Uganda - Demographic and Health Survey - 2001

Publication date: 2001

2000-2001Demographic andHealth Survey U ganda 2000-2001 D em ographic and H ealth Survey Uganda Uganda Demographic and Health Survey 2000-2001 Uganda Bureau of Statistics Entebbe, Uganda ORC Macro Calverton, Maryland, USA December 2001 DFID Department forInternationalDevelopme nt This report highlights the findings of the 2000-2001 Uganda Demographic and Health Survey (UD HS), a nationally representative survey of households, women age 15-49, and men age 15-54. Interviews were successfu lly completed with 7,246 women age 15-49 and 1,962 m en age 15 -54. Information about children born to these women was also collected. Detailed questions about vaccination, breastfeeding, food supplementation, and illnesses were asked about children born in the five years before the survey. The primary objective of the survey is to provide policy makers and programme managers with detailed information on fertility , family planning, childhood and adu lt mortality, maternal and child health, nutrition, and knowledge and attitudes about HIV/AIDS. The 2000-2001 Uganda Demographic and Health Survey (UDHS) was conducted by the Uganda Bureau of Statistics. Funding for the survey was provided by the U.S. Agency for International Development (USAID), the Department for International Development (DFID/Uganda), UNICEF/Uganda, and UNFPA/Uganda. The UDHS is part of the worldwide Demographic and Health Surveys (DHS) project designed to collect, analyse, and disseminate data on fertility, family planning, maternal and child health, and HIV/AIDS. Additional information about the survey may be obtained from the Uganda Bureau of Statistics (UBOS), P.O. Box 13, Entebbe, Uganda (Telephone: (256-41) 320-741; Fax: (256-41) 320-147; e-mail: ubos@ infocom.co.ug). Additional information about the DHS programme may be obtained by writing to MEASURE DHS+ , ORC Macro, 11785 Beltsville Drive, Suite 300, Calverton, MD 20705, USA (Telephone: 301-572-0200; Fax: 301-572-0999; e-mail: reports@macroint.com). Recommended citation: Uganda Bureau of Statistics (UBOS) and ORC Macro. 2001. Uganda Demographic and Health Survey 2000-2001. Calverton, Maryland, USA: UBOS and ORC M acro. Contents * iii CONTENTS Page Tables and figures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ix Preface . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xv Summary of Findings . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xvii Map of Uganda . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xxii CHAPTER 1 INTRODUCTION 1.1 Geography and Economy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 1.2 Population . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 1.3 National Population and Health Programmes . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 1.4 Objectives of the Survey . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 1.5 Organisation of the Survey . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 1.6 Response Rates . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 CHAPTER 2 CHARACTERISTICS OF HOUSEHOLDS AND HOUSEHOLD MEMBERS 2.1 Population by Age and Sex . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9 2.2 Household Composition . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11 2.3 Fosterhood and Orphanhood . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11 2.4 Educational Level of Household Population . . . . . . . . . . . . . . . . . . . . . . . . . . . 12 2.5 Child Labour . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14 2.6 Housing Characteristics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16 2.7 Household Durable Goods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18 CHAPTER 3 CHARACTERISTICS OF RESPONDENTS AND WOMEN’S STATUS 3.1 Characteristics of Survey Respondents . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19 3.2 Educational Attainment by Background Characteristics . . . . . . . . . . . . . . . . . . 21 3.3 Literacy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21 3.4 Access to Mass Media . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23 3.5 Employment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25 3.6 Occupation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27 3.7 Earnings, Employer, and Continuity of Employment . . . . . . . . . . . . . . . . . . . . 28 3.8 Control over Earnings and Women’s Contribution to Household Expenditure . . 30 3.9 Control over Earnings According to Contribution of Household Expenditure . . 33 3.10 Women’s Participation in Household Decisionmaking . . . . . . . . . . . . . . . . . . . 33 3.11 Women’s Agreement with Reasons for Wife Beating . . . . . . . . . . . . . . . . . . . . . 36 3.12 Women’s Agreement with Reasons for Refusing Sexual Relations . . . . . . . . . . . 36 3.13 Use of Tobacco and Alcohol . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39 iv * Contents Page CHAPTER 4 FERTILITY 4.1 Current Fertility Levels . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41 4.2 Fertility Differentials . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 42 4.3 Trends in Age-Specific Fertility Rates . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 44 4.4 Children Ever Born . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45 4.5 Birth Intervals . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 46 4.6 Age at First Birth . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48 4.7 Teenage Pregnancy and Motherhood . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49 CHAPTER 5 FERTILITY REGULATION 5.1 Knowledge of Contraceptive Methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 51 5.2 Ever Use of Contraception . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 54 5.3 Current Use of Contraception . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 54 5.4 Number of Children at First Use of Family Planning . . . . . . . . . . . . . . . . . . . . . 62 5.5 Knowledge of the Fertile Period . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 62 5.6 Source of Supply of Contraceptives . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 63 5.7 Informed Choice . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 65 5.8 Future Use of Contraception . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 66 5.9 Reasons for Nonuse of Contraception . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 67 5.10 Preferred method of contraception for future use . . . . . . . . . . . . . . . . . . . . . . . 67 5.11 Exposure to Family Planning Messages . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 68 5.12 Contact of Nonusers with Family Planning Providers . . . . . . . . . . . . . . . . . . . . 68 5.13 Attitudes of Couples toward Family Planning . . . . . . . . . . . . . . . . . . . . . . . . . . 71 5.14 Discussion of Family Planning with Husband . . . . . . . . . . . . . . . . . . . . . . . . . . 72 CHAPTER 6 OTHER PROXIMATE DETERMINANTS OF FERTILITY 6.1 Current Marital Status . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 73 6.2 Polygyny . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 75 6.3 Age at First Marriage . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 76 6.4 Median Age at First Marriage . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 77 6.5 Age at First Sexual Intercourse . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 78 6.6 Median Age at First Intercourse . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 79 6.7 Recent Sexual Activity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 80 6.8 Postpartum Amenorrhoea, Abstinence, and Insusceptibility . . . . . . . . . . . . . . . 82 6.9 Median Duration of Postpartum Insusceptibility by Background Characteristics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 83 6.10 Menopause . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 84 CHAPTER 7 FERTILITY PREFERENCES 7.1 Desire for More Children . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 85 Contents * v Page 7.2 Desire to Limit Childbearing by Background Characteristics . . . . . . . . . . . . . . . 87 7.2 Demand for Family Planning Services . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 88 7.3 Ideal Number of Children . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 90 7.4 Fertility Planning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 93 CHAPTER 8 INFANT AND CHILD MORTALITY 8.1 Definitions, Methodology and Assessment of Data Quality . . . . . . . . . . . . . . . . 97 8.2 Early Childhood Mortality Rates: Levels and Trends . . . . . . . . . . . . . . . . . . . . . 98 8.3 Early Childhood Mortality by Socioeconomic Characteristics . . . . . . . . . . . . . 100 8.4 Early Childhood Mortality by Demographic Characteristics . . . . . . . . . . . . . . 102 8.5 Early Childhood Mortality by Women’s Status . . . . . . . . . . . . . . . . . . . . . . . . 103 8.6 Perinatal Mortality . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 104 8.7 High-risk Fertility Behaviour . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 106 CHAPTER 9 REPRODUCTIVE HEALTH AND CHILD CARE 9.1 Antenatal Care . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 109 9.1.1 Number of Antenatal Care Visits and Timing of First Visit Care . . . . . 111 9.1.2 Quality of Antenatal Care . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 112 9.1.3 Place of Antenatal Care . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 113 9.1.4 Tetanus Toxoid Vaccination . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 114 9.2 Delivery . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 115 9.2.1 Assistance During Delivery . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 117 9.2.2 Characteristics of Delivery . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 119 9.3 Postnatal Care . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 120 9.4 Women’s Status and Reproductive Health Care . . . . . . . . . . . . . . . . . . . . . . . 121 9.5 Childhood Immunisation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 122 9.5.1 Childhood Immunisation by Background Characteristics . . . . . . . . . . 123 9.5.2 Vaccination Trends . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 126 9.6 Acute Respiratory Infection . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 126 9.7 Diarrhoea . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 128 9.7.1 Hand-washing Materials . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 128 9.7.2 Disposal of Children’s Stool . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 129 9.7.3 Prevalence of Diarrhoea . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 131 9.7.4 Knowledge of ORS Packets . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 132 9.7.5 Treatment of Diarrhoea . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 132 9.7.6 Feeding Practices during Diarrhoea . . . . . . . . . . . . . . . . . . . . . . . . . . 134 vi * Contents Page 9.8 Women’s Status and Health Care . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 134 9.8.1 Women’s Status and Children’s Health Care . . . . . . . . . . . . . . . . . . . . 134 9.8.2 Women’s Problems in Accessing Health Care . . . . . . . . . . . . . . . . . . . 135 9.9 Malaria . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 137 9.9.1 Possession and Use of Mosquito Nets . . . . . . . . . . . . . . . . . . . . . . . . . 137 9.9.2 Insecticide Treatment of Mosquito Nets . . . . . . . . . . . . . . . . . . . . . . . 138 9.9.3 Malaria Prophylaxis During Pregnancy . . . . . . . . . . . . . . . . . . . . . . . . 139 9.9.4 Type of Anti-Malarial Treatent . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 140 9.10 Birth Registration . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 140 CHAPTER 10 WOMEN’S NUTRITIONAL STATUS 10.1 Breastfeeding and Complementary Feeding . . . . . . . . . . . . . . . . . . . . . . . . . . 143 10.1.1 Initiation of Breastfeeding . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 143 10.1.2 Age Pattern of Breastfeeding . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 144 10.1.3 Types of Complementary Foods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 147 10.1.4 Frequency of Foods Consumed by Children . . . . . . . . . . . . . . . . . . . . 148 10.2 Micronutrients . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 149 10.2.1 Micronutrient Status of Young Children . . . . . . . . . . . . . . . . . . . . . . . 149 10.3 Nutritional Status of Children . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 153 10.3.1 Measures of Nutritional Status . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 153 10.3.2 Levels of Childhood Malnutrition . . . . . . . . . . . . . . . . . . . . . . . . . . . . 154 10.3.3 Nutritional Status of Women . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 156 10.4 Prevalence of Anaemia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 158 10.4.1 Prevalence of Anaemia in children . . . . . . . . . . . . . . . . . . . . . . . . . . . 158 10.4.2 Prevalence of Anaemia in Women . . . . . . . . . . . . . . . . . . . . . . . . . . . . 158 10.4.3 Prevalence of Anaemia in Men . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 160 10.4.4 Anaemia in Children and Severity of Anaemia in Mothers . . . . . . . . . 161 10.5 Vitamin A Status . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 162 10.5.1 Methodology for Measuring Vitamin A . . . . . . . . . . . . . . . . . . . . . . . . 162 10.5.2 Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 163 Contents * vii Page CHAPTER 11 HIV/AIDS AND OTHER SEXUALLY TRANSMITTED INFECTIONS 11.1 Knowledge of Ways to Prevent HIV/AIDS . . . . . . . . . . . . . . . . . . . . . . . . . . . . 167 11.1.1 Knowledge of Ways to Avoid HIV/AIDS . . . . . . . . . . . . . . . . . . . . . . . 167 11.1.2 Knowledge of Programmatically Important Ways to Avoid Contracting HIV/AIDS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 168 11.2 Knowledge of Other AIDS-related Issues . . . . . . . . . . . . . . . . . . . . . . . . . . . . 170 11.3 Perceptions of HIV/AIDS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 173 11.3.1 Discussion of AIDS with Partners . . . . . . . . . . . . . . . . . . . . . . . . . . . . 173 11.3.2 Stigma Associated with HIV/AIDS . . . . . . . . . . . . . . . . . . . . . . . . . . . 174 11.3.3 Discussion of HIV/AIDS in the Media . . . . . . . . . . . . . . . . . . . . . . . . . 176 11.4 Knowledge of Symptoms of Sexually Transmitted Infections . . . . . . . . . . . . . 177 11.5 Reports of Recent Sexually Transmitted Infections . . . . . . . . . . . . . . . . . . . . . 179 11.6 Treatment Seeking and Protection of a Partner from Sexually Transmitted Infections . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 181 11.7 Sexual Behaviour . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 183 11.7.1 Number of Sexual Partners . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 183 11.7.2 Payment for Sexual Relations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 186 11.7.3 Condom Use for Disease Prevention . . . . . . . . . . . . . . . . . . . . . . . . . . 186 11.8 Testing for HIV . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 189 CHAPTER 12 ADULT MORTALITY 12.1 The Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 195 12.2 Direct Estimates of Adult Mortality . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 196 12.3 Maternal Mortality . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 198 REFERENCES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 201 APPENDIX A SAMPLE DESIGN . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 203 APPENDIX B SAMPLING ERRORS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 209 APPENDIX C DATA QUALITY TABLES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 221 APPENDIX D PERSONS INVOLVED IN THE 2000-2001 UGANDA DEMOGRAPHIC AND HEALTH SURVEY . . . . . . . . . . . . . . . . . . . . . . . . . . 227 APPENDIX E QUESTIONNAIRES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 231 APPENDIX F UNICEF WORLD SUMMIT FOR CHILDREN: END-DECADE INDICATORS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 333 viii * Contents Tables and Figures * ix TABLES AND FIGURES Page CHAPTER 1 INTRODUCTION Table 1.1 Demographic characteristics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 Table 1.2 Results of the household and individual interviews . . . . . . . . . . . . . . . . . . . . . . 7 CHAPTER 2 CHARACTERISTICS OF HOUSEHOLDS AND HOUSEHOLD MEMBERS Table 2.1 Household population by age, sex, and residence . . . . . . . . . . . . . . . . . . . . . . . . 9 Table 2.2 Household composition . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11 Table 2.3 Children’s living arrangements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12 Table 2.4 Educational attainment of household population . . . . . . . . . . . . . . . . . . . . . . . 13 Table 2.5 Children’s economic activity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15 Table 2.6 Housing characteristics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17 Table 2.7 Household durable goods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18 Figure 2.1 Population Pyramid . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10 CHAPTER 3 CHARACTERISTICS OF RESPONDENTS AND WOMEN’S STATUS Table 3.1 Background characteristics of respondents . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20 Table 3.2 Educational attainment by background characteristics . . . . . . . . . . . . . . . . . . . 22 Table 3.3 Literacy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23 Table 3.4 Exposure to mass media . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24 Table 3.5 Employment status . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26 Table 3.6.1 Occupation: women . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28 Table 3.6.2 Occupation: men . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29 Table 3.7 Type of employment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30 Table 3.8 Decision on use of earnings and contribution of earnings to household expenditures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32 Table 3.9 Control over earnings according to contribution to household expenditures . . . 33 Table 3.10 Women’s participation in decisionmaking . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34 Table 3.11 Women’s participation in decisionmaking by background characteristics . . . . . 35 Table 3.12 Women's attitude toward wife beating . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37 Table 3.13 Women's attitude toward refusing sex with husband . . . . . . . . . . . . . . . . . . . . 38 Table 3.14 Smoking and alcohol consumption . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39 Figure 3.1 Employment of women . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27 Figure 3.2 Type of earnings of employed women . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31 Figure 3.3 Type of employer for women . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31 x * Tables and Figures Page CHAPTER 4 FERTILITY Table 4.1 Current fertility . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41 Table 4.2 Fertility by background characteristics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43 Table 4.3 Trends in age-specific fertility rates . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45 Table 4.4 Children ever born and living . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 46 Table 4.5 Birth intervals . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 47 Table 4.6 Age at first birth . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48 Table 4.7 Median age at first birth by background characteristics . . . . . . . . . . . . . . . . . . 49 Table 4.8 Teenage pregnancy and motherhood . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 50 Figure 4.1 Total fertility rates by background characteristics . . . . . . . . . . . . . . . . . . . . . . . 44 Figure 4.2 Trends in age-specific fertility rates, 1988-89 UDHS, 1995 UDHS, and 2000-2001 UDHS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45 Figure 4.3 Percentage of women age 15-49 who are mothers or pregnant with their first child, by level of education . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 50 CHAPTER 5 FERTILITY REGULATION Table 5.1 Knowledge of contraceptive methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 52 Table 5.2 Knowledge of contraceptive methods by background characteristics . . . . . . . . 53 Table 5.3 Ever use of contraception . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 55 Table 5.4 Current use of contraception . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 56 Table 5.5 Current use of contraception by background characteristics . . . . . . . . . . . . . . . 60 Table 5.6 Current use of contraception by women's status . . . . . . . . . . . . . . . . . . . . . . . . 61 Table 5.7 Number of children at first use of contraception . . . . . . . . . . . . . . . . . . . . . . . . 62 Table 5.8 Knowledge of fertile period . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 63 Table 5.9 Source of contraception . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 64 Table 5.10 Informed choice . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 65 Table 5.11 Future use of contraception . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 66 Table 5.12 Reason for nonuse of contraception . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 67 Table 5.13 Preferred method of contraception for future use . . . . . . . . . . . . . . . . . . . . . . . 68 Table 5.14 Exposure to family planning messages . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 69 Table 5.15 Contact of nonusers with family planning providers . . . . . . . . . . . . . . . . . . . . . 70 Table 5.16 Attitudes of couples toward family planning . . . . . . . . . . . . . . . . . . . . . . . . . . 71 Table 5.17 Discussion of family planning with husband . . . . . . . . . . . . . . . . . . . . . . . . . . . 72 Figure 5.1 Contraceptive use among currently married women 15-49 . . . . . . . . . . . . . . . . 57 Figure 5.2 Contraceptive use (percent) in selected eastern and southern African countries . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 57 Figure 5.3 Trends in the CPR among currently married women 15-49 years . . . . . . . . . . . 58 Figure 5.4 Contraceptive use among currently married women 15-49 by background characteristics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 61 Figure 5.5 Distribution of current users of modern contraceptive methods by source of supply . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 64 Tables and Figures * xi Page CHAPTER 6 OTHER PROXIMATE DETERMINANTS OF FERTILITY Table 6.1 Current marital status . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 74 Table 6.2 Number of co-wives . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 75 Table 6.3 Age at first marriage . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 76 Table 6.4 Median age at first marriage . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 77 Table 6.5 Age at first sexual intercourse . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 79 Table 6.6 Median age at first intercourse . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 80 Table 6.7 Recent sexual activity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 81 Table 6.8 Postpartum amenorrhoea, abstinence, and insusceptibility . . . . . . . . . . . . . . . . 82 Table 6.9 Median duration of postpartum insusceptibility by background characteristics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 83 Table 6.10 Menopause . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 84 Figure 6.1 Current marital status . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 74 Figure 6.2 Median age at first marriage aong women 25-49 by background characteristics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 78 Figure 6.3 Median duration of postpartum insusceptibility by background characteristics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 84 CHAPTER 7 FERTILITY PREFERENCES Table 7.1 Fertility preferences by number of living children . . . . . . . . . . . . . . . . . . . . . . . 86 Table 7.2 Desire to limit childbearing by background characteristics . . . . . . . . . . . . . . . . 88 Table 7.3 Need for family planning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 89 Table 7.4 Ideal number of children . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 91 Table 7.5 Mean ideal number of children by background characteristics . . . . . . . . . . . . . 92 Table 7.6 Fertility planning status . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 94 Table 7.7 Wanted fertility rates . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 95 Figure 7.1 Fertility preferences of currently married women 15-49 . . . . . . . . . . . . . . . . . . 85 Figure 7.2 Fertility preferences among women by number of children . . . . . . . . . . . . . . . 87 Figure 7.3 Unmet need for family planning services among currently married women 15-49 by background chracteristics . . . . . . . . . . . . . . . . . . . . . . . . . . . 90 Figure 7.4 Mean ideal number of children by background characteristics . . . . . . . . . . . . . 93 CHAPTER 8 INFANT AND CHILD MORTALITY Table 8.1 Early childhood mortality rates . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 99 Table 8.2 Early childhood mortality by socioeconomic characteristics . . . . . . . . . . . . . . 100 Table 8.3 Early childhood mortality by demographic characteristics . . . . . . . . . . . . . . . 102 Table 8.4 Early childhood mortality by woman’s status . . . . . . . . . . . . . . . . . . . . . . . . . 104 Table 8.5 Perinatal mortality . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 105 Table 8.6 High-risk fertility behavior . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 107 Figure 8.1 Trends in infant mortality . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 99 Figure 8.2 Under-five mortality by selected background characteristics . . . . . . . . . . . . . . 101 xii * Tables and Figures Page CHAPTER 9 REPRODUCTIVE HEALTH AND CHILD CARE Table 9.1 Antenatal care . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 110 Table 9.2 Number of antenatal care visits and timing of first visit . . . . . . . . . . . . . . . . . 112 Table 9.3 Antenatal care content . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 113 Table 9.4 Place of antenatal care . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 114 Table 9.5 Tetanus toxoid injections . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 115 Table 9.6 Place of delivery . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 116 Table 9.7 Assistance during delivery . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 118 Table 9.8 Delivery characteristics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 120 Table 9.9 Postnatal care by background characteristics . . . . . . . . . . . . . . . . . . . . . . . . . 121 Table 9.10 Women’s status and reproductive health care . . . . . . . . . . . . . . . . . . . . . . . . . 122 Table 9.11 Vaccinations by source of information . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 123 Table 9.12 Vaccinations by background characteristics . . . . . . . . . . . . . . . . . . . . . . . . . . 124 Table 9.13 Vaccination trends . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 126 Table 9.14 Prevalence and treatment of symptoms of acute respiratory infection and fever . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 127 Table 9.15 Hand-washing materials in households . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 129 Table 9.16 Disposal of children's stools . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 130 Table 9.17 Prevalence of diarrhoea . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 131 Table 9.18 Knowledge of ORS packets . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 132 Table 9.19 Diarrhoea treatment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 133 Table 9.20 Feeding practices during diarrhoea . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 134 Table 9.21 Child health care by women’s status . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 135 Table 9.22 Perceived problem in accessing women's health care by background characteristics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 136 Table 9.23 Possession and use of mosquito nets . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 137 Table 9.24 Mosquito net age and insecticide treatment for mosquito nets . . . . . . . . . . . . 138 Table 9.25 Malaria prevention during pregnancy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 139 Table 9.26 Birth registration . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 141 Figure 9.1 Percentge of births for which women received medical assistance during delivery, by background characteristics . . . . . . . . . . . . . . . . . . . . . . . . 119 Figure 9.2 Percentage of children age 12-23 months who are fully vaccinated, by background characteristics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 125 Figure 9.3 Type of malaria tablets taken during pregnancy . . . . . . . . . . . . . . . . . . . . . . . 140 CHAPTER 10 WOMEN’S NUTRITIONAL STATUS Table 10.1 Initial breastfeeding . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 144 Table 10.2 Breastfeeding status by child's age . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 145 Table 10.3 Median duration and frequency of breastfeeding . . . . . . . . . . . . . . . . . . . . . . 146 Table 10.4 Foods consumed by children in the day or night preceding the interview . . . . 147 Table 10.5 Frequency of foods received by children in the day or night preceding the interview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 148 Table 10.6 Frequency of foods received by children in preceding seven days . . . . . . . . . . 149 Table 10.7 Iodisation of household salt . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 150 Tables and Figures * xiii Page Table 10.8 Micronutrient intake among children . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 151 Table 10.9 Micronutrient intake among mothers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 152 Table 10.10 Nutritional status of children . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 155 Table 10.11 Nutritional status of women . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 157 Table 10.12 Prevalence of anaemia in children . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 159 Table 10.13 Prevalence of anaemia in women . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 160 Table 10.14 Prevalence of anaemia in men . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 161 Table 10.15 Prevalence of anaemia in children by anaemia status of mother . . . . . . . . . . . 162 Table 10.16 Prevalence of vitamin A deficiency in children . . . . . . . . . . . . . . . . . . . . . . . . 164 Table 10.17 Prevalence of vitamin A deficiency in women . . . . . . . . . . . . . . . . . . . . . . . . . 165 Figure 10.1 Percentge of children under five with low height-for-age, low weight- for-height, and low weight-for-age, by age of child . . . . . . . . . . . . . . . . . . . . 156 CHAPTER 11 HIV/AIDS AND OTHER SEXUALLY TRANSMITTED INFECTIONS Table 11.1 Knowledge of ways to avoid HIV/AIDS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 168 Table 11.2.1 Knowledge of programmatically important ways to avoid HIV/AIDS: women 169 Table 11.2.2 Knowledge of programmatically important ways to avoid HIV/AIDS: men . . . 170 Table 11.3.1 Knowledge of AIDS-related issues: women . . . . . . . . . . . . . . . . . . . . . . . . . . 171 Table 11.3.2 Knowledge of AIDS-related issues: men . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 172 Table 11.4 Discussion of HIV/AIDS with partner . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 173 Table 11.5.1 Social aspects of HIV/AIDS prevention and mitigation: women . . . . . . . . . . . 175 Table 11.5.2 Social aspects of HIV/AIDS prevention and mitigation: men . . . . . . . . . . . . . 176 Table 11.6 Discussion of AIDS in the media . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 177 Table 11.7.1 Knowledge of symptoms of STIs: women . . . . . . . . . . . . . . . . . . . . . . . . . . . 178 Table 11.7.2 Knowledge of symptoms of STIs: men . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 179 Table 11.8.1 Self-reporting of sexually transmitted infections and STI symptoms: women . 180 Table 11.8.2 Self-reporting of sexually transmitted infections and STI symptoms: men . . . 181 Table 11.9 Source of treatment of STIs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 182 Table 11.10 Protection of partner by women with an STI . . . . . . . . . . . . . . . . . . . . . . . . . 183 Table 11.11 Number of sexual partners: married women and men . . . . . . . . . . . . . . . . . . 184 Table 11.12 Number of sexual partners: unmarried women and men . . . . . . . . . . . . . . . . 185 Table 11.13 Payment for sexual relations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 186 Table 11.14 Knowledge of source of male condoms and access to condoms . . . . . . . . . . . 187 Table 11.15.1 Use of condoms by type of partner: women . . . . . . . . . . . . . . . . . . . . . . . . . . 188 Table 11.15.2 Use of condoms by type of partner: women . . . . . . . . . . . . . . . . . . . . . . . . . . 189 Table 11.16.1 HIV/AIDS tests: women . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 190 Table 11.16.2 HIV/AIDS tests: men . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 191 Figure 11.1 Demand for HIV Testing Services by Background Characteristics: Women . . 192 Figure 11.2 Demand for HIV Testing Services by Background Characteristics: Men . . . . . 192 CHAPTER 12 ADULT MORTALITY Table 12.1 Data on siblings . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 196 xiv * Tables and Figures Page Table 12.2 Adult mortality rates . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 197 Table 12.3 Maternal mortality rates . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 198 APPENDIX A SAMPLE DESIGN Table A.1 Sample implementation: women . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 206 Table A.2 Sample implementation: men . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 207 APPENDIX B ESTIMATES OF SAMPLING ERRORS Table B.1 List of selected variables for sampling errors . . . . . . . . . . . . . . . . . . . . . . . . . 212 Table B.2 Sampling errors for selected variables: total sample . . . . . . . . . . . . . . . . . . . . 213 Table B.3 Sampling errors for selected variables: urban sample . . . . . . . . . . . . . . . . . . . 214 Table B.4 Sampling errors for selected variables: rural sample . . . . . . . . . . . . . . . . . . . . 215 Table B.5 Sampling errors for selected variables: Central Region . . . . . . . . . . . . . . . . . . 216 Table B.6 Sampling errors for selected variables: Eastern Region . . . . . . . . . . . . . . . . . . 217 Table B.7 Sampling errors for selected variables: Northern Region . . . . . . . . . . . . . . . . 218 Table B.7 Sampling errors for selected variables: Western Region . . . . . . . . . . . . . . . . . 219 APPENDIX C DATA QUALITY TABLES Table C.1 Household age distribution . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 221 Table C.2.1 Age distribution of eligible and interviewed women . . . . . . . . . . . . . . . . . . . . 222 Table C.2.2 Age distribution of eligible and interviewed men . . . . . . . . . . . . . . . . . . . . . . 222 Table C.3 Completeness of reporting . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 223 Table C.4 Births by calendar year since birth . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 224 Table C.5 Reporting of age at death in days . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 225 Table C.6 Reporting of age at death in months . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 226 APPENDIX F UNICEF WORLD SUMMIT FOR CHILDREN: END-DECADE INDICATORS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 333 Preface * xv PREFACE The 2000-2001 Uganda Demographic and Health Survey (UDHS) was the third national Demographic and Health Survey in a series that started in 1988, with the second conducted in 1995. The major objective of these surveys was to collect and analyse data on fertility, mortality, family planning, and health. Compared with the 1988-1989 UDHS and the 1995 UDHS, the present survey was significantly expanded in scope to include questions on gender issues, a malaria module, and blood testing for haemoglobin and vitamin A deficiency. Thus, the 2000-2001 UDHS will not only update the information from the 1995 UDHS but will also provide more detailed findings. In the past, Population and Housing Censuses were the only sources of demographic statistics in Uganda. The vital registration system in Uganda is still underdeveloped and has been revived in only a few pilot districts. The Uganda Demographic and Health Survey series is therefore an important alternative source of demographic and health statistics. The 2000-2001 UDHS was conducted in all of the districts of the country except four, namely, Bundibugyo, Gulu, Kasese, and Kitgum. This was a considerable improvement in coverage over the 1988-1989 UDHS, which excluded nine districts. However, this is less coverage than the 1995 UDHS, which excluded only Kitgum District. The staff of the Uganda Bureau of Statistics (UBOS) participated in the planning and implementation of this survey. In addition, many government departments contributed to the successful completion of the 2000-2001 UDHS and the timely publication of this report. The Ministry of Health provided experts who participated in the training of fieldworkers and drafted some of the chapters of the report. This contribution is very much appreciated. Special thanks go to the Population Secretariat for chairing and hosting all the meetings of the Steering Committee. The United States Agency for International Development (USAID) provided most of the funds for this survey. Additional funding was received from the United Nations Children’s Fund (UNICEF)/Uganda, the United Nations Population Fund (UNFPA)/Uganda and the British Department for International Development (DFID)/Uganda. ORC Macro provided technical support. We acknowledge and appreciate the generous support from these groups. We are grateful for the endeavours of government officials at all levels of administration that supported the survey. Finally, special gratitude goes to all the respondents for having spared their valuable time to attend to the interviews, which were sometimes lengthy, as well as for providing the blood samples. John B. Male-Mukasa Executive Director Uganda Bureau of Statistics Summary of Findings * xvii SUMMARY OF FINDINGS The 2000-2001 Uganda Demographic and Health Survey (UDHS) is a nationally represen- tative survey of 7,246 women age 15-49 and 1,962 men age 15-54. The main purpose of the 2000-2001 UDHS is to provide policy- makers and programme managers with de- tailed information on fertility; family planning; childhood and adult mortality; maternal and child health and nutrition; and knowledge of, attitudes about, and practices related to HIV/AIDS. The 2000-2001 UDHS is the third national sample survey of its kind to be under- taken in Uganda. The first survey was imple- mented in 1988-1989 and was followed by the 1995 UDHS. Caution needs to be exercised when analysing trends using the three UDHS data sets because of some differences in geo- graphic coverage. FERTILITY Constant Fertility. The UDHS results show that fertility in Uganda has remained station- ary in recent years. The total fertility rate (TFR) declined from 7.3 births per woman recorded in the 1988 survey to 6.9 births for the 1995 UDHS. Since then, the TFR has remained at the same level. The crude birth rate (CBR) from the 2000-2001 survey is 47 births per 1,000 population, essentially the same as that recorded in 1995 (48 births per 1,000 population). Large Fertility Differentials. Fertility varies enormously across subgroups of women. Fertility levels are much higher in rural areas (7.4 children per woman) than in urban areas (4.0 children per woman). The TFR is lowest in the Central Region (5.7 children per wom- an) and highest in the Northern Region (7.9 children per woman). Women who have attended secondary education have a much lower fertility (3.9 children per woman) than women with no education (7.8 children per woman), a difference of four children. Early Marriage. Although the minimum legal age for a woman to get married in Uganda is 18 years, the 2000-2001 UDHS results show that marriage is common among young girls. Among women age 20-49, 17 percent were married by age 15 and more than half were married by age 18. The median age at first marriage among women is just before 18 years and has been fairly stable for the past 30 years. Men generally marry about four years later than women. Women start having sexual relations earlier than men, with a difference of about two years. The median age at first intercourse for women 20-49 is 16.7 years. The median age for women shows no evidence of change over time, while that for men has increased slightly from 18.5 years among men currently age 50-54 to 19.4 years among men 25-29. Early Childbearing. Childbearing begins early in Uganda. Three in ten women age 15-19 are already mothers or pregnant with their first child. Teenage childbearing is closely related to a woman's education. Six in ten teenagers with no education have become mothers or are pregnant with their first child, compared to 33 percent of women with some primary educa- tion, and only 17 percent of those who attended secondary school. Polygyny. One in three married women in Uganda is in a polygynous relationship. The prevalence of polygynous unions increases with age; young women are less likely to be in a polygynous marriage than older women. Women who live in rural areas and in the Western Region are less likely than other women to be in a polygynous union. The pro- portion of women who are in a polygynous union in 2000-2001 is slightly higher than that recorded in 1995 (32 compared with 30 per- cent). xviii * Summary of Findings Birth Intervals. The median interval between births in Uganda is 29 months. Overall, 28 percent of births occur less than 24 months after a prior birth. The survival status of the previous birth has a strong impact on the birth interval. Median birth intervals for births that follow a child who died are five months short- er than those for births following a surviving child (25 months and 30 months, respectively). Desire for Smaller Families. The UDHS data indicate that the desire to stop childbearing among women has doubled since 1988. The percentage of married women who say that they want no more children or have been sterilised grew from 19 percent in 1988-1989 to 38 percent in 2000-2001. There has been a decline in the ideal family size among women in Uganda from 6.5 children in 1998-99 to 4.8 children in 2000-2001. Men want larger fami- lies than women, with an ideal number of 5.6 children. Respondents in rural areas, those who live in the Northern Region, and those with no education are more likely to want larger families than other respondents. Unplanned Fertility. Despite increasing use of contraception, the survey data show that unplanned pregnancies are still common in Uganda. One in four births in the five years prior to the survey were mistimed (wanted later), and 15 percent were not wanted at all. If unwanted births could be prevented, the total fertility rate in Uganda would be 5.3 births per woman instead of the actual level of 6.9. FERTILITY REGULATION Increasing Use of Contraception. Contracep- tive use among currently married women in Uganda has increased from 15 percent in 1995 to 23 percent in 2000-2001. Most of the increase is due to greater use of modern meth- ods (8 percent in 1995 compared with 18 percent in 2000-2001). The most widely used methods in 2000-2001 were injectables (6 percent), the lactational amenorrhoea method (4 percent), and the pill (3 percent). There has been a shift in method mix since 1995, when periodic abstinence, the pill, and inject- ables were the most widely used methods. Condom use has also increased from 1 percent in 1995 to 2 percent in 2000-2001. Large Differentials in Use of Contraception. There are large differences in the use of modern contraceptive methods across subgroups of married women. Use of modern family planning methods is much higher in urban areas than in rural areas (42 and 15 percent, respectively). Contraceptive use is highest in the Central Region (31 percent) and lowest in the Eastern Region (11 percent). Women with at least some secondary education are four times more likely than women with no education to use modern methods (42 percent and 9 percent, respec- tively). Contraceptive use in Uganda is posi- tively associated with the number of living children and women's socioeconomic status. In general, married women who live in DISH districts have higher than average contraceptive use rates, while those who live in CREHP dis- tricts have lower than average use rates. Among districts included in the DISH project, Kampala has the highest level of modern method use (50 perecnt), while districts classi- fied in Group I (Mbarara and Ntungamo) and in Group IV (Kamuli and Jinja) have the lowest modern contraceptive prevalence rate (10 to 15 percent). Source of Supply. Thirty-six percent of modern contraceptive users obtain their methods from a public source, while the private medical sector provides methods to 46 percent of users. Among sources in the public sector, hospitals and health centres are the most common sources (15 percent and 13 percent, respec- tively). There has been a significant shift in the source of family planning from that recorded in the 1995 UDHS. Public sources declined from 47 percent to 36 percent, while private medical sources increased from 42 percent to 46 per- cent. Family Planning Messages in Media. Radio is the most common source for receiving family Summary of Findings * xix planning messages (62 percent). One-third of women saw a family planning message on a billboard in the six months preceding the survey and about one-fifth were exposed to messages at community meetings. Three in ten women were not exposed to any family plan- ning message at all in the preceding six months. Urban women are much more likely than rural women to have heard or seen a family planning message in any of the mass media (89 versus 65 percent). Women in the Central Region and better educated women are the most likely to have been exposed to family planning messages. Unmet Need for Family Planning. Thirty-five percent of currently married women have an unmet need for family planning services—21 percent for spacing and 14 percent for limiting. If all the unmet need were satisfied, 57 percent of married women would be using contracep- tion. The level of unmet need for family plan- ning among currently married women in Uganda has increased from 29 percent in 1995. MATERNAL AND CHILD HEALTH Antenatal Care. Survey data show that antena- tal coverage is very high in Uganda. Women receive at least some antenatal care for more than nine in ten births. In most cases, antena- tal care is provided by a nurse or a midwife (83 percent). Doctors provide antenatal care to 9 percent of pregnant women, while the role of traditional birth attendants is insignificant. Only 42 percent of pregnant women make four or more antenatal care visits, while another 42 percent make only two or three visits. More- over, very few women receive antenatal care during the first trimester of pregnancy. The majority of women (70 percent) receive teta- nus toxoid vaccination during pregnancy, with 42 percent of the women receiving two or more doses of vaccine. Delivery Care. Only four in ten births in Ugan- da are assisted by a trained health worker, while 18 percent are assisted by a TBA (tradi- tional birth attendant) and 28 percent are assisted by a relative or friend. Fifteen percent of births are unassisted. Most births take place at home; only 37 percent of births occur in a health facility. Childhood Immunisation. Childhood vaccina- tion coverage has declined from 47 percent fully immunised in 1995 to 37 percent in 2000-2001. The decline in immunisation coverage has occurred for all types of vaccination. Some of the children who received vaccinationss did not receive them at the recommended time. Only 29 percent of children 12-23 months are fully vaccinated within the first 12 months. Childhood Illnesses. Acute respiratory infec- tions, diarrhoea, and malaria are common causes of child death. In the two weeks before the survey, 23 percent of children under five were ill with symptoms of acute respiratory infections. Two-thirds of these children were taken to a health facility. Twenty percent of children had diarrhoea in the two weeks pre- ceding the survey, 45 percent of whom were taken to a health care provider. A small major- ity of children with diarrhoea received oral rehydration therapy—oral rehydration salts, a recommended homemade fluid, or increased fluids in general. This means that many chil- dren are not receiving adequate fluids when they have diarrhoea. Malaria Control. Although use of insecticide- impregnated mosquito nets is a proven way of preventing malaria, only 13 percent of house- holds in Uganda have mosquito nets. Further- more, only 7 percent of children under five and 7 percent of pregnant women age 15-49 slept under a mosquito net the night before the survey. Breastfeeding. Breastfeeding is universally practiced in Uganda, with 98 percent of babies breastfed for at least some time. The median duration of breastfeeding is 22 months. How- ever, supplementation with other liquids and foods occurs too early in Uganda. Although the World Health Organisation recommends exclu- sive breastfeeding for the first six months, only 63 percent of Ugandan children under six months are exclusively breastfed. xx * Summary of Findings Perceived Problems in Accessing Health Care. In the 2000-2001 UDHS, women were asked whether they have problems seeking medical advice or treatment for themselves. The results show that 85 percent of women experience some kind of problem in accessing health care. The majority of women mentioned that getting money for treatment was a problem (63 per- cent). Other problems commonly cited include distance to a health facility (44 percent), having to take transport (43 percent), and the negative attitude of health care providers (42 percent). Birth Registration. Birth registration is one of the recognised rights of a child in Uganda today. Although registration became compul- sory in 1903, Uganda has never had a sound registration system for either statistical or legal purposes. Survey results indicate that coverage of birth registration in Uganda is poor, with only 4 percent of recent births reported by the mother to be registered. NUTRITIONAL STATUS Nutritional Status of Children. Survey data show that there has been little improvement since 1995 in children's nutritional status. Overall, 39 percent of Ugandan children under five years are classified as stunted (low height- for-age), 4 percent of children under five years are wasted (low weight-for-height), and 23 percent are underweight. Nutritional Status of Women. The mean height for Ugandan women is 158 centimetres (cm), which is similar to the mean height obtained in the 1995 UDHS. The cutoff point below which women are identified as short in stature is in the range of 140 to 150 cm. Two percent of women are less than 145 cm tall. Another measure of women's nutritional status is the body mass index (BMI), which is derived by dividing the weight in kilograms by the height in metres squared (kg/m2). A cutoff point of 18.5 has been recommended for defining chronic undernutrition. In the 2000-2001 UDHS, the mean BMI for women was 21.9, which falls within normal limits. Prevalence of Anaemia. Children and women are more likely to be affected by anaemia than men. A simple blood test performed as part of the survey found that 65 percent of children age 6-59 months are anaemic, while 30 percent of women age 15-49 and 18 percent of men age 15-54 are anaemic. Vitamin A. The 2000-2001 UDHS tested blood samples from women 15-49 and children under five years for level of vitamin A. Results of the analysis show that 28 percent of children 6-59 months in Uganda suffer from vitamin A defi- ciency (VAD). At this level, VAD in Uganda can be perceived as a severe public health problem. As expected, the prevalence of VAD is lower among children 6-11 months, when the children are still benefiting from the positive effect of breastfeeding. The highest prevalence of VAD is found among children 12-23 months (32 percent). VAD is also more common among children living in rural areas and in the North- ern Region. More than half of the women in Uganda suffer from VAD. The deficiency level in women varies according to the woman's characteristics, but not as much as in young children. As with children, rural women and women with no education are more likely than other women to have VAD. Pregnant and lactating women are not substantially different in VAD level from women who are neither pregnant nor breast- feeding. HIV/AIDS Knowledge of HIV/AIDS. In Uganda, HIV/AIDS has been termed a “household disease”, because nine in ten respondents of either sex knew personally of someone with HIV or who had died of AIDS. Although knowledge of AIDS in Uganda is universal, the level of awareness about the disease is not matched by the knowl- edge of ways to avoid contracting the virus. Summary of Findings * xxi The most commonly cited ways are using condoms (54 percent of women and 72 per- cent of men), abstaining from sexual relations (50 percent of women and 65 percent of men), and having only one sexual partner (49 per- cent of women and 43 percent of men). Knowledge of Mother-to-Child Transmission. Most men and women in Uganda know that HIV can be transmitted from mother to child. However, among the women who know about this mode of transmission, the quality of knowledge is uneven. Overall, 58 percent of women know that HIV can be transmitted during pregnancy, 69 percent know about transmission during delivery, and 46 percent know about transmission during breastfeeding. Levels of knowledge among men are similar. Knowledge of Symptoms of Sexually Transmit- ted Infections (STIs). STIs have been identified as cofactors in HIV/AIDS transmission. Almost half of women and one in four men either have no knowledge of STIs at all or are unable to recognise any symptoms of STIs in a man. Sixty-four percent of women know of some symptoms of STIs in women and 53 percent know of some symptoms in men. Knowledge of symptoms of STIs among men is generally higher than among women. Prevalence of STIs. Eight percent of women and 3 percent of men reported having had an STI in the 12 months preceding the survey. Given the low level of knowledge about symp- toms of STIs, many people may have STIs without knowing it. Therefore, the true level of prevalence of STIs could be higher than the reported one. The rate in 2000-2001 for women is higher than in 1995 (4 percent), but for men, it is lower than in 1995 (6 percent). HIV/AIDS testing. Eight percent of women and 12 percent of men report that they have been tested for HIV. Women in their twenties and men age 25-39 are the most likely to have had the test. This test is much more common among respondents living in urban areas, in the Central Region, and in Kampala district and among those who have secondary educa- tion. Desire to be tested and desire to know the outcome of the test is high among women and men in Uganda. Respondents living in rural areas and in the Northern Region, those who have primary education, and those who have never married but have had sex are more likely to want to be tested. Nine in ten women and men who were tested for HIV received the test results. MORTALITY Infant and Child Mortality. At current mortality levels, 152 out of every 1,000 children born in Uganda die before their fifth birthday, 88 of whom die during the first year of life. Results from the 2000-2001 UDHS show no evidence of improvement in infant and childhood mortality in recent years. There are considerable variations in mortality by residence and region. Childhood mortality rates in urban areas are substantially lower than in rural areas. Under-five mortality is lowest in the Central Region (135 per 1,000 live births) and is highest in the Northern Region (178 per 1,000 live births). Under-five mortality among children born to mothers with no education is highest (187 per 1,000 live births), while chil- dren born to mothers with secondary education have by far the lowest mortality (93 per 1,000 births). The household's wealth status is nega- tively associated with childhood mortality. For all measures, children in the highest quintile have the lowest mortality rates, while those in the lowest quintile have the highest mortality rates. Adult Mortality. The mortality rate for the ten- year period before the 2000-2001 UDHS is 9 deaths per 1,000 females and 10 deaths per 1,000 males. Comparison with the adult mortal- ity experience in the ten years before the 1995 UDHS reveals that the situation has not im- proved in the past five years. Similarly, the maternal mortality ratio has remained at the same level as that recorded in 1995 (504 in the 2000-2001 UDHS compared with 527 deaths per 100,000 live births in the 1995 UDHS). Introduction * 1 INTRODUCTION 1 1.1 GEOGRAPHY AND ECONOMY The Republic of Uganda is located in East Africa and lies astride the equator. It is a landlocked country bordering Kenya in the east, Tanzania in the south, Rwanda in the southwest, the Democratic Republic of Congo in the west, and Sudan in the north. The country has an area of 241,039 square kilometres and is administratively divided into 56 districts (45 at the time of the survey). Uganda has a decentralised system of governance and several functions have been ceded to the local governments. However, the central government retains the role of making policy, setting standards, and supervising. National security is also the role of the central government. Uganda has a favourable climate because of its relatively high altitude. The Central, Eastern, and Western regions of the country have two rainy seasons per year, with heavy rains from March to May and light rains between September and December. The level of rainfall decreases towards the north, turning into just one rainy season a year. The soil fertility varies accordingly, being generally fertile in the Central and Western regions and becoming less fertile as one moves to the east and the north. Due to these combinations of climatic conditions, Uganda varies between tropical rain forest vegetation in the south and savannah woodlands and semidesert vegetation in the north. These climatic conditions determine the agricultural potential and thus the land’s population-carrying capacity, with high population densities in the Central and Western regions and declining densities towards the north. The economy is predominantly agricultural with the majority of the population dependent on subsistence farming and light agro-based industries. The country is self-sufficient in food, although the distribution is uneven over all areas. Coffee, tea, and cotton are the major earners of Uganda’s foreign exchange. During the period immediately following independence, from 1962 to 1970, Uganda had a flourishing economy with a gross domestic product (GDP) growth rate of 5 percent per annum, compared with a population growth rate of 2.6 percent per annum. However, in the 1970s through the early 1980s, Uganda faced a period of civil and military unrest, resulting in the destruction of the economic and social infrastructure. This seriously affected the growth of the economy and the provision of social services such as education and health care. Since 1986, however, the government has introduced and implemented several reform programmes that have steadily reversed the setbacks and aimed the country towards economic prosperity. Consequently, between 1996 and 2000, the country’s real GDP grew at an average rate of 6.2 percent per annum. This is far higher than the population growth rate, which was estimated at 2.9 percent. The GDP per capita grew at a rate of 2.6 percent per annum. 1.2 POPULATION In the past, most demographic statistics in Uganda were derived from population censuses, which started in 1948. Subsequent censuses have been held in 1959, 1969, 1980, and 1991. In addition, Demographic and Health Surveys (DHS) have been conducted in 1988-1989, 1995, and 2000-2001, the subject of the present report. Additional demographic data have been obtained from small-scale surveys devoted to specific subjects. 2 * Introduction Table 1.1 Demographic characteristics Selected demographic indicators, Population Censuses 1948-1991___________________________________________________________________________ Census year____________________________________________ Indicator 1948 1959 1969 1980 1991___________________________________________________________________________ Population (thousands) Intercensal growth rate Sex ratio Crude birth rate Total fertility rate Crude death rate Infant mortality rate Percent urban Density (pop/sq km) 4,958.5 6,536.6 9,535.1 12,636.2 16,671.7 na 2.5 3.9 2.7 2.5 100.2 100.9 101.9 98.2 96.5 42.0 44.0 50.0 50.0 52.0 5.9 5.9 7.1 7.2 7.1 25.0 20.0 19.0 na 17.0 200.0 160.0 120.0 na 122.0 na 4.8 7.8 8.7 11.3 25.2 33.2 48.4 64.4 85.0 ___________________________________________________________________________ Source: Statistics Department, 1995:27, 56, 139 na = Not applicable Civil registration was made compulsory in Uganda in 1973. However, its coverage is incomplete and is therefore unsatisfactory as a source of demographic statistics. Efforts to streamline the system were made between 1974 and 1978, but the achievements that were realised were later frustrated by the economic and civil instability mentioned above. Since 1995, an attempt has been made to revive the civil registration system in the country, but thus far, it has not reached a satisfactory level. Table 1.1 presents several demographic indices compiled from the population censuses of 1948 through 1991. The table shows that over that period, the population increased more than threefold. This represents an average annual growth rate of 2.9 percent. The high growth rate is brought about by high fertility and declining mortality levels. The level of urbanisation is still low but has been increasing over time. In 1991, a little more than 10 percent of the population lived in urban areas. Up to the late 1960s, there were more males than females in Uganda. This was mainly due to large numbers of male immigrants who came to the country to work at factories and plantations. In the mid-1970s these migrants left because of the deteriorating economic situation. Since then, the number of females exceeds that of males. 1.3 NATIONAL POPULATION AND HEALTH PROGRAMMES Uganda has instituted several policies to help improve the health status and life of its people. In 1995, Uganda adopted the National Population Policy for Sustainable Development. The policy document noted that indices of general health care are still unsatisfactory. Thus, the policy’s overall goal is to influence future demographic trends and patterns in desirable directions to improve the quality of life and standard of living of the people. In particular, the policy aims to reduce infant and child mortality, maternal mortality, and fertility and to increase the life expectancy of the population. The policy also aims to increase levels of full immunisation among children, increase levels of supervised deliveries, and increase the contraceptive prevalence rate. The National Reproductive Health Policy Guidelines for Reproductive Health Services state that the country’s priorities are “safe motherhood including post-abortion care, family planning, adolescent sexual and reproductive health, STIs including HIV/AIDS, reproductive organ cancer, and gender practices that perpetuate poor reproductive behaviour.” Introduction * 3 Other policies that indirectly impinge on population and health include the Adolescent Sexual and Reproductive Health Policy, the Nutrition Policy, the Framework for HIV/AIDS Activities in Uganda, Universal Primary Education, the Gender Policy, the Poverty Eradication Action Plan ,the Decentralisation Policy, the Liberalisation and Privatisation Policies, and the Plan for the Modernisation of Agriculture. To achieve the targets of these policies, the government, with the help of development partners, is implementing several population and reproductive health programmes in the country aimed at influencing the behaviour of the population. 1.4 OBJECTIVES OF THE SURVEY The 2000-2001 Uganda Demographic and Health Survey (UDHS) was designed to provide information on demographic, health, and family planning status and trends in the country. Specifically, the UDHS collected information on fertility levels, marriage, sexual activity, fertility preferences, awareness and use of family planning methods, and breastfeeding practices. In addition, data were collected on the nutritional status of mothers and young children; infant, child, adult, and maternal mortality; maternal and child health; awareness and behaviour regarding HIV/AIDS and other sexually transmitted infections; and levels of haemoglobin and vitamin A in the blood. The 2000-2001 UDHS is a follow-up to the 1988-1989 and 1995 UDHS surveys, which were also implemented by the Uganda Bureau of Statistics (UBOS, previously the Department of Statistics). The 2000-2001 UDHS is significantly expanded in scope but also provides updated estimates of basic demographic and health indicators covered in the earlier surveys. The specific objectives of the 2000-2001 UDHS are as follows: C To collect data at the national level that will allow the calculation of demographic rates, particularly the fertility and infant mortality rates C To analyse the direct and indirect factors that determine the level and trends in fertility and mortality C To measure the level of contraceptive knowledge and practice of women and men by method, by urban-rural residence, and by region C To collect data on knowledge and attitudes of women and men about sexually transmitted infections and HIV/AIDS, and to evaluate patterns of recent behaviour regarding condom use C To assess the nutritional status of children under age five and women by means of anthropometric measurements (weight and height), and to assess child feeding practices C To collect data on family health, including immunisations, prevalence and treatment of diarrhoea and other diseases among children under five, antenatal visits, assistance at delivery, and breastfeeding C To measure levels of haemoglobin and vitamin A in the blood of women and children C To collect information on the extent of child labour. 1 The number of districts has since increased to 56. The newly formed districts are Kayunga and Wakiso in the Central Region; Kaberamaido, Mayuge, and Sironko in the Eastern Region; Pader, Nakapiripirit, and Yumbe in the Northern Region; and Kanungu, Kamwenge, and Kyenjojo in the Western Region. 4 * Introduction 1.5 ORGANISATION OF THE SURVEY Sample Design and Implementation The sample was drawn through a two-stage design. The first-stage sample frame for this survey is the list of enumeration areas (EAs) compiled from the 1991 Population Census. In this frame, the EAs are grouped by parish within a subcounty, by subcounty within a county, and by county within a district. A total of 298 EAs (102 in urban areas and 196 in rural areas) were selected. Urban areas and districts included in the Delivery of Improved Services for Health (DISH) project and the Community Reproductive Health Project (CREHP) were oversampled in order to produce estimates for these segments of the population. Within each selected EA, a complete household listing was done to provide the basis for the second-stage sampling. The number of households to be selected in each sampled EA was allocated proportionally to the number of households in the EA. It was not possible to cover all districts in the country because of security problems in a few areas. The survey was hence limited to 41 out of the then 45 districts in the country,1 excluding the districts of Kasese and Bundibugyo in the Western Region and Gulu and Kitgum in the Northern Region. These districts cover approximately 5 percent of the total population. The sample for the 2000-2001 UDHS was aimed at providing reliable estimates of important indicators for the population of Uganda at the national level (less the excluded districts), for urban and rural areas, and for each of the four regions in Uganda defined as— Central: Kalangala, Kampala, Kiboga, Luwero, Masaka, Mpigi, Mubende, Mukono, Sembabule, Nakasongola, and Rakai Eastern: Bugiri, Busia, Iganga, Jinja, Kamuli, Kapchorwa, Katakwi, Kumi, Mbale, Pallisa, Soroti, and Tororo Northern: Adjumani, Apac, Arua, Kotido, Lira, Moyo, Moroto, and Nebbi Western: Bushenyi, Hoima, Kabale, Kabarole, Kibaale, Kisoro, Masindi, Mbarara, Ntungamo, and Rukungiri. The sample was also designed to generate estimates of contraceptive prevalence rates for the districts in the DISH project funded by the United States Agency for International Development (USAID) and districts in the CREHP project. These districts are grouped in six subdomains, namely, the following: Introduction * 5 DISH districts: Group I: Mbarara and Ntungamo Group II: Masaka, Rakai, and Sembabule Group III: Luwero, Masindi, and Nakasongola Group IV: Jinja and Kamuli Group V: Kampala CREHP districts: Kabale, Kisoro, and Rukungiri. In each group, a minimum of 500 completed interviews with women was targeted to allow for separate estimates. Consequently, data for Kampala District can be presented separately because it has more than the specified minimum number of completed interviews. The 2000-2001 UDHS covered the same EAs as were covered by the 1995 UDHS. However, a new list of households within the EA was compiled and the sample households were not necessarily the same as those selected in 1995. In the case of the CREHP districts (Kabale, Kisoro and Rukungiri), five extra EAs were selected to generate a sample size sufficient to allow independent estimates. Because the 1995 and 2000-2001 UDHS did not cover the same geographical areas, the two surveys are not exactly comparable. Details of the UDHS sample design are provided in Appendix A and estimations of sampling errors are included in Appendix B. Questionnaires Three questionnaires were used for the 2000-2001 UDHS, namely, the Household Questionnaire, the Women’s Questionnaire, and the Men’s Questionnaire. The contents of these questionnaires were based on the MEASURE DHS+ Model “B” Questionnaire, which was developed for use in countries with a low level of contraceptive use. In consultation with technical institutions and local organisations, UBOS modified these questionnaires to reflect relevant issues in population, family planning, and other health issues in Uganda. The revised questionnaires were translated from English into six major languages, namely, Ateso, Luganda, Lugbara, Luo, Runyankole/Rukiga, and Runyoro/Rutoro. The questionnaires were pretested prior to their finalisation. The pretest training took place from June 14 to July 8, 2000. For this exercise, seven women and seven men were trained to be interviewers, forming seven teams of one woman and one man each. Each team was assigned to test the questionnaires in one of the seven language groups (including English) into which the questionnaires had been translated. Three nurses were recruited to participate in the anemia testing exercise as health technicians. The pretest fieldwork was conducted during a one-week period (July 10-16, 2000). The Household Questionnaire was used to list all the usual members and visitors in selected households. Some basic information was collected on the characteristics of each person listed, including his or her age, sex, education, and relationship to the head of the household. The main purpose of the Household Questionnaire was to identify women and men who were eligible for the individual interview. In addition, the Household Questionnaire collected information on 6 * Introduction characteristics of the household’s dwelling unit, such as the source of water, type of toilet facilities, materials used for the floor of the house, and ownership of various durable goods. It also included questions that were designed to assess the extent of child labour and that were used to record the height and weight and the haemoglobin level of women 15-49 and children under the age of five. In households selected for the male survey, the haemoglobin level of men eligible for the individual interview was also recorded. The Women’s Questionnaire was used to collect information from all women age 15-49. These women were asked questions on topics related to their background, childbearing experience and preferences, marriage and sexual activity, employment, maternal and child care, and awareness and behaviour regarding AIDS and other sexually transmitted infections (STIs). Information necessary for the calculation of adult mortality including maternal mortality was also included in the Women’s Questionnaire. The Men’s Questionnaire was administered to all men age 15-54 living in every third household in the UDHS sample. The Men’s Questionnaire collected much of the same information found in the Women’s Questionnaire but was shorter because it did not contain questions on reproductive history, maternal and child health, nutrition, and maternal mortality. The questionnaires used in the UDHS are presented in Appendix E. The decision to include vitamin A testing was made rather late in the survey design process. As a result, ORC Macro and UBOS staff organized a special pretest of the vitamin A testing procedures shortly before the main training for the survey. Although there were some concerns about response rates, the pretest indicated that it was feasible to incorporate vitamin A testing into the UDHS. Therefore, ORC Macro staff and UBOS staff and consultants proceeded to develop a special set of training materials for the vitamin A testing. Training and Fieldwork A total of 70 interview staff (52 women and 18 men) was trained over a three-week period from August 23, 2000 to September 16, 2000. The trainers included the UBOS staff, guest lecturers, and consultants from ORC Macro. The training was conducted following the DHS training procedures, including class presentations, mock interviews, field practice, and tests. All of the participants were trained using the Household and Women’s Questionnaires. After training on the Women’s Questionnaire was completed, the male participants were trained separately in conducting an interview using the Men’s Questionnaire. The training included practice interviews using the questionnaire in English and the participant’s local language. A separate training was conducted for the 13 medical personnel who were designated as the team health technicians. This included training on parts of the Household Questionnaire that pertained to their tasks, taking blood samples from the subjects, using the HemoCue machine, and storing dry blood spots (DBS) samples. A one-day joint training session was conducted for all the field staff in taking the height and weight measurements of women and children. The interviewing team members were trained in anthropometric measurements so that in case the need arose, they could be called upon to assist the team’s health technician in performing these tasks. Eleven interviewing teams carried out data collection for the 2000-2001 UDHS. Each team consisted of one team supervisor, one field editor, one health technician, three or four female Introduction * 7 Table 1.2 Results of the household and individual interviews Number of households, number of interviews, and response rates, accord- ing to urban-rural residence, Uganda 2000-2001_____________________________________________________________ Residence_________________ Result Urban Rural Total_____________________________________________________________ Household interviews Households sampled Households found Households interviewed Household response rate Individual interviews: women Number of eligible women Number of eligible women interviewed Eligible woman response rate Individual interviews: men Number of eligible men Number of eligible men interviewed Eligible man response rate 2,912 5,880 8,792 2,704 5,530 8,234 2,499 5,386 7,885 92.4 97.4 95.8 2,636 5,081 7,717 2,416 4,830 7,246 91.7 95.1 93.9 775 1,531 2,306 601 1,361 1,962 77.5 88.9 85.1 interviewers, one male interviewer, and one driver. The actual data collection took place over a five- month period, from September 28, 2000 to March 3, 2001. Seven staff members from UBOS coordinated and supervised fieldwork activities. ORC Macro participated in field supervision for interviews and measurements. Two additional persons were hired to supervise the collection of blood samples for vitamin A testing. Data Processing All questionnaires for the UDHS were returned to the UBOS offices in Entebbe for data processing, which consisted of office editing, coding of open-ended questions, data entry, and editing computer-identified errors. A team of eight data entry clerks, an office editor, and two data entry supervisors processed the data. Data entry and editing started on October 19, 2000. In January 2001, when it was noted that the data processing pace was lagging behind data collection, another shift was added to the data processing team. The evening shift was also composed of eight people (working four hours per day). In addition, both shifts worked for four hours each on Saturdays. 1.6 RESPONSE RATES Table 1.2 shows response rates for the 2000-2001 UDHS. A total of 8,792 households were selected in the sample, of which 8,234 were occupied. The short fall was largely due to structures that were found to be vacant. Of the existing households, 7,885 were successfully interviewed, yielding a household response rate of 96 percent. 8 * Introduction In the successfully interviewed households, 7,717 women were identified for the individual interview, and of these, 7,246 were successfully interviewed, yielding a response rate of 94 percent. In a subsample of households, 2,306 eligible men were identified for the individual interview, of which 1,962 were successfully interviewed, yielding a response rate of 85 percent. The overall response rates for women and men were 90 percent and 82 percent, respectively. Rural response rates were higher than urban rates. The principal reason for nonresponse among both eligible men and women was the failure to find them at home despite repeated visits to the household. The lower response rate for men was due to their more frequent and longer absence from the household. The refusal rate in the 2000-2001 UDHS was slightly more than 1 percent each for women and men. 1 A household was defined as a person or group of persons that usually lives and eats together. Characteristics of Households and Household Members * 9 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 urban-rural residence, Uganda 2000-2001____________________________________________________________________________________________________ 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 + Missing/DK Total Number 17.3 15.9 16.6 21.2 19.8 20.5 20.7 19.3 20.0 14.4 14.1 14.2 18.1 17.1 17.6 17.7 16.7 17.2 12.6 13.8 13.2 15.7 14.7 15.2 15.3 14.6 15.0 11.3 13.6 12.5 9.1 8.7 8.9 9.4 9.3 9.4 11.0 12.7 11.9 6.0 7.7 6.9 6.6 8.3 7.5 10.4 9.9 10.1 6.0 6.9 6.5 6.5 7.3 6.9 7.7 6.2 6.9 5.5 5.3 5.4 5.8 5.4 5.6 5.4 4.7 5.0 4.0 4.3 4.2 4.2 4.4 4.3 2.9 2.6 2.8 3.0 3.1 3.1 3.0 3.1 3.0 2.8 1.8 2.2 2.5 2.4 2.4 2.6 2.3 2.4 1.3 1.8 1.6 1.9 2.8 2.3 1.8 2.6 2.3 0.8 0.6 0.7 1.7 1.9 1.8 1.6 1.7 1.7 0.7 0.8 0.8 1.7 2.0 1.8 1.6 1.8 1.7 0.6 0.6 0.6 1.3 1.1 1.2 1.2 1.1 1.1 0.4 0.4 0.4 0.9 1.2 1.1 0.8 1.1 1.0 0.1 0.2 0.2 0.7 0.4 0.5 0.6 0.3 0.5 0.2 0.3 0.2 0.7 0.5 0.6 0.6 0.5 0.6 0.2 0.0 0.1 0.0 0.0 0.0 0.0 0.0 0.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 2,221 2,453 4,674 15,436 16,418 31,855 17,657 18,871 36,528 __________________________________________________________________________________________________ Note: Table is based on the de facto population, i.e., persons who stayed in the household the night before the interview. 2CHARACTERISTICS OF HOUSEHOLDSAND HOUSEHOLD MEMBERS This chapter presents information on some of the socioeconomic characteristics of the household1 population and the individual survey respondents, such as age, sex, marital status, religion, urban-rural residence, and regional distribution. This chapter also considers the conditions of the households in which the survey population lives, including source of drinking water, availability of electricity, sanitation facilities, building materials, and possession of household durable goods. 2.1 POPULATION BY AGE AND SEX The 2000-2001 UDHS included a Household Questionnaire, which was used to elicit information on the socioeconomic characteristics of usual residents and visitors who had spent the previous night in the selected households. Table 2.1 shows the reported distribution of the household population in five-year age groups, by sex and urban-rural residence. The data show that there are slightly more women than men, with women constituting 52 percent of the population and men constituting 48 percent. The 10 * Characteristics of Households and Household Members sex composition of the population does not show significant variation by urban-rural residence. The table further depicts Uganda as a young population, with a large proportion of the population being in the younger age groups. The population under age 15 constitutes 52 percent of the total population. The older age groups are very small in comparison, as can be seen in the population pyramid (Figure 2.1). This type of age structure has a built-in momentum for the growth of the country’s population. When the young population eventually reaches reproductive age, the result will be a high population growth rate for some years to come. The data show an unexpected bulge in the proportion of women age 50-54. This is most likely due to women age 45-49 being deliberately pushed to the 50-54 age group to reduce the workload of the interviewer. There is also an unusually large number of girls age 14 relative to the number age 15 (see Appendix Table C.1), which is presumably due to the same phenomenon. This pattern has been observed in other DHS surveys (Rutstein and Bicego, 1990), but given the levels observed in the UDHS 2000-2001, its effect on the overall results is considered negligible. Characteristics of Households and Household Members * 11 Table 2.2 Household composition Percent distribution of households by sex of head of household and by household size, according to residence, Uganda 2000-2001________________________________________ 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 69.2 73.0 72.5 30.8 27.0 27.5 100.0 100.0 100.0 16.4 10.1 11.0 16.1 11.0 11.8 15.0 12.6 12.9 15.5 14.6 14.8 11.2 14.2 13.8 8.8 11.8 11.4 5.6 8.9 8.4 3.5 6.2 5.8 7.8 10.4 10.0 100.0 100.0 100.0 4.2 4.9 4.8 2.2 HOUSEHOLD COMPOSITION The headship and composition of households is presented in Table 2.2. Nearly three in four households are headed by males, while one in four are headed by women. The proportion of female-headed households is slightly higher in urban areas than in rural areas (31 percent and 27 percent, respectively). One in every nine households has only one member. However, very large households (nine persons or more) still exist in Uganda. Even in urban areas, which tend to have smaller household sizes than rural areas, 8 percent of the households have nine or more persons. In urban areas, 33 percent of the households have one or two members, compared with 21 percent in rural areas. Rural areas have consistently higher percent- ages of larger households (five persons or more) than urban areas. Table 2.2 shows that the mean household size is 4.8 persons. This is similar to the figure obtained from the 1991 Population and Housing Census and the 1995 UDHS (Statistics Department and Macro International Inc., 1996). The mean household size is larger in rural areas (4.9 persons) than in urban areas (4.2 persons). 2.3 FOSTERHOOD AND ORPHANHOOD In Uganda, a child is defined as a person less than 18 years old, while some countries classify a child as a person under 15 years old. Information on fosterhood and orphanhood of children under both definitions is presented in Table 2.3. Overall, 58 percent of children under 18 years of age are living with both their parents, while 18 percent are living with neither their natural father nor natural mother. The bulk of children living with only one parent are living with the mother (17 percent), compared with only 6 percent living with only the father. Among children under 15 years of age, the percentage living with both parents is slightly higher (60 percent), while the percentage living with neither parent is 16 percent. In Uganda, an orphan is defined as a child under 18 years old who has lost at least one of his/her biological parents. Fourteen percent of children under 18 years of age are orphans. Among these, 3 percent are those who have lost both parents, 8 percent have lost their father only, and 3 percent have lost their mother only. The corresponding percentage of children under 15 years of age who have been orphaned is 12 percent. Although orphanhood levels increase with age, there are no significant differentials in orphanhood and fostering levels according to the child’s sex and residence. However, fewer urban children and children in the Central Region live with both their natural parents. 12 * Characteristics of Households and Household Members Table 2.3 Children’s living arrangements Percent distribution of de jure children under age 18 by survival status of parents and children's living arrangements, according to background characteristics, Uganda 2000-2001____________________________________________________________________________________________________________ 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 0-2 2-5 6-9 10-14 Sex Male Female Residence Urban Rural Region Central Eastern Northern Western Total Total 0-14 77.2 15.9 1.6 0.8 0.1 2.9 0.3 0.2 0.2 0.8 100.0 4,498 67.2 13.1 3.3 3.2 0.5 8.6 1.0 1.6 0.9 0.6 100.0 4,068 55.3 11.5 5.2 4.8 1.8 13.2 1.6 2.9 2.4 1.2 100.0 5,317 40.3 7.8 10.3 4.8 3.2 15.1 3.9 5.3 5.5 3.7 100.0 2,218 59.8 11.9 5.1 4.3 1.7 9.2 1.6 2.8 2.6 1.2 100.0 10,816 56.9 11.9 5.5 3.8 1.5 11.6 1.9 2.8 2.6 1.4 100.0 10,941 46.8 14.0 5.4 6.3 2.0 13.0 2.2 4.6 4.2 1.5 100.0 2,521 59.8 11.6 5.3 3.7 1.5 10.1 1.6 2.6 2.4 1.3 100.0 19,236 48.9 12.2 5.4 5.7 2.3 13.1 2.6 4.4 3.9 1.5 100.0 6,594 62.8 10.9 3.4 4.7 0.7 11.1 0.9 2.2 1.9 1.4 100.0 6,282 61.4 14.4 6.1 2.9 1.0 7.6 1.4 2.0 2.1 1.1 100.0 3,428 62.7 11.1 6.8 2.0 2.1 8.2 1.8 2.3 2.0 1.0 100.0 5,453 58.3 11.9 5.3 4.0 1.6 10.4 1.7 2.8 2.6 1.3 100.0 21,757 60.4 12.4 4.7 4.0 1.4 9.9 1.5 2.5 2.3 1.0 100.0 19,539 2.4 EDUCATIONAL LEVEL OF HOUSEHOLD POPULATION Education affects many aspects of life, including individual demographic and health behaviour. Studies have shown that educational level is strongly associated with contraceptive use; fertility; and the health, morbidity, and mortality of children. In each household, for all persons age four or older, data were collected on the highest level of education attended and the highest class completed at that level. For comparison with data from previous UDHS surveys, Table 2.4 shows the distribution of female and male household members age six and above by the highest level of education ever attended (although not necessarily completed) and the median number of years of education completed according to background characteristics. One in four children age 4-5 has started school, with insignificant differences found between boys and girls. Overall, 15 percent are in preschool and 9 percent are in primary school (data not shown). More than one in four females (27 percent) age six and above in Uganda have never been to school, compared with only 15 percent of males. In all age groups except the youngest, males are less likely to have no education and more likely to have attained some secondary education than females. The proportion of boys and girls age 6-9 and 10-14 with no education is similar, which may be attributed to the Universal Primary Education programme introduced in 1997 for children under 15. Among older men and women, significant differentials in educational attainment between the sexes are observed. However, data in Table 2.4 show that sex differentials in education have been narrowing over time and the differences in educational attainment between school-age boys and girls have become insignificant. Characteristics of Households and Household Members * 13 Table 2.4 Educational attainment of household population Percent distribution of the de facto male and female household populations age six and over by highest level of education attended, according to background characteristics, Uganda 2000-2001________________________________________________________________________________________________________ Level of education _________________________________________________ More No Com- Some Completed than Don't Median Background educa- Some pleted second- second- second- know/ number characteristic tion primary primary ary ary ary missing Total Number of years__________________________________________________________________________________________________________ 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 Central Eastern Northern Western Total 34.6 65.1 0.0 0.0 0.0 0.0 0.3 100.0 2,551 0.0 3.6 90.2 5.1 1.0 0.0 0.0 0.1 100.0 2,705 2.4 3.2 53.7 20.0 22.4 0.2 0.3 0.2 100.0 1,661 5.3 7.4 47.7 12.6 23.0 2.6 5.6 1.2 100.0 1,171 5.7 7.0 46.8 12.3 21.5 2.8 8.2 1.5 100.0 1,149 5.6 9.1 46.7 13.0 18.3 1.6 9.2 2.1 100.0 1,019 5.5 13.9 45.6 10.7 16.4 2.5 9.3 1.6 100.0 739 5.4 15.8 43.9 12.2 17.2 1.8 7.2 1.9 100.0 524 5.5 14.6 50.0 8.8 16.3 1.0 7.0 2.2 100.0 450 5.2 14.6 46.6 13.6 14.8 0.1 7.9 2.4 100.0 322 5.1 21.4 42.9 12.4 13.6 0.6 7.5 1.6 100.0 282 4.2 32.0 43.3 12.1 9.6 0.0 2.2 0.8 100.0 277 2.9 52.0 34.4 5.3 4.0 0.3 1.7 2.3 100.0 579 0.0 8.2 40.6 7.4 25.7 3.6 12.0 2.4 100.0 1,775 6.0 16.3 62.0 9.3 9.1 0.5 2.1 0.7 100.0 11,661 2.8 14.0 53.5 8.2 14.9 1.8 5.3 2.2 100.0 4,322 3.8 11.4 62.1 10.7 12.1 0.4 3.0 0.4 100.0 3,639 3.2 19.7 58.4 10.2 8.5 0.3 2.5 0.5 100.0 2,066 2.7 18.2 63.6 7.7 7.7 0.5 2.0 0.3 100.0 3,410 2.5 15.2 59.1 9.1 11.3 0.9 3.4 1.0 100.0 13,436 3.1 _________________________________________________________________________________________________________ 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 Central Eastern Northern Western Total 32.6 67.3 0.0 0.0 0.0 0.0 0.0 100.0 2,611 0.0 4.6 88.0 6.4 0.9 0.0 0.0 0.1 100.0 2,756 2.5 9.9 49.9 16.1 22.9 0.4 0.6 0.2 100.0 1,755 5.0 15.9 50.3 11.7 15.7 1.2 4.7 0.4 100.0 1,574 4.4 22.6 47.7 9.7 14.4 0.4 5.0 0.2 100.0 1,380 4.0 25.9 49.0 10.8 9.5 0.4 3.6 0.8 100.0 1,028 3.0 32.1 46.7 8.5 7.4 0.3 4.5 0.6 100.0 824 2.5 33.8 47.1 7.7 8.4 0.0 2.3 0.8 100.0 579 2.4 46.1 38.5 6.2 6.1 0.0 2.0 1.1 100.0 430 0.7 59.7 28.2 4.2 6.0 0.0 0.8 1.2 100.0 500 0.0 69.0 23.9 3.3 1.2 0.0 2.0 0.7 100.0 328 0.0 77.1 18.6 1.7 0.0 0.0 1.1 1.6 100.0 342 0.0 79.8 16.6 1.7 0.5 0.0 0.5 0.9 100.0 565 0.0 11.7 46.1 9.6 22.1 1.4 8.2 0.8 100.0 1,993 5.2 28.8 57.5 7.0 5.5 0.1 0.8 0.3 100.0 12,687 1.6 19.4 53.2 9.0 13.5 0.6 3.5 0.8 100.0 4,628 3.3 23.3 60.3 8.3 6.6 0.1 1.3 0.2 100.0 4,053 2.0 39.4 50.7 5.3 3.4 0.1 0.8 0.3 100.0 2,272 0.5 30.9 57.7 5.5 4.6 0.2 0.9 0.2 100.0 3,727 1.4 26.5 55.9 7.3 7.8 0.3 1.8 0.4 100.0 14,680 1.9 __________________________________________________________________________________________________________ Note: Totals include eight men and six women for whom age is missing. An asterisk indicates that a figure has been suppressed because it is based on fewer than 25 respondents. 14 * Characteristics of Households and Household Members The percentage of both males and females who have never attended school increases steadily with age. Among females, this proportion decreases from 80 percent in the oldest age group (65 years or more) to 5 percent among those age 10-14. The decline is slightly less drastic among males, from 52 percent to 4 percent, respectively. It is worth noting that despite the existence of the UPE programme, about one-third of girls and boys age 6-9 years have never been to school. This could be attributed to hindrances like long distances to the nearest school and parents who consider these children to be too young to start schooling. Another possible factor is that the UDHS mostly occurred in the last few months of 2000, and children who turned age six may have been waiting to enter the school year that began in January 2001. Levels of educational attainment are higher in urban areas than in rural areas. The percentage with no education is lower and the percentage with secondary education is higher in urban areas than in rural areas. Similarly, the median number of years of schooling is higher in urban areas than in rural areas. Whereas women show wide variations across regions, educational levels of men are less varied. Both men and women in the Central Region have the highest levels of secondary education. On the other hand, in the Northern Region, while almost 40 percent of women have had no education, the educational levels of men are only slightly different from those in the Western Region. This pattern was also observed in the 1995 UDHS. 2.5 CHILD LABOUR Uganda is a signatory to the International Labour Organisation International Programme for the Elimination of Child Labour (ILO-IPEC). Despite all policies and laws put in place, child labour still exists in Uganda. In addition to exploiting children and subjecting them to a hazardous working environment, child labour has the effect of denying children a chance to get an education, thus affecting their future. The 2000-2001 UDHS collected information in the Household Questionnaire on the engagement of children age 5-17 in domestic and commercial employment. The objective was to establish the magnitude of child labour in the country and the circumstances under which these children work. The survey established whether in the week preceding the survey, a child was working outside the household or for a member of the household, the type of work done, the tenure of the job, the location/environment of the work, and number of hours worked. The survey also collected information on participation in domestic chores. The results are presented in Table 2.5. Overall, less than 5 percent of children age 5-17 worked for someone who was not a member of the household. Children’s employment does not vary much according to urban-rural residence, the sex of the household head or whether the child is in school or not. However, older boys and children in the Eastern Region are more likely to work than other children. It is worth noting that the chance for a child to be employed by someone outside the household is inversely related to the household’s wealth status. Children in the lowest quintile are the most likely to be working, and those in the highest quintile are the least likely to work. Most children (83 percent of boys and 88 percent of girls) helped around the house with chores such as cooking, shopping, cleaning, washing dishes, fetching water, and caring for animals. Although there is no difference by the sex of the household head, in general, children age 10-14, rural children, children in the Central Region, and those who are attending school are more likely Characteristics of Households and Household Members * 15 Table 2.5 Children’s economic activity Among children age 5-17, the percentage who worked for someone who was not a member of the household in the week preceding the survey, the percentage who regularly helped with household chores in the week preceding the survey, and the percentage who worked for the family in the week preceding the survey, by sex and background characteristics, Uganda 2000-2001 ________________________________________________________________________________________________ Boys Girls ___________________________________ ____________________________________ Worked for Worked for someone someone who is not Regularly who is not Regularly a member helps with Worked Number a member helps with Worked Number Background of the household for the of of the household for the of characteristic household chores family boys household chores family girls _________________________________________________________________________________________________ Age 5-9 10-14 15-17 Residence Urban Rural Region Central Eastern Northern Western Sex of household head Male Female Schooling status Attending school Not attending school Wealth index quintile Lowest Lower middle Middle Upper middle Highest Total 2.5 73.8 23.3 3,264 3.2 81.6 22.3 3,331 5.4 92.3 54.6 2,864 4.9 94.3 50.8 2,938 8.6 87.2 56.7 1,156 4.6 87.9 53.4 1,163 4.6 78.2 18.7 835 2.4 83.6 15.8 976 4.6 83.8 43.8 6,449 4.3 88.2 41.9 6,457 3.5 89.6 47.9 2,320 1.7 90.7 45.1 2,351 7.2 80.7 46.7 1,934 6.8 85.5 42.3 2,115 3.3 69.9 28.7 1,159 4.7 84.7 26.7 1,146 4.1 85.9 33.9 1,871 3.7 88.0 32.8 1,821 4.4 83.1 40.3 5,381 3.5 87.1 37.2 5,303 5.1 83.4 42.7 1,903 5.6 88.8 41.5 2,129 4.6 87.9 45.8 5,839 4.3 90.6 42.4 5,856 4.6 64.2 21.1 1,445 3.1 76.6 23.9 1,576 6.4 78.4 39.3 1,322 5.8 86.2 35.5 1,320 5.2 81.0 40.7 1,443 5.5 86.4 41.0 1,381 4.0 85.3 44.5 1,515 4.4 90.0 43.7 1,485 4.1 87.3 47.4 1,549 3.3 90.8 44.9 1,619 3.3 83.1 32.1 1,455 1.9 84.5 27.5 1,627 4.6 83.2 40.9 7,284 4.1 87.6 38.5 7,433 than other children to help with chores around the house. The household’s wealth status does not have a strong influence on the participation of children in household chores. Questions were also asked of all children age 5-17 about whether they worked for the family farm or business in the week prior to the survey. Data in Table 2.5 show that four in ten children worked for their family. This figure is higher for older children, children in the rural areas, and those attending school. There is no clear pattern of the involvement of children in the family business or farm by the household’s wealth status. Whereas children in the middle three quintiles seem to have gradually higher rates as their wealth status increases, children in the lowest and highest quintiles are the least likely to work for the family farm or business. 16 * Characteristics of Households and Household Members 2.6 HOUSING CHARACTERISTICS Information was collected about certain characteristics of the households, including access to electricity, source of drinking water, time to water source, type of sanitation facility, and construction materials of the dwelling. This information is used to assess the status of public health. The information on housing characteristics is presented by urban-rural residence in Table 2.6. Nine percent of households in Uganda have access to electricity. Although still low, this proportion shows a slight improvement from the 7 percent observed in the 1995 UDHS. Access to electricity is much higher in urban areas (44 percent) than in rural areas (2 percent). Table 2.6 shows that open wells are still a major source of drinking water, while boreholes are the second most important source. These two sources combined are used by one half of the households with another 16 percent of households getting water from protected wells. Only one in nine households has access to piped water, mainly from a public tap. The percentage of households with access to piped water is much higher in the urban areas (63 percent) compared to the rural areas (2 percent). The urban-rural difference is also reflected in the time taken to draw water. In urban areas, nearly two-thirds of the households are within 15 minutes of a water source, compared with only 15 percent of rural households. Although half of urban households take nine minutes to collect water, in the rural areas the median duration is 30 minutes, more than three times longer. Households without proper toilet facilities are more exposed to the risk of diseases like dysentery, diarrhoea, and typhoid fever. Most households (79 percent) in Uganda use traditional pit latrines; this is true in both urban and rural areas. Flush toilets, as well as ventilated improved pit (VIP) latrines, are less common in the rural areas than in the urban areas. Overall, one in six households in Uganda has no toilet facilities of any kind. This problem is more common in rural areas, where about one-fifth of the households have no toilet facilities, compared with only 3 percent of households in urban areas. The type of material used for the floor may be viewed as an indicator of the quality of housing (an income dimension) as well as an indicator of health risk. Some floor materials like earth, sand, and cow dung pose a health problem since they can act as breeding grounds for pests and may be a source of dust. They are also more difficult to keep clean. Overall, four out of every five households have floors made of earth, sand, or cow dung. In general, rural households have poorer quality floors than urban households. Ninety percent of rural households have earth or dung floors, while 73 percent of the urban households have cement or vinyl floors. Very few households (less than 1 percent) in both rural and urban areas have floors made from tiles or polished wood. When compared with the 1995 UDHS, the overall status of housing conditions shows an improving trend. The same trend was shown by the 1999-2000 Uganda National Household Survey (UNHS). Characteristics of Households and Household Members * 17 Table 2.6 Housing characteristics Percent distribution of households by housing characteristics, according to residence, Uganda 2000-2001_____________________________________________________ Residence Housing ______________ characteristic Urban Rural Total_____________________________________________________ Electricity Yes No Missing Total Source of drinking water Piped into dwelling Piped into yard/plot Public tap Open well in yard/plot Open public well Protected well in yard/plot Protected public well Borehole in yard/plot Public borehole Spring River, stream Pond, lake Dam Rainwater Tanker truck Bottled water Gravity flow scheme Other Missing Total Time to water source Percentage <15 minutes Median time to water source Sanitation facility Flush toilet Traditional pit toilet Ventilated improved pit latrine No facility, bush, field Other Missing Total Flooring material Earth, sand Dung Parquet or polished wood Vinyl, asphalt strips Ceramic tiles Cement Other Total Number 43.9 2.4 8.6 56.0 97.3 91.2 0.1 0.3 0.3 100.0 100.0 100.0 5.1 0.1 0.9 7.0 0.1 1.1 51.2 1.5 8.9 0.1 0.0 0.0 6.8 28.3 25.1 0.2 0.1 0.1 10.9 17.0 16.1 0.2 0.2 0.2 13.6 26.4 24.5 1.3 9.4 8.2 0.3 8.8 7.5 0.6 5.3 4.6 0.2 1.6 1.4 0.4 0.4 0.4 0.1 0.0 0.0 0.7 0.0 0.1 0.0 0.6 0.5 1.4 0.2 0.4 0.1 0.2 0.2 100.0 100.0 100.0 62.7 15.4 22.5 9.2 29.9 29.6 9.1 0.5 1.7 79.9 78.3 78.5 7.9 1.1 2.1 2.7 19.1 16.7 0.2 0.8 0.7 0.1 0.2 0.2 100.0 100.0 100.0 19.3 59.9 53.8 7.1 30.0 26.6 0.6 0.1 0.2 24.7 3.5 6.6 0.4 0.0 0.1 47.8 6.4 12.5 0.1 0.1 0.1 100.0 100.0 100.0 1,174 6,711 7,885 2 The wealth index is created by using factor analysis to identify the most important variables to divide households into quintiles by socioeconomic status. 18 * Characteristics of Households and Household Members Table 2.7 Household durable goods Percentage of households possessing various durable consumer goods and means of transport, by residence, Uganda 2000- 2001 ___________________________________________________ Residence Durable ________________ consumer goods Urban Rural Total ___________________________________________________ Household possessions Radio Television Telephone Refrigerator Lantern Cupboard Means of transport Bicycle Motorcycle/scooter Car/truck Boat/canoe None of the above Number of households 77.5 47.0 51.5 26.6 1.9 5.6 14.5 0.6 2.7 12.2 0.3 2.1 64.9 26.8 32.5 53.2 22.0 26.7 19.8 42.1 38.8 5.4 1.9 2.4 6.1 0.6 1.4 0.4 0.4 0.4 10.4 32.4 29.2 1,174 6,711 7,885 2.7 HOUSEHOLD DURABLE GOODS The 2000-2001 UDHS also collected information on the household’s ownership of selected durable goods. Combined with other indicators, information on ownership of durable goods can be used to generate a wealth index that acts as a proxy measure of the socioeconomic status of a household.2 Further, ownership of a radio or television is a measure of access to mass media; telephone ownership measures access to an efficient means of communication; cupboard and refrigerator ownership indicates the capacity for hygienic storage of foods and utensils; lantern ownership indicates a source of lighting; and ownership of a bicycle, motorcycle, boat/canoe, or private car shows the means of transport privately available to the household. Ownership of these items, in turn, has a bearing on the household’s access to information and health care. Table 2.7 shows that more than half of the households in Uganda own a radio; urban households are more likely than rural households to have a radio (78 percent compared with 47 percent). Only 6 percent of households own a television, and only 3 percent have a telephone. Refrigerators are also uncommon. One-third of Ugandan households own lanterns, while more than one-fourth have cupboards. Two-fifths of households own bicycles. Bicycles are more common in rural areas than in urban areas, while cars and motorcycles are almost exclusively owned by urban households. About one-third of rural households and 10 percent of urban households do not own any of the above durable goods. 1 In this table, "married" refers to those in a form al or offic ial marriage, while "living together" refers to those in informal or consensual unions. In the remainder of the report, marriage refers to both categories, i.e., formal and informal unions. Characteristics of Respondents and Women’s Status * 19 3CHARACTERISTICS OF RESPONDENTSAND WOMEN’S STATUS This chapter provides a description of the situation of men and women of reproductive age in Uganda. The description is presented in terms of the following variables: age at the time of the survey, marital status, residence, education, literacy, and media access. In addition, factors that enhance women’s empowerment are explored, including employment, occupation, earnings, and continuity of employment. Women’s decisionmaking autonomy at the household level is also explored. An analysis of these variables provides the socioeconomic context within which demographic and reproductive health issues are examined in the subsequent chapters. 3.1 CHARACTERISTICS OF SURVEY RESPONDENTS Background characteristics of the 7,246 women age 15-49 and 1,962 men age 15-54 interviewed in the 2000-2001 UDHS are presented in Table 3.1. The distribution of the respondents according to age shows a similar pattern for males and females. For both sexes, the proportion of respondents in each age group declines with increasing age. Forty-three percent of women and 39 percent of men are in the 15-24 age group, 32 percent of women and 31 percent of men are age 25-34, and the remaining respondents are age 35-49 and age 35-54 for women and men, respectively. Forty-five percent of women compared with 55 percent of men are formally married1. Male respondents were much more likely than female respondents to have never married (34 percent for males and 20 percent for females). It is interesting to note that 22 percent of females declared themselves to be living together with a man or in consensual unions, while the corresponding percentage for males is only 5 percent. Whereas 9 percent of women are divorced and 3 percent are widowed, the corresponding proportions for men are 5 percent and less than 1 percent, respectively. The distribution of male and female respondents by residence is the same. Less than 17 percent of respondents are found in the urban areas. The largest proportion of both male and female respondents (34 percent and 32 percent, respectively) is in the Central Region. The Northern Region is the least populated area with 16 percent of women and 15 percent of men. Data in Table 3.1 show that men are much more likely to have gone to school and attained higher levels of education than women. Whereas 22 percent of women have never attended school, the corresponding proportion for men is only 6 percent. Furthermore, whereas 29 percent of men have gone to secondary or higher education, only 18 percent of women have. According to 1991 census data, the DISH project serves 29 percent of the women of reproductive age in Uganda, and the CREHP project covers 7 percent. The projects cover similar proportions of men and women (30 percent and 6 percent, respectively). 20 * Characteristics of Respondents and Women’s Status Table 3.1 Background characteristics of respondents Percent distribution of women and men by background characteristics, Uganda 2000-2001__________________________________________________________________________________ Number of women Number of men_________________ _________________ Background Weighted Un- Weighted Un- characteristic percent Weighted weighted percent Weighted weighted__________________________________________________________________________________ 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 Central Eastern Northern Western Education No education Primary Secondary+ Missing DISH/CREHP districts DISH I Mbarara and Ntungamo II Masaka, Rakai, and Sembabule III Luwero, Masindi, and Nakasongola IV Kamuli and Jinja V Kampala CREHP (Kisoro, Kabale, and Rukungiri) Neither Total 22.3 1,615 1,687 22.5 441 440 20.8 1,504 1,542 16.4 321 337 18.5 1,341 1,326 15.8 310 315 13.6 983 955 14.8 291 283 11.2 810 783 11.8 231 225 7.9 570 547 8.4 165 166 5.8 423 406 6.1 120 117 na na na 4.2 83 79 20.1 1,456 1,603 34.4 675 700 45.1 3,267 3,075 55.3 1,085 1,056 22.3 1,614 1,600 4.8 95 111 9.2 665 708 4.8 94 83 3.4 245 260 0.7 13 12 16.7 1,207 2,416 16.6 325 601 83.3 6,039 4,830 83.4 1,637 1,361 32.3 2,341 2,445 34.2 671 677 27.0 1,956 1,767 26.7 523 466 16.0 1,158 1,041 14.5 284 273 24.7 1,792 1,993 24.7 484 546 21.9 1,584 1,459 6.2 122 118 59.8 4,330 4,098 64.8 1,272 1,201 18.4 1,331 1,688 28.9 568 643 0.0 1 1 0.0 0 0 28.7 2,077 2,317 29.7 582 622 5.4 392 446 5.8 115 132 6.7 486 541 7.5 147 162 3.3 240 206 3.4 66 53 4.9 356 554 4.3 84 124 8.3 604 570 8.7 171 151 6.5 472 755 5.8 114 188 64.8 4,696 4,174 64.5 1,265 1,152 100.0 7,246 7,246 100.0 1,962 1,962 ___________________________________________________________________________________ Note: Education refers to the highest level ever attended whether or not that level was completed. na = Not applicable 3.2 EDUCATIONAL ATTAINMENT BY BACKGROUND CHARACTERISTICS 2 These sentences include the following: 1) Breast m ilk is good for babies. 2) Most Ugandans live in villages. 3) Immunization can prevent children from getting diseases. 4) Family planning teaches people to be responsible to their family. Characteristics of Respondents and Women’s Status * 21 Table 3.2 shows the distribution of respondents according to the highest level of schooling attended. As mentioned before, the data show that men are better educated than women. Whereas 6 percent of men have never gone to school, the corresponding proportion for women is 22 percent. The reverse situation is observed for those who attended secondary or higher education. Younger people are more likely to be educated and to reach higher levels of education than older people. For women, the percentage without formal education is 9 percent for age 15-19, 15 percent for age 20-24, and 45 percent for age 45-49. For men, the increase is gradual, from 2 percent for age 15-19 to 5 percent for age 25-29 to 14 percent in the 50-54 age category. Rural people are less educated than their urban counterparts. One in four rural women do not have an education, compared with 7 percent of urban women. The corresponding figures for men are 7 percent and 2 percent for rural men and urban men, respectively. The pattern, however, changes for secondary or higher education. Whereas only 12 percent of rural women have attended secondary or higher education, 48 percent of urban women have at least some secondary education. School attainment among female respondents varies by region. Women in the Central Region are the least likely to have no education (12 percent). On the other hand, 39 percent of women in the Northern Region have not attended school. In the Eastern and Western regions, the percentage of women who have not attended school is 19 percent and 27 percent, respectively. Data for the male respondents, however, are less varied, with the percentage who have never attended school ranging between 4 and 9 percent. The last column in Table 3.2 shows the median number of years of schooling. The figures confirmed the previous findings: younger persons and those living in the urban areas and in the Central Region have had more years of schooling. The results also confirm the marginalisation of women regarding education and the evolution of women’s education in Uganda over the years. Women are still less likely to have formal education than men. 3.3 LITERACY A person’s ability to read is important in taking advantage of day-to-day opportunities. In the 2000-2001 UDHS, level of literacy is determined by the respondent’s ability to read none, part, or all of a simple sentence. Interviewers were given cards on which sentences2 were printed in all the major languages spoken in Uganda. Respondents who had attended secondary school were assumed to be literate and were not asked to read a sentence. Data in Table 3.3 reveal that 40 percent of women in the survey could not read at all, compared with 16 percent of the men. Literacy levels decrease with increasing age among women, from 57 percent among women 15-19 to 34 percent in the 45-49 age group. However, six out of ten men in all age groups are literate, showing their greater access to education over the years. 22 * Characteristics of Respondents and Women’s Status 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, by background characteristics, Uganda 2000-2001 ______________________________________________________________________________________________________________ Highest level of schooling attained ___________________________________________________________________________ More Number Median Background No edu- Some Completed Some Completed than of years of characteristic cation primary primary1 secondary secondary2 secondary Total women schooling _____________________________________________________________________________________________________________ WOMEN _____________________________________________________________________________________________________________ Age 15-19 20-24 25-29 30-34 35-39 40-44 45-49 Residence Urban Rural Region Central Eastern Northern Western Total 9.1 50.5 15.6 23.7 0.4 0.6 100.0 1,615 5.0 15.1 51.3 11.4 16.8 1.4 3.9 100.0 1,504 4.4 22.0 48.2 9.9 14.8 0.5 4.7 100.0 1,341 4.0 26.4 48.8 11.1 9.9 0.4 3.3 100.0 983 3.1 32.5 47.2 8.5 7.5 0.1 4.2 100.0 810 2.5 35.5 45.6 7.3 9.3 0.0 2.2 100.0 570 2.3 44.8 41.1 6.1 6.0 0.0 2.0 100.0 423 1.1 7.4 33.8 10.9 35.2 2.2 10.5 100.0 1,207 6.5 24.7 51.7 11.1 10.7 0.2 1.5 100.0 6,039 3.2 11.5 45.4 11.9 24.7 1.2 5.3 100.0 2,341 5.6 19.4 51.6 13.1 13.3 0.3 2.4 100.0 1,956 3.7 38.8 44.7 8.9 6.1 0.1 1.4 100.0 1,158 1.5 27.1 52.5 9.2 9.1 0.3 1.8 100.0 1,792 3.0 21.9 48.7 11.0 14.8 0.6 3.0 100.0 7,246 3.9 ____________________________________________________________________________________________________________ MEN ____________________________________________________________________________________________________________ Age 15-19 20-24 25-29 30-34 35-39 40-44 45-49 50-54 Residence Urban Rural Region Central Eastern Northern Western Total 1.6 59.0 12.7 26.7 0.1 0.0 100.0 441 5.5 2.1 47.8 18.0 23.5 3.2 5.4 100.0 321 6.0 5.0 49.6 12.2 18.7 4.0 10.5 100.0 310 5.5 5.7 50.2 14.3 18.9 1.1 9.7 100.0 291 5.6 12.9 46.8 14.9 15.6 1.9 7.9 100.0 231 5.1 12.9 41.1 17.0 16.8 3.5 8.7 100.0 165 5.5 11.9 47.4 17.8 15.8 1.9 5.2 100.0 120 5.3 13.6 46.0 12.1 19.8 0.0 8.5 100.0 83 4.8 2.2 24.7 12.0 38.3 4.7 18.2 100.0 325 8.4 7.0 55.3 15.2 17.2 1.4 3.9 100.0 1,637 5.2 5.1 43.7 13.6 23.1 3.7 10.8 100.0 671 6.1 4.3 55.1 10.3 25.4 1.0 3.9 100.0 523 5.4 8.6 50.9 19.5 16.4 0.5 4.0 100.0 284 5.4 8.4 53.5 17.8 14.6 1.5 4.1 100.0 484 5.1 6.2 50.2 14.6 20.7 2.0 6.3 100.0 1,962 5.5 _____________________________________________________________________________________________________________ 1Completed 7th grade at the primary level. 2Completed 6th grade at the secondary level. For both sexes, literacy levels are higher in urban areas than in rural areas. The gap between men and women is wide, particularly in the rural areas where 60 percent of the men are literate, compared with 42 percent of the women. The gap is also significant across regions. In the Northern Region, for example, the literacy level of men is 69 percent, compared with 24 percent for women. In other regions, the gap is less pronounced; in the Central and Western regions, it is 7 percentage points, and in the Eastern Region, the gap between the male and female literacy level is 21 percentage points. Characteristics of Respondents and Women’s Status * 23 Table 3.3 Literacy Percent distribution of women and men by level of schooling attended, level of literacy, and percentage who are literate, according to background characteristics, Uganda 2000-2001________________________________________________________________________________________________________________ No schooling or primary school ________________________________________ No card Secondary Can read Can read Cannot with Background school or a whole part of a read at required Percent characteristic higher sentence sentence all language Missing Total Number literate________________________________________________________________________________________________________________ WOMEN________________________________________________________________________________________________________________ Age 15-19 20-24 25-29 30-34 35-39 40-44 45-49 Residence Urban Rural Region Central Eastern Northern Western Total 24.8 32.1 12.9 28.3 1.4 0.5 100.0 1,615 56.9 22.1 26.4 10.4 39.2 1.5 0.4 100.0 1,504 48.6 20.0 27.9 10.3 38.7 2.7 0.5 100.0 1,341 47.9 13.7 29.0 10.9 43.1 2.5 0.8 100.0 983 42.7 11.8 30.2 8.0 47.3 1.8 0.9 100.0 810 42.0 11.6 31.7 6.0 47.8 2.1 0.9 100.0 570 43.3 8.0 25.5 9.1 55.2 2.0 0.2 100.0 423 33.5 47.8 28.2 8.2 14.0 1.3 0.5 100.0 1,207 76.0 12.5 29.3 10.7 44.9 2.0 0.6 100.0 6,039 41.8 31.2 38.6 7.6 18.6 2.9 1.0 100.0 2,341 69.8 15.9 19.5 11.2 51.5 1.4 0.5 100.0 1,956 35.4 7.6 16.4 9.9 65.5 0.5 0.2 100.0 1,158 24.0 11.2 35.4 13.1 37.8 2.2 0.3 100.0 1,792 46.6 18.4 29.1 10.3 39.7 1.9 0.6 100.0 7,246 47.5 _______________________________________________________________________________________________________________ MEN_______________________________________________________________________________________________________________ Age 15-19 20-24 25-29 30-34 35-39 40-44 45-49 50-54 Residence Urban Rural Region Central Eastern Northern Western Total 26.7 36.9 19.5 12.7 4.1 0.1 100.0 441 63.6 32.1 34.6 16.1 14.2 3.1 0.0 100.0 321 66.7 33.2 33.0 15.3 14.7 3.4 0.5 100.0 310 66.1 29.7 33.1 17.7 16.5 2.5 0.4 100.0 291 62.8 25.4 35.6 15.3 19.5 4.2 0.0 100.0 231 61.0 29.0 35.0 13.3 18.4 4.3 0.0 100.0 165 64.0 23.0 42.1 14.2 16.9 3.7 0.0 100.0 120 65.1 28.3 36.8 3.4 25.8 3.3 2.4 100.0 83 65.1 61.2 24.3 6.1 5.2 3.1 0.1 100.0 325 85.5 22.5 37.5 17.9 18.1 3.6 0.3 100.0 1,637 60.0 37.6 38.8 7.4 9.6 6.6 0.0 100.0 671 76.4 30.3 26.2 19.5 19.6 4.1 0.4 100.0 523 56.4 21.0 47.8 15.8 14.2 1.3 0.0 100.0 284 68.8 20.2 33.1 24.3 21.8 0.0 0.6 100.0 484 53.3 28.9 35.3 16.0 15.9 3.6 0.3 100.0 1,962 64.3 ________________________________________________________________________________________________________________ Note: Percent literate includes those who have attended secondary school and those who can read a whole sentence. 3.4 ACCESS TO MASS MEDIA Information access is essential in increasing people’s knowledge and awareness of what is taking place around them, which may eventually affect their perceptions and behaviour. In the survey, exposure to the media was assessed by asking how often a respondent reads a newspaper, watches television, or listens to a radio. Most of the population is exposed to some form of media. In general, men are more likely than women to have access to mass media; this is true for all types of media. Table 3.4 shows that radio is the most popular medium. Three in four men and more than half of the women listen to a radio broadcast at least once a week. Twenty-four percent of men read a newspaper at least once a week, compared with 15 percent of the women. 24 * Characteristics of Respondents and Women’s Status 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, Uganda 2000-2001 ________________________________________________________________________________________________ Reads a Watches Listens to newspaper television the radio at least at least at least All Background once a once a once a three No mass characteristic week week week media media Number _______________________________________________________________________________________________ WOMEN ________________________________________________________________________________________________ Age 15-19 20-24 25-29 30-34 35-39 40-44 45-49 Residence Urban Rural Region Central Eastern Northern Western Education No education Primary Secondary+ Total 20.1 13.8 54.9 7.6 35.2 1,615 14.9 9.2 56.5 5.2 36.9 1,504 13.5 10.7 53.4 5.6 39.2 1,341 13.3 8.5 50.3 4.9 41.6 983 12.6 6.3 50.7 3.9 41.7 810 12.2 6.8 48.3 3.5 40.7 570 8.3 6.1 42.2 3.3 48.0 423 43.7 36.5 81.5 23.2 10.7 1,207 9.0 4.4 46.8 1.8 44.7 6,039 30.6 24.1 73.1 14.2 18.8 2,341 8.9 3.8 48.1 1.4 42.0 1,956 4.9 1.4 24.9 0.6 69.3 1,158 6.8 2.7 48.6 1.2 42.8 1,792 0.2 2.0 30.5 0.0 62.6 1,584 9.0 6.1 51.5 1.9 39.4 4,330 50.6 30.8 82.5 23.0 9.7 1,331 14.7 9.7 52.6 5.4 39.1 7,246 ________________________________________________________________________________________________ MEN ________________________________________________________________________________________________ Age 15-19 20-24 25-29 30-34 35-39 40-44 45-49 50-54 Residence Urban Rural Region Central Eastern Northern Western Education No education Primary Secondary+ Total 19.7 14.5 76.8 8.0 15.4 441 24.8 15.4 78.0 9.2 13.5 321 32.8 20.5 75.0 15.2 14.6 310 22.2 12.5 78.0 9.0 14.0 291 24.5 12.4 69.3 7.8 16.3 231 28.3 15.5 70.4 11.6 19.7 165 19.8 6.7 71.7 3.3 18.4 120 21.8 6.2 63.9 3.7 23.6 83 59.9 49.3 92.4 38.8 2.4 325 17.3 7.4 71.1 3.4 18.4 1,637 38.3 27.5 87.4 20.8 7.4 671 17.6 10.6 67.5 4.2 22.9 523 17.7 5.1 57.7 2.4 27.3 284 16.3 5.5 74.5 2.9 12.9 484 0.1 2.3 43.3 0.0 45.0 122 13.4 7.9 70.9 2.9 18.6 1,272 54.1 31.3 89.7 25.7 3.0 568 24.4 14.3 74.6 9.3 15.8 1,962 ____________________________________________________________________________________________ Note: Total includes one woman with missing information on education Characteristics of Respondents and Women’s Status * 25 Given the low television broadcast coverage in the country, the percentage of women and men who watch television is low (10 percent of women and 14 percent of men). The proportion that has access to all three media at least once a week is generally low for both men and women (5 percent for women and 9 percent for men). Four in ten women and one in six men have no exposure to any mass media, which poses a challenge in the provision of information to the population. Table 3.4 further provides an analysis of the responses by background characteristics of respondents. The results by age show that the proportion of women and men who are exposed to any media at least once a week generally declines slowly with age. The proportion who have no access to any media increases with age for both sexes. The data show that urban residents are more likely to have access to mass media than rural residents. Among women, although less than 10 percent of the women in rural areas read a newspaper or watch television at least once a week, the percentages for urban women are 44 percent and 37 percent, respectively. A similar pattern is found for listening to the radio, with only 47 percent of rural women listening to a radio as opposed to 82 percent of their urban counterparts. For men, although 60 percent of men in the urban areas read a newspaper at least once a week, the corresponding proportion for rural men is only 17 percent. The findings depict the urban-rural gap in socioeconomic development as reflected in higher standards of living in the urban areas than in the rural areas. For both women and men, media access is highest in the Central Region. For example, 73 percent of women in the Central Region listen to a radio at least once a week, compared with less than 50 percent of women in the Eastern and Western regions and only one-quarter of women in Northern Region. The data on media access by educational attainment of respondents reveal that exposure to media is positively associated with educational attainment. For example, 83 percent of women who had reached secondary or higher education listen to a radio at least once a week, compared with 31 percent of women with no education. The same pattern is shown for men. 3.5 EMPLOYMENT Respondents were asked whether they were employed at the time of the survey and if not, whether they were employed in the 12 months that preceded the survey. Table 3.5 and Figure 3.1 show that 73 percent of women and 63 percent of men were currently employed. The proportion currently employed increases with age and number of living children among women. The data for men show a less distinct pattern. Women who were divorced, separated, or widowed are the most likely to be employed (83 percent), followed by those who were married (78 percent). Never- married women and men are the least likely to be employed (51 percent and 38 percent, respectively). Married men and men who are divorced, separated, or widowed show equal levels of current employment (76 percent). The current employment level for women is higher in rural areas than in urban areas, while the reverse is true for men. Women in the Western Region are the most likely to be employed (84 percent), followed by the Eastern and Northern regions (77 to 78 percent), while the level in the Central Region is 60 percent. For men, employment levels vary between 41 and 42 percent in the Eastern and Northern regions to 82 percent in the Western Region. It is worth noting that for both women and men, current employment levels are inversely associated with educational attainment. 26 * Characteristics of Respondents and Women’s Status Ta bl e 3. 5 E m pl oy m en t s ta tu s Pe rc en t d ist rib ut io n of w om en a nd m en b y em pl oy m en t s ta tu s an d co nt in ui ty o f e m pl oy m en t, ac co rd in g to b ac kg ro un d ch ar ac te ris tic s, U ga nd a 20 00 -2 00 1 __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ _ W O M EN M EN __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ _ E m pl oy ed in th e E m pl oy ed in th e 12 m on th s pr ec ed in g N ot 1 2 m on th s pr ec ed in g N ot th e su rv ey em pl oy ed t he s ur ve y em pl oy ed __ __ __ __ __ __ __ __ __ __ _ in th e __ __ __ __ __ __ __ __ __ __ _ in th e N ot 12 m on th s N ot 12 m on th s Ba ck gr ou nd C ur re nt ly cu rr en tly pr ec ed in g C ur re nt ly cu rr en tly pr ec ed in g M iss in g/ ch ar ac te ris tic em pl oy ed em pl oy ed th e su rv ey To ta l1 N um be r2 em pl oy ed em pl oy ed th e su rv ey do n’ t k no w To ta l N um be r __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ Ag e 1 5- 19 2 0- 24 2 5- 29 3 0- 34 3 5- 39 4 0- 44 4 5- 49 M ar ita l s ta tu s N ev er m ar rie d M ar rie d or in u ni on D iv or ce d, s ep ar at ed , w id ow ed N um be r of li vi ng c hi ld re n 0 1 -2 3 -4 5 + Re si de nc e U rb an R ur al Re gi on C en tra l E as te rn N or th er n W es te rn Ed uc at io n N o ed uc at io n P rim ar y S ec on da ry + To ta l 54 .4 6 .3 39 .2 10 0. 0 1, 61 5 27 .2 7. 5 64 .9 0. 4 10 0. 0 44 1 69 .5 7 .7 22 .8 10 0. 0 1, 50 4 64 .2 19 .4 16 .3 0. 0 10 0. 0 32 1 78 .3 5 .8 15 .9 10 0. 0 1, 34 1 73 .3 19 .5 7. 1 0. 0 10 0. 0 31 0 83 .0 5 .2 11 .8 10 0. 0 9 83 81 .5 18 .1 0. 4 0. 0 10 0. 0 29 1 83 .4 5 .2 11 .4 10 0. 0 8 10 78 .4 20 .3 1. 3 0. 0 10 0. 0 23 1 87 .4 4 .4 8 .2 10 0. 0 5 70 76 .0 22 .8 1. 1 0. 0 10 0. 0 16 5 83 .3 6 .4 10 .4 10 0. 0 4 23 67 .6 29 .2 3. 1 0. 1 10 0. 0 12 0 69 .0 23 .8 7. 2 0. 0 10 0. 0 83 51 .0 6 .9 41 .9 10 0. 0 1, 45 6 37 .8 10 .7 51 .3 0. 2 10 0. 0 67 5 78 .2 5 .8 15 .9 10 0. 0 4, 88 1 76 .3 22 .0 1. 8 0. 0 10 0. 0 1, 18 0 8 2. 9 6 .1 11 .0 10 0. 0 9 10 75 .6 15 .4 8. 9 0. 1 10 0. 0 10 7 56 .8 6 .4 36 .7 10 0. 0 1, 73 0 40 .0 12 .3 47 .5 0. 2 10 0. 0 72 7 72 .5 6 .6 21 .0 10 0. 0 2, 02 1 78 .7 17 .1 4. 2 0. 0 10 0. 0 39 2 80 .9 5 .5 13 .6 10 0. 0 1, 66 5 75 .3 23 .8 0. 9 0. 0 10 0. 0 30 7 83 .1 5 .8 11 .1 10 0. 0 1, 83 0 75 .7 22 .1 2. 2 0. 0 10 0. 0 53 5 56 .7 6 .7 36 .6 10 0. 0 1, 20 7 67 .1 7. 1 25 .6 0. 2 10 0. 0 32 5 76 .7 6 .0 17 .3 10 0. 0 6, 03 9 62 .2 19 .9 17 .9 0. 1 10 0. 0 1, 63 7 60 .3 6 .8 32 .9 10 0. 0 2, 34 1 75 .0 3. 7 21 .3 0. 0 10 0. 0 67 1 76 .6 5 .4 18 .0 10 0. 0 1, 95 6 42 .4 35 .4 22 .2 0. 0 10 0. 0 52 3 77 .8 10 .7 11 .4 10 0. 0 1, 15 8 40 .6 40 .8 18 .2 0. 4 10 0. 0 28 4 84 .0 2 .9 13 .1 10 0. 0 1, 79 2 81 .7 4. 6 13 .6 0. 1 10 0. 0 48 4 79 .1 8 .1 12 .8 10 0. 0 1, 58 4 78 .2 17 .0 4. 7 0. 1 10 0. 0 12 2 74 .9 5 .5 19 .6 10 0. 0 4, 33 0 63 .6 19 .1 17 .2 0. 1 10 0. 0 1, 27 2 61 .4 5 .8 32 .8 10 0. 0 1, 33 1 58 .3 14 .8 26 .8 0. 1 10 0. 0 56 8 73 .4 6 .1 20 .5 10 0. 0 7, 24 6 63 .0 17 .7 19 .2 0. 1 10 0. 0 1, 96 2 1 M ay n ot a dd u p to 1 00 .0 d ue to m iss in g ca se s 2 In cl ud es o ne w om an w ith m iss in g in fo rm at io n on e du ca tio n. Characteristics of Respondents and Women’s Status * 27 3.6 OCCUPATION Respondents who were currently employed were asked to state their occupation, and the results are presented in Tables 3.6.1 and 3.6.2. Among women who are currently employed, 77 percent are engaged in agriculture and 23 percent are involved in nonagricultural activities. The percentages for men are 54 percent and 46 percent, respectively. The strong involvement of the population in agriculture reflects the predominance of the agricultural sector in the Ugandan economy. Data in Table 3.6.1 and 3.6.2 also reveal that among women who are engaged in agriculture, most work on family land, while most men work on their own land. Tables 3.6.1 and 3.6.2 further show that most women and men who are engaged in nonagricultural activities work in sales and services occupations or unskilled manual labour. The professional, technical, and managerial occupations, which require more skill but have higher income-earning potential, employ only 3 percent of working women and 6 percent of working men. Data in Tables 3.6.1 and 3.6.2 show the expected patterns. Except for women in urban areas and those with secondary or higher education, the majority work in agriculture, whereas among men, only a majority of older men, married men, rural men, those in the Northern and Western regions, and those with less than secondary education work in agriculture. 28 * Characteristics of Respondents and Women’s Status Table 3.6.1 Occupation: women Percent distribution of currently employed women by occupation, according to background characteristics, Uganda 2000-2001 ______________________________________________________________________________________________________________________ Agricultural Nonagricultural ____________________________ _______________________________________________ Other/ Prof./ Sales Skilled Unskilled don’t Background Own Family Rented Other’s tech./ and manual manual know/ characteristic land land land land manag. Clerical services labour labour missing Total Number1 ______________________________________________________________________________________________________________________ Age 15-19 20-24 25-29 30-34 35-39 40-44 45-49 Marital status Never married Married/living together Divorced, separated Widowed Number of living children 0 1-2 3-4 5+ Residence Urban Rural Region Central Eastern Northern Western Education No education Primary Secondary+ Total 12.3 61.1 5.4 3.2 0.5 0.0 6.5 2.3 8.4 0.3 100.0 878 21.1 39.1 8.3 5.0 3.4 0.8 11.4 2.6 7.9 0.4 100.0 1,045 25.5 33.6 7.8 5.8 4.0 0.2 13.0 2.3 6.9 0.8 100.0 1,050 29.3 31.7 8.0 4.3 3.3 0.4 10.2 3.3 8.0 1.5 100.0 816 31.3 34.5 6.1 4.8 2.9 0.5 11.1 2.1 6.4 0.2 100.0 675 32.8 37.4 7.7 6.8 1.7 0.0 6.4 2.7 3.7 0.9 100.0 498 41.3 27.9 7.5 6.6 2.1 0.0 6.8 1.8 5.8 0.3 100.0 352 4.2 54.7 2.6 3.2 5.0 1.1 11.2 4.8 12.5 0.8 100.0 743 30.7 37.2 8.4 4.9 2.3 0.2 8.5 1.9 5.4 0.6 100.0 3,819 14.6 37.1 5.6 7.5 2.9 0.3 18.6 3.3 9.5 0.5 100.0 545 35.1 21.3 7.5 6.5 2.2 0.1 9.7 3.2 12.6 1.9 100.0 209 10.6 52.3 4.6 3.2 4.2 0.8 10.0 3.5 10.2 0.6 100.0 982 20.9 37.6 8.1 5.7 4.4 0.6 12.6 2.4 7.2 0.3 100.0 1,465 27.9 35.5 9.0 5.1 1.6 0.0 11.0 2.3 6.8 0.7 100.0 1,347 37.3 34.9 6.6 5.3 1.2 0.1 6.4 2.1 5.2 0.9 100.0 1,522 3.6 5.6 1.9 2.7 10.1 1.3 40.9 6.7 26.0 1.3 100.0 684 28.7 44.0 8.1 5.3 1.6 0.2 5.4 1.8 4.3 0.6 100.0 4,632 19.6 18.6 3.3 7.7 5.6 0.8 20.0 6.0 17.0 1.4 100.0 1,411 21.7 47.4 12.3 2.9 2.1 0.1 7.9 1.5 3.6 0.4 100.0 1,499 37.9 38.6 4.2 5.3 0.8 0.3 6.4 0.5 5.6 0.5 100.0 901 27.4 50.0 7.9 4.4 1.8 0.2 4.6 1.4 2.2 0.3 100.0 1,505 34.5 39.1 9.1 6.9 0.0 0.0 4.6 0.9 4.3 0.6 100.0 1,253 25.9 42.8 7.8 4.9 0.2 0.1 8.4 2.4 7.1 0.6 100.0 3,244 10.0 24.1 2.5 2.6 16.8 1.9 24.4 5.3 11.5 0.9 100.0 818 25.5 39.0 7.3 5.0 2.7 0.3 9.9 2.5 7.1 0.7 100.0 5,316 ______________________________________________________________________________________________________________________ 1Includes one woman with missing information on education. 3.7 EARNINGS, EMPLOYER, AND CONTINUITY OF EMPLOYMENT Table 3.7 shows the distribution of women and men by their employment status. The data indicate that 27 percent of employed women receive payment in cash only, 35 percent receive both cash and kind, 9 percent receive only payment in kind, and 29 percent receive no payment for their work (Figure 3.2). Men are more likely than women to be paid in cash for their work. Table 3.7 further shows that women and men who work in agriculture are much more likely to receive no payment than those who work in nonagricultural jobs. Data on type of employer in Table 3.7 indicate that 63 percent of working women are self- employed, while 28 percent are employed by a relative and 9 percent are employed by a nonrelative. These results are also displayed graphically in Figure 3.3. Table 3.7 further shows that Characteristics of Respondents and Women’s Status * 29 Table 3.6.2 Occupation: men Percent distribution of currently employed men by occupation, according to background characteristics, Uganda 2000-2001 ________________________________________________________________________________________________________________________ Agricultural Nonagricultural ___________________________ _______________________________________________ Other/ Prof./ Sales Skilled Unskilled don’t Background Own Family Rented Other’s tech./ and manual manual know/ characteristic land land land land manag. Clerical services labour labour missing Total 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 Number of living children 0 1-2 3-4 5+ Residence Urban Rural Region Central Eastern Northern Western Education No education Primary Secondary+ Total 9.2 35.0 3.2 11.1 1.3 0.2 13.0 4.1 16.9 6.0 100.0 120 13.8 21.9 5.5 7.4 4.6 0.0 16.4 9.5 15.7 5.3 100.0 206 24.0 8.7 6.4 6.0 7.5 1.5 18.0 9.5 14.8 3.5 100.0 227 30.7 5.7 7.1 4.4 8.0 0.5 17.5 8.0 14.8 3.2 100.0 237 36.6 6.1 9.3 6.7 6.8 0.0 13.6 7.0 11.1 2.9 100.0 181 47.8 2.9 4.3 3.9 9.3 0.0 16.7 4.6 7.2 3.4 100.0 125 57.5 6.0 6.7 2.6 5.4 1.7 9.5 6.1 2.4 2.1 100.0 81 54.5 3.3 9.3 1.4 3.7 1.9 3.2 5.1 17.6 0.0 100.0 57 6.9 28.6 3.2 7.9 7.0 0.0 15.6 8.3 17.0 5.7 100.0 255 36.8 7.0 7.8 4.8 6.4 0.8 15.7 6.9 10.7 3.2 100.0 900 24.3 7.7 2.4 11.0 3.3 0.0 7.3 10.1 31.7 2.1 100.0 73 * * * * * * * * * * 100.0 7 10.3 27.3 2.4 9.4 7.2 0.1 16.2 6.7 15.0 5.5 100.0 291 27.2 9.8 7.9 5.5 5.8 0.6 14.6 9.4 16.0 3.2 100.0 309 35.4 6.3 8.0 4.7 6.8 1.2 13.2 10.3 11.3 2.8 100.0 231 43.3 4.3 7.4 4.2 5.7 0.6 15.9 4.7 10.8 3.1 100.0 405 1.9 1.2 0.7 0.8 14.5 0.3 33.6 19.7 26.2 1.1 100.0 218 36.1 13.7 7.7 7.0 4.5 0.7 11.1 4.7 10.4 4.2 100.0 1,017 22.0 13.0 7.3 5.1 6.3 0.3 17.8 10.5 15.0 2.6 100.0 503 16.1 8.7 12.2 1.1 7.9 1.1 23.8 3.7 22.1 3.4 100.0 222 54.9 7.5 1.1 2.1 8.0 0.9 6.6 4.2 8.1 6.6 100.0 115 40.8 12.2 3.7 10.6 4.8 0.6 9.4 6.5 7.2 4.2 100.0 395 46.6 4.7 12.3 10.6 1.3 0.0 3.0 0.4 14.7 6.3 100.0 96 33.2 14.1 7.1 6.8 0.7 0.3 13.9 5.7 14.4 3.7 100.0 809 17.3 7.0 3.2 2.1 21.3 1.6 21.6 13.5 9.7 2.8 100.0 331 30.0 11.5 6.5 5.9 6.3 0.6 15.1 7.4 13.2 3.6 100.0 1,236 ________________________________________________________________________________________________ * Estimate based on fewer than 25 unweighted cases, and has been suppressed. 64 percent of women who work in agriculture are self-employed, compared with 58 percent of women who are self-employed in the nonagricultural sector. Table 3.7 presents the distribution of women by the continuity of their employment. Sixty- five percent of working women work all year, 29 percent work seasonally, and 6 percent work occasionally. The percentage of women who work all year is higher among women who work in nonagricultural occupations than among those working in agriculture (75 percent and 62 percent, respectively), while seasonal employment is high among agricultural workers (34 percent). 30 * Characteristics of Respondents and Women’s Status Table 3.7 Type of employment Percent distribution of currently employed women and men by type of employment (agricultural or nonagricultural), according to type of earnings, and for women according to type of employer and continuity of employment, Uganda 2000-2001 ___________________________________________________________________ Employment Non- characteristic Agricultural agricultural Total ___________________________________________________________________ WOMEN ___________________________________________________________________ Type of earnings Cash only Cash and in-kind In-kind only Not paid Total Type of employer Self-employed Employed by a nonrelative Employed by a relative Total Continuity of employment All year Seasonally Occasionally Total Number1 13.9 68.8 26.6 39.5 20.9 35.3 10.8 1.7 8.7 35.7 8.6 29.4 100.0 100.0 100.0 64.2 58.4 62.8 2.3 31.8 9.2 33.5 9.7 28.0 100.0 100.0 100.0 61.7 74.9 64.8 34.4 12.3 29.2 3.9 12.8 6.0 100.0 100.0 100.0 4,082 1,227 5,316 ___________________________________________________________________ MEN ___________________________________________________________________ Type of earnings Cash only Cash and in-kind In-kind only Not paid Total Number 8.8 79.3 41.3 48.0 13.8 32.2 5.6 0.6 3.3 37.6 6.3 23.2 100.0 100.0 100.0 665 569 1,236 ___________________________________________________________________ 1 Total includes ten women with missing information on occupation. 3.8 CONTROL OVER EARNINGS AND WOMEN’S CONTRIBUTION TO HOUSEHOLD EXPENDITURE Women who were working and receiving cash earnings were asked to state who decides how their earnings are used. In addition, they were asked what proportion of household expenditures were met by their earnings. Data in Table 3.8 show that six out of every ten women decide by themselves how their earnings are to be spent. One in every four working women reported that they make the decision jointly with someone else, while one in six reported that the decision on how to use their earnings is made by someone else entirely. Table 3.8 also shows how respondents’ degree of control over the use of their earnings varies by background characteristics. Regardless of age, the majority of respondents make their own decisions on how their cash earnings are spent. However, older women are more likely to make these decisions than younger women. Unmarried women tend to make their own decisions about Characteristics of Respondents and Women’s Status * 31 32 * Characteristics of Respondents and Women’s Status Table 3.8 Decision on use of earnings and contribution of earnings to household expenditures Percent distribution of currently employed women receiving cash earnings by person who decides how earnings are to be used, and by proportion of household expenditures met by earnings, according to background characteristics, Uganda 2000-2001 _______________________________________________________________________________________________________________ Person who decides Proportion of household how earnings are used expenditures met by earnings ______________________________ ____________________________________ Some- Almost Less Half Background Self one none/ than or characteristic only Jointly1 else2 Missing Total none half more All Missing Total Number ________________________________________________________________________________________________________________ Age 15-19 20-24 25-29 30-34 35-39 40-44 45-49 Marital status Never married Married/living together Divorced, separated, widowed Number of living children 0 1-2 3-4 5+ Residence Urban Rural Region Central Eastern Northern Western Education No education Primary Secondary+ Total 52.2 20.7 27.1 0.0 100.0 24.6 33.2 29.7 12.4 0.0 100.0 339 53.9 26.9 19.2 0.0 100.0 8.4 32.3 38.9 20.4 0.0 100.0 683 57.0 28.7 14.3 0.0 100.0 7.0 29.7 40.1 23.0 0.2 100.0 710 65.3 22.6 12.1 0.0 100.0 3.7 28.8 40.9 26.3 0.2 100.0 560 62.0 23.8 13.9 0.3 100.0 4.9 31.1 34.4 29.2 0.3 100.0 445 66.8 22.6 10.7 0.0 100.0 3.8 30.0 37.7 28.4 0.0 100.0 338 66.3 25.1 7.8 0.7 100.0 4.3 23.5 40.7 30.8 0.6 100.0 213 75.3 9.0 15.7 0.0 100.0 26.5 28.7 31.6 13.2 0.0 100.0 341 49.6 31.9 18.4 0.1 100.0 5.2 30.5 40.3 23.9 0.2 100.0 2,415 94.5 3.7 1.8 0.0 100.0 7.5 30.4 31.6 30.3 0.3 100.0 533 62.4 20.1 17.6 0.0 100.0 20.5 30.1 32.9 16.5 0.0 100.0 478 59.9 24.1 16.0 0.0 100.0 6.9 30.2 41.7 21.0 0.2 100.0 924 57.5 27.3 15.2 0.0 100.0 4.5 30.8 35.6 29.0 0.1 100.0 918 59.8 26.0 14.0 0.3 100.0 5.4 30.0 39.1 25.2 0.3 100.0 969 86.5 9.4 4.0 0.0 100.0 13.9 29.5 39.2 17.4 0.0 100.0 594 53.6 28.4 17.9 0.1 100.0 6.4 30.4 37.7 25.3 0.2 100.0 2,695 83.1 11.4 5.4 0.1 100.0 15.6 35.3 36.7 12.2 0.1 100.0 1,087 48.8 25.8 25.5 0.0 100.0 3.1 30.2 36.7 30.0 0.0 100.0 974 57.7 33.5 8.8 0.0 100.0 8.1 28.6 27.3 36.0 0.0 100.0 140 46.0 36.7 17.2 0.1 100.0 4.1 25.5 41.7 28.3 0.4 100.0 1,088 54.7 28.0 17.1 0.2 100.0 4.8 28.8 37.3 28.9 0.2 100.0 692 55.8 26.4 17.8 0.1 100.0 8.2 30.2 37.3 24.2 0.1 100.0 1,985 77.4 16.9 5.7 0.0 100.0 9.7 32.1 40.9 17.0 0.3 100.0 611 59.6 24.9 15.4 0.1 100.0 7.8 30.3 38.0 23.8 0.2 100.0 3,289 _______________________________________________________________________________________________________________ 1 With husband or someone else 2 Includes husband the use of their earnings, while married women are more likely to involve another person in making the decision. Urban women are more independent in making their own decisions than rural women (87 percent and 54 percent, respectively). In the rural areas, decisions on the use of women’s earnings are made either jointly (28 percent) or by someone else (18 percent). There are notable regional variations in the way decisions are made on how women’s earnings are used. The percentage of women who make decisions on their earnings by themselves ranges from 83 percent in the Central Region to 46 percent in the Western Region. The proportion of women who independently decide how to use their earnings increases with education: 55 to 56 percent for women with primary or less education, compared with 77 percent for women with secondary or higher education. Characteristics of Respondents and Women’s Status * 33 Table 3.9 Control over earnings according to contribution to household expenditures Percent distribution of currently employed women who received cash earnings by person who decides how earnings are used and current marital status, according to proportion of household expenditures met by earnings, Uganda 2000-2001 ___________________________________________________________________________________________________________________________ Currently married or living with a man Not currently married or living with a man_________________________________________________________________ __________________________________ Jointly Jointly Contribution Jointly with Someone with Someone to household Self with someone Husband else Self someone else expenditures only husband else only only Missing Total Number1 only else only Total Number1 ___________________________________________________________________________________________________________________________ Almost none/none Less than half Half or more All Total 77.6 12.3 4.0 6.2 0.0 0.0 100.0 126 81.2 9.8 9.0 100.0 130 59.7 25.3 0.0 14.5 0.3 0.2 100.0 736 83.7 5.2 11.1 100.0 260 45.9 35.3 0.7 17.8 0.2 0.1 100.0 972 89.3 5.2 5.6 100.0 276 36.8 36.5 0.1 26.2 0.3 0.0 100.0 577 91.9 4.7 3.4 100.0 207 49.6 31.4 0.5 18.2 0.2 0.1 100.0 2,415 87.0 5.7 7.2 100.0 874 1 Includes three married women and one unmarried woman with missing information on contribution to household expenditures. When asked the proportion of household expenditures met by their earnings, one in four working women reported that their earnings support the entire household expenditures and 38 percent reported that their earnings constitute half or more of household expenditures. Older women; women who are widowed, divorced, or separated; rural women; and less educated women are more likely to support their households financially. 3.9 CONTROL OVER EARNINGS ACCORDING TO CONTRIBUTION OF HOUSEHOLD EXPENDITURE Table 3.9 shows how decisions on use of women’s earnings are made and the contribution of these earnings to the household expenditure by the respondent’s marital status. Independence in decision-making is inversely related to the proportion of women’s contribution to the household expenses among currently married women, while those who decide with their husband show the reverse pattern. For example, 78 percent of women whose contribution is minimal decide for themselves how the earnings are used. On the other hand, only 37 percent of women who support all household expenses decide by themselves how their earnings are used. Of women who meet the entire household expenditure, 37 percent share the decision with their husband and 26 percent say their husband alone makes decisions. Most women who are not currently married (between 81 percent and 92 percent) make their own decisions, regardless of their contribution to the household expenditures. 3.10 WOMEN’S PARTICIPATION IN HOUSEHOLD DECISIONMAKING In addition to information on women’s education, employment status, and control over earnings, information was obtained on some direct measures of women’s autonomy and status. Specifically, questions were asked on women’s participation in household decisionmaking, on their acceptance of wife beating, and on their opinions about when a wife should be able to deny sex to her husband. Such information provides insight into women’s control over their environment and their attitudes toward gender roles, both of which are relevant to understanding women’s demographic and health behaviour. 34 * Characteristics of Respondents and Women’s Status Table 3.10 Women’s participation in decisionmaking Percent distribution of women by person who has the final say in making specific decisions, according to marital status and type of decision, Uganda 2000-2001 _____________________________________________________________________________________________________ Jointly with Some- Decision Jointly some- one not made/ Household Self with one Husband else not decisions only husband else only only applicable Total Number __________________________________________________________________________________________________ CURRENTLY MARRIED OR LIVING WITH A MAN____________________________________________________________________________________________________ Own health care 43.5 17.7 0.1 37.6 0.9 0.1 100.0 4,881 Large household purchases 11.3 26.5 0.2 60.0 1.6 0.4 100.0 4,881 Daily household purchases 18.9 26.6 0.3 52.5 1.4 0.2 100.0 4,881 Visits to family or relatives 24.8 31.2 0.6 41.7 1.1 0.5 100.0 4,881 What food to cook each day 83.1 6.0 1.3 8.0 1.3 0.2 100.0 4,881 Children’s health care 20.5 37.9 0.5 32.3 1.4 7.4 100.0 4,881 ____________________________________________________________________________________________________ NOT CURRENTLY MARRIED OR LIVING WITH A MAN_____________________________________________________________________________________________________ Own health care 45.6 na 3.9 na 41.9 8.6 100.0 2,365 Large household purchases 30.7 na 4.1 na 53.2 12.0 100.0 2,365 Daily household purchases 31.3 na 4.4 na 52.6 11.7 100.0 2,365 Visits to family or relatives 37.2 na 5.1 na 46.5 11.3 100.0 2,365 What food to cook each day 34.3 na 6.2 na 48.4 11.1 100.0 2,365 Children’s health care 32.8 na 3.7 na 22.0 41.5 100.0 2,365 ________________________________________________________________________________________________ Note: Not currently married refers to never-married, divorced, separated, or widowed women. na=Not applicable To assess women’s decisionmaking autonomy, information was sought on women’s participation in five different types of household decisions: on the respondents’ own health care; on making large household purchases; on making household purchases for daily needs; on visits to family, friends, or relatives; and on what food should be cooked each day. Having a final say in decisionmaking processes is the highest degree of autonomy. Table 3.10 shows the percent distribution of women according to who in the household usually has the final say on each aspect. The autonomy of women in this case would be measured by either their independently making such decisions or jointly deciding on such issues. Results in Table 3.10 indicate that among currently married women, independence in making household decisions ranges from 83 percent on what food to cook daily to a low of 11 percent on large household purchases. Although 44 percent of married women decide on their health care by themselves, husbands make such decisions for 38 percent of women. Husbands are more likely to decide on making large household purchases (60 percent), daily household purchases (53 percent), and visits to family or relatives (42 percent). Decisions on children’s health care are most likely to be made jointly by the respondents and their husbands (38 percent) or by the husbands only (32 percent). Only 20 percent of married women would make independent decisions on their children’s health care. Among nonmarried women, decisions on their own health care are made by the respondents (46 percent) or someone else (42 percent). The remaining decisions are made mostly by either the respondents themselves or by someone else, possibly because the majority are younger women who still live with their parents. Characteristics of Respondents and Women’s Status * 35 Table 3.11 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, Uganda 2000-2001 ________________________________________________________________________________________________________________________ Alone or jointly has final say in: _______________________________________________________________________________ Visits to What None Own Making Making family/ food All of the Background health large daily relatives/ to cook specified specified characteristic care purchases purchases friends daily decisions decisions Number1 ________________________________________________________________________________________________________________________ Age 15-19 20-24 25-29 30-34 35-39 40-44 45-49 Marital status Never married Married/living together Divorced, separated, widowed Number of living children 0 1-2 3-4 5+ Residence Urban Rural Region Central Eastern Northern Western Education No education Primary Secondary+ Employment Not currently employed Employed for cash Employed not for cash Total 24.9 8.4 10.7 20.3 30.4 5.8 57.2 1,615 56.6 27.5 33.9 48.2 76.8 18.9 11.9 1,504 66.4 42.5 51.0 59.1 86.3 33.4 5.2 1,341 71.0 53.5 58.4 65.7 91.3 41.0 2.8 983 71.4 53.4 59.2 66.4 91.6 39.3 2.6 810 74.1 57.9 64.1 71.5 94.5 47.7 2.3 570 76.5 63.5 69.6 77.4 91.9 55.2 1.5 423 27.0 11.6 12.4 19.0 18.0 10.3 66.9 1,456 61.4 38.0 45.8 56.6 90.4 26.1 3.4 4,881 85.5 71.9 73.0 79.4 76.5 69.3 10.8 910 30.0 13.6 16.4 24.5 32.0 11.3 56.3 1,730 61.6 35.3 41.2 54.9 79.9 26.6 8.5 2,021 66.5 45.3 53.4 61.1 90.8 35.1 3.3 1,665 70.8 53.3 58.8 66.1 92.4 40.3 2.0 1,830 65.7 39.6 46.1 58.2 71.0 32.6 19.0 1,207 55.9 36.4 41.8 50.7 74.7 27.5 16.7 6,039 64.7 39.5 45.0 58.4 75.6 31.6 16.6 2,341 50.6 27.7 34.0 34.8 80.3 18.0 15.0 1,956 59.7 41.7 48.0 68.7 55.7 31.8 19.2 1,158 54.2 40.5 45.1 51.3 77.3 33.1 18.7 1,792 63.7 46.8 50.5 59.8 84.5 35.5 6.9 1,584 55.0 33.3 39.4 49.1 72.9 25.1 18.5 4,330 58.3 36.9 43.1 51.6 65.6 30.3 24.8 1,331 44.7 20.7 24.8 39.2 59.5 14.4 31.0 1,917 70.4 50.6 57.9 61.8 88.8 40.4 6.2 3,289 48.7 30.0 34.2 48.0 64.1 21.9 21.6 2,027 57.5 36.9 42.5 51.9 74.1 28.4 17.1 7,246 _______________________________________________________________________________________________________________________ 1 Includes one woman with missing information on education and 11 women with missing information on employment. Table 3.11 shows that although more than one in four women have a say in all five areas of decisionmaking, 17 percent have no say in any of the specified areas. Women’s autonomy increases with age, from 6 percent among women age 15-19 to 55 percent among those 45-49. Women who have never married, have had no children, only have primary education, and who are not employed are the least likely to participate in decisionmaking in the household. Four in ten women who were employed for cash participate in making all decisions at the household level, compared with 22 percent of women who are not employed for cash and 14 percent of unemployed women. This implies that cash employment increases women’s decisionmaking power. 36 * Characteristics of Respondents and Women’s Status 3.11 WOMEN’S AGREEMENT WITH REASONS FOR WIFE BEATING Violence against women is one of the areas that are increasingly being recognised as affecting health-seeking behaviour. Violence against women has serious consequences for their mental and physical well-being, including their reproductive and sexual health (WHO, 1999). In most instances, the abuser is a member of the woman’s own family and the violent incidents take place at home (Centre for Health and Gender Equity, 1999). Wife beating is one of the most common forms of domestic violence worldwide. The 2000-2001 UDHS sought information on what women perceive to be the justifiable circumstances under which husbands can beat their wives. The reasons for wife beating that were asked about in the UDHS were burning the food, arguing with the husband, going out without informing the husband, neglecting the children, and refusing to have sexual relations with the husband. Table 3.12 shows that many women find wife beating justified in certain circumstances. More than three-quarters of Ugandan women agree that at least one of these factors is sufficient justification for wife beating. This is not surprising because traditional norms teach women to accept, tolerate, and even rationalise battery. This norm is a great barrier to women’s empowerment with consequences for their health. The most widely accepted reasons for wife beating are neglecting the children (67 percent) and going out without informing the husband (56 percent). Four in ten women think that arguing with a spouse is justifiable grounds for battery. Only 24 percent and 22 percent of women, respectively, feel that denying sex to the husband and burning food are justifications for wife beating. Table 3.12 also shows women’s perceptions of the justifications for wife beating by background characteristics. Except for urban women and women in the Central Region, two-thirds of women agree with some reason to justify wife beating. In general, younger women, women in rural areas, women in the Northern and Western regions, less educated women, and women who are employed but do not receive cash payment are more likely to agree with at least one of the reasons for wife beating. 3.12 WOMEN’S AGREEMENT WITH REASONS FOR REFUSING SEXUAL RELATIONS Female respondents were asked whether it is justifiable for a wife to withhold sex in the following circumstances: when she knows her husband has a sexually transmitted infection, when her husband has sex with other women, when she has recently given birth, and when she is tired or not in the mood. Overall, women agree that husbands can be denied sex. Two in three women in Uganda agree that all the above reasons are rational justifications for women refusing to have sexual relations with their husband, and only 4 percent agree with none of the reasons. Considering the specific reasons presented above, nine in ten women think that a woman is justified in not having sex with her husband if he has a sexually transmitted infection or if the woman has recently given birth. Younger women, women who have never married, women who have no children, women who live in rural areas and in the Northern Region, women with no education, women who are employed but do not receive cash payment, and women who have no say in household decisions are the least likely to agree with all of the reasons for refusing sex. Characteristics of Respondents and Women’s Status * 37 Table 3.12 Women's attitude toward wife beating Percentage of women who agree that a husband is justified in hitting or beating his wife for specific reasons, by background characteristics, Uganda 2000-2001 ______________________________________________________________________________________________ Husband is justified in hitting or beating his wife if she: Percentage ________________________________________________ who agree 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 Number1 ______________________________________________________________________________________________ Age 15-19 20-24 25-29 30-34 35-39 40-44 45-49 Marital status Never married Married/living together Divorced, separated, widowed Number of living children 0 1-2 3-4 5+ Residence Urban Rural Region Central Eastern Northern Western Education No education Primary Secondary+ Employment Not employed For cash Not for cash Number of decisions in which woman has final say2 0 1-2 3-4 5+ Total 27.1 37.9 58.1 66.9 22.2 78.0 1,615 21.7 36.6 58.8 69.7 23.1 78.6 1,504 19.4 32.7 55.1 67.3 24.3 76.8 1,341 20.7 41.0 54.8 65.8 27.3 74.7 983 19.5 35.4 54.1 66.5 23.1 75.2 810 18.5 37.9 51.8 66.6 24.4 73.1 570 27.9 39.7 57.7 67.2 30.7 73.1 423 22.5 31.3 52.9 64.1 17.6 75.4 1,456 22.6 39.2 57.5 69.2 26.4 77.3 4,881 19.5 33.8 55.3 62.4 23.4 73.5 910 23.7 34.2 54.5 65.3 19.8 75.9 1,730 22.0 37.9 58.1 69.4 23.3 78.4 2,021 20.6 36.5 57.4 68.1 25.8 77.2 1,665 22.4 38.8 54.9 66.3 28.2 74.2 1,830 10.9 20.6 45.0 57.7 12.7 65.6 1,207 24.5 40.2 58.5 69.3 26.5 78.6 6,039 11.2 16.9 45.2 52.5 13.1 63.5 2,341 25.4 45.7 58.9 72.2 24.6 78.5 1,956 42.9 66.8 61.8 80.2 44.3 88.7 1,158 19.7 34.2 64.3 73.0 25.4 83.2 1,792 27.5 44.2 60.2 71.2 32.2 79.7 1,584 22.9 38.7 58.3 68.5 24.7 78.1 4,330 13.5 22.6 45.0 58.9 13.3 67.3 1,331 20.3 33.9 56.4 66.0 19.9 76.1 1,917 16.1 30.9 52.2 63.0 19.8 71.9 3,289 33.9 49.6 63.1 75.8 35.6 84.3 2,027 26.9 35.9 55.9 68.4 23.0 78.1 1,210 27.4 44.0 63.6 71.3 28.3 80.6 1,966 20.8 36.4 56.5 65.8 20.9 76.4 1,427 16.9 32.4 50.9 64.7 23.6 72.7 2,643 22.2 36.9 56.3 67.3 24.2 76.5 7,246 ______________________________________________________________________________________________ 1Includes one woman with missing information on education and 11 women with missing information on employment. 2Either by herself or jointly 38 * Characteristics of Respondents and Women’s Status Table 3.13 Women's attitude toward refusing sex with husband Percentage of women who believe that a wife is justified in refusing to have sex with her husband for specific reasons, according to background characteristics, Uganda 2000-2001 ____________________________________________________________________________________________________ Wife is justified in refusing sex with husband if she: ___________________________________________ Knows Percentage Percentage Knows husband who agree who agree Has husband has with all with none Is tired recently has sex sexually of the of the Background or not given with other transmitted specified specified characteristic in mood birth women disease reasons reasons Number1 ____________________________________________________________________________________________________ Age 15-19 20-24 25-29 30-34 35-39 40-44 45-49 Marital status Never married Married/living together Divorced, separated, widowed Number of living children 0 1-2 3-4 5+ Residence Urban Rural Region Central Eastern Northern Western Education No education Primary Secondary+ Employment Not employed For cash Not for cash Number of decisions in which woman has final say2 0 1-2 3-4 5+ Number of reasons wife beating justified 0 1-2 3-4 5 Total 74.4 83.4 75.5 87.1 61.8 7.6 1,615 80.4 90.7 77.2 91.6 65.4 2.8 1,504 80.6 90.7 75.1 93.3 64.8 3.1 1,341 83.8 91.6 77.8 93.2 68.8 2.7 983 82.4 91.0 76.5 91.2 65.8 3.1 810 79.6 90.5 77.2 93.4 67.0 2.7 570 76.6 88.3 76.4 91.4 65.4 5.2 423 73.9 83.3 76.5 88.6 62.4 7.5 1,456 80.6 90.5 75.8 91.7 65.0 3.2 4,881 82.5 90.4 79.5 92.7 70.3 3.4 910 74.0 83.2 75.0 87.5 60.6 7.2 1,730 80.3 90.4 76.3 91.7 65.6 3.6 2,021 82.5 91.6 76.6 93.1 66.4 2.7 1,665 81.0 90.7 77.7 92.5 67.6 3.1 1,830 84.3 93.4 80.1 93.9 71.0 2.6 1,207 78.5 88.2 75.6 90.7 63.9 4.4 6,039 87.3 95.4 78.4 93.1 70.0 1.9 2,341 84.7 92.3 81.1 92.9 71.4 2.8 1,956 64.7 79.8 64.7 82.6 51.1 11.5 1,158 73.1 83.3 76.2 92.5 60.9 3.5 1,792 73.4 86.9 70.6 89.9 57.7 3.9 1,584 80.0 88.2 77.1 90.7 65.8 4.7 4,330 85.0 94.4 80.9 94.4 71.6 2.5 1,331 77.0 88.4 77.3 87.8 63.2 6.1 1,917 84.0 92.2 77.3 95.0 68.2 1.2 3,289 74.4 84.6 74.0 88.4 61.8 6.9 2,027 70.9 80.7 75.3 85.9 59.7 9.3 1,210 78.3 89.4 76.4 89.1 64.9 5.4 1,966 84.3 93.4 78.7 94.5 68.6 1.7 1,427 81.7 90.3 75.6 93.5 65.8 2.0 2,643 84.1 90.2 76.1 90.2 69.8 5.6 1,705 78.3 88.3 75.3 93.3 63.2 2.8 2,735 76.4 88.0 76.8 89.3 62.1 4.8 2,133 82.4 92.4 80.2 91.3 70.4 3.4 672 79.5 89.1 76.4 91.2 65.1 4.1 7,246 ___________________________________________________________________________________________________ 1Includes one woman with missing information on education and 11 women with missing information on employment. 2Either by herself or jointly Characteristics of Respondents and Women’s Status * 39 Table 3.14 Smoking and alcohol consumption Percentage of women and men who currently smoke, who have consumed alcohol in the past 30 days, who have been drunk in the past 30 days, and who currently smoke and have consumed alcohol in the past 30 days, by background characteristics, Uganda 2000-2001 ________________________________________________________________________________________________________________________________ WOMEN MEN _______________________________________________ ___________________________________________________ Currently Currently smokes smokes and has and has Consumed Been consumed Consumed Been consumed Currently alcohol drunk alcohol Currently alcohol drunk alcohol Background smokes in past in past in past smokes in past in past in past characteristic tobacco 30 days 30 days 30 days Number tobacco 30 days 30 days 30 days Number ________________________________________________________________________________________________________________________________ Age 15-19 20-24 25-29 30-34 35-39 40-44 45-49 50-54 Residence Urban Rural Region Central Eastern Northern Western Marital status Never married Married/living together Divorced, separated, widowed Occupation Prof., tech., manag., & clerical Sales Agriculture/self-employed Skilled manual Unskilled manual Not worked in past 12 months Total 0.7 12.8 2.5 0.2 1,615 2.9 17.1 6.4 1.4 441 2.1 20.1 3.9 0.7 1,504 15.0 39.7 12.0 6.3 321 2.7 28.2 6.2 1.1 1,341 33.2 49.8 25.7 20.8 310 3.9 28.2 7.9 1.6 983 35.0 56.5 29.8 25.9 291 5.6 31.0 8.4 2.8 810 31.7 58.5 30.9 24.9 231 7.2 32.9 11.0 3.3 570 44.2 65.2 39.6 35.1 165 8.0 32.1 9.6 5.4 423 41.1 57.4 44.9 27.8 120 na na na na na 39.4 59.0 32.9 33.5 83 0.8 23.6 6.4 0.5 1,207 19.6 41.0 17.7 10.4 325 3.8 24.1 5.9 1.7 6,039 26.3 45.7 24.0 18.9 1,637 1.2 21.3 5.8 0.5 2,341 24.2 39.2 17.2 13.6 671 0.8 27.1 6.2 0.5 1,956 15.3 46.8 28.6 11.6 523 2.9 34.7 9.5 2.2 1,158 39.8 54.0 30.2 33.0 284 9.0 17.2 3.7 3.5 1,792 28.6 45.6 20.5 20.1 484 0.7 12.4 2.3 0.1 1,456 9.0 25.6 7.6 4.6 675 3.8 26.7 6.5 1.8 4,881 31.9 54.9 30.6 22.8 1,180 4.5 27.8 9.1 2.1 910 53.2 57.6 35.7 39.8 107 0.1 29.4 4.4 0.1 177 14.2 54.5 17.6 11.2 89 0.9 28.4 7.0 0.6 581 20.6 49.4 23.3 13.8 212 4.4 25.7 6.6 2.1 4,428 33.6 52.8 29.1 24.0 996 2.1 26.1 4.7 0.9 145 29.4 46.6 22.2 14.1 102 2.6 27.1 8.3 0.9 420 32.9 46.7 23.8 22.6 181 1.6 15.5 3.3 0.6 1,489 3.4 18.4 7.4 2.4 378 3.3 24.0 6.0 1.5 7,246 25.2 45.0 23.0 17.5 1,962 ___________________________________________________________________________________________________ na = Not applicable 3.12 USE OF TOBACCO AND ALCOHOL The use of tobacco negatively affects the health of the persons consuming it as well as those with whom they share the environment. In particular, use of tobacco has a strong negative health impact on pregnant women. The 2000-2001 UDHS asked men and women whether they smoke, what type of tobacco they smoke, and how many cigarettes they had smoked in the past 24 hours. Alcohol consumption can lead to drunkenness and oftentimes uncontrolled sexual behaviour. The survey asked respondents whether they had ever drunk alcohol, whether they currently drink, and how often they had become drunk in the last 30 days. Table 3.14 gives the results for tobacco and alcohol consumption. The table shows that only 3 percent of women are active tobacco smokers, compared with 25 percent of men. Men smoke an average of four cigarettes per day (data not shown). Overall, one in four women and almost one in two men consumed alcohol at least once in the past 30 days. Among those who drank, one in four women and one in two men got drunk at least once. Eighteen percent of men and less than 2 percent of women both smoke and drink. 40 * Characteristics of Respondents and Women’s Status The percentage of smokers is very low among teenage men (3 percent) but increases rapidly initially and later slowly to a level of 44 percent among men age 40-44 years and declines gradually thereafter. The likelihood of women smoking increases with age. The age pattern for alcohol consumption in the last 30 days is the same as that for smoking. Urban women and men are less likely to engage in smoking and drinking than their rural counterparts. Although women in the Western Region are much more likely to smoke than other women, they are less likely to drink. Unmarried men and women (usually young and with no cash income) are less likely to engage in smoking and drinking than those who are currently married. However, those who are no longer in union show higher levels of indulgence. Women and men who did not work in the 12 months preceding the survey are less likely to drink alcohol than those who worked. However, consumption of alcohol among those who work does not vary much according to the type of occupation. Fertility * 41 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, Uganda 2000-2001____________________________________________ 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 119 192 178 238 354 332 193 319 298 137 278 259 84 203 187 27 83 76 5 44 40 4.0 7.4 6.9 4.0 7.1 6.7 158 258 241 41.3 48.0 47.3 ____________________________________________ Note: Rates are for the period 1 to 36 months preceding the survey, expressed per 1,000 women. Rates for the age group 45-49 may be slightly biased due to truncation. TFR: Total fertility rate for age 15-49, expressed per woman. GFR: General fertility rate (births divided by the number of women 15-44), expressed per 1,000 women. CBR: Crude birth rate, expressed per 1,000 population. FERTILITY 4 This chapter discusses current, cumulative, and past fertility in terms of levels, patterns, and trends that were observed on the basis of the 2000-2001 UDHS and past surveys. Data on fertility were obtained through the birth histories of women age 15-49 interviewed in the 2000-2001 UDHS. Each woman was asked about all of the births she had had in her lifetime. To ensure completeness of the responses, questions were asked separately about sons and daughters who live with the mother, who live elsewhere, and who have died. Subsequently, a list of all births was recorded along with name, age if still alive, and age at death if dead. 4.1 CURRENT FERTILITY LEVELS The current level of fertility is important as it presents the prevailing situation and relates to population policies and programmes. Current fertility can be measured using the age-specific fertility rate (ASFR), the total fertility rate (TFR), the general fertility rate (GFR), and the crude birth rate (CBR). The ASFR provides the age pattern of fertility, while the TFR refers to the number of live births that a woman would have had if she were subject to the current ASFRs throughout her reproductive ages (15–49 years). More generalised indicators of fertility include the number of live births per 1,000 women of reproductive age, which is the GFR, and the number of live births per 1,000 population, which is the CBR. The measures of fertility presented in this chapter refer to the period three years prior to the survey. This generates a sufficient number of births to provide robust and current estimates. The most commonly used measure of current fertility is the TFR. The 2000-2001 UDHS indicated a TFR of 6.9 children per woman, similar to that obtained from the 1995 UDHS. Table 4.1 shows that on average, a Ugandan woman would have 6.9 children by the end of her reproductive years if the current fertility pattern were to prevail. Table 4.1 also presents the GFR (241 live births per 1,000 women) and the CBR (47 live births per 1,000 women). Fertility levels in the urban areas are lower than in the rural areas, irrespective of the woman’s age. This phenomenon has been observed in earlier studies. Consequently, the TFR in the urban areas is much lower than in the rural areas (4.0 and 7.4 children, respectively). However, because of the small proportion of the urban population, this low urban fertility has a small impact on the level of fertility for the country as a whole, which remains high. 42 * Fertility Table 4.1 shows the age pattern of fertility in Uganda. It is evident that fertility starts early in the teen ages, rises rapidly to reach its peak in the 20–24 age group, and declines to only 40 live births per 1,000 women in the oldest age group (45-49 years). The relatively high level of fertility in the youngest age group, which constitutes a large proportion of the women, leads to a large number of births. As shown below, Uganda has the highest TFR of countries in eastern and southern Africa that have recently participated in the DHS programme: Country Year TFR Uganda 2000-2001 6.9 Malawi 2000 6.3 Zambia 1996 6.1 Eritrea 1995 6.1 Ethiopia 2000 5.9 Rwanda 2000 5.8 Tanzania 1999 5.6 Kenya 1998 4.7 Zimbabwe 1999 4.0 4.2 FERTILITY DIFFERENTIALS Fertility is known to vary by residence, educational background, and other background, characteristics of a woman. In this report, the study of fertility differentials is done using the TFR and completed fertility in terms of the mean number of births to women age 40–49 by these characteristics. Table 4.2 and Figure 4.1 show that there is a substantial regional variation in TFRs, ranging from 5.7 births per woman in the Central Region to 7.9 births per woman in the Northern Region. On the other hand, the mean number of births in all regions does not vary significantly (7.1 to 7.2 births per woman 40-49). The difference between the TFR and completed fertility is an indicator of the magnitude and direction of fertility change. For Uganda as a whole, the difference is 0.2 children, which reflects no significant change in the fertility level in the past 20 to 25 years. This is true in the Eastern and Western regions. In the Central Region, the difference is notable (TFR of 5.7 births per woman compared with mean number of children ever born to women 40-49 of 7.2 births). This implies that there has been a decline in fertility in this region. In the Northern Region it appears that fertility may have increased over the past decade or two. The spatial variation is further reflected in the panel, which shows the TFR by whether the districts are covered in the DISH and CREHP (CARE) projects. As a group, all districts in the DISH project and all districts in the CARE project show lower TFRs than those of the districts not covered by either project. Within the five groups of districts included in the DISH project, the TFR varies from 3.4 births per woman in Kampala to 7.4 births per woman in Group I (Mbarara and Ntungamo). Two variables are used as socioeconomic indicators: the woman’s education and the wealth status of her household. These indicators show a strong relationship with fertility levels. The TFR among women with no education (7.8) is twice as high as the TFR among women with secondary education (3.9). Even sharper variations in TFRs are shown by the woman’s wealth. Whereas the Fertility * 43 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, by background characteristics, Uganda 2000-2001___________________________________________________________ Mean number of children ever Total Percentage born to Background fertility currently women age characteristic rate1 pregnant 40-49___________________________________________________________ Residence Urban Rural Region Central Eastern Northern Western Education No education Primary Secondary+ DISH/CREHP districts DISH I Mbarara and Ntungamo II Masaka, Rakai, and Sembabule III Luwero, Masindi, and Nakasongola IV Kamuli and Jinja V Kampala CREHP (Kisoro, Kabale, and Rukungiri Neither Wealth index quintile Lowest Lower middle Middle Upper middle Highest Total 4.0 8.0 6.1 7.4 13.5 7.3 5.7 10.0 7.2 7.4 14.7 7.1 7.9 11.6 7.1 6.9 14.1 7.1 7.8 13.0 7.0 7.3 13.7 7.3 3.9 8.2 6.7 6.0 11.4 7.0 7.4 12.4 6.6 7.2 11.2 7.9 7.1 16.0 6.7 6.2 14.0 6.9 3.4 7.4 6.2 5.9 12.0 6.7 7.3 13.1 7.2 8.5 13.8 7.4 8.2 16.4 7.2 7.5 12.8 7.5 6.3 11.5 6.8 4.1 9.2 6.6 6.9 12.6 7.1 __________________________________________________________ 1 Rate for women age 15-49 TFR for women in the poorest 20 percent of the population is 8.5 births per woman, the TFR for the richest 20 percent is only 4.1 births per woman. At the time of the survey, 13 percent of women reported that they were pregnant. This is a slight decline from the 14 percent observed in the 1995 UDHS. 44 * Fertility 4.3 TRENDS IN AGE-SPECIFIC FERTILITY RATES One way of analysing trends is by comparing current data with those from previous studies. Unfortunately, the three Uganda DHS surveys did not share exactly the same geographic coverage. In the 1988-1989 survey, nine districts in the Northern Region were excluded. In the 1995 UDHS, eight enumeration areas (six in Kitgum District, one in Apac District, and one in Moyo District) were not covered, while in the 2000-2001 UDHS, Kasese and Bundibugyo districts in the Western Region and Gulu and Kitgum districts in the Northern Region were not surveyed. Although the estimates may be influenced by the exclusion of some districts, they provide a useful indicator for examining the changes in fertility that have taken place in Uganda over time. As shown in Figure 4.2, little change is observed. The TFR has barely changed from 7.3 recorded in the 1988-1989 UDHS (referring to mid-1987) to 6.9 recorded in both the 1995 and 2000-2001 UDHS surveys. Another way to examine trends in fertility is to compare age-specific fertility rates from the 2000-2001 UDHS for successive five-year periods preceding the survey, as presented in Table 4.3. Since women age 50 and above were not interviewed in the survey, the rates are successively truncated as the number of years before the survey increases. Generally, only small changes are observed, implying that fertility has remained at the same level over time. Fertility * 45 Table 4.3 Trends in age-specific fertility rates Age-specific fertility rates for five-year periods preceding the survey by mother’s age at the time of the birth, Uganda 2000-2001 ________________________________________________________ Number of years preceding survey _______________________________________ Age group 0-4 5-9 10-14 15-19 ________________________________________________________ 15-19 190 201 199 188 20-24 334 336 349 308 25-29 299 317 323 307 30-34 261 265 282 [282] 35-39 187 221 [249] - 40-44 84 [107] - - 45-49 [39] - - - Note: Age-specific fertility rates are per 1,000 women. Estimates in 4.4 CHILDREN EVER BORN Table 4.4 gives the percent distribution of women by number of children ever born (CEB) for all women as well as for currently married women. The table also shows the mean number of children ever born according to five-year age groups. Childbearing starts early in Uganda. Although the mean number of children ever born among women age 15-19 is 0.3 live births per woman, the figure increases rapidly, and by her late twenties, a woman would have given birth to more than three children and to more than six children by her late thirties. 46 * Fertility Table 4.4 Children ever born and living Percent distribution of all women and currently married women by number of children ever born, mean number of children ever born, and mean number of living children, according to age, Uganda 2000-2001 ___________________________________________________________________________________________________________________________ Mean Mean number number Number of children ever born Number of of ___________________________________________________________________________ of children living Age 0 1 2 3 4 5 6 7 8 9 10+ Total women ever born children ______________________________________________________________________________________________________________________________ ALL WOMEN _____________________________________________________________________________________________________________________________ 15-19 20-24 25-29 30-34 35-39 40-44 45-49 Total 74.4 19.3 5.1 1.0 0.2 0.0 0.0 0.0 0.0 0.0 0.0 100.0 1,615 0.3 0.3 15.6 22.0 30.0 21.4 8.6 2.1 0.3 0.1 0.0 0.0 0.0 100.0 1,504 1.9 1.7 4.4 10.1 14.3 20.7 25.4 15.8 6.2 2.9 0.2 0.1 0.0 100.0 1,341 3.4 2.9 3.5 3.5 6.3 9.0 15.2 18.1 19.7 14.6 6.2 2.4 1.4 100.0 983 5.0 4.2 3.6 4.6 5.4 4.7 8.5 9.2 13.1 17.0 16.1 11.5 6.4 100.0 810 6.1 5.0 4.7 4.1 4.7 3.4 6.3 7.2 8.2 12.3 12.9 14.2 22.0 100.0 570 6.9 5.6 3.7 2.4 2.7 3.8 3.6 9.3 10.1 11.9 12.4 15.1 25.0 100.0 423 7.4 5.8 22.1 12.2 12.0 10.7 10.20 8.00 6.60 6.10 4.4 3.6 4.1 100.0 7,246 3.4 2.9 ___________________________________________________________________________________________________________________________ CURRENTLY MARRIED WOMEN ___________________________________________________________________________________________________________________________ 15-19 20-24 25-29 30-34 35-39 40-44 45-49 Total 32.0 48.8 15.5 3.1 0.5 0.0 0.0 0.0 0.0 0.0 0.0 100.0 466 0.9 0.8 6.0 20.5 34.7 24.8 10.6 2.4 0.3 0.1 0.0 0.0 0.0 100.0 1,150 2.2 1.9 2.3 8.3 12.4 20.5 27.6 18.6 6.9 2.9 0.2 0.2 0.0 100.0 1,078 3.6 3.1 2.5 2.3 5.3 8.5 14.0 18.2 21.3 16.4 7.4 2.5 1.7 100.0 807 5.3 4.4 3.2 4.0 4.1 4.7 7.6 9.2 11.8 17.9 17.5 12.3 7.7 100.0 652 6.3 5.2 3.6 2.3 4.4 2.6 6.2 6.7 8.1 11.1 13.3 16.4 25.3 100.0 431 7.4 5.9 3.3 2.0 1.9 2.7 3.4 8.0 9.7 11.9 12.3 15.7 29.1 100.0 297 7.7 6.1 6.5 12.6 14.3 13.1 12.7 10.0 8.0 7.5 5.5 4.5 5.3 100.0 4,881 4.2 3.5 There is no significant difference in the mean number of children ever born between women in the general population and currently married women, except in the youngest age groups. Among women age 15-19, those in the general population have given birth to 0.3 children, while those who are currently married have had on average almost one child. Differences at older ages reflect the impact of marital dissolution through divorce and widowhood. The last column in Table 4.4 shows the mean number of children who survived. The difference between the mean number of CEB and living children is an indicator of the level of mortality in the population. Since voluntary childlessness is rare in Uganda, it is assumed that most married women with no births are unable to physiologically bear children. The percentage of women who are childless at the end of the reproductive period is an indirect measure of primary infertility (the proportion of women who are unable to bear children at all). Table 4.4 shows that primary infertility is low (about 3 percent). 4.5 BIRTH INTERVALS The study of birth intervals is important in understanding the health status of young children. Previous research has shown that short birth intervals are closely associated with poor health of children, especially during infancy. This is particularly true for children born at intervals of less than 24 months. The study of birth intervals is done using two measures, namely, median birth interval and proportion of non-first births that occur with an interval of 24 months or more after the previous birth. Table 4.5 presents the distribution of second and higher order births in the five years preceding the survey by the number of months since the previous birth, according to background characteristics. The table also presents the median number of months since last birth. Fertility * 47 Table 4.5 Birth intervals Percent distribution of non-first births in the five years preceding the survey by number of months since preceding birth, according to background characteristics, Uganda 2000-2001____________________________________________________________________________________________________ Median number of months Number Months since preceding birth since of Background ________________________________________________ preceding non-first characteristic 7-17 18-23 24-35 36-47 48+ Total birth births____________________________________________________________________________________________________ Age 15-19 20-29 30-39 40+ Birth order 2-3 4-6 7+ Sex of preceding birth Male Female Survival of preceding birth Living Dead Residence Urban Rural Region Central Eastern Northern Western Education No education Primary Secondary+ Total1 26.3 21.2 40.8 9.6 2.1 100.0 24.3 118 10.8 21.1 45.0 15.5 7.6 100.0 27.8 3,385 7.7 14.4 40.5 19.0 18.4 100.0 31.5 2,270 6.1 12.4 34.4 18.6 28.5 100.0 35.2 512 9.9 20.6 42.2 15.9 11.4 100.0 28.6 2,509 9.5 15.8 44.2 17.4 13.1 100.0 29.4 2,362 9.1 16.8 39.9 17.8 16.3 100.0 30.4 1,414 9.2 17.5 42.7 17.3 13.4 100.0 29.4 3,174 10.0 18.4 42.2 16.5 12.9 100.0 29.0 3,110 6.9 17.3 44.8 17.4 13.5 100.0 29.9 5,313 24.4 21.4 29.4 14.0 10.9 100.0 24.7 972 9.4 19.5 32.4 16.6 22.0 100.0 31.0 564 9.6 17.8 43.4 16.9 12.2 100.0 29.1 5,720 10.4 19.4 40.3 15.5 14.5 100.0 28.7 1,664 9.1 20.5 43.5 16.5 10.4 100.0 28.3 1,965 9.5 13.5 41.6 19.8 15.6 100.0 31.8 1,100 9.5 16.4 44.0 16.8 13.3 100.0 29.4 1,555 8.4 16.0 41.0 18.6 16.0 100.0 31.1 1,669 10.1 18.8 43.6 16.2 11.3 100.0 28.5 4,063 9.6 17.8 37.9 16.9 17.7 100.0 30.0 551 9.6 18.0 42.4 16.9 13.1 100.0 29.2 6,285 __________________________________________________________________________________________________ Note: First births are excluded. The interval for multiple births is the number of months since the preceding pregnancy that ended in a live birth. 1Total includes one birth with missing information on mother’s education. Table 4.5 shows that the majority of Ugandan children (72 percent) are born at least 24 months after their previous sibling. Ten percent of births occur less than 18 months after the previous birth. The overall median birth interval is 29 months, which is similar to what was observed in the 1995 UDHS. Children born to younger women tend to have shorter birth intervals than those born to older women. The proportion of births with intervals less than 24 months declines steeply from 48 percent among women age 15-19 to 19 percent among women age 40 and above. The median birth interval increases with age from 24 months among women 15-19 to 35 months among women age 40 or older. There are no strong differentials in median birth interval by residence, region, birth order, or sex of the previous child. However, the survival status of the previous birth has a strong impact on the birth interval. Median birth intervals for births that follow a child who died are five months 48 * Fertility Table 4.6 Age at first birth Percentage of women who have given birth by specified exact ages and median age at first birth, by current age, Uganda 2000-2001 ___________________________________________________________________________________ Percentage who have Median Age at first birth: 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 2.4 na na na na 74.4 1,615 a 4.9 41.9 70.1 na na 15.6 1,504 18.5 6.2 36.7 65.4 82.0 91.6 4.4 1,341 18.9 9.6 43.0 68.8 85.1 93.3 3.5 983 18.6 0.1 40.8 64.1 79.4 89.8 3.6 810 18.8 8.4 42.2 65.9 79.8 89.3 4.7 570 18.7 2.9 45.3 63.2 76.7 89.2 3.7 423 18.5 __________________________________________________________________________________ na = Not applicable a Omitted because less than 50 percent of the women in the age group 15-19 have had a birth by age 15. shorter than those for births following a surviving child (25 months and 30 months, respectively). The percentage of births occurring after a very short interval (less than 18 months) is more than three times higher among births whose previous sibling died than among those whose prior sibling survived. The shorter intervals for the former group is partially due to the shorter breastfeeding period for the previous birth, leading to an earlier return of ovulation and hence increased chance of pregnancy. 4.6 AGE AT FIRST BIRTH The age at which childbearing commences is an important determinant of the overall level of fertility as well as the health and welfare of the mother and the child. In some societies, postponement of first births due to an increase in age at marriage has contributed to overall fertility decline. However, in Uganda, it is not uncommon for women to have children before getting married. Table 4.6 shows the percentage of women who have given birth by specific ages, according to age at the time of the survey. Data in the last column of Table 4.6 show that the initiation of childbearing has not changed much over time. Data from the previous UDHS surveys show the same pattern. This suggests that there has been no significant change in age at first birth in Uganda for the past 30 years. Births to women under age 20 are considered unsafe to both mother and child. The proportion of women who had their first birth before age 15 has shown a decline over time from 10 percent among women age 30-34 to only 2 percent among women age 15-19. However, Table 4.6 also shows that the postponement is for a short time, since two-thirds of women have had a child before they reach age 20. Fertility * 49 Table 4.7 Median age at first birth by background characteristics Median age at first birth among women age 20-49, by current age and background characteristics, Uganda 2000-2001__________________________________________________________________________________________________ Current age Background _____________________________________________________ Age Age characteristic 20-24 25-29 30-34 35-39 40-44 45-49 20-49 25-49__________________________________________________________________________________________________ Residence Urban Rural Region Central Eastern Northern Western Education No education Primary Secondary+ Total 19.9 19.7 18.7 19.2 19.2 18.1 19.4 19.2 18.3 18.8 18.5 18.8 18.6 18.6 18.6 18.7 18.7 18.9 17.8 18.2 18.9 17.5 18.5 18.4 18.1 18.8 18.5 18.8 17.6 17.6 18.4 18.5 17.9 18.5 18.1 19.1 19.2 19.5 18.5 18.8 19.1 19.4 19.3 19.4 19.4 19.7 19.3 19.4 17.8 18.2 17.8 18.6 18.7 18.8 18.3 18.4 18.0 18.6 18.6 18.6 18.5 18.1 18.4 18.5 a 21.1 19.8 21.1 19.3 19.5 a 20.4 18.5 18.9 18.6 18.8 18.7 18.5 18.7 18.8 __________________________________________________________________________________________________ a Omitted because less than 50 percent of the women had a birth before entering the age group. To study differentials in age at first birth, Table 4.7 presents the median age at first birth for different subgroups of the population. Overall, the median age at first birth among women 20- 49 is 18.7 years. The age group 15-19 is excluded because only a small fraction of these women had a birth before age 15. Urban women, women who reside in the Western Region, and better educated women tend to have their first child at a later age than other women. The relationship between education and initiation of childbearing is clear: women with secondary education started having children two years later than those with less education (20.4 years and 18.4 years, respectively). 4.7 TEENAGE PREGNANCY AND MOTHERHOOD For some time now, teenage pregnancy and motherhood has been a major health and social concern in Uganda. Teenage pregnancy is singled out because of its association with higher morbidity and mortality for both the mother and child. In addition to the physiological risks, under the current school practice, pregnant girls have to terminate their education, which may indirectly affect the health of the mother and the child through loss of socioeconomic opportunities. Table 4.8 and Figure 4.3 show the proportion of women age 15-19 years who have begun childbearing, differentiating between those who are already mothers and those who are pregnant for the first time. Overall, 31 percent of teenagers have begun childbearing, with almost 26 percent having had a child already and 6 percent carrying their first child. This is a substantial decline from the 43 percent observed in the 1995 UDHS, which put Uganda at the top for teenage pregnancy among sub-Saharan countries. As expected, the percentage who have started their reproductive life increases with age due to longer exposure, from 3 percent of 15-year-olds to 61 percent of 19-year- olds. Compared with the situation in 1995, the decline in teenage pregnancy has been much faster among younger than older teenagers. Overall, rural teenage women are more likely to have started parenthood than their urban counterparts (34 percent and 23 percent, respectively). Teenage pregnancy also varies greatly with 50 * Fertility Table 4.8 Teenage pregnancy and motherhood Percentage of women age 15-19 who are mothers or pregnant with their first child, by background characteristics, Uganda 2000-20001_______________________________________________________________ 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 Central Eastern Northern Western Education No education Primary Secondary+ Total 1.9 1.4 3.3 300 9.9 3.0 12.9 339 17.1 6.1 23.2 306 43.1 11.0 54.0 379 54.6 6.6 61.2 290 18.8 3.7 22.5 313 27.2 6.3 33.6 1,302 25.9 5.3 31.2 577 29.6 6.9 36.5 401 30.3 4.0 34.3 260 17.6 6.7 24.3 377 50.4 8.5 59.0 148 26.7 6.4 33.1 1,067 13.5 3.2 16.7 400 25.6 5.8 31.4 1,615 the woman’s education (Figure 4.3). Although only 17 percent of girls with secondary education have begun their reproductive life, the corresponding proportion of those with no education is 59 percent. The higher levels of school attendance among urban adolescents, which tends to discourage early childbearing, is believed to account for the lower levels of motherhood and pregnancy among urban teenagers. Fertility Regulation * 51 FERTILITY REGULATION 5 This chapter presents the results for various aspects of contraceptive knowledge, attitudes, behaviour, and sources. Although the focus is on women, some results from the male survey are also presented, since men play an important role in the realisation of reproductive goals. To get an indication of interspousal communication and the extent of agreement in knowledge and attitude of couples about family planning, the responses of men were, where possible, compared with the responses of their wives who live in the same household. 5.1 KNOWLEDGE OF CONTRACEPTIVE METHODS One of the objectives of the UDHS was to develop a profile of Ugandan women and men about their knowledge of family planning methods. Individuals who are adequately informed about their options for methods of contraception are better able to develop a rational approach to planning their family. The level of knowledge of family planning methods was measured in two ways. Respondents were first asked to spontaneously name ways and methods by which couples could delay or avoid a pregnancy. When a respondent failed to name a particular method spontaneously, the interviewer described the method and asked whether the respondent recognised it. For each method recognised, respondents were asked whether they had ever used it. Information was collected for 12 modern methods—the pill, IUD/coil, injectables, diaphragm/cervical cap, foam/jelly, female and male condom, implants, female and male sterilisation, emergency contraception, and lactational amenorrhoea method (LAM)—and two traditional methods—namely periodic abstinence and withdrawal. Provision was also made for respondents to indicate whether they had heard of any other ways or methods to avoid pregnancy. Table 5.1 shows the percentage of women and men who know of any contraceptive method and specific methods according to marital status and sexual activity for those not married. Knowledge of any contraceptive method is almost universal, with 96 percent of all women and 98 percent of all men knowing at least one method of contraception. The level of knowledge among women has increased over time, from 82 percent in 1988-1989 to 92 percent in 1995 and to 96 percent in 2000-2001. Knowledge of at least one contraceptive method is slightly higher among men than among women. However, men are more likely to know of male methods such as male condoms, male sterilisation, and withdrawal. Women are more likely to know about female methods like the pill, IUD, and injectables. Consequently, the mean number of methods known does not show a significant difference by sex except for the sexually inactive and inexperienced, for whom the mean number of contraceptive methods known by men is substantially lower than the mean number known by women. Overall, the most commonly known methods are the pill, injectables, and male condoms, which are known by at least 80 percent of all men and women who have ever been sexually active. Despite the fact that contraceptive implants were only introduced recently in Uganda, this method is known by 41 percent of currently married women and 26 percent of currently married men. Compared to data from the 1995 UDHS, knowledge of implants has increased dramatically from 6 percent among currently married women. The vaginal methods (diaphragm/cervical cap, and foam/jelly) are not well known by either female or male respondents. Emergency contraception is hardly known since it was officially launched only in 2000. 52 * 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, Uganda 2000-2001 ___________________________________________________________________________________________________________________ Women Men __________________________________________ __________________________________________ Unmarried women Unmarried men who ever had sex Un- who ever had sex Un- Cur- ______________ married Cur- ______________ married rently Not women rently Not men who Contraceptive All married Sexually sexually who 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/cervical cap Foam/jelly Female condom Male condom Female sterilisation Male sterilisation Implants Emergency contraception Lactational amenorrhoea (LAM) Any traditional or folk method Periodic abstinence Withdrawal Other Mean no. of methods known Number 96.4 97.8 98.5 97.4 86.7 98.4 98.9 100.0 99.0 95.0 96.2 97.5 97.6 97.3 86.5 98.1 98.7 100.0 98.4 95.0 91.9 94.2 93.5 94.1 75.4 87.7 91.3 90.8 87.5 73.9 50.8 52.7 57.1 57.9 27.0 34.3 37.9 48.5 34.3 16.0 90.5 93.1 93.9 92.4 72.0 80.5 85.5 88.6 79.3 60.6 15.5 15.1 22.8 18.2 11.2 16.1 17.3 20.9 20.5 4.7 19.1 20.2 23.7 19.7 9.9 16.2 17.2 28.0 18.5 6.2 63.2 62.5 76.1 70.2 52.3 71.2 72.4 87.6 79.6 51.9 87.9 87.9 94.2 91.4 81.0 97.0 97.5 100.0 97.4 93.8 75.7 79.1 76.9 78.6 51.2 65.4 71.6 74.5 63.7 41.3 36.4 39.3 29.6 37.5 20.4 45.4 50.8 49.8 43.1 26.8 37.5 40.5 39.0 38.0 19.4 21.9 25.9 24.1 19.2 9.1 10.3 10.2 18.5 12.1 5.1 18.5 22.4 22.5 15.5 6.1 51.4 55.9 54.2 51.1 24.9 33.1 38.0 34.7 36.5 10.6 66.1 68.5 75.8 71.8 41.4 76.5 86.1 85.0 77.4 37.5 54.0 54.7 63.4 61.4 36.6 70.8 81.3 78.0 67.5 33.1 39.3 40.9 58.7 45.1 15.7 52.7 58.0 68.1 61.6 17.9 22.0 24.8 23.0 19.9 3.6 8.0 10.1 7.9 6.5 1.7 7.5 7.7 8.2 7.9 5.1 7.2 7.8 8.2 7.3 4.5 7,246 4,881 268 1,250 848 1,962 1,180 108 355 319 ______________________________________________________________________________________________________________________ 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 Among unmarried sexually active respondents, the pill, injectables, and male condoms are equally well known (94 percent) among women, while for men, knowledge of condoms is universal, followed by the pill and injectables. At least three in four women and men know about female sterilisation, and the lactational amenorrhoea method is known by 54 percent of women and 35 percent of sexually active unmarried men. Traditional methods are less widely recognised by women than by men. Whereas 77 percent of all men know of a traditional method, only 66 percent of all women do. Among women, unmarried sexually active women are the most knowledgeable about traditional methods (76 percent). The most widely known traditional method is periodic abstinence, which is recognised by 54 percent of all women and 71 percent of all men. Four in ten women (39 percent) know about withdrawal. This method is better known by unmarried women who have ever had sex than by currently married women. Fertility Regulation * 53 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, Uganda 2000-2001 __________________________________________________________________________________ Women Men ____________________________ ___________________________ Knows Knows Knows any Knows any Background any modern any modern characteristic method method1 Number method method1 Number __________________________________________________________________________________ Age 15-19 20-24 25-29 30-34 35-39 40-44 45-49 50-54 Residence Urban Rural Region Central Eastern Northern Western Education No education Primary Secondary+ Total 96.2 95.3 466 (100.0) (100.0) 28 98.0 98.0 1,15 99.2 99.2 139 98.8 98.3 1,078 99.6 98.9 237 98.3 98.3 807 100.0 100.0 250 96.8 96.5 652 99.4 98.8 203 98.8 98.8 431 96.2 96.2 146 94.5 94.5 297 100.0 100.0 106 na na na 94.8 94.8 72 99.7 99.6 636 100.0 100.0 148 97.5 97.2 4,245 98.8 98.5 1,032 99.8 99.8 1,377 100.0 100.0 322 99.4 99.3 1,487 100.0 100.0 344 91.7 90.6 823 95.7 94.2 209 97.6 97.5 1,194 98.9 98.9 305 94.3 93.6 1,264 93.0 91.6 92 98.8 98.7 2,978 99.2 99.0 781 99.9 99.9 639 100.0 100.0 307 97.8 97.5 4,881 98.9 98.7 1,180 _______________________________________________________________________________ na = Not applicable 1Pill, IUD, injectables, diaphragm/cervical cap, foam/jelly, female condom, male condom, female sterilisation, male sterilisation, implants, LAM, or emergency contraception ( ) Estimate based on 25 to 49 unweighted cases KNOWLEDGE OF CONTRACEPTIVE METHODS BY BACKGROUND CHARACTERISTICS Table 5.2 shows the percentage of currently married women and men who know of at least one contraceptive method and at least one modern method by background characteristics. Differentials by residence show that knowledge of methods among currently married women is universal in the Central and Eastern regions. Level of knowledge is also high in the Western Region (98 percent) and is lowest in the Northern Region (92 percent). A person’s level of education is positively associated with knowledge of modern methods. Knowledge increases from 94 percent for currently married women with no education to 100 percent among women with secondary or higher education. The variation across age groups is narrow (95 to 99 percent) among women and men (95 to 100 percent). 54 * Fertility Regulation 5.2 EVER USE OF CONTRACEPTION All women interviewed in the 2000-2001 UDHS who said that they had heard of a method of family planning were asked whether they had ever used it. Ever use refers to use of a method at any time with no distinction between past and current use. Table 5.3 shows the percentage of all women, of currently married women, and of sexually active unmarried women who have ever used a contraceptive method by specific method and age. Overall, 41 percent of women have used a method at some time and 35 percent have used a modern method. The level of ever use among currently married women is slightly higher than among all women. However, sexually active unmarried women are much more likely than all women or currently married women to have used contraception at some time. Among all women, the level of ever use of contraception increases with age up to age 25-29 years and then declines steadily. The same pattern was observed in the 1995 UDHS. The male condom was reported as the most commonly ever used method (13 percent), followed closely by the pill and injectables (12 percent), and LAM (10 percent). Other modern methods are much less likely to have been used (each used by 1 percent or less of women). Eleven percent of all women have used periodic abstinence, and 7 percent have used withdrawal. Most sexually active unmarried women have used a male condom (51 percent), which is the most widely used method among sexually active unmarried women. 5.3 CURRENT USE OF CONTRACEPTION Table 5.4 and Figure 5.1 show that the contraceptive prevalence rate (CPR), the percentage of currently married women who are using any method of contraception, is 23 percent. Eighteen percent of married women are using a modern method. The most commonly used methods are injectables (6 percent), LAM (4 percent), and the pill (3 percent), together accounting for about 14 percent of all currently married women or about 60 percent of current users. Use of female sterilisation, IUD, and implants is low, with these methods collectively being used by less than 3 percent of women, i.e., 11 percent of all family planning users. In this table, female condom, diaphragm, cervical cap, and emergency contraception are not shown because the percentage of users is less than 0.1 percent. Table 5.4 also displays the proportion of currently married women using a particular method by age. Use of modern methods increases with age from only 9 percent for women age 15-19 to a peak of 22 percent for women age 35-39, after which it declines to 12 percent for women 45-49. As expected, female sterilisation is most often used by older women, while pills, injectables, and LAM are used by women in the peak of child bearing years (age 20-39). The level of contraceptive use, especially of modern methods, is much higher among sexually active unmarried women (44 percent) than among married women (18 percent). The difference is almost entirely attributable to the greater use of condoms by unmarried women (29 percent) than by currently married women (2 percent). Pills are used by 8 percent of sexually active unmarried women, compared with 3 percent of married women. Figure 5.2 shows the current use of contraceptives among currently married women age 15- 49 in selected countries in eastern and southern Africa for which DHS data are available. Compared with these countries, contraceptive use in Uganda is low. Uganda’s contraceptive prevalence rate is only higher than that of Mozambique (Instituto Nacional de Estatística and Macro International, 1998), Ethiopia (Central Statistical Authority and ORC Macro, 2001), and Rwanda (ONAPO and ORC Macro, 2001). Fertility Regulation * 55 Ta bl e 5. 3 E ve r u se o f c on tr ac ep tio n 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 ag e, U ga nd a 20 00 -2 00 1 __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ M od er n m et ho d Tr ad iti on al m et ho d __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ _ Em er - A ny A ny D ia ph ra gm / Fe m al e M al e ge nc y tr ad i- Pe rio di c A ny A ny tr ad . A ny m od er n In je ct - ce rv ic al Fo am / Fe m al e M al e st er ili - st er ili - co nt ra - tio na l ab s- W ith - fo lk or fo lk A ge m et ho d m et ho d Pi ll IU D ab le s ca p je lly co nd om co nd om sa tio n sa tio n Im pl an ts ce pt io n LA M m et ho d tin en ce dr aw al m et ho d m et ho d N um be r __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ A LL W O M EN __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ 15 -1 9 21 .5 18 .4 2. 8 0. 1 1. 8 0. 0 0. 1 0. 1 14 .4 0. 0 0. 0 0. 0 0. 2 2. 8 8. 3 6. 2 3. 9 0. 4 8. 6 1, 61 5 20 -2 4 45 .5 38 .5 12 .6 0. 2 12 .5 0. 2 0. 2 0. 0 19 .6 0. 5 0. 0 0. 4 0. 1 9. 1 19 .0 13 .2 10 .7 1. 6 20 .0 1, 50 4 25 -2 9 50 .1 44 .2 16 .2 1. 3 18 .1 0. 1 0. 7 0. 1 16 .1 0. 4 0. 1 0. 6 0. 2 12 .8 18 .4 13 .1 8. 6 2. 3 20 .0 1, 34 1 30 -3 4 49 .1 40 .7 16 .8 1. 5 17 .8 0. 1 0. 5 0. 1 11 .0 1. 7 0. 2 0. 7 0. 6 11 .7 20 .2 15 .6 8. 0 3. 3 22 .4 98 3 35 -3 9 45 .7 40 .7 15 .5 2. 0 17 .0 0. 0 1. 0 0. 2 8. 9 3. 5 0. 2 0. 1 0. 2 15 .0 15 .2 10 .8 7. 3 3. 0 17 .5 81 0 40 -4 4 43 .8 35 .6 12 .2 1. 5 13 .1 0. 2 0. 8 0. 0 6. 2 5. 7 0. 1 0. 4 0. 3 10 .5 11 .8 7. 2 6. 0 5. 0 16 .4 57 0 45 -4 9 38 .4 30 .1 8. 6 1. 0 8. 8 0. 0 0. 6 0. 0 3. 5 3. 5 0. 4 0. 3 0. 1 14 .3 13 .3 9. 5 4. 7 5. 4 17 .6 42 3 To ta l 41 .0 34 .9 11 .7 0. 9 12 .2 0. 1 0. 5 0. 1 13 .4 1. 4 0. 1 0. 3 0. 2 9. 8 15 .3 11 .0 7. 3 2. 4 17 .1 7, 24 6 __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ C U RR EN TL Y M A RR IE D W O M EN __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ 15 -1 9 29 .6 22 .1 4 .1 0. 3 4 .1 0. 0 0. 3 0. 0 11 .5 0. 0 0. 0 0. 0 0. 6 7. 0 14 .9 10 .8 7. 8 0. 8 15 .5 46 6 20 -2 4 43 .4 35 .9 12 .8 0. 2 12 .2 0. 1 0. 1 0. 0 14 .9 0. 6 0. 0 0. 5 0. 1 9. 9 18 .6 13 .1 10 .2 1. 6 19 .8 1, 15 0 25 -2 9 48 .7 42 .0 14 .6 1. 6 17 .6 0. 1 0. 6 0. 0 12 .4 0. 5 0. 1 0. 6 0. 1 13 .4 17 .8 12 .9 8. 0 2. 6 19 .7 1, 07 8 30 -3 4 47 .8 39 .3 16 .2 1. 5 18 .7 0. 1 0. 5 0. 1 8 .9 2. 0 0. 2 0. 8 0. 5 11 .3 19 .3 14 .2 8. 3 3. 5 21 .5 80 4 35 -3 9 44 .1 39 .0 13 .7 2. 1 16 .9 0. 0 1. 1 0. 2 6 .4 3. 6 0. 2 0. 1 0. 1 14 .6 14 .8 10 .4 7. 4 3. 1 17 .3 65 2 40 -4 4 45 .1 36 .3 12 .7 1. 3 13 .1 0. 2 0. 8 0. 0 4 .9 7. 1 0. 1 0. 3 0. 4 10 .6 12 .8 8. 3 5. 8 4. 6 17 .3 43 1 45 -4 9 41 .9 32 .7 8 .7 1. 4 9 .6 0. 0 0. 9 0. 0 4 .0 4. 8 0. 5 0. 0 0. 2 14 .8 12 .5 9. 2 4. 6 6. 9 18 .7 29 7 To ta l 44 .1 36 .8 12 .8 1. 2 14 .2 0. 1 0. 6 0. 0 10 .4 2. 0 0. 1 0. 4 0. 2 11 .6 16 .8 12 .0 8. 1 2. 9 19 .0 4, 88 1 __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ SE XU A LL Y A C TI V E U N M A RR IE D W O M EN 1 __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ 15 -1 9 70 .4 67 .0 11 .9 0. 0 5 .8 0. 0 0. 0 0. 4 64 .9 0. 0 0. 0 0. 0 1. 1 3. 1 25 .2 24 .1 5. 1 1. 1 26 .3 93 20 -2 4 75 .4 71 .8 24 .6 0. 0 24 .7 0. 0 2. 7 0. 5 56 .2 0. 0 0. 0 0. 0 0. 5 5. 9 31 .8 18 .5 24 .6 4. 3 33 .2 59 25 + 65 .3 57 .8 24 .6 1. 6 20 .3 0. 0 0. 7 1. 1 37 .9 1. 8 0. 0 0. 0 0. 2 12 .2 27 .0 20 .4 12 .6 3. 4 28 .3 11 6 To ta l 69 .3 64 .1 20 .2 0. 7 16 .2 0. 0 0. 9 0. 7 51 .3 0. 8 0. 0 0. 0 0. 6 7. 7 27 .4 21 .3 12 .7 2. 8 28 .7 26 8 __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ 1 S ex ua lly 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 m on th p re ce di ng th e su rv ey . 56 * Fertility Regulation Ta bl e 5. 4 C ur re nt u se o f c on tr ac ep tio n Pe rc en t d ist rib ut io n of 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 b y co nt ra ce pt iv e m et ho d cu rr en tly u se d an d ag e, U ga nd a 20 00 -2 00 1 __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ M od er n m et ho d T ra di tio na l m et ho d __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ _ __ __ __ __ __ __ __ __ __ __ __ __ A ny A ny Fe m al e M al e tr ad i- Pe rio di c A ny N ot A ny m od er n In je ct - Fo am / M al e st er ili - st er ili - tio na l ab s- W ith - fo lk cu rr en tly A ge m et ho d m et ho d Pi ll IU D ab le s je lly co nd om sa tio n sa tio n Im pl an ts LA M m et ho d tin en ce dr aw al m et ho d us in g To ta l N um be r __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ A LL W O M EN __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ 15 -1 9 10 .4 9. 0 1. 0 0. 0 1. 0 0. 0 5. 7 0. 0 0. 0 0. 0 1. 3 1. 2 1. 0 0. 2 0. 2 89 .6 10 0. 0 1, 61 5 20 -2 4 22 .3 18 .7 3. 7 0. 0 5. 7 0. 0 4. 9 0. 5 0. 0 0. 2 3. 6 3. 2 2. 2 0. 9 0. 4 77 .7 10 0. 0 1, 50 4 25 -2 9 24 .0 20 .2 3. 6 0. 1 7. 2 0. 1 3. 7 0. 4 0. 0 0. 5 4. 4 3. 2 2. 2 1. 0 0. 6 76 .0 10 0. 0 1, 34 1 30 -3 4 25 .1 19 .5 4. 2 0. 2 7. 2 0. 0 2. 1 1. 7 0. 0 0. 5 3. 7 4. 4 3. 6 0. 8 1. 1 74 .9 10 0. 0 98 3 35 -3 9 24 .5 20 .8 2. 9 0. 6 6. 8 0. 2 2. 3 3. 5 0. 0 0. 0 4. 5 2. 8 1. 5 1. 4 0. 9 75 .5 10 0. 0 81 0 40 -4 4 23 .1 17 .3 1. 4 0. 3 5. 0 0. 0 2. 9 5. 7 0. 1 0. 2 1. 8 4. 2 2. 9 1. 3 1. 6 76 .9 10 0. 0 57 0 45 -4 9 13 .2 9. 1 1. 6 0. 1 1. 7 0. 0 0. 3 3. 5 0. 4 0. 0 1. 7 1. 7 1. 0 0. 7 2. 5 86 .8 10 0. 0 42 3 To ta l 20 .1 16 .5 2. 7 0. 2 5. 0 0. 0 3. 8 1. 4 0. 0 0. 2 3. 1 2. 9 2. 0 0. 8 0. 8 79 .9 10 0. 0 7, 24 6 _ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ C U RR EN TL Y M A RR IE D W O M EN __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ _ 15 -1 9 12 .0 9. 0 1. 3 0. 0 2. 4 0. 0 1. 8 0. 0 0. 0 0. 0 3. 5 2. 4 1. 8 0. 6 0. 6 88 .0 10 0. 0 46 6 20 -2 4 21 .0 17 .4 4. 0 0. 0 6. 2 0. 0 1. 9 0. 6 0. 0 0. 3 4. 4 3. 2 2. 1 1. 1 0. 4 79 .0 10 0. 0 1, 15 0 25 -2 9 24 .4 20 .2 3. 6 0. 2 7. 2 0. 1 2. 8 0. 5 0. 0 0. 5 5. 3 3. 5 2. 5 0. 9 0. 8 75 .6 10 0. 0 1, 07 8 30 -3 4 26 .6 20 .8 4. 6 0. 2 8. 2 0. 0 1. 3 2. 0 0. 0 0. 6 4. 0 4. 8 3. 8 1. 0 1. 0 73 .4 10 0. 0 80 7 35 -3 9 25 .8 21 .5 2. 5 0. 5 8. 0 0. 2 1. 6 3. 6 0. 0 0. 0 5. 1 3. 2 1. 6 1. 6 1. 1 74 .2 10 0. 0 65 2 40 -4 4 26 .7 19 .9 1. 8 0. 3 5. 7 0. 0 2. 6 7. 1 0. 1 0. 3 2. 0 5. 0 3. 7 1. 3 1. 8 73 .3 10 0. 0 43 1 45 -4 9 18 .0 12 .1 1. 6 0. 1 2. 4 0. 0 0. 4 4. 8 0. 5 0. 0 2. 4 2. 4 1. 4 1. 0 3. 5 82 .0 10 0. 0 29 7 To ta l 22 .8 18 .2 3. 2 0. 2 6. 4 0. 0 1. 9 2. 0 0. 0 0. 3 4. 2 3. 6 2. 5 1. 1 1. 0 77 .2 10 0. 0 4, 88 1 __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ _ SE XU A LL Y A C TI V E U N M A RR IE D W O M EN 1 __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ 15 -1 9 51 .6 47 .5 5. 4 0. 0 2. 6 0. 0 39 .5 0. 0 0. 0 0. 0 0. 0 4. 1 4. 1 0. 0 0. 0 48 .4 10 0. 0 93 20 -2 4 54 .2 50 .1 8. 5 0. 0 8. 6 0. 0 33 .0 0. 0 0. 0 0. 0 0. 0 3. 6 3. 6 0. 0 0. 6 45 .8 10 0. 0 59 25 + 42 .9 38 .1 9. 2 1. 6 6. 7 0. 2 18 .5 1. 8 0. 0 0. 0 0. 0 3. 9 1. 9 2. 0 1. 0 57 .1 10 0. 0 11 6 To ta l 48 .4 44 .0 7. 7 0. 7 5. 7 0. 1 29 .0 0. 8 0. 0 0. 0 0. 0 3. 9 3. 0 0. 9 0. 5 51 .6 10 0. 0 26 8 __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ 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 S ex ua lly 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 m on th p re ce di ng th e su rv ey . Fertility Regulation * 57 UDHS 2000-2001 Figure 5.1 Contraceptive Use among Currently Married Women 15-49 Traditional/folk methods 5% LAM 4% Female sterilisation 2% Clinical methods (IUD/coil, injectables and implants) 7% Supply methods (pill and condom) 5% Not using 77% Figure 5.2 Contraceptive Use (Percent) in Selected Eastern and Southern African Countries, 1996-2001 56 54 39 31 26 25 23 13 8 6 South Africa 1998 Zimbabwe 1999 Kenya 1998 Malawi 2000 Zambia 1996 Tanzania 1999 Uganda 2000-2001 Rwanda 2000 Ethiopia 2000 Mozambique 1997 DHS surveys 1996-2001 1 In the 1988-1989 and 1995 surveys, LAM was not specifically asked about; consequently, if mentioned by a respondent, it was written in as an “other” method and was tabulated as a traditional method. In the 2000- 2001 UDHS, LAM was asked about specifically and is tabulated as a modern method. 58 * Fertility Regulation Figure 5.3 Trends in the CPR among Currently Married Women 15-49 years 5 3 2 15 8 7 23 18 5 Any method Modern methods Traditional or folk methods 1988-1989 UDHS 1995 UDHS 2000-2001 UDHS UDHS 2000-2001 The contraceptive prevalence rate among currently married women has increased steadily from 5 percent in 1988-1989 to 15 percent in 1995 and 23 percent in 2000-2001 (Figure 5.3).1 The rate in the 2000-2001 UDHS shows an increase of more than 50 percent of the 1995 levels, with the greatest increase being in the use of modern methods (18 percent compared with 8 percent). Use of traditional family planning methods declined from 7 percent in 1995 to 5 percent in 2000- 2001. It should be noted that the increase in the use of family planning methods has not yet had much impact on the fertility levels, which only declined slightly from 7.1 children per woman in 1988-1989 to 6.9 children per woman in the 2000-2001. The current contraceptive method mix indicates a shift in the contraceptive behaviour of married Ugandan women. The use of injectables increased rapidly from 3 percent in 1995 to 6 percent in 2000-2001 and became the predominant method. Use of the pill, which was the most popular method in 1995, did not show any change (3 percent). Condom use has also increased from 1 percent in 1995 to 2 percent in 2000-2001. In the 2000-2001 UDHS, about half of pill users use the Pillplan brand that is distributed by the social marketing programme (data not shown). Fertility Regulation * 59 CURRENT USE OF CONTRACEPTION BY BACKGROUND CHARACTERISTICS Table 5.5 and Figure 5.4 show the percent distribution of currently married women by the contraceptive method currently used according to background characteristics. Urban women are much more likely to be using contraceptive methods than rural women (46 percent compared with 19 percent). The difference is more pronounced for modern method use (42 percent compared with 15 percent). Urban and rural women are equally likely to use traditional methods, especially periodic abstinence (3 percent). There are large differentials in contraceptive use by region. Although 37 percent of currently married women in the Central Region use contraception, the percentage in the other regions ranges between 15 percent and 21 percent. For traditional methods, the range is between 5 percent and 2 percent. Use of family planning methods increases with the woman’s education. It ranges from 13 percent for women with no formal education to 21 percent for women with primary education and 49 percent for women with secondary or higher education. The differentials for modern and traditional method use are similar. Contraceptive use is positively associated with the number of living children, as would be expected. The percentage of currently married women using any method rises rapidly from 4 percent among women with no living child to 27 percent among those with three or more children. Data in Table 5.5 show that Ugandan couples tend to adopt family planning after they have several living children. The last panels in Table 5.5 present the level of contraceptive use according to whether a woman lives in a district covered in the DISH or CREHP project and the woman’s wealth status. Overall, women who live in DISH districts have the highest contraceptive use, while those who live in CREHP districts have the lowest. Among districts included in the DISH project, Kampala has the highest level use of (54 percent), while districts in Group I (Mbarara and Ntungamo) and Group IV (Kamuli and Jinja) have the lowest contraceptive prevalence rate (16 to 17 percent). Use of contraception is positively associated with the woman’s socioeconomic status. Whereas contraceptive use among women in the lowest three quintiles ranges between 14 percent and 17 percent, contraceptive prevalence for women in the next-to-highest group is 24 percent, and for women in the highest quintile, it is 46 percent. CURRENT USE OF CONTRACEPTION BY WOMEN’S STATUS In this survey, women’s status is measured indirectly through selected questions about women’s participation in household decisionmaking, their attitudes toward women’s ability to refuse sex with their husband, and their attitudes toward wife beating. Table 5.6 shows the percent distribution of currently married women by contraceptive method currently used, according to selected indicators of women’s status. It is evident from these data that women who participate in more household decisions are more likely to use modern methods of contraception. On the other hand, women who had no say in household decisions are more likely to use traditional methods. Use of contraception is positively associated with the number of situations in which women feel it is justifiable to refuse sexual relations. For example, 13 percent of women who find no reason for refusing sexual relations use contraception, compared with 24 percent of women who agree with three or four reasons. Regarding the number of reasons to justify wife beating, women who agree with fewer reasons are more likely to use a method of contraception. 60 * Fertility Regulation Ta bl e 5. 5 C ur re nt u se o f c on tr ac ep tio n by b ac kg ro un d ch ar ac te ris tic s 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, U ga nd a 20 00 -2 00 1 __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ _ M od er n m et ho d T ra di tio na l m et ho d _ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ _ __ __ __ __ __ __ __ __ __ __ __ An y An y Fe m al e M al e tra di - Pe rio di c An y N ot Ba ck gr ou nd An y m od er n In je ct - Fo am / M al e st er ili - st er ili - Im - tio na l ab st i- W ith - fo lk 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 je lly co nd om sa tio n sa tio n pl an t LA M m et ho d ne nc e dr aw al m et ho d us in g To ta l N um be r __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ _ Re si de nc e U rb an R ur al Re gi on C en tra l E as te rn N or th en W es te rn Ed uc at io n N o ed uc at io n P rim ar y S ec on da ry + N um be r of li vi ng c hi ld re n 0 1 2 3 4 + D IS H /C RE H P di st ri ct s D IS H I M ba ra ra a nd N tu ng am o II M as ak a, R ak ai , a nd S em ba bu le II I L uw er o, M as in di , a nd N ak as on go la IV K am ul i a nd Ji nj a V K am pa la C RE H P (K iso ro , K ab al e, a nd R uk un gi ri) N ei th er W ea lth in de x qu in til e L ow es t L ow er m id dl e M id dl e U pp er m id dl e H ig he st To ta l 46 .3 41 .6 11 .8 0. 6 15 .3 0. 2 5. 0 3. 7 0. 1 1. 6 3. 4 4. 2 2. 7 1. 5 0. 6 53 .7 10 0. 0 63 6 19 .3 14 .7 1. 9 0. 1 5. 0 0. 0 1. 4 1. 7 0. 0 0. 1 4. 3 3. 5 2. 5 1. 0 1. 1 80 .7 10 0. 0 4, 24 5 37 .0 31 .4 7. 5 0. 4 10 .5 0. 1 3. 8 3. 3 0. 0 0. 7 5. 2 4. 2 2. 1 2. 1 1. 4 63 .0 10 0. 0 1, 37 7 14 .5 11 .2 1. 1 0. 1 4. 2 0. 0 1. 6 2. 0 0. 1 0. 2 1. 9 1. 9 1. 7 0. 2 1. 4 85 .5 10 0. 0 1, 48 7 21 .0 15 .4 0. 9 0. 1 3. 9 0. 0 0. 6 0. 5 0. 0 0. 0 9. 4 5. 2 5. 0 0. 2 0. 3 79 .0 10 0. 0 82 3 18 .0 13 .6 2. 5 0. 2 6. 0 0. 1 0. 9 1. 5 0. 0 0. 2 2. 3 3. 8 2. 1 1. 7 0. 6 82 .0 10 0. 0 1, 19 4 13 .2 9. 4 1. 1 0. 0 2. 4 0. 0 0. 7 1. 1 0. 0 0. 0 3. 9 3. 0 2. 3 0. 6 0. 8 86 .8 10 0. 0 1, 26 4 21 .2 16 .8 2. 5 0. 2 5. 9 0. 0 1. 5 1. 7 0. 1 0. 3 4. 5 3. 3 2. 1 1. 2 1. 1 78 .8 10 0. 0 2, 97 8 49 .1 42 .2 10 .6 0. 2 16 .1 0. 2 5. 9 5. 1 0. 1 0. 9 3. 2 6. 1 4. 4 1. 7 0. 8 50 .9 10 0. 0 63 9 4. 1 3. 3 0. 9 0. 0 0. 3 0. 0 1. 3 0. 9 0. 0 0. 0 0. 0 0. 5 0. 2 0. 3 0. 3 95 .9 10 0. 0 41 4 18 .0 13 .7 3. 7 0. 0 4. 3 0. 0 2. 6 0. 2 0. 0 0. 0 2. 8 4. 1 3. 1 0. 9 0. 3 82 .0 10 0. 0 73 2 21 .0 17 .9 3. 7 0. 2 7. 3 0. 0 1. 7 0. 8 0. 0 0. 3 3. 9 2. 4 2. 0 0. 5 0. 6 79 .0 10 0. 0 79 3 27 .3 21 .9 3. 9 0. 1 6. 7 0. 0 2. 3 1. 2 0. 1 0. 5 7. 2 4. 6 2. 7 1. 9 0. 8 72 .7 10 0. 0 74 8 27 .0 21 .4 3. 0 0. 3 7. 8 0. 1 1. 7 3. 5 0. 1 0. 4 4. 5 4. 1 2. 8 1. 2 1. 6 73 .0 10 0. 0 2, 19 4 28 .1 23 .6 5. 2 0. 3 7. 5 0. 1 2. 8 2. 8 0. 0 0. 8 4. 2 3. 6 2. 1 1. 5 0. 8 71 .9 10 0. 0 1, 33 1 16 .2 9. 8 1. 2 0. 2 4. 0 0. 0 1. 6 1. 6 0. 0 0. 0 1. 2 5. 8 2. 9 2. 9 0. 6 83 .8 10 0. 0 28 0 23 .8 18 .6 2. 9 0. 4 7. 7 0. 0 2. 3 1. 6 0. 0 0. 0 3. 7 3. 7 2. 1 1. 6 1. 6 76 .2 10 0. 0 32 7 27 .4 22 .9 1. 9 0. 0 4. 0 0. 0 1. 0 3. 3 0. 0 0. 0 12 .7 4. 5 0. 7 0. 8 0. 0 72 .6 10 0. 0 15 8 16 .8 14 .5 1. 0 0. 3 3. 1 0. 0 2. 1 5. 2 0. 0 0. 6 2. 2 0. 9 0. 8 0. 1 1. 3 3. 2 10 0. 0 26 2 53 .8 50 .0 16 .8 0. 3 16 .1 0. 3 5. 9 2. 8 0. 0 2. 8 4. 9 3. 5 1. 7 1. 7 0. 3 46 .2 10 0. 0 30 3 16 .8 14 .3 2. 8 0. 1 6. 2 0. 0 0. 2 1. 7 0. 0 0. 7 2. 6 2. 0 1. 0 1. 0 0. 6 83 .2 10 0. 0 29 4 21 .1 16 .4 2. 4 0. 1 5. 9 0. 0 1. 7 1. 7 0. 1 0. 1 4. 3 3. 7 2. 8 0. 9 1. 1 78 .9 10 0. 0 3, 25 6 15 .1 11 .3 0. 9 0. 0 2. 0 0. 0 1. 0 1. 3 0. 0 0. 0 6. 1 2. 9 2. 7 0. 3 0. 8 84 .9 10 0. 0 1, 04 2 13 .7 9. 3 0. 6 0. 0 3. 0 0. 0 1. 4 0. 5 0. 0 0. 0 3. 9 3. 8 3. 0 0. 8 0. 6 86 .3 10 0. 0 1, 02 9 17 .2 11 .9 2. 0 0. 0 3. 8 0. 0 0. 5 1. 4 0. 0 0. 0 4. 2 3. 6 2. 5 1. 1 1. 7 82 .8 10 0. 0 94 5 23 .8 19 .5 2. 2 0. 4 9. 2 0. 1 2. 3 1. 9 0. 0 0. 1 3. 2 3. 4 1. 3 2. 1 0. 9 76 .2 10 0. 0 92 6 45 .8 40 .6 10 .7 0. 5 14 .6 0. 1 4. 6 5. 1 0. 2 1. 4 3. 3 4. 2 2. 9 1. 3 1. 0 54 .2 10 0. 0 93 9 22 .8 18 .2 3. 2 0. 2 6. 4 0. 0 1. 9 2. 0 0. 0 0. 3 4. 2 3. 6 2. 5 1. 1 1. 0 77 .2 10 0. 0 4, 88 1 N ot e: I f 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. Fertility Regulation * 61 23 46 19 37 15 21 18 13 21 49 15 14 17 24 46 UGANDA RESIDENCE Urban Rural REGION Central Eastern Northern Western EDUCATION No education Primary Secondary+ WEALTH INDEX QUINTILE Lowest Lower middle Middle Upper middle Highest UDHS 2000-2001 Figure 5.4 Contraceptive Use among Currently Married Women 15-49 by Background Characteristics 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, Uganda 2000-2001 ___________________________________________________________________________________________ Type of method ___________________________________________ Any Any Any Not Women’s Any modern traditional folk using any status method method method method method Total Number ___________________________________________________________________________________________ Number of decisions in which woman has final say1 0 18.6 11.0 6.6 0.9 81.4 100.0 153 1-2 15.3 12.3 2.2 0.8 84.7 100.0 1,591 3-4 25.0 19.9 3.9 1.2 75.0 100.0 1,304 5-6 28.0 22.7 4.3 1.0 72.0 100.0 1,833 Number of reasons a wife can refuse sex with her husband 0 13.0 12.0 1.0 0.0 87.0 100.0 156 1-2 19.7 14.9 3.9 1.0 80.3 100.0 592 3-4 23.6 18.9 3.6 1.0 76.4 100.0 4,133 Number of circumstances in which wife beating is justified 0 27.1 21.6 4.3 1.2 72.9 100.0 1,106 1-2 24.1 19.8 3.4 0.9 75.9 100.0 1,765 3-4 19.1 14.9 3.0 1.2 80.9 100.0 1,526 5 19.4 15.2 4.1 0.1 80.6 100.0 484 Total 22.8 18.2 3.6 1.0 77.2 100.0 4,881 ____________________________________________________________________________________________ Note: If more than one method is used, only the most effective method is considered in this table. 1Either by herself or jointly with others 62 * Fertility Regulation 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, according to current age, Uganda 2000-2001 ___________________________________________________________________________________________ Number of living children at Never time of first use of contraception used _________________________________________________ contra- Current age ception 0 1 2 3 4+ Missing Total Number ___________________________________________________________________________________________ 15-19 20-24 25-29 30-34 35-39 40-44 45-49 Total 69.6 16.0 11.9 1.8 0.4 0.0 0.2 100.0 521 55.4 9.9 18.4 11.7 3.3 1.0 0.4 100.0 1,274 50.7 5.9 16.8 12.7 7.9 6.0 0.0 100.0 1,258 50.7 4.2 11.7 6.0 6.7 20.5 0.1 100.0 958 54.2 2.8 10.1 5.5 4.8 22.5 0.0 100.0 792 56.0 1.6 10.0 2.2 4.2 26.0 0.1 100.0 567 61.4 3.0 8.9 2.9 3.5 19.9 0.3 100.0 421 55.2 6.3 13.7 7.7 4.9 12.0 0.2 100.0 5,790 __________________________________________________________________________________________ a Omitted because less than 50 percent of respondents in the age group have had a child at time of first use of contraception. 5.4 NUMBER OF CHILDREN AT FIRST USE OF FAMILY PLANNING Couples may use contraceptive methods for either spacing births or limiting family size. UDHS respondents were asked the number of living children they had when they first used contraception. This information enables an examination of the cohort changes in the timing of adoption of contraceptive use. Table 5.7 shows the distribution of ever-married women by the number of living children at the time of first use of contraception, according to age. The results indicate that Ugandan women are gradually adopting family planning at an earlier age. Younger cohorts reported first use at lower parities than older women. For example, women age 40-44 reported using contraception after having more than four births, compared with no children or one child among women under age 30. From another perspective, although 16 percent of ever-married women age 15-19 started using contraception before they had any children, the proportion of women age 30-34 is 4 percent and that of women 45-49 is 3 percent. 5.5 KNOWLEDGE OF THE FERTILE PERIOD An elementary knowledge of reproductive physiology provides a useful background for successful practice of coitus-associated methods such as the calendar method, the Billings method, and other methods collectively called periodic abstinence. The successful use of these methods depends in part on an understanding of when during the ovulatory cycle a woman is most likely to conceive. Fertility Regulation * 63 Table 5.8 shows the percent distribution of women by knowledge of the fertile period during the ovula- tory cycle according to whether they use periodic abstinence as a family planning method. Correct knowledge of the fertile period is deficient among all women as well as among those who are currently using peri- odic abstinence. Thirty-seven percent of women either said they did not know when they were most likely to conceive or said “any time.” Only 18 percent of all women correctly mentioned that a woman is most likely to conceive in the middle of the ovulatory cycle. Women who are currently using a method of periodic abstinence do indeed know more about the ovulatory cycle than women who do not use the method. However, only one-third of women who reported using periodic abstinence gave the correct response on when the fertile period occurs. 5.6 SOURCE OF SUPPLY OF CONTRACEPTIVES Information on the source of modern contraceptive methods is useful for family planning managers and implementers. In the 2000-2001 UDHS, women who reported using a method of contraception at the time of the survey were asked where they obtained the method the last time. Table 5.9 and Figure 5.5 show the percent distribution of current users of modern contraceptive methods by the most recent source of supply. Thirty-six percent of users obtained their methods from a public (government) source, while private sources are reported by almost half (46 percent) of current users. Other private sources account for the remaining 16 percent of modern contraceptive users. Among sources in the public sector, hospitals and health centres are the most common sources (15 percent and 13 percent, respectively). The source of contraception varies according to the method. Whereas only three in ten pill users obtained their pill from a source in the public sector, seven in ten women who were sterilised had the operation at public sector source, most often in a government hospital. The most common source for the pill and injectables is a private clinic or hospital or, for pill users, a pharmacy/drug shop, while four in ten condom users obtain their condoms from a shop. There has been a significant shift in source of family planning supply from that recorded in the 1995 UDHS. Public sources declined from 47 percent to 36 percent, while the private medical sources increased from 42 percent to 46 percent. Although public sources continue to provide the majority of female sterilisation, the percentage of users of the pill and injectables who obtain the method from a government facility has declined. For the pill, the percentage has declined from 39 percent in the 1995 UDHS to 31 percent in the 2000-2001 UDHS, and for injectables, the decline is from 61 percent to 47 percent. In 1995, 24 percent of condom users obtained the condoms from a public sector source, while in 2000-2001 the corresponding percentage is 9 percent. Table 5.8 Knowledge of fertile period Percent distribution of women who use periodic abstinence, of women who do not use periodic abstinence, and of all women, by knowledge of the fertile period during the ovulatory cycle, Uganda 2000-2001 Nonusers Users of of Perceived periodic periodic All fertile period abstinence abstinence women Just before period begins 7.7 7.2 7.2 During menstrual period 0.0 0.8 0.8 Right after period has ended 41.2 36.1 36.2 Halfway between periods 33.3 17.6 17.9 No specific time 5.3 8.4 8.4 Other 0.3 0.3 0.3 Don't know 11.2 29.4 29.0 Missing 1.0 0.2 0.2 Total 100.0 100.0 100.0 Number 147 7,099 7,246 64 * Fertility Regulation Table 5.9 Source of contraception Percent distribution of current users of modern contraceptive methods by most recent source of supply, according to specific method, Uganda 2000-2001__________________________________________________________________ Female Inject- Male sterili- Source of supply Pill ables condom sation Total1__________________________________________________________________ Public sector Government hospital Government health centre Family planning clinic Outreach Government CBD agent Other Private medical sector Private clinic/hospital Pharmacy/drug shop Private doctor/nurse/midwife Outreach NGO CBD agent Other Other source Shop Religious institution Friends/relatives Other Missing Total Number 30.7 46.6 9.1 67.3 35.8 7.5 13.9 1.8 58.3 15.2 12.0 22.9 5.0 3.4 12.9 7.1 6.5 0.6 5.6 5.2 0.6 0.1 0.5 0.0 0.3 1.7 0.3 0.8 0.0 0.7 1.8 2.8 0.4 0.0 1.5 67.1 51.3 33.2 29.8 45.8 48.9 47.1 20.7 26.3 36.6 16.9 1.2 11.5 0.0 7.1 0.7 1.3 0.0 0.0 0.6 0.0 0.2 0.0 0.0 0.1 0.0 0.2 1.1 0.0 0.4 0.5 1.3 0.0 3.6 1.0 1.7 1.3 52.6 0.0 15.6 1.5 0.0 40.1 0.0 11.6 0.0 0.5 0.0 0.0 0.2 0.2 0.8 12.5 0.0 3.9 0.0 0.2 4.8 0.0 1.4 0.5 0.7 0.3 2.8 1.4 100.0 100.0 100.0 100.0 100.0 198 361 272 105 969 1Includes 2 users of male sterilisation, 19 IUD users, 23 implants users, and 3 users of foam or jelly. CBD = Community-based distribution NGO = Non-governmental organisation UDHS 2000-2001 Figure 5.5 Distribution of Current Users of Modern Contraceptive Methods by Source of Supply Other public 3% Govt. hospital 15% Govt. health centre 13%Family planning clinic 5% Private hospital 37% Pharmacy 7% Other 18% Other private medical 2% Fertility Regulation * 65 Table 5.10 Informed choice Among current users of modern contraceptive methods who adopted the current method in the five years preceding the survey, percentage who were informed about the side effects of the method used, percentage who were informed what to do if side effects were experienced, and percentage who were informed of other methods that could be used for contraception, by specific method, initial source of method, and background characteristics, Uganda 2000-2001________________________________________________________________________ Informed what Informed of Method, source, Informed about to do if side other methods background side effects effects were that could be characteristic of method used1 experienced1 used2 ________________________________________________________________________ Method Female sterilisation 28.9 24.5 35.4 Pill 53.2 45.0 62.6 Injectables 70.1 67.0 68.3 Other na na 33.3 Initial source of method Public sector 69.1 66.2 75.9 Government hospital 62.3 63.3 68.7 Government health center 76.1 66.9 80.9 Family planning clinic 73.5 76.5 85.0 Private medical sector 58.0 50.9 58.4 Private hospital, clinic 58.4 51.1 58.4 Pharmacy/drug shop (60.1) (50.4) (54.6) Other source 0.0 21.2 29.7 Residence Urban 59.2 58.4 65.9 Rural 58.7 52.3 50.2 Region Central 52.1 49.6 57.1 Eastern 67.3 61.9 62.5 Northern 64.5 55.8 34.0 Western 67.4 60.4 58.3 Education No education 45.2 48.5 43.4 Primary 59.9 52.2 50.9 Secondary+ 61.0 59.4 67.5 Total 58.9 54.5 55.0 Number3 692 692 920 _______________________________________________________________________ na = Not applicable ( ) = 25-49 cases 1 Among users of female sterilisation, pill, IUD, and injectables 2 Among users of female sterilisation, pill, IUD, injectables, diaphragm, foam, jelly, and LAM 3 Total includes one woman with missing information on education. 5.7 INFORMED CHOICE Women who are currently using a modern method of contraception and adopted the method in the five years preceding the survey were asked whether they were informed about the side effects of the methods they were using, what to do if they experienced any side effects, and whether they were informed about other methods of contraception they could use. Table 5.10 shows that 59 percent of women were informed about the side effects of the method, while 55 percent were informed about what to do about the side effects. A similar proportion was also informed about alternative methods. 66 * Fertility Regulation 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, Uganda 2000-2001 ______________________________________________________________________________________ Number of living children1 ___________________________________________ Intention 0 1 2 3 4+ Total ______________________________________________________________________________________ Unsure Intends to use Does not intend to use Missing Total Number 15.0 13.5 9.4 8.5 8.2 9.7 39.6 61.4 63.2 70.2 62.6 62.1 45.2 25.0 27.2 21.3 29.1 28.0 0.3 0.1 0.2 0.0 0.2 0.2 100.0 100.0 100.0 100.0 100.0 100.0 256 584 629 585 1,715 3,769 ______________________________________________________________________________________ 1Includes current pregnancy The quality of information varies according to the method used. Due to the small number of users of the IUD/coil and implants, data are not shown for these methods. The majority of women who use injectables were well informed; 70 percent were informed about side effects, 67 percent knew what to do when they had side effects, and 68 percent were informed about other available methods of contraception. More than half (53 percent) of pill users were informed about side effects, 45 percent were informed about what to do if they experienced side effects, and 63 percent were told about other contraceptive methods. It is worth noting that less than 30 percent of the sterilised women were informed about side effects, 25 percent were informed about what to if they experienced side effects, and 35 percent were informed about other methods. Contraceptive users who obtained their methods from a public source were more likely to have received information about the method than those who went to a private source. Differentials by residence show that urban women are slightly better informed than rural women. There are regional differences in the information given to contraceptive users, with women in the Central region being the least informed about the side effects of the method they are using and what to do if side effects are experienced. On the other hand, women in the Northern region are the least likely to be informed of other methods that they could use. The woman’s level of education is positively associated with the provision of information about the method’s side effects. Whereas 45 percent of women with no education were informed about side effects, the corresponding percentage for women with primary or higher education is 61 percent. The same pattern is observed for the other two types of information. 5.8 FUTURE USE OF CONTRACEPTION An important indicator of the changing demand for family planning is the extent to which women who are not using contraception intend to use family planning in the future. Currently married women who were not using contraception at the time of the survey were asked whether they intended to use family planning methods in future. The results are presented in Table 5.11 according to the number of living children. The table reveals that of the currently married nonusers, 62 percent intend to use in future, while 28 percent have no intention to use any method and 10 percent are not sure of their intention. There has been an increase in the percentage of nonusers who intend to use family planning from 55 percent in the 1995 UDHS. Fertility Regulation * 67 Table 5.12 Reason for nonuse of 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, Uganda 2000-2001_______________________________________________________ Age ________________ Preferred method 15-29 30-49 Total_______________________________________________________ Fertility-related reasons Infrequent sex/no sex Menopausal/hysterectomy Subfecund/infecund Wants children Opposition to use Opposed to family planning Partner opposed Others disapprove Religious prohibition Lack of knowledge Knows no method Knows no source Method-related reasons Health concerns Side effects Lack of access/too far Cost Inconvenient Interferes with body's normal processes Other Don't know/ missing Total Number 2.2 8.1 6.0 0.0 8.7 5.7 5.9 32.6 23.3 12.3 9.7 10.6 3.9 4.0 4.0 9.7 5.2 6.8 0.0 0.2 0.1 4.7 2.8 3.5 3.6 2.7 3.1 1.8 1.8 1.8 9.6 3.8 5.8 30.2 10.9 17.6 0.9 0.2 0.4 2.1 1.2 1.6 1.5 0.7 1.0 1.4 1.9 1.7 7.5 4.2 5.3 2.7 1.2 1.7 100.0 100.0 100.0 368 688 1,056 The proportion of women who intend to use contraception varies with the number of living children. For example, the proportion of women who intend to use contraception is 40 percent for childless women, 63 percent for women with two living children, and 70 percent for women with three living children. On the other hand, the proportion of women who do not intend to use contraception is highest among childless women (45 percent) and lowest among women with three or more living children (21 percent). 5.9 REASONS FOR NONUSE OF CONTRACEPTION All currently married women who were not using a method of contraception and said that they had no intention to use in the future were asked the main reason for not intending to use a method. The results are presented in Table 5.12. Over- all, the most commonly cited reasons for not using contraception are difficulty in becoming pregnant (23 percent), side effects (18 percent), and desire to have children (11 percent). Among women under age 30, the most frequently cited reasons for not using a method are side effects (30 per- cent), followed by desire for children (12 percent), partner opposed and health concerns (10 percent each). Although difficulty in getting pregnant was the most common reason for not using family planning among older women (33 per- cent), fear of side effects and wanting more children were other important reasons (11 and 10 percent, respectively). Menopause (9 percent) and infrequent or no sex (8 percent) were other main rea- sons for nonuse cited by women 30 years old or older. 5.10 PREFERRED METHOD OF CONTRA- CEPTION FOR FUTURE USE Asking nonusers who indicated an intention to use family planning methods in the future which method they would prefer to use can assess potential demand for specific methods of family planning. Table 15.13 shows the percent distribution of currently married women who are not using a contraceptive method but who intend to use in the future by preferred method and age. It is worth noting that 16 percent of women who say that they want to use contraception do not specify the method. Overall, 46 percent of women want to use injectables, 21 percent want to use the pill, 6 percent want to be sterilised, and 3 percent want to use implants. Differences by age group are minimal. 68 * Fertility Regulation Table 5.13 Preferred method of contraception for future use Percent distribution of currently married women who are not using a contraceptive method but who intend to use in the future by preferred method, according to age, Uganda 2000-2001 _______________________________________________________ Age ________________ Preferred method 15-29 30-49 Total _______________________________________________________ Pill IUD/coil Injectables Diaphragm Condom Female sterilisation Male sterilisation Periodic abstinence Withdrawal Implants Lactational amenorrhoea Female condom Foam and jelly Other Unsure Total Number 20.9 20.8 20.8 0.7 0.8 0.7 48.0 44.6 45.7 0.0 0.1 0.1 1.6 2.6 2.3 7.9 5.7 6.4 0.2 0.0 0.1 1.9 1.8 1.9 0.5 0.0 0.2 2.4 3.7 3.3 0.2 0.3 0.3 0.1 0.3 0.2 0.0 0.1 0.1 2.0 2.2 2.1 13.7 17.0 15.9 100.0 100.0 100.0 770 1,570 2,341 The pattern of preferred method has changed since the 1995 UDHS. In 1995, the pill was the first choice (32 percent), followed closely by inject- ables (31 percent). 5.11 EXPOSURE TO FAMILY PLANNING MESSAGES Information about the level of public exposure to family planning mes- sages allows policymakers and pro- gramme managers to ensure the use of the most effective means for targeting various groups in the population. To assess the effectiveness of family plan- ning messages from different sources, respondents were asked whether they had heard or seen messages about fam- ily planning on the radio, television, in printed materials, at community meet- ings, or by mobile van during the six months before the interview. Table 5.14 shows the percentage of women who had been exposed to family planning messages through various mass media or other sources, according to background characteristics. Radio is the most frequent source of messages: 62 percent of women listened to radio messages about family planning in the six months prior to the interview. One-third of women saw a family planning message on a billboard, while about one-fifth were exposed to messages at community meetings. Newspapers, television, and mobile vans are less common means of conveying family planning messages. Three in ten women were not exposed to any of the specified sources of family planning messages. Sharp contrasts in exposure to family planning messages are observed between the urban and rural respondents. Although at least 30 percent to 83 percent of urban women had heard or seen a family planning message in the mass media, the range for rural women was between 5 percent and 58 percent. Overall, women in the Central Region and better educated women are the most likely to have been exposed to family planning messages. 5.12 CONTACT OF NONUSERS WITH FAMILY PLANNING PROVIDERS In the UDHS, women were asked whether in the last 12 months they had received a visit from a community-based distribution agent (CBDA) or a community reproductive health worker (CRHW). They were also asked whether they had attended a health facility in the last 12 months and, if so, whether a health worker at the facility spoke to them about family planning methods. This information is useful for determining whether nonusers of family planning are being reached by family planning programmes in Uganda. Table 5.15 displays the results. Fertility Regulation * 69 Table 5.14 Exposure to family planning messages Percentage of women who heard or saw a family planning message in the past six months, by source of message and background characteristics, Uganda 2000-2001_______________________________________________________________________________________________ Com- None of Background Tele- Newspaper/ munity Mobile the specified characteristic Radio vision magazine Billboards meetings van sources Number1 _______________________________________________________________________________________________ Age 15-19 20-24 25-29 30-34 35-39 40-44 45-49 Residence Urban Rural Region Central Eastern Northern Western Education No education Primary Secondary+ Total 57.0 10.4 17.2 33.5 13.9 9.2 35.8 1,615 63.4 9.8 16.0 35.6 18.7 9.8 29.1 1,504 66.2 9.5 15.9 35.2 24.0 8.6 26.6 1,341 65.6 7.3 15.8 33.9 29.2 9.6 25.6 983 57.6 7.4 12.3 31.3 22.3 7.8 33.5 810 62.9 7.5 12.9 31.1 26.2 7.5 29.9 570 56.8 7.6 10.0 25.4 19.0 5.3 38.6 423 82.6 29.9 38.1 58.5 21.5 17.5 11.0 1,207 57.5 4.8 10.6 28.4 20.9 7.0 34.7 6,039 77.4 19.2 26.1 56.6 19.3 11.5 14.7 2,341 59.3 5.3 12.5 28.0 20.6 7.2 31.3 1,956 27.6 2.7 4.7 8.8 4.8 2.4 68.2 1,158 66.0 3.5 10.6 24.9 34.3 10.9 27.0 1,792 44.4 2.7 3.1 17.2 17.7 4.5 48.6 1,584 61.6 5.8 10.1 31.7 20.6 7.4 30.7 4,330 82.7 26.8 46.3 58.4 26.3 18.3 9.8 1,331 61.7 9.0 15.2 33.4 21.0 8.8 30.8 7,246 _______________________________________________________________________________________________ 1Total includes one woman with missing information on education. Eighty-six percent of nonusers reported that they had neither been visited by a CBDA/CRHW nor discussed family planning with a health worker at a health facility. This figure is slightly higher than that reported in the 1995 UDHS (84 percent). Forty-two percent of women were not visited by a CBDA/CRHW, and although they went to a health facility, family planning was not discussed while they were at the facility. The corresponding percentage in the 1995 UDHS is 34 percent. These figures can be interpreted as a missed opportunity by health service providers to inform a fairly large segment of noncontracepting women about their reproductive options. At the national level, only 6 percent of women age 15-49 had been contacted by a CBDA/CRHW in the last 12 months. Visits by a CBDA/CRHW are not common anywhere; urban women are as likely as rural women to be visited by a CBDA/CRHW (6 percent). Women in the Eastern Region were the most likely (9 percent) and women in the Northern Region were the least likely (3 percent) to have received a visit from a CBDA/CRHW in the past 12 months. 70 * Fertility Regulation Table 5.15 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 staff person about family planning methods in the 12 months preceding the interview, according to background characteristics, Uganda 2000-2001 _________________________________________________________________________________________________________________ Visited by a family planning worker _____________________________________________________ Yes No Neither ________________________ _______________________ visited by Attended Attended FP worker health facility, Didn’t health facility, Didn’t Data on nor discussed FP1 attend discussed FP1 attend visit by discussed Background ______________ health _______________ health FP worker FP at characteristic Yes No facility Yes No facility missing facility Total Number _________________________________________________________________________________________________________________ Age 15-19 20-24 25-29 30-34 35-39 40-44 45-49 Residence Urban Rural Region Central Eastern Northern Western Education No education Primary Secondary+ Total 0.6 1.2 1.4 2.4 32.6 61.7 0.1 94.3 100.0 1,447 2.2 2.1 1.2 10.8 50.1 33.6 0.1 83.6 100.0 1,169 1.5 2.0 1.2 12.1 47.0 36.1 0.1 83.1 100.0 1,020 3.6 3.9 2.2 13.6 42.5 34.1 0.1 76.5 100.0 737 3.2 2.3 2.5 9.1 42.9 39.6 0.4 82.5 100.0 611 1.5 1.5 1.7 6.0 39.0 50.2 0.2 89.2 100.0 438 0.4 3.6 1.4 4.9 37.4 52.3 0.0 89.7 100.0 367 2.2 2.1 1.2 9.2 42.8 42.5 0.0 85.3 100.0 771 1.7 2.2 1.6 8.2 41.6 44.4 0.1 86.1 100.0 5,018 2.0 1.9 1.0 7.7 43.2 44.1 0.0 87.3 100.0 1,610 3.4 3.4 2.4 13.0 46.5 31.2 0.0 77.8 100.0 1,675 0.7 1.1 1.4 7.1 35.1 54.6 0.0 89.8 100.0 963 0.5 1.7 1.3 4.9 39.3 51.8 0.5 91.1 100.0 1,540 1.1 1.3 1.4 6.8 41.0 48.4 0.0 89.4 100.0 1,399 1.8 2.2 1.5 9.0 42.4 42.9 0.2 85.2 100.0 3,549 2.7 3.4 2.1 8.2 40.8 42.7 0.1 83.5 100.0 841 1.8 2.2 1.6 8.4 41.8 44.2 0.1 86.0 100.0 5,788 ________________________________________________________________________________________________________________ 1Spoke with health facility staff about family planning methods Women’s level of education is positively associated with visits by a CBDA/CRHW: women with secondary or higher education are the most likely (8 percent) and women with no education are the least likely (4 percent) to have been visited by a CBDA/CRHW in the past 12 months. A woman’s age is strongly related to whether she has contact with family planning staff, either through a CBDA/CRHW visit or at a health facility. There is a an inverted U-shaped pattern for family planning contact, with the youngest and the oldest women being the least likely to have contact and women age 20-39 the most likely to have contact. The low level of family planning contact among young women is because they are less likely to visit a facility. Among women who went to a health facility, women 15-19 are less likely to have received family planning messages than older women. Fertility Regulation * 71 Table 5.16 Attitudes of couples toward family planning Percent distribution of currently married women who know of a method of family planning by approval of family planning and their perception of their husband's attitude toward family planning, according to background characteristics, Uganda 2000-2001 _________________________________________________________________________________________________________________ Respondent approves of Respondent disapproves of family planning family planning ____________________________ ______________________________ Husband Husband’s Husband Husband’s Background Husband dis- attitude Husband dis- attitude Respondent characteristic approves approves unknown approves approves unknown unsure Total Number ________________________________________________________________________________________________________________ Age 15-19 20-24 25-29 30-34 35-39 40-44 45-49 Residence Urban Rural Region Central Eastern Northern Western Education No education Primary Secondary+ Total 39.7 15.5 25.6 0.5 6.3 3.5 8.8 100.0 449 50.4 17.7 18.4 1.5 5.0 1.9 5.0 100.0 1,127 50.6 19.3 17.3 1.1 3.9 1.9 5.9 100.0 1,064 45.3 23.5 16.3 1.5 6.3 2.5 4.5 100.0 794 42.2 21.4 19.8 0.9 6.7 3.4 5.6 100.0 631 41.6 22.1 19.4 1.2 5.8 2.7 7.2 100.0 426 31.5 14.6 23.4 0.7 14.1 6.5 9.1 100.0 281 63.0 16.2 12.5 1.3 2.7 1.6 2.7 100.0 634 42.9 20.0 20.1 1.2 6.4 2.9 6.5 100.0 4,138 52.2 21.9 15.3 1.4 4.7 2.3 2.2 100.0 1,373 42.7 20.7 22.2 1.1 4.5 2.6 6.2 100.0 1,479 34.0 17.4 21.3 0.4 9.9 6.1 10.8 100.0 754 49.1 16.5 17.9 1.6 6.7 1.1 7.1 100.0 1,165 29.5 19.2 24.9 1.1 9.4 4.6 11.4 100.0 1,192 46.8 20.6 18.9 1.2 5.4 2.3 4.7 100.0 2,941 70.2 15.3 8.7 1.1 1.8 0.9 1.9 100.0 639 45.6 19.5 19.1 1.2 5.9 2.7 6.0 100.0 4,772 5.13 ATTITUDES OF COUPLES TOWARD FAMILY PLANNING Effective use of contraceptives is facilitated when couples have positive attitudes toward family planning. The attitudes of couples were assessed by asking women about their own attitudes and what they perceived as their husband’s attitude about couples using family planning. This information is useful for assessing the need for further education and publicity and for redesigning strategies to increase acceptance and use of family planning. The results presented in Table 5.16 show the percent distribution of currently married women who know of a method of family planning, by their own attitude toward family planning and their perception of their husband’s attitude toward family planning, according to background characteristics. Overall, 84 percent of married women approve of family planning, 47 percent believe that their husband approves, and 25 percent believe that their husband does not approve of family planning methods. It is notable that 22 percent of women do not know how their husband feels about family planning. The data show a slight increase in women who approve of contraceptive use from 79 percent in the 1995 UDHS. However, the percentage of women who believe their husband approves of family planning remains at the same level (46 percent in 1995 compared with 47 percent in 2000- 2001). 72 * Fertility Regulation Table 5.17 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, Uganda 2000-2001 _____________________________________________________________________________________________ Number of times _____________________________________________ 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 56.8 33.2 10.0 0.0 100.0 449 37.4 37.2 24.8 0.7 100.0 1,127 35.0 39.2 25.4 0.4 100.0 1,064 35.5 39.2 25.1 0.1 100.0 794 47.9 29.2 22.8 0.2 100.0 631 50.6 29.5 19.3 0.6 100.0 426 66.8 23.5 9.5 0.2 100.0 281 42.7 35.1 21.9 0.4 100.0 4,772 Where there is a perceived disagreement between spouses, respondents are more likely to report that their husband disapproves of family planning (20 percent) while the respondent approves, than that their husband approves while the respondent disapproves (1 percent). The likelihood that a woman will report that both she and her husband approve of family planning is highest among women age 25-29 (51 percent) and declines thereafter with age to 32 percent among women age 45-49. The level of both wife and husband approving is higher among the urban women (63 percent) than rural women (43 percent). The level of approval of family planning by a couple is highest in the Central region (52 percent) and lowest in the Northern region (34 percent). Approval of family planning is positively associated with the woman’s education. 5.14 DISCUSSION OF FAMILY PLANNING WITH HUSBAND Table 5.17 provides information on the percentage of currently married women who know of at least one contraceptive method by the number of times family planning was discussed with their husband in the past year, according to age. The 2000-2001 UDHS data indicate that 57 percent of women reported having discussed family planning with their husband. Women 20-39 are the most likely to have frequent discussions with their husband. Four in ten women had never discussed family planning with their husband in the past year. Other Proximate Determinants of Fertility * 73 OTHER PROXIMATE DETERMINANTS OF FERTILITY 6 This chapter explores the paramount circumstances, other than contraception, that affect a woman’s chances of becoming pregnant. These are referred to as other proximate determinants of fertility and include marriage and sexual intercourse, postpartum amenorrhoea and abstinence from sexual relations, and secondary infertility. The principal interest of the UDHS programme in the subject of nuptiality is that marriage is the leading indicator of exposure of women to the risk of pregnancy and therefore is important for the understanding of fertility. Marriage here refers to those recognised by civil and religious laws, as well as by the community. In most societies, marriage sanctions childbearing and married women are exposed to a greater risk of becoming pregnant than unmarried women. Thus, women in populations in which age at marriage is low tend to start childbearing early and have a high fertility level. For this reason, this chapter explores the trends in age at marriage. This chapter also includes information on more direct measures of the beginning of exposure to pregnancy and the level of exposure, namely, age at first sexual intercourse and the frequency of intercourse. Finally, measures of several other proximate determinants of fertility, which, like marriage and sexual intercourse, influence exposure to the risk of pregnancy, are presented. These are duration of postpartum amenorrhoea, postpartum abstinence, and secondary infertility. 6.1 CURRENT MARITAL STATUS The respondent’s marital status at the time of the survey is presented in Table 6.1 and Figure 6.1. In this table, the term “married” includes legal or formal marriage, while “living together” designates an informal union. However, in tables in this report, these two categories are combined and referred to collectively as “currently married” or “currently in union”. Respondents who are widowed, divorced, and not living together (separated) make up the remainder of the “ever- married” or “ever-in-union” category. Overall, two in three women age 15-49 are either formally married (45 percent) or in some other type of union (22 percent). One in five women have never been married, while about 13 percent are divorced, widowed, or no longer living together. The proportion of women who have never married declines sharply with age, and by age 30, almost all women have married. The reverse relationship is true for the married category as well as the widowed and divorced categories. The proportion of women in formal unions increases with age and peaks at age 35-39. The decline after age 40 could be the result of widowhood, divorce, and separation. As expected, older women are more likely to be widowed or divorced than young women. On the other hand, there is no clear age pattern for those who are not living together. The age pattern of marriage is similar to that observed in the 1995 UDHS and the 1991 Population and Housing Census. Men depict a pattern of marriage similar to that of women. However, men are more likely to have never been married (34 percent) than women (20 percent). Among the ever-married, men are more likely than women to stay married. This is partly due to remarriage and polygyny, which does not classify them as widowed or divorced. 74 * Other Proximate Determinants of Fertility Table 6.1 Current marital status Percent distribution of women and men by current marital status, according to age, Uganda 2000-2001____________________________________________________________________________________________ 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 Total 67.7 16.7 12.2 0.0 0.1 3.2 100.0 1,615 15.3 47.4 29.1 0.7 0.8 6.7 100.0 1,504 6.2 55.2 25.1 2.4 0.2 10.8 100.0 1,341 2.6 55.3 26.8 4.0 1.3 10.1 100.0 983 2.2 56.6 23.9 6.4 1.1 9.7 100.0 810 0.6 56.4 19.1 9.3 2.2 12.3 100.0 570 0.5 52.3 18.0 13.4 4.5 11.4 100.0 423 20.1 45.1 22.3 3.4 1.0 8.2 100.0 7,246 ____________________________________________________________________________________________ MEN____________________________________________________________________________________________ 15-19 20-24 25-29 30-34 35-39 40-44 45-49 50-54 Total 93.5 5.5 0.9 0.0 0.0 0.1 100.0 441 54.7 38.0 5.2 0.3 0.1 1.8 100.0 321 16.7 69.6 6.9 0.1 1.0 5.8 100.0 310 4.6 77.8 8.0 0.0 1.3 8.3 100.0 291 4.5 81.7 6.0 2.8 0.6 4.3 100.0 231 3.9 84.8 3.9 2.0 2.7 2.8 100.0 165 3.5 86.5 1.7 1.7 1.9 4.7 100.0 120 1.0 78.0 8.7 0.0 0.0 12.2 100.0 83 34.4 55.3 4.8 0.7 0.8 4.0 100.0 1,962 Other Proximate Determinants of Fertility * 75 Table 6.2 Number of co-wives Percent distribution of currently married women by number of co-wives, according to background characteristics, Uganda 2000-2001___________________________________________________________________ Number of co-wives___________________________ Don't Background know/ characteristic 0 1 2+ missing Total Number____________________________________________________________________ Age 15-19 20-24 25-29 30-34 35-39 40-44 45-49 Residence Urban Rural Region Central Eastern Northern Western Education No education Primary Secondary+ Total 79.1 14.3 6.2 0.3 100.0 466 74.5 16.4 9.0 0.2 100.0 1,150 68.1 21.8 9.9 0.2 100.0 1,078 60.4 27.6 11.1 0.9 100.0 807 60.7 25.4 13.3 0.6 100.0 652 62.0 27.0 10.9 0.1 100.0 431 59.8 23.5 14.9 1.8 100.0 297 63.6 22.3 13.4 0.6 100.0 636 67.9 21.7 9.9 0.4 100.0 4,245 63.6 19.6 15.8 1.0 100.0 1,377 65.0 25.0 9.9 0.1 100.0 1,487 63.2 26.8 9.4 0.6 100.0 823 77.5 17.0 5.4 0.1 100.0 1,194 65.2 22.9 11.5 0.5 100.0 1,264 68.0 22.0 9.5 0.5 100.0 2,978 68.5 19.0 12.3 0.2 100.0 639 67.3 21.8 10.4 0.5 100.0 4,881 6.2 POLYGYNY A man who is married to more than one woman is considered to be in a polygynous union. A monogamous union is one in which the husband has only one wife. The analysis of marriage relations is important for understanding the implications of different types of marriage on fertility behaviour. Table 6.2 presents the distribution of currently married women by number of co-wives, according to background characteristics. Overall, one in three married women in Uganda is in a polygynous union. This figure is slightly higher than that recorded in the 1995 UDHS (32 percent in 2000-2001 compared with 30 percent in 1995). In the 2000-2001 UDHS, two in three women in a polygynous union have only one co-wife (22 percent) compared with 10 percent who have two or more co-wives. The prevalence of polygynous unions increases with age; young women are more likely to be in a monogamous marriage than older women. The proportion of married women in a monogamous union declines from 79 percent for women age 15-19 to 60 percent for women age 45-49. Women who live in urban areas are slightly more likely to be in a polygynous union. Women in the Western region are less likely to be in a polygynous union than women in the other three regions, while women in the Central region are more likely to have multiple co-wives than women in other regions. Women with no education are slightly more likely to have co-wives than better educated women. It is interesting to note that women with secondary or higher education are just as likely to have two or more co-wives as women with primary education. 76 * 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, Uganda 2000-2001____________________________________________________________________________________________ WOMEN____________________________________________________________________________________________ Median Percentage who were first married by exact age: Percentage 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 20-49 25-49 6.6 na na na na 67.7 1,615 a 15.2 53.9 74.7 na na 15.3 1,504 17.7 15.5 49.9 71.3 83.8 91.3 6.2 1,341 18.0 16.8 52.6 74.4 85.1 92.4 2.6 983 17.8 17.1 52.3 72.3 84.6 92.7 2.2 810 17.8 21.0 59.5 76.7 87.9 94.8 0.6 570 17.4 22.2 55.8 72.0 82.4 90.9 0.5 423 17.5 16.9 53.2 73.5 na na 6.4 5,631 17.8 17.6 52.9 73.0 84.7 92.3 3.2 4,127 17.8 ____________________________________________________________________________________________ MEN____________________________________________________________________________________________ Median Percentage who were first married by exact age: Percentage age at_________________________________________ never first Current age 20 22 25 28 30 married Number marriage____________________________________________________________________________________________ 20-24 21.5 36.8 na na na 54.7 321 na 25-29 33.0 50.7 75.4 82.3 na 16.7 310 21.9 30-34 25.2 47.5 70.4 88.7 92.5 4.6 291 22.3 35-39 18.5 44.2 69.8 80.1 86.4 4.5 231 22.7 40-44 26.9 43.6 72.3 85.7 91.9 3.9 165 22.6 45-49 33.7 51.6 70.9 80.5 85.7 3.5 120 21.9 50-54 16.9 36.7 65.0 76.8 83.7 1.0 83 22.8 25-54 26.4 46.8 71.5 83.3 87.6 7.3 1,200 22.3____________________________________________________________________________________________ na = Not applicable a Omitted because less than half of women in the age group x to x+4 have married by age x. 6.3 AGE AT FIRST MARRIAGE Marriage is the leading social and demographic indicator of exposure of women to the risk of pregnancy, especially in the case of low levels of contraceptive use. Early marriages, in the Ugandan context where use of family planning is limited, lead to early childbearing and a longer period of exposure of women to reproductive risks, which lead to high cumulative fertility levels. Table 6.3 presents the percentage of women and men who were married by specific ages. Although the minimum legal age for a woman to get married is 18 years in Uganda, the 2000-2001 UDHS results show that the median age at first marriage among women 25-49 is just before 18 years and has been fairly stable for the past 30 years. Marriage among young girls is a common practice. Among women age 20-49, 17 percent were married by age 15 and more than half were married by age 18. A similar pattern is seen among women age 25-49. However, the trend has shifted toward fewer women marrying at very young ages. Only 7 percent of women age 15-19 were married before age 15 compared with 22 percent of women age 45-49. Other Proximate Determinants of Fertility * 77 Table 6.4 Median age at first marriage Median age at first marriage among women age 20-49 and men age 25-54, by current age and background characteristics, Uganda 2000-2001______________________________________________________________________________________________________ Current age (women) Women Men Background __________________________________________________ ______________ _____ characteristic 20-24 25-29 30-34 35-39 40-44 45-49 20-49 25-49 25-54______________________________________________________________________________________________________ Residence Urban Rural Region Central Eastern Northern Western Education No education Primary Secondary+ Total 19.7 19.7 18.7 18.5 17.9 17.6 19.0 18.7 24.5 17.3 17.8 17.7 17.7 17.3 17.5 17.6 17.7 22.0 18.2 18.4 17.9 17.9 17.8 17.3 18.1 18.0 23.6 16.9 17.6 17.8 17.5 16.5 16.7 17.2 17.4 21.6 17.1 17.6 16.8 17.9 17.3 17.7 17.3 17.4 21.8 18.0 18.4 18.2 18.1 17.9 18.4 18.2 18.2 22.2 16.9 17.1 16.7 17.3 16.9 17.1 17.0 17.0 21.9 17.1 17.6 17.6 17.6 17.4 17.5 17.4 17.6 21.7 a 21.5 20.4 21.1 19.0 20.0 a 20.8 24.3 17.7 18.0 17.8 17.8 17.4 17.5 17.8 17.8 22.3 ______________________________________________________________________________________________________ a Omitted because less than half of women in the age group x to x+4 were first married by age x. Marriage among men starts fairly late. By age 20, only 26 percent of men have been married, compared with 74 percent of women. The median age at first marriage for men age 25-54 is 22, while for women 25-49, it is 18, suggesting that men marry about four years later than women. 6.4 MEDIAN AGE AT FIRST MARRIAGE The median age at first marriage for women age 20-49, and men age 25-54 by current age and background characteristics is shown in Table 6.4 and Figure 6.2. Overall, rural women marry at least one year earlier than their urban counterparts. For men, the age difference between urban and rural men is more dramatic (24.5 years compared with 22.0 years, respectively). Across the regions, the median age at first marriage for women ranges from about 17 years in the Eastern and Northern regions to 18 years in the Central and Western regions. For both women and men, education has a positive association with age at first marriage. This may be due to education leading to postponement of marriage or the reverse—that marriage leads to curtailment of education. Under the Ugandan system it is not common to attend formal secondary school after marriage. Women with no formal education marry three to four years earlier than women who have secondary or higher education. Among men, those with no formal education marry at least two years earlier than men with secondary education. 78 * Other Proximate Determinants of Fertility 6.5 AGE AT FIRST SEXUAL INTERCOURSE The 2000-2001 UDHS collected data on age at first sexual intercourse. By age 15, 23 percent of women 20-49 were already sexually active. The cumulative percentage of sexually active women increases steadily to reach 92 percent by age 25. The median age at first sex for women across age groups is similar, indicating no recent change in the pattern of initiation of sexual activity. As in the case of marriage, sexual activity among men starts later than among women. Only 9 percent of men age 25-54 were sexually active by age 15. This percentage rises steadily to reach a level of 81 percent by age 25. The median age at first sexual intercourse for women 20-49 years is 16.7 years. The corresponding figure for men is 18.8 years. This further confirms that women start having sex earlier than men, with a difference of about two years. The median age for women shows no evidence of change over time, while that for men has increased slightly from 18.5 years among men age 50-54 to 19.4 years among men age 25-29. Data in Table 6.5 for men confirm that men enter sexual relations much later than women. Although more than four-fifths of women age 25-49 had had sexual intercourse by age 20, the corresponding proportion for men age 25-54 is three-fifths. Other Proximate Determinants of Fertility * 79 Table 6.5 Age at first sexual intercourse Percentage of women and men who had first sexual intercourse by specific exact ages and median age at first intercourse, by current age, Uganda 2000-2001_____________________________________________________________________________________________ Percentage who had first Percentage Median sexual intercourse by exact age: who never age at_________________________________________ had 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 14.2 na na na na 47.9 1,615 a 20.5 68.5 86.5 na na 3.7 1,504 a 20.7 65.0 81.7 88.9 92.1 0.6 1,341 16.8 25.1 70.7 83.9 89.6 91.5 0.5 983 16.5 21.5 64.3 81.5 88.7 90.4 0.4 810 16.7 25.8 70.7 84.7 89.3 91.5 0.3 570 16.4 27.2 65.4 79.8 86.5 89.9 0.0 423 16.6 22.6 67.5 83.5 89.4 91.5 1.3 5,631 16.7 23.3 67.1 82.4 88.8 91.3 0.4 4,127 16.6 ____________________________________________________________________________________________ MEN____________________________________________________________________________________________ 15-19 20-24 25-29 30-34 35-39 40-44 45-49 50-54 20-54 25-54 15.5 34.6 na na na 61.3 441 a 7.5 37.3 61.3 71.2 na 12.5 321 a 9.0 34.8 55.8 64.3 69.4 2.1 310 19.4 12.4 39.6 61.7 72.3 76.2 0.0 291 19.0 12.9 38.2 65.7 82.3 87.3 1.0 231 18.6 3.7 34.7 62.8 77.4 83.2 0.0 165 18.8 5.5 33.6 67.5 85.4 95.3 0.0 120 18.7 7.0 37.8 69.4 87.1 92.5 0.0 83 18.5 9.0 36.8 62.0 74.3 79.1 3.2 1,521 18.8 9.4 36.7 62.2 75.2 80.6 0.7 1,200 18.8 ____________________________________________________________________________________________ na = Not applicable a Omitted because less than half of the respondents in the age group x to x+4 had sexual intercourse by age x. 6.6 MEDIAN AGE AT FIRST INTERCOURSE Table 6.6 presents the median age at first sexual intercourse among women age 20-49 and men age 25-54, by current age and background characteristics. For women, the median age at first sexual intercourse is generally lower in rural areas than in urban areas, while the reverse is true for men. Examination by region reveals that women and men of the Eastern region engage in sexual relations earliest (16.0 and 18.1 years), while their counterparts in the Western region initiate sex at age 17.5 and 19.8 years, respectively. Women and men with no formal education show small variations with those with primary education. Women with at least some secondary education tend to delay sexual relations to almost two years later than less educated women. However, among men, there is no difference in the initiation of sexual intercourse by educational attainment. 80 * Other Proximate Determinants of Fertility Table 6.6 Median age at first intercourse Median age at first sexual intercourse among women age 20-49 and men age 25-54, by current age and background char- acteristics, Uganda 2000-2001 ___________________________________________________________________________________________________ Current age (women) Women Men Background ___________________________________________________ _______________ _____ characteristic 20-24 25-29 30-34 35-39 40-44 45-49 20-49 25-49 25-54 ___________________________________________________________________________________________________ Residence Urban Rural Region Central Eastern Northern Western Education No education Primary Secondary+ Total 17.1 17.3 16.4 16.9 16.9 16.8 17.0 16.9 18.6 16.6 16.7 16.5 16.6 16.3 16.6 16.6 16.6 18.9 16.7 16.9 16.0 16.4 16.8 16.5 16.6 16.5 18.7 16.1 16.1 16.1 16.0 15.3 16.2 16.0 15.9 18.1 16.6 17.0 16.5 17.3 17.1 16.9 16.8 16.9 19.5 17.5 17.6 17.2 17.9 17.2 17.6 17.5 17.4 19.8 16.3 16.3 16.0 16.6 16.4 16.6 16.4 16.4 18.9 16.4 16.5 16.4 16.5 16.1 16.5 16.4 16.4 18.9 18.2 18.7 17.7 18.3 17.1 17.4 18.2 18.2 18.8 16.7 16.8 16.5 16.7 16.4 16.6 16.7 16.6 18.8 6.7 RECENT SEXUAL ACTIVITY In societies with low use of contraception, the probability of becoming pregnant is closely related to the exposure to and frequency of sexual intercourse. Information on recent sexual activity is therefore useful as a measure of exposure to the risk of pregnancy. Table 6.7 presents the percent distribution of women by the timing of last sex, according to their background characteristics. Among women age15-49, more than half (56 percent) were sexually active in the four weeks prior to the survey, while 21 percent had had sex within the past year but not in the four weeks prior to the survey, and 11 percent had ever had sex but were not sexually active in the past 12 months. The highest level of recent sexual activity is observed among women age 20-39, 64 to 66 percent of whom were sexually active in the past month. The proportion of women who are sexually active gradually declines after age 30. The proportion sexually active in the four weeks preceding the survey among women in marital union declines gradually with the number of years in union. Women who were married in the past or have never been married are less likely to have had sex in the recent past. Women with secondary education are less likely to have engaged in sex in the past four weeks than those with no formal education (45 percent compared with 63 percent). Women in the rural areas are more likely to have had sex in the past four weeks than urban women (58 percent and 49 percent, respectively). There are small variations across regions. Overall, current users of contraception are more likely to be sexually active than women who are not using any method. The proportion varies according to the method used, ranging from 60 percent among condom users to 84 percent among women who have been sterilised. Other Proximate Determinants of Fertility * 81 Table 6.7 Recent sexual activity Percent distribution of women by timing of sexual activity, according to background characteristics, Uganda 2000-2001 ___________________________________________________________________________________ Timing of last sex _____________________________ Within the One or Background past 4 Within more Never had characteristic weeks one year1 years ago sex Total2 Number ___________________________________________________________________________________ Age 15-19 20-24 25-29 30-34 35-39 40-44 45-49 Marriage duration (years) Currently married Married only once 0-4 5-9 10-14 15-19 20-24 25+ Married more than once Divorced/separated/ widowed Never in union Residence Urban Rural Region Central Eastern Northern Western Education No education Primary Secondary+ Current contraceptive method Female sterilisation Pill IUD Condom Periodic abstinence Other method No method Total3 30.0 15.8 6.2 47.9 100.0 1,615 66.2 23.6 6.3 3.7 100.0 1,504 64.8 25.2 9.4 0.6 100.0 1,341 65.1 22.7 11.7 0.5 100.0 983 64.1 22.1 13.4 0.4 100.0 810 62.2 17.0 20.4 0.3 100.0 570 52.2 15.4 32.2 0.0 100.0 423 81.3 18.0 0.7 0.0 100.0 1,048 77.8 19.6 2.5 0.0 100.0 971 77.5 20.1 2.4 0.0 100.0 681 78.1 17.8 4.1 0.0 100.0 454 75.4 20.2 4.3 0.0 100.0 307 71.5 17.7 10.8 0.0 100.0 323 79.4 18.0 2.6 0.0 100.0 1,074 15.0 35.1 49.7 0.0 100.0 934 9.6 18.9 13.1 58.2 100.0 1,456 48.8 22.8 14.6 13.7 100.0 1,207 57.9 20.5 10.3 11.3 100.0 6,039 53.6 22.0 12.7 11.7 100.0 2,341 58.2 23.8 8.9 9.2 100.0 1,956 55.1 20.3 12.2 12.5 100.0 1,158 58.9 16.7 10.4 14.0 100.0 1,792 63.0 20.0 14.0 3.0 100.0 1,584 57.4 20.6 9.3 12.7 100.0 4,330 45.2 22.8 13.0 18.9 100.0 1,331 83.7 10.8 5.6 0.0 100.0 105 81.8 15.3 2.9 0.0 100.0 198 * * * * 100.0 11 59.5 36.6 3.9 0.0 100.0 272 73.7 16.9 9.4 0.0 100.0 147 76.2 19.1 4.5 0.0 100.0 725 51.9 20.9 12.6 14.6 100.0 5,788 56.4 20.9 11.0 11.7 100.0 7,246 Note: An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. 1 Excludes women who had sexual intercourse within the last 4 weeks. 2 May not add up to 100.0 due to missing cases. 3 Includes one woman with missing information on education. 82 * 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, Uganda 2000-2001________________________________________________________________ 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 95.9 75.0 96.0 202 87.1 38.1 90.6 262 77.8 22.8 81.5 278 72.4 16.2 75.7 246 66.1 12.4 68.3 271 54.3 14.0 57.0 288 42.5 7.8 47.1 273 40.3 5.0 41.3 239 24.5 6.0 29.7 307 25.4 4.8 28.8 277 20.4 3.0 22.3 291 12.7 4.5 15.5 252 7.3 4.2 10.4 266 1.6 2.0 3.5 288 3.7 3.2 6.0 248 2.7 2.6 4.8 235 0.8 4.5 5.4 195 2.2 5.4 7.5 193 35.7 12.2 38.7 4,611 11.5 2.1 12.2 na 13.0 5.0 14.1 na _______________________________________________________________ na = Not applicable 6.8 POSTPARTUM AMENORRHOEA, ABSTINENCE, AND INSUSCEPTIBILITY Among women who are not using contraception, the exposure to the risk of pregnancy in the period following birth is determined by two major factors, namely, breastfeeding and sexual abstinence. Postpartum protection from conception can be prolonged by breastfeeding, which can lengthen the duration of amenorrhoea (the period between birth and the return of menstruation), or by delayed resumption of sexual activities (postpartum abstinence). In Table 6.8, the percentage of births for which mothers are postpartum amenorrhoeic and abstaining is presented along with the percentage of births for which mothers are defined as still postpartum insusceptible, i.e., either amenorrhoeic or abstaining or both. These women are classified as not exposed (i.e., insusceptible) to the risk of pregnancy. The proportion of women remaining amenorrhoeic, abstaining, or insusceptible declines as duration since birth increases. Within the first two months after birth, 96 percent of women in Uganda are insusceptible to pregnancy, 96 percent are amenorrhoeic, and 75 percent are abstaining from sex. After six months (the recommended duration of exclusive breastfeeding), 76 percent of mothers are still insusceptible to the risk of pregnancy, mainly because their period has not returned. By 34 to 35 months after birth, only 2 percent of the mothers are amenorrhoeic, 5 percent are abstaining, and about 8 percent are insusceptible to pregnancy. The median duration of postpartum insusceptibility is 12 months; for postpartum amenorrhoea, it is 12 months; for postpartum sexual abstinence, it is 2 months. Compared with data from the 1995 UDHS, the duration of insusceptibility remains at the same level. Other Proximate Determinants of Fertility * 83 Table 6.9 Median duration of postpartum insusceptibility by background characteristics Median number of months of postpartum amenorrhoea, postpartum abstinence, and postpartum insusceptibility, by background characteristics, Uganda 2000- 2001_________________________________________________________________ Post Post- Post- partum Background partum partum insuscep- characteristic amenorrhoeic abstaining tible Number_________________________________________________________________ Age 15-29 30-49 Residence Urban Rural Region Central Eastern Northern Western Education No education Primary Secondary+ Total 10.6 2.0 11.4 3,120 13.2 2.3 13.6 1,491 8.1 2.2 8.9 508 12.2 2.1 12.7 4,103 8.9 2.0 9.7 1,323 11.6 2.9 12.5 1,348 14.1 2.9 14.7 796 12.7 1.1 12.9 1,145 13.3 2.1 14.4 1,105 11.5 2.0 12.0 2,971 7.2 2.5 8.3 535 11.5 2.1 12.2 4,611 _________________________________________________________________ Note: Total includes one child with missing information on mother’s education. 6.9 MEDIAN DURATION OF POSTPARTUM INSUSCEPTIBILITY BY BACKGROUND CHARACTERISTICS The median duration of postpartum amenorrhoea, abstinence, and insusceptibility by various background characteristics is presented in Table 6.9 and Figure 6.3. The median duration of postpartum abstinence shows very little variation across the background characteristics. Therefore, the variation in postpartum insusceptibility is mainly due to variations in postpartum amenorrhoea. Women under 30 years of age have a shorter median duration of postpartum amenorrhoea (11 months) than women over 30 years of age (13 months). The duration of postpartum amenorrhoea for rural women is longer than that for urban women (12 months compared with 8 months). On a regional basis, women in the Northern region have the longest duration of postpartum insusceptibility (15 months). On the other hand, women of the Central region have the shortest duration (10 months). Women with secondary or higher education show the shortest duration of postpartum amenorrhoea (7 months) compared with women with less education (12 months or longer). The pattern for postpartum insusceptibility is similar to that for postpartum amenorrhoea. 84 * Other Proximate Determinants of Fertility Table 6.10 Menopause Percentage of women age 30-49 who are menopausal, Uganda 2000-2001 ____________________________________ Percentage Number of Age menopausal1 women____________________________________ 30-34 1.8 983 35-39 3.5 810 40-41 4.1 299 42-43 9.4 203 44-45 14.7 207 46-47 28.2 153 48-49 41.8 131 Total 7.4 2,786_____________________________________ 1 Percentage of all women who are not pregnant and not postpartum amenorrhoeic whose last menstrual period occurred six or more months preceding the survey. 6.10 MENOPAUSE Table 6.10 presents the percentage of women age 30-49 who are menopausal. The proportion of women who are menopausal rises with age from about 2 percent for age group 30-34 to 42 percent for age group 48-49. It is clear that the onset of infertility with increasing age reduces the proportion of women who are exposed to the risk of pregnancy. For this analysis, a woman is considered menopausal if she is neither pregnant nor postpartum amenorrhoeic but did not have a menstrual period in the six months preceding the survey. Fertility Preferences * 85 FERTILITY PREFERENCES 7 In the 2000-2001 UDHS, women who were not pregnant were asked whether they wanted to have another child or whether they preferred not to have any more children. The question is phrased differently for women who have had no children. Similarly, women who reported that they were pregnant at the time of the survey were asked whether they wanted another child after the birth they were expecting or whether they preferred not to have any more children. Women who indicated that they wanted another child were asked to state the preferred interval between children. Finally, women were asked in total the number of children they would like to have, as well as their sex preference, if they were to start childbearing afresh. Given that ongoing family planning programmes are addressing male involvement and the vital role men play in the realisation of reproductive goals, men were asked similar questions on fertility preferences. 7.1 DESIRE FOR MORE CHILDREN Data on desire for more children can provide an indication of future reproductive behaviour on the assumptions that the required family planning services are available, affordable, and accessible and that people can realise their fertility preferences. Table 7.1 shows the distribution of currently married women according to the number of living children, and Figure 7.1 shows the percent distribution of these women by their fertility preferences. Desire to limit childbearing or delay a pregnancy may not necessarily lead to the use of family planning. 86 * Fertility Preferences Table 7.1 Fertility preferences by number of living children Percent distribution of currently married women and men by desire for more children, according to number of living children, Uganda 2000-2001______________________________________________________________________________________________________ Number of living children1_____________________________________________________________ Desire for children 0 1 2 3 4 5 6+ Total______________________________________________________________________________________________________ WOMEN___________________________________________________________________________________________________ Have another soon2 Have another later3 Have another, undecided when Undecided Want no more Sterilised4 Declared infecund5 Missing Total Number of women 74.4 28.3 26.0 15.4 10.5 10.7 3.9 18.5 3.2 57.2 52.2 48.9 35.8 24.1 10.1 34.7 1.3 3.6 1.2 1.7 1.7 0.6 0.3 1.4 1.2 2.1 2.7 3.3 4.0 7.3 4.0 3.6 1.0 5.3 15.0 27.8 42.3 54.6 74.1 36.4 1.3 0.2 0.8 1.2 1.7 1.4 5.3 2.0 17.2 2.9 2.0 1.7 3.8 1.4 2.1 3.1 0.4 0.5 0.1 0.0 0.2 0.0 0.1 0.2 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 273 716 795 789 668 506 1,134 4,881 ___________________________________________________________________________________________________ MEN___________________________________________________________________________________________________ Have another soon2 Have another later3 Have another, undecided when Undecided Want no more Sterilised4 Declared infecund5 Missing Total Number of men 53.8 32.0 30.7 30.3 28.4 21.9 20.5 27.7 37.8 62.4 54.8 50.0 37.6 31.9 24.3 39.9 1.5 1.4 4.3 1.4 1.9 0.9 0.6 1.6 1.9 0.0 1.4 2.3 2.0 2.1 3.6 2.2 3.1 4.1 8.8 13.6 28.8 42.1 48.4 27.1 0.0 0.0 0.0 0.0 0.0 1.1 0.6 0.3 1.9 0.0 0.0 2.3 0.0 0.0 2.1 1.1 0.0 0.0 0.0 0.0 1.3 1.1 0.6 0.5 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 69 154 166 152 132 118 389 1,180 ___________________________________________________________________________________________________ 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 Respondent reports that she/he is infecund. Overall, 36 percent of currently married women declared that they did not want to have any more children at all, 35 percent wanted another child after two years, and 19 percent wanted to wait for less than two years to have another child. Five percent of women reported not being able to have any more children either because they were infecund (3 percent) or have been sterilised (2 percent). Compared with women, men are generally less likely to want to stop having children (27 percent compared with 36 percent) and more likely to want to continue having children (69 percent compared with 55 percent). Data in Table 7.1 show that 73 percent of married women either want to space their next birth or to end childbearing. This proportion represents a potential demand for family planning in Uganda. In comparison with data from past Uganda DHS surveys, this is an increase from 53 percent in 1988-1989 and 69 percent in 1995. Table 7.1 further shows that desire for many children is strong in Uganda, with 14 percent of women with six or more children stating that they want to have another child. For men, the proportion is much higher (45 percent), with 21 percent saying that they want a child within two years. Fertility Preferences * 87 Figure 7.2 shows that there is a positive relationship between the desire to stop childbearing and the number of living children. Women with a larger number of children are more likely to want to stop childbearing. For instance, among childless women, only 2 percent stated that they did not want any more children or had been sterilised. This proportion increases steadily to 79 percent among women with six or more children. 7.2 DESIRE TO LIMIT CHILDBEARING BY BACKGROUND CHARACTERISTICS Table 7.2 shows the percentage of currently married women who want to limit childbearing by background characteristics. There are variations in the reproductive intentions across urban-rural residence and region. Although 43 percent of urban women wish to cease childbearing, the corresponding proportion among rural women is 38 percent. Variations by region range from 41 percent in the Central region to 33 percent in the Northern region. However, the Northern region shows a unique feature in that at least 10 percent of women with two or fewer children want no more children. Although this percentage increases with the number of living children, by the time women have two or more children, it is exceeded by the percentage in other regions. Women with no education are slightly more likely than educated women to report that they do not want to have any more children (41 percent compared with 38 percent). This is contrary to what was revealed in the 1995 UDHS, where women’s education had a positive relationship with the desire to stop having children. 88 * Fertility Preferences Table 7.2 Desire to limit childbearing by background characteristics Percentage of currently married women who want no more children, by number of living children and background characteristics, Uganda 2000-2001___________________________________________________________________________________________________ Number of living children1 Background ___________________________________________________ Total Total characteristic 0 1 2 3 4 5 6+ women men___________________________________________________________________________________________________ Residence Urban Rural Region Central Eastern Northern Western Education No education Primary Secondary+ Total 0.0 10.7 31.0 47.9 68.5 73.9 90.4 42.6 39.7 2.8 4.3 12.9 25.8 40.9 53.9 78.5 37.8 25.3 2.1 6.9 24.0 34.6 58.8 61.6 82.1 41.4 34.7 0.7 2.4 12.5 25.4 39.7 56.2 84.4 39.0 27.1 12.9 10.1 14.1 23.2 32.7 41.0 63.2 32.5 13.5 0.0 3.2 10.3 31.4 40.6 61.0 82.1 38.5 28.4 4.4 9.7 14.4 28.2 35.5 52.2 76.5 40.8 27.8 1.9 4.1 13.6 28.4 43.3 54.9 79.3 37.6 23.3 0.0 5.8 25.6 33.9 65.6 74.4 92.7 37.8 36.7 2.4 5.5 15.8 29.0 44.0 55.9 79.4 38.5 27.1 ______________________________________________________________________________________________________ Note: Women and men who have been sterilised are considered to want no more children. 1 Includes current pregnancy 7.2 DEMAND FOR FAMILY PLANNING SERVICES In the 2000-2001 UDHS, women who reported that they did not want to have more children (limiters) or want to wait two or more years before having another child (spacers), but who were not using contraception, are defined as having an unmet need for family planning. The percentage of women with unmet need for family planning and women who are currently using contraception constitute the total demand for family planning. Results from Table 7.3 show that overall, 35 percent of currently married women have an unmet need for family planning services, 21 percent for spacing and 14 percent for limiting. The corresponding percentages for all women and unmarried women are 24 percent and 4 percent, respectively. Among married women, 23 percent are using a family planning method—11 percent for spacing and 12 percent for limiting births. The percentage of married women who are using contraception constitutes 40 percent of the demand for family planning. This means that if all the demand were satisfied, 57 percent of married women would be using contraception. Table 7.3 shows that younger women are more likely to need family planning services for spacing than for limiting children. On the other hand, older women are in need of family planning more for limiting than for spacing purposes. Older women are also more likely to have met their demand for family planning. The unmet need for family planning services is low among the youngest and oldest age groups, resembling an inverted U shape. Whereas the total demand for family planning is higher in urban areas than in rural areas (70 percent and 56 percent, respectively), unmet need for family planning is much higher in rural areas than in urban areas (36 percent and 23 percent, respectively). Fertility Preferences * 89 Table 7.3 Need for family planning Percentage of currently married women, women with unmet need for family planning, with met need for family planning, and the total demand for family planning, by background characteristics, Uganda 2000-2001 _________________________________________________________________________________________________________________ Met need for Unmet need for family planning Total demand for Percentage family planning1 (currently using)2 family planning 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 Central Eastern Northern Western Education No education Primary Secondary+ DISH/CREHP districts DISH I Mbarara and Ntungamo II Masaka, Rakai, and Sembabule III Luwero, Masindi, and Nakosongola IV Kamuli and Jinja V Kampala CREHP (Kisoro, Kabale, and Rukungiri) Neither Currently married women Unmarried women All women 24.8 0.8 25.6 11.1 0.9 12.0 35.9 1.7 37.6 31.9 466 31.2 4.1 35.3 16.5 4.5 21.0 47.8 8.6 56.3 37.3 1,150 27.0 11.9 38.8 16.4 8.0 24.4 43.3 19.9 63.2 38.6 1,078 18.0 18.2 36.3 10.8 15.9 26.6 28.8 34.1 62.9 42.3 807 11.5 24.3 35.8 4.5 21.3 25.8 16.0 45.6 61.6 41.9 652 4.4 30.2 34.6 2.2 24.5 26.7 6.7 54.6 61.3 43.6 431 1.6 21.3 22.9 0.6 17.4 18.0 2.2 38.7 40.9 44.1 297 14.0 9.4 23.4 22.3 24.0 46.3 36.4 33.4 69.8 66.4 636 21.7 14.5 36.2 9.5 9.8 19.3 31.2 24.3 55.5 34.7 4,245 17.8 12.2 30.1 18.1 18.8 37.0 36.0 31.1 67.0 55.1 1,377 28.2 17.4 45.6 6.5 8.0 14.5 34.7 25.4 60.1 24.1 1,487 15.7 12.8 28.5 13.6 7.4 21.0 29.2 20.3 49.5 42.4 823 18.1 12.1 30.2 7.4 10.6 18.0 25.4 22.7 48.2 37.4 1,194 17.9 16.6 34.5 5.7 7.4 13.2 23.6 24.0 47.7 27.6 1,264 22.8 14.5 37.3 10.4 10.8 21.2 33.2 25.3 58.5 36.2 2,978 16.3 5.5 21.9 25.6 23.6 49.1 41.9 29.1 71.0 69.2 639 20.4 12.5 32.9 12.4 15.7 28.1 32.8 28.2 61.0 46.0 1,331 17.8 10.8 28.6 7.3 8.9 16.2 25.1 19.7 44.8 36.1 280 20.5 13.3 33.8 12.3 11.5 23.8 32.8 24.8 57.6 41.3 327 28.6 16.8 45.5 9.7 17.7 27.4 38.3 34.5 72.9 37.6 158 27.3 17.4 44.7 6.0 10.8 16.8 33.3 28.2 61.5 27.3 262 12.6 6.6 19.2 24.1 29.7 53.8 36.7 36.4 73.1 73.7 303 10.4 8.7 19.1 6.5 10.3 16.8 17.0 19.0 35.9 46.8 294 21.7 14.9 36.6 11.1 10.1 21.1 32.8 25.0 57.8 36.6 3,256 20.7 13.9 34.6 11.2 11.6 22.8 31.9 25.5 57.3 39.7 4,881 2.3 1.2 3.5 9.7 4.9 14.6 12.0 6.1 18.1 80.8 2,365 14.7 9.7 24.4 10.7 9.4 20.1 25.4 19.2 44.5 45.2 7,246 ________________________________________________________________________________________________________________ 1 Unmet need for spacing includes pregnant women whose pregnancy was mistimed, amorrhoeic 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. 90 * Fertility Preferences There are substantial regional differences in the level of unmet need and the degree of demand satisfied. Unmet need is highest in the Eastern region (46 percent) and lowest in the Northern region (29 percent). In terms of percentage of demand satisfied, the range is between 55 percent in the Central region and 24 percent in the Eastern region (Figure 7.3) A woman’s education is related to demand for family planning. Women with secondary or higher education have the highest demand for family planning services (71 percent), compared with 48 percent for women with no education. Since better educated women are also more likely to have the highest percentage of demand satisfied, they have the lowest level of unmet need. Unmet need in the DISH districts is only slightly lower than average, while unmet need in the CREHP districts is much lower than the national average. 7.3 IDEAL NUMBER OF CHILDREN Another measure of fertility preferences is the ideal number of children. Both women and men in the survey were asked, “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?” Data in Table 7.4 show that in general, men want to have a larger family than women. The mean ideal number of children among all women is 4.8 children, and among all men, it is 5.6 children. These figures show a decline in fertility preferences since the 1995 UDHS, where the corresponding figure is 5.3 children for women and 5.8 children for men. The desired number of children among currently married women is close to that for all women, while in general, married men have a considerably higher mean ideal family size than all men. Fertility Preferences * 91 Table 7.4 Ideal 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 for currently married women, according to number of living children, Uganda 2000-2001__________________________________________________________________________________________ Number of living children1 Ideal number ___________________________________________________ of children 0 1 2 3 4 5 6+ Total__________________________________________________________________________________________ WOMEN__________________________________________________________________________________________ 0 1 2 3 4 5 6+ Nonnumeric responses Total Number Mean ideal number for: All women Number2 Currently married women Number2 0.5 0.0 0.0 0.1 0.0 0.3 0.1 0.2 1.0 1.9 0.7 0.8 0.7 0.4 0.2 0.8 4.9 14.4 8.5 4.4 5.2 2.9 2.9 8.3 0.9 12.9 9.6 8.2 1.6 2.7 3.2 7.5 2.5 39.6 44.0 40.3 34.2 22.9 25.7 36.4 0.4 11.0 14.5 14.8 11.0 16.4 10.7 12.2 4.4 16.7 18.1 27.0 42.0 48.7 49.6 29.2 5.5 3.4 4.7 4.3 5.3 5.8 7.7 5.3 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 1,565 1,018 998 939 798 596 1,332 7,246 4.1 4.2 4.4 4.8 5.3 5.7 6.0 4.8 1,480 984 951 898 756 561 1,229 6,860 4.6 4.4 4.4 4.8 5.3 5.7 6.1 5.1 254 694 755 754 633 473 1,048 4,610 __________________________________________________________________________________________ MEN__________________________________________________________________________________________ 0 1 2 3 4 5 6+ Nonnumeric responses Total Number Mean ideal number for: All men Number Currently married men Number 0.3 0.0 0.0 0.0 0.0 0.0 0.0 0.1 1.1 0.8 0.0 0.0 0.0 0.0 0.0 0.5 5.8 7.0 5.0 1.3 3.7 0.0 2.6 4.3 11.7 15.2 11.4 6.4 5.7 4.3 3.7 9.0 36.5 29.0 33.9 21.2 20.9 25.0 13.9 27.7 19.7 17.8 19.2 21.1 14.0 18.1 7.7 16.6 19.1 29.2 27.5 41.6 52.2 50.2 64.0 36.5 5.8 1.0 3.1 8.4 3.5 2.4 8.0 5.3 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 727 214 179 165 142 137 397 1,962 4.6 4.7 4.9 5.6 6.1 6.3 8.0 5.6 685 212 173 151 137 134 366 1,858 4.7 4.8 5.0 5.7 6.0 6.6 7.9 6.2 67 152 161 138 127 115 357 1,117 __________________________________________________________________________________________ 1Includes current pregnancy 2Means are calculated excluding the women giving nonnumeric responses. The mean ideal number of children increases with the number of living children. Among women, it increases from 4.1 children for childless women to 6.0 children among women with 6 or more children. A similar pattern is shown by men, although the range is much wider—4.6 children for men with no living children and 8 children for men with 6 or more children. The mean ideal number of children by age and background characteristics is presented in Table 7.5 and Figure 7.4. In general, for all women and men, the average ideal number of children increases with age. The mean ideal number of children is 4.1 and 6.4 for the youngest and oldest women, respectively. Rural-urban differentials show that urban women prefer to have fewer children than rural women (3.8 children and 5.1 children, respectively). 92 * Fertility Preferences Table 7.5 Mean ideal number of children by background characteristics Mean ideal number of children for all women and men, by age and background characteristics, Uganda 2000-2001__________________________________________________________________________________________________ Age Background ______________________________________________________________________ characteristic 15-19 20-24 25-29 30-34 35-39 40-44 45-49 50-54 Total_________________________________________________________________________________________________ WOMEN________________________________________________________________________________________________ Residence Urban Rural Region Central Eastern Northern Western Education No education Primary Secondary+ Total 3.2 3.4 3.8 4.3 4.4 4.8 4.9 na 3.8 4.3 4.5 5.0 5.4 5.7 6.0 6.6 na 5.1 3.6 3.9 4.4 4.8 5.2 5.6 6.1 na 4.4 4.3 4.4 4.7 5.3 5.1 5.4 5.4 na 4.8 4.4 4.9 5.7 5.7 6.5 6.5 7.4 na 5.6 4.3 4.5 4.9 5.3 5.9 6.5 6.8 na 5.1 4.7 5.0 5.6 5.9 6.3 6.9 7.1 na 5.9 4.2 4.4 4.8 5.3 5.5 5.5 6.1 na 4.8 3.5 3.5 3.8 4.1 4.2 4.6 4.6 na 3.8 4.1 4.3 4.8 5.2 5.5 5.9 6.4 na 4.8 _________________________________________________________________________________________________ MEN________________________________________________________________________________________________ Residence Urban Rural Region Central Eastern Northern Western Education No education Primary Secondary+ Total 4.0 4.0 3.8 4.6 5.5 5.7 5.8 8.5 4.4 4.8 5.0 5.5 6.1 6.8 7.2 6.9 7.9 5.9 4.4 4.5 4.5 5.6 6.5 6.7 6.8 6.8 5.2 4.7 4.8 5.7 5.8 6.5 5.9 6.1 10.4 5.8 5.3 6.4 7.4 7.4 7.8 10.1 8.3 7.3 7.3 4.6 4.4 4.4 5.6 6.2 6.8 6.1 6.1 5.2 4.8 7.3 5.8 8.7 8.4 7.1 6.8 5.8 7.2 4.7 5.0 5.4 6.0 6.9 7.8 7.1 8.6 5.8 4.3 4.1 4.4 5.3 5.2 5.2 5.9 7.5 4.8 4.6 4.8 5.1 5.9 6.6 6.9 6.8 7.9 5.6 _________________________________________________________________________________ na = Not applicable There are variations in the mean ideal number of children across regions, ranging from 4.4 children in the Central region to 5.6 children in the Northern region. A similar pattern of regional differentials was observed in the 1995 UDHS. A person’s educational level has a negative association with his/her desire for children. Data in Table 7.5 reveal that for all ages, fertility preferences decline with increasing education. Although women with no education prefer to have 5.9 children, women with secondary or higher education want only 3.8 children. The same differentials are found among men. Men in urban areas, those who live in the Central and Western regions, and those who have secondary or higher education want to have fewer children than other men. Fertility Preferences * 93 7.4 FERTILITY PLANNING To be able to measure the degree to which couples control their fertility, women were asked, for all children born in the preceding five years, whether the pregnancy was wanted at the time, wanted but at a later time, or not at all wanted. For women who were pregnant at the time of interview, this question was also asked of the current pregnancy. In this procedure, the respondent was required to recall accurately her wishes at one or more points in the last five years. However, care needs to be taken because an unwanted conception may become a cherished child, leading to the rationalisation of responses to these questions. According to Table 7.6, 60 percent of the births in the five years preceding the survey were wanted then, 25 percent were wanted later (mistimed), and 15 percent were not wanted at the time they were conceived. The proportion of births that were wanted then declines with birth order and mother’s age. Although 73 percent of first births were wanted then, only 52 percent of fourth or higher order births were wanted at the time they occurred. On the other hand, the percentage of unwanted births increases with birth order and age. Less than 10 percent of births to women 15-19 were not wanted at all, compared with 61 percent of births to women age 40-44. 94 * Fertility Preferences Table 7.6 Fertility planning status Percent distribution of all 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, Uganda 2000-2001_____________________________________________________________________________ Planning status of birth Birth order and _________________________________ mother’s age Wanted Wanted Wanted at birth then later no more Missing Total Number_____________________________________________________________________________ Birth order 1 2 3 4+ Age at birth 15-19 20-24 25-29 30-34 35-39 40-44 45-49 Total 73.2 16.8 9.6 0.4 100.0 1,512 68.4 25.8 5.6 0.2 100.0 1,468 62.9 31.0 5.8 0.3 100.0 1,357 52.0 25.3 22.3 0.3 100.0 4,244 67.7 22.7 9.3 0.3 100.0 1,678 64.0 29.4 6.3 0.2 100.0 2,643 59.5 28.6 11.6 0.3 100.0 2,003 55.7 21.7 22.4 0.1 100.0 1,251 47.9 15.6 36.0 0.5 100.0 748 35.4 3.9 60.6 0.1 100.0 221 (53.7) (2.3) (41.0) (3.1) 100.0 38 60.3 24.8 14.6 0.3 100.0 8,581 _____________________________________________________________________________ Note: Figures in parentheses are based on 25-49 cases. Another measure of fertility preferences is the total wanted fertility rate, which expresses the theoretical level of fertility that would result if all unwanted births were prevented. It therefore provides another indicator of fertility aspirations and may be interpreted as the number of births that a woman would have by age 50 if she experienced the wanted fertility rate. This measure is calculated in the same manner as the conventional total fertility rate, except that unwanted births are excluded from the numerator. A birth is considered wanted if the number of living children at the time of conception was less than the current ideal number of children reported by the respondent. Comparison of the actual fertility rate with the wanted rate indicates the potential demographic impact of eliminating unwanted births. Table 7.7 compares the total wanted fertility rates and total fertility rates for the three years preceding the survey (as shown in Chapter 4). The gap between wanted and actual fertility shows how successful women were in achieving their reproductive intentions. For example, the data show that if all unwanted births were eliminated, the total fertility rate in Uganda would be 5.3 children per woman instead of the actual total fertility rate of 6.9 children per woman. This gap varies in subgroups of women. It is higher among rural women, women living in the Eastern region, and women with no education or primary education only. This suggests that these women are less successful in meeting their fertility goals than other women. Fertility Preferences * 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, Uganda 2000-2001____________________________________________ Total wanted Total Background fertility fertility characteristic rates rates____________________________________________ Residence Urban Rural Region Central Eastern Northern Western Mother's education No education Primary Secondary+ Total 3.2 4.0 5.7 7.4 4.5 5.7 5.3 7.4 6.4 7.9 5.6 6.9 6.3 7.8 5.6 7.3 3.2 3.9 5.3 6.9 Infant and Child Mortality * 97 INFANT AND CHILD MORTALITY 8 This chapter presents estimates of levels, trends, and differentials of neonatal, postneonatal, infant, and childhood mortality in Uganda. The data used in the estimation of these mortality rates were collected in the birth history section of the UDHS questionnaire. The section begins with questions about the respondent’s childbearing experience, i.e., the number of sons and daughters who live in the household, who live elsewhere, and who have died. Next, for each live birth, information on name, date of birth, sex, whether the birth was single or multiple, and survivorship status was recorded. For living children, information about his/her age and whether the child resided with his/her mother was obtained. For children who had died, the respondent was asked to provide the age at death. The information presented in this chapter is important not only for the demographic assessment of the country’s population, but also in the design and evaluation of health policies and programmes. The reduction of infant and child mortality and the incidence of high-risk pregnancies remain priority targets of the National Health Policy. 8.1 DEFINITIONS, METHODOLOGY AND ASSESSMENT OF DATA QUALITY The childhood mortality measures presented in this chapter are defined as follows: Neonatal mortality: the probability of dying within the first month of life Postneonatal mortality: the arithmetic difference between infant and neonatal mortality Infant mortality: the probability of dying between birth and the first birthday Child mortality: the probability of dying between exact age one and the fifth birthday Under-five mortality: the probability of dying between birth and the fifth birthday. All rates are expressed as deaths per 1,000 live births, except child mortality, which is expressed as deaths per 1,000 children surviving to the first birthday. A retrospective birth history, such as that included in the 2000-2001 UDHS, is susceptible to several possible data collection errors. First, only surviving women age 15-49 were interviewed; therefore, no data are available for children of women who had died. The resulting mortality estimates will be biased if the child mortality of surviving and nonsurviving women differs substantially. Another possible error is underreporting of events; respondents are likely to forget events that occurred in the past. Omission of infant deaths may take place, especially in cases where deaths occur early in infancy. If such deaths are selectively omitted, the consequence will not only be a lower infant mortality rate (IMR) and neonatal mortality rate (NNMR), but also a low ratio of 98 * Infant and Child Mortality neonatal deaths to infant deaths and deaths under seven days to neonatal deaths. On the other hand, misstatement of the date of birth and the age at death will result in distortion of the age pattern of death. This may affect the final indices obtained because of shifting ages above or below the borderline ages. Seventy percent of all the neonatal births in the 20 years prior to the 2000-2001 UDHS were early neonatal births (Appendix Table C.5). This figure is within the expected range and is the same as was observed in the 1995 UDHS. Furthermore, differences in the reporting of neonatal deaths for the different periods are not considered significant. Thus, there is no evidence of selective underreporting of early neonatal deaths. Similarly, neonatal deaths constituted 41 percent of all infant deaths, which is considered plausible. The rates vary within a narrow range (40 to 43 percent) over the 20 years prior to the survey (see Appendix Table C.6). The proportion of early neonatal deaths ranges between 65 and 72 percent for the periods 15 to 19 and 0 to 4 years prior to the survey. Another aspect that affects the childhood mortality estimates is the quality of reporting of age at death. In general, these problems are less serious for periods in the recent past than for those in the more distant past. If the ages are misreported, it will bias the estimates, especially if the net effect of the age misreporting results in transference of deaths from one age bracket to another. For example, a net transfer of deaths from under one month to over one month, will affect the estimates of neonatal and postneonatal mortality. To minimise errors in the reporting of age at death, the UDHS interviewers were instructed to record the age at death in days if the death took place within one month after birth, in months if the child died within 24 months, and in years if the child was two years or older. Table C.5 shows age heaping at ages seven and 14 days, which is a sign of approximation to one and two weeks, respectively. Although age heaping at 14 days may not bias any indicator, the heaping at seven days is likely to lead to a lower estimate of early neonatal mortality. Similarly, Table C.6 shows evidence of heaping at age 12 months (an approximation to one year), with the number of reported deaths at 12 months more than twice that at adjacent ages. If some of these deaths actually took place at less than 12 months of age, the transference to age 12 months or older will result in a lower estimate of infant mortality than the actual level. However, age heaping is higher for births in the 10 to 19 years prior to the survey than for the most recent births. Indeed, the reporting on deaths in the five years prior to the survey does not show any heaping. It is therefore not necessary to adjust the data before estimating the mortality levels. 8.2 EARLY CHILDHOOD MORTALITY RATES: LEVELS AND TRENDS In Uganda, infant mortality rates have been typically computed using two approaches— direct and indirect techniques. Direct estimates have been computed from the three UDHS surveys using information collected in the birth history table. On the other hand, lacking the necessary information for producing estimates using direct methods, the population censuses report indirect estimates based on the number of children ever born and children surviving. Although there is no conclusive agreement whether one estimate is better than the other, the underlying assumptions used in the indirect methods can introduce a potential bias in the estimate. Studies have found that for many sub-Saharan countries, even if an appropriate mortality model is applied in the indirect estimation method, the results of this method are consistently higher than those of the direct methods (Sullivan et al., 1994; Adetunji, 1996). In this report, only direct estimates are presented. Infant and Child Mortality * 99 Table 8.1 Early childhood mortality rates Neonatal, postneonatal, infant, child, and under-five mortality rates for five-year periods preceding the survey, Uganda 2000-2001 __________________________________________________________________ Years Neonatal Postneonatal Infant Child Under-five preceding mortality mortality mortality mortality mortality the survey (NN) (PNN) (1q0) (4q1) (5q0)__________________________________________________________________ 0-4 33.2 55.2 88.4 69.2 151.5 5-9 36.7 53.9 90.5 79.6 162.9 10-14 36.1 52.8 89.0 81.9 163.6 Various early childhood mortality rates for the 15 years preceding the survey are presented by five-year periods in Table 8.1. For the most recent period (i.e., zero to four years before the survey, reflecting roughly 1996 to 2000), the infant mortality rate is 88 deaths per 1,000 live births. This means that one in every 11 babies born in Uganda do not live to the first birthday. Of those who survive to the first birthday, 69 out of 1,000 would die before reaching their fifth birthday. The overall under-five mortality is estimated at 152 deaths per 1,000 live births, which implies that one in every seven Ugandan babies does not survive to the fifth birthday. During the first year of life, the first month is the hardest to survive. With the neonatal mortality rate of 33 deaths per 1,000 live births, nearly 40 percent of infant deaths occur during the first month of life. Although the postneonatal period represents a lower risk of death relative to the earlier period, it still indicates a poor mortality condition among Ugandan infants. Data in Table 8.1 and Figure 8.1 also show that infant mortality in Uganda has been high and constant in the last 15 years. On the other hand, between the two most recent five-year periods preceding the survey, there has been a decline in child mortality of ten points after being constant for the previous two periods. This decline translates into a decline in under-five mortality. 100 * Infant and Child Mortality Table 8.2 Early childhood mortality by socioeconomic characteristics Neonatal, postneonatal, infant, child, and under-five mortality rates for the ten-year period preceding the survey, by socioeconomic characteristics, Uganda 2000-2001__________________________________________________________________________ Post- Neonatal neonatal Infant Child Under-five Socioeconomic mortality mortality mortality mortality mortality characteristic (NN) (PNN) (1q0) (4q1) (5q0)__________________________________________________________________________ Residence Urban Rural Region Central Eastern Northern Western Education No education Primary Secondary+ Wealth index quintile Lowest Lower middle Middle Upper middle Highest Total 22.5 32.0 54.5 48.7 100.6 36.3 57.4 93.7 77.0 163.4 29.8 42.2 71.9 68.1 135.1 29.5 59.8 89.3 63.7 147.3 42.2 63.7 105.9 80.6 178.0 41.5 56.3 97.8 87.0 176.3 38.7 67.8 106.5 89.6 186.5 34.9 53.5 88.4 72.1 154.1 24.5 28.1 52.6 42.7 93.0 40.1 65.6 105.7 96.3 191.8 32.7 65.6 98.3 82.9 173.0 38.3 56.3 94.5 76.2 163.5 34.6 46.4 81.0 60.0 136.2 26.2 34.0 60.2 49.2 106.4 34.8 54.6 89.4 73.7 156.5 Another way of examining trends is by comparing the 2000-2001 UDHS figures with findings from other sources, such as the 1995 UDHS, which were collected using the same methodology and calculated with the same technique. Comparison of the mortality estimates from the two surveys shows that infant mortality in Uganda has increased by almost 10 percent in the last five years (from 81 to 88). This increase is mainly accounted for by an increase in neonatal mortality from 27 deaths per 1,000 births in the five years before the 1995 survey to 33 deaths per 1,000 for the 2000-2001 survey. Since the child mortality rate in 2000-2001 is similar to that in the 1995 UDHS, the under-five mortality rate in the 2000-2001 UDHS is slightly higher than that in the 1995 UDHS. These figures suggest that overall, childhood mortality in Uganda has remained at roughly the same level during the past ten years. 8.3 EARLY CHILDHOOD MORTALITY BY SOCIOECONOMIC CHARACTERISTICS Table 8.2 and Figure 8.2 present the early childhood mortality rates in Uganda by socioeconomic characteristics. The rates given in this table refer to the ten-year period preceding the survey. Mortality levels in the urban areas are considerably and consistently lower than in the rural areas. For example, under-five mortality in the rural areas is 60 percent higher than in the urban areas. The urban-rural gap in childhood mortality is most notable for postneonatal mortality, where the probability of dying before the first birthday for rural infants is 80 percent higher than for urban infants. Infant and Child Mortality * 101 There are marked regional mortality differences in Uganda. The Central and Eastern regions have lower mortality rates than the Northern and Western regions. For under-five mortality, the rate in the Central Region is 135 deaths per 1,000 live births, compared with 178 deaths per 1,000 live births in the Northern Region. As expected, a mother’s education is inversely associated with her child’s risk of dying. Children born to a mother with at least secondary education have by far the lowest mortality. Infants born to such women have half the mortality risk of infants whose mother had no education. Similarly, the IMR for children whose mothers had primary education is 17 percent lower than that of infants whose mothers had no education. Data in Table 8.2 indicate that the effect of mother’s education is far greater on postneonatal mortality than neonatal mortality. The neonatal mortality rate of infants whose mother had primary education is 10 percent lower than that of infants whose mother had no education. The corresponding figure for postneonatal mortality is more than 20 percent. The gap in neonatal mortality rates between infants whose mother had secondary or higher education and those with no education is 37 percent, compared with a nearly 60 percent gap in postneonatal mortality. This pattern of mortality differentials is not unexpected and is undoubtedly due to the fact that causes of neonatal mortality are more biological and less amenable to socioeconomic interventions, whereas causes of postneonatal mortality are more connected to standard of living factors. This means that efforts to reduce infant mortality in Uganda would yield greater results if they were targeted at the mother’s and household’s behavioural factors. 102 * Infant and Child Mortality Table 8.3 Early childhood mortality by demographic characteristics Neonatal, postneonatal, infant, child, and under-five mortality rates for the ten-year period preceding the survey, by demographic characteristics, Uganda 2000-2001_________________________________________________________________________________ Post- Neonatal neonatal Infant Child Under-five Demographic mortality mortality 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 interval (years) < 2 2 3 4+ Birth size Small or very small Average or large 37.0 56.4 93.4 77.3 163.5 32.4 52.8 85.2 70.2 149.4 42.4 63.0 105.4 81.8 178.6 29.8 52.1 81.9 71.9 147.9 38.4 52.7 91.1 68.8 153.6 40.1 49.6 89.7 81.9 164.2 48.3 62.4 110.7 73.5 176.0 25.5 53.4 78.9 76.1 149.0 30.3 51.2 81.5 74.4 149.9 44.7 54.2 98.9 67.8 160.0 49.2 76.5 125.6 88.9 203.3 23.3 43.9 67.3 72.9 135.2 20.2 35.9 56.1 63.0 115.5 25.1 40.9 66.0 47.9 110.7 44.9 52.7 97.6 na na 27.8 56.0 83.7 na na __________________________________________________________________________________ na = Not applicable The last panel in Table 8.2 shows that wealth status is inversely associated with childhood mortality. For all measures, the children in the highest quintile have the lowest mortality rates, while those in the lowest quintile have the highest mortality rates. 8.4 EARLY CHILDHOOD MORTALITY BY DEMOGRAPHIC CHARACTERISTICS The demographic characteristics of both the mother and child have been found to play an important role in the survival probability of children. Table 8.3 presents the demographic characteristics that were considered in the 2000-2001 UDHS, including sex of child, mother’s age at birth, birth order, previous birth interval, and birth size. In Uganda, mortality levels are consistently higher among male children than among their female counterparts. The difference ranges from 7 percent for postneonatal mortality to 14 percent for neonatal mortality. Although the traditional hypothesis of “too early and too late increases child’s mortality” is generally upheld, evidence from Table 8.3 suggests that in Uganda, too early childbearing is much more disadvantageous than too late. The safest age at which to have children is between 20 and 29. Having a child earlier than this increases the child’s risk of dying before age one by 29 percent. In comparison, having a child later than this age bracket increases the child’s risk of death before one year by about 10 percent. Infant and Child Mortality * 103 The effect of birth order operates mostly during infancy. Second and third order births have the lowest risk of dying within the first year of life. First order births, on the other hand, are at the highest risk of dying; the risk is 40 percent higher than that of the second and third order risk. The risk of mortality among infants continues to increase until the seventh order births. However, the influence of birth order seems to wear off in the case of child mortality. Short birth intervals are associated with increased risk of mortality. The interval with the highest risk is less than two years, while the most favourable is four or more years. Children born less than two years after a previous birth are almost twice as likely to die before reaching age five as those born after an interval of four years or longer. The 2000-2001 UDHS data therefore reinforce the need to promote child spacing mechanisms such as family planning and breastfeeding as ways of ensuring child survival. Birth weight is a factor often associated with the child’s survival, particularly during the first year. Since few women in Uganda give birth in a health facility, birth weight was not recorded for most children. As a measure of birth size, women were asked whether, in their judgement, their baby was very small, small, average, or larger than average at birth. As expected, babies who were reported as small or very small at birth have higher mortality rates than those who were reported as average or large at birth. Although 98 in 1,000 children who were reported as small at birth died before age one, the corresponding figure for children who were reported as average or large is 84 deaths per 1,000 births. 8.5 EARLY CHILDHOOD MORTALITY BY WOMEN’S STATUS Although there is no direct association, women’s status has been found to influence infant and child mortality levels through women’s ability to control resources and make decisions. In the 2000-2001 UDHS, women were asked about their attitudes toward certain aspects of their autonomy. They include the number of decisions in which the woman participates in the final say, the number of reasons a woman is justified in refusing sexual relations with her husband, and the number of reasons that justify wife beating. A woman is considered more independent if she participates in a larger number of household decisions and has more reasons to refuse sex with her husband. On the other hand, the more reasons she justifies wife beating, the less independent she is. Although there is an inverse relationship between women’s status and early childhood mortality, the relationship is not necessarily linear (see Table 8.4). The mother’s decisionmaking power seems to have its greatest importance in influencing infant mortality. Among children whose mother has no final say in any decision, 131 in 1,000 died before celebrating their first birthday, compared with 93 or fewer in 1,000 among children whose mother participates in some decisions. Data in this table suggest that decisionmaking is not additive. Children’s mortality level is associated with whether their mother has some power to make a final decision. It does not seem to depend on the number of decisions the mother makes. The relationship between mother’s ability to participate in decisionmaking and child mortality is not as strong as with mortality in the first year of life. This is probably because a child’s survival during infancy is more sensitive to health care interventions such as immunisation, feeding, and early care seeking. If mothers cannot freely and independently make decisions on these actions, the survival of their infants is likely to be adversely affected. 104 * Infant and Child Mortality Table 8.4 Early childhood mortality by woman’s status Neonatal, postneonatal, infant, child, and under-five mortality rates for the ten-year period preceding the survey, by women’s status indicators, Uganda 2000-2001_________________________________________________________________________________ Post- Neonatal neonatal Infant Child Under-five Women’s mortality mortality mortality mortality mortality status indicator (NN) (PNN) (1q0) (4q1) (5q0)__________________________________________________________________________________ Number of decisions with mother having final say 0 1-2 3-4 5 Number of reasons to refuse sexual relations 0 1-2 3-4 Number of reasons to justify wife beating 0 1-2 3-4 5 Total 54.7 76.2 131.0 75.2 196.3 29.2 56.4 85.6 79.2 158.0 41.3 52.0 93.3 65.9 153.0 33.3 52.1 85.4 74.0 153.1 27.9 51.1 79.0 49.1 124.3 38.5 63.0 101.5 98.0 189.5 34.5 53.6 88.1 71.4 153.2 33.9 46.9 80.8 62.4 138.1 34.4 47.9 82.3 70.9 147.4 35.4 63.5 98.9 85.0 175.5 36.1 68.1 104.3 76.4 172.7 34.8 54.6 89.4 73.7 156.5 The number of reasons justifying refusal of sexual relations operates in an unexpected way. Women who find no reasons are considered to have less independence. Therefore, their children are expected to be disadvantaged. However, data in Table 8.4 shows that the mortality rates of these women’s children are considerably lower than those of other children, including children whose mother agrees with three or four reasons for refusing sex. Wife beating is another reflection of women’s status. Women who do not approve any form of beating are assumed to enjoy a higher status, which in turn, translate into a more favourable mortality profile for their children. This is because they are more likely to have decisionmaking powers, which extend to child care. Table 8.4 shows the expected effect. Generally, children of lower status women have higher mortality. Although 81 in 1,000 children born to mothers who do not justify wife beating died before reaching age one, the corresponding rate for children whose mother agrees to all reasons of wife beating is 104 deaths per 1,000. The same picture is generally observed in the case of child mortality. 8.6 PERINATAL MORTALITY In the 2000-2001 UDHS, women were asked to report all pregnancy losses in the five years before the survey. For each such pregnancy, the duration was recorded. In this report, perinatal deaths include pregnancy losses occurring after seven completed months of gestation (stillbirths) and deaths to live births within the first seven days of life (early neonatal deaths). The 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. 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, in this report, both event types are combined and examined together. Infant and Child Mortality * 105 Table 8.5 Perinatal mortality Number of stillbirths and early neonatal deaths, and perinatal mortality rate for the five-year period preceding the survey, by background characteristics, Uganda 2000-2001________________________________________________________________________________ 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 1st pregnancy <15 months 15-26 months 27-38 months 39+ months Residence Urban Rural Region Central Eastern Northern Western Education No education Primary Secondary+ Total 38. 45 52.5 1,581 59 102 38.5 4,195 28 49 43.2 1,793 1 10 45.5 229 33 43 58.1 1,311 11 25 64.6 569 39 60 38.6 2,582 25 39 31.3 2,051 17 39 43.1 1,284 21 17 45.5 843 105 189 42.2 6,955 47 50 43.7 2,220 24 48 30.8 2,328 12 50 46.8 1,327 44 57 52.6 1,922 21 46 34.9 1,911 83 145 45.6 5,005 22 15 42.3 881 126 206 42.6 7,798 ______________________________________________________________________________ 1 A stillibirth is a foetal death that occurs in a pregnancy lasting seven or more months. 2 An early neonatal death is the death of a live-born child at age 0 to 6 days. 3 The 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. The perinatal mortality rate is a useful indicator of the state of delivery services, either in terms of their utilisation or their ability to cope with the demands of childbirth and thereby to deliver a healthy baby. Data in Table 8.5 show that overall, 126 stillbirths and 206 early neonatal deaths were recorded in the survey, resulting in a perinatal mortality rate in Uganda of 43 per 1,000 pregnancies. Perinatal mortality is highest among teenage mothers. Among Ugandan teenagers, 53 of 1,000 pregnancies of seven or more months end in a stillbirth or a death within one week after birth. This is most likely because teenage mothers are more likely to be unmarried and less likely to utilise antenatal services, as well as the lack of both the social and financial support to enable them to utilise delivery services. Furthermore, very young women are less biologically ready for safe childbearing. The perinatal rate is lowest among mothers age 20-29. This age group has been identified as the safest age to have children (see Table 8.3). Table 8.5 further demonstrates that the duration of the previous pregnancy interval has a strong influence on the outcome of the index pregnancy. Pregnancies occurring within 15 months of a previous birth and first pregnancies have the highest risk to pregnancy loss or early death (65 pregnancy losses or early deaths per 1,000 pregnancies), while the safest interval is between 27 and 38 months (31 pregnancy losses or early deaths per 1,000). 106 * Infant and Child Mortality The Eastern Region has the lowest perinatal mortality rate of only 31 per 1,000. The rates in the Central and Northern regions are 44 and 47 per 1,000, respectively, while the Western Region has the highest rate of 53 per 1,000. As is the case with other childhood mortality measures, better educated women are expected to experience lower perinatal mortality. However, the national average is close to the perinatal mortality rate of children whose mothers had secondary or higher education, and the rate of children whose mothers had no education is the lowest. This pattern raises questions about reporting biases; less educated women may have underreported the level of stillbirths and early deaths. 8.7 HIGH-RISK FERTILITY BEHAVIOUR This section examines the relative importance of under-five mortality risk factors. These factors are of particular interest because they are easily avoidable at a low cost. Generally, infants and children have a greater probability of dying if they are born to mothers who are too young or too old, if they are born after a short birth interval, or if they are of high birth order. In the analysis of the effects of high-risk fertility behaviour on child survival, a mother is classified as too young if she is less than 18 years of age, and too old if she is over 34 years of age at the time of delivery. A short birth interval is defined as a birth occurring less than 24 months after the previous birth, and a child is of high birth order if the mother had previously given birth to three or more children (i.e., if the child is of birth order four or higher). Although first births are commonly associated with high mortality risk, even if they occurred when the mother was between 18 and 34 years old, they are not included in the high-risk category because these births are considered unavoidable. The first column in Table 8.6 shows the percentage of births occurring in the five years before the survey that fall into these various risk categories. Two in three births in Uganda have elevated mortality risks, which are avoidable, and only one in five births were not in any high-risk category. Among those who are at risk, 44 percent of births were in only one of the high-risk categories and 23 percent fall into multiple high-risk categories due to a combination of mother’s age, birth order, and birth interval. The category with the highest percentage of births is birth order three or higher, which constitutes 27 percent of births. This is hardly surprising in a high-fertility population like Uganda. However, compared with births with no elevated mortality risk, the mortality increase associated with this category is minimal (4 percent). The category associated with the highest risk ratio is mother’s age under 18. Children born to mothers under 18 years old have a 60 percent higher risk of dying than children not in any high-risk category. Births to young mothers are most likely first order births. The second highest risk is associated with the birth interval. Children born less than 24 months after a prior birth have a mortality risk that is 48 percent higher than those who are not in any high-risk category. The risk ratio was not calculated for children born to mothers at age 35 or older because there were too few children. In reality, children are often found in more than one high-risk category. It would therefore make sense, for programmatic purposes, to consider multiple risks. The category with the highest multiple-risk ratio (1.62) is for births to older women (age 35 or older) with high birth order combined with short birth intervals (less than 24 months). This category involves only 2 percent of births. The second highest combination is of short birth intervals and higher birth order, which increases mortality risks by 40 percent. This category involves 11 percent of births. Infant and Child Mortality * 107 Table 8.6 High-risk fertility behavior Percent distribution of children born in the five years preceding the survey by category of elevated risk of dying and the risk ratio, and percent distribution of currently married women by category of risk if they were to conceive a child at the time of the survey, Uganda 2000-2001_________________________________________________________________ Births in the 5 years preceding the survey Percentage_____________________ of currently Percentage married Risk category of births Risk ratio women1_________________________________________________________________ Not in any high risk category Unavoidable risk category First order births between ages 18 and 34 years Single high-risk category Mother’s age <18 Mother’s age >34 Birth interval <24 months Birth order >3 Subtotal Multiple high-risk category Age <18 & birth interval <24 months2 Age >34 & birth order >3 Age >34 & birth interval <24 months & birth order >3 Birth interval <24 months and birth order >3 Subtotal In any avoidable high-risk category Total Number of births 21.8 1.00 16.3 a 11.2 1.19 4.9 7.6 1.60 0.7 0.2 * 2.9 9.1 1.48 9.8 27.2 1.04 20.7 44.1 1.22 34.2 0.9 1.35 0.6 9.4 1.02 20.0 2.1 1.62 6.0 10.5 1.40 18.1 22.8 1.26 44.7 67.0 1.23 78.8 100.0 na 100.0 7,674 na 4,881 _________________________________________________________________ Note: Risk ratio is the ratio of the proportion dead among births in a specific high-risk category to the proportion dead among births not in any high-risk category. An asterisk indicates that this figure is based on fewer than 25 unweighted cases and has been suppressed. na = Not applicable 1 Women are assigned to risk categories according to the status they would have at the birth of a child if they were to conceive at the time of the survey: current age less than 17 years and 3 months or older than 34 years and 2 months, latest birth less than 15 months ago, or latest birth being of order 3 or higher. 2 Includes the category age <18 and birth order >3a Includes sterilised women The fourth column of Table 8.6 shows the distribution of currently married women by category of increased risk if they were to conceive at the time of the survey. Although many women are protected from conception due to use of family planning, postpartum insusceptibility, and prolonged abstinence, for simplicity, only those who have been sterilised are included in the category for not in any high-risk. The criteria for placing women into specific risk categories is adjusted to take into account gestation. 108 * Infant and Child Mortality Data in Table 8.6 show that only 16 percent of currently married, nonsterilised women in Uganda are not in any high-risk category, while 79 percent are potentially at risk of conceiving a high-risk pregnancy. Forty-five percent of married women fall into multiple risks categories. There are two important points to note. First, although some high-risk categories were individually not associated with any enhanced mortality risk, the risk is considerably higher when considered in combination with others. Second, nearly half of married Ugandan women are at risk of conceiving a baby who will have a high risk of dying. Reproductive Health and Child Care * 109 REPRODUCTIVE HEALTH AND CHILD CARE 9 This chapter presents the 2000-2001 UDHS findings on the general state of reproductive health and child care in Uganda. The chapter is divided into two major sections. The first part covers women’s access to health care and utilisation of antenatal, delivery, and postnatal care. The second part of the chapter covers immunisation of children and prevalence and management of childhood diseases, including acute respiratory infection (ARI), fever, and diarrhoea. Hygiene practices and the relationship between women’s status and children’s health care are also discussed. The results of the 2000-2001 UDHS are very important in evaluating reproductive health programmes and achievements in implementing the action plan agreed upon at the 1994 International Conference on Population and Development in Cairo. These findings also provide an opportunity to evaluate the child health care programmes, particularly the introduction of the Integrated Management of Childhood Illnesses (IMCI) programmes. The findings further provide an evaluation of service utilisation and the implementation of appropriate strategies for improving the health of mothers and children. In this report, data about children refer to those born in the five-year period prior to the survey. These data are not comparable with those presented in the 1995 UDHS, which include only children under four years old. For studying trends since 1995, the 2000-2001 UDHS data have also been tabulated for children under four years. 9.1 ANTENATAL CARE The major objective of antenatal care is to identify and treat problems during pregnancy such as anaemia and infections. It is during an antenatal care visit that screening for complications and advice on a range of issues including place of delivery and referral of mothers with complications occur. In the UDHS, interviewers recorded source of antenatal care and the person who provided that care for women’s most recent births. If a woman received antenatal care from more than one provider, the provider with the highest qualifications is presented in the table. Table 9.1 shows the distribution of women who had live births in the five years preceding the survey according to the type of antenatal care provider. The results indicate that 94 percent of women in Uganda received antenatal care. Most women receive care from a medical professional: 83 percent from a nurse or a midwife, and 9 percent from a doctor. The role of traditional birth attendants in providing antenatal care is negligible (1 percent). Data in Table 9.1 further indicate that the choice of antenatal care provider varies slightly by the mother’s age. Mothers age 35-49 are less likely than younger mothers to receive antenatal care (89 percent compared with 96 percent for mothers less than 20). First births are the most likely to receive antenatal care. On the other hand, sixth order births are the least likely to receive antenatal care. 110 * Reproductive Health and Child Care 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 during pregnancy for the most recent birth, according to background characteristics, Uganda 2000-2001 ___________________________________________________________________________________________ Traditional Background Nurse/ birth characteristic Doctor midwife1 attendant No one Missing2 Total Number3 ___________________________________________________________________________________________ Age at birth <20 20-34 35-49 Birth order 1 2-3 4-5 6+ Residence Urban Rural Region Central Eastern Northern Western Education No education Primary Secondary+ Wealth index quintile Lowest Lower middle Middle Upper middle Highest DISH/CREHP districts DISH I Mbarara and Ntungamo II Masaka, Rakai and Sembabule III Luwero, Masindi and Nakasongola IV Kamuli and Jinja V Kampala CREHP (Kisoro, Kabale, and Rukungiri) Neither Total 9.0 85.4 1.7 3.8 0.2 100.0 746 9.8 83.1 1.3 5.6 0.2 100.0 3,058 8.0 80.0 0.9 10.9 0.2 100.0 685 14.8 81.6 1.1 2.4 0.2 100.0 717 10.0 82.9 1.6 5.1 0.4 100.0 1,380 8.4 83.7 1.5 6.2 0.2 100.0 1,057 6.6 83.2 1.0 9.0 0.1 100.0 1,335 25.5 71.3 0.1 2.9 0.1 100.0 560 7.1 84.7 1.5 6.6 0.2 100.0 3,930 17.5 76.3 1.8 4.3 0.0 100.0 1,323 4.3 89.7 0.7 5.1 0.2 100.0 1,273 4.5 87.4 0.6 7.2 0.3 100.0 775 8.9 80.2 1.8 8.6 0.5 100.0 1,119 4.3 82.1 1.6 12.1 0.0 100.0 1,103 8.1 85.5 1.4 4.7 0.3 100.0 2,791 25.0 73.0 0.5 1.4 0.1 100.0 594 4.1 84.0 1.7 9.8 0.4 100.0 980 4.8 84.6 1.3 9.3 0.0 100.0 955 7.5 86.7 1.3 4.3 0.2 100.0 897 8.9 84.9 1.8 3.8 0.5 100.0 851 23.8 73.7 0.2 2.2 0.1 100.0 806 15.4 76.9 1.7 5.9 0.2 100.0 1,239 11.7 77.9 2.2 7.8 0.4 100.0 263 11.0 80.0 3.5 5.5 0.0 100.0 327 10.5 76.9 1.5 10.2 0.9 100.0 162 7.6 87.1 0.6 4.7 0.0 100.0 219 33.6 63.6 0.0 2.8 0.0 100.0 268 10.0 79.0 0.7 10.3 0.0 100.0 255 6.9 85.9 1.2 5.8 0.2 100.0 2,995 9.4 83.0 1.3 6.1 0.2 100.0 4,489 ___________________________________________________________________________________________ Note: If more than one source of antenatal care was mentioned, only the provider with the highest qualifications is considered in this tabulation. 1 Includes medical assistant, clinical officer, and nursing aide 2 Includes women who don’t know the type of provider 3 Total includes one woman with missing information on education Reproductive Health and Child Care * 111 Practically all women in urban areas receive antenatal care. Mothers in urban areas are three times more likely than mothers in rural areas to receive antenatal care from a doctor (26 percent compared with 7 percent). Women in rural areas are more likely to get antenatal care from a nurse or a midwife than urban women (85 percent and 71 percent, respectively). Because the Central Region is the most urbanised region in Uganda with a relatively large number of health facilities and better access to health care than other regions, women in the Central Region are much more likely to receive antenatal care from a doctor than women in other regions (18 percent compared with 9 percent or less). Antenatal care coverage is strongly associated with the woman’s education. Better educated women are more likely to have antenatal care and more likely to be attended by a doctor than less educated women. Although one in four women who have attained secondary or higher education received antenatal care from a doctor, the corresponding proportion for women with primary education is only 8 percent, and for women with no education, it is 4 percent. Twelve percent of women with no education received no antenatal care, the highest level in any socioeconomic group. Antenatal coverage is clearly influenced by the woman’s wealth status: women in the lowest quintile are the least likely to receive antenatal care, and those in the highest quintile are the most likely to have care during pregnancy. Furthermore, women in the highest quintile are also the most likely to receive care from a doctor, while women in the lower quintiles receive care from a midwife or nurse. Antenatal coverage does not vary much by whether a woman lives in districts included in the DISH project or the CREHP project. However, women in these districts are more likely to receive care from a doctor, while in other districts the role of midwife and nurse is more visible. Data on antenatal care in the 2000-2001 UDHS are not directly comparable with that in the 1995 UDHS for two reasons. In the later survey, questions on antenatal care were asked only of the last live births in the preceding five years, while in 1995, data were collected for all live births. Furthermore, the 2000-2001 UDHS covered births occurring in the five years preceding the survey, while the 1995 UDHS covered only births in the four years prior to the survey. Despite these differences, the data show almost no differences in source of antenatal care. 9.1.1 NUMBER OF ANTENATAL CARE VISITS AND TIMING OF FIRST VISIT Antenatal care attendance is important in monitoring the progress of a pregnancy, identifying complications, and referring mothers for specialised care at an appropriate time for intervention. In Uganda, the Ministry of Health (MOH) recommends that a woman attend antenatal care at least four times during a pregnancy. It is further recommended that a woman attend antenatal care monthly during the first seven months, every two weeks in the eighth month, and then weekly until birth. Information on antenatal care visits and the stage at which pregnant women seek antenatal care is presented in Table 9.2. Overall, only 42 percent of women make four or more visits during a pregnancy. Furthermore, half of women make one to three visits, which is below the MOH recommendation, while 6 percent did not seek antenatal care at all. Table 9.2 further shows that half (49 percent) of women make their first antenatal care visits during the first six months of pregnancy, while 44 percent make their first visit during the last three months of pregnancy. Half of these women had their first visit when the pregnancy was at 5.9 months, when it is sometimes too late to identify complications and to refer the woman appropriately. 112 * Reproductive Health and Child Care Table 9.2 Number of antenatal care visits and timing of first visit 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 timing of the first visit, Uganda 2000-2001 ______________________________________ Number and timing of ANC visits Percent ______________________________________ Number of ANC visits None 1 2-3 4+ Don't know/missing Total 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) Total 6.1 7.7 42.3 41.9 2.1 100.0 6.1 14.4 34.9 37.6 6.7 0.3 100.0 5.9 4,489 9.1.2 QUALITY OF ANTENATAL CARE The Sexual and Reproductive Health Minimum Package for Uganda (1999) provides details of what is to be done by a health service provider during antenatal care. Some health workers have been trained to offer this package. Table 9.3 shows the percentage of mothers who receive antenatal care by content of antenatal care and background characteristics. The results show that not all women received the minimum package. The most common components of antenatal care include the administration of tetanus toxoid injection (74 percent), weight measurement (71 percent), measurement of blood pressure (56 percent), and receipt of iron tablets (54 percent). Height was measured for only 34 percent of pregnant women, while only one in five received information on pregnancy complications, and 35 percent were given antimalarial drugs. Certain patterns can be seen in Table 9.3. In general, older women, those pregnant with their first birth, urban women, women in the Central Region, and better educated women tend to get more comprehensive antenatal care than other women. For example, 36 percent of women with secondary education are informed of pregnancy complications, compared with less than 17 percent of less educated women. Reproductive Health and Child Care * 113 Table 9.3 Antenatal care content Percentage of women with a live birth in the five years preceding the survey who received antenatal care for the most recent birth, by content of antenatal care and background characteristics, Uganda 2000-2001 _____________________________________________________________________________________________________________________ Informed of signs of Received pregnancy Blood Urine Blood tetanus Received Received Background compli- Weight Height pressure sample sample toxoid iron anti- characteristic cations measured measured measured given given injection tablets malarial Number_____________________________________________________________________________________________________________________ Mother's age at birth <20 20-34 35+ Birth order 1 2-3 4-5 6+ Residence Urban Rural Region Central Eastern Northern Western Education No education Primary Secondary+ Total 16.5 68.0 31.2 54.8 9.7 15.4 79.3 59.6 34.9 717 19.5 71.3 34.7 55.9 10.7 15.1 73.9 53.6 33.8 2,880 19.0 74.7 36.4 59.3 12.1 14.1 68.9 51.6 37.6 609 22.0 71.8 38.5 61.6 16.4 22.6 83.8 61.6 35.7 699 20.9 73.3 34.7 56.2 8.6 14.4 78.8 55.0 33.4 1,304 16.6 67.3 32.8 52.3 9.3 12.4 69.9 51.4 31.9 990 16.9 71.9 32.8 56.2 10.9 13.3 66.8 51.8 37.3 1,213 38.1 88.2 59.4 83.7 32.0 36.6 83.7 66.1 38.3 543 16.1 68.7 30.6 52.1 7.6 11.8 72.6 52.6 34.0 3,663 26.6 73.9 41.2 71.3 20.1 22.7 74.6 67.2 40.7 1,265 14.1 72.3 29.3 46.8 6.5 10.3 78.5 55.3 39.4 1,206 18.3 81.0 37.3 57.0 8.7 11.0 77.5 60.0 31.4 716 15.5 59.8 29.7 48.0 5.6 13.6 65.8 33.1 23.4 1,018 14.6 68.5 31.9 51.4 7.2 10.5 71.1 46.0 30.5 970 16.6 69.6 31.4 53.5 8.6 13.6 73.1 54.6 34.4 2,650 36.3 83.4 51.7 76.6 26.3 28.6 83.4 67.1 42.2 585 18.9 71.3 34.3 56.2 10.8 15.0 74.1 54.3 34.6 4,206 _____________________________________________________________________________________________________________________ Note: Total includes one woman with missing information on education. In summary, the content of antenatal care in Uganda is inadequate. Coupled with poor coverage of antenatal care, this situation calls for concerted efforts to improve the attendance and quality of antenatal care. 9.1.3 PLACE OF ANTENATAL CARE The place where a woman receives antenatal care is important because it influences the frequency and quality of antenatal care received. Table 9.4 presents the distribution of women who delivered in the five years preceding the survey who received ANC, tabulated by place of ANC and background characteristics of the mother. Overall, 71 percent of mothers use a public facility for antenatal care. Among these, the most commonly used facilities are government health centres (38 percent), followed by government hospitals (28 percent). Private hospitals and clinics are the most often used by women who go to a private facility (24 percent). The place where a woman receives antenatal care does not seem to have a pattern according to mother’s age or the child’s birth order. However, place of antenatal care varies according to the woman’s education, urban or rural residence, and region. Government hospitals are frequented more by urban women, women who live in the Central Region, and those with secondary or higher education. 114 * Reproductive Health and Child Care Table 9.4 Place of antenatal care Percent distribution of women with a live birth in the five years preceding the survey who received antenatal care (ANC) for the most recent birth from a health professional by place of ANC, according to background characteristics, Uganda 2000-2001 ___________________________________________________________________________________________________________________________ Place where antenatal care was received _________________________________________________________________________________ Govt. Govt. Private Other Background Govt. health health Other hospital/ private characteristic hospital centre post public clinic medical Other Missing Total Number1 ___________________________________________________________________________________________________________________________ Mother's age at birth <20 20-34 35-49 Birth order 1 2-3 4-5 6+ Residence Urban Rural Region Central Eastern Northern Western Education No education Primary Secondary+ Total 28.6 39.0 4.9 0.4 23.3 0.2 0.2 3.5 100.0 704 28.1 37.4 5.4 0.1 24.5 0.5 0.2 3.6 100.0 2,840 24.5 40.4 5.4 0.3 22.4 1.4 0.6 5.0 100.0 603 31.8 33.9 4.3 0.0 26.5 0.4 0.0 3.3 100.0 691 29.0 37.8 4.4 0.3 24.1 0.3 0.2 3.9 100.0 1,282 24.5 39.1 7.5 0.2 24.4 1.0 0.3 3.1 100.0 974 26.4 40.1 5.2 0.2 22.3 0.7 0.5 4.5 100.0 1,200 53.2 12.4 1.2 0.1 31.6 0.0 0.0 1.5 100.0 542 23.8 42.0 5.9 0.2 22.9 0.7 0.3 4.1 100.0 3,606 35.3 21.1 1.7 0.0 38.7 0.1 0.5 2.6 100.0 1,241 29.0 44.6 8.8 0.5 13.5 0.9 0.0 2.7 100.0 1,197 28.6 45.5 3.8 0.2 18.2 0.4 0.0 3.3 100.0 712 15.9 46.3 6.7 0.0 22.6 1.0 0.7 6.9 100.0 997 22.8 45.8 6.3 0.2 19.7 0.5 0.3 4.4 100.0 952 26.6 39.3 5.4 0.2 23.5 0.7 0.3 4.0 100.0 2,612 40.5 20.2 3.5 0.0 33.3 0.6 0.2 1.9 100.0 583 27.7 38.1 5.3 0.2 24.0 0.6 0.3 3.8 100.0 4,148 ___________________________________________________________________________________________________________________________ Note: For women who had more than one antenatal care visit, the place refers to the last visit. Total includes one woman with missing information on education. 9.1.4 TETANUS TOXOID VACCINATION Neonatal tetanus is common among newborns in developing countries where deliveries are conducted at home or in places where hygiene conditions may be poor. Tetanus toxoid (TT) immunisation is given to pregnant women to prevent neonatal tetanus. For full protection, a pregnant woman needs two doses of TT injections. If a woman had been immunised before she became pregnant, she only needs one dose of TT injection. For a woman to have lifetime protection, a total of five doses is required. The 2000-2001 UDHS collected data for women’s most recent live birth in the five years preceding the survey as to whether the mother received a TT vaccination and the number of doses received. Table 9.5 shows that only 42 percent of pregnant women in Uganda receive two or more TT injections, 28 percent receive one dose, and 30 percent do not receive any TT vaccinations. Reproductive Health and Child Care * 115 Table 9.5 Tetanus toxoid injections Percent distribution of women who had a live birth in the five years preceding the survey by number of tetanus toxoid injections received during pregnancy for the most recent birth, according to background characteristics, Uganda 2000-2001 ________________________________________________________________________________ Two or Don’t Background One more know/ characteristic None injection injections missing Total Number ________________________________________________________________________________ Age at birth <20 20-34 35-49 Birth order 1 2-3 4-5 6+ Residence Urban Rural Region Central Eastern Northern Western Education No education Primary Secondary+ Total 23.4 30.9 45.4 0.3 100.0 746 29.7 27.8 42.0 0.5 100.0 3,058 38.1 24.4 36.4 1.1 100.0 685 18.1 27.8 53.8 0.3 100.0 717 24.6 30.6 44.4 0.4 100.0 1,380 34.1 28.1 37.1 0.7 100.0 1,057 38.4 24.6 36.2 0.7 100.0 1,335 18.4 25.6 55.6 0.4 100.0 560 31.6 28.1 39.8 0.6 100.0 3,930 28.5 25.9 45.5 0.1 100.0 1,323 25.2 33.3 41.0 0.5 100.0 1,273 27.2 28.5 43.0 1.3 100.0 775 38.8 23.3 37.3 0.6 100.0 1,119 36.5 25.1 37.5 0.9 100.0 1,103 29.9 29.3 40.3 0.5 100.0 2,791 17.7 25.5 56.5 0.3 100.0 594 29.9 27.8 41.7 0.5 100.0 4,489 ________________________________________________________________________________ Note: Total includes one woman with missing information on education. The age of the mother and the birth order influence TT vaccination. Young mothers and women pregnant with their first child are more likely to receive a TT vaccination than other mothers. This could be because older women and women pregnant with higher order births received the injections prior to the current pregnancy. Women in urban areas are more likely than rural women to have received two doses of TT vaccinations (56 percent and 40 percent, respectively). Women in the Western Region are less likely than other women to have received TT injections. TT vaccination coverage varies according to the woman’s education, with 57 percent of mothers with secondary education having received two or more doses, compared with 38 percent for mothers with no education. 9.2 DELIVERY Some of the factors associated with delivery outcome include the place where a mother delivers a baby and the hygiene practices associated with such delivery. Table 9.6 shows the percent distribution of live births in the five years preceding the survey by place of delivery by background characteristics of the mother. 116 * Reproductive Health and Child Care Table 9.6 Place of delivery Percent distribution of live births in the five years preceding the survey by place of delivery, according to background characteristics, Uganda 2000-2001_____________________________________________________________________________ Place of delivery___________________________________ Background Health At characteristic 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 Central Eastern Northern Western Education No education Primary Secondary+ Number of antenatal care visits1 None 1-3 visits 4+ visits Don’t know/missing Wealth index quintile Lowest Lower middle Middle Upper middle Highest DISH/CREHP districts DISH I Mbarara and Ntungamo II Masaka, Rakai and Sembabule III Luwero, Masindi and Nakasongola IV Kamuli and Jinja V Kampala CREHP (Kisoro, Kabale, and Rukungiri) Neither Total 46.5 52.2 0.6 0.7 100.0 1,543 35.3 63.3 0.9 0.6 100.0 5,236 27.2 71.0 0.9 0.9 100.0 892 55.0 43.4 0.7 0.9 100.0 1,378 36.6 62.3 0.6 0.5 100.0 2,519 31.6 66.5 1.2 0.7 100.0 1,733 28.4 70.2 0.9 0.6 100.0 2,042 79.2 19.6 0.8 0.4 100.0 821 31.5 67.0 0.9 0.7 100.0 6,850 56.9 41.5 0.8 0.8 100.0 2,173 36.5 61.8 1.1 0.6 100.0 2,305 24.5 74.7 0.4 0.4 100.0 1,316 21.7 76.8 0.9 0.6 100.0 1,878 20.8 77.9 0.9 0.5 100.0 1,890 36.4 62.1 0.8 0.6 100.0 4,922 72.2 25.5 1.2 1.0 100.0 858 7.8 91.3 0.6 0.3 100.0 274 28.5 70.3 0.9 0.3 100.0 2,242 53.4 45.1 1.0 0.5 100.0 1,881 52.8 42.9 0.0 4.3 100.0 92 18.4 80.5 0.6 0.5 100.0 1,745 26.4 72.6 0.4 0.6 100.0 1,677 29.7 68.8 0.8 0.7 100.0 1,565 44.3 53.4 1.6 0.7 100.0 1,457 76.0 22.3 1.1 0.7 100.0 1,228 48.8 50.3 0.7 0.2 100.0 2,068 20.6 78.3 0.8 0.3 100.0 448 37.5 61.9 0.5 0.1 100.0 568 33.6 65.2 1.3 0.0 100.0 286 70.7 28.8 0.5 0.1 100.0 390 88.5 10.1 0.8 0.6 100.0 376 20.6 78.0 0.5 0.9 100.0 419 33.0 65.3 0.9 0.8 100.0 5,184 36.6 61.9 0.9 0.6 100.0 7,672 _______________________________________________________________________________ Note: Total includes one woman with missing information on education 1 Includes only the most recent birth in the five years preceding the survey Reproductive Health and Child Care * 117 Overall, 37 percent of births occurred at health facilities, and 62 percent were delivered at home. This is cause for concern, given that 92 percent of women received antenatal care from a trained health worker. In general, births to younger women and low order births are more likely to be delivered in a health facility than births to older women and higher order births. For example, 27 percent of births to mothers age 35-49 are delivered at a health facility, whereas the corresponding figure for births to women under 20 years old is 47 percent. Similarly, 55 percent of first order births were delivered at health facilities, compared with 28 percent of sixth order births. The proportion of births delivered in a health facility is much higher in urban areas (79 percent) than in rural areas (32 percent). Mothers with secondary or higher education are three times more likely to deliver at a health facility than women with no education (72 percent 21 percent, respectively). Another related factor is antenatal care attendance. Mothers who made four or more antenatal care visits are seven times more likely to deliver at a health facility than women who do not attend antenatal care (53 percent and 8 percent, respectively). A woman’s wealth status has a direct relationship with the place she delivers her baby. Births to women in the highest quintile are the most likely to be delivered in a health facility, while those in the lowest quintile are the most likely to be delivered at home. Choice of place of delivery varies by whether a woman lives in districts included in the DISH project or the CREHP project. Women who live in a district included in the DISH project are more likely to deliver in a health facility (49 percent) than women in the CREHP districts (21 percent) and women who are in districts not included in either project (33 percent). As expected, women in Kamuli and Jinja (71 percent) and Kampala (89 percent) are the most likely to deliver in a health facility. 9.2.1 ASSISTANCE DURING DELIVERY In addition to place of delivery, assistance during delivery is an important variable that influences the delivery outcome and the health of the mother and the infant. This is because the skills of the person attending the delivery determine whether the provider can manage any complication and observe hygienic practices. Table 9.7 shows the percent distribution of live births in the five years preceding the survey, by person providing assistance, according to background characteristics. Overall, four in ten births in the five years preceding the survey were assisted by a trained medical professional during delivery. However, only 4 percent of births were delivered with the assistance of a doctor, and 35 percent were assisted by a nurse, a midwife or other trained medical professional. Eighteen percent of births were assisted by a traditional birth attendant and 28 percent by relatives or friends. For one in seven births, the mother did not receive any assistance during delivery. Births to younger women, low order births, and births to women in urban areas and in the Central Region are more likely to receive assistance at delivery from a doctor, a nurse, or a midwife than births to other women. The most striking differentials in assistance during delivery are by woman’s education and by urban-rural residence (see Figure 9.1). Women who have attained secondary education are more likely to be assisted at delivery by a medical professional than women with no education (76 percent compared with 22 percent). Similarly, 81 percent of births to urban women were attended by a trained medical staff, compared with 34 percent of births to rural women. 118 * Reproductive Health and Child Care Table 9.7 Assistance during delivery Percent distribution of live births in the five years preceding the survey by person providing assistance during delivery, according to background characteristics, Uganda 2000-2001 ______________________________________________________________________________________________ Tradi- tional Relative, Don’t Background Nurse/ birth friends, No know/ characteristic Doctor midwife1 attendant other one missing Total Number ______________________________________________________________________________________________ Age at birth <20 20-34 35-49 Birth order 1 2-3 4-5 6+ Residence Urban Rural Region Central Eastern Northern Western Mother's education No education Primary Secondary+ Wealth index quintile Lowest Lower middle Middle Upper middle Highest DISH/CREHP districts DISH I Mbarara and Ntungamo II Masaka, Rakai and Sembabule III Luwero, Masindi and Nakasongola IV Kamuli and Jinja V Kampala CREHP (Kisoro, Kabale, and Rukungiri) Neither Total 5.2 43.0 19.4 25.6 6.4 0.4 100.0 1,543 3.7 34.0 17.9 29.2 14.9 0.3 100.0 5,236 2.0 28.5 13.6 27.3 27.8 0.7 100.0 892 8.2 48.7 16.0 22.8 3.7 0.6 100.0 1,378 3.5 35.1 19.0 30.8 11.3 0.2 100.0 2,519 3.0 31.0 19.8 29.5 16.4 0.3 100.0 1,733 1.9 29.6 15.4 27.8 24.8 0.4 100.0 2,042 14.3 66.2 4.3 10.6 4.4 0.2 100.0 821 2.5 31.5 19.3 30.4 15.9 0.4 100.0 6,850 7.8 51.0 16.0 20.6 4.3 0.3 100.0 2,173 1.7 38.5 10.8 33.0 15.8 0.2 100.0 2,305 2.3 24.5 36.0 21.1 15.5 0.5 100.0 1,316 2.8 20.3 15.3 36.3 24.7 0.6 100.0 1,878 1.2 20.8 17.2 35.7 24.8 0.2 100.0 1,890 3.3 35.7 19.6 28.2 12.8 0.5 100.0 4,922 12.6 63.7 8.0 12.2 3.4 0.2 100.0 858 1.6 18.1 25.5 33.3 20.5 0.9 100.0 1,745 1.9 25.7 19.8 33.0 18.1 1.5 100.0 1,677 2.1 29.8 18.7 32.5 15.5 1.3 100.0 1,565 3.3 43.1 14.6 26.6 11.1 1.4 100.0 1,457 12.4 65.0 6.0 11.2 4.9 0.5 100.0 1,228 7.1 43.2 14.6 22.3 12.6 0.1 100.0 2,068 3.2 18.0 10.4 35.7 32.6 0.3 100.0 448 4.1 34.0 30.3 24.1 7.5 0.1 100.0 568 5.1 31.6 21.9 31.0 10.4 0.0 100.0 286 4.5 69.2 3.1 14.4 8.7 0.1 100.0 390 20.6 69.0 2.5 5.4 2.3 0.3 100.0 376 1.2 21.1 7.3 45.6 24.4 0.5 100.0 419 2.7 31.9 19.8 29.3 14.7 1.6 100.0 5,184 3.8 35.2 17.7 28.3 14.7 0.4 100.0 7,672 ______________________________________________________________________________________________ Note: If the respondent mentioned more than one person attending during delivery, only the most qualified person is considered in this tabulation. Total includes one woman with missing information on education 1 Includes medical assistant, clinical officer, and nursing aide Reproductive Health and Child Care * 119 UDHS 2000-2001 Figure 9.1 Percentage of Births for Which Women Received Medical Assistance During Delivery, by Background Characteristics 39 81 34 59 40 27 23 22 39 76 UGANDA RESIDENCE Urban Rural REGION Central Eastern Northern Western EDUCATION No education Primary Secondary+ Doctor Trained nurse/midwife The relationship between a woman’s wealth status and assistance at delivery shows that women in the highest quintile are the most likely to be assisted by a health professional. On the other hand, women in the lowest quintile are the most likely to be assisted by a traditional birth attendant. Women in the lowest quintile have the poorest care during delivery, since they are also more likely to be assisted by untrained personnel or not assisted at all (33 percent by friends or relatives and 21 percent by no one). In general, women who live in districts included in the DISH project are more likely to be assisted by a health professional during delivery (50 percent) than in CREHP districts (22 percent) or in districts not covered by either project (35 percent). Women in Kampala District are more likely to have their births assisted by a doctor, than women in other districts (21 percent compared with 5 percent or less). 9.2.2 CHARACTERISTICS OF DELIVERY Birth weight is a proxy indicator of a baby’s health status because infants born with low birth weight generally face higher morbidity and mortality risks. In the 2000-2001 UDHS, information was obtained on delivery characteristics, and the results are given in Table 9.8. The data show that 3 percent of live births are delivered by caesarean section. Caesarean section is more common for younger women, first births, births to women in urban areas, those in the Central Region, and births to better educated women. The majority of births (seven in ten) in the five years preceding the survey were not weighed. This is not surprising given that only 37 percent are delivered in a health facility. Among those who were weighed, 90 percent have a normal birth weight (2.5 kilograms or more). This proportion varies little by background characteristics. 120 * Reproductive Health and Child Care Table 9.8 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, Uganda 2000-2001 ________________________________________________________________________________________________________________ Birth weight Size of child at birth ___________________________________ _________________________________ Delivery Less 2.5 kg Does not Smaller Average Does not Background by C- Not than or know/ Very than or know/ characteristic section weighed 2.5 kg more missing small average larger missing Number ________________________________________________________________________________________________________________ Age at birth <20 20-34 35-49 Birth order 1 2-3 4-5 6+ Residence Urban Rural Region Central Eastern Northern Western Education No education Primary Secondary+ Total 3.8 65.0 4.9 27.9 2.2 8.0 13.5 76.8 1.6 1,543 2.4 69.9 2.5 25.6 2.0 6.2 11.0 81.4 1.3 5,236 1.3 78.0 2.1 18.2 1.8 6.8 12.7 78.2 2.3 892 4.5 55.8 5.2 35.8 3.2 8.5 14.3 75.8 1.4 1,378 2.7 70.0 2.9 25.5 1.6 6.1 10.9 81.8 1.3 2,519 2.1 73.0 1.8 23.1 2.0 5.9 11.3 81.4 1.5 1,733 1.4 76.5 2.5 19.2 1.8 6.8 11.5 79.9 1.8 2,042 7.3 27.2 6.0 64.5 2.2 6.7 11.3 81.6 0.4 821 2.0 75.0 2.6 20.4 2.0 6.7 11.8 79.9 1.6 6,850 4.8 52.1 4.7 41.0 2.2 9.0 11.0 79.5 0.4 2,173 1.2 70.9 2.7 25.4 1.0 5.4 9.0 84.6 1.0 2,305 2.1 76.3 2.6 19.1 2.0 8.6 16.7 69.3 5.5 1,316 1.8 84.6 1.5 10.7 3.1 4.1 12.5 82.9 0.5 1,878 1.2 82.6 2.0 13.5 1.9 8.1 13.4 76.3 2.3 1,890 2.4 71.3 2.9 23.8 2.1 6.2 11.2 81.3 1.3 4,922 6.4 33.4 5.6 59.0 2.0 6.2 11.4 81.9 0.5 858 2.5 69.8 3.0 25.2 2.0 6.7 11.7 80.1 1.5 7,672 ______________________________________________________________________________________________________________ Note: Total includes one woman with missing information on education. Mothers were also asked to estimate the size of their babies. Eight in ten women stated that their baby was either average size or larger than average. This proportion varies little by background characteristics, except that babies in the Northern Region are more likely to be reported as smaller than average. 9.3 POSTNATAL CARE Postnatal care is important for a woman’s health and that of the infant, particularly within the first six weeks after delivery (puerperium). The Sexual and Reproductive Health Minimim Package recommends that a mother should attend postnatal care during the puerperal period, because complications may arise. Through provision of integrated services, the Ministry of Health recommends that mothers receive postnatal care when they bring their infants for immunisation. In the 2000-2001 UDHS, women who delivered at home were asked if a health professional or a traditional birth attendant checked on their health after delivery. Table 9.9 presents data on postnatal care attendance by background characteristics of the woman. The table indicates that postnatal care for births delivered outside a health facility is poor, with more than nine in ten women not receiving postnatal care. Among women who received postnatal care, the majority (76 percent) were examined within two days after delivery. While a woman’s age and number of Reproductive Health and Child Care * 121 Table 9.9 Postnatal care by background characteristics Percent distribution of women who had a noninstitutional live birth in the five years preceding the survey by timing of postnatal care for the most recent noninstutional birth, according to background characteristics, Uganda 2000-2001 _______________________________________________________________________________________________ First postnatal checkup _________________________________________ 3-7 8-28 29-41 Did not Within 2 days days days receive Background days of after after after postnatal characteristic delivery birth birth birth care1 Total Number _______________________________________________________________________________________________ Age at birth <20 20-34 35-49 Birth order 1 2-3 4-5 6+ Residence Urban Rural Region Central Eastern Northern Western Education No education Primary Secondary+ Total 5.8 1.6 0.0 0.0 92.5 100.0 379 5.9 1.3 0.3 0.2 92.3 100.0 1,902 5.6 1.7 0.1 0.0 92.6 100.0 495 7.1 1.8 0.6 0.0 90.5 100.0 289 5.4 1.4 0.2 0.0 92.8 100.0 842 6.0 1.6 0.2 0.4 91.9 100.0 700 5.6 1.2 0.1 0.2 92.9 100.0 944 12.7 3.2 1.2 0.2 82.7 100.0 110 5.5 1.3 0.2 0.2 92.8 100.0 2,666 8.5 3.4 0.5 0.5 86.8 100.0 538 8.0 1.0 0.3 0.0 90.7 100.0 792 3.2 1.4 0.0 0.3 95.1 100.0 587 3.9 0.6 0.1 0.0 95.5 100.0 859 4.9 0.9 0.2 0.2 93.8 100.0 892 5.9 1.5 0.2 0.1 92.3 100.0 1,733 11.1 3.0 0.0 1.0 85.0 100.0 150 5.8 1.4 0.2 0.2 92.4 100.0 2,775 _______________________________________________________________________________________________ Note: Total includes one woman with missing information on education. 1 Includes women who received the first postnatal care after 41 days children have no clear relationship with whether she receives postnatal care, her residence and education play an important role in getting care after delivery. As expected, urban women and better-educated women are more likely than other women to get postnatal care. Women in the Central and Eastern regions are more likely to receive postnatal care than women in other regions. 9.4 WOMEN’S STATUS AND REPRODUCTIVE HEALTH CARE Table 9.10 presents data on the relationship between a woman’s status and her ability to access and use reproductive health services. In this report, three indicators of women’s status are presented. They are the number of household decisions in which she participates, the number of circumstances in which the woman says a wife is justified in refusing to have sex with her husband, and the number of reasons the woman believes wife beating is justified. Table 9.10 indicates that the number of decisions in which a woman participates does not correlate with antenatal care, postnatal care, or delivery from a medical professional. However, the number of circumstances in which a woman feels that refusing sex is justified seems to have an influence on a woman’s likelihood of receiving antenatal, postnatal, and delivery care. Women who 122 * Reproductive Health and Child Care Table 9.10 Women’s status and reproductive health care Among women who had a live birth in the five years preceding the survey, the percentage who received antenatal care and postnatal care (last birth only), and percentage of births in the five years preceding the survey for which mothers received delivery care, by women’s status indicators, Uganda 2000-2001 _________________________________________________________________________________________ Percentage Births for whom of women Women who received mothers received who received postnatal care within delivery care from antenatal care two days of delivery2 health professional1 Women's status from a health ____________________ ____________________ indicator professional1 Percent Number Percent Number ________________________________________________________________________________________ Number of decisions in which woman has final say3 0 1-2 3-4 5 Number of reasons to refuse sex with husband 0 1-2 3-4 Number of reasons that wife beating is justified 0 1-2 3-4 5 Total 91.3 39.3 97 38.2 139 92.4 39.4 700 35.4 1,110 92.6 46.2 542 42.7 881 92.4 41.5 536 38.0 801 89.7 30.9 40 29.9 65 90.6 29.3 153 27.2 243 92.7 43.8 1,683 40.0 2,621 93.7 47.4 461 43.7 707 91.9 44.7 743 41.3 1,162 92.9 37.2 529 33.6 842 89.7 33.0 143 29.8 219 92.4 41.8 1,876 38.2 2,929 _________________________________________________________________________________________ 1 Health professional includes doctor, midwife, nurse, medical assistant, clinical officer, and nursing aide 2 Includes mothers who delivered in a health facility 3 Either by herself or jointly with others agree with more reasons for refusing sex are more likely to receive postnatal and delivery care from medical professionals. For example, 31 percent of women who feel there are no justifiable reasons to refuse to have sex received postnatal care, compared with 44 percent of women who feel it is justifiable to refuse to have sex for three to four reasons. Similarly, women who do not justify wife beating for any reason are more likely to receive postnatal care and delivery care than women who think there are reasons to justify wife beating. 9.5 CHILDHOOD IMMUNISATION Since 1995, when immunisation coverage was found to have declined, there have been special efforts to revitalise immunisation services in Uganda. The Uganda National Expanded Programme for Immunisation (UNEPI) recommends the following schedule of immunisation: polio and BCG at birth; polio and DPT at six, ten, and 14 weeks; and measles at nine months. BCG vaccination protects a child from tuberculosis, and DPT vaccination protects a child from diphtheria, pertussis, and tetanus. To be considered fully immunised, a child should have received one dose of BCG vaccine, three doses of DPT vaccine, three doses of polio vaccine and one dose of measles vaccine. The 2000-2001 UDHS collected information on immunisation coverage among children born in the five years preceding the survey. Data on immunisation coverage for the 2000-2001 UDHS was obtained from two sources, the immunisation cards and mothers’ recall. If the mother was able Reproductive Health and Child Care * 123 Table 9.11 Vaccinations by source of information Percentage of children 12-23 months who 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, Uganda 2000-2001 ____________________________________________________________________________________________________ Percentage of children who received: _________________________________________________________________________ DPT Polio1 No Source of ___________________ ______________________ vacci- information BCG 1 2 3 0 1 2 3 Measles All2 nations Number ____________________________________________________________________________________________________ Vaccinated at any time before the survey Vaccination card Mother's report Either source Vaccinated by 12 months of age3 46.2 44.8 38.5 31.2 24.9 45.7 40.9 33.5 32.2 26.3 0.1 711 32.5 32.2 25.4 15.0 8.3 38.2 31.3 20.6 24.6 10.4 12.7 793 78.7 77.0 63.9 46.1 33.2 83.9 72.2 54.1 56.8 36.7 12.8 1,504 75.0 72.9 59.6 42.0 31.9 79.4 67.5 49.6 42.3 28.5 17.3 1,504 ______________________________________________________________________________________________________ 1 Polio 0 is the polio given at birth. 2 BCG, measles, and three doses each 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 during the first year of life was assumed to be the same as for children with a written record of vaccination. to present a vaccination card to the interviewer, information on immunisation was extracted from the card. The mother was then asked whether the child had received other vaccinations that were not recorded on the card. If the mother was not able to provide the card, then she was asked to recall whether the child had received BCG, polio, DPT, and measles vaccinations and the number of doses of polio and DPT. Table 9.11 presents the percentage of children 12-23 months who had received specific vaccines at any time before the survey by source of information. The data show that 37 percent of children have been fully immunised; for 26 percent, data were obtained from information recorded on the immunisation card, and for 10 percent, data were obtained from the mother’s recall. Coverage of individual vaccines varies from 79 percent for BCG to 33 percent for polio at birth. Only 29 percent of children are fully immunised by 12 months of age as recommended. Thirteen percent of children 12-23 months have not received any of the recommended vaccines. Another way to evaluate the success of an immunisation programme is to calculate the dropout rate for DPT and polio. The dropout rate is defined as the percentage of children who received the first dose but did not receive the third dose of a specific vaccine. Using data in Table 9.11, the dropout rate for DPT is 40 percent and the rate for polio is 36 percent. 9.5.1 CHILDHOOD IMMUNISATION BY BACKGROUND CHARACTERISTICS Table 9.12 shows immunisation by background characteristics among children age 12-23 months. The data show that the chance of a child being immunised does not vary by the child’s sex. However, the chance varies according to the child’s birth order. First order births are more likely to be immunised than higher order births. Similarly, children in urban areas are more likely to be immunised than children in rural areas. For all antigens, the percentage of children who received immunisations was higher in urban areas than in rural areas. 124 * Reproductive Health and Child Care Table 9.12 Vaccinations by background characteristics Percentage of children age 12-23 months who had received specific vaccines at any time before the survey (according to vaccination card or the mother’s report), and percentage with a vaccination card, by background characteristics, Uganda 2000-2001 ____________________________________________________________________________________________________________________ Per- Percentage of children who received: centage _______________________________________________________________________ with a DPT Polio1 No vacci- Background ________________ ______________________ vacci- nation characteristic BCG 1 2 3 0 1 2 3 Measles All2 nations card Number ____________________________________________________________________________________________________________________ Child's sex Male Female Birth order 1 2-3 4-5 6+ Residence Urban Rural Region Central Eastern Northern Western Mother's education No education Primary Secondary+ Wealth index quintile Lowest Lower middle Middle Upper middle Highest DISH/CREHP districts DISH I Mbarara and Ntungamo II Masaka, Rakai and Sembabule III Luwero, Masindi and Nakasongola IV Kamuli and Jinja V Kampala CREHP (Kisoro, Kabale, and Rukungiri) Neither Total 79.6 77.5 63.7 44.6 33.4 85.6 72.0 52.5 56.2 36.4 11.8 47.5 763 77.8 76.5 64.1 47.7 33.0 82.2 72.5 55.8 57.4 37.0 13.9 47.1 741 85.2 77.6 64.5 52.3 42.4 84.5 74.2 57.7 59.2 42.4 9.9 47.7 235 78.7 79.1 64.5 46.0 32.7 84.1 70.9 53.3 56.2 36.1 12.6 48.1 513 78.7 76.4 63.1 43.6 32.6 83.8 72.2 52.5 55.8 34.7 13.1 46.7 352 74.9 74.6 63.5 44.9 29.1 83.4 72.7 54.6 57.1 35.9 14.6 46.4 405 91.9 88.5 75.1 59.1 57.2 91.0 80.0 60.0 68.4 42.1 6.2 42.6 167 77.0 75.6 62.5 44.5 30.2 83.0 71.2 53.4 55.3 36.0 13.7 47.8 1,337 70.7 68.5 52.6 37.9 34.4 74.8 59.6 40.9 50.9 29.0 20.9 40.6 423 84.4 78.4 63.8 44.7 39.9 88.4 75.1 57.1 53.1 37.8 6.5 53.7 445 78.2 78.9 65.9 44.9 39.5 84.5 76.2 56.1 57.9 33.2 13.4 43.7 255 81.2 83.5 75.1 57.7 20.0 88.4 80.2 64.0 66.9 46.3 10.9 49.6 382 70.9 71.0 55.2 37.0 25.5 81.2 65.8 48.2 54.1 28.3 16.7 41.1 368 79.5 77.4 64.9 46.9 32.9 84.1 73.1 54.6 55.5 37.2 12.4 49.2 957 90.4 87.5 76.4 60.6 50.9 88.6 80.4 64.1 69.4 51.1 6.9 49.3 179 73.8 71.8 54.2 34.9 28.0 81.4 67.7 46.7 49.1 26.5 14.8 47.5 341 77.6 76.4 63.7 45.2 34.2 85.7 72.7 54.7 58.0 38.0 11.8 45.9 352 76.5 75.9 67.5 51.4 30.5 82.4 73.8 59.1 57.6 39.6 14.2 48.7 295 82.7 79.2 65.5 47.7 24.8 83.9 70.6 51.9 57.2 39.5 12.3 47.0 277 85.3 84.2 71.6 55.1 52.2 86.6 77.8 60.4 64.5 42.6 10.4 47.5 239 71.0 67.5 52.6 38.8 31.1 75.9 60.6 41.9 51.1 30.1 19.1 40.6 419 68.5 68.3 63.4 45.0 4.7 77.1 67.9 53.1 56.5 38.1 22.9 31.5 107 47.0 43.1 28.4 18.7 21.2 51.8 36.7 18.9 36.7 12.8 39.2 27.8 105 72.6 65.8 39.5 21.1 22.9 81.6 46.4 19.0 37.8 14.3 9.4 46.4 57 84.2 78.1 56.4 48.1 58.7 85.8 71.9 52.7 51.6 42.2 6.8 66.9 71 93.3 90.7 76.0 61.3 61.3 93.3 82.7 64.0 72.0 42.7 5.3 42.7 79 96.6 95.5 92.0 83.3 45.4 98.9 95.5 83.7 78.4 65.5 1.1 66.9 74 80.6 79.6 66.5 46.5 33.2 86.1 75.3 57.1 57.6 37.4 11.1 48.6 1,011 78.7 77.0 63.9 46.1 33.2 83.9 72.2 54.1 56.8 36.7 12.8 47.3 1,504 ____________________________________________________________________________________________________________________ Note: Total includes one woman with missing information on education. 1 Polio 0 is the polio given at birth 2 BCG, measles, and three doses each of DPT and polio vaccine (excluding polio vaccine given at birth) Reproductive Health and Child Care * 125 37 42 36 29 38 33 46 28 37 51 UGANDA RESIDENCE Urban Rural REGION Central Eastern Northern Western MOTHER'S EDUCATION No education Primary Secondary + UDHS 2000-2001 Figure 9.2 Percentage of Children Age 12-23 Months Who are Fully Vaccinated, by Background Characteristics Childhood immunisation coverage is highest in the Eastern and Western regions, while children in the Central Region have a comparatively lower coverage for all vaccines (see Figure 9.2). Mother’s education is strongly associated with the chances of children receiving immunisations: 51 percent of children whose mother has secondary education are fully immunised, compared with 28 percent of children whose mother has no education. Children who fall in the highest wealth index quintile also show the highest vaccination coverage (43 percent), while children in the lowest quintile have the lowest coverage (27 percent). This pattern holds true for all types of vaccines. Children living in districts included in the DISH project have lower than average immunisation coverage (30 percent). In fact, the highest coverage is shown by districts in the CREHP project (66 percent), followed by districts covered by neither the DISH nor the CREHP project (37 percent). 126 * Reproductive Health and Child Care Table 9.13 Vaccination trends Percentage of children 12-23 months who received specific vaccines at any time before the survey, Uganda 1995 and 2000-2001 _________________________________________________________________________________________________________ Percentage of children who received: ______________________________________________________________________ DPT Polio No ________________ _____________________ vacci- Survey BCG 1 2 3 0 1 2 3 Measles All nations Number _________________________________________________________________________________________________________ 1995 UDHS 2000-2001 UDHS 83.6 81.7 73.5 61.1 22.9 82.2 73.0 59.0 59.6 47.4 14.4 1,588 78.7 77.0 63.9 46.1 33.2 83.9 72.2 54.1 56.8 36.7 12.8 1,504 9.5.2 VACCINATION TRENDS Table 9.13 shows vaccination coverage of children 12-23 months from the vaccination card and mothers’ recall in the 1995 UDHS and the 2000-2001 UDHS. The overall vaccination coverage found in the 2000-2001 UDHS is lower than that in the 1995 UDHS (37 percent and 47 percent). The decline is in part due to a slightly lower proportion of children who received BCG, measles, and the first dose of DPT and polio. However, the most important reason for the decline in the proportion of children fully immunised is an increase in the dropout rate for polio and especially for DPT. For example, in the 1995 UDHS, 25 percent of children 12-23 months who received the first dose of DPT did not go on to receive the third dose. By 2000-2001, the DPT dropout rate was 40 percent. 9.6 ACUTE RESPIRATORY INFECTION The accuracy of data on childhood illnesses depends heavily on how the mother recalls the events of child illnesses and the details of the treatment given. The prevalence of symptoms for ARI was obtained by asking mothers whether their children under five years had been ill with a cough accompanied by short, rapid breathing. Mothers whose children had experienced these symptoms were asked what they had done to treat the illnesses. Table 9.14 presents data on prevalence and treatment of acute respiratory infections among children under five years who had a cough accompanied by short, rapid breathing during the two weeks preceding the survey. The table further presents the percentage of children with ARI taken to a health facility or provider by background characteristics. Reproductive Health and Child Care * 127 Table 9.14 Prevalence and treatment of symptoms of acute respiratory infection and fever Percentage of children under five years who had a cough accompanied by short, rapid breathing (symptoms of ARI), percentage of children who had fever in the two weeks preceding the survey, and percentage of children with symptoms of ARI and/or fever for whom treatment was sought from a health facility provider, by background characteristics, Uganda 2000-2001 ____________________________________________________________________________ Percentage Percentage of children Percentage of children with of children taken to a Background symptoms with health facility characteristic of ARI fever Number or provider 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 Central Eastern Northern Western Mother's education No education Primary Secondary+ Mother’s smoking status Smokes cigarettes/tobacco Does not smoke cigarettes/tobacco Total 22.1 32.3 715 60.0 303 32.8 56.6 770 72.6 491 28.5 57.5 1,504 70.2 967 21.8 44.6 1,256 59.8 645 18.6 40.0 1,334 60.1 599 13.9 29.7 1,232 60.0 434 22.8 44.7 3,372 66.5 1,741 22.2 43.1 3,439 62.7 1,697 19.9 37.2 1,199 68.0 515 20.9 43.3 2,244 65.4 1,107 23.9 45.1 1,564 63.7 824 25.0 48.1 1,803 62.8 992 18.6 32.9 767 78.1 298 23.0 45.3 6,044 63.4 3,140 19.4 37.9 1,956 77.7 849 23.3 54.1 2,077 63.1 1,227 23.1 50.4 1,133 63.4 643 24.6 33.8 1,646 53.0 718 23.3 43.0 1,649 57.4 827 22.6 45.7 4,357 65.9 2,267 20.1 36.4 805 73.5 344 24.7 36.0 233 59.9 102 22.4 44.2 6,575 64.8 3,334 22.5 43.9 6,811 64.7 3,438 ____________________________________________________________________________ Note: Total includes one woman with missing information on education, and two women with missing information on smoking status Table 9.14 indicates that 23 percent of children were reported to have had acute respiratory infection. Two in three of these children were taken to a health facility for treatment. The highest prevalence of ARI was found among children age 6-11 months (33 percent). The prevalence of ARI decreases with age to 14 percent for children age 48-59 months. 128 * Reproductive Health and Child Care Prevalence of ARI does not vary by children’s sex, but there are differentials by birth order. The prevalence gradually increases from 20 percent for first order births to 25 percent for sixth and higher order births. Residence is associated with prevalence of ARI and health-seeking behaviour. A smaller percentage of children in urban areas than in rural areas are reported to have the symptoms of ARI. Prevalence of ARI is slightly lower in the Central Region than the other three regions (19 percent compared with 23 percent or higher). Prevalence of ARI among children does not vary much with mother’s education. Children of mothers who smoke are slightly more likely than those who do not smoke to suffer from ARI (25 percent compared with 22 percent). Forty-four percent of children had a fever in the two weeks preceding the survey. The differentials in the prevalence of fever across subgroups of children are in general similar to those of ARI. However, children whose mother smokes are less likely to be reported as having fever than children whose mother does not smoke. Data in Table 9.14 also show that two in three children who showed symptoms of ARI and/or fever were taken to a health facility for treatment. This percentage fluctuates by the child’s age, with children age 6-23 months being the most likely to be taken for treatment. Treatment-seeking behaviour varies only slightly according to the child’s sex and birth order. Children in urban areas are more likely to be treated than those in rural areas (78 and 63 percent, respectively). Children in the Central Region are more likely than children in other regions to be taken for treatment (78 percent), while children in the Western Region are the least likely (53 percent). Mother’s education makes a difference in the treatment of ARI and fever in children. Whereas 74 percent of children whose mothers have at least some secondary education were taken for treatment, the corresponding percentage for children of women with no education is 57 percent. 9.7 DIARRHOEA Diarrhoea was singled out for investigation since dehydration from watery diarrhoea is a major cause of death in infancy and childhood and the condition responds well to oral rehydration therapy (ORT). The combination of a high cause-specific mortality rate and the existence of effective treatment make diarrhoea and its treatment priority concerns for health services in Uganda. 9.7.1 HAND-WASHING MATERIALS In the 2000-2001 UDHS, if a household has a designated place for washing hands in the dwelling, yard, or plot, the respondent to the Household Questionnaire was asked to show this place to the interviewer. The interviewer then recorded whether materials required for washing hands (water, soap or other cleansing agent, and a basin) were available. Frequent hand-washing is a hygienic practice that protects members of the household, particularly children, from infections that cause diarrhoeal diseases. The connection between hand-washing and diarrhoea prevalence is well established. Promoting the practice of hand-washing and ensuring the availability of water, soap, and a basin substantially decrease the occurrence of diarrhoea in young children. The data on the availability of hand-washing facilities in households are presented in Table 9.15. The table indicates that water was available in 14 percent of the households, soap in 10 percent of the households, and a basin in 17 percent of the households. Only 4 percent of the households had all three hand-washing materials. Water was available in 23 percent of households in urban areas, compared with 12 percent of rural households. Availability of water is higher in the Central Region (22 percent) than in the other regions Reproductive Health and Child Care * 129 Table 9.15 Hand-washing materials in households Percentage of households with hand-washing materials in dwelling/yard/plot, by background characteristics and presence in the household of a child with diarrhoea in the two weeks preceding the survey, Uganda 2000-2001 __________________________________________________________________________________ Hand-washing materials and facilities ________________________________________________ All three Background hand-washing characteristic Water Soap or ash Basin materials Number1 __________________________________________________________________________________ Residence Urban Rural Region Central Eastern Northern Western Source of drinking water Piped Protected well Open well Surface Other/missing Time to water source In dwelling <5 minutes 5 to 9 minutes 10+ minutes Total 22.9 20.9 29.2 9.0 1,174 12.1 7.7 14.6 3.6 6,711 22.3 19.3 29.5 6.7 2,603 14.7 8.0 11.8 6.3 2,106 0.6 2.3 8.4 0.3 1,191 9.3 3.3 10.3 1.7 1,985 27.7 22.9 30.8 10.0 854 14.0 9.7 18.4 3.9 1,293 14.0 9.6 19.0 5.6 1,981 12.3 7.7 14.2 3.0 1,708 8.6 5.8 10.0 2.2 2,049 45.8 36.9 37.1 20.5 271 17.8 23.3 30.9 3.9 149 16.6 14.7 23.3 6.7 600 12.1 7.9 15.1 3.5 6,859 13.7 9.7 16.8 4.4 7,885 __________________________________________________________________________________ 1 Includes eight households with missing information on time to source (15 percent or less). It should be noted that water is available in less than 1 percent of households in the Northern Region. The availability of hand-washing materials varies according to residence. Urban households and those in the Central and Eastern regions tend to have the three materials more often than households in the other areas. Access to water determines the degree to which the household is exposed to healthy practices. One in five households that have a water source within the dwelling have all of the required hand-washing materials, compared with only 4 percent of households that are ten minutes or more from a water source. 9.7.2 DISPOSAL OF CHILDREN’S STOOLS The manner of disposal of children’s stools is associated with the prevalence and spread of diarrhoeal diseases among children. The ideal methods of disposal include having a child use a toilet, throwing the waste in the toilet, and burying the stool in the yard. Table 9.16 presents data on disposal of children’s stools by background characteristics and type of toilet facilities in households. The table shows that 76 percent of mothers dispose of their children’s stools properly, namely, by throwing the stool in a toilet or a latrine (62 percent), having the child always use a toilet or a latrine (8 percent), and burying the stool in the yard (5 percent). Seventeen percent of mothers do not dispose of stools properly: they throw the stool outside the dwelling (8 percent) or in the yard (9 percent). Proper disposal of 130 * Reproductive Health and Child Care Table 9.16 Disposal of children's stools Percent distribution of mothers whose youngest child under five years lives with her by way in which youngest child's faecal matter is disposed of, according to background characteristics and type of toilet facilities in household, Uganda 2000-2001 ________________________________________________________________________________________________ Stools contained Stools uncontained ________________________ ______________________ Child always Thrown uses into Buried Thrown Thrown Background toilet/ toilet/ in outside in characteristic latrine latrine yard dwelling yard Other Missing Total Number1 __________________________________________________________________________________________________ Residence Urban Rural Region Central Eastern Northern Western Education No education Primary Secondary+ Toilet facilities None Pit latrine Improved latrine Flush toilet Other Total 13.5 75.7 1.0 3.9 2.5 3.3 0.1 100.0 499 7.5 60.5 6.0 8.5 10.4 6.5 0.5 100.0 3,689 12.1 74.7 1.5 6.8 2.6 1.9 0.4 100.0 1,205 6.6 62.5 5.5 6.9 13.3 4.8 0.3 100.0 1,215 3.9 38.3 9.4 17.3 21.5 9.0 0.5 100.0 718 8.7 64.4 7.1 4.0 4.6 10.6 0.7 100.0 1,050 6.9 54.0 7.7 10.6 12.8 7.6 0.4 100.0 1,030 7.8 64.0 5.3 7.5 9.0 5.8 0.5 100.0 2,616 12.7 70.2 1.6 4.8 5.1 5.2 0.5 100.0 543 1.6 20.8 18.0 20.9 31.2 7.2 0.3 100.0 682 9.0 71.0 3.0 5.5 5.2 5.9 0.5 100.0 3,325 25.1 63.6 0.0 4.2 1.8 5.3 0.0 100.0 94 19.6 73.6 0.0 3.7 0.0 3.1 0.0 100.0 46 * * * * * * * 100.0 32 8.2 62.4 5.4 7.9 9.4 6.2 0.5 100.0 4,188 __________________________________________________________________________________________________ Note: An asterisk indicates that the figure is based on fewer than 25 unweighted cases and has been suppressed. 1 Total includes one woman with missing information on education and seven women with missing information on toilet facility. children’s stools is much more common in urban areas and in the Central Region than in other regions. The data further show that the way in which the mother disposes of the child’s stool is related to mother’s level of education. For example, 85 percent of mothers with secondary education dispose of their youngest child’s stool properly, compared with 69 percent of mothers with no education. The disposal of a child’s stool varies according to the presence of a toilet or a latrine in the dwelling. Children are more likely to use a toilet or latrine if the amenity is available in the household. The same is true regarding use of a toilet or latrine to throw the stool away. Table 9.16 shows that 93 percent of mothers who have flush toilets dispose of their child’s stool by throwing it in a toilet, compared with 21 percent of mothers with no toilet facilities. It is possible that these women used a communal toilet or a neighbour’s toilet. It should be noted that unsanitary disposal of stools is more common in the Northern Region than in other regions. In the Northern Region, safe disposal of stools is practised by 52 percent of mothers, compared with 75 percent or higher in the other regions. Reproductive Health and Child Care * 131 Table 9.17 Prevalence of diarrhoea Percentage of children under five years with diarrhoea in the two weeks preceding the survey, by background characteristics, Uganda 2000-2001 _____________________________________________ Diarrhoea in Background preceding characteristic 2 weeks Number _____________________________________________ Child's age (in months) <6 6-11 12-23 24-35 36-47 48-59 Child's sex Male Female Residence Urban Rural Region Central Eastern Northern Western Education No education Primary Secondary+ Hand-washing materials1 Water Soap or ash Basin All three materials Source of water Piped Protected well Open well Surface Other/missing Total 17.8 715 38.1 770 29.4 1,504 17.9 1,256 11.1 1,334 7.9 1,232 20.4 3,372 18.7 3,439 15.5 767 20.1 6,044 14.5 1,956 23.3 2,077 26.7 1,133 16.0 1,646 21.0 1,649 20.3 4,357 12.8 805 17.1 1,018 12.5 665 15.4 1,225 14.1 314 15.6 565 17.9 1,122 18.6 1,773 22.2 1,513 20.6 1,837 19.6 6,811 _____________________________________________ 1 In dwelling, yard, or plot 9.7.3 PREVALENCE OF DIARRHOEA In the 2000-2001 UDHS, mothers were asked whether their children under five years had had diarrhoea in the two weeks before the survey. This measure of diarrhoea prevalence is affected by the ability of the mother to recall when the diarrhoea episode occurred and by seasonal variation in the occurrence. Because the UDHS data collection took place over a period of more than five months, it is believed that seasonal variation was not a problem during interpretation of the findings. Table 9.17 shows that 20 percent of children less than five years of age had diarrhoea in the two weeks preceding the survey. The prevalence of diar- rhoea is highest among children age 6–11 months (38 percent). The risk of diarrhoea decreases as the child grows; thus, the lowest level is found among children 48-59 months (8 percent). The prevalence of diarrhoea does not vary according to the child’s sex. However, residence plays a role, with urban children having a lower prevalence than rural children (16 percent compared with 20 per- cent). Diarrhoea prevalence is higher in the Eastern and Northern regions (23 percent and 27 percent, respectively) than in the Central and Western regions (15 to 16 percent). Mother’s education is negatively associated with a child’s risk of getting diarrhoea. Children born to mothers with secondary or higher education have a lower prevalence of diarrhoea than children whose mother has no education (13 percent and 21 percent, respectively). This finding is consistent with the results in Table 9.16, which show that mother’s education is associated with the correct practice of stool disposal, which reduces the spread of diarrhoeal diseases. Table 9.17 implies that the presence of hand- washing materials has only a slight impact on the prevalence of diarrhoea among children in the house- hold. Diarrhoea is most prevalent among children who live in households using surface water and least prevalent in households with piped water. 132 * Reproductive Health and Child Care Table 9.18 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 in young children, by selected background characteristics, Uganda 2000-2001 ______________________________________________ Percentage of mothers who Background know about characteristic ORS packets Number ______________________________________________ Age 15-19 20-24 25-29 30-34 35+ Residence Urban Rural Region Central Eastern Northern Western Education No education Primary Secondary+ Total 90.7 409 90.9 1,235 92.9 1,167 93.4 780 91.0 899 96.6 560 91.2 3,930 95.5 1,323 95.9 1,273 92.6 775 82.3 1,119 86.9 1,103 92.8 2,791 96.5 594 91.8 4,489 _____________________________________________ Note: Total includes one woman with missing information on education ORS = Oral rehydration salts 9.7.4 KNOWLEDGE OF ORS PACKETS Since prevalence of diarrhoea is high among children under age five, the management of diar- rhoea by mothers at home is of great importance. The 2000-2001 UDHS asked the mothers whether they had ever heard of a special product for the treatment of diarrhoea, oral rehydration salts (ORS). Table 9.18 presents data on mothers’ knowledge of ORS. Nine in ten mothers (92 percent) know about the use of ORS packets for treating diarrhoea. The level of knowledge of ORS ranges between 82 percent and 97 percent across all socioeconomic groups. Women in the Western Region and those with no education are least likely to know about ORS, with percentages below 90 percent. 9.7.5 TREATMENT OF DIARRHOEA The 2000-2001 UDHS sought information on medical care for diarrhoea episodes in the two weeks preceding the survey. Particular attention was given to treatment with oral rehydration therapy (ORT), which includes a solution prepared from ORS packets; recommended home fluids (RHF) (either cereal-based or a solution made from sugar, salt, and water); and increased fluids. Table 9.19 shows the percentage of children with diar- rhoea in the two weeks preceding the survey who were treated with ORT and other treatments. Table 9.19 shows that 45 percent of children who had diarrhoea in the two weeks preceding the survey were taken to a health facility for treatment. Wide differentials are seen in the proportion of children with diarrhoea who were taken to a health provider. Young children, first births, those in rural areas, and those whose mother has less education were less likely to be taken to a health provider for treatment. Reproductive Health and Child Care * 133 Ta bl e 9. 19 D ia rr ho ea tr ea tm en t Am on g ch ild re n un de r f iv e ye ar s w ho h ad d ia rr ho ea in th e tw o w ee ks p re ce di ng th e su rv ey , p er ce nt ag e ta ke n fo r t re at m en t t o a he al th p ro vi de r, pe rc en ta ge w ho re ce iv ed or al re hy dr at io n th er ap y (O RT ), an d th e pe rc en ta ge g iv en o th er tr ea tm en ts , a cc or di ng to b ac kg ro un d ch ar ac te ris tic s, U ga nd a 20 00 -2 00 1 __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ O ra l r eh yd ra tio n th er ap y O th er tr ea tm en ts __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ _ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ Pe rc en ta ge O RS , R H F, ta ke n to Ei th er or Ta bl et H om e Ba ck gr ou nd a he al th O RS O RS In cr ea se d in cr ea se d or In je c- In tra - re m ed y/ ch ar ac te ris tic pr ov id er pa ck et s RH F or R H F flu id s flu id s sy ru p tio n ve no us ot he r N on e M iss in g N um be r __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ C hi ld 's ag e (i n m on th s) < 6 6 -1 1 1 2- 23 2 4- 35 3 6- 47 4 8- 59 C hi ld 's se x M al e F em al e Bi rt h or de r 1 2 -3 4 -5 6 + Re si de nc e U rb an R ur al Re gi on C en tra l E as te rn N or th er n W es te rn Ed uc at io n N o ed uc at io n P rim ar y S ec on da ry + To ta l 29 .1 16 .9 10 .0 23 .0 13 .9 30 .2 39 .3 1 .3 0 .0 17 .3 34 .4 0 .0 1 27 51 .1 36 .5 14 .6 44 .8 25 .7 54 .9 49 .8 4 .4 0 .2 14 .2 17 .9 0 .0 2 93 49 .3 38 .1 18 .2 48 .5 31 .6 58 .2 52 .4 3 .6 0 .0 13 .2 16 .4 0 .1 4 43 46 .8 33 .2 14 .5 43 .2 26 .5 53 .7 52 .0 1 .8 0 .5 17 .6 15 .6 0 .0 2 25 36 .3 32 .8 21 .1 41 .3 31 .5 53 .6 52 .7 4 .3 0 .0 11 .8 18 .0 0 .4 1 48 35 .5 26 .1 27 .9 43 .8 31 .4 52 .9 50 .7 2 .6 0 .0 13 .6 14 .2 1 .2 9 7 44 .5 35 .6 17 .6 45 .1 27 .4 54 .1 47 .1 3 .8 0 .1 12 .8 21 .2 0 .3 6 89 45 .4 31 .2 16 .4 41 .2 28 .1 52 .1 54 .0 2 .7 0 .2 16 .2 15 .3 0 .0 6 44 39 .8 28 .3 11 .4 35 .0 25 .4 44 .3 49 .3 2 .5 0 .2 16 .4 22 .0 0 .5 2 12 47 .0 35 .8 18 .8 45 .9 27 .8 56 .6 49 .6 4 .5 0 .2 14 .3 17 .7 0 .1 4 62 42 .4 34 .0 17 .4 43 .1 27 .7 51 .9 48 .8 3 .2 0 .0 13 .9 20 .2 0 .2 2 95 47 .2 33 .1 17 .8 44 .7 28 .9 54 .9 53 .5 2 .1 0 .0 13 .9 15 .4 0 .0 3 64 63 .9 43 .5 17 .1 53 .3 41 .8 66 .6 67 .5 2 .9 1 .3 5 .3 11 .9 0 .2 1 19 43 .0 32 .5 17 .0 42 .2 26 .3 51 .8 48 .8 3 .3 0 .0 15 .3 19 .0 0 .1 1, 21 4 58 .1 39 .1 22 .7 55 .9 50 .6 71 .3 48 .1 2 .5 0 .4 12 .2 14 .2 0 .0 2 83 47 .2 39 .7 17 .1 45 .9 22 .8 54 .4 63 .2 4 .9 0 .1 8 .0 15 .7 0 .1 4 84 39 .4 30 .5 14 .7 40 .4 23 .9 49 .5 48 .1 2 .6 0 .0 7 .9 22 .7 0 .4 3 03 32 .8 19 .2 13 .6 27 .8 16 .6 35 .5 32 .3 1 .8 0 .0 36 .3 22 .7 0 .1 2 63 38 .9 32 .8 19 .6 42 .7 21 .6 50 .9 43 .7 3 .4 0 .0 14 .1 22 .5 0 .3 3 47 45 .0 32 .8 15 .6 42 .2 27 .9 52 .4 52 .0 3 .3 0 .1 14 .9 17 .3 0 .1 8 83 64 .0 41 .3 20 .6 53 .7 46 .5 67 .2 59 .9 1 .9 0 .5 11 .7 13 .0 0 .2 1 03 44 .9 33 .5 17 .0 43 .2 27 .7 53 .1 50 .4 3 .2 0 .1 14 .4 18 .3 0 .2 1, 33 3 __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ O RS = O ra l r eh yd ra tio n sa lts RH F = R ec om m en de d ho m e flu id s 134 * Reproductive Health and Child Care Table 9.20 Feeding practices during diarrhoea Percent distribution of children under five years who had diarrhoea in the two weeks preceding the survey by amount of liquids and amount of food given compared with normal practice, Uganda 2000-2001 __________________________________ Liquid/food offered Percent _________________________________ Amount of liquid offered Same as usual More Somewhat less Much less None Don't know/missing Total Amount of food offered Same as usual More Somewhat less Much less None (stopped) Never gave food Don't know/missing Total Number 31.2 27.7 20.6 10.7 9.4 0.4 100.0 29.2 4.6 23.5 16.1 10.9 14.9 0.8 100.0 1,333 More than half of the children with diarrhoea (53 percent) were treated with ORS, or recommended home fluids, or increased fluids. Individually, these treatments account for 34 percent (ORS packets), 17 percent (RHF), and 28 percent (increased fluids). Tablets and syrups were given to half of the children, and only a few children were treated with injections or intravenous fluids. Eighteen percent of the children with diarrhoea were not given any treatment at all. 9.7.6 FEEDING PRACTICES DURING DIARRHOEA The recovery of a child suffering from diarrhoea depends, among other things, on the feeding practices during the diarrhoea episode. In particular, consumption of extra fluids is essential. Table 9.20 presents data on feeding practices of children who had diarrhoea in the two weeks preceding the survey. The data show that only 28 percent of children with diarrhoea were given more fluids than usual, while 31 percent were given the same amount of fluids. It should be noted that four in ten children with diarrhoea were given less fluid or none at all. The table further shows that only 5 percent of children were given more food than usual, while 51 percent were given less food or none at all. Overall, the results of the 2000-2001 UDHS show that feeding practices for children with diarrhoea in Uganda are inconsistent with recommended interventions. 9.8 WOMEN’S STATUS AND HEALTH CARE 9.8.1 WOMEN’S STATUS AND CHILDREN’S HEALTH CARE The 2000-2001 UDHS investigated the relationship between children’s health care and women’s status as measured by their ability to influence household decisionmaking, the number of reasons a woman feels she is justified to refuse sex, and the number of reasons to justify wife beating. Table 9.21 shows that a woman’s independence is positively associated with her children’s health care. For example, women who participate in more decisions are slightly more likely to have fully vaccinated children. Data on the number of reasons for justifying wife beating do not show a strong pattern: children of women who have more reasons to refuse sexual relations with their husband are slightly less likely to be fully vaccinated. The opposite pattern is observed when the number of reasons to justify wife beating is considered: women with fewer reasons are also more likely to have fully vaccinated children. The relationship between women’s status and treatment during their children’s illness is less clear. Children whose mother does not justify wife beating for any reason are more likely than children of women who think there are reasons to justify wife beating to receive treatment from a health professional for diarrhoea. Reproductive Health and Child Care * 135 Table 9.21 Child health care by women’s status Percentage of children age 12-23 months who were fully vaccinated, and percentage of children under five years ill with a fever, symptoms of ARI, or diarrhoea, in the two weeks preceding the survey who were taken to a health provider for treatment, by women's status indicators, Uganda 2000-2001________________________________________________________________________________________ Children under five years ________________________________________ Children age Percentage 12-23 months Percentage with ____________________ with fever/ diarrhoea Percentage ARI taken taken to Women's status fully to health health indicator vaccinated Number provider Number provider Number ________________________________________________________________________________________ Number of decisions in which woman has final say2 0 1-2 3-4 5 Number of reasons to refuse sex 0 1-2 3-4 Number of reasons wife beating justified 0 1-2 3-4 5 Total * 18 (31.5) 49 * 27 36.0 225 30.4 473 42.6 240 35.3 143 30.5 279 49.9 178 40.7 167 26.8 218 45.5 154 * 7 (24.2) 27 * 24 40.2 65 23.4 79 40.0 63 37.1 480 30.5 913 45.4 512 39.3 122 27.5 201 54.5 134 38.6 219 31.5 371 46.5 206 35.3 176 28.5 333 40.9 198 (27.6) 36 31.3 114 38.0 60 36.7 552 29.6 1,018 44.9 599 ________________________________________________________________________________________ Note: Figures in parentheses are based on 25-49 unweighted cases. An asterisk indicates that the figure is based on fewer than 25 unweighted cases and has been suppressed. 1 Those who have received BCG, measles and three doses each of DPT and polio vaccine (excluding polio vaccine given at birth) 2 Either by herself or jointly with others 9.8.2 WOMEN’S PROBLEMS IN ACCESSING HEALTH CARE Many factors influence women’s access to health care. These include socioeconomic status and medical and cultural factors. Some of these factors prevent women from getting medical advice or treatment for themselves. In the 2000-2001 UDHS, all women were asked whether they had problems seeking medical advice or treatment for themselves. Women were asked whether they had problems with knowing where to go, getting permission to go, getting money for treatment, travelling long distances to a health facility, getting transport to a health facility, having a person accompany them, lacking a female provider, and negative attitudes of providers. Table 9.22 presents data on women’s problems in accessing health care for these specific reasons. The results show that 85 percent of women experience at least one problem in assessing health care. The greatest problem in assessing health care is getting the money for treatment (63 percent). In the 2000- 2001 UDHS, most of the fieldwork was carried out before February 2001, when cost sharing was abolished in government health units. This explains the high percentage of women who felt getting money to pay for treatment was a barrier in accessing health services. The other problems include distance to a health facility (44 percent), transportation (43 percent), and negative attitude of health care providers (42 percent). Table 9.22 shows that 7 percent of women have the problem of not knowing where to go and 8 percent have the problem of getting permission to seek health care. 136 * Reproductive Health and Child Care Table 9.22 Perceived problem 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, Uganda 2000-2001_______________________________________________________________________________________________________________________ Getting Getting money Distance Not Lack of a Negative Knowing per- for to Have to wanting female attitude of Any of the Background where mission treat- health take to go health health care specified characteristic to go to go ment facility transport alone provider 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 Central Eastern Northern Western Education No education Primary Secondary+ Current employment Not employed Works for cash Does not work for cash Total 9.8 15.7 58.0 41.3 40.3 32.9 25.9 45.0 84.3 1,615 6.0 6.8 60.8 42.1 41.6 19.1 15.6 42.5 84.1 2,846 5.5 4.7 65.7 46.5 45.9 17.3 11.6 39.5 85.1 1,793 6.7 5.5 73.2 48.1 49.1 17.6 13.6 40.0 89.6 993 9.9 14.5 55.8 39.8 39.5 32.9 24.8 46.6 83.5 1,730 6.4 7.1 61.2 41.2 40.7 17.6 15.3 42.2 84.3 2,021 5.1 5.3 65.5 47.3 45.5 18.1 13.9 40.4 85.7 1,665 6.0 5.5 70.0 47.4 48.2 18.1 12.8 38.9 87.2 1,830 10.4 15.1 56.7 37.8 38.7 34.1 26.3 47.8 83.2 1,456 5.7 6.9 63.0 44.5 43.4 18.5 13.9 39.8 84.9 4,881 7.4 2.7 73.6 50.2 50.8 17.5 15.7 44.6 89.5 910 4.5 5.3 45.4 14.3 18.2 14.4 16.3 53.1 73.2 1,207 7.3 8.6 66.6 49.8 48.5 22.9 16.7 39.8 87.5 6,039 5.5 5.5 50.4 36.8 38.1 16.3 22.7 60.1 82.5 2,341 4.7 6.2 71.6 44.2 44.3 23.7 15.6 38.3 89.9 1,956 12.9 16.9 80.9 58.4 53.2 25.7 16.6 22.3 92.0 1,158 7.0 7.7 59.0 43.2 43.1 23.1 9.8 35.0 79.0 1,792 7.6 9.3 76.5 51.1 49.6 20.6 14.4 37.7 90.5 1,584 7.5 8.3 63.9 46.1 45.8 22.9 17.4 40.9 85.6 4,330 3.7 5.9 44.6 27.9 28.4 18.2 16.7 50.7 77.3 1,331 9.3 12.2 56.4 37.6 37.7 25.1 23.4 43.8 80.9 1,489 4.0 4.3 60.6 39.2 39.8 14.9 12.4 41.4 82.6 3,511 9.7 11.2 71.4 55.3 52.9 29.4 18.7 41.6 91.9 2,246 6.8 8.1 63.1 43.9 43.4 21.5 16.6 42.0 85.2 7,246 The table shows variations by socioeconomic characteristics. The woman’s age and number of living children do not significantly affect the women’s health-seeking behaviour. In general, unmarried women cited more problems than married or formerly married women. Similarly, rural women were more likely to cite problems than their urban counterparts. For instance, distance to a health facility and having to take transport were cited by almost half of the rural women, compared with 14 to 18 percent of urban women. Comparison across regions shows that women in the Northern Region tend to cite more problems than women in other regions. However, women in the Central Region are the most likely to cite lack of a female health provider and negative attitude of the health worker as big problems. A woman’s education and employment status have an impact on their perceived problems in accessing health care. Women with secondary or higher education and unemployed women were generally the least likely to perceive the issues as problems. On the other hand, women with no education and women who do not work for cash are the most likely to cite problems. Reproductive Health and Child Care * 137 Table 9.23 Possession and use of mosquito nets Percentage of households with mosquito nets and the percentage of children under five who sleep under a mosquito net, by background characteristics, Uganda 2000-2001_________________________________________________________________________ Percentage of children under age 5 living with mothers who:______________________________ Households Slept Usually that own at least under a sleep one mosquito net mosquito under a Background ____________________ net last mosquito characteristic Percent Number night net Number_________________________________________________________________________ Residence Urban Rural Region Central Eastern Northern Western Quality of housing Electricity Piped water Finished floor None Total 32.9 1,174 21.1 23.4 773 9.2 6,711 5.7 6.3 6,793 15.3 2,603 7.3 8.2 2,093 15.4 2,106 9.9 11.1 2,315 14.6 1,191 9.8 10.7 1,297 5.5 1,985 2.2 2.4 1,862 46.1 675 21.5 23.3 464 33.2 854 21.0 23.0 572 30.7 1,532 15.2 17.2 1,122 8.3 6,101 5.8 6.4 6,210 12.8 7,885 7.3 8.1 7,566 9.9 MALARIA 9.9.1 POSSESSION AND USE OF MOSQUITO NETS Malaria is a major public health concern in Uganda, since it is a leading cause of morbidity and mortality. This disease especially affects children under 5 and pregnant women. In such a situation, the use of mosquito nets is important as a protection from the disease. Information on the possession and use of mosquito nets was collected from all households in the 2000-2001 UDHS. Table 9.23 shows that only 13 percent of households in Uganda have mosquito nets. Mosquito nets are less likely to be available in households in the Western Region than in the other regions (6 percent compared to 15 percent). Urban households are more than three times more likely to have a mosquito net than rural households. The availability of mosquito nets is closely related with the quality of the house. Households which have electricity, piped water and finished floors are much more likely to have mosquito nets than households which have none of these amenities. The last three columns in Table 9.23 refer to children under age 5 who live with their mothers. Eight percent of these children usually sleep under a mosquito net and 7 percent spent the night before the survey under a mosquito net. As mosquito nets are less available in the Western region, children in this region are also less likely to sleep under a mosquito net. Urban children are more than three times more likely than rural children to have slept under a mosquito net the night before interview (21 percent compared to 6 percent). Children living in households with the specified housing amenities are much more likely than children who live in households with none of the amenities to sleep under a net. 138 * Reproductive Health and Child Care Table 9.24 Mosquito net age and insecticide treatment for mosquito nets Age of mosquito nets and insecticide treatment pattern for mosquito nets that were used the previous night by children under age five, women age 15-49 and pregnant women 15-49, according to background characteristics, Uganda 2000-2001_____________________________________________________________________________________________________ Percentage of women Percentage of pregnant Children under 5 15-49 who slept under: women 15-49 who slept under: _____________________________________ __________________________ ________________________ Average Number of Average months children Any Any age Percent since using mos- Treated Number mos- Treated Number Background of nets of nets last mosquito quito mosquito of quito mosquito of characteristic (months) treated1 treatment nets2 net net1 women net net1 women_____________________________________________________________________________________________________ Residence Urban Rural Region Central Eastern Northern Western Mother's education No education Primary Secondary+ Total 24.8 4.3 2.9 193 13.0 0.8 1,207 13.3 0.4 97 28.8 2.7 5.1 431 5.8 0.2 6,039 5.8 0.5 813 25.0 3.8 3.4 184 6.8 0.4 2,341 4.1 0.2 235 27.0 3.2 5.0 254 9.5 0.3 1,956 10.3 0.7 287 37.4 1.6 1.0 140 10.3 0.1 1,158 8.9 0.0 135 13.1 5.9 6.6 45 2.3 0.3 1,792 3.5 1.0 253 31.8 6.1 2.7 84 5.1 0.3 1,584 6.0 0.6 206 26.0 2.0 2.8 349 5.4 0.2 4,330 5.6 0.3 593 28.6 4.0 6.0 191 14.4 0.7 1,331 13.4 1.8 110 27.6 3.2 4.4 624 7.0 0.3 7,246 6.6 0.5 910 _____________________________________________________________________________________________________ 1 Soaked or dipped in insecticide in last six months 2 Either usually or the night before the survey 9.9.2 INSECTICIDE TREATMENT OF MOSQUITO NETS Table 9.24 presents the age and insecticide treatment of mosquito nets used by children under five, women age 15-49 and pregnant women age 15-49 the night before the interview, by background characteristics. On average, the nets were bought or obtained more than two years preceding the survey (28 months). Nets used in households in the Northern region are older than average (37 months), while those in the Western region are more recently obtained (13 months). Mosquito nets in rural households are in general older than those in urban households. There is no relationship between the education attainment of the children's mothers and the mosquito net's age. Only 3 percent of nets had been treated or dipped in insecticide in the six months prior to the survey. On average, nets were dipped in insecticide more than 4 months prior to the survey. Nets in the Eastern and Western regions, in rural areas and in households where the child's mother has some secondary education have been dipped on average 5 months or more before the survey. While 7 percent of all women age 15-49 slept under a mosquito net the night before interview, only a small percentage used nets that had been treated with insecticide. As in the case of children, women in Eastern and Northern regions, those living in urban areas and women with some secondary education are much more likely than other women to have slept under a mosquito net. The pattern of use of mosquito nets among pregnant women is the same as that of all women. Reproductive Health and Child Care * 139 Table 9.25 Malaria prevention during pregnancy Percentage of women who took malaria prophylaxis during the last pregnancy in the five years preceding the survey by source of malaria drugs, according to background characteristics, Uganda 2000-2001__________________________________________________________________________________ Source of drug Percent ______________________________ of women During who Number During another From Background received of antenatal facility another characteristic prophylaxis women visit visit source Total____________________________________________________________________________________ Residence Urban Rural Region Central Eastern Northern Western Mother's education No education Primary Secondary Birth order 1-2 3+ Total 37.8 560 44.3 46.7 9.0 100.0 33.2 3,930 37.3 46.4 16.3 100.0 39.7 1,323 52.9 36.8 10.3 100.0 39.2 1,273 29.1 46.9 24.0 100.0 30.4 775 48.0 42.1 9.9 100.0 23.0 1,119 17.8 68.8 13.4 100.0 29.3 1,103 37.9 43.7 18.4 100.0 33.9 2,791 36.0 48.4 15.6 100.0 41.9 594 48.3 41.9 9.8 100.0 35.2 1,429 41.2 44.0 14.8 100.0 33.1 3,061 36.9 47.7 15.4 100.0 33.8 4,489 38.3 46.6 15.1 100.0 __________________________________________________________________________________ Note: Includes one woman with missing information on education 9.9.3 MALARIA PROPHYLAXIS DURING PREGNANCY In the UDHS, women who gave birth in the five years preceding the survey were asked whether they took drugs in order to prevent malaria during pregnancy. Women who took medicine were asked the type of drug and where they obtained the drug. Table 9.25 shows the responses to these queries. Data in Table 9.25 show that thirty-four percent of women took drugs against malaria during pregnancy. Small variations are found by the woman's residence, except in the Western region (23 percent). The likelihood of a pregnant woman taking malaria tablets increases gradually with her education, from 29 percent for women with no education to 42 percent for women with some secondary education. Table 9.25 also shows that pregnant women are more likely to obtain the malaria tablets during a visit to a health facility for other than antenatal care than during an antenatal care visit (47 percent compared to 38 percent). Women living in the Central and Northern regions, and women with secondary education are more likely than other women to obtain the malaria tablets during an antenatal care visit. 140 * Reproductive Health and Child Care UDHS 2000-2001 Figure 9.3 Type of Malaria Tablets Taken During Pregnancy Chloroquine 45% Fansidar 4% Camaquine 3% Quinine 3% Other 32% Don't know 13% 9.9.4 TYPE OF ANTI-MALARIAL TREATMENT Figure 9.3 shows the percent distribution of women who took malaria tablets during pregnancy by the type of drug. Almost half of pregnant women who took malaria prophylaxis took chloroquine (45 percent). Fansidar, Camaquine and quinine are taken by 3-4 percent of women. Unfortunately, many women are unable to report the type of drug they take (13 percent) or take drugs other than those which are specified in the survey questionnaire (32 percent). 9.10 BIRTH REGISTRATION Birth registration is one of the recognised rights of a child in Uganda today. Although registration has been compulsory since 1903, Uganda has never had a sound registration system for either statistical or legal purposes. The government of Uganda has started initiatives on a pilot basis to revive the civil registration system in the country. In the 2000-2001 UDHS, for each birth in the five years prior to the UDHS, women were asked whether the child was registered. If a child is registered in the local authority, a “short certificate” would normally be issued, while the Registrar General’s office issues a “long certificate.” Table 9.26 shows the distribution of births in the five years preceding the survey by whether the birth was registered and the type of certificate obtained. Overall, coverage of birth registration in Uganda is poor, with only 4 percent of all births in the past five years reported by the mother to be registered at any of the authorities. However, among those registered, for most (81 percent) births, no document was seen by the interviewer. Among registered births, 13 percent were registered in the local authority and the mother was able to show a short certificate. Six percent of births were registered at the Registrar General’s office, and less than 1 percent were registered at a local authority as well as the Registrar General’s office. Reproductive Health and Child Care * 141 Table 9.26 Birth registration Percentage of births in the five years preceding the survey that were registered and, of those registered, percent distribution by the type of certificate, according to background characteristics, Uganda 2000- 2001 ___________________________________________________________________________________________ Certificate seen Background Percent _________________________ Certificate characteristic registered Short Long Both not seen Total Number ___________________________________________________________________________________________ Age of mother <20 20-24 25-29 30-34 35-39 40-44 45-49 Residence Urban Rural Region Central Eastern Northern Western Education No education Primary Secondary+ Total 3.9 * * * * 100.0 518 5.0 8.9 6.7 1.9 82.5 100.0 2,237 4.7 12.2 3.9 0.0 83.9 100.0 2,116 3.2 (17.1) (8.6) (0.7) (73.5) 100.0 1,389 3.4 (17.6) (0.0) (0.0) (82.4) 100.0 901 2.3 * * * * 100.0 388 3.1 * * * * 100.0 123 11.0 14.1 10.6 1.5 73.8 100.0 821 3.4 12.8 3.6 0.5 83.1 100.0 6,850 7.1 16.6 9.4 1.6 72.4 100.0 2,173 1.9 (23.8) (0.5) (0.0) (75.7) 100.0 2,305 6.6 2.0 1.3 0.0 96.7 100.0 1,316 1.8 (12.4) (5.4) (0.0) (82.2) 100.0 1,878 2.0 (9.8) (3.2) (0.0) (87.0) 100.0 1,890 3.6 11.3 1.8 0.2 86.7 100.0 4,922 12.2 17.7 12.9 2.0 67.4 100.0 858 4.2 13.2 5.6 0.8 80.5 100.0 7,672 ___________________________________________________________________________________________ Note: Figures in parentheses are based on 25-49 unweighted cases. An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. Coverage of birth registration varies substantially by residence, region, and mother’s education. Births in urban areas are three times more likely to be registered than births in rural areas. Mother’s level of education is also important. Births to mothers with secondary or higher education are six times more likely to be registered than births to mothers with no education. Births in the Central and Northern regions are more likely to be registered than those in other regions. Infant Feeding and Children’s and Women’s Nutritional Status * 143 10INFANT FEEDING AND CHILDREN’S ANDWOMEN’S NUTRITIONAL STATUS The findings presented in this chapter relate to infant feeding, including breastfeeding practices, complementary feeding, and the nutritional status of children less than five years of age and of women 15-49. Appropriate feeding practices are of fundamental importance for the survival, growth, development, health, and nutrition of infants and young children. The mother’s nutritional well- being before and during conception can permanently influence the health of the child at all developmental stages, her own ability to successfully parturate and breastfeed, and her general health. The health benefits of breastfeeding for both mother and child are undisputed, and they are influenced by both the duration and intensity of breastfeeding and by the age at which the child receives complementary foods and liquids. 10.1 BREASTFEEDING AND COMPLEMENTARY FEEDING 10.1.1 INITIATION OF BREASTFEEDING Data presented in Table 10.1 confirm that breastfeeding in Uganda is universal, with 98 percent of children born in the five years preceding the survey having been breastfed at some time. This is true for all subgroups of children. Mother and child benefit from early initiation of breastfeeding. From the child’s perspective, colostrum (first breast milk) is important because it is rich in antibodies, which have the effect of protecting the child against infection and reducing the risk of dying. The mother is affected because breastfeeding lengthens the period of postpartum infertility, which lengthens the interval between births and results in the woman having fewer births and lower fertility. These effects are influenced by both the duration and intensity of breastfeeding. Table 10.1 shows that about one-third of babies are put to the breast within one hour of birth, while 86 percent initiate breastfeeding in the first day of life. There is little variation in the initiation of breastfeeding across background characteristics. The delay in starting breastfeeding immediately is an indication that some prelacteal feeding is begun during the period between birth and initiation of breastfeeding. The data show that four in ten children receive complementary feeding before breastfeeding. Prelacteal feeding is more likely in urban areas (51 percent) than in the rural areas (43 percent). More than half of the women in the Central Region (53 percent) give prelacteal feeds, whereas the proportion of those that do so in the other regions is less. Furthermore, 51 percent of women with secondary education report giving prelacteal feeds, compared with 41 percent among those with no education at all. 144 * Infant Feeding and Children’s and Women’s Nutritional Status 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 a prelacteal feed, by background characteristics, Uganda 2000-2001________________________________________________________________________________________________ Percentage who started breastfeeding:_____________________ Percentage Percentage Within Within who received Number Background ever 1 hour 1 day a prelacteal ever characteristic breastfed Number of birth of birth1 feed2 breastfed_______________________________________________________________________________________________ Sex Male Female Residence Urban Rural Region Central Eastern Northern Western Mother's education No education Primary Secondary+ Assistance at delivery Health professional3 Traditional birth attendant Other No one Place of delivery Health facility At home Other Total 98.2 3,814 30.6 86.0 45.0 3,746 98.5 3,858 32.5 86.5 42.4 3,798 98.3 821 32.3 88.6 51.2 807 98.3 6,850 31.5 86.0 42.8 6,737 98.4 2,173 31.7 89.7 53.3 2,137 98.9 2,305 28.5 88.1 48.6 2,278 98.2 1,316 33.0 84.3 38.1 1,292 97.8 1,878 34.3 81.3 30.7 1,836 98.8 1,890 33.5 85.7 41.1 1,868 98.1 4,922 30.3 86.4 43.5 4,827 98.9 858 34.9 86.2 50.5 849 98.3 2,929 35.7 89.3 45.8 2,880 98.2 1,357 28.6 85.9 41.7 1,333 98.7 2,169 29.3 85.0 45.4 2,141 98.1 1,126 29.9 82.9 39.3 1,105 98.2 2,806 35.9 89.3 45.6 2,755 98.5 4,471 29.4 84.4 42.7 4,403 97.8 345 26.8 89.4 45.1 338 98.3 7,672 31.6 86.2 43.7 7,544 ____________________________________________________________________________________________ Note: Total includes one woman with missing information on education, 85 missing data on delivery assistance, and 49 missing data on place of 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, midwife, medical assistant, clinical officer, or nursing aide 10.1.2 AGE PATTERN OF BREASTFEEDING The United Nations Children’s Fund (UNICEF, 2000) and the World Health Organisation (WHO, 2000) recommend that children be exclusively breastfed during the first six months of life. During this time, the child should receive no other liquid or food. It is further recommended that children be given solid (semisolid) complementary food beginning with the seventh month of life. The standard timely complementary feeding indicator is the percentage of children age 6-9 months who are breastfeeding and receiving complementary foods. The timing of introduction of complementary foods in addition to breast milk has important health benefits for both the child and mother. Early introduction of foods that are low in energy and nutrients and prepared under unhygienic conditions can result in undernutrition, infection with foreign organisms, and lowered immunity to disease for the baby. It would also cause the mother Infant Feeding and Children’s and Women’s Nutritional Status * 145 Table 10.2 Breastfeeding status by child's age Percent distribution of youngest children under three years living with the mother by breastfeeding status, and percentage of children under three years using a bottle with a nipple, according to age in months, Uganda 2000-2001 __________________________________________________________________________________________________________________ Children under three years _______________ Breastfeeding and consuming: Per- _________________________________________ Number of centage Water- youngest using a Not Plain based Comple- Don’t children bottle Child's age breast- Exclusively water liquids, mentary know/ living with with a in months feeding breastfed only juice Milk foods missing Total mother nipple1 Number __________________________________________________________________________________________________________________ <2 2-3 4-5 6-7 8-9 10-11 12-15 16-19 20-23 24-27 28-31 32-35 <6 6-9 0.8 83.2 1.7 1.4 7.0 5.1 0.8 100.0 196 3.6 207 0.0 68.3 2.9 2.5 18.9 6.0 1.4 100.0 247 4.4 265 1.1 43.5 2.7 7.3 23.0 21.0 1.5 100.0 262 5.5 283 1.1 9.9 0.6 8.0 13.0 64.6 2.8 100.0 238 8.0 253 1.3 3.9 0.4 5.0 4.7 84.2 0.5 100.0 250 3.8 278 4.0 1.7 0.2 2.2 1.3 89.2 1.5 100.0 270 2.8 292 10.7 0.8 0.7 1.7 0.5 85.5 0.2 100.0 464 2.1 524 23.3 0.6 0.0 0.4 0.2 75.0 0.6 100.0 495 1.5 588 50.0 0.1 0.0 0.3 0.0 49.3 0.3 100.0 431 0.4 546 75.4 0.0 0.0 0.0 0.0 24.6 0.0 100.0 331 0.2 561 87.8 0.0 0.0 0.0 0.0 12.2 0.0 100.0 224 0.7 491 91.5 0.0 0.0 0.0 0.0 8.5 0.0 100.0 158 0.2 392 0.6 63.2 2.5 3.9 17.1 11.3 1.3 100.0 705 4.6 755 1.2 6.8 0.5 6.5 8.7 74.6 1.6 100.0 488 5.8 531 _________________________________________________________________________________________________________________ 1 Questions in the 2000-2001 UDHS are not comparable to 1995 UDHS to breastfeed less, thus reducing suckling frequency and the quantity of milk produced. In turn, the introduction of foods may shorten the duration of the mother’s postpartum amenorrhoea, which may result in earlier pregnancy. Table 10.2 shows data on the breastfeeding status of young children from birth up to three years of age. Although two in three children younger than six months of age are exclusively breastfed, the proportion among children 6-9 months is only 9 percent. The percentage of children who no longer receive breast milk starts to rise from 11 percent at age 12-15 months to 50 percent at age 20-23. By age 30 months, nine in ten children have stopped receiving breast milk. In Uganda, infant feeding supplementation starts late, which is consistent with WHO’s recommendation. Only one in four children 2-3 months receive milk other than breast milk or complementary foods. This proportion increases to 83 percent at age 6-9 months. Bottle-feeding can be unhygienic due to the greater likelihood of unhealthy organisms being introduced and is not recommended at any age. However, this practice is becoming more common. Data in Table 10.2 show that 4 percent of infants 2-3 months are given bottles with nipples. This figure increases with the child’s age to 8 percent by the time the child is 6-7 months. Bottles with nipples are most commonly given to children 4-7 months. 1 Includes breast m ilk only, breast milk and water, water-based liquids, and/or juice only (excludes other milk) 146 * Infant Feeding and Children’s and Women’s Nutritional Status 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, Uganda 2000-2001____________________________________________________________________________________________________ Breastfeeding children under six months1 Median duration (months) of breastfeeding _________________________________________________________________________ Percentage Pre- breastfed Mean Mean Any Exclusive dominant 6+ times number number Background breast- breast- breast- All in last of day of night characteristic feeding feeding feeding2 children 24 hours feeds feeds Number____________________________________________________________________________________________________ Sex of child Male Female Residence Urban Rural Region Central Eastern Northern Western Mother's education No education Primary Secondary+ Total Mean for all children 21.8 4.0 4.5 1,809 93.4 7.3 4.7 346 21.5 3.4 4.3 1,758 94.5 7.4 4.7 355 20.8 2.4 3.4 405 92.3 6.8 4.5 77 21.7 3.8 4.5 3,161 94.2 7.5 4.7 624 20.8 4.4 5.2 999 93.9 7.7 4.9 207 20.4 2.5 3.1 1,047 94.9 7.3 4.2 215 23.4 4.6 5.1 631 94.6 7.7 4.5 113 22.2 4.4 5.0 891 92.4 6.9 5.1 166 23.1 3.9 4.7 880 95.0 7.7 4.8 145 21.3 3.7 4.5 2,248 94.6 7.4 4.7 471 20.3 3.2 3.7 438 88.5 6.5 4.2 85 21.6 3.7 4.4 3,566 94.0 7.4 4.7 701 22.6 4.7 5.5 na na na na ____________________________________________________________________________________________________ Note: Median and mean durations are based on current status. na = Not applicable 1Excludes children who do not have a valid answer on the number of times breastfed 2Either exclusively breastfed or received breast milk and plain water, water-based liquids, and/or juice only (excludes other milk) Table 10.3 shows the differentials in duration and frequency of breastfeeding by background characteristics. The overall median duration of any breastfeeding is 21.6 months, the median duration of exclusive breastfeeding is 3.7 months, and the median duration of predominant breastfeeding1 is 4.4 months. Whereas there are small differences in breastfeeding practices by the child’s sex and urban- rural residence, there are variations by region. For example, the median duration of any breastfeeding is 23 months in the Northern Region, compared with 20 months in the Eastern Region. Breastfeeding durations are longer for mothers with no education than for educated women. For mothers to enhance their supply of breast milk and to delay the return of menstruation, frequent breastfeeding must be practiced throughout the day and night. Data presented in Table 10.3 indicate that 94 percent of children under six months of age were breastfed six or more times in the 24 hours preceding the interview. Children are breastfed more frequently during the day than at night (seven and five times, respectively). 10.1.3 TYPES OF COMPLEMENTARY FOODS Infant Feeding and Children’s and Women’s Nutritional Status * 147 Table 10.4 Foods consumed by children in the day or night preceding the interview Percentage of youngest children under three years of age living with the mother who consumed specific foods in the day or night preceding the interview, by breastfeeding status and child's age, Uganda 2000-2001_____________________________________________________________________________________________________________________ Other Grains/ Fruit Meat/ Oils/ Foods milk/ bread/ and Tubers/ Beans/ fish/ fats/ rich in Child's age Infant cheese/ Other cereal/ vege- roots/ legumes/ poultry/ Any solid butter/ vitamin in months formula yogurt liquids1 porridge tables plantains lentils eggs food margarine A2 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 <6 6-9 Total 0.0 9.1 2.4 2.5 1.2 0.5 1.1 0.0 3.7 0.5 0.6 195 2.0 20.0 5.7 5.2 0.3 0.3 0.5 0.0 5.2 0.2 0.0 247 2.0 29.4 20.4 14.2 9.2 4.8 7.2 2.6 20.4 2.2 8.5 259 2.3 28.7 48.6 45.3 40.0 17.2 27.4 20.9 65.3 16.7 33.5 236 0.3 33.7 59.2 69.5 55.7 33.5 47.6 24.3 85.3 32.3 42.5 246 1.3 34.1 60.3 75.7 64.0 39.7 63.0 35.4 92.9 32.7 54.4 259 2.8 37.8 67.0 73.8 70.8 37.7 72.6 31.5 96.1 40.0 54.7 224 1.4 34.9 57.2 72.5 75.0 42.2 58.5 34.7 95.2 36.3 69.4 191 1.8 36.5 61.9 74.1 74.0 30.5 69.2 23.2 96.4 44.7 62.9 216 0.4 32.1 61.0 74.6 76.9 35.3 68.2 34.6 98.6 36.5 67.8 379 1.4 18.3 54.4 79.3 77.2 39.7 74.0 30.4 100.0 21.4 70.5 99 0.0 34.6 48.1 81.5 69.7 49.4 67.0 22.4 100.0 23.3 53.7 24 1.5 20.4 10.2 7.8 3.8 2.0 3.2 1.0 12.5 1.0 3.3 701 1.3 31.3 54.0 57.7 48.1 25.6 37.7 22.6 75.5 24.6 38.1 482 1.4 29.5 45.7 53.3 49.3 25.5 44.2 21.8 69.1 24.5 41.9 2,574 ______________________________________________________________________________________________________________________ NONBREASTFEEDING CHILDREN _____________________________________________________________________________________________________________________ 12-13 14-15 16-17 18-23 24-29 30-35 Total (7.7) (70.0) (70.1) (86.5) (62.8) (42.9) (53.8) (42.6) (100.0) (47.4) (51.0) 26 (0.0) (55.4) (60.0) (59.1) (77.4) (39.9) (68.0) (24.6) (95.1) (59.3) (72.6) 24 9.0 56.7 75.1 68.6 80.0 36.6 64.3 37.4 95.9 40.3 66.9 53 3.2 40.1 69.4 73.8 82.2 38.3 64.4 37.3 97.3 48.3 66.4 278 1.4 38.0 69.1 70.7 74.9 37.9 74.0 34.5 97.1 49.4 67.4 361 1.2 35.2 72.7 76.7 80.6 38.3 70.2 35.7 98.6 36.1 70.9 230 2.6 40.6 69.7 72.7 77.7 38.5 68.6 35.6 97.1 45.2 67.1 992 _______________________________________________________________________________________________________________________ Note: Breastfeeding status and food consumed refer to a “24-hour” period (yesterday and last night). Figures in parentheses are based on 25-49 unweighted cases. 1 Does not include plain water As mentioned above, the recommended age for introducing foods other than breast milk is 6-9 months. UDHS data show that three-quarters of breastfeeding children age 6-9 months receive solid foods (Table 10.4). Overall, 58 percent of these children receive cereal-type foods; 48 percent receive fruits and vegetables; 38 percent receive legumes; and 23 percent are given meat, poultry, fish, or eggs. Data in Table 10.4 also show that 42 percent of all breastfeeding children under three received foods rich in vitamin A, which include pumpkin, red or yellow yams or squash, carrots, red sweet potatoes, green leafy vegetables, mangoes, papayas, other locally grown fruits and vegetables, and meats. The level of vitamin A consumption may be slightly overestimated because the “meats” category in the questionnaire includes both “meat”, which is rich in vitamin A, and “poultry, fish, shellfish, or eggs,” which are not rich in vitamin A. It is not possible to separate meat from the other foods at the analysis stage. 2 Other liquids include sugar water, tea, coffee, soda, and soup broth. 148 * Infant Feeding and Children’s and Women’s Nutritional Status Table 10.5 Frequency of foods received by children in the day or night preceding the interview Mean number of times specific foods were consumed in the 24 hours preceding the interview by the youngest child under three years of age living with the mother, by breastfeeding status and age, Uganda 2000-2001______________________________________________________________________________________________________________ Other Grains/ Fruit Meat/ Oils/ Foods milk/ bread/ and Tubers/ Beans/ fish/ fats/ rich in Child's age Infant cheese/ Other cereal/ vege- roots/ legumes/ poultry/ butter/ vitamin in months formula yogurt liquids1 porridge tables plantains lentils eggs margarine A2 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 <6 6-9 Total 0.0 0.2 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 195 0.1 0.6 0.1 0.1 0.0 0.0 0.0 0.0 0.0 0.0 247 0.1 0.8 0.4 0.3 0.2 0.1 0.1 0.0 0.0 0.1 259 0.1 0.9 1.0 0.8 0.7 0.3 0.4 0.3 0.2 0.5 236 0.0 1.0 1.3 1.2 1.2 0.5 0.7 0.3 0.5 0.7 246 0.0 0.9 1.3 1.4 1.5 0.5 1.0 0.5 0.5 1.1 259 0.1 1.0 1.9 1.3 1.6 0.5 1.1 0.4 0.6 1.1 224 0.0 1.1 1.3 1.3 1.9 0.5 0.9 0.4 0.6 1.5 191 0.0 1.0 1.6 1.4 1.7 0.5 1.1 0.3 0.7 1.3 216 0.0 0.8 1.3 1.3 1.9 0.5 1.0 0.5 0.5 1.4 379 0.1 0.5 1.3 1.5 1.8 0.6 1.2 0.4 0.4 1.5 99 (0.0 ) (0.8) (1.1) (1.6) (1.8) (0.7) (1.0 ) (0.3) (0.4) (1.3) 24 0.0 0.6 0.2 0.2 0.1 0.0 0.9 0.0 0.0 0.1 701 0.0 0.9 1.1 1.0 1.0 0.4 0.6 0.3 0.4 0.6 482 0.0 0.8 1.0 1.0 1.1 0.4 0.7 0.3 0.4 0.8 2,574 ______________________________________________________________________________________________________________ NONBREASTFEEDING CHILDREN ______________________________________________________________________________________________________________ 12-13 14-15 16-17 18-23 24-29 30-35 Total (0.2) (2.1) (1.4) (1.3) (1.3) (0.7) (0.8) (0.5) (0.8) (1.0) 26 (0.0) (2.0) (1.9) (1.0) (1.8) (0.7) (1.1) (0.3) (0.9) (1.1) 24 0.2 1.6 1.8 1.3 2.0 0.5 1.1 0.5 0.7 1.3 53 0.1 1.2 1.8 1.4 2.2 0.6 1.0 0.5 0.8 1.4 278 0.0 0.9 1.5 1.3 2.2 0.6 1.1 0.5 0.8 1.6 361 0.0 0.9 1.8 1.4 2.1 0.5 1.1 0.5 0.5 1.4 230 0.1 1.1 1.7 1.3 2.1 0.6 1.1 0.5 0.7 1.4 992 ______________________________________________________________________________________________________________ Note: Breastfeeding status and food consumed refer to a “24-hour” period (yesterday and last night). Figures in parentheses are based on 25-49 unweighted cases. 1 Includes sugar water, tea, coffee, soda, and soup broth 10.1.4 FREQUENCY OF FOODS CONSUM ED BY CHILDREN Table 10.5 shows the number of times various foods were consumed in the 24 hours prior to the interview by the youngest children under three years old living with the mother. Breastfeeding children received other liquids,2 cereal-type foods, and fruits and vegetables on average once in the 24-hour period. The frequency of foods consumed generally increases with the child’s age. Whereas Table 10.5 refers to the 24-hour period preceding the survey, Table 10.6 shows the frequency of foods consumed in the seven days prior to the interview. Data in Table 10.5 show that overall, breastfeeding children received other liquids, grains, legumes, and foods rich in vitamin A about three times in the past week, less than once a day. As expected, older children are more likely to receive more varied food. Infant Feeding and Children’s and Women’s Nutritional Status * 149 Table 10.6 Frequency of foods received by children in preceding seven days Mean number of times specific foods were received in the seven days preceding the interview by the youngest child under three years of age living with the mother, by breastfeeding status and age, Uganda 2000-2001_____________________________________________________________________________________________________________ Other Grains/ Fruit Meat/ Oils/ Foods milk/ bread/ and Tubers/ Beans/ fish/ fats/ rich in Child's age Infant cheese/ Other cereal/ vege- roots/ legumes/ poultry/ butter/ vitamin in months formula yogurt liquids1 porridge tables plantains lentils eggs margarine A2 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 0.0 0.7 0.2 0.1 0.1 0.0 0.1 0.0 0.0 0.1 195 0.1 1.4 0.4 0.4 0.0 0.0 0.0 0.0 0.0 0.0 247 0.2 2.2 1.6 1.0 0.7 0.3 0.4 0.1 0.2 0.6 259 0.1 2.4 3.6 3.1 3.1 1.0 1.7 1.0 1.2 2.1 236 0.0 2.7 4.7 4.4 5.3 1.7 3.0 1.4 1.8 3.6 246 0.1 2.5 4.6 4.8 6.3 2.3 3.9 1.5 1.8 4.6 259 0.2 2.5 5.4 4.7 6.5 2.3 3.8 1.5 2.4 4.7 224 0.1 2.8 4.5 4.9 8.0 2.2 3.7 1.8 2.2 5.8 191 0.1 2.5 5.1 5.0 7.9 2.1 4.1 1.5 2.9 5.6 216 0.0 2.4 4.7 4.7 8.2 2.2 4.2 1.8 2.1 6.0 379 0.1 1.6 4.3 4.9 7.6 2.4 4.6 1.6 1.4 6.1 99 (0.0) (2.7) (3.7) (4.5) (6.8) (2.8) (4.3) (1.7) (1.8) (5.1) 24 0.1 1.1 0.3 0.3 0.1 0.0 0.1 0.0 0.0 0.0 442 0.2 2.2 1.6 1.0 0.7 0.3 0.4 0.1 0.2 0.6 259 0.1 2.6 4.1 3.8 4.2 1.4 2.4 1.2 1.5 2.9 482 0.1 2.2 3.6 3.4 4.9 1.5 2.7 1.1 1.5 3.5 2,574 ______________________________________________________________________________________________________________ NONBREASTFEEDING CHILDREN _____________________________________________________________________________________________________________ 12-13 14-15 16-17 18-23 24-29 30-35 Total (0.5) (4.9) (5.3) (5.0) (8.3) (2.7) (4.0) (2.9) (3.3) (6.1) 26 (0.0) (4.1) (5.0) (3.9) (7.9) (2.7) (4.1) (1.4) (2.3) (5.2) 24 0.4 3.9 5.9 4.3 8.9 2.3 4.0 1.9 2.6 6.0 53 0.2 3.3 6.0 5.0 9.1 2.3 4.0 2.0 2.8 6.0 278 0.1 2.8 5.5 4.6 8.9 2.3 4.5 1.8 2.7 6.5 361 0.0 2.7 6.0 5.2 9.1 2.4 4.4 1.9 2.2 6.5 230 0.1 3.1 5.7 4.8 8.9 2.4 4.2 1.9 2.6 6.2 992 ______________________________________________________________________________________________________________ Note: Breastfeeding status and food consumed refer to a “24-hour” period (yesterday and last night). Figures in parentheses are based on 25-49 unweighted cases. 1 Does not include plain water 2 Includes pumpkin, red or yellow yams or squash, carrots, red sweet potatoes, grean leafy vegetables, mangoes, As seen in Table 10.6, nonbreastfeeding children received a greater variety of foods than breastfeeding children. They were also more likely to have been given fruits and vegetables (nine times) and foods rich in vitamin A (six times). However, the differences between breastfeeding and nonbreastfeeding children are less significant when the same age groups are compared. 10.2 MICRONUTRIENTS Micronutrient deficiencies are of concern in Uganda. Vitamin A is essential for normal vision and enhancement of immunity, while iodine is necessary for adequate mental development and prevention of goitre. Minerals can be obtained by consuming a varied diet and more specifically by including foods that are rich in these micronutrients in the diet. 10.2.1 MICRONUTRIENT STATUS OF YOUNG CHILDREN Lack of a sufficient amount of iodine in the diet can lead to major nutritional deficiencies such as goitre, nutritional stunting, mental retardation, and cretinism. Many foods, particularly in 3 The test involved putting a small amount of salt on a piece of paper, putting a drop of a special solution on the salt, and recording the intensity of the blue colour that appeared. The test kits were supplied by UNICEF/Uganda. 150 * Infant Feeding and Children’s and Women’s Nutritional Status Table 10.7 Iodisation of household salt Percent distribution of households with salt tested for iodine content by level of iodine in salt (parts per million), percentage of households tested, and percentage of households not tested (no salt), according to background characteristics, Uganda 2000-2001_________________________________________________________________________________________________ Iodine content Percentage among households tested Percentage of house-______________________________ of house- holds not Number Background None Inadequate Adequate holds tested of characteristic (0 ppm) (<15 ppm) (15+ ppm) Total tested (no salt) households_________________________________________________________________________________________________ Residence Urban Rural Region Central Eastern Northern Western Total 0.1 1.1 98.8 100.0 91.6 8.4 1,174 1.7 4.3 94.1 100.0 89.0 11.0 6,711 0.1 2.8 97.1 100.0 92.3 7.7 2,603 0.0 1.1 98.9 100.0 92.7 7.3 2,106 0.1 4.1 95.8 100.0 90.7 9.3 1,191 6.2 8.2 85.6 100.0 81.1 19.1 1,985 1.5 3.8 94.8 100.0 89.4 10.6 7,885 the mountainous and flood-prone districts, lack natural iodine such that the population has started showing the effects of iodine deficiency and an increased prevalence of goitre. The government therefore initiated a campaign in December 1994 to introduce iodine in salt in order to overcome this deficiency and set a goal of reaching 90 percent coverage by the year 2000. To evaluate this programme, UDHS interviewers tested salt from each household for its iodine content.3 The test indicated that 95 percent of households for which the salt test was performed use adequately iodised salt (15 parts per million [ppm] or higher), while 4 percent have inadequately iodised salt (less than 15 ppm), and 2 percent use salt that is not iodised (see Table 10.7). The percentage of households that used iodised salt in 2000-2001 was higher than that recorded in 1995 (68 percent), although the figure for 1995 is underestimated since it refers to iodine levels of 25 parts per million or higher. Urban households are slightly more likely than rural households to use salt with adequate iodine content. Among the regions, although 96 to 98 percent of households in other regions have adequate iodine in salt, only 86 percent of households in the Western Region meet this requirement. The consumption of foods rich in micronutrients and supplements in the seven days preceding the survey by children under three years is shown in Table 10.8. Overall, 58 percent of these children received foods rich in vitamin A. Consumption of foods rich in vitamin A varies little across subgroups of children except by the child’s age, breastfeeding status, and region of residence. As expected, younger and breastfeeding children are less likely than older children to receive foods rich in vitamin A (3 percent for children under six months compared with 56 percent for children 6-11 months). Children in the Western Region are the least likely to receive foods rich in vitamin A, while children in the Eastern Region are the most likely to consume these foods (67 percent). Infant Feeding and Children’s and Women’s Nutritional Status * 151 Table 10.8 Micronutrient intake among children Percentage of youngest living children under age three living with the mother who consumed foods rich in vitamin A in the seven days preceding the survey, percentage of children 6-59 months who received vitamin A supplements in the six months preceding the survey, and percentage of children under five living in households using adequately iodised salt, by background characteristics, Uganda 2000____________________________________________________________________________________________ Consumed foods Received vitamin A Lives in household using rich in vitamin A1 supplements adequately iodised salt2 ___________________ ___________________ _____________________ Background characteristic Percent Number Percent Number Percent Number____________________________________________________________________________________________ Child's age in months <6 6-9 10-11 12-23 24-35 36-47 48-59 Sex Male Female Birth order 1 2-3 4-5 6+ Breastfeeding status Breastfeeding Not breastfeeding Missing Residence Urban Rural Region Central Eastern Northern Western Mother's education No education Primary Secondary+ Mother's age at birth <20 20-24 25-29 30-34 35-49 Total 3.3 705 na 0 94.0 665 47.9 488 22.3 497 96.6 462 70.7 270 38.4 272 95.4 243 75.7 1,390 41.0 1,504 95.7 1,390 77.1 713 42.1 1,256 93.8 1,156 na 0 36.7 1,334 95.1 1,234 na 0 35.9 1,232 96.8 1,130 56.9 1,809 37.5 3,018 95.4 3,110 58.0 1,758 37.7 3,078 95.2 3,169 51.3 572 37.5 1,064 95.8 1,115 59.4 1,127 39.9 2,025 96.2 2,065 56.3 856 37.1 1,387 94.8 1,445 59.8 1,011 35.2 1,620 94.3 1,654 50.0 2,574 36.5 1,892 95.2 2,395 76.8 986 38.2 4,162 95.3 3,842 71.7 6 23.5 42 100.0 42 57.6 405 42.9 687 99.0 730 57.5 3,161 36.9 5,409 94.8 5,549 58.5 999 34.1 1,746 97.9 1,883 67.0 1,047 37.4 1,854 98.3 1,974 52.8 631 43.5 1,017 95.7 1,025 48.4 891 38.0 1,479 87.3 1,397 56.5 880 31.1 1,501 94.1 1,507 57.2 2,248 38.2 3,876 95.1 4,012 61.0 438 48.0 717 98.5 760 56.7 608 37.3 1,215 95.8 1,239 58.4 1,078 39.5 1,889 95.7 1,948 56.6 884 37.4 1,423 95.7 1,472 57.6 519 36.2 860 93.6 894 57.8 478 35.0 709 94.6 726 57.5 3,566 37.6 6,096 95.3 6,279 ____________________________________________________________________________________________ Note: Total includes one woman with missing information on education na = Not applicable 1 Includes pumpkin, red or yellow yams or squash, carrots, red sweet potatoes, green leafy vegetables, mango, papaya, and other locally grown fruits and vegetables that are rich in vitamin A 2 Salt containing 15 ppm of iodine or more. Excludes children in households in which salt was not tested Thirty-five percent of children under age five received vitamin A supplements in the six months preceding the survey. This proportion varies little across subgroups of children. However, vitamin A supplementation increases with mother’s education. Children whose mother has secondary education are more likely to receive vitamin A supplements than other children (46 percent compared with 29 percent of children whose mother has no education). 152 * Infant Feeding and Children’s and Women’s Nutritional Status Table 10.9 Micronutrient intake among mothers Percentage of women who gave birth in the five years preceding the survey who received a vitamin A dose in the first two months after delivery, percentage who suffered from night blindness during pregnancy, percentage who live in households using adequately iodised salt, and percent distribution who took iron tablets or syrup for specific numbers of days, by background characteristics, Uganda 2000-2001 __________________________________________________________________________________________________________________ Living in households Number of days woman took iron during pregnancy using _______________________________________________ Received Night Night adequately Don't Background vitamin A blindness blindness iodised know/ characteristic postpartum1 reported adjusted2 salt3 None <60 60-89 90+ missing Total Number _____________________________________________________________________________________________________________________ Mother's age at birth <20 12.0 9.0 1.3 95.7 42.0 49.9 1.8 2.1 4.2 100.0 746 20-24 12.8 5.8 0.8 95.8 46.4 47.0 0.7 2.1 3.8 100.0 1,311 25-29 10.9 7.4 0.9 95.7 51.8 42.8 0.9 1.2 3.3 100.0 1,089 30-34 9.4 12.2 1.5 93.7 48.3 44.5 1.8 1.3 4.1 100.0 659 35-49 10.4 10.4 0.9 94.5 52.5 39.3 0.9 1.5 5.8 100.0 685 Number of children ever born 1 14.8 6.9 1.1 95.6 39.5 53.3 1.8 2.5 3.0 100.0 717 2-3 12.3 6.4 0.8 95.9 47.0 46.2 1.3 1.7 3.7 100.0 1,380 4-5 9.8 8.3 1.2 96.2 51.5 42.7 0.6 1.5 3.6 100.0 1,057 6+ 9.7 11.0 1.1 93.8 51.4 40.8 1.1 1.3 5.4 100/0 1,335 Residence Urban 22.7 3.0 0.6 99.0 35.6 54.3 2.4 3.1 4.6 100.0 560 Rural 9.7 9.1 1.1 94.9 50.0 43.6 1.0 1.5 4.0 100.0 3,930 Region Central 14.9 4.1 1.0 97.8 35.2 54.3 2.4 3.7 4.6 100.0 1,323 Eastern 14.9 9.4 0.7 98.4 46.4 48.5 0.4 1.1 3.6 100.0 1,273 Northern 9.7 15.4 1.5 95.9 43.7 49.5 1.6 1.3 3.9 100.0 775 Western 4.2 7.3 1.2 87.4 68.7 26.7 0.2 0.2 4.2 100.0 1,119 Education No education 6.7 11.7 1.1 93.8 58.3 36.9 0.5 0.6 3.7 100.0 1,103 Primary 10.0 7.7 1.0 95.3 47.2 46.0 1.0 1.4 4.3 100.0 2,791 Secondary + 26.0 5.1 1.2 98.6 33.7 54.7 3.0 4.7 3.9 100.0 594 Total 11.3 8.3 1.0 95.3 48.2 44.9 1.1 1.7 4.1 100.0 4,489 ______________________________________________________________________________________________________________________ Note: For women with two or more live births in the five-year period, data refer to the most recent birth. Total includes one woman with missing information on education 1 In the first two months after delivery 2 Women who reported night blindness but did not report difficulty with vision during the day 3 Salt containing 15 ppm of iodine or more. Excludes women in housholds in which salt was not tested Table 10.9 shows the micronutrient intake of mothers. Only 11 percent of mothers in Uganda receive vitamin A supplementation postpartum. There are variations in this percentage across subgroups of the population. It is higher for lower parity women, urban mothers, and those living in the Central and Eastern regions and is lowest (4 percent) in the Western Region. Infant Feeding and Children’s and Women’s Nutritional Status * 153 Night blindness is an indicator of severe vitamin A deficiency, to which pregnant women are especially prone. In the UDHS, women who had a birth in the five years preceding the survey were asked whether they suffered from night blindness during pregnancy. In general, 7 percent of mothers reported having this problem. Women in their twenties are the least likely to report this problem. Women in rural areas are much more likely than urban women to report night blindness during pregnancy. Whereas 15 percent of women in the Northern Region reported this problem, the corresponding percentage in the Central Region is only 4 percent. Half of women who had a birth in the five years preceding the survey took iron supplements during their most recent pregnancy. Most of these women took iron tablets or syrup for less than 60 days. The likelihood of pregnant women taking iron supplements during pregnancy decreases with age and number of children, and increases with level of education. Women in urban areas and in the Central region are more likely than other women to take iron supplements during pregnancy. 10.3 NUTRITIONAL STATUS OF CHILDREN The nutritional status of children is an outcome of many interrelated factors, including environment, economics, politics, education, culture, and food security. Among these factors, the ones that have the most immediate and direct effect on nutritional status are feeding practices and infections. The nutritional status of children can thus be used as an indicator of the socioeconomic development of a community. 10.3.1 MEASURES OF NUTRITIONAL STATUS In the 2000-2001 UDHS, the nutritional status of children is analysed and evaluated in comparison with the commonly used U.S. National Center for Health Statistics (NCHS) standard, which is recommended by the World Health Organisation. The use of this reference population is based on the finding that well-nourished young children of all population groups follow similar growth patterns. Although there are variations in height and weight, their distribution by the child’s age approximate a normal distribution when the population under study is large. In the 2000-2001 UDHS, all women 15-49 and children born since January 1995 were weighed using a digital scale with a precision of 100 grams. Their height was measured using a board manufactured by Shorr Productions. Children 24 months and older were measured standing, and children under age 24 months were measured lying down (recumbent length). Height and weight data, as well as information on the child’s age in months, were used to construct the three standard indices of physical growth that describe the nutritional status of children: height-for-age, weight-for-height, and weight-for-age. Each of these indices provides somewhat different information about the nutritional status of a population of children. Height-for-age is a measure of linear growth. Children who are more than two standard deviations below (-2 SD) the median of the NCHS reference population are considered short for their age or “stunted”, and those who are below three standard deviations (-3 SD) from the median of the reference population are considered severely stunted. Stunting is a condition that reflects failure to receive adequate food intake over a long period and is also affected by repeated episodes of illness. Height-for-age thus represents a measure of the long-term effects of undernutrition in a population and does not vary appreciably according to recent diet. Hence, it is not affected by the season in which data collection took place. 154 * Infant Feeding and Children’s and Women’s Nutritional Status The weight-for-height index describes current nutritional status. Children who are below -2 SD from the median of the reference population are considered “wasted” or too thin for their height, and children whose weight-for-height is below -3 SD of the reference median are considered severely wasted. Wasting represents the failure to receive adequate nutrition in the period immediately preceding the survey and may be the result of recent episodes of illness. Severe wasting is closely linked to mortality risk and may reflect acute shortage of food. Weight-for-age is an index that combines the information of both weight-for-height and height-for-age. Children whose weight-for-age is below -2 SD from the median of the reference population are classified as “underweight”, and those below -3 SD are classified as severely underweight. However, a child can be underweight for his age because he is stunted, wasted, or both. In a population in which children are healthy and well nourished, approximately 2 percent of children are expected to fall below -2 SD for each of the three indices. 10.3.2 LEVELS OF CHILDHOOD MALNUTRITION Table 10.10 and Figure 10.1 show the percentage of children under five years classified as malnourished according to height-for-age, weight-for-height, and weight-for-age by selected demographic characteristics. The proportion of all children who are stunted is 39 percent, and 15 percent are severely stunted. The prevalence of stunting is low among children under six months and increases with age. The highest prevalence (51 percent) is among children age 16-23 months. Male children are slightly more likely to be stunted than female children (40 percent compared with 36 percent). However, birth order shows little variation. Stunting is more prevalent among children in the rural areas, and in the Western Region, and children of mothers who have had no education. Children who were born less than 24 months after the previous sibling are more likely to be stunted than those with a longer birth interval (43 percent compared with 38 percent or lower). The presence of the mother in the same household as the child makes a slight difference in the child’s nutritional status. Among children of non-interviewed mothers, 41 percent of those who live in the same household with their mother are stunted, compared with 44 percent of those who do not live in the same household with their mother. This compares with 39 percent among children of interviewed mothers. Wasting affects 4 percent of children, with less than 1 percent severely wasted. The prevalence of wasting does not vary much across subgroups of children. However, wasting is much more prevalent among children 10-11 months (11 percent), corresponding with the period when complementary foods are introduced. Underweight, which reflects either stunting, wasting, or a combination of the two, affects 23 percent of children under five. The data also reflect the trend described in the 1995 UDHS, where the prevalence of underweight rises rapidly from 3 percent among children age six months to 38 percent at 10-11 months, then decreases as the children grow older. Male children, children born less than 24 months after a previous birth, children living in the rural areas, and children of uneducated women are more likely to be underweight. The prevalence of underweight increases with birth order: 19 percent among first births, increasing gradually to reach 26 percent for sixth or higher order children. Children in the Northern and Western regions are more likely to be underweight than children in the Central and Eastern regions. Infant Feeding and Children’s and Women’s Nutritional Status * 155 Table 10.10 Nutritional status of children Percentage of children under five years with interviewed mothers classified as malnourished according to three anthropometric indices of nutritional status (height-for-age, weight-for-height, and weight-for-age) by selected demographic characteristics, and percentage of children with noninterviewed mothers and all children classified as malnourished, Uganda 2000-2001___________________________________________________________________________________________________ Height-for-age Weight-for-height Weight-for-age (stunting) (wasting) (underweight)_________________________ ________________________ ________________________ 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_______________________________________________________________________________________________________________ Age in months <6 6-9 10-11 12-15 16-23 24-35 36-47 48-59 Sex Male Female Birth order 1 2-3 4-5 6+ Birth interval in months First birth2 <24 months 24-47 months 48+ months Residence Urban Rural Region Central Eastern Northern Western Mother's education No education Primary Secondary+ Children of interviewed mothers Children of non- interviewed mothers Mother living in household Mother not living in household3 Total 2.1 7.9 -0.5 0.5 2.5 0.5 0.6 2.8 0.0 538 4.4 22.9 -1.1 0.6 5.2 -0.2 4.2 22.0 -1.1 436 10.4 33.9 -1.4 1.7 10.7 -0.5 8.3 38.1 -1.5 240 14.6 35.9 -1.6 1.3 6.8 -0.5 6.6 33.2 -1.5 419 21.0 51.1 -2.0 0.5 7.4 -0.5 8.0 31.6 -1.5 909 17.1 41.6 -1.7 0.6 2.9 -0.2 6.2 24.7 -1.2 1,043 15.7 44.0 -1.8 0.1 1.7 -0.0 3.9 18.2 -1.1 1,078 18.5 44.2 -1.8 0.8 2.2 -0.0 2.8 19.3 -1.1 941 15.8 40.4 -1.6 0.6 5.0 -0.2 5.5 23.7 -1.2 2,783 13.8 36.9 -1.6 0.6 3.1 -0.1 4.3 21.4 -1.1 2,821 14.5 38.0 -1.6 0.6 3.2 -0.0 3.7 18.7 -1.0 890 13.7 38.2 -1.6 0.6 3.4 -0.2 4.0 21.6 -1.1 1,832 16.1 39.6 -1.6 0.7 4.0 -0.1 4.4 22.9 -1.1 1,327 15.2 38.6 -1.6 0.6 5.3 -0.2 7.0 25.5 -1.2 1,554 14.5 38.0 -1.6 0.6 3.2 -0.0 3.7 18.6 -1.1 895 17.9 42.6 -1.8 0.7 3.6 -0.1 6.0 25.3 -1.2 1,225 14.5 38.4 -1.6 0.6 4.3 -0.2 4.9 23.3 -1.2 2,867 10.5 32.3 -1.4 0.7 4.9 -0.1 4.4 19.2 -1.0 616 7.1 26.5 -1.1 0.5 2.9 -0.0 1.8 12.4 -0.7 536 15.6 39.9 -1.7 0.6 4.2 -0.2 5.2 23.6 -1.2 5,068 12.6 34.6 -1.5 0.4 3.6 -0.1 4.4 19.9 -1.0 1,485 12.0 35.4 -1.5 0.5 4.3 -0.3 4.1 22.5 -1.1 1,724 14.6 36.9 -1.6 0.6 3.8 -0.3 6.5 25.0 -1.2 969 20.7 47.8 -1.9 0.9 4.3 0.0 5.2 23.7 -1.2 1,426 18.5 45.5 -1.8 0.7 5.1 -0.2 7.7 28.6 -1.3 1,370 14.3 37.7 -1.6 0.7 3.9 -0.1 4.3 21.5 -1.1 3,608 9.7 28.9 -1.2 0.0 2.8 -0.1 2.3 15.2 -0.8 626 14.8 38.6 -1.6 0.6 4.0 -0.1 4.9 22.5 -1.1 5,604 15.4 40.9 -1.6 0.8 4.2 -0.4 7.0 24.6 -1.3 238 20.5 43.6 -1.7 2.0 4.0 -0.2 6.1 25.0 -1.2 361 15.3 39.1 -1.6 0.7 4.1 -0.2 5.1 22.8 -1.1 6,145 ______________________________________________________________________________________________________________ Note: Table is based on children whose mothers were interviewed (except for last three rows). Each of the indices is expressed in standard deviation units (SD) from the median of the NCHS/CDC/WHO International Reference Population. The percentage of children who are more than three or more than two standard deviations below the median of the International Reference Population (-3 SD and -2 SD) are shown according to background characteristics. Table is based on children with valid dates of birth (month and year) and valid measurement of both height and weight. 1 Includes children who are below -3 standard deviations (SD) from the median of the International Reference Population 2 First-born twins (triplets, etc.) are counted as first births because they do not have a previous birth interval 3 Includes children whose mother is deceased. 4 In 1995, only women who had given birth in the four years before the survey were measured, whereas in 2000-2001, all women 15-49 were eligible for measurem ents. 156 * Infant Feeding and Children’s and Women’s Nutritional Status 10.3.3 NUTRITIONAL STATUS OF WOMEN A woman’s nutritional status has important implications for her health status as well as that of her children. A woman who has poor nutritional status has a greater risk of having complications during pregnancy and childbirth as well as of giving birth to underweight babies. The height of a woman is also a risk factor for delivery complications, since small stature is often associated with small pelvis size. Women’s height and weight measurements are used to derive the body mass index (BMI), which is used to assess thinness or obesity. Table 10.11 shows that the mean height of all women measured in the survey is 158 centimetres, which is similar to that obtained in the 1995 UDHS.4 A woman is considered short in stature if she is less than 145 centimetres tall. In the 2000-2001 UDHS, 2 percent of women fall into this category. This percentage does not vary much by urban-rural residence; however, there are differentials according to the woman’s age, region of residence, education, and wealth status. Women in the youngest and oldest age groups are more likely than other women to be short. Short stature is negatively related to the woman’s education. Whereas 3 percent of women with no education are considered short, the corresponding proportion of women with some secondary education is only 1 percent. Women in the Western Region are more likely than women in other regions to be shorter than 145 centimetres. Wealth status may have some effect on a woman’s height: women in the two highest quintiles are the least likely to be shorter than 145 centimetres. Infant Feeding and Children’s and Women’s Nutritional Status * 157 Table 10.11 Nutritional status of women Among women age 15-49, mean height and percentage under 145 cm, mean body mass index (BMI), percentage of women whose BMI (kg/m2) is below 18.5 and above 25.0, by background characteristics, Uganda 2000-2001________________________________________________________________________________________________ Height Body mass index (BMI) ____________________________ ________________________________ Mean Percentage Background height below Mean Percentage Percentage characteristic in cm 145 cm Number BMI <18.5 $25.0 Number1 ________________________________________________________________________________________________ Age 15-19 20-24 25-29 30-34 35-39 40-44 45-49 Residence Urban Rural Region Central Eastern Northern Western Education No education Primary Secondary+ Wealth index quintile Lowest Lower middle Middle Upper middle Highest Total 156.3 3.8 1,444 21.4 12.9 9.7 1,274 157.8 1.8 1,392 21.9 7.0 12.1 1,053 158.4 2.3 1,245 22.0 8.0 13.6 980 159.3 0.7 921 22.2 10.7 17.5 756 158.9 0.7 746 22.0 13.3 16.0 652 159.3 1.6 531 22.3 10.5 15.8 502 158.4 4.9 388 22.2 11.4 18.2 383 158.0 2.0 1,021 23.6 4.7 30.2 914 158.1 2.2 5,647 21.6 11.5 10.6 4,687 156.7 2.3 2,029 22.8 5.8 21.5 1,768 159.3 1.5 1,833 21.2 13.9 9.0 1,480 160.7 0.5 1,102 20.7 17.7 5.1 936 156.7 4.0 1,704 22.3 7.5 14.8 1,416 158.3 2.9 1,489 21.4 12.4 8.8 1,247 157.7 2.3 3,996 21.7 11.1 12.0 3,298 159.0 0.9 1,182 23.2 5.7 25.0 1,055 157.9 2.3 1,304 21.0 15.4 7.4 1,068 158.5 2.9 1,301 21.1 14.6 6.4 1,050 157.6 2.9 1,274 21.5 9.2 7.9 1,060 158.0 1.4 1,302 22.1 9.1 14.7 1,109 158.3 1.6 1,488 23.5 4.9 28.8 1,314 158.1 2.2 6,668 21.9 10.4 13.8 5,601 _________________________________________________________________________________________________ 1Includes one woman with missing information on education. BMI is derived by dividing the weight in kilograms by the square of the height in metres (kg/m2). A cutoff point of 18.5 has been recommended for defining chronic undernutrition, while a level above 25 is considered overweight. Data in Table 10.10 show that the mean BMI of the women is 21.9, which falls in the normal category. Ten percent of women have a BMI below the 18.5 cutoff, which means they can be regarded as having a chronic nutritional deficit. This is the same as the level obtained in 1995. Fourteen percent of women in Uganda are overweight. BMI varies across subgroups of women. Women in the rural areas, in the Eastern and Northern regions, less educated women, and women in the two lowest wealth index quintiles are more likely to have a BMI below 18.5. On the other hand, urban women and women in the Central and Western regions are more likely than other women to be overweight. Better educated women and women in higher quintiles are also more likely to be overweight. 158 * Infant Feeding and Children’s and Women’s Nutritional Status 10.4 PREVALENCE OF ANAEMIA The level of haemoglobin concentration in the blood is used as an indicator to estimate the prevalence of anaemia in a population. Anaemia prevalence is used as an indicator of iron deficiency, which is a function of the bioavailability of iron in the average diet. Requirements for iron determine which members of the population are affected. In this regard, infants and young children are at special risk because of increased need related to growth. The effects of iron deficiency and anaemia in young children manifest later as impaired cognitive development that leads to reduced mental capacity and lower school retention, attendance, and enrolment. Women’s need for iron is higher than that of men because of the increased need during menstruation, pregnancy, and lactation. Iron deficiency often contributes to reproductive wastage and death. In the 2000-2001 UDHS, haemoglobin levels of women age 15-49, men 15-54, and children 6-59 months were measured using the HemoCue method. Retractable disposable cuvettes were used to puncture the fingertip or heel in order to draw and hold blood. The cuvette was inserted in the HemoCue machine, which consists of a battery-operated photometer. The haemogloblin level in the blood was analysed, and the result was displayed in a digital register. Levels of anaemia can be classified as severe, moderate, and mild based on the haemoglobin concentration in the blood and according to criteria developed by the World Health Organisation. Severe anaemia is diagnosed when the haemoglobin concentration is less than 7.0 grams per decilitre (g/dl), moderate anaemia is when the haemoglobin concentration is 7.0-9.9 g/dl, and mild anaemia is when the haemoglobin concentration is 10.0-11.9 g/dl (10.0-10.9 for pregnant women). 10.4.1 PREVALENCE OF ANAEMIA IN CHILDREN Table 10.12 shows data on the prevalence of anaemia in children under five years of age. In Uganda, anaemia affects 64 percent of children; only 36 percent of children are nonanaemic. Twenty-one percent of children have mild anaemia, 37 percent have moderate anaemia, and 7 percent of children are severely anaemic. Both severe and moderate anaemia are most prevalent among children age 6-15 months. In general, rural children are more likely to be anaemic than urban children (67 percent compared with 51 percent). Anaemia is most prevalent in the Northern Region, where 72 percent of children are anaemic. Anaemia has a negative relationship with wealth status: children in the lowest quintile are the most likely to be anaemic, while children in the highest quintile have the lowest level of anaemia. 10.4.2 PREVALENCE OF ANAEMIA IN WOMEN Data about the prevalence of anaemia among women is presented in Table 10.13. Overall, 30 percent of women in Uganda are anaemic; 22 percent have mild anaemia, 8 percent have moderate anaemia, and less than 1 percent are severely anaemic. Younger women, women who have not given birth, urban women, and better educated women are less likely to be anaemic than other women. As expected, women who are not pregnant and not breastfeeding are less likely to be anaemic than women who are either pregnant or breastfeeding. Infant Feeding and Children’s and Women’s Nutritional Status * 159 Table 10.12 Prevalence of anaemia in children Percent distribution of children age 6-59 months of interviewed mothers by anaemia status, according to background characteristics and percent distribution of children of noninterviewed mothers by anaemia status, Uganda 2000-2001__________________________________________________________________________________________ Percentage of children with anaemia Percentage__________________________________ of children Severe Moderate who are not Background (below 7.0 (7.0-9.9 Mild (10.0- anaemic characteristic g/dl) g/dl) 10.9 g/dl) (11.0+ g/dl) Total Number__________________________________________________________________________________________ Age in months 6-9 10-11 12-15 16-19 20-23 24-35 36-47 48-59 Sex of child Male Female Birth order 1 2-3 4-5 6+ Birth interval First birth1 <24 months 24-47 months 48+ months Residence Urban Rural Region Central Eastern Northern Western Mother’s education No education Primary Secondary+ Wealth index quintile Lowest Lower middle Middle Upper middle Highest Children of interviewed mothers Children of non- interviewed mothers Mothers living in household Mothers not living in household2 Total 16.8 50.5 14.9 17.8 100.0 442 15.1 52.1 16.5 16.3 100.0 248 13.4 54.5 12.2 19.9 100.0 426 8.3 48.8 20.5 22.4 100.0 473 9.7 45.0 18.6 26.6 100.0 449 4.6 36.1 22.8 36.4 100.0 1,048 3.2 29.7 23.2 43.9 100.0 1,079 1.4 23.9 22.2 52.4 100.0 937 7.0 39.5 20.1 33.5 100.0 2,539 6.7 36.6 20.6 36.1 100.0 2,561 6.4 33.7 20.8 39.2 100.0 791 6.9 36.5 19.9 36.7 100.0 1,656 7.1 41.7 20.4 30.9 100.0 1,212 6.7 39.1 20.6 33.6 100.0 1,441 6.5 33.7 20.6 39.1 100.0 795 6.5 39.6 19.7 34.1 100.0 1,111 7.2 39.7 20.4 32.7 100.0 2,623 6.3 33.2 20.8 39.6 100.0 571 2.2 29.2 19.8 48.8 100.0 468 7.3 38.9 20.4 33.4 100.0 4,632 5.8 38.4 19.4 36.4 100.0 1,312 7.0 40.0 22.9 30.2 100.0 1,594 6.5 43.6 22.2 27.7 100.0 884 7.9 31.6 16.9 43.6 100.0 1,311 7.6 40.4 19.4 32.5 100.0 1,295 7.0 38.3 20.9 33.9 100.0 3,247 4.3 30.9 19.3 45.6 100.0 558 7.8 39.3 22.2 30.7 100.0 2,450 9.5 39.9 19.6 31.0 100.0 2,468 6.7 38.1 19.3 35.9 100.0 2,303 5.2 37.4 20.4 37.1 100.0 2,137 2.3 30.4 20.8 46.5 100.0 1,575 6.8 38.0 20.3 34.8 100.0 5,100 5.3 34.1 21.5 39.0 100.0 241 3.3 29.4 21.3 46.0 100.0 534 6.5 37.1 20.5 35.9 100.0 5,833 __________________________________________________________________________________ Note: Table is based on children with interviewed mothers (except bottom 3 rows) 1 First-born twins (triplets, etc.) are counted as first births because they do not have a previous birth interval. 2 Includes children whose mother is deceased 160 * Infant Feeding and Children’s and Women’s Nutritional Status Table 10.13 Prevalence of anaemia in women Percent distribution of women age 15-49 years by anaemia status, according to background characteristics, Uganda 2000-2001___________________________________________________________________________________________ Percentage of women with anaemia Percentage__________________________________ of women Severe Moderate who are not Background (below 7.0 (7.0-9.9 Mild (10.0- anaemic characteristic g/dl) g/dl) 10.9 g/dl) (11.0+ g/dl) Total Number___________________________________________________________________________________________ Age 15-19 20-24 25-29 30-34 35-39 40-44 45-49 No. of children ever born No births 1 2-3 4-5 6+ Maternity status Pregnant1 Breastfeeding Neither Residence Urban Rural Region Central Eastern Northern Western Education No education Primary Secondary+ Total 0.6 6.3 17.6 75.5 100.0 1,418 0.6 6.7 24.3 68.3 100.0 1,355 0.8 8.0 22.2 69.1 100.0 1,232 0.6 8.1 22.9 68.4 100.0 897 1.1 8.7 21.3 68.9 100.0 739 0.2 9.5 22.3 67.9 100.0 522 1.8 6.7 30.4 61.0 100.0 384 0.7 6.1 15.8 77.4 100.0 1,388 0.1 8.7 25.4 65.8 100.0 789 0.6 7.3 22.7 69.4 100.0 1,494 0.9 6.8 24.2 68.1 100.0 1,205 1.0 8.8 23.9 66.4 100.0 1,673 2.0 17.1 22.1 58.8 100.0 860 0.4 6.2 25.6 67.9 100.0 2,361 0.6 5.9 19.7 73.7 100.0 3,327 0.4 5.4 15.4 78.8 100.0 967 0.8 7.9 23.3 68.1 100.0 5,581 0.6 6.3 20.6 72.5 100.0 1,942 1.3 9.7 25.2 63.8 100.0 1,822 0.2 4.6 24.7 70.5 100.0 1,092 0.7 8.3 18.9 72.1 100.0 1,692 1.0 9.6 25.1 64.3 100.0 1,460 0.7 7.3 22.5 69.6 100.0 3,936 0.6 5.6 17.1 76.6 100.0 1,151 0.7 7.5 22.1 69.6 100.0 6,548 ___________________________________________________________________________________________ Note: Table is based on women who stayed in the household the night before the interview. Total includes one woman with missing information on education 1 A pregnant woman is anaemic if her haemoglobin level is less than 10 g/dl. 10.4.3 PREVALENCE OF ANAEMIA IN MEN Data about the prevalence of anaemia among men are presented in Table 10.14. The criterion used to classify the prevalence of anaemia in men is different from that in women and children. A man is considered to be anaemic if the haemoglobin level in his blood is less than 13 grams per decilitre (WHO, 1997). In general, men are much less likely to suffer from anaemia than women or children. The overall level of anaemia among men is 18 percent. This level varies according to the man’s age; it is highest among those in the youngest age group (28 percent) and in the oldest age group (31 percent). Urban men and better educated men are less likely to be anaemic than other men. Whereas 24 percent of men with no education are anaemic, the corre- sponding percentage among those with secondary education is 14 percent. Variations across regions are slight; anaemia prevalence among men ranges between 17 (Northern) and 19 percent (Western and Central). Infant Feeding and Children’s and Women’s Nutritional Status * 161 Table 10.14 Prevalence of anaemia in men Percent distribution of men age 15-54 years by anaemia status, according to background characteristics, Uganda 2000-2001 __________________________________________________________________________________________ Percentage of men with anaemia Percentage ____________________________________ of men Severe Moderate who are not Background (below 9.0 (9.0-11.9 Mild (12.0- anaemic characteristic g/dl) g/dl) 12.9 g/dl) (13.0+ g/dl) Total Number __________________________________________________________________________________________ Age in months 15-19 20-24 25-29 30-34 35-39 40-44 45-49 50-54 Residence Urban Rural Region Central Eastern Northern Western Man's education No education Primary Secondary+ Total 0.4 10.7 16.6 72.3 100.0 487 2.1 3.6 6.0 88.3 100.0 371 0.2 3.5 5.8 90.5 100.0 392 0.4 4.4 10.6 84.6 100.0 346 0.6 9.4 8.4 81.5 100.0 277 1.1 9.4 8.0 81.6 100.0 200 0.9 12.9 9.7 76.6 100.0 162 4.7 12.3 13.7 69.4 100.0 114 1.0 2.4 5.8 90.9 100.0 244 1.0 8.0 10.4 80.6 100.0 2,106 1.3 7.6 10.5 80.6 100.0 649 0.8 7.4 9.9 81.9 100.0 683 0.3 6.7 9.5 83.5 100.0 536 1.5 7.9 9.6 81.0 100.0 482 2.0 10.5 11.0 76.5 100.0 203 0.7 8.1 10.5 80.7 100.0 1,561 1.2 4.8 8.0 85.9 100.0 566 1.0 7.4 9.9 81.7 100.0 2,349 10.4.4 ANAEMIA IN CHILDREN AND SEVERITY OF ANAEMIA IN MOTHERS Table 10.15 shows the relationship between the anaemia status of the mother and the anaemia status of the child, among children 6-59 months. The data indicate that there is a correlation between the level of anaemia in the mother and the level in the child. For example, if the child’s mother is moderately anaemic, the child is likely to be moderately anaemic (44 percent). Only 21 percent of children of mothers with moderate anaemia are not anaemic. Among children of mothers who are not anaemic, 40 percent are not anaemic. 162 * Infant Feeding and Children’s and Women’s Nutritional Status Table 10.15 Prevalence of anaemia in children by anaemia status of mother Percent distribution of children age 6-59 months by anaemia status, according to anaemia status of the mother, Uganda 2000-2001__________________________________________________________________________________________________ Percentage of children with anaemia Percentage__________________________________ of children Severe Moderate Mild who are not Number Anaemia status (below 7.0 (7.0-9.9 (10.0- anaemic of of mother g/dl) g/dl) 10.9 g/dl) (11.0+ g/dl) Total children___________________________________________________________________________________________________ Severe (below 7.0 g/dl) Moderate (7.0-9.9 g/dl) Mild (10.0-11.9 g/dl) Percentage of women who are not anaemic (12.0+ g/dl) Total (16.3) (35.1) (13.2) (35.4) 100.0 46 12.8 43.5 22.4 21.2 100.0 358 8.3 44.3 22.5 24.9 100.0 1,260 5.5 35.2 19.4 39.8 100.0 3,437 6.8 38.0 20.3 34.8 100.0 5,100 ___________________________________________________________________________________________________ Note: Table is based on children who slept in the household the night before the interview. Table includes only cases with anaemia measurements for both mother and child. Figures in parentheses are based on 25-49 unweighted cases. 10.5 VITAMIN A STATUS Vitamin A is an essential food nutrient found in very small quantities in some foods. It is important for normal sight, growth, and development particularly in children. Vitamin A is also considered to be important in protecting the body against some infectious illnesses such as measles and diarrhoeal disease. Lack of vitamin A (vitamin A deficiency or VAD) is associated with total loss of vision or with other vision impairments including night blindness. It is also believed to be the single most important cause of blindness among children in developing countries. VAD is also associated with increased susceptibility to severe infections and malnutrition. Prevention measures for VAD involve ensuring that the diet includes foods rich in vitamin A. This includes dark green leafy vegetables and fruits and vegetables in which the edible portion is yellow or dark orange in color like pawpaw, mango, carrot, and pumpkin. Liver, egg yolk and small fish are also good sources of vitamin A. Breast feeding children exclusively for at least 4-6 months is another important step in preventing VAD. In addition to dietary measures, many countries have begun a program of vitamin-A supplementation in which vitamin A capsules are given to vulnerable groups, such as children and lactating mothers. VAD is considered to be a widespread problem in many developing countries including Uganda, but few countries have had the opportunity to obtain nationally representative data on the prevalence of the problem. The DHS survey offered Uganda the chance to document levels of VAD in a representative sample of women and children under five. The results will be used by the Ministry of Health to help in the design of programmes to reduce the levels of VAD and to monitor progress in achieving this goal. 10.5.1 METHODOLOGY FOR MEASURING VITAMIN A Various indicators are used to assess the presence of vitamin A deficiency, including functional measures such as the prevalence of night blindness, clinical measures including eye examinations for signs of xerophthalmia, and biochemical testing for such factors as vitamin A levels in breast milk or serum retinol concentrations in blood samples. The latter approach was adopted in the 2000-2001 UDHS (ORC Macro, 2001). Infant Feeding and Children’s and Women’s Nutritional Status * 163 Blood spots were collected on a filter paper card from the finger or heel prick used for anaemia testing for all eligible women and children under age 5 in 810 households covered in the survey (one-half of the households eligible for the men’s survey). Five circles were preprinted on the paper, in which two were expected to be completely saturated with blood spots. The samples were identified by recording the identification information of the subject in a label attached to the paper. The filter paper specimen for each subject was placed in a specially designed box where it was protected from sunlight and moisture while drying overnight. On the following day, each sample was placed in a ziplock freezer bag and then put into an airtight container in a battery- operated refrigerator for storage. The samples were collected from the field teams by staff from UBOS approximately every two to three weeks and transported to the Uganda Virus Research Institute (UVRI) in Entebbe. Arrangements were made with the Centers for Disease Control (CDC) team at UVRI to ship the samples in batches to Craft Technologies in the United States. The analysis of the dried blood spots was conducted by eluting a 1/4-inch punch from the dried blood spot and using High Performing Liquid Chromatography (HPLC). Vitamin A levels derived from dried blood spot samples have been shown to be affected by the fact that the retinol-binding protein in the serum collected on filter paper decays in the first 7 to 10 days after collection. In order to adjust the vitamin A levels obtained from the UDHS for this phenomenon, a special study was carried out in May 2001, in which for 96 subjects (women and children), both filter paper and venous blood samples were collected. The filter paper samples were collected using the same procedures as those employed in the UDHS. The venous blood samples were immediately refrigerated in the field and, at the end of each day, were processed at UVRI to obtain serum. Both types of samples were sent to Craft Laboratories for analysis. The correlation between the vitamin A levels measured from dried blood spot retinol and plasma retinol level was used to determine a recovery factor that was applied to all of the samples analysed for this study. 10.5.2 RESULTS A total of 1,117 women 15-49 and 1,178 children under 6 years were eligible for the test. Among these, 978 women and 1,025 children were successfully tested. Failure to test the subjects was due to absence of the respondent, refusal, or loss of test data prior to analysis. The response rate, accounting for refusals and missing data, was 88 percent for women and 87 percent for children under 6 years. The results for children 6 to 59 months are shown in Table 10.16 and for women age 15-49 in Table 10.17. Table 10.16 is limited to children over 6 months, because infants less than 6 months, especially those who are exclusively breastfed, are less vulnerable than older children. Table 10.16 shows that 28 percent of children suffer from vitamin A deficiency (VAD). At this level, VAD in Uganda can be perceived as a public health problem (WHO, 1996). As expected, VAD is low among children 6-11 months, when the children are still benefiting from the positive effect of breastfeeding. The highest VAD is found among children 12-23 months (32 percent). VAD is more likely to be found among high-order births and children living in rural areas and in the Northern Region. Children of older mothers are more likely to suffer from VAD than those whose mothers are younger. For example, 21 percent of children whose mothers are 15-19 years old are vitamin A deficient compared with 34 percent of children whose mothers are 35-49 years old. Children whose mothers have no education are more likely to be deficient in vitamin A (35 percent) than those whose mothers have some formal education (26 percent or less). 164 * Infant Feeding and Children’s and Women’s Nutritional Status Table 10.16 Prevalence of vitamin A deficiency in children Percentage of children age 6-59 months classified as having vitamin A deficiency (VAD), by background characteristics, Uganda 2000-2001_______________________________________________ Percent Number Background with any VAD of characteristic (<0.7 µmol/L) children_______________________________________________ Age in months 6-11 12-23 24-35 36-47 48-59 Sex Male Female Birth order1 1 2-3 4-5 6+ Birth interval in months1 First birth <24 24-47 48+ Residence Urban Rural Region Central Eastern Northern Western Mother's education2 No education Primary Secondary+ Mother's age 15-19 20-24 25-29 30-34 35-49 Total 20.3 121 32.0 187 28.6 175 26.9 215 29.3 161 29.7 423 26.1 437 24.7 127 24.1 233 28.8 192 32.6 209 24.5 128 30.5 172 24.9 386 41.7 75 15.9 79 29.1 780 21.8 226 27.6 243 36.3 150 28.6 241 35.1 245 25.7 477 17.1 79 21.0 55 26.6 230 25.3 243 30.5 192 33.5 139 27.9 859 _______________________________________________ 1 Excludes children whose mothers were not interviewed 2 For mothers who were not interviewed, information is taken from the Household Questionnaire. Excludes children whose mothers are not listed in the household. Table 10.17 shows that more than half of women in Uganda have VAD. The level of deficiency in women varies according to the woman's characteristics, but not as much as that in young children. VAD fluctuates with the woman's age; low (50-51 percent) among women 15-29, peaks at age 30-34 (56 percent), and lower thereafter. The number of children a woman has had has no clear association with her vitamin A level. Pregnant and lactating women are not substantially different in VAD level from women who are neither pregnant nor breastfeeding. Infant Feeding and Children’s and Women’s Nutritional Status * 165 Table 10.17 Prevalence of vitamin A deficiency in women Percentage of women age 15-49 with vitamin A deficiency (VAD), by background characteristics, Uganda 2000-2001__________________________________________________________________________________________ Marginal Moderate Severe Any VAD deficiency deficiency deficiency Background (<1.05 (0.70-1.05 (0.35-0.69 (>0.35 characteristic µmol/L) µmol/L) µmol/L) µmol/L) Number__________________________________________________________________________________________ Age 15-19 20-24 25-29 30-34 35-39 40-44 45-49 Number of children ever born No births 1 2-3 4-5 6+ Maternity status Pregnant Breastfeeding (not pregnant) Neither Residence Urban Rural Region Central Eastern Northern Western Education No education Primary Secondary+ Total 50.3 32.0 17.1 1.3 214 50.6 28.1 19.5 3.0 183 51.4 26.2 20.3 4.9 192 56.3 29.6 25.7 1.0 146 49.3 22.9 25.9 0.5 80 53.4 35.4 17.9 0.0 81 (55.0) (33.3) (21.7) (0.0) 47 49.2 29.4 18.4 1.4 196 54.2 31.0 18.0 5.1 118 49.9 25.7 22.7 1.5 202 51.6 25.3 22.1 4.2 172 54.8 33.8 20.8 0.2 255 51.1 27.7 21.3 2.0 118 49.8 26.8 21.5 1.5 365 53.9 31.6 19.7 2.5 461 44.5 27.0 16.7 0.8 135 53.2 29.6 21.2 2.3 809 56.5 29.9 24.6 2.0 263 51.7 23.8 24.3 3.5 253 40.8 29.5 9.6 1.7 167 54.7 33.7 20.0 0.9 260 55.7 34.7 19.2 1.8 236 51.9 26.9 22.4 2.6 560 46.0 29.4 16.0 0.6 147 51.9 29.3 20.6 2.1 944 As in the case with children, rural women are more likely than urban women to be deficient in vitamin A (53 compared to 45 percent). The same pattern is seen by women's education; women with no education are more likely than other women to have VAD (56 percent compared to 46 percent for women with secondary education). With regard to regional differentials, there does not seem to be a direct relationship between children's vitamin A level and their mother's. HIV/AIDS and Other Sexually Transmitted Infections * 167 11HIV/AIDS AND OTHER SEXUALLY TRANSMITTED INFECTIONS The first AIDS case in Uganda was identified in 1982 in a fishing village along the shores of Lake Victoria. Since then, the disease has spread throughout the country. By the end of 1999, there were 55,861 reported clinical AIDS cases, which represent a small portion of all cases. At the same time, 1,438,000 persons were estimated to have been infected by HIV, while 838,000 deaths were estimated to have been caused by AIDS (MOH, 2000). The response to the epidemic has been characterised by collaboration among the government agencies, development partners, nongovernmental organisations, religious groups, individuals, cultural groups, community groups, research institutions, and networks of persons infected and affected by HIV/AIDS. To this effect, a new strategy, Multisectoral AIDS Control Approach (MACA), was adopted. 11.1 KNOWLEDGE OF WAYS TO PREVENT HIV/AIDS Since there is no cure for HIV/AIDS, the main strategy for combating the disease has been prevention through practising abstinence, being faithful to one sexual partner, and using condoms. This strategy depends heavily on the level of knowledge of the population and their perception of the HIV/AIDS problem. For this reason, the 2000-2001 UDHS sought to gauge the levels of knowledge of HIV/AIDS and other sexually transmitted infections and the behaviours people adopt to protect themselves against the infection. In Uganda, HIV/AIDS has been termed a “household disease” because nearly every household has lost a relative or friend to the disease. In a situation like this, it is expected that everybody has heard of AIDS. As was the case in 1995, Table 11.1 shows that in Uganda today, knowledge of HIV/AIDS is universal. 11.1.1 KNOW LEDGE OF WAYS TO AVOID HIV/AIDS The 2000-2001 UDHS asked respondents whether there is anything one can do to avoid getting infected with HIV/AIDS. Table 11.1 shows that the level of awareness about the disease is not matched by the knowledge of how to avoid contracting the virus. Only three methods to avoid infection with HIV/AIDS are widely known, namely, using condoms (spontaneously mentioned by 54 percent of women and 72 percent of men), abstaining from sexual relations (50 percent of women and 65 percent of men), and having only one sexual partner (49 percent of women and 43 percent of men). A sizeable proportion of respondents (14 percent of women and 5 percent of men) know that AIDS can be avoided but do not know a particular method to avoid contracting it. Thirteen percent of women and 5 percent of men either believe that there is no way to avoid AIDS or do not know whether AIDS can be avoided. 168 * HIV/AIDS and Other Sexually Transmitted Infections Table 11.1 Knowledge of ways to avoid HIV/AIDS Percentage of women and men who have heard of HIV/AIDS and who spontaneously mention ways to avoid HIV/AIDS, Uganda 2000-2001 ______________________________________________________________________________ Ways to avoid HIV/AIDS Women Men ______________________________________________________________________________ Has heard of HIV/AIDS Does not know if AIDS can be avoided Believes no way to avoid AIDS Does not know specific way Specific ways to avoid HIV/AIDS Abstain from sex Use condoms Limit sex to one partner/stay faithful to one partner Limit number of sexual partners Avoid sex with prostitutes Avoid sex with persons who have many partners Avoid sex with homosexuals Avoid blood transfusions Avoid injections Avoid kissing Avoid mosquito bites Seek protection from traditional healer Other ways 99.7 100.0 7.8 2.3 5.6 2.4 13.5 5.2 49.7 65.4 54.4 72.3 49.0 43.0 2.4 10.6 1.2 4.8 2.0 1.8 0.1 0.1 3.2 5.3 2.9 8.3 0.2 6.1 0.2 0.4 0.2 0.2 14.9 18.9 11.1.2 KNOWLEDGE OF PROGRAM MATICALLY IMPORTANT WAYS TO AVOID CONTRACTING HIV/AIDS As mentioned above, there are three programmatically recognised ways to avoid contracting HIV: using condoms, limiting the number of sexual partners, and abstaining from sex. In the UDHS, respondents were asked specific questions about whether condom use and limiting partners could reduce the risk of getting HIV. Currently, 78 percent of women and 90 percent of men know two or more programmatically important ways to avoid HIV/AIDS (Tables 11.2.1 and 11.2 2). Additionally, 9 percent of women and 5 percent of men know of one programmatic way of avoiding the disease. Knowledge of at least two programmatically important ways to avoid contracting the AIDS virus is high among women in urban areas (92 percent), women from the Central Region (93 percent), and women who have some secondary education (95 percent). Men show a similar pattern, although the relative differences are smaller. Marital status does not have a strong relationship with the knowledge of these selected ways. However, the level of education is positively associated with the level of knowledge of ways of avoiding HIV/AIDS. One in four women without any education do not know any way to avoid HIV/AIDS, compared with only 2 percent of women with secondary education. The corresponding percentages for men are 15 and 2 percent, respectively. Regarding the particular methods, 69 percent of women say that condom use can reduce the risk of getting AIDS, while 84 percent know that limiting the number of sexual partners is a way to avoid contracting HIV/AIDS. The percentages for men are 83 and 91 percent, respectively. Knowledge of these two ways to avoid contracting HIV/AIDS is generally highest among women and men in their twenties and thirties. HIV/AIDS and Other Sexually Transmitted Infections * 169 Table 11.2.1 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, Uganda 2000-2001 __________________________________________________________________________________________________ Knowledge of Knowledge of programmatically important specific ways to ways to avoid HIV/AIDS avoid HIV/AIDS ______________________________ ____________________ Limit Two number Background One or more Use of sexual characteristic None1 way ways Total condoms partners2 Number __________________________________________________________________________________________________ Age 15-19 20-24 25-29 30-39 40-49 Current marital status Married or in union Divorced, separated, widowed Never married, ever had sex Never had sex Residence Urban Rural Region Central Eastern Northern Western Education No education Primary Secondary+ Total 15.4 6.4 78.1 100.0 68.9 80.4 1,615 11.5 6.1 82.5 100.0 76.2 87.2 1,504 12.1 8.8 79.1 100.0 71.7 86.5 1,341 13.4 10.7 75.8 100.0 66.4 84.2 1,793 15.0 11.2 73.8 100.0 59.1 82.6 993 13.9 10.5 75.6 100.0 67.5 84.4 4,881 12.1 6.1 81.8 100.0 70.5 84.2 910 9.3 3.2 87.5 100.0 83.5 87.8 608 15.0 3.7 81.2 100.0 65.3 80.4 848 5.3 3.1 91.6 100.0 87.7 92.4 1,207 15.0 9.6 75.3 100.0 65.2 82.5 6,039 4.1 2.8 93.0 100.0 87.9 93.0 2,341 15.8 6.7 77.5 100.0 71.6 81.2 1,956 25.5 20.5 53.9 100.0 46.4 72.3 1,158 15.2 10.1 74.7 100.0 56.1 83.6 1,792 25.3 15.3 59.4 100.0 46.9 72.3 1,584 12.5 7.9 79.6 100.0 70.4 84.9 4,330 2.3 2.5 95.2 100.0 90.6 95.9 1,331 13.4 8.5 78.1 100.0 69.0 84.2 7,246 __________________________________________________________________________________________________ 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 the number of sexual partners, and limiting sex to one partner/staying faithful to one partner Women and men who are not married and have never had sex are the least knowledgeable about specific ways to avoid HIV/AIDS. However, unmarried women and men who have ever had sex are the most likely to know about condom use as a method to avoid contracting HIV/AIDS than other respondents. Residence accounts for a difference in levels of knowledge. Urban women are more likely than rural women to know about condom use and limiting the number of partners as methods of avoiding HIV/AIDS. Women in the Central Region are the most knowledgeable about these two methods for avoiding HIV/AIDS, while those from the Northern Region are the least knowledgeable. 170 * HIV/AIDS and Other Sexually Transmitted Infections Table 11.2.2 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, Uganda 2000-2001 __________________________________________________________________________________________________ Knowledge of Knowledge of programmatically important specific ways to ways to avoid HIV/AIDS avoid HIV/AIDS ______________________________ ____________________ Limit Two number Background One or more Use of sexual characteristic None1 way ways Total condoms partners2 Number __________________________________________________________________________________________________ Age 15-19 20-24 25-29 30-39 40-49 50-54 Current marital status Married or in union Divorced, separated, widowed Never married, ever had sex Never had sex Residence Urban Rural Region Central Eastern Northern Western Education No education Primary Secondary+ Total 8.4 5.3 86.3 100.0 82.8 83.9 441 2.5 3.4 94.1 100.0 89.4 93.4 321 1.9 5.8 92.3 100.0 84.9 96.9 310 3.5 4.5 92.0 100.0 85.2 93.6 522 8.6 6.1 85.3 100.0 74.5 88.5 285 10.7 7.4 81.9 100.0 71.1 86.1 83 4.3 5.4 90.3 100.0 82.8 93.7 1,180 7.1 2.8 90.0 100.0 80.5 89.7 107 4.2 3.6 92.1 100.0 90.9 89.9 356 9.2 6.1 84.7 100.0 76.9 81.8 319 2.5 2.5 95.0 100.0 90.4 94.1 325 5.8 5.6 88.7 100.0 81.7 90.2 1,637 3.5 1.7 94.8 100.0 88.8 93.1 671 9.0 7.0 84.0 100.0 83.2 85.8 523 5.1 12.1 82.8 100.0 72.3 92.6 284 3.6 3.5 92.8 100.0 81.6 92.3 484 15.0 6.4 78.6 100.0 64.3 80.8 122 6.1 5.8 88.1 100.0 81.4 89.2 1,272 1.5 3.5 95.0 100.0 90.3 95.8 444 5.2 5.0 89.7 100.0 83.2 90.9 1,962 __________________________________________________________________________________________________ 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, nd 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 the number of sexual partners, and limiting sex to one partner/staying faithful to one partner A woman’s education has a strong relationship to knowledge about use of condoms or limiting sexual partners as methods of avoiding HIV/AIDS. Women with secondary or higher education are more likely to know about these methods than women without education. Men show similar patterns of knowledge but with smaller differentials than women. 11.2 KNOWLEDGE OF OTHER AIDS-RELATED ISSUES Tables 11.3.1 and 11.3.2 show responses to questions about other important dimensions of HIV/AIDS information. The data show that 77 percent of women and 88 percent of men are aware that a healthy-looking person can carry the HIV virus. The level of knowledge does not show wide variations by the respondent’s age. However, female and male respondents who have never had sex, those from rural areas, and those with less education are less likely to know this fact. HIV/AIDS and Other Sexually Transmitted Infections * 171 Table 11.3.1 Knowledge of AIDS-related issues: women Percentage of women by responses to questions on various HIV/AIDS-related issues, according to background characteristics, Uganda 2000-2001 ___________________________________________________________________________________________________________ Respondent knows Percentage Percentage who someone who say a say HIV/AIDS can be Doesn't know personally healthy- transmitted from mother to child if HIV/AIDS who has the looking _______________________________ can be virus that person can During transmitted causes AIDS Background have the During During breast- from mother or has died characteristic AIDS virus pregnancy delivery feeding to child of AIDS Number1 ____________________________________________________________________________________________________________ Age 15-19 20-24 25-29 30-39 40-49 Marital status Married or in union Divorced, separated, widowed Never married Ever had sex Never had sex Residence Urban Rural Region Central Eastern Northern Western Education No education Primary Secondary+ Total 72.0 57.6 64.2 45.4 11.8 87.0 1,615 79.8 55.7 73.1 46.4 10.0 91.1 1,504 79.9 57.1 72.4 45.5 10.8 90.9 1,341 78.7 60.9 69.1 46.7 11.1 92.6 1,793 75.1 59.5 68.4 47.6 12.5 90.8 993 77.0 58.4 68.8 46.6 11.6 90.6 4,881 82.7 60.4 73.3 47.6 10.8 93.5 910 84.7 59.0 77.1 48.9 4.9 93.9 608 66.9 54.0 63.1 41.2 13.4 84.2 848 91.4 54.9 84.2 48.0 5.2 94.8 1,207 74.3 58.9 66.4 45.9 12.3 89.6 6,039 92.9 53.0 81.1 47.0 7.2 96.4 2,341 79.9 64.7 66.0 48.0 9.5 94.8 1,956 63.2 51.4 51.9 44.6 17.2 77.7 1,158 62.7 62.4 69.1 44.5 14.3 86.4 1,792 63.8 56.8 54.1 42.6 19.4 83.9 1,584 77.6 59.7 69.2 48.0 10.9 91.1 4,330 91.7 55.2 88.2 45.1 2.2 96.2 1,331 77.2 58.2 69.4 46.3 11.2 90.5 7,246 ___________________________________________________________________________________________________________ 1 Includes one woman with missing information on education. One of the objectives of the National Strategic Plan for HIV/AIDS prevention is to reduce the incidence of mother-to-child transmission of HIV. In the UDHS, respondents were asked whether the virus that causes AIDS can be transmitted from a mother to a child. They were also asked when the transmission occurs. Only a small percentage (11 percent) of men and women do not know that HIV can be transmitted from mother to child. Overall, 58 percent of women know that HIV can be transmitted during pregnancy, 69 percent know that it can be transmitted during delivery, and 46 percent know that it can be transmitted during breastfeeding. The corresponding figures for men are 53, 69, and 43 percent, respectively. The background characteristics of respondents do not account for large differences in the level of knowledge of the HIV transmission through pregnancy or breastfeeding, except that men in the Northern Region show a particularly high level of knowledge of HIV transmission during pregnancy (74 percent). However, the respondent’s residence, region, and education are related to differences in knowledge of HIV transmission during delivery. Women and men with secondary education are more likely to know about this mode (88 percent of women and 77 percent of men) 172 * HIV/AIDS and Other Sexually Transmitted Infections Table 11.3.2 Knowledge of AIDS-related issues: men Percentage of men by responses to questions on various HIV/AIDS-related issues, according to background characteristics, Uganda 2000-2001 ___________________________________________________________________________________________________________ Respondent knows Percentage Percentage who someone who say a say HIV/AIDS can be Doesn't know personally healthy- transmitted from mother to child if HIV/AIDS who has the looking _______________________________ can be virus that person can During transmitted causes AIDS Background have the During During breast- from mother or has died characteristic AIDS virus pregnancy delivery feeding to child of AIDS Number ____________________________________________________________________________________________________________ Age 15-19 20-24 25-29 30-39 40-49 50-54 Marital status Married or in union Divorced, separated, widowed Never married Ever had sex Never had sex Residence Urban Rural Region Central Eastern Northern Western Education No education Primary Secondary+ Total 80.1 54.0 59.5 44.7 11.0 86.5 441 87.4 53.9 76.8 42.2 6.8 91.6 321 92.4 55.3 79.3 42.9 8.4 92.0 310 92.3 50.0 67.2 43.3 12.6 93.4 522 85.4 57.4 69.1 41.4 14.0 87.1 285 87.6 50.2 61.6 48.4 13.1 90.1 83 89.8 53.6 71.4 43.4 11.6 90.9 1,180 93.3 57.7 61.8 48.0 10.4 91.6 107 87.4 50.5 73.0 42.7 6.1 94.3 356 77.6 54.8 58.1 42.3 13.7 83.0 319 95.8 49.4 82.5 40.5 4.9 96.5 325 86.0 54.3 66.3 43.9 12.0 89.0 1,637 96.6 50.8 79.6 42.7 7.0 97.9 671 78.7 50.5 56.2 44.4 12.6 93.5 523 76.3 73.6 70.8 55.1 8.4 68.5 284 91.3 48.5 67.0 36.1 15.8 89.0 484 81.2 46.1 53.5 46.1 24.0 83.3 122 86.0 57.1 65.0 46.3 12.8 89.3 1,272 90.7 45.9 77.2 35.4 4.2 92.8 444 87.6 53.4 69.0 43.3 10.9 90.3 1,962 than those without education (54 percent of both women and men). Urban women and men are more likely to know this mode of transmission than those in rural areas. Among women, awareness that the HIV virus can be transmitted during delivery is highest in the Central Region (81 percent) and lowest in the Northern Region (52 percent). Nine in ten respondents of both sexes know someone personally who has HIV or who died of AIDS. Urban residents, those who live in the Central and Eastern regions, and those with secondary or higher education are more likely than other respondents to know someone who has the AIDS virus or who died of AIDS. The lowest percentage is among women and men in the Northern Region (78 percent of women and 69 percent of men). HIV/AIDS and Other Sexually Transmitted Infections * 173 Table 11.4 Discussion of HIV/AIDS with partner Percent distribution of women and men who are currently married or living with a partner by whether they ever discussed HIV/AIDS prevention with their spouse/partner, according to background characteristics, Uganda 2000-2001 ________________________________________________________________________________________________________________________ WO MEN MEN _____________________________________________________ _____________________________________________ Ever Ever discussed Never Don 't Never discussed Never Don 't Background pre- discussed know/ heard pre- discussed know/ characteristic vention prevention missing of AIDS Total Number vention prevention missing Total Number ___________________________________________________________________________________________________________________________ Age 15-19 20-24 25-29 30-39 40-49 50-54 Residence Urban Rural Region Central Eastern Northern Western Education No education Primary Secondary+ Total 47.7 52.1 0.1 0.1 100.0 466 (68.6) (31.4) (0.0) 100 .0 28 60.4 39.5 0.0 0.1 100.0 1,150 81.9 18.1 0.0 100 .0 139 65.7 34.0 0.2 0.1 100.0 1,078 87.2 12.8 0.0 100 .0 237 66.4 33.3 0.1 0.2 100.0 1,459 83.8 16.2 0.6 100 .0 453 63.8 35.5 0.3 0.4 100.0 728 85.7 14.3 0.0 100 .0 252 na na na na na na 82.9 17.1 0.0 100 .0 72 76.1 23.8 0.1 0.0 100.0 636 91.4 8.6 0.0 100 .0 148 60.7 38.9 0.2 0.2 100.0 4,245 83.2 16.5 0.3 100 .0 1,032 66.0 34.0 0.0 0.0 100.0 1,377 88.5 11.0 0.5 100 .0 322 67.7 32.0 0.2 0.1 100.0 1,487 90.5 9.5 0.0 100 .0 344 51.4 47.8 0.1 0.7 100.0 823 62.1 37.9 0.0 100 .0 209 60.3 39.4 0.2 0.1 100.0 1,194 87.8 11.8 0.4 100 .0 305 48.4 50.8 0.2 0.6 100.0 1,264 68.8 31.2 0.0 100 .0 92 64.2 35.6 0.2 0.0 100.0 2,978 82.5 17.1 0.4 100 .0 781 83.7 16.2 0.1 0.0 100.0 639 91.9 8.1 0.0 100 .0 220 62.7 37.0 0.1 0.2 100.0 4,881 84.2 15.6 0.2 100 .0 1,180 ________________________________________________________________________________________________________________________ Note: Figures in parentheses are based on 25-49 unweighted cases. na = Not applicable 11.3 PERCEPTIONS OF HIV/AIDS 11.3.1 DISCUSSION OF AIDS WITH PARTNERS Discussions about HIV/AIDS with a spouse or partner are important in guarding against infection of either or both members of a couple. Currently married respondents and those living with a partner were asked whether they had ever discussed HIV/AIDS prevention with their partners. Table 11.4 shows that 63 percent of married women and 84 percent of married men said they had discussed HIV/AIDS with their partners. Similarly large differences in reporting discussions about AIDS between women and men have been observed in other African countries, such as Malawi (73 percent for females and 86 percent for males) (National Statistical Office and ORC Macro, 2001) and Zimbabwe (60 percent for females and 81 percent for males) (Central Statistical Office and Macro International Inc., 2000). 1 Positive living is an encouragement to people living with HIV/AIDS that they can live a meaningful life, enjoying their full rights in spite of their sero-positive status. 174 * HIV/AIDS and Other Sexually Transmitted Infections Table 11.4 further shows that urban couples are more likely to discuss HIV/AIDS than those in rural areas. Among regions, spousal discussions about HIV prevention vary between a high of 68 percent of women and 91 percent of men in the Eastern Region and a low of 51 percent of women and 62 percent of men in the Northern Region. Better educated couples are more likely to discuss HIV prevention with their partners than those with less education. For example, 84 percent of married women with secondary education have discussed HIV prevention with their partners, compared with only 48 percent of women with no education. 11.3.2 STIGMA ASSOCIATED WITH HIV/AIDS HIV/AIDS has introduced changes in cultural traditions. When the disease was first identified, it was difficult for individuals infected and affected to accept the tragedy. To change this attitude, a strategy of positive living to mitigate the social and psychological effects of the epidemic both at the individual and society level was promoted.1 However, positive living at the individual level can only succeed if there is no stigma from society toward people infected or affected by the disease. To assess whether society has accepted people living with HIV/AIDS, respondents were asked some questions about the social aspects of AIDS prevention and mitigation. In the UDHS, respondents were asked, “If a person learns that she/he is infected with the virus that causes AIDS, should the person be allowed to keep this fact private or should this information be available to the community?” Tables 11.5.1 and 11.5.2 show the responses. Less than half of the women and three in ten men feel that an HIV-positive person should be allowed to keep this fact confidential. The sentiment did not vary much across subgroups of respondents except by region. In the Western Region, women and men are more likely to feel this information should be confidential (61 percent for women and 35 percent for men) than in other regions (53 percent or lower for women and 28 percent or lower for men). Only one in ten women and men say they would not be willing to care for a relative with AIDS at their home. Younger respondents, as well as those who have never had sex, those living in rural areas and in the Eastern Region, and those with no education, are more likely to be unwilling to care for relatives with AIDS. Respondents were also asked, “If a female teacher has the AIDS virus, should she be allowed to continue teaching in the school?” The response to this question can be used to assess whether there is discrimination against persons with AIDS in the workplace. Respondents are split on this issue; half of the women and men believe an HIV-infected female teacher should not be allowed to continue teaching. Respondents with secondary education, those who live in urban areas, and women in the Central Region are less likely to believe that an HIV-positive female teacher should not be allowed to continue teaching. HIV/AIDS and Other Sexually Transmitted Infections * 175 Table 11.5.1 Social aspects of HIV/AIDS prevention and mitigation: women Percentage of women who gave specific responses to questions on various social aspects of HIV/AIDS prevention and mitigation, by background characteristics, Uganda 2000-2001 _____________________________________________________________________________________________________ Does not Believes a Does believe children person should not believe age 12-14 years be allowed Not willing HIV-positive should be taught to keep to care for teacher should about using Background HIV-positive relative with be allowed to condoms to characteristic status private AIDS at home keep teaching avoid AIDS Number1 _____________________________________________________________________________________________________ Age 15-19 20-24 25-29 30-39 40-49 Marital status Married or in union Divorced, separated, widowed Never married Ever had sex Never had sex Residence Urban Rural Region Central Eastern Northern Western Education No education Primary Secondary+ Total 49.1 15.8 54.2 25.7 1,615 48.2 10.7 48.4 21.8 1,504 47.9 9.0 46.6 25.1 1,341 46.0 8.6 48.0 26.2 1,793 45.0 8.6 50.6 28.5 993 46.9 10.7 50.9 24.8 4,881 50.3 5.8 44.7 26.7 910 49.1 11.2 44.0 19.8 608 45.7 15.9 51.4 30.3 848 46.3 7.1 32.0 23.7 1,207 47.6 11.4 53.1 25.6 6,039 53.1 6.6 36.7 26.5 2,341 39.3 16.5 59.7 15.5 1,956 28.1 17.2 56.8 23.3 1,158 61.0 5.6 50.8 35.7 1,792 45.0 14.4 57.4 26.1 1,584 48.8 10.5 52.6 25.4 4,330 45.4 6.9 30.3 23.8 1,331 47.4 10.7 49.6 25.3 7,246 ________________________________________________________________________________________________ 1 Includes one woman with missing information on education. In the 2000-2001 UDHS, respondents were asked whether they believe that children age 12- 14 should be taught about using a condom to avoid HIV/AIDS. Men are twice as likely as women to agree with this idea (58 percent compared with 25 percent). There are no large differentials across subgroups of women, except by region of residence. Thirty-six percent of women in the Western Region do not agree that children should be taught how to use condoms, compared with 16 percent in the Eastern Region. Men who have never had sex (47 percent) and those in the Northern Region are the least likely to believe that children age 12-14 should not be taught about condom use. 176 * HIV/AIDS and Other Sexually Transmitted Infections Table 11.5.2 Social aspects of HIV/AIDS prevention and mitigation: men Percentage of men who gave specific responses to questions on various social aspects of HIV/AIDS prevention and mitigation, by background characteristics, Uganda 2000-2001 _____________________________________________________________________________________________________ Does Does not Believes a not believe believe children person should HIV-positive age 12-14 years be allowed Not willing female teacher should be taught to keep to care for should be about using Background HIV-positive relative with allowed to condoms to characteristic status private AIDS at home keep teaching avoid AIDS Number _____________________________________________________________________________________________________ Age 15-19 20-24 25-29 30-39 40-49 50-54 Marital status Married or in union Divorced, separated, widowed Never married Ever had sex Never had sex Residence Urban Rural Region Central Eastern Northern Western Education No education Primary Secondary+ Total 37.6 12.3 55.6 54.9 441 26.1 7.8 50.6 63.0 321 24.9 9.1 49.2 59.5 310 27.0 6.8 52.7 59.8 522 21.8 8.5 55.5 51.1 285 28.2 8.2 55.7 62.4 83 28.1 8.0 52.0 64.7 463 30.6 10.9 69.4 52.4 107 27.4 7.2 46.8 68.4 356 39.0 15.2 57.1 46.6 319 23.5 5.5 35.4 65.9 325 29.1 9.5 56.5 56.5 1,637 28.4 7.0 49.5 63.4 671 26.9 12.2 54.3 64.4 523 18.5 8.3 53.3 45.2 284 35.1 8.2 56.1 51.1 484 40.6 12.3 62.5 53.6 122 30.3 10.3 60.4 55.5 1,272 20.1 5.3 39.0 64.4 444 28.2 8.9 53.0 58.0 1,962 11.3.3 DISCUSSION OF HIV/AIDS IN THE MEDIA Women and men were asked whether they think it is acceptable for AIDS to be discussed on the radio or television or published in a newspaper. Table 11.6 shows that respondents overwhelmingly accept the use of mass media in transmitting information on HIV/AIDS. In general, men are more likely than women to find discussion of HIV/AIDS in the media acceptable. Overall, more than 90 percent of women and 98 percent of men say that discussion of the disease in the mass media is acceptable. For both sexes, there are only minor variations in the acceptance level across subgroups of respondents. Urban and better educated respondents are more likely than other respondents to accept information on HIV/AIDS in the media. Women in the Northern Region show an unexpectedly low level of acceptance. However, the unusually low rates may be due to errors during the interview for selected field teams using the Lugbara and Luo versions of the questionnaire. HIV/AIDS and Other Sexually Transmitted Infections * 177 Table 11.6 Discussion of AIDS in the media Percentage of women and men who think that discussion of AIDS in the media is acceptable, by media type and background characteristics, Uganda 2000-2001 ________________________________________________________________________________________________________________ Women Men ___________________________________________ __________________________________________ Discussion of AIDS Discussion of AIDS AIDS is acceptable in: is not AIDS is acceptable in: is not ________________________ acceptable _______________________ acceptable Background Tele- News- in any Tele- News- in any characteristic Radio vision paper media Number Radio vision paper media Number ________________________________________________________________________________________________________________ Age 15-19 20-24 25-29 30-39 40-49 Marital status Married or in union Divorced, separated, widowed Never married Ever had sex Never had sex Residence Urban Rural Region Central Eastern Northern Western Education No education Primary Secondary+ Total 90.0 90.1 90.5 9.0 1,615 97.4 96.2 96.9 2.3 441 92.3 91.5 92.0 7.3 1,504 99.1 99.1 99.6 0.4 321 90.9 90.5 91.2 8.3 1,341 97.8 97.8 97.3 2.2 310 90.6 89.8 90.2 8.9 1,793 98.2 97.4 97.6 1.7 522 89.2 89.0 88.6 10.3 993 96.9 96.1 96.4 3.1 285 na na na na na 98.5 93.4 98.5 1.5 83 89.9 89.4 89.9 9.3 4,881 98.0 97.3 97.7 1.9 1,180 92.4 92.2 91.9 7.3 910 98.9 98.9 97.4 1.1 107 96.3 95.6 95.9 3.7 608 98.2 97.7 98.2 1.4 356 89.1 89.1 89.6 9.9 848 96.9 95.2 96.5 2.7 319 96.9 96.5 96.7 3.0 1,207 99.4 99.0 99.5 0.5 325 89.4 89.0 89.4 9.8 6,039 97.7 96.7 97.2 2.2 1,637 99.3 98.8 99.1 0.7 2,341 99.6 99.0 99.4 0.4 671 99.0 98.8 98.9 1.0 1,956 97.2 95.6 96.4 2.5 523 49.8 50.4 51.2 46.5 1,158 93.2 91.9 93.2 6.4 284 96.8 95.5 95.9 3.0 1,792 99.3 99.2 98.8 0.7 484 83.8 83.8 84.4 14.8 1,584 93.3 93.3 93.3 6.7 122 91.6 90.9 91.2 7.9 4,330 97.7 96.7 97.1 2.2 1,272 96.0 95.9 96.0 4.0 1,331 99.3 98.9 99.4 0.3 444 90.7 90.3 90.6 8.7 7,246 97.9 97.1 97.6 1.9 1,962 ________________________________________________________________________________________________________________ na = Not applicable 11.4 KNOWLEDGE OF SYMPTOMS OF SEXUALLY TRANSMITTED INFECTIONS Sexually transmitted infections have been identified as cofactors in HIV/AIDS transmission. The National Strategic Plan for HIV/AIDS prevention set a goal of reducing STIs by 25 percent by 2006. To achieve this goal, it is important for the population to know about STIs, their signs and symptoms, and treatment. People who do not know the symptoms of the disease may fail to recognise it and consequently may not get treatment. Tables 11.7.1 and 11.7.2 show the respondents’ knowledge of STIs and whether they know of any symptoms. Although the majority of the population know about STIs, this awareness is not translated into functional knowledge such as knowledge of symptoms. Forty-seven percent of women and 25 percent of men either have no knowledge of STIs at all or are unable to recognise any symptoms of STIs in a man. Among women, 64 percent know of some symptoms of a female 178 * HIV/AIDS and Other Sexually Transmitted Infections Table 11.7.1 Knowledge of symptoms of STIs: women Percent distribution of women by knowledge of symptoms associated with sexually transmitted infections (STIs) in a man or a woman, according to background characteristics, Uganda 2000-2001 ______________________________________________________________________________________________________________ Knowledge of Knowledge of symptoms of STIs in a man symptoms of STIs in a woman No _________________________________ _________________________________ Background knowledge Two Two characteristic of STIs None One or more Total None One or more Total Number ______________________________________________________________________________________________________________ Age 15-19 20-24 25-29 30-39 40-49 Marital status Married or in union Divorced, separated, widowed Never married Ever had sex Never had sex Residence Urban Rural Region Central Eastern Northern Western Education No education Primary Secondary+ Total 33.7 28.5 17.7 20.1 100.0 20.4 18.3 27.5 100.0 1,615 17.1 30.1 21.9 30.9 100.0 17.3 19.2 46.4 100.0 1,504 14.6 29.6 19.6 36.2 100.0 16.7 19.2 49.4 100.0 1,341 11.8 28.0 19.7 40.5 100.0 16.6 18.6 53.0 100.0 1,793 13.3 25.0 19.0 42.7 100.0 16.1 16.6 54.0 100.0 993 16.5 28.2 19.6 35.7 100.0 17.1 18.4 48.0 100.0 4,881 10.8 30.8 21.5 37.0 100.0 18.0 19.9 51.4 100.0 910 18.6 30.9 18.3 32.1 100.0 17.7 17.4 46.2 100.0 608 38.5 25.4 18.3 17.9 100.0 19.5 18.4 23.6 100.0 848 9.9 26.4 21.7 42.0 100.0 12.9 18.3 58.9 100.0 1,207 20.2 28.8 19.2 31.8 100.0 18.5 18.5 42.7 100.0 6,039 13.1 28.2 21.3 37.5 100.0 14.3 15.7 56.9 100.0 2,341 21.1 24.2 19.0 35.7 100.0 14.9 21.4 42.6 100.0 1,956 25.5 25.8 18.0 30.7 100.0 14.5 20.4 39.7 100.0 1,158 18.3 35.1 19.1 27.5 100.0 26.8 17.8 37.2 100.0 1,792 29.0 27.5 16.0 27.4 100.0 19.5 16.0 35.5 100.0 1,584 8.4 29.5 20.2 31.9 100.0 17.9 19.9 43.8 100.0 4,330 6.4 25.9 21.9 45.8 100.0 14.3 16.8 62.5 100.0 1,331 18.5 28.4 19.6 33.5 100.0 17.6 18.5 45.4 100.0 7,246 STI (19 percent know one symptom and 45 percent know at least two). Thirty-six percent either have no knowledge of any STIs or are unable to recognise any symptoms of an STI in a woman. Women are less knowledgeable of STI symptoms in men than in women (53 percent). These women are vulnerable because they may not know when to take precautions in protecting themselves. Knowledge of symptoms of STIs among men is generally higher than among women. Table 11.7.2 shows that 54 percent of men know at least two or more STI symptoms in men, 21 percent know of one symptom, and 14 percent do not know any symptoms at all. Although the level of knowledge about signs and symptoms of STIs varies across subgroups of respondents, the most important factors are respondents’ age and whether they have ever had sex. Respondents in the youngest age group and those who have never had sex are the least likely to know of STI symptoms. On the other hand, knowledge is high among older respondents and ever-married and better educated women and men. HIV/AIDS and Other Sexually Transmitted Infections * 179 Table 11.7.2 Knowledge of symptoms of STIs: men Percent distribution of men by knowledge of symptoms associated with sexually transmitted infections (STIs) in a man, according to background characteristics, Uganda 2000-2001 ________________________________________________________________________________ Knowledge of symptoms of STIs in a man No ___________________________ Background knowledge Two characteristic of STIs None One or more Total Number ________________________________________________________________________________ Age 15-19 20-24 25-29 30-39 40-49 50-54 Marital status Married or in union Divorced, separated, widowed Never married Ever had sex Never had sex Residence Urban Rural Region Central Eastern Northern Western Education No education Primary Secondary+ Total 30.3 20.9 18.5 30.3 100.0 441 6.1 14.8 29.5 49.6 100.0 321 5.2 14.5 22.5 57.8 100.0 310 5.8 10.4 18.9 65.0 100.0 522 4.5 10.2 18.2 66.9 100.0 285 5.9 14.0 7.1 73.0 100.0 83 5.3 11.8 19.5 63.4 100.0 1,180 1.5 14.0 24.0 60.4 100.0 107 12.2 16.2 23.7 48.0 100.0 356 34.3 21.2 19.7 24.7 100.0 319 8.4 13.5 22.6 55.4 100.0 325 11.6 14.4 20.1 53.9 100.0 1,637 14.8 11.7 23.9 49.6 100.0 671 8.5 11.1 16.9 63.3 100.0 523 6.1 15.8 21.5 56.6 100.0 284 11.5 20.1 19.2 49.2 100.0 484 23.9 16.4 18.5 41.2 100.0 122 13.3 15.9 21.4 49.5 100.0 1,272 3.5 11.8 19.6 65.0 100.0 444 11.1 14.2 20.5 54.2 100.0 1,962 11.5 REPORTS OF RECENT SEXUALLY TRANSMITTED INFECTIONS The 2000-2001 UDHS obtained data on the prevalence of STIs from responses to the question, “During the last 12 months, have you had a sexually transmitted disease?” This question was asked of respondents who had ever had sexual intercourse. Tables 11.8.1 and 11.8.2 show that 8 percent of women and 3 percent of men reported having had an STI in the 12 months preceding the survey. Given the low level of knowledge about symptoms of STIs, many people may have STIs without knowing it. Therefore, the true level of prevalence of STIs could be higher than the reported one. The rate in 2000-2001 for women is higher than in 1995 (4 percent), but for men, it is lower than in 1995 (6 percent). 180 * HIV/AIDS and Other Sexually Transmitted Infections Table 11.8.1 Self-reporting of sexually transmitted infections and STI symptoms: women Among women who have ever had sex, the percentage who report having an STI and/or associated symptoms in the 12 months preceding the survey, according to background characteristics, Uganda 2000-2001 _________________________________________________________________________________________ Percentage Percentage Percentage with with with STI, or Background Percentage genital genital sore discharge, or characteristic with an STI discharge or ulcer sore/ulcer Number1 _________________________________________________________________________________________ Age 15-19 20-24 25-29 30-39 40-49 Marital status Married or in union Divorced, separated, widowed Never married, ever had sex Residence Urban Rural Region Central Eastern Northern Western Education No education Primary Secondary+ Total 7.2 7.1 7.9 13.3 841 8.0 11.5 10.5 17.5 1,448 7.8 11.8 9.9 17.3 1,333 7.4 12.2 11.0 17.6 1,785 7.0 9.8 8.7 15.4 991 7.3 10.7 9.7 16.4 4,881 9.7 14.0 11.2 19.3 910 6.2 8.3 9.0 14.5 608 11.2 12.9 13.8 22.6 1,041 6.8 10.5 9.1 15.4 5,357 13.0 16.5 16.5 25.8 2,067 4.1 8.9 8.0 13.7 1,777 5.2 6.1 5.0 9.9 1,014 5.7 8.8 6.4 12.0 1,541 4.7 7.1 6.5 11.2 1,538 8.1 12.5 10.9 17.9 3,781 9.4 10.8 11.2 19.6 1,079 7.5 10.9 9.9 16.6 6,398 ________________________________________________________________________________________ 1 Includes one woman with missing information on education. Tables 11.8.1 and 11.8.2 also show that 11 percent of the women report having had an abnormal genital discharge, 10 percent report having had genital sores or ulcers, and 17 percent report having had one or more of the symptoms. Among men, 1 percent report having had an abnormal discharge, 3 percent report having had genital sores or ulcers, and 6 percent report having had at least one of the symptoms. Women in urban areas, in the Central Region, and with some education are more likely to report having had an STI. Men show very small differences in the prevalence of STIs and their symptoms. HIV/AIDS and Other Sexually Transmitted Infections * 181 Table 11.8.2 Self-reporting of sexually transmitted infections and STI symptoms: men Among men who have ever had sex, the percentage who report having an STI and/or associated symptoms in the 12 months preceding the survey, according to background characteristics, Uganda 2000-2001 _________________________________________________________________________________________ Percentage Percentage Percentage with with with STI, or Background Percentage genital genital sore discharge, or characteristic with an STI discharge or ulcer sore/ulcer Number _________________________________________________________________________________________ Age 15-19 20-24 25-29 30-39 40-54 50-54 Current marital status Married or living together Divorced, separated, widowed Never married, ever had sex Residence Urban Rural Region Central Eastern Northern Western Education No education Primary Secondary+ Total 2.2 0.2 0.8 2.7 171 3.3 2.2 4.6 7.4 281 4.8 0.7 4.1 7.0 304 3.0 1.4 2.7 5.2 520 2.0 1.8 3.1 4.4 285 1.6 1.8 1.6 5.1 83 3.1 1.3 3.1 5.5 1,180 2.4 1.4 2.4 3.8 107 3.3 1.9 3.5 5.9 356 4.2 0.7 4.0 6.0 277 2.8 1.5 2.9 5.4 1,365 2.9 0.8 4.1 5.6 559 3.4 2.1 2.1 5.3 469 1.0 0.0 0.5 1.5 243 4.2 2.2 4.5 8.1 372 3.5 1.6 5.8 7.7 116 3.5 1.5 2.9 5.5 1,037 2.1 1.1 3.0 5.4 370 3.1 1.4 3.1 5.5 1,643 11.6 TREATMENT SEEKING AND PROTECTION OF A PARTNER FROM SEXUALLY TRANSMITTED INFECTIONS Respondents who reported having an infection or STI symptoms in the 12 months preceding the survey were asked whether they sought advice or treatment. Table 11.9 shows that among women who reported having an STI in the last 12 months, 61 percent sought some form of treatment. More than half of these women went to a medical facility or a doctor (55 percent), 16 percent obtained advice or treatment from a pharmacy or a shop, and 16 percent got advice from a friend or relative. Younger women, women who are formerly married, urban women, women who live in the Central Region, and better educated women are more likely to go to a medical facility for treatment. The number of men who reported having an infection in the 12 months preceding the survey is too small to be presented in detail by background characteristics. Hence, findings for men are presented at the bottom of the table. In general, men are more likely than women to seek advice or treatment (70 percent). The majority of men go to a medical facility (64 percent) for treatment 182 * HIV/AIDS and Other Sexually Transmitted Infections Table 11.9 Source of treatment of STIs Percentage of women who reported an STI and/or associated symptoms in the 12 months preceding the survey, by source of treatment or advice and background characteristics, and the percentage of men who reported an STI and/or associated symptoms in the 12 months preceding the survey, by source of treatment or advice, Uganda 2000-2001 ___________________________________________________________________________________________________ Advice or Advice or medicine Advice treatment from from from No Background Clinic/ Traditional pharmacy friends or any advice or characteristic hospital healer or shop relatives source treatment Number ___________________________________________________________________________________________________ Age 15-19 20-24 25-29 30-39 40-49 Marital status Married or in union Divorced, separated, widowed Never married, ever had sex Residence Urban Rural Region Central Eastern Northern Western Education No education Primary Secondary+ Total women Men 59.2 5.6 18.8 19.4 65.7 34.1 111 56.8 8.4 14.2 14.0 61.9 36.5 253 57.7 4.8 17.3 17.3 61.8 36.0 230 52.2 6.3 15.7 15.0 60.1 37.5 315 47.3 6.8 16.8 15.5 53.2 42.3 153 53.5 5.9 15.6 14.5 59.7 38.0 799 60.4 8.3 18.0 18.4 65.6 32.5 175 51.9 8.5 17.5 22.0 57.8 39.8 88 63.4 5.6 23.2 18.9 67.7 29.9 235 52.0 6.7 14.2 14.9 58.4 39.4 827 62.2 8.5 17.4 18.4 67.2 30.6 534 41.5 4.1 17.2 16.7 48.9 49.0 243 39.2 8.2 7.7 3.4 46.7 49.1 101 57.7 2.8 15.9 13.8 63.8 34.6 184 47.4 8.1 14.5 12.7 55.9 42.3 173 52.5 6.4 14.2 15.1 58.6 38.6 678 66.7 5.5 24.1 20.5 70.4 29.0 211 54.5 6.5 16.2 15.8 60.5 37.3 1,062 64.3 11.7 30.5 27.3 69.9 28.3 90 or a pharmacy or shop (31 percent). Twenty-seven percent of men consult their friends or relatives for advice. Men are also more likely than women to seek help from a traditional healer (12 percent compared with 7 percent). Respondents who reported having an STI in the preceding 12 months were asked whether they informed their sexual partners. Table 11.10 shows that half of the women informed their partners; 37 percent of women reported having no partner or have missing information. Women 20-29 years, women in union, urban women, and more educated women are more likely to inform their partners. When asked whether they did anything to avoid infecting partners, 52 percent did not take any action, 38 percent took some action, and 7 percent had a partner who was already infected. Among those who took some action, use of medicines was most prevalent (33 percent), followed by abstaining from sexual relations (26 percent). The use of condoms was the least common (6 percent). HIV/AIDS and Other Sexually Transmitted Infections * 183 Table 11.10 Protection of partner by women with an STI Percent distribution of women and men who had an STI and/or associated symptoms in the 12 months preceding the survey by whether they informed their partner of their condition, and percentage who took actions to protect partner from infection, according to selected background characteristics (for women only), Uganda 2000-2001 _________________________________________________________________________________________________________________________ Informed partner(s) Actions taken to protect partner _______________________ _____________________________________________________________ No Stopped Partner Background Some/ partner/ having Used Take Any No already characteristic Yes not all No missing Total sex condoms medicine action action infected Number _____________________________________________________________________________________________________________________________ Age 15-19 20-24 25-29 30-39 40-49 Marital status Married or in union Divorced, separated, widowed Never married, ever had sex Residence Urban Rural Region Central Eastern Northern Western Education No education Primary Secondary+ Total women Men 49.3 1.1 15.2 34.3 100 .0 28.3 12.5 38.0 44.5 45.3 8.3 111 56.7 1.0 5.8 36.5 100 .0 30.9 8.3 38.0 45.6 45.7 5.5 253 51.1 1.3 11.6 36.0 100 .0 25.7 6.5 34.2 38.1 53.4 6.0 230 49.5 0.9 12.1 37.5 100 .0 23.6 4.5 30.8 35.1 55.0 5.9 315 43.3 0.3 14.1 42.3 100 .0 22.0 0.6 24.1 27.8 56.1 13.1 153 55.3 0.4 6.3 38.1 100 .0 26.2 4.2 33.3 38.1 50.8 7.7 799 39.4 2.6 25.5 32.5 100 .0 24.3 7.6 31.3 35.8 56.7 4.9 175 31.1 3.0 26.1 39.8 100 .0 28.4 20.5 34.7 44.0 48.5 5.8 88 53.9 1.7 14.4 30.0 100 .0 29.3 11.9 40.0 47.1 46.0 4.5 235 49.7 0.8 10.1 39.4 100 .0 25.2 4.5 31.1 35.7 53.2 7.8 827 54.3 1.5 13.6 30.7 100 .0 28.6 8.3 37.7 44.6 50.2 4.1 534 41.6 0.9 8.5 49.0 100 .0 20.1 3.1 22.9 26.3 60.2 11.1 243 40.8 0.0 10.1 49.1 100 .0 22.3 0.5 18.2 23.8 51.5 12.7 101 57.5 0.0 7.9 34.6 100 .0 28.6 6.8 41.1 43.2 44.3 7.4 184 44.6 1.3 11.8 42.3 100 .0 21.9 2.5 23.9 27.8 59.2 10.4 173 50.4 0.5 10.5 38.6 100 .0 25.1 5.3 32.1 37.6 52.3 6.7 678 56.3 2.2 12.3 29.2 100 .0 32.7 11.7 43.5 48.5 43.0 5.8 211 50.7 1.0 11.1 37.3 100 .0 26.1 6.1 33.1 38.2 51.6 7.1 1,062 63.2 1.6 28.2 7.2 100 .0 26.9 15.9 34.7 42.4 30.2 11.7 90 Due to the small number of men who reported having an STI, data for men are not specified by background characteristics and are presented at the bottom of Table 11.10. Men are more likely than women to say that they informed their sexual partners about STIs. They are also slightly more likely than women to protect their partners (42 percent of men take some action compared with 38 percent of women). It is interesting to note that men are more than twice as likely as women to report the use of condoms (16 percent compared with 6 percent). 11.7 SEXUAL BEHAVIOUR The sexual behaviour of an individual greatly affects the chances of getting infected with an STI. In this section, two aspects of sexual behaviour are studied: number of sexual partners and use of condoms for STI prevention. 11.7.1 NUMBER OF SEXUAL PARTNERS Information on sexual behaviour is important in designing and monitoring intervention programmes to control the spread of STIs. The 2000-2001 UDHS included questions on the respondents’ last three sexual partners in the 12 months preceding the survey. Two types of 184 * HIV/AIDS and Other Sexually Transmitted Infections Table 11.11 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, by background characteristics, Uganda 2000-2001 ____________________________________________________________________________________________________________ Number of sexual partners excluding spouse or cohabiting partner ____________________________________________________________________________________ Women Men Background ______________________________________________ ____________________________________________ characteristic 0 1 2+ Total Number 0 1 2+ Total Number _________________________________________________________________________________________________________________________ Age 15-19 20-24 25-29 30-39 40-49 50-54 Residence Urban Rural Region Central Eastern Northern Western Education No education Primary Secondary+ Total 97.0 2.9 0.1 100.0 466 77.0 23.0 0.0 100.0 28 97.0 2.9 0.1 100.0 1,150 85.7 13.2 1.1 100.0 139 97.2 2.8 0.0 100.0 1,078 81.4 15.2 3.4 100.0 237 97.9 2.0 0.1 100.0 1,459 89.0 8.0 3.0 100.0 453 98.0 1.6 0.3 100.0 728 93.2 6.2 0.6 100.0 252 na na na na na 93.9 3.4 2.7 100.0 72 97.1 2.8 0.1 100.0 636 80.9 15.5 3.6 100.0 148 97.5 2.4 0.1 100.0 4,245 89.0 8.9 2.1 100.0 1,032 95.7 4.3 0.0 100.0 1,377 83.9 12.0 4.1 100.0 322 97.8 1.9 0.2 100.0 1,487 87.5 9.9 2.6 100.0 344 97.2 2.6 0.2 100.0 823 92.5 7.2 0.2 100.0 209 99.1 0.8 0.0 100.0 1,194 89.8 8.9 1.4 100.0 305 97.3 2.3 0.3 100.0 1,264 96.2 2.4 1.4 100.0 92 97.7 2.3 0.0 100.0 2,978 88.7 9.2 2.1 100.0 781 96.6 3.3 0.1 100.0 639 84.2 12.6 3.2 100.0 220 97.4 2.4 0.1 100.0 4,881 88.0 9.7 2.3 100.0 1,180 _________________________________________________________________________________________________________________________ Note: Total iIncludes one woman with missing information on education. na = Not applicable partners are recognised: those who are cohabiting with the respondent (mostly spouses) and those who are not cohabiting with the respondent at the time of the last sexual encounter. Male respondents were 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. Table 11.11 shows that 97 percent of married women say they had no sexual partner other than their spouse or cohabiting partner in the 12 months preceding the survey. Two percent say they only had one partner other than their spouse or cohabiting partner, and almost none had two or more partners. Differences by background characteristics are negligible. Married men, however, are more likely than married women to have multiple partners. Overall, 12 percent of married men have had one or more partners other than their spouse or cohabiting partner in the previous year. The practice of having extramarital partners is common among younger married men (age 15-30), men living in urban areas, men in the Central Region, and better educated men. HIV/AIDS and Other Sexually Transmitted Infections * 185 Table 11.12 Number of sexual partners: unmarried women and men Percent distribution of unmarried women by number of persons with whom they had sexual intercourse in the 12 months preceding the survey, according to background characteristics, Uganda 2000-2001 ____________________________________________________________________________________________________________ Number of sexual partners ________________________________________________________________________________________ Women Men __________________________________________ __________________________________________ Don’t Don't Background know/ know/ characteristic 0 1 2+ missing Total Number1 0 1 2+ missing Total Number ____________________________________________________________________________________________________________ Age 15-19 20-24 25-29 30-39 40-49 50-54 Marital status Divorced, separated, widowed Never married Residence Urban Rural Region Central Eastern Northern Western Education No education Primary Secondary+ Total 77.8 20.5 1.7 0.0 100.0 1,149 77.8 17.2 4.8 0.1 100.0 413 53.0 44.8 1.8 0.4 100.0 354 49.0 30.8 20.2 0.0 100.0 182 65.4 31.9 2.7 0.0 100.0 263 43.7 35.5 20.8 0.0 100.0 73 69.9 27.4 2.7 0.0 100.0 334 61.0 22.3 16.7 0.0 100.0 70 80.8 17.2 (2.0) (0.0) 100.0 265 (60.3) (29.0) (10.7) (0.0) 100.0 33 na na na na na na * * * * 100.0 11 70.9 26.9 2.2 0.0 100.0 910 59.0 28.5 12.5 0.0 100.0 107 72.5 25.5 1.9 0.1 100.0 1,456 66.4 22.6 11.0 0.0 100.0 675 64.6 32.4 3.0 0.0 100.0 571 49.6 32.2 18.0 0.3 100.0 177 74.2 24.0 1.7 0.1 100.0 1,794 70.0 20.8 9.2 0.0 100.0 605 66.2 30.4 3.2 0.2 100.0 964 53.7 29.0 17.4 0.0 100.0 349 69.3 29.5 1.2 0.0 100.0 468 66.8 24.7 8.2 0.3 100.0 179 82.1 16.3 1.6 0.0 100.0 335 73.5 21.6 4.9 0.0 100.0 75 77.3 21.7 1.0 0.0 100.0 597 83.4 12.0 4.6 0.0 100.0 179 77.4 21.2 1.4 0.0 100.0 320 (59.5) (35.4) (5.1) (0.0) 100.0 30 74.4 23.8 1.8 0.0 100.0 1,352 69.5 19.3 11.2 0.0 100.0 491 64.5 32.5 2.8 0.2 100.0 692 58.6 30.6 10.6 0.2 100.0 224 71.9 26.0 2.0 0.1 100.0 2,365 65.4 23.4 11.2 0.1 100.0 782 ____________________________________________________________________________________________________________ Note: Figures in parentheses are based on 25-49 unweighted cases. An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. 1 Includes one woman with missing information on education. na = Not applicable The same questions were asked of respondents who are not currently married. Table 11.12 shows that 72 percent of unmarried women did not have any sexual partner in the 12 months preceding the survey, 26 percent had only one sexual partner, and 2 percent had two or more partners. Unmarried men are also less likely than women to have had no partner (65 percent and 72 percent, respectively) and are much more likely to report having had multiple partners (11 percent compared with 2 percent). Men in their twenties are the most likely to report having had more than one sexual partner in the previous 12 months. The practice of having multiple partners is also more common among respondents who live in urban areas or in the Central Region. 186 * HIV/AIDS and Other Sexually Transmitted Infections Table 11.13 Payment for sexual relations Among men who have had sexual intercourse in the last 12 months, percentage who paid for sex in the 12 months preceding the survey, by background characteristics, Uganda 2000-2001 ____________________________________________ Percent who Background have paid characteristic for sex Number ____________________________________________ Age 15-24 25-34 35-54 Marital status Married or in union Divorced, separated, widowed Never married, ever had sex Residence Urban Rural Region Central Eastern Northern Western Education No education Primary Secondary+ Alcohol consumption (last 30 days) Has not been drunk Has been drunk DISH/CREHP districts DISH I Mbarara and Ntungamo II Masaka, Rakai, and Sembabule III Luwero, Masindi, and Nakasongola IV Kamuli and Jinja V Kampala CREHP (Kisoro, Kabale, and Rukungiri Neither Total 2.3 354 2.3 547 0.5 547 0.8 1,163 5.3 55 4.9 229 2.1 237 1.5 1,211 1.4 485 0.9 398 0.0 229 3.8 336 0.0 104 1.8 927 1.6 315 1.4 1,039 2.1 407 2.5 426 5.4 88 3.5 105 (0.0) 44 0.0 67 1.9 122 2.4 75 1.1 946 1.6 1,448 11.7.2 PAYMENT FOR SEXUAL RELATION S Male respondents in the 2000-2001 UDHS were asked whether they had paid money in exchange for sex in the last 12 months. Table 11.13 shows that 2 percent of men who have ever had sex in the 12 months preceding the survey reported paying for sex. Younger men (15-34) are more likely than older men to have paid for sex, and married men are much less likely than unmarried men to have recently paid for sex. Men in the Western Region are more likely to have engaged in commercial sex than in other regions. Alcohol consumption does not seem to have a strong relationship with commercial sex. Men who have been drunk at least once in the last 30 days are slightly more likely to have engaged in commercial sex than men who have not been drunk. 11.7.3 CONDOM USE FOR DISEASE PREVENTION Condom use is one of the programmatically emphasised approaches to avoiding STI infection. Therefore, knowledge of, access to, and use of con- doms are essential to controlling the spread of STIs. Knowledge of the male condom was found to be over 80 percent (see Chapter 5). However, Table 11.14 shows that only 55 percent of women know a source of male condoms. The level of knowledge increases with level of education. Knowledge is also higher in urban areas than in rural areas. Wide variations do exist between regions and by marital status. The table further shows that only 38 percent of women say they could get a condom if they wanted. Women age 20-24 years are most likely to be able to get a condom. Other variations are similar to those observed in the knowledge of where to get a condom. HIV/AIDS and Other Sexually Transmitted Infections * 187 Table 11.14 Knowledge of source of male condoms and access to condoms Percentage of women who know a source for male condoms and the percentage who think they themselves could get a male condom, by background characteristics, Uganda 2000-2001 __________________________________________________________________ Know a source Could Background for male get a characteristic condoms condom Number __________________________________________________________________ Age 15-19 20-24 25-29 30-39 40-49 Current marital status Never married (never had sex) Ever had sex Never had sex Married or living together Divorced, separated, widowed Residence Urban Rural Region Central Eastern Northern Western Education No education Primary Secondary+ Total 53.1 32.3 1,615 62.1 47.1 1,504 58.1 42.0 1,341 51.3 34.8 1,793 37.7 20.9 993 57.7 36.6 1,456 77.5 58.9 608 43.6 20.5 848 51.5 35.8 4,881 56.2 37.9 910 85.0 61.9 1,207 47.0 31.1 6,039 83.5 59.3 2,341 48.7 32.4 1,956 20.3 13.6 1,158 40.3 25.0 1,792 27.1 16.1 1,584 52.6 34.6 4,330 87.0 65.4 1,331 53.3 36.2 7,246 Tables 11.15.1 and 11.15.2 show that overall, use of condoms is low (7 percent of women and 15 percent of men). However, there is a wide gap between condom use with a spouse/cohabiting partner and with a noncohabiting partner. It is encouraging that 38 percent of women and 59 percent of men report that a condom was used the last time they had sex with a noncohabiting partner. Use of condoms among women with noncohabiting partners was high, especially among those with secondary education (61 percent) and those in urban areas (58 percent). Condom use was also moderately high among women age 15-19 (50 percent), those who have never married but have had sex (50 percent), and women in the Central Region (49 percent). Use of condoms among men with noncohabiting partners is high among men in their early twenties (71 percent), those in urban areas (81 percent), and those with some secondary education (72 percent). 188 * HIV/AIDS and Other Sexually Transmitted Infections Table 11.15.1 Use of condoms by type of partner: women Percentage of women who have had sexual intercourse in the past year who used a condoms during last sexual intercourse with spouse or cohabiting partner, with non-cohabiting partner, and with any partner, by background characteristics, Uganda 2000-2001 _______________________________________________________________________________________________ Spouse or cohabiting partner Non-cohabiting partner Any partner Background ____________________ ____________________ ____________________ characteristic Percentage Number Percentage Number Percentage Number _______________________________________________________________________________________________ Age 15-19 20-24 25-29 30-39 40-49 50-54 Marital status Married or in union Divorced, separated, widowed Never married, ever had sex Residence Urban Rural Region Central Eastern Northern Western Education No education Primary Secondary+ DISH /CREH P districts DISH CREHP (Kisoro, Kabale, and R uku ngiri) Neither Total 1.9 483 49.6 266 18.8 740 2.8 1,171 36.9 197 7.1 1,351 3.2 1,095 33.9 122 5.7 1,204 2.1 1,447 32.0 132 4.1 1,561 2.3 682 10.2 63 3.0 737 na na na na na na 2.2 4,663 24.2 123 2.3 4,735 10.0 192 26.5 263 18.9 444 na na 49.6 393 47.5 415 6.9 653 58.4 219 19.3 863 1.9 4,224 29.7 561 4.7 4,731 5.3 1,407 49.1 383 13.9 1,767 1.6 1,458 37.2 173 4.8 1,603 1.1 794 14.8 82 2.4 871 1.4 1,218 21.0 141 3.4 1,353 0.6 1,226 18.8 105 1.5 1,312 2.1 3,001 27.9 408 4.8 3,377 8.3 650 60.6 265 22.8 904 3.4 1,339 45.3 299 10.6 1,621 0.3 295 (9.2) 19 0.9 312 2.4 3,243 34.0 461 5.9 3,661 2.5 4,877 37.8 780 6.9 5,594 _______________________________________________________________________________________________ Note: Total includes one woman with missing information on education na = Not applicable HIV/AIDS and Other Sexually Transmitted Infections * 189 Table 11.15.2 Use of condoms by type of partner: men Percentage of men who have had sexual intercourse in the past year who used a condoms during last sexual intercourse with spouse or cohabiting partner, with non-cohabiting partner, and with any partner, by background characteristics, Uganda 2000-2001 _______________________________________________________________________________________________ Spouse or cohabiting partner Non-cohabiting partner Any partner Background ____________________ ____________________ ____________________ characteristic Percentage Number Percentage Number Percentage Number _______________________________________________________________________________________________ Age 15-19 20-24 25-29 30-39 40-49 50-54 Marital status Married or in union Divorced, separated, widowed Never married, ever had sex Residence Urban Rural Region Central Eastern Northern Western Education No education Primary Secondary+ DISH /CREH P districts DISH CREHP (Kisoro, Kabale, and R uku ngiri) Neither Total (9.2) 28 51.5 97 41.8 120 5.8 141 71.0 113 31.1 235 3.5 230 60.7 85 14.8 273 4.2 454 63.6 76 7.5 484 3.1 248 (36.5) 29 4.7 263 0.0 69 * 9 0.0 74 3.8 1,152 59.7 139 4.7 1,165 * 13 (40.9) 44 32.4 55 na na 61.8 227 61.1 230 7.9 144 80.7 117 37.1 238 3.3 1,026 50.2 293 10.3 1,212 6.2 319 68.4 213 27.4 485 5.8 339 48.8 100 12.3 398 0.2 205 (39.1) 35 4.4 229 1.8 306 53.5 61 6.1 337 3.0 92 * 16 5.6 104 3.1 771 49.6 236 10.7 928 5.4 221 72.2 127 26.5 316 5.0 322 66.0 141 20.8 427 0.0 69 (37.0) 15 2.1 75 3.8 778 56.2 254 12.9 947 3.9 1,169 58.9 410 14.7 1,450 _______________________________________________________________________________________________ Note: Figures in parentheses are based on 25-49 unweighted cases An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. na = Not applicable 11.8 TESTING FOR HIV In the 2000-2001 UDHS, respondents were asked whether they had ever been tested for HIV Those who were tested were asked whether they got the results. Respondents who had never been tested were asked whether they would like to be tested and whether they know a place to get tested. Tables 11.16.1 and 11.16.2 present the findings of these queries. Eight percent of women and 12 percent of men report that they have been tested for HIV. Women in their twenties and men age 25-39 are the most likely to have had the test. This test is much more common among respondents living in urban areas, in the Central Region, and in Kampala District as well as among those who have secondary education. 190 * HIV/AIDS and Other Sexually Transmitted Infections Table 11.16.1 HIV/AIDS tests: women Percent distribution of women who have been tested for the AIDS virus, the percent distribution among women not tested but who want to be tested, the percent distribution among women tested by source of testing; and the percentage of women not tested, who know a source for the test, according to background characteristics, Uganda 2000-2001 _____________________________________________________________________________________________________________________________________ Have not been tested ____________________ Among Per- Don't those centage know/ Among those tested, tested, who Number Tested Do not don't source of testing Number per- know a of for the Want want know Number ____________________________ Total of centage source women Background AIDS to be to be of of all all women who got for the not characteristic virus tested tested AIDS Total women Public Private Other Missing sources tested results test tested _____________________________________________________________________________________________________________________________________ Age 15-19 6.0 62.2 29.1 2.8 100.0 1,615 62.8 17.5 0.0 19.7 100.0 96 91.7 26.6 1,518 20-24 11.4 67.8 18.3 2.5 100.0 1,504 59.1 24.6 0.2 16.1 100.0 172 89.9 34.8 1,332 25-29 11.1 64.7 21.9 2.3 100.0 1,341 52.2 24.2 0.0 23.7 100.0 149 91.2 29.9 1,193 30-39 7.6 61.7 27.1 3.6 100.0 1,793 63.1 19.5 0.2 17.2 100.0 137 88.9 26.0 1,656 40-49 5.5 62.0 28.0 4.5 100.0 993 54.8 24.9 2.7 17.6 100.0 55 91.1 24.0 938 Marital status Never married Ever had sex 14.2 68.8 15.5 1.4 100.0 608 52.4 24.3 0.0 23.2 100.0 86 92.6 42.8 522 Never had sex 2.9 52.8 40.5 3.8 100.0 848 (55.3) (12.3) (0.0) (32.3) 100.0 25 90.2 20.3 823 Married or living together 8.3 64.7 23.7 3.2 100.0 4,881 61.1 21.8 0.5 16.6 100.0 407 89.8 27.9 4,474 Divorced, separated, widowed 10.0 64.5 22.9 2.7 100.0 910 53.5 25.2 0.0 21.3 100.0 91 90.7 29.5 819 Residence Urban 22.7 47.3 27.8 2.1 100.0 1,207 55.5 24.7 0.2 19.6 100.0 274 93.2 34.4 933 Rural 5.5 66.9 24.3 3.3 100.0 6,039 61.0 20.3 0.4 18.3 100.0 334 88.1 27.3 5,705 Region Central 16.1 54.1 28.3 1.6 100.0 2,341 55.9 23.2 0.5 20.4 100.0 376 90.7 36.2 1,964 Eastern 5.6 70.1 22.0 2.2 100.0 1,956 64.7 13.6 0.2 21.4 100.0 110 91.0 24.7 1,846 Northern 3.6 73.1 18.2 5.1 100.0 1,158 63.2 28.0 0.0 8.8 100.0 42 86.8 22.1 1,116 Western 4.5 63.0 27.9 4.6 100.0 1,792 60.0 26.5 0.0 13.5 100.0 80 89.7 27.3 1,712 Education No education 2.8 63.1 28.7 5.4 100.0 1,584 (63.0) (19.8) (3.3) (13.8) 100.0 44 78.9 18.1 1,540 Primary 6.4 66.9 24.2 2.5 100.0 4,330 59.5 23.1 0.2 17.2 100.0 278 88.6 27.9 4,051 Secondary + 21.5 53.8 22.6 2.1 100.0 1,331 56.8 21.8 0.0 21.4 100.0 286 93.9 44.8 1,045 DISH/CREHP dis tricts DISH 15.0 55.3 28.0 1.7 100.0 2,077 56.4 22.8 0.2 20.7 100.0 312 90.5 32.2 1,766 I Mbarara and Ntungamo 6.2 61.4 30.2 2.2 100.0 392 78.3 14.2 0.0 7.6 100.0 24 88.7 35.9 368 II Masaka, Rakai and Sembabule 10.1 53.3 36.1 0.5 100.0 486 29.8 29.6 0.7 39.8 100.0 49 74.4 28.0 437 III Luwero, Masindi and Nakasongola 8.3 67.9 21.5 2.3 100.0 240 50.5 38.2 0.0 11.3 100.0 20 93.9 39.2 220 IV Kamuli and Jinja 12.9 67.5 17.1 2.6 100.0 356 66.1 8.9 0.5 24.5 100.0 46 92.3 25.4 310 V Kampala 28.6 40.9 28.9 1.6 100.0 604 58.9 23.9 0.0 17.2 100.0 173 94.5 34.4 431 CREHP (Kisoro, Kabale, and Rukungiri) 3.2 52.8 35.1 8.9 100.0 472 (43.9) (37.5) (0.0) (18.6) 100.0 15 93.5 17.7 457 Neither 6.0 68.4 22.5 3.1 100.0 4,696 61.7 20.9 0.5 16.9 100.0 281 90.1 27.9 4,415 Total 8.4 63.7 24.9 3.1 100.0 7,246 58.5 22.2 0.3 18.9 100.0 608 90.4 28.3 6,638 _____________________________________________________________________________________________________________________________________ Note: Figures in parentheses are based on 25-49 unweighted cases. HIV/AIDS and Other Sexually Transmitted Infections * 191 Table 11.16.2 HIV/AIDS tests: men Percent distribution of men who have been tested for the AIDS virus, the percent distribution among men not tested but who want to be tested, the percent distribution among men tested by source of testing; and the percentage of men not tested, who know a source for the test, according to background characteristics, Uganda 2000-2001 _____________________________________________________________________________________________________________________________________ Have not been tested ____________________ Among Per- Don't those centage know/ Among those tested, tested, who Number Tested Do not don't source of testing Number per- know a of for the Want want know Number ____________________________ Total of centage source men Background AIDS to be to be of of all all men who got for the not characteristic virus tested tested AIDS Total men Public Private Other Missing sources tested results test tested _____________________________________________________________________________________________________________________________________ Age 15-19 20-24 25-29 30-39 40-49 50-54 Marital status Never married Ever had sex Never had sex Married or living together Divorced, separated, widowed Residence Urban Rural Region Central Eastern Northern Western Education No education Primary Secondary + DISH/CREHP dis tricts DISH I Mbarara and Ntungamo II Masaka, Rakai and Sembabule III Luwero, Masindi and Nakasongola IV Kamuli and Jinja V Kampala CREHP (Kisoro, Kabale, and Rukungiri) Neither Total 3.2 69.3 26.3 1.2 100.0 441 * * * * 100.0 14 100.0 41.5 427 12.7 68.9 17.0 1.5 100.0 321 (60.3) (26.9) (10.8) (2.0) 100.0 41 (86.5) 54.1 280 18.5 63.4 17.6 0.6 100.0 310 62.5 18.7 17.2 1.6 100.0 57 95.6 53.4 253 15.5 64.6 17.6 2.3 100.0 522 71.4 18.7 5.8 4.1 100.0 81 90.7 46.6 441 12.4 63.0 23.6 1.0 100.0 285 (66.9) (26.7) (6.4) (0.0) 100.0 35 (96.3) 44.3 249 8.8 51.6 33.7 5.9 100.0 83 * * * * 100.0 7 * 41.7 76 11.7 68.6 19.4 0.2 100.0 356 61.8 17.7 20.5 0.0 100.0 42 92.7 58.4 314 1.5 67.8 28.9 1.7 100.0 319 * * * * 100.0 5 * 37.2 315 14.4 64.2 19.3 2.1 100.0 1,180 66.1 22.4 8.4 3.0 100.0 170 91.9 47.1 1,010 18.1 60.0 20.7 1.2 100.0 107 * * * * 100.0 19 * 40.6 87 19.9 54.1 25.7 0.4 100.0 325 55.6 21.7 21.6 1.1 100.0 65 96.3 66.4 261 10.4 67.6 20.0 1.9 100.0 1,637 69.0 23.2 5.2 2.5 100.0 171 91.6 43.6 1,466 18.5 58.0 22.8 0.7 100.0 671 58.3 27.7 14.0 0.0 100.0 124 95.0 54.4 547 11.3 62.7 24.1 1.9 100.0 523 82.3 8.8 5.7 3.3 100.0 59 89.9 47.3 464 4.7 79.6 13.4 2.3 100.0 284 * * * * 100.0 13 * 26.2 270 8.0 70.2 19.5 2.3 100.0 484 (71.8) (14.8) (5.5) (7.9) 100.0 39 (91.2) 50.3 445 4.2 59.7 30.0 6.1 100.0 122 * * * * 100.0 5 * 30.9 117 8.8 67.9 21.8 1.5 100.0 1,272 67.9 27.2 3.0 1.9 100.0 112 93.0 40.9 1,161 16.4 64.1 18.4 1.1 100.0 444 63.4 23.1 12.5 0.9 100.0 73 87.6 62.9 371 17.5 58.3 23.0 1.2 100.0 582 63.9 19.6 16.6 0.0 100.0 102 94.3 58.3 480 8.9 66.1 22.2 2.8 100.0 115 * * * * 100.0 10 * 53.0 104 12.6 66.1 20.5 0.8 100.0 147 * * * * 100.0 19 * 51.6 129 15.3 63.6 16.8 4.3 100.0 66 * * * * 100.0 10 * (50.4) 56 25.1 56.6 18.3 0.0 100.0 84 80.7 10.0 9.3 0.0 100.0 21 93.8 60.2 63 24.5 45.0 30.5 0.0 100.0 171 51.4 18.9 29.7 0.0 100.0 42 94.6 71.9 129 6.8 72.7 19.3 1.1 100.0 114 * * * * 100.0 8 * 32.9 107 10.0 68.0 20.2 1.9 100.0 1,265 66.5 26.0 4.2 3.3 100.0 126 91.4 43.5 1,139 12.0 65.4 21.0 1.6 100.0 1,962 65.4 22.8 9.7 2.1 100.0 236 92.9 47.0 1,726 _____________________________________________________________________________________________________________________________________ Note: Figures in parentheses are based on 25-49 unweighted cases. An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. 192 * HIV/AIDS and Other Sexually Transmitted Infections Desire to be tested is high in Uganda (see Figures 11.1 and 11.2). This is measured by adding the percentage of women and men who have been tested and those who want to be tested (72 percent of women and 77 percent of men). Respondents living in urban areas, in the Central Region, and those with more education are more likely to have been tested or want to be tested. Desire for HIV testing is also high among women who have never married and have never had sex, formerly married men, and respondents living in Kampala. Of those who have been tested, 59 percent of women and 65 percent of men had the test done in a public facility, and 22 to 23 percent had it done in a private facility. There are small variations in the source of testing by respondents’ background characteristics. HIV/AIDS and Other Sexually Transmitted Infections * 193 Nine in ten women and men who were tested for HIV received the test results. There are small differences in the percentage of respondents who received their HIV status. When asked whether they know where to go to get an AIDS test, 28 percent of women and 47 percent of men who have never been tested said that they could identify a place to get tested. Respondents who have never been married but have had sex and those with some secondary education are more likely than other respondents to know a place to get the AIDS test. 194 * HIV/AIDS and Other Sexually Transmitted Infections Adult Mortality * 195 ADULT MORTALITY 12 In Chapter 8 of this report, estimates of childhood mortality were presented and discussed. Early childhood mortality varies according to social and economic development and thus can be expected to be 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 factors of adult mortality are of interest in Uganda. First, female and male adult mortality in Uganda is not expected to decline in the near term, despite the reported decline in the rate of new HIV infections. Second, mortality related to pregnancy and childbearing (maternal mortality) serves as an important indicator for assessing the status of reproductive health programmes in the country. The 2000-2001 UDHS 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 that occurred 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 In the UDHS, all female respondents were asked to report the total number of siblings born to their natural mother, including the respondent, and to list all of these children, males and females, starting with the first born. The respondent was also asked to report the survival status of each sibling. For surviving siblings, their current age was recorded. For deceased siblings, years since death and age at death were ascertained. For each sister who died at the age of 12 or older, the respondent was asked extra questions to determine whether the death was a maternal death. The questions were as follows: “Was (NAME) pregnant when she died?” “Did (NAME) die during childbirth?” “Did (NAME) die within two months after the end of a pregnancy or childbirth?” Mortality estimates rely on the accuracy and completeness of reporting on siblings and their survival. Table 12.1 shows the number of siblings by sex and survival status and is intended to establish the level of completeness of data on siblings reported by the respondent. Overall, the data on survival status of siblings appear to be reasonably complete; survival status was missing in less than 1 percent of cases. Information on age at death was not reported for 7 percent of siblings who 1The 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. 196 * Adult Mortality Table 12.1 Data on siblings Number of siblings reported by female respondents and completeness of reported data on sibling’s age, age at death (AD), and years since death (YSD), Uganda 2000-2001 _________________________________________________________________________________________ Sisters Brothers Total Sibling status and __________________ _________________ ________________ completeness of reporting Number Percent Number Percent Number Percent __________________________________________________________________________________________ All siblings 23,417 100.0 23,660 100.0 47,077 100.0 Living 18,204 77.7 17,813 75.3 36,017 76.5 Dead 5,166 22.1 5,779 24.4 10,945 23.2 Missing survival status 47 0.2 68 0.3 115 0.2 Living siblings 18,204 100.0 17,813 100.0 36,017 100.0 Age reported 18,071 99.3 17,684 99.3 35,755 99.3 Age missing 133 0.7 129 0.7 262 0.7 Dead siblings 5,166 100.0 5,779 100.0 10,945 100.0 AD and YSD reported 4,424 85.6 4,804 83.1 9,228 84.3 Only AD missing 52 1.0 63 1.1 114 1.0 Only YSD missing 422 8.2 506 8.8 928 8.5 AD and YSD missing 268 5.2 407 7.1 676 6.2 have who died. Furthermore, respondents did not know the years since death for 15 percent of their siblings. Rather than excluding data for 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. From the data in Table 12.1, it is clear that there is little difference in the reporting of information about male and female siblings. The data also show that the quality of data elicited for adult mortality can be considered adequate. 12.2 DIRECT ESTIMATES OF ADULT MORTALITY To have a sufficiently large number of adult deaths to generate a robust estimate, the ten- year period (0-9 years) prior to the survey has been chosen. Estimates of adult mortality rates have been calculated for females and males separately. They were obtained by dividing the respective number of female and male deaths by the number of females and males age 15-49 years who were at risk of death over the study period. Table 12.2 presents age-specific mortality rates for women and men for the ten-year period preceding the survey (roughly 1991 to 2000). This is obtained by dividing the number of deaths in each age group of females and males by the total person-months of exposure to the risk of dying in that age Adult Mortality * 197 Table 12.2 Adult mortality rates Direct estimates of female and male adult mortality rates for the ten- year period preceding the survey by age, Uganda 2000-2001________________________________________________________ 2000-2001 UDHS 1995______________________________ UDHS Mortality mortality Age Deaths Exposure rates1 rates1________________________________________________________ WOMEN ________________________________________________________ 15-19 110 28,651 3.8 3.7 20-24 184 29,315 6.3 6.5 25-29 245 25,661 9.5 8.0 30-34 213 19,388 11.0 10.8 35-39 142 12,578 11.3 10.6 40-44 94 6,914 13.6 9.7 45-49 48 3,399 14.2 15.5 15-49 1,037 125,906 8.6 7.9________________________________________________________ MEN________________________________________________________ 15-19 96 27,256 3.5 2.9 20-24 165 27,961 5.9 5.3 25-29 214 24,706 8.6 10.5 30-34 241 18,946 12.7 14.6 35-39 193 12,567 15.3 13.3 40-44 134 6,971 19.2 18.2 45-49 71 3,494 20.4 19.5 15-49 1,113 121,899 9.7 9.5________________________________________________________ 1Expressed per 1,000 population group during the ten-year period prior to the survey. To obtain these rates, the age-specific death rates were adjusted using the age distribution of the de facto female population age 15-49 obtained from the Household Questionnaire. Data in Table 12.2 show that in general, the level of adult mortality is slightly higher among males than among females (9.7 and 8.6 deaths per 1,000 population). The age-specific mortality rates for females indicate that mortality increases consistently with age from 3.8 deaths per 1,000 for age 15-19 to 14.2 for women age 45-49. Among males, the corresponding figures are 3.5 and 20.4, respectively. Comparison of adult mortality during the ten-year period prior to the 2000-2001 UDHS and adult mortality during the ten-year period prior to the 1995 UDHS indicates that the mortality situation in Uganda has not improved in the past five years. The adjusted general mortality rate was about 8 deaths per 1,000 for women and 10 deaths per 1,000 for men in both periods. Overall, the female adult mortality level in the 2000-2001 UDHS and that recorded in the 1995 UDHS are higher than that estimated from the 1991 Population Census (Statistics Department and Macro International Inc., 1996). The available evidence points to rapidly rising adult mortality during the early to mid-1990s and stabilised or slightly rising mortality thereafter. 2 The standard medical definition of maternal mortality includes the puerperium period, i.e., up to 42 days, not two months postpartum. 3 The rate for the whole age range 15-49 is standardised on the UDHS household age structure. 4 This rate is dif ferent from that presented in the 1995 UDHS report in that this is arrived at using the age- adjusted general fertility rate and the age-adjusted mortality rate. 198 * Adult Mortality Table 12.3 Maternal mortality rates Direct estimates of female maternal mortality for the ten- year period preceding the survey, Uganda 2000-2001______________________________________________ 2000-2001 UDHS 1995_________________________ UDHS Exposure Mortality Mortality Age Deaths years rates1 rates1_____________________________________________ 15-19 12 28,651 0.4 0.8 20-24 29 29,315 1.0 1.0 25-29 52 25,661 2.0 1.4 30-34 33 19,388 1.7 2.2 35-39 20 12,578 1.6 1.8 40-44 8 6,914 1.2 0.6 45-49 2 3,399 0.5 1.0 15-49 155 125,906 1.2 1.3 General fertility rate (GFR) 0.237 0.239 Maternal mortality rate (MMR)2 505 527________________________________________________ 1 Expressed per 1,000 woman-years of exposure 2 Per 100,000 live births; calculated as the maternal mortality rate divided by the general fertility rate. Rate from the 1995 UDHS differs from the published, unadjusted rate. 12.3 MATERNAL MORTALITY Maternal mortality is a fraction of adult female mortality and represents all female deaths that occurred during pregnancy, childbirth, and two months after birth.2 The approach used to compute the maternal mortality results is the same as that 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 ten-year period before the survey, alongside estimates based on the 1995 UDHS data for the same period before that survey. Since the total number of maternal deaths reported in the survey is small (155), detailed study of age-specific maternal mortality is not advised. The preferred approach is to examine the estimate for all childbearing ages combined. For the ten-year period before the survey (centered on late 1995), the rate of mortality due to causes related to pregnancy and childbearing is 1.2 maternal deaths per 1,000 woman-years of exposure.3 The maternal mortality rate is converted to a maternal mortality ratio (MMR) and is expressed per 100,000 live births by dividing the rate by the general fertility rate (0.237) associated with the same period. In this way, the obstetrical risk of pregnancy and childbearing is underlined. Using direct estimation procedures based on the 2000-2001 UDHS survey, the maternal mortality ratio is estimated to be 505 maternal deaths per 100,000 live births applicable to the ten-year period before the survey. Given the large sampling errors inherent in the estima- tion technique, there is virtually no change in the maternal mortality situation in Uganda since 1995 (527 maternal deaths per 100,000 live births).4 While the 2000-2001 UDHS data can also be used to estimate the level of maternal mortality using indirect techniques (the sister- hood method), this estimate is not presented in this report because of its limitations, which make the estimate inferior to the one obtained using direct estimation. A major disadvantage of the indirect estimate is that it refers to a period 10-12 years prior to the survey, more than six years earlier than the reference period of the direct estimate. Hence, it loses its value to measure the impact of short-term pro- grammes. Adult Mortality * 199 This chapter presented the adult mortality rate and the maternal mortality ratio in Uganda for the ten-year period preceding the 2000-2001 UDHS. Adult mortality levels in Uganda remain very high, likely because the continuing impact of the AIDS epidemic. The maternal mortality ratio has also remained at the early 1990s level (505 to 527 deaths per 100,000 live births). 200 * Adult Mortality Table 12.3 Maternal mortality rates Direct estimates of female maternal mortality for the ten- year period preceding the survey, Uganda 2000-2001______________________________________________ 2000-2001 UDHS 1995_________________________ UDHS Exposure Mortality Mortality Age Deaths years rates1 rates1_____________________________________________ 15-19 12 28,651 0.4 0.8 20-24 29 29,315 1.0 1.0 25-29 52 25,661 2.0 1.4 30-34 33 19,388 1.7 2.2 35-39 20 12,578 1.6 1.8 40-44 8 6,914 1.2 0.6 45-49 2 3,399 0.5 1.0 15-49 155 125,906 1.2 1.3 General fertility rate (GFR) 0.237 0.239 Maternal mortality rate (MMR)2 505 527________________________________________________ 1 Expressed per 1,000 woman-years of exposure 2 Per 100,000 live births; calculated as the maternal mortality rate divided by the general fertility rate. Rate from the 1995 UDHS differs from the published, Adult Mortality * 201 References * 201 REFERENCES Adetunji, A. Jacob. 1996. Infant mortality levels in Africa: Does method of estimation matter? Genus 52 (3-4): 89-106. Bothwell, T.H. and R.W. Charlton. 1984. Iron deficiency in women. Report for the International Nutritional Consultative Group (INACG). Central Statistical Office [Zimbabwe] and Macro International Inc. (MI). 2000. Zimbabwe Demographic and Health Survey 1999. Calverton, Maryland: Central Statistical Office and Macro International Inc. Gaspar, Manual da Costa, Humberto A. Cossa, Clara Riberio dos Santos, Rosa Marlene Manjate, and Juan Schoemaker. 1998. Mocambique, Inquérito Demográfico e de Saúde, 1997. Calverton, Maryland, USA: Instituto Nacional de Estatística and Macro International Inc. Ghana Statistical Service (GSS) and Macro International Inc. (MI). 1999. Ghana Demographic and Health Survey 1998. Calverton, Maryland: GSS and MI. Gwatkin R. Davidson, Shea Rustein, Kiersten Johnson, Rohini Pande, and Adam Wagstaff. 2000. Socio-economic differences in health, nutrition, and population in Uganda. The HNP/Poverty Thematic Group. Washington, DC: The World Bank Heise, Lori, Mary Ellsberg, and Megan Gottemoeller. 1999. Ending violence against women. Population Reports, Series L, No. 11. Baltimore, Maryland, USA: Johns Hopkins University School of Public Health, Population Information Program. Kaijuka, Emannuel M., Edward Z.A Kaija, Anne Cross and Edilberto Loaiza. 1989. Uganda Demographic and Health Survey report 1998/99. Columbia, Maryland: IRD/Macro Systems. Kakitahi, J.T. and Olico-Okui. 1991. Iodine deficiency disorders in Kisoro, Bundibugyo, Hoima and Kapchorwa districts: A preliminary report. Unpublished. Kauma, M. and L. Serunjogi. 1991. Kamuli blindness and vitamin A deficiency study. Ministry of Health (MOH), Community Health Department. The national reproductive health policy guidelines for reproductive health services (PP3-4). Kampala, Uganda: MOH. Ministry of Health (MOH) [Uganda]. 1999. The sexual and reproductive health minimum package for Uganda. 1999. Kampala, Uganda: MOH. Ministry of Health (MOH) [Uganda]. 2000. HIV/AIDS surveillance report. Ministry of Health (MOH) [Uganda]. nd. The Reproductive Health Strategic Plan 2000-2004. Kampala, Uganda: MOH. Ministry of Health (MOH) [Uganda]. nd. National Health Policy 1999. Kampala, Uganda: MOH. 202 * References Ministry of Health (MOH) [Uganda]. nd. Health Sector Strategic Plan 2000-2004. Kampala, Uganda: MOH Ministry of Finance Planning and Economic Development (MFPED). nd. Background to the budget 1999-2000. Kampala, Uganda: MFPED. National Council for Population and Development (NCPD), Central Bureau of Statistics (CBS)(Office of the Vice President and Ministry of Planning and National Development)[Kenya], and Macro International Inc. (MI). 1999. Kenya Demographic and Health Survey 1998. Calverton, Maryland: NCPD, CBS, and MI. National Statistical Office [Malawi] and ORC Macro. 2001. Malawi Demographic and Health Survey 2000. Zomba, Malawi and Calverton, Maryland, USA: National Statistical Office [Malawi] and ORC Macro Rutstein, Shea O. and George T. Bicego. 1990. Assessment of the quality of data used to ascertain eligibility and age in the Demographic and Health Surveys. In An assessment of DHS-I data quality. DHS Methodological Reports No.1. Columbia, Maryland: Institute for Resource Development/Macro Systems Inc. Statistics Department, Ministry of Finance and Economic Planning [Uganda]. 1995. The 1991 Population and Housing Census Analytical Report, Vol. 3. Entebbe, Uganda: Statistics Department. Statistics Department [Uganda] and Macro International Inc. 1995. The 1991 Population and Housing Census Analytical Report, Vol. 1: Demographic characteristics. Entebbe, Uganda: Statistics Department. Statistics Department [Uganda] and Macro International Inc. 1996. Uganda Demographic and Health Survey, 1995. Calverton, Maryland: Statistics Department [Uganda] and Macro International Inc. Sullivan, Jeremiah M., Shea O. Rutstein and George T. Bicego. 1994. Infant and child mortality. DHS, Comparative Studies Number 15. Calverton, Maryland: Macro International Inc. Uganda Bureau of Statistics (UBOS). 2001. Uganda National Household Survey 1999/2000: Report on the Socio-Economic Survey. Entebbe, Uganda: UBOS. Uganda AIDS Commission. 2000. The national strategic framework for HIV/AIDS activities in Uganda (2000). Unpublished. UNICEF. 1999. Country program progress report, 1995-2000. Government of Uganda-UNICEF country program. Kampala, Uganda: UNICEF. World Health Organisation (WHO). 1995. Physical status: The use and interpretation of anthropometry. Expert Committee Report. Geneva: WHO. World Health Organisation (WHO). 1997. Iron deficiency: Indicators for assessment and strategies for prevention. WHO/ NUT/96.12. Geneva: WHO. World Health Organisation (WHO). 1999. Violence against women, a priority health issue. WHO/FRH/WHD/97.8. Geneva: WHO. Appendix A * 203 SAMPLE DESIGN APPENDIX A A major objective of the 2000-2001 UDHS is to provide policymakers and programme managers with information necessary for monitoring and evaluating population, health, and nutrition programmes. To achieve this objective, the UDHS collected information on fertility levels, marriage, sexual activity, fertility preferences, awareness and use of family planning methods, and breastfeeding practices. In addition, data were collected on the nutritional status of mothers and young children; infant, child, adult, and maternal mortality; maternal and child health; awareness of and behaviour regarding AIDS and other sexually transmitted infections; and levels of haemoglobin and vitamin A in the blood. The target of the 2000-2001 UDHS sample was to obtain about 6,500 completed interviews with women age 15-49. Using information on response rates and sampling errors from the 1995 UDHS, approximately 7,500 households were selected. In these households, all women age 15-49 were eligible to be interviewed. In every third household selected for the women’s interview, men age 15-54 were also interviewed. A total of 1,800 men’s interviews were expected to be successfully completed. Vitamin A testing was carried out in every other household selected for the male survey (one-sixth of all households). In these households, all women 15-49 and children under five years old were tested. Uganda is divided into 45 administrative districts, which are subdivided into counties, subcounties, and parishes. The subsequent administrative breakdown are counties, subcounties, and parishes. In addition to these administrative units, during the 1991 Population Census, for data collection purposes, each parish was subdivided into statistical areas called enumeration areas (EAs). Therefore, the sample frame of the UDHS was the list of EAs developed for the 1991 Population Census. The primary sampling unit (PSU) for the 2000-2001 UDHS is the EA from this list. SAMPLE ALLOCATION In the UDHS, the number of selected EAs in each district is not allocated proportionally to the district’s total population due to the need to present estimates by urban and rural residence. Because a large proportion of the population resides in rural areas, urban areas have been oversampled to generate unbiased estimates. Districts in the DISH and CREHP projects were also oversampled. Although the 2000-2001 UDHS was planned to be conducted throughout the country, problems related to insecurity in selected areas of the country caused the Gulu, Kitgum, Bundibugyo, and Kabarole districts to be excluded from the survey. The remaining districts cover approximately 7 percent of the total population of Uganda. Furthermore, the 2000-2001 UDHS was also designed to present separate estimates for urban and rural areas and for each of four regions, which are defined in Uganda as follows: Central: Kalangala, Kampala, Kiboga, Luwero, Masaka, Mpigi, Mubende, Mukono, Sembabule, Nakasongola, and Rakai Eastern: Bugiri, Busia, Iganga, Jinja, Kamuli, Kapchorwa, Katakwi, Kumi, Mbale, Pallisa, Soroti, and Tororo Northern: Adjumani, Apac, Arua, Kotido, Lira, Moyo, Moroto, and Nebbi 204 * Appendix A Western: Bushenyi, Hoima, Kabale, Kabarole, Kibaale, Kisoro, Masindi, Mbarara, Ntungamo, and Rukungiri. The sample was also designed to generate estimates for the districts in the USAID-funded DISH project and districts in the CREHP project. These districts are grouped in six subdomains for which specific indicators are presented. To allow for unbiased estimates for these groups, a minimum of 500 completed interviews was targeted for each group. These groups are the following: DISH districts Group I: Mbarara and Ntungamo Group II: Masaka, Rakai, and Sembabule Group III: Luwero, Masindi, and Nakasongola Group IV: Jinja and Kamuli Group V: Kampala CREHP districts: Kabale, Kisoro, and Rukungiri In each group, a minimum of 500 completed interviews with women was targeted to allow for separate estimates. Consequently, data for Kampala District can be presented separately because it has more than the specified minimum number of completed interviews. SAMPLE SELECTION The 2000-2001 UDHS sample was selected using a stratified, two-stage cluster design consisting of a total of 298 EAs (102 in urban areas and 196 in rural areas). Urban areas and districts under the DISH and CREHP projects were oversampled to generate unbiased estimates for this segment of the population. After the number of households was allocated to each district by urban and rural areas, the number of selected households in each EA was calculated based on an average of 25 completed interviews with women 15-49. This is true in all districts except Kampala, where 11 interviews per EA were expected to be completed. In each urban or rural area in the selected district, EAs were selected systematically with probability proportional to the number of households in each EA. The selection is done using the following formula: P1i = (a * Mi) / (3 Mi), where a is the number of EAs to be selected in the urban (or rural) area in the district, Mi is the number of households of the i th EA in the 1991 Population Census, 3 Mi is the number of households in the urban (or rural) area in the district according to the 1991 Population Census. In each selected EA, a complete household listing operation was carried out and households were selected to achieve a self-weighted sampling fraction within each urban (or rural) area in the district. However, since the 2000-2001 UDHS sample is not self-weighting, a final weighting adjustment was calculated for each study domain. Appendix A * 205 After the overall sampling fraction (f) by urban (or rural) area in the district was calculated, and if ci is the number of households selected out of the total number of households (Li) found in the listing process for the ith EA, the self-weighting condition can be expressed as follows: f = P1i * (ci / Li) The final number of households is ci = (f * Li) / P1i and the household selection interval is Ii = Li / ci Ii = P1i / f 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 8,792 potential households were selected, of which 8,231 proved to be actual inhabited households. Of these, the 2000-2001 UDHS fieldwork teams successfully completed interviews in 7,885 households, yielding a household response rate of 96 percent. The main reason for failure to interview was that the teams found no competent respondent at home, despite making at least three call-backs. In total, this accounted for 3 percent of households. The household response rate was highest in the Northern Region and the rural areas (97 percent) and was lowest in the urban areas (92 percent) and the Central Region (94 percent). In the interviewed households, 7,717 eligible women were identified, 94 percent of whom were successfully interviewed. The overall individual women's response rate was 90 percent. This rate varies widely across the urban and rural areas (85 percent and 93 percent, respectively) and across regions, where it ranges between 92 percent in the Northern and Western regions and 86 percent in the Central Region. For eligible men, the overall response rate was lower than for women (81 percent). This rate also has a wider range than that for women (between 72 and 88 percent). 206 * Appendix A Table A.1 Sample implementation: women Percent distribution of households and eligible women in the 2000-2001 Uganda DHS sample by result of the household and individual interview and response rates, according to region and urban-rural residence, Uganda 2000- 2001 _________________________________________________________________________________________________ Region Residence ___________________________________ ________________________ Result Central Eastern Northern Western Urban Rural Total __________________________________________________________________________________________________ Selected households Completed (C) No competent respondent (HP) Postponed (P) Refused (R) Dwelling not found (DNF) Absent (HA) Dwelling vacant (DV) Dwelling destroyed (DD) Total Number of households Household response rate (HRR)1 Eligible women Completed (EWC) Not at home (EWNH) Postponed (EWP) Refused (EWR) Partly completed (EWPC) Incapacitated (EWI) Other (EWO) Total Number of women Eligible woman response rate (EWRR)2 Overall response rate (ORR)3 88.5 90.6 91.8 89.4 85.8 91.6 89.7 4.1 2.9 1.8 2.3 5.5 1.8 3.0 0.1 0.0 0.1 0.0 0.0 0.0 0.0 1.0 0.7 0.7 0.4 1.2 0.5 0.7 0.3 0.0 0.0 0.2 0.4 0.1 0.2 1.7 2.6 1.9 2.2 1.7 2.3 2.1 3.8 2.7 3.5 4.5 5.2 3.0 3.7 0.4 0.5 0.3 1.0 0.3 0.7 0.6 100.0 100.0 100.0 100.0 100.0 100.0 100.0 3,122 2,076 1,155 2,439 2,912 5,880 8,792 94.1 96.1 97.2 96.8 92.4 97.4 95.8 91.7 95.1 94.8 95.2 91.7 95.1 93.9 4.6 2.9 2.8 2.1 4.7 2.5 3.2 0.1 0.0 0.0 0.0 0.0 0.0 0.0 1.9 0.8 0.7 0.8 2.0 0.7 1.2 0.5 0.2 0.5 0.3 0.5 0.3 0.4 0.5 0.6 0.9 1.1 0.6 0.8 0.7 0.7 0.5 0.2 0.6 0.5 0.6 0.6 100.0 100.0 100.0 100.0 100.0 100.0 100.0 2,667 1,858 1,098 2,094 2,636 5,081 7,717 91.7 95.1 94.8 95.2 91.7 95.1 93.9 86.3 91.4 92.2 92.2 84.7 92.6 89.9 ________________________________________________________________________________________________________ Note: The household response rate is calculated for completed households as a proportion of completed, no competent respondent, postponed, refused, and dwelling not found. The eligible woman 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 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 + P + R + DNF 2 Using the number of eligible women falling into specif ic response categories, the eligible woman response rate (EWRR) is calculated as: EWC _________________________________________________ * 100 EWC + EWNH + EWP + EWR + EWPC + EWI + EWO 3 The overall response rate (ORR) is calculated as: ORR = (HRR * EWRR) ÷ 100 Appendix A * 207 Table A.2 Sample implementation: men Percent distribution of households and eligible men in the 2000-2001 Uganda DHS sample by result of the household and individual interview and response rates, according to region and urban-rural residence, Uganda 2000-2001 __________________________________________________________________________________________________ Region Residence ___________________________________ ________________________ Result Central Eastern Northern Western Urban Rural Total __________________________________________________________________________________________________ Selected households Completed (C) No competent respondent (HP) Refused (R) Dwelling not found (DNF) Absent (HA) Dwelling vacant (DV) Dwelling destroyed (DD) Total Number of households Household response rate (HRR)1 Eligible men Completed (EMC) Not at home (EMNH) Postponed (EMP) Refused (EMR) Partly completed (EMPC) Incapacitated (EMI) Other (EMO) Total Number of men Eligible man response rate (EMRR)2 Overall response rate (ORR)3 88.5 91.2 90.1 90.4 86.8 91.4 89.9 4.2 2.8 1.5 2.1 5.3 1.8 2.9 1.4 0.7 1.0 0.7 1.4 0.8 1.0 0.3 0.1 0.0 0.1 0.2 0.2 0.2 2.3 2.3 2.8 1.6 1.8 2.3 2.2 2.8 2.6 4.1 4.3 4.2 2.9 3.3 0.6 0.3 0.5 0.9 0.3 0.7 0.6 100.0 100.0 100.0 100.0 100.0 100.0 100.0 1,051 704 394 822 983 1,988 2,971 93.7 96.1 97.3 96.9 92.6 97.1 95.6 79.9 85.8 90.4 88.9 77.5 88.9 85.1 15.5 9.6 7.3 6.8 17.4 7.3 10.7 0.0 0.2 0.0 0.0 0.0 0.1 0.0 1.3 2.2 1.0 1.1 2.2 1.0 1.4 0.0 0.2 0.0 0.0 0.1 0.0 0.0 0.7 1.1 0.7 1.6 0.8 1.2 1.0 2.6 0.9 0.7 1.5 1.9 1.5 1.6 100.0 100.0 100.0 100.0 100.0 100.0 100.0 847 543 302 614 775 1,531 2,306 79.9 85.8 90.4 88.9 77.5 88.9 85.1 74.9 82.5 87.9 86.1 71.8 86.3 81.4 _____________________________________________________________________________________________________ Note: The household response rate is calculated for completed households as a proportion of completed, no competent respondent, postponed, 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 man 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 man 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 * 209 SAMPLING ERRORS APPENDIX B The estimates from a sample survey are affected by two types of errors, namely, nonsampling errors and 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 2000-2001 Uganda DHS to minimise 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 2000-2001 Uganda DHS 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- 2001 Uganda DHS sample is the result of a stratified two-stage cluster design, and consequently, it was necessary to use more complex formulae. The computer software used to calculate sampling errors for the 2000-2001 Uganda DHS is the ISSA Sampling Error Module (SAMPERR). This module used the Taylor linearisation method of variance estimation for survey estimates that are means or proportions. The Jackknife repeated replication method is used for variance estimation of more complex statistics such as fertility and mortality rates. The Taylor linearisation 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: 210 * Appendix B in which where h represents the stratum that varies from 1 to H, mh is the total number of clusters selected in the h th stratum, yhi is the sum of the weighted values of variable y in the i th cluster in the hth stratum, xhi is the sum of the weighted number of cases in the i th cluster in the hth stratum, and f is the overall sampling fraction, which is so small that it is ignored. The Jackknife 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 cluster in the calculation of the estimates. Pseudoindependent replications are thus created. In the 2000-2001 Uganda DHS, of the 298 clusters selected in the sample, one cluster did not have any eligible women. Hence, 297 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 297 clusters, r(I) is the estimate computed from the reduced sample of 296 clusters (i th cluster excluded), and k is the total number of clusters. In addition to the standard error, SAMPERR 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. SAMPERR also computes the relative error and confidence limits for the estimates. Sampling errors for the 2000-2001 Uganda DHS are calculated for selected variables considered to be of primary interest. The sampling errors for women and men are presented in this appendix for the country as a whole, for urban and rural areas, and for each of the four regions (Central, Eastern, Northern and Western). 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.8 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 Appendix B * 211 (R±2SE), for each variable. The DEFT is considered undefined when the standard error, considering simple random sample, is 0 (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 subpopulations. For example, for the variable currently using any contraceptive method, the relative standard errors as a percentage of the estimated mean for the whole country, for urban areas, and for rural areas are 4.0 percent, 3.5 percent, and 5.1 percent, respectively. The confidence interval (e.g., as calculated for the variable using any method can be interpreted as follows: the overall national sample proportion is 0.228 (or 22.8 percent), and its standard error is 0.009. Therefore, to obtain the 95 percent confidence limits, one adds and subtracts twice the standard error to the sample estimate, i.e., 0.228 ± 2 × 0.009. There is a high probability (95 percent) that the true proportion of all women 15-49 using a contraceptive method is between 21.0 and 24.6 percent. 212 * Appendix B Table B.1 List of selected variables for sampling errors, Uganda 2000-2001 _________________________________________________________________________________________________________________ Variable Estimate Base population ________________________________________________________________________________________________________________ WOMEN _______________________________________________________________________________________________________________ Urban residence Proportion All women 15-49 No education Proportion All women 15-49 With secondary education or higher Proportion All women 15-49 Never married (in union) Proportion All women 15-49 Currently married (in union) Proportion All women 15-49 Children ever born to women 40-49 Mean All women 40-49 Knows any contraceptive method Proportion Currently married women 15-49 Knows any modern method Proportion Currently married women 15-49 Currently using any method Proportion Currently married women 15-49 Currently using a modern method Proportion Currently married women 15-49 Currently using pill Proportion Currently married women 15-49 Currently using IUD Proportion Currently married women 15-49 Currently using injectables Proportion Currently married women 15-49 Currently using implants Proportion Currently married women 15-49 Currently using condom Proportion Currently married women 15-49 Currently using female sterilisation Proportion Currently married women 15-49 Currently using periodic abstinence Proportion Currently married women 15-49 Currently using withdrawal Proportion Currently married women 15-49 Want no more children Proportion Currently married women 15-49 Ideal number of children Mean All women 15-49 Mothers received tetanus injection (1+ doses) Proportion Mothers having a live birth in last 5 years Received medical care at birth Proportion Birth in last 5 years Had diarrhoea in the last 2 weeks Proportion Children under five Received ORS treatment, RHF or increase fluids Proportion Children under 5 with diarrhea in last 2 weeks Received medical treatment Proportion Children under 5 with diarrhea in last 2 weeks Health card seen Proportion Children 12-23 months Received BCG vaccination Proportion Children 12-23 months Received DPT vaccination (3 doses) Proportion Children 12-23 months Received polio vaccination (3 doses) Proportion Children 12-23 months Received measles vaccination Proportion Children 12-23 months Fully immunised Proportion Children 12-23 months Weight-for-height (< -2 SD) Proportion Children under 5 who were measured Height-for-age (< -2 SD) Proportion Children under 5 who were measured Weight-for-age (< -2 SD) Proportion Children under 5 who were measured Total fertility rate (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-five mortality rate Rate Number of births Post-neonatal mortality rate Rate Number of births _______________________________________________________________________________________________________________ MEN _______________________________________________________________________________________________________________ Urban residence Proportion All men 15-54 No education Proportion All men 15-54 With secondary education or higher Proportion All men 15-54 Never married Proportion All men 15-54 Currently married Proportion All men 15-54 Knows any contraceptive method Proportion Currently married men 15-54 Knows any modern method Proportion Currently married men 15-54 Wants no more children Proportion Currently married men 15-54 Ideal number of children Mean All men 15-54 Appendix B * 213 Table B.2 Sampling errors for selected variables: total sample, Uganda 2000-2001 _______________________________________________________________________________________________________________ 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 0.167 0.009 7246 7246 2.084 0.055 0.148 0.185 No education 0.219 0.008 7246 7246 1.667 0.037 0.202 0.235 With secondary education or higher 0.184 0.009 7246 7246 1.943 0.048 0.166 0.201 Never married (in union) 0.201 0.007 7246 7246 1.503 0.035 0.187 0.215 Currently married (in union) 0.674 0.008 7246 7246 1.428 0.012 0.658 0.689 Children ever born to women 40-49 7.118 0.113 953 993 1.075 0.016 6.891 7.345 Knows any contraceptive method 0.978 0.005 4675 4881 2.103 0.005 0.969 0.987 Knows any modern m ethod 0.975 0.004 4675 4881 1.747 0.004 0.967 0.983 Currently using any method 0.228 0.009 4675 4881 1.471 0.040 0.210 0.246 Currently using a modern method 0.182 0.008 4675 4881 1.371 0.043 0.167 0.198 Curren tly using pill 0.032 0.003 4675 4881 1.288 0.104 0.025 0.038 Currently using IUD 0.002 0.001 4675 4881 0.950 0.332 0.001 0.003 Currently using injectables 0.064 0.004 4675 4881 1.170 0.066 0.055 0.072 Currently using im plants 0.003 0.001 4675 4881 0.986 0.260 0.001 0.005 Currently using condom 0.019 0.002 4675 4881 1.201 0.126 0.014 0.024 Currently using female sterilisation 0.020 0.003 4675 4881 1.278 0.131 0.015 0.025 Currently using periodic abstinence 0.025 0.003 4675 4881 1.132 0.104 0.020 0.030 Currently using withdrawal 0.011 0.002 4675 4881 1.087 0.151 0.008 0.014 Want no more children 0.364 0.009 4675 4881 1.338 0.026 0.346 0.383 Ideal number of children 4.843 0.040 6903 6860 1.586 0.008 4.762 4.924 Mothers received tetanu s injection (1+ doses) 0.695 0.010 4252 4489 1.502 0.015 0.675 0.716 Rece ived medical care at b irth 0.382 0.014 7113 7672 2.029 0.037 0.354 0.410 Had diarrhoea in the last 2 weeks 0.196 0.007 6350 6811 1.348 0.035 0.182 0.209 Received ORS treatment, RHF, or increased fluids 0.531 0.016 1178 1333 1.104 0.030 0.499 0.563 Received medical treatment 0.449 0.019 1178 1333 1.274 0.041 0.412 0.486 Health card seen 0.473 0.017 1400 1504 1.348 0.037 0.438 0.507 Received BCG vaccination 0.787 0.014 1400 1504 1.353 0.018 0.758 0.816 Rece ived DPT vaccination (3 doses) 0.461 0.019 1400 1504 1.481 0.041 0.423 0.500 Rece ived polio vaccination (3 doses) 0.541 0.018 1400 1504 1.414 0.034 0.505 0.578 Received measles vaccination 0.568 0.017 1400 1504 1.329 0.030 0.534 0.602 Fully immunised 0.367 0.017 1400 1504 1.385 0.047 0.332 0.402 Weight-for-height 0.040 0.003 5145 5604 1.235 0.081 0.034 0.047 Height-for-age 0.386 0.010 5145 5604 1.418 0.026 0.366 0.406 Weight-for-age 0.225 0.008 5145 5604 1.421 0.037 0.208 0.242 Total fe rtility rate (TFR) 0-3 years 6.852 0.140 na 20301 1.328 0.020 6.573 7.131 Neonatal mortality rate (last 5 years) 33.165 2.675 7265 7834 1.180 0.081 27.814 38.515 Infant m ortality rate 5 years) 88.411 4.789 7287 7854 1.342 0.054 78.834 97.989 Child m ortality rate (last 5 years) 69.189 4.616 7424 8007 1.373 0.067 59.958 78.421 Under-five m ortality rate (last 5 years) 151.483 6.664 7447 8028 1.464 0.044 138.156 164.811 Postneonatal m ortality rate (last 5 years) 55.247 3.695 7286 7853 1.307 0.067 47.857 62.636 ___________________________________________________________________________________________________________________ MEN __________________________________________________________________________________________________________________ Urban residence 0.166 0.010 1962 1962 1.138 0.058 0.147 0.185 No education 0.062 0.007 1962 1962 1.226 0.107 0.049 0.076 With secondary education 0.289 0.015 1962 1962 1.494 0.053 0.259 0.320 Never married (in union) 0.344 0.014 1962 1962 1.265 0.039 0.317 0.371 Currently married (in union) 0.602 0.015 1962 1962 1.345 0.025 0.572 0.631 Knows any contraceptive method 0.989 0.005 1167 1180 1.606 0.005 0.980 0.999 Knows any modern m ethod 0.987 0.005 1167 1180 1.397 0.005 0.977 0.996 Wants no more children 0.272 0.017 1164 1177 1.313 0.063 0.238 0.306 Ideal number of children 5.612 0.106 1865 1858 1.380 0.019 5.401 5.824 __________________________________________________________________________________________________________________ na = Not applicable 214 * Appendix B Table B.3 Sampling errors for selected variables: urban sample, Uganda 2000-2001 _______________________________________________________________________________________________________________ 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 2416 1207 na 0.000 1.000 1.000 No education 0.074 0.008 2416 1207 1.422 0.102 0.059 0.090 With secondary education or higher 0.478 0.014 2416 1207 1.419 0.030 0.449 0.507 Never married (in union) 0.323 0.014 2416 1207 1.465 0.043 0.295 0.351 Currently married (in union) 0.527 0.016 2416 1207 1.532 0.030 0.496 0.558 Children ever born to women 40-49 6.055 0.198 251 110 1.118 0.033 5.658 6.452 Knows any contraceptive method 0.997 0.001 1298 636 0.655 0.001 0.995 0.999 Knows any modern method 0.996 0.001 1298 636 0.739 0.001 0.994 0.999 Currently using any method 0.463 0.016 1298 636 1.177 0.035 0.430 0.496 Currently using a modern method 0.416 0.017 1298 636 1.264 0.042 0.381 0.450 Currently using pill 0.118 0.009 1298 636 0.950 0.072 0.101 0.135 Currently using IUD 0.006 0.002 1298 636 1.037 0.371 0.002 0.010 Currently using injectables 0.153 0.013 1298 636 1.305 0.085 0.127 0.179 Currently using implants 0.016 0.005 1298 636 1.289 0.280 0.007 0.025 Currently using condom 0.050 0.007 1298 636 1.230 0.149 0.035 0.065 Currently using female sterilisation 0.037 0.006 1298 636 1.177 0.168 0.024 0.049 Currently using periodic abstinence 0.027 0.006 1298 636 1.231 0.205 0.016 0.038 Currently using withdrawal 0.015 0.005 1298 636 1.435 0.327 0.005 0.024 Want no more children 0.389 0.016 1298 636 1.190 0.041 0.357 0.421 Ideal number of children 3.761 0.048 2353 1178 1.438 0.013 3.665 3.857 Mothers received tetanus injection (1+ doses) 0.812 0.016 1134 560 1.381 0.020 0.780 0.844 Received medical care at birth 0.803 0.016 1692 821 1.328 0.020 0.772 0.835 Had diarrhoea in the last 2 weeks 0.155 0.011 1564 767 1.167 0.073 0.133 0.178 Received ORS treatment, RHF, or increased fluids 0.666 0.042 252 119 1.285 0.064 0.581 0.751 Received medical treatment 0.639 0.033 252 119 0.989 0.052 0.573 0.706 Health card seen 0.426 0.041 338 167 1.514 0.097 0.343 0.508 Received BCG vaccination 0.919 0.020 338 167 1.352 0.022 0.878 0.959 Received DPT vaccination (3 doses) 0.591 0.033 338 167 1.204 0.055 0.526 0.656 Received polio vaccination (3 doses) 0.600 0.034 338 167 1.263 0.057 0.532 0.669 Received measles vaccination 0.684 0.034 338 167 1.317 0.049 0.617 0.752 Fully immunised 0.421 0.040 338 167 1.474 0.095 0.341 0.501 Weight-for-height 0.029 0.005 1118 536 1.039 0.181 0.019 0.040 Height-for-age 0.265 0.016 1118 536 1.067 0.060 0.233 0.297 Weight-for-age 0.124 0.013 1118 536 1.191 0.103 0.099 0.150 Total fertility rate (TFR) 0-3 years 4.012 0.176 na 3336 1.193 0.044 3.660 4.364 Neonatal mortality rate (last 10 years) 22.471 3.291 3239 1573 1.186 0.146 15.890 29.053 Infant mortality rate (last 10 years) 54.520 5.414 3242 1575 1.233 0.099 43.692 65.347 Child mortality rate (last 10 years) 48.699 5.720 3267 1588 1.363 0.117 37.259 60.140 Under-5 mortality rate (last 10 years) 100.564 7.843 3270 1589 1.331 0.078 84.879 116.249 Postneonatal mortality rate (last 10 years) 32.048 4.679 3242 1575 1.352 0.146 22.691 41.406 ______________________________________________________________________________________________________________ MEN ______________________________________________________________________________________________________________ Urban residence 1.000 0.000 601 325 na 0.000 1.000 1.000 No education 0.022 0.007 601 325 1.241 0.340 0.007 0.037 With secondary education 0.612 0.028 601 325 1.413 0.046 0.556 0.668 Never married (in union) 0.494 0.030 601 325 1.453 0.060 0.435 0.554 Currently married (in union) 0.455 0.025 601 325 1.232 0.055 0.405 0.505 Knows any contraceptive method 1.000 0.000 297 148 na 0.000 1.000 1.000 Knows any modern method 1.000 0.000 297 148 na 0.000 1.000 1.000 Wants no more children 0.397 0.037 297 148 1.292 0.093 0.324 0.471 Ideal number of children 4.440 0.144 582 317 1.471 0.032 4.152 4.728 ______________________________________________________________________________________________________________ na = Not applicable Appendix B * 215 Table B.4 Sampling errors: rural sample, Uganda 2000-2001 _______________________________________________________________________________________________________________ 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 4830 6039 na na 0.000 0.000 No education 0.247 0.010 4830 6039 1.550 0.039 0.228 0.267 With secondary education or higher 0.125 0.010 4830 6039 2.131 0.081 0.105 0.145 Never married (in union) 0.177 0.008 4830 6039 1.479 0.046 0.160 0.193 Currently married (in union) 0.703 0.009 4830 6039 1.367 0.013 0.685 0.721 Children ever born to women 40-49 7.250 0.122 702 883 0.983 0.017 7.006 7.494 Knows any modern method 0.972 0.005 3377 4245 1.604 0.005 0.963 0.981 Currently using any method 0.193 0.010 3377 4245 1.442 0.051 0.173 0.212 Currently using a modern method 0.147 0.008 3377 4245 1.340 0.056 0.131 0.163 Currently using pill 0.019 0.003 3377 4245 1.466 0.182 0.012 0.026 Currently using IUD 0.001 0.001 3377 4245 1.005 0.519 0.000 0.002 Currently using injectables 0.050 0.004 3377 4245 1.129 0.084 0.042 0.059 Currently using implants 0.001 0.001 3377 4245 1.002 0.514 0.000 0.002 Currently using condom 0.014 0.003 3377 4245 1.254 0.179 0.009 0.019 Currently using female sterilisation 0.017 0.003 3377 4245 1.262 0.163 0.012 0.023 Currently using periodic abstinence 0.025 0.003 3377 4245 1.069 0.116 0.019 0.030 Currently using withdrawal 0.010 0.002 3377 4245 1.011 0.170 0.007 0.014 Want no more children 0.361 0.011 3377 4245 1.280 0.029 0.340 0.382 Want to delay next birth at least 2 years 0.350 0.011 3377 4245 1.285 0.030 0.329 0.371 Ideal number of children 5.067 0.046 4550 5681 1.457 0.009 4.975 5.160 Mothers received tetanus injection (1+ doses) 0.679 0.012 3118 3930 1.395 0.017 0.656 0.702 Received medical care at birth 0.331 0.016 5421 6850 1.980 0.047 0.300 0.362 Had diarrhoea in the last 2 weeks 0.201 0.007 4786 6044 1.242 0.037 0.186 0.216 Received ORS treatment, RHF, or increased fluids 0.518 0.017 926 1214 1.010 0.033 0.484 0.553 Received medical treatment 0.430 0.020 926 1214 1.177 0.046 0.390 0.470 Health card seen 0.478 0.019 1062 1337 1.217 0.039 0.441 0.516 Received BCG vaccination 0.770 0.016 1062 1337 1.244 0.021 0.738 0.803 Received DPT vaccination (3 doses) 0.445 0.021 1062 1337 1.388 0.048 0.403 0.487 Received polio vaccination (3 doses) 0.534 0.020 1062 1337 1.315 0.038 0.494 0.574 Received measles vaccination 0.553 0.019 1062 1337 1.223 0.034 0.516 0.591 Fully immunised 0.360 0.019 1062 1337 1.271 0.052 0.323 0.398 Weight-for-height 0.042 0.004 4027 5068 1.129 0.086 0.034 0.049 Height-for-age 0.399 0.011 4027 5068 1.301 0.027 0.377 0.421 Weight-for-age 0.236 0.009 4027 5068 1.303 0.039 0.218 0.254 Total fertility rate (TFR) 0-3 years 7.364 0.142 na 16966 1.168 0.019 7.080 7.649 Neonatal mortality rate (last 10 years) 36.281 2.190 10055 12666 1.026 0.060 31.901 40.660 Infant mortality rate (last 10 years) 93.661 4.036 10074 12691 1.226 0.043 85.590 101.733 Child mortality rate (last 10 years) 76.971 4.261 10170 12803 1.333 0.055 68.449 85.493 Under-5 mortality rate (last 10 years) 163.423 5.819 10190 12829 1.370 0.036 151.786 175.061 Postneonatal mortality rate (last 10 years) 57.381 3.184 10073 12690 1.244 0.055 51.013 63.748 ______________________________________________________________________________________________________________ MEN ______________________________________________________________________________________________________________ Urban residence 0.000 0.000 1361 1637 na na 0.000 0.000 No education 0.070 0.008 1361 1637 1.138 0.112 0.055 0.086 With secondary education 0.225 0.017 1361 1637 1.490 0.075 0.191 0.259 Never married (in union) 0.314 0.015 1361 1637 1.198 0.048 0.284 0.344 Currently married (in union) 0.631 0.017 1361 1637 1.313 0.027 0.596 0.665 Knows any contraceptive method 0.988 0.005 870 1032 1.482 0.006 0.977 0.999 Knows any modern method 0.985 0.005 870 1032 1.289 0.005 0.974 0.996 Wants no more children 0.254 0.019 867 1028 1.269 0.074 0.216 0.291 Ideal number of children 5.853 0.123 1283 1541 1.281 0.021 5.608 6.098 ______________________________________________________________________________________________________________ na = Not applicable 216 * Appendix B Table B.5 Sampling errors for selected variables: Central Region, Uganda 2000-2001 _______________________________________________________________________________________________________________ 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 0.360 0.023 2445 2341 2.327 0.063 0.315 0.405 No education 0.115 0.010 2445 2341 1.624 0.091 0.094 0.136 With secondary education or higher 0.312 0.018 2445 2341 1.911 0.057 0.276 0.348 Never married (in union) 0.252 0.012 2445 2341 1.373 0.048 0.228 0.276 Currently married (in union) 0.588 0.013 2445 2341 1.315 0.022 0.562 0.614 Children ever born to women 40-49 7.200 0.214 275 271 1.094 0.030 6.772 7.628 Knows any contraceptive method 0.998 0.001 1400 1377 1.033 0.001 0.995 1.000 Knows any modern method 0.998 0.001 1400 1377 1.033 0.001 0.995 1.000 Currently using any method 0.370 0.018 1400 1377 1.360 0.048 0.334 0.405 Currently using a modern method 0.314 0.015 1400 1377 1.239 0.049 0.283 0.345 Currently using pill 0.075 0.009 1400 1377 1.256 0.118 0.057 0.092 Currently using IUD 0.004 0.002 1400 1377 1.050 0.471 0.000 0.007 Currently using injectables 0.105 0.010 1400 1377 1.162 0.091 0.086 0.124 Currently using implants 0.007 0.002 1400 1377 0.972 0.312 0.003 0.011 Currently using condom 0.038 0.006 1400 1377 1.155 0.155 0.027 0.050 Currently using female sterlisation 0.033 0.006 1400 1377 1.205 0.176 0.021 0.044 Currently using periodic abstinence 0.021 0.004 1400 1377 1.012 0.183 0.014 0.029 Currently using withdrawal 0.021 0.004 1400 1377 1.052 0.194 0.013 0.029 Want no more children 0.381 0.014 1400 1377 1.070 0.036 0.354 0.409 Want to delay next birth at least 2 years 0.359 0.017 1400 1377 1.340 0.048 0.325 0.394 Ideal number of children 4.390 0.065 2406 2303 1.650 0.015 4.261 4.519 Mothers received tetanus injection (1+ doses) 0.714 0.018 1329 1323 1.462 0.025 0.679 0.750 Received medical care at birth 0.588 0.031 2147 2173 2.394 0.053 0.526 0.650 Had diarrhoea in the last 2 weeks 0.145 0.010 1935 1956 1.198 0.066 0.126 0.164 Received ORS treatment, RHF, or increased fluids 0.713 0.030 289 283 1.108 0.042 0.653 0.773 Received medical treatment 0.581 0.026 289 283 0.849 0.044 0.530 0.633 Health card seen 0.406 0.035 420 423 1.474 0.086 0.336 0.476 Received BCG vaccination 0.707 0.028 420 423 1.268 0.039 0.652 0.763 Received DPT vaccination (3 doses) 0.379 0.030 420 423 1.310 0.080 0.318 0.440 Received polio vaccination (3 doses) 0.409 0.028 420 423 1.199 0.069 0.353 0.466 Received measles vaccination 0.509 0.030 420 423 1.245 0.059 0.449 0.569 Fully immunised 0.290 0.030 420 423 1.358 0.102 0.231 0.350 Weight-for-height 0.036 0.004 1446 1485 0.877 0.116 0.028 0.045 Height-for-age 0.346 0.018 1446 1485 1.378 0.053 0.309 0.382 Weight-for-age 0.199 0.012 1446 1485 1.076 0.059 0.175 0.223 Total fertility rate (TFR) 0-3 years 5.713 0.259 na 6510 1.324 0.045 5.195 6.232 Neonatal mortality rate (last 10 years) 29.772 3.180 3988 4039 1.087 0.107 23.413 36.131 Infant mortality rate (last 10 years) 71.948 6.027 3992 4044 1.358 0.084 59.894 84.002 Child mortality rate (last 10 years) 68.089 7.668 4026 4082 1.638 0.113 52.753 83.424 Under-5 mortality rate (last 10 years) 135.138 10.753 4031 4088 1.745 0.080 113.631 156.645 Postneonatal mortality rate (last 10 years) 42.176 4.498 3991 4042 1.297 0.107 33.180 51.172 _______________________________________________________________________________________________________________ MEN _______________________________________________________________________________________________________________ Urban residence 0.348 0.023 677 671 1.265 0.067 0.302 0.395 No education 0.051 0.010 677 671 1.168 0.193 0.031 0.071 With secondary education 0.376 0.024 677 671 1.265 0.063 0.329 0.423 Never married (in union) 0.450 0.023 677 671 1.226 0.052 0.403 0.497 Currently married (in union) 0.479 0.028 677 671 1.464 0.059 0.423 0.536 Knows any contraceptive method 1.000 0.000 327 322 na 0.000 1.000 1.000 Knows any modern method 1.000 0.000 327 322 na 0.000 1.000 1.000 Wants no more children 0.349 0.034 325 319 1.297 0.098 0.281 0.418 Ideal number of children 5.169 0.138 659 653 1.362 0.027 4.894 5.445 ______________________________________________________________________________________________________________ na = Not applicable Appendix B * 217 Table B.6 Sampling errors for selected variables: Eastern Region, Uganda 2000-2001 _______________________________________________________________________________________________________________ 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 0.103 0.015 1767 1956 2.009 0.141 0.074 0.132 No education 0.194 0.017 1767 1956 1.805 0.087 0.160 0.228 With secondary education or higher 0.159 0.013 1767 1956 1.445 0.079 0.134 0.184 Never married (in union) 0.153 0.013 1767 1956 1.513 0.085 0.127 0.179 Currently married (in union) 0.760 0.014 1767 1956 1.347 0.018 0.733 0.788 Children ever born to women 40-49 7.082 0.235 245 285 1.058 0.033 6.613 7.552 Knows any contraceptive method 0.994 0.003 1285 1487 1.493 0.003 0.988 1.001 Knows any modern method 0.993 0.003 1285 1487 1.440 0.003 0.987 1.000 Currently using any method 0.145 0.014 1285 1487 1.425 0.097 0.117 0.173 Currently using a modern method 0.112 0.011 1285 1487 1.293 0.102 0.089 0.135 Currently using pill 0.011 0.003 1285 1487 1.177 0.318 0.004 0.017 Currently using IUD 0.001 0.000 1285 1487 0.682 0.780 0.000 0.002 Currently using injectables 0.042 0.007 1285 1487 1.231 0.163 0.028 0.056 Currently using implants 0.002 0.001 1285 1487 1.088 0.657 0.000 0.005 Currently using condom 0.016 0.005 1285 1487 1.304 0.281 0.007 0.026 Currently using female sterlisation 0.020 0.005 1285 1487 1.394 0.270 0.009 0.031 Currently using periodic abstinence 0.017 0.004 1285 1487 1.218 0.256 0.008 0.026 Currently using withdrawal 0.002 0.002 1285 1487 1.547 0.933 0.000 0.006 Want no more children 0.369 0.021 1285 1487 1.524 0.056 0.328 0.410 Mothers received tetanus injection (1+ doses) 0.743 0.021 1092 1273 1.616 0.028 0.701 0.784 Received medical care at birth 0.402 0.028 1923 2305 2.088 0.071 0.345 0.458 Had diarrhoea in the last 2 weeks 0.233 0.013 1736 2077 1.292 0.058 0.206 0.260 Received ORS treatment, RHF, or increased fluids 0.544 0.021 379 484 0.817 0.038 0.503 0.585 Received medical treatment 0.472 0.034 379 484 1.316 0.071 0.405 0.540 Health card seen 0.537 0.036 367 445 1.421 0.067 0.465 0.608 Received BCG vaccination 0.844 0.024 367 445 1.333 0.029 0.795 0.892 Received DPT vaccination (3 doses) 0.447 0.041 367 445 1.646 0.092 0.365 0.530 Received polio vaccination (3 doses) 0.571 0.041 367 445 1.619 0.071 0.490 0.652 Received measles vaccination 0.531 0.037 367 445 1.456 0.069 0.458 0.605 Fully immunised 0.378 0.039 367 445 1.603 0.103 0.300 0.456 Weight-for-height 0.043 0.007 1405 1724 1.371 0.163 0.029 0.057 Height-for-age 0.354 0.017 1405 1724 1.296 0.048 0.320 0.389 Weight-for-age 0.225 0.016 1405 1724 1.396 0.069 0.194 0.256 Total fertility rate (TFR) 0-3 years 7.361 0.259 na 5496 1.304 0.035 6.842 7.880 Neonatal mortality rate (last 10 years) 29.495 3.928 3530 4201 1.202 0.133 21.639 37.351 Infant mortality rate (last 10 years) 89.327 7.305 3533 4204 1.376 0.082 74.716 103.938 Child mortality rate (last 10 years) 63.671 5.701 3558 4231 1.272 0.090 52.268 75.074 Under-5 mortality rate (last 10 years) 147.310 7.896 3561 4234 1.261 0.054 131.518 163.102 Postneonatal mortality rate (last 10 years) 59.832 5.799 3533 4204 1.369 0.097 48.234 71.430 _______________________________________________________________________________________________________________ MEN ______________________________________________________________________________________________________________ Urban residence 0.100 0.012 466 523 0.851 0.119 0.076 0.123 No education 0.043 0.011 466 523 1.130 0.247 0.022 0.065 With secondary education 0.303 0.039 466 523 1.850 0.130 0.224 0.381 Never married (in union) 0.284 0.027 466 523 1.314 0.097 0.229 0.339 Currently married (in union) 0.658 0.027 466 523 1.216 0.041 0.605 0.712 Knows any contraceptive method 1.000 0.000 313 344 na 0.000 1.000 1.000 Knows any modern method 1.000 0.000 313 344 na 0.000 1.000 1.000 Wants no more children 0.271 0.039 313 344 1.545 0.143 0.194 0.349 Ideal number of children 5.772 0.241 460 517 1.406 0.042 5.290 6.254 ______________________________________________________________________________________________________________ na = Not applicable 218 * Appendix B Table B.7 Sampling errors or selected variables: Northern Region, Uganda 2000-2001 _______________________________________________________________________________________________________________ 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 0.067 0.012 1041 1158 1.507 0.174 0.044 0.090 No education 0.388 0.025 1041 1158 1.647 0.064 0.338 0.438 With secondary education or higher 0.076 0.015 1041 1158 1.849 0.200 0.046 0.106 Never married (in union) 0.179 0.017 1041 1158 1.443 0.096 0.144 0.213 Currently married (in union) 0.710 0.017 1041 1158 1.233 0.024 0.676 0.745 Children ever born to women 40-49 7.078 0.196 159 185 0.789 0.028 6.687 7.469 Knows any contraceptive method 0.917 0.024 708 823 2.323 0.026 0.868 0.965 Knows any modern method 0.906 0.020 708 823 1.830 0.022 0.865 0.946 Currently using any method 0.210 0.020 708 823 1.293 0.094 0.170 0.249 Currently using a modern method 0.154 0.018 708 823 1.338 0.118 0.118 0.190 Currently using pill 0.009 0.004 708 823 1.129 0.456 0.001 0.016 Currently using IUD 0.001 0.001 708 823 0.471 0.576 0.000 0.002 Currently using injectables 0.039 0.008 708 823 1.055 0.197 0.024 0.054 Currently using implants 0.000 0.000 708 823 na na 0.000 0.000 Currently using condom 0.006 0.003 708 823 0.994 0.484 0.000 0.012 Currently using female sterlisation 0.005 0.004 708 823 1.356 0.692 0.000 0.013 Currently using periodic abstinence 0.050 0.007 708 823 0.818 0.134 0.037 0.064 Currently using withdrawal 0.002 0.002 708 823 0.951 0.732 0.000 0.006 Want no more children 0.319 0.021 708 823 1.192 0.065 0.277 0.361 Ideal number of children 5.552 0.126 928 1016 1.536 0.023 5.299 5.804 Mothers received tetanus injection (1+ doses) 0.715 0.013 663 775 0.745 0.018 0.690 0.741 Received medical care at birth 0.268 0.031 1112 1316 1.971 0.114 0.207 0.330 Had diarrhoea in the last 2 weeks 0.267 0.021 962 1133 1.536 0.079 0.225 0.310 Received ORS treatment, RHF, or increased fluids 0.495 0.041 246 303 1.266 0.082 0.414 0.576 Received medical treatment 0.394 0.034 246 303 1.112 0.088 0.325 0.463 Health card seen 0.437 0.039 217 255 1.176 0.088 0.360 0.514 Received BCG vaccination 0.782 0.032 217 255 1.185 0.041 0.718 0.847 Received DPT vaccination (3 doses) 0.449 0.040 217 255 1.226 0.090 0.369 0.530 Received polio vaccination (3 doses) 0.561 0.039 217 255 1.191 0.070 0.482 0.639 Received measles vaccination 0.579 0.037 217 255 1.137 0.064 0.505 0.653 Fully immunised 0.332 0.033 217 255 1.051 0.099 0.266 0.397 Weight-for-height 0.038 0.007 821 969 1.040 0.175 0.025 0.052 Height-for-age 0.369 0.025 821 969 1.403 0.068 0.319 0.419 Weight-for-age 0.250 0.024 821 969 1.573 0.095 0.203 0.297 Total fertility rate (TFR) 0-3 years 7.863 0.265 na 3224 1.076 0.034 7.332 8.393 Neonatal mortality rate (last 10 years) 42.169 5.267 2059 2413 1.038 0.125 31.635 52.703 Infant mortality rate (last 10 years) 105.890 8.078 2065 2421 1.090 0.076 89.733 122.047 Child mortality rate (last 10 years) 80.612 8.634 2082 2439 1.135 0.107 63.344 97.880 Under-5 mortality rate (last 10 years) 177.966 11.273 2088 2447 1.181 0.063 155.419 200.512 Postneonatal mortality rate (last 10 years) 63.721 7.213 2065 2421 1.292 0.113 49.294 78.147 _______________________________________________________________________________________________________________ MEN ______________________________________________________________________________________________________________ Urban residence 0.066 0.007 273 284 0.484 0.110 0.052 0.081 No education 0.086 0.026 273 284 1.513 0.299 0.035 0.137 With secondary education 0.210 0.035 273 284 1.420 0.167 0.139 0.280 Never married (in union) 0.232 0.018 273 284 0.713 0.079 0.195 0.268 Currently married (in union) 0.736 0.020 273 284 0.765 0.028 0.695 0.777 Knows any contraceptive method 0.957 0.025 187 209 1.679 0.026 0.907 1.007 Knows any modern method 0.942 0.024 187 209 1.420 0.026 0.893 0.991 Ideal number of children 7.286 0.434 226 229 1.331 0.060 6.418 8.154 ______________________________________________________________________________________________________________ na = Not applicable Appendix B * 219 Table B.8 Sampling errors for selected variables: Western Region, Uganda 2000-2001 _______________________________________________________________________________________________________________ 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 0.047 0.008 1993 1792 1.691 0.170 0.031 0.063 No education 0.271 0.016 1993 1792 1.559 0.057 0.240 0.302 With secondary education or higher 0.112 0.015 1993 1792 2.108 0.133 0.082 0.142 Never married (in union) 0.201 0.014 1993 1792 1.577 0.070 0.173 0.229 Currently married (in union) 0.667 0.016 1993 1792 1.555 0.025 0.634 0.699 Children ever born to women 40-49 7.100 0.237 274 252 1.246 0.033 6.627 7.573 Knows any contraceptive method 0.976 0.004 1282 1194 0.940 0.004 0.968 0.984 Knows any modern method 0.975 0.004 1282 1194 0.926 0.004 0.967 0.983 Ever used any contraceptive method 0.354 0.023 1282 1194 1.689 0.064 0.309 0.399 Currently using any method 0.180 0.017 1282 1194 1.629 0.097 0.145 0.215 Currently using a modern method 0.136 0.015 1282 1194 1.557 0.110 0.106 0.166 Currently using pill 0.025 0.006 1282 1194 1.287 0.225 0.014 0.036 Currently using IUD 0.002 0.001 1282 1194 1.057 0.723 0.000 0.004 Currently using injectables 0.060 0.008 1282 1194 1.228 0.136 0.043 0.076 Currently using implants 0.002 0.001 1282 1194 0.914 0.578 0.000 0.004 Currently using condom 0.009 0.003 1282 1194 1.290 0.389 0.002 0.015 Currently using female sterlisation 0.015 0.004 1282 1194 1.222 0.278 0.007 0.023 Currently using periodic abstinence 0.021 0.006 1282 1194 1.545 0.294 0.009 0.033 Currently using withdrawal 0.017 0.004 1282 1194 1.125 0.242 0.009 0.025 Want no more children 0.370 0.019 1282 1194 1.381 0.050 0.333 0.408 Ideal number of children 5.076 0.099 1861 1661 1.908 0.020 4.878 5.274 Mothers received tetanus injection (1+ doses) 0.606 0.024 1168 1119 1.745 0.040 0.557 0.654 Received medical care at birth 0.231 0.017 1931 1878 1.701 0.085 0.197 0.265 Had diarrhoea in the last 2 weeks 0.160 0.012 1717 1646 1.316 0.075 0.136 0.184 Received ORS treatment, RHF, or increased fluids 0.355 0.034 264 263 1.122 0.095 0.287 0.422 Received medical treatment 0.328 0.044 264 263 1.503 0.136 0.239 0.417 Health card seen 0.496 0.027 396 382 1.106 0.054 0.442 0.549 Received BCG vaccination 0.812 0.030 396 382 1.606 0.038 0.751 0.873 Received DPT vaccination (3 doses) 0.577 0.036 396 382 1.502 0.062 0.505 0.649 Received polio vaccination (3 doses) 0.640 0.031 396 382 1.325 0.048 0.579 0.702 Received measles vaccination 0.669 0.027 396 382 1.178 0.040 0.615 0.723 Fully immunised 0.463 0.029 396 382 1.199 0.063 0.405 0.521 Weight-for-height 0.043 0.007 1473 1426 1.394 0.173 0.028 0.058 Height-for-age 0.478 0.019 1473 1426 1.457 0.041 0.439 0.517 Weight-for-age 0.237 0.018 1473 1426 1.539 0.075 0.201 0.272 Total fertility rate (TFR) 0-3 years 6.886 0.255 na 5071 1.349 0.037 6.376 7.395 Neonatal mortality rate (last 10 years) 41.536 3.842 3717 3586 1.108 0.093 33.851 49.220 Infant mortality rate (last 10 years) 97.845 7.758 3726 3597 1.452 0.079 82.329 113.361 Child mortality rate (last 10 years) 86.980 8.737 3771 3638 1.639 0.100 69.507 104.454 Under-5 mortality rate (last 10 years) 176.314 12.005 3780 3649 1.703 0.068 152.304 200.324 Postneonatal mortality rate (last 10 years) 56.309 6.015 3726 3597 1.469 0.107 44.280 68.338 _______________________________________________________________________________________________________________ MEN _______________________________________________________________________________________________________________ Urban residence 0.042 0.009 546 484 1.028 0.210 0.024 0.060 No education 0.084 0.013 546 484 1.128 0.159 0.057 0.111 With secondary education 0.202 0.022 546 484 1.270 0.108 0.158 0.246 Never married (in union) 0.328 0.027 546 484 1.336 0.082 0.275 0.382 Currently married (in union) 0.631 0.030 546 484 1.430 0.047 0.571 0.690 Knows any contraceptive method 0.989 0.006 340 305 1.023 0.006 0.977 1.000 Knows any modern method 0.989 0.006 340 305 1.023 0.006 0.977 1.000 Wants no more children 0.285 0.025 339 304 1.012 0.087 0.236 0.335 Ideal number of children 5.226 0.151 520 459 1.427 0.029 4.924 5.528 ______________________________________________________________________________________________________________ na = Not applicable 220 * Appendix B Appendix C * 221 Table C.1 Household age distribution Single-year age distribution of the de facto household population by sex (weighted), Uganda 2000-2001 _________________________________________________________________________________________ Males Females Males Females ________________ ________________ ________________ _________________ Age Number Percent Number Percent Age Number Percent Number Percent _________________________________________________________________________________________ 0 807 4.6 775 4.1 1 768 4.4 754 4.0 2 664 3.8 710 3.8 3 739 4.2 722 3.8 4 674 3.8 682 3.6 5 569 3.2 548 2.9 6 766 4.3 767 4.1 7 640 3.6 666 3.5 8 597 3.4 666 3.5 9 548 3.1 512 2.7 10 638 3.6 689 3.6 11 479 2.7 420 2.2 12 553 3.1 651 3.4 13 490 2.8 542 2.9 14 545 3.1 455 2.4 15 403 2.3 333 1.8 16 348 2.0 374 2.0 17 310 1.8 323 1.7 18 385 2.2 419 2.2 19 215 1.2 306 1.6 20 329 1.9 418 2.2 21 215 1.2 287 1.5 22 232 1.3 303 1.6 23 204 1.2 297 1.6 24 190 1.1 270 1.4 25 322 1.8 358 1.9 26 189 1.1 278 1.5 27 191 1.1 239 1.3 28 295 1.7 346 1.8 29 152 0.9 160 0.8 30 365 2.1 358 1.9 31 130 0.7 155 0.8 32 239 1.4 211 1.1 33 126 0.7 128 0.7 34 158 0.9 176 0.9 35 206 1.2 185 1.0 36 163 0.9 186 1.0 37 115 0.7 128 0.7 38 176 1.0 227 1.2 39 80 0.5 99 0.5 40 226 1.3 216 1.1 41 69 0.4 84 0.4 42 105 0.6 128 0.7 43 64 0.4 84 0.4 44 59 0.3 68 0.4 45 132 0.7 149 0.8 46 88 0.5 92 0.5 47 58 0.3 58 0.3 48 105 0.6 86 0.5 49 67 0.4 44 0.2 50 115 0.7 125 0.7 51 38 0.2 84 0.4 52 70 0.4 145 0.8 53 41 0.2 71 0.4 54 58 0.3 76 0.4 55 66 0.4 86 0.5 56 81 0.5 76 0.4 57 44 0.2 37 0.2 58 66 0.4 86 0.5 59 25 0.1 42 0.2 60 131 0.7 183 1.0 61 21 0.1 26 0.1 62 51 0.3 58 0.3 63 39 0.2 31 0.2 64 36 0.2 44 0.2 65 93 0.5 82 0.4 66 34 0.2 19 0.1 67 27 0.2 37 0.2 68 38 0.2 46 0.2 69 19 0.1 14 0.1 70+ 368 2.1 366 1.9 Don’t know/ missing 8 0.0 6 0.0 Total 17,657 100.0 18,871 100.0 DATA QUALITY TABLES APPENDIX C 222 * 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 age groups, Uganda 2000-2001 _____________________________________________________________ Household Interviewed population of women Percentage women age 10-54 age 15-49 of eligible __________________ ________________ women Age group Number Percent Number Percent interviewed _____________________________________________________________ 10-14 2,756 na na na na 15-19 1,755 23.2 1,598 22.4 91.1 20-24 1,574 20.8 1,491 20.9 94.7 25-29 1,380 18.2 1,303 18.3 94.4 30-34 1,028 13.6 982 13.8 95.4 25-39 824 10.9 792 11.1 96.1 40-44 579 7.7 546 7.7 94.2 45-49 430 5.7 410 5.8 95.3 50-54 500 na na na na 15-49 7,572 na 7,121 na 94.0 ____________________________________________________ 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 10-64, and of interviewed men age 15-54, and percentage of eligible men who were interviewed (weighted) by five-year age groups, Uganda 2000- 2001 _____________________________________________________________ Household population Interviewed Percentage men age 10-64 men age 15-54 of eligible ______________________ __________________ men Age group Number Percent Number Percent Interviewed _____________________________________________________________ 10-14 987 na na na na 15-19 522 22.6 448 22.5 85.8 20-24 390 16.9 325 16.3 83.3 25-29 358 15.5 315 15.8 88.0 30-34 345 15.0 295 14.8 85.4 25-39 267 11.6 235 11.8 88.0 40-44 179 7.7 161 8.1 89.5 45-49 152 6.6 129 6.5 85.2 50-54 95 4.1 83 4.2 86.9 55-59 100 na na na na 60-64 79 na na na na 15-54 2,488 na 1,991 na 80.0 ____________________________________________________ na = Not applicable Appendix C * 223 Table C.3 Completeness of reporting Percentage of observations missing information for selected demographic and health questions (weighted), Uganda 2000-2001 _____________________________________________________________________________ Percentage with missing Subject Reference group information Number _____________________________________________________________________________ Birth date Births in past 15 years Month only 5.41 18,946 Month and year 0.11 18,946 Age at death Dead children in past 15 years 0.29 2,788 Age at/date of first union1 Ever-married women 15-49 0.96 5,790 Respondent’s education All women 15-49 0.03 7,246 Diarrhoea in past 2 weeks Living children 0-59 months 4.81 6,811 Anthropometry Living children 0-59 months Height in household 13.15 7,076 Weight 11.55 7,076 Height or weight missing 13.30 7,076 Anaemia Children Living children 0-59 months in household 13.78 7,076 Women All women age 15-49 9.63 7,246 _____________________________________________________________________________ 1Both year and age missing. 224 * Appendix C Ta bl e C .4 B irt hs b y ca le nd ar y ea r s in ce b irt h D ist rib ut io n of b irt hs b y ca le nd ar y ea rs si nc e bi rth 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, se x 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, U ga nd a 20 00 -2 00 1 __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ 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 01 68 2 70 10 0. 0 10 0. 0 10 0. 0 79 .0 0. 0 75 .0 na na na 30 0 30 38 2 40 20 00 1, 42 1 9 3 1 ,5 13 1 00 .0 1 00 .0 1 00 .0 1 01 .0 1 17 .0 1 01 .9 na na na 71 4 50 76 4 70 7 43 74 9 19 99 1, 51 4 15 1 1 ,6 65 1 00 .0 98 .9 99 .9 1 08 .7 97 .6 1 07 .6 11 2. 3 10 8. 4 11 2. 0 78 8 75 86 3 72 5 76 80 2 19 98 1, 27 5 18 6 1 ,4 61 99 .6 98 .0 99 .4 91 .6 1 54 .8 97 .8 90 .5 10 1. 5 91 .8 60 9 11 3 72 2 66 6 73 73 8 19 97 1 ,3 04 2 15 1 ,5 19 99 .6 97 .6 99 .3 94 .9 81 .4 92 .9 10 3. 3 10 3. 3 10 3. 3 63 5 97 73 2 66 9 11 9 78 8 19 96 1, 24 9 23 1 1 ,4 80 99 .6 97 .8 99 .3 92 .7 99 .0 93 .6 10 5. 6 12 2. 3 10 7. 9 60 1 11 5 71 6 64 9 11 6 76 5 19 95 1, 06 2 16 2 1 ,2 24 98 .9 97 .8 98 .7 1 02 .0 1 06 .4 1 02 .6 82 .9 66 .8 80 .3 53 6 84 62 0 52 6 79 60 4 19 94 1, 31 2 25 6 1 ,5 68 93 .7 88 .8 92 .9 1 13 .4 1 46 .4 1 18 .1 12 4. 0 12 2. 2 12 3. 7 69 7 15 2 84 9 61 5 10 4 71 9 19 93 1, 05 4 25 6 1 ,3 10 93 .6 84 .8 91 .9 1 01 .4 1 05 .9 1 02 .3 88 .1 10 6. 7 91 .2 53 1 13 2 66 2 52 3 12 4 64 7 19 92 1, 07 9 22 4 1 ,3 03 93 .3 83 .0 91 .5 96 .8 1 23 .1 1 00 .9 11 2. 2 10 3. 6 11 0. 6 53 1 12 4 65 4 54 8 10 0 64 9 19 91 87 0 17 7 1 ,0 47 93 .3 84 .9 91 .9 1 01 .4 93 .4 1 00 .0 na na na 43 8 85 52 3 43 2 91 52 3 19 96 -2 00 0 6 ,7 63 8 76 7 ,6 38 99 .8 98 .2 99 .6 98 .0 1 05 .2 98 .8 na na na 3, 34 7 44 9 3, 79 6 3, 41 5 42 7 3, 84 2 19 91 -1 99 5 5 ,3 77 1, 07 4 6 ,4 52 94 .6 87 .4 93 .4 1 03 .4 1 15 .6 1 05 .3 na na na 2, 73 3 57 6 3, 30 9 2, 64 4 49 8 3, 14 2 19 86 -1 99 0 3 ,9 53 8 42 4 ,7 95 90 .6 76 .8 88 .1 97 .7 1 16 .5 1 00 .8 na na na 1, 95 4 45 3 2, 40 7 1, 99 9 38 9 2, 38 8 19 81 -1 98 5 2 ,3 78 6 11 2 ,9 89 89 .6 78 .1 87 .3 97 .9 99 .4 98 .2 na na na 1, 17 6 30 4 1, 48 1 1, 20 2 30 6 1, 50 8 < 1 98 1 2, 17 4 80 4 2 ,9 77 88 .6 77 .0 85 .5 1 03 .9 1 16 .4 1 07 .2 na na na 1, 10 8 43 2 1, 54 0 1, 06 6 37 1 1, 43 7 Al l 20 ,6 44 4, 20 7 2 4, 85 1 94 .3 84 .2 92 .6 99 .9 1 11 .2 1 01 .7 na na na 10 ,3 18 2, 21 5 12 ,5 33 10 ,3 26 1, 99 2 12 ,3 18 __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ na = N ot a pp lic ab le 1 Bo th y ea r 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 rt hs , r es pe ct iv el y 3 [2 B x /(B x- 1+ B x + 1) ]* 10 0, w he re B x i s th e nu m be r o f b irt hs in c al en da r y ea r x Appendix C * 225 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 age 0-6 days, for five-year periods of birth preceding the survey, Uganda 2000- 2001 _____________________________________________________________ Number of years preceding the survey Age at death _________________________________ Total (in days) 0-4 5-9 10-14 15-19 0-19_____________________________________________________________ 0 92 95 59 43 289 1 41 27 26 11 105 2 19 15 13 10 58 3 10 12 11 8 41 4 8 7 9 5 29 5 5 7 2 0 13 6 4 4 2 4 14 7 27 30 16 16 89 8 1 1 2 0 5 9 4 1 6 3 14 10 3 1 2 3 9 11 2 0 0 0 2 12 1 0 0 1 2 13 0 2 1 0 3 14 18 18 15 16 67 15 2 2 0 1 5 16 0 8 0 1 9 18 1 1 2 0 4 19 0 0 1 2 3 20 1 0 0 0 1 21 3 3 2 1 8 23 1 0 0 0 2 24 2 0 0 0 2 26 1 0 0 0 1 28 0 2 0 0 2 29 0 0 1 0 1 30 0 2 0 0 2 31+ 1 0 0 0 1 Missing 1 0 0 0 2 Percent early neonatal1 72.3 70.3 71.3 64.8 70.3 Total 0-30 248 238 170 126 781 _______________________________________________________________________ 1 # 6 days/# 30 days 226 * 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 infant deaths reported to occur at ages under one month, for five-year periods of birth preceding the survey, Uganda 2000-2001 _______________________________________________________________ Number of years preceding the survey Age at death _______________________________ Total (in months) 0-4 5-9 10-14 15-19 0-19 _______________________________________________________________ <1 a 250 241 170 126 785 1 30 33 31 21 115 2 36 36 24 19 115 3 41 50 35 22 147 4 29 29 31 10 99 5 37 26 11 13 88 6 39 28 25 28 120 7 40 34 28 11 113 8 37 46 29 21 134 9 51 37 25 12 125 10 18 12 6 3 38 11 21 11 3 7 43 12 15 30 29 26 101 13 6 18 9 9 43 14 22 17 17 11 67 15 5 14 12 9 40 16 7 13 6 5 30 17 13 10 8 6 37 18 16 21 27 17 82 19 8 8 2 3 20 20 7 10 5 8 30 21 5 8 3 1 18 22 5 3 0 0 8 23 3 6 1 1 11 24+ 3 2 4 4 12 1 year 32 50 27 28 137 Percent neonatal b 39.7 41.4 40.6 42.7 40.9 Total 0-11 629 582 417 294 1,922 ______________________________________________________________ a Includes deaths under 1 month reported in daysb Under 1 month/under 1 year Appendix D * 227 D PERSONS INVOLVED IN THE 2000-2001 UGANDA DEMOGRAPHIC AND HEALTH SURVEY APPENDIX UGANDA BUREAU OF STATISTICS MANAGEMENT J. B. Male-Mukasa, Executive Director, Uganda Bureau of Statistics J.W. Mubiru, Deputy Executive Director, Uganda Bureau of Statistics Dr. J. Musinguzi, Director, Population Secretariat/Chairman, Technical Committee TECHNICAL STAFF Z.E.A. Kaija, Survey Director A.L. Mukulu, Project Coordinator H. Namirembe-Nviiri (Mrs.), Deputy Project Coordinator W. Nyegenye, Senior Statistician/Regional Supervisor J. Galande, Statistician/Regional Supervisor P. Nabukhonzo (Ms.), Statistician/Regional Supervisor A. Wassago, Statistician/Regional Supervisor J. Nassozi (Ms.), Statistician/Office Editor ORC MACRO Ann Way (Ph.D), Deputy Director for Survey Operations Greg Pappas (M.D.), Deputy Director for Health Anne R. Cross, Regional Coordinator Sri Poedjastoeti, Country Coordinator Alfredo Aliaga (Ph.D), Sampling Statistician Martin Wulfe, Data Processing Specialist Glen Heller, Data Processing Specialist Elizabeth Britton, Data Processing Specialist Abdikamal Alisalad (M.D.), Senior Health Specialist Jasbir Saggu, Health Specialist Sidney Moore (Ph.D), Editor Kaye Mitchell, Document Production Specialist Celia Khan, Document Production Specialist AUTHORS E. Ssekatawa (Ph.D) Report Writing Coordinator Z. E. A. Kaija Chapter 1: Introduction A. L. Mukulu Chapter 2: Household Characteristics I. Mulindwa (Ms.) Chapter 3: Women Characteristics V. Matovu (Ms.) Chapter 4: Fertility F. Ebanyat (M.D.) Chapter 5: Fertility Regulation J. K. Kagugube Chapter 6: Proximate Determinants of Fertility H. Namirembe-Nviiri (Ms.) Chapter 7: Fertility Preferences J. Ssekamatte-Ssebuliba (Ph.D) Chapter 8: Infant and Childhood Mortality A. K. Mbonye (M.D.) Chapter 9: Reproductive and Child Health U. Wangwe (Ms.) Chapter 10: Infant Feeding and Nutrition E. B. Kasheeka (Ph.D) Chapter 11: AIDs and Other Sexually Transmitted Infections N. Ayiga (Ph.D) Chapter 12: Adult Mortality 228 * Appendix D STEERING COMMITTEE (REPRESENTATIVES OF) Decentralization Secretariat DfID Institute for Statistics and Applied Economics, Makerere University ORC Macro Ministry of Gender, Labour and Social Development Ministry of Health National Council for Children Population Secretariat UBOS UNFPA UNICEF USAID TRAINERS Abdikamal Alisalad (M.D.) Z. E. A. Kaija H. Luyima (Ms.) V. Mukasa (M.D.) A. L. Mukulu M. Muwanga (M.D.) P. Nabukhonzo (Ms.) H. Namirembe-Nviiri (Mrs.) W. Nyegenye Sri Poedjastoeti U. Wangwe (Ms.) A. Wassago Translators D. Abiriga Lugbara E. Kansiime (Ms.) Runyankore/Rukiga I. Katorogo (Sr) Runyoro/Rutoro V. Matovu (Ms.) Luganda J. Nanyonga (Ms.) Luganda A. Okello (Sr) Luo S. Oluka (Ph.D) Ateso B. Twesigye Runyankore/Rukiga FIELD STAFF HEALTH SUPERVISORS Dr. V. Mukasa M. Bazibu-Kivumbi (Ms.) SUPERVIOSRS W. Epalitai J. Kakande S. Kambabazi (Ms.) B. Nakayenga (Ms.) O. J. Nanyonga (Ms.) B. Nawoova (Ms.) B. Okua C. J. Opobo D. Tendo J. Turyamureeba Appendix D * 229 FIELD EDITORS H. Akurut (Ms.) D. Andama (Ms.) H. Ekwau (Ms.) E. Kajura (Ms.) M. Mugasho (Ms.) R. J. Nalule (Ms.) J. Namara (Ms.) J. Namuddu (Ms.) N. Namuyiga (Ms.) M. Nansubuga (Ms.) HEALTH TECHNICIANS F. A. Akello (Ms.) C. S. Akurut (Ms.) B. Buhule (Ms.) A. Katusabe (Ms.) E. Kibaya O. Kibi (Ms.) S. R. Kiyimba (Ms.) M. Kyobutungi (Ms.) C. Mbabazi (Ms.) M. Metusera S. Owarwe J. Tiakoru (Ms.) J. Tikabibamu (Ms.) INTERVIEWERS G. Ajiku A. Ajore (Ms.) P. Akanyijuka (Ms.) L. Akech (Ms.) C. Akullo (Ms.) C. Aluma (Ms.) S. Asiimwe (Ms.) A. Atim (Ms.) H. Atyang (Ms.) F. Awio (Ms.) S. Bazaale (Ms.) W. Eriaku B. Iminu (Ms.) S. Isiru (Ms.) C. Kalimba I. B. Kanyunyuzi (Ms.) H. Katikajjira E. M. Kato (Ms.) J. Kemigisha (Ms.) G. Kibooli (Ms.) E. Kisakye (Ms.) F. Konyen W. J. Kyaligonza (Ms.) L. Kyobutungi (Ms.) G. Laker (Ms.) R. Luganda (Ms.) L. N. Lyadda (Ms.) R. Mbabazi (Ms.) I. Mugabe J. Mukasa A. M. Mwiine D. Nakabugo (Ms.) M. Nakibinge (Ms.) F. Nalubaale (Ms.) B. Nalubanga (Ms.) A. Naluyange (Ms.) E. Namanya (Ms.) R. Namutebi (Ms.) P. Namuyinda (Ms.) M. Nankwalu (Ms.) J. Nantume (Ms.) R. Naseeta (Ms.) R. Nassuna (Ms.) B. G. Nkunze G. Nsereko H. Nyende W. Ochieng N. Olwala B. Sserunkuma (Ms.) F. Uwimaana (Ms.) LISTERS G. Ajiku P. Batanda A. Bwire P. Byawaka W. Epalitai W. Hashaka S. Hungandula P. Kamiza C. Kasozi I. Kirigwa E. Lubowa 230 * Appendix D G. Lusinde M. Luzinda S. Maedero M. Kahwa S. Mugweri J. Mukasa P. Mukasa H. Musolini I. Mwesigwa W. Ochieng C. J. Opobo S. Otim K. G. Senteza W. Ssekyanzi N. Wandera G. Waswa DRIVERS C. Bazanye A. Kalulu E. Kavulu H. Matovu P. Matovu B. Mawazi S. Musisi S. Muyinga A. Shaban E. Wagooli DATA PROCESSING Data Entry Supervisor H. N. Mubiru J. Galande DATA ENTRY OPERATORS W. Anglokin (Ms.) S. Aseku (Ms.) G. Bawonga D. Birungi (Ms.) T. Egessa C. Kaitesi (Ms.) J. Karyegyesa (Ms.) R. Lubega B. Mayambala (Ms.) G. Mutangana (Ms.) E. Nambo (Ms.) A. Namwanje (Ms.) R. Nannono (Ms.) M. Ocen A. Okecha (Ms.) P. Semakula SUPPORT STAFF S. Etonu (Ms.) Secretary H. Kabura (Ms.) Secretary J. Ocokol Driver Appendix E * 231 QUESTIONNAIRES APPENDIX E HE1 2000 UGANDA DEMOGRAPHIC AND HEALTH SURVEY HOUSEHOLD QUESTIONNAIRE IDENTIFICATION REGION DISTRICT COUNTY SUBCOUNTY/TOWN PARISH/LC2 NAME EA NAME UDHS NUMBER URBAN/RURAL (URBAN=1, RURAL=2) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . LARGE CITY/SMALL CITY/TOWN/COUNTRYSIDE . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . (LARGE CITY=1, SMALL CITY=2, TOWN=3, COUNTRYSIDE=4) HOUSEHOLD NUMBER . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . NAME OF HOUSEHOLD HEAD HOUSEHOLD SELECTED FOR MALE SURVEY? (YES = 1, NO = 2) HOUSEHOLD SELECTED FOR VITAMIN A TESTING? (YES = 1, NO = 2) +))), *!!!* +)))3)))1 *!!!*!!!* .)))3)))1 *!!!* /)))1 *!!!* +)))3)))1 *!!!*!!!* /)))3)))1 *!!!*!!!* +)))0)))3)))3)))1 *!!!*!!!*!!!*!!!* .)))2)))2)))3)))1 *!!!* /)))1 *!!!* .)))- +)))0)))0))), *!!!*!!!*!!!* .)))2)))2)))- +))), *!!!* /)))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 QUEST. +)))0))), *!!!*!!!* .)))2)))- SUPERVISOR FIELD EDITOR OFFICE EDITOR KEYED BY NAME +)))0))), *!!!*!!!* .)))2)))- NAME +)))0))), *!!!*!!!* .)))2)))- +)))0))), *!!!*!!!* .)))2)))- +)))0))), *!!!*!!!* .)))2)))-DATE DATE HE2 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 RELATIONSHIP TO HEAD OF HOUSEHOLD SEX RESIDENCE AGE ELIGIBILITY Please give me the names of the persons who usually live in your household and guests of the household who stayed here last night, starting with the head of the household. (FIRST AND LAST NAME IN CAPITAL LETTERS) What is the relationship of (NAME) to the head of the household?* Is (NAME) male or female? Does (NAME) usually live here? Did (NAME) stay here last night? How old is (NAME)? CIRCLE LINE NUMBER OF ALL WOMEN AGE 15-49 CIRCLE LINE NUMBER OF ALL CHILDREN UNDER AGE 6 CIRCLE LINE NUMBER OF ALL MEN AGE 15-54 CIRCLE LINE NUMBER OF ALL CHILDREN AGE 5 - 17 (1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) M F YES NO YES NO IN YEARS 1 +)))0))), *!!!*!!!* .)))2)))- 1 2 1 2 1 2 +)))0))), *!!!*!!!* .)))2)))- 1 1 1 1 2 +)))0))), *!!!*!!!* .)))2)))- 1 2 1 2 1 2 +)))0))), *!!!*!!!* .)))2)))- 2 2 2 2 3 +)))0))), *!!!*!!!* .)))2)))- 1 2 1 2 1 2 +)))0))), *!!!*!!!* .)))2)))- 3 3 3 3 4 +)))0))), *!!!*!!!* .)))2)))- 1 2 1 2 1 2 +)))0))), *!!!*!!!* .)))2)))- 4 4 4 4 5 +)))0))), *!!!*!!!* .)))2)))- 1 2 1 2 1 2 +)))0))), *!!!*!!!* .)))2)))- 5 5 5 5 6 +)))0))), *!!!*!!!* .)))2)))- 1 2 1 2 1 2 +)))0))), *!!!*!!!* .)))2)))- 6 6 6 6 7 +)))0))), *!!!*!!!* .)))2)))- 1 2 1 2 1 2 +)))0))), *!!!*!!!* .)))2)))- 7 7 7 7 8 +)))0))), *!!!*!!!* .)))2)))- 1 2 1 2 1 2 +)))0))), *!!!*!!!* .)))2)))- 8 8 8 8 9 +)))0))), *!!!*!!!* .)))2)))- 1 2 1 2 1 2 +)))0))), *!!!*!!!* .)))2)))- 9 9 9 9 10 +)))0))), *!!!*!!!* .)))2)))- 1 2 1 2 1 2 +)))0))), *!!!*!!!* .)))2)))- 10 10 10 10 * CODES FOR Q.3 RELATIONSHIP TO HEAD OF HOUSEHOLD: 01 = HEAD 02 = WIFE OR HUSBAND 03 = SON OR DAUGHTER 04 = SON-IN-LAW OR DAUGHTER-IN-LAW 05 = GRANDCHILD 06 = PARENT 07 = PARENT-IN-LAW 08 = BROTHER OR SISTER 09 = CO-WIFE 10 = OTHER RELATIVE 11 = ADOPTED/FOSTER/ STEPCHILD 12 = NOT RELATED 98 = DON’T KNOW HE3 LINE NO. PARENTAL SURVIVORSHIP AND RESIDENCE FOR PERSONS LESS THAN 18 YEARS OLD** EDUCATION Is (NAME)’s natural mother alive? IF ALIVE Is (NAME)’s natural father alive? IF ALIVE IF AGE 4 YEARS OR OLDER IF AGE 4-24 YEARS Does (NAME)’s natural mother live in this house- hold? IF YES: What is her name? RECORD MOTHER’S LINE NUMBER Does (NAME)’s natural father live in this house- hold? IF YES: What is his name? RECORD FATHER’S LINE NUMBER Has (NAME) ever attended school? What is the highest level of school (NAME) has attended?*** What is the highest grade (NAME) completed at that level?*** Is (NAME) currently attending school? During the current school year (2000), did (NAME) attend school at any time? During the current school year (2000), what level and grade [is/was] (NAME) attending?*** During the previous school year (1999), did (NAME) attend school at any time? During that school year (1999), what level and grade did (NAME) attend?*** (12) (13) (14) (15) (16) (17) (18) (19) (20) (21) (22) YES NO DK YES NO DK YES NO LEVEL GRADE YES NO YES NO LEVEL GRADE YES NO LEVEL GRADE 01 1 2 8 +)))0))), *!!!*!!!* .)))2)))- 1 2 8 +)))0))), *!!!*!!!* .)))2)))- 1 2 NEXT =- LINE +))), *!!!* .)))- +)))0))), *!!!*!!!* .)))2)))- 1 2 .< GO TO 20 1 2 GO TO=- 21 +))), *!!!* .)))- +)))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 20 1 2 GO TO=- 21 +))), *!!!* .)))- +)))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 20 1 2 GO TO=- 21 +))), *!!!* .)))- +)))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 20 1 2 GO TO=- 21 +))), *!!!* .)))- +)))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 20 1 2 GO TO=- 21 +))), *!!!* .)))- +)))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 20 1 2 GO TO=- 21 +))), *!!!* .)))- +)))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 20 1 2 GO TO=- 21 +))), *!!!* .)))- +)))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 20 1 2 GO TO=- 21 +))), *!!!* .)))- +)))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 20 1 2 GO TO=- 21 +))), *!!!* .)))- +)))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 20 1 2 .< GO TO 21 +))), *!!!* .)))- +)))0))), *!!!*!!!* .)))2)))- 1 2 NEXT=- LINE +))), *!!!* .)))- +)))0))), *!!!*!!!* .)))2)))- ** Q.12 THROUGH Q.15 THESE QUESTIONS REFER TO THE BIOLOGICAL PARENTS OF THE CHILD. IN Q.13 AND Q.15, RECORD ‘00' IF PARENT NOT LISTED IN HOUSEHOLD SCHEDULE. ***CODES FOR Qs. 17, 20 AND 22 EDUCATION LEVEL: 0 = PRESCHOOL 1 = PRIMARY 2 = SECONDARY 3 = POST SECONDARY 8 = DON’T KNOW EDUCATION GRADE: 00 = LESS THAN 1 YEAR COMPLETED 98 = DON’T KNOW HE4 LINE NO. USUAL RESIDENTS AND VISITORS RELATIONSHIP TO HEAD OF HOUSEHOLD SEX RESIDENCE AGE ELIGIBILITY Please give me the names of the persons who usually live in your household and guests of the household who stayed here last night, starting with the head of the household. (FIRST AND LAST NAME IN CAPITAL LETTERS) What is the relationship of (NAME) to the head of the household?* Is (NAME) male or female? Does (NAME) usually live here? Did (NAME) stay here last night? How old is (NAME)? CIRCLE LINE NUMBER OF ALL WOMEN AGE 15-49 CIRCLE LINE NUMBER OF ALL CHILDREN UNDER AGE 6 CIRCLE LINE NUMBER OF ALL MEN AGE 15-54 CIRCLE LINE NUMBER OF ALL CHILDREN AGE 5 - 17 (1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) M F YES NO YES NO IN YEARS 11 +)))0))), *!!!*!!!* .)))2)))- 1 2 1 2 1 2 +)))0))), *!!!*!!!* .)))2)))- 11 11 11 11 12 +)))0))), *!!!*!!!* .)))2)))- 1 2 1 2 1 2 +)))0))), *!!!*!!!* .)))2)))- 12 12 12 12 13 +)))0))), *!!!*!!!* .)))2)))- 1 2 1 2 1 2 +)))0))), *!!!*!!!* .)))2)))- 13 13 13 13 14 +)))0))), *!!!*!!!* .)))2)))- 1 2 1 2 1 2 +)))0))), *!!!*!!!* .)))2)))- 14 14 14 14 15 +)))0))), *!!!*!!!* .)))2)))- 1 2 1 2 1 2 +)))0))), *!!!*!!!* .)))2)))- 15 15 15 15 16 +)))0))), *!!!*!!!* .)))2)))- 1 2 1 2 1 2 +)))0))), *!!!*!!!* .)))2)))- 16 16 16 16 17 +)))0))), *!!!*!!!* .)))2)))- 1 2 1 2 1 2 +)))0))), *!!!*!!!* .)))2)))- 17 17 17 17 18 +)))0))), *!!!*!!!* .)))2)))- 1 2 1 2 1 2 +)))0))), *!!!*!!!* .)))2)))- 18 18 18 18 19 +)))0))), *!!!*!!!* .)))2)))- 1 2 1 2 1 2 +)))0))), *!!!*!!!* .)))2)))- 19 9 9 9 20 +)))0))), *!!!*!!!* .)))2)))- 1 2 1 2 1 2 +)))0))), *!!!*!!!* .)))2)))- 20 20 20 20 * CODES FOR Q.3 RELATIONSHIP TO HEAD OF HOUSEHOLD: 01 = HEAD 02 = WIFE OR HUSBAND 03 = SON OR DAUGHTER 04 = SON-IN-LAW OR DAUGHTER-IN-LAW 05 = GRANDCHILD 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.12 THROUGH Q.15 THESE QUESTIONS REFER TO THE BIOLOGICAL PARENTS OF THE CHILD. IN Q.13 AND Q.15, RECORD ‘00' IF PARENT NOT LISTED IN HOUSEHOLD SCHEDULE. ***CODES FOR Qs. 17, 20 AND 22 EDUCATION LEVEL: 0 = PRESCHOOL 1 = PRIMARY 2 = SECONDARY 3 = POST SECONDARY 8 = DON’T KNOW EDUCATION GRADE: 00 = LESS THAN 1 YEAR COMPLETED 98 = DON’T KNOW HE5 LINE NO. PARENTAL SURVIVORSHIP AND RESIDENCE FOR PERSONS LESS THAN 18 YEARS OLD** EDUCATION Is (NAME)’s natural mother alive? IF ALIVE Is (NAME)’s natural father alive? IF ALIVE IF AGE 4 YEARS OR OLDER IF AGE 4-24 YEARS Does (NAME)’s natural mother live in this house- hold? IF YES: What is her name? RECORD MOTHER’S LINE NUMBER Does (NAME)’s natural father live in this house- hold? IF YES: What is his name? RECORD FATHER’S LINE NUMBER Has (NAME) ever attended school? What is the highest level of school (NAME) has attended?*** What is the highest grade (NAME) completed at that level?*** Is (NAME) currently attending school? During the current school year (2000), did (NAME) attend school at any time? During the current school year (2000), what level and grade [is/was] (NAME) attending?*** During the previous school year (1999), did (NAME) attend school at any time? During that school year (1999), what level and grade did (NAME) attend?*** (12) (13) (14) (15) (16) (17) (18) (19) (20) (21) (22) YES NO DK YES NO DK YES NO LEVEL GRADE YES NO YES NO LEVEL GRADE YES NO LEVEL GRADE 11 1 2 8 +)))0))), *!!!*!!!* .)))2)))- 1 2 8 +)))0))), *!!!*!!!* .)))2)))- 1 2 NEXT=- LINE +))), *!!!* .)))- +)))0))), *!!!*!!!* .)))2)))- 1 2 .< GO TO 20 1 2 GO TO=- 21 +))), *!!!* .)))- +)))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 20 1 2 GO TO=- 21 +))), *!!!* .)))- +)))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 20 1 2 GO TO=- 21 +))), *!!!* .)))- +)))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 20 1 2 GO TO=- 21 +))), *!!!* .)))- +)))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 20 1 2 GO TO=- 21 +))), *!!!* .)))- +)))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 20 1 2 GO TO=- 21 +))), *!!!* .)))- +)))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 20 1 2 GO TO=- 21 +))), *!!!* .)))- +)))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 20 1 2 GO TO=- 21 +))), *!!!* .)))- +)))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 20 1 2 GO TO=- 21 +))), *!!!* .)))- +)))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 20 1 2 .< GO TO 21 +))), *!!!* .)))- +)))0))), *!!!*!!!* .)))2)))- 1 2 NEXT=- LINE +))), *!!!* .)))- +)))0))), *!!!*!!!* .)))2)))- TICK HERE IF CONTINUATION SHEET USED +)), .))- Just to make sure that I have a complete listing: 1) Are there any other persons such as small children or infants that we have not listed? YES +))), .)))2))< ENTER EACH IN TABLE NO +))), .)))- 2) In addition, are there any other people who may not be members of your family, such as domestic servants, lodgers or friends who usually live here? YES +))), .)))2))< ENTER EACH 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))< ENTER EACH IN TABLE NO +))), .)))- HE6 NO. QUESTIONS AND FILTERS CODING CATEGORIES SKIP 23 What is the MAIN source of drinking water for members of your household? PIPED WATER PIPED INTO DWELLING . . . . . . . 11 PIPED INTO YARD/PLOT . . . . . . . 12 PUBLIC TAP . . . . . . . . . . . . . . . . . 13 WATER FROM OPEN WELL OPEN WELL IN YARD/PLOT . . . . 21 OPEN PUBLIC WELL . . . . . . . . . . 22 WATER FROM COVERED WELL PROTECTED WELL IN YARD/PLOT . . . . . . . . . . . . . . . 31 PROTECTED PUBLIC WELL . . . . 32 WATER FROM BOREHOLE BOREHOLE IN YARD/PLOT . . . . 33 BOREHOLE PUBLIC . . . . . . . . . . 34 SURFACE WATER SPRING . . . . . . . . . . . . . . . . . . . . 41 RIVER/STREAM . . . . . . . . . . . . . . 42 POND/LAKE . . . . . . . . . . . . . . . . . 43 DAM . . . . . . . . . . . . . . . . . . . . . . . 44 RAINWATER . . . . . . . . . . . . . . . . . . 51 TANKER TRUCK . . . . . . . . . . . . . . . 61 BOTTLED WATER . . . . . . . . . . . . . . 71 GRAVITY FLOW SCHEME . . . . . . . . 81 OTHER 96 (SPECIFY) ))< 25 ))< 25 ))< 25 ))< 25 ))< 25 ))< 25 ))< 25 24 How long does it take you to go there, get water, and come back? +)))0)))0))), MINUTES . . . . . . . . . . . . *!!!*!!!*!!!* .)))2)))2)))- ON PREMISES . . . . . . . . . . . . . . . . 996 25 What kind of toilet facility does your household have? FLUSH TOILET . . . . . . . . . . . . . . . . . 11 PIT TOILET/LATRINE TRADITIONAL PIT TOILET . . . . . 21 VENTILATED IMPROVED PIT (VIP) LATRINE . . . . . . . . . . . . . 22 NO FACILITY/BUSH/FIELD . . . . . . . 31 OTHER 96 (SPECIFY) ))< 27 26 Do you share this facility with other households? YES . . . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 27 Does your household have: Electricity? A radio? A television? A telephone? A refrigerator? A lantern? A cupboard? YES NO ELECTRICITY . . . . . . . . . . . . . . 1 2 RADIO . . . . . . . . . . . . . . . . . . . 1 2 TELEVISION . . . . . . . . . . . . . . . 1 2 TELEPHONE . . . . . . . . . . . . . . 1 2 REFRIGERATOR . . . . . . . . . . . 1 2 LANTERN . . . . . . . . . . . . . . . . . 1 2 CUPBOARD . . . . . . . . . . . . . . . 1 2 28 What type of fuel does your household mainly use for cooking? ELECTRICITY . . . . . . . . . . . . . . . . . . 01 LPG/NATURAL GAS . . . . . . . . . . . . . 02 BIOGAS . . . . . . . . . . . . . . . . . . . . . . 03 KEROSENE . . . . . . . . . . . . . . . . . . . 04 CHARCOAL . . . . . . . . . . . . . . . . . . . 05 FIREWOOD, STRAW . . . . . . . . . . . . 06 DUNG . . . . . . . . . . . . . . . . . . . . . . . . 07 OTHER 96 (SPECIFY) 29 What type of fuel does your household mainly use for lighting? ELECTRICITY . . . . . . . . . . . . . . . . . . 01 LPG/NATURAL GAS . . . . . . . . . . . . . 02 BIOGAS . . . . . . . . . . . . . . . . . . . . . . 03 KEROSENE . . . . . . . . . . . . . . . . . . . 04 CHARCOAL . . . . . . . . . . . . . . . . . . . 05 FIREWOOD, STRAW . . . . . . . . . . . . 06 DUNG . . . . . . . . . . . . . . . . . . . . . . . . 07 OTHER 96 (SPECIFY) NO. QUESTIONS AND FILTERS CODING CATEGORIES SKIP HE7 30 MAIN MATERIAL OF THE FLOOR. RECORD OBSERVATION. NATURAL FLOOR EARTH/SAND . . . . . . . . . . . . . . . . 11 DUNG . . . . . . . . . . . . . . . . . . . . . . 12 FINISHED FLOOR PARQUET AND POLISHED WOOD . . . . . . . . . . . . . . . . . . . 31 VINYL OR ASPHALT STRIPS . . . 32 CERAMIC TILES . . . . . . . . . . . . . . 33 CEMENT . . . . . . . . . . . . . . . . . . . . 34 OTHER 96 (SPECIFY) 31 MAIN MATERIAL OF THE ROOF. RECORD OBSERVATION. THATCHED . . . . . . . . . . . . . . . . . . . 01 IRON SHEETS . . . . . . . . . . . . . . . . . 02 ASBESTOS . . . . . . . . . . . . . . . . . . . 03 TILES . . . . . . . . . . . . . . . . . . . . . . . . 04 TIN . . . . . . . . . . . . . . . . . . . . . . . . . . 05 CEMENT . . . . . . . . . . . . . . . . . . . . . . 06 OTHER 96 (SPECIFY) 32 MAIN MATERIAL OF THE WALL. RECORD OBSERVATION. THATCHED . . . . . . . . . . . . . . . . . . . 01 MUD AND POLE . . . . . . . . . . . . . . . . 02 UNBURNT BRICKS . . . . . . . . . . . . . 03 BURNT BRICKS WITH MUD . . . . . . 04 BURNT BRICKS WITH CEMENT . . . 05 TIMBER . . . . . . . . . . . . . . . . . . . . . . 06 CEMENT BLOCKS . . . . . . . . . . . . . . 07 STONE . . . . . . . . . . . . . . . . . . . . . . . 08 OTHER 96 (SPECIFY) 33 Does any member of your household own: A bicycle? A motorcycle or motor scooter? A car or truck? A boat or canoe? A donkey? YES NO BICYCLE . . . . . . . . . . . . . . . . . 1 2 MOTORCYCLE/SCOOTER . . . 1 2 CAR/TRUCK . . . . . . . . . . . . . . . 1 2 BOAT/CANOE . . . . . . . . . . . . . 1 2 DONKEY . . . . . . . . . . . . . . . . . . 1 2 34 Does your household have any mosquito nets that can be used while sleeping? YES . . . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 ))< 38 35 CHECK COLUMNS (6) AND (7): NUMBER OF CHILDREN UNDER AGE 5 WHO SLEPT IN THE HOUSEHOLD LAST NIGHT NONE +))), .)))2)))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))))) ONE +))), TWO OR MORE +))), /)))- .)))2))))))))))))))))))))))))))))))))))) * ? ))< 38 ))< 37 36 Did (NAME) sleep under a mosquito net last night? YES . . . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 ), )2< 38 37 Did all, some or none of the children under age 5 who slept in the household last night sleep under a mosquito net? ALL CHILDREN . . . . . . . . . . . . . . . . . 1 SOME CHILDREN . . . . . . . . . . . . . . . 2 NONE . . . . . . . . . . . . . . . . . . . . . . . . . 3 38 Where do you usually wash your hands? IN DWELLING/YARD/PLOT . . . . . . . . 1 SOMEWHERE ELSE . . . . . . . . . . . . . 2 NOWHERE . . . . . . . . . . . . . . . . . . . . . 3 ), )2)< 40 39 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 40 ASK RESPONDENT FOR A TEASPOONFUL OF SALT. TEST SALT FOR IODINE. RECORD PPM (PARTS PER MILLION). 0 PPM (NO IODINE) . . . . . . . . . . . . . . 1 BELOW 15 PPM . . . . . . . . . . . . . . . . . 2 15 PPM+ . . . . . . . . . . . . . . . . . . . . . . . 3 NO SALT . . . . . . . . . . . . . . . . . . . . . . 4 HE8 CHILD LABOUR MODULE FOR CHILDREN AGES 5-17 LINE NO. FROM COL.(11) NAME FROM COL.(2) At any time during the past year, did ( NAME) do any kind of work for someone who is not a member of this household? WORKED AT ANY TIME IN THE PAST YEAR Since last [DAY OF THE WEEK], did (NAME) do any kind of work for someone who is not a member of this household? Describe briefly the main work or job* that (NAME) did. Since last [DAY OF THE WEEK], how many hours did (NAME) do this work? Since last (DAY OF THE WEEK] did (NAME) regularly help with household chores such as cooking, shopping, cleaning, washing clothes, fetching water or caring for animals? Since last [DAY OF THE WEEK], how many hours a week did (NAME) spend doing these chores? Since last (DAY OF THE WEEK), did (NAME) do any other family work (on the farm or in a business)? Since last (DAY OF THE WEEK), how many hours did (NAME) do this work? Describe briefly the main work or job* that (NAME) did. Was (NAME) a regular paid employee, a casual labourer, paid per piece or unpaid?** Where did (NAME) carry out the work? *** (1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) (13) YES NO## # YES NO## NO. OF HOURS YES NO## NO. OF HOURS YES NO## NO. OF HOURS +)))0))), *!!!*!!!* .)))2)))- ))))))))))))))))))))) 1 2 # *## GO TO 10=-## +)))0))), *!!!*!!!* .)))2)))- +))), *!!!* .)))- +)))0))), *!!!*!!!* .)))2)))- 1 2 ## *## GO TO 10=-## +)))0))), *!!!*!!!* .)))2)))- +)))0))), *!!!*!!!* .)))2)))- 1 2 # *## GO TO 12=-## +)))0))), *!!!*!!!* .)))2)))- 1 2 *# NEXT LINE=-# +)))0))), *!!!*!!!* .)))2)))- +)))0))), *!!!*!!!* .)))2)))- ))))))))))))))))))))) 1 2 # *## GO TO 10=-## +)))0))), *!!!*!!!* .)))2)))- +))), *!!!* .)))- +)))0))), *!!!*!!!* .)))2)))- 1 2 ## *## GO TO 10=-## +)))0))), *!!!*!!!* .)))2)))- +)))0))), *!!!*!!!* .)))2)))- 1 2 # *## GO TO 12=-## +)))0))), *!!!*!!!* .)))2)))- 1 2 *# NEXT LINE=-# +)))0))), *!!!*!!!* .)))2)))- +)))0))), *!!!*!!!* .)))2)))- ))))))))))))))))))))) 1 2 # *## GO TO 10=-## +)))0))), *!!!*!!!* .)))2)))- +))), *!!!* .)))- +)))0))), *!!!*!!!* .)))2)))- 1 2 ## *## GO TO 10=-## +)))0))), *!!!*!!!* .)))2)))- +)))0))), *!!!*!!!* .)))2)))- 1 2 # *## GO TO 12=-## +)))0))), *!!!*!!!* .)))2)))- 1 2 *# NEXT LINE=-# +)))0))), *!!!*!!!* .)))2)))- +)))0))), *!!!*!!!* .)))2)))- ))))))))))))))))))))) 1 2 # *## GO TO 10=-## +)))0))), *!!!*!!!* .)))2)))- +))), *!!!* .)))- +)))0))), *!!!*!!!* .)))2)))- 1 2 ## *## GO TO 10=-## +)))0))), *!!!*!!!* .)))2)))- +)))0))), *!!!*!!!* .)))2)))- 1 2 # *## GO TO 12=-## +)))0))), *!!!*!!!* .)))2)))- 1 2 *# NEXT LINE=-# +)))0))), *!!!*!!!* .)))2)))- +)))0))), *!!!*!!!* .)))2)))- ))))))))))))))))))))) 1 2 # *## GO TO 10=-## +)))0))), *!!!*!!!* .)))2)))- +))), *!!!* .)))- +)))0))), *!!!*!!!* .)))2)))- 1 2 ## *## GO TO 10=-## +)))0))), *!!!*!!!* .)))2)))- +)))0))), *!!!*!!!* .)))2)))- 1 2 # *## GO TO 12=-## +)))0))), *!!!*!!!* .)))2)))- 1 2 *# NEXT LINE=-# +)))0))), *!!!*!!!* .)))2)))- +)))0))), *!!!*!!!* .)))2)))- ))))))))))))))))))))) 1 2 # *## GO TO 10=-## +)))0))), *!!!*!!!* .)))2)))- +))), *!!!* .)))- +)))0))), *!!!*!!!* .)))2)))- 1 2 ## *## GO TO 10=-## +)))0))), *!!!*!!!* .)))2)))- +)))0))), *!!!*!!!* .)))2)))- 1 2 # *## GO TO 12=-## +)))0))), *!!!*!!!* .)))2)))- 1 2 *# END=-# +)))0))), *!!!*!!!* .)))2)))- +))), TICK HERE IF CONTINUATION SHEET USED *!!!* .)))- * CODES FOR COLUMN 4 AND 8 ** CODES FOR COLUMN 5 ***CODES FOR COLUMN 6 01 = SALES, SERVICES 1 = REGULAR PAID EMPLOYEE 01 = AT FAMILY DWELLING 02 = UNSKILLED MANUAL 2 = CASUAL LABOURER 02 = AT EMPLOYER’S HOUSE 03 = HOUSEHOLD/DOMESTIC 3 = PAID AT PIECE RATE 03 = ON THE STREET 04 = CROP FARMING 4 = UNPAID 04 = SHOP/MARKET/KIOSK 05 = LIVESTOCK REARING 05 = INDUSTRY/FACTORY 06 = FISHING 06 = PLANTATION/FARM/GARDEN 07 = MANUFACTURING 07 = CONSTRUCTION/QUARRYING SITES 08 = OTHER 08 = OTHER HE9 There will be an education survey done at a later point in time. Your household may or may not be asked to participate in this survey. If your household is included in the survey, someone will return to your house and ask additional questions about education. HE10 WEIGHT, HEIGHT AND HEMOGLOBIN MEASUREMENT * 1 = MEASURED; 2 = NOT PRESENT; 3= REFUSED; 4 = DISABLED; 6 = OTHER CHECK COLUMNS (8) AND (9): RECORD THE LINE NUMBER, NAME AND AGE OF ALL WOMEN AGE 15-49 AND ALL CHILDREN UNDER AGE 6. WOMEN 15-49 WEIGHT AND HEIGHT MEASUREMENT OF WOMEN 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* (41) (42) (43) (44) (45) (46) (47) (48) 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)))-.)))- +))), *!!!* .)))- 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* 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 +))), *!!!* .)))- MEN AGE 15-54 LINE NO. FROM COL.(10) NAME FROM COL.(2) AGE FROM COL.(7) +)))0))), *!!!*!!!* .)))2)))- +)))0))), *!!!*!!!* .)))2)))- +)))0))), *!!!*!!!* .)))2)))- +)))0))), *!!!*!!!* .)))2)))- +)))0))), *!!!*!!!* .)))2)))- +)))0))), *!!!*!!!* .)))2)))- TICK HERE IF CONTINUATION SHEET USED +)), .))- HE11 * RECORD ‘00' IF NOT LISTED IN HOUSEHOLD SCHEDULE ** CONSENT STATEMENT As part of this survey, we are studying anemia (and vitamin A deficiency) among women, men and children. This (these) problem(s) often result from poor nutrition. This survey will assist the government to develop programs to prevent and treat anemia (and vitamin A deficiency). We request that you (and all children born in 1995 or later) participate in the anemia (and vitamin A deficiency) testing as part of this survey and give a few drops of blood from a finger. The tests use disposable sterile instruments that are clean and completely safe. For anemia test, the blood will be analyzed with new equipment and the results of the test will be given to you right after the blood is taken. (The vitamin A test has to be done in a laboratory so you will not be given the results). The results of the (both) test(s) will be kept confidential. May I now ask that you (and NAME OF CHILD[REN]) participate in the anemia (and vitamin A deficiency test). However, if you decide not to have the test done, it is your right and we will respect your decision. Now please tell me if you agree to have the test(s) done. *** 1 = MEASURED; 2 = NOT PRESENT; 3 = REFUSED; 6 = OTHER HEMOGLOBIN AND VITAMIN A MEASUREMENTS OF WOMEN 15-49 CHECK COLUMN (43): LINE NO. OF PARENT/ RESPONSIBLE ADULT.* READ CONSENT STATEMENT TO WOMAN/PARENT/RESPONSIBLE ADULT** CIRCLE CODE (AND SIGN) TESTED FOR VITAMIN A DEFICIENCY HEMOGLOBIN LEVEL (G/DL) CURRENTLY PREGNANT RESULT*** (49) (50) (51) (52) (53) (54) (55) AGE 15-17 AGE 18-49 GRANTED REFUSED YES NO NA YES NO/DK 1 2 * GO TO 51 =)))- +)))0))), *!!!*!!!* .)))2)))- 1 ? SIGN 2 * NEXT LINE =)))- 1 2 3 +)))0))), +))), *!!!*!!!* *!!!* .)))2)))-.)))- 1 2 +))), *!!!* .)))- 1 2 * GO TO 51 =)))- +)))0))), *!!!*!!!* .)))2)))- 1 ? SIGN 2 * NEXT LINE =)))- 1 2 3 +)))0))), +))), *!!!*!!!* *!!!* .)))2)))-.)))- 1 2 +))), *!!!* .)))- 1 2 * GO TO 51 =)))- +)))0))), *!!!*!!!* .)))2)))- 1 ? SIGN 2 * NEXT LINE =)))- 1 2 3 +)))0))), +))), *!!!*!!!* *!!!* .)))2)))-.)))- 1 2 +))), *!!!* .)))- HEMOGLOBIN AND VITAMIN A MEASUREMENTS OF CHILDREN BORN IN 1995 OR LATER LINE NO. OF PARENT/ RESPONSIBLE ADULT. READ CONSENT STATEMENT TO PARENT/RESPONSIBLE ADULT** CIRCLE CODE (AND SIGN) TESTED FOR VITAMIN A DEFICIENCY HEMOGLOBIN LEVEL (G/DL) RESULT*** GRANTED REFUSED YES NO NA +)))0))), *!!!*!!!* .)))2)))- 1 ? SIGN 2 * NEXT LINE =)))- 1 2 3 +)))0))), +))), *!!!*!!!* *!!!* .)))2)))-.)))- +))), *!!!* .)))- +)))0))), *!!!*!!!* .)))2)))- 1 ? SIGN 2 * NEXT LINE =)))- 1 2 3 +)))0))), +))), *!!!*!!!* *!!!* .)))2)))-.)))- +))), *!!!* .)))- +)))0))), *!!!*!!!* .)))2)))- 1 ? SIGN 2 * NEXT LINE =)))- 1 2 3 +)))0))), +))), *!!!*!!!* *!!!* .)))2)))-.)))- +))), *!!!* .)))- HEMOGLOBIN MEASUREMENT OF MEN 15-54 CHECK COLUMN (43): LINE NO. OF PARENT/ RESPONSIBLE ADULT READ CONSENT STATEMENT TO WOMAN/PARENT/RESPONSIBLE ADULT** CIRCLE CODE (AND SIGN) HEMOGLOBIN LEVEL (G/DL) RESULT*** AGE 15-17 AGE 18-54 GRANTED REFUSED 1 2 * GO TO 51 =)))- +)))0))), *!!!*!!!* .)))2)))- 1 ? SIGN 2 * NEXT LINE =)))- +)))0))), +))), *!!!*!!!* *!!!* .)))2)))-.)))- +))), *!!!* .)))- 1 2 * GO TO 51 =)))- +)))0))), *!!!*!!!* .)))2)))- 1 ? SIGN 2 * NEXT LINE =)))- +)))0))), +))), *!!!*!!!* *!!!* .)))2)))-.)))- +))), *!!!* .)))- HE12 1 2 * GO TO 51 =)))- +)))0))), *!!!*!!!* .)))2)))- 1 ? SIGN 2 * NEXT LINE =)))- +)))0))), +))), *!!!*!!!* *!!!* .)))2)))-.)))- +))), *!!!* .)))- HE13 55 CHECK 52 AND 53: NUMBER OF PERSONS WITH HEMOGLOBIN LEVEL BELOW THE CUTOFF POINT* ONE OR MORE +), /)- ? GIVE EACH WOMAN/MAN/PARENT/RESPONSIBLE ADULT RESULT OF HEMOGLOBIN MEASUREMENT, REFERRAL LETTER AND END THE INTERVIEW. NONE +), /)- ? GIVE EACH WOMAN/MAN/PARENT/RESPONSIBLE ADULT RESULT OF HEMOGLOBIN MEASUREMENT AND END THE INTERVIEW. 56 We detected a low level of hemoglobin in (your blood/the blood of NAME OF CHILD(REN)). This indicates that (you/NAME OF CHILD(REN)) have developed severe anemia, which is a serious health problem. You should seek medical assistance for this problem. We will give you a letter of referral which you can take to the doctor or health facility you consult. It provides information on the results of your test that will help the doctor or health afcility. C The cutoff point is 9 g/dl for pregnant women and 7 g/dl for children, women who are not pregnant (or who don’t know if they are pregnant), and men. ** If more than one woman, man or child is below the cutoff point, read the statement in Q.56 to each woman who is below the cutoff point and each woman/parent/responsible adult for whom a child is below the cutoff point. TO BE FILLED IN AFTER COMPLETING INTERVIEW COMMENTS ABOUT MEASUREMENT: WE1 2000 UGANDA DEMOGRAPHIC AND HEALTH SURVEY WOMEN’S QUESTIONNAIRE IDENTIFICATION REGION DISTRICT COUNTY SUBCOUNTY/TOWN PARISH/LC2 NAME EA NAME UDHS NUMBER URBAN/RURAL (URBAN=1, RURAL=2) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . LARGE CITY/SMALL CITY/TOWN/COUNTRYSIDE . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . (LARGE CITY=1, SMALL CITY=2, TOWN=3, COUNTRYSIDE=4) HOUSEHOLD NUMBER . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . NAME AND LINE NUMBER OF WOMAN +))), !!*!!!* +)))3)))1 *!!!*!!!* .)))3)))1 !!!*!!!* /)))1 *!!!* +)))3)))1 *!!!*!!!* /)))3)))1 *!!!*!!!* +)))0)))3)))3)))1 *!!!*!!!*!!!*!!!* .)))2)))2)))3)))1 *!!!* /)))1 *!!!* +)))0)))3)))1 *!!!*!!!*!!!* .)))3)))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 +))), *!7!* /)))1 LANGUAGE USED IN INTERVIEW . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . *!!!* /)))1 RESPONDENT'S LOCAL LANGUAGE . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . *!!!* /)))1 TRANSLATOR USED (NOT AT ALL=1; SOMETIMES=2; ALL THE TIME=3) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . *!!!* LANGUAGE: 1 ATESO-KARAMOJONG 4 LUO 7 ENGLISH .)))- 2 LUGANDA 5 RUNYANKOLE-RUKIGA 8 OTHER 3 LUGBARA 6 RUNYORO-RUTORO SUPERVISOR FIELD EDITOR OFFICE EDITOR KEYED BY NAME +)))0))), *!!!*!!!* .)))2)))- NAME +)))0))), *!!!*!!!* .)))2)))- +)))0))), *!!!*!!!* .)))2)))- +)))0))), *!!!*!!!* .)))2)))-DATE DATE WE2 SECTION 1. RESPONDENT’S BACKGROUND INTRODUCTION AND CONSENT INFORMED CONSENT Hello. My name is and I am working with Uganda Bureau of Statistics. We are conducting a national survey about the health of women and children. We would very much appreciate your participation in this survey. I would like to ask you about your health (and the health of your children). This information will help the government to plan health services. The survey usually takes between 20 and 45 minutes to complete. Whatever information you provide will be kept strictly confidential and will not be shown to other persons. At this time, do you want to ask me anything about the survey? May I begin the interview now? Signature of interviewer: Date: RESPONDENT AGREES TO BE INTERVIEWED . . 1 ? RESPONDENT DOES NOT AGREE TO BE INTERVIEWED . . 2 ))<END NO. QUESTIONS AND FILTERS CODING CATEGORIES SKIP 101 RECORD THE TIME. +)))0))), HOUR . . . . . . . . . . . . . . . . . . . *!!!*!!!* /)))3)))1 MINUTES . . . . . . . . . . . . . . . . *!!!*!!!* .)))2)))- 102 For most of the time during the last five years, did you live in a city, in a town, or in the countryside? CITY . . . . . . . . . . . . . . . . . . . . . . . . . . 1 TOWN . . . . . . . . . . . . . . . . . . . . . . . . . 2 COUNTRYSIDE . . . . . . . . . . . . . . . . . 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 the countryside? CITY . . . . . . . . . . . . . . . . . . . . . . . . . . 1 TOWN . . . . . . . . . . . . . . . . . . . . . . . . . 2 COUNTRYSIDE . . . . . . . . . . . . . . . . . 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 post secondary? PRIMARY . . . . . . . . . . . . . . . . . . . . . . 1 SECONDARY . . . . . . . . . . . . . . . . . . . 2 POST SECONDARY . . . . . . . . . . . . . . 3 109 What is the highest (grade/form/year) you completed at that level? +)))0))), GRADE . . . . . . . . . . . . . . . . . . *!!!*!!!* .)))2)))- 109A Did you ever receive any vocational training? NO TRAINING . . . . . . . . . . . . . . . . . . 1 TEACHER TRAINING . . . . . . . . . . . . . 2 PARAMEDICAL TRAINING . . . . . . . . 3 OTHER TRAINING . . . . . . . . . . . . . . . 6 110 CHECK 108: PRIMARY +))), SECONDARY OR +))), /)))- POST SECONDARY .)))2))))))))))))))))))))))))))))))))))))))))))))))))) ? ))<114 NO. QUESTIONS AND FILTERS CODING CATEGORIES SKIP WE3 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 During the last 4 weeks, did you read a newspaper or magazine almost every day, at least once a week, less than once a week or not at all? ALMOST EVERY DAY . . . . . . . . . . . . 1 AT LEAST ONCE A WEEK . . . . . . . . . 2 LESS THAN ONCE A WEEK . . . . . . . 3 NOT AT ALL . . . . . . . . . . . . . . . . . . . . 4 115 During the last 4 weeks, did you listen to the radio almost every day, at least once a week, less than once a week or not at all? ALMOST EVERY DAY . . . . . . . . . . . . 1 AT LEAST ONCE A WEEK . . . . . . . . . 2 LESS THAN ONCE A WEEK . . . . . . . 3 NOT AT ALL . . . . . . . . . . . . . . . . . . . . 4 116 During the last 4 weeks, did you watch television almost every day, at least once a week, less than once a week or not at all? ALMOST EVERY DAY . . . . . . . . . . . . 1 AT LEAST ONCE A WEEK . . . . . . . . . 2 LESS THAN ONCE A WEEK . . . . . . . 3 NOT AT ALL . . . . . . . . . . . . . . . . . . . . 4 117 What is your religion? CATHOLIC . . . . . . . . . . . . . . . . . . . . . 1 PROTESTANT . . . . . . . . . . . . . . . . . . 2 MUSLIM . . . . . . . . . . . . . . . . . . . . . . . 3 OTHER 6 (SPECIFY) 119 Have you ever drunk an alcohol-containing beverage? YES . . . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 ))<123 120 In the last 30 days, on how many days did you drink an alcohol- containing beverage? +)))0))), NUMBER OF DAYS . . . . . . . . *!!!*!!!* .)))2)))- NONE . . . . . . . . . . . . . . . . . . . . . . . . 95 121 Have you ever gotten “drunk” from drinking an alcohol-containing beverage? YES . . . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 ))<123 121A CHECK 120: DRANK ALCOHOL ON +), NONE/NEVER +), AT LEAST ONE DAY /)- .)2)))))))))))))))))))))))))))))))))))))))))) ? ))<123 122 In the last 30 days, on how many occasions did you get “drunk”? +)))0))), NUMBER OF TIMES . . . . . . . . *!!!*!!!* .)))2)))- NONE/NEVER . . . . . . . . . . . . . . . . . 95 123 Have you had any kind of injection in the last 3 months? YES . . . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 ))<201 124 How many times did you have an injection in the last 3 months? +)))0))), NUMBER OF INJECTIONS . . *!!!*!!!* .)))2)))- EVERY DAY . . . . . . . . . . . . . . . . . . . 95 125 The last time you had an injection, who was the person who gave you the injection? HEALTH PROFESSIONAL . . . . . . . . . 1 TRADITIONAL HEALER . . . . . . . . . . . 2 FRIEND/RELATIVE . . . . . . . . . . . . . . 3 SELF . . . . . . . . . . . . . . . . . . . . . . . . . . 4 OTHER 6 (SPECIFY) WE4 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 hours or days? 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 WE5 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 What name was given to your (first/next) baby? (NAME) Were any of these births twins? Is (NAME) a boy or a girl? In what month and year was (NAME) born? PROBE: What is his/her birthday? Is (NAME) still alive? How old was (NAME) at his/her last birthday? RECORD AGE IN COM- PLETED YEARS. Is (NAME) living with you? RECORD HOUSEHOLD LINE NUMBER OF CHILD (RECORD ‘00' IF CHILD NOT LISTED IN HOUSEHOLD). How old was (NAME) when he/she died? IF ‘1 YR’, PROBE: How many months old was (NAME)? RECORD DAYS IF LESS THAN 1 MONTH; MONTHS IF LESS THAN TWO YEARS; OR YEARS. Were there any other live births between (NAME OF PREVIOUS BIRTH) and (NAME)? 01 SING . 1 MULT 2 BOY 1 GIRL 2 +)))0))), MONTH *!!!*!!!* .)))2)))- YEAR +)))0)))0)))0))), *!!!*!!!*!!!*!!!* .)))2)))2)))2)))- YES . 1 NO . . 2 * ? 220 AGE IN YEARS +)))0))), *!!!*!!!* .)))2)))- YES . . 1 NO . . . 2 LINE 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 AGE IN YEARS +)))0))), *!!!*!!!* .)))2)))- YES . . 1 NO . . . 2 LINE 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 AGE IN YEARS +)))0))), *!!!*!!!* .)))2)))- YES . . 1 NO . . . 2 LINE 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 AGE IN YEARS +)))0))), *!!!*!!!* .)))2)))- YES . . 1 NO . . . 2 LINE 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 AGE IN YEARS +)))0))), *!!!*!!!* .)))2)))- YES . . 1 NO . . . 2 LINE 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 AGE IN YEARS +)))0))), *!!!*!!!* .)))2)))- YES . . 1 NO . . . 2 LINE 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 AGE IN YEARS +)))0))), *!!!*!!!* .)))2)))- YES . . 1 NO . . . 2 LINE 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 WE6 What name was given to your next baby? (NAME) Were any of these births twins? Is (NAME) a boy or a girl? In what month and year was (NAME) born? PROBE: What is his/her birthday? Is (NAME) still alive? How old was (NAME) at his/her last birthday? RECORD AGE IN COM- PLETED YEARS. Is (NAME) living with you? RECORD HOUSEHOLD LINE NUMBER OF CHILD (RECORD ‘00' IF CHILD NOT LISTED IN HOUSEHOLD). How old was (NAME) when he/she died? IF ‘1 YR’, PROBE: How many months old was (NAME)? RECORD DAYS IF LESS THAN 1 MONTH; MONTHS IF LESS THAN TWO YEARS; OR YEARS. Were there any other live births between (NAME OF PREVIOUS BIRTH) and (NAME)? 08 SING . 1 MULT 2 BOY 1 GIRL 2 +)))0))), MONTH *!!!*!!!* .)))2)))- YEAR +)))0)))0)))0))), *!!!*!!!*!!!*!!!* .)))2)))2)))2)))- YES . 1 NO . . 2 * ? 220 AGE IN YEARS +)))0))), *!!!*!!!* .)))2)))- YES . . 1 NO . . . 2 LINE 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 AGE IN YEARS +)))0))), *!!!*!!!* .)))2)))- YES . . 1 NO . . . 2 LINE 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 AGE IN YEARS +)))0))), *!!!*!!!* .)))2)))- YES . . 1 NO . . . 2 LINE 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 AGE IN YEARS +)))0))), *!!!*!!!* .)))2)))- YES . . 1 NO . . . 2 LINE 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 AGE IN YEARS +)))0))), *!!!*!!!* .)))2)))- YES . . 1 NO . . . 2 LINE NUMBER +)))0))), *!!!*!!!* .)))2)))- * ? (GO TO 221) +)))0))), DAYS . . . 1 *!!!*!!!* /)))3)))1 MONTHS 2 *!!!*!!!* /)))3)))1 YEARS . . 3 *!!!*!!!* .)))2)))- YES . . . 1 NO . . . . 2 222 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'. +))), *!!!* .)))- WE7 NO. QUESTIONS AND FILTERS CODING CATEGORIES SKIP 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 E.G., 01, 02 .09. IF MONTHS ARE NOT KNOWN, RECORD 98 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 ))<236A 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 ))<236A 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 ))<236A 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. 235 Did you have any pregnancies that terminated before 1995 which did not result in a live birth? YES . . . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 ))<236A 236 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)))- 236A How old were you at the time you experienced your first menstruation? +)))0))), YEARS . . . . . . . . . . . . . . . . . . *!!!*!!!* .)))2)))- NEVER MENSTRUATED . . . . . . . . . 96 DON'T KNOW . . . . . . . . . . . . . . . . . . 98 WE8 NO. QUESTIONS AND FILTERS CODING CATEGORIES SKIP 237 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 ), !/<238 )- 237A Some women experience some pains during menstruation. Did/do you experience such pains? YES . . . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 DON’T KNOW . . . . . . . . . . . . . . . . . . . 8 238 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<240 239 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 . . . . . . . . . . . . . . . . . . . 8 240 Do you currently smoke cigarettes or tobacco? IF YES: What type of tobacco do you smoke? RECORD ALL MENTIONED. YES, CIGARETTES . . . . . . . . . . . . . . A YES, PIPES . . . . . . . . . . . . . . . . . . . . B YES, OTHER . . . . . . . . . . . . . . . . . . . C (SPECIFY) NO . . . . . . . . . . . . . . . . . . . . . . . . . . . Y ), !* !* !/<301 !* )- 241 In the last 24 hours, how many cigarettes did you smoke? +)))0))), CIGARETTES . . . . . . . . . . . . . *!!!*!!!* .)))2)))- WE9 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 FEMALE STERILIZATION Women can have an operation to avoid having any more children. YES . . . . . . . . 1 NO . . . . . . . . . 2 ), ? Have you ever had an operation to avoid having any more children? YES . . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . . 2 02 MALE STERILIZATION Men can have an operation to avoid having any more children. YES . . . . . . . . 1 NO . . . . . . . . . 2 ), ? Have you ever had a partner who had an operation to avoid having any more children? YES . . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . . 2 03 PILL Women can take a pill every day to avoid becoming pregnant. YES . . . . . . . . 1 NO . . . . . . . . . 2 ), ? YES . . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . . 2 04 IUD/COIL Women can have a loop or coil placed inside them by a doctor or a nurse. YES . . . . . . . . 1 NO . . . . . . . . . 2 ), ? YES . . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . . 2 05 INJECTABLES Women can have an injection by a health provider which stops them from becoming pregnant for one or more months. YES . . . . . . . . 1 NO . . . . . . . . . 2 ), ? YES . . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . . 2 06 IMPLANTS Women can have several small rods placed in their upper arm by a doctor or nurse which can prevent pregnancy for one or more years. YES . . . . . . . . 1 NO . . . . . . . . . 2 ), ? YES . . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . . 2 07 CONDOM Men can put a rubber sheath on their penis before sexual intercourse. YES . . . . . . . . 1 NO . . . . . . . . . 2 ), ? YES . . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . . 2 08 FEMALE CONDOM Women can place a sheath in their vagina before sexual intercourse. YES . . . . . . . . 1 NO . . . . . . . . . 2 ), ? YES . . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . . 2 09 DIAPHRAGM Women can place a thin flexible disk in their vagina before intercourse. YES . . . . . . . . 1 NO . . . . . . . . . 2 ), ? YES . . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . . 2 10 FOAM OR JELLY Women can place a suppository, jelly, or cream in their vagina before intercourse. YES . . . . . . . . 1 NO . . . . . . . . . 2 ), ? YES . . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . . 2 11 LACTATIONAL AMENORRHEA METHOD (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 RHYTHM OR PERIODIC ABSTINENCE Every month 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 pregnant. YES . . . . . . . . 1 NO . . . . . . . . . 2 ), ? YES . . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . . 2 13 WITHDRAWAL Men can be careful and pull out before climax. YES . . . . . . . . 1 NO . . . . . . . . . 2 ), ? YES . . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . . 2 14 EMERGENCY CONTRACEPTION (NORLEVO) Women can take pills up to three days after sexual intercourse to avoid becoming pregnant. 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 avoid 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) ))<307 304 Have you ever used anything or tried in any way to delay or avoid getting pregnant? YES . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . 2 ))<329 306 What have you used or done? CORRECT 302 AND 303 (AND 301 IF NECESSARY). WE10 NO. QUESTIONS AND FILTERS CODING CATEGORIES SKIP 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))))))))))))))))))))))))))))))))))))))))))))))))))) ? ))<329 310 Are you currently doing something or using any method to delay or avoid getting pregnant? YES . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . 2 ))<329 311 311A Which method are you using? CIRCLE ‘A' FOR FEMALE STERILIZATION. DO NOT PROMPT IF MORE THAN ONE METHOD MENTIONED, FOLLOW SKIP INSTRUCTION FOR HIGHEST METHOD ON LIST. FEMALE STERILIZATION . . . . . . A MALE STERILIZATION . . . . . . . . . B PILL . . . . . . . . . . . . . . . . . . . . . . . C IUD/COIL . . . . . . . . . . . . . . . . . . . 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 ))<316A ))<312A ))<316A ))<312B ), * * * /<316A * * * )- 312 What brand of pill are you currently using? PILPLAN . . . . . . . . . . . . . . . . . . . . 1 MICROGYNON . . . . . . . . . . . . . . . 2 EUGYEN . . . . . . . . . . . . . . . . . . . . 3 LOFEMINAL . . . . . . . . . . . . . . . . . 4 OVRETTE . . . . . . . . . . . . . . . . . . . 5 OTHER . . . . . . . . . . . . . . . . . . . . . 6 DON’T KNOW . . . . . . . . . . . . . . . . 8 ), * * /<316A * * )- 312A What brand of injections are you currently using? INJECTAPLAN . . . . . . . . . . . . . . . 1 DEPO-PROVERA . . . . . . . . . . . . . 2 DON’T KNOW . . . . . . . . . . . . . . . . 8 ), /<316A )- 312B What brand of condom are you currently using? PROTECTOR . . . . . . . . . . . . . . . . 1 ENGABU . . . . . . . . . . . . . . . . . . . . 2 LIFE GUARD . . . . . . . . . . . . . . . . 3 ROUGH RIDER . . . . . . . . . . . . . . . 4 PLEASURE . . . . . . . . . . . . . . . . . . 5 OTHER . . . . . . . . . . . . . . . . . . . . . 6 DON’T KNOW . . . . . . . . . . . . . . . . 8 ), * * /<316A * * )- 313 In what facility 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) PRIVATE MEDICAL SECTOR PRIVATE HOSPITAL/CLINIC . 21 PRIVATE DOCTOR’S OFFICE 23 OTHER PRIVATE MEDICAL 26 (SPECIFY) OTHER 96 (SPECIFY) DON’T KNOW . . . . . . . . . . . . . . . 98 NO. QUESTIONS AND FILTERS CODING CATEGORIES SKIP WE11 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 ‘A’ NOT +))), 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 316A In what month and year was the sterilization performed? When did you start using (CURRENT METHOD) without stopping? PROBE: In what month and year did you start using (CURRENT METHOD) continuously? +)))0))), MONTH . . . . . . . . . . . . . . . *!!!*!!!* .)))2)))- DON’T KNOW MONTH . . . . . . . . 98 +)))0)))0)))0))), YEAR . . . . . . . . . . *!!!*!!!*!!!*!!!* .)))2)))2)))2)))- DON’T KNOW YEAR . . . . . . . 9998 317 CHECK 316/316A: +))), +))), YEAR IS 1995 /)))- YEAR IS 1994 .)))2))))))))))))))))))))))))))))))))))))))))))))))))))) OR LATER ? OR EARLIER ))<327 319 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 MALE STERILIZATION . . . . . . . . 02 PILL . . . . . . . . . . . . . . . . . . . . . . 03 IUD/COIL . . . . . . . . . . . . . . . . . . 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 ))<322 ))<331 ))<320A ))<331 ))<331 ))<331 320 320A 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 OUTREACH . . . . . . . . . . . . . . . 14 GOV'T COMMUNITY BASED DISRIBUTOR . . . . . . . . . . . . 15 OTHER PUBLIC 16 (SPECIFY) PRIVATE MEDICAL SECTOR PRIVATE HOSPITAL/CLINIC . 21 PHARMACY/DRUG SHOP . . . 22 PRIVATE DOCTOR/NURSE/ MIDWIFE . . . . . . . . . . . . . . . 23 OUTREACH . . . . . . . . . . . . . . . 24 NGO COMMUNITY BASED DISTRIBUTOR . . . . . . . . . . . 25 OTHER PRIVATE MEDICAL 26 (SPECIFY) OTHER SOURCE SHOP . . . . . . . . . . . . . . . . . . . 31 RELIGIOUS INSTITUTION . . . 32 FRIEND/RELATIVE . . . . . . . . . 33 OTHER 96 (SPECIFY) 321 CHECK 311/311A: CIRCLE METHOD CODE: IF MORE THAN ONE METHOD CODE CIRCLED IN 311/311A, CIRCLE CODE FOR HIGHEST METHOD IN LIST. PILL . . . . . . . . . . . . . . . . . . . . . . 03 IUD/COIL . . . . . . . . . . . . . . . . . . 04 INJECTIONS . . . . . . . . . . . . . . . . 05 IMPLANTS . . . . . . . . . . . . . . . . . 06 CONDOM . . . . . . . . . . . . . . . . . . 07 FEMALE CONDOM . . . . . . . . . . 08 DIAPHRAGM . . . . . . . . . . . . . . . 09 FOAM/JELLY . . . . . . . . . . . . . . . 10 LACTATIONAL AMEN. METHOD 11 ))<328 ))<325 ))<325 ))<325 ))<325 NO. QUESTIONS AND FILTERS CODING CATEGORIES SKIP WE12 322 You obtained (CURRENT METHOD) from (SOURCE OF METHOD FROM 313 OR 320). At that time, were you told about side effects or problems you might have with the method? YES . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . 2 ))<324 323 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 ))<325 324 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 320), were you told about other methods of family planning which you could use? YES . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . 2 ))<327 326 Were you ever told by a health or family planning worker about other methods of family planning which you could use? YES . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . 2 327 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 MALE STERILIZATION . . . . . . . . 02 PILL . . . . . . . . . . . . . . . . . . . . . . 03 IUD/COIL . . . . . . . . . . . . . . . . . . 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 ))<331 ))<331 ))<331 ))<331 ))<331 ))<331 ))<331 ))<331 328 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 OUTREACH . . . . . . . . . . . . . . . 14 GOV'T COMMUNITY BASED DISTRIBUTOR . . . . . . . . . . . . 15 OTHER PUBLIC 16 (SPECIFY) PRIVATE MEDICAL SECTOR PRIVATE HOSPITAL/CLINIC . 21 PHARMACY/DRUG SHOP . . . 22 PRIVATE DOCTOR/NURSE/ MIDWIFE . . . . . . . . . . . . . . . . 23 OUTREACH . . . . . . . . . . . . . . . 24 NGO COMMUNITY BASED DISTRIBUTOR . . . . . . . . . . . . 25 OTHER PRIVATE MEDICAL 26 (SPECIFY) OTHER SOURCE SHOP . . . . . . . . . . . . . . . . . . . 31 RELIGIOUS INSTITUTION . . . 32 FRIEND/RELATIVE . . . . . . . . . 33 OTHER 96 (SPECIFY) ), * * * * * * * * * * /<331 * * * * * * * * * * )- 329 Do you know of a place where you can obtain a method of family planning? YES . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . 2 ))<331 NO. QUESTIONS AND FILTERS CODING CATEGORIES SKIP WE13 330 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 OUTREACH . . . . . . . . . . . . . . . . D GOV'T COMMUNITY BASED DISTRIBUTOR . . . . . . . . . . . . E OTHER PUBLIC F (SPECIFY) PRIVATE MEDICAL SECTOR PRIVATE HOSPITAL/CLINIC . . G PHARMACY/DRUG SHOP . . . . H PRIVATE DOCTOR/NURSE/ MIDWIFE . . . . . . . . . . . . . . . . . I OUTREACH . . . . . . . . . . . . . . . . J NGO COMMUNITY BASED DISTRIBUTOR . . . . . . . . . . . . K OTHER PRIVATE MEDICAL L (SPECIFY) OTHER SOURCE SHOP . . . . . . . . . . . . . . . . . . . . M RELIGIOUS INSTITUTION . . . . N FRIEND/RELATIVE . . . . . . . . . . O OTHER X (SPECIFY) 331 In the last 12 months, were you visited by a field worker who talked to you about family planning? YES . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . 2 332 In the last 12 months, have you visited a health facility for care for yourself (or your children)? YES . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . 2 ))<401 333 Did any staff member at the health facility speak to you about family planning methods? YES . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . 2 WE14 SECTION 4A. PREGNANCY, POSTNATAL CARE AND BREASTFEEDING 401 CHECK 224: ONE OR MORE +))), NO +))), BIRTHS /)))- BIRTHS .)))2)))))))))))))))))))))))))))))))))))))))))))))))<484 IN 1995 * IN 1995 OR LATER ? OR LATER 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 423)=)))))))- LATER . . . . . . . . . . . . . . . . . . . . 2 NOT AT ALL . . . . . . . . . . . . . . . . 3 (SKIP TO 423)=)))))))- 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 . . . . . . . . . . . . . . . . . A MIDWIFE/NURSE . . . . . . . . . . B MEDICAL ASSISTANT/ CLINICAL OFFICER . . . . . . . C NURSING AIDE . . . . . . . . . . . . D OTHER PERSON TRADITIONAL BIRTH ATTENDANT . . . . . . . . . . . . . E 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 407: CODE A, B, C OR D CIRCLED +))), /)))- ? CODE E, X OR Y CIRCLED +))), /)))- ? (SKIP TO 412) 410A CHECK 409: NUMBER OF TIMES RECEIVED ANTENATAL CARE ONCE +))), /)))- ? MORE THAN ONCE OR DK +))), /)))- ? (SKIP TO 411) WE15 LAST BIRTH NAME NEXT-TO-LAST BIRTH NAME 410B Where did you see the (HEALTH PROFESSIONAL MENTIONED IN 407) for antenatal care? PUBLIC SECTOR GOVT. HOSPITAL . . . . . . . . . . 21 GOVT. HEALTH CENTER . . . . 22 GOVT. HEALTH/ AID POST . . . . . . . . . . . . . . . 23 OTHER PUBLIC 26 (SPECIFY) PRIVATE MEDICAL SECTOR PRIVATE HOSPITAL/CLINIC . 31 OTHER PRIVATE MEDICAL 36 (SPECIFY) OTHER 96 (SPECIFY) 411 How many months pregnant were you the LAST time you received antenatal care? +)))0))), MONTHS . . . . . . . . . . . . *!!!*!!!* .)))2)))- DON’T KNOW . . . . . . . . . . . . . . . 98 411A Where did you see the (HEALTH PROFESSIONAL MENTIONED IN 407) the LAST time you saw someone for antenatal care? PUBLIC SECTOR GOVT. HOSPITAL . . . . . . . . . . 21 GOVT. HEALTH CENTER . . . . 22 GOVT. HEALTH/ AID POST . . . . . . . . . . . . . . . 23 OTHER PUBLIC 26 (SPECIFY) PRIVATE MEDICAL SECTOR PRIVATE HOSPITAL/CLINIC . 31 OTHER PRIVATE MEDICAL 36 (SPECIFY) OTHER 96 (SPECIFY) 412 When you were pregnant with (NAME), 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 Sometimes a pregnancy can have complications that lead to miscarriage or even death. Were you told about the signs of pregnancy complications? YES . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . 2 (SKIP TO 415)=)))))))1 DON’T REMEMBER . . . . . . . . . . 8 413A What are some of the signs and symptoms that indicate that a pregnancy may be in danger? PROBE: Any other signs or symptoms? RECORD ALL SIGNS AND SYMPTOMS MENTIONED. VAGINAL BLEEDING . . . . . . . . . A HIGH FEVER . . . . . . . . . . . . . . . B ABDOMINAL PAIN . . . . . . . . . . . C SWELLING OF HANDS AND FEET . . . . . . . . . . . . . . D DIFFICULT LABOR FOR MORE THAN 12 HOURS . . . . . . . . . E CONVULSIONS . . . . . . . . . . . . . F OTHER X (SPECIFY) DON’T KNOW ANY SIGNS OR SYMPTOMS . . . . Y 414 Were you told where to go or what to do if you had any of these signs? YES . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . 2 DON’T REMEMBER . . . . . . . . . . 8 LAST BIRTH NAME NEXT-TO-LAST BIRTH NAME WE16 415 When you were pregnant with (NAME), 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 417)=)))))))1 DON’T KNOW . . . . . . . . . . . . . . . 8 416 When you were pregnant with (NAME), how many times did you get this injection? +))), TIMES . . . . . . . . . . . . . . . . . . . *!!!* .)))- DON'T KNOW . . . . . . . . . . . . . . . 8 417 When you were pregnant with (NAME), were you given or did you buy any iron tablets or iron syrup? SHOW TABLET/SYRUP. YES . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . 2 (SKIP TO 419)=)))))))1 DON’T KNOW . . . . . . . . . . . . . . . 8 418 During the whole pregnancy, for how many days did you take the tablets or syrup? IF ANSWER IS NOT NUMERIC, PROBE FOR APPROXIMATE NUMBER OF DAYS. NUMBER OF +)))0)))0))), DAYS . . . . . . . . . . . . *!!!*!!!*!!!* .)))2)))2)))- DON’T KNOW . . . . . . . . . . . . . . 998 419 When you were pregnant with (NAME), did you have difficulty with your vision during the daylight? YES . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . 2 DON’T KNOW . . . . . . . . . . . . . . . 8 420 When you were pregnant with (NAME), did you suffer from night blindness [USE LOCAL TERM]? YES . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . 2 DON’T KNOW . . . . . . . . . . . . . . . 8 421 When you were pregnant with (NAME), did you take any drugs in order to prevent you from malaria? YES . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . 2 (SKIP TO 423)=)))))))1 DON’T KNOW . . . . . . . . . . . . . . . 8 422 What drugs did you take? RECORD ALL MENTIONED. IF TYPE OF DRUG IS NOT DETERMINED, SHOW TYPICAL ANTIMALARIAL DRUGS TO RESPONDENT. FANSIDAR . . . . . . . . . . . . . . . . . A CHLOROQUINE . . . . . . . . . . . . . B METAKELFIN . . . . . . . . . . . . . . . C CAMAQUINE . . . . . . . . . . . . . . . D QUININE . . . . . . . . . . . . . . . . . . . E DON’T KNOW . . . . . . . . . . . . . . . F OTHER X (SPECIFY) 422A CHECK 407: CODE “Y" CODE “Y" CIRCLED NOT CIRCLED +)), +)), /))- /))- .<(SKIP TO 423) ? 422B Did you get these medicines during an antenatal visit, another health facility visit or from some other source? ANTENATAL VISIT . . . . . . . . . . . 1 ANOTHER VISIT . . . . . . . . . . . . 2 OTHER SOURCE 6 (SPECIFY) 423 When (NAME) was born, was he/she very big, bigger than average, average, smaller than average, or very small? VERY BIG . . . . . . . . . . . . . . . . . . 1 BIGGER THAN AVERAGE . . . . . 2 AVERAGE . . . . . . . . . . . . . . . . . 3 SMALLER THAN AVERAGE . . . 4 VERY SMALL . . . . . . . . . . . . . . . 5 DON’T KNOW . . . . . . . . . . . . . . . 8 VERY BIG . . . . . . . . . . . . . . . . . . 1 BIGGER THAN AVERAGE . . . . . 2 AVERAGE . . . . . . . . . . . . . . . . . 3 SMALLER THAN AVERAGE . . . 4 VERY SMALL . . . . . . . . . . . . . . . 5 DON’T KNOW . . . . . . . . . . . . . . . 8 424 Was (NAME) weighed at birth? YES . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . 2 (SKIP TO 426)=)))))))1 DON’T KNOW . . . . . . . . . . . . . . . 8 YES . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . 2 (SKIP TO 426)=)))))))1 DON’T KNOW . . . . . . . . . . . . . . . 8 LAST BIRTH NAME NEXT-TO-LAST BIRTH NAME WE17 425 How much did (NAME) weigh? RECORD WEIGHT FROM HEALTH CARD, IF AVAILABLE. KILOGRAMS +))),!+))), FROM CARD . . . . . . 1 *!!!*.*!!!* .)))-!.)))- KILOGRAMS +))),!+))), FROM RECALL . . . . . 2 *!!!*.*!!!* .)))-!.)))- DON’T KNOW . . . . . . . . . . . . . . 998 KILOGRAMS +))),!+))), FROM CARD . . . . . 1 *!!!*.*!!!* .)))-!.)))- KILOGRAMS +))),!+))), FROM RECALL . . . . 2 *!!!*.*!!!* .)))-!.)))- DON’T KNOW . . . . . . . . . . . . . 998 425A Has (NAME) been registered? YES . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . 2 (SKIP TO 426)=)))))))1 DON’T KNOW . . . . . . . . . . . . . . . 8 YES . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . 2 (SKIP TO 426)=)))))))1 DON’T KNOW . . . . . . . . . . . . . . . 8 425B Does (NAME) have a birth certificate? IF YES: May I see it, please? SEEN, SHORT CERTIFICATE. . 1 SEEN, LONG CERTIFICATE. . . . 2 SEEN, BOTH CERTIFICATES. . . 3 NOT SEEN . . . . . . . . . . . . . . . . . 4 SEEN, SHORT CERTIFICATE. . 1 SEEN, LONG CERTIFICATE. . . . 2 SEEN, BOTH CERTIFICATES. . . 3 NOT SEEN . . . . . . . . . . . . . . . . 4 426 Who assisted with the delivery of (NAME)? Anyone else? PROBE FOR THE TYPE OF PERSON AND RECORD ALL PERSONS WHO ASSISTED. HEALTH PROFESSIONAL DOCTOR . . . . . . . . . . . . . . . . A MIDWIFE/NURSE . . . . . . . . . . B MEDICAL ASSISTANT/ CLINICAL OFFICER . . . . . . C NURSING AIDE . . . . . . . . . . . D OTHER PERSON TRADITIONAL BIRTH ATTENDANT . . . . . . . . . . . E RELATIVE/FRIEND . . . . . . . . F OTHER X (SPECIFY) NO ONE . . . . . . . . . . . . . . . . . . . Y HEALTH PROFESSIONAL DOCTOR . . . . . . . . . . . . . . . A MIDWIFE/NURSE . . . . . . . . . B MEDICAL ASSISTANT/ CLINICAL OFFICER . . . . . C NURSING AIDE . . . . . . . . . . D OTHER PERSON TRADITIONAL BIRTH ATTENDANT . . . . . . . . . . E RELATIVE/FRIEND . . . . . . . F OTHER X (SPECIFY) NO ONE . . . . . . . . . . . . . . . . . . Y 427 Where did you give birth to (NAME)? HOME YOUR HOME . . . . . . . . . . . . . 11 (SKIP TO 429)=)))))))1 TBA’S HOME . . . . . . . . . . . . . 12 OTHER HOME . . . . . . . . . . . . 13 (SKIP TO 429)=)))))))- PUBLIC SECTOR GOVT. HOSPITAL . . . . . . . . . 21 GOVT. HEALTH CENTER . . . 22 GOVT. HEALTH/ AID POST . . . . . . . . . . . . . . 23 OTHER PUBLIC 26 (SPECIFY) PRIVATE MEDICAL SECTOR PVT. HOSPITAL/CLINIC . . . . . 31 OTHER PVT. MEDICAL 36 (SPECIFY) OTHER 96 (SPECIFY) * (SKIP TO 429)=)))))))- HOME YOUR HOME . . . . . . . . . . . . 11 (SKIP TO 429)=)))))))1 TBA’S HOME . . . . . . . . . . . . 12 OTHER HOME . . . . . . . . . . . 13 (SKIP TO 429)=)))))))- PUBLIC SECTOR GOVT. HOSPITAL . . . . . . . . 21 GOVT. HEALTH CENTER . . 22 GOVT. HEALTH/ AID POST . . . . . . . . . . . . . 23 OTHER PUBLIC 26 (SPECIFY) PRIVATE MEDICAL SECTOR PVT. HOSPITAL/CLINIC . . . . 31 OTHER PVT. MEDICAL 36 (SPECIFY) OTHER 96 (SPECIFY) * (SKIP TO 429)=)))))))- 428 Was (NAME) delivered by caesarian section? YES . . . . . . . . . . . . . . . . . . . . . . 1 (SKIP TO 433)=)))))))1 NO . . . . . . . . . . . . . . . . . . . . . . . 2 YES . . . . . . . . . . . . . . . . . . . . . . 1 (SKIP TO 435)=)))))))1 NO . . . . . . . . . . . . . . . . . . . . . . . 2 429 After (NAME) was born, did a health professional or a traditional birth attendant check on your health? YES . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . 2 (SKIP TO 433)=)))))))- YES . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . 2 430 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 LAST BIRTH NAME NEXT-TO-LAST BIRTH NAME WE18 431 Who checked on your health at the time of the first check? PROBE FOR MOST QUALIFIED PERSON. HEALTH PROFESSIONAL DOCTOR . . . . . . . . . . . . . . . . 11 MIDWIFE/NURSE . . . . . . . . . . 12 MEDICAL ASSISTANT/ CLINICAL OFFICER . . . . . . 13 NURSING AIDE . . . . . . . . . . . 14 OTHER PERSON TRADITIONAL BIRTH ATTENDANT . . . . . . . . . . . 21 OTHER 96 (SPECIFY) 432 Where did this first check take place? HOME YOUR HOME . . . . . . . . . . . . . 11 OTHER HOME . . . . . . . . . . . . 12 TBA'S HOME . . . . . . . . . . . . . 13 PUBLIC SECTOR GOVT. HOSPITAL . . . . . . . . . 21 GOVT. HEALTH CENTER . . . 22 GOVT. HEALTH/ AID POST . . . . . . . . . . . . . . 23 OTHER PUBLIC 26 (SPECIFY) PRIVATE MEDICAL SECTOR PVT. HOSPITAL/CLINIC . . . . . 31 OTHER PVT. MEDICAL 36 (SPECIFY) OTHER 96 (SPECIFY) 432A Within the first six weeks after delivery, how many times did you have a check up? NUMBER OF +)))0))), TIMES . . . . . . . . . . . . . . . *!!!*!!!* .)))2)))- DON’T REMEMBER . . . . . . . . . . 98 433 In the first two months after delivery, did you receive a vitamin A dose like this one? SHOW AMPULE/CAPSULE/SYRUP. YES . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . 2 434 Has your period returned since the birth of (NAME)? YES . . . . . . . . . . . . . . . . . . . . . . 1 (SKIP TO 436)=)))))))- NO . . . . . . . . . . . . . . . . . . . . . . . 2 (SKIP TO 437)=)))))))- 435 Did your period return between the birth of (NAME) and your next pregnancy? YES . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . 2 (SKIP TO 439)=)))))))- 436 For how many months after the birth of (NAME) did you NOT have a period? +)))0))), MONTHS . . . . . . . . . . . . *!!!*!!!* .)))2)))- DON’T REMEMBER . . . . . . . . . . 98 +)))0))), MONTHS . . . . . . . . . . . *!!!*!!!* .)))2)))- DON’T REMEMBER . . . . . . . . . 98 437 CHECK 226: RESPONDENT PREGNANT? NOT +)), PREGNANT +)), PREG- /))- OR UNSURE .))1 NANT ? (SKIP TO 439)=))- 438 Have you resumed sexual relations since the birth of (NAME)? YES . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . 2 (SKIP TO 440)=)))))))- 439 For how many months after the birth of (NAME) did you NOT have sexual relations? +)))0))), MONTHS . . . . . . . . . . . . *!!!*!!!* .)))2)))- DON’T REMEMBER . . . . . . . . . . 98 +)))0))), MONTHS . . . . . . . . . . . *!!!*!!!* .)))2)))- DON’T REMEMBER . . . . . . . . . 98 440 Did you ever breastfeed (NAME)? YES . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . 2 (SKIP TO 447)=)))))))- YES . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . 2 (SKIP TO 447)=)))))))- LAST BIRTH NAME NEXT-TO-LAST BIRTH NAME WE19 441 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)))- 442 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 444)=)))))))- YES . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . 2 (SKIP TO 444)=)))))))- 443 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 GRIPE WATER . . . . . . . . . . . . . . D SALT AND SUGAR SOLUTION . E FRUIT JUICE . . . . . . . . . . . . . . . F INFANT FORMULA . . . . . . . . . . . G TEA/INFUSIONS . . . . . . . . . . . . H HONEY . . . . . . . . . . . . . . . . . . . . . I OTHER X (SPECIFY) MILK (OTHER THAN BREAST MILK) . . . . . . . . . . . A PLAIN WATER . . . . . . . . . . . . . B SUGAR OR GLUCOSE WATER C GRIPE WATER . . . . . . . . . . . . . D SALT AND SUGAR SOLUTION E FRUIT JUICE . . . . . . . . . . . . . . F INFANT FORMULA . . . . . . . . . . G TEA/INFUSIONS . . . . . . . . . . . H HONEY . . . . . . . . . . . . . . . . . . . . I OTHER X (SPECIFY) 444 CHECK 404: CHILD ALIVE? ALIVE +)), DEAD +)), /))- .))1 ? (SKIP TO 446)=))- ALIVE +)), DEAD +)), /))- .))1 ? (SKIP TO 446)=))- 445 Are you still breastfeeding (NAME)? YES . . . . . . . . . . . . . . . . . . . . . . 1 (SKIP TO 448)=)))))))- NO . . . . . . . . . . . . . . . . . . . . . . . 2 446 For how many months did you breastfeed (NAME)? +)))0))), MONTHS . . . . . . . . . . . . *!!!*!!!* .)))2)))- DON’T KNOW . . . . . . . . . . . . . . . 98 +)))0))), MONTHS . . . . . . . . . . . *!!!*!!!* .)))2)))- DON’T KNOW . . . . . . . . . . . . . . 98 446A After how many months did you start giving (NAME) fluids including water? IF NOT YET, RECORD ‘90' +)))0))), MONTHS . . . . . . . . . . . . *!!!*!!!* .)))2)))- DON’T KNOW . . . . . . . . . . . . . . . 98 +)))0))), MONTHS . . . . . . . . . . . *!!!*!!!* .)))2)))- DON’T KNOW . . . . . . . . . . . . . . 98 446B After how many months did you start giving (NAME) solid foods, including porridge? IF NOT YET, RECORD ‘90' +)))0))), MONTHS . . . . . . . . . . . . *!!!*!!!* .)))2)))- DON’T KNOW . . . . . . . . . . . . . . . 98 +)))0))), MONTHS . . . . . . . . . . . *!!!*!!!* .)))2)))- DON’T KNOW . . . . . . . . . . . . . . 98 447 CHECK 404: CHILD ALIVE? ALIVE +)), /))- * * * * * ? (SKIP TO 450A) DEAD +)), /))- ? (GO BACK TO 405 IN NEXT COLUMN; OR, IF NO MORE BIRTHS, GO TO 454) ALIVE +)), /))- * * * * * ? (SKIP TO 450A) DEAD +)), /))- ? (GO BACK TO 405 IN LAST COLUMN OF NEW QUESTION- NAIRE; OR, IF NO MORE BIRTHS, GO TO 454) 448 How many times did you breastfeed last night between sunset and sunrise (i.e., between going to bed and waking up)? IF ANSWER IS NOT NUMERIC, PROBE FOR APPROXIMATE NUMBER. NUMBER OF +)))0))), NIGHTTIME FEEDINGS . *!!!*!!!* .)))2)))- 449 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)))- LAST BIRTH NAME NEXT-TO-LAST BIRTH NAME WE20 450 Did you give (NAME) anything other than breast milk yesterday or last night? YES . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . 2 (SKIP TO 453)=)))))))1 DON’T KNOW . . . . . . . . . . . . . . . 8 450A What did you use to give (NAME) something yesterday or last night? CUP WITH SPOUT . . . . . . . . . . . A BOTTLE WITH NIPPLE . . . . . . . B SPOON . . . . . . . . . . . . . . . . . . . . C HAND . . . . . . . . . . . . . . . . . . . . . D DON’T KNOW . . . . . . . . . . . . . . . E OTHER X (SPECIFY) CUP WITH SPOUT . . . . . . . . . . A BOTTLE WITH NIPPLE . . . . . . B SPOON . . . . . . . . . . . . . . . . . . . C HAND . . . . . . . . . . . . . . . . . . . . D DON’T KNOW . . . . . . . . . . . . . . E OTHER X (SPECIFY) 451 Was sugar added to any of the foods or liquids (NAME) ate yesterday? YES . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . 2 DON’T KNOW . . . . . . . . . . . . . . . 8 YES . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . 2 DON’T KNOW . . . . . . . . . . . . . . . 8 452 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 . . . . . . . . . . . . . . . 8 453 GO BACK TO 405 IN NEXT COLUMN; OR, IF NO MORE BIRTHS, GO TO 454. GO BACK TO 405 IN LAST COLUMN OF NEW QUESTIONNAIRE; OR, IF NO MORE BIRTHS, GO TO 454. WE21 SECTION 4B. IMMUNIZATION, HEALTH AND NUTRITION 454 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). 455 LINE NUMBER FROM 212 LAST BIRTH +)))0))), LINE NUMBER . . . . . . . . . *!!!*!!!* .)))2)))- NEXT-TO-LAST BIRTH +)))0))), LINE NUMBER . . . . . . . . . *!!!*!!!* .)))2)))- 456 FROM 212 AND 216 NAME NAME ALIVE +)), /))- * * * * * ? DEAD +)), /))- ? (GO TO 456 IN NEXT COLUMN; OR, IF NO MORE BIRTHS, GO TO 484) ALIVE +)), /))- * * * * * ? DEAD +)), /))- ? (GO TO 456 IN LAST COLUMN OF NEW QUESTION- NAIRE; OR, IF NO MORE BIRTHS, GO TO 484) 457 Did (NAME) receive a Vitamin A dose like this one during the last 6 months? SHOW AMPULE/CAPSULE/SYRUP. YES . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . 2 DON’T KNOW . . . . . . . . . . . . . . . . 8 YES . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . 2 DON’T KNOW . . . . . . . . . . . . . . . . 8 458 Do you have a card where (NAME’S) vaccinations are written down? IF YES: May I see it please? YES, SEEN . . . . . . . . . . . . . . . . . . 1 (SKIP TO 460)=)))))))- YES, NOT SEEN . . . . . . . . . . . . . 2 (SKIP TO 462)=)))))))- NO CARD . . . . . . . . . . . . . . . . . . . 3 YES, SEEN . . . . . . . . . . . . . . . . . . 1 (SKIP TO 460)=)))))))- YES, NOT SEEN . . . . . . . . . . . . . 2 (SKIP TO 462)=)))))))- NO CARD . . . . . . . . . . . . . . . . . . . 3 459 Did you ever have a vaccination card for (NAME)? YES . . . . . . . . . . . . . . . . . . . . . . . 1 (SKIP TO 462)=)))))))1 NO . . . . . . . . . . . . . . . . . . . . . . . . 2 YES . . . . . . . . . . . . . . . . . . . . . . . 1 (SKIP TO 462)=)))))))1 NO . . . . . . . . . . . . . . . . . . . . . . . . 2 460 (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)))- WE22 LAST BIRTH NAME NEXT-TO-LAST BIRTH NAME 461 Has (NAME) received any vaccinations that are not recorded on this card, including vaccinations received during the National Immunization Day campaign? RECORD ‘YES’ ONLY IF RESPONDENT MENTIONS BCG, POLIO, DPT, AND/OR MEASLES VACCINE(S). YES . . . . . . . . . . . . . . . . . . . . . . . 1 (PROBE FOR VACCINATIONS =)- AND WRITE ‘66' IN THE CORRESPONDING DAY COLUMN IN 460 IF THE BOXES ARE BLANK) ))))))), (SKIP TO 464)=)))))))- NO . . . . . . . . . . . . . . . . . . . . . . . . 2 (SKIP TO 464)=)))))))1 DON’T KNOW . . . . . . . . . . . . . . . . 8 YES . . . . . . . . . . . . . . . . . . . . . . . 1 (PROBE FOR VACCINATIONS =)- AND WRITE ‘66' IN THE CORRESPONDING DAY COLUMN IN 460 IF THE BOXES ARE BLANK) ))))))), (SKIP TO 464)=)))))))- NO . . . . . . . . . . . . . . . . . . . . . . . . 2 (SKIP TO 464)=)))))))1 DON’T KNOW . . . . . . . . . . . . . . . . 8 462 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 466)=)))))))1 DON’T KNOW . . . . . . . . . . . . . . . . 8 YES . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . 2 (SKIP TO 466)=)))))))1 DON’T KNOW . . . . . . . . . . . . . . . . 8 463 Please tell me if (NAME) received any of the following vaccinations: 463A 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 463B Polio vaccine, that is, drops in the mouth? YES . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . 2 (SKIP TO 463E)=)))))))1 DON’T KNOW . . . . . . . . . . . . . . . . 8 YES . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . 2 (SKIP TO 463E)=)))))))1 DON’T KNOW . . . . . . . . . . . . . . . . 8 463C When was the first polio vaccine received, just after birth or later? JUST AFTER BIRTH . . . . . . . . . . . 1 LATER . . . . . . . . . . . . . . . . . . . . . 2 JUST AFTER BIRTH . . . . . . . . . . . 1 LATER . . . . . . . . . . . . . . . . . . . . . 2 463D How many times was the polio vaccine received? +))), NUMBER OF TIMES . . . . . . . . *!!!* .)))- +))), NUMBER OF TIMES . . . . . . . . *!!!* .)))- 463E 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 463G)=)))))))1 DON’T KNOW . . . . . . . . . . . . . . . . 8 YES . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . 2 (SKIP TO 463G)=)))))))1 DON’T KNOW . . . . . . . . . . . . . . . . 8 463F How many times? +))), NUMBER OF TIMES . . . . . . . . *!!!* .)))- +))), NUMBER OF TIMES . . . . . . . . *!!!* .)))- 463G An injection to prevent measles? YES . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . 2 DON’T KNOW . . . . . . . . . . . . . . . . 8 YES . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . 2 DON’T KNOW . . . . . . . . . . . . . . . . 8 464 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 466)=)))- NO VACCINATION IN THE LAST 2 YEARS . . . . . . . . 3 (SKIP TO 466)=)))- DON’T KNOW . . . . . . . . . . . . . . . . 8 (SKIP TO 466)=)))- YES . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . 2 (SKIP TO 466)=)))- NO VACCINATION IN THE LAST 2 YEARS . . . . . . . . 3 (SKIP TO 466)=)))- DON’T KNOW . . . . . . . . . . . . . . . . 8 (SKIP TO 466)=)))- 465 At which National Immunization Day campaigns did (NAME) receive vaccinations? RECORD ALL MENTIONED. POLIO (AUG/SEPT 1998) . . . . . . . A POLIO (AUG/SEPT 1999) . . . . . . . B MEASLES (MAR/APR 2000) . . . . . C POLIO (AUG/SEP/OCT 2000) . . . D POLIO (AUG/SEPT 1998) . . . . . . A POLIO (AUG/SEPT 1999) . . . . . . B MEASLES (MAR/APR 2000) . . . . C POLIO (AUG/SEP/OCT 2000) . . D 466 Has (NAME) been ill with a fever at any time in the last 2 weeks? YES . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . 2 DON’T KNOW . . . . . . . . . . . . . . . . 8 YES . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . 2 DON’T KNOW . . . . . . . . . . . . . . . . 8 467 Has (NAME) had an illness with a cough at any time in the last 2 weeks? YES . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . 2 (SKIP TO 469)=)))))))1 DON’T KNOW . . . . . . . . . . . . . . . . 8 YES . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . 2 (SKIP TO 469)=)))))))1 DON’T KNOW . . . . . . . . . . . . . . . . 8 468 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 LAST BIRTH NAME NEXT-TO-LAST BIRTH NAME WE23 469 CHECK 466 AND 467: FEVER OR COUGH? “YES” IN 466 OR 467 +)), /))- ? OTHER +)), /))- * ? (SKIP TO 474) “YES” IN 466 OR 467 +)), /))- ? OTHER +)), /))- * ? (SKIP TO 474) 470 Did you seek advice or treatment for the fever/cough? YES . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . 2 (SKIP TO 472)=)))))))- YES . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . 2 (SKIP TO 472)=)))))))- 471 Where did you seek advice or treatment? Anywhere else? RECORD ALL MENTIONED. PUBLIC SECTOR GOVT. HOSPITAL . . . . . . . . . . A GOVT. HEALTH CENTER . . . . B GOVT. AID POST . . . . . . . . . . . C CLINIC/OUTREACH SERVICES . . . . . . . . . . . . . . . D COMMUNITY HEALTH WORKER . . . . . . . . . . . . . . . . E OTHER PUBLIC F (SPECIFY) PRIVATE MEDICAL SECTOR PVT. HOSPITAL/CLINIC . . . . . . G PHARMACY/DRUG SHOP . . . . H PRIVATE DOCTOR . . . . . . . . . . I OTHER PVT. MEDICAL J (SPECIFY) OTHER SOURCE SHOP . . . . . . . . . . . . . . . . . . . . K TRAD. PRACTITIONER . . . . . . L HOME . . . . . . . . . . . . . . . . . . . . M OTHER X (SPECIFY) PUBLIC SECTOR GOVT. HOSPITAL . . . . . . . . . A GOVT. HEALTH CENTER . . . B GOVT. AID POST CLINIC/OUTREACH SERVICES . . . . . . . . . . . . . . D COMMUNITY HEALTH WORKER . . . . . . . . . . . . . . . E OTHER PUBLIC F (SPECIFY) PRIVATE MEDICAL SECTOR PVT. HOSPITAL/CLINIC . . . . . G PHARMACY/DRUG SHOP . . . H PRIVATE DOCTOR . . . . . . . . . I OTHER PVT. MEDICAL J (SPECIFY) OTHER SOURCE SHOP . . . . . . . . . . . . . . . . . . . K TRAD. PRACTITIONER . . . . . . L HOME . . . . . . . . . . . . . . . . . . . M OTHER X (SPECIFY) 472 CHECK 466: HAD FEVER? “YES” IN 466 +)), /))- * ? “NO”/”DK” IN 466 +)), /))- ? (SKIP TO 474) “YES” IN 466 +)), /))- * ? “NO”/”DK” IN 466 +)), /))- ? (SKIP TO 474) 473 Does (NAME) have a fever now? YES . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . 2 (SKIP TO 474)=)))))))1 DON’T KNOW . . . . . . . . . . . . . . . . 8 YES . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . 2 (SKIP TO 474)=)))))))1 DON’T KNOW . . . . . . . . . . . . . . . . 8 473A Was (NAME) given any medicines for the fever? YES . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . 2 (SKIP 474) =)))* DON’T KNOW . . . . . . . . . . . . . . . . 8 YES . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . 2 (SKIP 474) =)))* DON’T KNOW . . . . . . . . . . . . . . . . 8 473B In the past 2 weeks, which medicines were given to (NAME)? ASK TO SEE MEDICINE(S). IF NOT SEEN, SHOW MEDICINE(S) TO RESPONDENT. RECORD ALL MENTIONED ANTI-MALARIAL CHLOROQUINE . . . . . . . . . . . . A FANSIDAR . . . . . . . . . . . . . . . . B CAMAQUINE . . . . . . . . . . . . . . C QUININE . . . . . . . . . . . . . . . . . D OTHER DRUGS ASPIRIN . . . . . . . . . . . . . . . . . . E PANADOL . . . . . . . . . . . . . . . . F TRADITIONAL HERBS . . . . . . . . . G OTHER X (SPECIFY) DON’T KNOW . . . . . . . . . . . . . . . . Z ANTI-MALARIAL CHLOROQUINE . . . . . . . . . . . A FANSIDAR . . . . . . . . . . . . . . . . B CAMAQUINE . . . . . . . . . . . . . . C QUININE . . . . . . . . . . . . . . . . . D OTHER DRUGS ASPIRIN . . . . . . . . . . . . . . . . . E PANADOL . . . . . . . . . . . . . . . . . F TRADITIONAL HERBS . . . . . . . . G OTHER X (SPECIFY) DON’T KNOW . . . . . . . . . . . . . . . Z 473C CHECK 473B: WHICH MEDICINES? CODE “A" CODE “A" CIRCLED NOT CIRCLED +)), +)), /))- /))- .<(SKIP TO 473G) ? CODE “A" CODE “A" CIRCLED NOT CIRCLED +)), +)), /))- /))- .<(SKIP TO 473G) ? LAST BIRTH NAME NEXT-TO-LAST BIRTH NAME WE24 473D How long after the fever started did (NAME) first take Chloroquine? SAME DAY . . . . . . . . . . . . . . . . . . 0 NEXT DAY . . . . . . . . . . . . . . . . . . 1 TWO DAYS AFTER THE FEVER 2 THREE OR MORE DAYS AFTER THE FEVER . . . 3 DON’T KNOW . . . . . . . . . . . . . . . . 8 SAME DAY . . . . . . . . . . . . . . . . . . 0 NEXT DAY . . . . . . . . . . . . . . . . . . 1 TWO DAYS AFTER THE FEVER 2 THREE OR MORE DAYS AFTER THE FEVER . . . 3 DON’T KNOW . . . . . . . . . . . . . . . . 8 473E For how many days did (NAME) take Chloroquine for the fever? IF 7 OR MORE DAYS, RECORD ‘7'. +))), DAYS . . . . . . . . . . . . . . . . . . . *!!!* .)))- DON’T KNOW . . . . . . . . . . . . . . . 8 +))), DAYS . . . . . . . . . . . . . . . . . . . *!!!* .)))- DON’T KNOW . . . . . . . . . . . . . . 8 473F Where did you get the Chloroquine for (NAME)’s fever? PHARMACY/DRUG SHOP . . . . . . A GOV’T HEALTH FACILITY . . . . . . B NGO HEALTH FACILITY . . . . . . . C OTHER PRIVATE HEALTH FACILITY . . . . . . . . . . . . D COMMUNITY HEALTH WORKER E FRIEND/NEIGHBOUR . . . . . . . . . F HOME SUPPLY . . . . . . . . . . . . . . G OTHER X (SPECIFY) DON’T KNOW . . . . . . . . . . . . . . . . Z PHARMACY/SHOP . . . . . . . . . . . A GOV’T HEALTH FACILITY . . . . . B NGO HEALTH FACILITY . . . . . . C OTHER PRIVATE HEALTH FACILITY . . . . . . . . . . . D COMMUNITY HEALTH WORKER E FRIEND/NEIGHBOUR . . . . . . . . . F HOME SUPPLY . . . . . . . . . . . . . G OTHER X (SPECIFY) DON’T KNOW . . . . . . . . . . . . . . . . Z 473G CHECK 473B: WHICH MEDICINES? CODE “B" CODE “B" CIRCLED NOT CIRCLED +)), +)), /))- /))- .<(SKIP TO 473K) ? CODE “B" CODE “B" CIRCLED NOT CIRCLED +)), +)), /))- /))- .<(SKIP TO 473K) ? 473H How long after the fever started did (NAME) first take Fansidar? SAME DAY . . . . . . . . . . . . . . . . . . 0 NEXT DAY . . . . . . . . . . . . . . . . . . 1 TWO DAYS AFTER FEVER STARTED . . . . . . . . . . . . . . . . . 2 THREE OR MORE DAYS AFTER FEVER STARTED . . . . . 3 DON’T KNOW . . . . . . . . . . . . . . . . 8 SAME DAY . . . . . . . . . . . . . . . . . . 0 NEXT DAY . . . . . . . . . . . . . . . . . . 1 TWO DAYS AFTER FEVER STARTED . . . . . . . . . . . . . . . . . 2 THREE OR MORE DAYS AFTER FEVER STARTED . . . . . 3 DON’T KNOW . . . . . . . . . . . . . . . . 8 473I For how many days did (NAME) take Fansidar for the fever? IF 7 OR MORE DAYS, RECORD ‘7'. +))), DAYS . . . . . . . . . . . . . . . . . . . *!!!* .)))- DON’T KNOW . . . . . . . . . . . . . . . 8 +))), DAYS . . . . . . . . . . . . . . . . . . . *!!!* .)))- DON’T KNOW . . . . . . . . . . . . . . 8 473J Where did you get the Fansidar for (NAME)’s fever? PHARMACY/DRUG SHOP . . . . . . A GOV’T HEALTH FACILITY . . . . . . B NGO HEALTH FACILITY . . . . . . . C OTHER PRIVATE HEALTH FACILITY . . . . . . . . . . . . D COMMUNITY HEALTH WORKER E FRIEND/NEIGHBOUR . . . . . . . . . F HOME SUPPLY . . . . . . . . . . . . . . G OTHER X (SPECIFY) DON’T KNOW . . . . . . . . . . . . . . . . Z PHARMACY/SHOP . . . . . . . . . . . A GOV’T HEALTH FACILITY . . . . . B NGO HEALTH FACILITY . . . . . . C OTHER PRIVATE HEALTH FACILITY . . . . . . . . . . . D COMMUNITY HEALTH WORKER E FRIEND/NEIGHBOUR . . . . . . . . . F HOME SUPPLY . . . . . . . . . . . . . G OTHER X (SPECIFY) DON’T KNOW . . . . . . . . . . . . . . . . Z 473K CHECK 473B: WHICH MEDICINES? CODE “C" CODE “C" CIRCLED NOT CIRCLED +)), +)), /))- /))- ? .<(SKIP TO 473O) CODE “C" CODE “C" CIRCLED NOT CIRCLED +)), +)), /))- /))- ? .<(SKIP TO 473O) 473L How long after the fever started did (NAME) first take Camaquine? SAME DAY . . . . . . . . . . . . . . . . . . 0 NEXT DAY . . . . . . . . . . . . . . . . . . 1 TWO DAYS AFTER FEVER STARTED . . . . . . . . . . . . . . . . . 2 THREE OR MORE DAYS AFTER FEVER STARTED . . . . . 3 DON’T KNOW . . . . . . . . . . . . . . . . 8 SAME DAY . . . . . . . . . . . . . . . . . . 0 NEXT DAY . . . . . . . . . . . . . . . . . . 1 TWO DAYS AFTER FEVER STARTED . . . . . . . . . . . . . . . . . 2 THREE OR MORE DAYS AFTER FEVER STARTED . . . . . 3 DON’T KNOW . . . . . . . . . . . . . . . . 8 LAST BIRTH NAME NEXT-TO-LAST BIRTH NAME WE25 473M For how many days did (NAME) take Camaquine for the fever? IF 7 OR MORE DAYS, RECORD ‘7'. +))), DAYS . . . . . . . . . . . . . . . . . . . *!!!* .)))- DON’T KNOW . . . . . . . . . . . . . . . 8 +))), DAYS . . . . . . . . . . . . . . . . . . . *!!!* .)))- DON’T KNOW . . . . . . . . . . . . . . 8 473N Where did you get the Camaquine for (NAME)’s fever? PHARMACY/DRUG SHOP . . . . . . A GOV’T HEALTH FACILITY . . . . . . B NGO HEALTH FACILITY . . . . . . . C OTHER PRIVATE HEALTH FACILITY . . . . . . . . . . . . D COMMUNITY HEALTH WORKER E FRIEND/NEIGHBOUR . . . . . . . . . F HOME SUPPLY . . . . . . . . . . . . . . G OTHER X (SPECIFY) DON’T KNOW . . . . . . . . . . . . . . . . Z PHARMACY/SHOP . . . . . . . . . . . A GOV’T HEALTH FACILITY . . . . . B NGO HEALTH FACILITY . . . . . . C OTHER PRIVATE HEALTH FACILITY . . . . . . . . . . . D COMMUNITY HEALTH WORKER E FRIEND/NEIGHBOUR . . . . . . . . . F HOME SUPPLY . . . . . . . . . . . . . G OTHER X (SPECIFY) DON’T KNOW . . . . . . . . . . . . . . . . Z 473O CHECK 473B: WHICH MEDICINES? CODE “D" CODE “D" CIRCLED NOT CIRCLED +)), +)), /))- /))- .<(SKIP TO 474) ? CODE “D" CODE “D" CIRCLED NOT CIRCLED +)), +)), /))- /))- .<(SKIP TO 474) ? 473P How long after the fever started did (NAME) first take Quinine? SAME DAY . . . . . . . . . . . . . . . . . . 0 NEXT DAY . . . . . . . . . . . . . . . . . . 1 TWO DAYS AFTER FEVER STARTED . . . . . . . . . . . . . . . . . 2 THREE OR MORE DAYS AFTER FEVER STARTED . . . . . 3 DON’T KNOW . . . . . . . . . . . . . . . . 8 SAME DAY . . . . . . . . . . . . . . . . . . 0 NEXT DAY . . . . . . . . . . . . . . . . . . 1 TWO DAYS AFTER FEVER STARTED . . . . . . . . . . . . . . . . . 2 THREE OR MORE DAYS AFTER FEVER STARTED . . . . . 3 DON’T KNOW . . . . . . . . . . . . . . . . 8 473Q For how many days did (NAME) take Quinine for the fever? IF 7 OR MORE DAYS, RECORD ‘7'. +))), DAYS . . . . . . . . . . . . . . . . . . . *!!!* .)))- DON’T KNOW . . . . . . . . . . . . . . . 8 +))), DAYS . . . . . . . . . . . . . . . . . . . *!!!* .)))- DON’T KNOW . . . . . . . . . . . . . . 8 473R Where did you get the Quinine for (NAME)’s fever? PHARMACY/DRUG SHOP . . . . . . A GOV’T HEALTH FACILITY . . . . . . B NGO HEALTH FACILITY . . . . . . . C OTHER PRIVATE HEALTH FACILITY . . . . . . . . . . . . D COMMUNITY HEALTH WORKER E FRIEND/NEIGHBOR . . . . . . . . . . . F HOME SUPPLY . . . . . . . . . . . . . . G OTHER X (SPECIFY) DON’T KNOW . . . . . . . . . . . . . . . . Z PHARMACY/SHOP . . . . . . . . . . . A GOV’T HEALTH FACILITY . . . . . B NGO HEALTH FACILITY . . . . . . C OTHER PRIVATE HEALTH FACILITY . . . . . . . . . . . D COMMUNITY HEALTH WORKER E FRIEND/NEIGHBOR . . . . . . . . . . . F HOME SUPPLY . . . . . . . . . . . . . G OTHER X (SPECIFY) DON’T KNOW . . . . . . . . . . . . . . . . Z 474 Do you have any mosquito nets in your house? YES . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . 2 (SKIP TO 475) =))- CHECK FIRST COLUMN: HAS DOES NOT MOSQUITO HAVE NETS MOSQUITO NETS +), +), /)- .)2))< * (SKIP TO 475) ? 474A Does (NAME) usually sleep under a mosquito net? YES . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . 2 YES . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . 2 474B Did (NAME) sleep under a mosquito net last night? YES . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . 2 DON’T KNOW . . . . . . . . . . . . . . . . 8 YES . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . 2 DON’T KNOW . . . . . . . . . . . . . . . . 8 474C CHECK 474A AND 474B: CODE “1" CODE “1" CIRCLED CIRCLED FOR EITHER FOR NEITHER OR BOTH +)), +)), /))- /))- ? .<(SKIP TO 475) CODE “1" CODE “1" CIRCLED CIRCLED FOR EITHER FOR NEITHER OR BOTH +)), +)), /))- /))- ? .<(SKIP TO 475) LAST BIRTH NAME NEXT-TO-LAST BIRTH NAME WE26 474D How long ago was the mosquito net bought or obtained? IF LESS THAN 1 MONTH, RECORD ‘00'. IF MORE THAN 84 MONTHS, RECORD‘84'. +)))0))), MONTHS . . . . . . . . . . . . . *!!!*!!!* .)))2)))- DON’T KNOW . . . . . . . . . . . . . . . 98 +)))0))), MONTHS . . . . . . . . . . . . . *!!!*!!!* .)))2)))- DON’T KNOW . . . . . . . . . . . . . . . 98 474E Since you got the mosquito net, was it ever soaked or dipped in a liquid to repel mosquitoes or bugs? YES . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . 2 (SKIP TO 475)=)))1 DON’T KNOW . . . . . . . . . . . . . . . . 8 YES . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . 2 (SKIP TO 475)=)))1 DON’T KNOW . . . . . . . . . . . . . . . . 8 474F How long ago was the mosquito net last soaked or dipped? IF LESS THAN 1 MONTH, RECORD ‘00'. IF MORE THAN 84 MONTHS, RECORD ‘84'. +)))0))), MONTHS . . . . . . . . . . . . . *!!!*!!!* .)))2)))- DON’T KNOW . . . . . . . . . . . . . . . 98 +)))0))), MONTHS . . . . . . . . . . . . . *!!!*!!!* .)))2)))- DON’T KNOW . . . . . . . . . . . . . . . 98 475 Has (NAME) had diarrhoea in the last 2 weeks? YES . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . 2 (SKIP TO 483)=)))))))1 DON’T KNOW . . . . . . . . . . . . . . . . 8 YES . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . 2 (SKIP TO 483)=)))))))1 DON’T KNOW . . . . . . . . . . . . . . . . 8 476 How much was (NAME) given to drink during the diarrhoea. 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 given 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 . . . . . . . . . . . . . . . . 8 477 When (NAME) had diarrhoea, was he/she given less than usual to eat, about the same amount, more than usual, or nothing to eat? IF LESS, PROBE: Was he/she given 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 . . . . . . . . . . . . . . . . 8 478 Was he/she given any of the following to drink YES NO DK YES NO DK a A fluid made from a special packet called [LOCAL NAME]? FLUID FROM ORS PKT . . 1 2 8 FLUID FROM ORS PKT . 1 2 8 b A government-recommended home-made fluid? HOME-MADE FLUID . . . . . 1 2 8 HOME-MADE FLUID . . . . 1 2 8 479 Was anything (else) given to treat the diarrhoea? YES . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . 2 (SKIP TO 481)=)))))))1 DON’T KNOW . . . . . . . . . . . . . . . . 8 YES . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . 2 (SKIP TO 481)=)))))))1 DON’T KNOW . . . . . . . . . . . . . . . . 8 480 What was given to treat the diarrhoea? Anything else? RECORD ALL MENTIONED. TABLET OR SYRUP . . . . . . . . . . . A INJECTION . . . . . . . . . . . . . . . . . . B (I.V.) INTRAVENOUS . . . . . . . . . . C HOME REMEDIES/ HERBAL MEDICINES . . . . . . . . D OTHER X (SPECIFY) TABLET OR SYRUP . . . . . . . . . . A INJECTION . . . . . . . . . . . . . . . . . B (I.V.) INTRAVENOUS . . . . . . . . . C HOME REMEDIES/ HERBAL MEDICINES . . . . . . . D OTHER X (SPECIFY) 481 Did you seek advice or treatment for the diarrhoea? YES . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . 2 (SKIP TO 483)=)))))))- YES . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . 2 (SKIP TO 483)=)))))))- LAST BIRTH NAME NEXT-TO-LAST BIRTH NAME WE27 482 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 CLINIC/OUTREACH SERVICES . . . . . . . . . . . . . . . D COMMUNITY HEALTH WORKER . . . . . . . . . . . . . . . . E OTHER PUBLIC F (SPECIFY) PRIVATE MEDICAL SECTOR PVT. HOSPITAL/CLINIC . . . . . . G PHARMACY/DRUGSHOP . . . . H PRIVATE DOCTOR . . . . . . . . . . I MOBILE CLINIC . . . . . . . . . . . . . J OTHER PRIVATE MEDICAL K (SPECIFY) OTHER SOURCE SHOP . . . . . . . . . . . . . . . . . . . . L TRAD. PRACTITIONER . . . . . . M HOME . . . . . . . . . . . . . . . . . . . . N OTHER X (SPECIFY) PUBLIC SECTOR GOVT. HOSPITAL . . . . . . . . . A GOVT. HEALTH CENTER . . . B GOVT. HEALTH POST . . . . . . C CLINIC/OUTREACH SERVICES . . . . . . . . . . . . . . D COMMUNITY HEALTH WORKER . . . . . . . . . . . . . . . E OTHER PUBLIC F (SPECIFY) PRIVATE MEDICAL SECTOR PVT. HOSPITAL/CLINIC . . . . . G PHARMACY/DRUGSHOP . . . H PRIVATE DOCTOR . . . . . . . . . I MOBILE CLINIC . . . . . . . . . . . . J OTHER PRIVATE MEDICAL K (SPECIFY) OTHER SOURCE SHOP . . . . . . . . . . . . . . . . . . . . L TRAD. PRACTITIONER . . . . . M HOME . . . . . . . . . . . . . . . . . . . N OTHER X (SPECIFY) 483 GO BACK TO 456 IN NEXT COLUMN; OR, IF NO MORE BIRTHS, GO TO 484. GO BACK TO 456 IN LAST COLUMN OF NEW QUESTIONNAIRE; OR, IF NO MORE BIRTHS, GO TO 484. WE28 NO. QUESTIONS AND FILTERS CODING CATEGORIES SKIP 484 CHECK 456, ALL COLUMNS: NUMBER OF LIVING CHILDREN BORN IN 1995 OR LATER ONE OR +))), NONE +))), MORE /)))- .)))2)))))))))))))))))))))))))))))))))))))))))))) ? ))<487 485 What is usually done to dispose of (NAME OF CHILD/YOUNGEST CHILD)’s stools when he/she does not use any toilet facility? CHILD ALWAYS USES TOILET/LATRINE . . . . . . . . . . . . . . . 01 THROW IN THE TOILET/LATRINE . . 02 THROW OUTSIDE THE DWELLING . 03 THROW OUTSIDE THE YARD . . . . . . 04 BURY IN THE YARD . . . . . . . . . . . . . 05 OTHER 96 (SPECIFY) 486 CHECK 478 a), ALL COLUMNS: NO CHILD +))), ANY CHILD +))), RECEIVED FLUID /)))- RECEIVED FLUID .)))2)))))))))))))))))))))))))))))))))))))))))))) FROM ORS PACKET ? FROM ORS PACKET ))<488 487 Have you ever heard of a special product called [LOCAL NAME FOR ORS PACKET] you can get for the treatment of diarrhoea? YES . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 488 CHECK 218: HAS ONE OR MORE +))), HAS NO CHILDREN +))), CHILDREN LIVING /)))- LIVING WITH HER .)))2)))))))))))))))))))))))))))))))))))))))))))) WITH HER ? ))<494 489 When (your child/one of your children) is seriously ill, who decides 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? RESPONDENT . . . . . . . . . . . . . . . . . . . 1 RESPONDENT AND OTHER PERSON(S)2 OTHER PERSON(S) . . . . . . . . . . . . . . . 3 489B Sometimes children have severe illnesses and should be taken immediately to a health facility. What type of symptoms would cause you to take your child to a health facility right away? RECORD ALL SYMPTOMS MENTIONED. CHILD NOT ABLE TO EAT OR DRINK OR BREASTFEED . . . . . . . . . A CHILD BECOMES SICKER . . . . . . . . . B CHILD DEVELOPS A FEVER . . . . . . . . C CHILD HAS DIFFICULTY IN BREATHING . . . . . . . . . . . . . . . . . . . D CHILD HAS BLOOD IN STOOL . . . . . . E CHILD DRINKS POORLY . . . . . . . . . . . F OTHER G (SPECIFY) OTHER H (SPECIFY) OTHER I (SPECIFY) 491 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 492) ________________________________________ (NAME) ))<494 NO. QUESTIONS AND FILTERS CODING CATEGORIES SKIP WE29 492 Now I would like to ask you about liquids (NAME FROM Q. 491) drank over the last seven days, including yesterday. How many days during the last seven days did (NAME FROM Q. 491) 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. 491) drink (ITEM)? LAST 7 DAYS NUMBER OF DAYS YESTERDAY/ LAST NIGHT NUMBER OF TIMES a Plain water? a a b Cerelac or any other infant formula? b b c Any other milk such as tinned, powdered, or fresh animal milk? c c d Fruit juice? d d e Any other liquids such as sugar water, tea, coffee, soda, or soup broth? e e IF 7 OR MORE TIMES, RECORD ‘7'. IF DON’T KNOW, RECORD ‘8'. 493 Now I would like to ask you about the types of foods (NAME FROM Q. 491) ate over the last seven days, including yesterday. How many days during the last seven days did (NAME FROM Q. 491) 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. 491) eat (ITEM)? LAST 7 DAYS NUMBER OF DAYS YESTERDAY/ LAST NIGHT NUMBER OF TIMES a Any food made from grains: such as rice, posho, porridge, bread, chapati, pasta/ macaroni or pizza? Matooke? a a b Pumpkins, white or purple yams, carrots, or yellow sweet potatoes? b b c Any other food made from roots or tubers such as Irish potatoes or cassava? c c d Any green leafy vegetables such as dodo, nakati, bugga, sungsa, jjobyo, sukumaweek or marakwang? d d e Mango or paw-paw? e e f Any other fruits and vegetables: oranges, bananas, apples, guavas, jack fruit, water melon, berries, avocados, tomatoes, green beans, or cabbage? f f g Meat (beef, pork or goat/mutton), poultry (chicken, duck or other birds), fish, insects (such as ants and grassshoppers), or eggs? g g h Any food made from legumes: lentils, beans, soybeans, cow peas, pidgeon peas (nkolimbo or lapena) or groundnuts? Simsim (sesame seeds)? h h i Milk and other dairy products such as cheese, yoghurt/sour milk/curdled milk? i i j Any food made with oil, fat, butter or ghee? j j IF 7 OR MORE TIMES, RECORD ‘7'. IF DON’T KNOW, RECORD ‘8'. NO. QUESTIONS AND FILTERS CODING CATEGORIES SKIP WE30 494 CHECK 474 OR 474 NOT ASKED HAS MOSQUITO NET +))), DOES NOT HAVE +))), /)))- MOSQUITO NET .)))2)))))))))))))))))))))))))))))))))))))))))))) ? ))<495 494A Do you always sleep under a mosquito net? YES . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 494B Did you sleep under a mosquito net last night? YES . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 494C CHECK 494A AND 494B: CODE “1" CIRCLED FOR EITHER OR BOTH +)), /))- ? CODE “1" CIRCLED FOR NEITHER +)), /))- .))))))))))))))))))))))))))))))) ))< 495 494D How long ago was the mosquito net bought or obtained? IF LESS THAN 1 MONTH, RECORD ‘00' IF MORE THAN 84 MONTHS, RECORD ‘84' +)))0))), MONTHS . . . . . . . . . . . . . . . . . *!!!*!!!* .)))2)))- DON’T KNOW . . . . . . . . . . . . . . . . . . . 98 494E Since you got the mosquito net, was it ever soaked or dipped in a liquid to repel mosquitoes or bugs? YES . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 DON’T KNOW . . . . . . . . . . . . . . . . . . . . 8 ), )2)< 495 494F How long ago was the mosquito net last soaked or dipped? IF LESS THAN 1 MONTH, RECORD ‘00' IF MORE THAN 84 MONTHS, RECORD ‘84' +)))0))), MONTHS . . . . . . . . . . . . . . . . . *!!!*!!!* .)))2)))- DON’T KNOW . . . . . . . . . . . . . . . . . . . 98 495 The last time you prepared a meal for your family, before starting did you wash your hands? YES . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 NEVER PREPARED MEAL . . . . . . . . . 3 496 A number of 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 for you? 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 distance to the health facility. 1 2 Having to take transport. 1 2 Not wanting to go alone. 1 2 Concern that there may not be a female health provider. Negative attitude of health provider. 1 1 2 2 WE31 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 DON'T KNOW . . . . . . . . . . . . . . . . . . . 8 ))<510 ))<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? ONLY 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 MARRIED . . . . . 95 )<524 )<515 514A Did that partner become your husband or did you go ahead to live with him? YES . . . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 514B At the time you first had sex, how old was your partner? +)))0))), AGE IN YEARS . . . . . . . . . . . . *!!!*!!!* .)))2)))- DON'T KNOW . . . . . . . . . . . . . . . . . . 96 515 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)))- )<516 )<516 ))<524 NO. QUESTIONS AND FILTERS CODING CATEGORIES SKIP WE32 515A In the last one week, how many times did you have sexual intercourse with any man? +)))0))), NUMBER OF TIMES . . . . . . . . *!!!*!!!* .)))2)))- DON'T KNOW . . . . . . . . . . . . . . . . . . 96 516 The last time you had sexual intercourse, was a condom used? YES . . . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 )<516B 516A What was the main reason you used a condom on that occasion? RESPONDENT WANTED TO PREVENT STD/HIV . . . . . . . . . . . 01 RESPONDENT WANTED TO PREVENT PREGNANCY . . . . . . . 02 RESPONDENT WANTED TO PREVENT BOTH STD/HIV AND PREGNANCY . . . . . . . . . . . . . . . . 03 DID NOT TRUST PARTNERS/FEELS PARTNER HAS OTHER PARTNERS 04 PARTNER INSISTED . . . . . . . . . . . . 05 OTHER 96 (SPECIFY) DON’T KNOW . . . . . . . . . . . . . . . . . . 98 , * * * * * *<517 * * * - 516B What was the main reason for not using a condom? RESPONDENT WANTED TO BECOME PREGNANT . . . . . . . . . . . 01 TRUSTED PARTNER . . . . . . . . . . . . 02 PARTNER INSISTED . . . . . . . . . . . . 03 OTHER 96 (SPECIFY) DON’T KNOW . . . . . . . . . . . . . . . . . . 98 517 What is your relationship to the man with whom you last had sex? IF MAN IS "BOYFRIEND" OR "FIANCE", ASK: Was your boyfriend/fiance living with you when you last had sex? IF YES, CIRCLE ‘01'. IF NO, CIRCLE '02'. SPOUSE/COHABITING PARTNER . 01 MAN IS BOYFRIEND/FIANCE . . . . . 02 OTHER FRIEND . . . . . . . . . . . . . . . . 03 CASUAL ACQUAINTANCE . . . . . . . 04 RELATIVE . . . . . . . . . . . . . . . . . . . . 05 COMMERCIAL SEX WORKER . . . . . 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 another man, was a condom used? YES . . . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 ))<521 520A What was the main reason you used a condom on that occasion? RESPONDENT WANTED TO PREVENT STD/HIV . . . . . . . . . . 01 RESPONDENT WANTED TO PREVENT PREGNANCY . . . . . . . 02 RESPONDENT WANTED TO PREVENT BOTH STD/HIV AND PREGNANCY . . . . . . . . . . . . . . . . . . 03 DID NOT TRUST PARTNERS/FEELS PARTNER HAS OTHER PARTNERS 04 PARTNER INSISTED . . . . . . . . . . . . 05 OTHER 96 (SPECIFY) DON’T KNOW . . . . . . . . . . . . . . . . . . 98 NO. QUESTIONS AND FILTERS CODING CATEGORIES SKIP WE33 521 What is your relationship to this man? IF MAN IS "BOYFRIEND" OR "FIANCE", ASK: Was your boyfriend/fiance living with you when you last had sex with him? IF YES, CIRCLE '01'. IF NO, CIRCLE '02'. SPOUSE/COHABITING PARTNER . 01 MAN IS BOYFRIEND/FIANCE . . . . . 02 OTHER FRIEND . . . . . . . . . . . . . . . . 03 CASUAL ACQUAINTANCE . . . . . . . 04 RELATIVE . . . . . . . . . . . . . . . . . . . . 05 COMMERCIAL SEX WORKER . . . . . 06 OTHER 96 (SPECIFY) ))<523 522 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 sexual intercourse with anyone else in the last 12 months? YES . . . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 ))<524 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? RESPONDENT WANTED TO PREVENT STD/HIV . . . . . . . . . . . . 01 RESPONDENT WANTED TO PREVENT PREGNANCY . . . . . . . . 02 RESPONDENT WANTED TO PREVENT BOTH STD/HIV AND PREGNANCY . . . . . . . . . . . . . . . . . 03 DID NOT TRUST PARTNERS/FEELS PARTNER HAS OTHER PARTNERS 04 PARTNER INSISTED . . . . . . . . . . . . 05 OTHER 96 (SPECIFY) DON’T KNOW . . . . . . . . . . . . . . . . . . 98 522D What is your relationship to this other man? IF MAN IS “BOYFRIEND” OR “FIANCE”, ASK: Was your boyfriend/fiance living with you when you had sex with him? IF YES, CIRCLE ‘01'. IF NO, CIRCLE '02'. SPOUSE/COHABITING PARTNER . 01 MAN IS BOYFRIEND/FIANCE . . . . . 02 OTHER FRIEND . . . . . . . . . . . . . . . . 03 CASUAL ACQUAINTANCE . . . . . . . 04 RELATIVE . . . . . . . . . . . . . . . . . . . . 05 COMMERCIAL SEX WORKER . . . . . 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 In total, how many different men have you had sex with in the last 12 months? +)))0))), NUMBER OF PARTNERS . . . *!!!*!!!* .)))2)))- 523B When having sex with a non-regular partner, how often do you use a condom? NO NON-REGULAR PARTNER . . . . 1 NEVER USED . . . . . . . . . . . . . . . . . . . 2 LESS OFTEN . . . . . . . . . . . . . . . . . . . 3 OFTEN . . . . . . . . . . . . . . . . . . . . . . . . 4 ALWAYS . . . . . . . . . . . . . . . . . . . . . . . 5 524 Do you know of a place where a person can get condoms? YES . . . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 ))<527 NO. QUESTIONS AND FILTERS CODING CATEGORIES SKIP WE34 525 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 OUTREACH . . . . . . . . . . . . . . . . . . . D GOV'T COMMUNITY BASED DISTRIBUTOR . . . . . . . . . . . . . . . E OTHER PUBLIC F (SPECIFY) PRIVATE MEDICAL SECTOR PRIVATE HOSPITAL/CLINIC . . . . . G PHARMACY/DRUG SHOP . . . . . . . H PRIVATE DOCTOR/NURSE/ MIDWIFE . . . . . . . . . . . . . . . . . . . . I OUTREACH . . . . . . . . . . . . . . . . . . . . J NGO COMMUNITY BASED DISTRIBUTOR . . . . . . . . . . . . . . . . . K OTHER PRIVATE MEDICAL L (SPECIFY) OTHER SOURCE SHOP . . . . . . . . . . . . . . . . . . . . . . . M RELIGIOUS INSTITUTION . . . . . . . N FRIENDS/RELATIVES . . . . . . . . . . O STREET VENDOR . . . . . . . . . . . . . . P LODGE . . . . . . . . . . . . . . . . . . . . . . Q OTHER X (SPECIFY) 526 If you wanted to, could you yourself obtain a condom? YES . . . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 DON’T KNOW/UNSURE . . . . . . . . . . . 8 526A If you had a condom, could you convince your partner to use it? YES . . . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 DON’T KNOW/UNSURE . . . . . . . . . . . 8 527 Do you know of a place where a person can get female condoms? YES . . . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 ))<601 528 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 OUTREACH . . . . . . . . . . . . . . . . . . . D GOV'T COMMUNITY BASED DISTRIBUTOR . . . . . . . . . . . . . . . E OTHER PUBLIC F (SPECIFY) PRIVATE MEDICAL SECTOR PRIVATE HOSPITAL/CLINIC . . . . . G PHARMACY/DRUG SHOP . . . . . . . H PRIVATE DOCTOR/NURSE/ MIDWIFE . . . . . . . . . . . . . . . . . . . . I OUTREACH . . . . . . . . . . . . . . . . . . . . J NGO COMMUNITY BASED DISTRIBUTOR . . . . . . . . . . . . . . . . . K OTHER PRIVATE MEDICAL L (SPECIFY) OTHER SOURCE SHOP . . . . . . . . . . . . . . . . . . . . . . . M RELIGIOUS INSTITUTION . . . . . . . N FRIENDS/RELATIVES . . . . . . . . . . O STREET VENDOR . . . . . . . . . . . . . . P LODGE . . . . . . . . . . . . . . . . . . . . . . Q OTHER X (SPECIFY) 529 If you wanted to, could you yourself obtain a female condom? YES . . . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 DON’T KNOW/UNSURE . . . . . . . . . . . 8 SECTION 6. FERTILITY PREFERENCES WE35 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 UNDECIDED/DON’T KNOW 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 01 YEAR .)))2))))))))))))))))))))))) ? ? ))<610 NO. QUESTIONS AND FILTERS CODING CATEGORIES SKIP WE36 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? 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? NOT +))), NO, NOT +))), YES, CURRENTLY +))), ASKED /)))- CURRENTLY /)))- USING .)))2))))))))))))))))))))))))))))))) ? USING ? ))<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/COIL . . . . . . . . . . . . . . . . . . . . . 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 WE37 612 What is the main reason that you think you will not use a method at any time in the future? 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 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 six months have you heard/read about family planning: On the radio? On the television? In a newspaper or magazine? Billboards? Community meeting/church? Mobile van? YES NO RADIO . . . . . . . . . . . . . . . . . . . 1 2 TELEVISION . . . . . . . . . . . . . . . 1 2 NEWSPAPER OR MAGAZINE . 1 2 BILLBOARDS . . . . . . . . . . . . . . 1 2 COMMUNITY MEETING . . . . . . 1 2 MOBILE VAN . . . . . . . . . . . . . . 1 2 619 In the last six months, have you discussed the practice of family planning with your husband, partner, friends, neighbours, 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/NEIGHBOURS . . . . . . . . . . . I OTHER X (SPECIFY) NO. QUESTIONS AND FILTERS CODING CATEGORIES SKIP WE38 621 CHECK 501: YES, +))), YES, +))), NO, +))), CURRENTLY /)))- LIVING /)))- NOT IN .)))2))))))))))))))))))))))))))))))) MARRIED ? WITH A MAN ? UNION ))<628 622 CHECK 311/311A: ANY CODE CIRCLED +))), NO CODE CIRCLED +))), /)))- .)))2))))))))))))))))))))))))) ? ))<624 623 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) 624 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 . . . . . . . . . . . . . . . . . . . 8 625 How often have you talked to your husband/partner about family planning in the past year? NEVER . . . . . . . . . . . . . . . . . . . . . . . . 1 ONCE OR TWICE . . . . . . . . . . . . . . . . 2 MORE OFTEN . . . . . . . . . . . . . . . . . . 3 626 CHECK 311/311A: NEITHER +))), HE OR SHE +))), STERILIZED /)))- STERILIZED .)))2))))))))))))))))))))))))))))))))))))))))))))))))))) ? ))<628 627 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 . . . . . . . . . . . . . . . . . . . 8 628 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 WE39 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 post secondary? PRIMARY . . . . . . . . . . . . . . . . . . . . . . 1 SECONDARY . . . . . . . . . . . . . . . . . . . 2 POST SECONDARY . . . . . . . . . . . . . . 3 DON’T KNOW . . . . . . . . . . . . . . . . . . . 8 ))<706 705 What was the highest (grade/form/year) he completed at that level? +)))0))), GRADE . . . . . . . . . . . . . . . . . . *!!!*!!!* .)))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, during the past 7 days did you do any other work? 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 +))), AGRICULTURE /)))- IN AGRICULTURE .)))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 PUBLIC LAND . . . . . . . . . . . . . . . . . . 5 COMMUNAL LAND . . . . . . . . . . . . . . . 6 713 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 . . . . . . . . . . . . . . . 3 714 Do you usually work at home or away from home? HOME . . . . . . . . . . . . . . . . . . . . . . . . . 1 AWAY . . . . . . . . . . . . . . . . . . . . . . . . . 2 715 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 WE40 716 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<719 717 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 . . . . . . . . . . . . . . . . . . . . . 5 718 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? Children’s health care? Making large household purchases? Making household purchases for daily needs? Visits to family or relatives? What food should be cooked each day? 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 WE41 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 ALL MENTIONED. ABSTAIN FROM SEX . . . . . . . . . . . . . A USE CONDOMS . . . . . . . . . . . . . . . . . B LIMIT SEX TO ONE PARTNER/STAY FAITHFUL TO ONE PARTNER . . . . C LIMIT NUMBER OF SEXUAL PARTNERS . . . . . . . . . . . . . . . . . . . D AVOID SEX WITH PROSTITUTES . . . E AVOID SEX WITH PERSONS WHO HAVE MANY PARTNERS . . . . . . . . F AVOID SEX WITH HOMOSEXUALS . G AVOID SEX WITH PERSONS WHO INJECT DRUGS INTRAVENOUSLY H AVOID BLOOD TRANSFUSIONS . . . . . I AVOID INJECTIONS . . . . . . . . . . . . . . J AVOID KISSING . . . . . . . . . . . . . . . . . K AVOID MOSQUITO BITES . . . . . . . . . L SEEK PROTECTION FROM TRADITIONAL PRACTITIONER . . . M AVOID SKIN PIERCING/CUTTING INSTRUMENTS . . . . . . . . . . . . . . . . . N SHARING SYRINGE . . . . . . . . . . . . . . O SHARING A TOILET . . . . . . . . . . . . . . P AVOID TOUCHING A PERSON WITH AIDS . . . . . . . . . . . . . . . . . . . . . . . . . . Q AVOID SHARING FOOD . . . . . . . . . . R OTHER W (SPECIFY) OTHER X (SPECIFY) DON’T KNOW . . . . . . . . . . . . . . . . . . . Z 804 Can people reduce their chances of getting the AIDS virus by having just one sex partner who has no other partners? YES . . . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 DON’T KNOW . . . . . . . . . . . . . . . . . . . 8 805 Can a person get the AIDS virus from mosquito bites? YES . . . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 DON’T KNOW . . . . . . . . . . . . . . . . . . . 8 806 Can people reduce their chances of getting the AIDS virus by using a condom every time they have sex? YES . . . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 DON’T KNOW . . . . . . . . . . . . . . . . . . . 8 807 Can a person get the AIDS virus by sharing food with a person who has AIDS? YES . . . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 DON’T KNOW . . . . . . . . . . . . . . . . . . . 8 809 Is it possible for a healthy-looking person to have the AIDS virus? YES . . . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 DON’T KNOW . . . . . . . . . . . . . . . . . . . 8 810 Do you know someone personally (relative, friend or colleague) who has the virus that causes AIDS or someone who died from AIDS? YES . . . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 811 Can the virus that causes AIDS be transmitted from a mother to a child? YES . . . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 DON’T KNOW . . . . . . . . . . . . . . . . . . . 8 ), )2<813 812 When can the virus that causes AIDS be transmitted from a mother to a child: YES NO DK During pregnancy? During delivery? By breastfeeding? DURING PREG . . . . . 1 2 8 DURING DELIVERY . 1 2 8 BREASTFEEDING . . 1 2 8 NO. QUESTIONS AND FILTERS CODING CATEGORIES SKIP WE42 813 CHECK 501: YES, CURRENTLY MARRIED/ +))), NO, NOT IN UNION +))), LIVING WITH A MAN /)))- .)))2))))))))))))))))))))))))) ? ))<815 814 Have you ever talked about ways to prevent getting the virus that causes AIDS with (your husband/the man you are living with)? YES . . . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 815 If a person learns that he/she is infected with the virus that causes AIDS, should the person be allowed to keep this fact private or should this information be available to the community? CAN BE KEPT PRIVATE . . . . . . . . . . 1 AVAILABLE TO COMMUNITY . . . . . . 2 DK/NOT SURE . . . . . . . . . . . . . . . . . . 8 815A In your opinion, is it acceptable or unacceptable for AIDS to be discussed: on the radio? on the TV? in newspapers? NOT ACCEPT- ACCEPT- ABLE ABLE ON THE RADIO . . . . 1 2 ON THE TV . . . . . . . . 1 2 IN NEWSPAPERS . . 1 2 816 If a member of your family became sick with the virus that causes AIDS, would you be willing to care for her or him in your own household? YES . . . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 DK/NOT SURE/DEPENDS . . . . . . . . . 8 817 If a female teacher has the AIDS virus, should she/he be allowed to continue teaching in the school? CAN CONTINUE . . . . . . . . . . . . . . . . . 1 SHOULD NOT CONTINUE . . . . . . . . . 2 DK/NOT SURE/DEPENDS . . . . . . . . . 8 817A Should children aged 12-14 years be taught about using a condom to avoid AIDS? YES . . . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 DK/NOT SURE/DEPENDS . . . . . . . . . 8 817B Have you ever been tested to see if you have the AIDS virus? YES . . . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 ))<817E 817C Where did you go for the test the last time? PUBLIC SECTOR GOVT. HOSPITAL . . . . . . . . . . . . . 11 GOVT. HEALTH CENTER . . . . . . . 12 FAMILY PLANNING CLINIC . . . . . . 13 OTHER PUBLIC 16 (SPECIFY) PRIVATE MEDICAL SECTOR PRIVATE HOSPITAL/CLINIC . . . . . 21 PHARMACY . . . . . . . . . . . . . . . . . . 22 PRIVATE DOCTOR . . . . . . . . . . . . 23 OTHER PRIVATE MEDICAL 26 (SPECIFY) OTHER 96 (SPECIFY) 817D Did you get the result? DO NOT ASK FOR THE RESULT YES . . . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 )), ))2<818 817E Would you want to be tested for the AIDS virus? YES . . . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 DON’T KNOW/UNSURE . . . . . . . . . . . 8 ), )2<818 817F Do you know a place where you could go to get an AIDS test? YES . . . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 ))<818 NO. QUESTIONS AND FILTERS CODING CATEGORIES SKIP WE43 817G Where can you go for the test? 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 OTHER PUBLIC F (SPECIFY) PRIVATE MEDICAL SECTOR PRIVATE HOSPITAL/CLINIC . . . . . . G PHARMACY . . . . . . . . . . . . . . . . . . . H PRIVATE DOCTOR . . . . . . . . . . . . . . I OTHER PRIVATE MEDICAL L (SPECIFY) OTHER X (SPECIFY) 818 (Apart from AIDS), have you heard about (other) infections that can be transmitted through sexual contact? YES . . . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 ))<901 818A What infections do you know? RECORD ALL MENTIONED. SYPHILIS . . . . . . . . . . . . . . . . . . . . . . A GONORRHEA . . . . . . . . . . . . . . . . . . B GENITAL WARTS/CONDYLOMATA . C CHANCROID . . . . . . . . . . . . . . . . . . . D CHLAMYDIA . . . . . . . . . . . . . . . . . . . . E CANDIDA . . . . . . . . . . . . . . . . . . . . . . F OTHER X (SPECIFY 818B Infections that are transmitted through sexual contact can cause problems if left untreated. What are some of these problems? RECORD ALL MENTIONED. INFERTILITY . . . . . . . . . . . . . . . . . . . A MISCARRIAGE/STILLBIRTH . . . . . . . B EASIER TO GET HIV . . . . . . . . . . . . . C BABY BORN SICK . . . . . . . . . . . . . . . D MADNESS . . . . . . . . . . . . . . . . . . . . . E OTHER . . . . . . . . . . . . . . . . . . . . . . . . X DON’T KNOW . . . . . . . . . . . . . . . . . . . Y 819 If a woman has a sexually transmitted disease, what symptoms might she have? Any others? PROBE; DO NOT READ OUT THE OPTIONS RECORD ALL MENTIONED. ABDOMINAL PAIN . . . . . . . . . . . . . . . A GENITAL DISCHARGE . . . . . . . . . . . B FOUL SMELLING DISCHARGE . . . . . C BURNING PAIN ON URINATION . . . . D REDNESS/INFLAMMATION IN GENITAL AREA . . . . . . . . . . . . . . . . E SWELLING IN GENITAL AREA . . . . . F GENITAL SORES/ULCERS . . . . . . . . G GENITAL WARTS . . . . . . . . . . . . . . . . H GENITAL ITCHING . . . . . . . . . . . . . . . . I BLOOD IN URINE . . . . . . . . . . . . . . . . . J LOSS OF WEIGHT . . . . . . . . . . . . . . K HARD TO GET PREGNANT/ HAVE A CHILD . . . . . . . . . . . . . . . L OTHER W (SPECIFY) OTHER X (SPECIFY) NO SYMPTOMS . . . . . . . . . . . . . . . . . Y DON’T KNOW . . . . . . . . . . . . . . . . . . . Z NO. QUESTIONS AND FILTERS CODING CATEGORIES SKIP WE44 819A If a man has a sexually transmitted disease, what symptoms might she have? Any others? PROBE; DO NOT READ OUT THE OPTIONS RECORD ALL MENTIONED. ABDOMINAL PAIN . . . . . . . . . . . . . . . A GENITAL DISCHARGE . . . . . . . . . . . B FOUL SMELLING DISCHARGE . . . . . C BURNING PAIN ON URINATION . . . . D REDNESS/INFLAMMATION IN GENITAL AREA . . . . . . . . . . . . . . . . E SWELLING IN GENITAL AREA . . . . . F GENITAL SORES/ULCERS . . . . . . . . G GENITAL WARTS . . . . . . . . . . . . . . . . H GENITAL ITCHING . . . . . . . . . . . . . . . . I BLOOD IN URINE . . . . . . . . . . . . . . . . . J LOSS OF WEIGHT . . . . . . . . . . . . . . K IMPOTENCY/STERILITY . . . . . . . . . . L OTHER W (SPECIFY) OTHER X (SPECIFY) NO SIGNS/SYMPTOMS . . . . . . . . . . . Y DON’T KNOW . . . . . . . . . . . . . . . . . . . Z 820 CHECK 514: HAS HAD SEXUAL +), HAS NOT HAD SEXUAL +), INTERCOURSE /)- INTERCOURSE .)2))))))))))))))))))))))))))))))))))))))))) ? ))<901 820A Now I would like to ask you some questions about your health in the last 12 months. During the last 12 months, have you had a sexually-transmitted disease? YES . . . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 DON’T KNOW . . . . . . . . . . . . . . . . . . . 8 ), )2<820C 820B Which one? Any other? RECORD ALL MENTIONED. SYPHILIS . . . . . . . . . . . . . . . . . . . . . . A GONORRHEA . . . . . . . . . . . . . . . . . . B GENITAL WARTS/CONDYLOMATA . C CHANCROID . . . . . . . . . . . . . . . . . . . D CHLAMYDIA . . . . . . . . . . . . . . . . . . . . E CANDIDA . . . . . . . . . . . . . . . . . . . . . . F OTHER X (SPECIFY) DON'T KNOW . . . . . . . . . . . . . . . . . . . Z 820C During the last 12 months, have you had a genital discharge (abnormal, itchy, smelly)? YES . . . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 DON’T KNOW . . . . . . . . . . . . . . . . . . . 8 820D Sometimes women have a genital sore or ulcer. During the last 12 months, have you had a genital sore or ulcer? YES . . . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 DON’T KNOW . . . . . . . . . . . . . . . . . . . 8 820E CHECK 820B/820C/820D : HAS HAD +), AN INFECTION /)- ? HAS NOT HAD AN INFECTION OR DOES NOT KNOW +), .)2)))))))))))))))))) ))<901 820F The last time you had (INFECTION FROM 820B/820C/820D) did you seek any kind of advice or treatment? YES . . . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 ))<820I 820G The last time you had (INFECTION FROM 820B/820C/820D), did you do any of the following? Did you. Seek advice from a health worker in a clinic or hospital? Seek advice or medicine from a traditional healer? Seek advice or buy medicine in a drug shop or pharmacy? Ask for advice from friends or relatives? Do self medication? YES NO CLINIC/HOSPITAL . . . . . . . . . 1 2 TRADITIONAL HEALER . . . . . 1 2 DRUG SHOP/PHARMACY . . . 1 2 FRIENDS/RELATIVES . . . . . . 1 2 SELF MEDICATION . . . . . . . . 1 2 WE45 820H When you had (INFECTION FROM 820B/820C/820D), did you inform the person(s) (spouse/ regular partner/ casual partner) with whom you were having sex? YES . . . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 SOME/ NOT ALL . . . . . . . . . . . . . . . . 3 820I When you had (INFECTION FROM 820B/820C/820D), did you do something to avoid infecting your sexual partner(s)? YES . . . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 PARTNER(S) ALREADY INFECTED . 3 )), ))2<901 820J What did you do to avoid infecting your partner(s)? Did you. Stop having sex? Use a condom when having sex? Take medicine? Advise him to have medical consultation? YES NO STOP SEX . . . . . . . . . . . . . . . 1 2 USE CONDOM . . . . . . . . . . . . 1 2 TAKE MEDICINE . . . . . . . . . . 1 2 ADVISE TO CONSULT . . . . . . 1 2 WE46 SECTION 9. MATERNAL MORTALITY NO. QUESTIONS AND FILTERS CODING CATEGORIES SKIP 901 Now I would like to ask you some questions about your brothers and sisters, that is, all of the children born to your natural mother, including those who are living with you, those living elsewhere and those who have died. How many children did your mother give birth to, including you? NUMBER OF BIRTHS +)))0))), TO NATURAL MOTHER . . . . . *!!!*!!!* .)))2)))- 902 CHECK 901: +))), +))), TWO OR MORE BIRTHS /)))- ONLY ONE BIRTH .)))2)))))))))))))))))))))))))))))))))))))))) ? (RESPONDENT ONLY) ))<916 903 How many of these births did your mother have before you were born? NUMBER OF +)))0))), PRECEDING BIRTHS . . . . . . . *!!!*!!!* .)))2)))- 904 What was the name given to your oldest (next oldest) brother or sister? [1] [2] [3] [4] [5] [6] 905 Is (NAME) male or female? MALE . . . . 1 FEMALE . . 2 MALE . . . . 1 FEMALE . . 2 MALE . . . . 1 FEMALE . . 2 MALE . . . . 1 FEMALE . . 2 MALE . . . . 1 FEMALE . . 2 MALE . . . . 1 FEMALE . . 2 906 Is (NAME) still alive? YES . . . . . 1 NO . . . . . . 2 .)<GO TO 908 DK . . . . . . . 8 .)<GO TO [2] YES . . . . . 1 NO . . . . . . 2 .)<GO TO 908 DK . . . . . . . 8 .)<GO TO [3] YES . . . . . 1 NO . . . . . . 2 .)<GO TO 908 DK . . . . . . . 8 .)<GO TO [4] YES . . . . . 1 NO . . . . . . 2 .)<GO TO 908 DK . . . . . . . 8 .)<GO TO [5] YES . . . . . 1 NO . . . . . . 2 .)<GO TO 908 DK . . . . . . . 8 .)<GO TO [6] YES . . . . . 1 NO . . . . . . 2 .)<GO TO 908 DK . . . . . . . 8 .)<GO TO [7] 907 How old is (NAME)? +)))0))), *!!!*!!!* .)))2)))- GO TO [2] +)))0))), *!!!*!!!* .)))2)))- GO TO [3] +)))0))), *!!!*!!!* .)))2)))- GO TO [4] +)))0))), *!!!*!!!* .)))2)))- GO TO [5] +)))0))), *!!!*!!!* .)))2)))- GO TO [6] +)))0))), *!!!*!!!* .)))2)))- GO TO [7] 908 In what year did (NAME) die? GO TO 910=)- DK . . . . 9998 GO TO 910=)- DK . . . . 9998 GO TO 910=)- DK . . . . 9998 GO TO 910=)- DK . . . . 9998 GO TO 910=)- DK . . . . 9998 GO TO 910=)- DK . . . . 9998 909 How many years ago did (NAME) die? +)))0))), *!!!*!!!* .)))2)))- +)))0))), *!!!*!!!* .)))2)))- +)))0))), *!!!*!!!* .)))2)))- +)))0))), *!!!*!!!* .)))2)))- +)))0))), *!!!*!!!* .)))2)))- +)))0))), *!!!*!!!* .)))2)))- 910 How old was (NAME) when he/she died? +)))0))), *!!!*!!!* .)))2)))- IF MALE OR DIED BEFORE 12 YEARS OF AGE GO TO [2] +)))0))), *!!!*!!!* .)))2)))- IF MALE OR DIED BEFORE 12 YEARS OF AGE GO TO [3] +)))0))), *!!!*!!!* .)))2)))- IF MALE OR DIED BEFORE 12 YEARS OF AGE GO TO [4] +)))0))), *!!!*!!!* .)))2)))- IF MALE OR DIED BEFORE 12 YEARS OF AGE GO TO [5] +)))0))), *!!!*!!!* .)))2)))- IF MALE OR DIED BEFORE 12 YEARS OF AGE GO TO [6] +)))0))), *!!!*!!!* .)))2)))- IF MALE OR DIED BEFORE 12 YEARS OF AGE GO TO [7] 911 Was (NAME) pregnant when she died? YES . . . . . 1 GO TO 915=)- NO . . . . . . 2 YES . . . . . 1 GO TO 915=)- NO . . . . . . 2 YES . . . . . 1 GO TO 915=)- NO . . . . . . 2 YES . . . . . 1 GO TO 915=)- NO . . . . . . 2 YES . . . . . 1 GO TO 915=)- NO . . . . . . 2 YES . . . . . 1 GO TO 915=)- NO . . . . . . 2 912 Did (NAME) die during childbirth? YES . . . . . 1 GO TO 915=)- NO . . . . . . 2 YES . . . . . 1 GO TO 915=)- NO . . . . . . 2 YES . . . . . 1 GO TO 915=)- NO . . . . . . 2 YES . . . . . 1 GO TO 915=)- NO . . . . . . 2 YES . . . . . 1 GO TO 915=)- NO . . . . . . 2 YES . . . . . 1 GO TO 915=)- NO . . . . . . 2 913 Did (NAME) die within 2 months after the end of a pregnancy or childbirth? YES . . . . . 1 NO . . . . . . 2 YES . . . . . 1 NO . . . . . . 2 YES . . . . . 1 NO . . . . . . 2 YES . . . . . 1 NO . . . . . . 2 YES . . . . . 1 NO . . . . . . 2 YES . . . . . 1 NO . . . . . . 2 915 How many children did (NAME) give birth to during her lifetime? +)))0))), *!!!*!!!* .)))2)))- GO TO [2] +)))0))), *!!!*!!!* .)))2)))- GO TO [3] +)))0))), *!!!*!!!* .)))2)))- GO TO [4] +)))0))), *!!!*!!!* .)))2)))- GO TO [5] +)))0))), *!!!*!!!* .)))2)))- GO TO [6] +)))0))), *!!!*!!!* .)))2)))- GO TO [7] IF NO MORE BROTHERS OR SISTERS, GO TO 916 WE47 904 What was name given to your oldest (next oldest) brother or sister? [7] [8] [9] [10] [11] [12] 905 Is (NAME) male or female? MALE . . . . 1 FEMALE . . 2 MALE . . . . 1 FEMALE . . 2 MALE . . . . 1 FEMALE . . 2 MALE . . . . 1 FEMALE . . 2 MALE . . . . 1 FEMALE . . 2 MALE . . . . 1 FEMALE . . 2 906 Is (NAME) still alive? YES . . . . . 1 NO . . . . . . 2 .)<GO TO 908 DK . . . . . . . 8 .)<GO TO [8] YES . . . . . 1 NO . . . . . . 2 .)<GO TO 908 DK . . . . . . . 8 .)<GO TO [9] YES . . . . . 1 NO . . . . . . 2 .)<GO TO 908 DK . . . . . . . 8 .)<GO TO [10] YES . . . . . 1 NO . . . . . . 2 .)<GO TO 908 DK . . . . . . . 8 .)<GO TO [11] YES . . . . . 1 NO . . . . . . 2 .)<GO TO 908 DK . . . . . . . 8 .)<GO TO [12] YES . . . . . 1 NO . . . . . . 2 .)<GO TO 908 DK . . . . . . . 8 .)<GO TO [13] 907 How old is (NAME)? +)))0))), *!!!*!!!* .)))2)))- GO TO [8] +)))0))), *!!!*!!!* .)))2)))- GO TO [9] +)))0))), *!!!*!!!* .)))2)))- GO TO [10] +)))0))), *!!!*!!!* .)))2)))- GO TO [11] +)))0))), *!!!*!!!* .)))2)))- GO TO [12] +)))0))), *!!!*!!!* .)))2)))- GO TO [13] 908 In what year did (NAME) die? GO TO 910=)- DK . . . . 9998 GO TO 910=)- DK . . . . 9998 GO TO 910=)- DK . . . . 9998 GO TO 910=)- DK . . . . 9998 GO TO 910=)- DK . . . . 9998 GO TO 910=)- DK . . . . 9998 909 How many years ago did (NAME) die? +)))0))), *!!!*!!!* .)))2)))- +)))0))), *!!!*!!!* .)))2)))- +)))0))), *!!!*!!!* .)))2)))- +)))0))), *!!!*!!!* .)))2)))- +)))0))), *!!!*!!!* .)))2)))- +)))0))), *!!!*!!!* .)))2)))- 910 How old was (NAME) when he/she died? +)))0))), *!!!*!!!* .)))2)))- IF MALE OR DIED BEFORE 12 YEARS OF AGE GO TO [8] +)))0))), *!!!*!!!* .)))2)))- IF MALE OR DIED BEFORE 12 YEARS OF AGE GO TO [9] +)))0))), *!!!*!!!* .)))2)))- IF MALE OR DIED BEFORE 12 YEARS OF AGE GO TO [10] +)))0))), *!!!*!!!* .)))2)))- IF MALE OR DIED BEFORE 12 YEARS OF AGE GO TO [11] +)))0))), *!!!*!!!* .)))2)))- IF MALE OR DIED BEFORE 12 YEARS OF AGE GO TO [12] +)))0))), *!!!*!!!* .)))2)))- IF MALE OR DIED BEFORE 12 YEARS OF AGE GO TO [13] 911 Was (NAME) pregnant when she died? YES . . . . . 1 GO TO 915=)- NO . . . . . . 2 YES . . . . . 1 GO TO 915=)- NO . . . . . . 2 YES . . . . . 1 GO TO 915=)- NO . . . . . . 2 YES . . . . . 1 GO TO 915=)- NO . . . . . . 2 YES . . . . . 1 GO TO 915=)- NO . . . . . . 2 YES . . . . . 1 GO TO 915=)- NO . . . . . . 2 912 Did (NAME) die during childbirth? YES . . . . . 1 GO TO 915=)- NO . . . . . . 2 YES . . . . . 1 GO TO 915=)- NO . . . . . . 2 YES . . . . . 1 GO TO 915=)- NO . . . . . . 2 YES . . . . . 1 GO TO 915=)- NO . . . . . . 2 YES . . . . . 1 GO TO 915=)- NO . . . . . . 2 YES . . . . . 1 GO TO 915=)- NO . . . . . . 2 913 Did (NAME) die within two months after the end of a pregnancy or childbirth? YES . . . . . 1 NO . . . . . . 2 YES . . . . . 1 NO . . . . . . 2 YES . . . . . 1 NO . . . . . . 2 YES . . . . . 1 NO . . . . . . 2 YES . . . . . 1 NO . . . . . . 2 YES . . . . . 1 NO . . . . . . 2 915 How many children did (NAME) give birth to during her lifetime? +)))0))), *!!!*!!!* .)))2)))- GO TO [8] +)))0))), *!!!*!!!* .)))2)))- GO TO [9] +)))0))), *!!!*!!!* .)))2)))- GO TO [10] +)))0))), *!!!*!!!* .)))2)))- GO TO [11] +)))0))), *!!!*!!!* .)))2)))- GO TO [12] +)))0))), *!!!*!!!* .)))2)))- GO TO [13] IF NO MORE BROTHERS OR SISTERS, GO TO 916 916 RECORD THE TIME. +)))0))), HOURS . . . . . . . . . . . . . . . . . . . . . . . . . . *!!!*!!!* .)))2)))- +)))0))), MINUTES . . . . . . . . . . . . . . . . . . . . . . . . *!!!*!!!* .)))2)))- WE48 INTERVIEWER’S OBSERVATIONS TO BE FILLED IN AFTER COMPLETING INTERVIEW COMMENTS ABOUT RESPONDENT: COMMENTS ON SPECIFIC QUESTIONS: ANY OTHER COMMENTS: SUPERVISOR’S OBSERVATIONS NAME OF THE SUPERVISOR:______________________________________DATE: ___________________________________ EDITOR’S OBSERVATIONS NAME OF EDITOR:_______________________________________________DATE: ___________________________________ WE48 INSTRUCTIONS: ONLY ONE CODE SHOULD APPEAR IN ANY BOX. BIRTHS AND PREGNANCIES B BIRTHS P PREGNANCIES T TERMINATIONS 01 JAN 01 12 DEC 02 11 NOV 03 10 OCT 04 09 SEP 05 2 08 AUG 06 0 07 JUL 07 0 06 JUN 08 0 05 MAY 09 04 APR 10 03 MAR 11 02 FEB 12 01 JAN 13 12 DEC 14 11 NOV 15 10 OCT 16 09 SEP 17 1 08 AUG 18 9 07 JUL 19 9 06 JUN 20 9 05 MAY 21 04 APR 22 03 MAR 23 02 FEB 24 01 JAN 25 12 DEC 26 11 NOV 27 10 OCT 28 09 SEP 29 1 08 AUG 30 9 07 JUL 31 9 06 JUN 32 8 05 MAY 33 04 APR 34 03 MAR 35 02 FEB 36 01 JAN 37 12 DEC 38 11 NOV 39 10 OCT 40 09 SEP 41 1 08 AUG 42 9 07 JUL 43 9 06 JUN 44 7 05 MAY 45 04 APR 46 03 MAR 47 02 FEB 48 01 JAN 49 12 DEC 50 11 NOV 51 10 OCT 52 09 SEP 53 1 08 AUG 54 9 07 JUL 55 9 06 JUN 56 6 05 MAY 57 04 APR 58 03 MAR 59 02 FEB 60 01 JAN 61 12 DEC 62 11 NOV 63 10 OCT 64 09 SEP 65 1 08 AUG 66 9 07 JUL 67 9 06 JUN 68 5 05 MAY 69 04 APR 70 03 MAR 71 02 FEB 72 01 JAN 73 ME1 2000 UGANDA DEMOGRAPHIC AND HEALTH SURVEY MEN’S QUESTIONNAIRE IDENTIFICATION REGION DISTRICT COUNTY SUBCOUNTY/TOWN PARISH/LC2 NAME EA NAME UDHS NUMBER URBAN/RURAL (URBAN=1, RURAL=2) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . LARGE CITY/SMALL CITY/TOWN/COUNTRYSIDE . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . (LARGE CITY=1, SMALL CITY=2, TOWN=3, COUNTRYSIDE=4) HOUSEHOLD NUMBER . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . NAME AND LINE NUMBER OF MAN +))), !!*!!!* +)))3)))1 *!!!*!!!* .)))3)))1 !!!*!!!* /)))1 *!!!* +)))3)))1 *!!!*!!!* /)))3)))1 *!!!*!!!* +)))0)))3)))3)))1 *!!!*!!!*!!!*!!!* .)))2)))2)))3)))1 *!!!* /)))1 *!!!* +)))0)))3)))1 *!!!*!!!*!!!* .)))3)))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 +))), *!7!* /)))1 LANGUAGE USED IN INTERVIEW . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . *!!!* /)))1 RESPONDENT'S LOCAL LANGUAGE . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . *!!!* /)))1 TRANSLATOR USED (NOT AT ALL=1; SOMETIMES=2; ALL THE TIME=3) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . *!!!* LANGUAGE: 1 ATESO-KARAMOJONG 4 LUO 7 ENGLISH .)))- 2 LUGANDA 5 RUNYANKOLE-RUKIGA 8 OTHER 3 LUGBARA 6 RUNYORO-RUTORO SUPERVISOR FIELD EDITOR OFFICE EDITOR KEYED BY NAME +)))0))), *!!!*!!!* .)))2)))- NAME +)))0))), *!!!*!!!* .)))2)))- +)))0))), *!!!*!!!* .)))2)))- +)))0))), *!!!*!!!* .)))2)))-DATE DATE ME2 SECTION 1. RESPONDENT’S BACKGROUND INFORMED CONSENT Hello. My name is and I am working with Uganda Bureau of Statistics. We are conducting a national survey about the health of men, women and children. We would very much appreciate your participation in this survey. I would like to ask you some questions about yourself and your family. This information will help the government to plan health services. The survey usually takes about 35 to 45 minutes to complete. Whatever information you provide will be kept strictly confidential and will not be shown to other persons. At this time, do you want to ask me anything about the survey? May I begin the interview now? Signature of interviewer: Date: RESPONDENT AGREES TO BE INTERVIEWED . . 1 ? RESPONDENT DOES NOT AGREE TO BE INTERVIEWED . 2 ))<END NO. QUESTIONS AND FILTERS CODING CATEGORIES SKIP 101 RECORD THE TIME. +)))0))), HOUR . . . . . . . . . . . . . . . . . . . *!!!*!!!* /)))3)))1 MINUTES . . . . . . . . . . . . . . . . *!!!*!!!* .)))2)))- 102 For most of the time during the last five years, did you live in a city, in a town, or in the countryside? CITY . . . . . . . . . . . . . . . . . . . . . . . . . . 1 TOWN . . . . . . . . . . . . . . . . . . . . . . . . . 2 COUNTRYSIDE . . . . . . . . . . . . . . . . . 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 the countryside? CITY . . . . . . . . . . . . . . . . . . . . . . . . . . 1 TOWN . . . . . . . . . . . . . . . . . . . . . . . . . 2 COUNTRYSIDE . . . . . . . . . . . . . . . . . 3 105 In the last 12 months, have you ever traveled away from your home community and slept away? YES . . . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 ))<108 106 In the last 12 months, on how many separate occasions have you traveled away from your home community and slept away? +)))0))), NUMBER OF TRIPS AWAY . *!!!*!!!* .)))2)))- 107 In the last 12 months, have you been away from your home community for more than 1 month at a time? YES . . . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 108 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 109 How old were you at your last birthday? COMPARE AND CORRECT 108 AND/OR 109 IF INCONSISTENT. +)))0))), AGE IN COMPLETED YEARS *!!!*!!!* .)))2)))- 110 Have you ever attended school? YES . . . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 ))<114 111 What is the highest level of school you attended: primary, secondary, or post secondary? PRIMARY . . . . . . . . . . . . . . . . . . . . . . 1 SECONDARY . . . . . . . . . . . . . . . . . . . 2 POST SECONDARY . . . . . . . . . . . . . . 3 112 What is the highest (grade/form/year) you completed at that level? +)))0))), GRADE . . . . . . . . . . . . . . . . . . *!!!*!!!* .)))2)))- 112A Did you ever receive any vocational training? NO TRAINING . . . . . . . . . . . . . . . . . . 1 TEACHER TRAINING . . . . . . . . . . . . . 2 PARAMEDICAL TRAINING . . . . . . . . 3 OTHER TRAINING . . . . . . . . . . . . . . . 6 NO. QUESTIONS AND FILTERS CODING CATEGORIES SKIP ME3 113 CHECK 111: PRIMARY +))), SECONDARY OR +))), /)))- POST SECONDARY .)))2)))))))))))))))))))))))))))))))))))))))))))))))))) ? ))<117 114 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) 115 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 . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 116 CHECK 114: CODE ‘2' +))), CODE ‘1' +))), ‘3' OR ‘4' /)))- CIRCLED .)))2))))))))))))))))))))))))))))))))))))))))))))))))) CIRCLED ? ))<118 117 During the last four weeks, did you read a newspaper or magazine almost every day, at least once a week, less than once a week or not at all? ALMOST EVERY DAY . . . . . . . . . . . . 1 AT LEAST ONCE A WEEK . . . . . . . . . 2 LESS THAN ONCE A WEEK . . . . . . . 3 NOT AT ALL . . . . . . . . . . . . . . . . . . . . 4 118 During the last four weeks, did you listen to the radio almost every day, at least once a week, less than once a week or not at all? ALMOST EVERY DAY . . . . . . . . . . . . 1 AT LEAST ONCE A WEEK . . . . . . . . . 2 LESS THAN ONCE A WEEK . . . . . . . 3 NOT AT ALL . . . . . . . . . . . . . . . . . . . . 4 119 During the last four weeks, did you watch television almost every day, at least once a week, less than once a week or not at all? ALMOST EVERY DAY . . . . . . . . . . . . 1 AT LEAST ONCE A WEEK . . . . . . . . . 2 LESS THAN ONCE A WEEK . . . . . . . 3 NOT AT ALL . . . . . . . . . . . . . . . . . . . . 4 120 Are you currently working? YES . . . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 ))<123 121 Have you done any work in the last 12 months? YES . . . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 ))<123 122 What have you been doing for most of the time over the last 12 months? GOING TO SCHOOL/STUDYING . . . . 1 LOOKING FOR WORK . . . . . . . . . . . . 2 INACTIVE . . . . . . . . . . . . . . . . . . . . . . 3 COULD NOT WORK/HANDICAPPED 4 OTHER 6 (SPECIFY) ), * * /<129 * * )- 123 What is your occupation, that is, what kind of work do you mainly do? +)))0))), *!!!*!!!* .)))2)))- 124 CHECK 123: WORKS IN +))), DOES NOT WORK +))), AGRICULTURE /)))- IN AGRICULTURE .)))2))))))))))))))))))))))))))))))))))))))))))))))))) ? ))<126 125 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 PUBLIC LAND . . . . . . . . . . . . . . . . . . 5 COMMUNAL LAND . . . . . . . . . . . . . . . 6 126 During the last 12 months, how many months did you work? +)))0))), NUMBER OF MONTHS . . . . . *!!!*!!!* .)))2)))- 127 Are you paid 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<129 NO. QUESTIONS AND FILTERS CODING CATEGORIES SKIP ME4 128 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, HIS INCOME IS ALL SAVED . 6 129 What is your religion? CATHOLIC . . . . . . . . . . . . . . . . . . . . . 1 PROTESTANT . . . . . . . . . . . . . . . . . . 2 MUSLIM . . . . . . . . . . . . . . . . . . . . . . . 3 OTHER 6 (SPECIFY) ME5 SECTION 2. REPRODUCTION NO. QUESTIONS AND FILTERS CODING CATEGORIES SKIP 201 Now I would like to ask about any children you have had. I am interested only in the children that are biologically yours. Have you ever fathered any children with any woman? YES . . . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 DON’T KNOW . . . . . . . . . . . . . . . . . . . 8 ), )2<206 202 Do you have any sons or daughters that you have fathered 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 you have fathered 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 fathered a son or a daughter who was born alive but later died? IF NO, PROBE: Any baby who cried or showed signs of life but survived only a few hours or days? YES . . . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 DON’T KNOW . . . . . . . . . . . . . . . . . . . 8 ), )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 (In addition to the children that you have just told me about), have you ever fathered with any woman a) any sons or daughters who are alive? b) any sons or daughters who died? +))), +))), PROBE AND NO /)))- OTHER .)))2))< CORRECT TO BOTH * 201-207 AS ? NECESSARY. 209 SUM ANSWERS TO 203, 205, AND 207, AND ENTER TOTAL IF NONE, RECORD ‘00'. +)))0))), TOTAL CHILDREN . . . . . . . . . *!!!*!!!* .)))2)))- 210 CHECK 209: HAS HAD +))), HAS HAD +)))0)))))))))))))))))))))))))))))))))))))))))))))))))))))))))))) MORE THAN /)))- ONLY ONE .)))- ONE CHILD * CHILD HAS NOT HAD +))), ? ANY CHILDREN .)))2)))))))))))))))))))))))))))))) ))<213 ))<301 211 Do the children that you have fathered all have the same biological mother? YES . . . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 ))<213 212 In all how many women have you fathered children with? +)))0))), NUMBER OF WOMEN . . . . . . *!!!*!!!* .)))2)))- 213 How old were you when your (first) child was born? +)))0))), AGE IN YEARS . . . . . . . . . . . . *!!!*!!!* .)))2)))- 214 At the time when this child was born, were you married to the child’s mother? YES . . . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 ME6 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 IF APPLICABLE. 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 FEMALE STERILIZATION Women can have an operation to avoid having any more children. YES . . . . . . . . . . 1 NO . . . . . . . . . . 2 ), ? 02 MALE STERILIZATION Men can have an operation to avoid having any more children. YES . . . . . . . . . . 1 NO . . . . . . . . . . 2 ), ? Have you ever had an operation to avoid having any more children? YES . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . 2 03 PILL Women can take a pill every day to avoid becoming pregnant. YES . . . . . . . . . . 1 NO . . . . . . . . . . 2 ), ? 04 IUD/COIL Women can have a loop or coil placed inside them by a doctor or a nurse. YES . . . . . . . . . . 1 NO . . . . . . . . . . 2 ), ? 05 INJECTABLES Women can have an injection by a health provider which stops them from becoming pregnant for one or more months. YES . . . . . . . . . . 1 NO . . . . . . . . . . 2 ), ? 06 IMPLANTS Women can have several small rods placed in their upper arm by a doctor or nurse which can prevent pregnancy for one or more years. YES . . . . . . . . . . 1 NO . . . . . . . . . . 2 ), ? 07 CONDOM Men can put a rubber sheath on their penis before sexual intercourse. YES . . . . . . . . . . 1 NO . . . . . . . . . . 2 ), ? YES . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . 2 08 FEMALE CONDOM Women can place a sheath in their vagina before sexual intercourse. YES . . . . . . . . . . 1 NO . . . . . . . . . . 2 ), ? 09 DIAPHRAGM Women can place a thin flexibile disk in their vagina before intercourse. YES . . . . . . . . . . 1 NO . . . . . . . . . . 2 ), ? 10 FOAM OR JELLY Women can place a suppository, jelly, or cream in their vagina before intercourse. YES . . . . . . . . . . 1 NO . . . . . . . . . . 2 ), ? 11 LACTATIONAL AMENORRHEA METHOD (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 ), ? 12 RHYTHM OR PERIODIC ABSTINENCE Every month 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 pregnant. YES . . . . . . . . . . 1 NO . . . . . . . . . . 2 ), ? YES . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . 2 DON’T KNOW . . . . . . . . . . . . . . 8 13 WITHDRAWAL Men can be careful and pull out before climax. YES . . . . . . . . . . 1 NO . . . . . . . . . . 2 ), ? YES . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . 2 14 EMERGENCY CONTRACEPTION (NORLEVO) Women can take pills up to three days after sexual intercourse to avoid becoming pregnant. YES . . . . . . . . . . 1 NO . . . . . . . . . . 2 ), ? 15 Have you heard of any other ways or methods that women or men can use to avoid pregnancy? YES . . . . . . . . . . . . 1 (SPECIFY) (SPECIFY) NO . . . . . . . . . . . . 2 ME7 NO. QUESTIONS AND FILTERS CODING CATEGORIES SKIP 303 CHECK 301(01), 301(03), AND 301(04) : CODE ‘1' CIRCLED +), CODE ‘1' NOT +), FOR ANY METHOD /)- CIRCLED FOR .)2)))))))))))))))))))))))))))))))))))))))))))))))))))) ? ANY METHOD ))<308 304 READ BEFORE ASKING 305 FOR THE FIRST APPLICABLE METHOD Now I want to talk to you about contraceptive methods that women can use to delay or avoid becoming pregnant. CHECK 301(03): KNOWS PILL YES +)), NO +)), /))- .))2)< ? GO TO 304 IN NEXT COLUMN CHECK 301(04): KNOWS IUD/COIL YES +)), NO +)), /))- .))2)< ? GO TO 304 IN NEXT COLUMN CHECK 301(01): KNOWS FEMALE STERILIZATION YES +)), NO +)), /))- .))2)< ? GO TO 308 PILL IUD/COIL FEMALE STERILIZATION 305 In your opinion, is (METHOD) a good method for a couple to use if they want to plan their family? YES . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . 2), (SKIP TO 307)=)))))))- DEPENDS/UP TO THEM . . . . . . . . . 3), DON’T KNOW . . . . . . . . 8)1 * (GO TO 304 IN =)))))))- NEXT COLUMN) YES . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . 2), (SKIP TO 307) =)))))))- DEPENDS/UP TO THEM . . . . . . . . . . 3), DON’T KNOW . . . . . . . . . 8)1 * (GO TO 304 IN=)))))))- NEXT COLUMN) In your opinion, is female sterilization a good method for a couple to use if they do not want any more children? YES . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . 2), (SKIP TO 307) =)))))))- DEPENDS/UP TO THEM 3), DON’T KNOW . . . . . . . . . 8)1 (SKIP TO 308) =)))))))- 306 Why do you think (METHOD) is a good method for a couple to use if they want to plan their family? RECORD ALL REASONS MENTIONED. SIMPLE TO USE . . . . A), EFFECTIVE . . . . . . . . B)1 AFFORDABLE . . . . . . . C)1 NO/FEW SIDE * EFFECTS . . . . . . . . . D)1 CAN STOP WHEN * CHILDREN DESIRED E)1 NO NEED FOR MEDICAL * PERSONNEL . . . . . . F)1 * OTHER X)1 (SPECIFY) * DON’T KNOW . . . . . . . . Y)1 * (GO TO 304 IN =)))))))- NEXT COLUMN) SIMPLE TO USE . . . . . A), EFFECTIVE . . . . . . . . . B)1 AFFORDABLE . . . . . . . . C)1 NO/FEW SIDE * EFFECTS . . . . . . . . . . D)1 CAN BE REMOVED IF * CHILDREN DESIRED . E)1 ONCE INSERTED, NO * DAILY WORRY . . . . . . F)1 * OTHER X)1 (SPECIFY) * DON’T KNOW . . . . . . . . . Y)1 * (GO TO 304 IN =)))))))- NEXT COLUMN) Why do you think female sterilization is a good method for a couple to use if they do not want any more children? EFFECTIVE . . . . . . . . . A), AFFORDABLE . . . . . . . . B)1 NO/FEW SIDE * EFFECTS . . . . . . . . . . C)1 NO RISK OF GETTING * PREGNANT AGAIN. . . D)1 * OTHER X)1 (SPECIFY) * DON’T KNOW . . . . . . . . . Y)1 (SKIP TO 308) =)))))))- 307 Why do you think (METHOD) is not a good method for a couple to use if they want to plan their family? RECORD ALL REASONS MENTIONED. TOO EXPENSIVE . . . . . A), AGAINST RELIGION . B)1 MAY HARM WOMEN’S * HEALTH . . . . . . . . . . . C)1 HAS SIDE EFFECTS . D)1 INCREASES * PROMISCUITY . . . . . E)1 CAN CAUSE * STERILITY . . . . . . . . F)1 METHOD CAN FAIL . . . G)1 BABY IN DANGER IF * PREGNANCY * OCCURS . . . . . . . . . . H)1 INVOLVES DOCTOR/ * MED. PERSONNEL. . . I)* * OTHER X)1 (SPECIFY) * DON’T KNOW . . . . . . . . Y)1 (GO TO 304 IN =)))))))- NEXT COLUMN) TOO EXPENSIVE . . . . . . A), AGAINST RELIGION . . B)1 MAY HARM WOMEN’S * HEALTH . . . . . . . . . . . . C)1 HAS SIDE EFFECTS . . . D)1 INCREASES * PROMISCUITY . . . . . . E)1 CAN CAUSE * STERILITY . . . . . . . . . F)1 METHOD CAN FAIL . . . . G)1 BABY IN DANGER IF * PREGNANCY * OCCURS . . . . . . . . . . . H)1 INVOLVES DOCTOR/ * MED. PERSONNEL. . . . I)1 * OTHER X)1 (SPECIFY) * DON’T KNOW . . . . . . . . . Y)1 (GO TO 304 IN =)))))))- NEXT COLUMN) Why do you think female sterilization is not a good method for a couple to use if they do not want any more children? TOO EXPENSIVE . . . . . . . A AGAINST RELIGION . . . . B MAY HARM WOMEN’S HEALTH . . . . . . . . . . . . . C HAS SIDE EFFECTS . . . . D INCREASES PROMISCUITY . . . . . . . E CANNOT HAVE CHILDREN AGAIN . . . . . F METHOD CAN FAIL . . . . . G INVOLVES DOCTOR/ MED. PERSONNEL. . . . H CAN LEAD TO MED. COMPLICATIONS . . . . . . I OTHER X (SPECIFY) DON’T KNOW . . . . . . . . . . Y ME8 NO. QUESTIONS AND FILTERS CODING CATEGORIES SKIP 308 Now I would like to ask you about a woman’s risk of pregnancy. 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)<310 309 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 . . . . . . . . . . . . . . . . . . . 8 310 Do you think that a woman who is breastfeeding her baby can become pregnant? YES . . . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 DON’T KNOW/DEPENDS . . . . . . . . . . 8 311 CHECK 301(07) AND 302(07): KNOWLEDGE AND USE OF CONDOMS HAS HEARD OF +))), HAS HEARD OF +)))0)))))))))))))))))))))))))))))))