percent of births. For 85 percent of births, women reported that at least one tetanus toxoid injection was given during pregnancy; this compares with 86 percent in the 1992 MDHS survey. Iron supplements were provided to mothers for 70 percent of recent births, and antimalarials were given for 72 percent of recent births. The survey findings point to wide disparities in the type and quality of services rendered under the heading of “antenatal care”. Provision of protection against neonatal tetanus is apparently widespread in Malawi, but provision of information and medicines to mitigate against illnesses during pregnancy are less widely available and are found to vary among geographically and socioeconomically defined groups. For instance, about 86 percent of expectant mothers in Mulanje District received intermittent treatment against malaria parasites, compared with just 59 percent in Machinga District. Among women of higher socioeconomic standing (with a secondary education) 83 percent were informed about important signs of pregnancy complications, compared with just 66 percent of women who never attended school. Access to this type of information may be an important, but simple, way to help reverse the worsening maternal mortality in the country (see Chapter 12). 108 * Maternal and Child Health Table 9.3 Antenatal care content Among women who had a live birth in the five years preceding the survey and received some antenatal care during pregnancy, the percentage who received various services during antenatal care, by background characteristics, Malawi 2000 ____________________________________________________________________________________________________ Informed of signs of pregnancy Blood Urine Blood Received Received Received Background compli- pressure sample sample tetanus iron anti- characteristic cations measured taken taken toxoid tablets malarial Number __________________________________________________________________________________________________ Mother's age at birth <20 20-34 35-49 Birth order 1 2-3 4-5 6+ Residence Urban Rural Region Northern Central Southern Education No education Primary 1-4 Primary 5-8 Secondary+ Districts Blantyre Karonga Kasungu Lilongwe Machinga Mangochi Mulanje Mzimba Salima Thyolo Zomba Other districts Total 68.7 80.0 22.4 42.7 88.2 71.8 68.5 1,436 71.3 83.8 22.8 43.2 85.0 70.6 73.3 5,102 73.1 81.5 24.9 44.0 82.1 63.2 69.7 1,136 69.1 81.6 23.7 43.5 88.7 74.1 71.3 1,650 70.9 82.7 22.7 44.0 87.0 71.1 73.6 2,663 71.2 84.8 21.9 41.7 82.1 69.2 72.3 1,586 73.1 82.0 23.9 43.3 82.0 64.1 69.4 1,775 80.8 95.4 32.4 52.6 87.4 68.7 83.3 1,057 69.5 80.7 21.6 41.7 84.8 69.9 70.1 6,618 69.4 87.6 15.1 37.5 85.4 83.8 80.5 865 66.2 81.9 22.5 45.9 85.0 64.4 66.0 3,194 75.7 82.3 25.5 42.2 85.4 71.1 75.0 3,615 65.6 77.5 22.6 39.5 83.5 63.7 65.2 2,265 69.2 81.3 23.0 42.5 85.8 67.4 67.1 2,417 75.0 86.4 21.7 45.0 85.7 75.1 78.8 2,383 83.4 93.7 30.2 53.3 87.2 79.8 88.8 609 87.1 92.6 30.2 49.5 87.0 75.8 80.4 630 70.9 74.7 11.0 23.2 85.4 85.7 76.7 153 66.7 85.5 13.6 31.6 86.1 72.5 72.2 300 70.2 87.3 29.3 57.4 88.2 60.8 64.4 1,091 67.4 75.8 25.0 36.0 83.2 63.3 58.6 306 67.7 76.3 15.9 26.0 87.2 64.1 77.6 403 78.0 73.2 27.6 41.5 84.2 72.1 85.9 357 66.2 90.7 16.9 48.0 85.7 78.3 79.9 368 62.4 76.4 11.7 28.8 84.9 69.4 77.3 181 83.6 79.5 18.0 33.5 85.6 75.2 73.3 388 79.1 87.9 24.5 49.7 85.6 72.4 69.4 460 66.8 80.9 22.9 42.7 83.5 69.5 70.4 3,038 71.1 82.7 23.1 43.2 85.2 69.7 71.9 7,675 ___________________________________________________________________________________________________ Note: For women with two or more live births in the five-year period, data refer to the most recent birth. Access to services that involve more expensive procedures (testing of blood and urine) are not widely available to pregnant women and vary greatly from district to district. For instance, in Karonga District, for just 23 percent of births, blood testing was done during pregnancy, compared with 57 percent of births in Lilongwe district. Blood is drawn during ANC visits in Malawi largely to screen for syphilis and anemia, although some of the blood samples (i.e., in selected sentinel sites) are used by the National AIDS Control Programme to maintain HIV surveillance. Maternal and Child Health * 109 Table 9.4 Place of delivery Percent distribution of live births in the five years preceding the survey by place of delivery, according to background characteristics, Malawi 2000 _________________________________________________________________________________________ Government Private Background health health At characteristic facility facility home Other Missing Total Number _______________________________________________________________________________________ Mother's age at birth <20 20-34 35-49 Birth order 1 2-3 4-5 6+ Residence Urban Rural Region Northern Central Southern Mother's education No education Primary 1-4 Primary 5-8 Secondary+ Antenatal care visits1 None 1-3 visits 4 or more visits Total 41.6 16.3 41.2 0.4 0.5 100.0 2,445 40.6 14.8 43.5 0.7 0.3 100.0 8,197 35.4 15.4 47.5 1.4 0.3 100.0 1,558 44.4 17.5 37.2 0.4 0.6 100.0 2,831 40.7 13.5 45.0 0.6 0.3 100.0 4,287 38.7 15.5 44.6 1.0 0.3 100.0 2,505 36.1 15.0 47.3 1.3 0.3 100.0 2,578 64.3 17.6 17.7 0.2 0.2 100.0 1,502 36.8 14.8 47.2 0.8 0.4 100.0 10,698 49.3 13.3 36.6 0.7 0.2 100.0 1,334 37.5 14.3 47.3 0.5 0.4 100.0 5,287 40.5 16.4 41.7 1.0 0.4 100.0 5,580 32.0 12.4 54.3 0.9 0.3 100.0 3,897 37.3 14.4 47.1 0.8 0.4 100.0 3,911 47.8 16.3 35.0 0.6 0.4 100.0 3,611 60.1 27.4 12.0 0.3 0.2 100.0 782 10.0 6.1 83.1 0.5 0.2 100.0 622 39.1 14.1 45.6 0.8 0.4 100.0 4,810 43.8 16.7 38.4 0.7 0.3 100.0 6,629 40.2 15.2 43.6 0.8 0.4 100.0 12,201 ________________________________________________________________________________________ Note: Private health facility includes Mission health facilities. 1 Total includes 139 women who did not know or had missing information for the number of antenatal care visits. 9.2 ASSISTANCE AND MEDICAL CARE AT DELIVERY Another important component of efforts to reduce the health risks of mothers and children is increasing the proportion of babies that are delivered in facilities where medical intervention is available. Proper medical attention and hygienic conditions during delivery can reduce the risk of complications and infections that can cause the death or serious illness of the mother and/or the baby. Respondents were asked to report the place of birth of all children born in the five years before the survey (Table 9.4). At the national level, 55 percent of births in the last three years were delivered in health facilities; this is identical to the figure in the 1992 MDHS survey. Government-run health facilities were used for delivery to a much greater extent (40 percent) than privately run facilities (15 percent). About 44 percent of births were delivered at home, and 1 percent were delivered elsewhere, which includes places on the way to a health facility. 110 * Maternal and Child Health Women age 35 years or older are more likely than younger women to deliver at home. Similarly, high birth order of the child is associated with greater likelihood of home delivery. A child born in rural Malawi is nearly three times more likely than a child born in an urban area to have been delivered at home. A child whose mother did not go to school at all is more than four times as likely to have been delivered at home as a child whose mother attended some secondary school. Women who have visited health professionals during pregnancy are more likely to deliver at a health facility than women who have had no such contact. Only 16 percent of women who did not receive any antenatal care delivered in a health facility, compared with 61 percent of women with four or more antenatal visits. The type of assistance a woman receives during the birth of her child has important health consequences for both mother and child. Births that are delivered at home are more likely to be delivered without assistance from anyone, whereas births delivered at a health facility are more likely to be delivered by trained medical personnel. Table 9.5 shows that 56 percent of births were delivered under the supervision of personnel with medical training, mostly nurses or trained midwives. Traditional birth attendants assisted in 23 percent of births, while relatives and friends provided the primary assistance in 19 percent of births. Two percent of births were delivered without any assistance. The 1992 MDHS and 2000 MDHS results at the national level are similar, indicating little or no improvement in use of maternity services in Malawi during the 1990s. Age of the woman and birth order of the child are not strongly associated with type of assistance at delivery. Older women and women who have already had many births are more likely to have received no assistance at delivery and are less likely to receive assistance by trained medical personnel. Urban women are more likely than rural women to receive the benefit of medical supervision during delivery (Figure 9.1). Blantyre District shows a higher proportion of deliveries under medical supervision (81 percent) than other oversampled districts (45 to 64 percent). More than 25 percent of births in the Machinga, Mangochi, and Salima districts are delivered with assistance only from friends and relatives. In the northern districts of Mzimba and Karonga, more than 1 in 20 births is delivered with no assistance at all. Maternal education is closely tied to use of medically trained attendants at delivery. Women with some secondary education are twice as likely to receive assistance from a trained professional as women with no education. If a woman received antenatal care during pregnancy, she is more likely to deliver with medical assistance. Strikingly, only 16 percent of women not receiving antenatal care delivered their babies under the supervision of a trained professional, compared with 61 percent of women with at least four antenatal visits. The combination of poor antenatal care and inadequate medical supervision at delivery places these mothers at greater risk of adverse pregnancy outcomes, including maternal death. Maternal and Child Health * 111 Table 9.5 Assistance during delivery Percent distribution of live births in the five years preceding the survey by type of assistance during delivery, according to background characteristics, Malawi 2000 ________________________________________________________________________________________ Trained nurse/ Tradi- midwife/ tional Don’t Background ward birth Relative/ No know/ characteristic Doctor attendant attendant Other one missing Total Number ________________________________________________________________________________________ Mother's age at birth <20 20-34 35-49 Birth order 1 2-3 4-5 6+ Residence Urban Rural Region Northern Central Southern Mother's education No education Primary 1-4 Primary 5-8 Secondary+ Antenatal care visits None 1-3 visits 4 or more visits Don't know/Missing Districts Blantyre Karonga Kasungu Lilongwe Machinga Mangochi Mulanje Mzimba Salima Thyolo Zomba Other districts Total 5.9 52.3 23.2 17.6 0.7 0.3 100.0 2,445 5.3 50.2 23.0 19.0 2.2 0.3 100.0 8,197 5.2 46.3 20.4 21.6 6.3 0.3 100.0 1,558 6.8 55.3 22.4 14.7 0.4 0.4 100.0 2,831 5.0 49.3 23.3 20.5 1.6 0.2 100.0 4,287 5.2 48.9 23.0 19.8 2.8 0.3 100.0 2,505 4.7 47.1 21.6 20.7 5.7 0.2 100.0 2,578 9.3 72.3 10.5 6.8 1.0 0.1 100.0 1,502 4.9 47.0 24.4 20.8 2.6 0.3 100.0 10,698 4.0 58.2 18.6 13.7 5.4 0.1 100.0 1,334 5.1 47.1 28.6 17.1 1.8 0.3 100.0 5,287 6.0 51.2 18.1 22.1 2.3 0.3 100.0 5,580 4.2 40.8 24.3 26.5 3.9 0.3 100.0 3,897 5.2 46.7 26.2 20.0 1.6 0.3 100.0 3,911 5.5 58.4 20.4 13.2 2.1 0.3 100.0 3,611 11.9 75.8 7.3 4.1 0.7 0.2 100.0 782 3.4 12.4 31.9 44.7 7.4 0.2 100.0 622 6.0 47.6 23.4 20.4 2.3 0.4 100.0 4,810 5.2 55.5 21.3 15.7 2.1 0.2 100.0 6,629 5.0 51.3 23.8 15.1 1.9 3.0 100.0 139 7.3 73.5 10.5 7.3 1.5 0.0 100.0 881 2.0 42.7 34.3 15.3 5.6 0.0 100.0 236 4.1 40.5 27.8 23.0 4.4 0.2 100.0 489 3.8 49.3 31.8 14.0 0.7 0.4 100.0 1,829 11.5 41.7 15.0 29.1 2.6 0.0 100.0 469 6.0 40.6 14.0 38.5 0.4 0.4 100.0 637 2.5 50.9 25.3 18.4 2.6 0.3 100.0 553 5.2 58.4 12.7 16.2 7.5 0.0 100.0 562 9.2 37.5 26.0 25.2 1.4 0.6 100.0 293 3.6 56.2 21.6 16.7 1.5 0.3 100.0 566 4.0 49.3 20.1 23.9 2.5 0.2 100.0 727 5.8 48.8 23.4 18.9 2.7 0.3 100.0 4,959 5.4 50.2 22.7 19.0 2.4 0.3 100.0 12,201 ________________________________________________________________________________________ Note: If the respondent mentioned more than one attendant, only the most qualified attendant is considered in this tabulation. 112 * Maternal and Child Health 9.3 CAESAREAN SECTION AND SMALL SIZE AT BIRTH According to mothers' reports, 3 percent of babies born in Malawi are delivered by caesarean section, or C-section (Table 9.6). This is the same percentage as was estimated from the 1992 MDHS survey. Generally, a C-section rate below 5 percent is thought to be a reflection of limited access to maternal health services (FCI, 1998). This finding thus indicates that many Malawian women remain without access to life-saving emergency obstetrical care. C-sections are less common among rural women, older women, women with a large number of children, and those with little or no education. District estimates of C-section prevalence vary from 2 percent of deliveries in several districts to about 5 percent in the Zomba and Blantyre districts. Respondents were asked whether their baby had been weighed at birth, and if so, how much the baby weighed. Interviewers were trained to use any written record of birth weight available. In addition, because many women do not deliver at a health facility, the mother was asked for her own subjective assessment of whether the child was very large, larger than average, average size, smaller than average, or very small at birth. For slightly more than one-half of births, a birth weight was reported. Among births for which a birth weight was reported, 10 percent (or about 5 percent of all births) were less than 2.5 kilograms, the cutoff point below which a baby is considered to be low birth weight. When asked for the “size” of their child at birth, 17 percent of all mothers reported that their child was either smaller than average (13 percent) or very small (4 percent). This compares with 18 percent estimated from the 1992 MDHS survey using the same survey instrument. District estimates of low birth weight using subjective assessment (small or very small) vary from a low of 11 percent in the Zomba and Salima districts to a high of 24 percent in Mulanje District. Maternal and Child Health * 113 Table 9.6 Delivery characteristics Percentage of live births in the five years preceding the survey delivered by caesarean section, and percent distribution by birth weight, and by mother's estimate of baby's size at birth, according to background characteristics, Malawi 2000 ___________________________________________________________________________________________________________ Birth weight Size of child at birth ___________________________________ _________________________________ Delivery Less 2.5 kg Smaller Average Background by Not than or Don’t Very than or Don’t characteristic C-section weighed 2.5 kg more know Total small average larger know Total Number _____________________________________________________________________________________________________________ Mother's age at birth <20 20-34 35-49 Birth order 1 2-3 4-5 6+ Residence Urban Rural Region Northern Central Southern Mother's education No education Primary 1-4 Primary 5-8 Secondary+ Districts Blantyre Karonga Kasungu Lilongwe Machinga Mangochi Mulanje Mzimba Salima Thyolo Zomba Other districts Total 3.0 46.6 7.0 36.9 9.4 100.0 5.5 15.4 78.4 0.6 100.0 2,445 2.8 46.3 4.5 40.7 8.5 100.0 3.2 12.0 84.0 0.7 100.0 8,197 2.2 49.6 4.2 36.4 9.8 100.0 5.0 11.7 82.6 0.7 100.0 1,558 3.7 42.7 7.1 41.3 8.8 100.0 4.9 15.2 79.3 0.7 100.0 2,831 2.9 47.8 4.1 39.6 8.5 100.0 3.4 12.3 83.5 0.7 100.0 4,287 2.9 47.5 4.5 38.8 9.2 100.0 3.4 11.4 84.5 0.7 100.0 2,505 1.4 48.9 4.3 37.6 9.3 100.0 4.2 11.8 83.3 0.6 100.0 2,578 4.5 18.8 7.3 62.5 11.4 100.0 2.0 9.3 88.1 0.6 100.0 1,502 2.5 50.7 4.6 36.2 8.5 100.0 4.2 13.1 82.0 0.7 100.0 10,698 3.2 34.0 7.3 54.8 3.9 100.0 5.0 11.6 82.9 0.6 100.0 1,334 2.3 50.0 5.0 36.0 8.9 100.0 4.2 14.1 81.1 0.6 100.0 5,287 3.1 46.8 4.3 38.9 10.0 100.0 3.4 11.6 84.2 0.8 100.0 5,580 1.8 57.8 3.4 28.4 10.4 100.0 4.0 13.5 81.5 1.0 100.0 3,897 2.6 51.2 4.5 34.2 10.1 100.0 4.4 13.6 81.5 0.4 100.0 3,911 3.1 37.5 6.4 49.1 7.0 100.0 3.5 11.6 84.1 0.8 100.0 3,611 6.9 13.0 8.2 75.5 3.2 100.0 2.5 9.2 88.0 0.3 100.0 782 4.5 22.0 6.4 58.1 13.4 100.0 1.8 10.2 88.0 0.0 100.0 881 2.2 55.6 4.1 35.4 4.9 100.0 6.9 8.0 85.0 0.1 100.0 236 2.2 51.2 3.6 39.2 6.1 100.0 4.0 10.7 84.6 0.7 100.0 489 2.2 47.6 4.6 40.3 7.5 100.0 3.3 15.2 80.6 0.9 100.0 1,829 3.5 47.6 4.1 39.0 9.3 100.0 3.3 16.4 80.0 0.3 100.0 469 1.6 55.0 1.4 32.6 11.0 100.0 2.9 11.2 85.1 0.8 100.0 637 2.0 59.0 3.7 27.5 9.8 100.0 7.1 16.9 75.8 0.2 100.0 553 3.5 34.0 7.7 54.7 3.6 100.0 4.8 12.1 82.3 0.7 100.0 562 4.0 54.5 2.9 34.5 8.1 100.0 3.5 7.7 87.9 0.9 100.0 293 2.4 42.9 6.1 41.7 9.3 100.0 4.0 13.1 82.0 0.9 100.0 566 5.2 51.5 3.9 39.6 5.0 100.0 3.2 7.7 88.8 0.3 100.0 727 2.4 48.3 5.5 36.5 9.7 100.0 4.2 13.0 81.9 0.9 100.0 4,959 2.8 46.8 4.9 39.4 8.9 100.0 3.9 12.7 82.7 0.7 100.0 12,201 9.4 POSTNATAL CARE In the 2000 MDHS survey, for each last birth in the 5 years preceding the survey that occurred outside a health facility, mothers were asked whether “a health professional or traditional birth attendant checked on her [the respondent’s] health after the birth.” For just 7 percent of births, the mother received a postnatal checkup (data not shown). About half of these checkups were performed by traditional birth attendants, and the other half were performed by doctors or trained nurses or midwives. 1 The dropout rate is defined as the percentage of children receiving the first dose who do not subsequently receive the third dose of polio or DPT vaccine. Polio 0 (at birth) is not counted in this analysis. 114 * Maternal and Child Health 9.5 VACCINATIONS To assist in the evaluation of the Malawi Expanded Programme of Immunisation (EPI), the MDHS survey collected information on vaccination coverage for all children born in the five years preceding the survey, although the data presented here are restricted to children who were alive at the time of the survey. The Malawi EPI largely follows the World Health Organisation (WHO) guidelines for vaccinating children. To be considered fully vaccinated, a child should receive the following vaccinations: one dose of BCG, three doses each of DPT and polio vaccine, and one dose of measles vaccine. BCG should be given at birth or first clinic contact and protects against tuberculosis. DPT protects against diphtheria, pertussis (whooping cough), and tetanus. DPT and polio vaccine guidelines require three vaccinations at approximately 6, 10, and 14 weeks of age; the measles vaccine should be given at or soon after reaching nine months of age. The Malawi EPI recommends that children receive the complete schedule of vaccinations before 12 months of age. A dose of polio vaccine at or around birth is now being promoted although it is not yet widely given in Malawi because many children are not delivered in health facilities. Information on vaccination coverage was collected in two ways: from child health cards seen by the interviewer and from mothers' verbal reports. Health centres and clinics in Malawi typically provide cards on which vaccinations are recorded. If a mother was able to present such a card to the interviewer, this was used as the source of information, with the interviewer recording vaccination dates directly from the card. In addition to collecting vaccination information from cards, there were two ways of collecting the information from the mother herself. If a vaccination card had been presented, but a vaccine had not been recorded on the card as being given, the mother was asked to recall whether or not that particular vaccine had been given. If the mother was not able to provide a card for the child at all, she was asked through a series of probing questions whether or not the child had received BCG, polio, DPT (including the number of doses for each), and measles vaccinations. Information on vaccination coverage is presented in Table 9.7, according to the source of information used to determine coverage, i.e., the child health card or mother's report. Data are presented for children age 12-23 months, thereby including only children who should be fully vaccinated. By way of illustration, 77 percent of all children had evidence of a BCG vaccination recorded on their health card. However, not all children who are vaccinated have health cards available; 15 percent of children did not have a card but were reported by their mothers to have received the BCG vaccine. Thus, overall, 92 percent of children age 12-23 months are estimated to have been vaccinated against tuberculosis. Vaccinations are most effective when given at the proper age; 90 percent of children receive the BCG vaccine by 12 months of age. Coverage for the first doses of polio (polio 1) and DPT (DPT1) is nearly universal (96 percent). Polio vaccine coverage declines after the first dose, with 91 and 80 percent of children receiving the second and third doses, respectively. This yields a dropout rate1 of about 17 percent for polio vaccine. The dropout rate between DPT1 and DPT3 is 12 percent. Eighty-three percent of children age 12-23 months were vaccinated against measles, but only 64 percent were before their first birthday, indicating that some children are receiving their measles vaccine too late. This is important since measles at young ages is potentially life threatening, especially in already Maternal and Child Health * 115 Table 9.7 Vaccinations by source of information Percentage of children 12-23 months who had received specific vaccines at any time before the survey, by source of information (vaccination card or mother's report), and percentage vaccinated by 12 months of age, Malawi 2000 __________________________________________________________________________________________________ Percentage of children who received: ___________________________________________________________________ DPT Polio1 Source of _________________ ________________________ information BCG DPT1 DPT2 DPT3 Polio0 Polio1 Polio2 Polio3 Measles All2 None Number __________________________________________________________________________________________________ Vaccinated at any time before the survey Vaccination card Mother's report Either source Vaccinated by 12 months of age3 76.9 80.3 78.2 73.7 41.6 80.1 77.3 72.4 70.2 64.3 0.1 1,814 15.4 15.5 14.4 10.4 5.3 15.6 14.0 7.4 13.0 5.7 2.6 424 92.4 95.9 92.6 84.2 46.9 95.7 91.3 79.8 83.2 70.1 2.8 2,238 89.7 93.8 88.9 78.6 46.2 93.3 87.2 72.7 64.2 54.0 4.6 2,238 ________________________________________________________________________________________________ 1 Polio 0 is the polio vaccination given at birth. 2 Children who are fully vaccinated, i.e., those who have received BCG, measles, and three doses of DPT and polio vaccine (excluding polio vaccine given at birth). 3 For children whose information was based on the mother's report, the proportion of vaccinations given in the first year of life was assumed to be the same as for children with a written record of vaccination. malnourished children. About 3 percent of children age 12-23 months had received no vaccinations. Overall, 70 percent of children age 12-23 months had all the recommended vaccinations, 54 percent before their first birthday. The 2000 MDHS sample design and methods of data collection, data processing, and analysis were identical to those used in the 1992 MDHS survey, facilitating comparisons. The results of these comparisons indicate that once-high vaccination coverage levels have slipped. The first indication of the problem comes from a small drop in the percentage of children with a vaccination card from 86 to 81 percent (see Table 9.8). This in itself may indicate decreased access to services. Full coverage (all vaccines, ages 12-23 months) has fallen from 82 to 70 percent. BCG coverage has declined slightly from 97 to 92 percent, and measles coverage has fallen from 86 to 83 percent. The failure of some children to complete the polio series and the DPT series (described above) has resulted in a decline in third-dose polio coverage from 88 to 80 percent and third-dose DPT coverage from 89 to 84 percent since 1992. The 2000 MDHS survey collected information on polio vaccine received “at or around birth” (polio 0), which can be recorded on the vaccination card or reported by the mother. The results indicate that 47 percent of children 12-23 months had received polio vaccine at birth. This corresponds closely to the percentage of children that are delivered in a health facility. Table 9.8 presents vaccination coverage among children age 12-23 months by selected background characteristics. The differentials in coverage are similar irrespective of vaccine type; therefore, the focus is on differentials in complete coverage (i.e., all vaccines received). The results indicate virtually no difference in full coverage between boys and girls. Children of high birth order (six or higher) have lower coverage than children of lower birth order; for example, 79 percent of first births age 12-23 months have received all vaccines, compared with 58 percent of birth orders six or higher (Figure 9.2). 116 * Maternal and Child Health Table 9.8 Vaccinations by background characteristics Among children age 12-23 months, the percentage who had received specific vaccines by the time of the survey (according to vaccination card or the mother's report), and the percentage with a vaccination card, by background characteristics, Malawi 2000 ___________________________________________________________________________________________________________ Per- Percentage of children who had received: centage ______________________________________________________________________ with a DPT Polio1 vacci- Background __________________ _________________________ nation characteristic BCG DPT1 DPT2 DPT3 Polio0 Polio1 Polio2 Polio3 Measles All2 None card Number ___________________________________________________________________________________________________________ Child's sex Male Female Birth order 1 2-3 4-5 6+ Residence Urban Rural Region Northern Central Southern Mother's education No education Primary 1-4 Primary 5-8 Secondary+ Districts Blantyre Karonga Kasungu Lilongwe Machinga Mangochi Mulanje Mzimba Salima Thyolo Zomba Other districts Total 92.7 95.8 92.3 83.6 47.9 95.5 90.8 79.1 83.2 69.7 2.7 79.2 1,110 92.1 96.0 92.9 84.7 45.9 96.0 91.8 80.5 83.2 70.5 2.8 82.9 1,128 94.7 97.2 95.5 89.5 48.5 97.6 93.7 84.7 91.1 78.9 1.8 81.7 525 93.8 97.7 94.8 86.0 50.4 96.7 93.0 82.5 84.6 71.5 1.7 84.8 815 92.5 95.8 91.5 83.5 45.5 94.4 89.6 78.6 80.2 69.8 3.0 81.1 434 87.2 91.3 86.5 75.5 40.3 93.1 87.0 70.7 74.6 58.0 5.5 73.7 463 96.3 98.5 97.3 92.4 52.9 97.9 96.6 85.8 90.6 78.6 1.1 77.4 307 91.8 95.5 91.8 82.8 46.0 95.4 90.5 78.9 82.0 68.7 3.0 81.6 1,930 94.8 96.8 94.1 88.5 64.5 97.1 94.3 86.4 85.8 77.8 2.2 82.6 259 90.4 94.6 90.8 78.6 38.3 94.3 89.2 73.8 76.9 61.4 3.9 75.0 974 93.7 96.9 93.9 88.4 50.8 96.7 92.6 83.9 88.7 76.6 1.8 86.5 1,005 88.4 93.1 89.5 79.3 40.8 92.8 87.8 73.5 79.2 64.0 4.7 79.9 671 93.0 95.4 91.9 81.2 46.8 95.6 91.3 78.1 80.1 66.5 2.9 80.9 690 94.4 98.4 94.8 88.7 51.9 98.1 93.2 84.6 87.5 75.1 1.1 82.1 696 97.2 98.2 98.2 95.9 50.6 98.1 96.9 91.4 93.4 87.5 1.0 81.9 180 96.1 99.4 98.1 93.4 43.4 98.6 96.1 90.1 91.7 82.9 0.6 85.1 182 93.9 97.6 91.0 84.9 61.8 97.1 92.2 77.3 81.7 67.7 1.7 79.0 47 91.0 95.9 88.4 81.3 40.1 93.5 88.6 72.3 85.8 61.4 4.1 71.5 101 91.4 95.0 94.6 82.3 47.5 94.1 92.7 77.9 73.6 63.4 3.6 75.0 316 83.6 96.1 96.1 87.5 46.7 98.1 95.2 85.5 85.4 67.1 1.9 83.1 78 90.3 98.8 93.1 83.3 44.4 96.5 93.1 78.0 88.7 69.0 1.2 91.7 110 96.2 97.7 94.7 91.7 39.4 96.2 93.2 84.2 91.5 81.0 2.3 87.9 100 93.8 95.8 92.8 86.7 67.1 96.7 92.8 85.4 84.4 75.3 2.3 83.7 110 86.4 89.0 84.7 71.4 34.6 88.1 84.8 69.8 78.0 61.0 8.5 80.0 54 95.9 98.4 97.5 92.6 75.7 98.4 96.7 87.3 95.1 81.6 1.6 85.7 104 95.2 94.2 94.2 89.6 67.5 95.2 91.8 89.1 87.9 84.3 3.9 85.2 127 92.0 95.2 90.4 80.9 40.7 95.6 88.9 76.4 81.0 66.8 2.8 79.9 909 92.4 95.9 92.6 84.2 46.9 95.7 91.3 79.8 83.2 70.1 2.8 81.1 2,238 ___________________________________________________________________________________________________________ 1 Polio 0 is the polio vaccination given at birth. 2 Children who are fully vaccinated, i.e., those who have received BCG, measles, and three doses of DPT and polio vaccine (excluding polio vaccine given at birth). Full vaccination coverage among urban children (79 percent) is higher than among rural children (69 percent). As has been observed in previous surveys, children in the Central Region continue to have lower vaccination coverage levels than children in the rest of the country. District variation in vaccination coverage needs to be interpreted with caution because the number of observations on which the estimates are based is, in some cases, small. Some districts have full coverage of more than 80 percent (Blantyre, Mulanje, Thyolo, and Zomba), while others have coverage below 65 percent (Kasungu, Lilongwe, and Salima). Maternal and Child Health * 117 The educational level of the mother is linked to the likelihood that the children have been fully vaccinated. Among children whose mother has been to secondary school, full coverage is 88 percent, compared with just 64 percent among children whose mother has never been to school. 9.6 ACUTE RESPIRATORY INFECTION Pneumonia is a leading cause of death of young children in Malawi. The programme to control acute respiratory infection (ARI) aims at treating cases of ARI early before complications develop. Early diagnosis and treatment with antibiotics can prevent a large proportion of deaths due to pneumonia. There is therefore emphasis placed on recognition of signs of impending severity, both by mothers and primary health care workers so that help can be sought. The prevalence of ARI was estimated by asking mothers whether their children under age five had been ill with cough accompanied by short, rapid breathing (in a second question) in the two weeks preceding the survey. These symptoms are compatible with pneumonia. It should be borne in mind that morbidity data collected in surveys are subjective (i.e., mother's perception of illness) and not validated by medical examination. Table 9.9 shows that 27 percent of children under five years of age were ill with a cough and short, rapid breathing at some time in the two weeks preceding the survey. Using the same definition, the 1992 MDHS survey reported that 15 percent of children had ARI in the last two weeks. This large increase may be real or it may be related to improved mothers’ recognition of the signs of illness. Prevalence of respiratory illness varies by age of the child, with the highest prevalence occurring at 6-11 months. Sex and birth order of the child are not associated significantly with ARI prevalence. Education of the mother is only mildly associated with ARI prevalence, with children of women with no education and with secondary or more education having the lowest prevalence levels. 118 * Maternal and Child Health Table 9.9 Prevalence and treatment of acute respiratory infection Percentage of children under five years who were ill with a cough accompanied by short, rapid breathing (symptoms of ARI) in the two weeks preceding the survey, and percentage of children with symptoms of ARI taken to a health facility or provider, by background characteristics, Malawi 2000 ________________________________________________________ Percentage of Percentage children with of chil- symptoms of dren with ARI taken to a Background symptoms health facility characteristic of ARI or provider1 Number ________________________________________________________ Child's age <6 months 6-11 months 12-23 months 24-35 months 36-47 months 48-59 months Child's sex Male Female Birth order 1 2-3 4-5 6+ Residence Urban Rural Region Northern Central Southern Mother's education No education Primary 1-4 Primary 5-8 Secondary+ Districts Blantyre Karonga Kasungu Lilongwe Machinga Mangochi Mulanje Mzimba Salima Thyolo Zomba Other districts Total 29.2 21.2 1,274 34.8 29.7 1,243 29.2 31.8 2,238 26.4 25.1 2,107 21.6 25.7 2,047 21.9 22.9 1,650 25.8 25.9 5,225 27.5 27.4 5,334 24.8 28.8 2,366 26.2 27.9 3,706 27.6 23.2 2,214 28.4 26.3 2,273 15.7 48.3 1,358 28.3 24.9 9,201 24.1 36.4 1,166 28.7 21.8 4,594 25.3 29.7 4,799 24.3 22.0 3,388 29.1 23.9 3,303 27.5 29.3 3,150 22.6 52.8 718 15.5 36.2 755 9.4 35.5 213 33.7 13.0 437 21.2 27.9 1,596 31.7 26.9 411 21.1 32.8 553 31.3 30.2 468 31.4 28.9 490 20.4 34.7 244 20.5 25.0 479 29.4 25.2 633 30.7 25.7 4,281 26.7 26.7 10,559 ________________________________________________________ ARI = Acute respiratory infections 1 Excludes pharmacy, shop, and traditional practitioner ARI prevalence is much higher in rural areas (28 percent) than in urban areas (16 percent) and is slight- ly higher in the Central Region than in the Northern and Southern regions. District differentials are substantial. Prevalence is as low as 9 percent in Karonga District and as high as 34 percent in Kasungu District. Whether this wide range in ARI prevalence reflects genuine differences in morbid- ity or rather sociocultural differences in the perception of disease or disease severity cannot be ascertained from these data. Just 27 percent of children with a report of cough with short, rapid breathing were taken to a health facility of some kind. This compares with 49 percent from the 1992 MDHS survey. Children age 6-23 months are more likely to be taken to a health facility than younger and older chil- dren. Sex and birth order of the child are not strongly related to use of health facilities for ARI. Urban chil- dren with ARI are twice as likely to have been taken to a health facility than their rural counterparts. Children with ARI from the Central region are less likely than children in the other regions to have received treatment at a health facility. Use of a health facil- ity to treat under-five ARI cases ranges from just 13 percent in Kasungu Dis- trict to 36 percent in Blantyre and Karonga districts. These findings, although underscoring serious prob- lems of access to health services, may also suggest that mothers and other household members do not always understand the importance of quick response to ARI symptoms. Maternal and Child Health * 119 Table 9.10 Disposal of children's stools Percent distribution of children under five years of age by way in which child's fecal matter is disposed of, according to background characteristics and type of toilet facilities in household, Malawi 2000 ______________________________________________________________________________________ Child always Thrown Thrown uses into Buried away Not Number Background toilet/ toilet/ in from disposed Other/ of characteristic latrine latrine yard dwelling of Missing Total children ______________________________________________________________________________________ Residence Urban Rural Region Northern Central Southern Mother's education No education Primary 1-4 Primary 5-8 Secondary+ Toilet facilities1 None Pit and improved latrine Flush toilet Total 8.2 80.3 0.5 10.8 0.1 0.1 100.0 987 7.5 69.8 3.2 19.0 0.3 0.1 100.0 6,480 7.9 69.9 2.2 19.5 0.5 0.0 100.0 822 6.8 71.8 3.3 17.7 0.3 0.0 100.0 3,200 8.3 70.9 2.5 17.9 0.2 0.2 100.0 3,445 6.9 64.7 4.3 23.6 0.3 0.3 100.0 2,322 7.1 70.9 3.2 18.5 0.4 0.0 100.0 2,333 8.5 76.1 1.7 13.4 0.2 0.1 100.0 2,236 9.2 78.8 0.0 11.9 0.0 0.0 100.0 575 3.3 32.5 13.0 50.7 0.3 0.1 100.0 1,355 8.2 80.3 0.6 10.6 0.3 0.1 100.0 5,936 24.1 60.3 0.0 14.6 0.1 0.8 100.0 167 7.6 71.2 2.8 17.9 0.3 0.1 100.0 7,467 _____________________________________________________________________________________ 1 Total includes eight children for whom data on type of toilet facility is missing. 9.7 DIARRHOEAL DISEASE AND RELATED FINDINGS Dehydration caused by severe diarrhoea is a major cause of morbidity and mortality among young children in Malawi. Exposure to diarrhoeal-disease-causing agents is frequently related to use of contaminated water and unhygienic practises related to food preparation and excreta disposal. Recent efforts by the government of Malawi to improve access to safe water have been successful (see Chapter 2). In the 2000 MDHS survey, mothers of children under five years of age were asked about the manner in which the child’s fecal matter was disposed of. Table 9.10 presents the results according to background characteristics. The stools of 79 percent of children under age five are routinely disposed of in a latrine or toilet. The remaining children’s stools are either buried in the vicinity of the dwelling (3 percent) or thrown outside the dwelling into the bush or to be washed away (18 percent). As expected, use of latrines and toilets is more common in urban areas, among the better educated, and among households that claim access to these facilities. Little variation was observed across Malawi’s three regions. Table 9.11 shows the prevalence of diarrhoea in children under five years of age according to background characteristics. Eighteen percent of children had experienced diarrhoea at some time in the two weeks preceding the survey. This represents a decline from 22 percent reported in the 1992 MDHS survey and is consistent with an improvement in access to safe drinking water in Malawi during the 1990s. Diarrhoeal prevalence increases with age to a peak at 6-11 months (36 percent), then falls at older ages. 120 * Maternal and Child Health Table 9.11 Prevalence of diarrhoea Percentage of children under five years with diarrhoea in the two weeks preceding the survey, by background characteristics, Malawi 2000 _____________________________________________ Diarrhoea in Background preceding characteristic 2 weeks Number _____________________________________________ Child's age <6 months 6-11 months 12-23 months 24-35 months 36-47 months 48-59 months Child's sex Male Female Residence Urban Rural Region Northern Central Southern Mother's education No education Primary 1-4 Primary 5-8 Secondary+ Total 13.0 1,274 35.9 1,243 31.5 2,238 13.8 2,107 7.4 2,047 5.9 1,650 18.4 5,225 16.9 5,334 14.3 1,358 18.1 9,201 12.8 1,166 19.1 4,594 17.3 4,799 18.0 3,388 19.1 3,303 16.4 3,150 13.6 718 17.6 10,559 Table 9.12 Knowledge of ORS packets Percentage of mothers with births in the five years preceding the survey who know about ORS packets for treatment of diarrhoea, by background characteristics, Malawi 2000 _____________________________________________ Percentage of mothers who Background know about characteristic ORS packets Number _____________________________________________ Age 15-19 20-24 25-29 30-34 35-49 Residence Urban Rural Region Northern Central Southern Mother's education No education Primary 1-4 Primary 5-8 Secondary+ Districts Blantyre Karonga Kasungu Lilongwe Machinga Mangochi Mulanje Mzimba Salima Thyolo Zomba Other districts Total 85.9 726 86.5 2,403 87.8 2,076 86.3 1,211 80.3 1,642 95.6 1,075 83.9 6,983 83.2 894 83.1 3,407 88.2 3,758 76.7 2,477 86.4 2,531 90.4 2,435 98.0 615 94.0 638 71.8 157 89.3 316 85.4 1,173 76.3 314 84.6 412 94.7 368 88.2 382 76.0 189 93.1 398 90.0 469 82.8 3,242 85.5 8,057 _____________________________________________ ORS = Oral rehydration salts Sex of the child is not an important factor related to diarrhoea. Residential differ- entials are also not large, although children in urban areas experience a slightly lower rate of diarrhoea than rural children. The Northern Region has lower diarrhoeal prevalence (13 percent) than the Central region (19 per- cent) and Southern Region (17 percent). A simple and effective response to a child's dehydration is a prompt increase in the intake of appropriate fluids, i.e., oral rehydration therapy (ORT). In Malawi, families are encouraged to rehydrate children either with fluids prepared at home with locally obtained ingredients (e.g., soup, fruit juice) or with a solution prepared using prepackaged oral rehydration salts (ORS packets) mixed with water. In the 2000 MDHS survey, women who had a birth in the last five years were asked questions about their knowledge of ORS packets. Table 9.12 shows that most mothers (86 percent) know of these packets although women in rural areas, women without much formal education, and those living in certain districts of Malawi (e.g., Karonga, Machinga, and Salima) are less aware of this life-saving technology. In the 1992 MDHS survey, 90 percent of mothers of children under five knew of ORS packets. Maternal and Child Health * 121 Table 9.13 Diarrhoea treatment Among children under five years who had diarrhoea in the two weeks preceding the survey, the percentage taken for treatment to a health provider, the percentage who received oral rehydration therapy (ORT) (solution prepared from ORS packets, or increased fluids), and the percentage given other treatments, by background characteristics, Malawi 2000 ___________________________________________________________________________________________________ Oral rehydration therapy Other treatments ______________________ _______________________________ Percentage Either taken to In- ORS or Pill Home No Background a health creased increased or Injec- Intra- remedy/ treat- characteristic provider1 ORS fluid fluids syrup tion venous other ment Number ________________________________________________________________________________________________ Child's age <6 months 6-11 months 12-23 months 24-35 months 36-47 months 48-59 months Child's sex Male Female Birth order 1 2-3 4-5 6+ Residence Urban Rural Region Northern Central Southern Mother's education No education Primary 1-4 Primary 5-8 Secondary+ Total 26.1 35.1 27.5 48.8 24.2 0.0 0.4 11.1 39.8 166 30.3 50.6 34.6 63.0 25.0 0.6 2.1 15.8 22.7 447 28.3 52.5 38.1 66.5 27.5 0.6 0.5 12.3 20.6 705 28.6 44.9 35.5 59.8 29.1 0.4 1.5 11.3 26.1 292 25.3 42.0 33.1 57.5 33.5 0.0 2.1 7.9 24.8 151 26.9 41.8 36.5 63.3 33.6 3.2 0.0 13.4 22.5 98 27.5 46.5 33.5 60.5 28.7 0.5 0.3 10.6 25.5 960 29.2 49.3 37.5 63.8 26.5 0.7 2.0 14.7 22.6 899 29.1 50.1 39.4 65.5 31.4 0.6 1.3 10.3 23.1 405 28.4 49.4 35.0 63.3 28.3 0.4 0.7 11.5 22.2 645 29.5 50.3 35.2 64.6 22.9 0.3 1.2 15.3 25.2 395 26.4 40.9 32.4 54.6 27.5 1.2 1.4 13.9 27.0 414 34.9 48.7 33.0 61.9 34.9 0.2 0.9 5.0 24.8 195 27.6 47.8 35.7 62.1 26.8 0.7 1.1 13.5 24.0 1,664 38.1 48.0 23.2 57.1 37.9 2.1 2.8 11.5 22.9 149 21.2 43.4 36.6 60.1 22.7 0.3 1.3 13.6 27.2 878 34.2 52.6 36.4 65.2 31.1 0.7 0.6 11.7 21.1 832 25.3 42.9 28.9 54.4 27.6 0.5 0.5 15.6 28.5 611 30.3 49.3 37.6 64.2 25.6 0.4 1.6 13.6 21.7 632 27.9 50.5 37.5 66.1 27.2 1.0 0.7 10.2 23.9 518 37.3 55.7 51.3 75.4 43.6 0.2 3.2 0.0 13.0 98 28.3 47.9 35.4 62.1 27.7 0.6 1.1 12.6 24.1 1,859 ________________________________________________________________________________________________ ORS = Oral rehydration salts 1 Excludes pharmacy, shop, and traditional practitioner Mothers of children who were reported to have had diarrhoea were asked about their response to the illness. Just 28 percent reported that they took their child to a health facility, compared with 45 percent from the 1992 MDHS survey. Forty-eight percent of children with diarrhoea were reported to have been given ORS. This represents a small rise from 43 percent in the 1992 MDHS survey. Overall, 62 percent were given either ORS or increased fluids of some kind, which is nearly the same as the 63 percent estimate from the 1992 MDHS survey. Of course this means that more than one-third of young children sick with diarrhoea do not receive the necessary rehydration. Treatment-seeking behaviour, in particular use of ORT, is much more common among the more educated mothers. Other differentials are not large. 122 * Maternal and Child Health Table 9.14 Feeding practices during diarrhoea Percent distribution of children under five years who had diarrhoea in the two weeks preceding the survey, by amount of liquid offered and amount of food offered compared with normal practice, Malawi 2000 _________________________________ Feeding practice Percent _________________________________ Amount of liquid offered Same as usual More Somewhat less Much less None Don't know Amount of food offered Same as usual More Somewhat less Much less None Never gave food Don't know Total Number 31.6 35.4 18.3 11.0 3.6 0.1 33.2 27.4 19.2 11.8 4.5 3.9 0.1 100.0 1,859 There are some other common responses to diar- rhoea in Malawi. Twenty-eight percent of children were given a “pill” or “syrup”, and 13 percent were given some type of home remedy. Home remedies, which include predominantly herbal medicines, are more common in rural areas and for children whose mother is less educated. In 24 percent of the recent diarrhoeal cases, the mother reported that no treatment was provided to the child. This compares with 15 percent based on the 1992 MDHS survey. In the 2000 MDHS survey, mothers of children with diarrhoea in the last two weeks were asked to report whether the child received more liquid than usual, less liquid than usual, about the usual amount of liquid, or no liquid. The same was asked about food intake, except there was an option for “never gave food” (i.e., for exclusively breastfed babies). Table 9.14 shows that only 35 percent of children with diarrhoea were given more to drink. About the same percentage (32 percent) were given the same amount as usual, and 33 percent were given either some- what less, much less, or no fluids. When children experi- encing diarrhoea receive less fluid, the risks of serious complications and death are greatly increased. The feeding patterns reported by mothers are similar to those for fluid intake: about one-third of children with diarhhoea were receiving less food. These patterns reflect a gap in practical knowledge among some women about the nutritional requirements of children during episodes of diarrhoeal illness. 9.8 WOMEN’S PERCEPTIONS OF PROBLEMS IN ACCESSING HEALTH CARE The 2000 MDHS survey asked all women age 15-49 whether they thought certain issues or circumstances were “a big problem or not” when they wanted to get treatment for an illness that they (the respondents) were experiencing. Table 9.15 shows that 17 percent, or one in six women, felt that knowledge of a source was a big problem for them in gaining access to health services. Younger, unmarried, rural, and less educated women and those living in the country’s Central Region were most likely to report knowledge of a source as a big problem. Nine percent mentioned that needing “permission” would be a big problem; this response being much more common among the youngest women. Needing money for transport or treatment or having a shortage of time or transport options were by far the most commonly cited obstacles to health care access: each reported by more than 50 percent of women. Smaller percentages of women reported that they did not want to go alone or that they were concerned that a female health provider might not be available. That money and time are found to be the major constraints to women’s access to health services is no surprise; that these problems are most acutely felt among women living in remote parts of the country, and among women at lower socioeconomic levels is perhaps even less surprising. Still, these findings underscore the inequities in real access to health care in the country. As an example, 70 percent of women without formal education mention the cost of transport as a big problem for them in getting health services, compared with just 35 percent of women with some secondary education (Figure 9.3). Maternal and Child Health * 123 Table 9.15 Perceived problems in accessing women's health care by background characteristics Percentage of women who reported they had a big problem in accessing health care for themselves, by type of problem and background characteristics, Malawi 2000 ___________________________________________________________________________________________________________ Concern No Time that there Did not Did not money required Did not may not be Any know get per- for to get to Availability want a female of the Background where mission treat- health of Cost of to go health specified characteristic to go to go ment facility transport transport alone provider problems Number _________________________________________________________________________________________________________ Age 15-19 20-29 30-39 40-49 Number of living children 0 1-2 3-4 5+ Marital status Never married Married Divorced, separated, widowed Residence Urban Rural Region Northern Central Southern Education No education Primary 1-4 Primary 5-8 Secondary+ Total 20.1 11.5 54.0 53.2 48.6 57.6 31.0 16.5 76.6 2,867 15.9 7.7 54.1 53.8 49.6 57.5 22.9 12.4 75.0 5,358 16.2 7.5 58.1 58.6 55.0 62.6 25.2 11.7 77.3 2,990 17.3 8.2 62.1 62.9 60.4 66.7 29.0 12.6 82.2 2,004 19.6 11.1 53.5 52.9 47.6 57.0 30.7 17.0 75.8 3,216 16.2 8.0 55.1 54.6 50.7 58.4 23.1 12.4 75.9 4,628 16.2 7.0 57.1 57.8 54.9 61.6 24.9 11.1 76.6 2,877 16.6 8.2 60.8 61.4 58.1 65.2 27.1 12.0 80.7 2,499 19.3 10.7 53.4 51.1 46.2 57.3 31.3 16.9 75.2 2,243 16.5 8.0 55.4 56.6 52.8 59.5 24.8 12.5 76.7 9,452 17.7 9.0 65.4 60.5 57.8 67.7 26.5 11.6 81.0 1,525 6.4 4.3 38.0 32.1 23.1 37.9 11.4 6.8 52.1 2,106 19.1 9.4 59.7 60.7 57.8 64.2 28.9 14.4 81.7 11,114 13.2 10.1 38.4 44.7 41.1 28.3 19.2 10.6 59.7 1,453 19.0 9.2 52.0 51.6 48.2 58.4 25.0 13.1 75.5 5,321 16.3 7.7 63.7 62.5 58.2 68.6 28.5 13.8 82.0 6,446 18.2 9.6 65.2 63.5 60.5 69.9 27.1 14.1 83.6 3,574 19.5 10.0 60.1 60.7 58.6 66.4 28.4 14.1 82.9 4,025 16.8 8.2 51.9 53.2 48.1 54.1 26.4 13.6 73.7 4,152 8.6 3.0 36.0 34.0 26.8 35.2 16.5 7.1 53.9 1,468 17.1 8.6 56.2 56.2 52.3 60.0 26.1 13.2 76.9 13,220 124 * Maternal and Child Health 1 The remaining 2 percent are composed, in large part, of children who died during the neonatal period and were probably unable to start breastfeeding. Nutrition among Children and Women * 125 INFANT FEEDING, NUTRITIONAL PRACTISES, AND NUTRITIONAL STATUS AMONG YOUNG CHILDREN AND WOMEN Habib Somanje and George Bicego Malnutrition is one of the most important health and welfare problems facing Malawians today. Young children and women of reproductive age are especially vulnerable to nutritional deficits and micronutrient deficiency disorders. The 2000 MDHS survey collected data from mothers on the feeding patterns of their children under five years of age. In this chapter, these data are used to evaluate infant feeding practises, including breastfeeding durations, introduction of complementary weaning foods, and use of feeding bottles. Other important nutritional issues, including the level of vitamin A and iron supplementation and the iodisation of salt used in the household are also discussed. Last, the nutritional status of all under-five children and all women age 15-49, based on anthropometric indices (height and weight measures), is presented and discussed. 10.1 BREASTFEEDING AND SUPPLEMENTATION The pattern of infant feeding has an important influence on the health of both the child and the mother. Feeding practises are the underlying determinants of a child’s nutritional status. Poor nutritional status in young children exposes them to greater risk of illness and death. Breastfeeding also affects mothers through its biological suppression of the return to fertile status, thereby influencing the length of the interval between pregnancies and the pregnancy outcome. These effects are influenced by both the duration and frequency of breastfeeding and by the age at which the child receives foods and liquids to supplement breast milk. 10.1.1 INITIATION OF BREASTFEEDING Colostrum, which appears right after delivery and before a mother’s milk comes, has been shown to be highly nutritious and to contain a high concentration of antibodies that protect babies from infection before the child’s immune system has matured. To facilitate the early initiation of breastfeeding, women delivering at home and in health facilities in Malawi are increasingly encouraged to ensure that their newly born babies are breastfed soon after birth and thereafter on demand. Bottle-feeding is discouraged, and mothers are educated to breastfeed exclusively until the child is 4-6 months old. Table 10.1 shows that breastfeeding is nearly universal in Malawi, with 98 percent of children born in the last five years having been breastfed.1 Overall, 72 percent of children were breastfed within an hour of delivery and 97 percent within the first 24 hours after delivery. Variation among population subgroups is minimal, but certain characteristics tend to decrease the chance that a child will be breastfed within an hour of delivery. Residence in the Central Region and nonuse of medically trained personnel at delivery are associated with a smaller likelihood of initiating breastfeeding within an hour of delivery. 10 126 * Nutrition among Children and Women Table 10.1 Initial breastfeeding Percentage of children born in the five years preceding the survey who were ever breastfed, and among children ever breastfed the percentage who started breastfeeding within one hour and within one day of birth, and who received additional food or liquid before the mother’s milk began flowing, by background characteristics, Malawi 2000________________________________________________________________________________________________ Percent who received Percentage who started additional breastfeeding: food or Number_____________________ liquid of Percentage Number Within Within before children Background ever of 1 hour 1 day milk began ever characteristic breastfed children of birth of birth1 flowing2 breastfed_______________________________________________________________________________________________ Sex Male Female Residence Urban Rural Region Northern Central Southern Mother's education No education Primary 1-4 Primary 5-8 Secondary+ Assistance at delivery Health professional3 Traditional birth attendant Other No one Total 97.9 6,079 71.9 96.8 2.1 5,954 98.6 6,122 72.2 97.1 2.2 6,037 99.1 1,502 76.1 96.9 2.3 1,489 98.2 10,698 71.5 96.9 2.1 10,502 97.9 1,334 74.4 96.9 2.5 1,306 98.2 5,287 66.0 95.8 2.0 5,193 98.4 5,580 77.3 98.0 2.2 5,492 98.3 3,897 72.1 97.1 2.2 3,829 97.7 3,911 70.4 96.3 2.0 3,822 98.8 3,611 73.5 97.6 1.9 3,566 99.0 782.0 73.8 96.0 3.2 774 98.6 6,778 74.6 97.3 2.2 6,680 98.3 2,768 69.2 96.8 1.9 2,722 97.5 2,322 70.4 97.5 2.4 2,264 97.7 297 61.1 94.7 1.7 290 98.3 12,201 72.1 96.9 2.1 11,991 _______________________________________________________________________________________________ Note: Table is based on both living and dead children. Total includes 34 cases missing data for assistance at delivery. 1 Includes children who started breastfeeding within one hour of birth. 2 Children given something other than breast milk during the first three days of life before the mother started breastfeeding regularly. 3 Doctor, nurse, or midwife 10.1.2 AGE PATTERN OF BREASTFEEDING Breast milk is uncontaminated and contains all the nutrients needed by children in the first four to six months of life. Supplementing breast milk before 4 months of age is unnecessary and is strongly discouraged since the likelihood of contamination and resulting risk of diarrhoeal disease is high. Early supplementation also reduces breast milk output since the production and release of milk is modulated by the frequency and intensity of suckling. Table 10.2 shows breastfeeding practises from birth through the third year of life. Breastfeeding remains prevalent throughout the first 18 months: at age 16-17 months, 95 percent of children are still breastfed. Even at 22-23 months of age, two-thirds of children are being breastfed. However, by late in the second year, breastfeeding is rapidly reduced so that by 26-27 months of age just one-third of children are still breastfed. Virtually all children are completely weaned by their third birthday. 2 Exclusive breastfeeding is the practise of feeding only with breast milk for the first four to six months of life as recommended by the World Health Organisation and UNICEF. Nutrition among Children and Women * 127 Table 10.2 Breastfeeding status by child's age Percent distribution of youngest living children under three years of age by breastfeeding status, according to child's age in months, Malawi 2000 ____________________________________________________________________________________________________________ Breastfeeding and: ___________________________________ Water- Using a Not Plain based Comple- Don’t bottle Child's age breast- Exclusively water liquids, Other mentary know with a in months feeding breastfed only juice milk foods Missing Total nipple Number ___________________________________________________________________________________________________________ <2 2-3 4-5 6-7 8-9 10-11 12-13 14-15 16-17 18-19 20-21 22-23 24-25 26-27 28-29 30-31 32-33 34-35 <4 4-5 6-9 0.0 78.4 8.8 0.0 1.0 7.3 4.5 100.0 2.0 348 0.1 50.4 8.7 1.2 1.8 30.8 7.0 100.0 1.9 445 0.0 12.2 3.4 0.5 0.3 79.6 4.2 100.0 3.1 464 0.1 3.5 0.9 0.7 0.5 92.0 2.3 100.0 2.2 414 0.2 1.6 0.7 0.4 0.0 94.9 2.2 100.0 2.6 385 1.5 0.0 1.5 0.2 0.0 96.0 0.8 100.0 4.7 427 2.1 0.4 0.0 0.0 0.0 97.0 0.6 100.0 7.7 418 1.4 0.8 0.0 0.3 0.0 97.2 0.4 100.0 5.4 362 4.6 0.8 0.3 1.3 0.0 91.3 1.6 100.0 3.7 341 10.0 0.5 0.0 0.0 0.0 89.1 0.4 100.0 4.7 369 15.2 0.0 0.0 0.0 0.0 84.1 0.7 100.0 3.2 347 32.5 0.2 0.0 0.4 0.0 66.9 0.0 100.0 3.9 320 45.7 0.0 0.0 0.4 0.0 54.0 0.0 100.0 4.1 328 65.3 0.2 0.4 0.0 0.0 34.0 0.0 100.0 5.1 305 73.1 1.6 0.2 0.0 0.0 25.2 0.0 100.0 2.7 275 81.9 0.0 0.0 0.0 0.0 18.1 0.0 100.0 2.7 243 87.1 1.5 0.0 0.0 0.0 11.4 0.0 100.0 1.2 196 92.8 0.0 0.0 0.0 0.0 7.2 0.0 100.0 2.8 193 0.0 62.7 8.8 0.7 1.5 20.5 5.9 100.0 1.9 793 0.0 12.2 3.4 0.5 0.3 79.6 4.2 100.0 3.1 464 0.1 2.6 0.8 0.6 0.2 93.4 2.3 100.0 2.4 799 ____________________________________________________________________________________________________________ Note: Breastfeeding status based on mother’s reports in to last 24 hours. Exclusive breastfeeding2 is much more common than it was in the early 1990s. The 2000 MDHS data indicate that 63 percent of children under 4 months of age are exclusively breastfed, compared with just 3 percent in the 1992 MDHS survey. The biggest observed change is a large decrease in the percentage of children under 4 months of age that are given just plain water, which is unnecessary if a child is breastfed exclusively. Just 9 percent of children under 4 months are receiving plain water (in addition to breast milk). Early introduction of complementary foods (to children under 4 months) has decreased from 56 percent in the 1992 MDHS survey to 21 percent in the 2000 MDHS survey. These trends should improve prospects for child health and survival. After the 0-3 month age period, exclusive breastfeeding drops off sharply to 12 percent at age 4-5 months and 3 percent at 6-9 months of age. Use of complementary foods rises to 80 percent by 4-5 months and 97 percent by the child’s first birthday. Use of a feeding bottle with a nipple in infants runs counter to the promotion of healthy breastfeeding and infant feeding practises in Malawi. Infant formula, even if correctly prepared, does not adequately substitute for breast milk. Moreover, formula is often mixed incorrectly leading 128 * Nutrition among Children and Women Table 10.3 Median duration and frequency of breastfeeding Median duration of any breastfeeding, exclusive breastfeeding, and predominant breastfeeding among last-born children born in the three years preceding the survey, and the percentage of breastfeeding children under six months who were breastfed six or more times in the 24 hours preceding the survey, and mean number of feeds (day/night), by background characteristics, Malawi 2000____________________________________________________________________________________________________ Breastfeeding children under six months3 Median duration (months) of breastfeeding _________________________________________________________________________ Percentage Pre- breastfed Mean number Any Exclusive dominant Number 6+ times of feeds Background breast- breast- breast- of in last ______________ characteristic feeding feeding feeding1 children2 24 hours Day Night Number____________________________________________________________________________________________________ Sex of child Male Female Residence Urban Rural Region Northern Central Southern Mother's education No education Primary 1-4 Primary 5-8 Secondary+ Median for all children Mean for all children 24.4 2.0 2.4 3,359 97.0 7.6 5.4 629 24.1 2.1 2.4 3,394 97.9 7.4 5.4 627 22.7 2.5 3.1 877 97.8 8.6 5.8 148 24.6 2.0 2.4 5,876 97.4 7.3 5.4 1,108 23.4 2.1 2.4 765 95.7 6.8 5.4 134 24.4 1.5 2.0 2,878 97.5 7.7 5.3 520 24.5 2.5 2.9 3,110 97.8 7.4 5.5 602 25.8 2.0 2.3 2,060 96.5 7.5 5.4 356 24.7 1.6 2.0 2,128 98.2 7.5 5.5 405 23.6 2.3 2.8 2,075 97.5 7.4 5.3 381 21.9 3.4 4.0 490 97.9 7.5 5.6 114 24.3 2.0 2.4 6,753 97.5 7.5 5.4 1,256 23.8 3.3 3.9 6,753 na na na na ____________________________________________________________________________________________________ na = Not applicable 1 Either exclusively breastfed or received breast milk and plain water, water-based liquids, and/or juice. 2 Based on both living or dead children. 3 Excludes children who do not have a valid answer on number of times breastfed to undernutrition of infants. Last, formula and feeding bottles can easily become contaminated with disease-causing agents. Encouragingly, the 2000 MDHS findings indicate that use of feeding bottles in children under age 4 months has declined from 4 percent to 2 percent and among children 4-5 months old, from 10 percent to 3 percent. Table 10.3 shows that, at the national level, the median duration of any breastfeeding is 24 months, 3 months longer than the 21 months based on the 1992 MDHS data. The median duration of exclusive breastfeeding is 2.0 months and predominant breastfeeding (breastfeeding exclusively or with plain water, water-based liquids, or juice) is 2.4 months. The duration and frequency of breastfeeding vary across background characteristics of the mother. Median length of breastfeeding tends to be longer in rural areas (25 months) than in urban areas (23 months) and among uneducated women (26 months), compared with women with secondary education (22 months). Although length of breastfeeding is longer in rural areas and among less educated women, the same women tend to exclusively breastfeed for shorter durations. The daily frequency of breastfeeding in Malawi tends to be as recommended. Ninety-eight percent of children under 6 months of age were breastfed 6 times or more in the 24 hours preceding the survey. The average number of feeds was eight during the day and five during the night. The pattern of breastfeeding in the first six months varies little by background characteristics. Nutrition among Children and Women * 129 Table 10.4 Foods consumed by children in preceding 24 hours Percentage of youngest children under three years of age living with their mother who consumed specific foods in the 24 hours preceding the interview, by breastfeeding status and child's age, Malawi 2000____________________________________________________________________________________________________________ Foods Food Food Other made Fruit made Food Meat/ Any made Child’s milk/ from and from made Poultry solid or Vitamin with age in Infant cheese/ Other grains/ vege- roots or from Fish/ semisolid A rich oil/fat months formula yogurt liquids1 cereal tables tubers2 legumes Eggs food foods3 or butter Number____________________________________________________________________________________________________________ BREASTFEEDING CHILDREN____________________________________________________________________________________________________________ <2 2-3 4-5 6-7 8-9 10-11 12-13 14-15 16-17 18-23 24-29 30-35 <4 4-5 6-9 Total 1.0 0.8 1.0 7.3 0.0 0.2 0.0 0.3 9.7 0.3 0.0 348 2.1 1.0 3.5 30.7 1.3 0.4 0.7 0.4 36.1 2.0 0.0 445 1.8 2.1 14.1 79.6 7.4 2.1 1.6 2.9 82.6 7.4 0.8 462 1.9 4.2 30.4 91.9 27.0 8.4 9.9 15.6 95.9 30.1 3.1 413 2.9 6.3 40.8 93.8 51.1 17.9 19.9 28.7 96.7 55.2 6.0 385 4.7 7.7 48.2 96.8 63.8 33.4 27.7 35.4 98.8 69.0 9.2 420 3.8 6.5 49.8 98.4 74.6 30.1 32.0 44.1 100.0 78.4 10.1 408 4.7 7.2 57.4 95.7 77.6 43.1 32.4 39.4 99.3 81.6 8.3 357 1.2 8.7 55.4 92.6 72.7 43.4 30.2 41.7 98.7 78.0 9.9 324 2.5 7.5 57.4 95.4 78.4 46.8 33.8 43.4 99.7 84.7 8.2 842 1.3 6.0 48.9 94.0 79.8 55.1 28.6 39.4 100.0 85.3 5.6 358 1.6 2.9 41.0 94.0 75.3 45.3 31.5 32.8 100.0 78.5 6.4 82 1.6 0.9 2.4 20.4 0.7 0.4 0.4 0.4 24.5 1.2 0.0 793 1.8 2.1 14.1 79.6 7.4 2.1 1.6 2.9 82.6 7.4 0.8 462 2.4 5.2 35.5 92.8 38.6 13.0 14.7 21.9 96.3 42.2 4.5 798 2.5 5.3 38.2 81.3 50.4 26.9 20.7 27.4 85.1 54.0 5.7 4,844 __________________________________________________________________________________________________________ NONBREASTFEEDING CHILDREN___________________________________________________________________________________________________________ 0-17 18-23 24-29 30-35 Total 7.4 16.0 48.5 91.8 75.5 45.5 51.7 42.3 96.7 83.7 12.2 42 6.9 16.2 67.8 96.9 87.9 50.8 34.8 46.7 99.4 89.0 10.4 195 3.9 13.8 64.7 98.0 79.7 54.9 32.1 50.2 100.0 85.5 13.8 550 2.3 11.2 61.3 97.0 83.2 53.8 35.8 53.5 99.8 88.7 13.0 550 3.8 13.1 63.2 97.3 82.2 53.5 34.6 50.8 99.7 87.3 12.9 1,337 __________________________________________________________________________________________________________ Note: Breastfeeding status refers to last 24 hours. Food consumed in the 24 hours refer to consumption on the day and night preceding the interview. Percentage may sum to more than 100 percent because child may have received more than one type of supplement. 1 Does not include plain water 2 The category of tubers and roots also includes plantains and unripe bananas. 3 Vitamin A rich foods include pumpkin, yellow squash, carrots, yellow sweet potatoes, green leafy vegetables, mangoes, and papayas. Does not include animal products. 10.1.3 TYPES OF COMPLEMENTARY FOODS Table 10.4 presents information on the types of foods received by children in the first three years of life, according to whether or not the child is still being breastfed. Under 4 months of age, in addition to breast milk, about 25 percent of children receive some type of solid or semisolid food, mostly cereal-based foods like porridge. Very little of other food types is given at this age. By 4-5 months of age, 83 percent of children are getting some type of solid or semisolid food (80 percentage get grain- or cereal-based food), and 18 percent are getting fluids other than breast milk. The percent of children getting fruits and vegetables of any type at 4-5 months of age is still low (7 percent), and just 7 percent receive foods rich in vitamin A, like mango, sweet potato, carrots, and papaya. 130 * Nutrition among Children and Women By 6-9 months of age, all children should be receiving nutritious complementary foods in addition to breast milk. Virtually all children (96 percent) in this age group are receiving solid and semisolid foods, but the majority of these are not receiving important foods rich in vitamin A (mango, carrot, papaya, sweet potato); other fruits and vegetables; and meat, poultry, and eggs on a regular basis. Grain and cereal-based foods continue to dominate the infant feeding picture. The percentage of children receiving foods rich in vitamin A; fruits and vegetables; roots and tubers (e.g., potatoes); and meat, fish, poultry, or eggs in the last 24 hours increases and then levels off at age 9-17 months. The percentage of children receiving foods rich in vitamin A increases to about 80 percent at age 12-13 months and then plateaus. The same applies to feeding of fruits and vegetables (about 75 percent). About 40 percent of children have started to receive meat, poultry, fish, or eggs by 12-13 months of age. Nearly one-half of children are receiving some type of tuber, root, or plantain by the age of 18 months. Once a child is weaned from the breast, which occurs for most children between 18 and 24 months of age, the diet tends to stabilize at the following pattern: virtually all children receive grain or cereal-based foods; 80 to 85 percent of children receive fruits or vegetables; nearly 85 to 90 percent get foods rich in vitamin A; about 50 percent receive meats, poultry, fish, or eggs; one- third of children receive beans, legumes, or lentils; and 50 to 55 percent get tubers, roots, or plantains. Only 10 to 15 percent of children are getting some oils or fats added to their daily diet. Infant formula is rarely used in Malawi; use of formula peaks during age 8-15 months for 3 to 5 percent of children. Use of other types of milk (e.g., cow’s milk) and milk products is also not very common, peaking at 6 to 9 percent of children during age 8-29 months among breastfed children. When children are weaned, this percentage roughly doubles. 10.1.4 FREQUENCY OF FOODS CONSUM ED BY CHILDREN The nutritional requirements of young children are more likely to be met if they are fed a variety of foods. In the 2000 MDHS survey, interviewers read a list of specific foods or food types and asked the mother to report the number of times during the last 24 hours a child had consumed each food. Table 10.5 shows the pattern of complementary feeding by food type for children under age three. By age six months, children should be receiving solid foods in their diet in addition to breast milk. The frequency of use of plain porridge, a principle weaning food, peaks during age 4-9 months at 1.4 to 1.5 times per day. Other similar foods, including enriched porridge and other grain-based foods and drinks (e.g., thobwa, a fermented maize-based drink) are also increasingly given to children starting late in the first year. For children who are no longer breastfeeding, the need for varied and substantial nutritional inputs, is even greater than before weaning. The MDHS data show that among children who are fully weaned, principally those 24-35 months, the foods given most frequently are cereal-based foods (nsima, bread, and rice) and porridge at more than two times per day. Green leafy vegetables are given, on average, about once a day. Other foods rich in vitamin A, like carrots, pumpkin, mango, and papaya are also provided but with less frequency. Foods with a high protein content include meats, fish, poultry, and eggs as well as beans and other legumes. The data indicate that each of these two categories of foods is given to weaned children less than one time per day, on average. Nutrition among Children and Women * 131 Ta bl e 10 .5 F re qu en cy o f f oo ds c on su m ed b y ch ild re n in p re ce di ng 2 4 ho ur s M ea n nu m be r o f t im es sp ec ifi c fo od s w er e co ns um ed b y yo un ge st ch ild re n un de r t hr ee y ea rs o f a ge li vi ng w ith th ei r m ot he r i n th e 24 h ou rs p re ce di ng th e su rv ey , b y br ea stf ee di ng st at us a nd c hi ld ’s ag e, M al aw i 20 00 __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ _ Pu m pk in / O th er ye llo w vi ta m in Po w de re d/ sq ua sh / G re en A ric h O th er M ea t/ O th er O ils / tin ne d/ An y ca rr ot s/ le af y fru its / fru its / Tu be rs / Be an s/ fis h/ fo od s fa ts / C hi ld 's ag e In fa nt fre sh Fr es h ot he r ye llo w s w ee t ve ge - ve ge - ve ge - ro ot s/ le gu m es / po ul try / Pl ai n En ric he d co n- bu tte r/ in m on th s fo rm ul a m ilk ju ic e Th ob w a1 liq ui d2 C er ea l po ta to es ta bl es ta bl es ta bl es pl an ta in s le nt ils eg gs po rr id ge po rr id ge su m ed m ar ga rin e N um be r __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ _ BR EA ST FE ED IN G C H IL D RE N __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ < 2 2- 3 4- 5 6- 7 8- 9 10 -1 1 12 -1 3 14 -1 5 16 -1 9 18 -2 3 24 -2 9 30 -4 9 < 4 4- 5 6- 9 To ta l 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 1 0. 0 0. 1 0. 0 34 8 0. 1 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 5 0. 0 0. 5 0. 0 44 5 0. 0 0. 0 0. 0 0. 1 0. 1 0. 1 0. 0 0. 1 0. 0 0. 0 0. 0 0. 0 0. 0 1. 4 0. 1 1. 3 0. 0 46 2 0. 0 0. 1 0. 1 0. 1 0. 4 0. 5 0. 0 0. 3 0. 1 0. 1 0. 1 0. 1 0. 2 1. 5 0. 2 1. 8 0. 1 41 3 0. 1 0. 1 0. 1 0. 2 0. 4 1. 1 0. 1 0. 6 0. 1 0. 3 0. 2 0. 2 0. 4 1. 4 0. 3 2. 1 0. 1 38 5 0. 1 0. 1 0. 1 0. 3 0. 5 1. 5 0. 2 0. 8 0. 1 0. 4 0. 4 0. 3 0. 5 1. 1 0. 3 2. 3 0. 1 42 0 0. 1 0. 1 0. 1 0. 3 0. 5 1. 7 0. 1 0. 8 0. 2 0. 5 0. 3 0. 4 0. 6 1. 1 0. 3 2. 4 0. 1 40 8 0. 1 0. 1 0. 2 0. 4 0. 5 1. 6 0. 2 0. 9 0. 2 0. 4 0. 5 0. 4 0. 5 1. 1 0. 2 2. 4 0. 1 35 7 0. 0 0. 1 0. 2 0. 3 0. 5 1. 6 0. 2 0. 9 0. 2 0. 4 0. 4 0. 4 0. 6 1. 1 0. 2 2. 5 0. 1 32 4 0. 1 0. 1 0. 1 0. 4 0. 6 1. 8 0. 2 1. 0 0. 3 0. 5 0. 5 0. 4 0. 6 0. 9 0. 2 2. 5 0. 1 84 2 0. 0 0. 1 0. 1 0. 4 0. 5 1. 8 0. 3 1. 1 0. 2 0. 5 0. 7 0. 4 0. 5 0. 8 0. 1 2. 5 0. 1 35 8 0. 0 0. 1 0. 1 0. 5 0. 3 1. 9 0. 2 1. 0 0. 2 0. 4 0. 5 0. 4 0. 4 0. 8 0. 2 2. 6 0. 1 8 2 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 3 0. 0 0. 3 0. 0 79 3 0. 0 0. 0 0. 0 0. 1 0. 1 0. 1 0. 0 0. 1 0. 0 0. 0 0. 0 0. 0 0. 0 1. 4 0. 1 1. 3 0. 0 46 2 0. 0 0. 1 0. 1 0. 2 0. 4 0. 8 0. 0 0. 4 0. 1 0. 2 0. 1 0. 2 0. 3 1. 5 0. 3 1. 9 0. 1 79 8 0. 0 0. 1 0. 1 0. 2 0. 4 1. 1 0. 1 0. 6 0. 1 0. 3 0. 3 0. 3 0. 4 1. 0 0. 2 1. 9 0. 1 4, 84 4 __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ N O N BR EA ST FE ED IN G C H IL D RE N __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ 0- 17 18 -2 3 24 -2 9 30 -3 5 To ta l 0. 1 0. 3 0. 1 0. 5 0. 8 1. 6 0. 1 1. 0 0. 2 0. 5 0. 5 0. 8 0. 6 1. 1 0. 1 2. 6 0. 2 42 0. 1 0. 2 0. 2 0. 5 0. 9 1. 8 0. 2 1. 1 0. 3 0. 6 0. 6 0. 4 0. 6 1. 0 0. 3 2. 7 0. 2 19 5 0. 1 0. 2 0. 1 0. 4 0. 8 1. 9 0. 2 1. 0 0. 2 0. 5 0. 6 0. 5 0. 7 0. 8 0. 2 2. 7 0. 2 55 0 0. 0 0. 2 0. 1 0. 4 0. 7 1. 9 0. 2 1. 1 0. 3 0. 6 0. 6 0. 5 0. 7 0. 8 0. 2 2. 7 0. 2 55 0 0. 1 0. 2 0. 1 0. 4 0. 8 1. 9 0. 2 1. 1 0. 3 0. 5 0. 6 0. 5 0. 7 0. 8 0. 2 2. 7 0. 2 1, 33 7 __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ N ot e: B re as tfe ed in g st at us re fe rs to la st 2 4 ho ur s. P er ce nt ag e m ay s um to m or e th an 1 00 b ec au se th e ch ild m ay h av e re ce iv ed m or e th an o ne ty pe o f s up pl em en t. 1 Th ob w a is a fe rm en te d m ai ze -b as ed d rin k 2 D oe s no t i nc lu de p la in w at er 3 The interviewer showed a vitamin A capsule to the mother when asking the question to assist the mother in recalling. 132 * Nutrition among Children and Women 10.1.5 MICRONUTRIENTS Micronutrient deficiencies constitute a serious threat to child health and survival. The 2000 MDHS survey collected various types of data that are useful in assessing the micronutrient status and intake of young children and women. Micronutrient Status of Young Children In addition to vitamin A derived through one’s diet (foods and food fortification), vitamin A supplements may be received by children as part of primary prevention programmes. Women may get vitamin A supplements during the postpartum period to assist both the women and their breastfeeding children. Vitamin A is an essential micronutrient for the normal functioning of the visual system, growth and development, resistance to disease, and reproduction. It is now understood that improvement of the vitamin A status of young children reduces mortality rates. Table 10.6 shows that 61 percent of children under age three received some type of food containing vitamin A in the last 24 hours. A question was also asked in the MDHS survey for all children under age five as to whether the child received a vitamin A supplement in the six months preceding the survey.3 Sixty-five percent of children were reported to have recently received a supplement. As expected, the youngest children (under 7 months) were least likely to have either eaten foods rich in vitamin A or to have received a vitamin A supplement. Urban children are less likely than rural children to have received a vitamin A supplement in the last six months but were more likely to have eaten foods rich in vitamin A. District differentials are fairly substantial, with supplementation rates as low as 50 percent in Salima District and as high as 78 percent in Machinga District. Differences in vitamin A supplementation by mother’s education and birth order and sex of the child are minimal. In the 2000 MDHS survey, households were asked to present a sample of ordinary salt used in the household. The iodine content of salt was measured using a rapid test kit developed by UNICEF. Salt containing at least 15 ppm (parts per million) is considered to be adequately iodised. Disorders induced by dietary iodine deficiency constitute a major global nutrition concern. Iodine deficiency in the fetus leads to increased rates of abortion, stillbirths, congenital anomalies, cretinism, psychomotor defects, and neonatal mortality. In children and adults, the effects are demonstrated as goitre, hypothyroidism, impaired mental functions, retarded mental and physical development, and diminished school performance. Iodine deficiency can be avoided by using salt that has been fortified with iodine. Table 10.5 shows that less than one-half (49 percent) of children under age 5 live in households possessing adequately iodised salt. Iodisation of salt is more prevalent in urban areas, in the Northern Region, and in households where the children’s mothers are more educated. Variation among Malawi’s districts is substantial (Figure 10.1). In Machinga District, where significant amounts of raw salt are imported from Mozambique, only 22 percent of children live in households with iodised salt, compared with more than 62 percent in Kasungu, Blantyre, and Thyolo districts. Nutrition among Children and Women * 133 Table 10.6 Micronutrient intake of children Percentage of youngest living children under three years of age living with the mother who consumed vitamin A rich foods, percentage of youngest living children under five years of age living with the mother who received vitamin A supplements, and percentage of children under five living in households using adequately iodised salt, by background characteristics, Malawi 2000__________________________________________________________________________________ Number Vitamin A Iodine in Number Vitamin of supplement household of Background A rich children in last 6 salt children characteristic foods1 under 3 months 15+ ppm under 5__________________________________________________________________________________ Child's age in months <7 7-11 12-17 18-23 24-35 36-47 48-59 Sex of child Male Female Birth order 1 2-3 4-5 6+ Mother's age at birth <20 20-24 25-29 30-34 35-39 40-44 45-49 Mother's education No education Primary 1-4 Primary 5-8 Secondary+ Residence Urban Rural Region Northern Central Southern Districts Blantyre Karonga Kasungu Lilongwe Machinga Mangochi Mulanje Mzimba Salima Thyolo Zomba Other districts Total 6.4 1,467 27.7 48.4 1,467 57.3 1,016 72.9 44.9 1,016 79.7 1,121 79.8 46.0 1,121 85.5 1,037 79.3 49.5 1,037 86.2 1,540 74.7 49.8 1,540 na na 71.6 53.7 854 na na 58.0 53.4 432 61.2 3,068 64.5 49.5 3,697 61.2 3,113 66.1 48.3 3,769 60.3 1,358 65.3 52.3 1,537 60.7 2,211 64.9 48.0 2,597 62.0 1,300 65.8 47.7 1,554 62.4 1,313 65.5 48.3 1,779 61.0 1,176 65.2 49.8 1,339 60.5 1,984 64.4 50.8 2,308 60.8 1,407 65.7 46.8 1,687 64.1 797 66.7 47.1 1,001 62.7 551 64.1 50.7 733 61.2 198 67.3 48.4 307 51.2 67 67.8 34.5 92 59.8 1,897 63.2 41.9 2,322 59.8 1,914 65.4 47.1 2,333 63.4 1,905 67.7 53.9 2,236 64.2 465 64.1 65.4 575 66.9 809 58.2 66.3 987 60.4 5,372 66.4 46.2 6,480 61.1 699 68.2 59.2 822 63.0 2,647 65.4 46.8 3,200 59.6 2,835 64.5 48.4 3,445 66.0 469 53.1 62.8 568 59.9 123 71.8 46.0 146 66.3 253 65.6 73.1 303 65.6 913 65.1 46.0 1,120 61.0 233 78.2 21.5 285 60.0 320 56.9 41.3 385 65.7 273 63.6 57.0 330 64.4 297 63.4 54.3 352 58.7 132 49.9 57.1 171 54.5 276 65.8 65.3 354 60.2 376 65.8 43.1 440 58.7 2,516 68.3 45.6 3,012 61.2 6,181 65.3 48.9 7,467 __________________________________________________________________________________ na = Not applicable 1 Vitamin A rich foods include pumpkin, yellow squash, carrots, yellow sweet potatoes, green leafy vegetables, mangoes, and papayas. Does not include animal products. 4 When the question was asked, the interviewer showed a vitamin A capsule to the respondent. 5 Women are considered to experience night blindness if they report vision problems during the night, but not during the day. 134 * Nutrition among Children and Women Micronutrient Status and Supplements for Women During and After Pregnancy Provision of vitamin A supplements to women after delivery of a child is intended to boost stores and ensure adequate delivery of this essential micronutrient to the child in breast milk. The MDHS survey asked women whether they had received a vitamin A supplement in the two-month period after delivery of their last born child.4 The women were also asked whether they had experienced any vision problems during the night time and (in a separate question) during the day.5 Night blindness in pregnancy is a common manifestation of vitamin A deficiency (VAD). Table 10.7 shows that 41 percent of women received a vitamin A supplement during the postnatal period. Variation in postpartum vitamin A supplementation by child’s birth order and age of the mother is minimal. Supplementation is slightly higher in urban areas, in the Northern Region, and among women with more education. More substantial variation is found among the districts, ranging from just 32 percent in Salima District to 59 percent in Karonga District. Table 10.7 also shows that about 4 percent of women with a recent birth experience night blindness, an indicator of VAD. Although the small percentages make it difficult to examine variation among subgroups of Malawi’s population, certain observations are cautiously made. Night blindness is more prevalent among less educated women, women in rural areas, and women in the Central Region. District prevalence for night blindness ranges from 2 percent in Blantyre to 8 percent in Salima. Nutrition among Children and Women * 135 Table 10.7 Micronutrient intake among mothers Percentage of women who gave birth in the five years preceding the survey, who received vitamin A in the first two months after delivery, who suffered night blindness during pregnancy, and who took iron supplements during the pregnancy, by background characteristics, Malawi 2000____________________________________________________________________ Iron on Received Night blind 90+ days Background vitamin A during during characteristic postpartum pregnancy pregnancy Number____________________________________________________________________ Birth order 1 2-3 4-5 6+ Mother's age at birth <20 20-24 25-29 30-34 35-39 40-44 45-49 Mother's education No education Primary 1-4 Primary 5-8 Secondary+ Residence Urban Rural Region Northern Central Southern Districts Blantyre Karonga Kasungu Lilongwe Machinga Mangochi Mulanje Mzimba Salima Thyolo Zomba Other districts Total 41.4 4.2 12.9 1,703 43.3 4.1 11.4 2,780 41.3 4.2 13.4 1,664 40.0 4.7 11.9 1,909 41.4 3.3 11.8 1,487 41.8 4.3 11.2 2,482 42.6 4.4 13.3 1,787 44.1 4.4 13.9 1,073 38.0 5.3 11.3 787 38.3 5.4 13.1 340 44.0 3.4 12.3 101 38.3 4.1 9.9 2,477 39.3 5.5 11.0 2,531 44.9 3.4 14.5 2,434 52.2 3.3 17.5 615 45.4 2.6 13.5 1,075 41.1 4.5 12.0 6,982 49.6 4.6 18.5 894 39.2 5.3 9.0 3,407 42.1 3.3 13.7 3,757 43.7 2.2 13.6 638 59.2 5.5 18.7 157 42.1 5.9 13.5 316 41.9 2.9 9.1 1,173 52.2 2.5 7.2 314 35.5 3.3 10.4 412 36.2 3.1 11.5 368 38.7 4.9 18.3 382 31.9 8.0 5.5 189 43.4 2.5 9.8 397 32.8 6.8 21.8 469 42.8 5.0 12.1 3,242 41.7 4.3 12.2 8,057 Iron-deficiency anemia is a major threat to maternal health; it contributes to low birth weight, lowered resistance to infection, poor cognitive development, and decreased work capacity. Further, anemia increases morbidity from infections because it adversely affects the body’s immune response. The MDHS survey asked women who had a recent birth whether they had received or purchased any iron tablets (shown to the women) during their last pregnancy. If so, the woman was asked to report the number of days that the tablets were actually taken during that pregnancy. Interviewers assisted the respondent in converting responses provided on a daily or weekly basis to total number of days over the course of the pregnancy. Table 10.7 shows that 12 percent of women reported taking iron supplements on at least 90 days during the pregnancy, as 136 * Nutrition among Children and Women recommended. Although some groups of women were more likely than others to report taking iron supplements, no group reported supplementation rates exceeding 22 percent. Just 6 percent of women in Salima District reported the recommended level of iron supplementation during their last pregnancy, as compared with 22 percent in Zomba District. 10.2 NUTRITIONAL STATUS OF CHILDREN UNDER AGE FIVE The nutritional well-being of young children reflects household, community, and national investments in family health and contributes in both direct and indirect ways to the country’s development. In collecting anthropometric data (height and weight), the MDHS survey permits objective measurement and evaluation of nutritional status of young children in Malawi. This evaluation allows identification of subgroups of the child population who are at increased risk of growth faltering, disease, impaired mental development, and death. Trends in child malnutrition can be assessed by comparing the 2000 MDHS survey results with those obtained from the 1992 MDHS survey, which used the same methods. 10.2.1 MEASURES OF NUTRITIONAL STATUS IN CHILDHOOD Evaluation of nutritional status is based on the rationale that in a well-nourished population, there is a statistically predictable distribution of children of a given age with respect to height and weight of the child. Use of a standard reference population facilitates analysis of any given population over time as well as comparisons among population subgroups. One of the most commonly used reference populations, and the one used in this report, is the U.S. National Centre for Health Statistics (NCHS) standard, which is recommended for use by the World Health Organisation. Three standard indices of physical growth that describe the nutritional status of children are presented: C height-for-age C weight-for-height C weight-for-age. Each of these indices gives different information about growth and body composition used to assess nutritional status. Height-for-age is a measure of linear growth. A child who is more than two standard deviations below the median of the NCHS reference population (i.e., >-2 SD) in terms of height-for-age is considered short for his/her age, or stunted, a condition that reflects the cumulative effect of chronic malnutrition. If the child is more than three standard deviations below the reference mean (i.e., >-3 SD), then the child is considered to be severely stunted. A child between -2 SD and -3 SD is considered moderately stunted. Weight-for-height describes a child’s current nutritional status. A child who is more than two standard deviations below the weight-for-height reference mean is considered too thin for his/her height, or wasted, a condition reflecting acute or recent nutritional deficit. As with stunting, wasting is considered severe if the child is more than three standard deviations below the reference mean. Severe wasting is closely linked to mortality risk. Weight-for-age is a composite index of weight-for-height and height-for-age and thus does not distinguish between acute undernutrition (wasting) and chronic undernutrition (stunting). A Nutrition among Children and Women * 137 child can be underweight for his/her age because he/she is stunted, because he/she is wasted, or because he/she is wasted and stunted. Weight-for-age is a very good overall indicator of a population’s nutritional health. All surviving children in the household under age five were eligible for height and weight measurement. Of the 10,559 children under 60 months old at the time of the survey 9,967 (94 percent) were weighed and measured. The most commonly reported reason for not being measured was that the child was not home at the time of the survey (after repeated return visits). Of the children who were both weighed and measured, 654 (7 percent) were considered to have implausibly low or high values for height-for-age or weight-for-height. The following analysis focuses on the 9,318 children under 60 months of age for whom complete and plausible anthropometric data were collected. These children include only those whose mother was eligible for interview in the survey (i.e., women age 15-49 identified in the household schedule). The 2000 MDHS survey is different from previous DHS surveys (including the 1992 MDHS survey) in that children under age five whose mother was not in the household schedule (870 such children in this survey) were also weighed and measured. This allows for assessment of nutritional status of children whose mother is dead or otherwise not living with the child. Examination of these children shows that their nutritional status is not significantly different from the majority of children whose mother was living in the household. However, the following analysis focuses on the group of children whose mother was in the household to allow for the most robust comparisons with previous surveys. 10.2.2 LEVELS OF CHILD MALNUTRITION Table 10.8 shows the percentage of children under 60 months classified as malnourished according to height-for-age, weight-for-height, and weight-for-age indices, by the child’s age and background characteristics. The 2000 MDHS estimate of the prevalence of chronic malnutrition or stunting is 49 percent; almost one-half of these (24 percent of the total) are severely stunted. These estimates of stunting closely parallel those based on the 1992 MDHS data, suggesting no improvement in the long-term nutritional situation of young children over the last eight years. Figure 10.2 shows the distribution of children by age, according to the extent to which they differ from the reference population in terms of the three indicators discussed above, including low height-for-age (stunting). Clear from this presentation is the deterioration in nutritional status that begins shortly after birth. A rapid worsening in the linear growth of Malawian children begins during the first year, especially late in the first year, and continues through the second year, when stunting prevalence peaks at above 60 percent. The prevalence of stunting stays above 50 percent for the remainder of the under-five age period. Boys are slightly more likely to be stunted than girls, as are children of high birth order compared with those of lower birth order. Children born after a long birth interval (more than 48 months) are less likely to be stunted than children born after shorter birth intervals. The weight-for-height index gives information about children’s recent experience with food intake and illnesses. Wasting represents failure to receive adequate nutrition in the period immediately preceding the survey and may be complicated and worsened by a recent illness. About 6 percent of children under five in Malawi are wasted; 1 percent are severely wasted. Wasting is most common during age 6-23 months, indicating that complementary feeding practises during the weaning period may be inadequate. The level of wasting estimated from the 2000 MDHS survey is 5.5 percent, virtually the same as that found in the 1992 MDHS survey (5.4 percent). 138 * Nutrition among Children and Women Table 10.8 Nutritional status of children by demographic characteristics Percentage of children under five years classified as malnourished according to three anthropometric indices of nutritional status: height-for-age, weight-for-height, and weight-for-age, by background characteristics, Malawi 2000____________________________________________________________________________________________________ Height-for-age Weight-for-height Weight-for-age______________________ ______________________ ______________________ Per- Per- Per- Per- Per- Per- centage centage Mean centage centage Mean centage centage Mean Background below below Z-score below below Z-score below below Z-score characteristic -3 SD -2 SD1 (SD) -3 SD -2 SD1 (SD) -3 SD -2 SD1 (SD) Number____________________________________________________________________________________________________ Child's age in months <6 6-9 10-11 12-15 16-23 24-35 36-47 48-59 Sex of child Male Female Birth order 1 2-3 4-5 6+ Birth interval in months First birth <24 months 24-47 months 48+ months Residence Urban Rural Region Northern Central Southern Mother's education No education Primary 1-4 Primary 5-8 Secondary+ Districts Blantyre Karonga Kasungu Lilongwe Machinga Mangochi Mulanje Mzimba Salima Thyolo Zomba Other districts Total 3.0 11.4 -0.4 1.3 5.8 0.4 1.3 5.9 0.0 1,005 10.2 26.4 -1.1 2.0 8.9 -0.3 5.0 23.9 -1.1 739 13.4 31.8 -1.2 2.7 10.3 -0.3 6.5 29.1 -1.2 375 21.4 46.5 -1.8 1.6 13.0 -0.4 11.4 38.9 -1.6 717 34.0 64.0 -2.4 1.9 8.2 -0.2 8.4 35.3 -1.5 1,305 29.4 55.6 -2.2 1.1 4.8 -0.1 8.8 31.1 -1.4 1,930 30.8 59.1 -2.3 0.7 2.1 0.2 3.4 21.3 -1.2 1,804 27.6 57.4 -2.2 0.6 1.5 0.2 3.5 20.5 -1.2 1,443 25.8 50.5 -2.0 1.2 5.1 0.0 6.0 25.7 -1.2 4,622 23.0 47.6 -1.8 1.3 6.0 -0.0 5.7 25.1 -1.2 4,696 24.2 49.2 -1.9 1.3 5.7 -0.1 5.7 27.3 -1.2 1,990 23.8 48.7 -1.9 1.2 5.3 0.0 5.0 24.2 -1.2 3,278 23.0 47.4 -1.8 1.4 5.6 -0.0 6.4 24.5 -1.2 1,979 26.9 50.8 -2.0 1.1 5.6 0.0 6.8 26.3 -1.2 2,071 24.5 49.5 -1.9 1.3 5.8 -0.1 5.9 27.7 -1.2 2,010 29.9 53.9 -2.1 1.2 5.8 0.0 9.4 29.3 -1.3 1,181 23.4 48.4 -1.9 1.0 4.8 0.0 4.6 23.0 -1.1 4,599 22.9 46.2 -1.7 1.9 7.1 -0.1 6.8 26.5 -1.1 1,527 13.5 34.2 -1.3 0.9 4.9 0.1 1.4 12.8 -0.7 1,220 26.1 51.2 -2.0 1.3 5.6 -0.0 6.5 27.3 -1.2 8,098 16.2 39.0 -1.5 1.0 4.7 -0.1 3.4 17.4 -1.0 1,027 30.2 55.5 -2.1 1.2 5.0 0.1 6.7 27.9 -1.3 4,017 20.9 45.3 -1.7 1.3 6.2 -0.1 5.7 25.0 -1.1 4,273 28.5 54.1 -2.0 1.2 6.6 -0.0 6.9 29.0 -1.3 2,998 26.8 51.9 -2.0 1.4 5.2 -0.0 6.4 27.7 -1.2 2,932 21.1 45.4 -1.8 1.1 4.7 -0.0 5.0 22.6 -1.1 2,756 8.3 27.0 -1.1 1.1 5.6 0.1 2.1 9.7 -0.6 632 13.5 38.1 -1.4 1.2 6.7 -0.1 3.8 18.0 -0.9 666 14.6 38.8 -1.5 0.4 5.2 -0.0 3.1 16.0 -0.9 193 20.9 47.4 -1.8 0.6 2.7 0.1 2.8 20.7 -1.0 385 31.6 54.2 -2.1 1.6 5.9 0.1 7.2 27.6 -1.2 1,416 22.0 44.5 -1.8 0.3 3.3 -0.0 3.4 24.5 -1.1 367 24.2 47.5 -1.9 1.1 5.7 -0.1 8.5 28.8 -1.2 488 26.1 49.5 -2.0 1.1 4.0 -0.1 5.2 27.7 -1.3 418 17.8 43.9 -1.7 1.1 4.0 -0.1 3.3 18.7 -1.1 424 25.6 54.6 -2.1 1.8 5.7 -0.1 8.8 29.0 -1.3 202 23.3 46.3 -1.8 1.0 4.5 -0.0 5.5 25.9 -1.1 418 21.4 45.7 -1.8 2.4 7.7 -0.1 7.8 24.6 -1.1 574 25.8 51.3 -2.0 1.1 5.8 -0.0 6.0 26.9 -1.2 3,767 24.4 49.0 -1.9 1.2 5.5 -0.0 5.9 25.4 -1.2 9,318 ____________________________________________________________________________________________________ Note: This table refers to de facto children whose mothers were interviewed.1 Includes children who are below -3 standard deviations from the International Reference Population median Nutrition among Children and Women * 139 About one-quarter (25 percent) of children under five in Malawi are underweight—which reflects stunting, wasting, or both. Peak levels of low weight-for-age occur during the second year (age 12-23 months). Boys and girls are at equal risk of being underweight. The likelihood that a child will be severely underweight is highest when he/she is born after a birth interval of less than 24 months. Again, there has been little or no improvement in this broad index of nutritional status since the 1992 MDHS survey. A child’s nutritional status is in part determined by the socioeconomic situation of his/her household, which is in turn affected by where that household physically resides and the educational level the child’s mother. For instance, children living in rural areas are 50 percent more likely to be stunted and 15 percent more likely to be wasted than their urban counterparts. Regional variation in nutritional status of children is substantial. Children living in the Northern Region tend to be better nourished than children in the Southern and Central regions. Stunting is extremely prevalent in the country’s Central Region, where 56 percent of under-five children are too short for their age and where severe stunting is nearly twice as common as in the Northern Region. This regional pattern was also evident in the 1992 MDHS survey. Differentials among Malawi’s districts in the nutritional status of children are substantial. Children in the districts of Blantyre, Mzimba, and Karonga have underweight prevalence rates below 19 percent, compared with rates above 27 percent in Lilongwe, Mangochi, Mulanje, and Salima districts. Thirty-two percent of children in Lilongwe District are severely stunted, compared with 14 percent in Blantyre District. Education of the mother is closely linked to nutritional status of children. Children of women with no education are three times more likely to be underweight as children of women with at least some secondary education. 6 If 150 centimetres were used as the cutoff, 16 percent of women would be considered at risk. 140 * Nutrition among Children and Women 10.3 NUTRITIONAL STATUS OF WOMEN In the 2000 MDHS survey, data were collected on the height and weight of all women age 15-49. Several measures have been used to assess the nutritional status of women (Krasovec and Anderson, 1991). In this report, two indices are presented: the height of women and the body mass index (BMI)—an indicator combining height and weight measures. Of 13,220 women eligible for height assessment, 13,036 (99 percent) were measured. Of 11,281 women eligible for assessment of BMI (these exclude pregnant women and women less than two months postpartum), 11,125 women (99 percent) were weighed and measured and form the basis for the following analysis. Table 10.9 presents the mean values of the maternal anthropometric indicators and the proportions of women falling into high-risk categories, according to background characteristics of women. Height of a woman is associated with past socioeconomic status and nutrition during her childhood and adolescence. Maternal height is also used to predict the risk of difficult delivery, since small stature is often associated with small pelvis size and the potential for obstructed labour. The risk of low birth weight is also increased in short women. The optimal cutoff point, below which a woman can be identified as “at risk”, is in the range of 140 to 150 centimetres. The mean height of mothers measured in the MDHS survey was 156 centimetres. About 3 percent of mothers were less than 145 centimetres in height.6 Women of relatively higher socioeconomic level, i.e., those with at least some secondary school, are taller on average and less likely than their less educated counterparts to be “at risk” due to shortness. Regional differences in height of women are minimal, but rural women are on average shorter than women in urban areas and are more likely to be less than 145 centimetres in height. Short stature is less prevalent in the Lilongwe and Blantyre districts than in other districts. Various indices of body mass are used to assess thinness and obesity. The most commonly used body mass index is defined as the weight in kilograms divided by the squared height in metres. A lower cutoff point of 18.5 has been recommended for defining chronic energy deficiency. The mean BMI among the weighed and measured women was 21.9, with 9 percent having a BMI below 18.5, reflecting a nutritional deficit. There are large differentials across background characteristics in the percentage of mothers assessed as malnourished or “too thin” based on the BMI. Rural women are much more likely to be too thin than urban women. Women with some secondary education are significantly less likely to have a low BMI than their less educated counterparts. Variations in low BMI among the regions are minimal; however, women in the Southern Region are slightly more likely (10 percent) than women in the other regions (8 percent) to have a low BMI. Figure 10.3 shows district variation in the prevalence of malnutrition among women. In Lilongwe and Blantyre districts, the prevalence of malnutrition is less than 7 percent, compared with more than 12 percent in Salima and Mulanje districts. The BMI can also be used to evaluate the percentage of the population of women that is overweight and obese. A cutoff point of 25.0 has been recommended for defining “overweight”. The 2000 MDHS survey finds that one in eight Malawian women (12 percent) is overweight. Two percent of women have a BMI of 30 or more (data not shown), which places them in a category of severely overweight or obese. Nearly one-quarter of women living in urban areas are overweight, Nutrition among Children and Women * 141 Table 10.9 Nutritional status of women by background characteristics Among women age 15-49, mean height and percentage of women under 145 centimetres, mean body mass index (BMI), and percentage of women whose BMI (kg/m2) is below 18.5 or above 25.0, by background characteristics, Malawi 2000_________________________________________________________________________________ Height BMI__________________________ ___________________________________ Background Percentage Percentage Percentage characteristic Mean <145 cm Number Mean <18.5 >25.0 Number1_________________________________________________________________________________ Age 15-19 20-24 25-29 30-34 35-39 40-44 45-49 Residence Urban Rural Region Northern Central Southern Education No education Primary 1-4 Primary 5-8 Secondary+ Districts Blantyre Karonga Kasungu Lilongwe Machinga Mangochi Mulanje Mzimba Salima Thyolo Zomba Other districts Total 154.5 4.9 2,805 20.9 16.6 5.3 2,457 155.9 2.7 2,913 21.8 6.7 9.5 2,276 155.9 2.6 2,379 22.1 6.0 13.2 1,947 156.6 2.1 1,549 22.2 7.2 13.4 1,301 156.1 2.1 1,409 22.7 5.6 19.3 1,259 156.2 2.6 1,042 22.6 6.1 17.8 976 156.2 2.0 938 22.2 8.3 13.4 910 157.0 1.9 2,089 23.2 5.5 23.4 1,845 155.5 3.2 10,947 21.6 9.4 9.5 9,280 155.3 3.6 1,438 21.9 7.5 10.1 1,227 156.1 2.5 5,236 22.0 7.7 12.0 4,416 155.5 3.3 6,362 21.8 9.9 12.1 5,482 155.4 3.2 3,517 21.8 7.6 10.1 2,987 155.2 3.4 3,968 21.5 10.7 8.6 3,335 155.8 3.0 4,099 21.8 9.3 11.6 3,489 158.0 1.2 1,452 23.2 5.2 24.5 1,315 157.0 1.6 1,305 22.9 6.5 22.8 1,155 155.7 4.3 262 22.0 8.0 12.0 223 156.2 2.8 475 22.1 8.2 13.2 391 156.7 1.4 1,844 22.4 5.1 15.6 1,554 155.3 2.1 472 21.4 11.7 11.5 386 154.7 4.4 630 21.6 9.7 11.0 541 154.8 3.7 614 21.4 12.8 9.2 540 .155.4 2.9 596 21.8 7.8 9.8 509 155.4 3.4 292 21.4 12.3 7.8 242 155.0 4.1 680 21.4 10.9 7.7 587 155.5 2.9 841 21.7 8.4 10.4 730 155.5 3.5 5,023 21.7 9.6 9.1 4,268 155.8 3.0 13,036 21.9 8.8 11.8 11,125 __________________________________________________________________________________ 1 Excludes pregnant women and women who had a birth in the preceding two months. compared with 10 percent in rural areas. Women in Blantyre are nearly three times as likely to be overweight as their counterparts living in Salima and Thyolo districts. Likewise, having attended secondary school is associated with a much higher proportion of a women being overweight, compared with women with less education. Taken together, these findings suggest that for many Malawian women, adoption of a modern lifestyle has had some unhealthy consequences. 142 * Nutrition among Children and Women 1 These estimates of survival times assume no use of antiretroviral therapies. AIDS and other STIs * 143 11AIDS AND OTHER SEXUALLY TRANSMITTED INFECTIONS Henry Damisoni and George Bicego Acquired immune deficiency syndrome (AIDS) is one of the most serious public health and development challenges to ever visit sub-Saharan Africa. In Malawi, it is estimated that 15 percent of adults age 15-49 are currently infected with the human immunodeficiency virus (HIV), the virus that causes AIDS (NACP, 2001). This would mean that 740,000 men and women will develop or already have developed AIDS. Further, 65,000 children under age 15 are estimated to be HIV infected. About three-quarters of all AIDS cases occur among people in the most economically productive age group, 20-45 years. The deaths of these individuals constitute personal, economic, and social tragedies in the lives of surviving family, friends, and employers. The principal mode of HIV transmission in Malawi is heterosexual contact. This accounts for 90 percent of HIV infections in the country (UNAIDS, 2000). The duration between HIV infection and onset of AIDS varies but averages 9-10 years, and death typically ensues within 1-2 years of symptom onset.1 This is followed in importance by perinatal transmission (9 percent of all HIV infections), whereby the mother passes HIV to the child during pregnancy or around the time of birth. It has been estimated that approximately 20 percent of babies born to HIV-positive mothers will be infected around the time of birth. About one-half of children infected perinatally will die before their fifth birthday. It is now understood that the virus may also be passed from mother to infant during breastfeeding. The children of HIV-infected parents who are not themselves infected are still at a great disadvantage, due to health and social consequences of losing one or both parents to AIDS. It is estimated that between 1990 and 2000, the number of Malawian children under 15 who were living without one or both parents grew from about 740,000 to 1.20 million (Hunter and Williamson, 2000), with most of the increase being the result of sharp rises in the rates of adult mortality (see Chapter 12). The future course of Malawi’s AIDS epidemic depends on a number of important variables, including the level of public awareness about HIV/AIDS, the level and pattern of risk-related behaviours, access to high-quality services for sexually transmitted infections (STIs), and provision of HIV-testing and counseling. The impact of AIDS is now affecting all sectors of Malawian society, and the nation’s response needs to be matched with multisectoral strategies and interventions. The National AIDS Control Programme (NACP) is on the leading edge of efforts to bring down barriers to effective HIV/AIDS programmes and has identified the key challenges and opportunities to galvanise an effective national effort in “Malawi’s National Response to HIV/AIDS for 2000-2004: Combating HIV/AIDS with Renewed Hope and Vigour in the New Millennium” (NACP, 2001). The data obtained from the 2000 MDHS survey provide a good opportunity to assess levels and trends in some of these factors. This chapter first presents findings about current levels of general and more specific knowledge on AIDS-related issues. Since knowledge of one’s own HIV 2 This includes the small percentage who report that they do not know of AIDS. 144 * AIDS and other STIs status is considered an important step leading to a constructive attitude and behaviour change, information on the respondents’ experience with HIV-testing is provided. Next, findings are presented on knowledge of and experience with other sexually transmitted infections, which may be important cofactors in HIV transmission. The chapter concludes by providing information on patterns of sexual activity and condom use. The principle objective of this chapter is to establish the prevalence of relevant knowledge, perceptions, and behaviours at the national level and within geographic and socioeconomic subgroups of the population. In this way, AIDS control programmes can target those groups of individuals most in need of information and services and most vulnerable to the risk of HIV infection. 11.1 KNOWLEDGE OF WAYS TO PREVENT HIV/AIDS Table 11.1 shows that general awareness of AIDS is nearly universal in Malawi, with 99 percent of women and almost 100 percent of men reporting that they had “heard of AIDS.” Fewer, but still a large proportion of, women and men report that they think that there is “a way to avoid getting AIDS” (93 percent of women and 98 percent of men). Women and men living in rural areas and in the Northern Region are more likely to report that AIDS cannot be avoided than urban respondents and those living in the Central and Southern regions. Education is also strongly related to poor understanding of HIV/AIDS prevention. For example, less than 1 percent of women who ever attended secondary school reported that AIDS cannot be avoided, compared with 11 percent of women who have not attended school.2 If respondents reported that AIDS could be avoided, they were asked to report how “a person could avoid getting the AIDS virus.” Two types of questions were asked about ways to avoid getting HIV/AIDS. First, an open-ended question was asked, and respondents were allowed to give all the ways to avoid HIV/AIDS that they knew of without prompting. Next, women and men were asked specific questions on whether condom use and (in a separate question) limiting their sexual activity to just one partner can reduce their chances of getting AIDS. Table 11.2 provides results on AIDS prevention knowledge. The denominator or base for these estimates is all men and women (including those who reported that they did not know about HIV/AIDS at all, that they did not know whether it could be avoided, or that they thought it could not be avoided). The most frequently reported means to prevent HIV/AIDS was avoiding sex altogether, for both women (67 percent) and men (77 percent). Condom use was reported by 55 percent of women and 71 percent of men. Limiting the number of sexual partners was cited by 27 percent of women and 20 percent of men. Although HIV is rarely transmitted by sharing razor blades, 34 percent of women and 27 percent of men cited avoidance of this practise. All other means were reported much less frequently, but more than 10 percent of both women and men reported avoidance of injections as a means to prevent HIV/AIDS. The pattern of these reports indicates that the relative importance of different ways to prevent HIV infection in the population and the predominant role of unprotected sex with casual partners in the spread of HIV need to be better understood and accepted. AIDS and other STIs * 145 Table 11.1 Knowledge of AIDS Percentage of women and men who have heard of AIDS, and percentage who believe there is a way to avoid getting AIDS, by background characteristics, Malawi 2000 _________________________________________________________________________________________________ Women Men __________________________________ _________________________________ Believes Believes there is there is Has a way Has a way Background heard of to avoid heard of to avoid characteristic HIV/AIDS getting AIDS Number HIV/AIDS getting AIDS Number _________________________________________________________________________________________________ Age 15-19 20-24 25-29 30-39 40-49 (men, 40-54) Current marital status Married or living together Divorced, separated, widowed Never married Ever had sex Never had sex Residence Urban Rural Region Northern Central Southern Education No education Primary 1-4 Primary 5-8 Secondary+ Total 98.3 91.5 2,867 99.1 96.4 660 99.0 94.5 2,957 99.7 98.0 598 99.3 93.8 2,401 99.7 98.0 539 99.3 93.6 2,990 100.0 98.8 670 98.6 91.9 2,004 99.8 97.1 624 99.1 93.3 9,452 99.9 98.5 1,906 98.8 93.1 1,525 98.5 93.6 113 99.0 95.3 868 99.7 98.5 767 97.4 90.6 1,375 98.3 91.8 306 99.8 99.0 2,106 99.9 98.0 564 98.7 92.0 11,114 99.6 97.6 2,528 99.4 90.4 1,453 99.2 95.2 351 98.9 91.9 5,321 99.8 98.1 1,296 98.8 94.7 6,446 99.6 97.9 1,446 97.8 88.8 3,574 99.2 94.9 322 98.7 91.7 4,025 99.2 97.2 898 99.8 96.0 4,152 99.9 98.0 1,243 99.8 99.5 1,468 100.0 99.2 629 98.9 93.1 13,220 99.7 97.7 3,092 AIDS prevention programmes focus their messages and efforts on three important aspects of behaviour: use of condoms, limiting the number of sexual partners/staying faithful to one partner, and delaying sexual debut in young persons (i.e., abstinence). In the first three columns of Table 11.3, the percent distributions of men and women who reported 0, 1, or 2 to 3 of these ways to avoid AIDS are shown. Eighty-five percent of women and 92 percent of men knew of 2 or 3 ways to avoid getting HIV/AIDS. Women were nearly twice as likely as men to report 0 or just 1 of the key AIDS prevention methods (15 percent for women, 8 percent for men). Other characteristics related to knowledge of ways to prevent HIV infection include age, sexual activity, education, and residential characteristics. The link between educational level of the respondent and AIDS prevention knowledge is a strong one. Only 5 percent of women with secondary education knew fewer than two ways of AIDS prevention, compared with 21 percent of women with no schooling. Significantly, young respondents (age 15-19) and those reporting that they never had sex knew fewer AIDS prevention methods than older, sexually experienced men and women. 3 Comparison with the AIDS prevention knowledge data from the 1992 MDHS is not feasible. 146 * AIDS and other STIs Table 11.2.1 Knowledge of ways to avoid HIV/AIDS: women Percentage of all women 15-49 who know of specific ways to avoid HIV/AIDS, by background characteristics, Malawi 2000 ___________________________________________________________________________________________________________________________ Avoid sex with partners Seek Abstain Limit who Avoid Avoid protection from number have sex with Avoid sharing Avoid from Number Background sexual Use of sexual multiple prosti- trans- Avoid razors/ Avoid mosquito trad. of characteristic relations condoms partners partners tutes fusions injections blades kissing bites healer Other women1 __________________________________________________________________________________________________________________________ Age 15-19 20-24 25-29 30-39 40-49 Current marital status Married or living together Divorced, separated, widowed Never married Ever had sex Never had sex Residence Urban Rural Region Northern Central Southern Education No education Primary 1-4 Primary 5-8 Secondary+ Total 64.7 55.1 21.1 2.8 4.1 3.3 11.7 36.1 0.9 0.3 1.0 1.7 2,867 66.4 59.9 28.4 2.8 4.3 3.3 9.2 32.9 0.5 0.5 0.5 2.0 2,957 67.2 55.2 29.6 1.9 5.3 3.2 10.6 35.1 0.4 0.4 0.9 1.9 2,401 69.6 52.4 29.5 2.3 3.9 2.8 11.6 33.2 0.3 0.1 1.1 1.7 2,990 68.0 48.3 29.5 2.5 3.4 3.2 9.8 30.4 0.4 0.1 1.1 1.6 2,004 66.3 53.3 29.7 2.3 4.3 2.9 10.7 32.6 0.5 0.2 0.8 1.9 9,452 69.0 60.2 25.9 3.1 4.0 2.4 8.3 31.4 0.3 0.1 1.0 1.2 1,525 70.7 70.8 20.7 3.2 4.4 4.7 10.2 36.6 0.9 0.5 1.6 1.8 868 68.7 46.9 18.0 2.1 3.9 4.3 12.7 41.9 1.0 0.7 1.0 1.9 1,375 76.1 65.9 33.8 2.3 2.9 3.9 11.3 34.6 0.5 0.7 0.9 0.6 2,106 65.4 52.4 26.2 2.5 4.5 3.0 10.5 33.5 0.5 0.2 0.9 2.0 11,114 61.7 39.9 24.2 3.1 2.6 2.4 11.1 26.6 0.7 1.1 1.8 1.0 1,453 61.6 46.4 30.3 2.5 5.1 2.8 11.5 31.4 0.3 0.2 0.4 2.2 5,321 72.9 64.7 25.8 2.3 3.9 3.6 9.8 37.1 0.7 0.1 1.1 1.7 6,446 62.9 45.2 27.9 2.5 4.2 2.5 7.6 29.2 0.4 0.2 0.6 1.4 3,574 63.7 53.7 28.5 2.3 4.2 2.4 8.1 31.7 0.4 0.1 0.8 2.1 4,025 70.5 58.7 25.2 2.2 4.2 3.1 13.6 36.3 0.4 0.3 1.3 2.0 4,152 77.0 68.1 30.0 3.4 4.5 6.8 16.4 42.4 1.5 0.9 1.2 1.2 1,468 67.1 54.6 27.4 2.5 4.2 3.1 10.6 33.7 0.5 0.3 0.9 1.8 13,220 ___________________________________________________________________________________________________________________________ 1 Includes women who do not know AIDS and those who believe there is no way to avoid HIV/AIDS. On the right side of Table 11.3 are the MDHS results when prompting is used to ascertain whether women and men know about condom use and about limiting the number of sexual partners as ways to avoid HIV infection. When women are prompted, their reported knowledge of condom use for HIV/AIDS protection rises from 55 percent (unprompted) to 77 percent. In the same way, men’s knowledge rises from 71 to 86 percent. Without prompting, 27 percent of women and 20 percent of men reported limiting the number of sexual partners as a way to avoid HIV/AIDS. When prompted, the percentages rise to 82 and 84 percent, respectively. The methodology used in the 2000 MDHS survey to estimate knowledge about AIDS prevention is relatively new. As such, comparisons with the 1996 MKAPH are difficult.3 However, some comparisons are useful. Unprompted knowledge of condom use rose rapidly between 1996 and 2000, from 23 to 55 percent in women and from 47 to 71 percent in men. In 1996, 17 percent AIDS and other STIs * 147 Table 11.2.2 Knowledge of ways to avoid HIV/AIDS: men Percentage of all men 15-54 who know of specific ways to avoid HIV/AIDS, by background characteristics, Malawi 2000 ___________________________________________________________________________________________________________________________ Avoid sex with partners Seek Abstain Limit who Avoid Avoid protection from number have sex with Avoid sharing Avoid from Number Background sexual Use of sexual multiple prosti- trans- Avoid razors/ Avoid mosquito trad. of characteristic relations condoms partners partners tutes fusions injections blades kissing bites healer Other men1 ___________________________________________________________________________________________________________________________ Age 15-19 20-24 25-29 30-39 40-54 Current marital status Married or living together Divorced, separated, widowed Never married Ever had sex Never had sex Residence Urban Rural Region Northern Central Southern Education No education Primary 1-4 Primary 5-8 Secondary+ Total 69.3 73.0 11.3 1.2 7.5 5.1 10.7 33.3 1.0 0.5 0.7 2.6 660 73.9 80.2 17.6 1.5 6.4 4.9 10.9 28.4 1.7 0.2 0.6 3.0 598 80.9 69.5 21.9 1.7 9.4 4.1 10.5 26.8 1.0 0.5 1.1 1.4 539 82.2 72.4 25.6 1.1 5.5 3.2 11.8 24.2 1.8 0.5 0.2 1.4 670 80.7 61.7 25.8 1.1 7.2 2.2 10.6 21.8 0.9 0.2 1.1 2.8 624 80.1 68.6 25.3 1.3 7.2 3.0 10.8 24.1 1.2 0.4 0.8 2.1 1,906 79.2 75.7 16.0 1.0 7.1 3.2 9.7 25.6 2.5 0.0 0.0 4.3 113 71.6 82.3 12.6 1.1 6.3 5.3 12.3 32.4 0.9 0.4 0.9 2.3 767 73.6 59.7 10.9 1.8 8.9 6.0 8.7 31.2 2.5 0.5 0.0 2.6 306 84.5 77.5 20.8 2.5 12.6 6.2 14.7 33.5 1.9 0.5 0.3 3.8 564 75.7 70.0 20.3 1.0 5.9 3.4 10.1 25.5 1.2 0.4 0.8 1.9 2,528 55.0 66.0 29.8 2.8 17.0 2.6 9.1 24.5 1.4 0.0 0.1 2.9 351 80.2 66.9 19.1 0.7 4.7 5.5 11.2 26.0 0.9 0.1 0.6 1.1 1,296 80.2 76.7 19.3 1.5 6.9 2.8 11.1 28.4 1.6 0.8 1.0 3.1 1,446 78.1 61.2 25.1 0.3 3.2 1.6 4.7 18.2 0.4 0.3 0.3 1.4 322 75.1 68.8 21.0 0.6 2.9 1.5 5.5 18.6 0.6 0.4 0.6 1.5 898 73.0 72.6 19.4 1.3 8.6 4.1 12.7 29.8 1.0 0.3 0.6 2.1 1,243 88.6 77.9 19.2 2.8 12.2 8.1 18.4 37.7 3.4 0.7 1.3 4.1 629 77.3 71.4 20.4 1.3 7.1 3.9 10.9 26.9 1.3 0.4 0.7 2.3 3,092 ___________________________________________________________________________________________________________________________ 1 Includes men who do not know AIDS and those who believe there is no way to avoid HIV/AIDS. of women and 37 percent of men cited sexual abstinence as a ways to prevent HIV/AIDS, compared with 67 percent (women) and 77 percent (men) in 2000. It may be that this sharp rise relates more to increased acceptance of sexual abstinence and condom use as feasible or socially practical behaviours than a change in “knowledge” per se. This underscores the difficulty in the collection and interpretation of data on AIDS prevention knowledge. In this case, complex and changing psychosocial contextual factors are embedded in this indicator called “knowledge”. 148 * AIDS and other STIs Table 11.3.1 Knowledge of programmatically important ways to avoid HIV/AIDS: women Percent distribution of women by knowledge of programmatically important ways to avoid HIV/AIDS, and percentage of women who know of two specific ways to avoid HIV/AIDS, according to background characteristics, Malawi 2000 _______________________________________________________________________________________ Knowledge of Specific ways to programmatically important avoid HIV/AIDS ways to avoid HIV/AIDS ____________________ __________________________ Limit Two number of Background One or three Use sexual characteristic None1 way ways Total condoms partners2 Number _______________________________________________________________________________________ Age 15-19 20-24 25-29 30-39 40-49 Marital status Married or living together Divorced, separated, widowed Never married Ever had sex Never had sex Residence Urban Rural Region Northern Central Southern Education No education Primary 1-4 Primary 5-8 Secondary+ Total 9.1 9.5 81.4 100.0 75.7 77.0 2,867 5.6 7.3 87.1 100.0 81.0 82.2 2,957 6.5 6.6 86.9 100.0 76.7 85.1 2,401 6.5 6.3 87.2 100.0 76.5 84.1 2,990 8.4 8.4 83.3 100.0 71.3 80.7 2,004 6.9 7.4 85.7 100.0 76.2 83.1 9,452 7.1 7.3 85.6 100.0 78.8 80.6 1,525 4.7 7.2 88.1 100.0 86.9 79.5 868 10.4 9.4 80.2 100.0 69.9 75.3 1,375 1.2 5.7 93.0 100.0 85.1 88.3 2,106 8.3 7.9 83.8 100.0 74.9 80.6 11,114 9.7 7.5 82.8 100.0 63.6 86.2 1,453 8.5 9.9 81.6 100.0 71.6 78.9 5,321 5.4 5.7 88.8 100.0 83.6 83.2 6,446 11.6 9.7 78.7 100.0 68.7 77.6 3,574 8.7 7.9 83.5 100.0 75.2 79.6 4,025 4.2 6.6 89.2 100.0 81.1 84.9 4,152 0.6 4.3 95.1 100.0 86.6 89.3 1,468 7.2 7.6 85.3 100.0 76.6 81.8 13,220 _______________________________________________________________________________________ Note: Programmatically important ways are abstaining from sex, using condoms, and limiting the number of sexual partners. Abstinence from sex is measured from a spontaneous response only, and using condoms and limiting the number of sexual partners is measured from spontaneous and probed responses. 1 Those who have not heard of AIDS or who do not know of any programmatically important ways to avoid HIV/AIDS. 2 Refers to limiting number of sexual partners, and limiting sex to one partner/staying faithful to one partner. AIDS and other STIs * 149 Table 11.3.2 Knowledge of programmatically important ways to avoid HIV/AIDS: men Percent distribution of men by knowledge of programmatically important ways to avoid HIV/AIDS, and percentage of men who know of two specific ways to avoid HIV/AIDS, according to background characteristics, Malawi 2000 _______________________________________________________________________________________ Knowledge of Specific ways to programmatically important avoid HIV/AIDS ways to avoid HIV/AIDS ____________________ __________________________ Limit Two number of Background One or three Use sexual characteristic None1 way ways Total condoms partners2 Number _______________________________________________________________________________________ Age 15-19 20-24 25-29 30-39 40-54 Marital status Married or living together Divorced, separated, widowed Never married Ever had sex Never had sex Residence Urban Rural Region Northern Central Southern Education No education Primary 1-4 Primary 5-8 Secondary+ Total 4.0 8.7 87.3 100.0 86.9 77.7 660 2.1 4.6 93.3 100.0 91.2 88.0 598 2.0 6.6 91.5 100.0 85.9 82.7 539 1.2 4.1 94.7 100.0 87.5 85.0 670 2.9 5.5 91.6 100.0 80.1 84.9 624 1.5 5.2 93.3 100.0 85.1 85.7 1,906 6.4 5.8 87.7 100.0 87.0 78.8 113 1.8 6.1 92.1 100.0 92.7 83.5 767 8.6 9.4 82.0 100.0 77.3 72.5 306 2.1 2.9 95.0 100.0 89.0 83.4 564 2.5 6.6 90.9 100.0 85.7 83.6 2,528 5.0 9.6 85.4 100.0 78.9 85.4 351 2.0 7.2 90.8 100.0 84.4 80.1 1,296 2.2 3.9 94.0 100.0 89.8 86.3 1,446 5.1 7.3 87.6 100.0 81.2 78.5 322 2.9 7.7 89.4 100.0 84.9 80.9 898 2.2 5.3 92.5 100.0 86.8 84.7 1,243 0.8 3.8 95.4 100.0 89.9 87.9 629 2.4 5.9 91.7 100.0 86.3 83.6 3,092 _______________________________________________________________________________________ Note: Programmatically important ways are abstaining from sex, using condoms, and limiting the number of sexual partners. Abstinence from sex is measured from a spontaneous response only, and using condoms and limiting the number of sexual partners is measured from spontaneous and probed responses. 1 Those who have not heard of AIDS or who do not know of any programmatically important ways to avoid HIV/AIDS. 2 Refers to limiting number of sexual partners, and limiting sex to one partner/staying faithful to one partner. 150 * AIDS and other STIs Table 11.4 Knowledge of HIV/AIDS-related issues Percentage of women and men by responses to questions on various HIV/AIDS-related issues, according to background characteristics, Malawi 2000 ______________________________________________________________________________________________________________________________ Women Men ____________________________________________________ ___________________________________________________ Percentage Percentage Percentage Percentage who say who say who say who say that a Percentage who say that they know that a Percentage who say that they know healthy- HIV/AIDS can be transmitted someone healthy- HIV/AIDS can be transmitted someone looking from mother to child personally looking from mother to child personally person ________________________ who person _____________________ who can have By has AIDS Number can have By has AIDS Number Background the AIDS During During breast- or died of the AIDS During During breast- or died of characteristic virus pregnancy delivery feeding of AIDS women virus pregnancy delivery feeding of AIDS men ______________________________________________________________________________________________________________________________ Age 15-19 20-24 25-29 30-39 40-49 (men, 40-54) Marital status Married or living together Divorced, separated, widowed Never married Ever had sex Never had sex Residence Urban Rural Region Northern Central Southern Education No education Primary 1-4 Primary 5-8 Secondary+ Total 81.5 55.2 50.5 53.2 67.6 2,867 86.8 59.2 51.4 51.5 71.3 660 85.5 68.3 64.4 67.4 71.2 2,957 90.6 71.0 62.5 61.8 84.2 598 86.3 68.2 65.5 67.2 75.2 2,401 95.0 76.8 66.4 67.2 83.3 539 85.9 69.7 67.7 69.1 74.5 2,990 93.9 73.3 66.8 66.4 82.2 670 81.8 67.2 64.4 68.0 73.3 2,004 92.6 72.9 61.5 64.4 87.2 624 84.5 68.2 64.9 67.5 74.0 9,452 93.5 73.8 65.2 65.7 84.5 1,906 85.4 66.6 66.1 68.0 69.4 1,525 94.3 63.7 50.5 56.2 79.6 113 87.3 61.6 58.7 59.2 70.3 868 91.1 70.6 61.8 62.5 80.8 767 79.6 48.9 43.1 45.9 64.5 1,375 81.1 51.0 42.2 40.5 64.5 306 95.1 77.1 74.2 74.0 78.0 2,106 96.2 78.8 70.6 59.0 82.0 564 82.3 63.4 60.1 63.0 71.1 11,114 90.7 68.5 59.5 62.8 81.3 2,528 82.8 71.9 68.6 68.2 86.6 1,453 83.2 68.8 62.4 64.0 85.6 351 80.5 61.3 56.3 61.1 77.2 5,321 91.9 71.3 62.0 64.7 85.8 1,296 87.8 67.7 65.9 67.0 64.9 6,446 93.6 69.9 61.0 59.3 76.6 1,446 77.3 58.8 56.6 60.1 64.9 3,574 86.6 60.5 55.1 61.2 75.5 322 81.5 61.6 58.2 63.2 72.2 4,025 89.8 65.6 56.5 63.4 80.7 898 88.4 70.8 66.1 67.8 75.9 4,152 92.2 71.3 60.6 62.9 82.8 1,243 97.5 78.7 76.8 71.9 79.9 1,468 95.9 80.3 73.8 59.0 83.0 629 84.3 65.6 62.3 64.8 72.2 13,220 91.7 70.4 61.5 62.1 81.5 3,092 11.2 KNOWLEDGE OF OTHER AIDS-RELATED ISSUES Table 11.4 shows the distribution of women and men by their responses to questions intended to evaluate important aspects of a person’s knowledge of HIV/AIDS. When asked whether a “healthy-looking person can have the AIDS virus,” 84 percent of women and 92 percent of men correctly responded “yes.” This represents an increase in knowledge from the 1996 MKAPH when 74 percent of women and 86 percent of men responded correctly to the same question. Women and men least likely to respond correctly to this question tended to be young, sexually inexperienced, rural, and less educated. AIDS and other STIs * 151 Table 11.5 Discussion of HIV/AIDS with spouse/partner Percent distribution of women and men who are currently married or living with a partner by whether they ever discussed the prevention of HIV/AIDS with their spouse/partner, according to background characteristics, Malawi 2000 ____________________________________________________________________________________________________ Women Men ______________________________________ ______________________________________ Has not Has not Background heard heard characteristic Yes No of AIDS Total Number Yes No of AIDS Total Number _________________________________________________________________________________________________ Age 15-19 20-24 25-29 30-39 40-49 (men, 40-54) Residence Urban Rural Region Northern Central Southern Education No education Primary 1-4 Primary 5-8 Secondary+ Total 65.5 33.3 1.3 100.0 934 61.6 38.4 0.0 100.0 23 73.1 25.6 1.2 100.0 2,324 88.0 11.9 0.0 100.0 236 75.4 23.8 0.7 100.0 2,102 85.5 14.1 0.1 100.0 441 73.1 26.1 0.7 100.0 2,505 87.0 12.8 0.2 100.0 622 69.4 29.4 1.2 100.0 1,587 84.8 15.0 0.2 100.0 584 80.5 19.1 0.4 100.0 1,362 85.6 14.2 0.1 100.0 307 70.9 28.0 1.1 100.0 8,089 85.8 13.9 0.2 100.0 1,599 74.3 25.2 0.6 100.0 1,075 93.9 5.8 0.3 100.0 217 72.6 26.4 1.0 100.0 3,919 87.3 12.4 0.3 100.0 775 71.5 27.4 1.1 100.0 4,458 82.5 17.3 0.0 100.0 914 61.9 36.0 2.0 100.0 2,975 74.2 25.2 0.4 100.0 265 70.4 28.8 0.9 100.0 2,980 82.7 16.8 0.2 100.0 565 80.8 19.0 0.2 100.0 2,784 90.3 9.6 0.1 100.0 737 90.0 9.9 0.2 100.0 713 90.0 10.0 0.0 100.0 338 72.3 26.8 1.0 100.0 9,452 85.8 14.0 0.2 100.0 1,906 The 2000 MDHS survey asked respondents whether they thought the AIDS virus can be transmitted from a mother to her child during pregnancy, and (in separate questions) during delivery and during breastfeeding. The results indicate that about two-thirds of both women and men responded “yes,” that they understood each of these three modes of mother-to-child transmission. Again, young, sexually inexperienced, rural, and less educated men and women were least likely to be informed about this important AIDS-related issue. The survey also asked the question, “Do you personally know someone who has the AIDS virus or who has died from AIDS?” The same question was asked in the 1996 MKAPH, allowing assessment of changes in the personal impact of the epidemic. In 1996, 71 percent of women and 68 percent of men responded that they knew someone with the AIDS virus or who died from AIDS; these figures increased to 72 percent and 82 percent in the 2000 MDHS survey. 11.3 STIGMA ASSOCIATED WITH AIDS AND ACCEPTABILITY OF AIDS-RELATED MESSAGES IN THE MEDIA In the 2000 MDHS survey, currently married women and men who had heard of AIDS were asked whether they had ever discussed AIDS prevention with their spouse/partner. Table 11.5 shows that 72 percent of women and 86 percent of men reported that they had had this discussion. Higher level of education is associated with greater communication between spouses about AIDS prevention. 152 * AIDS and other STIs Table 11.6.1 Social aspects of HIV/AIDS prevention and mitigation: women Among women who have heard of AIDS, the percentage who gave specific responses to questions on various social aspects of HIV/AIDS prevention and mitigation, by background characteristics, Malawi 2000 ___________________________________________________________________________________________________ Believes Believes the children HIV positive Believes an age 12-14 Believes status of HIV positive years should couples community Willing to coworker be taught should member care for should be to use have should be relatives allowed condoms Believes HIV test Number Background considered with AIDS to keep to avoid condoms before of characteristic confidential at home working AIDS are safe marriage women ___________________________________________________________________________________________________ Age 15-19 20-24 25-29 30-39 40-49 Current marital status Married or living together Divorced, separated, widowed Never married Ever had sex Never had sex Residence Urban Rural Region Northern Central Southern Education No education Primary 1-4 Primary 5-8 Secondary+ Total 25.5 91.5 47.4 54.7 76.5 89.2 2,817 25.8 93.2 50.8 60.1 80.3 92.5 2,928 24.4 94.1 51.2 56.6 77.5 91.8 2,385 26.1 95.4 47.6 53.4 74.4 92.4 2,969 27.4 94.2 45.7 48.6 69.2 89.0 1,977 25.5 93.5 47.6 55.1 75.7 91.2 9,370 28.6 96.0 50.2 58.5 78.9 92.0 1,507 25.2 95.4 55.5 63.3 86.1 93.3 859 25.1 90.9 49.7 45.6 67.9 88.2 1,340 34.2 97.5 65.8 60.5 77.0 94.2 2,101 24.2 92.9 45.4 54.0 75.8 90.5 10,974 30.0 94.4 38.7 42.5 47.2 92.0 1,444 18.5 91.7 42.5 50.5 73.1 88.8 5,265 30.9 95.1 56.0 61.6 84.9 92.8 6,367 27.1 90.4 44.1 51.5 73.4 86.8 3,496 25.0 92.0 41.9 53.4 76.2 89.9 3,971 25.4 96.1 51.0 56.3 76.8 94.3 4,143 26.0 98.8 71.2 64.5 79.0 95.8 1,466 25.8 93.6 48.7 55.1 76.0 91.1 13,076 Table 11.6 provides responses to questions that are intended to evaluate the level of stigma attached to AIDS, to persons living with HIV and AIDS (PLWHAs), and condoms. First, respondents were asked, “If a person learns that he or she is infected with the AIDS virus, should the person be allowed to keep this fact private or should this information be available to the community?” Just 26 percent of women and 17 percent of men thought that HIV-positive individuals should be allowed to keep their HIV status private. Fear of public disclosure has been implicated as an important barrier to HIV-testing and programmes aimed at assisting PLWHAs and their families. Programmes designed to assist in the support and care of AIDS-affected persons are hindered by fear of association with HIV and AIDS. The 2000 MDHS survey asked, “If a relative of yours became sick with AIDS would you be willing to care for her or him in your own household?” The majority of both women (94 percent) and men (96 percent) responded that they would be willing to take care of a relative who had AIDS. AIDS and other STIs * 153 Table 11.6.2 Social aspects of HIV/AIDS prevention and mitigation: men Among men who have heard of AIDS, the percentage who gave specific responses to questions on various social aspects of HIV/AIDS prevention and mitigation, by background characteristics, Malawi 2000 ___________________________________________________________________________________________________ Believes Believes the children HIV pos. Believes an age 12-14 Believes status of HIV pos. years should couples community Willing to coworker be taught should member care for should be to use have should be relatives allowed condoms Believes HIV test Number Background considered with AIDS to keep to avoid condoms before of characteristic confidential at home working AIDS are safe marriage men ___________________________________________________________________________________________________ Age 15-19 20-24 25-29 30-39 40-54 Current marital status Married or living together Divorced, separated, widowed Never married Ever had sex Never had sex Residence Urban Rural Region Northern Central Southern Education No education Primary 1-4 Primary 5-8 Secondary+ Total 20.5 92.6 46.2 58.0 85.8 91.2 654 16.4 95.7 53.5 68.7 85.7 95.2 597 15.4 97.6 60.2 70.8 84.1 93.6 538 13.4 97.2 55.8 66.3 82.3 94.2 670 17.5 96.7 51.2 61.6 79.9 94.3 623 15.4 96.7 53.2 66.1 82.5 95.1 1,905 20.9 99.0 49.4 75.5 88.4 92.9 111 18.1 96.1 56.2 65.1 87.9 93.1 765 19.4 89.2 46.3 52.1 77.2 86.5 300 19.5 96.4 71.4 63.3 79.7 91.5 564 16.0 95.8 49.0 65.2 84.4 94.2 2,517 19.7 93.9 37.6 56.2 70.8 95.4 348 12.6 95.7 49.9 67.2 82.1 94.5 1,293 19.6 96.5 59.8 64.8 87.8 92.4 1,440 16.7 92.8 41.1 65.5 81.8 92.2 319 19.0 94.0 44.0 64.3 86.3 92.9 891 16.1 96.9 53.3 64.9 84.2 95.3 1,242 14.4 98.2 71.8 65.0 79.1 92.2 629 16.7 95.9 53.1 64.8 83.5 93.7 3,081 Discrimination in the workplace against those infected with HIV is a human rights abuse and has the potential to further weaken the Malawian workforce. The survey asked respondents, “Should persons with the AIDS virus who work with other persons such as in a shop, office, or on a farm be allowed to continue their work or not?” The results indicate that 49 percent of women and 53 percent of men think that HIV-positive individuals should keep their right to work. Of course, this means that about one-half of adults harbour some level of stigma against HIV-infected persons. This attitude is more prevalent among less educated respondents (Figure 11.1) and those living in rural areas. It is proposed that, as a public health intervention, children should be introduced to AIDS prevention messages before they reach an age at which sexual activity typically begins. The 2000 MDHS survey asked men and women whether they thought “children age 12-14 years should be 154 * AIDS and other STIs taught about using a condom to avoid AIDS.” The results are mixed, with men more likely to accept the idea (65 percent) than women (55 percent). For women, higher educational level and residence in urban areas and in the Southern Region are associated with a more positive attitude toward early introduction of the notion of condom use to avoid AIDS. For men, differentials are minimal. The MDHS survey asked women and men whether they thought “condoms are safe to use.” The findings indicate that 76 percent of women and 84 percent of men think that condoms are safe, but certain population subgroups are more likely to believe that condoms are not safe to use (i.e., respondent who answered “no” or “depends” to the question). For example, less than one-half of women in the Northern Region believe condoms are safe. Young women who have not yet started sexual activity are also less likely to believe condoms are safe. This belief may well represent a barrier to condom use when these young women do start to have sex. The prevailing fears about condom safety need to be better understood. Given the growing awareness about HIV/AIDS and the potential for devastating impacts on families, it has been proposed that individuals planning to be married should be tested for HIV. The survey asked “Do you think that men and women who intend to marry should be tested for the AIDS virus before marriage?” The results indicate that the majority of women (91 percent) and men (94 percent) agree with the idea of premarital HIV-testing. AIDS and other STIs * 155 Table 11.7 Discussion of HIV/AIDS in the media Among women and men who have heard of AIDS, the percentage who think that discussion of AIDS in the media is acceptable, by media type and background characteristics, Malawi 2000 _____________________________________________________________________________________________ Women Men __________________________________ _________________________________ Number Number Background of of characteristic Radio TV Newspaper women Radio TV Newspaper men ______________________________________________________________________________________________ Age 15-19 20-24 25-29 30-39 40-49 (men, 40-54) Current marital status Married or living together Divorced, separated, widowed Never married Ever had sex Never had sex Residence Urban Rural Region Northern Central Southern Education No education Primary 1-4 Primary 5-8 Secondary+ Total 93.1 89.3 91.0 2,817 95.9 91.0 94.8 654 95.5 90.7 93.4 2,928 96.0 94.1 96.3 597 94.3 87.9 91.7 2,385 97.9 96.7 98.7 538 95.2 90.2 93.0 2,969 97.8 93.7 97.0 670 90.7 85.1 88.4 1,977 97.1 91.4 95.9 623 94.1 88.6 91.6 9,370 97.3 93.8 97.0 1,905 93.9 89.4 92.4 1,507 99.7 93.7 98.0 111 95.9 92.2 95.2 859 96.3 94.0 96.1 765 92.1 88.4 89.9 1,340 95.1 87.9 93.8 300 96.6 93.4 96.0 2,101 98.4 96.8 98.9 564 93.5 88.1 90.9 10,974 96.6 92.5 95.9 2,517 94.7 86.8 91.0 1,444 95.2 93.1 96.4 348 91.8 86.3 89.8 5,265 96.5 93.5 95.8 1,293 95.6 91.5 93.5 6,367 97.8 93.1 97.1 1,440 90.2 84.7 87.3 3,496 94.3 86.5 89.2 319 92.7 86.4 89.7 3,971 96.9 93.4 96.3 891 96.5 92.0 95.0 4,143 97.1 93.5 97.5 1,242 99.3 97.2 99.0 1,466 97.9 95.8 98.3 629 94.0 88.9 91.8 13,076 96.9 93.2 96.5 3,081 All men and women who knew of AIDS were asked to report whether they thought it was acceptable for AIDS-related messages to be broadcast on television and radio and to be published in newspapers. Table 11.7 shows that more than 90 percent of men reported that it is acceptable for AIDS to be discussed in each of these three media. Women were slightly less likely than men to accept AIDS-related messages in the media. 156 * AIDS and other STIs 11.4 TESTING FOR HIV MDHS respondents were asked whether they had ever been tested for HIV or the AIDS virus. If they said that they had not, respondents were then asked whether they would like to be tested. If they said they would like to be tested, respondents were asked whether they knew of a specific place where they could go to get the test for the AIDS virus. It should be understood that responses to these questions do not necessarily represent experiences with voluntary counseling and testing (VCT) services. Further, we do not know from the survey data whether respondents received the results of the tests that were reported to have occurred. Last, the data on desire to be tested do not necessarily reflect a person’s likelihood of actually pursuing HIV-testing options. Table 11.8 shows that 9 percent of women and 15 percent of men reported that they had already been tested for HIV, with urban men and women, those with more education, and those in peak reproductive years (age 20-39) experiencing the highest levels of HIV-testing. The overall desire or demand to be tested includes both those who responded that they have not yet been tested but would like to be tested (i.e., unmet demand) and those who have already been tested (i.e., met demand). In this approach, columns 1 and 2 of Table 11.8 can be added together to get a rough estimate of the total demand for HIV-testing. For instance, 81 percent of women and 87 percent of men have a need or demand to be tested (see Figure 11.2). Just 9 percent of women had already had the test, meaning that 10 percent of demand has been satisfied. The corresponding figure for men is better, 17 percent. The same approach can be used across background characteristics of the population. For example, 5 percent of HIV-testing demand is satisfied among women who have never been to school, compared with 23 percent among women with more than a secondary school education. Among men living in urban areas of Malawi, 26 percent of demand for testing is being met, compared with just 16 percent among men in rural areas. Among respondents who reported that they had been tested for the AIDS virus, 58 percent of women and 49 percent of men said that they were tested at a public facility such as a government-run hospital or clinic. Thirty percent of women and 38 percent of men report that they were tested at a private facility. Eight percent of women and 10 percent of men said that they were tested for HIV at Macro, an organization providing voluntary HIV counseling and testing services at sites located only in Blantyre and Lilongwe (as of the survey date). The remainder reported that they were tested at other places, including BLM (Banja La Mtsogolo) centres. Of respondents who reported not having been tested, 67 percent of women and 76 percent of men said that they knew of a place where they could be tested if they so desired. Knowledge of a testing site is lower among women and men who live in rural areas, among those who have not started sexual activity, and especially among those who have had less formal schooling, compared with other women and men. AIDS and other STIs * 157 Ta bl e 11 .8 .1 T es tin g fo r H IV : w om en Pe rc en t d ist rib ut io n of w om en b y w he th er te st ed fo r H IV a nd , i f n ot , b y de sir e to b e te st ed ; p er ce nt d ist rib ut io n of w om en w ho h av e be en te st ed b y so ur ce o f t es tin g, a nd p er ce nt ag e of w om en w ho h av e no t b ee n te st ed w ho k no w a s ou rc e fo r t he te st , a cc or di ng to b ac kg ro un d ch ar ac te ris tic s, M al aw i 2 00 0 __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ N ot te st ed __ __ __ __ __ __ __ __ __ __ __ __ _ N ot te st ed Pe rc en t Pe rc en t D on ’t __ __ __ __ __ __ __ _ w ho w an t w ho d on ’t kn ow if Am on g th os e te st ed , s ou rc e of te st in g Kn ow s Pe rc en t to b e w an t t o th ey w an t _ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ _ so ur ce Ba ck gr ou nd te st ed te st ed be te st ed to b e Pu bl ic Pr iv at e fo r a ch ar ac te ris tic fo r H IV fo r H IV fo r H IV te st ed 1 To ta l N um be r fa ci lit y fa ci lit y BL M 2 M ac ro 3 O th er To ta l N um be r te st N um be r __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ _ Ag e 1 5- 19 2 0- 24 2 5- 29 3 0- 39 4 0- 49 C ur re nt m ar ita l s ta tu s M ar rie d or li vi ng to ge th er D iv or ce d, s ep ar at ed , w id ow ed N ev er m ar rie d Ev er h ad s ex N ev er h ad s ex Re si de nc e U rb an R ur al Re gi on N or th er n C en tra l S ou th er n Ed uc at io n N o ed uc at io n P rim ar y 1- 4 P rim ar y 5- 8 S ec on da ry + To ta l 6. 4 74 .1 17 .0 2. 6 10 0. 0 2, 86 7 53 .8 33 .2 2. 0 10 .8 0. 2 10 0. 0 18 3 65 .8 2, 68 4 11 .8 73 .1 12 .9 2. 1 10 0. 0 2, 95 7 59 .3 27 .4 2. 6 10 .6 0. 2 10 0. 0 34 9 71 .7 2, 60 8 10 .6 73 .4 13 .6 2. 5 10 0. 0 2, 40 1 59 .0 28 .1 4. 3 7. 6 1. 0 10 0. 0 25 4 69 .5 2, 14 7 7. 8 73 .3 17 .1 1. 8 10 0. 0 2, 99 0 58 .3 33 .3 1. 5 5. 7 1. 2 10 0. 0 23 2 68 .1 2, 75 8 5. 2 67 .7 24 .1 3. 0 10 0. 0 2, 00 4 55 .2 35 .1 2. 8 5. 0 1. 9 10 0. 0 10 4 59 .5 1, 90 1 9. 0 72 .4 16 .4 2. 3 10 0. 0 9, 45 2 57 .7 32 .9 2. 7 6. 2 0. 5 10 0. 0 84 9 67 .0 8, 60 3 9. 4 71 .4 17 .0 2. 2 10 0. 0 1, 52 5 65 .0 21 .4 2. 0 8. 9 2. 6 10 0. 0 14 4 67 .6 1, 38 1 8. 8 75 .7 13 .4 2. 0 10 0. 0 86 8 48 .7 21 .2 2. 7 26 .6 0. 8 10 0. 0 77 74 .0 79 2 3. 8 73 .6 19 .0 3. 5 10 0. 0 1, 37 5 51 .4 28 .1 3. 8 16 .7 0. 0 10 0. 0 53 64 .4 1, 32 2 16 .9 67 .0 14 .4 1. 7 10 0. 0 2, 10 6 52 .7 24 .4 2. 5 19 .9 0. 5 10 0. 0 35 6 80 .4 1, 75 0 6. 9 73 .7 16 .9 2. 5 10 0. 0 11 ,1 14 60 .1 33 .2 2. 7 3. 1 0. 9 10 0. 0 76 6 65 .0 10 ,3 48 8. 7 76 .2 13 .0 2. 1 10 0. 0 1, 45 3 71 .5 25 .5 2. 1 0. 3 0. 7 10 0. 0 12 6 70 .6 1, 32 7 7. 3 72 .0 18 .7 2. 1 10 0. 0 5, 32 1 55 .9 30 .4 3. 5 9. 5 0. 6 10 0. 0 38 9 66 .6 4, 93 2 9. 4 72 .3 15 .6 2. 7 10 0. 0 6, 44 6 56 .1 31 .5 2. 2 9. 4 0. 9 10 0. 0 60 7 67 .1 5, 83 9 4. 0 69 .6 22 .4 4. 1 10 0. 0 3, 57 4 58 .4 38 .7 0. 0 1. 0 1. 8 10 0. 0 14 3 54 .0 3, 43 1 7. 1 71 .8 18 .6 2. 5 10 0. 0 4, 02 5 56 .9 36 .7 3. 4 2. 3 0. 8 10 0. 0 28 5 62 .0 3, 74 0 9. 5 77 .8 11 .6 1. 1 10 0. 0 4, 15 2 63 .5 27 .6 2. 3 6. 3 0. 4 10 0. 0 39 4 77 .1 3, 75 9 20 .5 67 .3 10 .8 1. 5 10 0. 0 1, 46 8 50 .7 24 .3 3. 7 20 .6 0. 7 10 0. 0 30 0 91 .8 1, 16 8 8 .5 72 .6 16 .5 2. 4 10 0. 0 13 ,2 20 57 .8 30 .4 2. 7 8. 4 0. 8 10 0. 0 1, 12 2 67 .3 12 ,0 98 __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ _ 1 In cl ud es th os e w ho h av e ne ve r h ea rd o f A ID S 2 Ba nj a La M ts og ol o, fa m ily p la nn in g cl in ic 3 Vo lu nt ar y co un se lli ng a nd H IV te st in g ce nt re s. 158 * AIDS and other STIs Ta bl e 11 .8 .2 T es tin g fo r H IV : m en Pe rc en t d ist rib ut io n of m en b y w he th er te ste d fo r H IV a nd , i f n ot , b y de sir e to b e te st ed ; p er ce nt d ist rib ut io n of m en w ho h av e be en te st ed b y so ur ce o f t es tin g, a nd p er ce nt ag e of m en w ho ha ve n ot b ee n te st ed w ho k no w a s ou rc e fo r t he te st , a cc or di ng to b ac kg ro un d ch ar ac te ris tic s, M al aw i 2 00 0 __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ N ot te st ed __ __ __ __ __ __ __ __ __ __ __ __ _ N ot te st ed Pe rc en t Pe rc en t D on ’t __ __ __ __ __ __ __ _ w ho w an t w ho d on ’t kn ow if Am on g th os e te st ed , s ou rc e of te st in g Kn ow s Pe rc en t to b e w an t t o th ey w an t _ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ _ so ur ce Ba ck gr ou nd te st ed te st ed be te st ed to b e Pu bl ic Pr iv at e fo r a ch ar ac te ris tic fo r H IV fo r H IV fo r H IV te st ed 1 To ta l N um be r fa ci lit y fa ci lit y BL M 2 M ac ro 3 O th er To ta l N um be r te st N um be r __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ _ Ag e 1 5- 19 2 0- 24 2 5- 29 3 0- 39 4 0- 54 C ur re nt m ar ita l s ta tu s M ar rie d or li vi ng to ge th er D iv or ce d, s ep ar at ed , w id ow ed N ev er m ar rie d Ev er h ad s ex N ev er h ad s ex Re si de nc e U rb an R ur al Re gi on N or th er n C en tra l S ou th er n Ed uc at io n N o ed uc at io n P rim ar y 1- 4 P rim ar y 5- 8 S ec on da ry + To ta l 6. 6 79 .8 11 .5 2. 1 10 0. 0 66 0 45 .7 42 .7 1. 3 9. 6 0. 7 10 0. 0 43 71 .9 61 7 17 .8 73 .8 7. 8 0. 6 10 0. 0 59 8 41 .6 36 .3 9. 3 12 .3 0. 4 10 0. 0 10 6 81 .6 49 2 23 .7 65 .2 10 .3 0. 9 10 0. 0 53 9 49 .7 36 .2 1. 2 12 .8 0. 0 10 0. 0 12 8 78 .7 41 2 18 .0 70 .0 11 .3 0. 7 10 0. 0 67 0 49 .6 42 .3 1. 6 6. 6 0. 0 10 0. 0 12 0 77 .9 55 0 11 .6 71 .3 15 .5 1. 6 10 0. 0 62 4 59 .8 32 .7 1. 5 5. 5 0. 4 10 0. 0 72 72 .2 55 2 17 .8 69 .7 11 .7 0. 8 10 0. 0 1, 90 6 53 .2 36 .4 2. 2 8. 1 0. 1 10 0. 0 33 9 76 .0 1, 56 8 15 .6 73 .0 8. 6 2. 8 10 0. 0 11 3 46 .3 53 .7 0. 0 0. 0 0. 0 10 0. 0 18 70 .0 95 12 .6 76 .9 9. 5 0. 9 10 0. 0 76 7 37 .8 37 .3 6. 3 18 .0 0. 6 10 0. 0 97 81 .3 67 0 5. 7 75 .9 14 .7 3. 8 10 0. 0 30 6 33 .9 52 .6 8. 3 4. 2 0. 9 10 0. 0 17 66 .2 28 8 21 .9 62 .6 14 .5 0. 9 10 0. 0 56 4 49 .3 25 .6 2. 2 22 .3 0. 6 10 0. 0 12 4 91 .2 44 0 13 .7 74 .4 10 .6 1. 3 10 0. 0 2, 52 8 48 .9 42 .2 3. 6 5. 2 0. 1 10 0. 0 34 6 73 .1 2, 18 1 20 .5 66 .4 11 .8 1. 4 10 0. 0 35 1 62 .1 32 .5 2. 1 3. 0 0. 4 10 0. 0 72 72 .9 27 9 14 .1 74 .1 11 .3 0. 5 10 0. 0 1, 29 6 48 .2 35 .8 5. 2 10 .7 0. 0 10 0. 0 18 3 73 .3 1, 11 3 14 .9 72 .0 11 .2 1. 9 10 0. 0 1, 44 6 45 .4 41 .4 1. 9 11 .0 0. 4 10 0. 0 21 6 79 .3 1, 23 0 5. 5 79 .0 13 .5 1. 9 10 0. 0 32 2 77 .8 16 .4 0. 0 5. 7 0. 0 10 0. 0 18 61 .6 30 4 11 .4 75 .6 11 .0 2. 0 10 0. 0 89 8 42 .9 47 .7 6. 4 3. 0 0. 0 10 0. 0 10 2 67 .6 79 6 15 .1 74 .4 9. 7 0. 8 10 0. 0 1, 24 3 50 .5 40 .3 2. 8 6. 3 0. 0 10 0. 0 18 7 78 .6 1, 05 6 25 .9 59 .5 14 .0 0. 6 10 0. 0 62 9 48 .0 31 .2 2. 0 18 .1 0. 6 10 0. 0 16 3 94 .5 46 6 15 .2 72 .2 11 .3 1. 2 10 0. 0 3, 09 2 49 .0 37 .9 3. 2 9. 7 0. 2 10 0. 0 47 0 76 .1 2, 62 2 __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ _ 1 In cl ud es th os e w ho h av e ne ve r h ea rd o f A ID S 2 Ba nj a La M ts og ol o, fa m ily p la nn in g cl in ic 3 Vo lu nt ar y co un se lli ng a nd H IV te st in g ce nt re s. AIDS and other STIs * 159 MDHS 2000 Figure 11.2 Percentage of Respondents with a Need (Met and Unmet) for HIV-Testing Services, by Sex and (among Women) by Level of Education 9 15 4 7 10 21 73 72 70 72 78 67 All Women All Men WOMEN'S EDUCATION No education Primary 1-4 Primary 5-8 Secondary+ Already tested Not tested, wants to be tested 81 87 74 79 87 88 11.5 REPORTS ON RECENT SEXUALLY TRANSMITTED INFECTIONS The 2000 MDHS survey asked respondents whether they had had a sexually transmitted infection (other than HIV/AIDS) in the last 12 months. They were also asked whether they had experienced a genital sore or ulcer and whether they had any genital discharge in the past 12 months. These symptoms have been shown useful in identifying STIs in men; they are less easily interpreted in women since women are likely to experience more non-STI conditions of the reproductive tract that produce a discharge. Further, STIs in women may often not produce symptoms that can be easily recognised. Last, reporting of STIs and recognised STI symptoms is subject to a downward bias (i.e., underreporting) due to the social stigma attached to STIs. Table 11.9 shows that about 1 percent of women and 2 percent of men reported an STI in the past 12 months, which suggests underreporting of STIs especially among women. However, when asked whether they had experienced a genital discharge in the last 12 months, 5 percent of women and 4 percent of men reported that they had. Further, 8 percent of women and 4 percent of men reported a genital sore or ulcer. The finding of 8 percent of women reporting a genital sore or ulcer is significant in the context of evidence that sores or ulcers (whether resulting from an STI or not) may facilitate transmission of HIV, especially if left untreated. When all reports of ulcers and sores, discharge, and STIs are combined into one index, the MDHS survey findings indicate that 11 percent of women and 8 percent of men had some type of STI in the last 12 months. Among men, a clear age pattern to STI reports exists, with young men at much higher risk than older men. Among women, the reverse appears to be true but the pattern is not pronounced. STIs are more prevalent in urban areas among men but in rural areas among women. No clear pattern of STI reports is found across education categories, although reports of 4 The 2000 MDHS questions on HIV and AIDS are based on improvements recommended in the Joint United Nations Programme on HIV/AIDS guidelines for Monitoring and Evaluation of HIV/AIDS Programmes (UNAIDS, 2000). 160 * AIDS and other STIs Table 11.9.1 Self-reporting of sexually transmitted infections and STI symptoms: women Among women who ever had sex, the percentage self-reporting an STI (other than HIV/AIDS) and/or associated symptoms in the 12 months preceding the survey, by background characteristics, Malawi 2000 ___________________________________________________________________________________________ Percentage Percentage Percentage with STI, or with with discharge or Background Percentage genital genital sore genital characteristic with an STI discharge or ulcer sore/ulcer Number ___________________________________________________________________________________________ Age 15-19 20-24 25-29 30-39 40-49 Current marital status Married or living together Divorced, separated, widowed Never married Residence Urban Rural Region Northern Central Southern Education No education Primary 1-4 Primary 5-8 Secondary+ Alcohol consumption (last 3 mos.)1 Has not been drunk Has been drunk Total 0.9 3.9 5.2 8.4 1,643 1.2 4.0 7.8 10.4 2,830 1.1 4.9 8.8 11.6 2,383 1.6 6.2 9.9 13.2 2,988 1.3 4.5 7.2 9.9 2,001 1.2 4.9 8.2 11.3 9,452 1.4 5.2 8.9 11.5 1,525 1.1 3.3 4.7 6.8 868 1.2 2.7 6.7 8.1 1,834 1.3 5.2 8.3 11.5 10,011 1.7 3.4 2.5 5.6 1,284 1.5 5.3 8.1 11.6 4,706 1.0 4.7 9.2 11.6 5,855 1.2 3.9 7.2 9.3 3,505 1.3 6.0 10.2 13.7 3,616 1.3 4.7 7.5 10.7 3,535 1.2 4.2 5.7 8.2 1,189 1.2 4.8 8.1 11.0 11,604 2.8 5.7 6.8 10.8 223 1.3 4.8 8.0 11.0 11,845 ___________________________________________________________________________________________ 1 Total includes 18 women with missing values for alcohol consumption. an STI among men increases markedly with increasing educational level, which may reflect better recognition and diagnosis among men with greater access to and use of health services. Among both men and women, lower levels of STIs were reported in the Northern Region than in the Central and Southern regions. Some questions on STIs were asked in the 1996 MKAPH, but most are not comparable to the questions used in the 2000 MDHS survey.4 One indicator that is reasonably comparable is the self-reports by men of urethral discharge. In the 1996 MKAPH, 5 percent of men reported a AIDS and other STIs * 161 Table 11.9.2 Self-reporting of sexually transmitted infections and STI symptoms: men Among men who ever had sex, the percentage self-reporting an STI (other than HIV/AIDS) and/or associated symptoms in the 12 months preceding the survey, by background characteristics, Malawi 2000 ___________________________________________________________________________________________ Percentage Percentage Percentage with STI, or with with discharge or Background Percentage genital genital sore genital characteristic with an STI discharge or ulcer sore/ulcer Number ___________________________________________________________________________________________ Age 15-19 20-24 25-29 30-39 40-54 Current marital status Married or living together Divorced, separated, widowed Never married Residence Urban Rural Region Northern Central Southern Education No education Primary 1-4 Primary 5-8 Secondary+ Alcohol consumption (last 3 months) Has not been drunk Has been drunk Total 1.7 7.5 6.1 13.3 404 2.1 5.3 4.8 9.5 558 3.5 4.4 3.7 8.9 534 2.8 3.5 5.4 8.5 668 0.9 0.7 2.6 3.7 623 1.9 2.5 4.0 6.6 1,906 8.0 7.6 8.7 18.3 113 2.1 7.1 4.9 11.3 767 7.1 6.2 5.5 12.2 494 1.2 3.5 4.2 7.6 2,292 2.2 3.9 2.7 6.7 301 0.7 3.7 4.0 7.5 1,147 3.5 4.3 5.2 9.5 1,339 0.9 3.0 3.5 6.3 314 1.2 4.8 5.2 9.4 798 2.3 3.6 4.8 8.8 1,100 4.1 4.2 3.2 7.4 574 2.0 3.9 4.3 8.4 2,158 3.1 4.3 4.9 8.5 627 2.2 4.0 4.4 8.4 2,786 discharge, compared with 4 percent in the 2000 MDHS survey. This difference is small and should not be overinterpreted, because it falls within the bounds of statistical (sampling) error. In the 2000 MDHS survey, women and men were asked to report on their alcohol drinking habits and whether and how often they became “drunk” in the last three months. It is thought that drinking, especially excessive drinking, increases the likelihood of risky sexual behaviour that could lead to STIs. The findings indicate that the relationship between reported recent drinking behaviour and reports of recent STIs is not a strong one. For both women and men, respondents were indeed more likely to have reported an STI in the last 12 months if they reported having been “drunk”, but the difference is small. The reports of STI symptoms, discharge, or sore or ulcer, also do not differ much between categories of drinking behaviour. 162 * AIDS and other STIs Table 11.10.1 Source of treatment of STIs: women Percentage of women who reported an STI (other than HIV/AIDS) and/or associated symptoms in the 12 months preceding the survey, by source of treatment or advice and background characteristics, Malawi 2000 ___________________________________________________________________________________________________ Advice or Advice or Clinic medicine Advice treatment hospital from from from No Number Background or private Traditional pharmacy friends or any advice or of characteristic doctor healer or shop relatives source1 treatment women ___________________________________________________________________________________________________ Age 15-19 20-24 25-29 30-39 40-49 Current marital status Married or living together Divorced, separated, widowed Never married Residence Urban Rural Region Northern Central Southern Education No education Primary 1-4 Primary 5-8 Secondary+ Total 16.9 28.5 16.7 33.8 55.2 41.8 137 22.3 34.2 15.4 36.4 64.5 34.6 293 26.0 33.0 12.2 36.3 64.9 34.5 276 21.8 28.2 13.5 26.9 56.8 41.0 393 21.2 37.6 10.3 30.1 59.5 39.4 199 21.3 31.4 13.7 30.2 59.1 39.8 1,064 24.1 38.0 10.6 38.0 64.3 31.6 175 33.5 26.6 19.0 52.1 74.8 25.2 59 39.8 28.6 19.6 35.0 77.4 22.1 149 19.9 32.5 12.7 31.9 58.3 40.1 1,149 35.0 36.3 15.5 45.9 64.3 35.3 72 21.4 28.0 9.7 26.5 53.6 45.9 544 21.5 34.9 16.3 35.5 65.6 32.0 681 16.6 35.7 10.7 27.8 58.8 40.9 326 18.2 34.5 13.3 32.4 58.9 39.0 496 24.7 28.5 15.9 34.5 59.4 39.2 378 51.5 21.6 14.4 38.2 78.7 18.5 98 22.2 32.1 13.5 32.3 60.5 38.0 1,298 ___________________________________________________________________________________________________ 1 Based on columns 1-4 of this table. 11.6 TREATMENT-SEEKING AND OTHER BEHAVIOURS IN RESPONSE TO STIS If respondents reported an STI or an STI symptom (i.e., discharge or sore or ulcer) in the past 12 months, they were asked questions on their actions in response to the illness or symptom. Table 11.10 presents information on the 1,298 women and 234 men who reported an STI or STI symptom in the last 12 months. Men and women were equally likely to have reported that they sought some type of treatment or advice (women, 61 percent; men, 60 percent). A small male- female difference does emerge, however, when looking specifically at whether a health facility was attended (men, 28 percent; women, 22 percent). The low use of health facilities to seek treatment of reported STIs and STI symptoms among both men and women suggests either overreporting of STIs (not likely) or that large numbers of persons are not receiving adequate treatment for their STIs. The pattern of reports indicates lower levels of access and use of STI treatment services especially in Malawi’s rural, less educated population. AIDS and other STIs * 163 Table 11.10.2 Source of treatment of STIs: men Percentage of men who reported an STI (other than HIV/AIDS) and/or associated symptoms in the 12 months preceding the survey, by source of treatment or advice and background characteristics, Malawi 2000 ___________________________________________________________________________________________________ Advice or Advice or Clinic medicine Advice treatment hospital from from from No Number Background or private Traditional pharmacy friends or any advice or of characteristic doctor healer or shop relatives source1 treatment men ___________________________________________________________________________________________________ Age 15-19 20-24 25-29 30-39 40-54 Current marital status Married or living together Divorced, separated, widowed Never married Residence Urban Rural Region Northern Central Southern Education No education Primary 1-4 Primary 5-8 Secondary+ Total 11.6 16.5 22.0 22.0 42.1 57.9 54 31.0 16.0 15.8 22.1 56.9 43.1 53 38.6 18.3 28.4 31.8 63.7 36.3 47 29.1 35.1 35.6 22.7 68.7 29.0 57 * * * * * * 23 29.3 30.7 29.6 28.6 66.8 31.5 126 (46.7) (31.6) (22.1) (14.0) (65.8) (34.2) 21 22.8 11.6 20.9 23.7 47.3 52.7 87 49.8 30.5 46.5 33.1 86.9 13.1 60 21.0 21.3 18.4 22.8 49.9 48.9 173 (35.6) (15.0) (48.2) (46.8) (88.1) (11.9) 20 25.1 6.0 24.8 25.3 40.8 57.7 86 29.5 37.0 22.7 22.2 67.6 31.7 127 * * * * * * 20 25.0 18.9 30.3 26.6 66.4 33.6 75 20.8 33.5 17.5 24.2 55.1 42.7 97 60.2 17.8 34.3 27.3 68.1 31.9 42 28.4 23.7 25.7 25.5 59.5 39.6 234 ___________________________________________________________________________________________________ ( ) Estimate based on 25-49 unweighted cases * Less than 25 unweighted cases; estimate has been suppressed. 1 Based on columns 1-4 of this table. A gender differential was observed in the type of response to STIs. In Malawi, men are apparently more likely than women to go to seek advice or buy medicines at a shop or pharmacy; women are more likely than men to consult a traditional healer or to seek advice from friends and relatives. Table 11.11 shows that 71 percent of women and 47 percent of men reporting an STI in the past year said that they had informed (all of) their partner(s). About one-quarter of women and nearly one-half of men said that they did not inform (any of) their partner(s). Respondents reporting an STI were also asked whether they had done something to avoid infecting their partner(s). The results indicate that 44 percent of women and 47 percent of men took some action. When asked what action they took, the most frequently mentioned action was abstinence from sex (36 percent, women; 38 percent, men). About one-quarter of women and men mentioned use of medicines. Just 6 percent of women and 12 percent of men said that they used condoms to prevent 164 * AIDS and other STIs Table 11.11.1 Efforts to protect partners from infection: women with STIs Percent distribution of women who had an STI (other than HIV/AIDS) and/or associated symptoms in the 12 months preceding the survey by whether they informed their partner(s) of their condition, and percentage who took action to protect their partner(s) from infection, according to background characteristics, Malawi 2000 _______________________________________________________________________________________________________________________________ Action taken to protect partner Informed partner(s) _______________________________________________________________________ Avoided Partner Number Background Some/ sexual Used Used Any No already of characteristic Yes not all No Missing Total relations condoms medicine action action infected women ______________________________________________________________________________________________________________________________ Age 15-19 20-24 25-29 30-39 40-49 Current marital status Married or living together Divorced, separated, widowed Never married Residence Urban Rural Region Northern Central Southern Education No education Primary 1-4 Primary 5-8 Secondary+ Total 65.5 0.3 34.2 0.0 100.0 37.4 14.1 26.5 48.0 50.4 0.2 137 69.5 1.3 26.7 2.5 100.0 36.2 7.6 30.8 46.8 49.9 0.5 293 78.8 0.3 19.9 1.0 100.0 41.8 6.8 32.8 49.0 48.2 1.3 276 71.5 0.7 25.8 2.0 100.0 33.0 2.3 27.3 40.3 54.1 3.0 393 67.7 0.7 29.4 2.3 100.0 31.3 2.8 27.3 38.3 57.5 0.7 199 77.3 0.6 20.2 1.9 100.0 36.7 4.7 29.7 45.4 50.5 1.4 1,064 44.3 1.2 53.3 1.2 100.0 31.0 6.5 28.1 35.0 62.7 1.9 175 45.3 0.6 54.1 0.0 100.0 34.6 22.4 23.4 49.1 47.6 0.0 59 79.5 0.2 19.8 0.5 100.0 43.1 15.2 38.0 56.3 39.6 2.3 149 70.3 0.8 27.0 1.9 100.0 34.8 4.6 28.0 42.5 53.6 1.3 1,149 66.9 0.5 26.0 6.6 100.0 33.8 10.5 23.6 38.3 56.1 0.4 72 70.4 1.3 26.0 2.3 100.0 26.2 4.2 21.2 33.2 63.4 0.4 544 72.7 0.2 26.4 0.7 100.0 43.7 6.6 36.1 53.4 42.5 2.4 681 71.4 0.6 26.7 1.2 100.0 35.7 1.3 32.4 43.3 53.6 1.8 326 73.0 0.7 24.4 1.9 100.0 37.1 3.6 29.1 42.8 53.1 1.3 496 70.6 1.0 26.2 2.2 100.0 35.4 9.0 27.4 45.4 49.9 1.2 378 66.0 0.0 33.7 0.3 100.0 30.9 19.3 25.5 48.5 49.0 1.3 98 71.4 0.7 26.2 1.7 100.0 35.8 5.8 29.2 44.1 52.0 1.4 1,298 infecting their partner(s). Respondents with a higher educational level and those living in urban areas were more likely to report using condoms. Part of the explanation for such low levels of protective action among respondents who reported STIs or STI symptoms may be that many of the reported STIs were not recognised as such. In addition, if the respondent’s partner introduced the infection into the partnership, the respondent would probably feel no reason to adopt protective actions. AIDS and other STIs * 165 Table 11.11.2 Efforts to protect partners from infection: men with STIs Percent distribution of men who had an STI (other than HIV/AIDS) and/or associated symptoms in the 12 months preceding the survey by whether they informed their partner(s) of their condition, and percentage who took action to protect their partner(s) from infection, according to background characteristics, Malawi 2000 ______________________________________________________________________________________________________________________________ Action taken to protect partner Informed partner(s) _______________________________________________________________________ Avoided Partner Number Background Some/ sexual Used Used Any No already of characteristic Yes not all No Missing Total relations condoms medicine action action infected men ______________________________________________________________________________________________________________________________ Age 15-19 20-24 25-29 30-39 40-54 Current marital status Married or living together Divorced, separated, widowed Never married Residence Urban Rural Region Northern Central Southern Education No education Primary 1-4 Primary 5-8 Secondary+ Total 23.9 2.6 73.5 0.0 100.0 29.6 16.6 21.4 36.8 63.2 0.0 54 41.0 2.7 53.2 3.1 100.0 22.4 14.1 26.8 44.2 52.1 0.5 53 44.4 3.0 50.3 2.3 100.0 45.1 14.6 30.7 54.1 37.9 4.1 47 64.5 3.8 31.4 0.3 100.0 50.7 7.6 19.7 53.2 39.0 7.5 57 79.6 0.0 18.3 2.1 100.0 43.0 4.8 23.6 51.4 43.0 4.9 23 61.3 2.8 33.8 2.0 100.0 47.0 11.0 27.5 56.2 37.8 3.6 126 (49.7) (0.0) (50.3) (0.0) 100.0) (38.7) (8.9) (21.0) (48.1) (38.3) (13.6) 21 26.2 3.2 69.6 0.9 100.0 23.4 15.0 20.4 34.4 64.4 0.3 87 50.7 7.1 41.1 1.1 100.0 47.2 19.1 39.8 67.6 27.1 4.7 60 46.0 1.2 51.2 1.6 100.0 34.2 9.9 18.9 40.3 54.9 2.7 173 (71.0) (0.0) (23.6) (5.4) 100.0 (59.7) (7.2) (21.4) (62.2) (20.1) (12.4) 20 44.5 1.6 52.5 1.3 100.0 31.0 8.4 16.0 35.5 62.2 0.0 86 45.3 3.9 49.8 0.9 100.0 38.5 15.7 30.4 53.1 42.2 4.0 127 * * * * 100.0 * * * * * * 20 46.9 1.8 50.2 1.1 100.0 41.3 10.7 23.2 48.5 50.4 0.0 75 47.6 0.0 49.9 2.5 100.0 34.6 11.4 23.4 42.9 50.7 3.4 97 44.0 11.9 43.8 0.4 100.0 38.3 19.3 29.1 57.3 34.9 7.4 42 47.3 2.7 48.6 1.4 100.0 37.5 12.3 24.3 47.4 47.7 3.2 234 ________________________________________________________________________________________________________________________________ ( ) Estimate based on 25-49 unweighted cases * Less than 25 unweighted cases; estimate has been suppressed. 11.7 NUMBER OF SEXUAL PARTNERS Given that most HIV infections in Malawi are contracted through heterosexual contact, information on sexual behaviour is important in designing and monitoring intervention programmes to control the spread of the disease. The 2000 MDHS survey included questions on the respondent’s last three sexual partners in the 12 months preceding the survey, with two broad partner types recognised: 1) those cohabiting with the respondent (mostly spouses) and 2) those not cohabiting with the respondent at the time of the last sexual encounter with that partner. For male respondents, the question was also asked whether they had paid for sex in the last 12 months. Information on use of condoms at last sexual encounter with each of these partner types was collected. In the context of HIV/AIDS/STI prevention, the analysis in the following section is limited to higher risk sexual activity. Based on UNAIDS guidelines for monitoring and evaluation of HIV/AIDS programmes, a working definition of higher risk sex is sex outside the context of a cohabiting relationship, which, in broad terms, means extramarital sex among married individuals and all sex for the unmarried. Although these definitions are far from ideal, evaluation of data from previous surveys indicates that a more precise formulation is impractical and produces data that are difficult to interpret. 166 * AIDS and other STIs Table 11.12 Number of sexual partners: married women and men Percent distribution of currently married women and men by number of persons with whom they had sexual intercourse in the past 12 months, excluding spouse or cohabiting partner, according to background characteristics, Malawi 2000 ____________________________________________________________________________________________________ Women Men __________________________________ _________________________________________ Number of sexual partners excluding Number of sexual partners excluding spouse or cohabiting partner spouse or cohabiting partner Background __________________________________ ________________________________________ characteristic 0 1 2+ Total Number 0 1 2+ Total Mean Number ____________________________________________________________________________________________________ Age 15-19 20-24 25-29 30-39 40-49 (men, 40-54) Residence Urban Rural Region Northern Central Southern Education No education Primary 1-4 Primary 5-8 Secondary+ Alcohol consumption (last 3 months)1 Has not been drunk Has been drunk Total 97.8 2.0 0.2 100.0 934 (70.6) (16.3) (13.1) 100.0 (0.4) 23 99.2 0.7 0.0 100.0 2,324 83.6 14.9 1.5 100.0 0.2 236 99.6 0.3 0.1 100.0 2,102 79.6 17.8 2.6 100.0 0.3 441 99.5 0.4 0.0 100.0 2,505 82.4 16.0 1.6 100.0 0.2 622 99.5 0.5 0.0 100.0 1,587 84.8 13.4 1.8 100.0 0.2 584 99.5 0.4 0.1 100.0 1,362 80.9 15.9 3.2 100.0 0.3 307 99.3 0.7 0.0 100.0 8,089 82.8 15.4 1.8 100.0 0.2 1,599 99.7 0.3 0.0 100.0 1,075 84.4 13.7 1.9 100.0 0.2 217 99.4 0.6 0.0 100.0 3,919 83.3 15.0 1.6 100.0 0.2 775 99.1 0.8 0.1 100.0 4,458 81.3 16.3 2.4 100.0 0.2 914 99.3 0.6 0.0 100.0 2,975 83.0 15.0 1.8 100.0 0.2 265 99.1 0.9 0.1 100.0 2,980 82.0 16.0 2.0 100.0 0.2 565 99.5 0.4 0.1 100.0 2,784 82.7 15.8 1.5 100.0 0.2 737 99.2 0.8 0.0 100.0 713 82.4 14.3 3.3 100.0 0.2 338 99.4 0.6 0.0 100.0 9,256 84.5 13.7 1.8 100.0 0.2 1,389 96.5 1.3 2.2 100.0 180 77.1 20.3 2.6 100.0 0.3 517 99.3 0.7 0.1 100.0 9,452 82.5 15.5 2.0 100.0 0.2 1,906 _________________________________________________________________________________________________ 1 Excludes 16 women with missing alcohol consumption information. ( ) Estimate based on 25-49 unweighted cases. MARRIED MEN AND WOMEN Table 11.12 shows the percent distributions of married women and men by number of persons with whom they had sex in the last 12 months, excluding spouse or cohabiting partner, according to background characteristics. These data indicate that men report having more sexual partners than women. Only 1 percent of currently married women reported extramarital sexual activity in the last 12 months, compared with 18 percent of married men. About 2 percent of married men reported two or more extramarital partners in the last year, while virtually no married women reported the same. Previous survey experience suggests that extramarital sex is probably underreported by women. Age-related, urban-rural, regional, and education-related differentials in the number of recent noncohabiting sexual partners reported by men are negligible. The MDHS survey asked male respondents to report on their drinking pattern over the last three months, including whether and AIDS and other STIs * 167 Table 11.13 Number of sexual partners: unmarried women and men Percent distribution of unmarried women and men who ever had sex, by number of persons with whom they had sexual intercourse in the 12 months preceding the survey, according to selected background characteristics, Malawi 2000 ____________________________________________________________________________________________________________ Women Men __________________________________________ _______________________________________ Number of sexual partners excluding Number of sexual partners excluding spouse or cohabiting partner spouse or cohabiting partner Background __________________________________________ ________________________________________ characteristic 0 1 2+ Total Mean Number 0 1 2+ Total Mean Number ______________________________________________________________________________________________________________ Age 15-19 20-24 25-29 30-39 40-49 (men, 40-54) Current marital status Divorced, separated, widowed Never married Residence Urban Rural Region Northern Central Southern Education No education Primary 1-4 Primary 5-8 Secondary+ Alcohol consumption (last 3 months)1 Has not been drunk Has been drunk Total 32.5 65.4 2.1 100.0 0.7 709 29.4 56.1 14.5 100.0 1.0 381 57.5 40.5 2.1 100.0 0.5 507 29.3 54.0 16.7 100.0 1.0 322 73.8 24.2 2.0 100.0 0.3 280 34.8 53.5 11.7 100.0 0.8 93 80.4 18.7 0.9 100.0 0.2 483 57.9 27.3 14.8 100.0 0.6 46 90.8 8.2 1.0 100.0 0.1 414 75.1 21.7 3.3 100.0 0.3 39 81.7 16.8 1.5 100.0 0.2 1,525 55.0 35.6 9.4 100.0 0.6 113 28.5 69.6 1.9 100.0 0.7 868 30.3 54.4 15.3 100.0 1.0 767 50.7 47.8 1.5 100.0 0.5 471 33.3 48.3 18.4 100.0 1.0 187 65.2 33.1 1.7 100.0 0.4 1,922 33.5 53.0 13.5 100.0 0.9 693 65.8 33.2 1.1 100.0 0.4 208 37.0 56.8 6.2 100.0 0.7 83 64.9 33.7 1.4 100.0 0.4 787 36.3 49.4 14.3 100.0 0.9 372 60.4 37.6 1.9 100.0 0.4 1,398 30.3 53.3 16.4 100.0 1.0 425 83.7 15.5 0.8 100.0 0.2 530 56.2 34.6 9.1 100.0 0.5 49 65.5 32.5 2.0 100.0 0.4 636 34.8 48.6 16.6 100.0 0.9 233 54.1 43.7 2.2 100.0 0.5 751 27.7 57.2 15.2 100.0 1.0 363 47.5 51.2 1.3 100.0 0.5 476 36.3 51.1 12.7 100.0 0.9 235 62.7 35.8 1.5 100.0 0.4 2,334 35.6 51.7 12.7 100.0 0.8 724 49.7 40.7 9.6 100.0 0.7 53 23.6 53.3 23.0 100.0 1.2 156 62.4 36.0 1.7 100.0 0.4 2,393 33.4 52.0 14.5 100.0 0.9 880 ___________________________________________________________________________________________________________ 1 Excludes 6 women with missing alcohol consumption information. how often they got drunk. The findings indicate that married men who have gotten drunk in the last three months are more likely to have engaged in extramarital sexual activity (23 percent) than men who have not recently gotten drunk (16 percent). UNMARRIED MEN AND WOMEN Among unmarried men who have ever had sex, 67 percent had some sexual activity in the previous 12 months—about one-quarter of these reported two or more partners (Table 11.13). Unmarried women reported considerably less sexual activity than unmarried men. About 38 percent of the unmarried women who have ever had sex reported having had at least one sexual partner in the last year. Of those women who did report recent sexually activity, a much smaller percentage reported sex with more than one partner than men did (5 percent versus 22 percent). 168 * AIDS and other STIs More than two-thirds of unmarried women age 15-19 who have ever had sex reported at least one partner in the last 12 months; 2 percent have had two or more partners. The percentage of sexually active unmarried women goes down with increasing age to just 9 percent in the age group 40-49 years. This general pattern is seen among men as well. One in six unmarried men age 20-24 reported having two or more partners—a pattern of behaviour that places them at high risk of infection with HIV and other STIs. Residence in the Southern Region and higher levels of education are associated with higher levels of sexual activity in unmarried individuals. Unmarried women in urban areas are more likely to be sexually active than their rural counterparts. This is not true among men, but of those who are sexually active, urban men are more likely than rural men to have multiple partners. Among both women and men, having been drunk at least once in the last three months is strongly related to high-risk sexual activity. Twenty-three percent of unmarried men who reported that they got drunk recently had two or more partners in the last 12 months, compared with 13 percent of men who did not get drunk recently. The percentage of women who reported that they got drunk recently is small; however, the data suggest that women who engage in excessive drinking are also more likely to have multiple sex partners. 11.8 PAYMENT FOR SEXUAL RELATIONS Male respondents in the 2000 MDHS survey were asked whether they had paid money in exchange for sex in the last 12 months. Among men who have ever had sex, 21 percent reported paying for sex in the last 12 months (Table 11.14). Married men were almost as likely (20 percent) as unmarried men (21 percent) to have recently paid for sex. There is substantial variation in commercial sex differentials across population subgroups. Urban residence is associated with greater likelihood of having paid for sex among married men, but a smaller likelihood among unmarried men. Men in the Northern Region are much less likely to have engaged in commercial sex (9 percent) than in the Central Region (13 percent) and the Southern Region (30 percent). Men who have been drunk at least once in the last three months are more likely to have engaged in commercial sex (24 percent) than men who have not been drunk (19 percent). 11.9 KNOWLEDGE OF A SOURCE FOR CONDOMS Because of the important role that the condom plays in combating the transmission of HIV, respondents were asked if they know where they could be obtained. If they reported knowing a source and could cite a specific source, they were asked whether they could actually get a condom if they wanted to get one. This last question was intended to ascertain the level of personal access to condoms as opposed to having passing knowledge. Table 11.15 shows that 77 percent of women and 87 percent of men could cite a place where they could obtain a condom. This compares with 71 percent (women) and 89 percent (men) reported from the 1996 MKAPH. Knowledge of a source for condoms varies widely, with the lowest levels among men and women who are less educated and those living in rural areas. When asked whether they could actually get a condom, 57 percent of women and 79 percent of men reported that they could. An important and troubling finding is that more than half of women and more AIDS and other STIs * 169 Table 11.14 Payment for sexual relations Among men who have ever had sexual intercourse, percentage who paid for sex in the 12 months preceding the survey, by marital status and background characteristics, Malawi 2000 _________________________________________________________________________________________ Currently married Not currently married All Background __________________ __________________ __________________ characteristic Percent Number Percent Number Percent Number _________________________________________________________________________________________ Age 15-24 25-34 35-54 Residence Urban Rural Region Northern Central Southern Education No education Primary 1-4 Primary 5-8 Secondary+ Alcohol consumption (last 3 months) Has not been drunk Has been drunk Total 17.5 259 21.9 702 20.7 962 20.9 749 18.4 113 20.6 862 20.5 898 16.7 65 20.3 963 29.6 307 17.1 187 24.9 494 18.5 1,599 22.1 693 19.6 2,292 9.3 217 9.2 83 9.3 301 12.3 775 13.4 372 12.7 1,147 29.7 914 30.0 425 29.8 1,339 20.6 265 18.3 49 20.2 314 20.0 565 28.7 233 22.6 798 19.6 737 20.9 363 20.0 1,100 21.9 338 14.2 235 18.7 574 19.1 1,389 20.1 724 19.4 2,114 23.5 517 25.2 156 23.9 673 20.3 1,906 21.0 880 20.5 2,786 than one-quarter of men in the age group 15-19 reported that they could not get a condom themselves if they wanted to. Respondents living in rural areas, as well as less educated respondents, also reported low levels of personal access to condoms (Figure 11.3). Two-thirds of women who had never had sex reported that they could not get a condom if they wanted to. 11.10 CHISHANGO CONDOMS The MDHS survey asked men and women if they “had ever heard of a condom called Chishango,” in order to monitor condom brand awareness. Table 11.16 shows that virtually all men (97 percent) and most women (89 percent) had heard of this condom brand. The lowest Chishango brand awareness was among women in the oldest and youngest age groups, women in rural areas, women residing in the Northern Region, and women with less education. 170 * AIDS and other STIs Table 11.15 Knowledge of male condoms Percentage of women and men who know a source for condoms and who “could get a condom if they wanted to” by background characteristics, Malawi 2000 __________________________________________________________________________________________ Women Men ______________________________ ________________________________ Knows Knows a source Could get a source Could get Background for condoms for condoms characteristic condoms if wanted Number condoms if wanted Number __________________________________________________________________________________________ Age 15-19 20-24 25-29 30-39 40-49 (men, 40-54) Current marital status Married or living together Divorced, separated, widowed Never married Ever had sex Never had sex Residence Urban Rural Region Northern Central Southern Education No education Primary 1-4 Primary 5-8 Secondary+ Total 69.1 48.2 2,867 83.8 71.5 660 82.2 66.4 2,957 93.4 88.0 598 83.7 66.4 2,401 91.4 86.6 539 79.3 59.6 2,990 89.1 82.1 670 69.0 43.5 2,004 79.0 68.9 624 79.0 60.5 9,452 87.2 79.6 1,906 76.8 55.4 1,525 81.2 79.5 113 78.5 65.2 868 92.8 86.3 767 62.7 33.8 1,375 75.1 57.8 306 94.4 69.0 2,106 98.6 92.8 564 73.7 55.2 11,114 84.6 76.0 2,528 77.8 41.8 1,453 87.8 76.5 351 74.9 58.3 5,321 84.2 76.5 1,296 78.5 60.2 6,446 89.7 82.0 1,446 66.1 48.7 3,574 71.8 62.8 322 73.0 55.2 4,025 80.5 72.4 898 83.6 61.2 4,152 90.4 81.4 1,243 95.9 74.2 1,468 98.2 92.5 629 77.0 57.4 13,220 87.2 79.1 3,092 AIDS and other STIs * 171 Table 11.16 Knowledge of Chishango brand condom Percentage of women and men who have heard of Chishango brand condoms, by background characteristics, Malawi 2000 ________________________________________________________ Women Men _________________ ________________ Background characteristic Percent Number Percent Number ________________________________________________________ Age 15-19 20-24 25-29 30-34 35-39 40-44 45-49 50-54 Residence Urban Rural Region Northern Central Southern Education No education Primary 1-4 Primary 5-8 Secondary+ Total 89.1 2,867 94.1 660 92.8 2,957 99.2 598 91.9 2,401 98.9 539 90.6 1,566 98.5 330 88.0 1,424 99.2 340 83.6 1,053 94.7 240 78.7 951 93.8 207 na na 94.0 177 98.6 2,106 99.8 564 87.5 11,114 96.4 2,528 83.0 1,453 93.8 351 86.5 5,321 96.8 1,296 93.0 6,446 97.9 1,446 81.9 3,574 94.0 322 87.8 4,025 95.3 898 93.8 4,152 97.6 1,243 98.8 1,468 99.8 629 89.3 13,220 97.0 3,092 ________________________________________________________ na = Not applicable 172 * AIDS and other STIs Table 11.17.1 Use of condoms: women Percentage of women who had sexual intercourse in the 12 months preceding the survey who used a condom during last sexual intercourse with spouse or cohabiting partner, with noncohabiting partner, and with any partner, by background characteristics, Malawi 2000 _________________________________________________________________________________________ Spouse or cohabiting partner Noncohabiting partner Any partner Background __________________ __________________ __________________ characteristic Percent Number Percent Number Percent Number _________________________________________________________________________________________ Age 15-19 20-24 25-29 30-39 40-49 Current marital status Married or living together Divorced, separated, widowed Never married Residence Urban Rural Region Northern Central Southern Education No education Primary 1-4 Primary 5-8 Secondary+ Alcohol consumption (last 3 months)1 Has not been drunk Has been drunk Total 4.1 953 31.9 482 13.3 1,422 4.2 2,358 32.6 218 6.3 2,560 2.7 2,103 21.3 79 3.3 2,172 1.2 2,498 19.3 104 1.9 2,596 1.0 1,576 10.5 45 1.2 1,615 2.6 9,037 16.7 61 2.6 9,062 1.6 436 21.9 273 8.8 694 na na 33.1 593 32.5 608 3.3 1,372 44.3 235 9.1 1,600 2.4 8,117 23.4 692 3.9 8,764 5.7 988 44.4 72 8.3 1,060 1.9 3,943 28.1 283 3.6 4,211 2.4 4,558 27.0 572 4.9 5,094 1.6 3,001 9.1 101 1.8 3,089 1.8 3,011 17.2 237 2.8 3,221 3.1 2,757 27.0 339 5.7 3,090 7.1 720 49.7 250 17.7 965 2.5 9,297 28.2 889 4.7 10,140 2.1 176 41.4 33 7.3 206 2.5 9,489 28.7 927 4.7 10,365 _________________________________________________________________________________________ na = Not applicable 1 Total includes 19 women with missing alcohol consumption information. 11.11 USE OF CONDOMS Table 11.17 shows the percentages of men and women who used a condom during their last sexual encounter, by partner type and background characteristics. Taking all partner types together (i.e., any partner), men are about three times more likely than women to have used a condom at last sex (14 percent versus 5 percent). Condoms are used less frequently during sex with cohabiting partners (within formal and informal marriages) for both women (3 percent) and men (6 percent), compared with sex with noncohabiting partners (women, 29 percent; men, 39 percent). It is clear that many women and men understand that sex outside of stable relationships entails greater risk. The 1996 MKAPH collected similar condom use data, allowing an assessment of trends during the late 1990s. AIDS and other STIs * 173 Table 11.17.2 Use of condoms: men Percentage of men who had sexual intercourse in the 12 months preceding the survey who used a condom during last sexual intercourse with spouse or cohabiting partner, with noncohabiting partner, and with any partner, by background characteristics, Malawi 2000 _________________________________________________________________________________________ Spouse or cohabiting partner Noncohabiting partner Any partner Background __________________ __________________ __________________ characteristic Percent Number Percent Number Percent Number _________________________________________________________________________________________ Age 15-19 20-24 25-29 30-39 40-54 Current marital status Married or living together Divorced, separated, widowed Never married Residence Urban Rural Region Northern Central Southern Education No education Primary 1-4 Primary 5-8 Secondary+ Alcohol consumption (last 3 months) Has not been drunk Has been drunk Total (20.1) 23 28.9 274 28.1 293 7.5 226 46.9 263 27.3 459 7.5 428 45.5 140 13.7 495 6.4 609 41.4 94 7.7 635 3.0 577 28.5 51 3.5 587 5.8 1,831 42.4 243 6.7 1,861 (9.7) 30 37.0 49 26.0 74 na na 37.5 532 37.5 534 7.2 305 49.6 175 20.4 430 5.7 1,559 36.0 648 12.6 2,039 10.2 208 49.2 69 18.2 264 6.8 751 38.7 312 14.9 999 4.2 905 37.4 442 12.2 1,206 4.0 259 23.7 51 5.3 285 4.0 547 29.2 227 8.9 704 6.5 720 38.7 349 15.0 989 9.2 337 54.4 197 24.2 492 5.6 1,352 37.8 618 14.0 1,837 6.7 512 42.3 206 13.8 632 5.9 1,864 38.9 823 14.0 2,469 _________________________________________________________________________________________ na = Not applicable ( ) Estimate based on 25-49 unweighted cases. Condom use in sex with noncohabiting partners has increased from 20 to 29 percent among women; among men, there was a negligible change from 38 to 39 percent. Condom use within marriage has declined slightly since 1996; from 4 to 3 percent in women and from 9 to 6 percent in men. The pattern of condom use across age categories varies depending on the sex of the respondent. In women, during both cohabiting and noncohabiting sexual activity, use of a condom is highest in the youngest age groups and declines with increasing age. Looking at men’s sexual activity within marriage, condom use also declines with increasing age; but during sex with noncohabiting partners, condom use is lowest in the youngest (age 15-19) and the oldest (40-54) age groups. 174 * AIDS and other STIs Urban men and women were much more likely to use a condom at last sex than their rural counterparts. The urban-rural differential is especially pronounced for condom use with noncohabiting partners (Figure 11.4). Women living in urban areas are almost twice as likely to use a condom during sex with noncohabiting partners than women in rural areas. Education is uniformly associated with higher reported condom use by both men and women, but the effect is more pronounced in women. Women with a secondary school education are five times more likely to use a condom during sex with a noncohabiting partner (50 percent) than women who never attended school (9 percent). This strong influence of education on risk avoidance behaviour is unlikely to be wholly the result of formal schooling per se but suggests that educated women possess more personal autonomy and influence in negotiating safer sex practise. It might be expected that drinking, especially drinking to excess, would be associated with risky behaviour, namely, nonuse of condoms. However, the data do not generally support this. For men, condom use with both categories of partners is higher among those reporting having been drunk. Among women, this is true only for noncohabiting partners. Of course, this does not mean that drinking is protective; it does suggest that drinkers are self-selected into a category of sexual activity that recognises and, to a certain degree, responds to a higher-risk context. CONDOM USE DURING COMMERC IAL SEX Among men who reported having paid for sex in the last 12 months, only about one-third (35 percent) reported using a condom on the last occasion (Table 11.18). This is even lower than the estimate of condom use by men during sex with a noncohabiting partner and suggests that many men either have not heard, have not understood, or simply have not responded to the AIDS and other STIs * 175 Table 11.18 Use of condoms during commercial sex Among men who paid for sex in the 12 months preceding survey, the percentage who used a condom at last paid intercourse, by background characteristics, Malawi 2000 ____________________________________________ Percentage Number Background using a of characteristic condom men ____________________________________________ Age 15-24 25-34 35-54 Current marital status Currently married Not currently married Residence Urban Rural Region Northern Central Southern Education No education Primary 1-4 Primary 5-8 Secondary+ Alcohol consumption (last 3 months) Has not been drunk Has been drunk Total 37.1 199 44.4 178 25.5 195 34.0 386 38.4 185 45.6 123 32.6 449 41.4 28 35.5 145 35.0 399 19.8 64 29.7 180 36.4 220 52.0 107 34.9 411 36.6 161 35.4 572 message to use condoms during risky sex. A man’s educational level is closely associated with condom use; 52 percent of men who engaged in commercial sex used a condom if they had a secondary education, but just 20 percent used a condom if they had not attended school. Marital status and drinking patterns were only weakly associated with condom use at last paid sex. Adult and Maternal Mortality * 177 ADULT AND MATERNAL MORTALITY 12 Ann Phoya and George Bicego In an earlier chapter of this report, estimates of mortality during the first years of life were presented and discussed. Early childhood mortality varies substantially as an index of social and economic development and thus tends to be predictably high in disadvantaged settings. Mortality during later childhood and adolescence is, on the other hand, relatively low in all societies but begins to rise with age starting in the late teenage years. The pattern and pace of the rise in adult mortality with increasing age is tied closely to the occupational profile, fertility pattern, and epidemiological characteristics of a population. Two aspects of adult mortality dynamics deserve close attention in the Malawian context. First, given sharp rises in the prevalence of HIV infection and AIDS (discussed in the previous chapter) over the last 15 years, Malawi is expected to suffer increases in both female and male adult mortality in the near term. Second, mortality related to pregnancy and childbearing (maternal mortality) serves as an important indicator to monitor women’s and reproductive health programmes in the country. The 2000 MDHS Women’s Questionnaire included a sibling history, which is a detailed account of the survivorship of all of the live-born children of the respondent’s mother (i.e., maternal siblings). These data allow direct estimation of overall adult mortality (by sex), as well as maternal mortality in particular. The direct approach to estimating adult and maternal mortality maximises use of the available data, using information on the age of surviving siblings, the age at death of siblings who died, and the number of years ago the sibling died. This allows the data to be aggregated to determine the number of person-years of exposure to mortality risk and the number of sibling deaths occurring in defined calendar periods. Rates of adult mortality and maternal mortality are obtained by dividing all adult deaths (or maternal deaths) in a calendar period by person-years of exposure to death in those periods. The procedure calculates rates in each of the five-year age periods first and then aggregates the estimates for the whole 15-49 age range, weighting the age-specific estimates using the observed age structure of the female population. 12.1 THE DATA Each female respondent was first asked to give the total number of her mother's live births. Then the respondent was asked to provide a list of all of the children born to her mother starting with the first born and was asked whether each of these siblings was still alive at the survey date. For living siblings, current age was recorded; for deceased siblings, age at death and years since death were recorded. Interviewers were instructed that when a respondent could not provide precise information on ages or years ago, approximate but still quantitative answers were acceptable. For sisters who died at ages 12 years or above, three questions were used to determine whether the death was maternity-related: "Was [NAME OF SISTER] pregnant when she died?" and if negative, "Did she die during childbirth?" and if negative, "Did she die within two months of the birth of a child or pregnancy termination?" The estimation of adult and maternal mortality by either direct or indirect means requires reasonably accurate reporting of the number of sisters and brothers the respondent ever had, the number that have died, and (for maternal mortality) the number of sisters who have died of 1 The imputation procedure is based on the assumption that the reported birth order of siblings in the history is correct. The first step is to calculate birth dates. For each living sibling with a reported age and each dead sibling with complete information on both age at death and years since death, the birth date was calculated. For a sibling missing these data, a birth date was imputed within the range defined by the birth dates of the bracketing siblings. In the case of living siblings, an age was then calculated from the imputed birth date. In the case of dead siblings, if either the age at death or years since death was reported, that information was combined with the birth date to produce the missing information. If both pieces of information were missing, the distribution of the ages at death for siblings for whom the years since death were unreported, but age at death was reported, was used as a basis for imputing the age at death. 178 * Adult and Maternal Mortality Table 12.1 Data on siblings: completeness of reported data Number of siblings reported by survey respondents and completeness of the reported data on age, age at death, and years since death, Malawi 2000 _________________________________________________________________________________________ Sisters Brothers Total Sibling status and __________________ _________________ ________________ completeness of reporting Number Percent Number Percent Number Percent __________________________________________________________________________________________ Total siblings reported 39,447 100.0 39,744 100.0 79,191 100.0 Living 28,579 72.4 28,384 71.4 56,963 71.9 Dead 10,863 27.5 11,348 28.6 22,211 28.0 Missing survival status 4 0.0 12 0.0 16 0.0 Living siblings 28,579 100.0 28,384 100.0 56,963 100.0 Age reported 28,562 99.9 28,373 100.0 56,936 100.0 Age missing 17 0.1 10 0.0 28 0.0 Dead siblings 10,863 100.0 11,348 100.0 22,211 100.0 AD and YSD reported 10,802 99.4 11,278 99.4 22,080 99.4 Missing only AD 8 0.1 15 0.1 23 0.1 Missing only YSD 37 0.3 41 0.4 78 0.4 Missing both 16 0.1 14 0.1 30 0.1 __________________________________________________________________________________________ AD = Age at death YSD = Years since death/year of death maternity-related causes. There is no definitive procedure for establishing the completeness or accuracy of retrospective data on sibling survivorship. However, the MDHS sibling history data do not show any obvious defects that would indicate poor data quality or systematic underreporting. Table 12.1 shows the number of siblings reported by the respondents and the completeness of the reported data on current age, age at death, and years since death. Of the 79,191 siblings reported in the sibling histories of MDHS respondents, for only 16 (<0.1 percent) was survival status not reported. Among surviving siblings, current ages (used to estimate exposure to death) were not reported for less than 0.1 percent of siblings. Among deceased siblings, complete reporting of age at death and years since death was nearly universal. For 99 percent of deceased siblings, both age at death and years since death (or year of death) were reported. In less than 1 percent of cases, either the age at death or the years since death (and year of death) was missing. Rather than exclude the small number of siblings with missing data from further analysis, information on the birth order of siblings in conjunction with other information was used to impute the missing data.1 The sibling survivorship data, including cases with imputed values, were used in the direct estimation of adult and maternal mortality. Adult and Maternal Mortality * 179 Table 12.2 Adult mortality rates Direct estimates of age-specific mortality rates for women and men age 15-49, for the periods 0-6 years prior to the 2000 MDHS and 1992 MDHS_________________________________________________________________ 2000 MDHS 1992 MDHS ____________________________ _________ Mortality Mortality Age Exposure rates rates group Deaths (person-years) (/1000) (/1000)_________________________________________________________________ WOMEN_________________________________________________________________ 15-19 132 32,383 4.1 5.3 20-24 287 33,485 8.6 3.6 25-29 315 27,706 11.4 6.8 30-34 326 21,063 15.5 7.2 35-39 262 15,263 17.1 9.0 40-44 173 9,682 17.9 8.9 45-49 104 5,592 18.7 9.6 15-49 1,599 145,174 11.3 6.5 _________________________________________________________________ MEN_________________________________________________________________ 15-19 105 31,021 3.4 3.8 20-24 190 32,255 5.9 4.1 25-29 254 27,860 9.1 6.8 30-34 310 21,487 14.4 8.4 35-39 315 15,465 20.3 7.6 40-44 210 9,340 22.5 10.1 45-49 128 5,523 23.2 9.7 15-49 1,511 142,952 11.1 6.3 12.2 ADULT MORTALITY One way to assess the quality of data used to estimate maternal mortality is to evaluate the plausibility and stability of overall adult mortality. It is reasoned that if estimated rates of overall adult mortality are implausible, rates based on a subset of deaths—maternal deaths in particular—are unlikely to be free of serious problems. As described above, levels and trends in overall adult mortality have important implications in their own right for health and social programmes in Malawi, especially regarding mitigation of the impact of the AIDS epidemic. Table 12.2 shows age-specific mortality rates for men and women age 15-49, for the calendar period 0-6 years before the survey (i.e., 7-year period before the interview). Also shown are identically calculated estimates drawn from the 1992 MDHS survey, for a period 0-6 years before that survey. The centre of the reference period of the estimates from the 1992 and 2000 survey data are early 1989 and early 1997, respectively. Despite some small fluctuations in the age-specific rates, the results of this analysis are unambiguous. Figures 12.1 and 12.2 clearly show that mortality in both women and men has risen sharply between the period of the late 1980s to the early 1990s and the mid- to late 1990s. Indeed, when looking at the summary measure of mortality for the age group 15-49, one observes a 74 percent increase in all-cause adult female mortality and a 76 percent increase in adult male mortality. 180 * Adult and Maternal Mortality 2 The rate for the whole age range 15-49 is standardised on the MDHS household age structure. Adult and Maternal Mortality * 181 Table 12.3 Direct estimates of maternal mortality Direct estimates of maternal mortality rates and the maternal mortality ratio, for the period 0-6 years prior to the 2000 MDHS and 1992 MDHS_________________________________________________________________ 2000 MDHS 1992 MDHS ____________________________ _________ Mortality Mortality Age Exposure rates rates group Deaths (person-years) (/1000) (/1000) _________________________________________________________________ 15-19 13 32,383 0.4 1.3 20-24 80 33,485 2.4 0.5 25-29 75 27,706 2.7 1.5 30-34 79 21,062 3.7 1.8 35-39 44 15,263 2.9 1.9 40-44 43 9,682 4.5 0.8 45-49 11 5,591 1.9 3.4 15-49 344 145,174 2.4 1.4 General fertility rate (GFR) 0.210 0.220 Maternal mortality ratio (MMR)1 1,120 620_________________________________________________________________ 1 Per 100,000 live births, calculated as the maternal mortality rate divided by the general fertility rate. Of particular interest is the broad age-pattern “signature” to the rises in mortality, with the largest changes for men occurring from age 30 and older, whereas for women, an earlier impact is observed (age 20 and older). This sex differential in the age pattern of the rise in mortality is consistent with the sex differential in HIV infection and AIDS-related mortality in sub-Saharan Africa, which is in turn related to the age differential in sexual activity (i.e., older men with younger women). 12.3 MATERNAL MORTALITY Maternal deaths are a subset of all female deaths, specifically those associated with pregnancy and childbearing. The approach used to obtain the maternal mortality results is the same as that is used to obtain overall adult mortality. Direct, age-specific estimates of maternal mortality from the reported sibling survivorship histories are shown in Table 12.3 for the period 0-6 years before the survey, alongside estimates based on the 1992 MDHS data for the period 0-6 years before that survey. The number of maternal deaths is small from the 1992 survey (68), so the differences between age-specific rates from the 1992 MDHS survey and the 2000 MDHS survey should not be overinterpreted—the preferred approach is to focus attention on the estimate for all childbearing ages combined (15-49 years). For the period 0-6 years before the survey (centered on early 1997), the rate of mortality due to causes related to pregnancy and childbearing is 2.4 maternal deaths per 1,000 woman-years of exposure.2 3 These proportionate maternal mortality estimates are in the range of those presented by Stanton et al. (1997) in their exhaustive review of similar data collected around the world. 182 * Adult and Maternal Mortality The maternal mortality rate is converted to a maternal mortality ratio (MMR) and expressed per 100,000 live births by dividing the rate by the general fertility rate (0.210) associated with the same period. In this way, the obstetrical risk of pregnancy and childbearing is underlined. Using direct estimation procedures based on the 2000 MDHS survey, the maternal mortality ratio is estimated to be 1,120 maternal deaths per 100,000 live births applicable to the seven-year period before the survey (centered on early 1997). This estimate of the maternal mortality ratio exceeds by some 80 percent the estimate from the 1992 MDHS survey of 620 maternal deaths per 100,000 live births. The proportion of all female deaths that are maternity-related has remained constant at 20 to 21 percent between the late 1980s and the late 1990s.3 At face value, this means that maternal mortality has risen at roughly the same pace as nonmaternal mortality. This may appear implausible if one regards the rise in all-cause female mortality as principally AIDS driven, which would be expected to cause a disproportionate rise in nonmaternal mortality. Possible explanations include the following: 1. The maternal mortality component of all-cause female mortality may have been underestimated in the 1992 MDHS survey. This would result from either misclassification of maternal deaths as nonmaternal deaths or simply underreporting of maternal deaths. 2. The maternal mortality component of all-cause female mortality may have been overestimated in the 2000 MDHS survey. This could result from an increase in nonmaternal deaths that are, in part, being (mis)classified as maternal deaths. Given the prevailing social stigma associated with AIDS, some respondents may be biased toward reporting a sister’s AIDS-related death as being maternity-related. 3. It is also important to recall that (based on survey definitions) all deaths occurring during pregnancy through the postpartum period are considered maternal. Under this definition, it is expected that maternal mortality will rise in contexts with a combination of high fertility and high HIV prevalence. This methodological issue is discussed in Stecklov, 1995 and Khlat et al., 2000, but no solution is provided other than suggestions to focus measurement of maternal mortality on direct obstetrical causes, an approach probably not feasible in the context of a household survey. 4. Rather than being misclassified, some AIDS-related deaths may have simply been omitted in the 2000 MDHS survey. This would mean that the true rise in all-cause female mortality is even higher than described here. 5. There may have been a real rise in deaths that are at once maternity-related and directly HIV/AIDS-related. HIV-infection-induced immunosuppression may be expected to cause increases in case-fatality from pregnancy and delivery-related infections. Increases in pregnancy loss associated with HIV infection may also cause increased risks of maternal death (Gray et al, 1998). The evidence to support these explanations is, however, not strong. 6. There may have been a real rise in maternal deaths due in part to deterioration in maternal health services associated with the AIDS epidemic. Adult and Maternal Mortality * 183 Each of these explanations alone would probably not explain the observed patterns (very large and roughly proportional rises in both maternal and nonmaternal mortality), but taken together, they may help to place the findings in methodological and substantive contexts. In conclusion, the available evidence points to dramatic rises in both maternal and nonmaternal mortality during the 1990s. Malawi’s maternal mortality ratio stands at 1,120 maternal deaths per 100,000 live births. The MMR estimate may include mortality related to HIV infection and AIDS. This finding underscores the need to focus particular attention on reproductive health services in general and safe delivery practises in particular. Further, the 2000 MDHS findings strongly suggest that safe motherhood policies and initiatives need to be evaluated within the context of the nation’s AIDS epidemic. In-depth research is urgently needed to better understand the troubling rises in both maternal mortality and overall mortality in adult men and women. Malaria * 185 MALARIA 13 Jameson Ndawala, Gertrude Kalanda, and Mary Mahy Malaria is a major public health concern in Malawi, especially among pregnant women and children under the age of five. It is a leading cause of morbidity and mortality in Malawi, accounting for one-third of all outpatient visits and more than a third of visits among children under five years old. In the current five-year National Health Plan (1999-2004), the Ministry of Health and Population has singled out malaria as “the most serious health problem facing Malawi today.” There are more than 8 million episodes of malaria illness per year experienced by Malawi’s population of 10 million. About 40 percent of the deaths in children less than two years old are related to malaria. The type of malaria most common in Malawi (plasmodium falciparum) can lead to death; however, the most severe cases are typically limited to those who are not immune or have low immunity. People most at risk are children from age three months, who no longer have the immunity transferred from their mother, to about the age of five years when they have developed their own immunity. Also at particular risk are pregnant women because their natural immunity is reduced. Pregnant women are four times more likely to suffer from complications of malaria than nonpregnant women. Malaria is a cause of pregnancy loss, low birth weight, and neonatal mortality (Jamison et al, 1993). Malaria continues to be costly in both societal and economic terms. Absenteeism from school and work due to malaria is common. Poverty worsens in populations affected by malaria illness because the workforce is less productive. This affects food production and outputs from other industries. It is estimated that the government of Malawi spends US$2.7 million per annum in treating malaria cases, including both inpatients and outpatients. The public at large spends US$35.00 per annum per household on malaria treatment and yet malaria can be prevented. The recent global Roll Back Malaria (RBM) movement, which Malawi endorsed and to which Malawi committed itself in the Abuja Declaration, has set the framework within which the country is implementing malaria control. The movement’s goal is to halve the burden of malaria by 2010. It sets out to increase bednet usage to 60 percent of all pregnant women, as well as children under five years old. It also aims to improve access to prompt and appropriate treatment within 24 hours of onset of illness. In controlling malaria in Malawi, one of the strategies that the Ministry of Health and Population has adopted is the presumptive treatment of fever with sulpha-pyrimethamine (SP) (also known as Fansidar) as the first line drug and promotion of efforts to increase its availability at the community level. 13.1 BEDNETS The use of insecticide-treated bednets (mosquito nets) is a primary health intervention to reduce malaria transmission. Treated nets are being promoted through three main channels: 1) the 186 * Malaria Table 13.1 Possession and use of bednets Percentage of households with bednets, mean number of bednets per household, and percentage of children under five, women age 15-49, and men age 15-54, who slept under a bednet the night before the survey, by background characteristics, Malawi 2000 ________________________________________________________________________________________________________________ Households that Mean number of bednets Percentage who used a bednet the own at least one: per household1 night before the interview __________________ _________________ __________________________________________________ Background Coloured Coloured Children Women Men characteristic Bednet bednet2 Bednet bednet2 Total under 5 Number 15-49 Number 15-54 Number ________________________________________________________________________________________________________________ Residence Urban 32.0 16.7 1.8 1.6 1,949 20.8 1,358 19.2 2,106 10.6 564 Rural 10.1 3.6 1.5 1.3 12,264 5.7 9,201 5.4 11,114 5.4 2,528 Region Northern 24.8 6.4 1.7 1.3 1,496 16.8 1,166 14.4 1,453 9.6 351 Central 10.9 4.0 1.6 1.3 5,744 6.0 4,594 6.0 5,321 4.2 1,296 Southern 12.4 6.3 1.6 1.5 6,973 7.0 4,799 7.3 6,446 7.4 1,446 Owns a radio Yes 19.6 8.3 1.6 1.5 7,782 10.5 6,157 10.6 7,923 7.8 2,041 No 5.2 1.7 1.4 1.2 6,413 3.7 4,395 3.1 5,285 3.3 1,048 Household head’s/ mother’s/women’s/ men’s education No education 6.6 2.1 1.4 1.3 3,977 4.0 2,486 3.4 3,093 4.8 610 Primary 1-4 7.7 2.6 1.4 1.2 3,879 4.4 2,852 3.9 3,442 3.4 864 Primary 5-8 12.5 4.6 1.5 1.2 4,425 5.9 3,786 6.3 4,563 5.0 1,063 Secondary+ 38.6 19.3 1.8 1.6 1,932 24.6 1,436 22.5 2,123 15.1 554 Total 13.1 5.4 1.6 1.4 14,213 7.6 10,559 7.6 13,220 6.3 3,092 _________________________________________________________________________________________________________________ 1 Mean number of bednets per household households with bednets. 2 Coloured bednets (e.g. blue and green) are usually those available under recent social marketing initiatives. public sector as community-based projects, 2) public/private partnerships implemented by nongovernmental organisations directly to the community, and 3) the private sector’s social marketing initiatives such as those assisted by Population Services International (PSI), (BITNET). This section presents MDHS findings based on data collected at the household level on bednet possession and data collected at the individual level on use and treatment of bednets by household members. 13.1.1 POSSESSION OF BEDNETS All households in the 2000 MDHS survey were asked whether they owned bednets and how many they owned. To allow monitoring of the distribution of bednets made available under social marketing initiatives (blue and green nets), a question was asked as to how many of the bednets were white (as opposed to coloured). Table 13.1 presents results of the MDHS survey on household possession of bednets. Thirteen percent of households reported owning a bednet. Among the households that reported bednet ownership, the average number of bednets per household is 1.6. Ownership of at least one coloured bednet is 5 percent; in those households, the average number of coloured bednets is 1.4. Malaria * 187 Urban households, households in the Northern Region, and households with higher socioeconomic status are much more likely to possess at least one bednet. Twenty-five percent of households in the Northern Region have at least one bednet, compared with 12 percent in the Southern Region and 11 percent in the Central Region. Ownership of bednets is also high among urban households (32 percent versus 10 percent for rural households) and among households that own a radio (20 percent versus 5 percent in households with no radio). There is a strong relationship between the household head’s level of education and the presence of a bednet in the house. Households whose head has a secondary or higher education are about six times more likely to have a bednet (39 percent) than households in which the head of household has no education (7 percent). The differentials in possession of coloured bednets parallel those described above for all bednets, except that regional differences in coloured bednet possession are not as marked, and socioeconomic differentials are larger than shown for all bednets. 13.1.2 USE OF BEDNETS In the 2000 MDHS survey, women age 15-49 in households possessing a bednet were asked questions about their own use of bednets and the use of bednets for all of their own children under age five. Men age 15-54 in households possessing a bednet were asked similar questions about their own bednet use. Since the prevalence of malaria-carrying mosquitoes varies seasonally, with a peak during and immediately following periods of rain, use of bednets may be expected to follow a similar seasonal pattern. Since the survey was conducted mostly before the rainy season (July to November), estimates of bednet use should be understood to reflect the prevailing dry-season use levels. 1 Among pregnant women, 7 percent reported sleeping under a bednet on the night before the survey (not in Table 13.1). 188 * Malaria Table 13.2 Bednet age and insecticide treatment for bednets Age of bednets and insecticide treatment pattern for bednets that were used the previous night by children under age five, women age 15-49, and men age 15-54, according to background characteristics, Malawi 2000 _________________________________________________________________________________________________________________________ Children under 5 Women age 15-49 Men age 15-54 __________________________________ _________________________________ _________________________________ Percent of Average Number Percent of Average Number Percent Average Number Average bednets months of Average bednets months of Average of bednets months of age of ever since children age of ever since women age of ever since men Background bednets soaked or last using bednets soaked or last using bednets soaked or last using characteristic (months) dipped treatment bednets (months) dipped treatment bednets (months) dipped treatment bednets ________________________________________________________________________________________________________________________ Residence Urban 17.3 56.0 3.7 282 15.5 57.8 3.7 405 9.1 59.0 2.0 60 Rural 18.9 27.7 4.4 523 17.3 33.4 3.9 599 14.5 38.5 3.3 136 Region Northern 24.8 21.5 5.1 195 23.3 18.5 4.8 209 (13.9) (14.0) (2.8) 34 Central 17.7 33.4 3.9 275 15.8 42.9 3.7 322 13.0 59.0 1.9 55 Southern 15.0 50.5 3.8 334 14.1 54.3 3.7 473 12.3 47.2 3.4 107 Mother's/Women's/ Men's education No education 19.4 21.3 3.6 149 19.7 25.2 3.6 160 * * * 14 Primary1-4 18.9 26.9 5.4 141 16.6 37.5 4.3 173 (13.5) (50.6) (3.4) 31 Primary5-8 18.3 37.1 3.9 266 16.6 38.5 3.8 317 11.9 33.8 1.7 55 Secondary+ 17.5 54.1 3.8 249 15.2 58.4 3.7 353 10.5 52.1 2.9 95 Total 18.4 37.6 4.0 805 16.6 43.2 3.8 1,004 12.8 44.8 2.8 195 ________________________________________________________________________________________________________________________ * Fewer than 25 unweighted cases; estimate has been suppressed ( ) Estimate based on 25-49 cases Table 13.1 shows that 8 percent1 of women age 15-49 and 8 percent of children under age five slept under a bednet on the night before the survey. A slightly lower percentage of men (6 percent) reported sleeping under a bednet. The pattern of bednet use by children, women, and men across background characteristics closely resembles the pattern observed for bednet possession. 13.1.3 INSECTICIDE TREATMENT OF BEDNETS Table 13.2 presents the age and insecticide treatment pattern for bednets that were used the previous night by children under age five, women, and men by background characteristics. The average age of the bednets used by children under age 5 is 18 months. The average is higher in the Northern Region at 25 months, compared with the Central Region (18 months) and the Southern region (15 months). Differences in the age of the bednets by urban-rural residence and mother’s education are small. Regarding bednets that were used the previous night by children under five, 38 percent had been treated, and of those, the average period since last treatment was four months. The proportion of children using bednets that were ever soaked or dipped is higher in the Southern Region (51 percent) than in the Central (33 percent) or Northern (22 percent) regions. It is also twice as high in urban areas (56 percent) as in rural areas (28 percent). Children whose mothers have been 2 To avoid confusion with treatment doses of antimalarials (i.e., in response to an episode of malaria), the question was followed immediately with, “Not considered here are instances when you took the drug because you had malaria.” 3 Interviewers carried samples of antimalarials, so that if a respondent was not certain of the drug type, it could be ascertained by showing the samples. Malaria * 189 to secondary school are much more likely to have slept under a bednet that was treated. The duration since last treatment does not vary much across background characteristics, although it appears to be slightly longer in the Northern Region. The average age of the bednets used by women and men is 17 months and 13 months, respectively. Forty-three percent of the women and 45 percent of the men used bednets that had been treated. Thus, the bednets used by adults appear to be more recently purchased and more recently treated than those used by children. The pattern for both women and men by background characteristic is similar to that observed for children. 13.2 INTERMITTENT TREATMENT DURING PREGNANCY Pregnant women who carry the malaria parasite may be at risk of serious problems that jeopardise their own health, compromise the health of the foetus, and increase the likelihood of adverse pregnancy outcomes such as low birth weight. As a protective measure, it is recommended that pregnant women receive intermittent treatment (IT) with SP/Fansidar twice—once in the second trimester and once in the third trimester—to clear the malaria parasite from their body. In reference to the pregnancy that ended in their last live birth, women were asked whether any antimalarials were taken during the pregnancy,2 which drug was taken,3 and how many different times it was taken during the pregnancy. The data do not allow assessment of the timing of the doses relative to stage of pregnancy. 190 * Malaria Table 13.3 Intermittent treatment Percentage of women who received intermittent treatment with sulpha-pyrimethamine (SP) during the last pregnancy in last five years, by background characteristics, Malawi 2000________________________________________________________ Received Received SP SP at least 2 or more Number Background once during times during of characteristic pregnancy pregnancy births _________________________________________________________ Birth order 1 2-3 4-5 6+ Age of mother 15-24 25-34 35-49 Residence Urban Rural Region Northern Central Southern Woman’s education No education Primary 1-4 Primary 5-8 Secondary+ Total 67.8 29.8 1,703 70.3 30.8 2,780 67.3 27.6 1,664 63.4 28.1 1,909 67.3 28.0 3,129 69.7 31.0 3,286 63.5 28.4 1,642 81.3 32.1 1,075 65.4 28.9 6,982 76.8 27.0 894 60.6 29.7 3,407 71.5 29.5 3,757 58.9 26.3 2,585 62.9 28.0 2,423 76.2 31.9 2,434 87.3 37.0 615 67.5 29.3 8,057 Table 13.3 presents the percentage of women who received at least one dose and at least two doses of SP/Fansidar during the last pregnancy leading to a live birth in the last five years. The data indicate that, in Malawi, 68 percent of all mothers received at least one dose of SP/Fansidar as a prophylaxis and that 29 percent received at least two doses. Differentials by background characteristics are generally not large, although pregnant women in urban areas and in the Northern Region are more likely to receive at least one IT dose. More educated women are also more likely to receive IT than less educated women. Still, only about one-third of pregnant women with at least some secondary schooling reported that they had received two doses of Fansidar during their last pregnancy. 13.3 TREATMENT OF CHILDREN WITH FEVER Since the major manifestation of malaria is fever, mothers were asked whether their children under age five had had a fever in the two weeks preceding the survey. If a fever was reported, the mother was asked whether treatment was sought at a health facility and whether the child was given any medication. Interviewers in the MDHS survey used a chart to record information provided by the mother on the sequence of actions taken in response to the child’s fever. Potential actions included, among other things, what type of health facility the child was taken to and what types of medication were ultimately given to the child. Malaria * 191 Table 13.4 Treatment of children with fever Percentage of children under 5 with fever in the two weeks preceding the survey and, of those, the percentage who were taken to a health facility and percentage who received antimalarials, by background characteristics, Malawi 2000 _____________________________________________________________________________________________________ Among those with fever, percentage: _____________________________________________________ Don’t Number Percent Percent know of with taken Given Given what children fever in to a any Given other medication ill Background preceding health anti- Given Chloro- anti- was with characteristic 2 weeks Number facility malarial SP/Fansidar quine malarial given fever _____________________________________________________________________________________________________ Age of child (years) <1 46.6 2,517 39.0 22.4 18.4 1.5 2.7 1.9 1,173 1-2 49.0 4,345 35.3 27.7 23.8 1.5 3.2 1.4 2,129 3-4 29.6 3,697 30.8 30.6 27.3 0.9 3.2 0.6 1,093 Residence Urban 31.9 1,358 45.8 33.7 27.6 0.5 7.1 1.6 434 Rural 43.0 9,201 34.0 26.3 22.8 1.4 2.6 1.3 3,961 Region Northern 33.8 1,166 41.5 30.7 24.5 1.5 6.9 1.0 394 Central 43.6 4,594 34.4 26.4 22.1 2.1 2.9 1.2 2,003 Southern 41.6 4,799 34.8 26.9 24.2 0.5 2.5 1.5 1,998 Mother's education No education 42.0 3,538 30.4 23.5 20.6 1.7 1.6 2.3 1,486 Primary 1-4 46.1 3,153 32.8 25.6 22.5 1.5 2.2 1.0 1,455 Primary 5-8 39.1 3,150 40.0 29.9 25.3 0.8 4.3 0.7 1,231 Secondary+ 31.0 718 56.0 42.7 34.1 0.5 11.7 1.3 223 District Blantyre 39.4 755 36.3 23.7 19.1 0.3 4.7 2.0 298 Karonga 36.3 213 35.2 30.5 19.8 1.9 8.8 1.1 77 Kasungu 43.6 437 28.0 18.2 13.8 2.1 2.3 0.5 191 Lilongwe 38.1 1,596 35.5 28.2 23.0 3.1 3.0 1.9 608 Machinga 33.5 411 35.9 34.1 31.1 1.6 2.5 0.5 138 Mangochi 42.0 553 33.4 23.0 20.7 0.6 2.3 0.1 232 Mulanje 46.4 468 27.1 21.3 19.7 0.3 1.4 0.3 217 Mzimba 34.0 490 35.4 29.1 22.2 2.2 5.4 1.9 166 Salima 44.0 244 34.6 28.9 25.5 0.7 3.3 0.6 108 Thyolo 35.0 479 35.4 24.3 22.8 1.0 0.5 5.1 167 Zomba 39.8 633 31.0 27.3 26.1 0.5 0.7 0.5 252 Other districts 45.3 4,281 37.2 28.3 24.8 1.1 3.3 1.3 1,940 Total 41.6 10,559 35.2 27.0 23.2 1.3 3.1 1.3 4,394 Table 13.4 shows that 42 percent of children were reported to have had a fever in the two weeks prior to the survey, which is similar to the 41 percent from the 1992 MDHS survey. This varied by region: the Northern Region had a prevalence rate of 34 percent, while the Central and Southern regions had prevalence rates of 44 and 42 percent, respectively. Rural children were more likely to have had fever (43 percent), compared with urban children (32 percent). Children of women with no education were less likely to have had fever (42 percent) than children of mothers with one to four years of primary education (46 percent). Children of women with five to eight years of primary or some secondary education had lower prevalence of fever (39 and 31 percent, respectively). Children age 3-4 have a lower fever prevalence than younger children, probably because their bodies have become more immune after repeated episodes. 192 * Malaria Among children reported to have had a fever in the two weeks prior to the survey, 35 percent were taken to a health facility and 27 percent were given an antimalarial (mostly SP/Fansidar, 23 percent). Differentials in health facility use by background characteristics are similar to those for antimalarial use. Children living in the Northern Region, in urban areas, and children of more educated mothers are more likely to have been taken to a health facility and to have been given an antimalarial (Figure 13.2). District-level variation in health facility use is not pronounced, but levels of antimalarial use tend to vary more among districts, ranging from just 18 percent in Kasungu District to 34 percent in Machinga District. While younger children were more likely than older children to be taken to a health facility when a fever was recognised, they were less likely to be given an antimalarial. 13.4 TIMING OF ANTIMALARIAL RESPONSE TO CHILD’S FEVER Most deaths due to malaria in children could be avoided by prompt recognition and treatment with antimalarial drugs. For each medicine reported by the mother, MDHS interviewers asked, “How long after the fever began was [NAME OF MEDICINE] first given to [NAME OF CHILD]?” Of febrile children who were treated with an antimalarial, 83 percent were reported to have received the antimalarial within 0-1 days of onset of the fever (Table 13.5). Treatment with SP/Fansidar is more likely to be done in a timely manner than treatment with other antimalarials (mostly Chloroquine). Differentials are small, but treatment in rural areas, in the Central Region, and among children of mothers with less than secondary education tended to be less prompt. Malaria * 193 Table 13.5 Promptness of treatment of children with fever Among children under age five who had a fever in the two weeks preceding the survey and who were given specific antimalarial medicines, the percentage who were given treatment on the same day that the fever was recognised or the next day, by background characteristics, Malawi 2000____________________________________________________________________________________ Given other Given any Given SP/Fansidar antimalarial antimalarial ____________________ ____________________ ___________________ Percent Percent Percent given Number given Number given Number Background same of same of same of characteristic or next day children or next day children or next day children ___________________________________________________________________________________ Age of child (years) <1 2-3 4-5 Residence Urban Rural Region Northern Central Southern Mother's education No education Primary 1-4 Primary 5-8 Secondary+ Total 82.9 217 78.8 49 82.1 264 84.0 503 77.4 99 83.5 585 83.1 298 73.6 45 83.1 334 90.8 120 74.2 33 87.0 146 82.5 899 77.4 160 82.5 1,037 84.2 96 77.1 32 82.1 120 77.0 441 74.5 99 77.7 527 89.3 482 80.6 61 88.5 536 85.4 307 76.3 50 85.1 351 82.4 327 73.4 55 82.2 373 81.1 309 75.3 60 80.3 363 90.5 76 88.0 28 88.9 96 83.5 1,019 76.9 192 83.0 1,183 13.5 INITIAL RESPONSE TO CHILD’S FEVER Table 13.6 shows the distribution of febrile children by the mother’s report of first response to the fever. Twenty-six percent of the children were taken to a health facility as the first response; 21 percent on the same day or the day after fever onset. Forty percent of the children were given medicine that was bought at a pharmacy or shop (without a prescription) as a first response. An additional 23 percent were given medicine that was obtained at home, although this may have included anything that the respondent considered to be a medicine (modern pharmaceutical or traditional). Use of a traditional healer as a first response was reported for less than 1 percent of febrile cases. Children of mothers with more education were more likely to first respond by taking the febrile child to a health facility or giving the child a medicine already found at home, whereas women with less education were more likely to give the child a medicine obtained in a shop or pharmacy or not treat the child at all. This presentation of the 2000 MDHS findings on malaria is not exhaustive, nor does it involve use of all data collected in the survey related to malaria and malaria programmes. It is hoped and anticipated that this brief analysis will assist in the design and evaluation of malaria control initiatives in Malawi and will encourage others to implement further, more detailed studies of the 2000 MDHS data. 194 * Malaria Table 13.6 Initial response to fever Percent distribution of children with fever in preceding two weeks by specific actions taken as the first response to fever, according to background characteristics, Malawi 2000 ____________________________________________________________________________________________________________ Given medicine Taken from Taken to a Given pharmacy Given Did to a tradi- medicine or shop Given herbs Given nothing/ Background health tional from (non-pre- tepid at other don’t characteristic facility healer home scription) sponging home treatments know Total Number _____________________________________________________________________________________________________________ Age of child <1 29.8 (23.9) 1.1 20.6 38.1 3.0 1.0 0.3 6.2 100.0 1,173 1-2 26.4 (21.8) 0.6 22.3 40.0 3.6 0.6 0.2 6.3 100.0 2,129 3-4 21.1 (17.6) 0.4 27.7 40.8 3.8 0.6 0.2 5.4 100.0 1,093 Region Northern 28.5 (22.6) 0.5 34.8 24.1 4.1 0.8 0.4 6.8 100.0 394 Central 24.6 (20.3) 0.0 23.7 40.6 3.2 0.7 0.2 7.0 100.0 2,003 Southern 26.9 (22.1) 1.4 20.4 41.9 3.6 0.7 0.2 4.9 100.0 1,998 Residence Urban 34.1 (27.2) 0.1 21.0 39.6 2.6 0.1 0.1 2.4 100.0 434 Rural 25.1 (20.7) 0.7 23.5 39.7 3.6 0.8 0.2 6.4 100.0 3,961 Mother's education No education 23.9 (19.0) 0.6 23.5 40.5 2.7 1.2 0.0 7.7 100.0 1,486 Primary 1-4 23.5 (19.5) 1.1 22.1 42.4 3.6 0.7 0.4 6.1 100.0 1,455 Primary 5-8 30.2 (25.5) 0.4 22.2 37.7 4.5 0.2 0.2 4.7 100.0 1,231 Secondary+ 33.4 (26.1) 0.0 34.1 27.9 1.9 0.6 0.1 1.9 100.0 223 Total 26.0 (21.3) 0.7 23.2 39.7 3.5 0.7 0.2 6.0 100.0 4,394 ____________________________________________________________________________________________________________ Note: Number in parentheses is the percentage taken to a health facility as the first response, and on the same day that the fever was recognised or the next day. References * 195 REFERENCES Family Care International (FCI). 1998. The Safe Motherhood Action Agenda: Priorities for the next decade. New York: FCI. Gray, R.H., M.J. Wawer, D. Serwadda, N. Sewankambo, C. Li, F. Wabwire-Mangen, L. Paxton, N. Kiwanuka, G. Kigozi, J. Konde-Lule, T.C. Quinn, C.A. Gaydos, and D. McNairn. 1998. Population- based study of fertility in women with HIV-1 in Uganda. The Lancet 351:98-103 Hunter, S., and J. Williamson. 2000. Children on the brink. Updated estimates and recommendations for intervention. Washington, D.C.: The Synergy Project and USAID. Jamison, D., W.H. Mosley, A. Measham, and J.L. Bobadilla. 1993. Disease control priorities in developing countries. New York: Oxford University Press. Khlat, M., G. Pictet, and S. Le Couer. 2000. Maternal mortality revisited in the AIDS era. Journal of African Reproductive Health 5(1):56-65. Krasovec, K., and M. Anderson. 1991. Maternal nutrition and pregnancy outcomes: Anthropometric assessment. PAHO Scientific Publications No. 259 Washington, D.C.: Pan American Health Organization. National AIDS Control Programme (NACP). 2000. Malawi’s national response to HIV/AIDS for 2000-2004: Combating HIV/AIDS with renewed hope and vigour in the new millennium. Lilongwe, Malawi: NACP. National AIDS Control Programme (NACP). 2001. Estimating national HIV prevalence in Malawi from sentinel surveillance data. Lilongwe, Malawi: NACP. Office of the President and Cabinet (OPC), Department of Economic Planning and Development [Malawi] 1994. National Population Policy. Limbe, Malawi: Montford Press. Stanton, C., N. Abderrahim, and K. Hill. 1997. DHS maternal mortality indicators: An assessment of data quality and implications for data users. DHS Analytical Reports No. 4. Calverton, Maryland (USA): Macro International Inc. Stecklov G. 1995. Maternal mortality estimation: Separating pregnancy-related and nonprgnancy- related risks. Studies in Family Planning 1:33-38. UNAIDS/WHO. 2000. Epidemiological fact sheet on HIV/AIDS and sexually transmitted infections, 2000 update. Geneva, Switzerland. Appendix A * 197 SAMPLE DESIGN APPENDIX A A major objective of the 2000 MDHS sample design was to provide independent estimates with acceptable precision for important population and health indicators. The sample was designed to provide these estimates for different domains, including estimates for the country, for urban and rural areas, for each of the three regions, and for eleven selected districts (each as a separate domain). The selected districts were chosen based on the size of the district (the five largest) and for programmatic importance. The population covered by the 2000 MDHS was all women age 15-49 living in the selected households. The initial target sample was 14,000 completed eligible women interviews, and the final sample was 13,220 completed interviews. Information on sampling errors for five selected variables from the MDHS 1992 was used to help determine the most efficient allocation of the target number of interviews by domain with a minimum allocation of 900 for each of the 11 district domain. Based on this objective and some adjustments to ensure that the sample size requirements for each domain were met, the target number of completed interviews was distributed by districts (see table below). Sample design: Distribution of PUSs by district, Malawi 2000 District Minimum number of complete interviews Total number of PSUs Number of urban PSUs Number of rural PSUs Lilongwe 900 36 16 20 Blantyre 900 36 22 14 Mzimba 900 36 5 31 Mangochi 900 36 2 34 Zomba 900 36 4 32 Kasungu 900 36 2 34 Thyolo 900 36 2 34 Mulanje 900 36 2 34 Machinga Salima Karonga 900 900 900 36 36 36 2 3 5 34 33 31 Other Total 4,100 14,000 164 560 6 71 158 489 1 PSU, Primary Sampling Unit; corresponds to enumerations areas Sample Frame Based on the 1998 census frame, the National Statistical Office developed an updated preliminary master sample to use during the intercensal period. In order to maintain an integrated household survey approach for future household surveys, it was decided that the 2000 MDHS sample should use the preliminary master sample as the sample frame. The 2000 MDHS sample of enumeration areas (EAs) is thus a sub-sample of NSO’s preliminary master sample. 1 Rural enumerations areas (EAs) have populations of between 800 and 1,200 persons; urban EAs have populations of 1,000 to 1,500 persons 198 * Appendix A NSO’s preliminary master sample of EAs is stratified according to district designation and, within districts, by urban-rural designation.1 Since one objective of the master sample is to permit estimation at the district level, the total number of EAs per district was not allocated proportional to population size of the district. Instead, a minimum of 24 EAs were allocated to each district, with certain districts being allocated more EAs based on size and programmatic interest. For instance, Lilongwe and Blantyre districts were each allocated 48 EAs in the master sample. The master sample includes a total of 816 EAs out of the 9,213 EAs established in the 1998 census. A small number of EAs located in national parks and forest areas (representing less than 1 percent of the population of Malawi) were excluded from the master sample. The design features and stratification of the master sample are implicit in the 2000 MDHS and all other subsamples. Sample Selection Based on the 2000 MDHS sample design objectives of 36 EAs per “emphasis” district and adequate urban and rural representation, a total of 560 EAs were selected from the master sample: 489 in rural and 71 in urban areas. Figure A.1 shows the geographic distribution of the EAs or sample points included in the 2000 MDHS. All districts are represented in the sample, but the sample is specifically designed to allow for estimation of certain parameters for the following “oversampled” districts: Lilongwe, Blantyre, Karonga, Mzimba, Kasungu, Salima, Mangochi, Machinga, Zomba, Thyolo, and Mulanje. A simple systematic sample of EAs was implemented district by district; The sample “take” (i.e. number of households sampled) per EA was determined using the following formulae: P1i = {(a * Mi) / ( Σ Mi )} * {c/a} P2i = bi /Li where a is the number of EAs to be selected in each of the urban/rural components of the district sample from the master sample, c is the number of EAs to be selected in each of the urban/rural components of the district sample in the 2000 MDHS sample, Mi is the number of households in the i-th EA in each of the urban/rural components of the district according to the 1998 population census, Σ Mi is the total number of households in each of the urban/rural components of the district according to the 1998 population census, bi is the household sample take selected in each EA, and Appendix A * 199 Li is the total number of households listed in the selected i-th EA during the 2000 MDHS listing operation. Before the final household selection, a complete household listing operation was completed for each selected EA. Based on these household lists, the household selection was then implemented to maintain a self-weighted sample in each domain but the sampling rates differ between districts. Therefore, the total 2000 MDHS sample is weighted, and a final weighting adjustment is required to provide national estimates. All women age 15-49 were targeted for interview in the selected households. Every fourth household was identified for inclusion in the male survey; in those households, all men age 15-54 were identified and considered eligible for individual interview. Sample Implementation The results of the sample implementation for the households and the individual interviews are shown in Tables A.1 and A.2. The results indicate that 15,421 potential households were selected. The MDHS 2001 fieldwork teams successfully completed interviews in 14,213. The main reasons that potential households were not interviewed were that the potential household was found to be vacant at the time of the interview or the household was away for an extended period, in total this accounted for about 6 percent of potential households. A total of 14,352 households were occupied, of which 14,213 were successfully interviewed. Overall, the household response rate was 99 percent. The household response rate was similar among the urban and rural areas and among the three regions, between 98.7 and 99.2 percent. In the interviewed households, 13,538 eligible women were identified, of whom 97.7 percent were interviewed. The individual women’s response rate was also similar among the urban and rural areas and among the three regions (between 97.5 and 98.0 percent). For eligible men the response rate was lower overall (91.6 percent), with a range among domains between 88.8 and 93 percent. 200 * Appendix A Appendix A * 201 A.1 Sample implementation: women Percent distribution of households and eligible women in the 2000 MDHS sample by results of the household and individual interviews and response rates, according to region and urban-rural residence, Malawi 2000 _____________________________________________________________________________________________ Region Residence _________________________ ______________ Result Northern Central Southern Urban Rural Total ____________________________________________________________________________________________ Selected households Completed (C) Household present but no competent respondent at home (HP) Refused (R) Dwelling not found (DNF) Household absent (HA) Dwelling vacant/address not a dwelling (DV) Dwelling destroy (DD) Total Number of households Household response rate (HRR)1 Eligible women Completed (EWC) Not at home (EWNH) Refused (EWR) Partly completed (EWPC) Incapacitated (EWI) Other (EWO) Total Number of women Eligible woman response rate (EWRR)2 Overall response rate (ORR)3 91.7 92.1 92.4 93.4 91.9 92.2 0.3 0.6 0.5 0.6 0.5 0.5 0.0 0.2 0.0 0.2 0.1 0.1 0.4 0.2 0.4 0.5 0.3 0.3 2.0 0.9 0.7 0.8 1.0 1.0 5.1 5.4 5.2 3.9 5.6 5.3 0.4 0.8 0.8 0.7 0.7 0.7 100.0 100.0 100.0 100.0 100.0 100.0 2,490 5,250 7,681 2,868 12,553 15,421 99.2 99.1 99.0 98.7 99.1 99.0 97.7 97.7 97.6 98.0 97.5 97.7 1.4 0.9 1.5 1.1 1.4 1.3 0.0 0.4 0.2 0.3 0.3 0.3 0.0 0.1 0.1 0.1 0.1 0.1 0.8 0.7 0.4 0.4 0.6 0.6 0.1 0.2 0.1 0.1 0.1 0.1 100.0 100.0 100.0 100.0 100.0 100.0 2,239 4,613 6,686 2,929 10,609 13,538 97.7 97.7 97.6 98.0 97.5 97.7 96.9 96.8 96.6 96.8 96.7 96.7 _________________________________________________________________________________________ Note: The household response rate is calculated for completed households as a proportion of completed, no competent respondent, refused, and dwelling not found. The eligible woman response rate is calculated for completed interviews as a proportion of completed, not at home, refused, partially completed, incapacitated and "other." The overall response rate is the product of the household and eligible woman response rates. 1 Using the number of households falling into specific response categories, the household response rate (HRR) is calculated as: C ))))))))))))))))))))) * 100 C + HP + R + DNF 2 Using the number of eligible women falling into specific response categories, the eligible woman response rate (EWRR) is calculated as: EWC )))))))))))))))))))))))))))))))))))))))))))))))))) * 100 EWC + EWNH + EWR + EWPC + EWI + EWO 3 The overall response rate (ORR) is calculated as: ORR = (HRR * EWRR) ÷ 100 202 * Appendix A A.2 Sample implementation: men Percent distribution of households and eligible men in the 2000 MDHS sample by results of the household and individual interviews and response rates, according to region and urban-rural residence, Malawi 2000 _____________________________________________________________________________________________ Region Residence _________________________ ______________ Result Northern Central Southern Urban Rural Total ____________________________________________________________________________________________ Selected households Completed (C) Household present but no competent respondent at home (HP) Refused (R) Dwelling not found (DNF) Household absent (HA) Dwelling vacant/address not a dwelling (DV) Dwelling destroy (DD) Total Number of households Household response rate (HRR)1 Eligible men Completed (EWC) Not at home (EWNH) Postponed (EMP) Refused (EWR) Partly completed (EWPC) Incapacitated (EWI) Other (EWO) Total Number of men Eligible man response rate (EMRR)2 Overall response rate (ORR)3 93.2 92.7 92.9 92.9 92.9 92.9 0.2 0.8 0.7 1.1 0.5 0.6 0.0 0.2 0.1 0.3 0.0 0.1 0.3 0.2 0.4 0.5 0.3 0.3 2.1 1.1 0.7 1.3 1.0 1.1 4.1 4.1 4.5 3.3 4.5 4.3 0.2 1.0 0.6 0.5 0.7 0.7 100.0 100.0 100.0 100.0 100.0 100.0 630 1,307 1,935 748 3,124 3,872 99.5 98.8 98.7 98.0 99.1 98.9 93.0 91.8 90.9 88.8 92.4 91.6 5.0 4.3 6.3 7.4 4.7 5.3 0.3 0.1 0.1 0.1 0.1 0.1 0.5 0.8 0.6 1.5 0.4 0.7 0.2 0.0 0.1 0.0 0.1 0.1 0.3 1.9 1.0 0.9 1.3 1.2 0.7 1.2 1.1 1.4 1.0 1.1 100.0 100.0 100.0 100.0 100.0 100.0 585 1,216 1,576 812 2,565 3,377 93.0 91.8 90.9 88.8 92.4 91.6 92.5 90.7 89.7 87.0 91.6 90.5 _________________________________________________________________________________________ Note: The household response rate is calculated for completed households as a proportion of completed, no competent respondent, refused, and dwelling not found. The eligible man response rate is calculated for completed interviews as a proportion of completed, not at home, postponed, refused, partially completed, incapacitated and "other." The overall response rate is the product of the household and eligible woman response rates. 1 Using the number of households falling into specific response categories, the household response rate (HRR) is calculated as: C )))))))))))))))))))) * 100 C + HP + R + DNF 2 Using the number of eligible men falling into specific response categories, the eligible woman response rate (EMRR) is calculated as: EMC )))))))))))))))))))))))))))))))))))))))))))))))))))))))) * 100 EMC + EMNH + EMP + EMR + EMPC + EMI + EMO 3 The overall response rate (ORR) is calculated as: ORR = (HRR * EMRR) ÷ 100 Appendix B* 203 SAMPLING ERRORS APPENDIX B The estimates from a sample survey are affected by two types of errors: (1) nonsampling errors, and (2) sampling errors. Nonsampling errors are the results of mistakes made in implementing data collection and data processing, such as failure to locate and interview the correct household, misunderstanding of the questions on the part of either the interviewer or the respondent, and data entry errors. Although numerous efforts were made during the implementation of the 2000 MDHS to minimize this type of error, nonsampling errors are impossible to avoid and difficult to evaluate statistically. Sampling errors, on the other hand, can be evaluated statistically. The sample of respondents selected in the 2000 MDHS is only one of many samples that could have been selected from the same population, using the same design and expected size. Each of these samples would yield results that differ somewhat from the results of the actual sample selected. Sampling errors are a measure of the variability between all possible samples. Although the degree of variability is not known exactly, it can be estimated from the survey results. A sampling error is usually measured in terms of the standard error for a particular statistic (mean, percentage, etc.), which is the square root of the variance. The standard error can be used to calculate confidence intervals within which the true value for the population can reasonably be assumed to fall. For example, for any given statistic calculated from a sample survey, the value of that statistic will fall within a range of plus or minus two times the standard error of that statistic in 95 percent of all possible samples of identical size and design. If the sample of respondents had been selected as a simple random sample, it would have been possible to use straightforward formulas for calculating sampling errors. However, the 2000 MDHS sample is the result of a multi-stage stratified design, and, consequently, it was necessary to use more complex formulae. The computer software used to calculate sampling errors for the 2000 MDHS is the ISSA Sampling Error Module (ISSAS). This module used the Taylor linearization method of variance estimation for survey estimates that are means or proportions. The Jacknife repeated replication method is used for variance estimation of more complex statistics such as fertility and mortality rates. The Taylor linearization method treats any percentage or average as a ratio estimate, r = y/x, where y represents the total sample value for variable y, and x represents the total number of cases in the group or subgroup under consideration. The variance of r is computed using the formula given below, with the standard error being the square root of the variance: in which 204 * Appendix B where h represents the stratum which varies from 1 to H, mh is the total number of enumeration areas selected in the h th stratum, yhi is the sum of the values of variable y in EA i in the h th stratum, xhi is the sum of the number of cases in EA i in the h th stratum, and f is the overall sampling fraction, which is so small that it is ignored. The Jacknife repeated replication method derives estimates of complex rates from each of several replications of the parent sample, and calculates standard errors for these estimates using simple formulae. Each replication considers all but one clusters in the calculation of the estimates. Pseudo-independent replications are thus created. In the 2000 MDHS, there were 559 non-empty clusters (one cluster contained no eligible women). Hence, 559 replications were created. The variance of a rate r is calculated as follows: in which where r is the estimate computed from the full sample of 559 clusters, r(i) is the estimate computed from the reduced sample of 558 clusters (i th cluster excluded), and k is the total number of clusters. In addition to the standard error, ISSAS computes the design effect (DEFT) for each estimate, which is defined as the ratio between the standard error using the given sample design and the standard error that would result if a simple random sample had been used. A DEFT value of 1.0 indicates that the sample design is as efficient as a simple random sample, while a value greater than 1.0 indicates the increase in the sampling error due to the use of a more complex and less statistically efficient design. ISSAS also computes the relative error and confidence limits for the estimates. Sampling errors for the 2000 MDHS are calculated for selected variables considered to be of primary interest. The results are presented in this appendix for the country as a whole, for urban and rural areas, for north, central and south regions, and for each of 11 over-sampled district plus the rest of the country. For each variable, the type of statistic (mean, proportion, or rate) and the base population are given in Table B.1. Tables B.2 to B.18 present the value of the statistic (R), its standard error (SE), the number of unweighted (N) and weighted (WN) cases, the design effect (DEFT), the relative standard error (SE/R), and the 95 percent confidence limits (R±2SE), for each variable. The DEFT is considered undefined when the standard error considering simple random sample is zero (when the estimate is close to 0 or 1). In general, the relative standard error for most estimates for the country as a whole is small, except for estimates of very small proportions. There are some differentials in the relative standard error for the estimates of sub-populations. For example, for the variable contraceptive use among currently married women age 15-49, the relative standard errors as a percent of the estimated mean Appendix B* 205 for the whole country, for urban areas, and for rural areas are 2.2 percent, 4.7 percent, and 2.3 percent, respectively. The confidence interval (e.g., as calculated for contraceptive use among currently married women age 15-49) can be interpreted as follows: the overall national sample proportion is 0.306 and its standard error is 0.007. Therefore, to obtain the 95 percent confidence limits, one adds and subtracts twice the standard error to the sample estimate, i.e. 0.306±2(0.007). There is a high probability (95 percent) that the true average proportion of contraceptive use among currently married women age 15 to 49 is between 0.293 and 0.320. 206 * Appendix B Table B.1 List of selected variables for sampling errors, Malawi 2000___________________________________________________________________________________________________ Variable Estimate Base population___________________________________________________________________________________________________ Urban residence Proportion All eligible women 15-49 No education Proportion All eligible women 15-49 Secondary education or higher Proportion All eligible women 15-49 Never married Proportion All eligible women 15-49 Currently married (in union) Proportion All eligible women 15-49 Married before age 20 Proportion All eligible women 25-49 Had first sexual intercourse before 18 Proportion All eligible women 25-49 Children ever born Mean All eligible women 15-49 Children ever born to women 40-49 Mean All eligible women 40-49 Children surviving Mean All eligible women 15-49 Knows any contraceptive method Proportion Currently married women Knows any modern contraceptive method Proportion Currently married women Ever used any contraceptive method Proportion Currently married women Currently using any method Proportion Currently married women Currently using modern method Proportion Currently married women Currently using pill Proportion Currently married women Currently using IUD Proportion Currently married women Currently using injectables Proportion Currently married women Currently using implants Proportion Currently married women Currently using condom Proportion Currently married women Currently using female sterilisation Proportion Currently married women Currently using male sterilisation Proportion Currently married women Currently using periodic abstinence Proportion Currently married women Currently using withdrawal Proportion Currently married women Using public sector source for contraception Proportion Married using modern Want no more children Proportion Currently married women Want to delay next birth at least 2 years Proportion Currently married women Ideal number of children Mean All eligible women 15-49 Mother received tetanus injections Proportion Births in last 5 years Mother received medical care at birth Proportion Births in last 5 years Child had diarrhoea in the last 2 weeks Proportion Children Under-5 Child treated for diarrhoea with ORS packet Proportion Children Under-5 with diarrhoea in last 2 weeks Child received medical treatment for diarrhoea Proportion Children Under-5 with diarrhoea in last 2 weeks Child had health card Proportion Children 12-23 months Child received BCG vaccination Proportion Children 12-23 months Child received DPT vaccination (3 doses) Proportion Children 12-23 months Child received polio vaccination (3 doses) Proportion Children 12-23 months Child received measles vaccination Proportion Children 12-23 months Child fully immunised Proportion Children 12-23 months Weight-for-height (Below -2SD) Proportion Children 0-47 months Height-for-age (Below -2SD) Proportion Children 0-47 months Weight-for-age (Below -2SD) Proportion Children 0-47 months Total fertility rate (last 3 years) Rate Woman-years of exposure to childbearing Neonatal mortality rate Rate Number of births Infant mortality rate Rate Number of births Child mortality rate Rate Number of births Under-5 child mortality rate Rate Number of births Postneonatal mortality rate Rate Number of births ___________________________________________________________________________________________________ MEN__________________________________________________________________________________________________ Urban residence Proportion All eligible men 15-59 No education Proportion All eligible men 15-59 Secondary education or higher Proportion All eligible men 15-59 Never married Proportion All eligible men 15-59 Currently married (in union) Proportion All eligible men 15-59 Knows any contraceptive method Proportion Currently married 15-59 Knows any modern contraceptive method Proportion Currently married 15-59 Ever used any contraceptive method Proportion Currently married 15-59 Currently using any method Proportion Currently married 15-59 Currently using modern method Proportion Currently married 15-59 Currently using pill Proportion Currently married 15-59 Currently using IUD Proportion Currently married 15-59 Currently using injectables Proportion Currently married 15-59 Currently using implants Proportion Currently married 15-59 Currently using condom Proportion Currently married 15-59 Currently using female sterilisation Proportion Currently married 15-59 Currently using male sterilisation Proportion Currently married 15-59 Currently using periodic abstinence Proportion Currently married 15-59 Currently using withdrawal Proportion Currently married 15-59 Want no more children Proportion Currently married 15-59 Want to delay next birth at least 2 years Proportion Currently married 15-59 Ideal number of children Mean All eligible men 15-59 Appendix B* 207 Table B.2 Sampling errors: Total sample, Malawi 2000________________________________________________________________________________________________________ Number of cases_________________ Standard Un- Design Relative Confidence limits Value error weighted Weighted effect error ________________ Variable (R) (SE) (N) (WN) (DEFT) (SE/R) R-2SE R+2SE________________________________________________________________________________________________________ WOMEN________________________________________________________________________________________________________ Urban residence 0.159 0.010 13220 13220 3.181 0.064 0.139 0.180 No education 0.270 0.007 13220 13220 1.849 0.026 0.256 0.285 Secondary education or higher 0.111 0.006 13220 13220 2.310 0.057 0.098 0.124 Never married 0.170 0.005 13220 13220 1.389 0.027 0.161 0.179 Currently married (in union) 0.715 0.005 13220 13220 1.396 0.008 0.704 0.726 Married before age 20 0.746 0.006 10306 10353 1.303 0.007 0.735 0.757 Had first sexual intercourse before 18 0.637 0.006 10306 10353 1.365 0.010 0.624 0.650 Children ever born 3.132 0.029 13220 13220 1.156 0.009 3.074 3.190 Children ever born to women 40-49 6.799 0.079 1966 2004 1.171 0.012 6.642 6.956 Children surviving 2.423 0.022 13220 13220 1.103 0.009 2.380 2.466 Knows any contraceptive method 0.986 0.001 9361 9452 1.077 0.001 0.984 0.989 Knows any modern contraceptive method 0.984 0.001 9361 9452 1.032 0.001 0.982 0.987 Ever used any contraceptive method 0.524 0.007 9361 9452 1.438 0.014 0.509 0.538 Currently using any method 0.306 0.007 9361 9452 1.422 0.022 0.293 0.320 Currently using modern method 0.261 0.007 9361 9452 1.581 0.027 0.247 0.276 Currently using pill 0.027 0.002 9361 9452 1.317 0.081 0.023 0.032 Currently using IUD 0.001 0.000 9361 9452 1.093 0.333 0.000 0.002 Currently using injectables 0.164 0.006 9361 9452 1.528 0.036 0.152 0.176 Currently using implants 0.001 0.000 9361 9452 1.049 0.424 0.000 0.001 Currently using condom 0.016 0.001 9361 9452 1.066 0.087 0.013 0.018 Currently using female sterilisation 0.047 0.003 9361 9452 1.233 0.057 0.042 0.053 Currently using male sterilisation 0.001 0.000 9361 9452 1.062 0.459 0.000 0.001 Currently using periodic abstinence 0.009 0.001 9361 9452 1.200 0.129 0.007 0.011 Currently using withdrawal 0.015 0.001 9361 9452 1.162 0.097 0.012 0.018 Using public sector source for contraception 0.673 0.016 2767 2844 1.815 0.024 0.641 0.705 Want no more children 0.375 0.006 9361 9452 1.179 0.016 0.363 0.387 Want to delay next birth at least 2 years 0.371 0.005 9361 9452 1.098 0.015 0.360 0.382 Ideal number of children 4.994 0.047 13155 13152 1.105 0.009 4.901 5.088 Mother received tetanus injection 0.852 0.005 7626 7675 1.205 0.006 0.842 0.862 Mother received medical care at birth 0.556 0.012 11926 12201 2.191 0.021 0.532 0.579 Child had diarrhoea in the last 2 weeks 0.176 0.004 10367 10559 1.111 0.024 0.168 0.184 Child treated for diarrhoea with ORS packet 0.621 0.014 1755 1859 1.186 0.022 0.594 0.649 Child received medical treatment for diarrhoea 0.283 0.014 1755 1859 1.260 0.048 0.256 0.310 Child had health card 0.811 0.010 2216 2238 1.176 0.012 0.791 0.830 Child received BCG vaccination 0.924 0.006 2216 2238 1.129 0.007 0.911 0.937 Child received DPT vaccination (3 doses) 0.842 0.011 2216 2238 1.430 0.013 0.819 0.864 Child received polio vaccination (3 doses) 0.798 0.012 2216 2238 1.438 0.015 0.774 0.823 Child received measles vaccination 0.832 0.009 2216 2238 1.158 0.011 0.814 0.851 Child fully immunised 0.701 0.013 2216 2238 1.315 0.018 0.675 0.727 Weight-for-height (Below -2 SD) 0.055 0.003 9156 9318 1.375 0.060 0.049 0.062 Height-for-age (Below -2 SD) 0.490 0.007 9156 9318 1.347 0.015 0.476 0.504 Weight-for-age (Below -2 SD) 0.254 0.006 9156 9318 1.373 0.025 0.241 0.267 Total fertility rate (last 3 years) 6.349 0.095 na 37062 1.382 0.015 6.158 6.539 Neonatal mortality (last 5 years) 41.830 2.464 12136 12427 1.204 0.059 36.902 46.759 Infant mortality (last 5 years) 103.804 3.759 12185 12477 1.246 0.036 96.286 111.323 Child mortality (last 5 years) 94.556 3.737 12494 12812 1.202 0.040 86.882 101.831 Under-5 mortality (last 5 years) 188.566 4.702 12548 12868 1.195 0.025 178.962 197.771 Postneonatal mortality (last 5 years) 61.974 2.722 12180 12470 1.158 0.044 56.530 67.418________________________________________________________________________________________________________ MEN________________________________________________________________________________________________________ Urban residence 0.182 0.014 3092 3092 1.950 0.074 0.155 0.210 No education 0.104 0.007 3092 3092 1.202 0.063 0.091 0.117 Secondary education or higher 0.204 0.010 3092 3092 1.320 0.047 0.184 0.223 Never married 0.347 0.010 3092 3092 1.214 0.030 0.326 0.368 Currently married (in union) 0.616 0.010 3092 3092 1.171 0.017 0.596 0.637 Knows any contraceptive method 0.997 0.001 1903 1906 1.116 0.001 0.994 1.000 Know any modern contraceptive method 0.995 0.002 1903 1906 1.219 0.002 0.991 0.999 Ever used any contraceptive method 0.787 0.013 1903 1906 1.359 0.016 0.762 0.813 Currently using any method 0.313 0.012 1901 1904 1.147 0.039 0.288 0.337 Currently using modern method 0.269 0.011 1901 1904 1.109 0.042 0.246 0.291 Currently using pill 0.036 0.007 1901 1904 1.680 0.199 0.022 0.051 Currently using IUD 0.001 0.000 1901 1904 0.840 0.775 0.000 0.002 Currently using injectables 0.114 0.008 1901 1904 1.112 0.071 0.098 0.130 Currently using implants 0.001 0.000 1901 1904 0.820 0.790 0.000 0.001 Currently using condom 0.068 0.007 1901 1904 1.134 0.096 0.055 0.081 Currently using female sterilisation 0.047 0.005 1901 1904 1.097 0.113 0.036 0.058 Currently using male sterilisation 0.001 0.001 1901 1904 0.952 0.817 0.000 0.002 Currently using periodic abstinence 0.008 0.002 1901 1904 1.208 0.309 0.003 0.013 Currently using withdrawal 0.017 0.003 1901 1904 1.017 0.178 0.011 0.023 Want no more children 0.373 0.012 1901 1905 1.077 0.032 0.349 0.397 Want to delay next birth at least 2 years 0.382 0.013 1901 1905 1.180 0.034 0.355 0.408 Ideal number of children 4.814 0.095 3074 3073 1.147 0.020 4.624 5.005__________________________________________________________________________________________________________ na = Not applicable 208 * Appendix B Table B.3 Sampling errors: Urban sample, Malawi 2000________________________________________________________________________________________________________ Number of cases_________________ Standard Un- Design Relative Confidence limits Value error weighted Weighted effect error ________________ Variable (R) (SE) (N) (WN) (DEFT) (SE/R) R-2SE R+2SE________________________________________________________________________________________________________ WOMEN________________________________________________________________________________________________________ Urban residence 1.000 0.000 2871 2106 na 0.000 1.000 1.000 No education 0.103 0.013 2871 2106 2.322 0.128 0.077 0.129 Secondary education or higher 0.364 0.022 2871 2106 2.417 0.060 0.320 0.407 Never married (in union) 0.248 0.017 2871 2106 2.166 0.070 0.213 0.283 Currently married (in union) 0.647 0.019 2871 2106 2.114 0.029 0.609 0.685 Married before age 20 0.632 0.019 2185 1616 1.862 0.030 0.594 0.671 Had first sexual intercourse before 18 0.560 0.019 2185 1616 1.827 0.035 0.521 0.599 Children ever born 2.331 0.078 2871 2106 1.702 0.034 2.174 2.487 Children ever born to women 40-49 5.923 0.273 308 231 1.718 0.046 5.377 6.469 Children surviving 1.959 0.059 2871 2106 1.512 0.030 1.842 2.077 Knows any contraceptive method 0.999 0.001 1853 1362 1.188 0.001 0.996 1.001 Knows any modern contraceptive method 0.998 0.001 1853 1362 1.158 0.001 0.996 1.001 Ever used any contraceptive method 0.638 0.016 1853 1362 1.442 0.025 0.606 0.671 Currently using any method 0.412 0.019 1853 1362 1.702 0.047 0.373 0.451 Currently using modern method 0.382 0.021 1853 1362 1.856 0.055 0.340 0.424 Currently using pill 0.042 0.008 1853 1362 1.731 0.193 0.025 0.058 Currently using IUD 0.003 0.002 1853 1362 1.303 0.594 0.000 0.006 Currently using injectables 0.229 0.016 1853 1362 1.631 0.070 0.197 0.261 Currently using implants 0.003 0.002 1853 1362 1.217 0.513 0.000 0.006 Currently using condom 0.026 0.004 1853 1362 1.191 0.171 0.017 0.034 Currently using female sterilisation 0.076 0.006 1853 1362 0.960 0.078 0.064 0.088 Currently using male sterilisation 0.001 0.001 1853 1362 1.421 0.998 0.000 0.003 Currently using periodic abstinence 0.007 0.003 1853 1362 1.458 0.409 0.001 0.012 Currently using withdrawal 0.010 0.003 1853 1362 1.099 0.248 0.005 0.016 Using public sector source for contraception 0.613 0.047 799 635 2.726 0.077 0.519 0.707 Want no more children 0.389 0.012 1853 1362 1.038 0.030 0.365 0.412 Want to delay next birth at least 2 years 0.355 0.010 1853 1362 0.893 0.028 0.335 0.375 Ideal number of children 4.129 0.081 2863 2103 1.056 0.019 3.968 4.290 Mother received tetanus injections 0.874 0.011 1458 1057 1.299 0.013 0.852 0.897 Mother received medical care at birth 0.816 0.022 2084 1502 2.170 0.027 0.772 0.859 Child had diarrhoea in the last 2 weeks 0.143 0.010 1891 1358 1.152 0.066 0.124 0.162 Child treated for diarrhoea with ORS packet 0.619 0.031 261 195 0.987 0.049 0.558 0.680 Child received medical treatment for diarrhoea 0.349 0.044 261 195 1.454 0.126 0.261 0.438 Child had health card 0.774 0.032 417 307 1.547 0.041 0.711 0.837 Child received BCG vaccination 0.963 0.013 417 307 1.361 0.013 0.938 0.988 Child received DPT vaccination (3 doses) 0.924 0.024 417 307 1.872 0.026 0.876 0.972 Child received polio vaccination (3 doses) 0.858 0.028 417 307 1.621 0.032 0.803 0.914 Child received measles vaccination 0.906 0.022 417 307 1.548 0.024 0.862 0.950 Child fully immunised 0.786 0.036 417 307 1.793 0.046 0.714 0.858 Weight-for-height (Below -2 SD) 0.049 0.010 1697 1220 1.703 0.196 0.030 0.069 Height-for-age (Below -2 SD) 0.342 0.019 1697 1220 1.574 0.056 0.303 0.381 Weight-for-age (Below -2 SD) 0.128 0.011 1697 1220 1.248 0.085 0.106 0.150 Total fertility rate (last 3 years) 4.506 0.247 na 5875 1.894 0.055 4.013 4.999 Neonatal mortality (last 10 years) 29.825 5.332 3846 2772 1.758 0.179 19.160 40.490 Infant mortality (last 10 years) 82.519 8.207 3861 2792 1.802 0.099 66.104 98.934 Child mortality (last 10 years) 71.262 8.173 3879 2805 1.682 0.115 54.917 87.608 Under-5 mortality (last 10 years) 147.900 13.959 3894 2825 2.152 0.094 119.982 175.819 Postneonatal mortality (last 10 years) 52.694 9.097 3861 2792 2.474 0.173 34.500 70.887________________________________________________________________________________________________________ MEN________________________________________________________________________________________________________ Urban residence 1.000 0.000 721 564 na 0.000 1.000 1.000 No education 0.034 0.009 721 564 1.379 0.273 0.016 0.053 Secondary education or higher 0.469 0.031 721 564 1.674 0.066 0.407 0.531 Never married 0.414 0.023 721 564 1.262 0.056 0.368 0.461 Currently married (in union) 0.544 0.024 721 564 1.312 0.045 0.496 0.593 Knows any contraceptive method 1.000 0.000 399 307 na 0.000 1.000 1.000 Knows any modern contraceptive method 0.999 0.001 399 307 0.651 0.001 0.997 1.001 Ever used any contraceptive method 0.782 0.033 399 307 1.613 0.043 0.715 0.848 Currently using any method 0.379 0.031 399 307 1.279 0.082 0.317 0.441 Currently using modern method 0.352 0.029 399 307 1.197 0.081 0.294 0.409 Currently using pill 0.069 0.034 399 307 2.685 0.494 0.001 0.138 Currently using IUD 0.001 0.001 399 307 0.656 1.008 0.000 0.003 Currently using injectables 0.135 0.022 399 307 1.261 0.160 0.092 0.178 Currently using implants 0.000 0.000 399 307 na na 0.000 0.000 Currently using condom 0.076 0.020 399 307 1.510 0.264 0.036 0.116 Currently using female sterilisation 0.069 0.017 399 307 1.337 0.246 0.035 0.103 Currently using male sterilisation 0.001 0.001 399 307 0.611 1.002 0.000 0.003 Currently using periodic abstinence 0.005 0.005 399 307 1.400 0.980 0.000 0.015 Currently using withdrawal 0.020 0.009 399 307 1.252 0.436 0.003 0.038 Want no more children 0.367 0.038 398 307 1.576 0.104 0.290 0.443 Want to delay next birth at least 2 years 0.309 0.038 398 307 1.639 0.123 0.233 0.385 Ideal number of children 3.946 0.186 718 561 1.358 0.047 3.575 4.317 __________________________________________________________________________________________________________ na = Not applicable Appendix B* 209 Table B.4 Sampling errors: Rural sample, Malawi 2000________________________________________________________________________________________________________ Number of cases_________________ Standard Un- Design Relative Confidence limits Value error weighted Weighted effect error ________________ Variable (R) (SE) (N) (WN) (DEFT) (SE/R) R-2SE R+2SE________________________________________________________________________________________________________ WOMEN________________________________________________________________________________________________________ Urban residence 0.000 0.000 10349 11114 na na 0.000 0.000 No education 0.302 0.008 10349 11114 1.672 0.025 0.287 0.317 Secondary education or higher 0.063 0.005 10349 11114 1.942 0.074 0.054 0.072 Never married (in union) 0.155 0.004 10349 11114 1.217 0.028 0.146 0.164 Currently married (in union) 0.728 0.006 10349 11114 1.272 0.008 0.717 0.739 Married before age 20 0.767 0.005 8121 8737 1.149 0.007 0.756 0.778 Had first sexual intercourse before 18 0.651 0.007 8121 8737 1.302 0.011 0.637 0.665 Children ever born 3.284 0.030 10349 11114 1.040 0.009 3.224 3.344 Children ever born to women 40-49 6.913 0.080 1658 1774 1.088 0.012 6.754 7.072 Children surviving 2.511 0.022 10349 11114 1.000 0.009 2.466 2.555 Knows any contraceptive method 0.984 0.001 7508 8089 1.038 0.002 0.981 0.987 Knows any modern contraceptive method 0.982 0.002 7508 8089 0.991 0.002 0.979 0.985 Ever used any contraceptive method 0.504 0.008 7508 8089 1.363 0.016 0.489 0.520 Currently using any method 0.289 0.007 7508 8089 1.252 0.023 0.276 0.302 Currently using modern method 0.241 0.007 7508 8089 1.380 0.028 0.227 0.254 Currently using pill 0.025 0.002 7508 8089 1.180 0.085 0.021 0.029 Currently using IUD 0.001 0.000 7508 8089 1.045 0.400 0.000 0.002 Currently using injectables 0.153 0.006 7508 8089 1.436 0.039 0.141 0.165 Currently using implants 0.000 0.000 7508 8089 0.995 0.721 0.000 0.001 Currently using condom 0.014 0.001 7508 8089 1.014 0.098 0.011 0.017 Currently using female sterilisation 0.043 0.003 7508 8089 1.298 0.071 0.037 0.049 Currently using male sterilisation 0.000 0.000 7508 8089 0.967 0.508 0.000 0.001 Currently using periodic abstinence 0.010 0.001 7508 8089 1.155 0.136 0.007 0.012 Currently using withdrawal 0.016 0.002 7508 8089 1.142 0.104 0.013 0.019 Using public sector source for contraception 0.690 0.017 1968 2209 1.607 0.024 0.657 0.724 Want no more children 0.373 0.007 7508 8089 1.185 0.018 0.360 0.386 Want to delay next birth at least 2 years 0.373 0.006 7508 8089 1.108 0.017 0.361 0.386 Ideal number of children 5.159 0.053 10292 11049 1.088 0.010 5.052 5.266 Mother received tetanus injections 0.848 0.005 6168 6618 1.186 0.006 0.838 0.859 Mother received medical care at birth 0.519 0.013 9842 10698 2.114 0.024 0.494 0.544 Child had diarrhoea in the last 2 weeks 0.181 0.005 8476 9201 1.084 0.025 0.172 0.190 Child treated for diarrhoea with ORS packet 0.621 0.015 1494 1664 1.178 0.024 0.591 0.651 Child received medical treatment for diarrhoea 0.276 0.014 1494 1664 1.199 0.051 0.248 0.304 Child had health card 0.816 0.010 1799 1930 1.112 0.012 0.796 0.837 Child received BCG vaccination 0.918 0.007 1799 1930 1.073 0.008 0.903 0.932 Child received DPT vaccination (3 doses) 0.828 0.012 1799 1930 1.351 0.015 0.804 0.853 Child received polio vaccination (3 doses) 0.789 0.013 1799 1930 1.373 0.017 0.762 0.815 Child received measles vaccination 0.820 0.010 1799 1930 1.073 0.012 0.801 0.840 Child fully immunised 0.687 0.013 1799 1930 1.198 0.019 0.661 0.714 Weight-for-height (Below -2 SD) 0.056 0.004 7459 8098 1.315 0.063 0.049 0.063 Height-for-age (Below -2 SD) 0.512 0.007 7459 8098 1.214 0.014 0.498 0.527 Weight-for-age (Below -2 SD) 0.273 0.007 7459 8098 1.328 0.026 0.259 0.287 Total fertility rate (last 3 years) 6.667 0.088 na 31188 1.211 0.013 6.491 6.842 Neonatal mortality (last 10 years) 47.938 2.142 18245 19865 1.166 0.045 43.654 52.223 Infant mortality (last 10 years) 116.709 3.293 18308 19937 1.240 0.028 110.123 123.294 Child mortality (last 10 years) 106.037 3.210 18501 20158 1.159 0.030 99.617 112.457 Under-5 mortality (last 10 years) 210.370 4.309 18569 20237 1.234 0.020 201.752 218.989 Postneonatal mortality (last 10 years) 68.770 2.397 18303 19930 1.181 0.035 63.977 73.564________________________________________________________________________________________________________ MEN________________________________________________________________________________________________________ Urban residence 0.000 0.000 2371 2528 na na 0.000 0.000 No education 0.120 0.008 2371 2528 1.157 0.064 0.104 0.135 Secondary education or higher 0.144 0.011 2371 2528 1.491 0.075 0.123 0.166 Never married 0.332 0.012 2371 2528 1.216 0.035 0.308 0.355 Currently married (in union) 0.633 0.011 2371 2528 1.156 0.018 0.610 0.655 Knows any contraceptive method 0.996 0.002 1504 1599 1.083 0.002 0.993 1.000 Knows any modern contraceptive method 0.995 0.002 1504 1599 1.201 0.002 0.990 0.999 Ever used any contraceptive method 0.788 0.014 1504 1599 1.311 0.018 0.761 0.816 Currently using any method 0.300 0.013 1502 1597 1.096 0.043 0.274 0.326 Currently using modern method 0.253 0.012 1502 1597 1.055 0.047 0.229 0.277 Currently using pill 0.030 0.005 1502 1597 1.130 0.166 0.020 0.040 Currently using IUD 0.001 0.001 1502 1597 0.895 1.001 0.000 0.002 Currently using injectables 0.110 0.009 1502 1597 1.084 0.080 0.092 0.128 Currently using implants 0.001 0.001 1502 1597 0.796 0.789 0.000 0.002 Currently using condom 0.066 0.007 1502 1597 1.058 0.103 0.053 0.080 Currently using female sterilisation 0.043 0.005 1502 1597 1.046 0.128 0.032 0.054 Currently using male sterilisation 0.001 0.001 1502 1597 1.005 1.000 0.000 0.002 Currently using periodic abstinence 0.009 0.003 1502 1597 1.171 0.325 0.003 0.014 Currently using withdrawal 0.016 0.003 1502 1597 0.968 0.194 0.010 0.023 Want no more children 0.374 0.012 1503 1598 0.978 0.033 0.350 0.399 Want to delay next birth at least 2 years 0.396 0.014 1503 1598 1.073 0.034 0.369 0.423 Ideal number of children 5.008 0.108 2356 2512 1.098 0.022 4.793 5.224__________________________________________________________________________________________________________ na = Not applicable 210 * Appendix B Table B.5 Sampling errors: Northern sample, Malawi 2000________________________________________________________________________________________________________ Number of cases_________________ Standard Un- Design Relative Confidence limits Value error weighted Weighted effect error ________________ Variable (R) (SE) (N) (WN) (DEFT) (SE/R) R-2SE R+2SE________________________________________________________________________________________________________ WOMEN________________________________________________________________________________________________________ Urban residence 0.201 0.068 2187 1453 7.913 0.337 0.065 0.337 No education 0.111 0.017 2187 1453 2.503 0.151 0.078 0.145 Secondary education or higher 0.145 0.022 2187 1453 2.880 0.150 0.101 0.188 Never married (in union) 0.155 0.014 2187 1453 1.866 0.093 0.126 0.184 Currently married (in union) 0.740 0.021 2187 1453 2.190 0.028 0.699 0.781 Married before age 20 0.796 0.012 1671 1121 1.173 0.015 0.773 0.819 Had first sexual intercourse before 18 0.660 0.013 1671 1121 1.142 0.020 0.634 0.687 Children ever born 3.144 0.059 2187 1453 1.011 0.019 3.026 3.261 Children ever born to women 40-49 6.418 0.192 316 215 1.331 0.030 6.035 6.802 Children surviving 2.562 0.045 2187 1453 0.924 0.017 2.473 2.651 Knows any contraceptive method 0.981 0.004 1564 1075 1.051 0.004 0.974 0.988 Knows any modern contraceptive method 0.977 0.004 1564 1075 1.011 0.004 0.970 0.985 Ever used any contraceptive method 0.640 0.022 1564 1075 1.784 0.034 0.597 0.683 Currently using any method 0.354 0.027 1564 1075 2.269 0.078 0.299 0.408 Currently using modern method 0.254 0.036 1564 1075 3.284 0.142 0.181 0.326 Currently using pill 0.044 0.008 1564 1075 1.602 0.189 0.027 0.061 Currently using IUD 0.000 0.000 1564 1075 0.657 1.008 0.000 0.001 Currently using injectables 0.109 0.028 1564 1075 3.512 0.254 0.054 0.165 Currently using implants 0.000 0.000 1564 1075 0.729 1.003 0.000 0.001 Currently using condom 0.047 0.005 1564 1075 0.950 0.108 0.037 0.058 Currently using female sterilisation 0.049 0.008 1564 1075 1.455 0.162 0.033 0.065 Currently using male sterilisation 0.001 0.001 1564 1075 1.231 0.984 0.000 0.003 Currently using periodic abstinence 0.007 0.003 1564 1075 1.398 0.432 0.001 0.012 Currently using withdrawal 0.077 0.012 1564 1075 1.727 0.151 0.054 0.100 Using public sector source for contraception 0.774 0.059 402 299 2.810 0.076 0.657 0.891 Want no more children 0.362 0.016 1564 1075 1.303 0.044 0.330 0.393 Want to delay next birth at least 2 years 0.400 0.015 1564 1075 1.225 0.038 0.369 0.430 Ideal number of children 5.099 0.106 2180 1449 1.207 0.021 4.887 5.311 Mother received tetanus injections 0.854 0.013 1262 865 1.290 0.015 0.829 0.879 Mother received medical care at birth 0.622 0.035 1936 1334 2.708 0.056 0.552 0.691 Child had diarrhoea in the last 2 weeks 0.128 0.011 1718 1166 1.280 0.082 0.107 0.149 Child treated for diarrhoea with ORS packet 0.571 0.038 214 149 1.094 0.067 0.495 0.647 Child received medical treatment for diarrhoea 0.381 0.053 214 149 1.537 0.139 0.276 0.487 Child had health card 0.826 0.022 379 259 1.146 0.027 0.782 0.870 Child received BCG vaccination 0.948 0.016 379 259 1.313 0.016 0.917 0.979 Child received DPT vaccination (3 doses) 0.885 0.024 379 259 1.483 0.027 0.837 0.933 Child received polio vaccination (3 doses) 0.864 0.026 379 259 1.514 0.031 0.812 0.917 Child received measles vaccination 0.858 0.028 379 259 1.514 0.033 0.801 0.914 Child fully immunised 0.778 0.039 379 259 1.806 0.050 0.699 0.856 Weight-for-height (Below -2 SD) 0.047 0.007 1527 1027 1.292 0.147 0.033 0.061 Height-for-age (Below -2 SD) 0.390 0.022 1527 1027 1.739 0.057 0.346 0.434 Weight-for-age (Below -2 SD) 0.174 0.015 1527 1027 1.510 0.087 0.144 0.204 Total fertility rate (last 3 years) 6.240 0.244 na 4051 1.263 0.039 5.752 6.729 Neonatal mortality (last 10 years) 40.850 7.670 3610 2535 1.989 0.188 25.511 56.189 Infant mortality (last 10 years) 101.532 8.624 3618 2546 1.550 0.085 84.284 118.780 Child mortality (last 10 years) 76.550 8.072 3640 2571 1.465 0.105 60.406 92.693 Under-5 mortality (last 10 years) 170.309 13.122 3648 2582 1.724 0.077 144.065 196.554 Postneonatal mortality (last 10 years) 60.682 8.778 3618 2546 2.183 0.145 43.126 78.238________________________________________________________________________________________________________ MEN________________________________________________________________________________________________________ Urban residence 0.251 0.085 544 351 4.555 0.337 0.082 0.421 No education 0.027 0.007 544 351 1.028 0.264 0.013 0.041 Secondary education or higher 0.258 0.032 544 351 1.719 0.125 0.194 0.323 Never married 0.352 0.019 544 351 0.938 0.055 0.314 0.391 Currently married (in union) 0.620 0.018 544 351 0.847 0.028 0.584 0.655 Knows any contraceptive method 1.000 0.000 336 217 na 0.000 1.000 1.000 Knows any modern contraceptive method 0.999 0.001 336 217 0.653 0.001 0.996 1.001 Ever used any contraceptive method 0.884 0.022 336 217 1.236 0.025 0.840 0.927 Currently using any method 0.385 0.026 336 217 0.960 0.066 0.334 0.436 Currently using modern method 0.291 0.030 336 217 1.209 0.103 0.231 0.351 Currently using pill 0.080 0.047 336 217 3.174 0.589 0.000 0.174 Currently using IUD 0.000 0.000 336 217 na na 0.000 0.000 Currently using injectables 0.049 0.019 336 217 1.605 0.387 0.011 0.087 Currently using implants 0.001 0.001 336 217 0.650 1.007 0.000 0.004 Currently using condom 0.111 0.023 336 217 1.342 0.208 0.065 0.157 Currently using female sterilisation 0.045 0.012 336 217 1.042 0.262 0.022 0.069 Currently using male sterilisation 0.005 0.005 336 217 1.294 1.003 0.000 0.015 Currently using periodic abstinence 0.000 0.000 336 217 na na 0.000 0.000 Currently using withdrawal 0.080 0.020 336 217 1.345 0.249 0.040 0.120 Want no more children 0.314 0.031 335 216 1.203 0.097 0.253 0.375 Want to delay next birth at least 2 years 0.484 0.063 335 216 2.307 0.130 0.357 0.610 Ideal number of children 4.820 0.285 542 350 1.841 0.059 4.249 5.391__________________________________________________________________________________________________________ na = Not applicable Appendix B* 211 Table B.6 Sampling errors: Central sample, Malawi 2000________________________________________________________________________________________________________ Number of cases_________________ Standard Un- Design Relative Confidence limits Value error weighted Weighted effect error ________________ Variable (R) (SE) (N) (WN) (DEFT) (SE/R) R-2SE R+2SE________________________________________________________________________________________________________ WOMEN________________________________________________________________________________________________________ Urban residence 0.131 0.009 4508 5321 1.816 0.070 0.113 0.149 No education 0.269 0.011 4508 5321 1.715 0.042 0.247 0.292 Secondary education or higher 0.094 0.009 4508 5321 2.119 0.098 0.075 0.112 Never married (in union) 0.178 0.007 4508 5321 1.266 0.040 0.164 0.193 Currently married (in union) 0.737 0.008 4508 5321 1.251 0.011 0.720 0.753 Married before age 20 0.728 0.009 3534 4200 1.175 0.012 0.710 0.746 Had first sexual intercourse before 18 0.572 0.012 3534 4200 1.399 0.020 0.549 0.595 Children ever born 3.302 0.050 4508 5321 1.122 0.015 3.203 3.402 Children ever born to women 40-49 7.285 0.122 637 762 1.052 0.017 7.042 7.528 Children surviving 2.529 0.035 4508 5321 1.046 0.014 2.459 2.600 Knows any contraceptive method 0.985 0.002 3287 3919 1.118 0.002 0.980 0.990 Knows any modern contraceptive method 0.983 0.002 3287 3919 1.099 0.003 0.978 0.988 Ever used any contraceptive method 0.515 0.013 3287 3919 1.458 0.025 0.489 0.540 Currently using any method 0.314 0.011 3287 3919 1.399 0.036 0.292 0.337 Currently using modern method 0.272 0.012 3287 3919 1.521 0.043 0.248 0.296 Currently using pill 0.021 0.003 3287 3919 1.290 0.152 0.015 0.028 Currently using IUD 0.001 0.000 3287 3919 0.985 0.664 0.000 0.002 Currently using injectables 0.182 0.011 3287 3919 1.585 0.059 0.160 0.203 Currently using implants 0.001 0.000 3287 3919 0.889 0.630 0.000 0.001 Currently using condom 0.011 0.002 3287 3919 1.140 0.190 0.007 0.015 Currently using female sterilisation 0.052 0.005 3287 3919 1.269 0.095 0.042 0.061 Currently using male sterilisation 0.000 0.000 3287 3919 1.015 0.998 0.000 0.001 Currently using periodic abstinence 0.012 0.002 3287 3919 1.142 0.180 0.008 0.016 Currently using withdrawal 0.009 0.002 3287 3919 1.063 0.194 0.006 0.013 Using public sector source for contraception 0.690 0.026 952 1182 1.705 0.037 0.638 0.741 Want no more children 0.433 0.011 3287 3919 1.238 0.025 0.411 0.454 Want to delay next birth at least 2 years 0.356 0.009 3287 3919 1.094 0.026 0.338 0.375 Ideal number of children 5.087 0.082 4481 5293 1.065 0.016 4.924 5.250 Mother received tetanus injections 0.850 0.008 2696 3194 1.221 0.010 0.833 0.866 Mother received medical care at birth 0.522 0.020 4394 5287 2.288 0.039 0.481 0.563 Child had diarrhoea in the last 2 weeks 0.191 0.007 3822 4594 1.075 0.036 0.177 0.205 Child treated for diarrhoea with ORS packet 0.601 0.022 729 878 1.198 0.037 0.556 0.645 Child received medical treatment for diarrhoea 0.212 0.021 729 878 1.375 0.100 0.170 0.254 Child had health card 0.750 0.017 829 974 1.114 0.022 0.717 0.784 Child received BCG vaccination 0.904 0.011 829 974 1.058 0.012 0.882 0.926 Child received DPT vaccination (3 doses) 0.786 0.022 829 974 1.508 0.027 0.743 0.829 Child received polio vaccination (3 doses) 0.738 0.022 829 974 1.408 0.029 0.695 0.782 Child received measles vaccination 0.769 0.016 829 974 1.103 0.021 0.736 0.801 Child fully immunised 0.614 0.019 829 974 1.105 0.031 0.576 0.651 Weight-for-height (Below -2 SD) 0.050 0.006 3331 4017 1.454 0.110 0.039 0.061 Height-for-age (Below -2 SD) 0.555 0.011 3331 4017 1.245 0.020 0.533 0.577 Weight-for-age (Below -2 SD) 0.279 0.011 3331 4017 1.390 0.039 0.257 0.301 Total fertility rate (last 3 years) 6.823 0.142 na 14959 1.229 0.021 6.540 7.106 Neonatal mortality (last 10 years) 42.013 3.241 8179 9832 1.252 0.077 35.532 48.494 Infant mortality (last 10 years) 97.585 4.600 8199 9856 1.268 0.047 88.386 106.784 Child mortality (last 10 years) 114.611 5.017 8314 10002 1.220 0.044 104.576 124.646 Under-5 mortality (last 10 years) 201.012 6.839 8337 10031 1.356 0.034 187.334 214.689 Postneonatal mortality (last 10 years) 55.572 3.237 8196 9852 1.190 0.058 49.099 62.045 ________________________________________________________________________________________________________ MEN________________________________________________________________________________________________________ Urban residence 0.154 0.017 1116 1296 1.573 0.111 0.120 0.188 No education 0.118 0.012 1116 1296 1.200 0.098 0.094 0.141 Secondary education or higher 0.172 0.018 1116 1296 1.562 0.103 0.136 0.207 Never married 0.373 0.019 1116 1296 1.283 0.050 0.335 0.410 Currently married (in union) 0.598 0.018 1116 1296 1.194 0.029 0.563 0.633 Knows any contraceptive method 0.998 0.002 672 775 1.012 0.002 0.995 1.002 Knows any modern contraceptive method 0.998 0.002 672 775 1.012 0.002 0.995 1.002 Ever used any contraceptive method 0.785 0.022 672 775 1.366 0.028 0.742 0.828 Currently using any method 0.336 0.022 671 774 1.219 0.066 0.292 0.381 Currently using modern method 0.282 0.019 671 774 1.077 0.066 0.245 0.320 Currently using pill 0.024 0.007 671 774 1.201 0.295 0.010 0.038 Currently using IUD 0.000 0.000 671 774 na na 0.000 0.000 Currently using injectables 0.128 0.013 671 774 1.010 0.102 0.101 0.154 Currently using implants 0.001 0.001 671 774 0.836 0.998 0.000 0.003 Currently using condom 0.072 0.011 671 774 1.093 0.152 0.050 0.094 Currently using female sterilisation 0.053 0.010 671 774 1.142 0.186 0.034 0.073 Currently using male sterilisation 0.000 0.000 671 774 na na 0.000 0.000 Currently using periodic abstinence 0.013 0.005 671 774 1.144 0.382 0.003 0.023 Currently using withdrawal 0.013 0.004 671 774 1.011 0.336 0.004 0.022 Want no more children 0.399 0.019 672 775 1.025 0.049 0.360 0.438 Want to delay next birth at least 2 years 0.390 0.021 672 775 1.105 0.053 0.348 0.431 Ideal number of children 4.645 0.146 1111 1290 1.194 0.031 4.353 4.936__________________________________________________________________________________________________________ na = Not applicable 212 * Appendix B Table B.7 Sampling errors: Southern sample, Malawi 2000________________________________________________________________________________________________________ Number of cases_________________ Standard Un- Design Relative Confidence limits Value error weighted Weighted effect error ________________ Variable (R) (SE) (N) (WN) (DEFT) (SE/R) R-2SE R+2SE________________________________________________________________________________________________________ WOMEN________________________________________________________________________________________________________ Urban residence 0.173 0.011 6525 6446 2.318 0.063 0.152 0.195 No education 0.307 0.009 6525 6446 1.613 0.030 0.289 0.325 Secondary education or higher 0.118 0.009 6525 6446 2.222 0.075 0.100 0.136 Never married (in union) 0.166 0.006 6525 6446 1.370 0.038 0.153 0.179 Currently married (in union) 0.692 0.007 6525 6446 1.303 0.011 0.677 0.706 Married before age 20 0.750 0.009 5101 5033 1.410 0.011 0.733 0.767 Had first sexual intercourse before 18 0.686 0.008 5101 5033 1.239 0.012 0.670 0.702 Children ever born 2.989 0.039 6525 6446 1.120 0.013 2.910 3.067 Children ever born to women 40-49 6.518 0.119 1013 1027 1.242 0.018 6.280 6.757 Children surviving 2.303 0.031 6525 6446 1.113 0.013 2.242 2.365 Knows any contraceptive method 0.989 0.002 4510 4458 1.007 0.002 0.986 0.992 Knows any modern contraceptive method 0.987 0.002 4510 4458 0.937 0.002 0.984 0.990 Ever used any contraceptive method 0.503 0.009 4510 4458 1.149 0.017 0.486 0.521 Currently using any method 0.288 0.007 4510 4458 1.037 0.024 0.274 0.302 Currently using modern method 0.253 0.007 4510 4458 1.078 0.028 0.239 0.267 Currently using pill 0.029 0.003 4510 4458 1.191 0.103 0.023 0.035 Currently using IUD 0.002 0.001 4510 4458 1.125 0.396 0.000 0.003 Currently using injectables 0.161 0.006 4510 4458 1.052 0.036 0.150 0.173 Currently using implants 0.001 0.000 4510 4458 1.147 0.615 0.000 0.002 Currently using condom 0.012 0.002 4510 4458 1.043 0.139 0.009 0.016 Currently using female sterilisation 0.043 0.003 4510 4458 1.068 0.075 0.037 0.050 Currently using male sterilisation 0.001 0.000 4510 4458 1.070 0.606 0.000 0.002 Currently using periodic abstinence 0.007 0.001 4510 4458 1.149 0.202 0.004 0.010 Currently using withdrawal 0.005 0.001 4510 4458 1.037 0.210 0.003 0.008 Using public sector source for contraception 0.636 0.018 1413 1362 1.439 0.029 0.600 0.673 Want no more children 0.328 0.007 4510 4458 1.027 0.022 0.313 0.342 Want to delay next birth at least 2 years 0.377 0.008 4510 4458 1.055 0.020 0.361 0.392 Ideal number of children 4.894 0.064 6494 6409 1.077 0.013 4.766 5.023 Mother received tetanus injections 0.854 0.007 3668 3615 1.132 0.008 0.840 0.867 Mother received medical care at birth 0.572 0.014 5596 5580 1.839 0.025 0.543 0.600 Child had diarrhoea in the last 2 weeks 0.173 0.006 4827 4799 1.050 0.033 0.162 0.185 Child treated for diarrhoea with ORS packet 0.652 0.019 812 832 1.110 0.029 0.614 0.689 Child received medical treatment for diarrhoea 0.342 0.017 812 832 1.028 0.050 0.307 0.376 Child had health card 0.865 0.013 1008 1005 1.217 0.015 0.839 0.891 Child received BCG vaccination 0.937 0.008 1008 1005 1.109 0.009 0.920 0.954 Child received DPT vaccination (3 doses) 0.884 0.012 1008 1005 1.170 0.014 0.860 0.908 Child received polio vaccination (3 doses) 0.839 0.016 1008 1005 1.361 0.019 0.807 0.871 Child received measles vaccination 0.887 0.011 1008 1005 1.083 0.012 0.865 0.909 Child fully immunised 0.766 0.019 1008 1005 1.385 0.024 0.729 0.803 Weight-for-height (Below -2 SD) 0.062 0.005 4298 4273 1.265 0.077 0.052 0.071 Height-for-age (Below -2 SD) 0.453 0.009 4298 4273 1.182 0.020 0.434 0.471 Weight-for-age (Below -2 SD) 0.250 0.008 4298 4273 1.225 0.033 0.233 0.266 Total fertility rate (last 3 years) 5.958 0.135 na 18052 1.347 0.023 5.687 6.229 Neonatal mortality (last 10 years) 50.462 2.555 10302 10270 1.038 0.051 45.352 55.572 Infant mortality (last 10 years) 129.563 4.398 10352 10327 1.196 0.034 120.766 138.359 Child mortality (last 10 years) 95.244 3.829 10426 10390 1.033 0.040 87.587 102.902 Under-5 mortality (last 10 years) 212.467 5.619 10478 10450 1.215 0.026 201.229 223.705 Postneonatal mortality (last 10 years) 79.101 3.464 10350 10325 1.210 0.044 72.173 86.029________________________________________________________________________________________________________ MEN________________________________________________________________________________________________________ Urban residence 0.192 0.011 1432 1446 1.024 0.056 0.170 0.213 No education 0.111 0.009 1432 1446 1.107 0.083 0.092 0.129 Secondary education or higher 0.219 0.011 1432 1446 1.034 0.052 0.196 0.241 Never married 0.323 0.013 1432 1446 1.050 0.040 0.297 0.349 Currently married (in union) 0.632 0.014 1432 1446 1.112 0.022 0.604 0.660 Knows any contraceptive method 0.995 0.003 895 914 1.111 0.003 0.989 1.000 Knows any modern contraceptive method 0.992 0.004 895 914 1.243 0.004 0.984 0.999 Ever used any contraceptive method 0.767 0.018 895 914 1.275 0.024 0.730 0.803 Currently using any method 0.275 0.016 894 913 1.041 0.057 0.244 0.306 Currently using modern method 0.252 0.016 894 913 1.072 0.062 0.221 0.283 Currently using pill 0.036 0.006 894 913 1.028 0.177 0.023 0.049 Currently using IUD 0.001 0.001 894 913 0.833 0.776 0.000 0.003 Currently using injectables 0.118 0.011 894 913 1.055 0.096 0.095 0.141 Currently using implants 0.000 0.000 894 913 na na 0.000 0.000 Currently using condom 0.054 0.009 894 913 1.128 0.158 0.037 0.071 Currently using female sterilisation 0.042 0.007 894 913 0.996 0.159 0.029 0.055 Currently using male sterilisation 0.000 0.000 894 913 0.529 1.000 0.000 0.001 Currently using periodic abstinence 0.006 0.003 894 913 1.142 0.514 0.000 0.011 Currently using withdrawal 0.005 0.002 894 913 1.064 0.508 0.000 0.010 Want no more children 0.365 0.018 894 914 1.105 0.049 0.329 0.401 Want to delay next birth at least 2 years 0.351 0.016 894 914 1.020 0.046 0.318 0.384 Ideal number of children 4.966 0.140 1421 1433 1.010 0.028 4.685 5.247__________________________________________________________________________________________________________ na = Not applicable Appendix B* 213 Table B.8 Sampling errors: Blantyre sample, Malawi 2000________________________________________________________________________________________________________ Number of cases_________________ Standard Un- Design Relative Confidence limits Value error weighted Weighted effect error ________________ Variable (R) (SE) (N) (WN) (DEFT) (SE/R) R-2SE R+2SE________________________________________________________________________________________________________ WOMEN________________________________________________________________________________________________________ Urban residence 0.682 0.022 1023 1324 1.535 0.033 0.638 0.727 No education 0.100 0.013 1023 1324 1.346 0.126 0.075 0.126 Secondary education or higher 0.341 0.028 1023 1324 1.880 0.082 0.285 0.396 Never married (in union) 0.251 0.018 1023 1324 1.341 0.072 0.215 0.287 Currently married (in union) 0.632 0.019 1023 1324 1.234 0.029 0.595 0.669 Married before age 20 0.658 0.027 781 1008 1.562 0.040 0.604 0.711 Had first sexual intercourse before 18 0.550 0.020 781 1008 1.100 0.036 0.511 0.589 Children ever born 2.360 0.110 1023 1324 1.349 0.046 2.140 2.579 Children ever born to women 40-49 6.346 0.412 132 164 1.623 0.065 5.522 7.169 Children surviving 1.906 0.084 1023 1324 1.262 0.044 1.739 2.074 Knows any contraceptive method 1.000 0.000 656 837 na 0.000 1.000 1.000 Knows any modern contraceptive method 1.000 0.000 656 837 na 0.000 1.000 1.000 Ever used any contraceptive method 0.655 0.018 656 837 0.949 0.027 0.620 0.690 Currently using any method 0.408 0.015 656 837 0.758 0.036 0.379 0.437 Currently using modern method 0.384 0.013 656 837 0.685 0.034 0.358 0.410 Currently using pill 0.038 0.009 656 837 1.201 0.237 0.020 0.055 Currently using IUD 0.005 0.003 656 837 1.002 0.566 0.000 0.010 Currently using injectables 0.226 0.011 656 837 0.697 0.050 0.203 0.249 Currently using implants 0.004 0.002 656 837 1.027 0.671 0.000 0.008 Currently using condom 0.020 0.005 656 837 0.850 0.231 0.011 0.030 Currently using female sterilisation 0.083 0.007 656 837 0.639 0.083 0.069 0.097 Currently using male sterilisation 0.002 0.002 656 837 1.072 0.992 0.000 0.005 Currently using periodic abstinence 0.005 0.003 656 837 1.047 0.591 0.000 0.010 Currently using withdrawal 0.007 0.003 656 837 0.961 0.441 0.001 0.014 Using public sector source for contraception 0.560 0.035 301 390 1.225 0.063 0.490 0.630 Want no more children 0.349 0.018 656 837 0.971 0.052 0.312 0.385 Want to delay next birth at least 2 years 0.369 0.015 656 837 0.818 0.042 0.338 0.400 Ideal number of children 3.900 0.086 1023 1324 0.847 0.022 3.728 4.072 Mother received tetanus injections 0.870 0.011 500 630 0.714 0.013 0.848 0.892 Mother received medical care at birth 0.808 0.021 703 881 1.274 0.027 0.765 0.850 Child had diarrhoea in the last 2 weeks 0.172 0.015 599 755 0.965 0.089 0.141 0.202 Child treated for diarrhoea with ORS packet 0.592 0.042 105 130 0.844 0.071 0.507 0.676 Child received medical treatment for diarrhoea 0.324 0.042 105 130 0.873 0.131 0.239 0.409 Child had health card 0.851 0.047 143 182 1.550 0.055 0.758 0.944 Child received BCG vaccination 0.961 0.015 143 182 0.944 0.016 0.931 0.992 Child received DPT vaccination (3 doses) 0.934 0.024 143 182 1.122 0.025 0.887 0.981 Child received polio vaccination (3 doses) 0.901 0.022 143 182 0.874 0.024 0.857 0.945 Child received measles vaccination 0.917 0.018 143 182 0.780 0.020 0.881 0.953 Child fully immunised 0.829 0.031 143 182 0.971 0.037 0.767 0.891 Weight-for-height (Below -2 SD) 0.067 0.017 531 666 1.441 0.252 0.033 0.100 Height-for-age (Below -2 SD) 0.381 0.027 531 666 1.200 0.072 0.326 0.436 Weight-for-age (Below -2 SD) 0.180 0.020 531 666 1.122 0.110 0.140 0.220 Total fertility rate (last 3 years) 4.295 0.322 na 10594 2.487 0.075 3.651 4.939 Neonatal mortality (last 10 years) 37.812 6.809 1338 1671 1.062 0.180 24.194 51.430 Infant mortality (last 10 years) 106.080 10.173 1345 1681 1.105 0.096 85.735 126.426 Child mortality (last 10 years) 94.675 11.191 1351 1686 1.116 0.118 72.294 117.057 Under-5 mortality (last 10 years) 190.712 17.237 1359 1696 1.430 0.090 156.239 225.186 Postneonatal mortality (last 10 years) 68.268 7.365 1344 1680 1.051 0.108 53.539 82.998________________________________________________________________________________________________________ MEN________________________________________________________________________________________________________ Urban residence 0.698 0.026 252 321 0.892 0.037 0.646 0.749 No education 0.040 0.015 252 321 1.203 0.372 0.010 0.070 Secondary education or higher 0.473 0.027 252 321 0.868 0.058 0.418 0.528 Never married 0.385 0.030 252 321 0.967 0.077 0.326 0.444 Currently married (in union) 0.574 0.031 252 321 0.997 0.054 0.512 0.637 Knows any contraceptive method 1.000 0.000 146 184 na 0.000 1.000 1.000 Knows any modern contraceptive method 1.000 0.000 146 184 na 0.000 1.000 1.000 Ever used any contraceptive method 0.820 0.027 146 184 0.838 0.033 0.766 0.873 Currently using any method 0.361 0.027 146 184 0.672 0.074 0.307 0.414 Currently using modern method 0.331 0.024 146 184 0.620 0.073 0.282 0.379 Want no more children 0.409 0.041 146 184 0.997 0.099 0.328 0.491 Want to delay next birth at least 2 years 0.287 0.032 146 184 0.863 0.113 0.222 0.351 Ideal number of children 3.874 0.202 247 316 0.946 0.052 3.470 4.278__________________________________________________________________________________________________________ na = Not applicable 214 * Appendix B Table B.9 Sampling errors: Karonga sample, Malawi 2000________________________________________________________________________________________________________ Number of cases_________________ Standard Un- Design Relative Confidence limits Value error weighted Weighted effect error ________________ Variable (R) (SE) (N) (WN) (DEFT) (SE/R) R-2SE R+2SE________________________________________________________________________________________________________ WOMEN________________________________________________________________________________________________________ Urban residence 0.157 0.009 941 266 0.785 0.059 0.138 0.175 No education 0.152 0.016 941 266 1.366 0.105 0.120 0.184 Secondary education or higher 0.102 0.009 941 266 0.931 0.090 0.084 0.121 Never married (in union) 0.155 0.012 941 266 0.994 0.076 0.131 0.178 Currently married (in union) 0.719 0.017 941 266 1.126 0.023 0.686 0.752 Married before age 20 0.794 0.019 719 204 1.270 0.024 0.755 0.832 Had first sexual intercourse before 18 0.680 0.018 719 204 1.046 0.027 0.644 0.717 Children ever born 2.926 0.070 941 266 0.802 0.024 2.787 3.065 Children ever born to women 40-49 6.129 0.260 139 39 1.092 0.042 5.609 6.648 Children surviving 2.407 0.063 941 266 0.871 0.026 2.281 2.534 Knows any contraceptive method 0.951 0.009 672 191 1.081 0.009 0.933 0.969 Knows any modern contraceptive method 0.948 0.009 672 191 1.089 0.010 0.930 0.967 Ever used any contraceptive method 0.534 0.019 672 191 0.973 0.035 0.497 0.572 Currently using any method 0.285 0.017 672 191 0.959 0.059 0.252 0.319 Currently using modern method 0.168 0.017 672 191 1.145 0.098 0.135 0.201 Currently using pill 0.018 0.005 672 191 1.084 0.313 0.007 0.029 Currently using IUD 0.002 0.002 672 191 1.022 1.008 0.000 0.005 Currently using injectables 0.064 0.010 672 191 1.059 0.156 0.044 0.084 Currently using implants 0.000 0.000 672 191 na na 0.000 0.000 Currently using condom 0.037 0.006 672 191 0.874 0.171 0.025 0.050 Currently using female sterilisation 0.045 0.013 672 191 1.583 0.280 0.020 0.071 Currently using male sterilisation 0.000 0.000 672 191 na na 0.000 0.000 Currently using periodic abstinence 0.006 0.004 672 191 1.242 0.611 0.000 0.014 Currently using withdrawal 0.091 0.009 672 191 0.851 0.104 0.072 0.110 Using public sector source for contraception 0.645 0.044 136 38 1.060 0.068 0.557 0.732 Want no more children 0.269 0.021 672 191 1.231 0.078 0.227 0.311 Want to delay next birth at least 2 years 0.461 0.018 672 191 0.941 0.039 0.425 0.498 Ideal number of children 4.969 0.076 937 265 0.803 0.015 4.818 5.121 Mother received tetanus injection 0.854 0.015 539 153 1.003 0.018 0.823 0.884 Mother received medical care at birth 0.447 0.031 831 236 1.545 0.069 0.386 0.509 Child had diarrhoea in the last 2 weeks 0.127 0.015 749 213 1.186 0.115 0.097 0.156 Child treated for diarrhoea with ORS packet 0.422 0.080 94 27 1.496 0.190 0.262 0.582 Child received medical treatment for diarrhoea 0.292 0.048 94 27 1.001 0.163 0.197 0.387 Child had health card 0.790 0.040 165 47 1.268 0.051 0.710 0.871 Child received BCG vaccination 0.939 0.020 165 47 1.093 0.022 0.899 0.980 Child received DPT vaccination (3 doses) 0.849 0.026 165 47 0.943 0.031 0.797 0.902 Child received polio vaccination (3 doses) 0.773 0.034 165 47 1.030 0.044 0.706 0.841 Child received measles vaccination 0.817 0.042 165 47 1.346 0.051 0.734 0.900 Child fully immunised 0.677 0.041 165 47 1.118 0.061 0.595 0.760 Weight-for-height (Below -2 SD) 0.052 0.011 681 193 1.272 0.211 0.030 0.074 Height-for-age (Below -2 SD) 0.388 0.016 681 193 0.888 0.042 0.355 0.421 Weight-for-age (Below -2 SD) 0.160 0.014 681 193 0.968 0.085 0.133 0.188 Total fertility rate (last 3 years) 5.642 0.226 na 2176 1.985 0.040 5.190 6.094 Neonatal mortality (last 10 years) 37.610 6.483 1531 435 1.266 0.172 24.644 50.576 Infant mortality (last 10 years) 93.160 10.264 1532 435 1.278 0.110 72.632 113.689 Child mortality (last 10 years) 57.906 6.321 1542 438 0.875 0.109 45.265 70.547 Under-5 mortality (last 10 years) 145.672 11.331 1543 438 1.166 0.078 123.010 168.334 Postneonatal mortality (last 10 years) 55.551 6.661 1532 435 1.087 0.120 42.229 68.872________________________________________________________________________________________________________ MEN________________________________________________________________________________________________________ Urban residence 0.156 0.015 245 64 0.636 0.095 0.127 0.186 No education 0.033 0.012 245 64 1.043 0.362 0.009 0.057 Secondary education or higher 0.269 0.022 245 64 0.773 0.082 0.225 0.313 Never married 0.310 0.026 245 64 0.881 0.084 0.258 0.362 Currently married (in union) 0.629 0.030 245 64 0.966 0.047 0.569 0.689 Knows any contraceptive method 1.000 0.000 154 40 na 0.000 1.000 1.000 Knows any modern contraceptive method 0.993 0.007 154 40 1.030 0.007 0.980 1.007 Ever used any contraceptive method 0.882 0.019 154 40 0.744 0.022 0.843 0.921 Currently using any method 0.437 0.037 154 40 0.934 0.086 0.362 0.512 Currently using modern method 0.280 0.032 154 40 0.880 0.114 0.216 0.344 Want no more children 0.211 0.035 154 40 1.056 0.165 0.141 0.281 Want to delay next birth at least 2 years 0.554 0.043 154 40 1.070 0.078 0.468 0.640 Ideal number of children 5.184 0.235 244 64 1.029 0.045 4.715 5.653 __________________________________________________________________________________________________________ na = Not applicable Appendix B* 215 Table B.10 Sampling errors: Kasungu sample, Malawi 2000________________________________________________________________________________________________________ Number of cases_________________ Standard Un- Design Relative Confidence limits Value error weighted Weighted effect error ________________ Variable (R) (SE) (N) (WN) (DEFT) (SE/R) R-2SE R+2SE________________________________________________________________________________________________________ WOMEN________________________________________________________________________________________________________ Urban residence 0.058 0.013 728 484 1.462 0.218 0.033 0.084 No education 0.212 0.024 728 484 1.604 0.115 0.163 0.260 Secondary education or higher 0.097 0.021 728 484 1.893 0.214 0.056 0.139 Never married (in union) 0.163 0.015 728 484 1.064 0.090 0.133 0.192 Currently married (in union) 0.759 0.015 728 484 0.919 0.019 0.730 0.788 Married before age 20 0.777 0.025 573 384 1.414 0.032 0.728 0.826 Had first sexual intercourse before 18 0.576 0.020 573 384 0.979 0.035 0.536 0.617 Children ever born 3.477 0.109 728 484 0.996 0.031 3.259 3.696 Children ever born to women 40-49 7.572 0.275 88 66 0.972 0.036 7.022 8.123 Children surviving 2.670 0.091 728 484 1.081 0.034 2.489 2.851 Knows any contraceptive method 0.993 0.004 540 367 1.085 0.004 0.986 1.001 Knows any modern contraceptive method 0.991 0.004 540 367 1.065 0.004 0.982 1.000 Ever used any contraceptive method 0.637 0.022 540 367 1.072 0.035 0.593 0.681 Currently using any method 0.361 0.021 540 367 0.992 0.057 0.320 0.402 Currently using modern method 0.263 0.019 540 367 0.982 0.071 0.226 0.301 Currently using pill 0.042 0.010 540 367 1.135 0.235 0.022 0.061 Currently using IUD 0.000 0.000 540 367 0.491 1.000 0.000 0.001 Currently using injectables 0.142 0.014 540 367 0.950 0.101 0.113 0.170 Currently using implants 0.003 0.002 540 367 0.946 0.728 0.000 0.008 Currently using condom 0.033 0.008 540 367 1.036 0.243 0.017 0.048 Currently using female sterilisation 0.032 0.010 540 367 1.332 0.315 0.012 0.052 Currently using male sterilisation 0.000 0.000 540 367 na na 0.000 0.000 Currently using periodic abstinence 0.027 0.010 540 367 1.474 0.380 0.007 0.048 Currently using withdrawal 0.029 0.006 540 367 0.894 0.223 0.016 0.042 Using public sector source for contraception 0.709 0.047 178 109 1.367 0.066 0.615 0.802 Want no more children 0.445 0.023 540 367 1.089 0.052 0.398 0.491 Want to delay next birth at least 2 years 0.344 0.020 540 367 0.975 0.058 0.304 0.384 Ideal number of children 6.676 0.453 720 477 1.568 0.068 5.771 7.582 Mother received tetanus injections 0.861 0.021 436 300 1.303 0.025 0.818 0.903 Mother received medical care at birth 0.447 0.033 701 489 1.543 0.073 0.381 0.512 Child had diarrhoea in the last 2 weeks 0.213 0.016 625 437 0.983 0.075 0.181 0.245 Child treated for diarrhoea with ORS packet 0.687 0.035 136 93 0.888 0.051 0.617 0.756 Child received medical treatment for diarrhoea 0.229 0.044 136 93 1.197 0.192 0.141 0.317 Child had health card 0.715 0.045 142 101 1.204 0.062 0.626 0.804 Child received BCG vaccination 0.910 0.022 142 101 0.957 0.024 0.866 0.955 Child received DPT vaccination (3 doses) 0.813 0.032 142 101 0.992 0.039 0.749 0.876 Child received polio vaccination (3 doses) 0.723 0.046 142 101 1.246 0.063 0.632 0.814 Child received measles vaccination 0.858 0.027 142 101 0.954 0.032 0.804 0.913 Child fully immunised 0.614 0.034 142 101 0.842 0.055 0.547 0.681 Weight-for-height (Below -2 SD) 0.027 0.008 555 385 1.268 0.315 0.010 0.044 Height-for-age (Below -2 SD) 0.474 0.027 555 385 1.277 0.057 0.421 0.528 Weight-for-age (Below -2 SD) 0.207 0.017 555 385 1.010 0.082 0.173 0.241 Total fertility rate (last 3 years) 6.954 0.307 na 4048 1.716 0.044 6.340 7.568 Neonatal mortality (last 10 years) 37.490 6.868 1344 936 1.274 0.183 23.754 51.226 Infant mortality (last 10 years) 93.063 10.056 1348 939 1.312 0.108 72.951 113.174 Child mortality (last 10 years) 125.709 13.719 1370 956 1.324 0.109 98.271 153.147 Under-5 mortality (last 10 years) 207.073 13.099 1374 959 1.130 0.063 180.875 233.270 Postneonatal mortality (last 10 years) 55.572 7.410 1348 939 1.200 0.133 40.753 70.392________________________________________________________________________________________________________ MEN________________________________________________________________________________________________________ Urban residence 0.058 0.014 215 142 0.881 0.242 0.030 0.086 No education 0.099 0.032 215 142 1.573 0.324 0.035 0.164 Secondary education or higher 0.177 0.031 215 142 1.181 0.174 0.116 0.239 Never married 0.370 0.028 215 142 0.855 0.076 0.314 0.427 Currently married (in union) 0.590 0.030 215 142 0.879 0.050 0.531 0.649 Knows any contraceptive method 1.000 0.000 124 84 na 0.000 1.000 1.000 Knows any modern contraceptive method 1.000 0.000 124 84 na 0.000 1.000 1.000 Ever used any contraceptive method 0.957 0.020 124 84 1.119 0.021 0.917 0.998 Currently using any method 0.331 0.051 124 84 1.198 0.153 0.230 0.433 Currently using modern method 0.297 0.044 124 84 1.072 0.149 0.208 0.385 Want no more children 0.417 0.042 124 84 0.956 0.102 0.332 0.502 Want to delay next birth at least 2 years 0.457 0.043 124 84 0.949 0.093 0.372 0.543 Ideal number of children 4.998 0.367 213 140 1.208 0.074 4.263 5.733__________________________________________________________________________________________________________ na = Not applicable 216 * Appendix B Table B.11 Sampling errors: Lilongwe sample, Malawi 2000________________________________________________________________________________________________________ Number of cases_________________ Standard Un- Design Relative Confidence limits Value error weighted Weighted effect error ________________ Variable (R) (SE) (N) (WN) (DEFT) (SE/R) R-2SE R+2SE________________________________________________________________________________________________________ WOMEN________________________________________________________________________________________________________ Urban residence 0.316 0.024 871 1864 1.535 0.077 0.267 0.364 No education 0.241 0.022 871 1864 1.485 0.089 0.198 0.284 Secondary education or higher 0.134 0.021 871 1864 1.781 0.154 0.093 0.175 Never married (in union) 0.173 0.015 871 1864 1.156 0.086 0.144 0.203 Currently married (in union) 0.752 0.017 871 1864 1.150 0.022 0.718 0.786 Married before age 20 0.696 0.018 697 1502 1.015 0.025 0.661 0.732 Had first sexual intercourse before 18 0.621 0.026 697 1502 1.391 0.041 0.569 0.672 Children ever born 3.148 0.103 871 1864 1.079 0.033 2.941 3.355 Children ever born to women 40-49 6.827 0.284 103 224 0.911 0.042 6.260 7.394 Children surviving 2.403 0.065 871 1864 0.905 0.027 2.273 2.532 Knows any contraceptive method 0.997 0.002 637 1402 1.053 0.002 0.992 1.002 Knows any modern contraceptive method 0.997 0.002 637 1402 1.053 0.002 0.992 1.002 Ever used any contraceptive method 0.520 0.028 637 1402 1.409 0.054 0.464 0.576 Currently using any method 0.361 0.026 637 1402 1.354 0.071 0.309 0.412 Currently using modern method 0.328 0.028 637 1402 1.481 0.084 0.272 0.383 Currently using pill 0.024 0.007 637 1402 1.103 0.278 0.011 0.038 Currently using IUD 0.000 0.000 637 1402 na na 0.000 0.000 Currently using injectables 0.221 0.025 637 1402 1.541 0.115 0.170 0.272 Currently using implants 0.000 0.000 637 1402 na na 0.000 0.000 Currently using condom 0.012 0.005 637 1402 1.053 0.378 0.003 0.021 Currently using female sterilisation 0.066 0.010 637 1402 1.054 0.157 0.045 0.087 Currently using male sterilisation 0.000 0.000 637 1402 na na 0.000 0.000 Currently using periodic abstinence 0.007 0.004 637 1402 1.085 0.510 0.000 0.014 Currently using withdrawal 0.006 0.003 637 1402 0.822 0.421 0.001 0.011 Using public sector source for contraception 0.692 0.045 243 514 1.515 0.065 0.602 0.781 Want no more children 0.436 0.024 637 1402 1.207 0.054 0.389 0.484 Want to delay next birth at least 2 years 0.342 0.019 637 1402 1.036 0.057 0.303 0.381 Ideal number of children 4.964 0.125 869 1860 0.699 0.025 4.715 5.214 Mother received tetanus injections 0.882 0.014 503 1091 0.949 0.015 0.855 0.909 Mother received medical care at birth 0.531 0.043 820 1829 2.067 0.081 0.445 0.617 Child had diarrhoea in the last 2 weeks 0.165 0.014 727 1596 1.026 0.086 0.137 0.194 Child treated for diarrhoea with ORS packet 0.558 0.043 113 264 0.923 0.076 0.473 0.644 Child received medical treatment for diarrhoea 0.195 0.052 113 264 1.450 0.269 0.090 0.300 Child had health card 0.750 0.028 142 316 0.775 0.037 0.694 0.805 Child received BCG vaccination 0.914 0.019 142 316 0.833 0.021 0.875 0.952 Child received DPT vaccination (3 doses) 0.823 0.046 142 316 1.458 0.056 0.731 0.915 Child received polio vaccination (3 doses) 0.779 0.045 142 316 1.319 0.058 0.689 0.869 Child received measles vaccination 0.736 0.025 142 316 0.698 0.034 0.685 0.787 Child fully immunised 0.634 0.035 142 316 0.883 0.055 0.564 0.704 Weight-for-height (Below -2 SD) 0.059 0.014 651 1416 1.444 0.234 0.031 0.086 Height-for-age (Below -2 SD) 0.542 0.024 651 1416 1.152 0.043 0.495 0.589 Weight-for-age (Below -2 SD) 0.276 0.022 651 1416 1.258 0.080 0.232 0.320 Total fertility rate (last 3 years) 6.455 0.329 na 15381 2.078 0.051 5.796 7.113 Neonatal mortality (last 10 years) 42.394 7.371 1497 3377 1.265 0.174 27.652 57.136 Infant mortality (last 10 years) 98.487 10.444 1502 3385 1.278 0.106 77.599 119.375 Child mortality (last 10 years) 105.032 11.356 1521 3442 1.342 0.108 82.319 127.745 Under-5 mortality (last 10 years) 193.175 16.150 1527 3453 1.441 0.084 160.874 225.475 Postneonatal mortality (last 10 years) 56.093 6.869 1501 3382 1.079 0.122 42.355 69.832________________________________________________________________________________________________________ MEN________________________________________________________________________________________________________ Urban residence 0.361 0.047 217 487 1.432 0.130 0.267 0.454 No education 0.080 0.022 217 487 1.202 0.277 0.036 0.125 Secondary education or higher 0.228 0.037 217 487 1.282 0.161 0.154 0.301 Never married 0.395 0.037 217 487 1.108 0.093 0.322 0.469 Currently married (in union) 0.574 0.031 217 487 0.908 0.053 0.512 0.635 Knows any contraceptive method 1.000 0.000 122 279 na 0.000 1.000 1.000 Knows any modern contraceptive method 1.000 0.000 122 279 na 0.000 1.000 1.000 Ever used any contraceptive method 0.718 0.048 122 279 1.180 0.067 0.622 0.815 Currently using any method 0.336 0.048 122 279 1.112 0.142 0.241 0.432 Currently using modern method 0.288 0.040 122 279 0.978 0.140 0.207 0.368 Want no more children 0.398 0.040 122 279 0.901 0.101 0.318 0.478 Want to delay next birth at least 2 years 0.399 0.040 122 279 0.903 0.101 0.319 0.479 Ideal number of children 4.383 0.194 216 485 0.827 0.044 3.994 4.772__________________________________________________________________________________________________________ na = Not applicable Appendix B* 217 Table B.12 Sampling errors: Machinga sample, Malawi 2000________________________________________________________________________________________________________ Number of cases_________________ Standard Un- Design Relative Confidence limits Value error weighted Weighted effect error ________________ Variable (R) (SE) (N) (WN) (DEFT) (SE/R) R-2SE R+2SE________________________________________________________________________________________________________ WOMEN________________________________________________________________________________________________________ Urban residence 0.050 0.007 798 481 0.935 0.144 0.036 0.065 No education 0.429 0.027 798 481 1.563 0.064 0.374 0.484 Secondary education or higher 0.046 0.012 798 481 1.629 0.264 0.022 0.070 Never married (in union) 0.115 0.010 798 481 0.870 0.086 0.095 0.134 Currently married (in union) 0.777 0.019 798 481 1.272 0.024 0.739 0.814 Married before age 20 0.769 0.015 636 386 0.914 0.020 0.739 0.800 Had first sexual intercourse before 18 0.740 0.018 636 386 1.046 0.025 0.704 0.777 Children ever born 3.227 0.074 798 481 0.733 0.023 3.079 3.375 Children ever born to women 40-49 6.668 0.333 122 79 1.349 0.050 6.002 7.334 Children surviving 2.474 0.076 798 481 0.969 0.031 2.321 2.626 Knows any contraceptive method 0.964 0.010 604 374 1.317 0.010 0.944 0.984 Knows any modern contraceptive method 0.962 0.010 604 374 1.337 0.011 0.941 0.983 Ever used any contraceptive method 0.492 0.028 604 374 1.378 0.057 0.435 0.548 Currently using any method 0.266 0.021 604 374 1.179 0.080 0.224 0.308 Currently using modern method 0.226 0.022 604 374 1.291 0.097 0.182 0.270 Currently using pill 0.025 0.008 604 374 1.213 0.306 0.010 0.041 Currently using IUD 0.000 0.000 604 374 0.456 0.999 0.000 0.001 Currently using injectables 0.160 0.016 604 374 1.093 0.102 0.128 0.193 Currently using implants 0.000 0.000 604 374 0.459 1.006 0.000 0.001 Currently using condom 0.015 0.005 604 374 1.015 0.338 0.005 0.025 Currently using female sterilisation 0.020 0.007 604 374 1.171 0.330 0.007 0.034 Currently using male sterilisation 0.002 0.002 604 374 1.108 1.008 0.000 0.006 Currently using periodic abstinence 0.004 0.003 604 374 1.052 0.649 0.000 0.010 Currently using withdrawal 0.004 0.003 604 374 1.060 0.654 0.000 0.010 Using public sector source for contraception 0.821 0.042 160 93 1.385 0.051 0.737 0.905 Want no more children 0.323 0.022 604 374 1.129 0.066 0.280 0.366 Want to delay next birth at least 2 years 0.396 0.022 604 374 1.102 0.055 0.352 0.439 Ideal number of children 6.053 0.374 795 479 1.488 0.062 5.305 6.801 Mother received tetanus injections 0.832 0.023 499 306 1.378 0.027 0.786 0.878 Mother received medical care at birth 0.533 0.038 757 469 1.859 0.072 0.456 0.609 Child had diarrhoea in the last 2 weeks 0.152 0.019 668 411 1.363 0.123 0.115 0.190 Child treated for diarrhoea with ORS packet 0.671 0.065 101 63 1.376 0.097 0.541 0.800 Child received medical treatment for diarrhoea 0.383 0.040 101 63 0.798 0.104 0.303 0.463 Child had health card 0.831 0.046 132 78 1.397 0.056 0.739 0.924 Child received BCG vaccination 0.836 0.048 132 78 1.461 0.057 0.741 0.932 Child received DPT vaccination (3 doses) 0.875 0.025 132 78 0.870 0.029 0.824 0.926 Child received polio vaccination (3 doses) 0.855 0.040 132 78 1.282 0.047 0.776 0.935 Child received measles vaccination 0.854 0.033 132 78 1.054 0.038 0.788 0.920 Child fully immunised 0.671 0.049 132 78 1.182 0.073 0.572 0.769 Weight-for-height (Below -2 SD) 0.033 0.007 595 367 0.920 0.201 0.020 0.046 Height-for-age (Below -2 SD) 0.445 0.023 595 367 1.123 0.052 0.399 0.492 Weight-for-age (Below -2 SD) 0.245 0.025 595 367 1.283 0.100 0.196 0.294 Total fertility rate (last 3 years) 6.963 0.309 na 4121 1.917 0.044 6.345 7.582 Neonatal mortality (last 10 years) 56.254 7.484 1346 842 1.014 0.133 41.286 71.222 Infant mortality (last 10 years) 118.242 11.638 1350 845 1.178 0.098 94.966 141.518 Child mortality (last 10 years) 98.839 11.774 1365 855 1.139 0.119 75.291 122.387 Under-5 mortality (last 10 years) 205.394 17.138 1369 858 1.341 0.083 171.119 239.669 Postneonatal mortality (last 10 years) 61.988 9.093 1350 845 1.233 0.147 43.803 80.174________________________________________________________________________________________________________ MEN________________________________________________________________________________________________________ Urban residence 0.056 0.010 173 119 0.570 0.179 0.036 0.076 No education 0.161 0.046 173 119 1.637 0.284 0.070 0.253 Secondary education or higher 0.143 0.033 173 119 1.242 0.232 0.077 0.209 Never married 0.322 0.031 173 119 0.858 0.095 0.261 0.383 Currently married (in union) 0.634 0.042 173 119 1.141 0.066 0.550 0.717 Knows any contraceptive method 0.989 0.011 108 75 1.113 0.011 0.966 1.011 Knows any modern contraceptive method 0.989 0.011 108 75 1.113 0.011 0.966 1.011 Ever used any contraceptive method 0.775 0.043 108 75 1.060 0.055 0.689 0.860 Currently using any method 0.309 0.044 108 75 0.979 0.142 0.221 0.396 Currently using modern method 0.261 0.042 108 75 0.991 0.161 0.177 0.345 Want no more children 0.396 0.059 108 75 1.249 0.149 0.278 0.514 Want to delay next birth at least 2 years 0.322 0.064 108 75 1.428 0.200 0.193 0.451 Ideal number of children 6.642 0.899 171 117 1.404 0.135 4.844 8.440__________________________________________________________________________________________________________ na = Not applicable 218 * Appendix B Table B.13 Sampling errors: Mangochi sample, Malawi 2000________________________________________________________________________________________________________ Number of cases_________________ Standard Un- Design Relative Confidence limits Value error weighted Weighted effect error ________________ Variable (R) (SE) (N) (WN) (DEFT) (SE/R) R-2SE R+2SE________________________________________________________________________________________________________ WOMEN________________________________________________________________________________________________________ Urban residence 0.078 0.007 654 637 0.659 0.088 0.065 0.092 No education 0.492 0.024 654 637 1.245 0.050 0.443 0.540 Secondary education or higher 0.053 0.011 654 637 1.234 0.204 0.031 0.075 Never married (in union) 0.136 0.016 654 637 1.186 0.117 0.104 0.168 Currently married (in union) 0.734 0.016 654 637 0.932 0.022 0.701 0.766 Married before age 20 0.706 0.027 505 494 1.347 0.039 0.651 0.760 Had first sexual intercourse before 18 0.784 0.025 505 494 1.352 0.032 0.735 0.834 Children ever born 3.290 0.105 654 637 0.917 0.032 3.081 3.499 Children ever born to women 40-49 6.888 0.417 103 107 1.320 0.061 6.054 7.721 Children surviving 2.540 0.081 654 637 0.943 0.032 2.378 2.703 Knows any contraceptive method 0.986 0.005 467 467 0.822 0.005 0.977 0.995 Knows any modern contraceptive method 0.983 0.005 467 467 0.857 0.005 0.973 0.993 Ever used any contraceptive method 0.432 0.023 467 467 1.005 0.053 0.386 0.478 Currently using any method 0.216 0.016 467 467 0.826 0.073 0.184 0.247 Currently using modern method 0.167 0.014 467 467 0.789 0.082 0.140 0.194 Currently using pill 0.030 0.009 467 467 1.130 0.300 0.012 0.047 Currently using IUD 0.003 0.003 467 467 1.033 0.834 0.000 0.009 Currently using injectables 0.080 0.014 467 467 1.142 0.179 0.051 0.109 Currently using implants 0.000 0.000 467 467 na na 0.000 0.000 Currently using condom 0.011 0.006 467 467 1.138 0.489 0.000 0.023 Currently using female sterilisation 0.034 0.007 467 467 0.804 0.199 0.020 0.047 Currently using male sterilisation 0.000 0.000 467 467 na na 0.000 0.000 Currently using periodic abstinence 0.000 0.000 467 467 na na 0.000 0.000 Currently using withdrawal 0.005 0.004 467 467 1.125 0.702 0.000 0.013 Using public sector source for contraception 0.649 0.059 105 83 1.265 0.091 0.531 0.768 Want no more children 0.287 0.026 467 467 1.227 0.090 0.236 0.339 Want to delay next birth at least 2 years 0.430 0.034 467 467 1.493 0.080 0.362 0.499 Ideal number of children 7.027 0.302 651 633 0.985 0.043 6.424 7.631 Mother received tetanus injections 0.872 0.018 392 403 1.119 0.021 0.836 0.909 Mother received medical care at birth 0.466 0.056 601 637 2.354 0.120 0.355 0.578 Child had diarrhoea in the last 2 weeks 0.198 0.022 524 553 1.266 0.109 0.155 0.241 Child treated for diarrhoea with ORS packet 0.620 0.050 101 110 1.027 0.080 0.521 0.719 Child received medical treatment for diarrhoea 0.343 0.052 101 110 1.107 0.152 0.239 0.447 Child had health card 0.917 0.032 108 110 1.215 0.034 0.854 0.980 Child received BCG vaccination 0.903 0.033 108 110 1.168 0.036 0.838 0.968 Child received DPT vaccination (3 doses) 0.833 0.046 108 110 1.301 0.055 0.742 0.924 Child received polio vaccination (3 doses) 0.780 0.035 108 110 0.891 0.044 0.711 0.849 Child received measles vaccination 0.887 0.023 108 110 0.783 0.026 0.840 0.933 Child fully immunised 0.690 0.050 108 110 1.149 0.072 0.590 0.790 Weight-for-height (Below -2 SD) 0.057 0.011 463 488 1.106 0.201 0.034 0.079 Height-for-age (Below -2 SD) 0.475 0.031 463 488 1.328 0.065 0.413 0.536 Weight-for-age (Below -2 SD) 0.288 0.025 463 488 1.206 0.088 0.238 0.339 Total fertility rate (last 3 years) 7.410 0.310 na 5512 1.993 0.042 6.790 8.030 Neonatal mortality (last 10 years) 51.748 7.266 1107 1168 1.030 0.140 37.216 66.280 Infant mortality (last 10 years) 115.606 10.366 1112 1172 1.062 0.090 94.874 136.338 Child mortality (last 10 years) 95.509 12.436 1119 1181 1.147 0.130 70.638 120.380 Under-5 mortality (last 10 years) 200.073 15.283 1125 1187 1.149 0.076 169.507 230.639 Postneonatal mortality (last 10 years) 63.858 7.498 1111 1171 1.022 0.117 48.863 78.853________________________________________________________________________________________________________ MEN________________________________________________________________________________________________________ Urban residence 0.080 0.015 154 154 0.684 0.188 0.050 0.110 No education 0.192 0.040 154 154 1.255 0.208 0.112 0.272 Secondary education or higher 0.106 0.022 154 154 0.872 0.205 0.063 0.150 Never married 0.370 0.046 154 154 1.175 0.124 0.278 0.461 Currently married (in union) 0.594 0.057 154 154 1.444 0.097 0.479 0.708 Knows any contraceptive method 0.986 0.014 91 92 1.151 0.014 0.958 1.015 Knows any modern contraceptive method 0.986 0.014 91 92 1.151 0.014 0.958 1.015 Ever used any contraceptive method 0.654 0.063 91 92 1.264 0.097 0.527 0.781 Currently using any method 0.172 0.059 91 92 1.471 0.340 0.055 0.290 Currently using modern method 0.144 0.045 91 92 1.204 0.309 0.055 0.234 Want no more children 0.361 0.048 90 91 0.940 0.133 0.266 0.457 Want to delay next birth at least 2 years 0.371 0.041 90 91 0.810 0.112 0.288 0.454 Ideal number of children 6.049 0.391 153 153 0.794 0.065 5.266 6.832__________________________________________________________________________________________________________ na = Not applicable Appendix B* 219 Table B.14 Sampling errors: Mulanje sample, Malawi 2000________________________________________________________________________________________________________ Number of cases_________________ Standard Un- Design Relative Confidence limits Value error weighted Weighted effect error ________________ Variable (R) (SE) (N) (WN) (DEFT) (SE/R) R-2SE R+2SE________________________________________________________________________________________________________ WOMEN________________________________________________________________________________________________________ Urban residence 0.032 0.004 905 624 0.651 0.120 0.024 0.039 No education 0.277 0.021 905 624 1.382 0.074 0.235 0.318 Secondary education or higher 0.051 0.008 905 624 1.044 0.150 0.036 0.066 Never married (in union) 0.128 0.012 905 624 1.037 0.090 0.105 0.151 Currently married (in union) 0.688 0.017 905 624 1.080 0.024 0.654 0.721 Married before age 20 0.822 0.015 730 502 1.090 0.019 0.791 0.852 Had first sexual intercourse before 18 0.894 0.011 730 502 0.940 0.012 0.872 0.915 Children ever born 3.038 0.080 905 624 0.894 0.026 2.877 3.198 Children ever born to women 40-49 6.297 0.339 133 94 1.299 0.054 5.619 6.974 Children surviving 2.354 0.073 905 624 1.005 0.031 2.207 2.500 Knows any contraceptive method 1.000 0.000 623 429 na 0.000 1.000 1.000 Knows any modern contraceptive method 1.000 0.000 623 429 na 0.000 1.000 1.000 Ever used any contraceptive method 0.550 0.024 623 429 1.203 0.044 0.502 0.598 Currently using any method 0.306 0.027 623 429 1.465 0.089 0.252 0.360 Currently using modern method 0.263 0.028 623 429 1.614 0.108 0.206 0.320 Currently using pill 0.038 0.008 623 429 1.005 0.202 0.023 0.054 Currently using IUD 0.000 0.000 623 429 na na 0.000 0.000 Currently using injectables 0.167 0.024 623 429 1.619 0.145 0.119 0.216 Currently using implants 0.000 0.000 623 429 na na 0.000 0.000 Currently using condom 0.006 0.003 623 429 0.977 0.498 0.000 0.012 Currently using female sterilisation 0.051 0.011 623 429 1.281 0.221 0.028 0.074 Currently using male sterilisation 0.000 0.000 623 429 na na 0.000 0.000 Currently using periodic abstinence 0.005 0.003 623 429 1.044 0.575 0.000 0.011 Currently using withdrawal 0.004 0.003 623 429 1.011 0.643 0.000 0.009 Using public sector source for contraception 0.624 0.045 217 141 1.366 0.072 0.534 0.714 Want no more children 0.306 0.020 623 429 1.076 0.065 0.266 0.346 Want to delay next birth at least 2 years 0.356 0.017 623 429 0.872 0.047 0.322 0.389 Ideal number of children 4.889 0.163 905 624 1.108 0.033 4.564 5.215 Mother received tetanus injections 0.842 0.021 515 357 1.294 0.025 0.801 0.884 Mother received medical care at birth 0.534 0.038 792 553 1.881 0.071 0.458 0.610 Child had diarrhoea in the last 2 weeks 0.179 0.014 673 468 1.000 0.081 0.150 0.207 Child treated for diarrhoea with ORS packet 0.799 0.031 115 83 0.855 0.039 0.736 0.861 Child received medical treatment for diarrhoea 0.378 0.043 115 83 0.978 0.114 0.291 0.464 Child had health card 0.879 0.031 144 100 1.136 0.035 0.818 0.941 Child received BCG vaccination 0.962 0.014 144 100 0.901 0.015 0.934 0.991 Child received DPT vaccination (3 doses) 0.917 0.025 144 100 1.072 0.027 0.868 0.966 Child received polio vaccination (3 doses) 0.842 0.034 144 100 1.138 0.041 0.773 0.911 Child received measles vaccination 0.915 0.027 144 100 1.163 0.029 0.861 0.969 Child fully immunised 0.810 0.044 144 100 1.336 0.054 0.723 0.897 Weight-for-height (Below -2 SD) 0.040 0.007 598 418 0.846 0.166 0.027 0.054 Height-for-age (Below -2 SD) 0.495 0.022 598 418 1.047 0.045 0.450 0.539 Weight-for-age (Below -2 SD) 0.277 0.019 598 418 1.010 0.068 0.239 0.314 Total fertility rate (last 3 years) 5.515 0.196 na 5251 1.850 0.035 5.123 5.906 Neonatal mortality (last 10 years) 61.613 6.235 1456 1009 0.923 0.101 49.142 74.083 Infant mortality (last 10 years) 130.313 8.893 1458 1010 0.874 0.068 112.526 148.100 Child mortality (last 10 years) 111.675 8.429 1479 1024 0.850 0.075 94.817 128.533 Under-5 mortality (last 10 years) 227.435 9.817 1481 1025 0.802 0.043 207.801 247.069 Postneonatal mortality (last 10 years) 68.700 7.775 1458 1010 1.075 0.113 53.150 84.251________________________________________________________________________________________________________ MEN________________________________________________________________________________________________________ Urban residence 0.033 0.009 171 117 0.652 0.269 0.016 0.051 No education 0.062 0.022 171 117 1.184 0.352 0.018 0.106 Secondary education or higher 0.150 0.037 171 117 1.356 0.248 0.076 0.224 Never married 0.312 0.036 171 117 1.023 0.117 0.239 0.385 Currently married (in union) 0.640 0.032 171 117 0.865 0.050 0.577 0.704 Knows any contraceptive method 1.000 0.000 110 75 na 0.000 1.000 1.000 Knows any modern contraceptive method 1.000 0.000 110 75 na 0.000 1.000 1.000 Ever used any contraceptive method 0.679 0.059 110 75 1.326 0.087 0.560 0.797 Currently using any method 0.312 0.050 110 75 1.124 0.160 0.212 0.411 Currently using modern method 0.302 0.048 110 75 1.094 0.159 0.206 0.398 Want no more children 0.529 0.045 110 75 0.942 0.085 0.439 0.619 Want to delay next birth at least 2 years 0.318 0.038 110 75 0.856 0.120 0.242 0.395 Ideal number of children 3.954 0.132 171 117 1.063 0.033 3.690 4.218__________________________________________________________________________________________________________ na = Not applicable 220 * Appendix B Table B.15 Sampling errors: Mzimba sample, Malawi 2000________________________________________________________________________________________________________ Number of cases_________________ Standard Un- Design Relative Confidence limits Value error weighted Weighted effect error ________________ Variable (R) (SE) (N) (WN) (DEFT) (SE/R) R-2SE R+2SE________________________________________________________________________________________________________ WOMEN________________________________________________________________________________________________________ Urban residence 0.199 0.025 781 603 1.714 0.123 0.150 0.248 No education 0.147 0.025 781 603 1.978 0.170 0.097 0.197 Secondary education or higher 0.122 0.016 781 603 1.330 0.128 0.091 0.153 Never married (in union) 0.161 0.018 781 603 1.332 0.109 0.126 0.196 Currently married (in union) 0.760 0.025 781 603 1.642 0.033 0.710 0.810 Married before age 20 0.795 0.015 599 464 0.897 0.019 0.766 0.825 Had first sexual intercourse before 18 0.660 0.017 599 464 0.895 0.026 0.626 0.695 Children ever born 3.310 0.092 781 603 0.910 0.028 3.125 3.495 Children ever born to women 40-49 6.666 0.315 115 101 1.294 0.047 6.037 7.296 Children surviving 2.623 0.068 781 603 0.856 0.026 2.486 2.760 Knows any contraceptive method 0.988 0.005 568 458 1.157 0.005 0.978 0.999 Knows any modern contraceptive method 0.986 0.005 568 458 1.103 0.006 0.975 0.997 Ever used any contraceptive method 0.635 0.033 568 458 1.656 0.053 0.568 0.702 Currently using any method 0.345 0.028 568 458 1.399 0.081 0.289 0.400 Currently using modern method 0.216 0.025 568 458 1.431 0.114 0.167 0.266 Currently using pill 0.043 0.008 568 458 0.979 0.194 0.026 0.060 Currently using IUD 0.000 0.000 568 458 na na 0.000 0.000 Currently using injectables 0.088 0.012 568 458 1.001 0.135 0.064 0.112 Currently using implants 0.001 0.001 568 458 0.668 0.997 0.000 0.002 Currently using condom 0.032 0.007 568 458 0.979 0.226 0.018 0.047 Currently using female sterilisation 0.046 0.014 568 458 1.549 0.296 0.019 0.074 Currently using male sterilisation 0.002 0.002 568 458 1.098 0.952 0.000 0.007 Currently using periodic abstinence 0.009 0.005 568 458 1.387 0.625 0.000 0.019 Currently using withdrawal 0.102 0.018 568 458 1.425 0.178 0.065 0.138 Using public sector source for contraception 0.648 0.054 172 111 1.472 0.083 0.540 0.755 Want no more children 0.379 0.023 568 458 1.110 0.060 0.333 0.424 Want to delay next birth at least 2 years 0.405 0.023 568 458 1.130 0.057 0.359 0.452 Ideal number of children 5.293 0.191 780 603 1.000 0.036 4.910 5.675 Mother received tetanus injections 0.857 0.021 459 368 1.331 0.025 0.814 0.899 Mother received medical care at birth 0.636 0.050 689 562 2.369 0.078 0.537 0.735 Child had diarrhoea in the last 2 weeks 0.138 0.018 611 490 1.283 0.131 0.102 0.174 Child treated for diarrhoea with ORS packet 0.591 0.045 80 67 0.842 0.076 0.501 0.680 Child received medical treatment for diarrhoea 0.325 0.074 80 67 1.327 0.227 0.178 0.472 Child had health card 0.837 0.039 143 110 1.240 0.046 0.760 0.914 Child received BCG vaccination 0.938 0.025 143 110 1.257 0.027 0.887 0.989 Child received DPT vaccination (3 doses) 0.867 0.030 143 110 1.058 0.035 0.806 0.927 Child received polio vaccination (3 doses) 0.854 0.033 143 110 1.121 0.039 0.787 0.920 Child received measles vaccination 0.844 0.034 143 110 1.064 0.040 0.776 0.912 Child fully immunised 0.753 0.045 143 110 1.216 0.060 0.662 0.844 Weight-for-height (Below -2 SD) 0.040 0.010 538 424 1.174 0.245 0.020 0.059 Height-for-age (Below -2 SD) 0.439 0.032 538 424 1.455 0.073 0.375 0.503 Weight-for-age (Below -2 SD) 0.187 0.024 538 424 1.434 0.129 0.139 0.235 Total fertility rate (last 3 years) 6.714 0.386 na 5189 2.064 0.058 5.941 7.487 Neonatal mortality (last 10 years) 52.596 11.657 1296 1075 1.563 0.222 29.281 75.911 Infant mortality (last 10 years) 105.239 15.415 1300 1079 1.507 0.146 74.408 136.070 Child mortality (last 10 years) 84.688 11.124 1308 1086 1.188 0.131 62.440 106.935 Under-5 mortality (last 10 years) 181.014 19.735 1312 1090 1.499 0.109 141.545 220.484 Postneonatal mortality (last 10 years) 52.643 7.485 1300 1079 1.104 0.142 37.674 67.613________________________________________________________________________________________________________ MEN________________________________________________________________________________________________________ Urban residence 0.252 0.036 199 142 1.152 0.141 0.181 0.323 No education 0.030 0.013 199 142 1.095 0.441 0.004 0.057 Secondary education or higher 0.254 0.036 199 142 1.169 0.142 0.182 0.327 Never married 0.300 0.030 199 142 0.917 0.100 0.240 0.359 Currently married (in union) 0.668 0.031 199 142 0.935 0.047 0.605 0.730 Knows any contraceptive method 1.000 0.000 125 95 na 0.000 1.000 1.000 Knows any modern contraceptive method 1.000 0.000 125 95 na 0.000 1.000 1.000 Ever used any contraceptive method 0.872 0.036 125 95 1.184 0.041 0.801 0.943 Currently using any method 0.343 0.039 125 95 0.914 0.113 0.265 0.421 Currently using modern method 0.245 0.032 125 95 0.822 0.129 0.182 0.309 Want no more children 0.347 0.042 124 94 0.980 0.121 0.263 0.431 Want to delay next birth at least 2 years 0.515 0.054 124 94 1.198 0.105 0.407 0.623 Ideal number of children 5.275 0.460 198 142 1.351 0.087 4.355 6.196__________________________________________________________________________________________________________ na = Not applicable Appendix B* 221 Table B.16 Sampling errors: Salima sample, Malawi 2000________________________________________________________________________________________________________ Number of cases_________________ Standard Un- Design Relative Confidence limits Value error weighted Weighted effect error ________________ Variable (R) (SE) (N) (WN) (DEFT) (SE/R) R-2SE R+2SE________________________________________________________________________________________________________ WOMEN________________________________________________________________________________________________________ Urban residence 0.094 0.007 784 301 0.637 0.071 0.081 0.108 No education 0.363 0.038 784 301 2.206 0.104 0.288 0.439 Secondary education or higher 0.092 0.017 784 301 1.690 0.190 0.057 0.127 Never married (in union) 0.162 0.013 784 301 1.014 0.082 0.135 0.189 Currently married (in union) 0.739 0.017 784 301 1.110 0.024 0.704 0.774 Married before age 20 0.698 0.023 610 233 1.224 0.033 0.652 0.743 Had first sexual intercourse before 18 0.578 0.023 610 233 1.170 0.040 0.532 0.625 Children ever born 3.194 0.129 784 301 1.227 0.040 2.937 3.452 Children ever born to women 40-49 7.104 0.187 105 42 0.691 0.026 6.729 7.478 Children surviving 2.415 0.104 784 301 1.271 0.043 2.208 2.622 Knows any contraceptive method 0.954 0.018 577 223 2.034 0.019 0.918 0.989 Knows any modern contraceptive method 0.952 0.018 577 223 2.005 0.019 0.916 0.987 Ever used any contraceptive method 0.365 0.031 577 223 1.545 0.085 0.303 0.427 Currently using any method 0.185 0.024 577 223 1.481 0.130 0.137 0.233 Currently using modern method 0.155 0.025 577 223 1.639 0.160 0.105 0.204 Currently using pill 0.013 0.005 577 223 0.984 0.357 0.004 0.022 Currently using IUD 0.000 0.000 577 223 na na 0.000 0.000 Currently using injectables 0.096 0.020 577 223 1.591 0.203 0.057 0.135 Currently using implants 0.000 0.000 577 223 na na 0.000 0.000 Currently using condom 0.004 0.002 577 223 0.802 0.524 0.000 0.008 Currently using female sterilisation 0.041 0.010 577 223 1.231 0.248 0.021 0.061 Currently using male sterilisation 0.000 0.000 577 223 na na 0.000 0.000 Currently using periodic abstinence 0.005 0.003 577 223 1.053 0.631 0.000 0.011 Currently using withdrawal 0.007 0.003 577 223 0.996 0.499 0.000 0.014 Using public sector source for contraception 0.542 0.051 116 41 1.099 0.094 0.439 0.644 Want no more children 0.381 0.021 577 223 1.018 0.054 0.340 0.422 Want to delay next birth at least 2 years 0.334 0.020 577 223 1.034 0.061 0.293 0.374 Ideal number of children 5.150 0.225 779 299 1.237 0.044 4.699 5.600 Mother received tetanus injections 0.849 0.017 467 181 1.033 0.020 0.815 0.883 Mother received medical care at birth 0.467 0.048 746 293 2.262 0.103 0.371 0.564 Child had diarrhoea in the last 2 weeks 0.162 0.017 629 244 1.097 0.103 0.129 0.195 Child treated for diarrhoea with ORS packet 0.526 0.052 96 40 1.020 0.098 0.423 0.629 Child received medical treatment for diarrhoea 0.244 0.033 96 40 0.777 0.134 0.179 0.309 Child had health card 0.800 0.041 145 54 1.215 0.051 0.718 0.882 Child received BCG vaccination 0.864 0.048 145 54 1.651 0.055 0.769 0.960 Child received DPT vaccination (3 doses) 0.714 0.060 145 54 1.554 0.083 0.595 0.833 Child received polio vaccination (3 doses) 0.698 0.056 145 54 1.450 0.081 0.585 0.811 Child received measles vaccination 0.780 0.046 145 54 1.304 0.059 0.688 0.871 Child fully immunised 0.610 0.059 145 54 1.422 0.097 0.492 0.729 Weight-for-height (Below -2 SD) 0.057 0.013 525 202 1.285 0.224 0.031 0.083 Height-for-age (Below -2 SD) 0.546 0.025 525 202 1.119 0.046 0.497 0.596 Weight-for-age (Below -2 SD) 0.290 0.032 525 202 1.551 0.110 0.226 0.354 Total fertility rate (last 3 years) 6.706 0.261 na 2510 1.113 0.039 6.183 7.228 Neonatal mortality (last 10 years) 55.049 7.616 1387 546 1.062 0.138 39.817 70.281 Infant mortality (last 10 years) 131.883 15.748 1388 547 1.461 0.119 100.386 163.379 Child mortality (last 10 years) 123.923 12.438 1414 558 1.075 0.100 99.046 148.799 Under-5 mortality (last 10 years) 239.462 20.247 1416 559 1.523 0.085 198.968 279.957 Postneonatal mortality (last 10 years) 76.834 10.172 1387 546 1.250 0.132 56.489 97.178________________________________________________________________________________________________________ MEN________________________________________________________________________________________________________ Urban residence 0.109 0.011 174 65 0.450 0.098 0.088 0.130 No education 0.187 0.044 174 65 1.489 0.236 0.099 0.275 Secondary education or higher 0.211 0.053 174 65 1.697 0.249 0.106 0.317 Never married 0.294 0.043 174 65 1.254 0.148 0.207 0.381 Currently married (in union) 0.664 0.048 174 65 1.336 0.072 0.568 0.760 Knows any contraceptive method 1.000 0.000 115 43 na 0.000 1.000 1.000 Knows any modern contraceptive method 1.000 0.000 115 43 na 0.000 1.000 1.000 Ever used any contraceptive method 0.690 0.058 115 43 1.337 0.084 0.574 0.806 Currently using any method 0.220 0.042 115 43 1.076 0.190 0.137 0.303 Currently using modern method 0.196 0.040 115 43 1.078 0.205 0.115 0.276 Want no more children 0.380 0.027 115 43 0.603 0.072 0.325 0.434 Want to delay next birth at least 2 years 0.380 0.038 115 43 0.829 0.099 0.305 0.456 Ideal number of children 4.959 0.383 174 65 1.131 0.077 4.193 5.725__________________________________________________________________________________________________________ na = Not applicable 222 * Appendix B Table B.17 Sampling errors: Thyolo sample, Malawi 2000________________________________________________________________________________________________________ Number of cases_________________ Standard Un- Design Relative Confidence limits Value error weighted Weighted effect error ________________ Variable (R) (SE) (N) (WN) (DEFT) (SE/R) R-2SE R+2SE________________________________________________________________________________________________________ WOMEN________________________________________________________________________________________________________ Urban residence 0.029 0.010 882 687 1.766 0.344 0.009 0.049 No education 0.293 0.035 882 687 2.284 0.120 0.223 0.363 Secondary education or higher 0.062 0.013 882 687 1.641 0.215 0.035 0.089 Never married (in union) 0.130 0.011 882 687 0.970 0.084 0.108 0.152 Currently married (in union) 0.664 0.019 882 687 1.218 0.029 0.625 0.703 Married before age 20 0.782 0.018 698 551 1.162 0.023 0.745 0.818 Had first sexual intercourse before 18 0.710 0.028 698 551 1.603 0.039 0.654 0.765 Children ever born 2.871 0.085 882 687 0.976 0.030 2.700 3.041 Children ever born to women 40-49 5.962 0.235 137 107 0.954 0.039 5.492 6.433 Children surviving 2.191 0.077 882 687 1.104 0.035 2.038 2.344 Knows any contraceptive method 1.000 0.000 575 456 na 0.000 1.000 1.000 Knows any modern contraceptive method 0.998 0.002 575 456 1.035 0.002 0.994 1.002 Ever used any contraceptive method 0.431 0.023 575 456 1.127 0.054 0.384 0.478 Currently using any method 0.259 0.020 575 456 1.078 0.076 0.219 0.298 Currently using modern method 0.244 0.017 575 456 0.973 0.072 0.209 0.279 Currently using pill 0.015 0.005 575 456 0.901 0.301 0.006 0.025 Currently using IUD 0.002 0.002 575 456 1.033 0.999 0.000 0.006 Currently using injectables 0.163 0.019 575 456 1.251 0.118 0.124 0.202 Currently using implants 0.000 0.000 575 456 na na 0.000 0.000 Currently using condom 0.011 0.005 575 456 1.044 0.410 0.002 0.020 Currently using female sterilisation 0.049 0.011 575 456 1.231 0.227 0.027 0.071 Currently using male sterilisation 0.002 0.002 575 456 1.044 1.010 0.000 0.006 Currently using periodic abstinence 0.001 0.001 575 456 0.723 0.994 0.000 0.003 Currently using withdrawal 0.002 0.002 575 456 0.944 0.818 0.000 0.006 Using public sector source for contraception 0.437 0.045 203 156 1.296 0.103 0.347 0.528 Want no more children 0.306 0.017 575 456 0.884 0.056 0.272 0.340 Want to delay next birth at least 2 years 0.330 0.021 575 456 1.074 0.064 0.288 0.372 Ideal number of children 4.158 0.102 880 686 1.319 0.025 3.953 4.363 Mother received tetanus injections 0.856 0.012 487 388 0.765 0.014 0.832 0.880 Mother received medical care at birth 0.599 0.045 706 566 2.188 0.075 0.508 0.689 Child had diarrhoea in the last 2 weeks 0.136 0.014 598 479 1.061 0.106 0.107 0.165 Child treated for diarrhoea with ORS packet 0.630 0.055 80 65 1.013 0.087 0.521 0.739 Child received medical treatment for diarrhoea 0.315 0.049 80 65 0.958 0.155 0.217 0.413 Child had health card 0.857 0.030 129 104 0.978 0.035 0.797 0.917 Child received BCG vaccination 0.959 0.014 129 104 0.826 0.015 0.931 0.988 Child received DPT vaccination (3 doses) 0.926 0.023 129 104 1.017 0.025 0.880 0.973 Child received polio vaccination (3 doses) 0.873 0.032 129 104 1.112 0.037 0.809 0.938 Child received measles vaccination 0.951 0.011 129 104 0.580 0.011 0.929 0.973 Child fully immunised 0.816 0.034 129 104 1.000 0.041 0.748 0.884 Weight-for-height (Below -2 SD) 0.045 0.010 523 418 1.147 0.225 0.025 0.065 Height-for-age (Below -2 SD) 0.463 0.023 523 418 1.041 0.050 0.417 0.508 Weight-for-age (Below -2 SD) 0.259 0.025 523 418 1.291 0.097 0.208 0.309 Total fertility rate (last 3 years) 5.283 0.281 na 5756 1.931 0.053 4.721 5.844 Neonatal mortality (last 10 years) 58.183 8.917 1315 1047 1.185 0.153 40.349 76.018 Infant mortality (last 10 years) 145.456 13.749 1318 1049 1.216 0.095 117.958 172.953 Child mortality (last 10 years) 93.573 9.184 1326 1055 0.908 0.098 75.204 111.941 Under-5 mortality (last 10 years) 225.418 16.598 1329 1057 1.196 0.074 192.221 258.614 Postneonatal mortality (last 10 years) 87.272 8.962 1318 1049 1.045 0.103 69.349 105.196 _______________________________________________________________________________________________________ MEN________________________________________________________________________________________________________ Urban residence 0.027 0.010 179 141 0.789 0.355 0.008 0.046 No education 0.116 0.026 179 141 1.079 0.223 0.064 0.168 Secondary education or higher 0.175 0.033 179 141 1.169 0.190 0.109 0.242 Never married 0.293 0.038 179 141 1.117 0.130 0.217 0.369 Currently married (in union) 0.671 0.039 179 141 1.109 0.058 0.593 0.749 Knows any contraceptive method 1.000 0.000 120 94 na 0.000 1.000 1.000 Knows any modern contraceptive method 1.000 0.000 120 94 na 0.000 1.000 1.000 Ever used any contraceptive method 0.811 0.044 120 94 1.212 0.054 0.724 0.898 Currently using any method 0.216 0.041 120 94 1.091 0.190 0.134 0.299 Currently using modern method 0.198 0.040 120 94 1.089 0.201 0.119 0.278 Want no more children 0.428 0.045 120 94 0.987 0.105 0.338 0.518 Want to delay next birth at least 2 years 0.374 0.040 120 94 0.898 0.107 0.294 0.454 Ideal number of children 3.982 0.115 179 141 0.814 0.029 3.751 4.213__________________________________________________________________________________________________________ na = Not applicable Appendix B* 223 Table B.18 Sampling errors: Zomba sample, Malawi 2000________________________________________________________________________________________________________ Number of cases_________________ Standard Un- Design Relative Confidence limits Value error weighted Weighted effect error ________________ Variable (R) (SE) (N) (WN) (DEFT) (SE/R) R-2SE R+2SE________________________________________________________________________________________________________ WOMEN________________________________________________________________________________________________________ Urban residence 0.111 0.014 899 846 1.346 0.127 0.083 0.139 No education 0.292 0.023 899 846 1.510 0.078 0.247 0.338 Secondary education or higher 0.066 0.011 899 846 1.337 0.167 0.044 0.089 Never married (in union) 0.176 0.013 899 846 1.031 0.074 0.150 0.203 Currently married (in union) 0.668 0.014 899 846 0.916 0.022 0.639 0.696 Married before age 20 0.782 0.021 695 659 1.325 0.027 0.741 0.824 Had first sexual intercourse before 18 0.672 0.016 695 659 0.874 0.023 0.641 0.703 Children ever born 3.182 0.072 899 846 0.743 0.023 3.038 3.326 Children ever born to women 40-49 6.112 0.234 162 171 0.921 0.038 5.645 6.580 Children surviving 2.347 0.048 899 846 0.649 0.021 2.250 2.443 Knows any contraceptive method 0.989 0.006 597 564 1.367 0.006 0.978 1.001 Knows any modern contraceptive method 0.985 0.006 597 564 1.167 0.006 0.973 0.997 Ever used any contraceptive method 0.439 0.021 597 564 1.039 0.048 0.397 0.481 Currently using any method 0.263 0.019 597 564 1.060 0.073 0.225 0.301 Currently using modern method 0.220 0.020 597 564 1.150 0.089 0.181 0.259 Currently using pill 0.014 0.006 597 564 1.185 0.411 0.002 0.025 Currently using IUD 0.000 0.000 597 564 na na 0.000 0.000 Currently using injectables 0.168 0.018 597 564 1.205 0.110 0.131 0.205 Currently using implants 0.001 0.001 597 564 0.593 1.005 0.000 0.002 Currently using condom 0.011 0.006 597 564 1.304 0.510 0.000 0.022 Currently using female sterilisation 0.026 0.007 597 564 1.094 0.272 0.012 0.041 Currently using male sterilisation 0.000 0.000 597 564 na na 0.000 0.000 Currently using periodic abstinence 0.010 0.005 597 564 1.287 0.529 0.000 0.020 Currently using withdrawal 0.004 0.003 597 564 1.173 0.728 0.000 0.011 Using public sector source for contraception 0.843 0.042 169 151 1.504 0.050 0.759 0.927 Want no more children 0.375 0.014 597 564 0.701 0.037 0.347 0.403 Want to delay next birth at least 2 years 0.293 0.017 597 564 0.928 0.059 0.258 0.328 Ideal number of children 4.558 0.128 895 843 0.932 0.028 4.302 4.815 Mother received tetanus injections 0.856 0.022 480 460 1.405 0.026 0.812 0.901 Mother received medical care at birth 0.533 0.025 740 727 1.172 0.047 0.482 0.583 Child had diarrhoea in the last 2 weeks 0.178 0.016 653 633 1.006 0.089 0.146 0.209 Child treated for diarrhoea with ORS packet 0.661 0.048 111 113 1.018 0.072 0.566 0.757 Child received medical treatment for diarrhoea 0.280 0.045 111 113 1.106 0.162 0.190 0.371 Child had health card 0.852 0.024 125 127 0.797 0.029 0.803 0.901 Child received BCG vaccination 0.952 0.019 125 127 1.023 0.020 0.914 0.990 Child received DPT vaccination (3 doses) 0.896 0.019 125 127 0.710 0.021 0.859 0.933 Child received polio vaccination (3 doses) 0.891 0.025 125 127 0.925 0.028 0.841 0.940 Child received measles vaccination 0.879 0.031 125 127 1.115 0.036 0.817 0.942 Child fully immunised 0.843 0.027 125 127 0.867 0.032 0.788 0.897 Weight-for-height (Below -2 SD) 0.077 0.016 592 574 1.477 0.210 0.045 0.109 Height-for-age (Below -2 SD) 0.457 0.025 592 574 1.186 0.054 0.407 0.506 Weight-for-age (Below -2 SD) 0.246 0.024 592 574 1.317 0.098 0.198 0.295 Total fertility rate (last 3 years) 6.219 0.226 na 7613 1.143 0.036 5.766 6.671 Neonatal mortality (last 10 years) 42.590 7.377 1360 1324 1.155 0.173 27.837 57.344 Infant mortality (last 10 years) 151.023 15.671 1371 1336 1.430 0.104 119.682 182.364 Child mortality (last 10 years) 76.690 7.468 1377 1340 0.869 0.097 61.755 91.626 Under-5 mortality (last 10 years) 216.131 16.344 1388 1352 1.297 0.076 183.444 248.818 Postneonatal mortality (last 10 years) 108.433 13.702 1371 1336 1.428 0.126 81.029 135.836 ________________________________________________________________________________________________________ MEN________________________________________________________________________________________________________ Urban residence 0.143 0.015 213 177 0.639 0.107 0.113 0.174 No education 0.133 0.028 213 177 1.180 0.207 0.078 0.188 Secondary education or higher 0.151 0.024 213 177 0.994 0.162 0.102 0.199 Never married 0.328 0.032 213 177 1.003 0.099 0.264 0.393 Currently married (in union) 0.591 0.031 213 177 0.912 0.052 0.529 0.653 Knows any contraceptive method 1.000 0.000 118 105 na 0.000 1.000 1.000 Knows any modern contraceptive method 0.997 0.003 118 105 0.599 0.003 0.991 1.003 Ever used any contraceptive method 0.831 0.035 118 105 1.003 0.042 0.762 0.901 Currently using any method 0.338 0.042 117 104 0.966 0.125 0.254 0.423 Currently using modern method 0.328 0.045 117 104 1.029 0.137 0.238 0.417 Want no more children 0.342 0.050 118 105 1.140 0.146 0.242 0.442 Want to delay next birth at least 2 years 0.251 0.047 118 105 1.163 0.186 0.157 0.344 Ideal number of children 5.378 0.417 212 176 0.962 0.078 4.543 6.213__________________________________________________________________________________________________________ na = Not applicable 224 * Appendix B Appendix C * 225 Table C.1 Household age distribution Single-year age distribution of the de facto household population by sex (weighted), Malawi 2000 __________________________________________________________________________________________________ Males Females Males Females ________________ ________________ ______________ ________________ Age Number Percent Number Percent Age Number Percent Number Percent __________________________________________________________________________________________________ 0 1,319 4.4 1,301 4.1 1 1,110 3.7 1,136 3.6 2 1,043 3.5 1,119 3.5 3 1,071 3.6 1,115 3.5 4 889 3.0 921 2.9 5 812 2.7 780 2.5 6 1,200 4.0 1,226 3.9 7 932 3.1 983 3.1 8 960 3.2 977 3.1 9 860 2.9 843 2.7 10 860 2.9 900 2.8 11 719 2.4 743 2.3 12 900 3.0 908 2.9 13 754 2.5 935 2.9 14 778 2.6 825 2.6 15 651 2.2 559 1.8 16 694 2.3 604 1.9 17 586 2.0 529 1.7 18 635 2.1 739 2.3 19 514 1.7 530 1.7 20 606 2.0 751 2.4 21 540 1.8 620 2.0 22 533 1.8 513 1.6 23 477 1.6 593 1.9 24 489 1.6 536 1.7 25 599 2.0 595 1.9 26 412 1.4 507 1.6 27 421 1.4 431 1.4 28 471 1.6 506 1.6 29 340 1.1 379 1.2 30 474 1.6 463 1.5 31 269 0.9 251 0.8 32 409 1.4 371 1.2 33 200 0.7 238 0.7 34 254 0.8 249 0.8 35 348 1.2 322 1.0 36 352 1.2 347 1.1 37 242 0.8 220 0.7 38 279 0.9 341 1.1 39 202 0.7 208 0.7 40 335 1.1 335 1.1 41 157 0.5 143 0.5 42 289 1.0 264 0.8 43 166 0.6 150 0.5 44 118 0.4 164 0.5 45 198 0.7 193 0.6 46 168 0.6 167 0.5 47 140 0.5 181 0.6 48 182 0.6 217 0.7 49 160 0.5 181 0.6 50 210 0.7 229 0.7 51 158 0.5 238 0.8 52 149 0.5 266 0.8 53 154 0.5 156 0.5 54 111 0.4 193 0.6 55 134 0.4 180 0.6 56 133 0.4 152 0.5 57 116 0.4 141 0.4 58 130 0.4 172 0.5 59 96 0.3 97 0.3 60 198 0.7 225 0.7 61 62 0.2 107 0.3 62 90 0.3 117 0.4 63 64 0.2 112 0.4 64 71 0.2 84 0.3 65 100 0.3 146 0.5 66 46 0.2 74 0.2 67 73 0.2 62 0.2 68 94 0.3 106 0.3 69 84 0.3 77 0.2 70+ 600 2.0 694 2.2 Total 29,990 100.0 31,735 100.0 __________________________________________________________________________________________________ Note: The de facto population includes all residents and nonresidents (visitors) who slept in the household the night before the interview. DATA QUALITY TABLES APPENDIX C 226 * Appendix C Table C.2.1 Age distribution of eligible and interviewed women Percent distribution of the de facto household population of women age 10-54, and of interviewed women age 15-49, and percentage of eligible women who were interviewed (weighted) by five-year groups, Malawi 2000 ______________________________________________________________ Percentage Household population of eligible of women Interviewed women women __________________ ________________ interviewed Age Number Percent Number Percent (weighted) ______________________________________________________________ 10-14 4,311 na na na na 15-19 2,961 22.1 2,842 21.7 96.0 20-24 3,013 22.5 2,945 22.5 97.8 25-29 2,417 18.0 2,372 18.1 98.1 30-34 1,572 11.7 1,546 11.8 98.3 25-39 1,439 10.7 1,413 10.8 98.2 40-44 1,057 7.9 1,036 7.9 98.1 45-49 939 7.0 926 7.1 98.6 50-54 1,082 na na na na 15-49 13,397 na 13,080 na 97.6 ______________________________________________________________ Note: The de facto population includes all residents and nonresidents (visitors) who slept in the household the night before the interview. Weights for both household population of women and interviewed women are household weights. na = Not applicable Table C.2.2 Age distribution of eligible and interviewed men Percent distribution of the de facto household population of men age 10-59, and of interviewed men age 15-54, and percentage of eligible men who were interviewed (weighted) by five-year groups, Malawi 2000 ______________________________________________________________ Percentage Household population of eligible of men Interviewed men men __________________ ________________ interviewed Age Number Percent Number Percent (weighted) ______________________________________________________________ 10-14 1,111 na na na na 15-19 714 21.5 655 21.6 91.7 20-24 644 19.4 584 19.2 90.6 25-29 566 17.1 527 17.3 93.0 30-34 357 10.8 323 10.6 90.5 25-39 355 10.7 332 10.9 93.5 40-44 265 8.0 240 7.9 90.6 45-49 215 6.5 197 6.5 91.7 50-54 199 6.0 179 5.9 90.1 55-59 170 na na na na 15-54 3,317 na 3,038 na 91.6 _____________________________________________________________ Note: The de facto population includes all residents and nonresidents (visitors) who slept in the household the night before the interview. Weights for both household population of men and interviewed men are household weights. na = Not applicable Appendix C * 227 Table C.3 Completeness of reporting Percentage of observations missing information for selected demographic and health questions (weighted), Malawi 2000 ________________________________________________________________________________ Percentage Number missing of Subject Reference group information cases ________________________________________________________________________________ Birth Date Births in past 15 years Month only 1.46 30,271 Month and year 0.02 30,271 Age at death Dead children born in past 15 years 0.24 5,883 Age at/date of first union1 Ever-married women age 15-49 0.39 10,977 Respondent’s education All women age 15-49 0.00 13,220 Child’s size at birth Births in previous 5 years 16.65 6,493 Anthropometry Height Living children 0-59 months 2.05 10,559 Weight 1.37 10,559 Height or weight 2.29 10,559 Diarrhoea in past 2 weeks Living children 0-59 months 1.59 10,559 _______________________________________________________________________________ 1 Both year and age missing 228 * Appendix C Ta bl e C .4 B irt hs b y ca le nd ar y ea rs D ist rib ut io n of b irt hs b y ca le nd ar y ea rs fo r l iv in g (L ), de ad (D ), an d to ta l ( T) c hi ld re n, a cc or di ng to re po rti ng c om pl et en es s, s ex ra tio a t b irt h, a nd ra tio o f b irt hs b y ca le nd ar y ea r, M al aw i 2 00 0 __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ _ Pe rc en ta ge w ith N um be r o f b irt hs co m pl et e bi rth d at e1 Se x ra tio a t b irt h2 C al en da r r at io 3 M al e Fe m al e __ __ __ __ __ __ __ __ __ _ __ __ __ __ __ __ __ __ __ _ __ __ __ __ __ __ __ __ __ _ __ __ _ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ _ __ __ __ __ __ __ __ __ __ _ Ye ar (L ) (D ) (T ) (L ) (D ) (T ) (L ) (D ) (T ) (L ) (D ) (T ) (L ) (D ) (T ) (L ) (D ) (T ) __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ 20 00 1, 79 5 14 7 1, 94 2 10 0. 0 10 0. 0 10 0. 0 10 0. 3 10 8. 3 10 0. 9 - - - 89 9 7 6 97 6 89 6 7 0 96 7 19 99 2, 37 3 29 3 2, 66 6 10 0. 0 99 .7 10 0. 0 95 .2 11 4. 5 97 .1 12 1. 3 11 6. 8 12 0. 8 1, 15 7 15 7 1, 31 3 1, 21 6 13 7 1, 35 2 19 98 2, 11 7 35 5 2, 47 2 10 0. 0 10 0. 0 10 0. 0 98 .2 11 3. 9 10 0. 3 95 .3 10 6. 3 96 .7 1, 04 9 18 9 1, 23 8 1, 06 8 16 6 1, 23 4 19 97 2, 06 9 37 5 2, 44 4 10 0. 0 10 0. 0 10 0. 0 99 .8 10 0. 2 99 .9 10 6. 6 98 .9 10 5. 3 1, 03 4 18 8 1, 22 1 1, 03 6 18 7 1, 22 3 19 96 1, 76 7 40 3 2, 16 9 10 0. 0 99 .8 99 .9 97 .1 99 .2 97 .5 10 0. 1 12 1. 4 10 3. 5 87 0 20 0 1, 07 1 89 6 20 2 1, 09 8 19 95 1, 46 0 28 8 1, 74 9 99 .8 98 .7 99 .6 10 2. 5 97 .5 10 1. 6 74 .4 57 .6 71 .0 73 9 14 2 88 2 72 1 14 6 86 7 19 94 2, 15 9 59 9 2, 75 8 98 .2 95 .6 97 .6 98 .5 10 7. 1 10 0. 3 14 1. 8 15 4. 3 14 4. 3 1, 07 1 31 0 1, 38 1 1, 08 8 28 9 1, 37 7 19 93 1, 58 6 48 8 2, 07 3 99 .0 94 .6 98 .0 10 0. 4 93 .5 98 .7 83 .3 94 .8 85 .7 79 4 23 6 1, 03 0 79 1 25 2 1, 04 3 19 92 1, 65 0 43 0 2, 08 0 97 .9 94 .5 97 .2 10 8. 3 10 6. 8 10 8. 0 11 4. 7 10 3. 8 11 2. 3 85 8 22 2 1, 08 0 79 2 20 8 1, 00 0 19 91 1, 29 0 34 1 1, 63 1 98 .3 93 .8 97 .4 88 .4 11 1. 3 92 .8 - - - 60 5 18 0 78 5 68 5 16 1 84 6 19 96 -2 00 0 10 ,1 21 1, 57 2 11 ,6 93 10 0. 0 99 .9 10 0. 0 98 .0 10 6. 2 99 .0 - - - 5, 00 9 81 0 5, 81 9 5, 11 2 76 2 5, 87 4 19 91 -1 99 5 8, 14 5 2, 14 7 10 ,2 91 98 .6 95 .3 97 .9 99 .8 10 3. 1 10 0. 5 - - - 4, 06 8 1, 09 0 5, 15 8 4, 07 7 1, 05 7 5, 13 4 19 86 -1 99 0 5, 89 0 2, 08 4 7, 97 4 98 .0 94 .9 97 .2 98 .9 11 3. 8 10 2. 6 - - - 2, 92 8 1, 10 9 4, 03 8 2, 96 2 97 5 3, 93 7 19 81 -1 98 5 3, 99 0 1, 55 5 5, 54 4 98 .2 95 .1 97 .3 10 1. 8 11 6. 4 10 5. 7 - - - 2, 01 3 83 6 2, 84 9 1, 97 7 71 8 2, 69 5 < 1 98 1 3, 88 4 2, 01 6 5, 90 1 97 .1 93 .8 96 .0 10 0. 6 10 7. 2 10 2. 8 - - - 1, 94 8 1, 04 3 2, 99 1 1, 93 6 97 3 2, 91 0 Al l 32 ,0 29 9, 37 5 41 ,4 04 98 .7 95 .6 98 .0 99 .4 10 9. 0 10 1. 5 - - - 15 ,9 66 4, 88 9 20 ,8 54 16 ,0 63 4, 48 6 20 ,5 50 __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ na = N ot a pp lic ab le 1 B ot h ye ar a nd m on th o f b irt h gi ve n 2 (B m /B f)* 10 0, w he re B m a nd B f a re th e nu m be rs o f m al e an d fe m al e bi rth s, re sp ec tiv el y 3 [2 B x /(B x- 1+ B x + 1)] *1 00 , w he re B x i s th e nu m be r b irt hs in c al en da r y ea r x Appendix C * 229 Table C.5 Reporting of age at death in days Distribution of reported deaths under 1 month of age by age at death in days, and the percentage of early neonatal deaths reported to occur at ages 0-6 days, for five-year periods preceding the survey, Malawi 2000 ________________________________________________________________ Number of years preceding survey Age at death _________________________________ Total (in days) 0-4 5-9 10-14 15-19 0-19 _______________________________________________________________ <1 125 131 97 70 424 1 81 74 52 42 249 2 44 48 31 24 146 3 34 43 30 31 138 4 31 21 16 10 79 5 18 24 25 11 78 6 9 12 14 16 51 7 64 61 41 28 194 8 9 8 6 6 28 9 6 7 3 3 19 10 7 11 4 4 25 11 2 0 1 2 5 12 1 2 5 1 8 13 3 2 1 1 6 14 19 34 33 16 103 15 4 3 3 1 12 16 2 0 0 2 4 17 4 1 5 0 10 18 0 1 1 0 2 19 1 0 0 1 2 20 2 2 3 4 12 21 12 13 19 6 50 22 0 3 0 1 4 23 5 5 1 0 11 24 5 3 0 0 8 26 3 1 0 1 5 27 1 1 3 0 4 28 6 4 1 3 14 29 6 2 1 0 9 30 10 10 8 2 30 31+ 1 0 0 0 1 % early neonatal2 66.6 67.2 65.7 71.2 67.3 Total 0-30 512 525 404 288 1,729 _______________________________________________________________ 1 Includes cases for which age at death (in exact days) is not known 2 (0-6 days/0-30 days) * 100 230 * Appendix C Table C.6 Reporting of age at death in months Distribution of reported deaths under 2 years of age by age at death in months and the percentage of neonatal deaths reported to occur at ages under one month, for five-year periods preceding the survey, Malawi 2000 _____________________________________________________________ Number of years preceding the survey Age at death _______________________________ Total (in months) 0-4 5-9 10-14 15-19 0-19 _____________________________________________________________ < 1 Montha 515 526 408 288 1,737 1 60 67 60 34 221 2 59 79 66 55 259 3 83 69 66 44 261 4 82 75 67 37 261 5 54 55 40 38 188 6 65 70 75 36 247 7 55 63 80 25 223 8 67 55 68 39 229 9 54 70 75 60 259 10 28 40 44 27 138 11 38 37 36 21 131 12 84 166 148 99 498 13 28 38 45 22 132 14 34 39 31 26 130 15 17 26 18 16 76 16 11 22 13 13 60 17 18 14 6 3 42 18 23 28 21 16 88 19 7 4 12 12 35 20 20 14 10 4 49 21 7 5 3 5 19 22 4 12 3 1 20 23 14 26 14 4 58 24+ 4 4 1 8 17 Missing 0 4 1 0 4 1 Year 18 47 26 17 107 Percent neonatalb 44.4 43.6 37.6 40.9 41.8 Total 0-11 1,159 1,206 1,084 705 4,155 _____________________________________________________________ a Includes deaths under 1 month reported in days b (under 1 month/under 1 year) * 100 Appendix D * 231 SURVEY STAFF APPENDIX D 2000 Malawi Demographic and Health Survey Staff Senior Supervisors L. F. Golosi, Project Manager C. Machinjili, Assistant Project Manager J. S. Ndawala, Project Director L. R. S. Mpando, Field Coordinator L. Magombo, Field Coordinator J. Kaphuka, Field Coordinator R. Chinula, Field Coordinator S. Kang’oma (Mrs), Field Coordinator Field Staff Team Mem bers Position Team 1 W. Nyondo (Mr) Team Leader C. Mponda (Miss) Field Editor J. Galimoto (M rs) Female Interviewer M. Ndovi (M iss) Female Interviewer L. Sichali (Miss) Female Interviewer M. Ng'ambi (Miss) Female Interviewer J. Khumalo (Mr) Male Interviewer/ Asst. Editor I. Msiska (Mr) Male Interviewer/ Health Technician Team 2 J. L. Banda (Mrs) Team Leader/ Health Technician A. Munthali (Mrs) Field Editor P. Chinula (Mrs) Female Interviewer S. Mwithokoma (Mrs) Female Interviewer J. Msowoya (Miss) Female Interviewer A. Nhlema (Miss) Female Interviewer G. Chimpondera (Mrs) Female Interviewer M. Njikho (M r) Male Interviewer/ Asst. Editor Team Mem bers Position Team 3 B. Haleke (Mrs) Team Leader J. Chiwaya (Mrs) Field Editor M. Mchom bo (M rs) Fem. Interviewer/ Health Technician F. M'bawa (Miss) Female Interviewer F. Mhango (Mrs) Female Interviewer G. Nkhoma (Miss) Female Interviewer Z. Veremu (Mr) Male Interviewer E. P. Mulumbi (Mr) Male Interviewer/ Asst. Editor Team 4 J. Ziba (M rs) Team Leader P. Matonyola (Mrs) Field Editor M. R. Mwale (Mrs) Fem. Interviewer/ Health Technician R. Chiumia (Miss) Fem. Interviewer E. Longwe (Miss) Female Interviewer B. Mangoche (M iss) Female Interviewer D. Kantwanje (Miss) Female Interviewer O. Y. Banda (Mr) Male Interviewer G. M. Msiska (Mr) Male Interviewer/ Asst. Editor 232 * Appendix D Team Mem bers Position Team 5 N. Nkhoma (Mrs) Team Leader R. Kumwenda (Miss) Field Editor/ Health Technician S. Mumba (Miss) Female Interviewer D. Saka (Miss) Female Interviewer Y. Chikwawa (Miss) Female Interviewer C. Makwemba (Miss) Female Interviewer M. Mtonga (Miss) Female Interviewer L. Chirwa (Mr) Male Interviewer/ Asst. Editor Team 6 D. Munyenyembe (Mrs) Team Leader/ Health Technician D. Nyirondo (Mrs) Field Editor/ Health Technician C. Kambalame (Mrs) Female Interviewer E. Nanga (Miss) Female Interviewer E. Phiri (Miss) Female Interviewer E. Chilembwe (Miss) Female Interviewer S. Chinjala (Mr) Male Interviewer E. Matewere (Mr) Male Interviewer/ Asst. Editor Team 7 E. Mankhwala (Mr) Team Leader M. Namalueso (Miss) Field Editor/ Health Technician E. Pulaizi (Mrs) Fem. Interviewer/ Health Technician J. Nandolo (M rs) Female Interviewer S. Mbewe (Miss) Female Interviewer I. Kaomba (Miss) Female Interviewer J. Chibayo (Miss) Female Interviewer J. Gomani (Mr) Male Interviewer/ Asst. Editor Team 8 J. Masanche (Mrs) Team Leader/ Health Technician R. Zakaria (Miss) Field Editor R. Saidi (Mrs) Female Interviewer F. Mphedwa (Miss) Female Interviewer Z. Chikho (M iss) Female Interviewer S. Kunje (Miss) Female Interviewer E. Kupatsa Banda (Mrs) Female Interviewer J. Khakona (Mr) Male Interviewer H. A. M. Banda (Mr) Male Interviewer/ Asst. Editor Team Mem bers Position Team 9 S. Chitsanthi (Mr) Team Leader L. Kandikole (M rs) Field Editor/ Health Technician T. Khubvinda (Mrs) Female Interviewer J. Nyalugwe (Miss) Female Interviewer R. Chipatala (Mrs) Female Interviewer F. Chikhaula (Miss) Female Interviewer M. Lembani (Mrs) Female Interviewer J. B. Kapalamula (Mr) Male Interviewer/ Asst. Editor Team 10 G. Kapanga (Mrs) Team Leader M. Malota (Miss) Field Editor R. Kafandiko (Mrs) Fem. Interviewer/ Health Technician S. Malamba (Mrs) Fem. Interviewer/ Health Technician M. Chitete (Mrs) Female Interviewer S. Ndalira (Mrs) Female Interviewer G. Mkandawire (Miss) Female Interviewer V. Pheleni (Mr) Male Interviewer/ Asst. Editor Team 11 C. Chikumba (Mrs) Team Leader E. Ntaba (Miss) Field Editor/ Health Technician C. Matita (Mrs) Female Interviewer F. Nkhoma (Miss) Female Interviewer H. Mtenje (Miss) Female Interviewer T. Phiri (Miss) Female Interviewer O. Balanda (M r) Male Interviewer P. Kasowanjete (Mr) Male Interviewer/ Asst. Editor Team 12 E. Kaulembe (Mrs) Team Leader/ Health Technician I. Gawa (Miss) Field Editor N. Kantunda (Miss) Female Interviewer S. Chiswe (Miss) Female Interviewer G. Hanjahanja (Miss) Female Interviewer F. Matenje (M iss) Female Interviewer B. Ponyani (Mr) Male Interviewer/ Asst. Editor P. Langwani (Mr) Male Interviewer Appendix D * 233 Team Mem bers Position Team 13 F. Matola (Miss) Team Leader/ Health Technician E. Medi (Mrs) Field Editor S. Rashid (Miss) Female Interviewer E. Nguku (Miss) Female Interviewer L. Milambe (Miss) Female Interviewer R. Thingo (Mrs) Female Interviewer M. Soya (Miss) Female Interviewer A. Mteteka (Mr) Male Interviewer/ Asst. Editor Team 14 M. Mituka (Mrs) Team Leader/ Health Technician L. Vito (Miss) Field Editor N. Panje (Miss) Female Interviewer C. Matale (Miss) Female Interviewer E. Potani (Mrs) Female Interviewer M. Kawo (Mrs) Female Interviewer F. Mang'anya (Miss) Female Interviewer L. Golosi (Mr) Male Interviewer/ Asst. Editor Team 15 L. Gombwa (Mr) Team Leader M. Zikapanda (Mrs) Field Editor L. Mbolembole (M iss) Fem. Interviewer/ Health Technician S. Msanama (Miss) Female Interviewer M. Mawina (Miss) Female Interviewer G. Chikoja (Miss) Female Interviewer C. D. Phiri (Miss) Female Interviewer Chai Chen (Mr) Male Interviewer C. Chawawa (M r) Male Interviewer/ Asst. Editor Team 16 E. Sambani (Mr) Team Leader F. Mpando (Mrs) Field Editor B. Kachiwanda (Miss) Fem. Interviewer/Health Technician F. Bechman (Miss) Female Interviewer E. Chimphangu (M rs) Female Interviewer E. Nguluwe (Mrs) Female Interviewer S. Mpasuka (Miss) Female Interviewer Z. Mwabile (Miss) Male Interviewer B. Kakhiwa (Mr) Male Interviewer/ Asst. Editor Team Mem bers Position Team 17 E. Kalilombe (Mrs) Team Leader T. Lipenga (Miss) Field Editor M. Soko (Mrs) Fem. Interviewer/ Health Technician A. Nthemwe (Miss) Female Interviewer J. Maloya (Miss) Female Interviewer M. Kachikuni (Mrs) Female Interviewer I. Bendala (Miss) Female Interviewer V. Mzama (Miss) Female Interviewer G. Jimu (Mr) Male Interviewer/ Asst. Editor Team 18 G. Mshali (Mrs) Team Leader T. Chimutu (Mrs) Field Editor R. Mzumzu (Mrs) Fem. Interviewer/ Health Technician M. Ndoliro (M iss) Fem. Interviewer/ Health Technician D. Chikoti (Miss) Female Interviewer D. Sosola (Miss) Female Interviewer M. Mtende (Miss) Female Interviewer J. Mkandawire (Mr) Male Interviewer/ Asst. Editor S. Chipwatali (Mr) Male Interviewer Team 19 S. Mac Jessie (Mrs) Team Leader/ Heath Technician M. Chakanza (M rs) Field Editor M. Chipili (Miss) Female Interviewer E. Golosi (Miss) Female Interviewer A. U. Phiri (Miss) Female Interviewer M. Nkangala (Miss) Female Interviewer G. Naliya (Mr) Male Interviewer/ Asst. Editor Team 20 M. Botomani (Miss) Team Leader/ Heath Technician T. Mwangala (Miss) Field Editor Y. Mpinganjira (Miss) Female Interviewer L. Fwataki (Mrs) Female Interviewer M. Kunsiya (M iss) Female Interviewer N. Chimwala (Miss) Female Interviewer A. Namarika (Mr) Male Interviewer/ Asst. Editor J. Chipili (Mr) Male Interviewer 234 * Appendix D Team Mem bers Position Team 21 E. Kaleke (Mrs) Team Leader A. Kabango (Mrs) Field Editor E. Bvutula (Mrs) Female Interviewer/ Health Technician C. Mataka (Miss) Female Interviewer D. Michongwe (Miss) Female Interviewer M. Mwachande (Miss) Female Interviewer H. Chizinga (Miss) Female Interviewer L. Wandale (Mr) Male Interviewer/ Asst. Editor Team Mem bers Position Team 22 V. Kandoje (M rs) Team Leader A. Chilumpha (Mrs) Field Editor/ Health Technician E. Lilani (Miss) Female Interviewer M. Kamwana (Miss) Female Interviewer F. Mang'anda (Miss) Female Interviewer S. Ngoma (Miss) Female Interviewer E. Njehani (Mr) Male Interviewer/ Asst. Editor K. Uzale (Mr) Male Interviewer ORC Macro Staff George Bicego, Country Coordinator Mary Mahy, Country Coordinator Holly Newby, Country Coordinator Glen Heller, Data Processing Specialist Alfredo Aliaga, Sampling Statistician Sidney Moore, Editor Celia Khan, Document Production Specialist Appendix E * 235 QUESTIONNAIRES APPENDIX E EH 1 MALAWI DEMOGRAPHIC AND HEALTH SURVEY-II MALAWI GOVERNMENT – NATIONAL STATISTICAL OFFICE HOUSEHOLD QUESTIONNAIRE IDENTIFICATION VILLAGE/PLACE NAME NAME OF HOUSEHOLD HEAD MDHS CLUSTER NUMBER . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HOUSEHOLD NUMBER . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . URBAN/RURAL (URBAN=1, RURAL=2) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . +)))0)))0))), *!!!*!!!*!!!* .)))3)))3)))1 *!!!*!!!* .)))3)))1 *!!!* .)))- INTERVIEWER VISITS 1 2 3 FINAL VISIT DATE INTERVIEWER’S NAME RESULT* +)))0))), DAY *!!!*!!!* /)))3)))1 MONTH *!!!*!!!* +)))0)))3)))3)))1 YEAR *!!!*!!!*!!!*!!!* .)))2)))3)))3)))1 NAME *!!!*!!!* .)))3)))1 RESULT *!!!* .)))- NEXT VISIT: DATE TOTAL NO. OF VISITS +)), *!!* .))-TIME *RESULT CODES: 1 COMPLETED 2 NO HOUSEHOLD MEMBER AT HOME OR NO COMPETENT RESPONDENT AT HOME AT TIME OF VISIT 3 ENTIRE HOUSEHOLD ABSENT FOR EXTENDED PERIOD OF TIME 4 POSTPONED 5 REFUSED 6 DWELLING VACANT OR ADDRESS NOT A DWELLING 7 DWELLING DESTROYED 8 DWELLING NOT FOUND 9 OTHER (SPECIFY) TOTAL PERSONS IN HOUSEHOLD +))0)), *!!*!!* .))2))- TOTAL ELIGIBLE WOMEN +))0)), *!!*!!* .))2))- TOTAL ELIGIBLE MEN +))0)), *!!*!!* .))2))- LINE NO. OF RESP. TO HOUSEHOLD SCHEDULE +))0)), *!!*!!* .))2))- LANGUAGE OF QUESTIONNAIRE !ENGLISH . . . . . . . . . . . . . . . . . . . . 3 LANGUAGE OF CHICHEWA . . . . . . . . . . . . . . . . . . . . . . 1 INTERVIEW TUMBUKA . . . . . . . . . . . . . . . . . . . . . . . 2 OTHER 3 (SPECIFY) SUPERVISOR FIELD EDITOR OFFICE EDITOR KEYED BY NAME +))0)), *!!*!!* .))2))- NAME +))0)), *!!*!!* .))2))- +))0)), *!!*!!* .))2))- +))0)), *!!*!!* .))2))-DATE DATE EH 2 HOUSEHOLD SCHEDULE Now we would like some information about the people who usually live in your household or who are staying with you now. LINE NO. USUAL RESIDENTS AND VISITORS REL AT IONSH IP TO HEAD OF HOU SEHO LD SEX RESIDENCE AGE ELIGIBILITY Please give me the names of the persons who usually live in your h ous eho ld and gue sts of the household who stayed here last nigh t, starting w ith the head of the household. W hat is the relat ionship of (NAME) to the head of the household?* Is (NAME) male or female? Does (NAME) usua lly live here? Did (NAME) stay he re last nigh t? Ho w o ld is (NA ME )? CIRCLE LINE NUMBER OF ALL W OMEN AGE 15-49 CIRCLE LINE NUMBER OF ALL MEN AGE 15-54 CIRCLE LINE NUMBER OF ALL CHILD-REN UNDER AGE 6 (1) (2) (3) (4) (5) (6) (7) (8) (8a) (9) M F YES NO YES NO IN YEARS 01 +))0)), *!!*!!* .))2))- 1 2 1 2 1 2 +))0)), *!!*!!* .))2))- 01 01 01 02 +))0)), *!!*!!* .))2))- 1 2 1 2 1 2 +))0)), *!!*!!* .))2))- 02 02 02 03 +))0)), *!!*!!* .))2))- 1 2 1 2 1 2 +))0)), *!!*!!* .))2))- 03 03 03 04 +))0)), *!!*!!* .))2))- 1 2 1 2 1 2 +))0)), *!!*!!* .))2))- 04 04 04 05 +))0)), *!!*!!* .))2))- 1 2 1 2 1 2 +))0)), *!!*!!* .))2))- 05 05 05 06 +))0)), *!!*!!* .))2))- 1 2 1 2 1 2 +))0)), *!!*!!* .))2))- 06 06 06 07 +))0)), *!!*!!* .))2))- 1 2 1 2 1 2 +))0)), *!!*!!* .))2))- 07 07 07 08 +))0)), *!!*!!* .))2))- 1 2 1 2 1 2 +))0)), *!!*!!* .))2))- 08 08 08 09 +))0)), *!!*!!* .))2))- 1 2 1 2 1 2 +))0)), *!!*!!* .))2))- 09 09 09 10 +))0)), *!!*!!* .))2))- 1 2 1 2 1 2 +))0)), *!!*!!* .))2))- 10 10 10 * CO DE S F OR Q.3 RELATIONSHIP TO HEAD OF HOUSEHOLD: 01 = HEAD 02 = W IFE OR HUSBAND 03 = SON OR DAUGHTER 04 = SON- IN-LAW OR DAUGHTER- IN-LAW 05 = GRAN DCH ILD 06 = PARENT 07 = PARENT-IN-LAW 08 = BROTHER OR SISTER 10 = OTHER RELATIVE 11 = ADOPTED/FOSTER/ STEPCHILD 12 = NOT RELATED 98 = DON’T KNOW EH 3 LINE NO. PARENTAL SURVIVORSHIP AND RESIDENCE FOR PER SON S LES S TH AN 15 YE ARS OLD** EDUCATION Is (NAM E)’s natural mother al ive? IF ALIVE Is (NA ME )’ s natural father al ive? IF ALIVE IF AGE 5 YEARS OR OLDER IF AGE 5-24 YEARS Does (NAM E)’s natural mother l ive in this house- hold? IF YES: W hat is her name? RECORD MOTHER’S LINE NUMBER Does (NAM E)’s natural father live in this house- hold? IF YES: W hat is his name? RECORD FATHER’S LINE NUMBER Has (NAME) ever attended sch oo l? W hat is the highest level of school (NAME) has attended?*** W hat is the highest year (NAME) completed at that level?*** Is (NAME) curren tly attending sch oo l? During the current school year, did (NAME) attend school at any time? During the current school year, what level and class [ is /was] (NAME) attending?*** During the previous school year, did (NAME) attend school at any time? During that school year, what level and yea r did (NAME) attend?*** (10) (11) (12) (13) (14) (15) (16) (17) (18) (19) (20) YES NO DK YESNO DK YES NO LEVEL YEARS YES NO YES NO LEVEL YEARS YES NO LEVEL YEARS 01 1 2 8 +))0)), *!!*!!* .))2))- 1 2 8 +))0)), *!!*!!* .))2))- 1 2 NEXT=- LINE +)), *!!* .))- +))0)), *!!*!!* .))2))- 1 2 .< GO TO 18 1 2 GO TO=- 19 +)), *!!* .))- +))0)), *!!*!!* .))2))- 1 2 NEXT =- LINE +)), *!!* .))- +))0)), *!!*!!* .))2))- 02 1 2 8 +))0)), *!!*!!* .))2))- 1 2 8 +))0)), *!!*!!* .))2))- 1 2 NEXT=- LINE +)), *!!* .))- +))0)), *!!*!!* .))2))- 1 2 .< GO TO 18 1 2 GO TO=- 19 +)), *!!* .))- +))0)), *!!*!!* .))2))- 1 2 NEXT =- LINE +)), *!!* .))- +))0)), *!!*!!* .))2))- 03 1 2 8 +))0)), *!!*!!* .))2))- 1 2 8 +))0)), *!!*!!* .))2))- 1 2 NEXT=- LINE +)), *!!* .))- +))0)), *!!*!!* .))2))- 1 2 .< GO TO 18 1 2 GO TO=- 19 +)), *!!* .))- +))0)), *!!*!!* .))2))- 1 2 NEXT =- LINE +)), *!!* .))- +))0)), *!!*!!* .))2))- 04 1 2 8 +))0)), *!!*!!* .))2))- 1 2 8 +))0)), *!!*!!* .))2))- 1 2 NEXT=- LINE +)), *!!* .))- +))0)), *!!*!!* .))2))- 1 2 .< GO TO 18 1 2 GO TO=- 19 +)), *!!* .))- +))0)), *!!*!!* .))2))- 1 2 NEXT =- LINE +)), *!!* .))- +))0)), *!!*!!* .))2))- 05 1 2 8 +))0)), *!!*!!* .))2))- 1 2 8 +))0)), *!!*!!* .))2))- 1 2 NEXT=- LINE +)), *!!* .))- +))0)), *!!*!!* .))2))- 1 2 .< GO TO 18 1 2 GO TO=- 19 +)), *!!* .))- +))0)), *!!*!!* .))2))- 1 2 NEXT =- LINE +)), *!!* .))- +))0)), *!!*!!* .))2))- 06 1 2 8 +))0)), *!!*!!* .))2))- 1 2 8 +))0)), *!!*!!* .))2))- 1 2 NEXT=- LINE +)), *!!* .))- +))0)), *!!*!!* .))2))- 1 2 .< GO TO 18 1 2 GO TO=- 19 +)), *!!* .))- +))0)), *!!*!!* .))2))- 1 2 NEXT =- LINE +)), *!!* .))- +))0)), *!!*!!* .))2))- 07 1 2 8 +))0)), *!!*!!* .))2))- 1 2 8 +))0)), *!!*!!* .))2))- 1 2 NEXT=- LINE +)), *!!* .))- +))0)), *!!*!!* .))2))- 1 2 .< GO TO 18 1 2 GO TO=- 19 +)), *!!* .))- +))0)), *!!*!!* .))2))- 1 2 NEXT =- LINE +)), *!!* .))- +))0)), *!!*!!* .))2))- 08 1 2 8 +))0)), *!!*!!* .))2))- 1 2 8 +))0)), *!!*!!* .))2))- 1 2 NEXT=- LINE +)), *!!* .))- +))0)), *!!*!!* .))2))- 1 2 .< GO TO 18 1 2 GO TO=- 19 +)), *!!* .))- +))0)), *!!*!!* .))2))- 1 2 NEXT =- LINE +)), *!!* .))- +))0)), *!!*!!* .))2))- 09 1 2 8 +))0)), *!!*!!* .))2))- 1 2 8 +))0)), *!!*!!* .))2))- 1 2 NEXT=- LINE +)), *!!* .))- +))0)), *!!*!!* .))2))- 1 2 .< GO TO 18 1 2 GO TO=- 19 +)), *!!* .))- +))0)), *!!*!!* .))2))- 1 2 NEXT =- LINE +)), *!!* .))- +))0)), *!!*!!* .))2))- 10 1 2 8 +))0)), *!!*!!* .))2))- 1 2 8 +))0)), *!!*!!* .))2))- 1 2 NEXT=- LINE +)), *!!* .))- +))0)), *!!*!!* .))2))- 1 2 .< GO TO 18 1 2 GO TO=- 19 +)), *!!* .))- +))0)), *!!*!!* .))2))- 1 2 NEXT =- LINE +)), *!!* .))- +))0)), *!!*!!* .))2))- ** Q.10 THROUG H Q.13 THESE QUESTIONS REFER TO THE BIOLOGICAL PARENTS OF THE CHILD. IN Q.11 AND Q.13, RECORD ‘00' IF PARENT NOT LISTED IN HOUSEHOLD SCHEDULE. ***COD ES FOR Qs. 15, 18 AND 20 EDUC ATION LEVE L: 1 = PRIMARY 2 = SECONDARY 3 = HIGHER 8 = DON’T KNOW YEARS COMPLETED: 00 = LESS THAN 1 YEAR COMPLETED 98 = DON’T KNOW EH 4 LINE NO. USUAL RESIDENTS AND VISITORS REL AT IONSH IP TO HEAD OF HOU SEHO LD SEX RESIDENCE AGE ELIGIBILITY Please give me the names of the persons who usually live in your h ous eho ld and gue sts of the household who stayed here last nigh t, starting w ith the head of the household. W hat is the relat ionship of (NAME) to the head of the household?* Is (NAME) male or female? Does (NAME) usua lly live here? Did (NAME) stay he re last nigh t? Ho w o ld is (NA ME )? CIRCLE LINE NUMBER OF ALL W OMEN AGE 15-49 CIRCLE LINE NUMBER OF ALL MEN AGE 15-54 CIRCLE LINE NUMBE R OF ALL CHILD- REN UNDER AGE 6 (1) (2) (3) (4) (5) (6) (7) (8) (8a) (9) M F YES NO YES NO IN YEARS 11 +))0)), *!!*!!* .))2))- 1 2 1 2 1 2 +))0)), *!!*!!* .))2))- 11 11 11 12 +))0)), *!!*!!* .))2))- 1 2 1 2 1 2 +))0)), *!!*!!* .))2))- 12 12 12 13 +))0)), *!!*!!* .))2))- 1 2 1 2 1 2 +))0)), *!!*!!* .))2))- 13 13 13 14 +))0)), *!!*!!* .))2))- 1 2 1 2 1 2 +))0)), *!!*!!* .))2))- 14 14 14 15 +))0)), *!!*!!* .))2))- 1 2 1 2 1 2 +))0)), *!!*!!* .))2))- 15 15 15 16 +))0)), *!!*!!* .))2))- 1 2 1 2 1 2 +))0)), *!!*!!* .))2))- 16 16 16 17 +))0)), *!!*!!* .))2))- 1 2 1 2 1 2 +))0)), *!!*!!* .))2))- 17 17 17 18 +))0)), *!!*!!* .))2))- 1 2 1 2 1 2 +))0)), *!!*!!* .))2))- 18 18 18 19 +))0)), *!!*!!* .))2))- 1 2 1 2 1 2 +))0)), *!!*!!* .))2))- 19 19 19 20 +))0)), *!!*!!* .))2))- 1 2 1 2 1 2 +))0)), *!!*!!* .))2))- 20 20 20 * CO DE S F OR Q.3 RELATIONSHIP TO HEAD OF HOUSEHOLD: 01 = HEAD 02 = W IFE OR HUSBAND 03 = SON OR DAUGHTER 04 = SON- IN-LAW OR DAUGHTER- IN-LAW 05 = GRAN DCH ILD 06 = PARENT 07 = PARENT-IN-LAW 08 = BROTHER OR SISTER 10 = OTHER RELATIVE 11 = ADOPTED/FOSTER/ STEPCHILD 12 = NOT RELATED 98 = DON’T KNOW ** Q.10 THROUG H Q.13 THESE QUESTIONS REFER TO THE BIOLOGICAL PARENTS OF THE CHILD. IN Q.11 AND Q.13, RECORD ‘00' IF PARENT NOT LISTED IN HOUSE HOLD SCHEDULE. ***COD ES FOR Qs. 15, 18 AND 20 EDUC ATION LEVE L: 1 = PRIMARY 2 = SECONDARY 3 = HIGHER 8 = DON’T KNOW EDUCATION YEAR: 00 = LESS THAN 1 YEAR COMPLETED 98 = DON’T KNOW EH 5 LINE NO. PARENTAL SURVIVORSHIP AND RESIDENCE FOR PER SON S LES S TH AN 15 YE ARS OLD** EDUCATION Is (NAM E)’s natural mother al ive? IF ALIVE Is (NAM E)’s natural father al ive? IF ALIVE IF AGE 5 YEARS OR OLDER IF AGE 5-24 YEARS Does (NAM E)’s natural mother live in this household ? IF YES: W hat is her name? RECORD MOTHER’S LINE NUMBER Does (NAM E)’s natural father l ive in this household ? IF YES: W hat is his name? RECORD FATHER’S LINE NUMBER Has (NAME) ever attended sch oo l? W hat is the highest level of schoo l (NAME) has attended?*** W hat is the highest class (NAME) completed at that level?*** Is (NAME) curren tly attending sch oo l? During the current school year, did (NAME) attend school at any time? During the current school year, what level and class [ is /was] (NAME) attending?*** During the previous school year, did (NAME) attend school at any time? During that school year, what level and cla ss d id (NAME) attend?*** (10) (11) (12) (13) (14) (15) (16) (17) (18) (19) (20) YES NO DK YES NO DK YES NO LEVEL YEAR YES NO YES NO LEVEL YEAR YES NO LEVEL YEAR 11 1 2 8 +))0)), *!!*!!* .))2))- 1 2 8 +))0)), *!!*!!* .))2))- 1 2 NEXT =- LINE +)), *!!* .))- +))0)), *!!*!!* .))2))- 1 2 .< GO TO 18 1 2 GO TO=- 19 +)), *!!* .))- +))0)), *!!*!!* .))2))- 1 2 NEXT =- LINE +)), *!!* .))- +))0)), *!!*!!* .))2))- 12 1 2 8 +))0)), *!!*!!* .))2))- 1 2 8 +))0)), *!!*!!* .))2))- 1 2 NEXT =- LINE +)), *!!* .))- +))0)), *!!*!!* .))2))- 1 2 .< GO TO 18 1 2 GO TO=- 19 +)), *!!* .))- +))0)), *!!*!!* .))2))- 1 2 NEXT =- LINE +)), *!!* .))- +))0)), *!!*!!* .))2))- 13 1 2 8 +))0)), *!!*!!* .))2))- 1 2 8 +))0)), *!!*!!* .))2))- 1 2 NEXT =- LINE +)), *!!* .))- +))0)), *!!*!!* .))2))- 1 2 .< GO TO 18 1 2 GO TO=- 19 +)), *!!* .))- +))0)), *!!*!!* .))2))- 1 2 NEXT =- LINE +)), *!!* .))- +))0)), *!!*!!* .))2))- 14 1 2 8 +))0)), *!!*!!* .))2))- 1 2 8 +))0)), *!!*!!* .))2))- 1 2 NEXT =- LINE +)), *!!* .))- +))0)), *!!*!!* .))2))- 1 2 .< GO TO 18 1 2 GO TO=- 19 +)), *!!* .))- +))0)), *!!*!!* .))2))- 1 2 NEXT =- LINE +)), *!!* .))- +))0)), *!!*!!* .))2))- 15 1 2 8 +))0)), *!!*!!* .))2))- 1 2 8 +))0)), *!!*!!* .))2))- 1 2 NEXT =- LINE +)), *!!* .))- +))0)), *!!*!!* .))2))- 1 2 .< GO TO 18 1 2 GO TO=- 19 +)), *!!* .))- +))0)), *!!*!!* .))2))- 1 2 NEXT =- LINE +)), *!!* .))- +))0)), *!!*!!* .))2))- 16 1 2 8 +))0)), *!!*!!* .))2))- 1 2 8 +))0)), *!!*!!* .))2))- 1 2 NEXT =- LINE +)), *!!* .))- +))0)), *!!*!!* .))2))- 1 2 .< GO TO 18 1 2 GO TO=- 19 +)), *!!* .))- +))0)), *!!*!!* .))2))- 1 2 NEXT =- LINE +)), *!!* .))- +))0)), *!!*!!* .))2))- 17 1 2 8 +))0)), *!!*!!* .))2))- 1 2 8 +))0)), *!!*!!* .))2))- 1 2 NEXT =- LINE +)), *!!* .))- +))0)), *!!*!!* .))2))- 1 2 .< GO TO 18 1 2 GO TO=- 19 +)), *!!* .))- +))0)), *!!*!!* .))2))- 1 2 NEXT =- LINE +)), *!!* .))- +))0)), *!!*!!* .))2))- 18 1 2 8 +))0)), *!!*!!* .))2))- 1 2 8 +))0)), *!!*!!* .))2))- 1 2 NEXT =- LINE +)), *!!* .))- +))0)), *!!*!!* .))2))- 1 2 .< GO TO 18 1 2 GO TO=- 19 +)), *!!* .))- +))0)), *!!*!!* .))2))- 1 2 NEXT =- LINE +)), *!!* .))- +))0)), *!!*!!* .))2))- 19 1 2 8 +))0)), *!!*!!* .))2))- 1 2 8 +))0)), *!!*!!* .))2))- 1 2 NEXT =- LINE +)), *!!* .))- +))0)), *!!*!!* .))2))- 1 2 .< GO TO 18 1 2 GO TO=- 19 +)), *!!* .))- +))0)), *!!*!!* .))2))- 1 2 NEXT =- LINE +)), *!!* .))- +))0)), *!!*!!* .))2))- 20 1 2 8 +))0)), *!!*!!* .))2))- 1 2 8 +))0)), *!!*!!* .))2))- 1 2 NEXT =- LINE +)), *!!* .))- +))0)), *!!*!!* .))2))- 1 2 .< GO TO 18 1 2 GO TO=- 19 +)), *!!* .))- +))0)), *!!*!!* .))2))- 1 2 NEXT =- LINE +)), *!!* .))- +))0)), *!!*!!* .))2))- TICK HERE IF CONTINUATION SHEET USED +)), .))- Just to make sure that I have a complete l ist ing: 1) Are there any other persons such as small children or infants that we have not l isted? YES +)), .))2))< ENTE R EAC H IN TABLE NO +)), .))- 2) In add ition , are the re a ny o the r pe op le w ho may n ot b e m em bers o f you r fam ily, such as domestic servants, lodgers or friends who usually l ive here? YES +)), .))2))< ENTE R EAC H IN TABLE NO +)), .))- 3) Are there any guests or temporary visitors staying here, or anyone else who slept here last night, who have not been listed? YES +)), .))2))< ENTE R EAC H IN TABLE NO +)), .))- EH 6 NO. QUESTIONS AND FILTERS CODING CATEGORIES SKIP 21 What is the main source of drinking water for members of your household? PIPED WATER PIPED INTO DWELLING . . . . . . . 11 PIPED INTO YARD/PLOT . . . . . . . 12 COMMUNITY STAND PIPE . . . . . 13 UNPROTECTED WELL . . . . . . . . . . 21 PROTECTED WELL . . . . . . . . . . . . . 31 BOREHOLE . . . . . . . . . . . . . . . . . . . 41 SURFACE WATER SPRING . . . . . . . . . . . . . . . . . . . . 51 RIVER/STREAM . . . . . . . . . . . . . . 52 POND/LAKE . . . . . . . . . . . . . . . . . 53 DAM . . . . . . . . . . . . . . . . . . . . . . . 54 RAINWATER . . . . . . . . . . . . . . . . . . 61 TANKER TRUCK/BOWSER . . . . . . . 71 BOTTLED WATER . . . . . . . . . . . . . . 81 OTHER 96 (SPECIFY) ))< 23 ))< 23 ))< 23 ))< 23 22 How long does it take you to go there, get water, and come back? +)))0)))0))), MINUTES . . . . . . . . . . *!!!*!!!*!!!* .)))2)))2)))- ON PREMISES . . . . . . . . . . . . . . . . 996 23 What kind of toilet facility does your household use? FLUSH TOILET . . . . . . . . . . . . . . . . . 11 PIT TOILET/LATRINE TRADITIONAL PIT TOILET . . . . . 21 VENTILATED IMPROVED PIT (VIP) LATRINE . . . . . . . . . . . . . 22 NO FACILITY . . . . . . . . . . . . . . . . . . 31 OTHER 96 (SPECIFY) ))< 25 24 Do you share this facility with other households? YES . . . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 25 Does your household have: Electricity? A paraffin lamp? A radio? A television? YES NO ELECTRICITY . . . . . . . . . . . . . . 1 2 PARAFFIN LAMP . . . . . . . . . . . 1 2 RADIO . . . . . . . . . . . . . . . . . . . 1 2 TELEVISION . . . . . . . . . . . . . . . 1 2 26 What type of fuel does your household mainly use for cooking? ELECTRICITY . . . . . . . . . . . . . . . . . . 01 PARAFFIN . . . . . . . . . . . . . . . . . . . . 02 CHARCOAL . . . . . . . . . . . . . . . . . . . 03 FIREWOOD . . . . . . . . . . . . . . . . . . . 04 STRAW . . . . . . . . . . . . . . . . . . . . . . . 05 OTHER 96 (SPECIFY) NO. QUESTIONS AND FILTERS CODING CATEGORIES SKIP EH 7 27 MAIN MATERIAL OF THE FLOOR. RECORD OBSERVATION. NATURAL FLOOR EARTH/SAND . . . . . . . . . . . . . . . . 11 DUNG . . . . . . . . . . . . . . . . . . . . . . 12 RUDIMENTARY FLOOR WOOD PLANKS . . . . . . . . . . . . . . 21 PALM/BAMBOO . . . . . . . . . . . . . . 22 BROKEN BRICKS . . . . . . . . . . . . . 23 FINISHED FLOOR PARQUET OR POLISHED WOOD . . . . . . . . . . . . . . . . . . . 31 VINYL OR ASPHALT STRIPS . . . 32 CERAMIC TILES . . . . . . . . . . . . . . 33 CEMENT . . . . . . . . . . . . . . . . . . . . 34 BRICK . . . . . . . . . . . . . . . . . . . . . . 35 OTHER 96 (SPECIFY) 28 Does any member of your household own: A bicycle? A motorcycle or motor scooter? A car or truck? YES NO BICYCLE . . . . . . . . . . . . . . . . . 1 2 MOTORCYCLE/SCOOTER . . . 1 2 CAR/TRUCK . . . . . . . . . . . . . . . 1 2 29 Does your household have any mosquito nets that can be used while sleeping? IF YES ASK: How many? +))), YES . . . . . . . . . . . . . . . . . . . . . . *!!!* .)))- NO . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 ))< 33 30 How many mosquito nets are white in color? +))), NUMBER . . . . . . . . . . . . . . . . . . *!!!* .)))- NONE . . . . . . . . . . . . . . . . . . . . . . . . . 0 33 Where do you usually wash your hands? IN DWELLING/YARD/PLOT . . . . . . . . 1 SOMEWHERE ELSE . . . . . . . . . . . . . 2 NOWHERE . . . . . . . . . . . . . . . . . . . . . 3 ))< 35 ))< 35 34 ASK TO SEE THE PLACE AND OBSERVE IF THE FOLLOWING ITEMS ARE PRESENT. YES NO WATER/TAP . . . . . . . . . . . . . . . 1 2 SOAP, ASH OR OTHER CLEANSING AGENT . . . . . . 1 2 BASIN . . . . . . . . . . . . . . . . . . . . 1 2 35 ASK RESPONDENT FOR A TEASPOONFUL OF SALT. TEST SALT FOR IODINE. RECORD PPM (PARTS PER MILLION). 0 - 14 PPM . . . . . . . . . . . . . . . . . . . . . 1 15 - 20 PPM . . . . . . . . . . . . . . . . . . . . 2 20 - 74 PPM . . . . . . . . . . . . . . . . . . . . 3 75 + PPM . . . . . . . . . . . . . . . . . . . . . . 4 EH 8 CHILD LABOUR Now I would like to ask you about any work children in this household may do. 36. L INE NO. COPY L INE NUMBER OF CHILDREN AGES 5 - 14 YEARS FROM THE HOU SEHO LD LISTING 37. CHILD’S NAME COPY THE NAMES OF CHILDREN AGES 5 - 14 YEARS FROM THE HOUSEHOLD LISTING 38. During the past week, d id (NAME) do a ny kind of w ork for som eone who is not a memeber of this household? IF YE S: F or pay? 39. Since last (DAY OF TH E W EE K), about how m any hours did he/she do this work for someone who is not a mem ber of the household?* 40. During the past week, d id (NAM E) h elp with housekeeping chores such as cooking, shopping, cleaning, washing clothes, fetchin g wa ter, or caring for chi ldren? 41.Since last (DAY OF THE W EEK), about how many hours did he/she spend doing these chores? 42. During the past week, d id (NAME) do any other family work on the farm or in a business? 43. Since last (DAY OF THE W EEK), about how many hours did he /she do this work? PA ID U NPA ID NO YES NO YES NO 1 2 3 GO TO=- 40 +))0)), *!!*!!* .))2))- 1 2 GO TO=- 42 +))0)), *!!*!!* .))2))- 1 2 GO TO=- NEXT LINE +))0)), *!!*!!* .))2))- 1 2 3 GO TO=- 40 +))0)), *!!*!!* .))2))- 1 2 GO TO=- 42 +))0)), *!!*!!* .))2))- 1 2 GO TO=- NEXT LINE +))0)), *!!*!!* .))2))- 1 2 3 GO TO=- 40 +))0)), *!!*!!* .))2))- 1 2 GO TO=- 42 +))0)), *!!*!!* .))2))- 1 2 GO TO=- NEXT LINE +))0)), *!!*!!* .))2))- 1 2 3 GO TO=- 40 +))0)), *!!*!!* .))2))- 1 2 GO TO=- 42 +))0)), *!!*!!* .))2))- 1 2 GO TO=- NEXT LINE +))0)), *!!*!!* .))2))- 1 2 3 GO TO=- 40 +))0)), *!!*!!* .))2))- 1 2 GO TO=- 42 +))0)), *!!*!!* .))2))- 1 2 GO TO=- NEXT LINE +))0)), *!!*!!* .))2))- 1 2 3 GO TO=- 40 +))0)), *!!*!!* .))2))- 1 2 GO TO=- 42 +))0)), *!!*!!* .))2))- 1 2 GO TO=- NEXT LINE +))0)), *!!*!!* .))2))- 1 2 3 GO TO=- 40 +))0)), *!!*!!* .))2))- 1 2 GO TO=- 42 +))0)), *!!*!!* .))2))- 1 2 GO TO=- NEXT LINE +))0)), *!!*!!* .))2))- 1 2 3 GO TO=- 40 +))0)), *!!*!!* .))2))- 1 2 GO TO=- 42 +))0)), *!!*!!* .))2))- 1 2 GO TO=- NEXT LINE +))0)), *!!*!!* .))2))- 1 2 3 GO TO=- 40 +))0)), *!!*!!* .))2))- 1 2 GO TO=- 42 +))0)), *!!*!!* .))2))- 1 2 GO TO=- NEXT LINE +))0)), *!!*!!* .))2))- 1 2 3 GO TO=- 40 +))0)), *!!*!!* .))2))- 1 2 GO TO=- 42 +))0)), *!!*!!* .))2))- 1 2 GO TO=- NEXT LINE +))0)), *!!*!!* .))2))- * IF MORE THAN ONE JOB, INCLUDE ALL HOURS AT ALL JOBS. EH 9 WEIGHT AND HEIGHT MEASUREMENT CHEC K COLU MNS (8) AND (9): RECO RD TH E LINE NUMBE R, NAME AN D AGE OF ALL W OMEN AGE 15-49 AND ALL C HILDREN UN DER A GE 6. W OMEN 15-49 W EIGHT AND HEIGHT ME ASUR EMEN T OF W OMEN 15-49 LINE NO. FROM COL.(8) NAME FROM COL.(2) AGE FROM COL.(7) What is (NAME)’s date of birth? WEIGHT (KILOGRAMS) HEIGHT (CENTIMETERS) MEASURED LYING DOWN OR STANDING UP RESULT 1 MEASURED 2 NOT PRESENT 3 REFUSED 6 OTHER (44) (45) (46) (47) (48) (49) (50) (51) YEARS +))0)), *!!*!!* .))2))- +))0)), *!!*!!* .))2))- +)))0)))0))), +)), *!!!*!!!*!!!* *!!* .)))2)))2)))-.))- +)))0)))0))), +))), *!!!*!!!*!!!* *!!!* .)))2)))2)))-.)))- +)), *!!* .))- +))0)), *!!*!!* .))2))- +))0)), *!!*!!* .))2))- +)))0)))0))), +)), *!!!*!!!*!!!* *!!* .)))2)))2)))-.))- +)))0)))0))), +))), *!!!*!!!*!!!* *!!!* .)))2)))2)))-.)))- +)), *!!* .))- +))0)) , *!!*!! * .))2)) - +))0)), *!!*!!* .))2))- +)))0)))0))), +)), *!!!*!!!*!!!* *!!* .)))2)))2)))-.))- +)))0)))0))), +))), *!!!*!!!*!!!* *!!!* .)))2)))2)))-.)))- +)), *!!* .))- +))0)) , *!!*!! * .))2)) - +))0)), *!!*!!* .))2))- +)))0)))0))), +)), *!!!*!!!*!!!* *!!* .)))2)))2)))-.))- +)))0)))0))), +))), *!!!*!!!*!!!* *!!!* .)))2)))2)))-.)))- +)), *!!* .))- +))0)) , *!!*!! * .))2)) - +))0)), *!!*!!* .))2))- +)))0)))0))), +)), *!!!*!!!*!!!* *!!* .)))2)))2)))-.))- +)))0)))0))), +))), *!!!*!!!*!!!* *!!!* .)))2)))2)))-.)))- +)), *!!* .))- CHILDREN UNDER AGE 6 WEIGHT AND HEIGHT MEASUREMENT OF CHILDREN BORN IN 1995 OR LATER LINE NO. FROM COL.(9) NAME FROM COL.(2) AGE FROM COL.(7) What is (NAME)’s date of birth? WEIGHT (KILOGRAMS) HEIGHT (CENTIMETERS) MEASURED LYING DOWN OR STANDING UP RESULT 1 MEASURED 2 NOT PRESENT 3 REFUSED 6 OTHER DAY MO. YEAR LYING STAND. +))0)), *!!*!!* .))2))- +))0)), *!!*!!* .))2))- +)))0))),+)))0))),+)))0)))0)))0 ))), *!!!*!!!**!!!*!!!**!!!*!!!*!!!* !!!* .)))2)))-.)))2)))-.)))2)))2)))2 )))- +)))0)))0))), +))), *!0!*!!!*!!!* *!!!* .)))2)))2)))-.)))- +)))0)))0))), +))), *!!!*!!!*!!!* *!!!* .)))2)))2)))-.)))- 1 2 +)), *!!* .))- +))0)), *!!*!!* .))2))- +))0)), *!!*!!* .))2))- +)))0))),+)))0))),+)))0)))0)))0 ))), *!!!*!!!**!!!*!!!**!!!*!!!*!!!* !!!* .)))2)))-.)))2)))-.)))2)))2)))2 )))- +)))0)))0))), +))), *!0!*!!!*!!!* *!!!* .)))2)))2)))-.)))- +)))0)))0))), +))), *!!!*!!!*!!!* *!!!* .)))2)))2)))-.)))- 1 2 +)), *!!* .))- +))0)), *!!*!!* .))2))- +))0)), *!!*!!* .))2))- +)))0))),+)))0))),+)))0)))0)))0 ))), *!!!*!!!**!!!*!!!**!!!*!!!*!!!* !!!* .)))2)))-.)))2)))-.)))2)))2)))2 )))- +)))0)))0))), +))), *!0!*!!!*!!!* *!!!* .)))2)))2)))-.)))- +)))0)))0))), +))), *!!!*!!!*!!!* *!!!* .)))2)))2)))-.)))- 1 2 +)), *!!* .))- +))0)), *!!*!!* .))2))- +))0)), *!!*!!* .))2))- +)))0))),+)))0))),+)))0)))0)))0 ))), *!!!*!!!**!!!*!!!**!!!*!!!*!!!* !!!* .)))2)))-.)))2)))-.)))2)))2)))2 )))- +)))0)))0))), +))), *!0!*!!!*!!!* *!!!* .)))2)))2)))-.)))- +)))0)))0))), +))), *!!!*!!!*!!!* *!!!* .)))2)))2)))-.)))- 1 2 +)), *!!* .))- +))0)), *!!*!!* .))2))- +))0)), *!!*!!* .))2))- +)))0))),+)))0))),+)))0)))0)))0 ))), *!!!*!!!**!!!*!!!**!!!*!!!*!!!* !!!* .)))2)))-.)))2)))-.)))2)))2)))2 )))- +)))0)))0))), +))), *!0!*!!!*!!!* *!!!* .)))2)))2)))-.)))- +)))0)))0))), +))), *!!!*!!!*!!!* *!!!* .)))2)))2)))-.)))- 1 2 +)), *!!* .))- EH 10 +))0)), *!!*!!* .))2))- +))0)), *!!*!!* .))2))- +)))0))),+)))0))),+)))0)))0)))0 ))), *!!!*!!!**!!!*!!!**!!!*!!!*!!!* !!!* .)))2)))-.)))2)))-.)))2)))2)))2 )))- +)))0)))0))), +))), *!0!*!!!*!!!* *!!!* .)))2)))2)))-.)))- +)))0)))0))), +))), *!!!*!!!*!!!* *!!!* .)))2)))2)))-.)))- 1 2 +)), *!!* .))- TICK HERE IF CONTINUATION SHEET USED +)), .))- EW 1 MALAWI DEMOGRAPHIC AND HEALTH SURVEY–II MALAWI GOVERNMENT- NATIONAL STATISTICAL OFFICE WOMAN’S QUESTIONNAIRE IDENTIFICATION VILLAGE/PLACE NAME NAME OF HOUSEHOLD HEAD MDHS CLUSTER NUMBER . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HOUSEHOLD NUMBER . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . URBAN/RURAL (URBAN=1, RURAL=2) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . NAME AND LINE NUMBER OF WOMAN +)))0)))0))), *!!!*!!!*!!!* .)))3)))3)))1 *!!!*!!!* .)))3)))1 !!!*!!!* +)))3)))1 *!!!*!!!* .)))2)))- INTERVIEWER VISITS 1 2 3 FINAL VISIT DATE INTERVIEWER’S NAME RESULT* +)))0))), DAY *!!!*!!!* /)))3)))1 MONTH *!!!*!!!* +)))0)))3)))3)))1 YEAR*!!!*!!!*!!!*!!!* .)))2)))3)))3)))1 NAME *!!!*!!!* .)))3)))1 RESULT *!!!* .)))- NEXT VISIT: DATE TOTAL NO. OF VISITS +))), *!!!* .)))-TIME *RESULT CODES: 1 COMPLETED 2 NOT AT HOME 3 POSTPONED 4 REFUSED 5 PARTLY COMPLETED 6 INCAPACITATED 7 OTHER __________________________ (SPECIFY) LANGUAGE OF QUESTIONNAIRE ENGLISH . . . . . . . . . . . . . . . . . 3 LANGUAGE OF CHICHEWA . . . . . . . . . . . . . . . . . . . . . . 1 INTERVIEW TUMBUKA . . . . . . . . . . . . . . . . . . . . . . . 2 OTHER 3 (SPECIFY) SUPERVISOR FIELD EDITOR OFFICE EDITOR KEYED BY NAME +)))0))), *!!!*!!!* .)))2)))- NAME +)))0))), *!!!*!!!* .)))2)))- +)))0))), *!!!*!!!* .)))2)))- +)))0))), *!!!*!!!* .)))2)))-DATE DATE EW 2 SECTION 1. RESPONDENT’S BACKGROUND NO. QUESTIONS AND FILTERS CODING CATEGORIES SKIP 101 RECORD THE TIME. +)))0))), HOUR . . . . . . . . . . . . . . . . . . *!!!*!!!* /)))3)))1 MINUTES . . . . . . . . . . . . . . . *!!!*!!!* .)))2)))- 102 First I would like to ask some questions about you and your household. For most of the time until you were 12 years old, did you live in a city, in a town, or in a village? CITY . . . . . . . . . . . . . . . . . . . . . . . . . . 1 TOWN . . . . . . . . . . . . . . . . . . . . . . . . . 2 VILLAGE . . . . . . . . . . . . . . . . . . . . . . . 3 103 How long have you been living continuously in (NAME OF CURRENT PLACE OF RESIDENCE)? IF LESS THAN ONE YEAR, RECORD ‘00' YEARS. +)))0))), YEARS . . . . . . . . . . . . . . . . . *!!!*!!!* .)))2)))- ALWAYS . . . . . . . . . . . . . . . . . . . . . . 95 VISITOR . . . . . . . . . . . . . . . . . . . . . . 96 ), )2<105 104 Just before you moved here, did you live in a city, in a town, or in a village? CITY . . . . . . . . . . . . . . . . . . . . . . . . . . 1 TOWN . . . . . . . . . . . . . . . . . . . . . . . . . 2 VILLAGE . . . . . . . . . . . . . . . . . . . . . . . 3 105 In what month and year were you born? +)))0))), MONTH . . . . . . . . . . . . . . . . . *!!!*!!!* .)))2)))- DON’T KNOW MONTH . . . . . . . . . . . 98 +)))0)))0)))0))), YEAR . . . . . . . . . . *!!!*!!!*!!!*!!!* .)))2)))2)))2)))- DON’T KNOW YEAR . . . . . . . . . . . 9998 106 How old were you at your last birthday? COMPARE AND CORRECT 105 AND/OR 106 IF INCONSISTENT. +)))0))), AGE IN COMPLETED YEARS*!!!*!!!* .)))2)))- 107 Have you ever attended school? YES . . . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 ))<111 108 What is the highest level of school you attended: primary, secondary, or higher? PRIMARY . . . . . . . . . . . . . . . . . . . . . . 1 SECONDARY . . . . . . . . . . . . . . . . . . . 2 HIGHER . . . . . . . . . . . . . . . . . . . . . . . 3 109 How many years of school did you complete at that level? +)))0))), YEARS . . . . . . . . . . . . . . . . . *!!!*!!!* .)))2)))- NO. QUESTIONS AND FILTERS CODING CATEGORIES SKIP EW 3 110 CHECK 108: PRIMARY +))), SECONDARY +))), /)))- OR HIGHER .)))2)))))))))))))))))))))))))))))))))))))))))))))))) ? ))<114 111 Now I would like you to read this sentence to me. SHOW CARD TO RESPONDENT. IF RESPONDENT CANNOT READ WHOLE SENTENCE, PROBE: Can you read any part of the sentence to me? CANNOT READ AT ALL . . . . . . . . . . . 1 ABLE TO READ ONLY PARTS OF SENTENCE . . . . . . . . . . . . . . . . . . 2 ABLE TO READ WHOLE SENTENCE 3 NO CARD WITH REQUIRED LANGUAGE 4 (SPECIFY LANGUAGE) 112 Have you ever participated in a literacy program or any other program that involves learning to read or write (not including primary school)? YES . . . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 113 CHECK 111: CODE ‘2', ‘3' +))), CODE ‘1' +))), OR ‘4' /)))- CIRCLED .)))2)))))))))))))))))))))))))))))))))))))))))))))))) CIRCLED ? ))<115 114 Do you read a newspaper or magazine almost every day, at least once a week, less often than that or not at all? ALMOST EVERY DAY . . . . . . . . . . . . 1 AT LEAST ONCE A WEEK . . . . . . . . . 2 LESS OFTEN . . . . . . . . . . . . . . . . . . . 3 NOT AT ALL . . . . . . . . . . . . . . . . . . . . 4 115 Do you listen to the radio almost every day, at least once a week, less often than that or not at all? ALMOST EVERY DAY . . . . . . . . . . . . 1 AT LEAST ONCE A WEEK . . . . . . . . . 2 LESS OFTEN . . . . . . . . . . . . . . . . . . . 3 NOT AT ALL . . . . . . . . . . . . . . . . . . . . 4 116 Do you watch television almost every day, at least once a week, less often than that or not at all? ALMOST EVERY DAY . . . . . . . . . . . . 1 AT LEAST ONCE A WEEK . . . . . . . . . 2 LESS OFTEN . . . . . . . . . . . . . . . . . . . 3 NOT AT ALL . . . . . . . . . . . . . . . . . . . . 4 117 What is your religion? CATHOLIC . . . . . . . . . . . . . . . . . . . . 01 CCAP . . . . . . . . . . . . . . . . . . . . . . . . 02 ANGLICAN . . . . . . . . . . . . . . . . . . . . 03 SEVENTH DAY ADVENT./BAPTIST 04 OTHER CHRISTIAN . . . . . . . . . . . . . 05 MUSLIM . . . . . . . . . . . . . . . . . . . . . . 06 NO RELIGION . . . . . . . . . . . . . . . . . 07 OTHER _______________________ 96 (SPECIFY) 118 What is your tribe or ethnic group? CHEWA . . . . . . . . . . . . . . . . . . . . . . 01 TUMBUKA . . . . . . . . . . . . . . . . . . . . 02 LOMWE . . . . . . . . . . . . . . . . . . . . . . 03 TONGA . . . . . . . . . . . . . . . . . . . . . . . 04 YAO . . . . . . . . . . . . . . . . . . . . . . . . . 05 SENA . . . . . . . . . . . . . . . . . . . . . . . . 06 NKONDE . . . . . . . . . . . . . . . . . . . . . 07 NGONI . . . . . . . . . . . . . . . . . . . . . . . 08 OTHER_________________________96 (SPECIFY) 119 Have you heard that when a child is born in Malawi, you can register that child with the government and receive a birth certificate? YES . . . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 EW 4 SECTION 2: REPRODUCTION NO. QUESTIONS AND FILTERS CODING CATEGORIES SKIP 201 Now I would like to ask about all the births you have had during your life. Have you ever given birth? YES . . . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 ))<206 202 Do you have any sons or daughters to whom you have given birth who are now living with you? YES . . . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 ))<204 203 How many sons live with you? And how many daughters live with you? IF NONE, RECORD ‘00'. +)))0))), SONS AT HOME . . . . . . . . . *!!!*!!!* /)))3)))1 DAUGHTERS AT HOME . . . *!!!*!!!* .)))2)))- 204 Do you have any sons or daughters to whom you have given birth who are alive but do not live with you? YES . . . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 ))<206 205 How many sons are alive but do not live with you? And how many daughters are alive but do not live with you? IF NONE, RECORD ‘00'. +)))0))), SONS ELSEWHERE . . . . . . *!!!*!!!* /)))3)))1 DAUGHTERS ELSEWHERE *!!!*!!!* .)))2)))- 206 Have you ever given birth to a boy or girl who was born alive but later died? IF NO, PROBE: Any baby who cried or showed signs of life but survived only a few moments? YES . . . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 ))<208 207 How many boys have died? And how many girls have died? IF NONE, RECORD ‘00'. +)))0))), BOYS DEAD . . . . . . . . . . . . . *!!!*!!!* /)))3)))1 GIRLS DEAD . . . . . . . . . . . . *!!!*!!!* .)))2)))- 208 SUM ANSWERS TO 203, 205, AND 207, AND ENTER TOTAL. IF NONE, RECORD ‘00'. +)))0))), TOTAL . . . . . . . . . . . . . . . . . *!!!*!!!* .)))2)))- 209 CHECK 208: Just to make sure that I have this right: you have had in TOTAL _____ births during your life. Is that correct? +))), +))), PROBE AND YES /)))- NO .)))2)< CORRECT * 201-208 AS ? NECESSARY. 210 CHECK 208: ONE OR MORE +))), NO BIRTHS +))), BIRTHS /)))- .)))2)))))))))))))))))))))))))))))))))))))))))))))))))))) ? ))<226 EW 5 211 Now I would like to record the names of all your births, whether still alive or not, starting with the first one you had. RECORD NAMES OF ALL THE BIRTHS IN 212. RECORD TWINS AND TRIPLETS ON SEPARATE LINES. 212 213 214 215 216 217 IF ALIVE: 218 IF ALIVE: 219 IF ALIVE: 220 IF DEAD: 221 W hat name was given to your (first/ne xt) baby? (NAME) W ere any of these births twins? Is (NAME) a boy or a gir l? In what month and year was (NAME) born? PROBE: W hat is his/her birthday? Is (NAME) still al ive? How old was (NAME) at his/her last birthday? RECORD AG E IN COM- PLETED YEARS. Is (NAME) l iving with you? RECORD HOU SEHO LD LINE NUMBER OF CHILD (RECOR D ‘00' IF CHILD NOT LIS TE D IN HO US EH OL D). How old was (NAME) when he/she died? IF ‘1 YR’, PROBE: How many months old was (NA ME )? RECORD DAYS IF LESS THAN 1 MONTH; MONTHS IF LESS THAN TWO YEARS; OR YEARS. W ere the re any other l ive births between (NAME OF PREVIOUS BIRTH) and (NA ME )? 01 SING . 1 MULT 2 BOY . 1 GIRL . 2 +)))0))), MONTH *!!!*!!!* .)))2)))- YEAR +)))0)))0)))0))), *!!!*!!!*!!!*!!!* .)))2)))2)))2)))- YES . 1 NO . . 2 * ? 220 AG E IN YEARS +)))0))), *!!!*!!!* .)))2)))- YES . 1 NO . . 2 L INE NUMBER +)))0))), *!!!*!!!* .)))2)))- * ? (NEXT BIRTH) +)))0))), DAYS . . . . 1 *!!!*!!!* /)))3)))1 MONTHS . 2 *!!!*!!!* /)))3)))1 YEARS . . . 3 *!!!*!!!* .)))2)))- 02 SING . 1 MULT 2 BOY . 1 GIRL . 2 +)))0))), MONTH *!!!*!!!* .)))2)))- YEAR +)))0)))0)))0))), *!!!*!!!*!!!*!!!* .)))2)))2)))2)))- YES . 1 NO . . 2 * ? 220 AG E IN YEARS +)))0))), *!!!*!!!* .)))2)))- YES . 1 NO . . 2 L INE NUMBER +)))0))), *!!!*!!!* .)))2)))- * ? (GO TO 221) +)))0))), DAYS . . . . 1 *!!!*!!!* /)))3)))1 MONTHS . 2 *!!!*!!!* /)))3)))1 YEARS . . . 3 *!!!*!!!* .)))2)))- YES . . . . . 1 NO . . . . . . 2 03 SING . 1 MULT 2 BOY . 1 GIRL . 2 +)))0))), MONTH *!!!*!!!* .)))2)))- YEAR +)))0)))0)))0))), *!!!*!!!*!!!*!!!* .)))2)))2)))2)))- YES . 1 NO . . 2 * ? 220 AG E IN YEARS +)))0))), *!!!*!!!* .)))2)))- YES . 1 NO . . 2 L INE NUMBER +)))0))), *!!!*!!!* .)))2)))- * ? (GO TO 221) +)))0))), DAYS . . . . 1 *!!!*!!!* /)))3)))1 MONTHS . 2 *!!!*!!!* /)))3)))1 YEARS . . . 3 *!!!*!!!* .)))2)))- YES . . . . . 1 NO . . . . . . 2 04 SING . 1 MULT 2 BOY . 1 GIRL . 2 +)))0))), MONTH *!!!*!!!* .)))2)))- YEAR +)))0)))0)))0))), *!!!*!!!*!!!*!!!* .)))2)))2)))2)))- YES . 1 NO . . 2 * ? 220 AG E IN YEARS +)))0))), *!!!*!!!* .)))2)))- YES . 1 NO . . 2 L INE NUMBER +)))0))), *!!!*!!!* .)))2)))- * ? (GO TO 221) +)))0))), DAYS . . . . 1 *!!!*!!!* /)))3)))1 MONTHS . 2 *!!!*!!!* /)))3)))1 YEARS . . . 3 *!!!*!!!* .)))2)))- YES . . . . . 1 NO . . . . . . 2 05 SING . 1 MULT 2 BOY . 1 GIRL . 2 +)))0))), MONTH *!!!*!!!* .)))2)))- YEAR +)))0)))0)))0))), *!!!*!!!*!!!*!!!* .)))2)))2)))2)))- YES . 1 NO . . 2 * ? 220 AG E IN YEARS +)))0))), *!!!*!!!* .)))2)))- YES . 1 NO . . 2 L INE NUMBER +)))0))), *!!!*!!!* .)))2)))- * ? (GO TO 221) +)))0))), DAYS . . . . 1 *!!!*!!!* /)))3)))1 MONTHS . 2 *!!!*!!!* /)))3)))1 YEARS . . . 3 *!!!*!!!* .)))2)))- YES . . . . . 1 NO . . . . . . 2 06 SING . 1 MULT 2 BOY . 1 GIRL . 2 +)))0))), MONTH *!!!*!!!* .)))2)))- YEAR +)))0)))0)))0))), *!!!*!!!*!!!*!!!* .)))2)))2)))2)))- YES . 1 NO . . 2 * ? 220 AG E IN YEARS +)))0))), *!!!*!!!* .)))2)))- YES . 1 NO . . 2 L INE NUMBER +)))0))), *!!!*!!!* .)))2)))- * ? (GO TO 221) +)))0))), DAYS . . . . 1 *!!!*!!!* /)))3)))1 MONTHS . 2 *!!!*!!!* /)))3)))1 YEARS . . . 3 *!!!*!!!* .)))2)))- YES . . . . . 1 NO . . . . . . 2 07 SING . 1 MULT 2 BOY . 1 GIRL . 2 +)))0))), MONTH *!!!*!!!* .)))2)))- YEAR +)))0)))0)))0))), *!!!*!!!*!!!*!!!* .)))2)))2)))2)))- YES . 1 NO . . 2 * ? 220 AG E IN YEARS +)))0))), *!!!*!!!* .)))2)))- YES . 1 NO . . 2 L INE NUMBER +)))0))), *!!!*!!!* .)))2)))- * ? (GO TO 221) +)))0))), DAYS . . . . 1 *!!!*!!!* /)))3)))1 MONTHS . 2 *!!!*!!!* /)))3)))1 YEARS . . . 3 *!!!*!!!* .)))2)))- YES . . . . . 1 NO . . . . . . 2 212 213 214 215 216 217 IF ALIVE: 218 IF ALIVE: 219 IF ALIVE: 220 IF DEAD: 221 EW 6 W hat name was given to your next baby? (NAME) W ere any of these births twins? Is (NAME) a boy or a gir l? In what month and year was (NAME) born? PROBE: W hat is his/her birthday? Is (NAME) still al ive? How old was (NAME) at his/her last birthday? RECORD AG E IN COM- PLETED YEARS. Is (NAME) l iving with you? RECORD HOU SEHO LD LINE NUMBER OF CHILD (RECOR D ‘00' IF CHILD NOT LIS TE D IN HO US EH OL D). How old was (NAME) when he/she died? IF ‘1 YR’, PROBE: How many months old was (NA ME )? RECORD DAYS IF LESS THAN 1 MONTH; MONTHS IF LESS THAN TWO YEARS; OR YEARS. W ere the re any other l ive births between (NAME OF PREVIOUS BIRTH) and (NA ME )? 08 SING . 1 MULT 2 BOY . 1 GIRL . 2 +)))0))), MONTH . *!!!*!!!* .)))2)))- YEAR +)))0)))0)))0))), *!!!*!!!*!!!*!!!* .)))2)))2)))2)))- YES . 1 NO . . 2 * ? 220 AG E IN YEARS +)))0))), *!!!*!!!* .)))2)))- YES . 1 NO . . 2 L INE NUMBER +)))0))), *!!!*!!!* .)))2)))- * ? (GO TO 221) +)))0))), DAYS . . . . . 1 *!!!*!!!* /)))3)))1 MONTHS . . 2 *!!!*!!!* /)))3)))1 YEARS . . . . 3 *!!!*!!!* .)))2)))- YES . . . . . . 1 NO . . . . . . . 2 09 SING . 1 MULT 2 BOY . 1 GIRL . 2 +)))0))), MONTH *!!!*!!!* .)))2)))- YEAR +)))0)))0)))0))), *!!!*!!!*!!!*!!!* .)))2)))2)))2)))- YES . 1 NO . . 2 * ? 220 AG E IN YEARS +)))0))), *!!!*!!!* .)))2)))- YES . 1 NO . . 2 L INE NUMBER +)))0))), *!!!*!!!* .)))2)))- * ? (GO TO 221) +)))0))), DAYS . . . . 1 *!!!*!!!* /)))3)))1 MONTHS . 2 *!!!*!!!* /)))3)))1 YEARS . . . 3 *!!!*!!!* .)))2)))- YES . . . . . 1 NO . . . . . . 2 10 SING . 1 MULT 2 BOY . 1 GIRL . 2 +)))0))), MONTH *!!!*!!!* .)))2)))- YEAR +)))0)))0)))0))), *!!!*!!!*!!!*!!!* .)))2)))2)))2)))- YES . 1 NO . . 2 * ? 220 AG E IN YEARS +)))0))), *!!!*!!!* .)))2)))- YES . 1 NO . . 2 L INE NUMBER +)))0))), *!!!*!!!* .)))2)))- * ? (GO TO 221) +)))0))), DAYS . . . . 1 *!!!*!!!* /)))3)))1 MONTHS . 2 *!!!*!!!* /)))3)))1 YEARS . . . 3 *!!!*!!!* .)))2)))- YES . . . . . 1 NO . . . . . . 2 11 SING . 1 MULT 2 BOY . 1 GIRL . 2 +)))0))), MONTH *!!!*!!!* .)))2)))- YEAR +)))0)))0)))0))), *!!!*!!!*!!!*!!!* .)))2)))2)))2)))- YES . 1 NO . . 2 * ? 220 AG E IN YEARS +)))0))), *!!!*!!!* .)))2)))- YES . 1 NO . . 2 L INE NUMBER +)))0))), *!!!*!!!* .)))2)))- * ? (GO TO 221) +)))0))), DAYS . . . . 1 *!!!*!!!* /)))3)))1 MONTHS . 2 *!!!*!!!* /)))3)))1 YEARS . . . 3 *!!!*!!!* .)))2)))- YES . . . . . 1 NO . . . . . . 2 12 SING . 1 MULT 2 BOY . 1 GIRL . 2 +)))0))), MONTH *!!!*!!!* .)))2)))- YEAR +)))0)))0)))0))), *!!!*!!!*!!!*!!!* .)))2)))2)))2)))- YES . 1 NO . . 2 * ? 220 AG E IN YEARS +)))0))), *!!!*!!!* .)))2)))- YES . 1 NO . . 2 L INE NUMBER +)))0))), *!!!*!!!* .)))2)))- * ? (GO TO 221) +)))0))), DAYS . . . . 1 *!!!*!!!* /)))3)))1 MONTHS . 2 *!!!*!!!* /)))3)))1 YEARS . . . 3 *!!!*!!!* .)))2)))- YES . . . . . 1 NO . . . . . . 2 EW 7 NO. QUESTIONS AND FILTERS CODING CATEGORIES SKIP 222 Have you had any live births since the birth of (NAME OF LAST BIRTH)? YES . . . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 223 COMPARE 208 WITH NUMBER OF BIRTHS IN HISTORY ABOVE AND MARK: NUMBERS +))), NUMBERS ARE +))), ARE SAME /)))- DIFFERENT .)))2))< (PROBE AND RECONCILE) * ? CHECK: FOR EACH BIRTH: YEAR OF BIRTH IS RECORDED. FOR EACH LIVING CHILD: CURRENT AGE IS RECORDED. FOR EACH DEAD CHILD: AGE AT DEATH IS RECORDED. FOR AGE AT DEATH 12 MONTHS OR 1 YEAR: PROBE TO DETERMINE EXACT NUMBER OF MONTHS. +))), *!!!* /)))1 *!!!* /)))1 *!!!* /)))1 *!!!* .)))- 224 CHECK 215 AND ENTER THE NUMBER OF BIRTHS IN 1995 OR LATER. IF NONE, RECORD ‘0'. +))), *!!!* .)))- 225 FOR EACH BIRTH SINCE JANUARY 1995, ENTER ‘B’ IN THE MONTH OF BIRTH IN THE CALENDAR. FOR EACH BIRTH, ASK THE NUMBER OF MONTHS THE PREGNANCY LASTED AND RECORD ‘P’ IN EACH OF THE PRECEDING MONTHS ACCORDING TO THE DURATION OF PREGNANCY. (NOTE: THE NUMBER OF ‘P’s MUST BE ONE LESS THAN THE NUMBER OF MONTHS THAT THE PREGNANCY LASTED.) WRITE THE NAME OF THE CHILD TO THE LEFT OF THE ‘B’ CODE. 226 Are you pregnant now? YES . . . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 UNSURE . . . . . . . . . . . . . . . . . . . . . . . 8 ), )2<229 227 How many months pregnant are you? RECORD NUMBER OF COMPLETED MONTHS. ENTER ‘P’s IN THE CALENDAR, BEGINNING WITH THE MONTH OF INTERVIEW AND FOR THE TOTAL NUMBER OF COMPLETED MONTHS. +)))0))), MONTHS . . . . . . . . . . . . . . . *!!!*!!!* .)))2)))- 228 At the time you became pregnant did you want to become pregnant then, did you want to wait until later, or did you not want to have any (more) children at all? THEN . . . . . . . . . . . . . . . . . . . . . . . . . 1 LATER . . . . . . . . . . . . . . . . . . . . . . . . 2 NOT AT ALL . . . . . . . . . . . . . . . . . . . . 3 229 Have you ever had a pregnancy that miscarried, was aborted, or ended in a stillbirth? YES . . . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 ))<236 230 When did the last such pregnancy end? +)))0))), MONTH . . . . . . . . . . . . . . . . . *!!!*!!!* +)))0)))3)))3)))1 YEAR . . . . . . . . . . *!!!*!!!*!!!*!!!* .)))2)))2)))2)))- 231 CHECK 230: LAST PREGNANCY +))),LAST PREGNANCY +))), ENDED IN /)))- ENDED BEFORE .)))2)))))))))))))))))))))))))))))))))))))))))))))))))) JAN. 1995 OR LATER ? JAN. 1995 ))<236 232 How many months pregnant were you when the last such pregnancy ended? RECORD NUMBER OF COMPLETED MONTHS. ENTER ‘T’ IN THE CALENDAR IN THE MONTH THAT THE PREGNANCY TERMINATED AND ‘P’ FOR THE REMAINING NUMBER OF COMPLETED MONTHS. +)))0))), MONTHS . . . . . . . . . . . . . . . *!!!*!!!* .)))2)))- 233 Have you ever had any other pregnancies which did not result in a live birth? YES . . . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 ))<236 EW 8 NO. QUESTIONS AND FILTERS CODING CATEGORIES SKIP 234 ASK THE DATE AND THE DURATION OF PREGNANCY FOR EACH EARLIER NON-LIVE BIRTH PREGNANCY BACK TO JANUARY 1995. ENTER ‘T’ IN THE CALENDAR IN THE MONTH THAT EACH PREGNANCY TERMINATED AND ‘P’ FOR THE REMAINING NUMBER OF COMPLETED MONTHS. 234A Did you have any pregnancies that terminated before 1995 which did not result in a live birth? YES . . . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 ))<236 235 FILL IN THE MONTH AND YEAR OF TERMINATION OF THE LAST NON-LIVE BIRTH PREGNANCY PRIOR TO JANUARY 1995. +)))0))), MONTH . . . . . . . . . . . . . . . . . *!!!*!!!* +)))0)))3)))3)))1 YEAR . . . . . . . . . . *!!!*!!!*!!!*!!!* .)))2)))2)))2)))- 236 When did your last menstrual period start? (DATE, IF GIVEN) +)))0))), DAYS AGO . . . . . . . . . . . . 1 *!!!*!!!* /)))3)))1 WEEKS AGO . . . . . . . . . . 2 *!!!*!!!* /)))3)))1 MONTHS AGO . . . . . . . . . 3 *!!!*!!!* /)))3)))1 YEARS AGO . . . . . . . . . . . 4 *!!!*!!!* .)))2)))- IN MENOPAUSE/ HAS HAD HYSTERECTOMY . . 994 BEFORE LAST BIRTH . . . . . . . . . . 995 NEVER MENSTRUATED . . . . . . . . 996 237 From one menstrual period to the next, are there certain days when a woman is more likely to become pregnant if she has sexual relations? YES . . . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 DON’T KNOW . . . . . . . . . . . . . . . . . . . 8 ), )2<301 238 Is this time just before her period begins, during her period, right after her period has ended, or halfway between two periods? JUST BEFORE HER PERIOD BEGINS . . . . . . . . . . . . . . . . . . . . . 1 DURING HER PERIOD . . . . . . . . . . . . 2 RIGHT AFTER HER PERIOD HAS ENDED . . . . . . . . 3 HALFWAY BETWEEN TWO PERIODS . . . . . . . . . . . . . . . 4 OTHER 6 (SPECIFY) DON’T KNOW . . . . . . . . . . . . . . . . . . . 8 EW 9 SECTION 3. CONTRACEPTION Now I would like to talk about family planning - the various ways or methods that a couple can use to delay or avoid a pregnancy. CIRCLE CODE 1 IN 301 FOR EACH METHOD MENTIONED SPONTANEOUSLY. THEN PROCEED DOWN COLUMN 301, READING THE NAME AND DESCRIPTION OF EACH METHOD NOT MENTIONED SPONTANEOUSLY. CIRCLE CODE 1 IF METHOD IS RECOGNIZED, AND CODE 2 IF NOT RECOGNIZED. THEN, FOR EACH METHOD WITH CODE 1 CIRCLED IN 301, ASK 302. 301 Which ways or methods have you heard about? FOR METHODS NOT MENTIONED SPONTANEOUSLY, ASK: Have you ever heard of (METHOD)? 302 Have you ever used (METHOD)? 01 FE MA LE ST ER ILIZAT ION W om en can have an ope ration to avo id having any more chi ldren. YES . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . 2 ), ? Ha ve you eve r had an opera tion to avoid having any more chi ldren? YES . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . 2 02 MALE STE RILIZATION Men can have an operation to avoid having any more chi ldren. YES . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . 2 ), ? Have you ever had a partner who had an o pera tion to a void hav ing an y mo re chi ldren? YES . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . 2 03 PILL W om en c an take a pill eve ry day to av oid be com ing pre gna nt. YES . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . 2 ), ? YES . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . 2 04 IUD W omen can have a loop or coi l placed inside them by a doctor or a nurse. YES . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . 2 ), ? YES . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . 2 05 INJECTIONS W omen can have an injection by a health provider which stops them from becom ing pregnant for three months. YES . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . 2 ), ? YES . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . 2 06 IMPLANTS W omen can have several small rods placed in their upper arm by a do ctor or n urse whic h ca n pre ven t pregn anc y for one or m ore years. YES . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . 2 ), ? YES . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . 2 07 CON DOM Men can put a rubber sheath on their penis before sexual intercourse. YES . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . 2 ), ? YES . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . 2 08 FE MA LE CO ND OM W om en c an p lace a she ath in th eir vag ina be fore sexual intercourse. YES . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . 2 ), ? YES . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . 2 09 DIAPHRA GM W omen can place a thin f lexible disk in their vagina before intercourse. YES . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . 2 ), ? YES . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . 2 10 FO AM OR JE LLY W om en can plac e a s upposito ry, jelly, or crea m in their vagina before intercourse. YES . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . 2 ), ? YES . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . 2 11 LACTA TIONAL AMEN ORR HEA ME THOD (LAM) Up to 6 months after childbirth, a woman can use a method that requires that she breastfeeds frequently, day and night, and that her menstrual period has not returned. YES . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . 2 ), ? YES . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . 2 12 RH YT HM , BILL ING S O R O TH ER NA TU RA L ME TH OD S E very m onth that a woman is sexually active she can avoid pregnancy by not having sexual intercourse on the days of the month she is most likely to get preg nan t. YES . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . 2 ), ? YES . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . 2 13 W ITHD RA W AL M en ca n be ca reful and pu ll out before clim ax. YES . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . 2 ), ? YES . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . 2 14 EMER GENC Y CONT RACE PTION W omen can take pil ls up to three days after sexual inte rcou rse to a void bec om ing pre gna nt. YES . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . 2 ), ? YES . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . 2 15 Have you heard of any other ways or methods that women or men can use to a vo id pregnancy? YES . . . . . . . . . . . . . . 1 (SPECIFY) (SPECIFY) NO . . . . . . . . . . . . . . . . 2 YES . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . 2 YES . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . 2 303 CHECK 302: NOT A SINGLE +))), AT LEAST ONE +))), “YES” /)))- “YES” .)))2)))))))))))))))))))))))))))))))))))))))))))))))) (NEVER USED) ? (EVER USED) ))<307 EW 10 NO. QUESTIONS AND FILTERS CODING CATEGORIES SKIP 304 Have you ever used anything or tried in any way to delay or avoid getting pregnant? YES . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . 2 ))<328 306 What have you used or done? CORRECT 302 AND 303 (AND 301 IF NECESSARY). 307 Now I would like to ask you about the first time that you did something or used a method to avoid getting pregnant. How many living children did you have at that time, if any? IF NONE, RECORD ‘00'. +)))0))), NUMBER OF CHILDREN . *!!!*!!!* .)))2)))- 308 CHECK 302 (01): WOMAN NOT +))), WOMAN +))), STERILIZED /)))- STERILIZED .)))2)))))))))))))))))))))))))))))))))))))))))))))))))) ? ))<311A 309 CHECK 226: NOT PREGNANT +))), PREGNANT +))), OR UNSURE /)))- .)))2)))))))))))))))))))))))))))))))))))))))))))))))))) ? ))<320 310 Are you currently doing something or using any method to delay or avoid getting pregnant? YES . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . 2 ))<320 311 311A Which method are you using? CIRCLE ‘A' FOR FEMALE STERILIZATION. IF MORE THAN ONE METHOD MENTIONED, FOLLOW SKIP INSTRUCTION FOR HIGHEST METHOD ON LIST. FEMALE STERILIZATION . . . . . . . A MALE STERILIZATION . . . . . . . . . . B PILL . . . . . . . . . . . . . . . . . . . . . . . . C IUD . . . . . . . . . . . . . . . . . . . . . . . . . D INJECTIONS . . . . . . . . . . . . . . . . . . E IMPLANTS . . . . . . . . . . . . . . . . . . . F CONDOM . . . . . . . . . . . . . . . . . . . . G FEMALE CONDOM . . . . . . . . . . . . H DIAPHRAGM . . . . . . . . . . . . . . . . . . I FOAM/JELLY . . . . . . . . . . . . . . . . . J LACT. AMEN. METHOD . . . . . . . . . K PERIODIC ABSTINENCE . . . . . . . . L WITHDRAWAL . . . . . . . . . . . . . . . . M OTHER X (SPECIFY) ), )2<313 ), * * * /<319 * * )- ))<319A ), /<319B * )- 313 Where did the sterilization take place? IF SOURCE IS HOSPITAL, HEALTH CENTER, OR CLINIC, WRITE THE NAME OF THE PLACE. PROBE TO IDENTIFY THE TYPE OF SOURCE AND CIRCLE THE APPROPRIATE CODE. (NAME OF PLACE) IF BOTH CODE ‘A’ AND CODE ‘B’ ARE CIRCLED IN 311, ASK 313- 317 ABOUT FEMALE STERILIZATION ONLY. PUBLIC SECTOR GOVT. HOSPITAL . . . . . . . . . . . 11 GOVT. HEALTH CENTER . . . . . 12 FAMILY PLANNING CLINIC . . . 13 OTHER PUBLIC 16 (SPECIFY) MISSION HOSPITAL . . . . . . . . . . . . . . . . . 21 HEALTH CENTER . . . . . . . . . . . 22 PRIVATE MEDICAL SECTOR PRIVATE HOSPITAL/CLINIC . . 31 PRIVATE DOCTOR’S OFFICE . 32 OTHER PRIVATE MEDICAL 36 (SPECIFY) BLM . . . . . . . . . . . . . . . . . . . . . . . 41 OTHER 96 (SPECIFY) DON’T KNOW . . . . . . . . . . . . . . . . 98 NO. QUESTIONS AND FILTERS CODING CATEGORIES SKIP EW 11 314 CHECK 311: CODE ‘A’ +))), CIRCLED /)))- * ? Before your sterilization operation, were you told that you would not be able to have any (more) children because of the operation? CODE ‘B’ +))), CIRCLED /)))- * ? Before the sterilization operation, was your husband/partner told that he would not be able to have any (more) children because of the operation? YES . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . 2 DON’T KNOW . . . . . . . . . . . . . . . . . 8 316 In what month and year was the sterilization performed? +)))0))), MONTH . . . . . . . . . . . . . . . *!!!*!!!* +)))0)))3)))3)))1 YEAR . . . . . . . . *!!!*!!!*!!!*!!!* .)))2)))2)))2)))- 317 CHECK 316: STERILIZED BEFORE 1995 +))), /)))- ? 326 STERILIZED IN 1995 +))), OR LATER /)))- ? 320 319 319A Where did you obtain (CURRENT METHOD) when you started using it? Where did you learn to use the lactational amenorrhea method? IF SOURCE IS HOSPITAL, HEALTH CENTER, OR CLINIC, WRITE THE NAME OF THE PLACE. PROBE TO IDENTIFY THE TYPE OF SOURCE AND CIRCLE THE APPROPRIATE CODE. (NAME OF PLACE) PUBLIC SECTOR GOVT. HOSPITAL . . . . . . . . . . . 11 GOVT. HEALTH CENTER . . . . . 12 FAMILY PLANNING CLINIC . . . 13 MOBILE CLINIC . . . . . . . . . . . . . 14 CBDA/FIELD WORKER . . . . . . . 15 OTHER PUBLIC 16 (SPECIFY) MISSION HOSPITAL . . . . . . . . . . . . . . . . . 21 HEALTH CENTER . . . . . . . . . . . 22 MOBILE CLINIC . . . . . . . . . . . . . 23 PRIVATE MEDICAL SECTOR PRIVATE HOSPITAL/CLINIC . . 31 PHARMACY . . . . . . . . . . . . . . . 32 PRIVATE DOCTOR . . . . . . . . . . 33 MOBILE CLINIC . . . . . . . . . . . . . 34 CBDA/FIELD WORKER . . . . . . . 35 OTHER PRIVATE MEDICAL 36 (SPECIFY) BLM . . . . . . . . . . . . . . . . . . . . . . . 41 OTHER SOURCE SHOP . . . . . . . . . . . . . . . . . . . . 51 CHURCH . . . . . . . . . . . . . . . . . . 52 FRIEND/RELATIVE . . . . . . . . . . 53 OTHER 96 (SPECIFY) 319B For how many months have you been using (METHOD) continuously? IF LESS THAN 1 MONTH RECORD ‘00'. +)))0))), MONTHS . . . . . . . . . . . . . *!!!*!!!* .)))2)))- 8 YEARS OR LONGER . . . . . . . . 96 NO. QUESTIONS AND FILTERS CODING CATEGORIES SKIP EW 12 320 CHECK 311/311A: CIRCLE METHOD CODE: IF MORE THAN ONE METHOD CODE CIRCLED IN 311/311A, CIRCLE CODE FOR HIGHEST METHOD IN LIST. NO CODE CIRCLED . . . . . . . . . . . 00 FEMALE STERILIZATION . . . . . . 01 MALE STERILIZATION . . . . . . . . . 02 PILL . . . . . . . . . . . . . . . . . . . . . . . 03 IUD . . . . . . . . . . . . . . . . . . . . . . . . 04 INJECTIONS . . . . . . . . . . . . . . . . . 05 IMPLANTS . . . . . . . . . . . . . . . . . . 06 CONDOM . . . . . . . . . . . . . . . . . . . 07 FEMALE CONDOM . . . . . . . . . . . 08 DIAPHRAGM . . . . . . . . . . . . . . . . 09 FOAM/JELLY . . . . . . . . . . . . . . . . 10 LACTATIONAL AMEN. METHOD . 11 PERIODIC ABSTINENCE . . . . . . . 12 WITHDRAWAL . . . . . . . . . . . . . . . 13 OTHER METHOD . . . . . . . . . . . . . 96 ))<328 ))<330 ))<327 ), /<325 * )- ), /<330 )- 322 You obtained (CURRENT METHOD) from (SOURCE OF METHOD FROM 313 OR 319). At that time, were you told about side effects or problems you might have with the method? YES . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . 2 ))<323 322A Were you ever told by a health or family planning worker about side effects or problems you might have with the method? YES . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . 2 ))<325 323 Were you told what to do if you experienced side effects or problems? YES . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . 2 325 CHECK 322: CODE ‘1' +))), CIRCLED /)))- * ? At that time, were you told about other methods of family planning which you could use? CODE ‘1' NOT +))), CIRCLED /)))- * ? When you obtained (CURRENT METHOD) from (SOURCE OF METHOD FROM 313 OR 319), were you told about other methods of family planning which you could use? YES . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . 2 ))<326 325A Were you ever told by a health or family planning worker about other methods of family planning which you could use? YES . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . 2 326 CHECK 311/311A: CIRCLE METHOD CODE: IF MORE THAN ONE METHOD CODE CIRCLED IN 311/311A, CIRCLE CODE FOR HIGHEST METHOD IN LIST. FEMALE STERILIZATION . . . . . . 01 PILL . . . . . . . . . . . . . . . . . . . . . . . 03 IUD . . . . . . . . . . . . . . . . . . . . . . . . 04 INJECTIONS . . . . . . . . . . . . . . . . . 05 IMPLANTS . . . . . . . . . . . . . . . . . . 06 FEMALE CONDOM . . . . . . . . . . . 08 DIAPHRAGM . . . . . . . . . . . . . . . . 09 FOAM/JELLY . . . . . . . . . . . . . . . . 10 LACTATIONAL AMEN. METHOD . 11 ))<330 ))<330 ))<330 ))<330 NO. QUESTIONS AND FILTERS CODING CATEGORIES SKIP EW 13 327 Where did you obtain (CURRENT METHOD) the last time? IF SOURCE IS HOSPITAL, HEALTH CENTER, OR CLINIC, WRITE THE NAME OF THE PLACE. PROBE TO IDENTIFY THE TYPE OF SOURCE AND CIRCLE THE APPROPRIATE CODE. (NAME OF PLACE) PUBLIC SECTOR GOVT. HOSPITAL . . . . . . . . . . . 11 GOVT. HEALTH CENTER . . . . . 12 FAMILY PLANNING CLINIC . . . 13 MOBILE CLINIC . . . . . . . . . . . . . 14 CBDA/FIELD WORKER . . . . . . . 15 OTHER PUBLIC 16 (SPECIFY) MISSION HOSPITAL . . . . . . . . . . . . . . . . . 21 HEALTH CENTER . . . . . . . . . . . 22 MOBILE CLINIC . . . . . . . . . . . . . 23 PRIVATE MEDICAL SECTOR PRIVATE HOSPITAL/CLINIC . . 31 PHARMACY . . . . . . . . . . . . . . . 32 PRIVATE DOCTOR . . . . . . . . . . 33 MOBILE CLINIC . . . . . . . . . . . . . 34 CBDA/FIELD WORKER . . . . . . . 35 OTHER PRIVATE MEDICAL 36 (SPECIFY) BLM . . . . . . . . . . . . . . . . . . . . . . . 41 OTHER SOURCE SHOP . . . . . . . . . . . . . . . . . . . . 51 CHURCH . . . . . . . . . . . . . . . . . . 52 FRIEND/RELATIVE . . . . . . . . . . 53 OTHER 96 (SPECIFY) ), * * * * * * * * * * /<330 * * * * * * * * * * * * * * * * * * )- 328 Do you know of a place where you can obtain a method of family planning? YES . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . 2 ))<330 329 Where is that? IF SOURCE IS HOSPITAL, HEALTH CENTER, OR CLINIC, WRITE THE NAME OF THE PLACE. PROBE TO IDENTIFY THE TYPE OF SOURCE AND CIRCLE THE APPROPRIATE CODE. (NAME OF PLACE) Any other place? RECORD ALL MENTIONED. PUBLIC SECTOR GOVT. HOSPITAL . . . . . . . . . . . . A GOVT. HEALTH CENTER . . . . . . B FAMILY PLANNING CLINIC . . . . C MOBILE CLINIC . . . . . . . . . . . . . . D CBDA/FIELD WORKER . . . . . . . . E OTHER PUBLIC F (SPECIFY) MISSION HOSPITAL . . . . . . . . . . . . . . . . . . G HEALTH CENTER . . . . . . . . . . . . H MOBILE CLINIC . . . . . . . . . . . . . . . I PRIVATE MEDICAL SECTOR PRIVATE HOSPITAL/CLINIC . . . J PHARMACY . . . . . . . . . . . . . . . . K PRIVATE DOCTOR . . . . . . . . . . . L MOBILE CLINIC . . . . . . . . . . . . . . M CBDA\FIELD WORKER . . . . . . . . N OTHER PRIVATE MEDICAL O (SPECIFY) BLM . . . . . . . . . . . . . . . . . . . . . . . . P OTHER SOURCE SHOP . . . . . . . . . . . . . . . . . . . . . Q CHURCH . . . . . . . . . . . . . . . . . . . R FRIEND/RELATIVE . . . . . . . . . . . S OTHER X (SPECIFY) 330 In the last 12 months, were you visited by a community-based distribution agent who talked to you about family planning? YES . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . 2 331 In the last 12 months, have you visited a health facility for care for yourself (or your children)? YES . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . 2 ))<401 332 Did any staff member at the health facility speak to you about family planning methods? YES . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . 2 EW 14 SECTION 4A. PREGNANCY, POSTNATAL CARE AND BREASTFEEDING 401 CHECK 224: ONE OR MORE +))), NO +))), BIRTHS /)))- BIRTHS .)))2))))))))))))))))))))))))))))))))))))))))))))))) IN 1995 * IN 1995 OR LATER ? OR LATER )<486 402 ENTER IN THE TABLE THE LINE NUMBER, NAME, AND SURVIVAL STATUS OF EACH BIRTH IN 1995 OR LATER. ASK THE QUESTIONS ABOUT ALL OF THESE BIRTHS. BEGIN WITH THE LAST BIRTH. (IF THERE ARE MORE THAN 2 BIRTHS, USE LAST COLUMN OF ADDITIONAL QUESTIONNAIRES). Now I would like to ask you some questions about the health of all your children born in the last five years. (We will talk about each separately.) 403 LINE NUMBER FROM 212 LAST BIRTH +)))0))), LINE NUMBER . . . . . . . . . *!!!*!!!* .)))2)))- NEXT-TO-LAST BIRTH +)))0))), LINE NUMBER . . . . . . . . . *!!!*!!!* .)))2)))- 404 FROM 212 AND 216 NAME +)), +)), ALIVE /))- DEAD /))- ? ? NAME +)), +)), ALIVE /))- DEAD /))- ? ? 405 At the time you became pregnant with (NAME), did you want to become pregnant then, did you want to wait until later, or did you not want to have any (more) children at all? THEN . . . . . . . . . . . . . . . . . . . . . . . 1 (SKIP TO 407)=)))))))- LATER . . . . . . . . . . . . . . . . . . . . . . 2 NOT AT ALL . . . . . . . . . . . . . . . . . . 3 (SKIP TO 407)=)))))))- THEN . . . . . . . . . . . . . . . . . . . . . . . 1 (SKIP TO 422)=)))))))- LATER . . . . . . . . . . . . . . . . . . . . . . 2 NOT AT ALL . . . . . . . . . . . . . . . . . . 3 (SKIP TO 422)=)))))))- 406 How much longer would you like to have waited? +)))0))), MONTHS . . . . . . . . . . . 1 *!!!*!!!* /)))3)))1 YEARS . . . . . . . . . . . . . 2 *!!!*!!!* .)))2)))- DON’T KNOW . . . . . . . . . . . . . . . . 998 +)))0))), MONTHS . . . . . . . . . . . 1 *!!!*!!!* /)))3)))1 YEARS . . . . . . . . . . . . . 2 *!!!*!!!* .)))2)))- DON’T KNOW . . . . . . . . . . . . . . . . 998 407 Did you see anyone for antenatal care for this pregnancy? IF YES: Whom did you see? Anyone else? PROBE FOR THE TYPE OF PERSON AND RECORD ALL PERSONS SEEN. HEALTH PROFESSIONAL DOCTOR/CLINICAL OFFICER . . A NURSE/MIDWIFE . . . . . . . . . . . . B WARD ATTENDANT . . . . . . . . . . C OTHER PERSON TRADITIONAL BIRTH ATTENDANT . . . . . . . . . . . . . . D OTHER X (SPECIFY) NO ONE . . . . . . . . . . . . . . . . . . . . . Y (SKIP TO 415)=)))))))- 408 How many months pregnant were you when you first received antenatal care for this pregnancy? +)))0))), MONTHS . . . . . . . . . . . . . *!!!*!!!* .)))2)))- DON’T KNOW . . . . . . . . . . . . . . . . 98 409 How many times did you receive antenatal care during this pregnancy? +)))0))), NO. OF TIMES . . . . . . . . . *!!!*!!!* .)))2)))- DON’T KNOW . . . . . . . . . . . . . . . . 98 410 CHECK 409: NUMBER OF TIMES RECEIVED ANTENATAL CARE ONCE +))), /)))- ? (SKIP TO 412) MORE THAN ONCE OR DK +))), /)))- * ? EW 15 LAST BIRTH NAME NEXT-TO-LAST BIRTH NAME 411 How many months pregnant were you the last time you received antenatal care? +)))0))), MONTHS . . . . . . . . . . . . . *!!!*!!!* .)))2)))- DON’T KNOW . . . . . . . . . . . . . . . . 98 412 During this pregnancy, were any of the following done at least once? Were you weighed? Was your height measured? Was your blood pressure measured? Did you give a urine sample? Did you give a blood sample? YES NO WEIGHT . . . . . . . . . . . . 1 2 HEIGHT . . . . . . . . . . . . 1 2 BLOOD PRESSURE . . . 1 2 URINE SAMPLE . . . . . . 1 2 BLOOD SAMPLE . . . . . 1 2 413 Were you told about the signs of pregnancy complications? YES . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . 2 (SKIP TO 415)=)))))))1 DON’T KNOW . . . . . . . . . . . . . . . . . 8 414 Were you told where to go if you had these complications? YES . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . 2 DON’T KNOW . . . . . . . . . . . . . . . . . 8 415 During this pregnancy, were you given an injection in the arm to prevent the baby from getting tetanus, that is, convulsions after birth? YES . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . 2 (SKIP TO 416)=)))))))1 DON’T KNOW . . . . . . . . . . . . . . . . . 8 415A During this pregnancy, how many times did you get this injection? +))), TIMES . . . . . . . . . . . . . . . . . . . . *!!!* .)))- DON'T KNOW . . . . . . . . . . . . . . . . . 8 416 During this pregnancy, were you given or did you buy any iron tablets? SHOW TABLET. YES . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . 2 (SKIP TO 418)=)))))))1 DON’T KNOW . . . . . . . . . . . . . . . . . 8 417 During the whole pregnancy, for how many days did you take the tablets? IF ANSWER IS NOT NUMERIC, PROBE FOR APPROXIMATE NUMBER OF DAYS. NUMBER OF +)))0)))0))), DAYS . . . . . . . . . . . . *!!!*!!!*!!!* .)))2)))2)))- DON’T KNOW . . . . . . . . . . . . . . . . 998 418 During this pregnancy, did you have difficulty with your vision during the daylight? YES . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . 2 DON’T KNOW . . . . . . . . . . . . . . . . . 8 419 During this pregnancy, did you have difficulty with your vision at night? YES . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . 2 DON’T KNOW . . . . . . . . . . . . . . . . . 8 420 During this pregnancy, did you take any drugs in order to prevent you from getting malaria? Not considered here are instances where you took the drug because you had malaria. YES . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . 2 (SKIP TO 422)=)))))))1 DON’T KNOW . . . . . . . . . . . . . . . . . 8 LAST BIRTH NAME NEXT-TO-LAST BIRTH NAME EW 16 421 Which medicines did you take to prevent malaria? RECORD ALL MENTIONED. IF TYPE OF DRUG IS NOT DETERMINED, SHOW TYPICAL ANTIMALARIAL DRUGS TO RESPONDENT. FOR EACH DRUG CIRCLED ASK: How many times did you take the malaria medicine(s) during the pregnancy? TIMES +))), SP (NOVIDAR, FANSIDAR) . A*!!!* .)))- +))), QUININE . . . . . . . . . . . . . . . . B*!!!* .)))- +))), CHLOROQUINE . . . . . . . . . . C*!!!* .)))- +))), AMODIAQUINE . . . . . . . . . . D*!!!* .)))- +))), HALAFAN . . . . . . . . . . . . . . . E*!!!* .)))- +))), OTHER X*!!!* (SPECIFY) .)))- 422 When (NAME) was born, was he/she very large, larger than average, average, smaller than average, or very small? VERY LARGE . . . . . . . . . . . . . . . . . 1 LARGER THAN AVERAGE . . . . . . 2 AVERAGE . . . . . . . . . . . . . . . . . . . 3 SMALLER THAN AVERAGE . . . . . 4 VERY SMALL . . . . . . . . . . . . . . . . . 5 DON’T KNOW . . . . . . . . . . . . . . . . . 8 VERY LARGE . . . . . . . . . . . . . . . . . 1 LARGER THAN AVERAGE . . . . . . 2 AVERAGE . . . . . . . . . . . . . . . . . . . 3 SMALLER THAN AVERAGE . . . . . 4 VERY SMALL . . . . . . . . . . . . . . . . . 5 DON’T KNOW . . . . . . . . . . . . . . . . . 8 423 Was (NAME) weighed at birth? YES . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . 2 (SKIP TO 425)=)))))))1 DON’T KNOW . . . . . . . . . . . . . . . . . 8 YES . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . 2 (SKIP TO 425)=)))))))1 DON’T KNOW . . . . . . . . . . . . . . . . . 8 424 How much did (NAME) weigh? RECORD WEIGHT FROM HEALTH CARD, IF AVAILABLE. GRAMS FROM +)))0)))0)))0))), CARD . . . . . . 1 *!!!*!!!*!!!*!!!* .)))2)))2)))2)))- GRAMS FROM +)))0)))0)))0))), RECALL . . . . 2 *!!!*!!!*!!!*!!!* .)))2)))2)))2)))- DON’T KNOW . . . . . . . . . . . . . . 99998 GRAMS FROM +)))0)))0)))0))), CARD . . . . . . 1 *!!!*!!!*!!!*!!!* .)))2)))2)))2)))- GRAMS FROM +)))0)))0)))0))), RECALL . . . . 2 *!!!*!!!*!!!*!!!* .)))2)))2)))2)))- DON’T KNOW . . . . . . . . . . . . . . 99998 425 Who assisted with the delivery of (NAME)? Anyone else? PROBE FOR THE TYPE OF PERSON AND RECORD ALL PERSONS ASSISTING. HEALTH PROFESSIONAL DOCTOR/CLINICAL OFFICER . . A NURSE/MIDWIFE . . . . . . . . . . . . B WARD ATTENDANT . . . . . . . . . . C OTHER PERSON TRADITIONAL BIRTH ATTENDANT . . . . . . . . . . . . . D RELATIVE/FRIEND . . . . . . . . . . E OTHER X (SPECIFY) NO ONE . . . . . . . . . . . . . . . . . . . . . Y HEALTH PROFESSIONAL DOCTOR . . . . . . . . . . . . . . . . . . A NURSE/MIDWIFE . . . . . . . . . . . . B WARD ATTENDANT . . . . . . . . . . C OTHER PERSON TRADITIONAL BIRTH ATTENDANT . . . . . . . . . . . . . D RELATIVE/FRIEND . . . . . . . . . . E OTHER X (SPECIFY) NO ONE . . . . . . . . . . . . . . . . . . . . . Y LAST BIRTH NAME NEXT-TO-LAST BIRTH NAME EW 17 426 Where did you give birth to (NAME)? HOME YOUR HOME . . . . . . . . . . . . . . 11 (SKIP TO 428)=)))))))1 OTHER HOME . . . . . . . . . . . . . 12 PUBLIC SECTOR GOVT. HOSPITAL . . . . . . . . . . 21 GOVT. HEALTH CENTER . . . . 22 GOVT. HEALTH POST . . . . . . . 23 OTHER PUBLIC 26 (SPECIFY) MISSION HOSPITAL . . . . . . . . . . . . . . . . . 31 HEALTH CENTER . . . . . . . . . . . 32 PRIVATE MEDICAL SECTOR PVT. HOSPITAL/CLINIC . . . . . . 41 OTHER PVT. MEDICAL 46 (SPECIFY) OTHER 96 (SPECIFY) * (SKIP TO 428)=)))))))- HOME YOUR HOME . . . . . . . . . . . . . . 11 (SKIP TO 428)=)))))))1 OTHER HOME . . . . . . . . . . . . . 12 PUBLIC SECTOR GOVT. HOSPITAL . . . . . . . . . . 21 GOVT. HEALTH CENTER . . . . 22 GOVT. HEALTH POST . . . . . . . 23 OTHER PUBLIC 26 (SPECIFY) MISSION HOSPITAL . . . . . . . . . . . . . . . . . 31 HEALTH CENTER . . . . . . . . . . . 32 PRIVATE MEDICAL SECTOR PVT. HOSPITAL/CLINIC . . . . . . 41 OTHER PVT. MEDICAL 46 (SPECIFY) OTHER 96 (SPECIFY) * (SKIP TO 428)=)))))))- 427 Was (NAME) delivered by caesarian section? YES . . . . . . . . . . . . . . . . . . . . . . . . 1 (SKIP TO 432)=)))))))1 NO . . . . . . . . . . . . . . . . . . . . . . . . . 2 YES . . . . . . . . . . . . . . . . . . . . . . . . 1 (SKIP TO 434)=)))))))1 NO . . . . . . . . . . . . . . . . . . . . . . . . . 2 428 After (NAME) was born, did a health professional or a traditional birth attendant check on your health? YES . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . 2 (SKIP TO 432)=)))))))- YES . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . 2 429 How many days or weeks after the delivery did the first check take place? RECORD ‘00' DAYS IF SAME DAY. +)))0))), DAYS AFTER DEL . . . . 1 *!!!*!!!* /)))3)))1 WEEKS AFTER DEL . . 2 *!!!*!!!* .)))2)))- DON’T KNOW . . . . . . . . . . . . . . . . 998 430 Who checked on your health at that time? PROBE FOR MOST QUALIFIED PERSON. HEALTH PROFESSIONAL DOCTOR/CLINICAL OFFICER . . 1 NURSE/MIDWIFE . . . . . . . . . . . . 2 WARD ATTENDANT . . . . . . . . . . 3 OTHER PERSON TRADITIONAL BIRTH ATTENDANT . . . . . . . . . . . . . 4 OTHER 6 (SPECIFY) LAST BIRTH NAME NEXT-TO-LAST BIRTH NAME EW 18 431 Where did this first check take place? HOME YOUR HOME . . . . . . . . . . . . . . 11 OTHER HOME . . . . . . . . . . . . . 12 PUBLIC SECTOR GOVT. HOSPITAL . . . . . . . . . . 21 GOVT. HEALTH CENTER . . . . 22 GOVT. HEALTH POST . . . . . . . 23 OTHER PUBLIC 26 (SPECIFY) MISSION HOSPITAL . . . . . . . . . . . . . . . . . 31 HEALTH CENTER . . . . . . . . . . . 32 PRIVATE MEDICAL SECTOR PVT. HOSPITAL/CLINIC . . . . . . 41 OTHER PVT. MEDICAL 46 (SPECIFY) OTHER 96 (SPECIFY) 431A At that first check, did any health worker discuss use of family planning? YES . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . 2 432 In the first two months after delivery, did you receive a vitamin A capsule like this? SHOW CAPSULE. YES . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . 2 433 Has your period returned since the birth of (NAME)? YES . . . . . . . . . . . . . . . . . . . . . . . . 1 (SKIP TO 435)=)))))))- NO . . . . . . . . . . . . . . . . . . . . . . . . . 2 (SKIP TO 436)=)))))))- 434 Did your period return between the birth of (NAME) and your next pregnancy? YES . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . 2 (SKIP TO 438)=)))))))- 435 For how many months after the birth of (NAME) did you not have a period? +)))0))), MONTHS . . . . . . . . . . . . . *!!!*!!!* .)))2)))- DON’T KNOW . . . . . . . . . . . . . . . . 98 +)))0))), MONTHS . . . . . . . . . . . . . *!!!*!!!* .)))2)))- DON’T KNOW . . . . . . . . . . . . . . . . 98 436 CHECK 226: RESPONDENT PREGNANT? NOT +)), PREGNANT +)), PREG- /))- OR UNSURE .))1 NANT ? (SKIP TO 438)=))- 437 Have you resumed sexual relations since the birth of (NAME)? YES . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . 2 (SKIP TO 439)=)))))))- 438 For how many months after the birth of (NAME) did you not have sexual relations? +)))0))), MONTHS . . . . . . . . . . . . . *!!!*!!!* .)))2)))- DON’T KNOW . . . . . . . . . . . . . . . . 98 +)))0))), MONTHS . . . . . . . . . . . . . *!!!*!!!* .)))2)))- DON’T KNOW . . . . . . . . . . . . . . . . 98 439 Did you ever breastfeed (NAME)? YES . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . 2 (SKIP TO 444)=)))))))- YES . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . 2 (SKIP TO 444)=)))))))- 440 How long after birth did you first put (NAME) to the breast? IF LESS THAN 1 HOUR, RECORD ‘00' HOURS. IF LESS THAN 24 HOURS, RECORD HOURS. OTHERWISE, RECORD DAYS. IMMEDIATELY . . . . . . . . . . . . . . . 000 +)))0))), HOURS . . . . . . . . . . . . . 1 *!!!*!!!* /)))3)))1 DAYS . . . . . . . . . . . . . . 2 *!!!*!!!* .)))2)))- IMMEDIATELY . . . . . . . . . . . . . . . 000 +)))0))), HOURS . . . . . . . . . . . . . 1 *!!!*!!!* /)))3)))1 DAYS . . . . . . . . . . . . . . 2 *!!!*!!!* .)))2)))- LAST BIRTH NAME NEXT-TO-LAST BIRTH NAME EW 19 440A Within the first three days after delivery, before your milk began flowing regularly, was (NAME) given anything to drink other than breast milk? YES . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . 2 (SKIP TO 441)=)))))))- YES . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . 2 (SKIP TO 441)=)))))))- 440B What was (NAME) given to drink before your milk began flowing regularly? Anything else? RECORD ALL MENTIONED. MILK (OTHER THAN BREAST MILK) . . . . . . . . . . . . . A PLAIN WATER . . . . . . . . . . . . . . . . B SUGAR OR GLUCOSE WATER . . . C PHALA . . . . . . . . . . . . . . . . . . . . . . D GRIPE WATER . . . . . . . . . . . . . . . . E SALT AND SUGAR SOLUTION . . . F FRUIT JUICE . . . . . . . . . . . . . . . . . G INFANT FORMULA (E.G.LACTOGEN) . . . . . . . . . . . H TEA/INFUSIONS . . . . . . . . . . . . . . . I HONEY . . . . . . . . . . . . . . . . . . . . . . . J OTHER______________________X (SPECIFY) MILK (OTHER THAN BREAST MILK) . . . . . . . . . . . . . A PLAIN WATER . . . . . . . . . . . . . . . . B SUGAR OR GLUCOSE WATER . . . C PHALA . . . . . . . . . . . . . . . . . . . . . . D GRIPE WATER . . . . . . . . . . . . . . . . E SALT AND SUGAR SOLUTION . . . F FRUIT JUICE . . . . . . . . . . . . . . . . . G INFANT FORMULA (E.G.LACTOGEN) . . . . . . . . . . . H TEA/INFUSIONS . . . . . . . . . . . . . . . I HONEY . . . . . . . . . . . . . . . . . . . . . . . J OTHER______________________X (SPECIFY) 441 CHECK 404: CHILD ALIVE? ALIVE +)), DEAD +)), /))- .))1 ? (SKIP TO 443)=))- ALIVE +)), DEAD +)), /))- .))1 ? (SKIP TO 443)=))- 442 Are you still breastfeeding (NAME)? YES . . . . . . . . . . . . . . . . . . . . . . . . 1 (SKIP TO 445)=)))))))- NO . . . . . . . . . . . . . . . . . . . . . . . . . 2 YES . . . . . . . . . . . . . . . . . . . . . . . . 1 (SKIP TO 445)=)))))))- NO . . . . . . . . . . . . . . . . . . . . . . . . . 2 443 For how many months did you breastfeed (NAME)? +)))0))), MONTHS . . . . . . . . . . . . . *!!!*!!!* .)))2)))- DON’T KNOW . . . . . . . . . . . . . . . . 98 +)))0))), MONTHS . . . . . . . . . . . . . *!!!*!!!* .)))2)))- DON’T KNOW . . . . . . . . . . . . . . . . 98 444 CHECK 404: CHILD ALIVE? ALIVE +)), /))- * ? (SKIP TO 447) DEAD +)), /))- ? (GO BACK TO 405 IN NEXT COLUMN; OR, IF NO MORE BIRTHS, GO TO 451) ALIVE +)), /))- * ? (SKIP TO 447) DEAD +)), /))- ? (GO BACK TO 405 IN LAST COLUMN OF NEW QUESTION- NAIRE; OR, IF NO MORE BIRTHS, GO TO 451) 445 How many times did you breastfeed last night between sunset and sunrise? IF ANSWER IS NOT NUMERIC, PROBE FOR APPROXIMATE NUMBER. NUMBER OF +)))0))), NIGHTTIME FEEDINGS . . *!!!*!!!* .)))2)))- NUMBER OF +)))0))), NIGHTTIME FEEDINGS . . *!!!*!!!* .)))2)))- 446 How many times did you breastfeed yesterday during the daylight hours? IF ANSWER IS NOT NUMERIC, PROBE FOR APPROXIMATE NUMBER. NUMBER OF +)))0))), DAYLIGHT FEEDINGS . . . *!!!*!!!* .)))2)))- NUMBER OF +)))0))), DAYLIGHT FEEDINGS . . . *!!!*!!!* .)))2)))- LAST BIRTH NAME NEXT-TO-LAST BIRTH NAME EW 20 447 Did (NAME) drink anything from a bottle with a nipple yesterday or last night? YES . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . 2 DON’T KNOW . . . . . . . . . . . . . . . . . 8 YES . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . 2 DON’T KNOW . . . . . . . . . . . . . . . . . 8 447A Was sugar added to any of the foods or liquids (NAME) ate yesterday? YES . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . 2 YES . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . 2 448 How many times did (NAME) eat solid, semi-solid or soft foods other than liquids yesterday during the day or at night? IF 7 OR MORE TIMES, RECORD ‘7'. +))), NUMBER OF TIMES . . . . . . . . . *!!!* .)))- DON’T KNOW . . . . . . . . . . . . . . . . . 8 +))), NUMBER OF TIMES . . . . . . . . . *!!!* .)))- DON’T KNOW . . . . . . . . . . . . . . . . . 8 450 GO BACK TO 405 IN NEXT COLUMN; OR, IF NO MORE BIRTHS, GO TO 451. GO BACK TO 405 IN LAST COLUMN OF NEW QUESTIONNAIRE; OR, IF NO MORE BIRTHS, GO TO 451. EW 21 SECTION 4B. IMMUNIZATION, HEALTH, AND NUTRITION 451 ENTER IN THE TABLE THE LINE NUMBER, NAME, AND SURVIVAL STATUS OF EACH BIRTH IN 1995 OR LATER. (IF THERE ARE MORE THAN 2 BIRTHS, USE LAST COLUMN OF ADDITIONAL QUESTIONNAIRES). 452 LINE NUMBER FROM 212 LAST BIRTH +)))0))), LINE NUMBER . . . . . . . . . . *!!!*!!!* .)))2)))- NEXT-TO-LAST BIRTH +)))0))), LINE NUMBER . . . . . . . . . . *!!!*!!!* .)))2)))- 453 FROM 212 AND 216 NAME NAME ALIVE +)), /))- * * * * * ? DEAD +)), /))- ? (GO TO 453 IN NEXT COLUMN; OR, IF NO MORE BIRTHS, GO TO 481) ALIVE +)), /))- * * * * * ? DEAD +)), /))- ? (GO TO 453 IN LAST COLUMN OF NEW QUESTION-NAIRE; OR, IF NO MORE BIRTHS, GO TO 481) 454 Did (NAME) receive a Vitamin A dose like this during the last 6 months? SHOW CAPSULE. YES . . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . . 2 DON’T KNOW . . . . . . . . . . . . . . . . . . 8 YES . . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . . 2 DON’T KNOW . . . . . . . . . . . . . . . . . . 8 455 Do you have a card where (NAME’S) vaccinations are written down? IF YES: May I see it please? YES, SEEN . . . . . . . . . . . . . . . . . . . . 1 (SKIP TO 457)=)))))))- YES, NOT SEEN . . . . . . . . . . . . . . . 2 (SKIP TO 459)=)))))))- NO CARD . . . . . . . . . . . . . . . . . . . . . 3 YES, SEEN . . . . . . . . . . . . . . . . . . . . 1 (SKIP TO 457)=)))))))- YES, NOT SEEN . . . . . . . . . . . . . . . 2 (SKIP TO 459)=)))))))- NO CARD . . . . . . . . . . . . . . . . . . . . . 3 456 Did you ever have a vaccination card for (NAME)? YES . . . . . . . . . . . . . . . . . . . . . . . . . 1 (SKIP TO 459)=)))))))1 NO . . . . . . . . . . . . . . . . . . . . . . . . . . 2 YES . . . . . . . . . . . . . . . . . . . . . . . . . 1 (SKIP TO 459)=)))))))1 NO . . . . . . . . . . . . . . . . . . . . . . . . . . 2 457 (1) COPY VACCINATION DATE FOR EACH VACCINE FROM THE CARD. (2) WRITE ‘44' IN ‘DAY’ COLUMN IF CARD SHOWS THAT A VACCINATION WAS GIVEN, BUT NO DATE IS RECORDED. DAY MONTH YEAR DAY MONTH YEAR BCG POLIO 0 (POLIO GIVEN AT BIRTH) POLIO 1 POLIO 2 POLIO 3 DPT 1 DPT 2 DPT 3 MEASLES VITAMIN A (MOST RECENT) +)))0)))H)))0)))H)))0)))0)))0))), BCG*!!!*!!!5!!!*!!!5!!!*!!!*!!!*!!!* /)))3)))O)))3)))O)))3)))3)))3)))1 P0 *!!!*!!!5!!!*!!!5!!!*!!!*!!!*!!!* /)))3)))O)))3)))O)))3)))3)))3)))1 P1 *!!!*!!!5!!!*!!!5!!!*!!!*!!!*!!!* /)))3)))O)))3)))O)))3)))3)))3)))1 P2 *!!!*!!!5!!!*!!!5!!!*!!!*!!!*!!!* /)))3)))O)))3)))O)))3)))3)))3)))1 P3 *!!!*!!!5!!!*!!!5!!!*!!!*!!!*!!!* /)))3)))O)))3)))O)))3)))3)))3)))1 D1 *!!!*!!!5!!!*!!!5!!!*!!!*!!!*!!!* /)))3)))O)))3)))O)))3)))3)))3)))1 D2 *!!!*!!!5!!!*!!!5!!!*!!!*!!!*!!!* /)))3)))O)))3)))O)))3)))3)))3)))1 D3 *!!!*!!!5!!!*!!!5!!!*!!!*!!!*!!!* /)))3)))O)))3)))O)))3)))3)))3)))1 MEA*!!!*!!!5!!!*!!!5!!!*!!!*!!!*!!!* /)))3)))O)))3)))O)))3)))3)))3)))1 VIT . A*!!!*!!!5!!!*!!!5!!!*!!!*!!!*!!!* .)))2)))J)))2)))J)))2)))2)))2)))- +)))0)))H)))0)))H)))0)))0)))0))), BCG*!!!*!!!5!!!*!!!5!!!*!!!*!!!*!!!* /)))3)))O)))3)))O)))3)))3)))3)))1 P0 *!!!*!!!5!!!*!!!5!!!*!!!*!!!*!!!* /)))3)))O)))3)))O)))3)))3)))3)))1 P1 *!!!*!!!5!!!*!!!5!!!*!!!*!!!*!!!* /)))3)))O)))3)))O)))3)))3)))3)))1 P2 *!!!*!!!5!!!*!!!5!!!*!!!*!!!*!!!* /)))3)))O)))3)))O)))3)))3)))3)))1 P3 *!!!*!!!5!!!*!!!5!!!*!!!*!!!*!!!* /)))3)))O)))3)))O)))3)))3)))3)))1 D1 *!!!*!!!5!!!*!!!5!!!*!!!*!!!*!!!* /)))3)))O)))3)))O)))3)))3)))3)))1 D2 *!!!*!!!5!!!*!!!5!!!*!!!*!!!*!!!* /)))3)))O)))3)))O)))3)))3)))3)))1 D3 *!!!*!!!5!!!*!!!5!!!*!!!*!!!*!!!* /)))3)))O)))3)))O)))3)))3)))3)))1 MEA*!!!*!!!5!!!*!!!5!!!*!!!*!!!*!!!* /)))3)))O)))3)))O)))3)))3)))3)))1 VIT . A*!!!*!!!5!!!*!!!5!!!*!!!*!!!*!!!* .)))2)))J)))2)))J)))2)))2)))2)))- EW 22 LAST BIRTH NAME NEXT-TO-LAST BIRTH NAME 458 Has (NAME) received any vaccinations that are not recorded on this card, including vaccinations received in a national immunization day campaign? RECORD ‘YES’ ONLY IF RESPONDENT MENTIONS BCG, POLIO 0-3, DPT 1-3, AND/OR MEASLES VACCINE(S). YES . . . . . . . . . . . . . . . . . . . . . . . . . 1 (PROBE FOR VACCINATIONS =)- AND WRITE ‘66' IN THE CORRESPONDING DAY COLUMN IN 457) ))))))))))))))))), (SKIP TO 461)=)))))))- NO . . . . . . . . . . . . . . . . . . . . . . . . . . 2 (SKIP TO 461)=)))))))1 DON’T KNOW . . . . . . . . . . . . . . . . . . 8 YES . . . . . . . . . . . . . . . . . . . . . . . . . 1 (PROBE FOR VACCINATIONS =)- AND WRITE ‘66' IN THE CORRESPONDING DAY COLUMN IN 457) ))))))))))))))))), (SKIP TO 461)=)))))))- NO . . . . . . . . . . . . . . . . . . . . . . . . . . 2 (SKIP TO 461)=)))))))1 DON’T KNOW . . . . . . . . . . . . . . . . . . 8 459 Did (NAME) ever receive any vaccinations to prevent him/her from getting diseases, including vaccinations received in a national immunization day campaign? YES . . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . . 2 (SKIP TO 463)=)))))))1 DON’T KNOW . . . . . . . . . . . . . . . . . . 8 YES . . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . . 2 (SKIP TO 463)=)))))))1 DON’T KNOW . . . . . . . . . . . . . . . . . . 8 460 Please tell me if (NAME) received any of the following vaccinations: 460A A BCG vaccination against tuberculosis, that is, an injection in the arm or shoulder that usually causes a scar? YES . . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . . 2 DON’T KNOW . . . . . . . . . . . . . . . . . . 8 YES . . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . . 2 DON’T KNOW . . . . . . . . . . . . . . . . . . 8 460B Polio vaccine, that is, drops in the mouth? YES . . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . . 2 (SKIP TO 460E)=)))))))1 DON’T KNOW . . . . . . . . . . . . . . . . . . 8 YES . . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . . 2 (SKIP TO 460E)=)))))))1 DON’T KNOW . . . . . . . . . . . . . . . . . . 8 460C When was the first polio vaccine received, just after birth or later? JUST AFTER BIRTH . . . . . . . . . . . . . 1 LATER . . . . . . . . . . . . . . . . . . . . . . . 2 JUST AFTER BIRTH . . . . . . . . . . . . . 1 LATER . . . . . . . . . . . . . . . . . . . . . . . 2 460D How many times was the polio vaccine received? +))), NUMBER OF TIMES . . . . . . . . . . *!!!* .)))- +))), NUMBER OF TIMES . . . . . . . . . . *!!!* .)))- 460E DPT vaccination, that is, an injection given in the thigh or buttocks, sometimes at the same time as polio drops? YES . . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . . 2 (SKIP TO 460G)=)))))))1 DON’T KNOW . . . . . . . . . . . . . . . . . . 8 YES . . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . . 2 (SKIP TO 460G)=)))))))1 DON’T KNOW . . . . . . . . . . . . . . . . . . 8 460F How many times? +))), NUMBER OF TIMES . . . . . . . . . . *!!!* .)))- +))), NUMBER OF TIMES . . . . . . . . . . *!!!* .)))- 460G An injection to prevent measles? YES . . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . . 2 DON’T KNOW . . . . . . . . . . . . . . . . . . 8 YES . . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . . 2 DON’T KNOW . . . . . . . . . . . . . . . . . . 8 461 Were any of the vaccinations (NAME) received during the last two years given as a part of a national immunization day campaign? YES . . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . . 2 (SKIP TO 463)=)))- NO VACCINATION IN THE LAST 2 YEARS . . . . . . . . . . 3 (SKIP TO 463)=)))- DON’T KNOW . . . . . . . . . . . . . . . . . . 8 (SKIP TO 463)=)))- YES . . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . . 2 (SKIP TO 463)=)))- NO VACCINATION IN THE LAST 2 YEARS . . . . . . . . . . 3 (SKIP TO 463)=)))- DON’T KNOW . . . . . . . . . . . . . . . . . . 8 (SKIP TO 463)=)))- 462 At which national immunization day campaigns did (NAME) receive vaccinations? RECORD ALL MENTIONED. MEASLES 1998 . . . . . . . . . . . . . . . . A MEASLES 1999 . . . . . . . . . . . . . . . . B MEASLES 2000 . . . . . . . . . . . . . . . . C POLIO 1999 . . . . . . . . . . . . . . . . . . . D POLIO 2000 . . . . . . . . . . . . . . . . . . . F MEASLES 1998 . . . . . . . . . . . . . . . . A MEASLES 1999 . . . . . . . . . . . . . . . . B MEASLES 2000 . . . . . . . . . . . . . . . . C POLIO 1999 . . . . . . . . . . . . . . . . . . . D POLIO 2000 . . . . . . . . . . . . . . . . . . . F 463 Has (NAME) been ill with a fever at any time in the last 2 weeks? YES . . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . . 2 (SKIP TO 464)=)))- DON’T KNOW . . . . . . . . . . . . . . . . . . 8 (SKIP TO 464)=)))- YES . . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . . 2 (SKIP TO 464)=)))- DON’T KNOW . . . . . . . . . . . . . . . . . . 8 (SKIP TO 464)=)))- EW 23 LAST BIRTH NAME NEXT-TO-LAST BIRTH NAME 463A Does (NAME) have a fever now? YES . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 DON’T KNOW . . . . . . . . . . . . . . . . . . . . . 8 YES . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 DON’T KNOW . . . . . . . . . . . . . . . . . . . . . 8 463B I would like to know what things were done in response to (NAME’S) fever. What was done first? What was done after that? NOTE: CIRCLE ONE CODE IN EACH COLUMN FOR FIRST FOUR ACTIONS. EACH COLUMN SHOULD HAVE ONLY ONE CODE CIRCLED. ALL COLUMNS SHOULD CONTAIN AN ACTION. 1st 2nd 3rd 4th 1st 2nd 3rd 4th GAVE MEDICINE FROM HOME 01 01 01 01 GAVE MEDICINE FROM HOME 01 01 01 01 GAVE MEDICINE FROM A PHARMACIST/ SHOPKEEPER (WITHOUT A PRESCRIP- TION) 02 02 02 02 GAVE MEDICINE FROM A PHARMACIST/ SHOPKEEPER (WITHOUT A PRESCRIP- TION) 02 02 02 02 TAKEN TO A GOVERNMENT- RUN HEALTH CENTER 03 03 03 03 TAKEN TO A GOVERNMENT- RUN HEALTH CENTER 03 03 03 03 TAKEN TO A MISSION HEALTH CENTER 04 04 04 04 TAKEN TO A MISSION HEALTH CENTER 04 04 04 04 TAKEN TO A PRIVATE HEALTH CENTER 05 05 05 05 TAKEN TO A PRIVATE HEALTH CENTER 05 05 05 05 CONSULTED TRADITIONAL HEALER 06 06 06 06 CONSULTED TRADITIONAL HEALER 06 06 06 06 CONSULTED A CHW 07 07 07 07 CONSULTED A CHW 07 07 07 07 GAVE TEPID SPONGING 08 08 08 08 GAVE TEPID SPONGING 08 08 08 08 GAVE HERBS AT HOME 09 09 09 09 GAVE HERBS AT HOME 09 09 09 09 OTHER 96 96 96 96 OTHER 96 96 96 96 DID NOTHING (ELSE) 10 10 10 10 DID NOTHING (ELSE) 10 10 10 10 DON’T KNOW 98 98 98 98 DON’T KNOW 98 98 98 98 463C CHECK 463B: CODE “01" CODE “01" OR “02" OR “02" NOT CIRCLED CIRCLED IN ANY COLUMN +)), +)), /))- /))- .<(SKIP TO 463E) ? CHECK 463B: CODE “01" CODE “01" OR “02" OR “02" NOT CIRCLED CIRCLED IN ANY COLUMN +)), +)), /))- /))- .<(SKIP TO 463E) ? EW 24 LAST BIRTH NAME NEXT-TO-LAST BIRTH NAME 463D Which medicines were given to (NAME)? ASK TO SEE MEDICINE(S). IF NOT SEEN, SHOW MEDICINE(S) TO RESPONDENT. FOR EACH ANTI- MALARIAL MEDICINE: How long after the fever started did (NAME) start taking the medicine? RECORD ALL MENTIONED. DAY CODES: SAME DAY = 0 NEXT DAY AFTER THE FEVER = 1 TWO DAYS AFTER THE FEVER = 2 THREE OR MORE DAYS AFTER THE FEVER = 3 ANTI-MALARIAL SP (FANSIDAR, NOVIDAR) . A 0 1 2 3 QUININE . . . . . . . . . . . . . . B 0 1 2 3 CHLOROQUINE . . . . . . . . C 0 1 2 3 AMODIAQUINE . . . . . . . . . D 0 1 2 3 HALAFAN . . . . . . . . . . . . . E 0 1 2 3 OTHER DRUGS ASPIRIN . . . . . . . . . . . . . . . . . . . . . . . F PANADOL . . . . . . . . . . . . . . . . . . . . . . G OTHER X (SPECIFY) UNKNOWN . . . . . . . . . . . . . . . . . . . . . . . Z ANTI-MALARIAL SP (FANSIDAR, NOVIDAR) . A 0 1 2 3 QUININE . . . . . . . . . . . . . . B 0 1 2 3 CHLOROQUINE . . . . . . . . C 0 1 2 3 AMODIAQUINE . . . . . . . . . D 0 1 2 3 HALAFAN . . . . . . . . . . . . . E 0 1 2 3 OTHER DRUGS ASPIRIN . . . . . . . . . . . . . . . . . . . . . . . F PANADOL . . . . . . . . . . . . . . . . . . . . . . G OTHER X (SPECIFY) UNKNOWN . . . . . . . . . . . . . . . . . . . . . . . Z 463E CHECK 463B: CODE “03" CODE “03" CIRCLED IN NOT CIRCLED ANY COLUMN +)), +)), /))- /))- .<(SKIP TO 463J) ? CHECK 463B: CODE “03" CODE “03" CIRCLED IN NOT CIRCLED ANY COLUMN +)), +)), /))- /))- .<(SKIP TO 463J) ? 463F How long after you noticed the fever was (NAME) taken to a government-run health center? SAME DAY . . . . . . . . . . . . . . . . . . . . . . . 0 NEXT DAY . . . . . . . . . . . . . . . . . . . . . . . 1 TWO DAYS AFTER THE FEVER . . . . . 2 THREE OR MORE DAYS AFTER THE FEVER . . . . . . . . . . . . . . 3 SAME DAY . . . . . . . . . . . . . . . . . . . . . . . 0 NEXT DAY . . . . . . . . . . . . . . . . . . . . . . . 1 TWO DAYS AFTER THE FEVER . . . . . 2 THREE OR MORE DAYS AFTER THE FEVER . . . . . . . . . . . . . . 3 463G Were any drugs or prescriptions for drugs given at the government-run health center for (NAME)? YES . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 (SKIP TO 463I)=))1 DON’T KNOW . . . . . . . . . . . . . . . . . . . . . 8 YES . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 (SKIP TO 463I)=))1 DON’T KNOW . . . . . . . . . . . . . . . . . . . . . 8 463H Which medicines were given to (NAME)? ASK TO SEE MEDICINE(S). IF NOT SEEN, SHOW MEDICINE(S) TO RESPONDENT. FOR EACH ANTI- MALARIAL MEDICINE: How long after the fever started did (NAME) start taking the medicine? RECORD ALL MENTIONED. DAY CODES: SAME DAY = 0 NEXT DAY AFTER THE FEVER = 1 TWO DAYS AFTER THE FEVER = 2 THREE OR MORE DAYS AFTER THE FEVER = 3 ANTI-MALARIAL SP (FANSIDAR, NOVIDAR) . A 0 1 2 3 QUININE . . . . . . . . . . . . . . B 0 1 2 3 CHLOROQUINE . . . . . . . . C 0 1 2 3 AMODIAQUINE . . . . . . . . . D 0 1 2 3 HALAFAN . . . . . . . . . . . . . E 0 1 2 3 OTHER DRUGS ASPIRIN . . . . . . . . . . . . . . . . . . . . . . . F PANADOL . . . . . . . . . . . . . . . . . . . . . . G OTHER X (SPECIFY) UNKNOWN . . . . . . . . . . . . . . . . . . . . . . . Z ANTI-MALARIAL SP (FANSIDAR, NOVIDAR) . A 0 1 2 3 QUININE . . . . . . . . . . . . . . B 0 1 2 3 CHLOROQUINE . . . . . . . . C 0 1 2 3 AMODIAQUINE . . . . . . . . . D 0 1 2 3 HALAFAN . . . . . . . . . . . . . E 0 1 2 3 OTHER DRUGS ASPIRIN . . . . . . . . . . . . . . . . . . . . . . . F PANADOL . . . . . . . . . . . . . . . . . . . . . . G OTHER X (SPECIFY) UNKNOWN . . . . . . . . . . . . . . . . . . . . . . . Z LAST BIRTH NAME NEXT-TO-LAST BIRTH NAME EW 25 463I Did (NAME) receive any injection at the government- run health center? YES . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 DON’T KNOW . . . . . . . . . . . . . . . . . . . . . 8 YES . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 DON’T KNOW . . . . . . . . . . . . . . . . . . . . . 8 463J CHECK 463B: CODE “04" CODE “04" CIRCLED IN NOT CIRCLED ANY COLUMN +)), +)), /))- /))- .<(SKIP TO 463O) ? CHECK 463B: CODE “04" CODE “04" CIRCLED IN NOT CIRCLED ANY COLUMN +)), +)), /))- /))- .<(SKIP TO 463O) ? 463K How long after you noticed the fever was (NAME) taken to a mission health center? SAME DAY . . . . . . . . . . . . . . . . . . . . . . . 0 NEXT DAY . . . . . . . . . . . . . . . . . . . . . . . 1 TWO DAYS AFTER THE FEVER . . . . . 2 THREE OR MORE DAYS AFTER THE FEVER . . . . . . . . . . . . . . 3 SAME DAY . . . . . . . . . . . . . . . . . . . . . . . 0 NEXT DAY . . . . . . . . . . . . . . . . . . . . . . . 1 TWO DAYS AFTER THE FEVER . . . . . 2 THREE OR MORE DAYS AFTER THE FEVER . . . . . . . . . . . . . . 3 463L Were any drugs or prescriptions for drugs given at the mission health center for (NAME)? YES . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 (SKIP TO 463N)=))1 DON’T KNOW . . . . . . . . . . . . . . . . . . . . . 8 YES . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 (SKIP TO 463N)=))1 DON’T KNOW . . . . . . . . . . . . . . . . . . . . . 8 463M Which medicines were given to (NAME)? ASK TO SEE MEDICINE(S). IF NOT SEEN, SHOW MEDICINE(S) TO RESPONDENT. FOR EACH ANTI- MALARIAL MEDICINE: How long after the fever started did (NAME) start taking the medicine? RECORD ALL MENTIONED. DAY CODES: SAME DAY = 0 NEXT DAY AFTER THE FEVER = 1 TWO DAYS AFTER THE FEVER = 2 THREE OR MORE DAYS AFTER THE FEVER = 3 ANTI-MALARIAL SP (FANSIDAR, NOVIDAR) . A 0 1 2 3 QUININE . . . . . . . . . . . . . . B 0 1 2 3 CHLOROQUINE . . . . . . . . C 0 1 2 3 AMODIAQUINE . . . . . . . . . D 0 1 2 3 HALAFAN . . . . . . . . . . . . . E 0 1 2 3 OTHER DRUGS ASPIRIN . . . . . . . . . . . . . . . . . . . . . . . F PANADOL . . . . . . . . . . . . . . . . . . . . . . G OTHER X (SPECIFY) UNKNOWN . . . . . . . . . . . . . . . . . . . . . . . Z ANTI-MALARIAL SP (FANSIDAR, NOVIDAR) . A 0 1 2 3 QUININE . . . . . . . . . . . . . . B 0 1 2 3 CHLOROQUINE . . . . . . . . C 0 1 2 3 AMODIAQUINE . . . . . . . . . D 0 1 2 3 HALAFAN . . . . . . . . . . . . . E 0 1 2 3 OTHER DRUGS ASPIRIN . . . . . . . . . . . . . . . . . . . . . . . F PANADOL . . . . . . . . . . . . . . . . . . . . . . G OTHER X (SPECIFY) UNKNOWN . . . . . . . . . . . . . . . . . . . . . . . Z 463N Did (NAME) receive any injection at the mission health center? YES . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 DON’T KNOW . . . . . . . . . . . . . . . . . . . . . 8 YES . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 DON’T KNOW . . . . . . . . . . . . . . . . . . . . . 8 463O CHECK 463B: CODE “05" CODE “05" CIRCLED IN NOT CIRCLED ANY COLUMN +)), +)), /))- /))- .<(SKIP TO 463T) ? CHECK 463B: CODE “05" CODE “05" CIRCLED IN NOT CIRCLED ANY COLUMN +)), +)), /))- /))- .<(SKIP TO 463T) ? 463P How long after you noticed the fever was (NAME) taken to a private health center? SAME DAY . . . . . . . . . . . . . . . . . . . . . . . 0 NEXT DAY . . . . . . . . . . . . . . . . . . . . . . . 1 TWO DAYS AFTER THE FEVER . . . . . 2 THREE OR MORE DAYS AFTER THE FEVER . . . . . . . . . . . . . . 3 SAME DAY . . . . . . . . . . . . . . . . . . . . . . . 0 NEXT DAY . . . . . . . . . . . . . . . . . . . . . . . 1 TWO DAYS AFTER THE FEVER . . . . . 2 THREE OR MORE DAYS AFTER THE FEVER . . . . . . . . . . . . . 3 463Q Were any medicines or prescriptions for medicines given at the private health center for (NAME)? YES . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 (SKIP TO 463S)=))1 DON’T KNOW . . . . . . . . . . . . . . . . . . . . . 8 YES . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 (SKIP TO 463S)=))1 DON’T KNOW . . . . . . . . . . . . . . . . . . . . . 8 LAST BIRTH NAME NEXT-TO-LAST BIRTH NAME EW 26 463R Which medicines were given to (NAME)? ASK TO SEE MEDICINE(S). IF NOT SEEN, SHOW MEDICINE(S) TO RESPONDENT. FOR EACH ANTI- MALARIAL MEDICINE: How long after the fever started did (NAME) start taking the medicine? RECORD ALL MENTIONED. DAY CODES: SAME DAY = 0 NEXT DAY AFTER THE FEVER = 1 TWO DAYS AFTER THE FEVER = 2 THREE DAYS OR MORE AFTER THE FEVER = 3 ANTI-MALARIAL SP (FANSIDAR, NOVIDAR) . A 0 1 2 3 QUININE . . . . . . . . . . . . . . B 0 1 2 3 CHLOROQUINE . . . . . . . . C 0 1 2 3 AMODIAQUINE . . . . . . . . . D 0 1 2 3 HALAFAN . . . . . . . . . . . . . E 0 1 2 3 OTHER DRUGS ASPIRIN . . . . . . . . . . . . . . . . . . . . . . . F PANADOL . . . . . . . . . . . . . . . . . . . . . . G OTHER X (SPECIFY) UNKNOWN . . . . . . . . . . . . . . . . . . . . . . . Z ANTI-MALARIAL SP (FANSIDAR, NOVIDAR) . A 0 1 2 3 QUININE . . . . . . . . . . . . . . B 0 1 2 3 CHLOROQUINE . . . . . . . . C 0 1 2 3 AMODIAQUINE . . . . . . . . . D 0 1 2 3 HALAFAN . . . . . . . . . . . . . E 0 1 2 3 OTHER DRUGS ASPIRIN . . . . . . . . . . . . . . . . . . . . . . . F PANADOL . . . . . . . . . . . . . . . . . . . . . . G OTHER X (SPECIFY) UNKNOWN . . . . . . . . . . . . . . . . . . . . . . . Z 463S Did (NAME) receive any injection during the visit to the private health center? YES . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 DON’T KNOW . . . . . . . . . . . . . . . . . . . . . 8 YES . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 DON’T KNOW . . . . . . . . . . . . . . . . . . . . . 8 463T CHECK 463B: CODE “07" CODE “07" CIRCLED IN NOT CIRCLED ANY COLUMN +)), +)), /))- /))- .<(SKIP TO 464) ? CHECK 463B: CODE “07" CODE “07" CIRCLED IN NOT CIRCLED ANY COLUMN +)), +)), /))- /))- .<(SKIP TO 464) ? 463U How long after you noticed the fever did (NAME) see the community health worker? SAME DAY . . . . . . . . . . . . . . . . . . . . . . . 0 NEXT DAY . . . . . . . . . . . . . . . . . . . . . . . 1 TWO DAYS AFTER THE FEVER . . . . . 2 THREE OR MORE DAYS AFTER THE FEVER . . . . . . . . . . . . . 3 SAME DAY . . . . . . . . . . . . . . . . . . . . . . . 0 NEXT DAY . . . . . . . . . . . . . . . . . . . . . . . 1 TWO DAYS AFTER THE FEVER . . . . . 2 THREE OR MORE DAYS AFTER THE FEVER . . . . . . . . . . . . . 3 463V What did the community health worker do? RECORD ALL MENTIONED. GAVE MEDICINE . . . . . . . . . . . . . . . . . . A RECOMMENDED PURCHASE OF MEDICINE . . . . . . . . . . B REFERRED TO HEALTH CENTER/DOCTOR . . . . . . . . . C OTHER X (SPECIFY) GAVE MEDICINE . . . . . . . . . . . . . . . . . . A RECOMMENDED PURCHASE OF MEDICINE . . . . . . . . . . B REFERRED TO HEALTH CENTER/DOCTOR . . . . . . . . . C OTHER X (SPECIFY) 463W CHECK 463V: CODE “A" NEITHER CODE “A" AND/OR CODE NOR CODE “B” “B” CIRCLED CIRCLED +)), +)), /))- /))- .<(SKIP TO 464) ? CHECK 463V: CODE “A" NEITHER CODE “A" AND/OR CODE NOR CODE “B” “B” CIRCLED CIRCLED +)), +)), /))- /))- .<(SKIP TO 464) ? LAST BIRTH NAME NEXT-TO-LAST BIRTH NAME EW 27 463X Which medicines were given to (NAME) by the community health worker? ASK TO SEE MEDICINE(S). IF NOT SEEN, SHOW MEDICINE(S) TO RESPONDENT. FOR EACH ANTI- MALARIAL MEDICINE: How long after the fever started did (NAME) start taking the medicine? RECORD ALL MENTIONED. DAY CODES: SAME DAY = 0 NEXT DAY AFTER THE FEVER = 1 TWO DAYS AFTER THE FEVER = 2 THREE DAYS OR MORE AFTER THE FEVER = 3 ANTI-MALARIAL SP (FANSIDAR, NOVIDAR) . A 0 1 2 3 QUININE . . . . . . . . . . . . . . B 0 1 2 3 CHLOROQUINE . . . . . . . . C 0 1 2 3 AMODIAQUINE . . . . . . . . . D 0 1 2 3 HALAFAN . . . . . . . . . . . . . E 0 1 2 3 OTHER DRUGS ASPIRIN . . . . . . . . . . . . . . . . . . . . . . . F PANADOL . . . . . . . . . . . . . . . . . . . . . . G OTHER X (SPECIFY) UNKNOWN . . . . . . . . . . . . . . . . . . . . . . . Z ANTI-MALARIAL SP (FANSIDAR, NOVIDAR) . A 0 1 2 3 QUININE . . . . . . . . . . . . . . B 0 1 2 3 CHLOROQUINE . . . . . . . . C 0 1 2 3 AMODIAQUINE . . . . . . . . . D 0 1 2 3 HALAFAN . . . . . . . . . . . . . E 0 1 2 3 OTHER DRUGS ASPIRIN . . . . . . . . . . . . . . . . . . . . . . . F PANADOL . . . . . . . . . . . . . . . . . . . . . . G OTHER X (SPECIFY) UNKNOWN . . . . . . . . . . . . . . . . . . . . . . . Z EW 28 LAST BIRTH NAME NEXT-TO-LAST BIRTH NAME 464 Has (NAME) had an illness with a cough at any time in the last 2 weeks? YES . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . 2 (SKIP TO 472)=)))))))1 DON’T KNOW . . . . . . . . . . . . . . . 8 YES . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . 2 (SKIP TO 472)=)))))))1 DON’T KNOW . . . . . . . . . . . . . . . 8 465 When (NAME) had an illness with a cough, did he/she breathe faster than usual with short, fast breaths? YES . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . 2 DON’T KNOW . . . . . . . . . . . . . . . 8 YES . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . 2 DON’T KNOW . . . . . . . . . . . . . . . 8 467 Did you seek advice or treatment for the cough? YES . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . 2 (SKIP TO 472)=)))))))- YES . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . 2 (SKIP TO 472)=)))))))- 468 Where did you seek advice or treatment? Anywhere else? RECORD ALL MENTIONED. PUBLIC SECTOR GOVT. HOSPITAL . . . . . . . . . A GOVT. HEALTH CENTER . . . B GOVT. HEALTH POST . . . . . . C MOBILE CLINIC . . . . . . . . . . . D FIELD WORKER . . . . . . . . . . . E OTHER PUBLIC F (SPECIFY) MISSION HOSPITAL . . . . . . . . . . . . . . . . G HEALTH CENTER . . . . . . . . . . H MOBILE CLINIC . . . . . . . . . . . . . I PRIVATE MEDICAL SECTOR PVT. HOSPITAL/CLINIC . . . . . . J PHARMACY . . . . . . . . . . . . . . K PRIVATE DOCTOR . . . . . . . . L MOBILE CLINIC . . . . . . . . . . . M FIELD WORKER . . . . . . . . . . . N OTHER PVT. MEDICAL O (SPECIFY) OTHER SOURCE SHOP . . . . . . . . . . . . . . . . . . . P TRAD. PRACTITIONER . . . . . Q OTHER X (SPECIFY) PUBLIC SECTOR GOVT. HOSPITAL . . . . . . . . . A GOVT. HEALTH CENTER . . . B GOVT. HEALTH POST . . . . . . C MOBILE CLINIC . . . . . . . . . . . D FIELD WORKER . . . . . . . . . . . E OTHER PUBLIC F (SPECIFY) MISSION HOSPITAL . . . . . . . . . . . . . . . . G HEALTH CENTER . . . . . . . . . . H MOBILE CLINIC . . . . . . . . . . . . . I PRIVATE MEDICAL SECTOR PVT. HOSPITAL/CLINIC . . . . . . J PHARMACY . . . . . . . . . . . . . . K PRIVATE DOCTOR . . . . . . . . L MOBILE CLINIC . . . . . . . . . . . M FIELD WORKER . . . . . . . . . . . N OTHER PVT. MEDICAL O (SPECIFY) OTHER SOURCE SHOP . . . . . . . . . . . . . . . . . . . P TRAD. PRACTITIONER . . . . . Q OTHER X (SPECIFY) 472 Has (NAME) had diarrhea in the last 2 weeks? YES . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . 2 (SKIP TO 480)=)))))))1 DON’T KNOW . . . . . . . . . . . . . . . 8 YES . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . 2 (SKIP TO 480)=)))))))1 DON’T KNOW . . . . . . . . . . . . . . . 8 472A Did [NAME]’s stool contain blood? YES . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . 2 YES . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . 2 473 Now I would like to know how much (NAME) was offered to drink during the diarrhea. Was he/she offered less than usual to drink, about the same amount, or more than usual to drink? IF LESS, PROBE: Was he/she offered much less than usual to drink or somewhat less? MUCH LESS . . . . . . . . . . . . . . . . 1 SOMEWHAT LESS . . . . . . . . . . . 2 ABOUT THE SAME . . . . . . . . . . 3 MORE . . . . . . . . . . . . . . . . . . . . . 4 NOTHING TO DRINK . . . . . . . . . 5 DON’T KNOW . . . . . . . . . . . . . . . 8 MUCH LESS . . . . . . . . . . . . . . . . 1 SOMEWHAT LESS . . . . . . . . . . . 2 ABOUT THE SAME . . . . . . . . . . 3 MORE . . . . . . . . . . . . . . . . . . . . . 4 NOTHING TO DRINK . . . . . . . . . 5 DON’T KNOW . . . . . . . . . . . . . . . 8 LAST BIRTH NAME NEXT-TO-LAST BIRTH NAME EW 29 474 When (NAME) had diarrhea, was he/she offered less than usual to eat, about the same amount, more than usual, or nothing to eat? IF LESS, PROBE: Was he/she offered much less than usual to eat or somewhat less? MUCH LESS . . . . . . . . . . . . . . . . 1 SOMEWHAT LESS . . . . . . . . . . . 2 ABOUT THE SAME . . . . . . . . . . 3 MORE . . . . . . . . . . . . . . . . . . . . . 4 STOPPED FOOD . . . . . . . . . . . . 5 NEVER GAVE FOOD . . . . . . . . . 6 DON’T KNOW . . . . . . . . . . . . . . . 8 MUCH LESS . . . . . . . . . . . . . . . . 1 SOMEWHAT LESS . . . . . . . . . . . 2 ABOUT THE SAME . . . . . . . . . . 3 MORE . . . . . . . . . . . . . . . . . . . . . 4 STOPPED FOOD . . . . . . . . . . . . 5 NEVER GAVE FOOD . . . . . . . . . 6 DON’T KNOW . . . . . . . . . . . . . . . 8 475 Was he/she given a drink made from a special packet called ORS? YES . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . 2 DON’T KNOW . . . . . . . . . . . . . . . 8 YES . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . 2 DON’T KNOW . . . . . . . . . . . . . . . 8 476 Was anything (else) given to treat the diarrhea? YES . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . 2 (SKIP TO 478)=)))))))1 DON’T KNOW . . . . . . . . . . . . . . . 8 YES . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . 2 (SKIP TO 478)=)))))))1 DON’T KNOW . . . . . . . . . . . . . . . 8 477 What was given to treat the diarrhea? Anything else? RECORD ALL MENTIONED. PILL OR SYRUP . . . . . . . . . . . . . A INJECTION . . . . . . . . . . . . . . . . . B (I.V.) INTRAVENOUS . . . . . . . . . C HOME REMEDIES/ HERBAL MEDICINES . . . . . . . D OTHER X (SPECIFY) PILL OR SYRUP . . . . . . . . . . . . . A INJECTION . . . . . . . . . . . . . . . . . B (I.V.) INTRAVENOUS . . . . . . . . . C HOME REMEDIES/ HERBAL MEDICINES . . . . . . . D OTHER X (SPECIFY) 478 Did you seek advice or treatment for the diarrhea? YES . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . 2 (SKIP TO 480)=)))))))- YES . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . 2 (SKIP TO 480)=)))))))- 479 Where did you seek advice or treatment? Anywhere else? RECORD ALL MENTIONED. PUBLIC SECTOR GOVT. HOSPITAL . . . . . . . . . A GOVT. HEALTH CENTER . . . B GOVT. HEALTH POST . . . . . . C MOBILE CLINIC . . . . . . . . . . . D FIELD WORKER . . . . . . . . . . . E OTHER PUBLIC F (SPECIFY) MISSION HOSPITAL . . . . . . . . . . . . . . . . G HEALTH CENTER . . . . . . . . . . H MOBILE CLINIC . . . . . . . . . . . . . I PRIVATE MEDICAL SECTOR PVT. HOSPITAL/CLINIC . . . . . . J PHARMACY . . . . . . . . . . . . . . K PRIVATE DOCTOR . . . . . . . . L MOBILE CLINIC . . . . . . . . . . . M FIELD WORKER . . . . . . . . . . . N OTHER PRIVATE MEDICAL O (SPECIFY) OTHER SOURCE SHOP . . . . . . . . . . . . . . . . . . . P TRAD. PRACTITIONER . . . . . Q OTHER X (SPECIFY) PUBLIC SECTOR GOVT. HOSPITAL . . . . . . . . . A GOVT. HEALTH CENTER . . . B GOVT. HEALTH POST . . . . . . C MOBILE CLINIC . . . . . . . . . . . D FIELD WORKER . . . . . . . . . . . E OTHER PUBLIC F (SPECIFY) MISSION HOSPITAL . . . . . . . . . . . . . . . . G HEALTH CENTER . . . . . . . . . . H MOBILE CLINIC . . . . . . . . . . . . . I PRIVATE MEDICAL SECTOR PVT. HOSPITAL/CLINIC . . . . . . J PHARMACY . . . . . . . . . . . . . . K PRIVATE DOCTOR . . . . . . . . L MOBILE CLINIC . . . . . . . . . . . M FIELD WORKER . . . . . . . . . . . N OTHER PRIVATE MEDICAL O (SPECIFY) OTHER SOURCE SHOP . . . . . . . . . . . . . . . . . . . P TRAD. PRACTITIONER . . . . . Q OTHER X (SPECIFY) EW 30 LAST BIRTH NAME____________________________ NEXT-TO-LAST BIRTH NAME_____________________________ 480 Do you have any mosquito nets in your house? YES . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 480G =))- CHECK FIRST COLUMN: HAS MOSQUITO NETS +), /)- * ? DOES NOT HAVE MOSQUITO NETS +), .)2))<480G 480A Does (NAME) usually sleep under a mosquito net? YES . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 YES . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 480B Did (NAME) sleep under a mosquito net last night? YES . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 (SKIP TO 480G)=)))1 DON’T KNOW . . . . . . . . . . . . . . . . . . . . . 8 YES . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 (SKIP TO 480G)=)))1 DON’T KNOW . . . . . . . . . . . . . . . . . . . . . 8 480C Where was the mosquito net (NAME) slept under bought or obtained? SHOP . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 VENDOR . . . . . . . . . . . . . . . . . . . . . . . . 2 NGO OR OTHER ORGANIZATION . . . . . . . . . . . . . . . . 3 OTHER 6 (SPECIFY) DON’T KNOW . . . . . . . . . . . . . . . . . . . . . 8 SHOP . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 VENDOR . . . . . . . . . . . . . . . . . . . . . . . . 2 NGO OR OTHER ORGANIZATION . . . . . . . . . . . . . . . . 3 OTHER 6 (SPECIFY) DON’T KNOW . . . . . . . . . . . . . . . . . . . . . 8 480D How long ago was the mosquito net bought or obtained? WRITE THE ANSWER IN MONTHS (LESS THAN 1 MONTH = 00) IF MORE THAN 7 YEARS, RECORD ‘95'. +)))0))), MONTHS . . . . . . . . . . . . . . . . . *!!!*!!!* .)))2)))- DON’T KNOW . . . . . . . . . . . . . . . . . . . . 98 +)))0))), MONTHS . . . . . . . . . . . . . . . . . *!!!*!!!* .)))2)))- DON’T KNOW . . . . . . . . . . . . . . . . . . . . 98 480E Since you got the mosquito net was it ever soaked or dipped in an insecticide to repel mosquitoes or bugs? YES . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 (SKIP TO 480G)=)))1 DON’T KNOW . . . . . . . . . . . . . . . . . . . . . 8 YES . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 (SKIP TO 480G)=)))1 DON’T KNOW . . . . . . . . . . . . . . . . . . . . . 8 480F How long ago was the mosquito net last soaked or dipped? WRITE THE ANSWER IN MONTHS (LESS THAN 1 MONTH = 00) +)))0))), MONTHS . . . . . . . . . . . . . . . . . *!!!*!!!* .)))2)))- DON’T KNOW . . . . . . . . . . . . . . . . . . . . 98 +)))0))), MONTHS . . . . . . . . . . . . . . . . . *!!!*!!!* .)))2)))- DON’T KNOW . . . . . . . . . . . . . . . . . . . . 98 480G GO BACK TO 451 IN NEXT COLUMN, OR, IF NO MORE CHILDREN, GO TO 481. GO BACK TO 451 IN NEXT COLUMN, OR, IF NO MORE CHILDREN, GO TO 481. EW 31 NO. QUESTIONS AND FILTERS CODING CATEGORIES SKIP 481 CHECK 453, ALL COLUMNS: NUMBER OF LIVING CHILDREN BORN IN 1995 OR LATER ONE OR +))), NONE +))), MORE /)))- .)))2)))))))))))))))))))))))))))))))))))))))))))) ? ))<486 482 The last time you fed your child(ren), did you wash your hands immediately before feeding (him/her/them)? YES . . . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 NEVER FED CHILD(REN) . . . . . . . . . 3 483 The last time you had to clean (your child/one of your children) after he/she defecated, did you wash your hands immediately afterwards? YES . . . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 NEVER CLEANED CHILD(REN) . . . . 3 484 What is usually done to dispose of your (youngest) child’s stools when he/she does not use any toilet facility? ALWAYS USE TOILET/LATRINE . . . 01 THROW IN THE TOILET/LATRINE . 02 THROW OUTSIDE THE DWELLING 03 THROW OUTSIDE THE YARD . . . . . 04 BURY IN THE YARD . . . . . . . . . . . . 05 RINSE AWAY . . . . . . . . . . . . . . . . . . 06 NOT DISPOSED OF . . . . . . . . . . . . . 07 OTHER 96 (SPECIFY) 485 CHECK 475, ALL COLUMNS: NO CHILD +))), ANY CHILD +))), RECEIVED FLUID /)))- RECEIVED FLUID .)))2)))))))))))))))))))))))))))))))))))))))))))) FROM ORS PACKET ? FROM ORS PACKET ))<487 486 Have you ever heard of a special product called ORS you can get for the treatment of diarrhea? YES . . . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 487 CHECK 218: HAS ONE OR MORE +))), HAS NO CHILDREN +))), CHILDREN LIVING /)))- LIVING WITH HER .)))2))))))))))))))))))))))))))))))))))))))))))) WITH HER ? ))<489 488 When (your child/one of your children) is seriously ill, can you decide by yourself whether or not the child should be taken for medical treatment? IF SAYS NO CHILD EVER SERIOUSLY ILL, ASK: If (your child/one of your children) became seriously ill, could you decide by yourself whether the child should be taken for medical treatment? YES . . . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 DEPENDS . . . . . . . . . . . . . . . . . . . . . 3 489 Now I would like to ask you some questions about medical care for you yourself. Many different factors can prevent women from getting medical advice or treatment for themselves. When you are sick and want to get medical advice or treatment, is each of the following a big problem or not? BIG PROBLEM NOT A BIG PROBLEM Knowing where to go. 1 2 Getting permission to go. 1 2 Getting money needed for treatment. 1 2 The time required to cover distance to facility. 1 2 The availability of means of transport. 1 2 The cost of transport. 1 2 Not wanting to go alone. 1 2 Concern that there may not be a female health provider. 1 2 EW 32 489A CHECK 215 AND 218: DOES NOT HAVE ANY HAS AT LEAST ONE CHILD +))), CHILDREN BORN IN +))), BORN IN 1997 OR LATER /)))- 1997 OR LATER AND .)))2))))))))))))))))))))))))))))) AND LIVING WITH HER ? LIVING WITH HER RECORD NAME OF YOUNGEST CHILD LIVING WITH HER (AND CONTINUE TO 489B) ____________________________ (NAME) ))<491 489B Now I would like to ask you about liquids (NAME FROM Q. 489A) drank over the last seven days, including yesterday. How many days during the last seven days did (NAME FROM Q. 489A) drink each of the following? FOR EACH ITEM GIVEN AT LEAST ONCE IN LAST SEVEN DAYS, BEFORE PROCEEDING TO THE NEXT ITEM, ASK: In total, how many times yesterday during the day or at night did (NAME FROM Q. 489A) drink (ITEM)? LAST 7 DAYS NUMBER OF DAYS YESTERDAY/ LAST NIGHT NUMBER OF TIMES a Plain water? a a b Commercially produced infant formula? (e.g. Lactogen) b b c Any other milk such as tinned, powdered, or fresh animal milk? c c d Fruit juice? d d e Thobwa? e e f Any other liquids such as tea, coffee, carbonated drinks, “freezes,” or soup broth? f f Now I would like to ask you about the types of foods (NAME FROM Q. 489A) ate over the last seven days, including yesterday. How many days during the last seven days did (NAME FROM Q. 489A) eat each of the following foods either separately or combined with other food? FOR EACH ITEM GIVEN AT LEAST ONCE IN LAST SEVEN DAYS, BEFORE PROCEEDING TO THE NEXT ITEM, ASK: In total, how many times yesterday during the day or at night did (NAME FROM Q. 489A) eat (ITEM)? g Any food, such as bread or nsima, made from grains [e.g., millet, sorghum, maize, rice, wheat, or other local grains]? g g h Plain porridge? h h i Porridge enriched with foods such as legumes, vegetables, fruits, ground nut flour, fish, or meat? i i j Pumpkin, yellow squash, carrots, or yellow sweet potatoes? j j k Any other food made from roots or tubers [e.g., white potatoes, cassava, or other local roots/tubers]? k k l Any green leafy vegetables? l l m Mango or papaya? m m n Any other fruits and vegetables [e.g., oranges, bananas, guava, green beans, avocados, tomatoes]? n n o Meat, poultry, fish, termites, or eggs? o o p Any food made from legumes [e.g., peas, beans, cowpeas, pulses, or groundnuts]? p p q Cheese or yoghurt? q q r Any food made with oil, fat, margarine, or butter? r r IF 7 OR MORE TIMES, RECORD ‘7'. IF DON’T KNOW, RECORD ‘8'. 491 The last time you prepared a meal for your family, before starting did you wash your hands? YES . . . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 NEVER PREPARED MEAL . . . . . . . . 3 EW 33 NO. QUESTIONS AND FILTERS CODING CATEGORIES SKIP 492 Do you currently smoke cigarettes or tobacco? IF YES: What type of tobacco do you smoke? RECORD ALL MENTIONED. YES, CIGARETTES . . . . . . . . . . . . . . A YES, PIPE . . . . . . . . . . . . . . . . . . . . . B YES, OTHER TOBACCO . . . . . . . . . . C NO . . . . . . . . . . . . . . . . . . . . . . . . . . . Y 492A CHECK 492: CODE ‘A’ CIRCLED +), CODE ‘A’ NOT CIRCLED +), /)- .)2)))))))))))))))))))))))))))))))))))))))))) ? ))<493A 493 In the last 24 hours, how many cigarettes did you smoke? +)))0))), CIGARETTES . . . . . . . . . . . *!!!*!!!* .)))2)))- 493A Have you ever drunk an alcohol-containing beverage? YES . . . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 ))<493F 493B Have you ever gotten “drunk” from drinking an alcohol-containing beverage? YES . . . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 493C In the last 3 months, on how many days did you drink an alcohol- containing beverage? +)))0))), NUMBER OF DAYS . . . . . . . *!!!*!!!* .)))2)))- NONE/NEVER . . . . . . . . . . . . . . . . . 97 ))<493F 493D CHECK 493B: YES +), NO +), /)- .)2))))))))))))))))))))))))))))))))))))))))) ? ))<493F 493E In the last 3 months, on how many occasions did you get “drunk”? +)))0))), NUMBER OF TIMES . . . . . . . *!!!*!!!* .)))2)))- NONE/NEVER . . . . . . . . . . . . . . . . . 97 493F Have you had any kind of injection In the last 3 months? YES . . . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 )<494F 493G How many times did you have an injection in the last 3 months? +)))0))), NUMBER OF INJECTIONS . *!!!*!!!* .)))2)))- EVERY DAY . . . . . . . . . . . . . . . . . . . 96 493H The last time you had an injection, who was the person who gave you the injection? HEALTH PROFESSIONAL . . . . . . . . . 1 PHARMACIST . . . . . . . . . . . . . . . . . . 2 TRADITIONAL HEALER . . . . . . . . . . . 3 FRIEND/RELATIVE . . . . . . . . . . . . . . 4 SELF . . . . . . . . . . . . . . . . . . . . . . . . . . 5 OTHER 6 (SPECIFY) EW 34 NO. QUESTIONS AND FILTERS CODING CATEGORIES SKIP 494F CHECK 226: CURRENTLY +)), NOT PREGNANT +)), PREGNANT /))- OR UNSURE .))2)))))))))))))))))))))))))))))))))))))))))))))))))) ? )<494K 494G Did you have a fever at any time in the last two weeks? YES . . . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 )<494K 494H Did you take any medicine for the fever? YES . . . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 )<494K 494I Which medicines did you take? ASK TO SEE MEDICINE(S). IF NOT SEEN, SHOW MEDICINE(S) TO RESPONDENT. FOR EACH ANTI-MALARIAL MEDICINE: How long after the fever started did you start taking the medicine? RECORD ALL MENTIONED. DAY CODES: SAME DAY = 0 NEXT DAY AFTER THE FEVER = 1 TWO DAYS AFTER THE FEVER = 2 THREE DAYS OR MORE AFTER THE FEVER = 3 ANTI-MALARIAL SP (FANSIDAR, NOVIDAR) . . . . . . . . . A 0 1 2 3 QUININE . . . . . . . . . . . . B 0 1 2 3 CHLOROQUINE . . . . . . C 0 1 2 3 AMODIAQUINE . . . . . . . D 0 1 2 3 HALAFAN . . . . . . . . . . . E 0 1 2 3 OTHER DRUGS ASPIRIN . . . . . . . . . . . . . . . . . . . . . F PANADOL . . . . . . . . . . . . . . . . . . . . G OTHER X (SPECIFY) UNKNOWN . . . . . . . . . . . . . . . . . . . . . Z 494J How many times did you take this medicine(s)? +)))0))), NO OF TIMES . . . . . . . . . . . . *!!!*!!!* .)))2)))- 494K Did you sleep under a mosquito net last night? YES . . . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 ))<501 494L Where was the mosquito net you slept under bought or obtained? SHOP . . . . . . . . . . . . . . . . . . . . . . . . . 1 NGO OR OTHER ORGANIZATION . . 2 OTHER 6 (SPECIFY) DON’T KNOW . . . . . . . . . . . . . . . . . . . 8 494M How long ago was the mosquito net bought or obtained? WRITE THE ANSWER IN MONTHS (LESS THAN 1 MONTH = 00) IF MORE THAN 84 MONTHS, WRITE 95. +)))0))), NO OF MONTHS . . . . . . . . . *!!!*!!!* .)))2)))- DON’T KNOW . . . . . . . . . . . . . . . . . . . 8 494N Since you got the mosquito net, was it ever soaked or dipped in an insecticide to repel mosquitoes or bugs? YES . . . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 DON’T KNOW . . . . . . . . . . . . . . . . . . . 8 ), )2<501 494O How long ago was the mosquito net last soaked or dipped? WRITE THE ANSWER IN MONTHS (LESS THAN 1 MONTH = 00) IF MORE THAN 84 MONTHS, WRITE 95. +)))0))), MONTHS . . . . . . . . . . . . . . . *!!!*!!!* .)))2)))- DON’T KNOW . . . . . . . . . . . . . . . . . . 98 EW 35 SECTION 5. MARRIAGE AND SEXUAL ACTIVITY NO. QUESTIONS AND FILTERS CODING CATEGORIES SKIP 501 Are you currently married or living with a man? YES, CURRENTLY MARRIED . . . . . . 1 YES, LIVING WITH A MAN . . . . . . . . . 2 NO, NOT IN UNION . . . . . . . . . . . . . . 3 ), )2<505 502 Have you ever been married or lived with a man? YES, FORMERLY MARRIED . . . . . . . 1 YES, LIVED WITH A MAN . . . . . . . . . 2 NO . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 ))<510 ))<514 504 What is your marital status now: are you widowed, divorced, or separated? WIDOWED . . . . . . . . . . . . . . . . . . . . . 1 DIVORCED . . . . . . . . . . . . . . . . . . . . . 2 SEPARATED . . . . . . . . . . . . . . . . . . . 3 ), )3<510 )- 505 Is your husband/partner living with you now or is he staying elsewhere? LIVING WITH HER . . . . . . . . . . . . . . . 1 STAYING ELSEWHERE . . . . . . . . . . . 2 506 RECORD THE HUSBAND’S/PARTNER’S NAME AND LINE NUMBER FROM THE HOUSEHOLD QUESTIONNAIRE. IF HE IS NOT LISTED IN THE HOUSEHOLD, RECORD ‘00'. NAME +)))0))), *!!!*!!!* LINE NO. . . . . . . . . . . . . . . . .)))2)))- 507 Does your husband/partner have any other wives besides yourself? Yes . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 No . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 ))<510 508 How many other wives does he have? +)))0))), NUMBER . . . . . . . . . . . . . . . *!!!*!!!* .)))2)))- DON’T KNOW . . . . . . . . . . . . . . . . . . 98 510 Have you been married or lived with a man only once, or more than once? ONCE . . . . . . . . . . . . . . . . . . . . . . . . . 1 MORE THAN ONCE . . . . . . . . . . . . . . 2 511 CHECK 510: MARRIED/ +))), LIVED WITH A MAN /)))- ONLY ONCE * ? In what month and year did you start living with your husband/partner? MARRIED/ +))), LIVED WITH A MAN /)))- MORE THAN ONCE * ? Now we will talk about your first husband/partner. In what month and year did you start living with him? +)))0))), MONTH . . . . . . . . . . . . . . . . . *!!!*!!!* .)))2)))- DON’T KNOW MONTH . . . . . . . . . . . 98 +)))0)))0)))0))), YEAR . . . . . . . . . . *!!!*!!!*!!!*!!!* .)))2)))2)))2)))- DON’T KNOW YEAR . . . . . . . . . . . 9998 ))<514 512 How old were you when you started living with him? +)))0))), AGE . . . . . . . . . . . . . . . . . . . *!!!*!!!* .)))2)))- 514 Now I need to ask you some questions about sexual activity in order to gain a better understanding of some family life issues. How old were you when you first had sexual intercourse (if ever)? NEVER . . . . . . . . . . . . . . . . . . . . . . . 00 +)))0))), AGE IN YEARS . . . . . . . . . . . *!!!*!!!* .)))2)))- FIRST TIME WHEN STARTED LIVING WITH (FIRST) HUSBAND/PARTNER 96 ))<524 515 When was the last time you had sexual intercourse? RECORD ‘YEARS AGO’ ONLY IF LAST INTERCOURSE WAS ONE OR MORE YEARS AGO +)))0))), DAYS AGO . . . . . . . . . . . . 1 *!!!*!!!* /)))3)))1 WEEKS AGO . . . . . . . . . . 2 *!!!*!!!* /)))3)))1 MONTHS AGO . . . . . . . . . 3 *!!!*!!!* /)))3)))1 YEARS AGO . . . . . . . . . . . 4 *!!!*!!!* .)))2)))- ))<524 516 The last time you had sexual intercourse, was a condom used? YES . . . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 ))<517 EW 36 NO. QUESTIONS AND FILTERS CODING CATEGORIES SKIP 516A What was the main reason you used a condom on that occasion? OWN CONCERN PREVENT STD/HIV 1 OWN CONCERN TO PREVENT PREGNANCY . . . . . . . . . . . . . . . . 2 OWN CONCERN TO PREVENT BOTH STD/HIV AND PREGNANCY . . . . . . . . . . . . . . . . 3 DID NOT TRUST PARTNER/FEELS PARTNER HAS OTHER PARTNERS . . . . . . . . . . . . . . . . . . 4 PARTNER INSISTED . . . . . . . . . . . . . 5 DON’T KNOW . . . . . . . . . . . . . . . . . . . 6 OTHER 7 (SPECIFY) 517 What is your relationship to the man with whom you last had sex? IF “BOYFRIEND” OR “FIANCE”, ASK: Was your boyfriend/fiance living with you when you last had sex? IF ‘YES’ RECORD ‘1' IF ‘NO’ RECORD ‘2' HUSBAND/COHABITING PARTNER 01 BOYFRIEND/FIANCE . . . . . . . . . . . 02 OTHER FRIEND . . . . . . . . . . . . . . . . 03 CASUAL ACQUAINTANCE . . . . . . . 04 RELATIVE . . . . . . . . . . . . . . . . . . . . 05 COMMERCIAL SEX CUSTOMER . . . 06 OTHER 96 (SPECIFY) ))<519 518 For how long have you had sexual relations with this man? +)))0))), DAYS . . . . . . . . . . . . . . . . 1 *!!!*!!!* /)))3)))1 WEEKS . . . . . . . . . . . . . . . 2 *!!!*!!!* /)))3)))1 MONTHS . . . . . . . . . . . . . 3 *!!!*!!!* /)))3)))1 YEARS . . . . . . . . . . . . . . . 4 *!!!*!!!* .)))2)))- 519 Have you had sex with any other man in the last 12 months? YES . . . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 ))<524 520 The last time you had sexual intercourse with this other man, was a condom used? YES . . . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 ))<521 520A What was the main reason you used a condom on that occasion? OWN CONCERN PREVENT STD/HIV 1 OWN CONCERN TO PREVENT PREGNANCY . . . . . . . . . . . . . . . . 2 OWN CONCERN TO PREVENT BOTH STD/HIV AND PREGNANCY . . . . . . . . . . . . . . . . 3 DID NOT TRUST PARTNER/FEELS PARTNER HAS OTHER PARTNERS . . . . . . . . . . . . . . . . . . 4 PARTNER INSISTED . . . . . . . . . . . . . 5 DON’T KNOW . . . . . . . . . . . . . . . . . . . 6 OTHER 7 (SPECIFY) 521 What is your relationship to this man? IF “BOYFRIEND” OR “FIANCE”, ASK: Was your boyfriend/fiance living with you when you last had sex? IF ‘YES’ RECORD ‘1' IF ‘NO’ RECORD ‘2' HUSBAND/COHABITING PARTNER 01 BOYFRIEND/FIANCE . . . . . . . . . . . 02 OTHER FRIEND . . . . . . . . . . . . . . . . 03 CASUAL ACQUAINTANCE . . . . . . . 04 RELATIVE . . . . . . . . . . . . . . . . . . . . 05 COMMERCIAL SEX CUSTOMER . . . 06 OTHER 96 (SPECIFY) ))<522A 522 For how long have you had sexual relations with this man? +)))0))), DAYS . . . . . . . . . . . . . . . . 1 *!!!*!!!* /)))3)))1 WEEKS . . . . . . . . . . . . . . . 2 *!!!*!!!* /)))3)))1 MONTHS . . . . . . . . . . . . . 3 *!!!*!!!* /)))3)))1 YEARS . . . . . . . . . . . . . . . 4 *!!!*!!!* .)))2)))- 522A Other than these two men, have you had sex with anyone else in the last 12 months? YES . . . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 ))<523 NO. QUESTIONS AND FILTERS CODING CATEGORIES SKIP EW 37 522B The last time you had sexual intercourse with this other man, was a condom used? YES . . . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 ))<522D 522C What was the main reason you used a condom on that occasion? OWN CONCERN PREVENT STD/HIV 1 OWN CONCERN TO PREVENT PREGNANCY . . . . . . . . . . . . . . . . 2 OWN CONCERN TO PREVENT BOTH STD/HIV AND PREGNANCY . . . . . . . . . . . . . . . . 3 DID NOT TRUST PARTNER/FEELS PARTNER HAS OTHER PARTNERS . . . . . . . . . . . . . . . . . . 4 PARTNER INSISTED . . . . . . . . . . . . . 5 DON’T KNOW . . . . . . . . . . . . . . . . . . . 6 OTHER 7 (SPECIFY) 522D What is your relationship to this man? IF “BOYFRIEND” OR “FIANCE”, ASK: Was your boyfriend/fiance living with you when you last had sex? IF ‘YES’ RECORD ‘1' IF ‘NO’ RECORD ‘2' HUSBAND/COHABITING PARTNER 01 BOYFRIEND/FIANCE . . . . . . . . . . . 02 OTHER FRIEND . . . . . . . . . . . . . . . . 03 CASUAL ACQUAINTANCE . . . . . . . 04 RELATIVE . . . . . . . . . . . . . . . . . . . . 05 COMMERCIAL SEX CUSTOMER . . . 06 OTHER 96 (SPECIFY) ))<523 522E For how long have you had a sexual relationship with this man? +)))0))), DAYS . . . . . . . . . . . . . . . . 1 *!!!*!!!* /)))3)))1 WEEKS . . . . . . . . . . . . . . . 2 *!!!*!!!* /)))3)))1 MONTHS . . . . . . . . . . . . . 3 *!!!*!!!* /)))3)))1 YEARS . . . . . . . . . . . . . . . 4 *!!!*!!!* .)))2)))- 523 Altogether, with how many different men have you had sex in the last 12 months? +)))0))), NUMBER OF PARTNERS . . *!!!*!!!* .)))2)))- 524 Do you know of a place where one can get condoms? YES . . . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 ))<527 525 Where is that? RECORD FIRST RESPONSE ONLY. IF SOURCE IS HOSPITAL, HEALTH CENTER, OR CLINIC, WRITE THE NAME OF THE PLACE. PROBE TO IDENTIFY THE TYPE OF SOURCE AND CIRCLE THE APPROPRIATE CODE. (NAME OF PLACE) PUBLIC SECTOR GOVT. HOSPITAL . . . . . . . . . . . . . 11 GOVT. HEALTH CENTER . . . . . . . 12 FAMILY PLANNING CLINIC . . . . . 13 MOBILE CLINIC . . . . . . . . . . . . . . . 14 FIELD WORKER . . . . . . . . . . . . . . 15 OTHER PUBLIC 16 (SPECIFY) MISSION HOSPITAL . . . . . . . . . . . . . . . . . . . 21 HEALTH CENTER . . . . . . . . . . . . . 22 MOBILE CLINIC . . . . . . . . . . . . . . . 23 PRIVATE MEDICAL SECTOR PRIVATE HOSPITAL/CLINIC . . . . 31 PHARMACY . . . . . . . . . . . . . . . . . 32 PRIVATE DOCTOR . . . . . . . . . . . . 33 MOBILE CLINIC . . . . . . . . . . . . . . . 34 FIELD WORKER . . . . . . . . . . . . . . 35 OTHER PRIVATE MEDICAL 36 (SPECIFY) BLM . . . . . . . . . . . . . . . . . . . . . . . . . 41 OTHER SOURCE SHOP . . . . . . . . . . . . . . . . . . . . . . 51 CHURCH . . . . . . . . . . . . . . . . . . . . 52 FRIEND/RELATIVE . . . . . . . . . . . . 53 OTHER 96 (SPECIFY) NO. QUESTIONS AND FILTERS CODING CATEGORIES SKIP EW 38 526 If you wanted to, could you yourself get a condom? YES . . . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 DON’T KNOW/UNSURE . . . . . . . . . . . 8 527 Do you know of a place where one can get female condoms? YES . . . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 ))<530 528 Where is that? RECORD FIRST RESPONSE ONLY. IF SOURCE IS HOSPITAL, HEALTH CENTER, OR CLINIC, WRITE THE NAME OF THE PLACE. PROBE TO IDENTIFY THE TYPE OF SOURCE AND CIRCLE THE APPROPRIATE CODE. (NAME OF PLACE) PUBLIC SECTOR GOVT. HOSPITAL . . . . . . . . . . . . . 11 GOVT. HEALTH CENTER . . . . . . . 12 FAMILY PLANNING CLINIC . . . . . 13 MOBILE CLINIC . . . . . . . . . . . . . . . 14 FIELD WORKER . . . . . . . . . . . . . . 15 OTHER PUBLIC 16 (SPECIFY) MISSION HOSPITAL . . . . . . . . . . . . . . . . . . . 21 HEALTH CENTER . . . . . . . . . . . . . 22 MOBILE CLINIC . . . . . . . . . . . . . . . 23 PRIVATE MEDICAL SECTOR PRIVATE HOSPITAL/CLINIC . . . . 31 PHARMACY . . . . . . . . . . . . . . . . . 32 PRIVATE DOCTOR . . . . . . . . . . . . 33 MOBILE CLINIC . . . . . . . . . . . . . . . 34 FIELD WORKER . . . . . . . . . . . . . . 35 OTHER PRIVATE MEDICAL 36 (SPECIFY) BLM . . . . . . . . . . . . . . . . . . . . . . . . . 41 OTHER SOURCE SHOP . . . . . . . . . . . . . . . . . . . . . . 51 CHURCH . . . . . . . . . . . . . . . . . . . . 52 FRIEND/RELATIVE . . . . . . . . . . . . 53 OTHER 96 (SPECIFY) 529 If you wanted to, could you yourself get a female condom? YES . . . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 DON’T KNOW/UNSURE . . . . . . . . . . . 8 530 Have you heard of a condom called “Chishango”? YES . . . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 DON’T KNOW/UNSURE . . . . . . . . . . . 8 EW 39 SECTION 6. FERTILITY PREFERENCES NO. QUESTIONS AND FILTERS CODING CATEGORIES SKIP 601 CHECK 311/311A: NEITHER +))), HE OR SHE +))), STERILIZED /)))- STERILIZED .)))2)))))))))))))))))))))))))))))))))))))))))))))))))) ? ))<614 602 CHECK 226: NOT PREGNANT +))), OR UNSURE /)))- * ? Now I have some questions about the future. Would you like to have (a/another) child, or would you prefer not to have any (more) children? PREGNANT +))), /)))- * ? Now I have some questions about the future. After the child you are expecting now, would you like to have another child, or would you prefer not to have any more children? HAVE (A/ANOTHER) CHILD . . . . . . . 1 NO MORE/NONE . . . . . . . . . . . . . . . . 2 SAYS SHE CAN’T GET PREGNANT . 3 UNDECIDED/DON’T KNOW AND PREGNANT . . . . . . . . . . . . . . 4 AND NOT PREGNANT OR UNSURE . . . . . . . . . . . . . . 5 ))<604 ))<614 ))<610 ))<608 603 CHECK 226: NOT PREGNANT +))), OR UNSURE /)))- * ? How long would you like to wait from now before the birth of (a/another) child? PREGNANT +))), /)))- * ? After the birth of the child you are expecting now, how long would you like to wait before the birth of another child? +)))0))), MONTHS . . . . . . . . . . . . . 1 *!!!*!!!* /)))3)))1 YEARS . . . . . . . . . . . . . . . 2 *!!!*!!!* .)))2)))- SOON/NOW . . . . . . . . . . . . . . . . . . 993 SAYS SHE CAN’T GET PREGNANT 994 AFTER MARRIAGE . . . . . . . . . . . . 995 OTHER 996 (SPECIFY) DON’T KNOW . . . . . . . . . . . . . . . . . 998 ))<609 ))<614 ), * /<609 * )- 604 CHECK 226: NOT PREGNANT +))), PREGNANT +))), OR UNSURE /)))- .)))2))))))))))))))))))))))))))))))))))))))))))))))))))) ? ))<610 605 CHECK 310: USING A METHOD? NOT NOT +))), CURRENTLY +))), CURRENTLY +))), ASKED /)))- USING /)))- USING .)))2)))))))))))))))))))))))))))))) ? ? ))<608 606 CHECK 603: NOT +))), 24 OR MORE MONTHS +))), 00-23 MONTHS +))), ASKED /)))- OR 02 OR MORE YEARS /)))- OR 00-01 YEAR .)))2))))))))))))))))))))))) ? ? ))<610 NO. QUESTIONS AND FILTERS CODING CATEGORIES SKIP EW 40 607 CHECK 602: WANTS TO HAVE +)), A/ANOTHER CHILD /))- ? You have said that you do not want (a/another) child soon, but you are not using any method to avoid pregnancy. Can you tell me why? Any other reason? RECORD ALL MENTIONED. WANTS NO MORE/ +)), NONE /))- ? You have said that you do not want any (more) children, but you are not using any method to avoid pregnancy. Can you tell me why? Any other reason? NOT MARRIED . . . . . . . . . . . . . . . . . . A FERTILITY-RELATED REASONS NOT HAVING SEX . . . . . . . . . . . . . B INFREQUENT SEX . . . . . . . . . . . . . C MENOPAUSAL/HYSTERECTOMY. . D SUBFECUND/INFECUND . . . . . . . . E POSTPARTUM AMENORRHEIC . . . F BREASTFEEDING . . . . . . . . . . . . . . G FATALISTIC . . . . . . . . . . . . . . . . . . H OPPOSITION TO USE RESPONDENT OPPOSED . . . . . . . . I HUSBAND/PARTNER OPPOSED . . . J OTHERS OPPOSED . . . . . . . . . . . . K RELIGIOUS PROHIBITION . . . . . . . L LACK OF KNOWLEDGE KNOWS NO METHOD . . . . . . . . . . M KNOWS NO SOURCE . . . . . . . . . . . N METHOD-RELATED REASONS HEALTH CONCERNS . . . . . . . . . . . O FEAR OF SIDE EFFECTS . . . . . . . . P LACK OF ACCESS/TOO FAR . . . . . Q COST TOO MUCH . . . . . . . . . . . . . R INCONVENIENT TO USE . . . . . . . . S INTERFERES WITH BODY’S NORMAL PROCESSES . . . . . . . . T OTHER X (SPECIFY) DON’T KNOW . . . . . . . . . . . . . . . . . . . Z 608 In the next few weeks, if you discovered that you were pregnant, would that be a big problem, a small problem, or no problem for you? BIG PROBLEM . . . . . . . . . . . . . . . . . . 1 SMALL PROBLEM . . . . . . . . . . . . . . . 2 NO PROBLEM . . . . . . . . . . . . . . . . . . 3 SAYS SHE CAN’T GET PREGNANT/ NOT HAVING SEX . . . . . . . . . . . . . . . 4 609 CHECK 310: USING A METHOD? NO, YES, NOT +))), NOT CURRENTLY +))), CURRENTLY +))), ASKED /)))- USING /)))- USING .)))2))))))))))))))))))))))))))))))) ? ? ))<614 610 Do you think you will use a method to delay or avoid pregnancy at any time in the future? YES . . . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 DON’T KNOW . . . . . . . . . . . . . . . . . . . 8 ), )2<612 611 Which method would you prefer to use? FEMALE STERILIZATION . . . . . . . . 01 MALE STERILIZATION . . . . . . . . . . . 02 PILL . . . . . . . . . . . . . . . . . . . . . . . . . 03 IUD . . . . . . . . . . . . . . . . . . . . . . . . . . 04 INJECTIONS . . . . . . . . . . . . . . . . . . . 05 IMPLANTS . . . . . . . . . . . . . . . . . . . . 06 CONDOM . . . . . . . . . . . . . . . . . . . . . 07 FEMALE CONDOM . . . . . . . . . . . . . 08 DIAPHRAGM . . . . . . . . . . . . . . . . . . 09 FOAM/JELLY . . . . . . . . . . . . . . . . . . 10 LACT. AMEN. METHOD . . . . . . . . . . 11 PERIODIC ABSTINENCE . . . . . . . . . 12 WITHDRAWAL . . . . . . . . . . . . . . . . . 13 OTHER 96 (SPECIFY) UNSURE . . . . . . . . . . . . . . . . . . . . . . 98 ), * * * * * * /<614 * * * * * * * * )- NO. QUESTIONS AND FILTERS CODING CATEGORIES SKIP EW 41 612 What is the main reason that you think you will not use a method at any time in the future? NOT MARRIED . . . . . . . . . . . . . . . . . 11 FERTILITY-RELATED REASONS INFREQUENT SEX/NO SEX . . . . . 22 MENOPAUSAL/HYSTERECTOMY 23 SUBFECUND/INFECUND . . . . . . . 24 WANTS AS MANY CHILDREN AS POSSIBLE . . . . . . . . . . . . . . . . . 26 OPPOSITION TO USE RESPONDENT OPPOSED . . . . . . 31 HUSBAND/PARTNER OPPOSED . 32 OTHERS OPPOSED . . . . . . . . . . . 33 RELIGIOUS PROHIBITION . . . . . . 34 LACK OF KNOWLEDGE KNOWS NO METHOD . . . . . . . . . 41 KNOWS NO SOURCE . . . . . . . . . . 42 METHOD-RELATED REASONS HEALTH CONCERNS . . . . . . . . . . 51 FEAR OF SIDE EFFECTS . . . . . . . 52 LACK OF ACCESS/TOO FAR . . . . 53 COST TOO MUCH . . . . . . . . . . . . 54 INCONVENIENT TO USE . . . . . . . 55 INTERFERES WITH BODY’S NORMAL PROCESSES . . . . . . . 56 OTHER 96 (SPECIFY) DON’T KNOW . . . . . . . . . . . . . . . . . . 98 ), * * * * * * * * * * * * /<614 * * * * * * * * * * * * * )- 613 Would you ever use a method if you were married? YES . . . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 DON’T KNOW . . . . . . . . . . . . . . . . . . . 8 614 CHECK 216: +)), HAS LIVING CHILDREN /))- ? If you could go back to the time you did not have any children and could choose exactly the number of children to have in your whole life, how many would that be? +)), NO LIVING CHILDREN /))- ? If you could choose exactly the number of children to have in your whole life, how many would that be? +)))0))), NUMBER . . . . . . . . . . . . . . . *!!!*!!!* .)))2)))- OTHER 96 (SPECIFY) ))<616 PROBE FOR A NUMERIC RESPONSE. 615 How many of these children would you like to be boys, how many would you like to be girls and for how many would the sex not matter? BOYS GIRLS EITHER +)))0))),+)))0))),+)))0))), NUMBER *!!!*!!!**!!!*!!!**!!!*!!!* .)))2)))-.)))2)))-.)))2)))- OTHER 96 (SPECIFY) 616 Would you say that you approve or disapprove of couples using a method to avoid getting pregnant? APPROVE . . . . . . . . . . . . . . . . . . . . . 1 DISAPPROVE . . . . . . . . . . . . . . . . . . . 2 DON’T KNOW/UNSURE . . . . . . . . . . . 3 617 In the last few months have you seen or heard about family planning: On the radio? On the television? In a newspaper or magazine? On a poster? On clothing (i.e. cap, chitenji, t-shirt) In a drama? YES NO RADIO . . . . . . . . . . . . . . . . . . . 1 2 TELEVISION . . . . . . . . . . . . . . . 1 2 NEWSPAPER OR MAGAZINE . 1 2 POSTER . . . . . . . . . . . . . . . . . . 1 2 CLOTHING . . . . . . . . . . . . . . . . 1 2 DRAMA . . . . . . . . . . . . . . . . . . . 1 2 NO. QUESTIONS AND FILTERS CODING CATEGORIES SKIP EW 42 618 In the last few months, have you listened to any of the following program series about family planning or health on the radio? Uchembere Wabwino? Phukusi la Moyo? Pa Mtondo? Women’s Talking Point? Window Through Health? Umoyo M’Malawi? Tinkanena? Radio Doctor? Chitukuku M’Malawi? Women’s Forum? Tichitenji? Kulera? YES NO UCHEMBERE WABWINO . . 1 2 PHUKUSI LA MOYO . . . . . . . 1 2 PA MTONDO . . . . . . . . . . . . 1 2 WOMEN’S TALKING PT . . . . 1 2 WINDOW THRU HEALTH . . 1 2 UMOYO M’MALAWI . . . . . . . 1 2 TINKANENA . . . . . . . . . . . . . 1 2 RADIO DOCTOR . . . . . . . . . 1 2 CHITUKUKU M’MALAWI . . . 1 2 WOMEN’S FORUM . . . . . . . . 1 2 TICHITENJI . . . . . . . . . . . . . 1 2 KULERA . . . . . . . . . . . . . . . . 1 2 619 In the last few months, have you discussed the practice of family planning with your friends, neighbors, or relatives? YES . . . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 ))<621 620 With whom? Anyone else? RECORD ALL MENTIONED. HUSBAND/PARTNER . . . . . . . . . . . . A MOTHER . . . . . . . . . . . . . . . . . . . . . . B FATHER . . . . . . . . . . . . . . . . . . . . . . . C SISTER(S) . . . . . . . . . . . . . . . . . . . . . D BROTHER(S) . . . . . . . . . . . . . . . . . . . E DAUGHTER . . . . . . . . . . . . . . . . . . . . F SON . . . . . . . . . . . . . . . . . . . . . . . . . . G MOTHER-IN-LAW . . . . . . . . . . . . . . . . H FRIENDS/NEIGHBORS . . . . . . . . . . . . I OTHER X (SPECIFY) 621 CHECK 501: YES, +))), YES, +))), NO, +))), CURRENTLY /)))- LIVING /)))- NOT IN .)))2))))))))))))))))))))))))))))))) MARRIED ? WITH A MAN ? UNION ))<624A 621A CHECK 311/311A: ANY CODE CIRCLED +))), NO CODE CIRCLED +))), /)))- .)))2)))))))))))))))))))))))) ? ))<622 621B You have told me that you are currently using contraception. Would you say that using contraception is mainly your decision, mainly your husband’s/partner’s decision or did you both decide together? MAINLY RESPONDENT . . . . . . . . . . . 1 MAINLY HUSBAND/PARTNER . . . . . 2 JOINT DECISION . . . . . . . . . . . . . . . . 3 OTHER 6 (SPECIFY) 622 Now I want to ask you about your husband’s/partner’s views on family planning. Do you think that your husband/partner approves or disapproves of couples using a method to avoid pregnancy? APPROVES . . . . . . . . . . . . . . . . . . . . 1 DISAPPROVES . . . . . . . . . . . . . . . . . 2 DON’T KNOW . . . . . . . . . . . . . . . . . . . 8 623 How often have you talked to your husband/partner about family planning in the past year? NEVER . . . . . . . . . . . . . . . . . . . . . . . . 1 ONCE OR TWICE . . . . . . . . . . . . . . . . 2 MORE OFTEN . . . . . . . . . . . . . . . . . . 3 NO. QUESTIONS AND FILTERS CODING CATEGORIES SKIP EW 43 623A CHECK 311/311A: NEITHER +))), HE OR SHE +))), STERILIZED /)))- STERILIZED .)))2)))))))))))))))))))))))))))))))))))))))))))))))))) ? ))<624A 624 Do you think your husband/partner wants the same number of children that you want, or does he want more or fewer than you want? SAME NUMBER . . . . . . . . . . . . . . . . . 1 MORE CHILDREN . . . . . . . . . . . . . . . 2 FEWER CHILDREN . . . . . . . . . . . . . . 3 DON’T KNOW . . . . . . . . . . . . . . . . . . . 8 624A CHECK 501 & 502: EVER IN UNION NEVER IN UNION CODE ‘3' NOT CIRCLED +))), CODE ‘3' CIRCLED +))), IN 501 OR 502 /)))- IN 501 AND 502 .)))2)))))))))))))))))))))))))))))) ? ))<701 625 Husbands and wives do not always agree on everything. Please tell me if you think a wife is justified in refusing to have sex with her husband when: YES NO DK She knows her husband has a sexually transmitted disease? She knows her husband has sex with other women? She has recently given birth? She is tired or not in the mood? HAS STD . . . . . . . . . . . . . 1 2 8 OTHER WOMEN . . . . . . . 1 2 8 RECENT BIRTH . . . . . . . . 1 2 8 TIRED/MOOD . . . . . . . . . . 1 2 8 EW 44 SECTION 7. HUSBAND'S BACKGROUND AND WOMAN'S WORK NO. QUESTIONS AND FILTERS CODING CATEGORIES SKIP 701 CHECK 501 AND 502: CURRENTLY +))), FORMERLY +)))0)))))))))))))))))))))))))))))))))))))))))))))))) MARRIED/ /)))- MARRIED/ .)))- LIVING WITH * LIVED WITH NEVER MARRIED +))), A MAN ? A MAN AND NEVER .)))2)))))))))))) LIVED WITH A MAN ))<703 ))<707 702 How old was your husband/partner on his last birthday? +)))0))), AGE IN COMPLETED YEARS*!!!*!!!* .)))2)))- 703 Did your (last) husband/partner ever attend school? YES . . . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 ))<706 704 What was the highest level of school he attended: primary, secondary, or higher? PRIMARY . . . . . . . . . . . . . . . . . . . . . . 1 SECONDARY . . . . . . . . . . . . . . . . . . . 2 HIGHER . . . . . . . . . . . . . . . . . . . . . . . 3 DON’T KNOW . . . . . . . . . . . . . . . . . . . 8 ))<706 705 How many years of school did he complete at that level? +)))0))), YEARS . . . . . . . . . . . . . . . . . *!!!*!!!* .)))2)))- DON’T KNOW . . . . . . . . . . . . . . . . . . 98 706 CHECK 701: CURRENTLY MARRIED/ +)), LIVING WITH A MAN /))- ? What is your husband’s/partner’s occupation? That is, what kind of work does he mainly do? FORMERLY MARRIED/ +)), LIVED WITH A MAN /))- ? What was your (last) husband’s/ partner’s occupation? That is, what kind of work did he mainly do? +)))0))), *!!!*!!!* .)))2)))- 707 Aside from your own housework, are you currently working? YES . . . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 ))<710 708 As you know, some women take up jobs for which they are paid in cash or kind. Others sell things, have a small business or work on the family farm or in the family business. Are you currently doing any of these things or any other work? YES . . . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 ))<710 709 Have you done any work in the last 12 months? YES . . . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 ))<719 710 What is your occupation, that is, what kind of work do you mainly do? +)))0))), *!!!*!!!* .)))2)))- 711 CHECK 710: WORKS IN +))), DOES NOT WORK +))), FARMING /)))- IN FARMING .)))2))))))))))))))))))))))))))))))))))))))))))))))))))) ? ))<713 712 Do you work mainly on your own land or on family land, or do you work on land that you rent from someone else, or do you work on someone else's land? OWN LAND . . . . . . . . . . . . . . . . . . . . 1 FAMILY LAND . . . . . . . . . . . . . . . . . . 2 RENTED LAND . . . . . . . . . . . . . . . . . . 3 SOMEONE ELSE'S LAND . . . . . . . . . 4 713 Do you do this work for a member of your family, for someone else, or are you self-employed? FOR FAMILY MEMBER . . . . . . . . . . . 1 FOR SOMEONE ELSE . . . . . . . . . . . . 2 SELF-EMPLOYED . . . . . . . . . . . . . . . 3 713A Do you usually work at home or away from home? HOME . . . . . . . . . . . . . . . . . . . . . . . . . 1 AWAY . . . . . . . . . . . . . . . . . . . . . . . . . 2 714 Do you usually work throughout the year, or do you work seasonally, or only once in a while? THROUGHOUT THE YEAR . . . . . . . . 1 SEASONALLY/PART OF THE YEAR . 2 ONCE IN A WHILE . . . . . . . . . . . . . . . 3 NO. QUESTIONS AND FILTERS CODING CATEGORIES SKIP EW 45 715 Are you paid or do you earn in cash or kind for this work or are you not paid at all? CASH ONLY . . . . . . . . . . . . . . . . . . . . 1 CASH AND KIND . . . . . . . . . . . . . . . . 2 IN KIND ONLY . . . . . . . . . . . . . . . . . . 3 NOT PAID . . . . . . . . . . . . . . . . . . . . . . 4 ), )2<719 716 Who mainly decides how the money you earn will be used? RESPONDENT . . . . . . . . . . . . . . . . . 1 HUSBAND/PARTNER . . . . . . . . . . . . 2 RESPONDENT AND HUSBAND/PARTNER JOINTLY . . . 3 SOMEONE ELSE . . . . . . . . . . . . . . . . 4 RESPONDENT AND SOMEONE ELSE JOINTLY . . . . . . . . . . . . . . . . . . . . . 5 717 On average, how much of your household’s expenditures do your earnings pay for: almost none, less than half, about half, more than half, or all? ALMOST NONE . . . . . . . . . . . . . . . . . 1 LESS THAN HALF . . . . . . . . . . . . . . . 2 ABOUT HALF . . . . . . . . . . . . . . . . . . . 3 MORE THAN HALF . . . . . . . . . . . . . . 4 ALL . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 NONE, HER INCOME IS ALL SAVED. 6 719 Who in your family usually has the final say on the following decisions: RESPONDENT = 1 HUSBAND/PARTNER = 2 RESPONDENT & HUSBAND/PARTNER JOINTLY = 3 SOMEONE ELSE = 4 RESPONDENT & SOMEONE ELSE JOINTLY = 5 DECISION NOT MADE/NOT APPLICABLE = 6 Your own health care? Making large household purchases? Making household purchases for daily needs? Visits to family or relatives? What food should be cooked each day? The number of children you should bear? 1 2 3 4 5 6 1 2 3 4 5 6 1 2 3 4 5 6 1 2 3 4 5 6 1 2 3 4 5 6 1 2 3 4 5 6 720 PRESENCE OF OTHERS AT THIS POINT (PRESENT AND LISTENING, PRESENT BUT NOT LISTENING OR NOT PRESENT) PRES/ PRES/ NOT LISTEN. NOT PRS LISTEN. CHILDREN <10 . . . . . 1 2 8 HUSBAND . . . . . . . . 1 2 8 OTHER MALES . . . . 1 2 8 OTHER FEMALES . . 1 2 8 721 Sometimes a husband is annoyed or angered by things which his wife does. In your opinion, is a husband justified in hitting or beating his wife in the following situations: YES NO DK If she goes out without telling him? If she neglects the children? If she argues with him? If she refuses to have sex with him? If she burns the food? GOES OUT . . . . . . . . 1 2 8 NEGL. CHILDREN . . 1 2 8 ARGUES . . . . . . . . . . 1 2 8 REFUSES SEX . . . . . 1 2 8 BURNS FOOD . . . . . 1 2 8 EW 46 SECTION 8: AIDS AND OTHER SEXUALLY TRANSMITTED DISEASES NO. QUESTIONS AND FILTERS CODING CATEGORIES SKIP 801 Now I would like to talk about something else. Have you ever heard of an illness called AIDS? YES . . . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 ))<818 802 Is there anything a person can do to avoid getting AIDS or the virus that causes AIDS? YES . . . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 DON’T KNOW . . . . . . . . . . . . . . . . . . . 8 ), )2<809 803 What can a person do? Anything else? RECORD AL