Zambia - Demographic and Health Survey - 1993

Publication date: 1993

Zambia Demographic and Health Survey 1992 University of Zambia • ! ,~ Central Statistical Office ~DHS Demographic and Health Su~'eys Macro International Inc, Zambia Demographic and Health Survey 1992 KwesiGaisie Anne R. Cross Geoffrey Nsemukila University of Zambia Lusaka, Zambia Central Statistical Office Lusaka, Zambia Macro International Inc. Columbia, Maryland USA March 1993 This report summarises the findings of the 1992 Zambia Demographic and Health Survey (ZDHS) conducted by the University of Zambia, in collaboration with the Central Statistical Office and the Ministry of Health. Macro International Inc. provided technical assistance. Funding was provided by the U.S. Agency for International Develop- ment (USAID), the United Nations Population Fund (UNFPA), the Norwegian Agency for Development (NORAD) and the Government of Zambia. The ZDHS is part of the worldwide Demographic and Health Surveys (DHS) programme, which is designed to collect data on fertility, family planning and maternal and child health. Additional information about the Zambia survey may be obtained from the DeparUnent of Social Development Studies, School of Humanities and Social Sciences, University of Zambia, P.O. Box 32379, Lusaka, Zambia (Telephones 260632, 260637, 260640, 252514, 260644, 260645, 260626, 260627; Fax 260-1-253952; Telex ZA44370). Additional information about the DHS programme may be obtained by writing to: DHS, Macro International Inc., 8850 Stanford Boulevard, Suite 4000, Columbia, MD 21045, USA (Telephone 410-290-2800; Fax 410-290-2999). CONTENTS Page TABLES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . vii F IGURES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xi PREFACE . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xiii SUMMARY OF F INDINGS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xv MAP OF ZAMBIA . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xviii CHAPTER 1 INTRODUC~ON 1.1 History, Geography and Economy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 1.2 Population . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 1.3 Population and Family Planning Policies and Programmes . . . . . . . . . . . . . . . . . . . . . . 4 1.4 Health Priorities and Programmes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 1.5 Objectives and Organisation of the Survey . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 CHAPTER 2 CHARACTERIST ICS OF HOUSEHOLDS AND RESPONDENTS 2.1 Characteristics of the Household Population . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11 2.2 Housing Characteristics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19 2.3 Background Characteristics of Survey Respondents . . . . . . . . . . . . . . . . . . . . . . . . . . . 21 CHAPTER 3 FERTILITY 3.1 Fertility Levels and Trends . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27 3.2 Children Ever Born . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31 3.3 Birth Intervals . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33 3.4 Age at First Birth . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33 3.5 Teenage Fertility . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35 CHAPTER 4 FERTILITY REGULAT ION 4.1 Knowledge of Contraception . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37 4.2 Ever Use of Contraception . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 40 4.3 Current Use of Contraception . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41 4.4 Number of Children at First Use of Contraception . . . . . . . . . . . . . . . . . . . . . . . . . . . . 44 4.5 Knowledge of Fertile Period . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 44 4.6 Sources of Family Planning Methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45 4.7 Intention to Use Family Planning Among Nonusers . . . . . . . . . . . . . . . . . . . . . . . . . . . 48 4.8 Exposure to Family Planning Messages on Radio and Television . . . . . . . . . . . . . . . . 52 4.9 Approval of Family Planning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 54 iii CHAPTER 5 Page OTHER PROXIMATE DETERMINANTS OF FERTILITY 5.1 Marital Status . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 57 5.2 Polygyny . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 58 5.3 Age at First Marriage . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 60 5.4 Age at First Sexual Intercourse . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 62 5.5 Recent Sexual Activity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 63 5.6 Postpartum Amenorrhoea, Abstinence, and Insusceptibility . . . . . . . . . . . . . . . . . . . . . 65 5.7 Termination of Exposure to Pregnancy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 67 CHAPTER 6 FERTILITY PREFERENCES 6.1 Desire for More Children . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 69 6.2 Demand for Family Planning Services . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 72 6.3 Ideal Family Size . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 75 6.4 Fertility Planning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 76 CHAPTER 7 INFANT AND CHILD MORTALITY 7.1 Assessment of Data Quality . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 79 7.2 Levels and Trends in Infant and Child Mortality . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 81 7.3 Socioeconomic Differentials in Infant and Child Mortality . . . . . . . . . . . . . . . . . . . . . 82 7.4 Demographic Differentials in Infant and Child Mortality . . . . . . . . . . . . . . . . . . . . . . . 83 7.5 High-Risk Fertility Behaviour . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 86 CHAPTER 8 MATERNAL AND CHILD HEALTH 8.1 Antenatal Care and Delivery Assistance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 89 8.2 Vaccinations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 96 8.3 Acute Respiratory Infection . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 100 8.4 Fever . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 102 8.5 Diarrhoea . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 104 CHAPTER 9 INFANT FEEDING AND CHILDHOOD AND MATERNAL NUTRITION 9,1 Bmasffeeding and Supplementation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 109 9.2 Nutritional Status of Children . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 114 9.3 Nutritional Status of Mothers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 118 iv CHAPTER 10 10.1 10.2 10.3 Page KNOWLEDGE OF AIDS Knowledge About AIDS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 121 Sources of Information about AIDS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 124 Attitudes about AIDS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 125 REFERENCES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 127 APPENDIX A A.1 A.2 A.3 APPENDIX B APPENDIX C APPENDIX D APPENDIX E SURVEY DESIGN . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 129 Sample Design and Implementation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 131 Fieldwork . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 132 Data Processing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 134 EST IMATES OF SAMPL ING ERRORS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 135 DATA QUAL ITY TABLES . 153 PERSONS INVOLVED IN THE ZAMBIA DEMOGRAPHIC AND HEALTH SURVEY . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 161 SURVEY INSTRUMENTS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 165 V CHAPTER 1 Table 1.1 Table 1.2 CHAPTER 2 Table 2.1 Table 2.2 Table 2.3 Table 2.4.1 Table 2.4.2 Table 2.5 Table 2.6 Table 2.7 Table 2.8 Table 2.9 Table 2.10 Table 2.11 CHAPTER3 Table 3.1 Table 3.2 Table 3.3 Table 3.4 Table 3.5 Table 3.6 Table 3.7 Table 3.8 Table 3.9 Table 3.10 Table 3.11 CHAPTER 4 Table 4.1 Table 4.2 Table 4.3 Table 4.4 Table 4.5 Table 4.6 Table 4.7 Table 4.8 Table 4.9 Table 4.10 Table 4.11 TABLES Page INTRODUCTION Demographic indicators, Zambia 1969, 1989 and 1990 . . . . . . . . . . . . . . . . . . . . 4 Results of the household and individual interviews . . . . . . . . . . . . . . . . . . . . . . 9 CHARACTERISTICS OF HOUSEHOLDS AND RESPONDENTS Household population by age, residence and sex . . . . . . . . . . . . . . . . . . . . . . . 11 Population by age from other sources . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13 Household composition . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14 Educational level of the male household population . . . . . . . . . . . . . . . . . . . . . 16 Educational level of the female household population . . . . . . . . . . . . . . . . . . . . 17 School enrolment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18 Housing characteristics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19 Household durable goods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21 Percent distribution of women of reproductive age, Zambia, 1980 and 1992 . . . . 21 Background characteristics of respondents . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22 Level of education . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24 Access to mass media . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25 FERTILITY Age-specific fertility rates over time . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27 Current fertility . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28 Fertility by background characteristics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30 Age-specific fertility rates . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30 Fertility by marital duration . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31 Children ever born and living . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31 Birth intervals . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32 Age at first birth . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33 Median age at first birth . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34 Teenage pregnancy and motherhood . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35 Children bom to teenagers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36 FERTILITY REGULATION Knowledge of contraceptive methods and source for methods . . . . . . . . . . . . . . 37 Knowledge of modem contraceptive methods and source for methods . . . . . . . . 39 Ever use of contraception . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 40 Current use of contraception . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41 Current use of contraception by background characteristics . . . . . . . . . . . . . . . . 42 Number of children at first use of contraception . . . . . . . . . . . . . . . . . . . . . . . 44 Knowledge of fertile period . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45 Source of supply for modem contraceptive methods . . . . . . . . . . . . . . . . . . . . . 46 Time to source of supply for modem contraceptive methods . . . . . . . . . . . . . . . 48 Future use of contraception . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49 Reasons for not using contraception . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 50 vii Table 4.12 Table 4.13 Table 4.14 Table 4. I5 Table 4.16 CHAPTER 5 Table 5.1 Table 5.2 Table 5.3 Table 5.4 Table 5.5 Table 5.6 Table 5.7 Table 5.8 Table 5.9 Table 5.10 Table 5.11 CHAPTER 6 Table 6.1 Table 6.2 Table 6.3 Table 6.4 Table 6.5 Table 6.6 Table 6.7 Table 6.8 CHAPTER7 Table 7.1 Table 7.2 Table 7.3 Table 7.4 Table 7.5 CHAPTER 8 Table 8.1 Table 8.2 Table 8.3 Table 8.4 Table 8.5 Page Preferred method of contraception for future use . . . . . . . . . . . . . . . . . . . . . . . 51 Family planning messages on radio and television . . . . . . . . . . . . . . . . . . . . . . 52 Acceptability of the use of mass media for disseminating family planning messages . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 53 Discussion of family planning by couples . . . . . . . . . . . . . . . . . . . . . . . . . . . . 54 Attitudes of couples toward family planning . . . . . . . . . . . . . . . . . . . . . . . . . . 55 OTHER PROXIMATE DETERMINANTS OF FERTILITY Current marital status . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 57 Polygyny . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 58 Number of co-wives . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 59 Age at first marriage . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 60 Median age at first marriage . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 61 Age at first sexual intercourse . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 62 Median age at first intercourse . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 63 Recent sexual activity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 64 Postpartum amenorrhoea, abstinence and insusceptibility . . . . . . . . . . . . . . . . . 65 Median duration of postpartum insusceptibility by background characteristics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 66 Termination of exposure to the risk of pregnancy . . . . . . . . . . . . . . . . . . . . . . 67 FERTILITY PREFERENCES Fertility preferences by number of living children . . . . . . . . . . . . . . . . . . . . . . 70 Fertility preferences by age . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 71 Desire to limit (stop) childbearing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 72 Need for family planning services . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 73 Ideal number of children . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 75 Mean ideal number of children by background characteristics . . . . . . . . . . . . . . 76 Fertility planning status . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 77 Wanted fertility rates . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 78 INFANT AND CHILD MORTALITY Indices for underreporting of infant deaths . . . . . . . . . . . . . . . . . . . . . . . . . . . 80 Infant and child mortality . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 81 Infant and child mortality by background characteristics . . . . . . . . . . . . . . . . . . 82 Infant and child mortality by demographic characteristics . . . . . . . . . . . . . . . . . 84 High-risk fertility behaviour . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 86 MATERNAL AND CHILD HEALTH Antenatal care . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 89 Number of antenatal care visits and stage of pregnancy . . . . . . . . . . . . . . . . . . 91 Tetanus toxoid vaccination . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 92 Place of delivery . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 93 Assistance during delivery . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 94 viii Table 8.6 Table 8.7 Table 8.8 Table 8.9 Table 8.10 Table 8.11 Table 8.12 Table 8.13 Table 8.14 Table 8.15 CHAPTER 9 Table 9.1 Table 9.2 Table 9.3 Table 9.4 Table 9.5 Table 9.6 Table 9.7 Table 9.8 CHAPTER 10 Table 10.1 Table 10.2 Table 10.3 Table 10.4 Table 10.5 APPENDIX A Table A.1 Table A.2 APPENDIX B Table B.1 Table B.2 Table B.3 Table B.4 Table B.5 Table B.6 Table B.7 Table B.8 Table B.9 Table B.10 Page Characteristics of delivery . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 95 Vaccinations by source of information . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 97 Vaccinations by background characteristics . . . . . . . . . . . . . . . . . . . . . . . . . . . 98 Vaccinations in the first year of life . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 100 Prevalence and tmalment of acute respiratory infection . . . . . . . . . . . . . . . . . . 101 Prevalence and trealment of fever . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 103 Prevalence of diarrhoea . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 104 Knowledge and use of ORS packets . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 105 Treatment of diarrhoea . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 106 Feeding practices during diarrhoea . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 107 INFANT FEEDING AND CHILDHOOD AND MATERNAL NUTRITION Initial breastfeeding . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 110 Breasffeeding status . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 111 Breastfeeding and supplememation by age . . . . . . . . . . . . . . . . . . . . . . . . . . 112 Median duration and frequency of breastfeeding . . . . . . . . . . . . . . . . . . . . . . 113 Nutritional status by demographic characteristics . . . . . . . . . . . . . . . . . . . . . . 115 Nutritional status by socioeconomic characteristics . . . . . . . . . . . . . . . . . . . . . 117 Anthmpometric indicators of maternal nutritional status . . . . . . . . . . . . . . . . . 119 Differentials in maternal anthmpometric indicators . . . . . . . . . . . . . . . . . . . . . 120 KNOWLEDGE OF AIDS Knowledge of AIDS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 121 Perceived modes of AIDS transmission . . . . . . . . . . . . . . . . . . . . . . . . . . . . 123 Perceptions about AIDS prevention . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 124 Sources of AIDS information . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 124 Attitudes toward AIDS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 125 SURVEY DESIGN Sample design parameters . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 131 Sample implementation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 133 ESTIMATES OF SAMPLING ERRORS List of selected variables for sampling errors, Zambia 1992 . . . . . . . . . . . . . . 139 Sampling errors, entire sample, Zambia 1992 . . . . . . . . . . . . . . . . . . . . . . . . 140 Sampling errors, urban areas, Zambia 1992 . . . . . . . . . . . . . . . . . . . . . . . . . . 141 Sampling errors, mral areas, Zambia 1992 . . . . . . . . . . . . . . . . . . . . . . . . . . 142 Sampling errors, Central Province, Zambia 1992 . . . . . . . . . . . . . . . . . . . . . . 143 Sampling errors, Copperbelt Province, Zambia 1992 . . . . . . . . . . . . . . . . . . . 144 Sampling errors, Eastem Province, Zambia 1992 . . . . . . . . . . . . . . . . . . . . . . 145 Sampling errors, Luapula Province, Zambia 1992 . . . . . . . . . . . . . . . . . . . . . 146 Sampling errors, Lusaka Zambia 1992 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 147 Sampling errors, No,them Province, Zambia 1992 . . . . . . . . . . . . . . . . . . . . . 148 ix Page Table B. 11 Table B.12 Table B.13 Sampling errors, North-Westem Province, Zambia 1992 . . . . . . . . . . . . . . . . . 149 Sampling errors, Southern Province, Zambia 1992 . . . . . . . . . . . . . . . . . . . . . 150 Sampling errors, Western Province, Zambia 1992 . . . . . . . . . . . . . . . . . . . . . 151 APPENDIX C DATA QUALITY TABLES Table C. 1 Table C.2 Table C.3 Table C.4 Table C.5 Table C.6 Household age distribution . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 156 Age distribution of eligible and interviewed women . . . . . . . . . . . . . . . . . . . . 157 Completeness of reporting . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 157 Births by calendar year since birth . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 158 Reporting of age at death in days . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 159 Reporting of age at death in months . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 160 CHAPTER 2 Figure 2.1 Figure 2.2 Figure 2.3 CHAPTER 3 Figure 3.1 Figure 3.2 Figure 3.3 Figure 3.4 CHAPTER 4 Figure 4.1 Figure 4.2 Figure 4.3 CHAPTER 6 Figure 6.1 Figure 6.2 Figure 6.3 CHAPTER 7 Figure 7.1 Figure 7.2 CHAPTER 8 Figure 8.1 Figure 8.2 Figure 8.3 CHAPTER 9 Figure 9.1 CHAPTER 10 Figure 10.1 FIGURES Page CHARACTERISTICS OF HOUSEHOLDS AND RESPONDENTS Number of persons reported at each age by sex, Zambia 1992 . . . . . . . . . . . . . . . . . . 12 Distribution of the (de facto) household population by age, Zambia 1992 . . . . . . . . . 12 Percentage of the household population with no education . . . . . . . . . . . . . . . . . . . . . 18 FERTILITY Age-specific fertUity rates, Zambia, 1980 and 1992 . . . . . . . . . . . . . . . . . . . . . . . . . . 28 Age-specific fertility rates by residence . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29 Total fertility rates by province . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29 Percentage of teenagers who have begun childbearing, by age . . . . . . . . . . . . . . . . . . 36 FERTILITY REGULATION Percentage of currently married women who know specific contraceptive methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38 Percentage of currently married women using a contraceptive method . . . . . . . . . . . . 43 Distribution of current users of contraception by source of supply . . . . . . . . . . . . . . . 47 FERTILITY PREFERENCES Fertility preferences among currently married women 15-49 . . . . . . . . . . . . . . . . . . . 69 Fertility Preferences among currently married women by number of living children . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 71 Number of women with uumet need for family planning services, by province . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 74 INFANT AND CHILD MORTALITY Infant mortality rates by background characteristics . . . . . . . . . . . . . . . . . . . . . . . . . . 83 Infant mortality rates by demographic characteristics . . . . . . . . . . . . . . . . . . . . . . . . . 85 MATERNAL AND CHILD HEALTH Antenatal care, tetanus vaccinations, place of delivery, and delivery assistance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 90 Vaccination coverage among children age 12-23 months . . . . . . . . . . . . . . . . . . . . . . 97 Percentage of children 12-23 months who am fully vaccinated . . . . . . . . . . . . . . . . . . 99 INFANT FEEDING AND CHILDHOOD AND MATERNAL NUTRITION Percentage of children under five who are chronically undernourished (stunted) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 118 KNOWLEDGE OF AIDS Knowledge of AIDS among women age 15-49 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 122 xi PREFACE The Zambia Demographic and Health Survey (ZDHS) was a nationwide sample survey of women of reproductive age designed to provide, among other things, information un fertility, family planning, child survival and health of children. The survey was conducted by the University of Zambia (Department of Social Development Studies) in collaboration with the Central Statistical Office (CSO) and Ministry uf Health (MOH) as part of the worldwide Demographic and Health Surveys programme which is being administered by Macro International Inc. of Columbia, Maryland. The major objectives of the ZDHS were to provide the country with data useful for informed policy choices and for enhancing the design and implementation ofprogrammes aimed at promoting family planning and improving the health status of the populafmn. As noted above, the survey collected data on major health phenomena, family planning, fertility and infant and child mortality. Besides providing a primary source uf population and health data, it developed the technical skills and resources necessary to the conduct future demographic and health surveys. The successful implementation of all aspects of the project including the production of this volume was due to untiring effo~s and contributions of many individuals and organizations. We owe a special debt of gratitude to the Central Statistical Office (CSO) for providing strong logistical support and financial assistance, which facilitated the successfulimplementation ufthe project. Our grateful thanks are due to David Diangamo, Director of the Central Statistical Office, fur his unparalleled cooperation, encouragement and advice. We wish to thank Emmanuel Silanda, Modesto Banda, Kumbutso Dzekedzeke (Sampler), George Namasiku, Isaac Muzeya and all the CSO staffwho participated in the survey in many specific ways. We are deeply grateful to the Ministry of Health which provided the bulk of the field staff. We thank Dr. John A. Mbomena, Assistant Director of Medical Services, for spearheading the contributions of the Ministry. We wish to record our sincere gratitude to many individuals at the University of Zambia, especially in the Demography Division of the Department of Social Development Studies and the Bursar's office. Our heartfelt thanks are due to Kwesi Gaisie (Project Director), Geoffrey Nsemukila (Deputy Director), Muses Nzima (Head, Demography Division), Record Malungo (Research Assistant), Joyce Simbeya, Lister Madubansi and Felicitas Moyo (Secretaries). We wish to acknowledge the unstinting support andassistance of the Dean of the School of Humanities and Social Sciences, Dr. John Chileshe. We owe an immense debt to the Field Coordinators, Interviewers, Supervisors, Field Editors, Provincial Statist'teal Officers and Drivers for their meticulous assistance and hard work; theirs was the most delicate and risky job. We have therefore printed a list of their names in Appendix D as a perpetual token of our deepest gratitude for their help and kindness. We are also grateful to all the respondents for their patience and generosity with their time. Very special acknowledgment is due to U.S, Agency for Intemational Development (USAID), the United Nations Population Fund (UNFPA), the Norwegian Agency for Development (NORAD), the Government of the Republic of Zambia and the United Nations Department of Economic and Social Development (DESD) for providing funding and technical assistance fur the survey. We thank Moses Mukasa, UNFPA Country Director and Charles Ejiogu, Chief, Population Branch, Population Division (DESD) for their unfailing encouragement, advice and assistance. xiii Finally, we are most grateful to Macro International Inc. for providing technical assistance. We wish to record our deepest gratitude to Anne Cross, Thanh Le, Kaye Mitchell, Guillermo Roj as, Robert Wolf, and George Bicego. Special thanks are due to the reviewers of the ZDHS report. These include Albert Marckwardt, Jeremiah Sullivan, Ties Boerma, Elisabeth Sommerfelt, George Bicego, Shea Rutstein, and Sidney Moore. Prof. A.A. Siwela Acting Vice-Chancellor University of Zambia xiv SUMMARY OF FINDINGS The 1992 Zambia Demographic and Health Survey (ZDHS) was a nationally representative sample survey of women age 15-49. The survey was designed to provide information onlevels and trends of fertility, infant and child mortality, family planning knowledge and use, and maternal and child health. The ZDHS was carried out by the University of Zambia in collaboration with Central Statistical Office and the Ministry of Health. Fieldwork was conducted from mid-January to mid-May 1992, during which time, over 6000 households and 7000 women were interviewed. Results imply that fertility in Zambia has been declining over the past decade or so; at current levels, Zambian women will give birth to an average of 6.5 children during their reproductive years. Fertility rates are highest in Luapula and Northem Provinces and lowest in Lusaka Province, Childbearing begins early in Zambia; over one-quarter of teenagers (age 15-19) have borne a child. By the time they reach age 19, two- thirds of Zambian women am either mothers or pregnant with their first child. Contraceptive knowledge is nearly universal in Zambia; over 90 percent of married women reported knowing about at least one modern contraceptive method. Fifteen percent of married women am using contraception; 9 percent am using modern methods and 6 percent are using traditional methods. The most popular contraceptive methods are the pill (4 percent), withdrawal (3 percent), female sterilisation (2 percent) and condoms (2 percent). Contraceptive use is twice as high among urban women as among rural women; it is also highest in the more urbanised provinces of Lusaka and Copperbelt. Contraceptive use increases steadily with increasing level of education, from 8 percent of married women with no education to 59 percent of those with more than secondary education. Over half of women using modern methods obtained them from government sources. Women in Zambia am marrying somewhat later than they did previously. The median age at marriage has increased from 17 years or under among women now in their 30s and 40s to 18 years or older among women in their 20s. Women with secondary education marry three years later (19.9) than women with no education (16.7). Over one-fifth (22 percent) of currently married women do not want to have any more children. An additional41 percentofwomenwantto wait atleasttwoyearsbeforehaving anotherchild. When asked how many children they would like to have if they could live their lives over and choose exactly, women reported an average ideal family of 5.8 children. Results from the survey suggest that if all unwanted births were eliminated, the total fertility rate at the national level would be 5.4 children per woman, one child lower than the actual level of 6.5. One of the most striking findings from the ZDHS is the high level of child mortality and its apparent increase in recent years. Currently, nearly 1 in 5 Zambian children dies before reaching age five. From 1977- 81 to 1987-91, under-five mortality rose by 15 percent, from 152 to 191 deaths per 1000 births. The infant mortality rate is currently 107 deaths per 1000 births. Infalat and child mortality are higher in Lnapula and Northern Provinces and lowest in Southern Province. ZDHS data indicate that spacing births can potentially reduce childhood mortality levels; children born less than two years after a preceding birth were almost three times more likely to die during their first year of life than children born at least four years after a preceding birth. Information on various aspects of maternal and child healtlr--antenatal care, vaccinations, bmastfeeding and food supplementation, and illness---was collected in the ZDHS on births in the five years preceding the survey. The findings show that 90 percent ofbirtha were to mothers who had received antenatal XV care during pregnancy. Thirty-nine percent of births were to mothers who received two or more injections of tetanus toxoid during pregnancy. ZDHS data indic ate that haft of the births in Zambia are delivered at home and half in health facilities. For this reason, only half are assisted by medically trained personnel; one-third of births in Zambia are assisted by relatives and 7 percent are delivered without assistance. Based on information obtained from health cards and mothers' reports, 95 percent of children age 12- 23 months are vaccinated against tuberculosis, 94 percent have received at least one dose of DPT and polio vaccines, and 77 percent have been vaccinated against measles. Sixty-seven percent of children age 12-23 months have been fully immunised and only 4 percent have not received any immuhisations. During the two weeks preceding the survey, 13 percent of children under age five had symptoms of acute lower respiratory infection (cough with difficult breathing). Almost two-thirds of these children were taken to a health facility for treatment. Over the same two-week period, 44 percent of children under five suffered from a fever, of whom 61 percent were taken to a health facility. Twenty-three percent of children had diarrhoea during the two weeks before the survey. Over half of these children were given a solution prepared from ORS packets (oral rehydration salts), and 23 percent received a homemade solution of sugar, salt and water. Knowledge and use of ORS packets is widespread in Zambia; 95 percent of women who gave birth in the five years before the survey had heard of ORS and 78 percent had used it. Almost all children in Zambia (98 percent) are breastfed. The median duration of breasffeeding is relatively long (19 months), but supplemental liquids and foods are introduced at an early age. By age 2-3 months, half of all children are being given supplementary food or liquid. ZDHS data indicate that undemutrition is an obstacle to improving child health; 40 percent of children under age five are stunted or short for their age, compared to an international reference population. Five percent of children are wasted or thin for their height and 25 percent are underweight for their age. The ZDHS included several questions about knowledge of AIDS. Almost all respondents (99 percent) had heard of AIDS and the vast majority (90 percent) knew that AIDS is transmitted through sexual intercourse. xvi ZAMBIA I I ANGOLA [ : NORTH WESTERN NAMIBIA • MULTIPLE URBAN CSAs • URBAN C.5A II RURAL CSA ZAIRE .- 4 II LAKE MWERU LAKE • CENTRAL TANZANIA II NORTHERN I l l i LAKE BANGWEULU I A II • / "• SOUTHERN ~ • " . y • • LAKE" KARIBA • • ZIMBABWE i • I1• f" , • ~.J MALAWI EASTERN ~'~ MOZAMBIQUE xviii CHAPTER 1 INTRODUCTION 1.1 History, Geography and Economy History Historical and archaeological evidence indicates that by 1500 much of modern Zambia was occupied by fanning people who were ancestors of the present inhabitants. In the late nineteenth century various parts of what was to become Northern Rhodesia were administered by the British South Africa Company. In 1924 the British Colonial Office assumed responsibility for administering the territory and in 1953 Northern Rhodesia (Zambia) and Southern Rhodesia (Zimbabwe) joined Nyasaland (Malawi) to form the Central African Federation of Rhodesia and Nyasaland, despite the opposition of Northern Rhodesia's Africans. The Federation was, however, dissolved in 1963. In October 1964, Zambia became an independent nation and adopted a multiparty system with the United National Independence Party (UNIP) as the ruling party and the African National Congress (ANC), led by Harry Nkumbula, in the opposition. By 1973, Zambia had become a one-party participatory democracy under President Kenneth Kaunda's UNIP. The present government headed by President Frederick Chihiba came to power hi November 1991 after winning both presidential and parliamentary elections in the reinstituted multi-party democracy. There are 73 officially recognised ethno-linguistic groups in Zambia. The major groups are Bemba, Kaonde, Lozi, Lunda, Luvale, Mambwe, Ngoni, Nyanja, Tonga, and Tumbuka. However, the ethnic and provincial alignments seldom involve the smaller ethnic groups among the seventy-three official groups. Most ethnic groups are concentrated in different parts of the country. The Bemba live primarily in Northern and Luapula Provinces, the Tonga inhabit Southern Province, the Lozi Western Province, the Nyanja and Nsenga Eastem and Central Provinces and the Luvale, Lunda and Kaonde are found in North-Western Province. Most people in Zambia are Christians; however, indigenous traditional religion is the second most widespread belief system. Geography Zambia is a land-locked country covering an area of 752,614 square kilometres and consisting of about 2.5 percent of the area of Africa. It shares borders with Zaire and Tanzania in the north; Malawi and Mozambique in the east; Zimbabwe and Botswana in the south; Namibia in the southwest and Angola in the west. Administratively, the country is divided into nine provinces and fifty-seven districts. Zambia lies in the southern tropics between 8 and 18 degrees south latitude and between 20 and 35 degrees east longitude, a huge butterfly sprawling over the Central African Plateau, with an average altitude of 1,127 metres above sea level. The mountainous areas are found chiefly along the border with Tanzania (Mbala Highlands in the northeast) and Malawi (Mafmga Mountains, particularly the Muchinga Escarpment) where the land rises to 2,000 metres above sea level. The broad depressions at the edges of the plateau form Lakes Tanganyika, Mwem and Bangweulu in the north, the Luangwa River in the east, and the Kafue basin and the alluvial plains of the Zambezi River in the west. The Zambezi River forms Zambia's southern border with Zimbabwe. Among the other major rivers in the country are the Kafue, Luangwa and Luapula. Zambia has a tropical climate and vegetation. There are three distinct seasons: the warm-wet season stretching from November through April, a cool dry winter season from May to August with the mean temperature varying between 14 and 30 degrees centigrade and a hot dry season during September and October with mean daytime temperatures rising to between 29 and 32 degrees centigrade in the north and northwest and to 35 degrees centigrade over most of westem Zambia. The Copperbelt, North-Western, Northem and Luapula Provinces receive the highest precipitation, with the annual average ranging from 1,100 mm to over 1,400 mm. There is a systematic decrease in rainfall towards the south and east, with an annual average ranging between 600 mm and 1,100 mm. The typical vegetation cover is woodland savanna with a mixture of various types of trees, tall grass, herbs and other woodlands which are mainly of the deciduous type usually found on the main plateau. These are also found in other areas, especially the successful maize- farming areas of Southern and Lusaka Provinces. Forests are found in North-Western and Northem Provinces. Grasslands occur mainly in the seasonal flood plains of Western Province and in the Kafue and Bangweulu swamps. Economy Zambia has a mixed economy consisting of a modem and urban-oriented sector confined to the line of rail (the area roughiy within forty kilometres of either side of the north-south railroad running from the Copperbelt in the north to Livingstone on the Zambezi River) and a rural agricultural sector. The modem sector is dominated by parastatal organisations, while the private sector has been predominant in construction and agriculture. Most of these parastatals are now being privatised by the Movement for Multiparty Democracy (MMD) Government. Copper mining is the country's main economic activity, accounting for 95 percent of export eamings and contributing 45 percent of govemment revenue during the decade following the attainment of political independence (i.e., 1965-1975). This situation was sharply changed by the drastic decline in world copper prices in late 1974 and 1975. Some improvement in prices began in 1978, but in 1981 and 1982 prices dropped sharply again. The fall in copper prices, rising oil prices and the slow pace of industrialisation with a heavy dependence on imports have driven the economy to a very difficult situation. In 1989 the gross domestic product grew by a meagre 0.1 percent in contrast to 6.3 percent in 1988. Real output declined by an average of about 1.0 percent annually between 1989 and 1991, with the decline in 1991 amounting to 1.8 percent. Real per capita gross domestic product, on the other hand, declined by an average of 1.6 percent per annum between 1984 and 1990. In spite of attractive copper prices in 1989, acute shortage of foreign exchange remained a major constraint in the development of the economy. This was largely attributed to reduced volume of copper sales associated with difficulties in production and transportation. The development of non-traditional exports remained below expectations. Essential commodities and services cominued to remain in short supply and inflation reached an unprecedented level of well over 100 percent. As a result of an apparent decline in the national economy, the provision of social services such as health and education were drastically affected. For instance, the share of the Government budget for the education sector in 1989 was only 8 percent and in the health sector there was growing evidence of increased malnutrition and higher infant mortality. In an effort to halt the economic recession, the Movement for Multiparty Democracy (MMD) Govemment has launched an Economic Recovery Programme (ERP) to turn around the "protracted decline of the economy into sustained positive real growth, coupled with lower inflation and consequent improvement in living standards and the quality of life of the people" (Republic of Zambia, 1992). In the 1992 budget, the Government adopted certain policy measures which were intended to achieve, among other things, the following objectives: i) To halt the decline in real gross domestic product in the economy and achieve a moderate rate of growth in 1992; ii) To limit the growth in the money supply to around 25 percent and consequently bring inflation down to around 60 percent; iii) To reduce the budget deficit to 1.9 percent of GDP so as to minimise the use of inflationary finance and facilitate the reduction in inflation; iv) To restore medical and educational services to decent levels by increasing recurrent and capital funding to these sectors; and v) To rehabilitate the mad network in both rural and urban areas (Republic of Zambia 1992). 1.2 Population The 1969, 1980 and 1990 national censuses reported total populations of 4.0 million, 5.7 million and 7.8 million respectively, implying growth rates of 3.1 and 3.2 percent per annum between 1969-80 and 1980- 90 respectively (see Table 1.1). The growth rates, however, range from 2.2 and 2.3 percent in Luapula, Western and Copperbelt Provinces to 4.0 percent in Eastern Province and 5.6 percent in Lusaka Province during the 1980-90 intercensal period. The enumerated population in 1990 is lower by 0.25 million than the projected population based on the 1980 census data (Central Statistical Office, 1985b), by 0.20 million from the World Bank projections and by 0.63 million from the latest medium variant projections of the United Nations for the same year (World Bank, 1992; United Nations, 1991). Thus, there seems to be an undercount in the 1990 population census by between 2 and 7 percent. The growth rates would therefore be underestimates. The population density increased from 5.3 people per square kilometre in 1969 to 7.5 in 1980 and 10.4 in 1990. The average density in 1990 ranged from 55 people per square kilometre in Lusaka Province and 50 in Copperbelt Province (both heavily urbanised) to 5 and 3 people per square kilometre in Western and North-Western Provinces, respectively. There has been almost continuous migration of people to mining towns and urban centres and as a result, the proportion of the population living in urban areas has increased steadily from 29 percent in 1969 to 42 percent in 1990. The proportion urban varies among the provinces from 91 percent in Copperbclt Province to 9 percent in Eastern Province. While the population in urban areas has grown by 3.7 percent per annum during the decade 1980-90, the population of rural areas has increased by 2.8 percent. During the previous period 1969-80, the urban population grew at an even higher 5.8 percent per annum, compared with 1.6 in the rural areas. Thus, the speed of migration to the urban areas slowed down considerably during the 1980-90 period compared to the earlier period. Table 1.1 Demographic indicators, Zambia 1969 T 1989 and 1990 National censuses Indicator 1969 1980 1990 Population (millions) 4.0 5.7 7.8 Density (pop./sq.km.) 5.3 7.5 10.4 Percent urban 29.4 39.9 42.0 Crude birth rate (per 1000) 47.7 50.0 49.5 a Crude death rate (per 1000) 19.7 16.7 13.2 a Growth rate (per 1000) 28.0 33.3 36.0 a Total fertility rate 7.1 7.2 7.0 a Completed family size (women age 40-49) 5.1 b 6.7 b NA Infant mortality rate 141 97 89.6 a Life expectancy at birth Male 41.8 50.4 52.9 a Female 45.0 52.5 55.0 a NA = Not applicable aEstimates based on projections of 1980 census data bRepor ted figures Sources: Central Statistical Office, 1974; Central Statistical Office, 1985a and 1985b; Central Statistical Office, 1990a. The estimated fertility levels have remained virtually constant during the 1969-80 period. The crude birth rate has ranged between 48 and 50 bin/as per 1000 population per year and the crude death rate is estimated to have declined from 16.7 during the quinquennium 1975-1980 to 13.2 during 1985-1990 (Central Statistical Office, 1985b). The previously estimated total fertility rates lie in the neighbourhood of 7.0 children per woman. The reported total fertility rate of 4.0 in 1969 and 5.7 in 1980 are indicative of underreporting of live births in the two censuses. The life expectancy at birth climbed from 43 years in 1969 to 51 years in 1980; it was projected to have risen to 54 years by 1990. Zambian women live, on average, 2 to 3 years longer than men. Mortality levels are highest in Eastern, Luapula and Western Provinces, followed by Northern and Southern Provinces, with Lusaka, Copperbelt and Central Provinces experiencing the lowest mortality rates; life expectancy at birth ranged from 44.9 years in Eastern Province to 56.5 years in Copperbelt (Central Statistical Office, 1985b). The overall child mortality declined from 175 deaths per 1000 births in the mid- 1970s to 160 in the late 1970s and early 1980s. 1.3 Population and Family Planning Policies and Programmes For the first decade and a half after independence, Zambia did not view her high rate of population growth as a developmental problem. The only concern then was with the high rate of migration from rural to urban areas and uneven spatial distribution of the population. The results of the 1980 Population and Housing Census exposed the rapidity with which the population was expanding and the implied adverse effect on development and individual welfare. This led to government reappraisal of the perceptions of the role of population in national development efforts. The government realised that the nation's development planning 4 and plan implementation processes should not only aim at accommodating the increased demands for goods and services brought about by population growth, but should also aim at influencing those aspects of the country's sociocultural life that underpin high levels of reproduction and thus of population growth. In 1984, the National Commission for Development Planning (NCDP)---now the Ministry of Planning and Development Cooperation--was given a mandate to initiate a draft population policy which would aim at achieving a population growth rate consistent with the growth rate of the economy. The National Population Policy was formally launched by the President in May 1989. The ultimate objective of the policy is to improve the standard of living and quality of life of all Zambians. The immediate objectives of the policy are to: i) Initiate, improve and sustain measures aimed at slowing down the nation's high population growth rate; ii) Enhance the people's health and welfare and prevent premature death and illness especially among the high health risk groups of mothers and children; iii) Systematically integrate population factors into the nation's development planning and the plan implementation processes; iv) Ensure that all couples and individuals have the basic right to decide freely and responsibly the number and spacing of their children and to have the information, education and means to do so; v) Achieve a more even distribution of the population between urban and rural areas and to regulate international migration; vi) Expand and maintain the nation's population database. The main targets of the national population policy are to: i) Reduce the rate of population growth from 3.7 percent per annam in 1989 to 3.4 percent per annum by the year 2000 and to 2.5 percent per annum by the year 2015; ii) Reduce the total fertility rate from 7.2 to 6 by the year 2000 and 4 by the year 2015; i i i) Reduce the infant mortality rate from 97 per 1000 live births to 65 per 1000 live births by the year 2000 and to 50 by the year 2015; iv) Make family planning services available, accessible and affordable by at least 30 percent of all adults in need of such services by the year 2000 (National Commission for Development Planning, n.d.). The strategies for implementing the policy are predicated on the voluntary acceptance of family planning methods in accordance with fundamental haman rights. The main strategies include: i) Formulating and implementing fertility regulation and family planning programmes within the context of the nation's health care and related systems; ii) Providing necessary information and education on the value of a small family size norm to both the individual family and the nation as a whole in achieving self-reliance; iii) Intensifying the primary health care programme especially matemai and child health care, so as to reduce the levels of infant, child and matemal morbidity and mortality; iv) Improving the status of women through the removal of various social, legal, administrative and cultural barriers to their effective participation in national affairs in order to enhance their participation in national development efforts and as a way of ensuring demographic transition from high to low population growth rates (National Commission for Development Planning, n.d.). Non-governmental agencies such as the United Nations Population Fund (UNFPA), Intemationai Planned Parenthood Federation (IPPF) through its Zambian affiliate--the Planned Parenthood Association of Zambia (PPAZ)--and the Family Life Movement of Zambia (FLMZ) provide material, financial and technical assistance and operate family planning clinics, supplementing the efforts of the Ministry of Health (MOH). 1.4 Health Priorities and Programmes The Government's commitment to the objectives of attaining health for all means not only improving the accessibility of health services and reducing mortality and morbidity, but also improving the quality of life of all Zambians. The strategy for achieving this objective is the Primary Health Care (PHC) programme, which constitutes an important component of the health care delivery system. To ensure that the PHC programme operates efficiently in tackling the main health problems of the individual, the family, and the community, the health service has been decentralised, with the responsibility of planning, implementing, monitoring, and managing PHC programmes falling to the districts. The integrated health plans developed out of the District Heaith Boards' Basic Health Programme constitute the PHC package. The reformulated PHC programme aims, among other things, to tackle the main health problems in the community, focusing on the needs of the underserved, high risk, and vulnerable groups. Thus, attention is paid to the rural and peri-urban areas where the health needs of the people are greatest, with particular emphasis placed on maternal and child care, family planning, nutrition, control of communicable diseases (e.g., diarrhoea, cholera, dysentery, sexually transmitted diseases, HIV/AIDS, malaria, etc.), immunisation, and environmental sanitation in order to secure adequate health care for all Zambians. The 1992 National Health Policies and Strategies (Health Reforms) establishes the Government's commilment to improve the health of the population by progress towards the achievement of the following targets by the year 2000: To make family planning (child spacing) available, accessible, and affordable by at least 30 percent of all adults in need. To reduce the percentage of underweight children (0-5 years) from 23 to 18 percent. To bring under control 80 percent of tuberculosis cases. To reduce matemal mortality (through promotion of safe motherhood) by 50 percent. To increase from 75 to 85 percent the proportion of infants vaccinated with DPT, polio, measles and BCG and to increase the tetanus immunisation coverage of pregnant women as follows: TT5 from 10 to 50 percent and TT3 from 33 to 70 percent in 5 years' time. To increase the percentage of the population having adequate sanitation from 66 to 75 percent in urban areas and from 37 to 57 percent in rural areas in 5 years' time (Ministry of Health, 1992). The implementation of all these aspects of the PHC programmes requires multi-sectoral action and close collaboration among the various govemment institutions. The Govemment has therefore set up multi- sectoral PHC committees as an integral part of the PHC basic supportive manpower and inter-sectoral collaboration with other ministries has been given prominence. 1.5 Objectives and Organisation of the Survey Objectives The Zambia Demographic and Health Survey (ZDHS) is a nationwide sample survey of women of reproductive age designed to provide, among other things, information on fertility, family planning, child survival and health of children. The primary objectives of the ZDHS are: i) To collect up-to-date information on fertility, infant and child mortality and family planning; ii) To collect information on health-related matters such as breastfeedIng, antenatal care, children's immunisations and childhood diseases; iii) To assess the nutritional status of mothers and children; iv) To support dissemination and utilisation of the results in planning, managing and improving family planning and health services in the country; and v) To enhance the survey capabilities of the institutions Involved in order to facilitate the implementation of surveys of this type in the future. Organisation The Zambia Demographic and Health Survey (ZDHS) was conducted by the University of Zambia (Department of Social Development Studies), with the assistance of the Central Statistical Office (CSO) and the Ministry of Health (MOH). Macro Intemational Inc. of Columbia, Maryland provided technical assistance to the project through its contract with the United States Agency for International Development (USAID). Funding for the survey was supplied by Macro International (from USAID), the United Nations Population Fund (UNFPA), the Norwegian Agency for Development (NORAD), and the Government of Zambia (through the University of Zambia and the Central Statistical Office (CSO)). 7 Funds from USAID were administered by Macro International and were used for training of interviewers, supervisors and editors, field allowances for interviewers and supervisors, purchase of anthropometric and other survey equipment, data processing, printing of questionnaires and publication of reports. NORAD funds were used for training interviewers, supervisors, editors and purchase of a personal computer and a printer. UNFPA provided funds for fuel and field allowances for the Survey Director and his deputy. In addition to providing vehicles for the survey, the Central Statistical Office (CSO) paid the field allowances for editors, field coordinators and drivers, as well as providing fuel for the household listing exercise. The Ministry of Health contributed most of the field staff. Sample In preparation for the 1990 Census of Population, Housing and Agriculture, the entire country was demarcated into Census Supervisory Areas (CSAs). Each CSA was in turn divided into Standard Enumera- tion Areas (SEAs) of roughly equal size. The frame of 4240 CSAs was stratified into urban and rural areas within each province. The ZDHS sample was selected from this frame in three stages. First, 262 CSAs were selected from this frame with probability proportional to size. One SEA was then selected from within each CSA, again with probability proportion to size. After a household listing operation in all selected SEAs, a systematic sample of households was then selected. As a result of oversampling of households in Luapula, North-Western and Western Provinces in order to pmduce province-level estimates for some variables, the ZDHS sample is not self-weighting at the national level. A more detailed description of the sample design is presented in Appendix A. Questionnaires Two types of questionnaires were used for the ZDHS: the Household Questionnaire and the Individual Questionnaire. The contents of these questionnaires were based on the DHS Model B Questionnaire, which is designed for use in countries with low levels of contraceptive use. Additions and modifications to the model questionnaires were made after consultation with members of the Department of Social Development Studies of the University of Zambia, the Central Statistical Office (CSO), the Ministry of Health, the Planned Parenthood Association of Zambia (PPAZ), and the National Commission for Development Planning (see Appendix E). The questionnaires were developed in English and then translated into and printed in seven of the most widely spoken languages (Bemba, Kaonde, Lozi, Lunda, Luvale, Nyanja and Tonga). The Household Questionnaire was used to list all the usual members and visitors of a selected household. Some basic information was collected on the characteristics of each person listed, including his/her age, sex, education, and relationship to the head of the household. The main purpose of the Household Questionnaire was to identify women who were eligible for the individual interview. In addition, information was collected on the household itself, such as the source of water, type of toilet facilities, material used for the floor of the house, and ownership of various consumer goods. The Individual Questionnaire was used to collect information from women age 15-49 about the following topics: Background characteristics (education, religion, etc.); Reproductive history; Knowledge and use of family planning methods; Antenatal and delivery care; Breastfeeding and weaning practices; Vaccinations and health of children under age five; 8 Marriage; Fertility preferences; Husband's background and respondent's work; and Awareness of AIDS. In addition, interviewing teams measured the height and weight of all children under age five and their mothers. Fieldwork The fieldwork for the ZDHS was carried out by 10 interviewing teams. Each consisted of one supervisor, one field editor, four interviewers and one driver;, however, due to heavier workloads in two provinces, one team had five interviewers and another six. In total, there were 10 supervisors, 10 field editors, 43 interviewers, and 10 drivers. Of the interviewers, 34 were women and 9 were men. In addition, each team was assigned a fieldwork coordinator, generally one of the trainers, who spent approximately half of the fieldwork time in the field with his/her team. Fieldwork commenced on 18th January and was completed on 15th May 1992. The people involved in the survey are listed in Appendix D. A more complete description of the fieldwork is presented in Appendix A. Table 1.2 is a summary of response rates from the household and the individual interviews. A total of 6,709 households were selected; of these 6,209 were successfully interviewed. The shortfall is due primarily to dwellings being vacant at the time they were visited by the interviewing team. Of the 6,458 households that were occupied, 96 percent were successfully interviewed. In these households, 7,247 women were identified as eligible for the individual interview and 7,060 were successfuUy interviewed. Table 1.2 Results of the household and individual interviews Number of households, number of interviews, and response rates. Zambia 1992 Result Urbma Rural Total Households sampled 2577 4132 6709 Households found 2522 3936 6458 Households interviewed 2480 3729 6209 Household response rate 98.3 94.7 96.1 Eligible women 3446 3801 7247 Eligible women inte~iewed 3358 3702 7060 Eligible women response rate 97.4 97.4 97.4 CHAPTER 2 CHARACTERISTICS OF HOUSEHOLDS AND RESPONDENTS Information on the characteristics of the households and the individual women interviewed in the survey is essential for the interpretation of survey findings and can provide an approximate indication of the representativeness of the survey. This chapter presents this information in three sections: characteristics of the household population, housing characteristics, and background characteristics of survey respondents. 2.1 Characteristics of the Household Population The Zambia Demographic and Health Survey collected information on all usual residents and visitors who spent the previous night in the household. The household was defined as a person or group of people l iving together and sharing a common source of food. Age and Sex The distribution of the household population in the ZDHS is shown in Table 2.1 by f ive-year age groups, according to sex and urban-rural residence. The age distribution is typical of high fertility populations, i.e., a much higher proportion of the population in the younger than in the older age groups. Examination of the single-year age distributions (see Appendix C. 1 and Figure 2.1 ) indicates slight distortions Table 2.1 Household population by age r residence and sex Percent distribution of the de facto household population by five-year age group, according to urban-rural residence and sex, Zambia 1992 Urban Rural Total Age group Male Female Total Male Female Total Male Female Total 0-4 16.5 17.0 16.8 18.8 17.4 18.1 17.7 17.2 17.5 5-9 15.1 15.8 15.4 16.1 16.2 16.2 15.6 16.0 15.8 10-14 12.9 15.5 14.2 14.0 13.9 13.9 13.4 14.6 14.0 15-19 13.0 13.9 13.5 11.9 10.9 11.3 12.4 12.3 12.4 20-24 10.1 9.6 9.9 7.4 8.2 7.8 8.8 8.9 8.8 25-29 7.6 7.9 7.7 6.4 6.5 6.5 7.0 7.2 7.1 30-34 6.1 6.4 6.2 4.7 4.9 4.8 5.4 5.6 5.5 35-39 5.3 4.4 4.8 4.0 3.6 3.8 4.6 4.0 4.3 40-44 3.8 2.8 3.3 2.6 3.3 3.0 3.2 3.1 3.1 45-49 3.2 1.7 2.5 2.4 3.0 2.7 2.8 2.4 2.6 50-54 2.3 2.3 2.3 2.4 3.6 3.1 2.4 3.0 2.7 55-59 1.6 1.2 1.4 2.3 2.8 2.6 2.0 2.0 2.0 60-64 1.0 0.7 0.8 2.5 2.1 2.3 1.7 1.4 1.6 65-69 0.6 0.4 0.5 1.5 1.4 1.5 1.1 0.9 1.0 70-74 0.4 0.3 0.4 1.4 1.2 1.3 0.9 0.8 0.8 75-79 0.2 0.1 0.1 0.9 0.5 0.7 0.5 0.3 0.4 80 + 0.2 0A 0.1 0.6 0.4 0.5 0.4 0.2 0.3 Missing, don't know 0.2 0.0 0.1 0.1 0.0 0.0 0.1 0.0 0.1 Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 Number 8247 8275 16527 8414 8985 17406 16662 17261 33933 11 Figure 2.1 Number of Persons Reported at Each Age by Sex, Zambia 1992 No. of Persons 800 r 633 400 200 0 5 10 15 20 25 30 35 40 45 50 55 60 65 70 Age ZDHS 1992 Age 80+ 75 70 65 60 55 50 45 4O Figure 2.2 Distribution of the (de facto) Household Population by Age, Zambia 1992 35 33 25 20 15 10 5 3 10 9 8 7 6 5 4 3 2 1 0 1 Percent 2 3 4 5 6 7 8 9 1 0 ZDHS 1392 12, of the data due to misreporting of date of birth and/or age and preference for particular digits, though this preference is much less pronounced than in census data and data in many other countries. The distribution by five-year age groups is depicted in Figure 2.2. There appears to be a slight deficit of males at age 10-14 (especially in urban areas), which causes the excess of females over males to be high at this age group. The irregular bulge of women at age 50-54 is indicative of slight pushing of women from age group 45-49 to 50-54, presumably to reduce the workload of the interviewer. This pattern has been observed to a much greater degree in other DHS surveys (Rutstein and Bicego, 1990). However, the impact of these phenomena on the quality of the data is minimal because the shifting is not as pronounced as noted in other surveys. Table 2.2 compares the population structures derived from the 1969 and 1980 Population and Housing Censuses and the 1992 ZDHS. Dependency ratios are also shown. The age dependency ratio is the ratio of the number of persons aged 0-14 and 65 and over divided by the number of persons aged 15-64. It is an indication of the dependency responsibility of adults in their productive years. Table 2.2 Population by age from other sources Percent distribution of the population by broad age groups, 1969, 1980 and 1992, Zambia Census ZDHS 1992 Age group 1969 1980 De jure De facto Less than 15 46.4 49.8 46.7 47.3 15-64 51.3 47.4 50.6 50.1 65+ 2.3 2.8 2.6 2.6 Missing 0.0 0.0 0.1 0.1 Total 100.0 100.0 100.0 100.0 Median age 15.3 16.3 16.0 Dependency ratio 0.95 1.11 0.98 1.00 Sources: Central Statiatieal Office, 1974; Central Statistical Office, 1985a and 1985b. The dependency burden in Zambia is similar to that found in other African countries. With close to 50 percent of the population under age 15 and about 3 percent over age 64, there is one dependent person for each adult in the population. As in many rapidly growing populations, old age dependency is minimal, compared to child dependency. Household Composition The vast majority of households in Zambia are headed by males (84 percent), with only 16 percent headed by women (see Table 2.3). The ZDHS data show a higher proportion of male-headed households than the 1980 census (72 percent; Central Statistical Office, 1991). Both sources show that female-headed households arcmorecommoninthe ruralthanintheurbanarcas (19vs. 13 percentintheZDHS). A sizeable number of households in Western (33 percent), North-Western (22 percent) and Eastern (20 percent) Provinces are headed by women. 13 Table 2.3 Household composition Percent distribution of households by sex of head of household, household size, relationship st~uctttm, mad presence of foster children, according to urban-rural residence and province, Zambia 1992 Cbaract~fistic Residence Province Copper- North- South- Urban Rural Central belt Eastern Luapula Lusaka Northern Western era Western Total Household headship Male 86.9 81,3 86.0 88.3 80.0 80.6 87.2 82.1 78.2 87.8 67.4 83.8 Female 13.1 18.7 14.0 11.7 20.0 19.4 12.8 17.9 21.8 12.2 32.6 16.2 Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 Number of usual members 1 5,2 7.6 9.6 4.1 5.8 6.2 6.3 6.6 10.6 6.3 9.3 6.5 2 8.0 11.4 I lA 5.9 11.7 14.9 9.0 8.2 17.5 8.9 13.4 9.9 3 9.9 14.2 10.4 8.8 13.1 12.6 12.9 17.4 18.5 10.1 14.7 12.3 4 11.8 14.8 15.3 10.2 14.8 16.5 11.5 16.5 18.0 11.3 16.5 13.5 5 13.1 13.4 11.8 12.7 14.7 15.1 12.7 14.1 13.1 11.8 15.2 13.2 6 11.2 10.1 9.8 10.8 11.7 10.5 11.5 12.5 7.9 8.9 8.5 10.6 7 10.2 8.5 9.5 10.9 9.1 8.7 10.2 8.1 6.1 8.1 8.2 9.2 8 9.5 6.4 8.0 10.5 7.0 6.9 8.3 6.9 4.2 7.0 5.4 7.8 9+ 21.1 13.7 14.4 26.1 12.1 8.5 17.4 9.7 4.1 27.6 8.8 17.0 Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 I00.0 100.0 100.0 100.0 Meanslze 6.0 5.3 5.3 6.5 5.2 4.8 5.7 4.9 4.0 6.7 4.7 5.6 Relationship structure One adult 7.9 12.2 13.4 6.5 8.6 12.3 8.7 12.4 18.9 8.7 16.3 10.3 Two related adults: Of opposite sex 29.8 41.6 34.9 27.5 40.3 45.6 35.2 43.8 54.2 32.0 36.9 36.3 Of same sex 3.4 3.6 4.0 2.6 2.2 5.8 2.6 3.5 5.2 3.6 6.6 3.5 Three or more related adults 54.1 38.3 43.8 60.2 44.8 31.6 49.4 37.1 19.6 47.7 32.7 45.4 Other 4.7 4.3 3.6 3.3 4.0 4.3 4.1 3.3 2.0 7.9 7.5 4.4 Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 With foster children I 26.0 23.3 22.7 27.8 23.6 22.5 24.5 18.7 22.2 27.9 24.5 24.5 Note: Table is based on de jure members, i.e., usual residents. Zoster children are those under age 15 living in households with neither their mother nor their father present. 14 Single person households are also more common in the rural areas as well as in North-Western, Western, and Central Provinces than in the urban and the other provinces. On the other hand, large households with nine or more persons are common in the urban areas (21 percent) and in Southern (28 percent), Copperbelt (26 percent), and Lusaka (17 percent) Provinces. As a result, average household size is larger in the urban than rural areas (6.0 vs. 5.3 people), and in Southern (6.7), Copperbelt (6.5), and Lusaka (5.7) Provinces than in the other provinces (between 4 and 5). Overall, households in Zambia consist of an average of 5.6 people. Almost hail of the households in Zambia consist of those with three or more related adults, while most of the rest consist of those with two adults of opposite sex. Ten percent of households consist of only one adult, either with or without children. The patterns of the household structures have been influenced by the high rates of rural-urban migration and urbanisation experienced by the country over the past two decades. One-quarter of the households include one or more children under age 15 years who have neither their natural mother nor natural father living with them. The proportion of households with foster children is higher in the urban areas (26 percent), Copperbelt (28 percent), Southem (28 percent) Lusaka (25 percent) and Westem (25 percent) Provinces than in the rural areas and in the other provinces (19 to 23 percent). Education On the eve of independence, Zambia had barely 1,000 Africans with secondary school certificates and only 109 university graduates. Development plans were therefore designed to provide educated and skilled manpower for the civil service and industry. The government adopted a policy of achieving universal first level education; one of the major objectives of the Fourth National Development Plan (1989-1993) was to reach this goal of universal primary education by the year 2000. Zambia's formal education is based on a three-tier system. Under this system, primary education consists of 7 years and secondary education of 5 years (2 years junior secondary and 3 years senior secondary). Graduates of secondary school may then choose to further their education either by attending university for a four-year course leading to a degree or by attending a vocational or technical institute for a two- or three-year certificate/diploma course. The goal is for the nation to meet its manpower requirements in various areas of social, economic and political growth, as well as achieving national development and modemisation. The information presented in Tables 2.4.1 and 2.4.2 indicates that one-fifth of the population age 6 and over has received no formal education (15 percent of males and 24 percent of females). About 60 percent of both males and females have attended only primary school and 22 percent of males and 13 percent of females have attended secondary school. Only 2 percent of males and 1 percent of females have obtained higher education. There is evidence that the sharp differential in educational attainment by sex is narrowing (see Figure 2.3). For example, among people in their early fifties, the propo~on of women with no education is thrice the proportion of men with no education (60 vs. 19 percent); among those age 15-19, the difference is considerably smaller (10 vs. 7 percen0. The proportion with no education is much higher in rural than in urban areas for both males and females. Rural residents are more than thrice as likely to have never attended school (30 percent) as urban dwellers (9 percent). Of the provinces, Eastern Province has the highest proportion of both men and women with no education, while Copperbelt Province has the lowest. 15 Table 2.4.1 Educatinnal level of the male household population Percent distribution of the de facto male household population age six and over by highest level of education attended, according to selected background characteristics, Zambia 1992 Level of education Don't Number Median Background More than know/ of number characteristic None Primary Secondary secondary missing Total men of years Age ~ 6-9 39.4 59.0 0.1 0.0 1.5 100.0 2079 0.8 10-14 10.7 87.5 1.6 0.1 0.1 100.0 2237 3.9 15-19 6.7 65.9 27.3 0.1 0.1 100.0 2074 6.9 20-24 7.3 45.9 45.2 1.2 0.3 100.0 1460 7.7 25-29 5.4 45.8 43.5 5,2 0.2 100.0 1163 7.9 30-34 4.6 45.7 42,9 6.5 0.3 100.0 899 7.9 35-39 5.4 39.1 47.5 7.8 0.2 100.0 768 8.4 40-44 9.2 45.1 37.6 7.7 0.4 100.0 531 7.7 45-49 10.0 58.0 24.7 5.4 1.8 100.0 462 6.5 50-54 18.9 61.8 15.3 2.8 1.I 100.0 396 4.6 55-59 24.3 65.3 6.6 3.1 0.7 100.0 328 3.5 60-64 32.5 59.7 4.1 1.0 2.7 100,0 290 2.4 65+ 46.0 48.1 2.8 1.3 1.8 100.0 489 1.2 Residence Urban 6.7 54.6 34.2 3.6 0.8 I00.0 6638 7.2 Rural 24.0 64.3 10.3 0.9 0.6 100.0 6561 3.7 Province Central 15.1 66.2 17.0 1.4 0.3 100.0 1310 4.9 Copperbelt 7.3 55.4 34.4 1.7 1.2 100.0 3317 7.1 Eastern 32.0 56,2 10,6 0.6 0,7 100.0 1422 2.8 Luapula 15.5 63.7 16,6 3.3 0.9 100.0 725 4.3 Lusaka 9.3 53.4 31.1 5.7 0.5 100.0 2276 7.2 Northern 19.7 65.3 13.3 0.9 0.9 100.0 1166 4.4 North-Western 24.6 60.6 11.4 3.0 0.4 100.0 331 3.6 Southern 16,9 63.9 17.5 1.6 0.1 100.0 1942 5.0 Western 23.2 65.2 9.9 1.1 0.6 100.0 710 3.4 Total 15.3 59.4 22.3 2.2 0.7 100.0 13199 5.5 1Excludes 21 men with age missing. 16 Table 2.4.2 Educational level of the female household population Percent distribution of the de facto female household population age six and over by highest level of education attended, according to selected background characteristics. Zambia 1992 Level of education Don't Number Median Background More than know/ of number characteristic None Primary Secondary secondary missing Total women of years Age t 6-9 36.3 62.5 0.0 0.0 1.2 100.0 2180 0.8 10-14 10.6 86.4 2.8 0.0 0.2 100.0 2526 4.1 15-19 10.1 65.7 24.0 0.1 0.1 100.0 2123 6.9 20-24 11.5 58.4 29.1 0.8 0.2 100.0 1531 7.2 25-29 12.5 59.6 25.0 2.9 0.0 100.0 1241 7.1 30-34 17.3 60.9 18.7 3.1 0.0 100.0 964 7.0 35-39 19.5 55.3 20.8 4.3 0.0 100.0 687 6.5 40-44 34.9 51.1 10.5 3.4 0.1 100.0 534 2.8 45-49 45.7 49.4 4.4 0.5 0.0 100.0 410 1.3 50-54 60.2 35.7 1.9 0.6 1.6 100.0 518 0.0 55-59 66.1 31.5 1.1 0.3 1.0 100.0 354 0.0 60-64 77.7 19.9 0.5 0.0 1.9 100.0 247 0.0 65+ 83.9 14.5 0.0 0.0 1.6 100.0 385 0.0 Residence Urban 11.5 64.7 21.7 1.7 0.4 100.0 6598 6.0 Rural 36.4 58.4 4.5 0.3 0.5 100.0 7105 2.1 Provtnee Cuntral 26.0 62.4 10.6 0.9 0.1 100.0 1246 3.2 Copperhelt 11.5 66.9 20.0 0.9 0.7 I00.0 3272 5.9 Eastern 45,6 49,5 4,3 0,5 0,2 100,0 1495 1,0 Luapula 26.5 63.3 8.3 1.0 0.9 100.0 825 2.9 Lusaka 15.7 61.2 20.3 2,7 0.2 100.0 2239 5.8 Northern 35.3 57.0 6,7 0.3 0.7 100.0 1325 2.3 North-Western 36.2 54.8 8.1 0.6 0.3 100.0 370 2.4 Southern 23.2 66.3 9.7 0.5 0.3 100.0 2075 3.9 Western 35.8 57.0 6.1 0.5 0.6 100.0 855 2.3 Total 24.4 61.4 12.7 1.0 0.4 100.0 13703 4.0 IExcludes 3 women with age missing. 17 Figure 2.3 Percentage of the Household Population with No Education, by Sex Percent 100 60 40 20 ' ~ - f 0 i 10-14 15-19 20-24 25-29 30-'~4 35-39 40-44 45-49 50-54 55-59 80-84 65+ Age ZDHS 1992 Table 2.5 presents enrolment rates by age, sex and residence. Seventy percent of children aged 6-15 years are enrolled in school. Enrolment is higher in urban areas (8 of 10 children are enrolled) than in rural areas (nearly 6 of 10 children are enrolled); and boys and girls have a virtually equal chance of being enrolled (71 percent vs. 69 percent). Enrolment after age 15 drops substantially; only 34 percent of the older teenagers are still in school and only 5 percent of those in their early twenties are still in school; the proportions are higher in urban than rural areas in all groups. By age group 11-15 and above, women are much less likely than men to be enrolled in school; this may in part be due to early childbearing. Table 2.5 School enrolment Percentage of the de facto household population age 6-24 years enrolled in school, by age group, sex, and urban- rural residence, Zambia 1992 Age group Male Female Total Urban Rural Total Urbma Rural Total Urban Rural Total 6-10 75.9 48.9 61.7 81.5 51.3 65.6 78.8 50.2 63.8 11-15 89.7 72.3 80.8 82.2 64.5 73.8 85.7 68.4 77.2 6-15 82.4 59.7 70.6 81.9 57.1 69.4 82.1 58.4 70.0 16-20 51.5 39.7 45.9 32.0 12.7 22.9 41.6 26.1 34,3 21-24 9.6 6.4 8.2 2.6 0.3 1.5 6.1 3.0 4.7 18 2.2 Housing Characteristics Socioeconomic conditions were assessed by asking respondents specific questions relating to their household environment. Table 2.6 presents this information for all households in which women were interviewed. Table 2.6 Housing characteristics Percent dis~bufion of households by housing characteristics, according to urban-rural residence and province, Zambia 1992 Residence Province Copper- North- South- Characteristic Urban Rural Cena'al bblt Eastern Luapula Lusakn Northern Western em Western Total Electrldty 39.2 3.1 13.8 45.8 2.7 6.3 31.0 2.1 5.2 17.0 0.9 19.2 Source of drinklng water Piped into rcsldoncc 55.5 3.3 13.1 66.7 1.4 7.9 50.2 4.9 5.0 15.0 2.0 26.6 Public tap 33.6 7.2 22.2 18.5 10.2 2.7 39.2 4.6 10.2 24.0 17.8 19.0 Well in ~sidence 2.8 2.6 6.9 3,3 1,9 4.1 0.6 2.2 1.2 2.9 0.6 2.7 Public well 6.2 38.0 42.2 7.3 42.0 24.7 4.6 9.3 58.6 21.4 64.8 23.8 Spring 0.9 12,3 9.9 0.3 0,0 36.3 0.1 31.3 0.8 1.6 0.2 7.2 River, sUcam 0.5 23.5 4.8 3.3 13.3 18.3 4.5 34.8 24.0 24.2 10.0 13.2 Pond, lake 0.3 12.6 0.7 0.1 30.4 5.7 0.3 12.7 0.0 11.0 4.1 7.1 Other 0.0 0.2 0.0 0.0 0.8 0.2 0.2 0.0 0.0 0.0 0.0 0.2 Missing, don't know 0.2 0.3 0.2 0.5 0.0 0.2 0.2 0.0 0.2 0.I 0.5 0.2 Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 Sanitation fadHty Own flush t~let 43.3 1.4 12.2 57.4 1,1 8.3 30,8 3.6 4.1 7.0 0.5 20,2 Shared flush toilet 4.6 0.3 0.4 4.1 0.5 1.2 1.4 0.3 0.0 7.2 0.2 2.2 Trad. pit toilet 46.6 42.4 55.9 35.8 30.6 59.5 57.8 60.4 77.0 24.0 22.9 44.3 Vent.imp.pit latrine 1.0 1.8 1.6 0.4 7.3 0.2 1.3 0.2 1.7 0.1 0.5 1.5 No fertility, bush 4.3 53.8 29.9 1.8 60.5 30.7 8.5 35.3 17.1 61.5 75.9 31.7 Other 0.0 0.0 0.0 0.1 0.0 0.0 0.0 0.2 0.0 0.0 0.0 0.0 Missing. don't know 0,1 0.2 0.0 0.4 0.0 0,2 0.1 0.0 0.2 0.1 0.0 0.1 Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 Flooring Earth, sand 14.1 83.8 65.7 12.5 84.5 79.1 12.7 85.1 82.2 56.7 90.6 52.6 Wood pianks/~aarquet 1.1 0.2 0.4 0.2 0.2 0.2 2.6 0.2 0.0 0.4 0.0 0.6 PVC/~rrazo tiles 4.6 0.1 0.6 3.8 0.0 0.8 7.4 0.0 0.0 0.3 0.0 2.1 Cement 78,9 15.2 32.5 81.2 15.1 19.4 76.8 14.6 17.6 42.0 8.4 43.7 Other 1.0 0,2 0.9 1.3 0.0 0,4 0.4 0.0 0.0 0.4 0.7 0.6 Missing, don't know 0.3 0.4 0.0 1.1 0.3 0.2 0.2 0.2 0.2 0.1 0.3 0.4 Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 Persons per sleeping room 1-2 54.2 55.2 65.9 52.1 66.4 58.3 52.4 37.3 58.1 49.8 61.0 54.8 3-4 37.7 33.7 29.5 41.0 29.4 30.2 36.8 40.6 32.6 37.1 31.3 35.5 5-6 6.0 7.4 2.6 4.8 3.2 5.7 8.7 13.2 6.6 10.1 6.1 6.8 7 + 1.4 3.0 0.6 1.0 0.6 4.0 1.8 8.9 2.0 2.0 1.5 2.3 Missing, don't know 0.7 0.6 0.5 1.1 0.3 1.7 0.4 0.0 0.6 1.0 0.0 0.7 Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 Mean 2.8 2.8 2.4 2.8 2.5 2.8 2.9 3.5 2.6 3.0 2.6 2.8 Number of households 2777 3432 626 1271 717 437 1010 659 247 793 448 6209 19 Electricity is available to only 19 percent of the households in Zambia. Moreover, most of those with electricity are urban households; 39 percent and 3 percent of the urban and rural households, respectively, have electricity. The proportion of households with electricity ranges from less than 1 percent in Western Province to 31 and 46 percent in Lusaka and Copperbelt Provinces, respectively. Sources of drinking water differ considerably by area of residence. In urban areas, piped water is the primary source; 56 percent of households have water piped into the residence and another 34 percent obtain water from a public tap. In rural areas, public wells (38 percent) and rivers and streams (24 percent) are the main sources of drinking water. A sizeable proportion of rural households depends on ponds or lakes (13 percent) and springs (12 percent) for drinking water. Seven in ten households in the Copperbelt and half in Lusaka Province have water piped into their residence, compared with only 1 and 2 percent in Eastem and Western Provinces, respectively. Public wells are the major sources of drinking water in Central, Eastem, North-Westem and Westem Provinces. Households in Northern, North-Westem and Southern Provinces also depend to a large extent on rivers and streams. One in five Zambian households has a flush toilet, while two in five have traditional pit toilets; almost one-third have no sanitation facilities at all, using the bush. Modem sanitation facilities are absent from virtually all rural households as well as more than one-half of urban households. Traditional pit toilets are common in both urban and rural areas (47 percent and 42 percent, respectively); in urban areas, most of the rest of the households have flush toilets (48 percent), while in rural areas, the majority of the households have no toilet facilities (54 percent). Besides Copperbelt, Lusaka and North-Western Provinces, between one- quarter and three-quarters of households in the other provinces have no toilet facilities. In North-Western Province, eight in ten households use traditional pit toilets. Almost all Zambian households live in residences with either earthen (53 percent) or cement (44 percent) floors. Cement flooring is most common for urban households (79 percent), whilst earthen floors are most common for rural households (84 percent). Cement flooring is most common in the Copperbelt and Lusaka Province and, to some extent, in Southern Province. Earth is the common flooring material in the remainder of the provinces. Information was collected on the number of rooms households use for sleeping (a measure of crowding). The majority of households have one or two persons per sleeping room, while in one third of the households, three or four persons share a room for sleeping. Although there are more people per household in urban areas, the dwelling units there must consist of more bedrooms, since there is almost no difference between urban and rural households in number of people per sleeping room. Households in Northern and Southem Provinces tend to sleep in relatively more crowded conditions than those in other provinces; the average number of persons per room ranges between 3.0 and 3.5, compared with between 2.4 and 2.9 in the other provinces (See Table 2.6). Household Durable Goods Respondents were asked about ownership of particnlar household goods such as radios and televisions (to assess access to media), refrigerators (to assess food storage) and modes of transportation (bicycle, motorcycle, car). The results presented in Table 2.7 indicate that 39 percent of households own a radio (59 percent in urban areas and 23 percent in rural areas) and 8 percent own a television (18 percent in urban areas, 1 percent in rural areas). Seven percent of households own refrigerators (15 percent in urban and 1 percent in rural areas). Thus, televisions and refrigerators are mostly restricted to urban areas, presumably as a result of lack of electricity and/or financial resources in the rural areas. Due to the greater level of urbanisation, households in the Copperbelt and Lusaka Provinces are more likely to own radios, televisions and refrigerators than households in the other provinces. 20 Table 2.7 Household durable goods Percentage of households possessing wrious durable consumer goods, according to urbaa-rmal residence and !m-evince, Zambia 1992 Residence Province Copper- North- Soudi- Characteristic Urban Rural Central belt Eastern Luapala Lusaka Northern Western era Western Total Radio 59.4 23.0 39.0 54.5 25.0 23.0 64.3 19.5 24.5 37.7 18.5 39.3 Television 17.5 0.9 5.6 16.5 1.1 2.7 21.6 0.3 3.2 2.7 0.5 8.3 Refrigerator 15.0 0.7 5.9 15.2 0.8 1.8 16.9 0.7 2.3 2.0 0.2 7.1 Bicycle 15.8 21.7 26.4 16.7 27.3 11.9 13.5 23.9 31.4 19.3 8.3 19.1 Motorcycle 1.3 0.5 1.6 0.9 0.3 0.7 1.1 0.9 1.1 0.6 0.5 0.9 Car 8.1 1.0 4.0 6.6 1.7 1.1 11.9 0.7 0.2 1.0 0.2 4.2 Number of households 2777 3432 626 1271 717 437 1010 659 247 793 448 6209 Overall, one in five households owns a bicycle, while only 4 percent own a car and less than one percent own a motorcycle. Bicycles are the only household possession listed that are more common among rural than urban households. The proportion owning a private car ranges from 12 percent of households in Lusaka Province to less than one percent in the Western and Norda-Westem Provinces. 2.3 Background Characteristics of Survey Respondents General Characteristics Women were asked two questions in the individual interview to assess their age: "In what month and year were you born?" and "How old were you at your last birthday?" Interviewers were trained to probe situations in which respondents did not know their age or date of birth; and as a last resort, interviewers were instructed to record their best estimate of the respondent's age. Examination of the single-year age distribution of women (not shown) indicates no systematic preference for reporting ages ending in particular digits (age heaping) that is often found in sur- veys and censuses. The irregularities found in the ZDHS may be attributable to nonsystematic misreporting of date of birth and/or age. The distortions are, however, virtually eliminated by the con- ventional five-year grouping of the data. Table 2.8 presents the age distribution of women in the ZDHS compared with that of women enumerated in the 1980 census. Although the proportion of women of reproductive age is virtually the same in both cases (44 percent of the female population), the age structure for women 15-49 in the ZDHS is younger than that for women 15-49 in the census. Specifi- cally, the proportion of women age 15-19 is higher in the ZDHS than in the census: 28 percent, compared with 25 percent in 1980. It is not clear whether this difference is real or whether it is the result of some pattern of age misreporting. Table 2.8 Age distribution of women) 1980 and 1992 Percent distribution of women of reproductive age, Zambia, 1980 and 1992 1980 1992 Age Census ZDHS 15-19 24.6 28.1 20-24 20.0 20.4 25-29 16.3 16.7 30-34 13.3 13.0 35-39 10.5 9.3 40-44 8.6 7.2 45~.9 6.7 5.4 Total 100.0 100.0 21 Table 2.9 Background characteristics of respondents Percent distribution of women by selected background characteristics, Zambia 1992 Number of women Background Weighted Un- characteristic percent Weighted weighted Age 15-19 28.1 1984 1964 20-24 20.4 1441 1435 25-29 16.7 1179 1178 30-34 13.0 915 922 35-39 9.3 656 660 40-44 7.2 505 5 l l 45-49 5.4 380 390 Marital status Single 25.4 1791 1765 Married 61.1 4316 4334 Living together 2.0 141 133 Widowed 2.3 162 166 Divorced 7.0 493 508 Separated 2.2 156 154 Education No education 16.4 1161 1212 Primary 59.7 4213 4246 Secondax2¢ 22.1 1561 I486 ttig her 1.8 124 115 Residence Urban 51.5 3636 3358 Rural 48.5 3424 3702 Province Central 8.8 622 565 Copperbeit 24.7 1743 1606 Eastern 10.3 729 658 Luapula 6.1 431 589 Lusaka 17.5 1234 1137 Northern 9.2 652 590 North-Western 2.6 183 387 Southern 14.8 1045 947 Western 6.0 422 581 Religion Catholic 27.9 1973 1914 Protestant 69.0 4871 4912 Other 3.0 210 228 Missing, don't know 0.I 7 6 Ethnic group Bemba 34.4 2430 2421 Tonga 18.5 I308 1193 Northwestern 9.1 645 864 Baroste 6.9 485 567 Nyanja 17.5 1238 1133 Mambwe 5.6 393 362 Tumbuka 5.4 381 349 Other 2.4 167 155 Missing, don't know 0.2 15 16 All women 100.0 7060 7060 22 The data in Table 2.9 indicate that 63 percent of the respondents are currently in a union (either married or living together), ~ 25 percent have never been married, 9 percent are either divorced or separated and 2 percent are widowed. The percentage of women who are currently married appears to be declining. The 1980 census reported a higher percentage currently married (67 percent) among women age 15-49. Marriage pattems are discussed in detail in Chapter 5. A large majority of the ZDHS respondents have had some education. Sixty percent have attended only primary school, 22 percent have attended secondary school and 2 percent have gone beyond the secondary level; 16 percent have never attended school. The rapid increase in urbanisation in the country over the past two decades is reflectexl in ZDHS data on the distribution of the women by residence: nearly equal numbers of women live in urban and rural areas. The data indicate that over 40 percent of the women live in the most urbanised provinces: Copperbelt (25 percent) and Lusaka (18 percent); 19 percent reside in Central and Eastern Provinces, 6 percent in Luapula and 15 percent in Southern Province, whilst North-Western and Western Provinces account for a total of 9 percent of the women interviewed. Nearly all the women interviewed report themselves as Christian (97 percent), either Protestant (69 percent) or Catholic (28 percent). Those who adhere to other belief systems (traditional religion, Islam, and no religion) account for 3 percent (with less than 0.5 percent reporting themselves as Muslim). The Bemba group is the largest ethnic grouping, accounting for a little over one-third of the respondents; 19 and 18 percent of women belong to the Tonga and Nyanja groups, respectively. The No~th- Western group (comprised of Luvale, some Lunda groups, Kaonde, and other smaller tribes in North-Western Province) is the fourth largest with 9 percent of the women; the B aroste language group (which includes Lozi) comprises 7 percent of respondents, with Mambwe and Tumbuka accounting for 6 and 5 percent, respec- tively. Differentials in Education Table 2.10 presents the distribution of the respondents by education according to selected characteristics. Education is inversely related to age; that is, older women are generally less educated than younger women. For instance, 46 percent of the women aged 45-49 years have had no formal schooling, compared to only 11 percent of the women age 15-19 years. Rural women are educationally disadvantaged compared to urban women. More than one-quarter of rural women of childbearing age have never been to school, compared to only 7 percent of urban women. Conversely, four times as many urban women go beyond the primary level as rural women (38 percent vs. 9 percent). Table 2.10 also indicates that women residing in Copperbelt and Lusaka Provinces are more likely to have received secondary education, followed by women in Central and Southern Provinces. And though the differences by province in the percentage of women who have had only primary schooling are minor, the percentage of women with no education is higher in four provinces; Eastem (36 percent), Northern (27 percent), Western (25 percent) and North-Westem (23 percent). Throughout this report, the l~rm "married" includes both those in formal and informal marriages (living together). 23 Table 2.10 Level of education Percent distribution of women by the highest level of education attended, according to selected background characteristics, Zambia 1992 Level of education Number Background of characteristic None Primaly Secondary Higher Total women Age 15-19 10.7 65.2 24.1 0.1 100.0 1984 20-24 11.4 58.9 28.9 0.8 100.0 1441 25-29 11.9 59.8 25.5 2.8 100.0 1179 30-34 17.2 60.6 18.9 3.3 100.0 915 35-39 20.5 55.1 19.8 4.4 100.0 656 4044 35.1 52.0 9.5 3.4 100.0 505 45-49 46.1 49.6 4.0 0.3 100.0 380 Residence Urban 7.0 55.2 34.9 2.9 100.0 3636 Rural 26.5 64.5 8.6 0.5 100.0 3424 Province Central 15.7 63.1 19.5 1.8 100.0 622 Copperbelt 6.7 58.5 33.3 1.5 100.0 1743 Eastern 36.4 54.3 8.4 0.9 100.0 729 Luapula 16.6 66.4 15.1 1.8 100.0 431 Lusaka 11.5 52.5 31.6 4.4 100.0 1234 Northern 27.0 60.2 12.3 0.5 100.0 652 Nor th-Westem 23.2 61.6 14.0 1.2 100.0 183 Southern 13.7 67.4 18.0 0.9 100.0 1045 Western 25.3 62.1 11.9 0.7 100.0 422 Total 16.4 59.7 22.1 1.8 100.0 7060 Access to Media Women were asked if they usually read a newspaper, listen to the radio or watch television at least once a week. This information is important to programme planners seeking to reach women with family planning and health messages through the media. Table 2.11 shows that whilst nearly 57 percent of the women interviewed listen to radio weekly, 42 percent read a newspaper and only 22 percent watch television at least once a week. Media access is higher among younger women (i.e., age 15-39 years), about 43 percent of whom read a newspaper at least once a week, slightly over 20 percent watch television and between 56 and 60 percent listen to the radio once a week. Much higher proportions of educated women, women in urban areas and women residing in Copperbelt and Lusaka Provinces read newspapers, watch television and listen to the radio. 24 Table 2.11 Access to mass media Percentage of women who usually read a newspaper once a week, watch television once a week, or listen to radio once a week, by selected background characteristics, Zambia 1992 Read Watch Listen to Number Background newspaper television radio of characteristic weekly weekly weekly women Age 15-19 43.0 27.4 56.4 1984 20-24 44.3 21.1 60.2 1441 25-29 43.9 22.4 60.9 1179 30-34 45.2 20.7 60.5 915 35-39 42.9 20.7 56.7 656 40~14 32.3 12.9 46.5 505 45-49 21.7 4.8 38.4 380 Education No education 1.9 3.6 27.5 1161 Primary 37.5 16.1 55.0 4213 Secondary 79.0 45.6 80.3 1561 Higher 92.2 72.8 96.5 124 Residence Urbma 59.2 38.5 76.7 3636 Rural 23.3 3.5 35.6 3424 Province Central 44.7 15.8 54.2 622 Copperbelt 59.1 39.6 75.1 1743 Eastern 23.8 5.4 36.2 729 Luapula 32.9 5.9 38.2 431 Lusaka 62.9 41.2 81.7 1234 Northern 26.7 3.0 33.4 652 Nor th-Westom 30.8 8.2 49.9 183 Southern 23.6 9.6 41.7 1045 Westem 17.0 5.9 43.3 422 Total 41.8 21.5 56.8 7060 Compared to DHS surveys in other countries, women in Zambia are r~latively morn likely to read newspapers and less likely to watch television. For example, the proportion of women who read newspapers once a week is 11 perccnt in Jordan, 16 percent in the Dominican Republic, 14 percent in Pakistan, 27 percent in Indonesia and about 70 perccnt in Peru and Paraguay. The proportion of women who watch television at least once a week is lower in Zambia than in all these other countries. This implies that printed media might be a more effective vehicle than television for disseminating messages. 25 CHAPTER 3 FERTILITY The fertility measures presented in this chapter are based on the reported reproductive histories of women age 15-49 who were interviewed in the ZDHS. Each woman was asked the number of sons and daughters living with her, the number living elsewhere, and the number who had died. She was then asked for a history of all her live-born children, including the month and year each was born, the name, the sex, and if dead, the age at death and if alive, the current age and whether he/she was living with the respondent. Based on this information, measures of completed fertility (number ofchildron ever born) and current fertility (age-specific and total fertility rates) are examined. These measures are also analysed in connection with various background characteristics. 3.1 Fertility Levels and Trends Age-specific fertility rates for the three-year perind preceding the survey are shown in Table 3.1, along with data from the 1980 census for comparison. It appears that fertility has declined in Zambia over the past decade (see Figure 3.1); data from the 1990 census should shed more light on trends in fertility. The sum of the age-specific fertility rates (known as the total fertility rate) is a useful means of summarising the level of fertility. It can be interpreted as the number of childron a woman would have by the end of her childbearing years if she were to pass through those years bearing children at the currently observed rates. If fertility were to remain constant at the levels measured in the ZDHS, a Zambian woman would bear 6.5 children in her lifetime. This is lower than the rate of 7.2 estimated from the 1980 census data, implying a decline of about 10 percent over the past decade. Age-specific fertility rates from the ZDHS are shown in Table 3.2 by urban-rural residence and by province. ~ Data for some provinces have been combined to increase sample sizes to acceptable levels; however, despite this precaution, readers are urged to view the data with caution as sampling errors are probably still large. Table 3.1 Al~e-specific fertility rates over time Age-specific fertility rates as reported and adjusted in the 1980 census and as reported in the 1992 ZDH$ 1980 ~ ZDHS As As Age group reported. Ad'~te~ T~ported 15-19 61 153 156 20-24 239 318 294 25-29 253 323 271 30-34 223 289 242 35-39 181 225 194 40-44 108 115 105 45-49 70 17 31 TFR 15-49 5.7 7.2 6.5 Note: The ZDH$ rates refer to the three-year period preceding the survey, Source: Central Statistical Office~ 1985b. ' Numerators of the age-specific fertility rates in Table 3.2 are calculated by summing the number of live births that occurred in the period 1-36 months preceding the survey (determined by the da~ of interview and date of birth of the child), and classifying them by the age (in five-year groups) of the mother at the time of birth (determined by the mother' s date of birth). The denominators of the rates are the number o[ woman-years lived in each of the specified five- year age groups during the 1-36 months preceding the survey. 27 550 300 250 200 150 ' 100 50 0 Figure 3.1 Age-Specific Fertility Rates Zambia, 1980 and 1992 i i i , ; 15-19 20-24 25-29 30-34 35-39 40-44 45-49 Table 3.2 Current fertility Age-specific and cumulative fertility rates and crude birth rates for the three years preceding the survey, by urban-rural residence and province, Zambia 1992 Province Residence North- Age Copper- Eastern, Luapula, Western, group Urban Rural beh Central Lusaka Northern Southern Western Total 15-19 133 184 130 204 134 159 168 158 156 20-24 263 328 291 289 263 363 284 268 294 25-29 265 276 274 268 268 274 284 245 271 30-34 222 264 234 269 168 282 296 223 242 35-39 171 221 168 208 170 243 (213) 188 194 40-44 78 121 (104) 94 (76) 126 (120) (112) 105 45-49 28 32 (43) (29) * (33) * (10) 31 TFR 15-49 5.8 7.1 6.2 6.8 5.5 7.4 7.1 6.0 6.5 TFR 15-44 5.7 7.0 6.0 6.7 5.4 7.2 6.8 6.0 6.3 GFR 199 238 208 232 191 241 230 207 218 CBR 44 46 44 46 43 50 46 43 45 TFR: Total fertility rate expressed per woman GFR: General fertility rate (births divided by number of women 15-44), expressed per 1,000 women CBR: Crude birth rate, expressed per 1,000 population Note: Rates are for the period 1-36 months preceding the survey. Rates for age group 45-49 may be slightly biased due to truncation. Rates shown in parentheses are based on 125-249 woman-years of exposure; an asterisk means the rate was based on fewer than 125 woman-years of exposure and has been suppressed. Some provinces have been grouped together to increase sample sizes. 28 350 300 250 2OO 150 100 50 Figure 3.2 Age.Specific Fertility Rates By Residence Births per 1,000 Women 15-19 20-24 25-29 30-34 35-39 40-44 45-49 Age ZDHS 1992 Figure 3.3 Total Fertility Rates by Province No. o! Chi|dren / 7.4 8.0 6.0 i 4.0 J 2.0 J i / 0.0 Copperbelt 9.8 _/ / Eastern, Lusaka Luapula, Southern North-West., Central Northern Western ZDHS 1992 29 The data show that rural fertility rates are higher than urban rates; a rural woman can expect to have 7.1 children on average, compared to 5.8 for an urban wom- an. Rural fertility also peaks at an earlier age than urban fertility (see Figure 3.2). There is considerable variation in fertility levels by province. Fertility is lowest in Lusaka Province with a total fertility rate of 5.5 children born per woman, fol- lowed by North-Western and Western Provinces, with a combined total fertility rate of 6.0 children per woman. Fertility is highest in Luapula and Northem Provinces, with a combined total fertility rate of 7.4. Thus, women in the latter two provinces give birth to an average of two more children than women in Lusaka Province by the time they finish childbearing (see Figure 3.3). Fertility also varies considerably by education level of women (see Table 3.3). Women with no educa- tion can expect to give birth to 7.1 children on average, compared to 4.9 for women with secondary or higher education. In addition to comparing the ZDHS data with previous data such as the 1980 census, another way of examining trends in fertility over time is to compare the Table 3.3 Fertility by background characteristics Total fertility rate for the three years preceding the survey and mean number of children ever born to women age 40-49, by selected background characteristics, Zambia 1992 Mean number of children Total ever born Background fertility to women characteristic rate t age 40-49 Residence Urban 5.8 7.4 Rural 7.1 7.9 Province Copperbelt 6.2 7.9 Eastern, Central 6.8 7.8 Lusaka 5.5 7.1 Luapula, Northern 7.4 8.1 Southern 7.1 8.0 North-Western, Western 6.0 7.0 Education No education 7.I 7.8 Primary 6.8 7.8 Secondary+ 4.9 6.7 Total 6.5 7.7 tWomen age 15-49 years total fertility rates for the three years preceding the survey with the average number of children ever bom to women at the end of their childbearing period, age 40-49. The former is a measure of current fertility, while the latter is a measure of past or completed fertility. The data in Table 3.3 imply that there has been a decline of about one child over the past 10-20 years in Zambia. Further evidence of a fertility decline ap- pears in Table 3.4, which shows age-specific fer- tility rates for five-yearperiods prior to the survey, using data from respondents' birth histories. Fig- ures in brackets represent partial fertility rates due to truncation; women 50 years of age and older were not included in the survey and the further back into time rates are calculated, the more se- vere is the truncation. For example, rates cannot be calculated for women age 45-49 for the period 5-9 years before the survey, because those women would have been age 50-54 at the time of the sur- vey and were not interviewed. It should also be noted that misreporting of the date of birth of chil- dren can result in the appearance of false trends in fertility. The data, however, show a steady decline in fertility rates at all ages for almost all periods, but this will have to be confirmed by analysis of other sources of fertility information. Table 3.4 Age-specific fertility rates Age-specific fertility rates for five-yearpefiods preceding the survey, by mother's age, Zaml~a 1992 Numberofyearspreceding thesurvey Mother's age 0-4 5-9 10-14 15-19 15-19 152 173 200 243 20÷24 281 295 328 364 25-29 266 309 304 352 30-34 238 281 280 [331] 35-39 189 239 [246] 40-44 109 [156] 45-49 ~2] Note: Age-specific fertility rates are per 1,000 women. Es~rnams enclosed in brackets are truncated. 30 Table 3.5 presents fertility rates for ever-married women by duration since first marriage for five-year periods preceding the survey. It is analogous to Table 3.4, but is con- fined to ever-married women and replaces age with duration since first marriage. The data confirm that the decline in fertility is apparent for all marriage durations. 3.2 Children Ever Born The distribution of women by number of children ever bom is presented in Table 3.6 for all women and for currently married wom- en. The table also shows the mean number of children ever born (CEB) to women in each five-year age group. On average, women have given birth to three children by their late twen- Table 3.5 Fertility by marital duration Fertility rates for ever-married women by duration since first marriage in years, for five-year periods preceding the survey, Zambia 1992 Marriage Number of years preceding the survey duration at birth 0-4 5-9 10-14 15-19 0-4 341 348 367 398 5-9 296 321 324 382 10-14 256 298 316 355 15-19 223 279 266 [300] 20-24 169 216 [211] 25-29 76 [155] Note: Fertility rates are per 1,000 women. Estimates enclosed in brackets ~e truncated. ties, six children by their late thirties, and eight children by the end of their childbearing years. The distribution of women by number of births indicates that over one-quarter of teens (age 15-19) have already bome a child, and over one-third of women age 45-49 have borne ten or more children. Table 3.6 Children ever born and living Percent distribution of all women and of currently married women by number of children ever born (CEB) and mean number ever born and living, according to five-year age groups, Zambia 1992 Number of children ever born (CEB) Number Mean no. Mean no. Age of of of living group 0 1 2 3 4 5 6 7 8 9 10+ Total women CEB children ALL WOMEN Age 15-19 72.8 22.5 4.0 0.6 0.0 0.0 0.0 0.0 0.0 0.0 0.0 100.0 1984 0.3 0.3 20-24 20.4 29.6 28.7 15.3 5.0 0.8 0.1 0.0 0.0 0.0 0.0 100.0 1441 1.6 1.3 25-29 8.2 11.3 16.3 23.6 19.9 12.7 5.2 2.4 0.3 0.1 0.0 100.0 1179 3.1 2.6 30-34 3.9 4.4 7.8 11.6 15.5 17.7 15.3 12.8 7.9 2.5 0.5 100.0 915 4.8 4.0 35-39 2.0 2.7 3.8 5.4 8.4 11.9 14.7 14.9 16.3 9.7 10.1 100.0 656 6.4 5.4 40-44 1.4 1.9 3.9 3.3 6.8 9.8 7.8 12.0 13.3 13.9 25.9 100.0 505 7.4 6.0 45-49 1.4 2.5 2.7 2.8 3.6 5.3 7.5 11.2 12.1 14.9 35.9 100.0 380 8.1 6.4 Total 26.9 15.4 11.5 9.6 7.8 6.7 5.2 4.9 4.2 3.0 4.8 100.0 7060 3.1 2.6 CURRENTLY MARRIED WOMEN Age 15-19 36.1 48.8 13.3 1.8 0.0 0.0 0.0 0.0 0.0 0.0 0.0 100.0 526 0.8 0.7 20-24 10.7 28.1 33.7 19.4 6.8 1.0 0.2 0.0 0.0 0.0 0.0 100.0 989 1.9 1.5 25-29 5.1 8.2 15.4 25.1 21.8 15.1 6.3 2.6 0.3 0.1 0.0 100.0 943 3.4 2.8 30-34 2.0 3.4 7.6 9.9 14.1 18.8 16.8 14.2 9.4 3.0 0.7 100.0 755 5.1 4.3 35-39 1.2 1.8 2.5 5.0 7.0 11.2 15.3 15.3 17.6 11.3 12.0 100.0 537 6.7 5.7 40-44 0.9 1.8 3.8 2.0 5.6 9.1 6.9 12.3 13.0 15.5 29.4 100.0 412 7.7 6.3 45-49 1.3 1.7 1.9 2.1 3.7 4.7 6.6 11.7 12.1 14.3 39.9 100.0 295 8.4 6.7 Total 8.4 14.8 14.4 12.4 10.1 9.1 7.1 6.7 5.8 4.3 6.9 100.0 4457 4.2 3.5 31 The results for younger women who are currently married differ from those for the sample as a whole because of the large number of unmarried women with minimal fertility. Differences at older ages, though minimal, generally reflect the impact of marital dissolution (either divorce or widowhood). The parity distribution for older, currently married women provides a measure of primary infertility--the proportion of women who are unable to have children at all. Voluntary childlessness is rare in Zambia, and married women with no live binahs are most likely unable to bear children. The ZDHS results suggest that primary infertility is low, with only about one percent of Zambian women unable to bear children. It should be noted that this estimate of primary infertility does not include women who may have had one or more births but who are unable to have more (secondary infertility). Table 3.7 Birth intervals Percent distiibution of births in the five years preceding the survey by number of months since previous birth, according to demographic and socioeconomic characteristics, Zambia 1992 Number of months since previous birth Characteristic 7-17 18-23 24-35 3647 48+ Median number of Number months since of Total previous bh-th births Age of mother 15-19 17.8 22.5 50.2 5.7 3.8 100,0 26,3 103 20-29 7.7 14.5 51.0 14.0 12.8 100.0 29.9 2465 30-39 5.1 9.4 47.5 18.3 19.7 100.0 33.2 1818 40 + 3.3 9.7 41.0 20.5 25.6 I00.0 36.2 482 Birth order 2-3 7.5 14.5 47.6 13.2 17.2 100.0 30.2 1937 4-6 5.8 10.5 50.0 17.7 16.0 100.0 32.0 1721 7 + 6.0 11.2 48.5 18.4 15.9 100.0 32.6 1212 Sex of prior birth Male 6.7 l l .8 49.3 15.1 17.1 100.0 31.5 2409 Female 6.3 12.8 48.1 17.1 15.8 100.0 31.4 2460 Survival of prior birth Living 3.4 11.0 51.9 17.0 16.8 100.0 32.0 3983 Dead 20.7 18.1 34.4 12.0 14.9 100.0 27.3 887 Residence Urban 6.3 12.1 47.2 16.4 18.1 100.0 31.4 2230 Rural 6.7 12.4 49.9 15.8 15.1 100.0 31.5 2640 Province Cenmd 5.9 11.6 52.4 16.7 13.4 100.0 30.9 467 Copperbelt 6.6 10.6 51.8 14.6 16.4 100.0 31.0 1129 Eastern 10.1 11.2 47.2 16.1 15.4 100.0 31.8 504 Luapula 8.3 14.8 52.7 12.1 12.2 100.0 29.2 332 Lusaka 5.2 13.3 43.4 16.1 22.0 100.0 32.0 707 Northern 7.5 14.9 48.1 17.7 11.9 100.0 30.8 520 North-Western 7.2 11.2 46.7 19.4 15.5 100.0 32.4 143 Southern 4.7 13.1 49.9 16.5 15.8 100.0 31.5 802 Western 4.7 9.9 39.3 20.1 25.9 100.0 35.9 264 Education No education 6.1 12.8 46,0 15.5 19.5 100.0 32.9 893 Primary 6.9 11.8 50.7 15.7 14.9 100.0 31.1 3093 Secondary 5.3 13.5 44.9 18.2 18.2 100.0 31.3 805 Higher 8.5 15.6 34.9 15.6 25.5 100.0 31.6 77 Total 6.5 12.3 48.7 16.1 16.5 100.0 31.4 4869 Note: First-order births are excluded. The interval for multiple Waths is the number of months since the preceding pregnancy that ended in a live birth. 32 3.3 Birth Intervals Research has shown that children born too close to a previous birth are at increased risk of dying. The risk is particularly high when the interval between births is less than 24 months. Table 3.7 shows the percent distribution of births in the five years preceding the survey by the number of months since the previous birth. Almost one in five births occurs after an interval of less than 24 months. Half the births take place 24-35 months (two years) after the previous birth and one-third have a previous birth interval of three years or more. The median birth interval length (31 months) is only six months longer than the minimum considered safe. The median birth interval is relatively short for younger women and for women living in Luapula Province. As expected, children whose preceding sibling died before the survey had the shortest previous birth interval; almost 40 percent of these children were bern less than 24 months after the birth of the preceding child. Birth intervals in Western Province are notably longer than in other provinces (36 months). 3.4 Age at First Birth The age at which childbearing begins has important demographic consequences for society as well as health consequences for the mother and child. On the demographic side, early initiation into childbearing is generally a major determinant of large family size and rapid population growth, particularly in countries where family planning is not widely used. On the health side, bearing children at a young age involves substantial risks to the health of both the mother and child. Early childbearing also tends to restrict educational and economic opportunities for women. Table 3.8 presents the distribution of Zambian women by age at first birth, according to their current age. Childbearing begins early in Zambia, with the majority of women becoming mothers before they reach the age of 20. Childbearing before age 15 was not uncommon among older women; however, it has become less common over time. More than 40 percent of women age 25-49 had their first birth before age 18 and about 70 percent had their first birth by age 20. It seems that younger cohorts am tending to delay somewhat their Hrst births. The median age at first birth is slightly l'dgher among women age 20-24 than among women in their late 20s or 30s. Also, the proportion of women who begin childbearing in their teenage years shows a decline, from 76 percent of women age 35-39 to 61 percent of women age 20-24. Table 3.8 Age at first birth Percent distribution of women 15-49 by age at first birth, according to current age, Zambia 1992 Current age Women Median with Age at fast birth Number age at no of first births <15 15-17 18-19 20-21 22-24 25+ To ml women birth 15-19 72.8 1.8 17.4 8.0 NA NA NA 100.0 1984 a 20-24 20.4 3.7 30.5 27.1 14.5 3.7 NA 100.0 1441 19.1 25-29 8.2 5.7 33.3 25.5 14.9 9.4 3.0 100.0 1179 18.8 30-34 4.0 8.2 38.4 25.2 13.7 7.2 3.4 100.0 915 18.2 35-39 2.0 9.0 37.9 28.9 11.6 7.3 3.4 100.0 656 18.2 4044 1.4 9.7 32.9 25.2 15.6 9.1 6.2 100.0 505 18.6 45-49 1.4 14.0 31.7 24.0 12.5 9.6 6.8 100.0 380 18.3 NA = Not applicable aLess than 50 percent of the women in the age group x to x+4 have had a birth by age x 33 Differentials in the age at first birth are shown in Table 3.9. The median age at first birth for all women age 20-49 is 18.6. Overall, there is little variation in the median age at first birth by background characteristics of women, except that women with secondary education or higher tend to delay their first birth later than those with less education. Women in Lusaka, Eastern and Northern Provinces have the highest median age at first birth, while women in North-Western Province have the lowest. Table 3.9 Median age at first birth Median age at first birth among women age 20-49 years, by current age and selected b~ekground characteriatics, Zambia 1992 Current age Background Ages Ages characteristic 20-24 25-29 30-34 35-39 40-44 45.49 20.49 25.49 Residence Urban 19.5 19.0 18.2 18.1 18.6 18.3 18.8 18.5 Rural 18.8 18.6 18.3 18.3 18.7 18.3 18.6 18.4 Province Central 18.7 18.8 18.1 (18.2) (18.2) (17.7) 18.5 18.4 Copperbelt 19.5 19.1 18.3 17.9 18.0 18.1 18.7 18.4 Eastern 18.7 18.9 18.8 19.2 18.4 (18.3) 18.8 18.8 Luapula 18.8 18.7 18.4 18.6 18.0 (17.5) 18.5 18.4 Lusaka 19.7 19.0 18.2 18.1 19.2 (19.2) 18.9 18.6 Northern 19.1 18.8 17.9 (18.4) (19.9) (18.9) 18.8 18.6 North-Western 18.0 18.5 18.1 (17.2) (17.4) * 18.1 18.1 Southern 19.1 18.5 17.6 18.0 18.5 (18.7) 18.4 18.2 Western 19.1 18.4 19.0 18.2 (18.9) 17.7 18.7 18.5 Education No education 19.0 18.8 18.1 18.3 18.3 18.5 18.5 18.4 Primary 18.5 18.2 17.8 17.8 18.3 18.2 18.2 18.0 Secondary+ a 20.5 20.0 19.2 20.4 * a 20.0 To~l 19.1 18.8 18,2 18.2 18.6 18.3 18.6 18.5 Note: Rates shown in parentheses are based on 25-49 women, while an asterisk meeaas the rate is based on fewer than 25 women and has been suppressed. The medians for cohort 15-19 could not be determined because half the women have not yet had a birth. aMedians were not calculated for these cohorts because less than 50 percent of women in the age group x to x+4 have had a birth by age x. 34 3.5 Teenage Fertility Fertility among teenagers (those under age 20) is receiving increasing attention from policymakers. Table 3.10 shows the percentage of wometa age 15-19 who arc mothers or pregnant with their first child. The sum of these two percentages represents the proportion of young women who have begun childbearing. More than one-quarter of teenage women have already had a child and another 7 percent were preg- nant with their first child at the time of the survey. As stated before, childbearing begins early in Zambia, Table 3.10 Teenage pref~nency and motharhood Percentage of teenagers 15-19 who are mothers or wegnent with their first child, by selected background characteristics, Zambia 1992 Percentage who are: Percentage who have Pregnant begun Number Background with first child- of characteristic Mothers child bearing ~enagers Age 15 1.9 3.4 5.3 384 16 8.7 6.1 14.7 427 17 22.1 7.8 29.9 392 18 44.2 10.2 54.3 380 19 59.9 5.7 65.6 401 Residence Urban 22.6 5.8 28.5 1076 R~al 32.5 7.5 40.0 907 Province Central 31.9 7.8 39.8 155 Copperbelt 23.8 4.3 28.0 535 Eastern 35.7 8.1 43.7 193 Luapuia 29.5 6.6 36.1 127 Lusaka 22.0 8.5 30.5 320 Northern 26.8 9.8 36.7 202 North-Western 28.7 3.2 31.9 50 Southern 29.5 5.0 34.4 311 Western 27.6 8.7 36.4 91 Education No education 37.3 8.2 45.4 211 Primary 29.0 7.6 36.5 1293 Secondary 17,9 3.3 21.2 479 Total 27.2 6.6 33.8 1984 35 with the proportion of women having begun childbearing increasing rapidly in the late teen years. By age 17, one-third of women have begun childbearing; by age 18, one-half of women and by age 19, two-thirds have (see Figure 3.4). Early childbearing is particularly characteristic of rural women, those in Eastern Province, and those who have not attended school. Whereas most teenage women who have begun childbearing have given b i~ only once, a small proportion have had two births. Table 3.11 shows the distribution of women age 15-19 by number of children ever born. Overall, five percent of women age 15-19 have delivered more than one child. Fifteen percent of women age 19 have had two or more births. 80 60 40 20 Figure 3.4 Percentage of Teenagers Who Have Begun Childbearing by Age Percent 66 15 16 17 18 Age []Mothers []Pregnant (let child) i 19 • ZDHS 1992 Table 3.11 Children born to teenagers Percent distribution of teenagers 15-19 by namber of children ever born (CEB), Zambia 1992 Age 0 1 2+ Number of Mean children ever born number Number of of Total CEB teenagers 15 98.1 16 91.3 17 77.9 18 55.8 19 40.1 Total 7Z8 1.7 0.2 I00.0 0.07, 384 8.7 0.0 100.0 0.09 427 21.1 1.0 100.0 0.23 392 37.5 6.7 100.0 0.52 380 44.5 15.4 100.0 0.77 401 22.5 4.6 100.0 0.32 1984 36 CHAPTER 4 FERTILITY REGULATION 4.1 Knowledge of Contraception Determining the level of knowledge of contraceptive methods and of services was a major objective of the Zambia Demographic and Health Survey, since knowledge of specific methods and of the places whom they can be obtained is a precondition for their use. Information about knowledge of contraceptive methods was collected by asking the respondent to name ways or methods by which a couple could delay or avoid pregnancy. If the respondent failed to mention a particular method spontaneously, the interviewer described the method and asked if she recognised it. Eight modem methods---the pill, IUD, injection, vaginal methods (foaming tablets, jelly, sponge and diaphragm), condoms, female sterilisation and male sterilisation---were described, as well as two traditional methods--natural family planning (periodic abstinence or the rhythm method) and withdrawal. Any other methods mentioned by the respondent, such as herbs, st]hags or breastfceding, were also recorded. For each method recognised, the respondent was asked if she knew where a person could go to get the method. Ifsbe reported knowing about natural family planning, she was asked if she knew where a person could obtain the advice on how to use the method. Table 4.1 indicates that nine of ten Zambian women aged 15-49 know at least one method of family planning. In other words, only 11 percent reported that they did not know any method of family planning. Table 4.1 Knowledge of contraceptive methods and source for methods Percentage of all women mad of currently married women who know specific contraceptive methods and who know a source (for information or services), by specific methods, Zambia 1992 Know method Know a source Currently Curremfly Contraceptive All married All married method women women women women Any method 89.4 93.7 81.4 87.5 Any modern methnd 87.1 90.7 81.1 g7.2 Pill 78.1 84.7 71.1 79.0 IUD 43.0 49.2 38.1 44.0 Injection 38.1 42.9 34.3 39.0 Diaphragm/foam/jelly 23.8 26.7 21.5 24,6 Condom 72.0 73.3 60.7 64.4 Femal~ sterilisatlon 63,6 7t,0 58A 66,0 Male sterllisation 17,9 20.8 16.8 19.7 Any traditional method 66.4 77.6 NA NA Periodic abstinence 36.1 40.3 29.0 33.0 Withdrawal 47.8 58.5 NA NA Other 34.7 42.7 NA NA Number of women 7060 4457 7060 4457 NA = Not applicable 37 Knowledge of methods is slightly higher among currently married women than among all women. Since it is currently married women who are at greatest risk of pregnancy, this chapter focuses primarily on them. A high proportion of married women reported knowing a modem method (91 percent) and 78 percent of them have some knowledge about a traditional method. The most widely known methods are the pill, condom, and female sterilisation, known by 85, 73 and 71 percent of married women, respectively (see Figure 4.1). Following these, IUD and injection are the most commonly known methods (reported by 49 and 43 percent of married women, respectively). Twenty-seven percent of married women know about foaming tablets, jelly or diaphragm and just over one-fifth know about male sterilisation. As regards the traditional methods, 59 and 40 percent of married women know of withdrawal and periodic abstinence (natural family planning), respectively, while 43 percent reported other methods (mostly strings and herbs). Figure 4.1 Percentage of Currently Married Women Who Know Specific Contraceptive Methods Pil l~ IUD~ Injection Diaph ragm/Foam/Jelly ~ Condom i Female Sterilisation Male Sterillsation Periodic Abstinence Withdrawal 0 ~ 8 5 49 ~ 4 3 ~ 2 7 1 7 3 ~ 9 9 20 40 60 80 100 Percent ZDHS 1992 Knowledge of sources for obtaining family planning methods is widespread in Zambia. Overall, nearly nine of ten married women know a place where they can obtain some method of family planning and 90 percent or more of the women who know specific modem family planning methods also know where they can obtain them. Knowledge of places to get information about periodic abstinence is somewhat lower, with about 80 percent of the women who know the method knowing a source of information. As with knowledge of the methods themselves, knowledge of places where specific methods can be obtained is slightly higher among currently married women than among all women. The proportion of women who know of at least one contraceptive method is higher among women in their 20s and 30s than among younger and older women (see Table 4.2). This is also true for knowledge of at least one modem method and knowledge of a place to obtain a modem method. 38 Table 4.2 Knowledge of modern contraceptive methods and source for methods Percentage of currently married women who know at least one modem contraceptive method and who know a source (for information or services), by selected baekgrotmd characteristics, Zambia 1992 Know a Know Know sot~ce for Number Background any a modem modem of characteristic method method 1 method women Age 15-19 86.7 83.6 77.3 526 20-24 94.6 92.7 89.1 989 25-29 95.9 94.3 92.3 943 30-34 96.3 92.7 90.8 755 35-39 95.4 94.4 91.0 537 40-44 91.4 86.2 80.2 412 45-49 g9.6 80.1 76.1 295 Residence Urban 97.2 96.5 94.1 2091 Rural 90.6 85.7 81.2 2366 Province Central 74.3 70.6 66.4 418 Copperbelt 99.2 98.8 97.0 1023 Eastern 92.5 89.8 84.7 536 Luapula 94.9 90.0 87.7 281 Lusaka 95.4 94.5 91.0 738 Northern 91.9 82.1 80.6 423 North-Weatem 91.6 90.9 87.4 124 Southern 96.7 94.7 90.3 673 Weatem 95.7 86,2 78.3 24l Education No education 84.5 76.9 70.5 864 Primary 95.0 92.7 89.2 2754 Secondary 98.5 98.4 97.6 745 Higher 100.0 100.0 100.0 93 Tom] 93.7 90.7 87.2 4457 lIncludes pill, IUD, injection, vaginal methods (foaming tablets/diaphragm/ foam/jelly), condom, female sterilisation, and male sterillsadon. Knowledge of contraceptive methods and their sources is somewhat more widespread in urban than in rural areas. The proportion of urban married women who know at least one family planning method is 97 percent, compared with 91 percent of rural women. The differential, however, widens with respect to knowledge of a modem method and a source for a modem method, with 94 percent of urban women knowing a source, compared to 81 percent of rural women. Differences in contraceptive knowledge by province are not large except for Central Province where the proportion of married women who have heard of at least one family planning method is relatively low: 39 74 percent as compared to between 92 and 99 percent in the other provinces. The level of knowledge of at least one modem method is higher in Copperbelt (99 percent), Southern (95 percent) and Lusaka (95 percent) Provinces than in the other provinces. The same pattem holds for knowledge of where these methods can be obtained. The level of knowledge of family planning methods and places where they can be obtained increases with the level of education, with knowledge of modem family planning methods increasing from 77 percent among uneducated women to an estimated 100 percent among women with higher education (more than secondary). Married women with no education or only primary education are also less likely than women with secondary or higher education to know of a source of these methods; the proportions increase from 71 percent among married women with no education to an estimated 100 percent among women with higher education (see Table 4.2). 4.2 Ever Use of Contracept ion All women interviewed in the ZDHS who said that they had heard of a method of family planning were asked if they had ever used it. Forty percent of Zambian women of reproductive age have used a method of family planning sometime and nearly one-quarter have used a modem method (see Table 4.3). Table 4.3 Ever use of contraception Among all women and among currently married women, the percentage who have ever used a contraceptive method, by specific method and age, Zambia I992 Any Any modern Age method method Pill IUD Modem methods I Traditional methods Diaphragm/ Female Male Any Periodic Number Injec- Foam/ Con- sterili- sterili- tra& absfi- With- of tion Je l ly dom sarion sation method nence drawal Other women ALL WOMEN Age 15-19 12.9 7.3 1.9 0.0 0.1 0.4 5.6 0.0 0.1 8.4 2.6 5.2 1.8 1984 20-24 41.6 24.1 12.8 0.6 0.5 1.6 15.1 0.1 0.0 28.7 8.7 19.8 5.8 1441 25-29 53.5 32.3 24.2 2.3 1.0 2.8 13.7 0.4 0.2 35.8 10.9 25.1 8.5 1179 30-34 55.2 31.7 25.3 3.9 1.6 1.3 9.8 1.4 0.0 38.4 10.0 25.9 12.7 915 35-39 58.9 36.0 29.7 7.8 4.5 3.5 6.1 5.0 0.5 39.8 8.8 25.1 16.8 656 40-44 52.1 27.3 21.4 4.2 4.7 1,5 2.9 6.2 0.2 36.7 5.7 21.6 20.3 505 45-49 47.1 20,9 14.3 3.3 5.5 0.5 1.6 5.7 0.3 36.9 4.2 20.4 20.4 380 Total 39.9 22.9 15.5 2.2 1.5 1.5 9.1 1.5 0.1 27.5 7.1 18.0 8.9 7060 CURRENTLy MARKIED WOMEN Age 15-19 27.0 14.7 4.1 0.0 0.2 0.4 11.6 0.0 0.0 19.3 4.6 13.9 3.6 526 20-24 45.4 24.7 13.2 0.7 0.5 1.6 15.6 0.1 0.0 32.5 8.0 23.6 7.5 989 25-29 54.2 31.2 23.9 2.1 0.7 2.9 14.2 0.2 0.2 37.5 10.9 27.0 9.1 943 30-34 56.3 31.4 25.1 3.9 1.7 1.4 9.5 1.3 0.1 39.9 8.7 27.9 13.2 755 35-39 56.9 34.6 27.9 7.2 4.5 3.2 5.6 6.1 0.4 38.5 8.4 24.8 16.3 537 40-44 52.3 26.7 19.8 4.3 5.0 1.1 2.8 7.3 0.3 37.2 5.9 20.8 21.6 412 45-49 49.1 19.5 13.3 2.1 5.3 0,2 1.3 5,3 0.4 40,1 4.7 22.6 22.0 295 Total 49.2 27.1 18.8 2.6 1.9 1.8 10.5 2.1 0.2 34.9 7.9 23.7 11.7 4457 1Includes pill, IUD, injection, vaginal methods (foaming tablet s/diaphragm/fomn/j elly), condom, female sterilisatio~a, and male sterilisatinn. 40 The corresponding proportions among currently married women are 49 and 27 percent, respectively. Ever- use is lowest among the youngest age group (15-19 years), rises to a peak among the 35-39 year olds and then drops slightly among older women. More married women have used traditional methods than modem methods, with the most widely used methods being withdrawal (24 percent) and the pill (19 percent). Condom and natural family planning (periodic abstinence) have also been commonly used methods, with 11 and 8 percent of married women having used them. Three percent of married women have used the IUD, while 2 percent have used female sterilisation, injection, and vaginal methods (foaming tablets, jelly, sponge, diaphragm). 4.3 Current Use of Contraception Though over 90 percent of married women in Zambia have heard of and nearly half have used a family planning method, only 15 percent reported that they were currently using a method at the time of the survey (see Table 4.4). Nine percent of women are using modem methods, while 6 percent are using traditional methods. The most popular contraceptive method is the pill (4 percent), followed by withdrawal (3 percent), female sterilisation (2 percent) and condom (2 percent). Other traditional methods---mostly abstinence, strings and herbs---are used by 2 percent of married women. Table 4.4 Current use of contraception Percent distribution of all women and of currently married women by contraceptive method currently used, according to age, Zamb~.a 1992 Age A.y modern Any meth- m eahod od Mnde~'a methods I Traditional methods Dia- Fcmal~ Male Peri- Nm plragm, steri- ,~ i - Any odic With- cur- Injec- foam, Con- lisa- lisa- ~rad. abe- draw- Miss- rently Pill IUD tion jelly dora llon t i~ methnd hence el Oth~ ing using ToNal Ntm~b~ WOMEN 15-19 3.5 1.5 0.7 0.0 0.0 0.I 0.7 0.0 0.0 2.0 0.3 1.0 0.7 0.0 96.5 I00.0 1984 20-24 11.2 7.1 4.2 0.2 0.I 0.I 2.4 0.I 0.0 4.1 0.8 2.4 0.8 0.2 88.8 I00.0 1441 25-29 15.0 9.0 6.2 0,6 0.1 0.0 1.7 0,4 0.0 6.0 1,3 2.7 2.0 0.0 85.0 1(30.0 1179 30-34 17.5 10.7 5.4 1.3 0.1 0.4 2.1 1.4 0.0 6.8 1.0 2.6 3.1 0.1 82.5 100.0 915 35-39 20.6 12.7 5.5 0.3 0.2 0.3 1.2 5.0 0.2 7.9 1,3 3.3 2.8 0.5 79,4 100.0 656 40-44 15.7 10.1 1,7 0.9 0.2 0.2 0.9 6.2 0.0 5.6 0.9 1.0 3.5 0.2 84.3 100.0 505 45~19 9.4 6.4 0.5 0.0 0.3 0.0 0.0 5.7 0.0 3.0 0.0 0.3 2.5 0.2 90.6 100.0 380 ToN 11.6 7.0 3.5 0,4 0,1 0.1 1.4 1.5 0.0 4,6 0.8 1.9 1.7 0.1 88.4 1~.0 7060 CURRENTLY MARRIED WOMEN 15-19 8.7 3.4 1.8 0.0 0.0 0.0 1,7 0.0 0.0 5.2 0.4 3.4 1A 0.0 91.3 100,0 526 20-24 13.1 7.7 4.3 0.I 0.1 0.0 3.0 0. I 0.0 5.5 0.7 3.4 I.I 0.2 86.9 I00.0 989 25-29 15.3 8.6 6.0 0.5 0. I 0.0 1.8 0.2 0.0 6.6 1.3 3.2 2.0 0.0 84.7 100.0 943 30-34 18.3 10.7 5.5 1.3 0. I 0.4 2.0 1.3 0.0 7.6 1.0 3.0 3.5 0. I 81.7 I00.0 755 35-39 22.5 14.1 6.0 0.2 0.2 0.4 1.0 6.1 0.2 8A IA 4.0 2.6 0A 77.5 I00.0 537 40-44 17.4 11.0 1.3 1.1 0.3 0.3 0.8 7,3 0.0 6,4 1.1 1.2 3.8 0.3 82.6 1(30.0 412 4549 9.0 6.3 0.6 0.0 0.4 0.0 0.0 5.3 0.0 2.7 0.0 0,4 2,1 0.2 91.0 1(30,0 295 Total 15£ 8.9 4.3 0.5 0.I 0.1 1.8 2.1 0.0 6.3 0.9 3.0 2.2 0.2 84.8 I00.0 4457 qncludcs pill, IUD, injection, vaginal methods (fo~ming table~diaphragm/foam/j~llly), condom, female st~-ilisatioe, and male st~ilisatice. 41 Contraceptive use is highest among women in their late 30s, and lowest among women aged 15-19 and 45-49 years. This pattern is most likely due to the fact that younger women are just starting their families, whilst older women are more likely to have reached their desired family size and want to stop childbearing altogether. For the same reasons, younger women are more likely to use less effective methods such as withdrawal or temporary methods such as condom, while older women are more likely to use more effective, long-term methods such as female sterilisation. About six percent of married women in their 40s have been sterilised. Use among the oldest women (i.e., 45-49) might be lower because they are more likely to have reached menopause and thus are not in need of family planning. While overall use of family planning is quite low, the ZDHS data show that some married women are more likely to be using contraception than others (see Table 4.5 and Figure 4.2). Women most likely to be using contraception are those resident in urban areas as well as those in Lusaka, Copperbelt, Western and Northern Provinces, those with higher education and those with four or more children. Not only are urban women twice as likely as rural women to be using a method (21 percent vs. 10 percent), but urban users are also more likely to be using a modem method. Urban women depend on methods such as the pill, female stcrilisation and condom, whilst rural women rely primarily on traditional methods such as withdrawal, wearing beads or herbs around the waist, drinking African medicine made with roots and leaves, etc. Table 4.5 Current use of contraception by background characteristics Percent distribution of currently married women by contraceptive method currently used, according to background characteristics, Zambia 1992 Age Any modern Any meth. method od Modem methods I Traditions1 methods Din- Female Male peti- Not phragm, steri- steri- Any odic With- cur- Injec- foam, Con- lisa- lisa- trad. absti- draw- Miss- rently Pill IUD don jelly dora tion tion method nence al Other ing using Total Number Residence Urbma 20.8 15.3 7.9 1.0 0.3 0.3 2.6 3.3 0.0 5.5 1.4 2.3 1.6 0.3 79.2 100.0 2091 Rural 10.3 3.2 1.1 0.0 0.0 0.0 1.1 1.0 0.0 7.0 0.5 3.6 2.8 0.1 89.7 100.0 2366 Province Central 9.2 6.8 4.2 0.0 0.0 0.0 1.6 0.8 0,3 2.4 0,8 0.5 1.1 0.0 90.8 100.0 418 Copperbelt 19.0 13.6 7.1 0.7 0.4 0,1 1.7 3.5 0,0 5.4 1.2 1.8 2.2 0.2 81.0 IG0.0 1023 Eastern 9.7 4.7 1.2 0.2 0.0 0.2 1.7 1.5 0.0 5.0 0.2 1.5 3.3 0.0 90.3 1130.0 536 Luapula 9.5 6.0 2.8 0.0 0.0 1.2 1.2 0.9 0.0 3.5 0.5 0.5 2.5 0.0 90.5 100.0 281 Lusaka 24.2 17.6 8.1 1.3 0.1 0.1 4.3 3.7 0.0 6.6 1.5 3.5 1.3 0.3 75.8 100.0 738 Northern 17.5 3.1 1.8 0.0 0.0 0.0 0.3 1.0 0.0 14.4 1.0 12.1 1.0 0,3 82.5 100.0 423 North-Western 10.4 5,9 1.8 0.0 0.0 0.0 1.3 2.8 0.0 4.4 0.9 1.9 1.3 0.3 89.6 100.0 12tl Southern 8.5 4.2 2.3 0.2 0.0 0.0 1.2 0.7 0.0 4.3 1.0 2.3 0.8 0.2 91.5 100.0 673 Western 17.8 2.9 0.3 0.5 0.5 0.0 0.6 1.1 0.0 14.9 0,3 3.4 10.9 0.3 82.2 100.0 241 Education No education 8.0 2.7 0.9 0.0 0.1 0.0 0.4 1.2 0.0 5.3 0.1 2.3 2.9 0.0 92.0 100.0 864 Primary 12.8 6.3 3.1 0.1 0.2 0.0 1.4 1.4 0.0 6.5 0.4 3.5 2.4 0.2 87.2 100.0 2754 Secondary 27.1 20.7 10.6 1.5 0.1 0.4 4.1 3.8 0.1 6.4 3.0 2.1 1.1 0.1 72.9 100.0 745 Higher 58.5 49.6 19.3 7.0 0.0 2.3 7.0 14,0 0.0 8.9 6.5 1.2 L2 0.0 41.5 I00.0 93 Number or living children 0 0.9 0.4 0.2 0.0 0.0 0.0 0.2 0.0 0.0 0.4 0.2 0.0 0.2 0.0 99.1 100.0 488 1 12.2 7.2 3.4 0.1 0.0 0.0 3.1 0.5 0.0 5.0 1.0 2.6 1.1 0.3 87.8 100.0 802 2 16.3 9.6 4.4 0.9 0.0 0.2 2.6 1.6 0.0 6.7 0.8 4.3 1.5 0.0 83.7 100.0 695 3 15.4 9.9 6.3 0.7 0.0 0.2 2.1 0.6 0.0 5.5 0.5 3.5 1.5 0.1 84.6 100.0 590 4+ 19.7 11.2 5.0 0.5 0.3 0.2 1.2 3.9 0.l 8.5 1.3 3.2 3.7 0.3 80.9 100.0 1882 Total 15.2 8.9 4.3 0.5 0.1 0.1 1.8 2.1 0.0 6.3 0.9 3.0 2.2 0.2 84.8 100.0 4457 Ilncludes pill, IUD, injection, vaginal methods (foaming tablets/diaphragm/foam/jelly), condom, female sterilisation, and male sterilisation. 42 Figure 4.2 Percentage of Currently Married Women Using a Contraceptive Method RESIDENCE Urban Rurnl PROVINCE / Cent re l~ Copperbolt Eastern Luapula Luscka Northern ~ North-Western Southern Western EDUCATION No Education Prlmary~ Secondary H lgher~ 0 21 ~ I 0 ~ 9 1 9 ~ I 0 ~ 1 0 24 ~ 1 8 ~ I 10 ~ 9 r . 18 ~ 8 ~ 1 3 . • . 27 . - . - 59 10 20 30 40 50 60 Percent 70 ZDHS 1992 The proportion of married women using any method of contraception also varies widely by province, from 9 percent in Southern and CentralProvinces to 24 percent in Lusaka Province. In Western and Northern Provinces, traditional methods (withdrawal and African medicine, beads, etc.) are by far the most frequently used methods, accounting for over 80 percent of all contraceptive use. In Southern, Eastern, North-Western and Luapula Provinces, modem and traditional methods are almost equally used, with the pill, condom, withdrawal and other traditional African methods being the most common. In Central Province, the pill and condom are the most widely used methods. In Copperbelt Province, the most commonly used methods are the pill and female sterilisatlon, followed by withdrawal and condom. In addition to the pill, condom, female sterihsation and withdrawal, which are the most frequently used methods in Lusaka Province, the IUD and periodic abstinence have a relatively high level of use. The largest differentials in current use of contraception are found for educational groups. Contraceptive use increases steadily with increasing level of education, from 8 percent of married women with no education to 59 percent of those with higher than secondary education. (The latter figure should be viewed with caution, since the number of women in that category is small.) Moreover, the proportion of users who are using modem methods increases dramatically with education level. For example, twice as many women with no education use traditional as modem methods, mostly withdrawal and other methods like beads and herbs. Among women with primary education, modem methods account for half of all use, with withdrawal being the most common method, followed by the piU. Among those with secondary or higher education, modem methods account for 75 percent or more of total use, with the pill, condom and female sterilisation prominent. Periodic abstinence is also commonly used among highly educated married women. The use of foaming tablets and other vaginal methods appears to be limited to women with more than secondary education. 43 Contraceptive use also increases with the number of children a woman has. As the number of children increases, use of modern methods becomes more important in the overall method mix. 4.4 Number of Children at First Use of Contraception In many cultures, family planning is used only when couples have already had as many children as they want. However, as the concept of family planning gains acceptance, couples may begin to use contraception for spacing births as well as for limiting family size. Moreover, unmarried young women may be particularly motivated to use family planning to avoid an unwanted pregnancy. Table 4.6 shows the number of children ever-married respondents had when they first used contraception. For the older cohorts (35-49 years), women generally started using family planning only after they had four or more children, although almost as many started using after their first child. For the younger cohorts (15-29 years), women are more likely to have started using family planning after their first child. For instance, roughly the same proportion of women age 25-29 and 40-44 have used a contraceptive method (54 and 52 percent, respectively). However, while half of the ever-users age 40-44 years waited until they had had at least three children, half of the ever-users age 25-29 started to use after their first child. Seven percent of ever-married women under age 25 started to use family planning before they had any children, compared to only one percent of women 40-44. This reflects a shift towards use of family planning for spacing purposes. Table 4.6 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, Zambia 1992 Number of living children at time Never of first use of contraception Number Current used of age contraception 0 1 2 3 4+ Missing Total women 15-19 73.6 6.9 17.8 0.9 0.0 0.0 0.8 100.0 588 20-24 55,8 6.6 27.6 6.6 2.4 0.3 0.7 100.0 1136 25-29 46.3 4.1 24.8 14.3 6.1 3.4 1A 100.0 1112 30-34 44.6 1.5 21.0 12.9 8.3 10.9 0.7 I00.0 897 35-39 41.3 2.6 17.6 9.8 9.5 18.2 1.0 100.0 652 40-44 48.0 1.0 14.4 6.2 7.6 22.4 0.3 100.0 504 45-49 52.9 0.3 18.0 6.4 5.8 16.5 0.0 100.0 380 Total 51.1 3.7 21.6 9.0 5.5 8.2 0.8 100.0 5269 4.5 Knowledge of Fertile Period A basic knowledge of reproductive physiology is useful for the successful practice of coitus- dependent methods such as withdrawal, the condom, or barrier methods, but it is especially important for users of periodic abstinence or natural family planning. The successful practice of periodic abstinence depends on an understanding of when during the ovulatory cycle a woman is most likely to conceive. Table 4,7 presents the percent distribution of all respondents and those who have ever used periodic abstinence by reported knowledge of the fertile period in the ovulatory cycle. 44 Table 4.7 Knowledge of fertile period Percent distribution of all women and of women who have ever used periodic abstinence by knowledge of the fertile period during the ovulatory cycle, Zambia 1992 Ever USers Perceived All of periodic fertile period women abstinence During menstrual period 0.7 0.4 Right after period has ended 27.5 42.4 In the middle of the cycle 13.7 30.2 Just before period begins 8.1 10.7 Other 0.4 0.7 No particular time 16.0 9.2 Don't know 33.7 6.4 Missing 0.1 0.0 Total 100.0 10O.0 Number 7060 499 Thirty-four percent of the women interviewed said they did not know when a woman is most rtkely to conceive and 28 percent said that a woman is most likely to conceive right after her period has ended. Only 14 percent gave the correct response: that a woman is most likely to conceive in the middle of her ovulatory cycle. Ever-users of periodic abstinence are more knowledgeable about the ovulatory cycle than women in general. Thirty percent identified the fertile period as occurring in the middle of the cycle, and only 6 percent said they did not know when it occurred. It should be noted that the precoded response categories for this question are only one way of dividing the cycle into distinct periods. Women may actually have a more accurate understanding of their fertility cycles than is reflected by these categories, especially those who answered "right after her period has ended." However, it appears that half of all women and one-sixth of those who have used periodic abstinence clearly do not understand the ovulatory process, since they either said that there is no particular time when a woman has a greater chance of becoming pregnant or they said there was a particular time but they did not know when it was or they thought it occurred "during her period." 4.6 Sources of Family Planning Methods All current users of modem methods of family planning were asked to report the source from which they most recently obtained their methods. Since women often do not know exactly which category the source they use falls into (e.g., government hospital, mission health centre, etc.), interviewers were instructed to write the name of the source. Supervisors and field editors were to verify that the name and the type of sources were consistent, asking cluster informants for the names of local family planning sources if necessary. This practice was designed to improve the reporting of data on sources of family planning. 45 Table 4.8 and Figure 4.3 indicate that most users of modem methods (56 percent) obtain their methods from public (government) sources, while 36 percent rely on private medical sources and 7 percent use other sources such as shops or friends. Government health centres are the single most frequently cited source, serving 32 percent of users, followed by government hospitals (24 percent) and private hospitals and clinics (20 percent)) In fact, eight in ten users obtain their methods from hospitals, health centres or clinics, whether public or private. Table 4.8 Source of supply for modem contraceptive methods Percent distribution of current users of modem contraceptive methods by most recent source of supply, according to specific methods, Zambia 1992 Female sterili- Source of supply Pill IUD Condom sation Total I PubUc 67.2 (64.0) 41.9 45.1 56.1 Government hospital 17.6 (48.0) 10.9 45.1 24.1 Government health centre 49.5 (16.0) 30.9 0.0 32.0 Private (medical) 26.7 (36.0) 36.8 53.5 36.0 Private hospital, clinic 17.7 (28.0) 5.5 36.3 20.0 Mission hospital, clinic 2.6 (0.0) 3.3 17.2 5.6 Pharmacy 4.4 (0.0) 24.4 0.0 7.6 Private doctor 1.3 (8.0) 0.0 0.0 1.8 Mobile clinic 0.2 (0.0) 3.7 0.0 0.8 Field worker 0.4 (0.0) 0.0 0.0 0.2 Other private 6.2 (0.0) 19.1 0.0 7.2 Shop 4.4 (0.0) 16.3 0.0 5.5 Filends/relatives 1.8 (0.0) 2.8 0.0 1.7 Don't know 0.0 (0.0) 2.2 0.0 0.4 Missing 0,0 (0.0) 0.0 1.4 0.3 Total 100.0 100.0 100~0 100.0 100.0 Number 245 27 100 104 493 1Includes 6 users of injection, 9 of vaginal methods and 1 of made sterilisation. The source a woman uses to obtain contraceptive methods depends on many things, one of which is the type of method she may have chosen. Most pill users obtain their method from public sources, one-half from govemment health centres and about one-sixth from government hospitals. Condom users are likely to use a wide range of sources--government facilities (42 percent), phannacies (24 percen0, shops (16 percent), as well as a few from private or mission clinics and friends or relatives. Female sterilisations are somewhat more likely to be performed in private institutions (54 percent), with almost as many of the operations undertaken in govemment hospitals (45 percent). Interviewers were instructed to consider health facilities run by mining companies as private facilities. 46 Figure 4.3 Distribution of Current Users of Contraception by Source of Supply Govt. Health Centre 3 l e rnment HospRal 24% Don't Know/Missing 1% Other 7% ,J PHvate (medical) 36% ZDHS 1992 Women who were currently using a modem contraceptive method were asked how long it takes to travel from their home to the place where they obtain the method. Nonusers were asked if they knew a place where they could obtain a modem method and, if so, how long it would take to travel there. The results are presented in Table 4.9. Among the women currently using a modem method, 44 percent are within 30 minutes (one-way travel time) of the place to which they go to get their method, while 27 percent are 30 minutes to one hour from their source. One'quarter °fusers °f m°dem meth°ds are °ne h°ur °r m°re fr°m their s°urce °f supply" As expected, urban users are generaUy closer than rural users to their supply sources; half of urban users are within 30 minutes of their supply sources as compared to less than one-fifth of the rural users. Half of the latter have to travel for one hour or more to get their supplies. Among women who are not using a modem method, almost one-quarter do not know a source for a modem contraceptive method. It should be noted that this question was asked of all nonusers and thus includes the 11 percent of women who do not know any method. Since these women presumably do not know of a source for family planning, they would account for almost half of those nonusers who do not know of a source. The last panelofTable 4.9 is based on all women who know a contraceptive method. Among women who know at least one family planning method, 28 percent are within 30 minutes of a source for a modem method and 15 percent say they do not know of a place to get a modem method. 47 Table 4.9 Time to source of supply for modern contraceptive methods Percent dlsa'ibution of women who are currently using a modern contr~eptive method, of women who are not using a modern method, and of women who know a method, by time to reach a source of supply, according to urban-rural residence, Zambia 1992 Woman who are currently using a modern method Woman who are not using a modem method Women who know a contraceptive method Minutes to source Urban Rural Total Urban Rural Total Urban Rural Total 0-14 26.2 16.1 24.2 19.3 10.0 14.6 21.3 11.3 16.7 15-29 24.2 2.9 19.9 16.0 2.7 9.3 17.9 3.2 11.1 30-59 28.7 18.6 26.6 24.8 7.7 16.1 26.5 9.2 18.5 60 or more 18.2 50.8 24.8 20.2 48.1 34.3 21.1 53.7 36.2 Does not know time 2.2 10.0 3.8 1.5 2.8 2.1 1.7 3.5 2.5 Does not know source 0.0 0.0 0.0 17.9 28.5 23.2 11.2 18.8 14.7 Not stated 0.6 1.5 0.7 0.3 0.2 0.2 0.4 0.3 0.3 Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 Median time to source 25.9 60.8 30.3 30.4 50.1 30.3 45.4 Number of women 393 100 493 3243 3324 6567 3387 2926 6313 - Median cannot be calculated 4.7 Intention to Use Family Planning Among Nonusers Women who were not using a contraceptive method at the time of the survey were asked i f they thought they would do something to keep from getting pregnant at any time in the future. Currently married nonusers are about evenly split between those who intend to use family planning in the future (48 percent) and those who say they do not intend to use (45 percent) (see Table 4.10). Almost three-quarters of those who intend to use say they intend to use a method within the next 12 months. Intention to use family planning is closely related to the number of children a woman has. Thus, while only 22 percent of childless nonusers would use family planning in the future, 50 percent of nonusers with four or more children expressed the intention to use a method in the future. About half of the women who say they intend to use contraception in the future have used it in the past, while the other half have never used a method, I f all the married women who say they intend to use family planning were to actually adopt it and use continuously, the contraceptive prevalence rate would rise substantially, from 15 percent of married women to about 56 percent. 48 Table 4.10 Future use of enntraeeption Percent dislxibutien of currently married women who are not using a conta'aceptive method by past experience with cont~caeeption and intention to use in the future, according to nurnbex of living children, Zambia 1992 Past experience with conU, aception end future intentions Number of living children I 0 1 2 3 4+ Total Never used contraception Intend to use in next 12 months 4.5 18.8 18.9 13.2 15.0 15.2 Intend to use later 10.9 11.0 6.3 7.4 3.8 6.7 Unsure as to timing 0.7 1.5 0.4 1.0 1.1 1.0 Unsure as to intention 11.5 7.4 5.5 3.5 3.6 5.3 Do not intend to use 57.7 32.7 28.2 28.0 28.5 31.7 Missing 0.0 0.0 0.4 0.0 0.1 0.1 Previously used contraception Intend to use in next 12 months 0.7 11.9 21.2 22.0 24.7 19.3 Intend to use later 4.7 5.2 6.3 7.7 4.8 5.5 Unsure as to timing 0.0 0.4 0.4 0.4 0.5 0.4 Unsure as to intention 0.8 1.4 2.4 1.9 1.6 1.7 Do not intend to use 8.5 9.7 10.2 14.8 16.2 13.1 Missing 0.0 0.0 0.0 0.2 0.2 0.1 Total 100.0 100.0 100.0 100.0 100.0 190.0 All currently married nonusers Intend to use in next 12 months 5.2 30.7 40.0 35.2 39.7 34.5 Intend to use later 15.6 16.2 12.6 15.0 8.6 12.2 Unsure as to timing 0.7 1.9 0.8 1.4 1.6 1.4 Unsure as to intention 12.3 8.8 7.9 5.4 5.1 6.9 Do not intend to use 66.2 42.4 38.4 42.8 44.7 44.8 Missing 0.0 0,0 0.4 0.2 0.3 0.2 Total 100.0 100.0 100.0 100.0 100.0 I00.0 Number of women 317 725 599 523 1616 3780 qz~ludes current pregnancy 49 Table 4.11 presents the main masons for not using contraception given by married women who are not using any contraceptive method and do not intend to use it in the future. Over one-third (37 percent) of these women say they do not intend to use because they want children, while another one-third cite infecundity (either "difficult to get pregnant" or "menopausal") as the reason. Other reasons given are lack of knowledge (11 percent) and opposition to family planning, either by the respondent, her husband or someone else (7 percent). The younger cohort (under age 30) are more likely to say they do not to intend to use contraception in the future because they want more children or because they lack knowledge, while those age 30 and over are more likely to cite reasons such as being menopausal or infecund. Table 4.11 Reasons for not using contraception Percent distribution of curtent!y married women who are not using a contraceptive method and who do not intend to use in the future by main reason for not using, according to age, Zambia 1992 Age Reason for not using contraception 15-29 30-49 Total Want children 50.7 25.2 36.7 Lack of knowledge 15.2 6.9 10.6 Partner opposed 3.5 3.8 3.7 Cost too much 0.1 0.3 0.2 Side effects 6.0 3.3 4.5 Health concerns 1.2 1.7 1.5 Hard to get methods 1.2 0.4 0.8 Religion 0.7 1.9 1.3 Opposed to family planning 2.4 3.1 2.8 Fatalisdc 0.3 0,9 0.6 Other people opposed 0.4 0.1 0.3 Infrequent sex 0.3 1.0 0.7 Difficult to get pregnant 11.5 27.3 20.2 Menopausal, had hysterectomy 0.1 19.4 10.7 Inconvenient 0.9 1.1 1.0 Other 2.3 2.6 2.4 Don't know 3.1 1.0 1.9 Missing 0.1 0.0 0.1 Total 100.0 100.0 100.0 Number of women 763 930 1693 50 Nonusers who said that they did intend to use family planning in the fulurc were asked which method they preferred to use. The data arc presented in Table 4.12. Most of these women said they preferred to use the pill (59 percent), with female sterllisation the next most preferred method (8 percent). The same pattern of method preference is noted among women regardless of whether they intend to use in the next 12 months or later. There is a tendency for women who are unsure about the timing of future use to also be unsure of which method they might use. Table 4.12 Preferred method of contraception fox futom use Percent distribution of currently married women who are not using a con~aceptive method but who intend to use in the future by la'eferred method, according to whether they intend to use in the next 12 months or later. Zambia 1992 Intend to use In next After Unsure Preferred method 12 12 as to of contraception months months timing Total Pill 58.2 64.0 50.0 59.4 IUD 2.8 1.8 2.0 2.5 Injection 5,6 3.6 4.1 5.0 Diaphragm/Foam/Jelly 1.8 0.8 0.0 1.5 Condom 2.6 3.1 0.0 2.6 Female sterilisatinn 8.5 6.3 5,5 7.9 Periodic abstinence 2.4 3.3 0.0 2.7 Withdrawal 3.3 2.9 4.0 3.2 Other 7.2 5.1 6.1 6.6 Unsoxe 7.4 9.1 28.2 8.5 Total 100.0 I00.0 I00.0 100.0 Number of women 1304 459 54 1819 51 4.8 Exposure to Family Planning Messages on Radio and Television All respondents in the ZDHS were asked i f they had heard a message about family planning on radio or television in the month preceding the interview. Eight in ten women said they had not heard a message on either radio or television (see Table 4.13). Most of those who heard a message heard it on radio (18 percent), while 7 percent saw a message on television; only 5 percent had heard a message on both radio and television. The proportion of women who had heard family planning messages in the month prior to the survey varied widely by background characteristics. One-third of women resident in urban areas and in Copperbelt and Lusaka Provinces had heard messages, compared to only 7 percent of women living in rural areas or in Eastern and Western Provinces. Women with higher education are much more likely to have heard a family planning message on radio or television than those with primary or no education. Table 4.13 Family planning messages on radio and television Percent distribution of all women by whether they have heard a family planning message on radio or on television in the month preceding the survey, according to selected background characteristics, Zambia 1992 Heard family plauning message on radio or on television Number Background Radio Television of char aeterlstic Neither only only Both Miss'rag Total women Residence Urban 67.8 20.0 2.9 9.0 0.3 100.0 3636 Rural 92.8 5.8 0.4 0.9 0.1 100.0 3424 Province Cenural 85.4 10.1 1.6 3.0 0.0 100.0 622 Copperbelt 65,7 21.3 2.2 10.5 0.3 100.0 1743 Eastern 93.2 4.8 0.3 1.5 0.2 100.0 729 Luapula 86.0 10.1 0.4 3.5 0.0 100.0 431 Lusaka 68.1 18.6 4.4 8.5 0.4 100.0 1234 Northern 89.7 9.3 0.5 0.3 0.2 100.0 652 North-We.stem 86.1 10.3 1.8 1.4 0.4 100.0 183 Southern 90.4 7.5 0.5 1.6 0.0 100.0 1045 Westem 92.6 5.8 0.6 1.0 0.0 100.0 422 Education No education 93.8 4.9 0.3 1.0 0.0 100.0 1161 Primary 82.0 13.2 1.0 3.6 0.3 100.0 4213 Secondary 65.7 18.8 4.1 11.2 0.1 100.0 1561 Higher 57.0 16.7 9.6 16.7 0.0 100.0 124 Total 79.9 13.1 1.7 5.1 0.2 100.0 7060 52 Table 4.14 presents results from a question on whether women believe it is acceptable or not acceptable to air family planning messages over radio or television. Nearly t/nee-quarters of the women interviewed said that such messages are acceptable to them. The proportion of women who think family planning messages are acceptable is highest among women in their 20s and 30s and falls off among older women. Women living in urban areas or in Western, Central, Luapula, and Copperbelt Provinces, as well as more educated women are much more likely to accept family planning messages on radio or television than other women. Women in Eastern and Southern Provinces are particularly likely to oppose family planning messages on the media. Table 4.14 Acceptability of the use of mass media for diasamiunting family planning messages Percent distribution of women by acceptability of having messages about family planning on radio or television, according to age end selected background characteristics, Zambia 1992 Not Number Background Accept- ar, cept- Unsure/ of characteristic able able Mi~s'mg Total women Age 15-19 68.3 31.1 0.6 100.0 1984 20-24 78.1 21.5 0.4 100.0 1441 25-29 80.0 19.5 0.4 100.0 1179 30-34 76.9 22.5 0.6 100.0 915 35-39 73.7 26.2 0.2 100.0 656 40~14 66.4 33.5 0.1 100.0 505 45-49 57.9 41.8 0.3 100.0 380 Residence Urban 78.9 20.7 0.4 100.0 3636 Rural 67.1 32.5 0.5 100.0 3424 Province Cen~al 87.7 12.3 0.0 100.0 622 Copperbelt 80.9 18.8 0.3 100.0 1743 Eastern 44.7 54.9 0.5 I00.0 729 Luapula 81.0 19.0 0.0 100.0 431 Lusaka 78.4 21.3 0.3 100.0 1234 Northern 64.5 35.5 0.0 100.0 652 North-Western 75.6 14.6 9,8 100.0 183 Southera 57.3 42.7 0.0 100.0 1045 Western 97.8 2.2 0.0 100.0 422 Educatlon No education 59.8 40.0 0.2 I00.0 1161 Primary 71.2 28.3 0,5 I00.0 4213 Second~+ 87.4 t2.3 0A 100.0 1685 Total 73.2 26.4 0.4 I00.0 7060 53 4.9 Approval of Family Planning An indication of the acceptability of family planning is the extent to which couples discuss the topic with each other. Table 4.15 indicates that 58 percent of married women who know a contraceptive method had discussed family planning with their husbands in the year prior to the survey. Most of these women had discussed the topic only once or twice with their husbands, but almost as many had discussed family planning more often. The tendency to discuss family planning with spouses is greater among women in their 20s and 30s than among older or younger women. Table 4.15 Discussion of family planning by couples Percent distribution of currently married non-sl~filiscd women who know a contraceptive method by the number of times family planning was discussed with husband in the year preceding the survey, according to current age, Zambia 1992 Age Never Number of times family planning discussed Num~r Once or Three Not of twice or more ascertained Total women 15-19 51.6 30.8 17.1 0.5 100.0 456 20-24 38.9 35.3 25.7 0.1 100.0 935 25-29 37.9 31.7 30.1 0.2 100.0 902 30-34 38.4 32.9 28.2 0.4 100.0 717 35-39 38.4 27.0 34.4 0.1 100.0 479 40-44 45.2 28.9 25.6 0.3 100.0 346 45-49 60.2 22.9 16.9 0.0 100.0 249 Total 41.8 31.3 26.6 0.2 100.0 4083 In order to obtain more direct information about the acceptability of family planning, respondents were asked if they approved or disapproved of couples using a method to avoid pregnancy. Although all women were asked this question, the data presented in Table 4.16 are confined to currently married, non- sterilised women and exclude those women who had never heard of a contraceptive method. Currently married, non-sterilised women were also asked if they thought that their husbands approved of the use of family planning. It should be noted that wives' opinions of their husbands' attitudes may be incorrect, either because they have misconstrued their husbands' true attitudes, or because of a tendency to report their husbands' attitudes as similar to their own. Overall, 81 percent of married women who know a contraceptive method approve of family planning. Just over half of the women say that their husbands also approve of family planning; 17 percent say that they approve of family planning and their husbands do not. Approval of family planning by married women does not vary much by age of the woman except that women age 45-49 are less likely to approve than younger cohorts. Married women who live in urban areas or in Westem, Central or Northern Provinces, and those who are better educated are more likely than other women to approve of the use of family planning. Among 54 husbands, the proportion who reportedly disapprove of family planning decreases with increasing level of education of their wives. A sizeable proportion of married women living in rural areas do not know their husbands' attitudes towards family planning, an indication of the extent to which family planning is discussed by rural couples. The proportion of wives who say they do not know their husbands' attitude toward family planning use is also high among women in Eastern and Western Provinces and among uneducated women. Table 4.16 Attitudes of couples toward family planning Among curr~fly married non-sterilised women who lmow a contraceptive method, the percentage who approve of family planning, by thdtr perception of their husband's attitude and selected baekgrotmd eharacterlsties, Zambia 1992 Respondent approves Respondent disapproves Unsme Uusurc Both Husband of Husband Husband of Respondent Characteristic approve disapproves husband approves disapproves husband unsure Percent Total Age 15-19 41.0 12.7 22.5 3.8 12.0 6.5 1.3 100.0 456 20-24 53.2 14.5 15.9 2.6 9.8 3.7 0.4 100.0 935 25-29 54.2 17,8 12.4 2.4 8.9 3.4 0.9 100.0 902 30-34 51.5 17.9 12.8 2.5 10,2 4.0 1.1 100.0 717 35-39 52.0 18.0 11.5 2.8 9.4 5.7 0.5 100.0 479 40-44 44.1 20.5 14.9 1.3 13.6 5.4 0.1 100.0 346 45-49 36.7 14.4 13.8 4.6 17.8 12.2 0.4 100.0 249 Residence Urban 57.7 17.9 8.5 2.6 10.0 2.1 1.1 100.0 1963 Rural 42,5 15.3 20.2 2.8 11.3 7.5 0.3 100.0 2120 Province CenU'al 51.4 20.8 13.7 1.8 9.0 1.4 1.8 100.0 306 Copperbelt 55.2 21.1 7.3 4.0 9.4 1.7 1.3 100.0 979 Eastern 33.3 10.2 27.3 3.4 9.5 16.1 0.2 100.0 488 Luapula 43.8 18.2 19.5 1.3 10.3 6.4 0.5 100.0 264 Lusaka 59.9 13.5 10.0 1.6 12.0 2.2 0.8 100.0 678 Northern 60.2 14.5 11.3 1.7 9.2 3.2 0.0 100.0 384 North-Western 47.6 22.3 5.1 4.4 14.5 5.7 0.4 100.0 110 Southern 40,5 15.6 19.0 3.4 14.9 6.5 0.2 100.0 646 Western 47.6 15.9 25,9 0,6 5.9 3.6 0.5 100.0 228 Education No education 37.0 15.8 20.3 2.7 14.1 10.0 0.2 100.0 719 Primary 46.8 17.7 15.1 3.0 12.0 4.7 0.7 100.0 2577 Secondary 69.9 14.0 8.3 1.8 3.5 1.1 1.4 100.0 705 Higher 87.0 8.9 2.8 0.0 1.4 0.0 0.0 100.0 80 Total 49.8 16.5 14.6 2.7 10.7 4.9 0.7 100.0 4083 55 CHAPTER 5 OTHER PROXIMATE DETERMINANTS OF FERTILITY This chapter addresses the principal factors, other than contraception, which affect a woman's risk of becoming pregnant: nuptiality and sexual intercourse, postpartum amenorrhoea and abstinence from sexual relations, and secondary infertility. While it is by no means exact, marriage is an indicator of exposure of women to the risk of pregnancy, and is therefore important for the understanding of reality. Populations in which age at marriage is low also tend to experience early childbearing and high feltility; hence the motivation to examine trends in age at marriage. This chapter also includes more direct measures of the beginning of exposure to pregnancy and the level of exposure: age at first sexual intercourse and the frequency of intercourse. Measures of other proximate determinants of fertility are the durations of postpartum amenorrhoea and postpartum abstinence and the level of secondary infertility. 5.1 Marital Status Data on the marital status of respondents at the time of the survey are shown in Table 5.1. The term "married" refers to legal or formal marriage, while "living together" refers to informal unions. In subsequent tables, these two categories are combined and referred to collectively as "currently married" or "currently in union." Women who are widowed, divorced, and no longer living together (separated) make up the remainder of the "ever-married or "ever in union" category. Table 5.1 Current marital status Percent distribution of women by current marital status, according to age, Zambia 1992 Age Marital status No longer Number Never Living living of married Married together Widowed Divorced together Total women 15-19 70.4 26.0 0.5 0.2 1.8 1.1 100.0 1984 20-24 21,2 66.5 2.1 1.1 6.2 2.9 100.0 1441 25-29 5,7 76.7 3.2 2.1 8.7 3.6 100.0 1179 30-34 Z0 79.5 3,0 3,8 10,3 1,5 100,0 915 35-39 0,7 79.7 2.2 3.5 11.8 2.2 100.0 656 40-44 0,1 79.3 2.3 5.7 9.8 2.8 100.0 505 45-49 0.0 75,2 2.5 8.5 11.6 2.2 100.0 380 Total 25,4 61,1 2.0 2.3 7.0 2.2 100.0 7060 57 Most Zambian women of reproductive age are currently in a marital union (63 percent). The 1980 census which also defined marriage to include unions "where no ceremony has been performed but the man and woman are living as husband and wife," reported a slightly higher figure (67 percent of women). Some of the decrease in the proportion married is probably due to a rising age at first marriage (see section 5.3), though some is no doubt due to the relatively larger proportion of teenagers surveyed in the ZDHS, most of whom have not yet married. Consequently, the proportion never married appears to have increased slightly from 24 percent in 1980 to 25 percent in 1992. The proportion who have never married drops precipitously among women in their late 20s. The proportion divorced or separated (no longer living together) rises steeply after age group 15-19 until age 25-29, after which it stays relatively constant at about 12-14 percent of women. The proportion widowed rises more gradually, reaching about 9 percent of women age 45-49. 5.2 Polygyny Since polygyny is practiced in Zambia, married women were asked in the ZDHS whether their husbands had other wives, and if so, how many. Overall, 18 percent of currently married women are in a polygynous union. The figures presented in Table 5.2 indicate that polygyny exists in aU provinces and among all socioeconomic groups, although prevalence varies. Rural women are about three times more likely than urban women to be in such unions. One-third of married women in Southern Province and one-quarter Table 5.2 Polygyny Percentage of currently married women in a polygynous union, by age and selected background characteristics, Zambia 1992 Age of woman Background All characteristic 15-19 20,24 25-29 30-34 35-39 40-44 45-49 ages Residence Urban 1.7 4.8 9.1 12.2 11.5 13.6 19.6 9.3 Rural 13.4 15.6 25.8 34.9 33.5 29.4 35.6 25.1 Province Central (4.5) 14.6 11.8 17.0 (20.6) (22.8) (44.4) 16.6 Col)perMit 3.4 3.3 8.5 11,3 10.4 11.1 13.8 8.2 Eastern 13.4 14.4 19.6 30.4 (27.6) (31.1) (36,8) 22.3 Luapula 9.5 10.8 24.0 24.1 (16.2) (22.5) * 17.3 Lusaka 3.5 6.6 6.6 12.5 6.6 12.4 (21.3) 8,7 Northern 10.0 15.7 26.8 (36.2) (37.6) (34.3) (39.0) 25.7 North-Western (0.0) 6.7 12.1 (24.1) (36.9) * * 15.6 Southern 19.0 18.4 35.2 44.7 45.9 35.3 (36,8) 32.8 Western * 10.6 16.5 32.1 (26.3) (24.4) (36.2) 22.1 Education No education 12.4 17.9 21.8 33.9 30.3 22.3 32.2 24.8 Primary 8.9 10.9 18.8 22.7 22.5 24.9 29.0 17.7 Secondary (4.3) 5.2 12.2 14.2 17.5 (19,9) * 11.3 Total 9.1 10.6 17.2 22.6 22.3 22.6 30.2 17.7 Note: Rates shown in parentheses are based on 25 to 49 women, while an asterisk means the rate is based on fewer than 25 women and has been suppressed. 58 in the Nolthem Province are in polygynous unions, compared to 22 percent of women in Eastern and Western Provinces, between 16 and 18 percent in Luapula, North-Western and Central Provinces and between 8 and 9 percent in Copperbelt and Lusaka Provinces. Nearly one-quarter of the women with no formal schooling are in a polygynous union, compared to 11 percent of those with secondary education. Most women in polygynous unions have only one co-wife, however, one-third of the women (6 percent of all married women) have two or more co-wives (see Table 5.3). In fact, in Southern and North- Western Provinces, though a majority of women are in monogamous unions (67 and 84 percent, respectively), more women have two or more co-wives (20 percent and 11 percent) than have one co-wife (13 percent and 4 percent, respectively). Table 5.3 Number of co-wives Percent distribution of currently married women by number of co-wive*, according to selected background characteristics, Zambia 1992 Number of co-wive* Number Background of characteristic 0 1 2+ Missing Total women Age 15-19 90.9 6.9 2.2 0.0 100.0 526 20-24 89.4 7.1 3.3 0.1 100.0 989 25-29 82.8 10.8 6.4 0.0 100.0 943 30-34 77.4 13.8 8.7 0.1 100.0 755 35-39 77.7 13.5 8.8 0.1 100.0 537 40-44 77.4 13.7 9.0 0.0 100.0 412 45-49 69.8 19.4 10.8 0.0 100.0 295 Residence Urban 90.7 6.6 2.6 0.1 100.0 2091 Rural 74.9 15.3 9.8 0.0 100.0 2366 Province Central 83.4 10.3 6.1 0.3 1(30.0 418 Copperbeh 91.8 6.5 1.6 0.1 I00.0 1023 Eastern 77.7 16.5 5.8 0.0 100.0 536 Luapula 82.7 14.8 2.5 0,0 100.0 281 Lusaka 91,3 5.2 3.6 0.0 100.0 738 Northern 74.3 20.5 5.2 0.0 100.0 423 North-Western 84.4 3.9 11.4 0.3 100.0 124 Southern 67.2 12.7 20.1 0.0 100.0 673 Western 77.9 18.5 3.6 0.0 100.0 241 Educatlon No education 75.2 17.2 7.6 0.0 I00.0 864 Primary 82.3 10.8 6.9 0.I 100,0 2754 Secondary 88,7 7.2 4.1 0.1 I00.0 745 Higher 97.7 1.2 1.2 0.0 100.0 93 Total 82.3 11.2 6.4 0.1 100,0 4457 59 The tendency to have another wife (either one or two or more co-wives) increases with age, a reflection of changes in the marital status as widowed and divorced women are remarried. Whilst a rural woman is twice as likely as an urban woman to have one co-wife, she is four times more likely than her urban counterpart to have two or more co-wives. More educated women are less likely to have a co-wife: 17 percent of women with no education have one co-wife, compared to 11 percent and 7 percent of those who have primary and secondary education, respectively. Women with no education are also nearly twice as likely as those with secondary education to have two or more co-wives. 5.3 Age at First Marriage ZDHS data show that half the women in Zambia marry before they reach age 18. The reported mean age at first union is 18.5 years; the 1980 census reported a mean age at first marriage of 18.3 years (Central Statistical Office, 1985a). The data presented in Table 5.4 indicate a median age at first marriage of 17.4 for women age 25-49 and 17.7 among the 20-49 year olds; the pattern shows a trend toward later age at marriage for younger women. Table 5.4 Age at first marriage Percentage of women who were first married by exact age 15, 18, 20, 22, and 25, and median age at first marriage, according to current age, Zambia 1992 Percentage of women who were Percentage Median first married by exact age: who had age at Number never first of Current age 15 18 20 22 25 married marriage women 15-19 4.2 NA NA NA NA 70.4 a 1984 20-24 9.0 43.3 63.6 NA NA 21.2 18.6 1441 25-29 12.0 50.4 69.5 81.9 91.6 5.7 18.0 1179 30-34 17.7 60.6 78.4 87.8 94.6 2.0 17.2 915 35-39 19.3 63.8 82.7 90.8 96,2 0.7 17.2 656 40-44 22.6 62.9 81.2 91.6 95,8 0.1 17.0 505 45-49 31.1 64.8 79.3 90.0 96.1 0.0 16.6 380 20-49 15.6 54.3 73.0 83.7 89.9 7.8 17.7 5076 25-49 18.2 58.6 76.8 87.2 94.2 2.5 17.4 3635 NA = Not applicable aOmitted because less than 50 percent of the women in the age group x to x+4 were first married by age x Cohort trends in age at marriage can also be described by comparing the cumulative distribution for successive age groups, as shown in Table 5.4. ~ The age at marriage appears to have increased over time. The proportion of women married by age 15 has decreased systematically from 31 percent among those age For each cohort the accumulated percentages stop at the lower age boundary of the cohort to avoid censoring problems. For instance, for the cohort currently aged 20-24, accumulation stops with the percentage married by exact age 20. 60 45-49 to 4 percent among the 15-19 year-olds. The median age at marriage has increased from 17 years or less among women now in their 30s and 40s to 18 and over among women in their 20s. Thus, the median age at marriage has increased by between one to one and a half years. The national picture masks large differentials in marriage behaviour patterns; Table 5.5 presents a more detailed picture of the trends in the median age at marriage. It can be seen that the changes observed at the national level have been achieved primarily through changes in the behaviour of women in urban areas, where the median age at marriage has increased by more than 3 years between cohorts of women age 20-24 and 45-49. Increases of 2 years or more have taken place among women in Copperbelt, Central and Luapula Provinces, whilst the median age at marriage among women in North-Western, Eastern and Southern Provinces has risen by over one year. Level of education attended is closely related to age at first marriage. The median age at first marriage for women 25-49 increases steadily with education, from 16.7 among women with no education to 19.9 for women with secondary or higher schooling. Table 5.5 Median age at first marriage Median age at first marriage among women age 20-49 years, by current age and selected background characteristics, Zambia 1992 Current age Woman Woman Background age age characteristic 20-24 25-29 30-34 35-39 40-44 45-49 20-49 25-49 Residence Urban 19.7 18,4 17.2 17,2 17.1 16.4 18.0 17.5 Rural 17.9 17.6 17.2 17.1 17.0 16.7 17.4 17.2 Province Central 18.0 18.0 17.5 (16.6) (16.4) (15.8) 17.5 17.2 Copperbelt 18,9 18.3 16.9 16.8 16.8 16.5 17.6 17.2 Eastern 17.6 17.7 17.4 18.0 17.0 (16.3) 17.5 17.4 Luapula 17.6 17.3 16.7 17.0 16.4 (15.6) 17.0 16.8 Lusaka a 18.5 17.5 17.1 17.5 (18.0) 18.4 17.8 Northern 17.8 17.5 16.6 (17.3) (18.1) (17.2) 17.4 17.3 North-Western 17.6 17.8 17.8 (15.7) (15.6) * 17.1 17.0 Southern 18.8 18.0 17.0 17.5 16.8 (17.6) 17.8 17.5 Western a 18.1 18.4 17,4 (17,8) 16.8 18.2 17.8 Education No education 17.7 17.4 16.4 16.3 16.6 16.5 16.9 16.7 Primary 17.8 17.3 16.7 16.8 16.8 16,7 17.1 16.9 Secondary+ a 20.8 20.0 18.7 19.6 * a 19.9 Total 18.6 18.0 17.2 17.2 17.0 16.6 17.7 17.4 Note: Rates shown in parentheses are based on 25 to 49 women, while art asterisk means the rate is based on fewer than 25 women and has been suppressed. Medians are not shown for women 15-19 because less thma 50 percent of these women bad married by age 15. aomitted because less than 50 percent of the woman in the age group were first married by age 20. 61 5.4 Age at First Sexual Intercourse While age at first marriage is often used as a proxy for exposure to intercourse, the two events do not necessarily occur at the same time. Women may engage in sexual relations prior to marriage, especially if they are postponing the age at which they marry. The ZDHS asked women the age at which they first had sexual intercourse (see Tables 5.6 and 5.7). (Note that the information on age at first sexual intercourse in Tables 5.6 and 5.7 parallels the information on age at first marriage in Tables 5.4 and 5.5). In many cases sexual activity precedes marriage (see Table 5.6). For instance, by age 18, 72 percent of the women age 20-49 had had sexual intercourse, whereas only 54 percent had married; similarly, by age 20, 88 percent had had intercourse, while 73 percent had married. Overall, the median age at first sexual intercourse is 16.3 years, which is about 1.4 years earlier than the median age at first marriage of 17.7. Analysis of cohorts indicates that there has been little change in the median age at first sexual intercourse over time. Table 5.6 Age at first sexual intercourse Percentage of women who had first sexual intercourse by exact age 15, 18, 20, 22, and 25, and median age at first intercourse, according to current age, Zambia 1992 Percentage of women who had first intercourse by exact age: Current age 15 18 20 22 Median Percentage age at who fast Number never had inter- of 25 intercourse course women 15-19 19.2 NA NA NA NA 39.5 a 1984 20-24 20.2 68.9 86.9 NA NA 4.3 16,6 1441 25-29 23.3 70.9 87.2 93.8 98.1 0.6 16.4 1179 30-34 28.1 77.1 90.7 96.1 98.4 0.2 16.0 915 35-39 27.5 75.8 90.8 95.7 98.4 0.0 16.2 656 40-44 28.9 72.5 88.8 95.6 97.4 0.0 16.3 505 45-49 36.8 71.4 86.6 92.7 98.1 0.0 16.0 380 20-49 25.4 72.3 88.3 94.6 97.3 1.4 16.3 5076 25-49 27.5 73.6 88.9 94.8 98.1 0.3 16.2 3635 NA = Not applicable aOmitted because less than 50 percent of the women in the age group x to x+4 had had intercourse by age x I f women do not wait for marriage to become sexually active, has the increasing age at marriage among women in urban areas and in Central, Copperbelt and Luapula Provinces had any effect on delaying exposure to intercourse? Table 5.7 indicates some trend toward later initiation of sexual intercourse among younger urban women; however, it is nowhere near as strong as the trend toward later age at marriage. While age at marriage has been increasing, the age of initiating sexual activity has remained unchanged in Lusaka and Northem Provinces where it has been relatively high. 62 More educated women tend to delay initiating sexual relations longer than uneducated women (median age at first intercourse for those with secondary or higher education is 2 years more than for those with no education), but they postpone marriage even longer (the median age at first marriage for the most educated women is three years greater than that of women with no education). On the other hand, the differentials between the urban and the rural women in respect of age at marriage and age at first sexual intercourse are virtually the same: urban women have a median age at marriage of 0.6 years later than rural women (20-49 age group); their median age at first intercourse is also 0.6 years later. Even among the younger women (20-24 years), while the median age at marriage in urban areas is about 2 years later than in the rural areas, the median age at first intercourse is less than one year later in urban than in rural areas. Table 5.7 Median age at first intercourse Median age at first sexual intercourse among women age 20-49 years, by current age and selected backgmtmd characteristics, Zambia 1992 Current age Women Women Background age age characteristic 20-24 25-29 30-34 35-39 40-44 45-49 20-49 25-49 Residence Urban 17.0 16.8 16.2 16.4 16.4 16.1 16.6 16.5 Rural 16.2 16.0 15.8 15.9 16.1 16.0 16.0 16.0 Province Cen~al 16.4 16.3 16.0 (15.5) (15.8) (15.0) 16.0 15.9 Copperbelt 16.8 16.8 16.1 16.1 15.9 16.3 16.5 16.3 Eastern 16.2 16.6 15.7 17.4 16.6 (15.4) 16.3 16.3 Luapula 16.1 15.8 16.0 16.5 15.6 (15.1) 15.9 15.8 Lusaka 17.2 16.9 16.3 16.6 17.0 (16.8) 16.8 16.7 Northern 16.7 16.6 16.3 (17.0) (17.3) (17.2) 16.7 16.7 North-Wastem 15.5 15.7 15.4 (15.3) (14.9) * 15.5 15.5 Southern 16.3 16.0 15.9 15.7 16.0 (16.3) 16,0 15.9 Western 16.4 16.3 16.3 15.8 (16.4) 16.3 16.2 16.2 Education No education 16.5 16.1 15.4 15.7 15.9 16.2 15.9 15.8 Primary 16.1 15.9 15.8 15.9 16.1 15.8 16.0 15.9 Secondary+ 18.1 18.0 17.6 17.6 17.8 * 17.9 17.8 Total 16.6 16.4 16.0 16.2 16.3 16.0 16.3 16.2 Note: Rates shown in parentheses are based on 25 to 49 women, while an asterisk means the rate is based on fewer than 25 women and has been suppressed. Medians are not shown for women 15-19 because loss than 50 percent of those women had had intorenurs~ by age 15. 5,5 Recent Sexual Activity In the absence of contraception, the probability of pregnancy is related to the frequency of intercourse. Thus, information on sexual activity can be used to refine measures of exposure to pregnancy. Only 12 percent of women interviewed in the ZDHS had never had sexual intercourse. But not all women who have ever had intercourse are currently sexually active. Table 5.8 presents data on levels of sexual activity by background characteristics; the distributions are shown for women who have ever had intercourse. 63 Table 5.8 Recent sexual activity Percent distribution of women who have ever had sexual intercourse by sexua/activity in the four weeks preceding the survey and the duration of abstinence by whether or not postpartum, according to selected background characteristics, Zambia 1992 Not sexually active in last 4 weeks SexuaHy Abstaining Abstaining active (postpartum) (not postpartum) Number Background in last , of characteristic 4weeks 0-1 years 2+ years 0-1 years 2* years Total women Age 15-19 55.7 16.3 1.0 25,0 2.0 100.0 1200 20-24 60.9 16.6 2.2 19.5 0.8 100.0 1378 25-29 65.3 12.3 1.8 18.5 1.8 100.0 1172 30-34 65,5 13.4 1.9 17.3 2.0 100.0 913 35-39 64.8 10.9 2.3 18.6 3.4 100.0 656 40-44 70,2 5.4 1.8 18.3 4.3 100.0 505 45~19 59.4 1.6 1.3 22.5 15.1 100.0 380 Duration of union 0 J, 69.3 15.4 0.7 14.5 0.1 100.0 1308 5-9 66.5 15.1 1.4 15.8 1.3 100.0 1095 10-14 68,4 12,2 2,2 15,4 1,6 100,0 857 15-19 67.5 12.7 1.2 16.6 2.0 100.0 769 20-24 64.7 9,6 2.1 19.9 3.6 100.0 574 25+ 64.3 2,6 1.7 21.4 10,1 100,0 664 Never in union 36.2 16.5 3.6 38.9 4.6 100,0 936 Residence Urban 62.1 11.7 1.5 21.7 2.9 100,0 3109 Rural 62.9 13.9 2.0 18.3 2.8 100.0 3096 Province Central 66.4 11.2 0.4 19,1 2.7 100.0 559 Copperbelt 62.0 10.7 1.8 22.3 3.2 100.0 1471 Eastern 60.1 12.7 2.5 19,8 4.9 100.0 672 Luapula 65.4 11,4 1.8 19,0 2.4 100.0 372 Lusaka 63.0 11.7 1.1 21,8 2.3 100.0 1078 Northern 53.3 19.9 3.2 19~6 4.0 100.0 546 Nor th-Westem 59.6 18.3 1.5 18.0 2.6 100.0 165 Southern 70.6 11.5 1.2 15.7 0.9 100.0 945 Western 53.4 18.9 3.8 21.4 2.5 100.0 395 Education No education 63.1 13,0 1.9 17.4 4.7 100.0 1083 Primary 64.1 13.6 1.6 18.7 2.0 100.0 3716 Secondary 57.0 11.0 2.3 26.2 3.5 100.0 1281 Higher 65.3 6.2 0.9 21.3 6.2 100.0 123 Current contraceptive method No method 60.5 13.8 1.9 20.7 3.0 100.0 5388 Pill 83.8 2.6 0.3 13.3 0.0 100.0 245 IUD (72.0) (4.0) (0.0) (12.0) (12.0) 100.0 27 Stetilisation 69.6 5.2 0.4 20.3 4.5 100.0 106 Periodic abstinence 78.8 6.1 0.0 15.1 0.0 100.0 55 Other 72.6 9.2 1.0 I6.2 1.0 100.0 375 Total 62.5 12.8 1.8 20.0 2.8 100.0 6205 Note: Figures in parentheses are based on 25 to 49 women 64 Women are considered to be sexually active if they had intercourse at least once in the four weeks prior to the survey. Women who are not sexually active may be abstaining in the period following a birth, or may be abstaining for various other reasons. Among women who have had sexual intercourse, 63 percent were sexually active in the month prior to the interview, while 15 percent were abstaining postpartum and 23 percent were abstaining for other reasons. Women who have never been in a union are less likely to be sexually active than those who are in a union. As expected, women who are using a method of family planning are more likely to be sexually active than those who are not. 5.6 Postpartum Amenorrhoea , Abst inence, and Insusceptibi l i ty Postpartum protection from conception can be prolonged by broastfeeding, which can lengthen the duration of amenorrhoea (the period foUowing a birth, but prior to the return of menses). Protection can also be prolonged by delaying the resumption of sexual relations. Table 5.9 presents the percentage of births whose mothers are postpartum amenorrhoeic and abstaining, as well as the percentage of births whose mothers are classified as still postpartum insusceptible to pregnancy for either mason; data are presented by months since the birth. Table 5.9 Postpartum amanorrhooa r abstinence and insusceptibility Percentage of births whose mothers are postpartttm arnanorthceic, abstaining and insusceptible, by number of months since birth, and median and moan durations, Zambia 1992 Number Months Amenur- Inans- of since birth rhoeic Abstaining eeptible births < 2 97.5 95.3 99.1 192 2-3 87.1 68.2 91.3 257 4-5 80.0 47.9 86.3 254 6-7 72.4 30.6 77.4 265 8-9 65.2 27.4 73.2 227 10-11 55.5 21.4 62.5 221 12-13 47.0 17.4 54.0 225 14-15 36.6 16.2 45.5 237 16-17 24.8 13.9 32.4 200 18-I9 17.5 12.3 24.3 217 20-21 15.1 10.7 22.7 219 22-23 8,0 8.9 13.7 209 24-25 4.9 5.9 9.6 201 26-27 4.3 3.8 7.2 223 28-29 1.7 3.6 5.0 237 30-31 0.3 5.8 5.8 198 32-33 1.1 5.2 6.3 210 34-35 0.9 6.4 7.3 196 Total 36.0 22.8 41.8 3987 Median 11.7 4.4 13.3 Mean 12.7 8.3 14.7 Prevalence/Incidence mean 12.8 8.1 14.8 65 Nearly three-quarters of Zambian women remain amenorrhoeic for at least six months following a birth; only one-third abstain from sexual intercourse during this period. The proportion remaining amenorrhoeic 18 months after birth drops significantly to 18 percent and those still abstaining to 12 percent. Overall, three-quarters of women become susceptible to pregnancy within 18-19 months of giving birth. The average duration of the postpartum insusceptible period is 15 months. The median durations of postpartum amenorrhoea, abstinence and insusceptibility are presented in Table 5.10 by background characteristics of the mothers. Postpartum amenorrhoea generally lasts slightly longer among older (age 30 and above) than younger mothers. The duration is also longer among rural (14 months) than urban mothers (9 months), a possible indication of shorter duration of breastfeeding among urban women. Mothers in Northern Province show a particularly long median duration of amenorrhoea, while those in Westem and Nonla-Westem Province tend to abstain for considerably longer periods (10-12 months) after birth than the 3-5 months that mothers in other provinces report. The long abstinence in the latter two provinces may account in part for their relatively low fertility (see Chapter 3). With regard to educational level, the higher the level of education of the mother, the shorter the median duration of amenorrhoea, The median duration of amenorrhoea decreases from 14 months for women with no education to 12 months for those with primary schooling and to only 8 months for women with secondary education. Table 5.10 Median duration of postpartum insusceptibility by background characteristics Median number of months of postpartum amenorrhoea, postpartum abstinence, and postpartum insusceptibility, by selected background characteristics, Zambia 1992 Postpartum Number Background Postpartum Postpartum insuscep- of characteristic amenorrhoea abstinence tibility births Age <30 11.0 4.3 12.9 2687 30+ (13.9) 4.5 14.9 1301 Residence Urban 9.4 4.6 11.3 1878 RurN 13.5 4.2 14.6 2109 Education No education * (4.4) (15.3) 654 Primary 11.7 4.5 13.1 2544 Secondary (8.3) * (11.9) 725 Total 11.7 4.4 13.3 3987 Note: Medians are based on current status. Rates shown in parentheses are based on 25 to 49 women, while an asterisk means the rate is based on fewer than 25 women and has been suppressed. 66 5.7 Termination of Exposure to Pregnancy Later in life, the risk of pregnancy begins to decline with age, typically beginning around age 30. While the onset of infecundity is difficult to determine for any individual woman, there are ways of estimating it for a population. Table 5.11 presents indicators of decreasing exposure to the risk of pregnancy for women age 30 and above. The first, an indicator of menopause, includes women who are neither pregnant nor postpartum amenorrhoeic, but have not had a menstrual period in the six months preceding the survey. Forty-two percent of the oldest women interviewed are menopausal according to this indicator. The other indicator is long-term abstinence which is the percentage of currently married women who did not have intercourse in the last three years. This percentage is very low even among the oldest women. Table 5.11 Termination of exposure to the risk of pre~nane,/ Indicators of menopause and long-term abstinence among eurronfly married women age 30-49, by age, Zambia 1992 Long-teaxn Monopause I abstinene~ Age Percent N Percent N 30-34 3.8 388 0.1 755 35-39 2.6 334 0.7 537 40-41 6.6 87 0.8 134 42-43 11.7 161 1.1 193 44-45 25.6 138 2.8 157 46-47 28.1 104 1.8 109 48-49 41.7 109 1.9 114 Total 12.0 1321 0.8 1999 IPercentage of non-pregnam, non-amenorrhonic currc~tiy married women whose last menstrual period occurred six or more months preceding the survey or who report that they are menopausal. 2Percentage of currently married women who did not have int~course in the three years preceding the survey. 67 CHAPTER 6 FERTILITY PREFERENCES Several questions were asked in the ZDHS concerning women's fertility preferences. These questions dealt with: 1) whether the respondent wanted another child, 2) if so, how long she would like to wait to have the next child, and 3) how many children she would want in total if she could start afresh. The answers to these questions allow the estimation of levels of unmet need for family planning services either to limit or space births and of levels of unwanted fertility. The value of the data on fertility preferences as a vehicle for predicting future fertility is questionable. Women's attitudes towards childbearing may not be fully formed and may change over time. Moreover, the data do not reflect the effects of social pressures or the attitudes of other family members, particularly the husband, who may have a major influence on reproductive decisions. Also, women need the means to fulfill their desires. However, on a macro level, data on fertility preferences can be useful as an indicator of the direction that future fertility may take. 6.1 Desire for More Children In the ZDHS, currently married women were asked "Would you like to have (a/another) child or would you prefer not to have any (more) children?" Interviewers were instructed to alter the wording depending on whether the respondent already had children or not. If the woman was pregnant, she was asked Figure 6,1 Fertility Preferences among Currently Married Women 15-49 Want no more 22% Undec ided 5~ I n feeund 4% Ster i l i sed 2% Want a ch i ld soon 26% (within 2 yrs) Want a ch i ld la ter 41% (a f ter 2 or more yrs) ZDHS 1992 69 if she wanted another child after the one she was expecting. Women who said they did want to have another child were then asked how long they would like to wait before the birth of the next child. As Figure 6.1 shows, two-thirds of married women in Zambia want to have another child; however, most of these women (41 percent of all married women) want to wait two or more years before having their next birth. Over one-fifth (22 percent) of women do not want to have any more children. Thus, a majority of married women want to either space their next birth (want a child later) or limit childbearing altogether (want no more). These women can be considered to be potentially in need of family planning services. Not surprisingly, the desire for more children declines noticeably as the number of living children increases (Table 6.1 and Figure 6.2). Thus, 77 percent of married women with no children want to have a child soon (within two years), whereas only 7 percent of women with six or more children want to have another soon, Table 6,1 Fertility preferences by number of living children Percent distribution of currently married women by desire for more children, according to number of living children, Zambia 1992 Number of living children I Desire ~or children 0 1 2 3 4 5 6+ Total Have another soon 2 76.9 36.4 28.3 29.1 21.1 16.1 6.9 26.3 Have another later 3 8.8 56.3 58.1 55,0 44.5 38.5 17.3 40.6 Have another, undecided when 3.0 1.1 0.8 0.6 0.5 0.8 0.7 0.9 Undecided 2.0 1.4 3.2 2.8 6.6 7.1 7.1 4.4 Wants no more 1.0 2.4 6.2 10,0 22.7 32.0 56.3 22.0 Sterilised 0.0 0.5 1.5 0.5 1.7 1.6 5.5 2.1 Declared infecund 8.2 1.3 1.6 2.0 3.0 3,4 6.0 3.5 Missing 0.0 0.4 0.3 0.0 0.0 0.4 0,2 0.2 Total 100.0 100.0 100.0 100.0 I00.0 100.0 100,0 I00,0 Number of women 321 822 712 614 481 428 1078 4457 tlncludes current pregnancy 2Wants next birth within 2 years 3Wants to delay next birth for 2 or more years 70 Figure 6.2 Fertility Preferences among Currently Married Women by Number of Living Children Percent 100 80 60 40 20 0 0 1 2 3 4 5 6+ No. of Living Children ZDHS 1992 Table 6.2 Fertility preferences by age Percent distribution of currently married women by desire for more children, according to age, Zambia I992 Age of woman Desire for children 15-19 20-24 25-29 30-34 35-39 40-44 45-49 Total Have another soon I 32.2 31.6 29.1 27.4 21.4 16.9 8.3 26.3 Have another later ~ 59.8 60.3 50.7 36.6 18.6 8.5 2.6 40.6 Have another, undecided when 1.9 1.2 0.5 0.4 0.6 1.5 1.0 0.9 Undecided 2.5 2.0 6.1 6.7 6.1 2.8 4.2 4.4 Wants no more 2.0 4.2 12.3 24.7 42.8 52.3 61.4 22.0 Sterilised 0.0 0.1 0.2 1.3 6.3 7.3 5.3 2.1 Declared infeeund l . l 0.4 0.9 2.8 4.2 10.4 16.9 3.5 Missing 0.4 0.1 0.2 0.1 0.1 0.3 0.4 0.2 Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 Number 526 989 943 755 537 412 295 4457 1Wants next birth within 2 years awants to delay next birth for 2 or more years Table 6.2 shows similar data according to the age of the woman instead of the number of children. The desire to limit births rises rapidly with age, from two percent of married women age 15-19 to 61 percent of those age 45-49. Conversely, the desire to space births declines with age. In other words, the potential need for family planning services is greatest among older women for limiting childbearing and among 71 younger women for spacing births. The net effect of these two opposing patterns is that the proportion of women falling into one of these two groups is almost constant at about 60-64 percent of women. The desire to stop childbearing shows little variation according to background characteristics of the respondents (see Table 6.3). Urban women are more likely than rural women to want to stop childbearing, especially those women with four or more children. Women in Copperbelt, North-Western and Lusaka Provinces are slightly more likely than women in other provinces to want to stop childbearing, while women in Western and Luapula Provinces appear to be somewhat more pmnatalist. Women with either no education or secondary education are more likely than women with only primary education to want no more children; in other words, the data exhibit a U-shaped pattern of relationship. The positive effect of some primary education on fertility has been widely noted and may be due to enhanced means of support for more children. In any case, the differences in Zambia are small. Table 6.3 Desire to limit (stop) childbearing Percentage of currently married women who want no more children, by number of living children and selected background characteristics, Zambia 1992 Number of living children I Background characteristic 0 1 2 3 4 5 6+ Total Residence Urban 1.6 2.9 11.8 10.2 28.8 39.7 66.3 27.2 Rural 0.6 3.1 4.0 10.7 19.8 28.0 57.7 21.3 Province Centra/ (0.0) 2.9 4.6 10.9 (28.1) 01.1) 66.0 24.3 Copperbelt 1.8 1.9 5.9 9.2 26.4 38.4 67.7 28.0 Eastern 2.0 4.6 9.8 21.2 (30.5) (40.4) 62.8 24.4 Luapula (0.0) 1.2 2.4 4.4 (10.7) (27.9) 48.2 16.2 Lusaka (2.6) 2.3 17.0 11.3 32.3 41.0 61.0 26.6 Northern * 1.2 3.0 5.7 (20.6) (29.0) 61.1 21.7 Nor th-Westem * (12.2) (3.7) (23.7) (27.4) (56.0) 61.4 26.9 Southern 0.0 4.6 7.2 7.7 16.8 21.2 59.7 23.0 Western (0.0) 3.0 (2.0) 3.5 (15.6) (11.7) 46.5 14.0 Education No education Primary Secondary+ 2.0 6.0 7.1 13.0 24.3 31.6 58.9 29.3 0.5 2.1 4.0 8.0 18.0 28.2 61.0 21.5 1.8 3.1 16.2 16.7 43.0 56.7 72.6 27.1 Total 1.0 3.0 7.7 10.5 24.3 33.6 61.8 24.1 Note: Figures in parentheses are based on 25 to 49 women, while an asterisk means the figure is based on fewer than 25 women and h~ been suppressed. Women who have been sterilised are considered to want no more children. 1Includes current pregnancy 6.2 Demand for Family Planning Services Women who are currently married and who say either that they do not want any more children or that they want to wait two or more years before having another child, but are not using contraception, are considered to have an unmet need for family planning, t Women who are using family planning methods are 1 For an exact description of the calculation, see feomote 1, Table 6.4. 72 said to have a met need for family planning. Women with unmet and met need constitute the total demand for family planning. Table 6.4 presents data on unmet need, met need and total demand for family planning, according to whether the need is for spacing or limiting birtha. One-third of married Zambian women have an unmet need for family planning services, 21 percent for spacing purposes and 12 percent for limiting births. Combined with the 15 percent of married women who arc currently using a contraceptive method, the total demand for family planning comprises almost half of the married women in Zambia. Thus, if all women who say they want to space or limit their children were to use methods, the contraceptive prevalence rate could be increased from 15 percent to 49 percent of married women. Presently, only one-third of the potential demand for family planning is being met (last column in Table 6.4). Table 6.4 Need for family planning services Percentage of currently married women with unmct need far family planning, mot need for family planning, and the total demand for family planning services, by selected background charnctcaistics, Zambia 1992 Met need for Unroof need for family planning Total domaod for Percentage family planning I (cm-rcntiy using) 2 family planning of demand Number For For For For For For saris- of spacing limiting Total spacing limiting Total spacing linfiting Total fled wormn Background charnct~dstic Age 15-19 23.9 3.9 27.8 8.5 0.2 8.7 32.3 4.2 36.5 23.8 526 20-24 25.9 3.0 28.9 12.2 0.9 13.1 3g.1 3.9 42.0 31.2 989 2.5-29 26.1 5.4 31.5 12.5 2.8 15.3 38.6 8.2 46.8 32.6 943 30-34 23.0 10.2 33.2 10.9 7.5 18.3 33.9 17.7 51.5 35.6 755 35-39 16,9 22.6 39,5 4,8 17,7 22.5 2L7 40,3 62.0 36,3 537 40-44 9.9 32.4 42.4 1.8 15.6 17.4 11.8 48,0 59.8 29.1 412 45-49 6.6 35.5 42.1 0.4 8.6 9.0 6.9 44.1 51.1 17.6 295 Residence Urban 22.3 12.1 34.4 11.5 9.2 20.8 33.9 21.3 55.2 37.7 2091 Rural 20.5 12.1 32,6 6.7 3.6 10.3 27.2 15.7 42.9 23.9 2366 PrOVinCe (Mnmd 14.4 12.I 26.6 5.5 3.7 9.2 20.0 15.8 35.8 25.7 418 Copperbclt 26.2 13.1 39.3 11.2 7.7 19.0 37.4 20.9 58.3 32,5 1023 Eastern 23.6 t l .6 35,1 6.0 3.7 9.7 29.5 15.3 44.8 21.6 536 Luapnia 17.1 8.4 25.6 5.3 4.2 9.5 22.4 12.6 35.1 27.1 281 Lusaka 18.3 12.2 30,5 11.9 12.3 24.2 30.1 24.5 54.7 44.3 738 Nort~ra 24.1 11.0 35.1 12.8 4.7 17.5 36.9 15.7 52.6 33.3 423 North-Western 20.3 14.1 34.5 5.7 4.7 10.4 26.1 18,8 44.9 23.1 124 Southern 25.0 12.2 37.1 4.7 3.8 8.5 29.7 15.9 45.6 18.6 673 Western 8.2 13.0 21.2 14.1 3.7 17.8 22.3 16.7 39.0 45.7 241 Education No education 17.3 17.3 34.6 3.8 4.2 8.0 21.1 21.4 42.6 18.7 864 Primary 22.9 11.9 34.7 8.5 4.2 12.8 31.4 16.1 47.5 26.9 2754 Secondary 22.4 7.8 30.2 15.1 11.9 27.1 37.5 19.8 57.2 47.3 745 Higher 6.5 4.7 11.2 20.5 37.9 58.5 27.0 42.6 69.6 83.9 93 Total 21.4 12.1 33.4 9.0 6.2 15.2 30.3 18.3 48.6 31.2 4457 1Unmet need for spacing includes pregnant women whose pregnancy was mistimed, amenorrhonic women whose last birth was mistimed, and women who are neither pregnant nor arncnorrho~c and who are not using any method of family planning and say they want to wait 2 or more years for their next birth. Also included in unmet need for spa~mg arc women who arc unsure whether they want another child or who want another child but are unsme when to have the birth. Unmct need for limiting refers to pregnant women whose pregnancy was unwanted, amenorrhonic women who~e last child was unwanted and women who are ncithar pregnant nor amenorrhoei~ and who axe not using any method of family planning and who want no mo~ children. 2Using for spacing is defined as women who are using some method of family planning and say they want to have another child or axe undecided whether to have another. Using for limifng is defined as women who arc using and who want no more children. Note that the specific methods used are not taken into account here. 73 The overallunmet need for family planning increases with age. As expected, unmet need for spacing purposes is higher among younger women, while unmet need for limiting childbearing is higher among older women. There is almost no difference in the level of unmet need among urban and rural women, although it is highest among women in Copperbelt and Southern Provinces. Unmet need is higher among women with no education or only primary schooling than among better educated women. This is primarily due to the fact that much larger proportions of educated women are currently using family planning, leading to a larger percent of their demand being satisfied. An estimate of the actual number of married women with unmet need for family planning services can be calculated by applying the proportions presented in Table 6.4 to the estimated number of women in Zambia. The results of this exercise indicate that approximately 350,000 married women in Zambia are in need of family planning services .2 The number of women in need and the proportion in need for spacing and limiting purposes differ greatly by province (see Figure 6.3). Copperbelt Province has more women in need than any other province, beth because it is the largest province and because it has the highest proportion of women with unmet need. Figure 6.3 Number of Women with Unmet Need for Family Planning Services by Province Central Copperbelt Eastern Luapula Lusaka Northern North-Western Southern Western iiiiiiiiii ii iii!iiiiiii!iiiiiii iiiii i iii l O 20 40 60 80 100 No. of MarrledWomen (in Thousands) ZDHS 1992 2 This number was calculated as follows: the number of women in each province from the preliminary report for the 1990 census (Central Statistical Office, 1990a) was projected from 1990 to 1992 using the growth rates by province (also from the 1990 census report). The proportion of all women who are age 15-49 was calculated using similar data from the ZDHS and the proportion of women age 15-49 who are married was also calculated from ZDHS data. Then the proportions in need for spacing and limiting were applied to these numbers. 74 6.3 Ideal Family Size In the ZDHS, information on what women feel is the ideal family size was elicited through two questions. Women who had no children were asked, "If you could choose exactly the number of children to have in your whole life, how many would that be?" For women who had children, the question was rephrased as follows: "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?" Some women, especially those for whom fertility control is an unfamiliar concept, may have had difficulty in answering this hypothetical question. The data in Table 6.5 indicate that the vast majority of women were able to give a numeric answer to this question; only 6 percent of women gave a non-numeric answer such as "it is up to God," "any number" or "does not know." Those who gave numeric responses generally want to have large families. Almost half (46 percent) of all respondents said they would choose to have six or more children, with an average of 5.8 children. There is a possibility that some women may report their actual number of children as their ideal number, since they may find it difficult to admit that they would not choose to have so many children if they could start afresh. Indeed, women who have fewer children do report smaller ideal family sizes than women with more children. For example, the average ideal family size is 5.2 among women with one child, compared to 7.2 among women with six or more children. Many of the women with fewer children are young and, to the extent that their fertility preferences do not increase over time and that they can realize their ideal number of children, fertility in Zambia may decline. Table 6.5 Ideal number of children Percent distribution of all women by ideal number of children end mean ideal number of children for all women and for currently married women, according to number of living children, Zambia 1992 Number of living children I Ideal number of children 0 1 2 3 4 5 6+ Total 0 0.2 0.1 0.2 0.0 0.2 0.4 0.1 0.2 1 0.8 0.8 0.9 0.4 0.5 0.0 0.3 0.6 2 6.8 5.5 4.6 1.7 3.2 2.1 2.5 4.4 3 7.8 8.4 5.4 4.6 1.4 2.7 2.2 5.4 4 26.2 23.5 24.8 17.7 16.5 11.5 12.0 20.4 5 21.4 23.0 19.9 17.7 11.1 10.3 7.2 17.1 6+ 31,6 33.9 41.3 51.9 61.0 65.6 64.6 45.8 Non-numeric response 5.3 4.8 2.9 6.0 6.1 7.4 11.2 6.2 Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 Number of women 1862 1280 900 741 574 497 1205 7060 Mean ideal number 5.1 5.2 5.4 6.1 6.2 6.6 7.2 5.8 Number of women 1764 1219 874 697 539 461 1070 6624 Mean for women in union 5.9 5.4 5.5 6.1 6.3 6.5 7.2 6.2 Number of women in union 297 778 694 576 455 396 963 4159 Note: The means exclude women who gave non-numeric responses. lIncludes current pregnancy 75 Despite the fact that family size norms are large in Zambia, the data in Table 6.5 show evidence of unwanted fertility. For example, one-quarter of the women with six or more children said that they would ideally like to have fewer than 6 children. Table 6.6 shows the mean ideal number of children for all women by age according to selected background characteristics. The mean ideal family size increases with age, from 5.1 among women age 15-19 to 8.0 among women age 45-49. At every age group, rural women have higher family size norms than urban women. This is reflected in the fact that women in Lusaka have the smallest ideal family sizes on average; women in Western and Northern Provinces have the highest. Ideal family size is negatively related to education level attained; women with no education have the highest family size desires, while women with secondary education have the smallest. Table 6.6 Mean ideal number of children by background characteristics Mean idea/number of children for all women, by age and selected background characteristics, Zambia 1992 Age of woman Background characteristic I5-19 20-24 25-29 30-34 35-39 40-44 4549 Total Residence Urban 4.7 4.8 5.2 5.6 6.1 6.4 7.0 5.2 Rural 5.7 5.9 6.1 6.8 7.4 7.6 8.6 6,4 Province Central 5.4 5.6 5.7 6.2 (7.2) (7.6) * 6,0 Copperbelt 5.0 5.1 5.4 5.8 6.3 6.8 7.5 5,5 Eastern 4,5 4.8 5.2 5.8 (6.3) (6.3) (7.9) 5,3 Luapula 5,9 6.0 6.1 6.9 7.0 (8.2) (8.4) 6.5 Lusaka 4A 4.5 4.7 5,0 5.8 5.7 (5.3) 4,7 Northern 6,2 6.6 6.5 (7.1) (7.3) (7.9) (7.9) 6.8 North-Western 5.3 5.5 5.7 6.1 (7.7) * * 6.0 Southern 5.2 5.5 5,9 6.7 7.1 7.4 (8.5) 6.0 Western 5.9 6.5 6.9 7.6 8.4 (9.3) 10,7 7.4 Education No education 5.6 5.9 6.6 7.0 7.2 7.6 8.6 6.8 Primary 5.3 5.6 5.9 6.4 7.3 7,3 7.9 6.0 Secondary* 4.4 4.5 4.7 4.8 5.2 5,1 * 4.6 Total 5.1 5.3 5.6 6.1 6.7 7,1 8.0 5.8 Note: Figures in parentheses are based on 25 to 49 women, while an asterisk means the figure is based on fewer than 25 women and has bean suppressed. 6.4 Fertility Planning There are two ways of estimating levels of unwanted fertility from ZDHS data. One is based on responses to a question on whether each birth in the five years before the survey was planned (wanted then), mistimed (wanted, but at a later time), or unwanted (wanted no more children). These data are likely to result in underestimates of unplanned childbearing, since women may rationalize unplanned births and declare them as planned once they are born. The other method of measuring unwanted fertility utilizes the data on ideal 76 family size to calculate "wanted" fertility rates. These too, may suffer from underestimation to the extent that women are unwilling to report an ideal family size lower than their actual family size. Table 6.7 shows the percent distribution of births in the five years before the survey by whether the birth was wanted then, wanted later, or not wanted. Only 7 percent of recent births were reported to be unwanted, while 26 percent were reported as mistimed (wanted later). Fourth and higher births are more likely than first, second or third births to be unwanted. Similarly, a much larger proportion of births to older women are unwanted--almost 30 percent among women in their 40s. Table 6.7 Fertility planning status Percent distribution of births in the five years preceding the survey by fertility planning status, according te birth order and mother's age, Zambia 1992 Planning stems of birth Birth order Wanted Number and mother's Wanted Wanted no of age then later more Missing Total births Birth order 1 70.8 22.6 5.8 0.8 100.0 1597 2 72.4 23.9 2.9 0.8 100.0 1253 3 70.4 26.8 2.4 0.4 100.0 988 4+ 59.5 28.2 11.3 1.0 100.0 3322 Age at birth <20 66.9 26.7 5.8 0.6 100.0 1516 20-24 70.0 26.1 3.0 0.9 100.0 2072 25-29 68.8 26.1 4.1 1.0 100.0 1590 30-34 60.6 28.7 9.8 0.9 100.0 1085 35-39 54.4 25.0 19.9 0.7 100.0 593 40-44 55.6 14.2 29.4 0.8 100.0 269 45-49 (61.3) (10.3) (28.4) (0.0) 100.0 36 Total 65.8 26.0 7.4 0.8 100.0 7160 Note: Table includes current pregnancies. Table 6.8 presents wanted fertility rates. The wanted fertility rate is calculated in the same manner as the total fertility rate, but unwanted births are excluded from the numerator. For this purpose, unwanted births are defined as those which exceed the number considered ideal by the respondent. (Women who did not report a numeric ideal family size were assumed to want all their births.) This rate represents the level of fertility that would have prevailed in the three years preceding the survey if all unwanted births bad been prevented. A comparison of the total wanted fertility rate and the actual total fertility rate suggests the potential demographic impact of the elimination of unwanted births. The wanted total fertility rate was 5.4 for Zambia as a whole, one child lower than the actual total fertility rate. Moreover, this difference of approximately one child between the wanted and actual total fertility rates is apparent for all categories of background characteristics. The only exception is among women in Western Province, where there appears to be less unwanted fertility than in other provinces. 77 Table 6.8 Wanted fertillcy rates Total wanted fertility rates and total fertility rates for the three years preceding the survey, by selected background characteristics, Zambia 1992 Total wanted Total Background fertility fertility characteristic rate rate Residence Urban 4.7 5.8 Rural 6.2 7.1 Region Copperbelt 5.0 6.2 Eastern, Central 5.7 6.8 Lusaka 4.5 5.5 Luapula, Northern 6.4 7.4 Southern 6.0 7.1 North-Western, Western 5.5 6.0 Education No education 6.3 7.1 Primary 5.7 6.8 Secondary+ 3.9 4.9 Total 5.4 6.5 Note: Races are based on bir01s to women 15-49 in the period 1-36 months preceding the survey. The total fertility rates are the same as those presented in Table 3.3. Some provinces have been grouped Cogefl~er co increase sa~nple sizes. 78 CHAPTER 7 INFANT AND CHILD MORTALITY According to the 1980 Census of Population and Housing, over 20 percent of Zambia's population consists of children below the age of five. This proportion is large enough to draw attention to any analysis on the situation of children's health. Furthermore, infant and particularly childhood mortality rates are basic indicators of a country's socioeconomic situation in terms of the quality of life. This is because children are the most vulnerable members of any society. This chapter presents information on childhood mortality in Zambia, especially on levels, trends and differentials in neonatal, postneonatal, infant and child mortality. Disaggregation of this information by sex, socioeconomic characteristics, province and other factors helps in identifying segments of the population requiring special attention. This makes health programme monitoring and evaluation easier. Mortality estimates can also prove useful in making population projections and in identifying those sectors of the child population that are at high risk. 7.1 Assessment of Data Quality The estimates of infant and child mortality are based on information from the birth histories of interviewed individual women. For each reported live birth, information was collected on the month and year of birth, sex, survivorship status and among dead children, age at death. This information has been used to calculate the following period probabilities of dying for three five- year periods---1977-81, 1982-86, and 1987-91: Neonatal mortality: Postneonatal mortality: Infant mortality: Child mortality: Under-five mortality: the probability of dying within the first month of life; the difference between infant and neonatal mortality; the probability of dying before the first birthday; the probability of dying between the first and fifth birthday; the probability of dying between birth and the fifth birthday. The reliability of mortality estimates calculated from retrospective birth histories depends upon the completeness with which deaths ofch'tldren are reported and the extent to which birth dates and ages at deaths are accurately reported and recorded. Since the ZDHS data imply that childhood mortality has increased in the 15 years prior to the survey, it is important to look at some basic quality checks of the data. Although ZDHS data relating to infant and child mortality are in general of good quality, they may still suffer from several deficiencies which could lead to biased interpretation of the results. Underreporting of infant deaths in particular is usually most severe for deaths which occur very early in infancy. If early neonatal deaths are selectively underreported, the result would be an abnormally low ratio of deaths under seven days to all neonatal deaths and an abnormally low ratio of neonatal to infant mortality. Changes in these ratios over time can be examined to detect the hypothesis that underreporting of early infant deaths is more common for births that occurred longer before the survey. Results from Table 7.1 suggest that early infant deaths have not been severely underreported in the ZDHS, since the ratios of deaths in the first 6 days to all neonatal deaths (top row) are quite high (a ratio of less than 25 percent is often used as a guideline to indicate underreporting of early neonatal deaths). However, the ratios increase substantially overtime, from 49 to 67 percent, implying that some early infant 79 deaths were not reported by older women. The percentages of infant deaths that occurred during the neonatal period 0ower row in Table 7.1) are reasonable and show no evidence of selective underreporting over time. Misreporting of age at death will bias esti- mates of the age pattern of mortality if the net result of the misreporting is the transference of deaths between age segments for which rates are ca/culated; for example, an overestimate of child mortality relative to infant mortality may result if children dying during the first year of life are reported as having died at age one or older. There was some misreporting of age at death due to preference for reporting ages at death of 7, 14, and 21 days, corresponding to one, two, and three weeks respectively (see Appendix Table C.5). In fact, the preference for reporting deaths at age 7 days is stronger for the period 10-14 years before the survey and accounts for some of Table 7.1 Indices for detecting underreporting of infant deaths Percentage of neonatal deaths reported to occur at age 0-6 days and percentage of infant deaths reported to occur at age under one month for five-year periods preceding the survey, Zambia 1992 Time period of death (years preceding survey) Percentage of deaths 0 ~, 5-9 10-14 Percentage of neonatal deaths occurring at 0-6 days of age Percentage of infant deaths occurring under one month of age 67.4 57.5 48.7 42.4 42.1 40.2 the apparent increase over time in the percentage of neonatal deaths occurring at ages 0-6 days. There was surprisingly little "heaping" on particular months of death, and due to strong emphasis during training, there were very few deaths reported to have occurred at age one year (see Appendix Table C.6) /making any adjustment in infant and child mortality rates unneccessary. This brief check on internal consistency of the ZDHS childhood mortality data indicates that there is no serious underreporting of deaths during the time periods for which the mortality rates are estimated and that though there is some evidence of heaping in age at death at certain ages, the bias in infant and child mortality rates arising from this heaping is negligible. It is seldom possible to establish, with confidence, mortality levels for a period more than 15 years before a survey. Even within the recent 15-year period considered here, apparent trends in mortality rates should be interpreted with caution, for several reasons. First, there may exist differences in the completeness of death reporting related to the length of time before the survey. Second, the accuracy of reports of age at death and of date of birth may deteriorate systematically with time. The third reason relates to truncation of mortality rates further back in time, because women age 50 and over who were bearing children during these periods were not included in the survey. This truncation particularly affects mortality trends. For example, for the period 1977-1981 (10-14 years before the survey), the rates do not include any births for women 40-49 since these women were over 50 at the time of the survey and not eligible for interview. Since these excluded births to older women were likely to be at a somewhat greater risk of dying than births to younger women, the mortality levels for the period may be slightly underestimated. However, the ratio for later periods are less affected by the truncation bias since fewer otder women are excluded. Thus, without a detailed evaluation of birth history data quality (which is not attempted in this report), conclusions regarding changes in mortality should be considered preliminary. However, attempts should be made later to compare estimates from the 1990 census with those from the ZDHS. Interviewers in the ZDblS were instructed to record the age at death in months for all children who died under age two years and in days for all children who died under one month of age. 80 Finally, it is important to note that the use of birth histories to estimate childhood mortality rates probably results in underreporting of deaths due to mutually fatal congenital diseases such as AIDS. This is because the respondent for the information on child deaths is the mother herself; if her child has died of AIDS, she herself may also have died and thus, the child's death cannot be reported. The methodology of measuring childhood mortality through mothers' birth histories rests on the assumption that maternal mortality is low and that there is little or no correlation between the mortality risks of mothers and their children. In countries with high death rates due to AIDS, these assumptions do not hold and the resulting childhood mortality rates are probably underestimated to some degree. 7.2 Levels and Trends in Infant and Child Mortality In the five years preceding the survey (i.e., in the period 1987-1991), nearly 1 in 5 Zambian children died before their fifth birthday (see Table 7.2). Child mortality (at age 1-4 years) is almost as high as the level of infant mortality (94 vs. 107). Table 7.2 Infant and child mortality Infant and child mortality rates by five-year periods preceding the survey, Zambia 1992 Yoar$ preceding survey Neonatal Posmeonatal Infant Child Under-five mortality mortality mortality mortality mortality (NN) (PNN) (lqe) (4q3 (~qo) 0-4 42.5 64.7 107.2 93.6 190.7 5-9 37.1 50.5 87.6 81.7 162.2 10-14 31.6 47.9 79.5 78.8 151.9 One of the most striking findings from the ZDHS is the apparent downturn in child survival prospects over the last decade. From 1977-81 to 1987-91, under-five mortality has risen 15 percent from 152 to 191 per 1000 live births. Much of this increase resulted from an increase in mortality under the age of one year. Both neonatal and postneonatal mortality increased by 35 percent in the 15-year period before the survey. In this same period child mortality increased by almost 20 percent. The infant mortality rate of 107 calculated from the ZDHS data is also considerably higher than the rate of 97 estimated from the 1980 census (see Table 1.1). The rate had been projected to drop to 90 by 1990. Analysis of the actual 1990 census data should shed some light on levels and trends in childhood mortality. These findings may signal the beginning of an era of increased early childhood mortality in Zambia (and perhaps in other parts of sub-Saharan Africa) in which deteriorating economic conditions, coupled with the spread of new infections such as HIV/AIDS, have led to the breakdown of infrastructures and institutions that at one time supported the downward trend in childhood mortality. In summary, child survival in Zambia is much worse today than it was 10 years ago. 81 7.3 Socioeconomic Differentials in Infant and Child Mortality This section presents early childhood mortality indicators by selected background characteristics of the mother for the 10-year period preceding the survey. A 10-year reference period is used to allow adequate numbers of events in each population subgroup. Early childhood mortality rates are shown in Table 7.3 by urban-mral residence, province (grouped for more reliable estimates), mother's level of education and medical maternity care. Table 7.3 Infant and child mortality by background characteristics Infant and child mortality rates for the ten-year period preceding the survey, by selected background characteristics, Zambia 1992 Background ch~acteristic Neonatal Postneonatal Infant Child Under-five mortality mortality mortality mortality mortality (NN) (PNN) qqo) (4q0 (sqo) Residence Urban 31.7 46.3 78.0 78.9 150.8 Rural 47.3 68.5 115.8 96.6 201.2 Province Copperbelt 22.3 46.6 68.9 80.8 144.2 Eastern, Central 50.6 63.5 114.1 108.2 210.0 Lusaka 32.0 44.7 76.8 69.3 140.8 Luapula, Northern 55.1 93.4 148.5 112.6 244.4 Southern 33.7 36.8 70.5 68.5 134.2 North-Western, Western 59.9 72.1 132.0 90.2 210.3 Education No education 46.7 68.1 114.9 101.2 204.4 Primary 39.5 59.2 98.7 92.1 181.7 Secondary+ 35.0 44.3 79.4 60.2 134.8 Medical maternity care 1 No antenatal/delivery care (79.9) (108.9) (188.8) * (299.5) Either antenatal or delivery 41.8 62.3 104.1 88.9 183.7 Both antenatal & delivery 38.2 63.1 101.3 83.0 175.8 Total 40.0 58.2 98.2 88.1 177.6 Note: Rates based on 250-499 cases (exposed children) are enclosed in parentheses. Rates based on fewer than 250 cases are suppressed and marked with an asterisk. 1Rates for the five-year period before survey. Medical care is that given by a doctor, nurse, trained midwife or received in a hospital, clinic or health centre. Children in rural areas of Zambia experience 33 percent higher risk of dying before their fifth birthday than urban children. This urban-rural differential is larger during infancy (50 percent higher rural risk) than during the 1 to 5 year age period (22 percent), and may be explained by the relative unavailability of antenatal and delivery services in the more remote, rural settings. In other words, whereas one in 13 children in urban areas dies before their first birthday, the ratio for the rural areas is one in 9 children (see Figure 7.1). 82 Figure 7.1 Infant Mortality Rates by Background Characteristics RESIDENCE Urban Rura l PROVINCE Copperbnlt Cent ra l , Eas tern Lusaka Luapula, Northern Southern Nor th -West , Western EDUCATION No Educat ion P r imary~ Secondary+ 0 78 . . . . . 1 1 6 . . . . . 69 114 , 7 7 149 . . . 7 1 . . . . . 132 115 , . 99 . " , . . 79 50 100 150 200 Deaths per 1,000 Births ZDHS 1992 Differences in mortality rates by province are also quite marked. Childhood mortality is highest in Northem/Luapula Provinces, where almost 25 percent of children do not live to see their fifth birthday. Eastern/Central and North-Westem/Western Provinces also have high childhood mortality, Mortality is lowest in Southem Province with an estimate of 134 deaths under age five per 1000 live births. The pal:tem of higher infant than child mortality is common among all Zambia's provinces except Copperbelt Province. The pattern in Copperbelt Province might be due to the fact that the bulk of the work force in this province obtains health care through the copper mining companies; this may have a more favourable effect on infant than on child mortality. All early childhood mortality rates are higher for women with little or no education, presumably in part because they have more limited access to basic health services. Children born to uneducated mothers are 50 percent more likely to die before their fifth birthday than their counterparts born to mothers with secondary or higher education. The strength of the relationship increases with increasing age of the child at risk. Maternal care during pregnancy and dertvery is associated with childhood mortality. Children born to women who obtained both antenatal and delivery care from a medically-trained person have lower mortality rates at every age than children whose mothers received only antenatal or delivery care. (Although the sample of chitdren whose mothers received neither type of care is small, the rates are so high as to be compelling.) 7.4 Demographic Differentials in Infant and Child Mortality This section examines differentials in early childhood mortality by various demographic charactetistics of both the child and the mother. Table 7.4 presents mortality rates for the ten years preceding the survey by sex of child, age of mother at birth, b i~ order, length of the previous birth interval and size of the child at birth. 83 Table 7.4 Infant and child mortality by demographic characteristics Infant and child mortality rates for the ten-year period preceding the survey, by selected demographic characteristics, Zambia 1992 Neonatal Posmeonatal Infant Child Under-five Demographic mortality mortality mortality mortality mortality characteristic (NN) (PNN) (tq0) (4ql) (sqo) Sex of child Male 46.3 59.9 106.2 91.3 187.8 Female 33.9 56.5 90.3 85.1 167.8 Age of mother at birth < 20 53.3 69.8 123.2 110.1 219.7 20-29 36.0 56.4 92.4 85.0 169.5 30-39 34.4 52.7 87.1 76.2 156.6 40-49 (53.8) (47.7) (101.5) (79.8) (173.2) Birth order 1 50.8 70.8 121.5 104.6 213.4 2-3 35.2 60.9 96.2 92.6 179.8 4-6 35.3 50.7 86.0 74.8 154.4 7+ 42.6 51.3 93.9 84.9 170.8 Previous birth Interval < 2 yrs 70.0 85.8 155.8 104.5 244.0 2-3yrs 28.3 48.2 76.5 80.1 150.5 4 yrs + 20.1 36.0 56.1 69.5 121.7 Size at birth 1 Very small * * * * * Smaller than average 122.2 (78.3) (200.5) (131.6) 305.8 Average or larger 28.4 64.1 92.4 84.4 169.0 Note: Rates based on fewer thma 250499 cases (exposed children) are enclosed in parentheses. Those based on fewer than 250 cases are suppressed and marked with an asterisk. tRates for the five-year period preceding the survey. It is well established that male children are at increased mortality risk both before and shortly after birth, presumably due to genetic factors. This is true of Zambian male children who are 12 percent more likely to die before their fifth birthday than their female counterparts. Although male mortality exceeds female mortality for every age interval studied, the differences are largest for the neonatal period; during the first month of life, male children are 37 percent more likely to die than female children (46 vs. 34 deaths per 1000 births). Afterwards, the differential diminishes to negligible levels. Male children are only 18 percent more likely to die during infancy than their female counterparts. The relationship between mother's age at the time of birth and childhood mortality exhibits the expected curvilinear pattern. In other words, the highest mortality occurs for children of very young mothers and mothers nearing the end of their reproductive lives (see Figure 7.2). This pattern can be observed for all 84 Figure 7.2 Infant Mortality Rates by Demographic Characteristics AGE OF MOTHER <20 20-29 30-39 40-49 PRIOR BIRTH INTERVAL <2 years 2-3 years 4 years+ i 0 . ,, 123 - 92 87 102 156 r7 se 50 100 150 200 Deaths per 1,000 Births ZDHS 1992 mortality rates in Table 7.4 except for postneonatal mortality, where the rate is slightly lower for women age 40-49 than that of women 30-39. This pattern is most pronounced in the first month of life and much less pronounced during the 1 to 5 year age period. Rates for the oldest women should be viewed with caution, since they are based on a relatively small number of births. Since birth order of the child and maternal age are highly correlated, it is not surprising to fred mortality risks to be greater among first births (which are generally to young mothers) and birt.hs of order seven or higher (which are generally to older mothers). Moaality differentials by birth order are more pronounced among neonates and infants where first births are 44 and 26 percent more likely to die than second and third children, respectively. Shorter birth intervals are associated with higher mortality both during and after infancy. This is particularly true within the first month of life, when children born less than two years after a previous birth are three and a half times more likely to die than babies born four or more years after the previous birth. The birth interval effect on moaality risk persists after the neonatal period, but with diminished strength. During infancy, children born less than two years after a previous birth are almost three tunes more likely to die than their counterparts born four or more years after the previous birth. These differentials suggest that mort~ity risks for Zambian children, particularly those born to young mothers, would be substantially reduced if birth intervals were increased, possibly through family plauning. Children who are perceived by their mothers to be smaller than average at birth experience higher mortality rates than children perceived to be average or larger, particularly in their first month of life and in infancy. The patl:ern is consistent among all rates in the table. Since only two percent of babies are considered to be very small at birth (see Table 8.6 in next chapter), there are too few cases to make reliable mortality estimates. 85 7.5 High.Risk Fertility Behaviour Infants and ch i ldren have a greater probabi l i ty o f dy ing i f they are 10om to mothers who are too young or too old, i f they are born after a short birth interval or i f they are o f h igh birth order. Tab le 7.5 presents the distr ibut ion o f ch i ldren born in the f ive years preceding the survey accord ing to the above categor ies o f increased r isk o f infant and chi ld mortal i ty. In this analysis, a mother is c lass i f ied as "too young" i f she is less than 18 years o f age and "too old" i f she is over 34 years o f age at the t ime o f del ivery. A "short birth Table 7.5 High-risk fertility behaviour Percent distribution of children born in the five years preceding the survey who are at elevated risk of mortality, and the percent distribution of currently married women at risk of conceiving a child with an elevated risk of mortality, by category of increased risk, Zambia 1992 Births in last 5 years preceding the survey Percentage of currently Risk Percentage Risk married category of births ratio women a Not in any high-risk category 37.4 1.0 24.7 b Single high-risk category Mother's age < 18 9.0 1.2 1.4 Mother's age > 34 0.1 * 1.5 Birth interval < 24 6.2 (1.3) 11.3 Birth order > 3 28.0 0.8 18.9 Subtotal 43.2 0.9 33.0 Multiple high-risk category Age <18 & birth interval <24 c 0.5 * 0.5 Age >34 & birth interval<24 0.0 * 0.0 Age >34 & birth order>3 11.0 0.7 21.0 Age >34 & birth interval <24 & birth order >3 1.6 * 5.9 Birth interval <24 & birth order >3 6.3 (1.4) 14.8 Subtotal 19.4 1.0 42.2 In any high-risk category 62.6 0.9 75.3 Total 100.0 NA 100.0 Number 6215 NA 4457 Note: Risk ratio is tim ratio of the proportion dead of births in a specific high-risk category to the proportion dead of births not in any high-risk category. Figures in parentheses are ratios based on 250-499 cases. An asterisk means the data are based on fewer than 250 cases and have been suppressed. NA = Not applicable aWomen were assigned to risk categories according to the status they would have at the birth of a child, if the child were conceived at the time of the survey: age less than 17 years and 3 months, age older than 34 years and 2 months, latest birth less than 15 months ago, and latest birth of order 3 or higher. blncludes sterilised women Clncludes the combined categories Age <18 and birth order >3. 86 interval" means the birth occurred less than 24 months after the previous birth and a child is considered of "high birth order" if the mother had previously given birth to three or more children. In the table, births are divided into two major categories: those falling into a single high-risk category (such as those born to mothers below the age of 18 or over the age of 34, those born after an interval of less than 24 months and those of birth order 4 or higher) and those falling into a multiple high-risk category (such as those born to mothers below the age of 18 and bom after an interval of less than 24 months or those born to mothers over the age of 34 and of birth order over 3). The data show that, while 63 percent of children in Zambia are at elevated risk of mortality due to their mother's fertility behaviour, only 37 percent am free from such risk. Births in the single high-risk categories (43 percent) are more than double those in the multiple high-risk categories (19 percent). It is evident from the table that birth order higher than 3 is the major factor contributing to elevated mortality risks. Almost half of the births (47 percent) are at risk because of high birth order. An even larger proportion of married women (61 percent) are at risk of conceiving a child of birth order over three. Fifteen percent of babies bom in Zambia are at elevated risk of mortality because they are born after an interval of less than 24 months. Thirteen percent of babies are at risk because their mothers are over age 34 when they are born and a further 10 percent are at risk because their mothers are under age 18. The table also presents the relative risk of mortality of children bom in the last five years by comparing the proportion dead of births in each risk category to the proportion dead of births with no risk factor. This risk ratio is shown in the second column of Table 7.5. The ratios show no significant differences among categories. It is interesting to note that three-quarters of currently married women are at risk of conceiving a child with an elevated risk of mortality. This proportion is higher than that for births. To reduce the number of high-risk births, there is need for a concerted effort to generate demand for family planning, pa~icularly to limit births of higher parity. This, together with improved availability of contraceptive methods to couples, would reduce high risk births, which in tum would reduce childhood mortality. 87 CHAPTER 8 MATERNAL AND CHILD HEALTH This chapter presents findings in three areas of importance to maternal and child health: matemal care and characteristics of the newborn, vaccinations, and common childhood illnesses and their treatment. Coupled with information on neonatal and infant mortality rates, this information can be used to identify subgroups of women whose babies are "at risk" because ofnonuse nfmatemal health services, and to provide information to assist in the planning of appropriate improvements in services. Data were obtained for all live births which occurred in the five years preceding the survey. 8.1 Antenatal Care and Delivery Assistance Table 8.1 shows the percent distribution of births in the five years preceding the survey by source of antenatal care received during pregnancy, according to maternal and background characteristics. Table 8.1 Antenatal care Percent distribution of births in the five years pa'eceding the survey, by source of matenatal care during pregnancy, according to selected background characteristics, Zambia 1992 AnU~natal care provider 1 Trained Traditional Background nurse/ birth characteristic Doctor Midwife attendant No one Missing Total Number Mother's age at birth <20 3.6 88.4 lA 6.8 O.l 100.0 1327 20-34 4.7 88.3 1.2 5.7 0.2 1000.0 4095 35t 5.8 84.2 0.9 8.8 0.3 100.0 788 Birth order 1 4.9 87.3 1.3 6.4 0.1 100.0 1390 2-3 4.7 88.8 1.1 5.3 0.1 100.0 1917 4-5 4.0 88.2 1.5 6.0 0.2 100.0 1242 6+ 4.7 86.7 0.8 7.6 0.2 100.0 1662 Residence Urban 6.9 91.1 0.0 1.8 0.1 100.0 2885 Rural 2.6 84.8 2.1 10.2 0.2 100.0 3326 Province Central 9.6 79.6 0.0 10.8 0.0 100.0 595 Copperbalt 7.3 90.7 0.0 2.0 0.1 100.0 1429 Eastem 4.0 88.9 1.8 5.0 0.3 100.0 669 Luapnla 0.6 86.6 2.5 10.0 0.3 100.0 419 Lusaka 5.3 93.8 0.0 0.8 0.0 100,0 935 Northern 2.4 75.0 1.4 21.3 0.0 100.0 647 North-Western 4.4 85.6 0.9 8.8 0.2 100.0 172 Southern 2,0 94.4 0,3 3.0 0.3 100,0 1008 Western 1.0 78.0 10.6 9.9 0.4 100.0 337 Mother's education No education 2.1 78.9 1,7 16.9 0.4 100.0 1061 Primary 3.7 89.8 1.2 5.1 0.1 100.0 3907 Secondary 8.7 89.5 0.5 1.3 0.0 100.0 1138 Higher 19.6 80.4 0.0 0.0 0.0 100.0 103 Total 4.6 87.8 1.2 6.3 0.2 100.0 6211 Note: Figures are for births in the period 1-59 months preceding the survey. 1If the respondent mentioned m~e than one provider, only the most qualified provider is considered. 89 Interviewers were instructed to record all persons a woman may have seen for care, but in the table, only the provider with the highest qualification is considered (if more than one person was seen). For nine in ten births, mothers received antenatal care from a doctor, trained nurse or midwife. Women received antenatal care from a traditional birth attendant (TBA) for only 1 percent of births and no antenatal care at all for 6 percent of births (see Figure 8.1). Thus, almost all Zambian women receive antenatal care and they rely mostly on a nurse or midwife (88 percent) or a doctor (5 percent). There are differences in the sources of antenatal care for births in urban and rural areas. Whilst nearly all the births to urban women receive antenatal care from medically trained providers (98 percent), 10 percent of births to rural women receive no antenatal care at all. Also, births to urban women are more likely to have received antenatal care from a doctor. There are several factors underlying this pattem: rural women may not have access to antenatal care facilities, or they may not be aware of the importance of antenatal care, or they may not be able to afford to pay for costs involved in obtaining the care (transport, fees). Figure 8.1 Antenatal Care, Tetanus Vaccinations, Place of Delivery, Delivery Assistance ANTENATAL CARE Doctor Nurse/Midwi fe No One TETANUS VACCINATION None One Two or More PLACE OF DELIVERY Health Faci l i ty Home DELIVERY ASSISTANCE [ Doctor Nurse /M dw fe Trad. Birth Attend, Relat ive/Other No One Note: Based on births In the five years preceding the survey. 5 88 ~s 60 80 100 Percent ZDHS 1992 ~ 1 9 . . 42 • 39 - -~ 46 . . . . . . . . . 49 [ l s 49 , ~ 9 33 0 20 40 Births to women in Lusaka, Copperbelt and Southem Provinces are more likely than births in other provinces to receive antenatal care from a doctor and births to women in Northern, Central, Luapula, Western and North-Western Provinces are more likely than births to women in the other provinces to receive no antenatal care at all (9 to 21 percent, compared to 5 percent or less). Women in Westem Province rely to some significant degree on traditionalbirth attendants for antenatalcare, whereas none of the births to women in the more urbanised provinces of Central, Copperbelt and Lusaka received care from traditional birth attendants. There is a strong association between education and receiving antenatal care. Births to women with no education are more likely to receive no antenatal care, whereas it is unlikely that a birth to a woman with secondary or higher education will receive no antenatal care. As the mother's level of education increases, so does the likelihood that she will be seen by a doctor during the pregnancy; 2 percent of births to mothers 90 with no education received antenatal care from a doctor, compared to 20 percent of births to women with more than secondary education. Antenatal care can be more effective when it is sought early in the pregnancy and continues through to parturition. Obstetricians generally recommend that antenatal visits be made on a monthly ba- sis to the 28th week (7th month), fortnightly to the 36th week (8th month) and then weekly until the 40th week (until birth). Regular visits allow proper monitoring of the mother and the child throughout the pregnancy. If the first antenatal visit is made at the third month of pregnancy, this schedule translates to a total of 12 to 13 visits dur- ing the pregnancy. Information about the number and timing of visits made by pregnant women is presented in Table 8.2. In 69 percent of births, mothers made four or more antenatal care visits, indicating women are aware of the importance of regular attendance. Nonetheless, for a large proportion of births (almost one-quarter), mothers made few- er than four visits; the median number of antenatal care visits was five, far fewer than the recommended number of 12. Delayed initia- tion of visits contributes to the low frequency of attendance. Nearly six in ten births received some antenatal cam before the 6th month of gestation (see Table 8.2). The median duration of gestation at which the first antenatal care visit was made was 5.6 months. This is rather late if mothers are to receive the maximum benefits of antenatal care. The advantage of starting antenatal care within the first three months of pregnancy is that a woman's normal Table 8.2 Number of antenatal cme visits and sta~e of l)regnaney Percent distribution of live births in the last 5 years by number of antenatal care (ANC) visits, and by the stage of pregnancy at the time of the first visit, Zambia 1992 Antenatal visits/ Stage of Fregnancy All at first visit births Number of ANC visits 0 6.3 I 2.0 2-3 20.6 4+ 68.5 Don't know, missing 2.6 Total I00.0 Median no. of visits 5.3 Number of meeths pregnant at the time of first ANC visit No antenatal care 6.3 <= 5 months 56.8 6-7 months 34.4 8+ months 2.1 Don't know, missing 0.4 Total I00.0 Median number of months pregnant at fast visit 5.6 Number of live births 6211 Nora: Figures are for births in the period 1-59 months preceding the survey. health can be assessed. Knowledge of a woman's normal health will make early detection of any abnor- malilies easier, this, in turn, assists health workers in taking appropriate action to care for the mother. An important component of antenatal care in Zambia is ensuring that pregnant women are adequately protected against tetanus. Tetanus toxoid injections are given during pregnancy for prevention of neonatal tetanus, one of the principal causes of death among infants in many developing countries. For full protection, a pregnant woman should receive two doses of the toxoid. However, if a woman has been vaccinated during a previous pregnancy, she may only require one dose for a current pregnancy. Table 8.3 presents data on tetanus toxoid coverage during pregnancy for all births in the five years preceding the ZDHS. Thirty-nine percent of births received the protection of two or more doses of tetanus toxoid during gestation, while 42 percent received protection from one dose and 19 percent were not protected by any tetanus toxoid vaccination. Births occurring in the rural areas are about twice as likely to have received no protection by the vaccination than those in the urban areas. There are no marked provincial differentials in the proportion of births whose mothers received two or more tetanus toxoid doses during gestation, but the probability of births not being protected against neonatal tetanus at all is greater in Western, Luapnia, Central, and North-Western Provinces and it is particularly high in Northern Province (38 percent of births with no antenatal tetanus vaccination). 91 Table 8.3 Tetanus toxoid vaccination Percent disa'ibution of births in the five years preceding the survey, by number of tetanus toxoid injections given to the mother during pregnancy and whether the respondent received an antenatal card, according to selected background characteristics, Zambia 1992 Number of tetanus toxoid injections Percentage Two given Number Background One doses Don't know/ antenatal of characteristic None dose or more Missing Total card births Mother's age at birth < 20 19.1 41.3 39.5 0.1 100.0 92.7 1327 20-34 17.7 42.0 39.6 0.7 100.0 94.0 4095 35+ 22.0 40.7 36.6 0.7 100.0 90.2 788 Birth order 1 18.5 39.7 41.4 0.4 100.0 93.2 1390 2-3 18.1 40.9 40.5 0.5 100.0 94.4 1917 4-5 17.7 44.5 36.9 0.9 100.0 93.5 1242 6+ 19.6 42.3 37.5 0.6 100.0 91.8 1662 Residence Urban 12.8 45.8 41,0 0.5 100.0 97.9 2885 Rural 23.5 38.2 37.6 0.7 100.0 89.2 3326 Province Central 21.5 33.9 43.6 0.9 100.0 89.0 595 Copperbelt 13.2 47.7 38.7 0.4 100.0 97.7 1429 Eastern 16.4 41.5 41.6 0.5 100.0 94.0 669 Luapula 22.3 42.0 35.2 0.5 100.0 89.4 419 Lusaka 14.6 46.8 38.0 0.6 100.0 99.2 935 Northern 38.4 29.9 31.5 0.2 100.0 78.1 647 Nor th-Westem 20.8 41.1 37.7 0.5 100.0 90.9 172 Southern 13.0 42.1 43.9 1.1 100.0 96.7 1008 Western 23.7 38.0 38.1 0.2 100.0 88.6 337 Mother's education No education 32.8 36.3 30.4 0.5 100.0 81.9 1061 Primary 17.0 43.6 38.8 0.6 100.0 94.6 3907 Secondary 10.8 41.4 47.1 0.7 100.0 98.6 1138 Higher 13.3 28,4 58.3 0.0 100.0 100.0 103 All births 18.5 41.7 39.2 0.6 100.0 93.2 6211 Note: Figures are for births in the period 1-59 months preceding the survey. There is a direct relationship between education of mothers and vaccination status; the proportion of live births for which two or more doses of tetanus toxoid were received increases steadily from 30 percent among women with no education, to 58 percent of births to women with more than secondary education. Conversely, the proportion of births for which no tetanus vaccination was received decreases with higher education levels. Educated women may have greater accessibility to modem medical care, or may have a better understanding of the benefits of vaccinations, or may be more able to utilise the services provided. 92 Table 8.4 Place of delivery Perce.m distribution of births in the five years preceding the survey, by place of delivery, according to selected background characteristics, Zambia 1992 Place of delivery Number Background Health At Don't know/ of characteristic facility home Other Missing Total births Mother's age at birth < 20 50.6 48.9 0.3 0.2 100.0 1327 20-34 52.2 47.2 0.4 0.3 100.0 4095 35+ 43.1 56.1 0.7 0.1 100.0 788 Birth order l 57.9 41.4 0.5 0.2 100.0 1390 2-3 49.6 50.1 0.2 0.2 100.0 1917 4-5 50.4 48.9 0.4 0.3 100.0 1242 6+ 46.1 53.0 0.6 0.3 100.0 1662 Residence Urban 78.8 20.9 0.0 0.3 100.0 2885 Rural 26.3 72.7 0.7 0.2 100.0 3326 Province Central 39.2 60.8 0.0 0.0 100.0 595 Copperbelt 79.7 20.0 0.0 0.3 100.0 1429 Eastern 36.3 60.4 2.7 0.7 100.0 669 Luapula 36.1 62.9 0.5 0.6 100.0 419 Lusaka 76.2 23.7 0.l 0.0 100.0 935 Northern 19.2 80.7 0.2 0,0 100.0 647 North-We.stem 54.1 45.4 0.2 0.2 100.0 172 Southern 33.9 65.8 0.1 0.2 100.0 1008 Western 32.8 66.4 0.4 0.4 100.0 337 Mother's education No education 22.4 76.5 0.6 0.6 100.0 1061 Primary 48.1 51.3 0.4 0.2 100.0 3907 Secondary 81.8 17.9 0.2 0.1 100.0 1138 Higher 95.7 4.3 0.0 0.0 100.0 103 Antenatal care visits None 2.5 95.1 0.7 1.7 100.0 392 1-3 visits 34.0 65.8 0.2 0.0 100.0 1401 4 or more visits 60.6 39.0 0.4 0.0 100.0 4255 Don't know/missing 51.2 42.8 0.7 5.3 100.0 163 All births 50.7 48.7 0.4 0.2 100.0 6211 Note: Figures are for births in the period 1-59 months preceding the survey. Mothers received antenatal cards for nine in ten births in the five years preceding the survey. Those who were less likely to have cards were births to rural women, births to women from Northern Province, and births to women with no education. Another crucial element in reducing the health risks of mothers and children is increasing the proportion of babies that are delivered in medical facilities. Proper medical attention and hygienic conditions during delivery can reduce the risk of complications and infections that can cause the death or serious illness of either the mother or the baby. Respondents in the ZDHS were asked to report the place of birth of all children born in the five years before the survey (Table 8.4). 93 Table 8.5 Assistance during delivery Percent distribution of births in the five years preceding the survey by type of assistance during delivery, according to selected background characteristics, Zambia 1992 Attendant assisting during delivery I Trained Traditional Number Background nurse/ birth Relative/ Don't Know/ of characteristic Doctor Midwife attendant Other No One Missing Total births Mother's age at birth <20 3.6 46.8 11.0 36.4 2.1 0.1 100.0 1327 20-34 4.8 47.3 9.0 31.9 6.9 0.2 100.0 4095 35+ 5.8 36.7 8.5 31.3 17.5 0.1 100.0 788 Birth order 1 5.3 52.4 9.4 31.9 0.8 0.1 100.0 1390 2-3 4.9 44.4 10.2 36.3 4.1 0.1 100.0 1917 4-5 4.3 46.0 8.4 32.2 8.9 0.2 100.0 1242 6+ 4.0 41.9 9.2 30.0 14.8 0.1 100.0 1662 Residence Urban 8.1 70.9 5.3 11.3 4.3 0.1 100.0 2885 Rural 1.7 24.1 12.9 51.4 9.7 0.2 100.0 3326 Province Central 3.3 35.7 10.2 39.8 11.0 0.0 100.0 595 Copperbelt 6.8 73.0 6.4 8.6 5.1 0.1 100.0 1429 Eastern 2.0 33.8 11.1 42.1 10.6 0.3 100.0 669 Luapnla 1.4 34.2 9.9 43.9 10.3 0.3 100.0 419 Lusaka 12.1 64.4 5.5 14.3 3.8 0.0 100.0 935 Northern 1.4 17.6 10.9 60.7 9.4 0.0 100.0 647 North-Western 3.1 46.7 26.9 21.8 1.2 0.2 100.0 172 Southern 1.6 32.3 13.0 45.0 7.9 0.2 100.0 1008 Western 2.8 29.6 4.7 57.4 5.0 0.4 100.0 337 Mother's education No education 1.3 20.4 9.8 55.8 12.3 0.4 100.0 1061 Primary 3.6 44.4 11.2 33.3 7.3 0.1 100.0 3907 Secondary 10.6 71.1 3.5 12.3 2.5 0.0 100.0 1138 Higher 13.3 82.4 1.1 2.2 1.1 0.0 100.0 103 Antenatal care visits None 0.2 3.2 14.9 64.1 17.6 0.0 100.0 392 1-3 visits 2.5 31.2 13.0 44.8 8.5 0.0 100.0 1401 4 or more visits 5,9 54,5 7.9 25.9 5.9 0.0 100.0 4255 Don't know/Missing 2.7 48.6 5.0 33.8 4.7 5.3 100.0 163 Total 4.7 45.8 9.4 32.8 7.2 0.1 100.0 6211 Note: Figures are for births in the period 1-59 months prior to the survey. 1If the respondent mentioned more than one attendant, only the most quafified attendant is considered. 94 Overall, half of births in Zambia are delivered at home and half are delivered in health facilities. Delivery of births at home is much more common in rural areas and in Northern Province than in urban, Copperbelt and Lusaka Provinces, where about 3 in 4 births are delivered in health facilities. The high proportion of births delivered at home has serious consequences for both maternal and child health. The relationship between education of the mother and place of delivery is striking; the proportion of births delivered in a health facility increases steadily from 22 percent among women with no education to 96 percent among women with higher than secondary education. Women who are in touch with health professionals during pregnancy are much more likely to deliver at a health facility than women who have no such contact; 61 percent of births to women who made four or more antenatal care visits were delivered in health facilities, compared to 3 percent of births to women who made no antenatal care visits. The type of assistance a woman receives during the birth of her child also has health implications for the mother and child. Births that are delivered at home are more likely to be delivered without assistance from anyone, whereas, births delivered at a health facility are more likely to be delivered by trained medical personnel. Given the rather high proportion of deliveries occurring at home, it is not surprising that only half of births are assisted by medically trained personnel (doctor, trained nurse or midwife) (see Table 8.5 and Figure 8.1). It is, however, surprising that one-third of births in Zambia are assisted by relatives and 7 percent are deliv- ered without assistance. Births to rural women, births to women in Central, Eastern, Luapula, and Northern Provinces, births to wom- en with no education, births to older women and births to women who made no antenatal visits, are more likely to be delivered with- out any type of assistance. These characteristics identify women who are at greater risk of dying due to complications occurring dur- ing pregnancy and delivery. Also notable is the relatively high pro- portion of births in Nonh-Westem Province that are delivered by traditional birth attendants (27 percent vs. 9 percent nationally). It appears that doctors assist in delivering most of the births for which they provided some antenatal care (see Tables 8.1 and 8.5), while trained nurses and midwives provided antenatal care to 88 percent of births and assisted in delivering only 46 percent (Table 8.5). Doctors and trained nurses or midwives delivered close Table 8.6 Characterisdes of delivery Percent distribution of births in the five years preceding the survey by whethar the delivery was by caesarean section, whether premature, and by birth weight and the mother's estimate of baby's size at birth, Zambia 1992 Delivery Percent eharaetaristie of births C-section Yes 2.6 No 95.3 Missing 2.1 Total 100.0 Premature birth Yes 5.0 No 94.8 Don't knowhnissing 0.3 Toud 100.0 Birth weight Less than 2.5 kg 4.9 2.5 kg or more 38.2 Don't knowhnissing 56.9 Total 100.0 Size at birth Very large 3.2 Larger than average 16.6 Average 68.2 Smaller than average 9.4 Very small 2.2 Don't knowhnissing 0.4 Total 100.0 Number 6211 Note: Figures are for births in the period 1-59 months preceding the survey. to 80 percent of births in Copperbelt and Lusaka Provinces, compared to 30 to 50 percent in Central, Eastern, Luapula, Southern, Western and North-Westem Provinces and less than 20 percent of births in Northern Province. Less than three percent of babies born in Zambia are delivered by caesarean section and 5 percent are reported by their mothers to have been born prematurely. ZDHS respondents were asked to report the weight at birth of all children who were born in the five years preceding the survey and who were weighed 95 at birth. In addition, they were asked for their assessment of the size of each of these children at birth, i.e., whether the child was very large, larger than average, etc. The results show that 38 percent of births weighed 2.5 kilograms or more and 5 percent weighed less than 2.5 kilograms at birth. Birth weight information was not available for 57 percent of births, which is not surprising, since almost half are delivered at home. Only 20 percent of babies born in the five years preceding the survey were reported by the mother to be very large or larger than average, 12 percent to be very small or smaller than average, and seven in ten to be of average size at birth (see Table 8.6). 8.2 Vaccinations In order to assist in the evaluation of the Expanded Programme on Immunisation (EPI), the ZDHS collected information on vaccination coverage for all children bom in the five years preceding the survey, although the data presented here are restricted to children who were alive at the time of the survey. The EP1 follows the World Health Organisation (WHO) guidelines for vaccinating children. In order to be considered fully vaccinated, a child should receive the following vaccinations: BCG, measles and three doses each of DPT and polio. BCG is for protection against tuberculosis, and DPT is for protection against diphtheria, pertussis, and tetanus; both DPT and polio require three vaccinations at intervals of several weeks. WHO recommends that children receive the complete schedule of vaccinations by 12 months of age. Information on vaccination coverage was collected in two ways: from vaccination cards shown to the interviewer and from mothers' verbal reports. The majority of health centres and clinics in Zambia provide cards on which vaccinations are recorded. If a mother was able to present such a card to the interviewer, this was used as the source of information, with the interviewer recording vaccination dates directly from the card. In addition to collecting vaccination information from cards, there were two ways of collecting the information from the mother herself. If a vaccination card had been presented, but a vaccine had not been recorded on the card as being given, the mother was asked to recall whether that particular vaccine had been given. If the mother was not able to provide a card for the child at all, she was asked to recall whether the child had received BCG, polio (including the number of doses for polio), or measles vaccinations. Unlike many other DHS surveys, mothers in the ZDHS were also asked whether their children had received Dtrl" vaccine and if so, the number of doses. Information on vaccination coverage is presented in Table 8.7, according to the source ofinformatinn used to determine coverage, i.e., the vaccination card or mother' s report. Data are presented for children age 12-23 months, thereby including only those children who have reached the age by which they should be fully vaccinated. Figure 8.2 presents coverage figures as assessed from both vaccination cards and mothers' reports. According to the information from vaccination cards, three-quarters of children received a BCG vaccination. However, not all children who are vaccinated have cards available; 20 percent of children who did not have a card were reported by their mothers to have received the BCG vaccine. Thus, overall, 95 percent of children age 12-23 months are vaccinated against tuberculosis. Vaccinations are most effective when given at the proper age; according to the card information, 94 percent of children receive the BCG vaccine by 12 months of age. 96 Table 8.7 Vaccinations by source of information Percentage of children 12-23 months who had received speeille vaccines at any time before the survey and the percentage vaccinated by 12 months of age, by whether the information was from a vaccination card or from the mother, Zambia 1992 Percentage of children who received: DPT Polio Number Source of of information BCG 1 2 3+ 1 2 3+ Measles All 1 None children Vaccinated at any time before the survey Vaccination card 75.0 74.1 69.6 63.4 74.4 69.8 64.1 61.4 56.5 0.4 1123 Mother's report 20.1 19,6 17.9 13.4 19.6 18.2 12,2 15.6 10.1 3.7 1123 Either source 95.1 93.8 87.5 76.8 93.9 87,9 76.4 7%0 66.6 4.1 1123 Vaccinated by 12 months of age 93.5 92.3 83.6 69.8 92.3 84.6 70.2 65.9 54.8 6.8 1123 Note: For cldldrcn whose information was based on the mother's report, the proportion of vaccinations given during the first year of llfe was assumed to be the same as for children with a written record of vaccination. 1Children who arc fully vaccinated (i.e., those who have received BCG, measles and thr~ doses of DPT and polio). Figure 8.2 Vaccination Coverage among Children Age 12-23 Months Percent 100 80 60 40 20 0 BCG 1 2 Pol io Note: Based on health cards end mothers' reports. Meas les All None ZDHS 1992 97 Coverage of the first dose of polio and the first dose of DPT is virtually the same as for BCG; 94 percent have received the first dose and 92 percent received it by 12 months of age. Coverage declines aRer the first dose, with 88 and 76 percent receiving the second and third doses respectively. This yields a dropout rate of about 18 percent for DPT and polio. The proportion vaccinated by 12 months of age aiso falls to about 85 percent at the second dose and 70 percent at the third dose. Sixty-six percent of children age 12-23 months were vaccinated against measles before their first birthday. Overall, 55 percent of all children age 12-23 months had all the recommended vaccinations by their first birthday, although 67 percent were fully vaccinated in due course. Only 4 percent of children age 12-23 months have never received any vaccinations. As noted above, 94 percent of children age 12-23 months received a BCG vaccination; the next highest coverage levelis 92 percent for the first dose of polio and DPT vaccines. Thus, whether or not a child has received BCG appears to be indicative of whether the child will ever receive any vaccinations; the pattern is reflected for all the background characteristics presented in Table 8.8. Figure 8.3 shows the percentage of children age 12-23 months who are fully vaccinated (according to card information and mothers' reports) by selected background characteristics of the mother. T~tble 8.8 Vacc~,neXlons by back~round ebJtmcterlsties Percentage of children 12-23 months who had received specific vaccines by the time of the survey (according to vace'mation cards or mothers' reports) and die percentage with a vaccination card, by selected background characteristics, Zambia 1992 Pun:enrage of children who received: Percentage DPT Polio with Number Background a of characteristic BCG 1 2 3+ 1 2 3+ Measles All t None card children Sex Mal~ 95.7 94.7 87.1 77.1 95.1 88.0 77.0 77.2 66.3 3.5 75.3 560 Female 94.5 92.8 87.8 76.5 92`8 87.9 75.8 76.9 66.9 4.7 76.0 562 Birth order 1 97.1 96.6 91.6 83.4 97.0 92.3 83,9 84.9 75.4 1.6 73.3 252 2-3 96.4 96.3 89.0 79.1 95.9 90.7 79.9 79.8 70.5 2.8 75.9 329 4-5 95.1 93.1 89.7 78.5 93.3 87.9 77.1 75.7 66.4 4.4 79.1 236 6+ 92.0 89.2 80.7 67.6 89.9 81.4 65.8 68.6 55.3 7.3 74.8 306 Residence Urban 98.3 95,6 92,0 84.5 96,4 92,6 83,8 81.3 74,4 1,5 76.9 515 Rural 92.4 92.2 83.6 70.3 91.8 84.0 70.0 73.4 60.0 6.3 74.7 607 ProvinCe Cennal 91.8 90.8 87.7 76.5 91.8 87.7 75.4 72.4 63.2 7.2 75.5 108 Copperbelt 98.0 95.5 93.1 85.0 96.3 93.9 83.4 81.3 73.6 1.6 76.9 267 Eastern 95.8 94.7 87.4 70.6 94.7 89.5 68.5 76.9 57.9 3.2 74.8 105 Luapula 93.3 92.5 84.9 74.3 92.5 83.2 74.0 73.5 62.0 6.7 75.5 79 Lus~a 98.7 96.0 91.2 84.5 96.0 91.2 83.8 77.0 73.0 1.3 77.0 161 Northern 85.0 84.0 68.9 54.9 83.0 72.9 59.9 59.9 50.9 13.0 62,9 111 North-We, stem 90.7 91.8 82.5 77.9 91.8 83.7 76.7 83.7 70.9 7.0 84.9 35 Southern 97,2 97.8 91,l 80,6 97,2 88,9 78.4 83.9 71,2 1.7 79.5 200 Western 94.0 90.9 80.1 61.4 92.8 83.2 66.9 76.0 56.6 4.8 74.6 57 Mother's education No education 87.1 86.0 76.8 62.1 85.4 77.8 58.8 68.2 49.3 11.7 71.3 190 Prinmry 95.9 94.4 87.6 76.5 94.5 87.8 76.4 75.1 65.7 3.1 76.1 704 Secondary 99.2 98.2 95.7 89.3 99.2 96.7 90.3 89.8 82.6 0.8 77.7 216 All children 95.1 93.8 87.5 76.8 93.9 87.9 76.4 77.0 66.6 4.1 75.7 1123 IChildren who ~tre fully vaccinated (i.e., throe who have received BCG, measles and three doses of DPT and polio). 98 Figure 8.3 Percentage of Children 12-23 Months Who Are Fully Vaccinated ZAMBIA RESIDENCE Urban Rural PROVINCE Central Copperbslt Eastern Luapula Lusaka Northern North-Western Southern Western EDUCATION No Education Primary Secondary 67 " - 74 60 ~ 6 3 . - ~ ' ~ • ---- - 74 ~ 5 8 6 2 . . . 7 3 ~ S l 71 ~ 7 1 " - 5 7 ~ 4 9 . . . . 6 6 20 40 60 80 Percent Note: Rased on health cards and mothers' reports. 100 ZDHS 1992 The highest proportion of children who are fully vaccinated is among mothers with secondary education (83 percent); the lowest proportion is among children of mothers with no formal education (49 percent) and among children in Northern Province (51 percent). Vaccination status does not differ significantly by the sex of child, but it does differ appreciably by birth order, with the proportion fully vaccinated declining from 75 percent among children of mothers with one child to 55 percent of children whose mothers have 6 or more children. There is also a distinct advantage for urban children, three-quarters of whom are fully vaccinated, compared to only 60 percent of rural children. Thus far, the discussion has focused on children age 12-23 months. Information on the proportion of children age 12-59 months who had been vaccinated by 12 months of age, by their current age is presented in Table 8.9 and can be used to assess trends; the table also shows the percentage with a vaccination card seen by the interviewer. The coverage figures are based on both card information and mothers' reports. Cards were shown to interviewers by mothers for 66 percent of the children age 12-59 months. The percentage of children with vaccination cards decreases with increasing age, from 76 percent for children age 12-23 months to 55 percent among those aged 48-59 months of age. This decline may be due to either a genuine increase in coverage over time or to the loss of cards over time. Mothers may be incrmed to reta'm cards only so long as they need them to present to health staff; once children are fully vaccinaW.d and/or reach a certain age, there may be a tendency to discard the cards. By comparing vaccination coverage among the various age groups of children, it is possible to obtain a picture of changes in the success of the vaccination programme over time. This analysis implies that the programme gradually improved its coverage rates in all but the most recent time period. For example, the proportion of children who were fully immunised by their first birthday rose from 50 percent of those who were four years old at the time of the survey to 54 percent of three-year-olds and 60 percent oftwo-year-olds, 99 Table 8.9 Vaccinations in the fkst year of life Percentage of children one to four years of age for whom a vaccination card was see~ by the interviewer and the percentage vaccinated for BCG, DPT, polio, arid measles during the first year of llfe, by current age of the child, Zambia 1992 Current age of child in months All children Vaccination card/ 12-59 Vaccination status 12-23 24-35 36-47 48-59 months Vaccination card seen by Interviewer 75.7 69.4 59.0 55.0 65.5 Percent vaccinated at 0-11 months a BCG 93.5 92.8 91.9 88.9 91.9 DPT 1 92.3 90.8 89.2 87.9 90.2 DPT 2 83.6 85.2 82.8 78.7 82.8 DPT 3 69.8 73.1 69.4 64.2 69.4 Polio 1 92.3 91.7 90.1 88.3 90.7 Polio 2 84.6 85.4 82.3 78.5 82.9 Polio 3 70.2 70.6 66.3 63.0 67.8 Measles 65.9 68.7 65.3 65.2 66.4 All vaccinations b 54.8 59.5 53.7 49.7 54.7 No vaccinations 6.8 8.0 8.7 10.l 8.3 Number of children 1123 1125 921 911 4080 alnformation was obtained either from a vaccination card or from the mother if there was no wriaon record. For children whose iafonnatlon 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 that for children with a written vaccination record. bchildren who have received BCG. measles and three doses of DPT and polio vaccines, but declined slightly to 55 percent of one-year-olds. There is a similar pattern of increasing coverage followed by a recent decline for the second doses of both DPT and polio, as well as for measles vaccinations. The fact that there is no recent decline in coverage for either B CG or the first doses of DPT and polio implies that the programme is continuing to reach the vast majority of children, but that more emphasis is needed to ensure that these children are given all subsequent doses of the appropriate vaccines. 8.3 Acute Respiratory Infection Medical records show that pneumonia is one of the major causes of infant mortality in Zambia. Its prevalence was estimated in the ZDHS by asking mothers if their children under age five had been ill with coughing accompanied by short, rapid breathing, in the two weeks preceding the survey. These symptoms are compatible with pneumonia. Early diagnosis and treatment with antibiotics can prevent alarge proportion of pneumonia deaths. It bears mentioning that information on disease prevalence is more subjective than many other topics covered in the ZDHS; it is highly dependent on what symptoms the mother considers serious. Similarly, reporting of treatment practices depends on how much mothers know about the medicines their children may receive. Mothers may not know whether the pills or syrups their children receive contain antibiotics or not. Thus, reporting may vary widely within the country, due to cultural differences in reporting. 100 Table 8.10 Prevalence and ~eatment of acute respiratory infection Percentage of children under five years who were ill with a cough accompanied by rapid I~e, athin 8 during the two weekJ preceding the survey, and the percentage of ill children who were Ixeated With specific remedies, by selected background characteristics, Zambia 1992 Among children with cough and rapid Meathing Percentage Percentage Percentage treated with: of children taken to with cough a health Antibiotic None] Number Background and rapid facility or pill or Cough Hone Don't ~ow/ of chm'neteristlc breathing provider 1 syrup Injection syrup remedy Other Missing children Child's age < 6 months 11.9 58.3 16.6 3.6 30.1 14.6 54.4 12.1 598 6-11 months 18.3 71.4 11.2 12.3 40.7 9.1 65.9 9.7 651 12-23 months 15.6 64.8 10.6 15.4 46.7 12.4 56.8 11.3 1123 24-35 months 11.4 57.5 17.1 6.5 41,6 15.2 52.2 12.2 1125 36-47 months 12.2 56.8 14.2 4.5 32.7 10.1 48.2 17.4 921 48-59 months 8.0 56.6 16.6 4.4 37.7 18.0 43.7 20.1 911 Sex Male 12.9 60.9 13.5 9.6 40.4 13.9 53.0 14.8 2645 Female 12.6 62.5 14.1 8.3 38.9 11.7 56.0 11.6 2684 Birth order 1 11.2 64.9 10.1 8.8 34.0 13.0 55.9 15.3 1145 2-3 13.2 65.5 14.2 10.0 43,5 11.0 52.3 13.7 1643 4-5 12.1 60.8 15.0 6.0 44.9 13.2 53.7 11.4 1089 6+ 13.8 56.2 14.9 9.8 35.7 14.4 56.5 12.6 1453 Residence Urban 10.2 73.4 23.2 12.2 54.9 4.6 50.6 9.7 2514 Rural 15.0 54.6 8.1 6.9 30.4 17.8 56.8 15.3 2815 Province Central 9,0 (67.5) (11.5) (9.3) (44.1) (11.7) (72.2) (9.3) 525 Copperbelt 11.7 83.0 25.7 10.3 58.1 2.2 51.5 10.3 1260 Eastern 26.3 49.2 9.3 7.7 23.1 23.1 55.4 14.6 547 Luapula 17.7 55.5 7,5 3.4 38.9 7.9 69.5 13,2 331 Lusaka 6.4 (55.1) (22.4) (10.2) (61.2) (10.2) (49.0) (6.1) 826 Northern 14.1 46.2 14.9 6.0 31.1 17.9 35.8 19.5 528 North-Westam 8.1 * * * * * * * 145 Southern 8.9 59.7 6.9 12.4 40.3 13.9 48.7 12.5 893 Western 22.6 68.4 5.1 8.4 23.9 15.5 62.2 20.5 276 Mother's education No education 16.7 42.7 8.6 6.9 29.1 18.9 47.1 22.3 903 Primary 12.7 64.9 12.0 10.2 40.2 12.2 57.0 12.1 3332 Secondary 9.6 75.2 27.8 7.5 51.5 7.0 54.3 4.8 1000 1ligher 7.8 * * * * * * * 92 All children 12.7 61.7 13.8 8.9 39.7 12.8 54.5 13.2 5330 Note: Figures are for children born in the period 1-59 months preceding the survey. Figua'es in parentheses are based on 25 to 49 children; those based on fewer than 25 children are suppressed and marked with all asterisk. llncludes health clinic, health tense, hospital, and private doctor. 101 Table 8.10 shows that 13 percent of children under five years of age were ill with a cough and rapid breathing at some lime in the two weeks preceding the survey. Sixty-two percent of these children visited a health facility of some kind, 14 percent received an antibiotic treatment, 9 percent injections, and 40 percent received cough syrup. The occurrence of the illness as well as treatment practices for sick children differ by background characteristics of the mother and child. Coughs with difficult breathing appear to be most prevalent among children age 6-11 months. Children of mothers in rural areas, those in Eastern, Western, Luapula and Northern Provinces and children whose mothers have no education are more likely to have pneumonia-like symptoms than other children (see Table 8.10). Children of mothers resident in Copperbelt Province are more likely than children in other provinces to be taken to a health facility and to be given antibiotics when they have coughs with difficult breathing. Children of more educated mothers are more likely to be taken to a health facility (75 percent) than children of uneducated mothers (43 percent). Treatment with antibiotics and cough syrup is a more common practice among more educated mothers than among their less educated counterparts. There are no marked differentials in treatment practices by age, sex or birth order of the ill child. 8.4 Fever Malaria is endemic throughout Zambia and is the most common cause of hospital admission for all age groups (Ministry of Health, 1990:11). During the period 1978-1988, there was a four-fold increase in the number of hospital deaths due to malaria. Moreover, the number of cases reported to medical facilities shows wide variations by province (Ministry of Health, 1990:29). In order to collect information on prevalence and treatment of malaria in children outside of a health facility setting, the ZDHS included several questions about malaria. Since the major manifestation of malaria is fever, mothers were asked whether their children under age five had had a fever in the two weeks preceding the survey, and what type of treatment was sought, if any. Table 8.11 shows that 44 percent of children under five years of age were reported to have had fever in the two weeks prior to the survey. Of these children, three in five were taken to a health facility and a little over half received antimalarial treatment. Fever is more common among children in Western and Eastern Provinces and is relatively uncommon among children in urban areas and Lusaka Province. There are also differences in treatment practices for those children who have fever. Children in urban areas, and those in Copperbelt, North-Western and Lusaka Provinces are more likely to be taken to a health facility and/or given antibiotics for treatment of their fever than children in the rural areas or in the other provinces; the same is true for children of the most educated mothers (secondary or higher), compared to children whose mothers had primary or no education. It is important to note the relatively frequent use of home remedies in treating fevers of children of the least educated women and of children in rural areas (see Table 8.11). 102 Table 8.11 Prevalence and treatment of fever Percentage of children under five years who had a fever during the two weeks preceding the survey, and the percentage of children with a fever who were treated with specific remedies, by selected background characteristics, Zambia 1992 Among children with fever Percentage Percentage percentage treated with: of taken to children a health Antibiotle None/ Number Background with facility or Anti- pill or Home Cough Don't know/ of characteristic fever provider I malarial syrup Injection remedy syrup Missing children Child's age < 6 months 32.8 58.8 47.2 12.8 2.0 6.0 55.7 14.8 598 6-11 Months 54.4 70.3 51.7 13.5 8.8 6.6 53.7 10.2 651 12-23 Months 54.2 63.9 53.2 8.3 7.0 8.9 53.0 14.1 1123 24-35 Months 46.8 58.3 51.3 10.7 6.0 7.6 49.2 15.9 1125 36-47 Months 38.7 58.3 51.9 10.8 3.4 6.8 42.1 18.8 921 48-59 Months 31.7 55.1 47.1 7.2 3.5 8.9 51.8 18.2 911 Sex Male 44.1 61.3 52.1 10.2 5.5 7.7 50.0 15.2 2645 Female 43.3 61.1 50.1 10.3 5.7 7.6 51.3 15.2 2684 Birth order 1 41.1 64.3 49.5 8.2 4.8 8.6 55.1 13.1 1145 2-3 44.1 61.9 50.5 11.8 5.4 6.8 48.7 14.8 1643 4-5 41.5 60.2 55.4 9.4 6.1 8.0 49.0 14.6 1089 6+ 47.1 59.1 50.0 10.6 6.1 7.7 50.9 17.5 1453 Residence Urban 34.0 73.0 53.4 16.2 6.3 3.0 66,3 5.7 2514 Rural 52.4 54.4 49.7 6.8 5.3 10.4 41.6 20.7 2815 Provltlce Central 35.5 58.6 50.2 8,3 2.4 11.3 55.5 14.3 525 Copperbelt 35.7 77.0 53.6 17.1 5.1 2.9 64.2 7.0 1260 Eastern 58.5 47.4 45.7 7.6 4.5 18.0 55.0 12.5 547 Luupula 45.1 47.4 59.5 5.5 2.7 4.4 37.7 20.9 331 Luscka 29.1 67.8 45.2 14.4 9.5 4.1 70.0 7.3 826 Northern 53.5 47.0 43.5 16.0 6.3 9.0 34.4 25,5 528 North-Westam 45.2 73.7 72.3 5.5 7.6 7,8 43.2 12.3 145 Southern 51.8 63.3 54.3 5.5 6.9 5.5 43.0 18.7 893 Western 63.4 64.3 52.3 2.8 4.8 8.3 36.7 23.5 276 Mother's education No education 52.4 44.4 38.1 7.2 3.8 11.1 37,8 29.4 903 Primary 45.8 62.7 53.5 9.4 5.8 8.0 50.5 13.6 3332 Secondary 30.4 77.8 58.6 17.5 7.4 1.5 69.6 2.4 1000 I/igher 30.3 86.0 58.6 29.6 7.8 0.0 72.7 3.9 92 All children 43.7 61.2 51.1 10.2 5.6 7.7 50.7 15.2 5330 Note: Figures are for children born in the period 1-59 months preceding the survey. llnelades health clinic, health centre, hospital, and private doeth. 103 8.5 Diarrhoea Dehydration engendered by se- vere diarrhoea is a major cause of mor- bidity and mortality among Zambian children. One treatment for dehydration is oral rehydration therapy (ORT): a solution prepared from commercially produced packets of oral rehydration salts (ORSIalSO called by its Zambian name madzi a moyo); or a homemade solution prepared from sugar, salt and water. The former is distributed through health centres and pharmacies, whereas preparation of the latter is taught in health centres. ORT has been taught actively in Zambia since the 1980s. The Ministry of Health believes that the decline in the incidence ofdiar- rhoeal disease reported by health insti- tutions may be due to an increase in home management of diarrhoea, rather than to a drop in frequency of the dis- ease itself (Ministry of Health, 1990:12). Table 8.12 indicates the prev- alence of diarrhoea in children under five years of age. Nearly one-quarter of children had experienced diarrhoea at some time in the two weeks preceding the survey, About 4 percent of children had experienced bloody diarrhoea dur- ing the same period, whilst 8 percent were still having an episode of diar- rhoea at the time of the survey (i.e., within the last 24 hours). Children aged 6-23 months were the most likely to have experi- enced diarrhoea in the two weeks pre- ceding the survey. Children aged 24-35 months experienced slightly higher rates of bloody diarrhoea than children in other age groups. Prevalence of diar- rhoea was found to be slightly higher among rural than among urban chil- Table 8.12 Prevalence of diarrhoea Percentage of children under five years who had diarrhoea and diarrhoea with blood in the two weeks preceding the survey, and the percentage of children who had dianheea in the preceding 24 horn-s, by setected boekgro~md ch~acteristlcs, Zambia 1992 Diarrhoea in the All preceding 2 weeks I diarrhoea in the Number Background All Diarrhoea preoedthJmg of charac~ristie diarrhoea with blood 24 hotw~ z children Child's age < 6 months 14,5 1.3 7.2 598 6-11 months 33.4 2.6 14.2 651 12-23 months 36,4 4.8 13.6 1123 24-35 months 24.0 5.2 7.4 1125 36-47 months 15.8 3.6 4.0 921 48-59 months 9.5 1.7 2.3 911 Sex Male 24.3 3.4 8.9 2645 Female 21.4 3.6 7.3 2684 Birth order 1 25.2 2.7 8.4 1145 2-3 24.8 3.6 8.5 1643 4-5 19.0 2.3 7.1 1089 6+ 21.6 4.8 8.0 1453 Residence Urban 20.0 2.5 6.6 2514 Rural 25.3 4.4 9.4 2815 Province Central 22,1 3,0 10,7 525 Copperbelt 17.7 1.8 5.5 1260 Eastern 31.8 6.7 9.5 547 Luapula 21.2 2.9 11.0 331 Lusaka 19.8 2.8 5.8 826 Northern 28.3 5.2 12.0 528 North-Western 18.2 1.7 8.5 145 Southern 24.8 3.8 7.0 893 Western 26.0 4.8 11.0 276 Mother's education No education 26.2 4.6 8.7 903 Primary 24.0 3.6 8.6 3332 Secondary 16.9 2.4 6.1 1000 Higher 10.6 0.0 3.6 92 All children 22.8 3.5 8.1 5330 Note: Figures are for children born in the period 1-59 months preceding the survey. llncludes diarrhoea in the past 24 hours 21ncludes diarrhoea with blood dren, and higher among children in Eastem, Northern, Western, and Southern Provinces than among those in the other provinces. Similarly, children of the least educated mothers are more likely to be reported as having had diarrhoea than children with educated mothers. 104 Knowledge of ORS packets is nearly universal among Zambian mothers; 95 percent of women who had births in the five years pre- ceding the survey had heard of such packets and almost 8 in I0 of these mothers had ever used a packet (see Table 8.13). There are no significant differences in the level of knowl- edge of ORS by background characteristics of the mothers, except that uneducated mothers are less likely to know about the packets. Use of ORS differs more widely by background characteristics of the mother. Mothers most likely to have used ORS are those living in urban areas, and those resident in North- Western, Lusaka and Copperbelt Provinces, as well as mothers with more education. The youngest cohorts (i.e., age 15-19) are least likely to have used ORS. Table 8.14 shows the percentage of children with recent bouts of diarrhoea who were given various treatments. Half of all chil- dren who had a recent bout of diarrhoea were takento a health facility orprovider. Children in urban areas are more likely to visit a health facility or provider than are rural children (62 vs. 50 percent), and children in Southern, Cop- perbelt, and Lusaka Provinces, as well as those whose mothers are more educated, are more likely to be taken to a health facility than other children. More than half of the children (53 per- cent) who recently had diarrhoea were given a solution prepared from ORS packets and 23 percent were given a homemade solution of sugar, salt and water. Almost half the children were given more liquids to drink than they would normally receive. Despite these encour- aging statistics, it is important to note that one- quarter of the children with diarrhoea were not Table 8.13 Knowledge and use of ORS packets Percentage of mothers with births in the five years preceding the survey who know about and have ever used ORS packets, by selected background characteristics, Zambia 1992 Know Have ever Number Background about ORS used ORS of cbaract~a'istie packets packets mothers Age 15-19 91.2 63.1 538 20-24 94.8 78.0 1077 25-29 97.5 83.6 924 30-34 95.7 80.8 670 35+ 93.4 78.6 771 Residence Urban 96.3 82.8 1880 Rur~ 93.6 73.5 2100 Province Central 95.8 77.8 368 Copperbdt 94.2 80.6 917 Eastern 89.1 70.0 440 Luapula 96.1 78.6 250 Lusaka 98.8 82.7 629 Northern 92.7 73.1 392 North-Western 98.8 89.0 104 Southern 96.1 77.6 652 Western 92.9 72.6 230 Education No education 85.6 63.8 689 Primary 96.2 78.2 2464 Secondary 98.3 88.2 755 Higher 100.0 93.8 69 All mothers 94.8 77.9 3980 Not~: Figurers include mothers who have given ORS for diarrhoea during the preceding two weeks, although they were not asked about knowledge of ORS packets. given either ORT (whether fluid made from ORS packets or a homemade solution) or increased fluids to drink. The use of homemade sugar, salt and water solutions appears to be rather low, although increasing the fluid intake of sick children may have much of the benefit of the homemade solution even if the fluids do not have the exact proportions of ingredients. A higher percentage of children from the urban areas, from Copperbelt and Southem Provinces, and who had educated mothers (i.e., with primary or secondary education) were given the homemade solution. In fact, the use of ORT whether ORS packets or a homemade solutiorr--is more common among the most educated and urban mothers than among the least educated and rural mothers. 105 Table 8.14 Treatment of diarrhoea Percentage of children under five years who had diarrhoea hi the two weeks preceding the survey who were taken for treatment to a health facility or provider, the percentage who received oral rehydradon therapy (ORT), the percentage who received increased fluids, the percentage who received neither ORT nor increased fluids, and the peromtage receiving other treatments, according to selected background characteristics, Zambia 1992 Oral rehydmtion Per- Percentage P~.enmge receiving percentage therapy (ORT) ¢entage receiving other tl~ttr~nts: Number taken to recclving neither of a health Either in- ORT tin* ttorr~ ekildr~n Background facility or ORS ORS creased increased Anti- In- remedy/ with characteristic provider 1 packets RHS or RHS fluids fluids biotics jecdon Other None diarrhoea Age of child <6 months 46.9 40.5 19.4 51.1 39.8 37.8 8.8 1.3 34.1 22.9 87 6-11 months 56.8 55.3 24.2 66.8 42.5 23.1 5.8 0.0 83.1 14.0 217 12-23 months 56.7 56.7 24.7 66.7 47.8 23.0 8.3 0.4 33.9 14.4 409 24-35 months 54.9 54.1 23.8 65.6 48.3 21.8 9.7 1.0 38.6 10.6 270 36-47 months 51.8 45.5 20.5 58.4 45.9 26.1 8.0 0.0 35.1 15.8 146 48-59 months 50.6 50.1 15.0 57.2 40.4 29.8 10.1 0.0 38.1 17.3 87 Sex Male 55.8 54.5 22.6 65.4 44.7 23.6 8.0 0.4 34.6 13.9 642 Female 53.3 51.1 23.1 61.8 46.7 25.9 8.6 0.5 36.0 15.1 573 Birth order 1 57.6 58.5 18.2 65.7 45.6 22.2 7.9 0.0 37.4 14.5 288 2-3 56.6 53.7 24.5 66.8 47.2 21.6 8.6 0.7 32.5 12.7 407 4-5 49.7 49.4 25.9 61.2 49.7 26.6 8.4 0.0 32.4 16.8 207 6+ 52.5 49.0 22.8 59.5 41.0 29.7 8.2 0.9 38.7 15.2 313 Residence Urban 61.9 59.3 29.5 73.3 48.5 17.2 13.1 0.6 36.9 7.8 502 Rural 49.5 48.4 18.1 56.9 43.6 29.9 4.9 0.3 34.1 19.2 713 Province Central 52.5 62.8 19.0 70.4 62.9 16.2 6.7 0.0 33.2 12.4 116 Copperbelt 62.0 53.7 38.5 72.7 53.2 16.1 14.1 0.5 35.1 7.3 223 Eastern 50.3 51.5 21.6 61.1 58.6 20.4 8.9 0.0 47.2 9.6 174 Luapula 43.9 46.5 21.5 62.3 46.9 24.8 5.3 2.5 41.5 16.0 70 Lusaka 58.2 57.6 14.6 68.8 36.4 23.9 15.2 0.0 40.4 10.0 164 Northern 37.8 41.5 11.1 51,1 17.0 40.1 3.7 0.7 40,7 24,5 150 North-Western 56.2 53.1 8.7 56.2 60.3 24.4 4.1 0.0 34.2 19.9 26 Southern 66.6 58.1 29.7 64.1 46.2 25.0 5.0 0.5 19.9 17.0 222 Western 45.5 41.1 11.7 48.9 35.4 44.2 0.0 1.0 28.6 29.8 72 Education 2 No education 38.3 44.7 11.7 49.9 35.5 39.1 1.2 0.0 41.6 23.9 237 Primary 56.2 52.3 24.3 64.1 45.9 23.1 9.3 0.4 34.5 13.1 799 Secondary 70.5 66.3 32.2 80.2 57.7 13.6 13.3 1.3 30.7 8.4 169 Total 54.6 52.9 22.8 63.7 45.6 24.7 8.3 0.5 35.2 14.5 1216 Note: Figures am for chilcken born in the period 1-59 months preceding the survey. Oral rehydradon therapy (ORT) includes solution prepared from ORS packets and recommended home solution (RHS) prepared from sugar, salt and water. lIncludes health clinic, health centre, hospital, private doctor 2Excludes children of women with higher education due to snaall sarffple sizes (9 children with diarrhoea). 106 Use of antibiotics and injections was relatively low (8 and less than 1 percent of cases, respectively), which is consistent with the acceptance of ORT as the modem treatment for diarrhoea. A high percentage of children (35 percent) were given remedies other than the recommended home solution, a more widespread practice in the Eastern, Luapula, Lusaka and Northern Provinces and among uneducated women. Table 8.15 shows that 73 percent of children who had diarrhoea and who were stiff being breastfed continued to be breasffed as usual, without increasing the frequency of feeds. Nearly half of all children with diarrhoea were given the same amount of fluid as usual, while 43 percent were given more fluids. This high proportion of children who were given increased fluids suggests that the importance of increasing fluid intake during a bout of diarrhoea is well understood by a sizeable proportion of Zambian women. Table 8.15 Feeding practices during diarrhoea Percem distribution of feeding practices among children under five years who had diarrhoea in the two weeks preceding the survey, Zambia 1992 Feeding practices during diarrhoea Percent Breasffeedlng frequency t Same as usual 72.9 Increased 13.3 Reduced 11.5 Stopped 0.7 Don't know/missing 1.5 Total 100.0 Number of children 965 Amount of fluids given Same as usual 46.6 More 42.7 Less 9.7 Don't know/missing 1.0 Total 100.0 Number of children with diarrhoea 1216 Note: Figures arc for children born in the period 1-59 months tneceding the survey. tApplies only to children who we still breast fed. 107 CHAPTER 9 INFANT FEEDING AND CHILDHOOD AND MATERNAL NUTRITION This chapter covers two related topics: infant feeding (including breast feeding practices, introduction of supplementary weaning foods, and use of feeding bottles) and nutritional status of young children and their mothers (based on height and weight measurements of the respondent's children under the age of five years and of hersel0. 9.1 Breastfeeding and Supplementation Infant feeding has an impact on both the child and the mother. Feeding practices are important determinants of the child's nutritional status, which in turn influences the risk of dying. The mother is affected by breastfeeding through its influence on postpartum infertility, which is related to the length of birth intervals, and thus fertility levels. These effects are influenced by both the duration and intensity of breastfeeding, and by the age at which the child receives foods and liquids. The data presented in Table 9.1 indicate that almost aU Zambian children (98 percent) are breasffed for some period of time. Forty percent of the children were put to the breast within an hour of birth and 87 percent within the first day. With the exception of North-Western Province, where 63 percent of last-born children were put to the breast within the first hour of birth and Western Province, where only 25 percent of newborns are put to the breast within the first hour of life, there are no marked differentials in breastfeeding initiation practices among the provinces. However, rural children are slightly more likely to be breastfed within either the first hour or the first day after birth than urban children. The proportions of children breastfed within the first hour and/or the first day of birth are inversely related to the level of education, and children who were delivered at home or by non-medically trained assistants are also more likely to be put to the breast sooner after delivery than those delivered at health facilities or by medically trained personnel. Breast milk is uncontaminated, and contains all the nutrients needed by children in the first few months of life. In addition, it provides some immunity to disease through the mother's antibodies. The percent distribution of children under age three years by breastfeeding status at the time of the survey is presented in Table 9.2, based on information about feeding practices in the 24 hours preceding the survey. Only 2 percent of children age 12-13 months are not breastfeeding, i.e., almost all children are breastfed for at least one year. By age 16-17 months, 18 percent of children are no longer being breastfed and seven of ten children are no longer being breastfed by the time they are 22-23 months old. 109 Table 9.1 Initial breastfeedin/~ Percentage of children born in the five years preced~mg the survey who were ever breasffed, and the percentage of last-born children who started bre~stfeeding within one hour of birth and within one day of birth, by selected background characteristics, Zambia 1992 Among all children: Among last-born children, percentage who started breasffeeding: Percentage Number Within Within Number Background ever of 1 hour 1 day of characteristic breastfed children of birth of birth children Sex Male 97.3 3142 39.9 87.3 2032 Female 97.7 3132 40.3 86.7 2031 Residence Urbari 97.4 2915 36.8 83.8 1914 Rural 97.6 3360 43.0 89.8 2148 Province Central 98.7 600 39.1 91.8 372 Copperbelt 97.6 1444 37.2 84.5 940 Eastern 95.4 675 47.7 86.7 449 Luapula 98.5 423 34,8 89.1 254 Lusaka 96.9 945 39.6 81.0 637 Northern 98.2 659 39.2 90.3 398 North-Western 96.9 173 62.4 87.1 106 Southern 97.9 1016 44.3 92.6 666 Western 96.6 340 25,4 82.2 239 Mother's education No educalion 97.8 1074 43.4 89.4 704 Primary 97.3 3950 42.2 87.8 2519 Secondary 97.5 1145 31.1 82.8 769 Higher 97.9 103 29.2 7g.1 69 Assistance at delivery Medically trained person 97,2 3165 35.3 83.7 2063 Traditional birth attendant 98.3 589 48.9 91,9 388 Other or none 97.9 2512 44.1 90.1 1610 Place of delivery Health facility 97.5 2876 35.4 83.5 1890 At home 98.1 3057 45.2 90.6 1967 All children 97.5 6275 40.1 87.0 4062 Note: Table excludes 17 children born in places other than at home or health facility and 189 whose place of birth was missing, Also excluded are 1 child whose mother's education is miss'ltag and 1 for whom assistance at delivery is missing. l lO Table 9.2 Breastfeeding status Percent distribution of living children by breasffeeding stares, according to child's age in months, Zambia 1992 Age in months Percentage of living children who are: Breasffeeding and: Number Not Exclusively Plain of breast- breast- water Supple- living feeding fed only ments Total children 0-1 1.2 15.9 67.9 15.0 100.0 186 2-3 1.3 11.3 39.3 48.1 100.0 245 4-5 0.0 2.9 13.1 84.1 100.0 231 6-7 0.9 0.7 7.0 91.4 100.0 253 8-9 1.1 0.0 6.2 92.7 100.0 204 10-11 1.9 0.0 3.7 94.4 100.0 194 12-13 2.3 0.0 4.5 93.2 100.0 190 14-15 16.1 0.0 2.9 81.0 100.0 206 16-17 18.2 0.0 3.8 77.9 100.0 174 18-19 44.2 0.0 0.4 55.4 100.0 187 20-21 58.8 0.0 0.8 40.4 100.0 194 22-23 73.6 0.0 0.6 25.8 100.0 171 24-25 82.0 0.0 0.6 17.4 100.0 180 26-27 90.5 0.0 0.6 9.0 100.0 199 28-29 97.1 0.0 0.0 2.9 100.0 215 30-31 99.2 0.0 0.0 0.8 100.0 178 32-33 96.3 0.0 0.0 3.7 100.0 185 34-35 98.7 0.0 0.0 1.3 100.0 167 Note: Breasffeeding status refers to preceding 24 hours. Children classified as breasrfeeding and plain water on/y receive no supplements. Exclusive breastfeeding is not common in Zambia: only 16 percent of children under 2 months of age are fed only breast milk. Most children are given water in addition to breast milk (68 percent of children under 2 months of age). Supplements (other than water) are introduced mainly when the children are 2-3 months old; as many as 48 percent of children age 2-3 months are receiving supplements, as are 84 percent of children age 4-5 months. The percentage receiving supplements increases to 94 percent among children aged 10-11 months, and thereafter drops as children stop breasffeeding altogether. Whilst most children are breastfed for a full year, 5 percent of those aged 12-13 months are reportedly not yet receiving supplements to their diet of breast milk and water. 111 Solid or mushy food is introduced into the diet as early as one month after birth, when 5 percent of breasffeeding children are given food (see Table 9.3). By age 4-5 months, seven out of ten breastfeeding children have food introduced into their diets and by the time they are one and half years old, nearly all the breastfeeding infants (96 percent) are receiving supplements of solid or mushy food. Bottle feeding is not common in Zambia; only 3 percent of babies age 0-1 months are being given a bottle and teat (nipple) in addition to being breastfed. These f'mdings are encouraging, since neonates are particularly vulnerable to infections and use of unsterilised bottles with nipples is a prime source of infections. Table 9.3 Breastfeeding mad supplementation by age Percentage of breasffeeding children who are receiving specific types of food supplementation, and the percentage who are using a boule with a nipple, by age in months, Zambia 1992 Ageinmonths Percentage of breasffeeding children who are: Receiving supplement Using a bottle Number Infant Other Other Solid/ with a of formula milk liquid mushy nipple children 0-1 2.4 2.4 6.9 4.8 3.4 184 2-3 3.6 4.6 13.4 37.5 3.0 242 4-5 4.7 11.6 20.0 72.1 7.1 231 6-7 6.3 11.2 37.5 87.5 4.6 251 8-9 4.8 13.5 44.4 90.1 9.5 202 10-11 4.6 11.0 57.4 93.0 7.6 190 12-13 2.7 13.2 52.4 92.9 1.7 185 I4-15 2.5 13.8 52.4 92.8 1.5 173 16-17 1.5 9.4 53.9 92.1 4.4 142 18-19 2.1 13.2 60.6 96.3 5.6 105 20-21 0.0 7.7 57.7 94.9 0.5 80 22-23 (0.0) (13.0) (49.5) (95.2) (3.3) 45 24-25 (0.0) (7.7) (48.6) (88.6) (0.0) 32 Note: Figures in parentheses are based on 25 to 49 unweighted cases. Breasffeedirtg status refers to preceding 24 hours. Percents by type of supplement among breastfeeding children may sum to more then 100 percent, as children may have received more then one type of supplement. The median duration of breastfeeding is 19 months (see Table 9.4). The duration of breastfeeding is longest for the children in North-Western and Westem Provinces (between 22 and 23 months). As mentioned above, exclusive breastfeeding is not common in Zambia; the median duration of breastfeeding with no supplementation is less than one month. Children are classified as fully breasOeed i f they are receiving only breast milk, or i f wa~r is the only addition to their diet of breast milk. The median duration of full breastfeeding is 2.3 months. The longest duration of full breastfeeding is for children in the Central, Western, and Southem Provinces (4 months). 112 Table 9.4 Median duration and frequen~ of brcesffeeding Median duration of any breasffeedlcg, exclusive breasffanding, and full bressffeeding and the percentage of children under 6 months of age who were breasffed six or more times in the 24 hours preceding the interview, according to background characteristics, Zambia 1992 Children trader 6 months Median duration in months t Number of Breasffed children 6+ times Any Exclusive Full undur in Number Back_ground breast- breast- breast- 3 years preceding of ch~acteristic feeding feeding feeding 2 of age 24 hours children Residence Urban 18,2 0.5 2.2 1912 88.7 327 Rural 19.0 0.4 2.6 2149 96.1 335 Province Central 17.4 0.4 3.7 378 94.8 63 Copp~helt 18.1 0.4 1.9 955 84.7 156 Eastern 17.8 0.4 0.7 440 95.1 67 Luapnla 18.6 0.4 2.3 270 92.7 48 Lusaka 17.7 0.5 2.2 638 91.2 99 Northern 19,4 0,4 2.4 412 98.6 77 North-Wastem 22.2 0.4 2.0 114 89.6 21 Southern 19.4 0.7 3.5 644 96.6 98 Western 22.9 0.4 3.6 211 97.9 33 Education No education 19.1 0.5 2.3 664 94.3 119 Primary 18.8 0.4 2.4 2596 91.6 422 Sacondary 18.0 0.4 2.1 737 94.2 112 Assistance at delivery Medically tralned 18.5 0.4 2.1 2046 90.8 319 Traditional midwife 18.7 0.5 2.4 385 89.4 58 Other or none 19.1 0.4 2.7 1628 94,9 285 Sex of child Male Female 18.9 0.5 2.3 2048 91,7 332 18.3 0.4 2.4 2013 93.2 330 Total 18.7 0.4 2.3 4061 92.5 662 Mean 18.3 1.3 3.9 97.8 Prevalence/Incidence 3 18.3 0.6 3.3 iMedians and means are based on ctrrent status 2Either exclusively txeesffed or received only plain wate~ in Addilion to breasffeeding 3Prey alence-incidence mean 113 Frequency of breasffeeding influences the nutritional status of the baby by affecting the overall amount of milk he or sbe receives. It also affects the mother by influencing the return of ber menstruai period after the birth. Medical research has shown that mothers who nurse their babies more frequently have longer durations of postpartum amenorrhoea than mothers whose infants suckle less intensely. ZDHS data indicate that 93 percent of children under 6 months of age were breastfed six or more times in the 24 hours preceding the interview. The percentage is slightly higher in the rural areas (96 percent) than in the urban areas (89 percent) and is relatively low in Copperbelt Province (85 percent). There are no appreciable differences in the frequency of feeds for the other background characteristics. 9.2 Nutritional Status of Children One of the major contributions of the ZDHS to the study of child heaith status is the anthropometric data collected on respondents' children under age five. These data allow for calculation of indicators of nutritional status. These indicators are important because children's nutritional status influences their susceptibility to disease and untimely death. Children's nutritional status reflects infant and child feeding practices as well as recurrent and chronic infections. In the ZDHS, all respondents with children born since January 1987 were eligible for anthropometric measurement as were the children. Data on the mothers' nutritional status are presented in the next section (Section 9.3). Both the height and weight were measured; these data were used to construct the following indices for children: height-for-age weight-for-height weight-for-age The validity of these indices is determined by the coverage of the population of children under study. Not all children eligible to be weighed and measured are included in the results presented here; the height and weight measurement is missing for 6 percent of eligible children, and one or both of the measurements are grossly improbable in 3 percent of cases. The month and year of birth is not known for less than one percent (0.4 percent) of cases, which renders two of the indices (height-for-age, and weight-for-age) incalculable. Hence, height and weight data are shown for 91 percent of the eligible children. (Although the term "height" is used here; children younger than 24 months were measured lying down on a measuring board (recumbent length), while standing height was measured for older children). As recommended by the World Health Organisation (WHO), the nutritional status of children in the survey is compared with an intenmtionai reference population defined by the U.S. National Center for Health Statistics (NCHS) and accepted by the U.S. Center for Disease Control (CDC). Each of the three nutritional status indicators described below are expressed in standard deviation units (z-scores) from the median for the reference population. The use of this reference population is based on the finding that well-nourished young children of all population groups (for which data exist) follow very similar growth patterns (see Martorell and Habicht, 1986). The reference population serves as a point of comparison, facilitating the examination of differences in the anthropometrie status of subgroups in a population and of changes in nutrifmnal status over time. In any large population, there is variation in height and weight; this variation approximates a normal distribution. The height-for-age index is an indicator of linear growth retardation. Children whose height-for-age z-score is below minus two standard deviations (-2 SD) from the median of the reference population are considered short for their age, stunted, and are chronically undernourished. Children who are below minus three standard deviations (-3 SD) from the median of the reference population are considered severely stunted. Stunting reflects the outcome of a failure to receive adequate nutrition over a long period of time, 114 and is also affected by recurrent and chronic illness. Height-for-age, therefore, represents a measure of the long-term effects of undemutrition in a population and does not vary appreciably according to season o f data coUection. Stunted children are not immediately obvious in a population; a stunted three-year old child could look like a well-fed two-year old. The weight-for-height index measures body mass in relation to body length, and describes current nutritional status. Children whose z-scores are below minus two standard deviations (-2 SD) from the median of the reference population are considered thin, wasted, and are acutely undernourished. 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, causing loss of weight and the onset of undemutrition. Wasting may also reflect acute food shortage. Children whose weight-for-height is below minus three standard deviations (-3 SD) from the median of the reference population are considered to be severely wasted. Table 9.5 Nutritional status b~/demographic characteristics Percentage of children under five years who are classified as undernourished according to thr~ anthropometric indices of nutritional status: height-for-age, weight-for-height, and weight-for-age, by seioeted demographic characteristics, Zambia 1992 Demographic characteristic Height-for-age Weight-fur-height Weight-fur-age Percentage Percentage Percentage Pementage Pumentage Percentage Number below below below below below below of -3 SD -2 SD l -3 SD -2 SD 1 -3 SD - 2 SD 1 eh'tidren Age Under 6 months 2.2 9.1 0.7 2.1 0.7 3.6 588 6-11 months 5.4 22.1 1.2 5.7 4.6 18.2 623 12-23 months 16.7 47.8 1.7 9.9 8.6 35.9 1055 24-35 months 20.4 49.3 1.2 4.9 9.1 34.2 1035 36-47 months 21.6 49.5 0.9 2.4 4.6 24.7 822 48-59 months 16.7 42.5 0.6 3.9 3.1 20.8 776 Sex Male 16.0 41.0 1.0 5.0 6.1 25.6 2427 Female 14.3 38.3 1.2 5.3 5.4 24.7 2472 Birth order 1 14.8 40.2 1.3 4.8 6.3 26.0 1017 2-3 14.8 39.5 1.2 5.1 5.0 25.3 1522 4-5 15.3 39.8 0.9 6.2 6.7 24.5 1002 6+ 15.5 39.3 0.9 4.7 5.4 24.8 1357 Birth Interval First birth 14.9 40.4 1.3 4.7 6.4 26.0 1023 Under 24 months 20.7 46.0 0.6 5.3 7.4 26.2 669 24-47 months 14.6 39.2 1.4 5.5 5.7 25.7 2544 48+ months 11.9 33.7 0.3 4.4 2.8 20.5 663 All children 15.1 39.6 1.1 5.1 5.7 25.1 4899 Note: Figures are for children born in the period 1-59 months preceding the survey. Each index is expressed in terms of the number of standard deviation (SD) units from the median of the NCHS/CDC/WHO international reference population. Children are classified as undemourisbed if their z-scores are bdow minus two or minus three standard deviations (-2 SD or -3 SD) from the median of the reference popu/mion. 1Includes children who are below -3 SD 115 Weight-for-age is a composite index of height-for-age and weight-for-beight; it takes into account both acute and chronic undemutrition. It is a useful tool in clinical settings for continuous assessment of nutritional progress and growth. Children whose weight-for-age is below minus two standard deviations from the median of the reference population are classified as underweight. In the reference population only 2.3 percent of children fall below minus two (-2 SD) for each of the three indices. Table 9.5 shows the percentage of children under five years of age classified as tmdernourished according to height-for-age, weight-for-height, and weight-for-age indices, by the child's age and selected demographic characteristics. Forty percent of the children are classified as stunted (this includes 15 percent who are severely stunted). The figures are high and they suggest that feeding practices for children are very poor. Stunting is relatively uncommon in the first few months of life, but becomes increasingly common as children get older; more than twice as many children aged 6-11 months are stunted as children under 6 months of age; and then, twice as many more children are stunted by two years of age. Almost half of the children age two years and older are stunted. The prevalence of stunting varies very little by sex or birth order. However, stunting occurs more frequently among children born after a short birth interval (less than 24 months), than those bom after a long interval (4 years or more) (46 percent vs. 34 percent). The weight-for-height index gives information about children's recent nutritional status. Severe wasting represents failure to receive adequate nutrition in the period intmediately preceding the survey and may be the result of recent illness, or of seasonal variations in food supply. Five percent of children are reported as wasted, i.e., below minus two standard deviations (-2 SD) from the median of the reference population; one percent are severely wasted (-3 SD). Variations in the level of wasting by demographic characteristics of the child are minimal. Weight-for-age provides an index for chronic and acute undernutrition, but does not distinguish between a child who is underweight because of stunting and one who is underweight because of wasting. One-quarter of children are underweight, implying that the Government's target of 18 percent has not yet been achieved (see Section 1.4). Six percent of children under five are severely underweight (i.e., below minus three standard deviations from the median of the reference population). The likelihood of being underweight v aries little by sex or birth order, but children born 4 years or more after a sibling are less likely to be underweight than those with birth intervals of less than 4 years (26 vs. 21 percent). Children under 6 months of age are the least likely to be underweight (4 percent). This is most likely due to the positive effects of breastfeeding. As shown in Table 9.2, less than 2 percent of children of this age are not being breastfed. After six months of age, the percentage of children who arc underweight rises substantially to 36 percent among the 12-23 month-olds and remains relatively high. The percentage of children under five years of age classified as undemourished according to the three anthropometric indices is presented in Table 9.6 by socioeconomic characteristics. Stunting occurs more frequently among rural than urban children (46 vs. 33 percent). The percentage of children stunted is highest in Northern and Luapula Provinces, followed by Eastem and North-Western Provinces, and lowest in Lusaka and Copperbelt Provinces. One-fifth of the children in Eastern Province and over one-quarter of those in Luapula and Northem Provinces are severely stunted. Similar provincial patterns have been observed in other studies (see Central Statistical Office 1990b). Stunting is inversely related to the level of education of the mother, ranging from almost half of children whose mothers are uneducated to only 9 percent of the children whose mothers have higher than secondary education. Figure 9.1 shows the percentage of children under five years of age who are stunted, by selected socioeconomic characteristics of the mother. 116 Table 9.6 Nutritional status by socioeconomic characteristics Percentage of children unde~ five years who are classified as undernourished eecerding to three enthropometrle indices of nutritional status: height-for-age, weight-for-height end weight-for-age, by selected socioeconomic characteristics, Zambia 1992 Socioeconomic characteristic Height-for-age Walght-fer-height Weight-fee-age Percentage Percentage Percentage Percentage Percentage Percentage Number below below below below below below of -3 SD -2 SD 1 -3 SD -2 SD 1 -3 SD -2 SD 1 children Residence Urban 10.5 32.5 1.2 5.4 3.9 20.8 2305 Rural 19.2 46.0 1.0 5.0 7.3 29.0 2594 Province Central 13.8 38.4 0.7 3.3 4.4 21.5 474 Copparbek 11.7 33.5 1.4 5.3 4.2 22.7 1164 Eastern 20.6 47.6 0.2 3.2 5.4 24.9 490 Luapula 29.6 55.8 0.9 6.0 11.7 39.9 303 Lusaka 10.0 30.8 1.4 8.6 4.9 22.0 757 Northern 28.9 56.5 1.5 6.8 11.7 35.3 502 Nurth-Westem 19.0 42.3 1.5 4.3 7.5 26.4 128 SoutheaTt 8.8 35.4 0.9 3.3 3.8 21.7 824 Western 12.1 41.1 0.8 3.2 4.6 25.8 256 Mother's education No education 21.4 46.0 0.8 5.4 7.8 29.1 831 Primary 15.5 41.6 1.2 5.5 6.0 26.6 3061 Secondary 9.5 30.5 0.8 3.8 3.4 18.0 918 Higher 0.0 8.5 2.5 5.0 1.3 12.6 86 All children 15.1 39.6 1.1 5.1 5.7 25.1 4899 Note: Figures are for children born in the period 1-59 months preceding the survey. Each index is expressed in tetras of the number of standard deviation (SD) units from the me, dlm of the NCHS/CDC/WHO international reference population. Children are classified as undernourished if their z-seems are below minus two or minus three standard deviations (-2 SD or -3 SD) from the median of the reference population. llncludes children who are below -3 SD With regard to the level of wasting among children, there is no significant difference between urban and rural children (5 percent in beth areas). It is surprising to note that the highest level of wasting (8 percent) is reported for children in Lusaka Province, where the national capital is located. The proportion of children underweight (low weight-for-age) is higher in the rural than in the urban areas and children in Luapula and Northern Provinces are more likely to be underweight (35-40 percent). Most of the severely underweight children are also found in these two provinces, provinces with the highest levels of stunting. The proportion of children who are underweight is inversely related to the level of mother's education. 117 Figure 9.1 Percentage of Children Under Five Who Are Chronically Undernourished (Stunted) ZAMBIA RESIDENCE Urban Rural PROVINCE Central Copperbelt Eastern Luapula Luauka Northern North-Western Southern Western EDUCATION No Education Primary Secondary Higher 40 - '' 33 ~ k____ 46 38 48 ~ ' ~ ' ~ " - - 56 31 - - • ~ 57 42 35 • - ~ - - - . 4 1 . ~ a ~ n 46 • ~. - • 42 10 20 30 40 50 60 Percent Note: Chronically undernourished children are those whose height-for-age z-score Is below -2SD based on the NCHS/CDC/WHO reference population. ZDHS 1992 9.3 Nutritional Status of Mothers As mentioned above, all mothers of children born since January 1987--approximately the five years preceding the survey--were eligible to be weighed and measured in the ZDHS. The objective was to obtain a picture of the nutritional status of women of reproductive age; however, since weighing and measuring all respondents would add considerably to the length and cost of the fieldwork, it was decided to limit the anthropometric section to women with young children who would be measured anyway) Women were weighed on an electronic bathroom-type scale which measured the weight to an accuracy of 100 grams and their height was measured with an L-shaped wooden board that was specially designed for the DHS project. Tiffs information was used to construct the following indicators of mothers' nutritional status: Mean height (in centimetres) Mean weight (in kilograms) Body mass index Height and weight measurement is missing for about 2 percent of eligible women. Purthermom, women who were pregnant at the time of the survey and those who had delivered within the two months preceding the survey were excluded from the tables on weight and body mass index. Thus, data on height are available for 3917 women, while data on weight are available for 3418 women. 1 Interviewers were instructed to weigh and measure all women who had a birth since January 1987, regardless of whether or not the child was still living. 118 Table 9.7 presents the distribution of mothers by height, weight and body mass index, along with the means and standard deviations for each of these measures. Height, as well as being a good indicator of socioeconomic status of the mother, is also used to identify mothers at nutritional risk. Height ofmothers can be used to predict the risk of difficulty in delivering children, given the association between height and size of the pelvis. Also, the risk of giving birth to children of low weight is greater among women of small stature. Although the cut-off point at which the mother can be considered at risk varies between popoulations, it probably falls in the range of 140-150 centimetres. The average height of the mothers measured in Zambia (158 centimetres) falls above the critical point. Less than one percent of mothers are shorter than 140 centimetres and less than ten percent are shorter than 150 centimetres. Low pre-pregnancy weight is an important risk factor for unfavourable pregnancy outcomes, although height also needs to be taken into account. The data shown in Table 9.7 exclude pregnant women, as well as those who gave birth in the two months preceding the survey. The mean weight of mothers is 55 kilograms, with a large proportion of women (44 percent) falling in the 50-59 kilogram range. Indices of body mass are used to assess thinness or obesity. The most commonly used index is the BMI (also referred to as the Quetelet index), which is defmed as weight in kilograms divided by the square of the height in meters. The main advantage of the BMI is that it does not require a reference table compiled from a well-nourished population; widely accepted reference tables exist for children, however they are still being developed for women of reproductive age. For the BMI, a cut-off point of 18.5 has been recommended for defining chronic energy deficiency. Obesity has not been defined clearly in terms of the scale. Table 9.7 shows the distribution of women who had a birth in the five years preceding the survey by BMI, as well as the mean BMI. The mean BMI is 22.4, well above the cut-off point of 18.5. Ten percent of mothers fall below the cut-offpeint. Table 9.8 presents differentials by selected socioeconomic characteristics for height, weight and BMI. For each indicator, the mean is presented, as well as the proportion falling below certain rather arbitrary cut-off points. There are few differentials in height of mothers, however the proportion of mothers falling below the cut-off point for BMI is rather high in Western Province (20 percen0. Table 9.7 Anthropometrie indicators of maWr'hal nutritional status Percent distribution of women who delivered a child in the five years preceding th~ sm'vey according to anthropornetric indicatu~, and mean height, weight and body mass index, Zambia 1992 Distribution including Variables rrdssin 8 Height (cms.) <140 0.4 140-144 1,1 145-149 6,9 150-159 51,8 160-169 35.5 170-179 2.6 >= 180 0.1 Missing 1.6 Total 100.0 Mean 157.9 Standard deviation 7.6 Number of women 3980 Weight (kgs.) <40 1.5 40-49 30.1 50-59 43.4 60-69 17.2 >= 70 6.0 Missing 1.8 Total 100.0 Mean 54.9 Standard deviation 9.7 Number of women I 3481 BMI <16.0 0.6 16.0-18.4 9.0 18.5-19.9 18.5 20.0-22.9 41.5 23.0-25.9 17.9 26.0-28.9 6.9 >=29.0 3.7 Missing 1.9 Total 100.0 Mean 22,4 Standard deviation 15.7 Number of women I 3481 1Excludes/msgnam women and lhose who gave birth in the two months preceding the survey 119 Table 9.8 Differentials in maternal anthropometric indicators Mean height and the percentage of women shorter than 145 eentimetres, mean body mass index (BMI) and the percentage of women whose BM[ is less thart 18.5, according to selected background characteristics, Zambia 1992 Height Body mass index (BM/) Background Percent Number Percent Number characteristic Mean <145 of women Mean <18.5 of women Age < 20 157.1 1.2 528 21.1 12.5 455 20-34 158.1 1.7 2629 22.4 9.9 2256 >= 35 157.9 1.3 759 23.0 10.2 705 Residence Urban 158.6 0.8 1847 23.4 8.3 1647 Rural 157.3 2.2 2070 2L4 12.2 1769 Province Central 158.2 0.6 362 22.1 6.8 292 Copperbelt 158.7 1.0 904 24.0 9.7 805 Eastern 156.9 2.0 438 21.6 8.9 385 Luapula 155.1 4. ~1. 243 21.1 13.9 208 Lusaka 158,4 1.1 619 22.8 9.3 566 Northern 156.1 2.9 389 21.1 11.7 323 North~Westem 157.2 3.0 102 21.6 13.0 87 Southern 158.9 0.9 634 22.0 9.2 551 Western 158.4 1.5 227 20.9 19.9 200 Education No education 156.6 2.7 675 21.3 11.5 571 Prim,try 157.7 1,7 2423 22.4 10.5 2105 Secondary 159.4 0.3 749 22.6 9.3 676 Higher 160.9 0.0 69 23.3 7.1 62 Children ever born 1 157.7 1.3 860 21.2 12.8 749 2-3 158.0 1.3 1198 21.5 11.1 1007 4-5 158.3 2.0 764 22.7 8.6 656 6+ 157.6 1.6 1095 23.9 8.8 1004 Total 157.9 1.5 3917 22.4 10.3 3416 Note: Excluded from the BMI index are pregnant women and those who gave birth in the two months preceding the survey. 120 CHAPTER 10 KNOWLEDGE OF AIDS 10.1 Knowledge About AIDS AIDS is a major health problem in Zambia. In order to assess basic knowledge about AIDS transmission and prevention, the ZDHS questionnaire included a section of ten questions about AIDS. Women were first asked i f they had ever heard of AIDS and i f so, from what source they heard information in the last month. They were then asked several questions about various possible means of transmission of the AIDS virus and whether they thought it was possible to prevent AIDS transmission and i f so, how. Finally, respondents were asked what they thought government should do for people with AIDS and who they would prefer to care for a relative with AIDS. Knowledge of AIDS is almost universal among women in Zambia: 99 percent of women interviewed said they had heard of the disease (see Table 10.1 and Figure 10.1). Moreover, this same high level ofknowl- Table 10.1 Knowledge of AIDS Perceaxtage of women who have ever heard of AIDS and percentage reporting variotm modes of transmission, by selected background characterlsitcs, Zambia 1992 Mode of AIDS transmission Ever Ne(~lles, heard Sexual blades, Mother Blood Number Background of inter- skin to trmm- Don't of characteristic AIDS eourso punctures child fusion Other know women Age 15-19 98.0 86.3 14.3 0.8 7.7 2.3 11.7 1984 20-24 98.9 92.3 15.1 0.9 7.3 1.8 6.8 1441 25-29 99.5 93.6 18.0 0.7 9.7 2.3 5.1 1179 30-34 99.5 90.9 17.6 0.3 10.3 1.7 7.5 915 35-39 99.0 92.4 18.6 1.3 10.3 2.3 5.8 656 40-44 99.2 86.6 15.5 1.2 6.2 2.0 11.6 505 45-49 97.5 86.6 14.6 0.8 4.0 2.2 12.4 380 Residence Urban 99.4 93.8 16.6 0.9 12.6 1.5 5.1 3636 Rural 98.1 85.8 15.4 0.7 3.6 2.8 12.2 3424 Province Central 99.1 85.8 9.6 0.5 5.0 3.4 12.2 622 Copperbelt 99.6 93.6 16.4 0.5 11.8 1.8 5.2 1743 Eastern 98.8 76.7 17.4 0.5 4.6 3.9 20.6 729 Luapola 96.9 96.1 30.6 1.6 9.2 1.2 3.4 431 Lusaka 99.4 93.3 13.7 1.1 12.9 1.2 5.6 1234 Northern 97.3 91.6 27.0 2.6 7.6 0.7 6.3 652 North-Western 98.7 90.2 11.6 0.2 7.2 1.8 9.2 183 Sonthem 98.7 87.3 11.3 0.3 3.6 1.4 10.8 1045 Western 97.4 91.6 10.3 0.3 2.6 6.2 6.8 422 Education No education 95.9 81.3 8.7 0.8 1.9 1.5 17.3 1161 Primary 99.2 89.2 13.9 0.4 4.7 2.7 9.0 4213 Secondary 99.7 97.4 23.9 1.5 18.3 1.2 1.6 1561 Higher 100.0 99.1 53.3 6.7 59.7 0.0 0.0 124 Total 98.8 90.0 16.0 0.8 8.2 2.1 8.5 7060 121 100 80 60 40 20 Percent Figure 10.1 Knowledge of AIDS among Women Age 15-49 Ever heard Know AIDS is Know AIDS can Think AIDS can of AIDS transmitted be passed from be prevented sexual ly mother to child ZDHS 1992 edge is found among women at every age group, in rural as well as urban areas and in every province and education group. It is also encouraging that the vast majority of women (90 percent) know that AIDS is transmitted through sexual intercourse. Far fewer reported other modes of transmission such as needles, skin punctures, birth, or blood transfusions. This may indicate lack of knowledge, but it could also be due to the interviewing process. Interviewers were instructed to mark all modes of transmission mentioned by the respondent and to probe for other means; however, it is likely that many marked only the first answer the respondent gave and did not probe for others. In any case, it appears that women in Eastern Province are relatively less knowledgable about how AIDS is transmitted---only three-quarters of them said that AIDS could be transmitted by sexual intercourse and one in five said they did not know how AIDS is transmitted. Knowledge of AIDS transmission is better among more educated women. ZDHS respondents were also asked if they thought they could get AIDS from a variety of not uncommon social situations such as shaking hands with somone who has AIDS or sharing clothing or eating utensils with someone who has AIDS. These situations are generally believed to pose extremely low risk of transmission of the AIDS vires. Women were also asked if they thought it was possible for a healthy-looking person to be carrying the AIDS virus or for a woman with the AIDS virus to give birth to a ch'tld with the virus. The results are shown in Table 10.2. 122 Table 10.2 Perceived modes of AIDS transmission Percentage of women who think it is possible to get AIDS by various means, according to urban-rural residence, Zambia 1992 Mode of transmission Urban Rural Total Possible to get AIDS by: Shaking hands with someone who has AIDS 7.8 23.6 15.4 Hugging someone who has AIDS 9.6 26.9 17.9 Kissing someone who has AIDS 42.0 54.5 48.0 Sharing the clothes of someone who has AIDS 21.7 43.9 32.4 Sharing eating utensils with someone who has AIDS 20.1 39.6 29.5 Stepping on the urine or stool of someone who has AIDS 40.7 58.0 49.0 Mosquito, flies or bedbug bites 53.6 68.1 60.6 Possible for a healthy-looking person to carry AIDS? Yes 83.0 67.0 75.3 No 12.4 23.4 17,7 Don't know 4.1 9.4 6.7 Missing 0.5 0.2 0.3 Possible for a woman with AIDS to give birth to a child with AIDS virus? Yes 91.0 80.8 86.1 No 4.6 9.6 7.0 Don't know 4.1 9.5 6.7 Missing 0.3 0.2 0.2 Number of women 3616 3357 6973 Less than 20 percent of women believe that it is possible to get AIDS from shaking hands with or hugging someone who has AIDS, however, almost half say that it is possible to get AIDS from kissing someone with the disease. Sharing clothes or eating utensils with someone with AIDS was mentioned as a mode of transmission by less than one-third of the women interviewed, while stepping on the urine or stools of someone who has AIDS was mentioned by half of the women and mosquito, flea or bedbug bites were mentioned as a possible means of transmission by 61 percent of women. Rural women are much more likely than urban women to believe that it is possible to contract AIDS from the situations asked about in the ZDHS. Three-quarters of the ZDHS respondents said that it was possible for a healthy-looking person to be carrying the AIDS virus and 86 percent said that it is possible for a woman with AIDS to give birth to a child with the virus, A higher proportion of urban than rural women responded affirmatively to these two questions. These results show that Zambian women are generally quite knowledgable about the main sources of AIDS transmission; however, many also believe that it can be transmitted through casual contact and insect bites as well. Urban women appear to be considerably more knowledgable about the means of AIDS transmission than rural women. Only 63 percent of women believe that AIDS can be prevented (see Table 10.3). The vast majority of them say that sticking to one partner is a way to prevent the disease, with very few reporting other means of prevention. Again, this could be due to lack of probing by interviewers rather than lack of knowledge of other means of prevention, Differences between urban and rural women are minimal. 123 Table 10,3 Perceptions about AIDS prevention Percent distribution of women age 15-49 by whether they believe AIDS can be prevented and, of those who believe it can be prevented, the percentage reporting various means of prevention, according to urbma-rural residence, Zambia 1992 AIDS preventability/ Means of prevention Urban Rural Total Can AIDS be prevented? Yes 69.6 56.1 63.1 No 26.1 31.4 28.6 Don't know 3.9 12.4 8.0 Missing 0.4 0.1 0.3 Total 100.0 100.0 100.0 Number of women 3616 3357 6973 Among those who believe AIDS Is preventable, percentage reporting means: Stick to one partner 94.2 90.7 92.7 Use condoms 9.1 5.9 7.8 Sterilise needles 7.5 6.5 7.1 Other 6.8 10.3 8.3 Number of women 3616 3357 6973 10.2 Sources of Information about AIDS The government of Zambia has been actively seeking to inform the general public about AIDS and how to prevent its spread. Table 10.4 indicates that dissemination of AIDS information is widespread. Although the largest single source of information cited was friends and relatives (60 percent), almost 40 percent of women had heard about AIDS on the radio in the month preceding the survey and one-third said they had heard about AIDS from health workers. Ten percent of women had heard about AIDS from television and 10 percent from slogans, pamphlets or posters in the month preceding the interview. In fact, only 9 percent of women said they had not heard any information about AIDS in the pre- vious month. As might be expected, radio, television and newspapers are a more impor- tant source of AIDS information for urban women than for rural women. Table 10.4 Sources of AIDS information Percentage of women who report hearing of AIDS from various sources in the month before the survey, by urban-rural residence, Zambia 1992 Source of information Urban Rural Total Radio 54.3 22.3 38.9 Television 18.1 1.4 10.1 Newspaper 13.8 3.2 8.7 Health worker 33.6 35.6 34.5 Church 4.9 5.6 5.2 Friend/relative 58.0 62.1 60.0 School/teacher 8.7 4.5 6.7 Slogan/poster/pamphlet 14.2 5.3 9.9 Community meeting 2.7 2.0 2.4 Other 1.2 4.1 2.6 None 8.5 10.5 9.4 Number of women 3616 3357 6973 124 10.3 Attitudes about AIDS ZDHS respondents were asked what they thought was the most important thing the government should do for people who have AIDS. As shown in Table 10.5, three in five said govemment should provide medical treatment. Ten percent think that government should quarantine those with AIDS and ten percent think government should not be involved. Three in five women say that i f a relative were suffering from AIDS, they would prefer relatives and friends to care for him or her. Almost one-quarter say they would prefer government to provide care. Urban and rural women do not differ much in their responses to these questions. Table 10.5 Attitudes toward AIDS Percent distribution of women by perception of the most important action government could take for people with AIDS and by preferred caretakers for a relative with AIDS, according to urban-rural residence, Zambia 1992 Government action/ Preferred caretaker Urban Rural Total Suggested government action Provide medical treatment 58.7 64.7 61.6 Help relatives provide care 4.6 1.7 3.2 Isolate/Quorantine/Jail 11.9 8.7 10.4 Not be involved 10.7 9.1 9.9 Other 13.7 15.6 14.6 Missing 0.3 0.1 0.2 Total I00.0 100.0 100.0 Preferred caretaker Relatives/friends 62.8 60,9 61.9 Government 24.5 22.2 23.4 Religious organisation/mission 0.2 0.1 0.1 Nobody, abandon 2.8 6.7 4.6 Other 9.7 10.1 9.9 Missing 0.1 0.0 0.1 Total 100.0 100.0 100.0 Number of women 3616 3357 6973 125 REFERENCES Arnold, Fred. 1990. Assessment of the Quality of Birth History Data in the Demographic and Health Surveys. InAnAssessmentofDHS-I Data Quality, 81-111, DHS Methodological Reports No. 1. Columbia, Maryland: Institute for Resource Development/Macro Systems Inc. Central Statistical Office [Republic of Zambia]. 1974. 1969 Population and Housing Census of Zambia, Final Report Vol. Ill--Demographic Analysis. Lusaka: Central Statistical Office. Central Statistical Office [Republic of Zambia]. 1985a. 1980 Population and Housing Census of Zambia, Analytical Reports Vol. ll--Demographic and Socio-economic Characteristics of Zambia. Lusaka: Central Statistical Office. Central Statistical Office [Republic of Zambia]. 1985b. 1980 Population andHousing Census of Zambia, Analytical Reports Vol. IV. Lusaka: Central Statistical Office. Central Statistical Office [Republic of Zambia]. 1990a. 1990 Census of Population, Housing and Agriculture: Preliminary Report. Lusaka: Central Statistical Office. Central Statistical Office [Republic of Zambia]. 1990b. Report of the Pilot Nutrition Module: Survey of Rural Zambia Undertaken As Part of the Crop Forecasting Survey. Lusaka: Central Statistical Office. Central Statistical Office [Republic of Zambia]. 1991. Women and Men in Zambia. Lusaka: Central Statistical Office. Martorell, R. and LP. Habiclat. 1986. Growth in Early Childhood in Developing Countries. In Human Growth: A Comprehensive Treatise. ed. by Frank Falkner and J.M. Tanner, Vol. 3,241-262. New York: Plenum Press. Ministry of Health [Republic of Zambia]. 1990. Bulletin of Health Statistics 1987-1988: Major Health Trends 1978-1988. Lusaka: Minislry of Health, Health Information Unit. Ministry of Health [Republic of Zambia]. 1992. National Health Policies and Strategies (Health Reforms). Lusaka: Ministry of Health, Planning Unit. National Commission for Development Planning [Republic of Zambia]. n.d. Zambia' s National Population Policy. Lusaka: National Commission for Development Planning. Republic of Zambia. 1992. Budget Address. Lusaka: Government Printer. Rutstein, Shea Oscar and Bicego, George T. 1990. Assessment of the Quality of Data Used to Ascertain Eligibility and Age in the Demographic and Health Surveys. In An Assessment ofDHS-lData Quality, 3-37, DHS Methodological Reports No. 1. Columbia, Maryland: Institute for Resource Development/Macro Systems Inc, United Nations. 1991. WorldPopulationProspects 1990. New York: Department oflntematinnalEconomic and Social Affairs. Population Division (Population Studies No. 120). World Bank. 1992. World Development Report: Development and Environment. New York: Oxford University Press. 127 APPENDIX A SURVEY DESIGN APPENDIX A SURVEY DESIGN A.1 Sample Design and Implementation Zambia is divided administratively into 9 provinces and 57 districts. In preparation for the 1990 Census of Population, Housing and Agriculture, the entire country was demar- cated into Census Supervisory Areas (CSAs). Each CSA was in turn divided into Standard Enumeration Areas (SEAs) of roughly equal size. The measure of size used for selecting the ZDHS sample was the number of households obtained during a quick count operation carried out in 1987. The frame of 4240 CSAs was stratified into urban anti rural areas within each province, with the districts ordered geog- raphically within provinces, thus providing further implicit stratification. The ZDHS sample was selected from this frame in three stages. First, 262 CSAs (149 in urban areas and 113 in rural areas) were selected from this frame with probability pro- portional to size (the number of households from the quick count). One SEA was then selected from within each sampled CSA, again with probability proportion to size. The Central Statistical Office (CSO) then organised a household listing operation, in which all struc- tures in the selected SEAs were numbered (on doors), the names of the heads of households were listed and the households were marked by number on sketch maps of the SEAs. These household lists were used to select a systematic sample of households for the third and final stage of sampling. Initially, the objective of the ZDHS sample design was to be able to produce esti- mates at the national level, for urban and rural areas separately, and for the larger provinces. Since Zambia's population is almost equally divided by urban and rural residence, a self- weighting sample was originally designed. Later, it was decided that it would be desirable to be able to produce separate estimates for all Table A.1 Sample desi~ parameters Distrlbut'tort of 1990 census population and. number of CSAs allocated end number of households selected in the ZDHS sample Number Number of Population of CSAs households Stratum (1990) Percent allocated selected Urban Centr~ 216023 6.6 10 203 Copperbelt 1428697 43.5 64 1036 Eastern 85714 2.6 4 61 Luapula 83036 2.5 4 79 Lusaka 1041473 31.7 47 831 Northern 123457 3.8 6 82 North-Western 45599 1.4 2 44 Southern 190384 5.8 9 234 Western 71383 2.2 3 37 Total 3285766 100.0 149 2607 Rural Cen~ 509588 11.2 10 394 Copperbelt 150845 3.3 3 131 Eastern 888104 19.6 17 604 Luapula 443669 9.8 16 577 Lusaka 166507 3.7 3 113 Northern 744338 16.4 14 527 North-Western 337547 7.5 18 624 Southern 755969 16.7 15 508 Westem 536114 11.8 17 624 ToM 4532681 100.0 113 4102 Total Central 725611 9.3 20 597 Copperbelt 1579542 20.2 67 1167 Eastern 973818 12.5 21 665 Luapula 526705 6.7 20 656 Lusaka 1207980 15.5 50 944 Northern 867795 ll.l 20 609 North-Western 383146 4.9 20 668 Southern 946353 12.1 24 742 Wastem 607497 7.8 20 661 Total 7818447 100.0 262 6709 131 nine provinces. To achieve this objective, additional rural CSAs (and SEAs) were selected inLuapula, North- Western and Western Provinces and the sample take (number of households) in each rural SEA in these provinces was reduced from 42 to 35 in order to minimise the total sample size increase (the sample take was 20 households in urban areas). As a result of this oversampling in Luapula, North-Western and Western Provinces, the ZDHS sample is not self-weighting at the national level. Table A.1 presents data on the distribution of the population and various sample parameters by province. Results of the sample implementation by province and urban-rural residence am presented in Table A.2. The results indicate that of the 6709 households selected, ZDHS interviewers successfully interviewed 93 percent. Three percent of the households selected were found to be either vacant or not a valid household, while another 3 percent were absent (not at home). The response rate at the household level was 96 percent. In the interviewed households, 7247 eligible women were found, of whom 97 percent were interviewed. A.2 Fieldwork The ZDHS household and individual questionnaires were pretested September-October 1991. Sixteen staff from the Ministry of Health (mostly nurses and clinical officers) who spoke the languages into which the questionnaires had been translated were trained for two weeks at the Mwachisompola Health Demonstration Clinic, about one hour's drive from Lusaka. In the following I0 days, these interviewers completed 109 interviews mostly in Lusaka and Central Province. Training of field staff for the main survey was conducted at the University of Zambia. Atter one-week training sessions--first for the trainers and then for the supervisors and field editors in early Decem- ber-interviewers were trained from 16 December 1991 to 5 January 1992. Staff from the University, the CSO, the Ministry of Health, Planned Parenthood Association of Zambia, and Macro International conducted the four-week training course. A total of 72 candidates were trained, including most of those who had par- licipated in the pretest. With the exception of two supervisors from the CSO, all candidates for fieldstaff positions were recruited from the Ministry of Health and consisted of nurses, nurse/midwives and clinical officers. The training course consisted of instruction in general interviewing techniques, field procedures, a detailed review of items on the questionnaires, instruction and practice in weighing and measuring children, mock interviews between participants in the classroom, and practice interviews in the field. Trainees who performed satisfactorily in the training programme were selected as interviewers, while those whose performance was rated as superior were selected as field editors. Those whose performance was satisfactory, but who either could not travel in the field or who did not speak one of the major languages in Zambia, were selected as data processing staff. The fieldwork for the ZDHS was carried out by 10 teams. Each consisted of one supervisor, one field editor, four interviewers and one driver; however, due to heavier workloads in their provinces, one team had five interviewers and another had six. In total, there were 10 supervisors, 10 field editors, 43 interviewers, and 10 drivers. Of the interviewers, 34 were women and 9 were men. In addition, each team was assigned a fieldwork coordinator, generally one of the trainers, who spent approximately half of the fieldwork lime in the field with his/her team. Each team was assigned a vehicle either by the CSO or another government agency and team members moved together through the areas assigned to them. Fieldwork commenced on 18th January and was completed on 15th May 1992. 132 Table A.2 Sample implementation Percent dislribution of households and eligible women by result of the intea'view and household response rates, eligible woman response rates, mad overall response rates, according to sample domain and urbm-rural residence, Zambia 1992 Province North Residence Coppex-East- Lua- North- West- South- West- Result Central belt em pola Lusaka era em em em Urban Rural Total Selected households Completed (C) 92.1 97,0 94.1 90.4 95.3 94.6 75.6 97.8 92.0 96.2 90.2 92.5 tloesehold present but no competent respondent at home (P) 0.3 0,4 0.0 0.3 0.3 0.2 0.0 0.4 0.3 0.3 0.2 0.3 Refused (R) 0.2 0,1 0.0 0.3 0.0 0.0 0.0 0.1 0.0 0.1 0.1 0.1 Dwelling not found (DNF) 0.2 0,0 0.6 0.3 0.0 0.2 0.6 0.0 0.2 0.1 0.2 0.2 Household absent (HA) 3.2 0,5 1.4 1.4 1.1 2.6 12.8 0.6 2.1 1.1 3.6 2.6 Dwelling vacant/address not a dwelling (DV) 3.2 1.9 2.4 6.6 3.2 2.1 6.7 1.0 4.5 2.1 4.2 3.4 Dwelling destroyed (DD) 0.8 0.0 1.2 0.8 0.1 0.3 O.ll 0.1 0.3 0.1 0.5 0.4 Other (O) 0.0 0.1 0.3 0.0 0.0 0.0 4.3 0.0 0.6 0.ll 0.9 0.6 Total percent 1011.0 100.0 100.0 100.0 100.ll 100.0 100.ll 100.0 100.0 100.0 100.0 100.0 Number 597 1167 665 656 944 609 698 712 661 2577 4132 6709 Household response rate (HRR) 1 96.0 98.9 97.7 97.5 98.6 97.0 81.1 98.9 96.7 98.3 94.7 96.1 Ellgthle women Completed (EWC) 97.6 96.6 97.3 98.5 97.8 97.8 94.6 98.3 97.8 97.4 97.4 97.4 Not at home (EWNH) 1.4 2.6 1.5 0.5 1.7 1.5 4.6 1.5 1.2 2.0 1.7 1.8 Postponed (EWP) 0.0 0.0 0.0 0.0 0.0 0.0 0.2 0.0 0.0 0.0 0.0 0.0 Refused (EWR) 0.3 0.4 0.3 0.3 0.3 0.2 0.0 0.0 0.0 0.3 0.2 0.2 Partly completed (EWPC) 0.0 0.1 0.1 0.3 0.1 0.3 0.2 0.0 0.2 0.1 0.2 0.1 Other (EWe) 0.7 0.2 0.7 0.3 0.2 0.2 0.2 0.2 0.8 0.2 0.5 0.4 Total Percent I00.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 Number 579 1662 676 598 1163 603 409 963 594 3446 3801 7247 Eligible woman response rate (EWRR) 2 97.6 96.6 97.3 98.5 97.8 97.8 94.6 98.3 97.8 97.4 97,4 97.4 Overall resl~ouse rate (eRR) a 93.7 95.5 95.1 96.1 96.4 94.9 76,7 97.2 94.5 95.8 92,3 93.7 Note: The household response rate is calculated for completed households as a proportion of completed, no competent respondent, postponed, refused, dwelling not found and household absent. The eligible woman response rate is calculated for completed interviews as a proportion of completed, not at home, postponed, refused, partially completed and "other." The overall response rate is the product of the household and woman response rates. 1Using the number of households falling into specific response categories, the household response rate (HRR) is caleolated as: C C+RP+ P +R+ DNF-~HA 2Using the number of eligible women falling into specific response categories, the eligible woman response rate (EWRR) is calculated as: EWC EWC + EWNH + EWP + EWR + EWPC + Ewe ~The overall response rate (eRR) is calculated as: eRR -- HRR * EWRR 133 A.3 Data Processing All questionnaires for the ZDHS were retumed to the University of Zambia for data processing. The processing operation consisted of office editing, coding of open-ended questions, data entry, and editing errors found by the computer programs. Two programmers (one from the CSO and one from the University), one questionnaire administrator, two office editors, and three data entry operators were responsible for the data processing operation. The data were processed on four microcomputers owned by the Department of Social Development Studies at the University of Zambia. The ZDHS data entry and editing programs were written in ISSA (Integrated System for Survey Analysis) and followed the standard DHS consistency checks and editing procedures. Simple range and skip errors were corrected at the data entry stage. Secondary machine editing of the data was initiated as soon as a sufficient number of questionnaires had been entered. The purpose of the secondary editing was to detect and correct, if possible, inconsistencies in the data. No major problems were encountered during data editing. Data processing commenced on 22nd January and was completed on 20th June 1992. 134 APPENDIX B ESTIMATES OF SAMPLING ERRORS APPENDIX B ESTIMATES OF SAMPLING ERRORS The estimates from a sample survey are affected by two types of errors: (1) nonsampling error, and (2) sampling error. Nonsampling error is the result 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 ZDHS to minimize this type of error, nonsampling errors are impossible to avoid and difficult to evaluate statistically. Sampling errors, on the other hand, can be evaluated statistically. The sample of women selected in the ZDHS 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. The sampling error is 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. 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 women had been selected as a simple random sample, it would have been possible to use straightforward formulas for calculating sampling errors. However, the ZDHS sample is the result of a three-stage stratified design, and, consequently, it was necessary to use more complex formulas. The computer package CLUSTERS, developed by the International Statistical Institute for the World Fertility Survey, was used to compute the sampling errors with the proper statistical methodology. The CLUSTERS package 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: mr(r) = l - f mh ,r-, 2 Zh x 2 h=l ~ 2.+,z~--L-- Ir=l tt;h in which zss -- y~- r .xu , and z h -- Yh-r, xh where h mk Yhi xhl f represents the stratum which varies from 1 to H, is the total number of standard enumeration areas selected in the h th stratum, is the sum of the values of variable y in SEA i in the h th stratum, is the sum of the number of cases (women) in SEA i in the h th stratum, and is the overall sampling fraction, which is so small that CLUSTERS ignores it. 137 In addition to the standard errors, CLUSTERS 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 DEbT 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. CLUSTERS also computes the relative error and confidence limits for the estimates. Sampling errors for the ZDHS are calculated for selected variables considered to be of primary interest. The results are presented in this appendix for the country as a whole, for urban and rural areas, and for the nine provinces. For each variable, the type of statistic (mean or proportion) and the base population are given in Table B. 1. Tables B.2 to B. 13 present the value of the statistic (R), its standard error (SE), the number of unweighted (N) and weighted (WN) cases, the design effect (DEFT), the relative standard error (SE/R), and the 95 percent confidence limits (R-~SE), for each variable. In general, the relative standard error for most estimates for the country as a whole is small, except for estimates of very small proportions. There are some differentials in the relative standard error for the estimates of sub-populations such as geographical areas. For example, for the variable EVBORN (children ever born to women aged 15-49), the relative standard error as a percent of the estimated mean for the whole country, for urban areas and for rural areas is 1.3 percent, 1.7 percent, and 1.9 percent, respectively. The confidence interval (e.g., as calculated for EVBORN) can be interpreted as follows: the overall average from the national sample is 3.105 and its standard error is .040. Therefore, to obtain the 95 percent confidence limits, one adds and subtracts twice the standard error to the sample estimate, ie. %105+.080. There is a high probability (95 percent) that the true average number of children ever born to all women aged 15 to 49 is between 3.025 and 3.185. 138 Table B.1 List of Selected Variables for Sampling Errors, Zambia 1992 Variable Estimate Base population URBAN SECOND CURMAR MAR20 SEX18 EVBORN EVB4049 SURVIV KMETHOD KMODMET KSOURCE EVUSE CUSING CUMODERN CUPILL CUIUD CUCOND CUSTERIL CUPABST PSOURCE NOMORE DELAY IDEAL TETANUS MDCARE DIARR1 DIARR2 ORSTRE MEDTRE HCARD BCG DFT3 POLIO3 MEASLES FULLIM Urban Proportion With secondary education or higher Proponiun Currently married Proportion Married before age 20 Proportion Had first sexual intercourse before 18 Proportion Children aver born Mean Children ever born to women over 40 Mean Children surviving Mean Knowing any contraceptive method Proportion Knowing any modern method Proportion Knowing source for any method Proportion Ever used may contraceptive method Proportion Currently using any method Proportion Currently using a modem method Proportion Currently using pill Proportion Currently using IUD Proportion Currently using condom Proportion Currently using female sterilization Proportion Currently using periodic abstinenea Proportion Using public sector sunrea Proportion Wanting no more children Proportion Wenting to delay m least 2 ye~s Proportion Ideal number of children Mean Mothers received tetanus injection Proportion Received medical care at birth Proportion Had diarrhea in last 24 hours Proportion Had diarrhea in last 2 weeks Proportion Treated with ORS packets Proportion Consulted a medical facility Proportion Having health card, seen Proportion Received BCG vaccination Proportion Received DPT vaccination (3 doses) Proportion Received polio vaccination (3 doses) Proportion Received measles vaccination Proportion Fully immunized Proportion All women All women All women Women aged 20 and older Women aged 20 end older All women Worama aged 40-49 All women Cu~entl r married women Currentl : m~'ried women Currunll t married women Cunentl t married women Cusrentl : m~ women Currantl : married women Cun'entl manied women Currentl t married women Currend mmied women Onrunfl ¢ married women Cmrenfl I married women Current users of modern method Curreauly married women Curtentiy married women All women Births in last 5 years Births in last 5 years Children under 5 Chilthen under 5 Children onder 5 with diarrhea in last 2 weeks Children under 5 with diarrhea in last 2 weeks Children 12-23 months Children 12-23 months Children 12-23 months Children 12-23 months Children 12-23 months Children 12-23 months 139 Table B,2 Sampling errors t entire sample t Zambia 1992 Number of cases Variable Standard Value error (R) (SE) Design Relative Confidence limits Unweighted Weighted effect error (N) (WN) (DEFT) (SE/R) R-2SE R+2SE URBAN SECOND CURMAR MAR20 SEX18 EVBORN EVB4049 SURVIV KMETHOD KMODMET KSOURCE EVUSE CUSING CUMODERN CUPILL CUIUD CUCOND CUSTERIL CUPABST PSOURCE NOMORE DELAY IDEAL TETANUS MDCARE DIARR 1 DIARR2 ORSTRE MEDTRE HCARD BCG DPT3 POLIO3 MEASLES FULLIM .515 .012 .239 .009 .631 .008 .730 .008 .723 .007 3,105 ,040 7.694 .110 2.566 .032 • 937 .004 • 907 .006 • 875 .007 • 492 .012 .152 .008 .089 .006 .043 .004 ,005 ,001 .018 .002 .021 .002 .009 .002 .561 ,O27 .220 ,007 A06 .009 5.786 .042 .814 .010 .505 .015 ,081 ,004 .228 .007 .529 .016 .546 .017 .757 .016 .951 .009 .768 .016 .764 .016 .770 .016 .666 .017 7060 7060 1.944 .022 .492 .538 7060 7060 1.719 .037 .221 .256 7060 7060 1,317 .012 .616 .646 5096 5076 1.232 .010 .715 .746 5096 5076 1.187 .010 .708 .738 7060 7060 1,069 .013 3,025 3,185 901 885 1,106 .014 7.473 7.915 7060 7060 1.010 .012 2.502 2.630 4467 4457 1.233 .005 .928 .946 4467 4457 1,432 .007 .895 .920 4467 4457 1,469 .008 .861 .890 4467 4457 1.615 .025 .468 .516 4467 4457 1.430 .051 .137 .167 4467 4457 1.352 .065 .077 .100 4467 4457 1.162 .082 .036 .050 4467 4457 1,045 ,230 ,002 .007 4467 4457 1.159 .129 .013 .022 4467 4457 1.092 .113 .016 .025 4467 4457 1.197 .185 .006 .013 473 493 1,170 .048 .507 .614 4467 4457 1,080 ,030 ,207 ,234 4467 4457 1,170 .021 .389 .423 6636 6624 1.358 .007 5.703 5.870 6236 6215 1.705 .012 .795 .834 6236 6215 1.843 .029 .476 .534 5332 5332 1,050 ,050 .073 ,089 5332 5332 1.166 .030 .214 .242 1207 1216 1.061 .030 .497 .561 1207 1216 1.102 .030 ,513 .579 1134 1123 1.215 .021 .725 .788 1134 1123 1.449 .010 .932 .970 1134 1123 1.285 .021 .735 .801 1134 1123 1.280 .022 .731 .797 1134 1123 1.262 .021 .738 .802 1134 1123 1.207 .026 .632 .700 140 Table B.3 Sampling errors T urban areas I Zambia 1992 Value Variable (R) Number of cases Standard Design Relaf~ve error Unweighted Weighted effect error (SE) (N) (WN) (DEFT) (SE/R) Confidence Funi~ R-2SE R+2SE URBAN 1.000 SECOND .378 CURMAR .575 MAR20 .676 SEX18 ,682 EVBORN 2.786 EVB4049 7.443 SURVIV 2.384 KMETHOD .972 KMODMET .965 KSOURCE .945 EVUSE .596 CUSING .208 CUMODERN ,153 CUPILL .079 CUIUD .010 CUCOND .026 CUSTERIL .033 CUPABST .014 PSOURCE .554 NOMORE .240 DELAY .419 IDEAL 5.206 TETANUS .872 MDCARE .790 DIARR1 .066 DIARR2 .200 ORSTRE .593 MEDTRE .619 HCARD .769 BCO .983 DI:q'3 .845 POLIO3 .838 MEASLES .813 FULLIM .744 .000 3358 3636 .000 .000 1.000 1.000 ,014 3358 3636 1,615 ,036 .351 ,405 .009 3358 3636 1.109 .016 .556 .594 .011 2364 2560 1.138 .016 .654 .697 ,012 2364 2560 1,212 .017 ,659 ,705 .048 3358 3636 .927 .0]7 2.691 2,882 .180 323 350 1.097 .024 7.083 7.802 .042 3358 3636 .936 .018 2.300 2,469 .004 1931 2091 1.099 .004 ,963 .980 .005 1931 2091 1.104 .~15 .956 .974 .006 1931 2091 1.224 .(~7 .932 ,957 .015 1931 2091 1.338 .025 .566 .626 .012 1931 2091 1.333 .059 .183 .Z32 .011 1931 2091 1,313 .070 .131 .174 .007 1931 2091 1.092 .085 .065 .(392 .002 1931 2091 1.003 .229 .005 .014 .004 1931 2091 1,045 .146 .018 .033 .004 1931 2091 1,106 .137 .024 .042 .003 1931 2091 1,174 .224 .008 .020 .030 363 393 1,143 .054 .494 .613 .011 1931 2091 1, l l l .045 .218 .261 .014 1931 2091 1,208 .032 .392 .447 .048 3201 3466 1,243 .009 5.110 5.303 .007 2664 2885 1,047 .008 .858 .887 .014 2664 2885 1.485 .018 .762 .818 .005 2322 2514 1.008 .083 .055 .077 .010 2322 2514 1.218 .052 .179 .221 • 022 464 502 .912 .037 .549 .636 .023 464 502 .979 .037 .572 .665 .020 476 515 1.046 .027 .728 .810 .006 476 515 1.010 .tD6 .971 .995 .017 476 515 1.000 .020 .811 .879 .018 476 515 1.021 .021 .803 .873 .018 476 515 .971 .022 ,778 .848 .020 476 515 .987 .027 .704 .784 141 Table B.4 Sampling errors~ rural areas~ Zambia 1992 Number of cases Variable Standard Value error (R) (SE) Design Relative Confidence limits Unweighted Weighted effect error (N) (WN) (DEFT) (SE/R) R-2SE R+2SE URBAN SECOND CURMAR MAR20 SEX18 EVBORN EVB4049 SURVIV KMETHOD KMODMET KSOURCE EVUSE CUSINO CUMODERN CUPILL CUIUD CUCOND CUSTERIL CUPABST PSOURCE NOMORE DELAY IDEAL TETANUS MDCARE DIARR1 DIARR2 ORSTRE MEDTRE HCARD BCG DPT3 POLIO3 MEASLES FULLIM .000 .000 .091 .010 .691 .011 .786 .010 .764 .009 3.443 .065 7.858 .139 2.760 .048 .906 .007 .857 .010 .814 .012 .400 .017 .103 .009 .032 .005 .011 .003 .000 .000 .011 .003 .010 .002 .005 .002 .588 .058 .203 .008 .394 .011 6,423 ,062 .764 .018 .258 .019 .094 .006 .253 .009 .484 .022 .495 .022 .747 .023 .924 .017 .703 .027 .700 .027 .734 .026 .600 .027 3702 3424 .000 .000 ,000 .000 3702 3424 2.088 .109 .071 .110 3702 3424 1.469 .016 .669 .713 2732 2516 1.310 .013 .765 .807 2732 2516 1.136 .012 .746 .783 3702 3424 1.213 .019 3.313 3.573 578 535 1.106 .018 7.581 8,136 3702 3424 1.088 .017 2.663 2.856 2536 2366 1.250 .008 .892 .921 2536 2366 1.508 .012 .836 .878 2536 2366 1.547 .015 .790 .838 2536 2366 1.705 .041 .367 .433 2536 2366 1.560 .092 .084 .121 2536 2366 1.378 .150 .023 .042 2536 2366 1.346 .256 .005 .016 2536 2366 .000 .0130 .000 .000 2536 2366 1.329 .253 .005 .016 2536 2366 .924 .185 .006 .013 2536 2366 1.177 ,327 .002 .008 110 100 1.223 .098 .473 .704 2536 2366 1.046 .041 .186 .220 2536 2366 1.120 .028 .372 .415 3435 3158 1,352 ,010 6,300 6.546 3572 3330 2.093 .023 .728 .799 3572 3330 2.171 .073 .220 .296 3010 2817 1.101 .064 .082 .105 3010 2817 1.114 .035 .235 ,271 743 713 1.141 .045 .441 .527 743 713 1.138 .044 .452 ,538 658 607 1.360 .031 .700 ,794 658 607 1.593 .018 .890 .957 658 607 1.493 .038 .649 .757 658 607 1.478 .038 .647 .754 658 607 1.471 .035 .683 .785 658 607 1,394 .045 ,546 .654 142 Table B.5 Sampling enors, Centcal Province, Zambia 1992 Variable Number of cases Standard Design Relative Confidence limits Value error Unweighted Weighted effect error (R) (SE) (N) (WN) (DEFT) (SE/P.) R -2SE R+2SE URBAN SECOND CURMAR MAR20 SEX18 EVBORN EVB4049 SURVIV KMETHOD KMODMET KSOURCE EVUSE CUSING CUMODERN CUPILL CUIUD CUCOND CUSTERIL CUPABST PSOURCE NOMORE DELAY IDEAL TETANUS MDCARE DIARR1 DIARR2 ORSTRE MEDTRE HCARD BCG DPT3 POLIO3 MEASLES FULLIM .355 .039 .212 .036 .671 .032 .739 .020 .762 .028 3.211 .149 7.573 .434 2.687 .123 .743 .022 .706 .029 .677 .034 .339 .023 .092 .020 .068 .016 .042 .010 A~00 .000 .016 ,005 .008 .004 .008 .006 .875 ,071 .232 ,027 .390 .021 6.022 .180 .785 ,051 .390 .049 .107 ,016 .221 ,016 .628 .040 .525 ,049 .755 ,053 .918 ,054 .765 ,069 .754 .070 .724 .064 .632 .072 565 622 1.939 .110 .277 .433 565 622 2.101 .170 .140 .285 565 622 1.595 .047 .608 .735 424 467 .944 .027 .699 ,779 424 467 1.354 .037 .706 .818 565 622 1.115 .046 2.913 3.510 79 87 1.187 .057 6.706 8,440 565 622 1.078 .046 2.441 2.933 379 418 .964 .029 .700 .786 379 418 1.255 .042 .647 .765 379 418 1.397 .050 .610 .744 379 418 .938 .067 .293 .385 379 418 1.370 .221 .051 .133 379 418 1.204 .229 .037 .099 379 418 1.013 .249 .021 .063 379 418 .000 .1300 .000 .000 379 418 .748 .303 .006 .025 379 418 .981 .565 -.001 .017 379 418 1.229 .705 -.003 .019 32 35 1.193 .081 .733 1.017 379 418 1.239 .116 .179 .286 379 418 .852 .055 .347 .433 512 564 1.697 .030 5.663 6.382 540 595 2.459 .065 .682 .887 540 595 1.905 .127 .291 .489 476 525 1.057 .145 .076 .138 476 525 .826 .072 .189 .253 105 116 .787 .063 .549 .707 105 116 .966 .094 .427 .624 98 108 1.180 .070 .649 .861 98 108 1.939 .059 .810 1.025 98 108 1.601 .090 .627 .902 98 108 1.613 .093 £14 .895 98 108 1.414 .089 .596 .852 98 108 1.477 .115 .487 .777 143 Table B.6 Sampling errors T Copperbelt Provinc% Zambia 1992 Standard Value error Variable (R) (SE) Number of cases Design Relative Confidence limits Unweighted Weighted effect enror (N) (WN) (DEBT) (SE/R) R-2SE R+2SE URBAN .920 .007 1606 1743 1,088 ,008 ,905 ,934 SECOND .348 .017 1606 1743 1.425 .049 .314 .381 CURMAR .587 .013 1606 1743 1,082 .023 .561 .614 MAR20 .724 .016 1113 1208 1,164 .022 .692 .755 SEX18 .695 .014 1113 1208 1.025 .020 .667 .723 EVBORN 2.907 .069 1606 1743 .890 .024 2.769 3.045 EVB4049 7.884 .200 153 166 .936 .025 7.483 8.284 SURVIV 2.514 .056 1606 1743 .821 .022 2.402 2.626 KMETHOD .992 .003 943 1024 1.032 .003 .985 .998 KMODMET .988 .004 943 1024 1.054 .004 .981 .996 KSOURCE .970 .007 943 1024 1,321 .008 .956 .985 EVUSE .599 .022 943 1024 1.363 .036 .556 .643 CUSING .190 .015 943 1024 1.152 .078 .160 ,219 CUMODERN .136 .013 943 1024 1.196 .098 .109 .162 CUPILL ,071 .009 943 1024 1.091 .129 .053 .089 CUIUD .007 .004 943 1024 1.262 .476 .000 .014 CUCOND .017 .004 943 1024 ,915 ,227 .009 .025 CUSTERIL .035 .007 943 1024 1.089 .187 .022 .048 CUPABST .012 .004 943 1024 1.213 .364 .003 .020 PSOURCE .400 .043 155 168 1.094 .108 .314 .487 NOMORE .245 .017 943 1024 1.187 .068 .212 .278 DELAY .478 .021 943 1024 1.277 ,043 .437 .520 IDEAL 5.507 .072 1541 1672 1,359 .013 5.363 5.651 TETANUS .868 .011 1317 1429 1.082 .013 .845 .891 MDCARE ,798 .025 1317 1429 1,856 .031 .749 .848 DIARR1 .055 .007 1161 1259 1,034 .133 .041 .070 DIARR2 .177 .012 1161 1260 1,076 .070 .152 .201 ORSTRE .537 .036 205 223 .993 .068 .464 .610 MEDTRE .620 .044 205 223 1.236 .070 .532 .707 HCARD .769 .030 246 267 1.115 .040 .708 .830 BCG .980 .009 246 267 1,010 .009 .962 .998 DPT3 .850 .024 246 267 1,028 .028 .802 ,898 POLIO3 .834 .026 246 267 1,086 .032 .781 .886 MEASLES .813 .024 246 267 .954 .029 .766 .861 FULL1M .736 .030 246 267 1.051 .041 .676 .796 144 Table B.7 Sampling errors, Eastern Province r Zambia 1992 Variable Standard Value error CR) CSE) Number of cases Design Relative Confidence limits Unweighted Weighted effect error (N) (WN) (DEBT) (SE/R) R-2SE R+2SE URBAN SECOND CURMAR MAR20 SEX18 EVBORN EVB4049 SURVIV KMETHOD KMODMET KSOURCE EVUSE CUSING CUMODERN CUPILL CUIUD CUCOND CUSTERIL CUPABST PSOURCE NOMORE DELAY IDEAL TETANUS MDCARE DIARR1 DIARR2 ORSTRE MEDTRE HCARD BCG DPT3 POLIO3 MEASLES FULLIM .122 .012 .093 .016 .736 .025 ,789 .022 .733 .025 3.342 .114 7.887 .376 2,546 .098 .925 .010 .898 .013 .847 .022 .386 .029 .097 .027 .047 .01i .012 .005 .002 .002 .017 .009 .015 .005 .002 .002 .498 .095 .229 .016 .329 .020 5.339 .118 .830 .033 ,356 ,033 .095 .019 .317 .031 .515 .046 .503 .036 .748 .047 .958 .021 .706 .055 .685 .054 .769 .047 .579 .060 658 729 .938 .098 .098 .146 658 729 1,421 .173 .061 .126 658 729 1.440 .034 .686 .785 484 536 1.163 .027 .746 .832 484 536 1.229 .034 .684 .783 658 729 .899 .034 3.114 3.570 104 115 1,220 .048 7,134 8.640 658 729 .988 .039 2.350 2.742 484 536 .856 .011 .905 .946 484 536 .961 .015 .872 .925 484 536 1.317 .025 .804 .890 484 536 1.310 .075 .328 .444 484 536 1.976 .274 .044 .150 484 536 1.185 .242 .024 .070 484 536 1,012 .414 .002 .022 484 536 .989 1.00{3 -.002 .006 484 536 1.499 .526 -.001 .034 484 536 .908 .340 .005 ,024 484 536 1.012 1.010 -.002 ,006 30 33 1,023 .191 .308 ,688 484 536 .817 .068 .198 .260 484 536 .957 .062 .288 ,370 555 615 1.167 ,022 5.104 5,575 608 674 1.869 .040 .764 ,897 608 674 1,441 ,093 ,290 ,422 496 550 1.353 .196 .057 A32 496 550 1.468 .097 .255 ,378 157 174 1.072 .089 .424 ,607 157 174 .844 .071 .431 ,574 95 105 1.051 .063 .653 ,842 95 105 1,002 .022 .916 ,999 95 105 1.138 .078 .596 ,815 95 105 1,096 .078 .577 ,792 95 105 1.055 .062 .674 .863 95 105 1.153 .103 .460 .699 145 Table B.8 Sampling errors~ Luapula Province, Zambia 1992 Variable Standard Value error (R) (SE) Number of cases Design Relative Confidence limits Unweighted Weighted effect error (N) (WN) (DEFT) (SEfR) R-2SE R+2SE URBAN SECOND CURMAR MAR20 SEX18 EVBORN EVB4049 SURVIV KMETHOD KMODMET KSOURCE EVUSE CUSING CUMODERN CUP[LL CU1UD CUCOND CUSTERIL CUPABST PSOURCE NOMORE DELAY /DEAL TETANUS MDCARE DIARR1 DIARR2 ORSTRE MEDTRE HCARD BCG DPT3 POLIO3 MEASLES FULLIM .241 .022 .169 .034 .652 .021 .805 .030 .765 .031 3.428 .157 8.183 .388 2.659 .128 .949 .015 .900 .014 .879 .022 .215 .037 .095 .029 .060 .023 .028 .009 .000 .000 .012 .007 .009 .005 .005 .005 .683 .085 .153 .018 .398 .028 6.496 .138 .777 .060 .356 .062 .110 .018 .212 .031 .465 .079 .439 .087 .755 .053 .933 .051 .743 .067 .740 .068 .735 .075 .620 .079 589 431 1.233 .090 .198 .285 589 431 2.194 .201 .101 .237 589 431 1.073 .032 .610 .694 419 304 1.555 .037 .744 .865 419 304 1.510 .041 .703 .828 589 431 1.136 .046 3.115 3.742 88 62 1.208 .047 7.408 8.959 589 431 1.126 .048 2.404 2.915 390 281 1.357 .016 .919 .979 390 281 .894 .015 .873 .927 390 281 1.346 .025 .834 .924 390 281 1.795 .174 .140 .289 390 281 1.958 .306 .037 .153 390 281 1.865 .373 .015 .106 390 281 1.126 .337 .009 .047 390 281 .000 .000 .000 .000 390 281 1.176 .531 -.001 .026 390 28I 1.114 .607 -.002 .019 390 281 1.383 1.018 -.005 .014 21 19 .815 .124 .513 .853 390 28I .979 .117 .118 .189 390 281 1.141 .071 .342 .455 553 406 1.286 .021 6.220 6.772 576 419 2.847 .078 .657 .898 576 419 2.414 .174 .232 .480 457 331 1.200 .162 .074 .146 457 331 1.509 .145 .150 .273 96 70 1.489 .169 .308 .623 96 70 1.670 .199 .264 .614 111 79 1.283 .071 .648 .861 111 79 2.117 .055 .831 1.035 111 79 1.558 .090 .609 .877 111 79 1.584 .093 .603 .877 111 79 1.761 .102 .585 .885 111 79 1.672 .128 .462 .779 146 Table B.9 Sampling errors r Lusaka Province) Zambia 1992 Value Variable (R) Number of cases Standard Design Relative error Unweighted Weighted effect error (SE) (N) (WN) (DEFT) (SF.JR) Confidence limits R-28E R+2SE URBAN .914 SECOND .360 CURMAR .598 MAR20 .638 SEX18 .647 EVBORN 2.793 EVB4049 7.088 SURVIV 2.421 KMETHOD .954 KMODMET .945 KSOURCE .916 EVUSE .601 CUS1NG .242 CUMODERN .176 CUP[LL ,08l CUIUD .013 CUCOND .043 CUSTERIL .037 CUPABST .015 PSOURCE .599 NOMORE .229 DELAY .339 IDEAL 4,711 TETANUS .854 MDCARE .765 DIARR1 .058 DIARR2 .198 ORSTRE .576 MEDTRE .582 HCARD .770 BCG .987 DPT3 .845 POLIO3 .838 MEASLES .770 FULLIM .730 .026 1137 1234 3.099 .028 .863 .966 ,022 1137 1234 1,541 .061 .316 .404 .015 1137 1234 1.058 .026 .568 .629 .018 842 914 1.084 .028 .602 .674 .022 842 914 1.364 .035 ,602 .692 .078 1137 1234 .892 .028 2.637 2.948 .325 129 140 1.186 .046 6.437 7.738 .070 1137 1234 .907 .029 2.281 2.562 .007 680 738 .902 .008 .940 .969 .009 680 738 .978 .009 .928 .963 .011 680 738 1.007 .012 .895 .938 .023 680 738 1.247 .039 .554 .648 .023 680 738 1.404 .095 .196 .288 .021 680 738 1.447 .120 .134 .218 ,012 680 738 1,137 .147 ,057 .104 .003 680 738 .763 .253 .007 .020 .009 680 738 1.137 .207 .025 .060 .008 680 738 1.109 .218 .021 .053 .005 680 738 1.107 .348 .004 .025 .052 147 159 1,275 .086 .495 .702 .020 680 738 1.236 .087 .189 .269 .021 680 738 1.160 .062 .297 .382 .087 1064 1155 1.288 .018 4.537 4.884 .014 861 935 1.104 .016 .827 .882 .014 861 935 .814 .019 .737 .794 .010 761 826 1.122 .176 .037 .078 .020 761 826 1.279 .100 .159 .238 .039 151 164 .896 .068 .498 .654 .048 151 164 1.098 .082 .487 .678 .031 148 161 .882 .040 .709 .831 .009 148 161 .989 .010 .968 1.005 .026 148 161 .878 .031 .792 .897 .025 148 161 .827 .030 .788 .888 .034 148 161 .972 .044 .703 .838 .030 148 161 .816 .I)41 .670 .790 147 Table B.I0 Sampling errors T Northern Province T Zambia 1992 Variable Standard Value error (R) (SE) Number of cases Design Relative Confidence limits Unweighted Weighted effect error (N) (WN) (DEFT) (SFdR) R-2SE R+2SE URBAN SECOND CURMAR MAR20 SEX18 EVBORN EVB4049 SURVIV KMETHOD KMODMET KSOURCE EVUSE CUSING CUMODERN CUPILL CUIUD CUCOND CUSTERIL CUPABST PSOURCE NOMORE DELAY IDEAL TETANUS MDCARE DIARR1 DIARR2 ORSTRE MEDTRE HCARD BCG DPT3 POLIO3 MEASLES FULLIM .179 .014 .128 .021 .648 .035 .804 .024 .680 .024 3.367 .205 8.053 .202 2,607 .139 .919 .021 .821 .030 .806 .032 .704 .024 .175 .030 .031 .015 .018 .012 .(3O0 .000 .003 .003 .010 .006 .010 .004 .867 .084 .207 .014 .586 .032 6.768 .132 .616 .028 ,190 ,020 .120 .011 .283 .020 .415 .032 .378 .037 .629 .070 ,850 .053 .549 .071 .599 .075 .599 .078 .509 .070 590 652 .858 .076 .152 .206 590 652 1.549 .167 .085 .170 590 652 1,789 ,054 .578 .718 407 450 1.196 .029 .757 .851 407 450 1,053 .036 .632 .729 590 652 1,489 .061 2.958 3.777 90 100 .692 .025 7.649 8.457 590 652 1.267 .053 2.329 2.884 382 423 1.519 .023 .876 .961 382 423 1.537 .037 .761 .882 382 423 1.565 .039 .742 .869 382 423 1.026 .034 .656 .752 382 423 1.519 .169 .116 .234 382 423 1.653 .471 .002 .061 382 423 1.676 .628 -.005 .041 382 423 .000 .000 .000 .000 382 423 1,014 1.012 -.003 .008 382 423 1.177 .589 -.002 .023 382 423 .687 .344 .003 .018 15 17 .929 .097 .699 1.036 382 423 .680 .068 .178 .235 382 423 1.272 .055 .522 .651 534 590 1.143 .019 6.504 7.031 585 647 1.131 .045 .560 .672 585 647 1,002 ,103 ,151 ,229 477 528 .716 .091 .098 .141 477 528 .980 .071 .243 .324 135 150 .724 .077 .351 .478 135 150 .852 .097 .304 .451 100 111 1.460 .112 .488 .770 100 111 1,493 .063 .743 .956 100 1l l 1,419 .129 .408 .690 100 111 1.531 .125 .449 .749 100 111 1,584 .130 .444 .754 100 111 1,395 .137 .369 .648 148 Table B.11 Sampling errors, Nor th-Wostea'n ProvinceT Zambia 1992 Numb~ of cases Variable Stmada~d Value error (R) (SE) Design Relative Confidemoz limits Unweightext Wcightexl effect error (N) (WIN) (DEFT) (SF.JR) R-2SE R+2SE URBAN SECOND CURMAR MAR20 SEX18 EVBORN EVB4049 SURVIV KMETHOD KMODMET KSOURCE EVUSE CUSING CUMODERN CUPILL CUIUD CUCOND CUSTERIL CUPABST PSOURCE NOMORE DELAY IDEAL TETANUS MDCARE DIARR1 DIARR2 ORSTRE MEDTRE HCARD BCG Dvr3 POLIO3 MEASLES FULLIM .237 .028 .152 .043 .680 .027 .754 .o26 .845 .026 3.175 .135 7.069 .602 2.569 .093 .916 .029 .909 .030 .877 .037 .483 .035 .lO4 .020 .o59 .o15 .o18 .010 .0oo .000 .o13 .oo8 .028 .o12 .009 .009 .414 .13o .241 .022 .324 .028 5.954 .117 .792 .032 .499 .057 .085 .015 .182 .027 .531 .064 .562 .074 .849 .060 .907 .046 .779 .073 .767 .074 .837 .061 .709 .075 387 183 1.278 .117 .181 .292 387 183 2.328 .280 .067 .237 387 183 1.154 .040 .625 .734 286 133 1.026 .035 .702 .806 286 133 1,19o .030 .794 .896 387 183 .888 .042 2.905 3.444 47 20 1.236 .085 5.865 8.274 387 183 .739 .036 2.382 2.755 265 124 1.7o5 .032 ,857 .974 265 124 1.698 .033 .849 .969 265 124 1.843 .043 .802 .951 265 124 1.148 .073 .413 .554 265 124 1.045 .189 .065 .143 265 124 1.025 ,251 .030 .089 265 124 1.255 .564 -.002 .039 265 124 .000 .0oo .00o .000 265 124 1.123 .603 -.003 ,o29 265 124 1.181 .427 .004 .o52 265 124 1.527 1.0o3 -.009 .026 20 9 1.148 .313 .155 .674 265 124 .823 .090 .198 .284 265 124 .988 .088 .267 .381 365 174 .886 .020 5.721 6.187 364 172 1.289 .040 .728 .856 364 172 1.731 .114 .385 .612 310 145 .971 .182 .054 .115 31o 145 1.258 .149 .128 .237 57 26 .921 .121 .402 .660 57 26 1.o68 .132 .413 .71o 74 35 1.279 .071 .728 .969 74 35 1.229 .051 .814 .oo0 74 35 1.392 .094 .633 .925 74 35 1.386 .o96 .619 .914 74 35 1.267 .073 .715 .959 74 35 1.342 .106 .558 .859 149 Table B.12 Sampling errors, Southern Province, Zambia 1992 Number of eases Stand~d Design Relative Confidence limits Value error Unweighted Weighted effect error Variable (R) (SE) (N) (WN) (DEFI') (SE/R) R-2SE R+2SE URBAN .262 .029 947 1045 2.027 .111 .204 .320 SECOND .189 .027 947 1045 2.131 .143 .135 .243 CURMAR .644 .1320 947 1045 1.280 .031 .604 .684 MAR20 .749 .023 665 734 1.388 .031 .703 .796 SEX18 .794 .012 665 734 .788 .016 .769 .819 EVBORN 3.205 .103 947 1045 .997 .032 3.000 3.410 EVB4049 8.021 .300 108 119 1.089 .037 7.422 8.620 SURVIV 2.736 .087 947 1045 .982 .032 2.562 2.910 KMETHOD .967 .008 609 673 1,075 .008 .951 .983 KMODMET .947 .013 609 673 1.390 .013 .922 .972 KSOURCE .908 .015 609 673 1,312 .017 .877 .939 EVUSE .331 .040 609 673 2.099 .121 .251 ,411 CUSING .085 ,014 609 673 1.243 .165 .057 .113 CUMODERN .042 .010 609 673 1.167 .225 .023 .061 CUP|LL ,023 ,006 609 673 ,973 ,259 ,011 ,ff34 CUIUD .002 .002 609 673 .984 .994 -.002 .005 CUCOND .012 .005 609 673 1.243 .467 .001 .022 CUSTERIL .007 .002 609 673 .758 .378 .002 .012 CUPABST .010 .005 609 673 1.312 .535 -.001 .020 PSOURCE .673 .057 37 41 .725 .084 .559 .786 NOMORE .223 .015 609 673 .916 .069 .192 .254 DELAY .368 .020 609 673 .998 .053 .329 .407 IDEAL 6.047 .097 933 1030 1.295 .016 5.853 6.241 TETANUS .870 .015 912 1008 1.147 .017 .841 .900 MDCARE .339 .040 912 1008 2.142 .119 .258 .420 DIARR1 .070 .008 808 893 .886 .116 .054 .087 DIARR2 .248 .014 808 893 .911 .056 .221 .276 ORSTRE .581 .045 201 222 1.240 .077 .491 .671 MEDTRE .666 .044 201 222 1.263 .066 .578 .754 HCARD .795 .042 181 200 1.362 .052 .712 .879 /~CG .972 .011 181 200 .934 .012 .950 .995 DPT3 .806 .036 181 200 1.195 ,045 .734 .878 POLIO3 .784 .032 181 200 1.016 .041 .720 .847 MEASLES .839 .030 181 200 1.086 .035 .780 .899 FULLIM .712 .031 181 200 .903 .043 .650 .773 150 Table B.13 Sampling errors, Westexn Province T Zambia 1992 Number of cases Variable Standard Value error (R) (SE) Design Relative Confidence limits Onweighted Weighted effect error (N) (WN) (DEFT) (SE/R) R-2SE R+2SE URBAN .136 .027 581 422 1.866 .195 .083 .189 SECOND .126 .024 581 422 1.773 .194 .077 .175 CURMAR .570 .017 581 422 .847 .031 .536 .605 MAR20 .682 .023 456 330 1.034 .033 .637 .727 SEX18 .772 .018 456 330 .929 .024 .736 .809 EVBORN 3.253 .164 581 422 1.288 .050 2.926 3.580 EVB4049 7.009 .317 103 74 1.016 .045 6.375 7.644 SURVIV 2.486 .123 581 422 1.205 .049 2.241 2.732 KMETHOD .957 .010 335 241 .898 ,010 .937 ,977 KMODMET .862 .039 335 241 2.067 .045 .784 .940 KSOURCE .783 .038 335 241 1.678 .048 .708 .859 EVUSE .610 .031 335 241 1.147 .050 .549 .672 CUSING ,178 .019 335 241 ,899 .106 .141 .216 CUMODERN .029 .014 335 241 1.474 ,466 .002 .056 CUPILL .003 .003 335 241 .969 ,988 -.003 ,009 CUIUD .005 .004 335 241 1.190 .969 -.004 .013 CUCOND .006 .006 335 241 1.366 .984 -.006 .017 CUSTERIL .011 .006 335 241 .000 .508 -.000 ,023 CUPABST .003 .003 335 241 .965 .984 -.003 ,009 PSOURCE .675 .090 16 12 .743 .133 .495 .855 NOMORE .129 .013 335 241 .692 .099 .103 .154 DELAY .338 .023 335 241 .871 .067 .293 .383 IDEAL 7.420 ,236 579 420 1.602 ,032 6.947 7,893 TETANUS .763 .052 473 337 2.284 .068 .659 .867 MDCARE .324 .044 473 337 1.723 .134 .237 .411 DIARR1 .110 .019 386 275 1.219 .175 .071 ,148 D1ARR2 .260 .012 386 276 .560 .048 .235 .285 ORSTRE .411 .057 100 72 1.106 .138 .297 .524 MEDTRE .455 .050 100 72 .966 .110 .355 .554 HCARD .746 .039 81 58 .798 .053 .668 .825 BCG .940 .037 81 58 1.393 .040 .865 1.014 DPT3 .614 .110 81 58 1.987 .178 .395 .833 POLIO3 .669 .103 81 58 1.936 .154 .463 .875 MEASLES .760 .077 81 58 1.604 .102 .605 .915 FULLIM .566 .101 81 58 1.802 .179 .363 .769 151 APPENDIX C DATA QUALITY TABLES APPENDIX C DATA QUALITY TABLES The purpose of this Appendix is to provide the data user with an initial view of the general quality of the ZDHS data. Appendix B is concerned with sampling errors and their effects on the survey results. The tables in this appendix refer to possible non-sampling errors: digit preference, rounding or heaping on certain ages or dates; omission of events occurring farther in the past; deliberate distortion of information by some interviewers in an attempt to lighten their workloads; non-cooperation of the respondent in providing information or refusal to be measured and weighed, etc. A description of the magnitude of such non- sampling errors is provided in the following paragraphs. The distribution of the de facto household population by single year of age is presented in Table C. 1 (see also Figure 2.1). The data show little preference to report ages that end in zeros and fives (age "heaping" or digit preference) that is commonly found in countries where ages are not known well. There is some evidence of irregularities in the age distribution, e.g., relatively higher numbers among men at ages 9, 12, and 27 and among women at ages 13, 19, 23 and 27. However, it is difficult to find any pattern to these results and they may be due to random errors. The irregularities appear to be somewhat worse among women than among men. There is also some evidence that interviewers "displaced" women outside of the eligible age range (15-49), presumably in order to avoid the need to interview them. For example, while the number of men age 15 is substantially higher than the number age 14 and 13 (perhaps due to the tendency mentioned above to round ages to the nearest age ending in zero or five), the number of women age 15 is substantially lower than the number age 14 or 13. At the other end of the range, the number of men age 49 exceeds the number age 50, while the converse is true for women, implying that interviewers assigned an age of 50 (or 51) to women whose ages might not have been known with certainty, in order to avoid interviewing them. In any case, this displacement out of the eligible age range is much less severe than in many other DHS surveys (Rutstein and Bicego, 1990). Table C.2 shows that response rates vary little according to age of respondents. The five-year age distribution of respondents shows a larger proportion than expected in age group 15-19 (28 percent) and a smaller proportion in the older age groups, 35-49 (see also Chapter 2, Section 2.3). The fact that men enumerated in the household have a similar distribution at age groups 15-19 and 20-24 as the women (see Table C.1) indicates that the large proportion of women age 15-19 is not sex selective and might be real. Information on the completeness of reporting selected important variables is provided in Table C.3. Overall, the percentage of cases with missing information is extraordinarily low. Month of birth was missing for two percent of births that occurred in the 15 years before the survey and beth month and year were missing for less than half of one percent. Age at death was missing for an infinitesimal proportion of non- surviving births. Only for the anthropometric measurements is there a sizeable proportion for which data are missing; about 6 percent of children under five were not measured. This level of nonresponse is still very acceptable in comparison with rates from other DHS surveys. The main reason for not measuring children was that the child was not present, either because be/sbe did not live with the mother or because he/she was not home. Very few mothers refused to let their children be measured. 155 Table C. 1 Household age distribution Single-year age distribution of the de facto household population by sex (weighted), Zambia 1992 Males Females Males Females Age Number Percent Number Percent Age Number Percent Number Percent <1 702 4.2 730 4.2 36 148 0.9 136 1 596 3.6 572 3.3 37 156 0.9 131 2 607 3.6 618 3.6 38 139 0.8 127 3 521 3.1 527 3.1 39 134 0.8 121 4 517 3.1 528 3.1 40 111 0.7 106 5 520 3.1 582 3.4 41 100 0.6 76 6 566 3.4 559 3.2 42 118 0.7 119 7 492 3.0 562 3.3 43 108 0.6 129 8 468 2.8 553 3.2 44 94 0.6 104 9 554 3.3 506 2.9 45 119 0.7 93 10 469 2.8 563 3.3 46 95 0.6 83 11 439 2.6 443 2.6 47 65 0.4 75 12 507 3.0 502 2.9 48 80 0.5 83 13 396 2.4 523 3.0 49 104 0.6 76 14 426 2.6 495 2.9 50 98 0.6 115 15 454 2.7 427 2.5 51 83 0.5 113 16 435 2.6 444 2.6 52 91 0.5 126 17 420 2.5 422 2.4 53 66 0.4 94 18 384 2.3 401 2.3 54 58 0.3 70 19 381 2.3 430 2.5 55 70 0.4 104 20 342 2.1 309 1.8 56 84 0.5 69 21 319 1.9 315 1.8 57 55 0.3 54 22 289 1.7 320 1.9 58 48 0.3 62 23 274 1.6 359 2.1 59 70 0.4 64 24 235 1.4 228 1.3 60 97 0.6 78 25 259 1.6 238 1.4 61 46 0.3 51 26 196 1.2 241 1.4 62 58 0.3 35 27 283 1.7 307 1.8 63 42 0.3 42 28 248 1.5 226 1.3 64 46 0.3 41 29 177 1.1 229 1.3 65 44 0.3 49 30 202 1.2 202 1.2 66 31 0.2 17 31 168 1.0 196 1.1 67 40 0.2 29 32 218 1.3 197 1.1 68 34 0.2 31 33 166 1.0 201 1.2 69 29 0.2 29 34 145 0.9 167 1.0 70+ 310 1.9 231 35 191 1.1 172 1.0 Don'tknow, missing 21 0.1 3 0.8 0.8 0.7 0.7 0.6 0.4 0.7 0.7 0.6 0.5 0.5 0.4 0.5 0.4 0.7 0.7 0.7 0.5 0.4 0.6 0.4 0.3 0.4 0.4 0.5 0.3 0.2 0.2 0.2 0.3 0.1 0.2 0.2 0.2 1.3 0.0 Total 16662 100.0 17261 100.0 I Note: The de facto population includes all residents and rtortresidertts who slept in the household the night before the interview. 156 Table C.2 Age distribution of eligible and interviewed women Five-year age distribution of the de facto household population of women aged 10-54, five year age distribution of interviewed women aged 15-49, and percentage of eligible woman who were interviewed (weighted), Zambia 1992 Household population of women Age Number Percent Interviewed women Percent interviewed Number Percent (weighted) 10-14 2526 NA NA NA NA 15-19 2123 28.3 1984 28.1 93.4 20-24 1531 20.4 1441 20.4 94.1 25-29 1241 16.6 1179 16.7 95.0 30-34 964 12.9 915 13.0 94.9 35-39 687 9.2 656 9.3 95.6 40-44 534 7.1 505 7.2 94.6 45-49 410 5.5 380 5.4 92.6 50-54 518 NA NA NA NA 15-49 7490 100.0 7060 100.0 94,3 Note: The de facto population includes all residents and nomesidonts who slept in the household the night before interview. NA -~ Not applicable Table C,3 Completeness of reporting Percentage of observations missing information for selected demographic and health questions (weighted), Zambia 1992 Percemage Number missing of Subject F, ef~ence group in£onnation cases Birth date Births in last 15 years Month only 1.8 15825 Month and year 0.1 15825 Age at death Deaths to births in last 15 years 0.1 2535 Age/date at first onion ~ Ever-married women 1.3 5269 Respondent's education All women 0.1 7060 Cbild's size at birth B h'ths in l~st 59 months 0.2 3171 Anthropometry 2 Living children age 0-59 months Height 5.7 5393 Weight 5.5 5393 Height mad weight missing 6,0 5393 Diarrhoea in last 2 weeks Living children age 0-59 months 2.2 5393 1Both year and age missing :tChild not measured 157 Table C.4 Births by calendar year since birth DJsLrlbution of births by calendar years since birth for living (L), dead (D), and all (T) children, according to ~eporting completeness, sex ratio at birth, and ratio of births by calendar year, Zambia 1992 Percentage with Sex ratio Number of births complete birth date 1 at birth 2 Caleaadar ratio 3 Male Female Year L D T L D T L D T L D T L D T L D T 92 284 17 301 99.6 100.0 99.6 100.2 100,3 100.2 NA NA NA 142 8 151 142 8 150 91 1297 162 1459 99.8 93.7 99.1 101.0 113.6 102.4 186.2 155.8 182,3 652 86 738 645 76 721 90 1108 191 1300 99,2 97.7 99.0 97.5 97.2 97,5 93,2 I l i a 95.5 547 94 641 561 97 658 89 1082 182 1264 99.2 93.4 98.3 101.1 124.4 104.2 107.2 97.2 105.6 544 101 645 538 Sl 619 88 911 I84 1094 99.2 98.1 99.0 96,3 113.7 99.0 91.6 97.2 92,5 447 98 544 464 86 550 87 907 196 1102 99.6 95.0 98.8 93.9 125,9 98.9 95.7 93,8 95,4 439 109 548 468 87 554 86 984 233 1217 99,1 95.2 98.4 92.3 102.0 94.1 108.5 117.1 110,0 472 118 590 512 115 627 85 908 203 1111 98.9 96.9 98.5 91.1 100,9 92.8 98.5 96.0 98.0 433 102 535 475 101 576 84 860 189 1049 98,6 93.5 97.7 80.2 114.9 85.6 99.7 101.7 100.1 383 101 484 477 88 565 83 817 169 985 98,3 94.4 97.6 105.4 102.2 104.9 NA NA NA 419 85 504 398 84 481 88-92 4682 736 5418 99,4 95.9 98.9 99,2 111.2 100,8 NA NA NA2332 388 2719 2350 348 2698 83-87 4475 990 5465 98,9 95.0 98.2 92.1 108.6 94.9 NA NA NA2146 515 2661 2329 474 2804 78-82 3649 705 4354 98.5 92,6 97.5 97.2 105.3 98.5 NA NA NA1799 362 2160 1850:343 2194 73-77 2777 561 3338 97.6 90.1 96,3 101.9 86.2 99.1 NA NA NA1402 260 1661 1376 301 1677 <73 2537 809 3346 95,2 86.9 93.2 101.7 96,6 100.4 NA NA NA1279 398 1677 1258 412 1669 All 18119 3801 21920 98.2 92.3 97.2 97.8 102.3 98.5 NA NA NA8957 1922 10878 9163 1879 11042 NA = Not applicable tBoth year and month of birth given 2(B=/B~)* 100, where B= and Bf are the numbers of male and female births, respectively 3[2B,/(B~.I+B.,I)]* 100, where B 1 is the number of blobs in calendar year x According to Table C.4, the information on birth dating is good: both month and year of birth were provided for 97 percent of all births and for 99 percent of births in the five years before the survey. As expected, information on birth dates is more complete for children who were still living at the time of the survey than for those who had died. Still, both month and year of birth were provided for 92 percent of non- surviving children. Sex ratios are somewhat on the low side; the expected value would be 102 to 103, while those from the ZDHS are often less than 100. This indicates some possible undercounting of male births, especially those that occurred earlier in time. The data in Table C.4 also indicate that there was transference of births out of 1987 to earlier years, particularly to 1986. The ratio of births in 1987 to the average of the two adjoining years is 95. This is almost surely not accidental, but rather represents the deliberate attempt by some interviewers to Flghten their workloads, since several sections of the ZDHS questionnaire are applicable to only those children born since January 1987. This transference of births across the five-year cutoff point has been noted in many other DHS surveys (Arnold, 1990); in fact, the level of transference is lower in Zambia than in most of the sub-Saharan countries covered (e.g., Botswana 93; Burundi 83; Ghana 101; Liberia 71; Mali 84; Nigeria 77; Senegal 89; Togo 81; Uganda 96; Zimbabwe 97). 158 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 neonatal deaths reported to occur at ages 0-6 days, for five-yes periods of birth preceding the sta'vey, Zambia 1992 Number of years preceding the survey Age at de~th Total (in days) 0-4 5-9 10-14 15-19 0-19 <1 63 41 12 21 138 1 40 24 17 5 85 2 30 21 10 12 74 3 15 11 9 7 42 4 16 9 9 2 36 5 12 7 6 2 28 6 2 3 2 2 9 7 31 40 30 19 120 8 1 2 3 0 5 9 1 0 2 0 3 10 2 0 1 2 5 11 0 0 1 0 1 12 2 1 1 1 6 13 1 0 0 2 3 14 24 23 17 4 67 15 0 1 1 0 2 16 1 0 0 1 2 17 0 1 1 0 2 18 2 0 0 0 2 19 0 1 0 0 1 20 0 1 0 0 1 21 16 10 7 7 40 22 0 I 0 0 1 23 0 0 0 I 1 25 2 1 0 0 3 27 1 0 0 0 1 28 2 I I 1 5 29 1 0 0 0 1 30 0 2 3 3 8 31+ 1 0 0 0 1 Total 0.30 264 202 133 94 693 Percent early neonatal I 67.5 57.5 48.7 55.2 59.3 I(0-6 days/0-30 days) * I00 Measurement of childhood deaths through retrospective household surveys often suffers from underreporting of deaths, in particular those deaths which occur very early in infancy. If early neonatal deaths are selectively underrcportcd, the result would be an abnormally low ratio of deaths under seven days to all neonatal deaths and an abnormally low ratio of neonatal to infant mortality. Changes in these ratios over time can be examined to detect the hypothesis that underrcporting of early infant deaths is more common for births that occurred longcr before the survey. Table C.5 shows the distribution of deaths under one month of age by age at death in days, while Table C.6 shows the distribution of deaths under two years of age by age at death in months. The data suggest that early infant deaths have not been severely underreported in the ZDHS, since the percentage of neonatal deaths occurring in the first 6 days (next-to-last row in Table C.5) and the percentage of infant deaths 159 occurring during the neonatal period (next-to-last row in Table C.6) are reasonable. The former proportions increase over time, implying that some early infant deaths were not reported in the earlier periods; however, much, if not all, of this pattern can be attributed to heaping on 7 days at death, which is more severe for the earlier periods. As mentioned in Chapter 7, there was very little heaping on age at death of 12 months. Table C.6 Reporting of age at death in months Distribution of reported deaths trader 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, Zambia 1992 Number of years preceding the survey Age atdeath Toml (inmonths) 0-4 5-9 10-14 15-19 0-19 <1 a 264 202 133 94 693 1 41 27 21 18 106 2 37 30 28 12 107 3 44 29 16 12 101 4 38 25 19 11 92 5 40 27 16 5 88 6 35 41 28 17 121 7 32 19 10 I0 70 8 25 23 21 12 82 9 31 25 19 10 85 10 19 13 11 10 53 11 18 19 8 1 47 12 25 26 22 15 87 13 24 21 21 8 74 14 19 38 11 17 84 15 19 17 12 10 58 16 18 14 5 5 43 17 12 20 5 5 42 18 14 47 22 20 104 19 14 9 8 8 38 20 17 20 9 2 47 21 11 11 7 1 30 22 1 4 0 0 6 23 4 7 1 1 13 24+ 5 1 7 2 16 1 year 3 12 7 5 28 Total0-11 623 480 330 213 1646 Percent neonatal b 42.4 42.1 40.2 44.1 42.1 aIncludes deaths under 1 month reported in days b(Under 1 month/under 1 year) * 100 160 APPENDIX D PERSONS INVOLVED IN THE ZAMBIA DEMOGRAPHIC AND HEALTH SURVEY APPENDIX D PERSONS INVOLVED IN THE ZAMBIA DEMOGRAPHIC AND HEALTH SURVEY MINISTRY OF HEALTH John A. Mbomena, ZDHS Coordinator CENTRAL STATISTICAL OFFICE David S. Diangamo, ZDHS Coordinator Project Director Kwesi Gaisie Research Assistant Record Malungo Anthropometric Consultant Mr. Chowa Typists Mrs. Joyce Simbcya Ms. Lister Madubansi Ms. Felicitas Moyo Sampler Kumhutso Dzekedzeke ZDHSSTAFF Deputy Project Director Geoffrey Nsemukila Data Processing Staff George Namasiku Ireen Muzyambo Lubita Musambo Julius Lwenje M.C. Muleya G. Chubili B.M. Mulomba Health Trainers Eunicc Sichinga Grace Phiri Christine Kakoma Anne Cross George Bicego Kayc Mitchell DHS/MACRO STAFF Thanh Le Guillermo Rojas Sidney Moore FIELD STAFF Mr. Modesto Banda (CSO - Assistant Coordinator) Copperbelt Province 1 Copperbelt Province 2 Grace Phiri and J. Chiumia, Fieldwork Coordinators Martin Bwalya, Supervisor Grace Phiri, Field Editor M. Chishimba Rose Mankombwe Yothan G. Musonda Catherine Nyakamenji Derrick Mweemba, Supervisor P. P. Mbukwa, Field Editor Boaz M. Chahosh¢li S. Kanema Jacob Luya M. Mkandawire 163 Central Province Eastern Province R. Banda and P.K. Musonda, Coordinators C. Lwindi, Supervisor E. Mukuka, Field Editor Hope Kalaba Rose Mnbiana J. Muyoya Beatrice Mwiiya Luapula Province Harrison Mulenga and E. Mwanza, Coordinators M. Bwalya, Supervisor Moses Bwalya, Field Editor Mary N. Benkeni Gertrude P. Kambole Rose Njimu R. Phiri Lusaka Province Geoffrey Nsemukila and B. Mbolongwe, Coordinators Eunice Sichinga, Supervisor Record Malungo, Supervisor Eneles Chipoka, Field Editor Queen Chisanga Christine Chuzu Regina Kasina Anna P. Katulubushi Adam Siamungulu Mary Njovu North-Western Province Christine Kakoma and T.M. Siasendeka, Coordinators Alister Makalicha, Supervisor M. Nakufa, Field Editor Kaluvi Chilila M. Fweka B. Ntankaila R. Sweta Kumbutso Dzekedzeke and K.S. Banda, Coordinators R. Zulu, Supervisor Charity A. Banda, Field Editor D. Kumwenda Agnes Mwanza Leonlssa Tembo Lucy M.L. Zuh Northern Province E.M. Chnni and P. Sikazwe, Coordinators E. Malumo Hilda Machuchuti E. Kanda Mary Lungu W. C. K. Malabwa P. Namusoke Southern Province Nelson Nyangu and L Chilufya, Coordinators Simon Siachobe, Supervisor Betty Chimimba, Field Editor B. John Hangoma Cotridah Lwcendo Brendah Nambala Bertson Mulasu Nellie Muchimba Western Province Isaac Muzeya and D. Njungu, Coordinators Muzombo Mazombo Mwangala Linyama, Field Editor Harriet Kalimukwa Marion Masheke Ilukena Munalula Peunja Peanja 164 APPENDIX E SURVEY INSTRUMENTS Household Questionnaire Individual Questionnal~ ZAMBIA DEMOGRAPHIC AND HEALTH SURVEY HOUSEHOLD QUEST IONNAIRE IDENTIF ICAT ION PROVINCE D ISTR ICT CSA NUMBER . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . SEA NUMBER . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HOUSEHOLD NUMBER . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . NAME OF HOUSEHOLD HEAD URBAN/RURAL (urban=l , rura l=2) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . LUSAKA/OTHER C ITY /TOWN/V ILLAGE . . . . . . . . . . . . . . . . . . . . . . . . . . . . . (Lusaka=l , o ther c i ty=2, town=3, v i l l age=4) i i INTERVIEWER V IS ITS 1 2 3 [ F INAL V IS IT DATE INTERVIEWER'S NAME RESULT* NEXT V IS IT : DATE T IME *RESULT CODES: 1 COMPLETED 2 HOUSEHOLD PRESENT BUT NO COMPETENT RESP. AT HOME DAY MONTH YEAR NAME RESULT TOTAL NUMBER [---7 OF V IS ITS H I TOTAL IN [---7---q HOUSEHOLD I L i 3 HOUSEHOLD ABSENT 4 POSTPONED 5 REFUSED 6 DWELL ING VACANT OR ADDRESS NOT A DWELL ING 7 DWELL ING DESTROYED 8 DWELL ING NOT FOUND 9 OTHER (SPECIFY) LANGUAGE OF QUEST IONNAIRE: ENGL ISH TOTAL ELIGIBLE i i L WOMEN L INE NO. OF RESP. TO HOUSE- HOLD SCHEDULE 0 1 DATEN E ]I I LOEOITEOBY][O ICEEOIT OBYI[ KE EoBY 167 N(]USE HOLD SCHEDULE Now we would like s~ inforIP, ation about the people who usually live in your household or who are staying with you rK)W. NO, " VISITORS TO HEAD OF FOR PERSONS LESS THAN 15 YEARS OLD*** HOUSEHOLD* IF AGED 6 YEARS OR OLDER L - - | | I Please give me the Jhat is The Does I Did Is How old Has IF ATTENDED SCHOOL ]s IF ALIVE Is ]E AL names of the persons -elation!hip (NAME) I (NAME) (NAME) is -(NAME) - - • (NAME)'s , - - (NAME)'s -- who usually live in )f (NAME to usually sleep m~te (NAME)? ever Whet is IF AGED natural Does natural Doe your household arxJ :he head Live here or been the highest LESS n!other (NAME)~s father (NAM gk}ests of the house- )i the here? last f~le ) to Level of THAN all.e? rN~tural alive? natu hold who stayed here 1ousehol(;? I | night? ? i schooL? school 25 ~w)ther fath last night, starting I , (NAME) YEARS ~ live in llve , this this with the head of the attef~ed? I house- hous household. How any I hold? hold years did Is ]T YES: IF Y (NAME) (NAME) t~at is What complete st~ll in her name? his n at that school ? RECORD REED [eve [?** MOTHER ' S FAIN LINE LIN ! I NUMBER NUMB I (I) I (2) (3) (4) I (5) (6) (7) (8) (9) (10) (11) (12) (13) (14 i III I I I l W i N ] I I I I I i i l I YES NO FES NO M F IN YEARS YES NO LEVEL YEARS YES NO YES NO DK YES NO DK I I - - I ~ I ~ . I . I I | L I t I I i - - I ~ I 1 ~ I I I I i - - I I I I I | | - - l ~ ~ = == I I I - - | I I ' i I I ~ I 1 ~ I I I I I I I I I I ' I-F- 2. IT1 TIFF- FF , 05 I 2 I 2 I I 2 I 2 I 2 8 I 2 8 i I I - - I I I I I I -I I # I 06 ~ 1 2 1 2 1 2 ~ 1 2 ~ ~ 1 2 1 2 8 ~ 1 2 8 ~ I - - - - I I I I I J I I I I I 07 i I - - I ~ I 1 ~ I I I I ( I I I I [~-: 1 2 1 2 1 ~ 1 2 ~ ~ 1 2 1 2 8 ~ 1 2 B ~] 08 2 = n i i m i i i m m I m - - m - - m - - m ~ m I I m m I I m [ I I ELIGI- BILITY ALIVE CIRCLE - - LINE Does NUMBER (WAME)~s )E ~K)MEN natural !LIGIBLE father FOR live in INDI- VIDUAL house- INTER- hold? VIEW YES: is ~n~e? REC~D FATHER'S LINE NUMBER (14) (15) I I 01 02 I I ~T~ . 04 05 m 08 og H 2 HOUSEHOLD SCHEDULE CONTINUED (11 I (2) | (31 mm| (4) ll| iS) (6) (71 [8) (9) (10) (11) (12) (131 (1~,1 (151 n l i~ . N = ~ l a ~ I ~ 1 I mum l i ~ rES NO fES NO Iq F IN YEARS fEB BO LEVEL YEARS YES NO YES NO BK YES NO OK 11 I 1 1 2 1 2 1 2 1 2 8 1 2 8 ' 12 I 1 2 1 2 1 2 1 2 1 2 1 2 8 1 2 8 12 I t , - - . . n -n n n q n , n n n - . . . . . . . . . . . . . . . . ~ , ! n • I | i - - I 1 ~ 1 I -I I I - - I I I I I - 15 ~ 2 1 2 2 ~ 1 2 ~ ~ 1 Z 1 E B ~ 1 2 , ~ 15 i A m - - | - i l l l I I l l I I l 16 2 1 2 2 1 Z 1 2 1 2 8 , 1 2 8 16 r I m --m u n n | i I l i i z n 1 ,, I ~1 I - - I ~ I I I I I I I I I , • , - -n n = i i i i ~ ~ , - l - - i I I I i I I L I I i 20 212 2o 1) Are there any other persons such as smat¢ cnltaren or ~_~ infants that we have not Lister? YES ~ ~ ENTER EACH IN TABLE NO ! 2) In addition, are there any other people who may pot be ~ I ~ members of your family, such as domestic servants, Lodgers or friec~ds who usually live here? YES [-~ ~ ENTER EACH l# TABLE NO 3) Do you have any guests or teqxrary visitors staying here, or anyone else who slept here last night? YES ~ = ENTER EACH IN TABLE NO * COOES FOR 0.3 ** COOES FOR 0.9 RELATIONSHIP 70 HEAD OF HOUSEHOLC: LEVEL OF EDUCATION: YEARS: 01= HEAD 05= ERANDCHILD 09= OTHER RELATIVE 1 = PRIPIARY OO=LESS THAN 1 YEAR COMPLETED 02= ~]FEOR HUSBAND 06= FARENT IO=ADOPTED,FOSTER,STEPCHXLD 2= SECONDARY 9B=DK 03= SON DR DAUGHTER 07= EAREH]']H*LA~ 11= NOT RELATED 3 = HIGHER 04= SON OR DAUGHTER-IN-LA~ 08= [ROTHER OR SISTER 9B= DR B = DK These questions refer to the biological parents of the child. Record DO if parent not member of household. H 3 NO. Q4JESTIONB AND FILTERS 16 What is the source of water your household uses for ha~ashing and dishwashing? SKIP COOING CATEGORIES I TO PIPED WATER | PIPED INTO HOME OR PLOT . 11 ~18 PUBLIC TAP . . . . . . . . . . . . . . . . . . . . 12 | I WELL WATER WELL IN RESIDENCE/YARD/PLOT,,,Z1 ~18 PUBLIC WELL . 22 I I SURFACE WATER SPRIRG . 31 R%VER/STREAM . 32 POND~LAKE . . . . . . . . . . . . . . . . . . . . . 33 RAINWATER . 41 r18 TANKER TRUCK . 51 I BOTTLED WATER . 61 ~lB OTHER 71 l (SPECIFY) 17 m Ho, t~g does it take to go there, get water, I and c~ ~ck? i ,:O,E, . I t l l I PRENI SEE . 996 ~8 I Ooes your household get drinking water m YES . 1 ~20 I fr~ this s~ source? I NO . 2 I 19 What is the source of drinking water for mc,~t~ers of your household? PIPED WATER PIPED INTO HONE OR PLOT . 11 PUBLIC TAP . 12 WELL WATER kELL IN RESIDEBCE/YARO/PLOT.21 PUBLIC WELL . 22 SURFACE WATER SPRIMG . 31 RIVER/STREAM . 32 POND/LAKE . 33 RAINWATER . 41 TANKER TRUCK . 51 BOTTLED WATER . 61 OTHER 71 (SPECIFY) ZO What kind of toilet facility does your househoLd have? FLUSH TOILET OWN FLUSH TOILET . 11 SHARED FLUSH TOILET . 12 PIT TOILET/LATRINE TRADITIONAL PIT TOILET . 21 VENTILATED IMPROVED PIT (V/P) LATRINE . 22 NO FACILITY/BUSH/FIELD . 31 OTHER 41 (SPECIFY) 21 I Does your household have: Electricity? A radio? A te lev i s ion? A refrigerator? I YES NO ] ELECTRICITY . I 2 RADIO . I 2 TELEVISION . 1 2 REFRIGERATOR . 1 2 22 1R° ' 'nY r°- - in y°ur h "h°ld'r" 'leeOi°B? I . . . . . . . . . . . . . . . . . . . . . . i l i l 23 What is the material of the floor? NATURAL FLOOR EARTH/SAND . 11 RUDIMENTARY FLOOR PLANKS/BOARDS . 21 FINISHED FLOOR PARQUET OR POLISHED WOCO . 31 TERRAZD TILE . 32 PVC TILES . 33 CEMENT . 34 CARPET . 35 OTHER 41 (SPECIFY) 24 Does any member of your household own: m YES NO m A bicycle? I BICYCLE . . . . . . . . . . . . . . . . . . . . 1 2 I A motorcycle? MOTORCYCLE . I 2 A car? CAR . 1 2 EN H 4 l?O ZAMBIA DEMOGRAPHIC AND HEALTH SURVEY QUEST IONNAIRE FOR INDIV IDUAL WOMEN IDENTIF ICAT ION PROVINCE DISTRICT CSA NUMBER . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . SEA NUMBER . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HOUSEHOLD NUMBER . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . NAME OF HOUSEHOLD HEAD URBAN/RURAL (urban=l, rural=2) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Lusaka / /OTHER C ITY /TOWN/V ILLAGE . . . . . . . . . . . . . . . . . . . . . . . . . . . . (Lusaka=l, other city=2, town=3, vi l lage=4) NAME AND LINE NUMBER OF WOMAN INTERVIEWER VIS ITS L I I DATE INTERVIEWER'S NAME RESULT* NEXT VISIT: DATE T IME 1 i FINAL V IS IT * RESULT CODES: 1 COMPLETED 2 NOT AT HOME 3 POSTPONED LANGUAGE OF QUEST IONNAIRE** LANGUAGE USED IN INTERVIEW**. . . 2 3 [I II u ::::::::::::::::::::::::::: Eiii ii Ei!iiii iii i! iii! 4 REFUSED 5 PARTLY COMPLETED 6 OTHER (SPECIFY) DAY MONTH YEAR NAME RESULT TOTAL NUMBER OF V IS ITS ENGLISH RESPONDENT' S LOCAL LANGUAGE** . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . TRANSLATOR USED (1--NOT AT ALL; 2=SOMETIME; 3=ALL THE TIME). . 0 i **LANGUAGE CODES: 01 ENGLISH 03 KAONDE 05 LUNDA 07 NYANJA 09 OTHER 02 BEMBA 04 LOZI 06 LUVALE 08 TONGA FIELD EDITED BY: OFF ICE EDITED BY: I KEYED BY: KEYED BY: DATE 171 SECTI~ 1. RESPORp[RT,S DACKqS~b SKLP GUESTIORS AND FILTERS COOING CATEGORIES TO | NO. 101 RECORD THE TIME. 102 I First I w~ld like to ask a~ questi~ m~t you 8rid m I y~r househotcl. For ~st of the ti~ =tit you were 12 I years old, did yog Live in a c~ty, ~n a to~, or in a viLLage? • HOUR . . . . . . . . . . . . . . . . . . . . . . . . • MINUTES . . . . . . . . . . . . . . . . . . . . . CITY . 1 TOWN . 2 VILLAGE . 3 103 CURRENTH°W t~gpLAcEhave yOUoF RESIDENCE)?been Living continuously in (NAME OF |1 YEARS . ~ . . , |1 I I AL~AYS . 95 7 VISITOR . 96 =105 I0, i Jet 'or. you--v He" "'0 Live in ' o'tY ICLTY . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 I in m town, or in a village? TORN . 2 VILLAGE . 3 105 in what ~nth and year were you ~rn? MONTH . OK NORTH . 98 YEAR . . . . . . . . . . . . . . . . . . . . . . . ~-~ OK YEAR . . . . . . . . . . . . . . . . . . . . . . . . 9S 106 How o ld were you at your Last b i r thday? I AGE 'R c°"PLETED YEARS . ~-~1 COMPARE AND CORRECT 105 AND/OR 106 IF iNCORSISTENT. NO . 2. -~ 111 primary, secondary, or higher? SECONDARY . 2 HIGHER . . . . . . . . . . . . . . . . . . . . . . . . . . 3 YEARS . CONMERT 111 Can you ree, d a~<l ~rsta~ a Letter or news~ber easily, with difficulty, or not at all? EASILY . 1 WITH DIFFICULTY . 2 NOT AT ALL . 3 I r113 112 | DO you U=ualty remd a r.iwsbeper or mllgzzine at least I YE; . 1 I I o¢~::e a ueek? | NO . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 I 113 I O° You ~u"=LtY (islam t° a radi° at (ea't ~ea ~ek? I YEERo. . . . . .Z1 I 11' I °° v°u us'lLY watch tel"i'i~ "t least ~e ' "k? I TEa .o . . . . 2 11 I I CATHOLIC . 1 115 What religic~t are you? PROTESTANT . 2 MUSLZM . 3 OTHER 4 (SPECIFY) EN 2 173 NO. 118 QUESTIONS AND FILTERS CHECK Q,4 IN THE HOUSEHOLD QUESTIONNAIRE THE WOMAN INTERVIEWED IS NOT A USUAL RESIDENT Now I would like to ask about the place in which you usual ly Live. Do you usuaLLy live in a city, in a town, or in a village? IF CITY: In which city do you live? SKIP COOING CATEGORIES I TO I THE I~3MAN INTERVIEWED IS A USUAL RESIDENT | I =201 LUSAI(A, LARGE CITY . I SISAL L CITY . 2 TOWN . 3 V I L LAGE . 4 119 In which province is that located? CENTRAL . 1 COPPERBELT . 2 EASTERN . 3 LUAPULA . 4 LUSAKA . 5 NORTHERN . 6 NORTH-WESTERN . 7 SOUTHERN . 8 WESTERN . 9 OUTSIDE ZAMBIA/OTHER . 0 120 Bow I would like to ask about the household in which you usually Live. What is the source of water your household uses for har~dwashing and dishwashing? PIPED WATER I PIPED INTO HOME OR PLOT . 11 ~ 122 PUBLIC TAP . 12 | WELL WATER I WELL IN RESIDENCE~YARD~PLOT.21 =122 PUBLIC WELL . 22 | SURFACE WATER SPRING . 31 RIVER/STREAM . 32 POND/LAKE . 33 RAINWATER . . . . . . . . . . . . . . . . . . . . . . . 41 ~122 TANKER TRUCK . 51 J BOTTLED WATER . . . . . . . . . . . . . . . . . . . 61 ~122 OTHER 71 I (SPECIFY) 121 HOW tong does it take to go there, get water, MINUTES . F ~ I and come back? I ON PREMISES . I 122 Does your household get drinking water YES . 1 ~124 From this same source? | I NO . 2 123 What is the source of drinking water for raeel)ers of your household? PIPED WATER PIPED INTO HOME OR PLOT . 11 PUBLIC TAP . 12 WELL WATER WELL IN RESIDENCE/YARD/PLOT.21 PUBLIC WELL . 22 SURFACE WATER SPRING . 31 RIVER/STREAM . 32 POND/LAKE . 33 RAINWATER . 41 TANKER TRUCK . 51 BOTTLED WATER . 61 OTHER 71 (SPECIFY) ]74 EN 3 gO. QUESTIONS AND FILTERS 124 What kind of toilet facility does your household hove? COOING CATEGORIES FLUSH TOILET OWN FLUSH TOILET . 11 SHARED FLUSH TOILET . 12 PIT TOILET/LATRINE TRADITIONAL PIT TOILET . 21 VENTILATED IMPROVED PXT (VIP) LATRINE . 22 NO FACILITY/BUSH/FIELD . 31 OTHER 41 (SPECIFY) SKIP TO 125 Does your household hove: Electricity? A radio? A television? A refrigerator? YES NO ELECTRICITY . 1 2 RADIO . 1 2 TELEVISION . I 2 REFRIGERATOR . 1 2 12'1Ho,- to- I --s . . . . . . . . . . . . . . . . . . . . . . 127 Could you describe the main material of the floor of your home? NATURAL FLOOR EARTH/SAND . 11 RUDIMENTARY FLOOR ~000 PLANKS/BOARDS . 21 FINISHED FLOOR PARQUET OR POLISHED WCX30 . 31 TERRAZO TILE . 32 PVC TILES . 33 CEMENT . 34 CARPET . 35 OTHER 41 (SPECIFY) 128 Does any member of your hc~sehold own: A bicycle? A motorcycle? A car? YES HO BICYCLE . 1 2 MOTORCYCLE . 1 2 CAR . 1 2 EN 4 175 SECTION 2. REPROOUCTION NO. I QUESTIONS AND FILTERS i I 201 I Now I would Like to ask about all the births you have I had during your life. Have you ever given birth? SKIP I COOING CATEGORIES I TO YES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . I J NO . 2 ~206 2021 it, you, IY S . II NO . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 .204 And how many daughters live with you? DAUGHTERS AT HONE . IF NONE RECORD '00 ~. given b i r th who are a l i ve but do not l i ve with you? NO . 2 .206 205 1 How many sons are alive but do not live with you? J SONS ELSEWHERE . I And how many daughters are alive but do not Live with I you? DAUGHTERS ELSEWHERE . IF NONE RECORD '00'. baby who cried or showed any sign of Life bot NO . 2 L208 only survived a few hours or days? 207 In all, how many boys have died? And how many girls have died? IF NONE RECORD '00'. SUM ANSWERS TO 203, 205, AND 207, AND ENTER TOTAL. IF HONE RECORD '00 ~. ::::::::::::::::::::::::::::: I TOTAL . . . . . . . . . . . . . . . . . . . . . . 209 210 CHECK 208: Just to make sure that I have this r ight : you have had in TOTAL births during your life. Is that correct? YES v PROBE AND NO II ~ CORRECT 201-208 AS NECESSARY CHECK 208: I ONE OR NORE 9 NO BIRTHS ~-] ~223 BIRTHS g Ef~ 5 176 211 Nou I would Like to talk to you about all of your births, vhether still alive or not, starting with the one you had. RECORD NAMES OF ALL THE BIRTHS IN 212. RECORD TWINS AND TRIPLETS OR SEPARATE LINES. 212 What name was givet~ to your (first,next) boby? (NAME) ( NAME ) (NAME) 213 RECORD SINGLE ON MULTIPLE giRTH STATUS, SING.1 MULT.2 SING.1 h~JLT.2 S ING. , .1 MULT.2 214 215 216 217 ;218 219 % ( NAME ) % (NAME) % (NAME) (NAME) first i s (NAME) a boy or a girl? ROY.1 GIRL.2 BOY.1 GIRL.,2 BOY,.,1 GIRL.2 ROY.1 GIRL,,2 BOY.,1 GIRL.2 BOY.1 GIRL.2 BOY,.1 G[RL.2 in ~hat month and year was (NAME) born? PRONE : What is his/ her birthday? OR: In what season MBs he/she born? i ] i Is (NAME) still alive? I v 220 ~ONTH.~I YES.1 YEAR,. NO.,.2 t v 22O YES.1 NO,,.2 I v 22O YES.,.1 177 IF ALIVE: How old was (NAME) at his/her last birthday? RECORD AGE 1N COMPLETED YEARS. AGE ] N YEARS AGE IN YEARS AGE %N YEARS AGE IN TEARS AGE IN YEARS AGE IN TEARS IF ALIVE: Ls (NAME) Living with you? YES . 1- (GO TO NEXT BIRTH)* NO . 2 YES.,, ~ (GO TO NEXT B]RTH)~ NO . Z YES . 1 (GO TO NEXT R[RTH)~ NO . 2 YES . 1 (GO TO NEXT .NTR) NO . 2 YES . 1 (GO TO NEXT BIRTH)4 NO . 2 YES . 1 (GO TO NEXT BXRTH)~ NO . 2 IF LESS THAN 15 YRS. OF AGE: With whom does he/she Live? ZF 15+: GO TO NEXT BERTH. FATHER . 1 OTHER RELATIVE.2 SOMEONE ELSE.] (GO NEXT BERTH) FATHER . 1 OTHER RELAT]VE.2 SOMEONE ELSE.] (GO NEXT BIRTH) FATHER . 1 OTHER RELATIVE.2 SOMEONE ELSE.] (GO NEXT BIRTH) FATHER . 1 OTHER RELATLVE,2 SOMEONE ELSE.,,] (GO NEXT BIRTH) FATHER . 1 OTHER RELATIVE,2 SOMEONE ELSE,.] (GO NEXT BIRTH) FATHER . 1 OTHER RELATIVE.2 SOMEONE ELSE.] (GO NEXT BIRTH) 220 ]F DEAD: How old ~as he/she when he/she died? IF "I YR,', PROBE: How many months old was (NAME)? RECORD DAYS iF LESS THAN I MONTH,MONTHS ]F LESS THAN TWO YEARS, OR YEARS. m DAYS,.1 ~ MONTHS.2 YEARS,.3 DAYS,,.1 MONTHS.2 YEARS.3 DAYS,.1 MONTHS.2 YEARS.] DAYS.1 ! MONTHS.2 YEARS.] DAYS.1 NONTHS.Z TEARS,.] DAYS.1 MONTHS.2 YEARS.] AGE IN I YES . '11 FATHER . 1 DAYS.1 YEARS TI (GO TO NEXT B[RTH)~J OTHER RELATIVE.2 MOHTHS.,2 NO . 2 SOI4EONE ELSE.,.3 YEARS,.3 ~ l l l l m l l L m L ~ ~ ( G O NEXT gIRTH) EN 6 212 213 What n~ was given to your (first,next) baby? RECORD SINGLE OR MULTIPLE BIRTH STATUS. 08~ SING.1 NULT.2 (NAME) 09] SING.,,1 ICJLT,,.2 (NAME) SING.1 NULT.2 (NAME) 1~ SING.,1 NULT,.2 (NAME) SING.1 MULT.2 (NAME) SING.1 E~JLT.2 (NAME) 221 21/* IS (NA~E) a boy or a girL? BOY. I GIRL.2 BOY,.1 GIRL.2 BOY.1 GIRL.Z BOY.1 GIRL.,2 ROY.I GIRL.2 BOY.1 GIRL.2 215 In what ~l~nth and year was (NAME) born? PROBE: What is his/ her birthday? OR: In what seaso~ WB$ he/she born? MONTH.,~ YEAR. MORTH. ,~ YEAR. MONTH.~ TEAR. MONTH.~ YEAR. MONTH. ,~ YEAR. MORTH.~ YEAR. 216 Is (NAME) sti{( alive? YES.1 NO.2 L v 220 217 218 IF ALIVE: IF ALIVE: HOW old WaS IS (NAME) (MANE) aC (ivin g his/her Last with you? birthday? RECORD AGE IN COMPLETED YEARS. AGE IN YES . 1 YEARS (GO TO NEXT BIRTH) NO . 2 YES.1 AGE IN YES . 1- YEARS (GO TO NEXT NO,.2 r ~ BIRTH)q- I v NO . 2 220 YES.,1 AGE lR YES . 1 YEARS (GO TO NEXT GO.2 RIRrH}4- v NO . 2 220 YES,.1 AGE IN YES . I YEARS (GO TO NEXT NO.2 I ~ DIRTH),~ / v ' l No . . . . . . . . 2 I 220 ~ES,.I J AGE IN YES . I YEARS (GO TO NEXT NO.2 B IRTH)-,~ v NO . 2 220 YES.,.1 AGE IN YES . 1 YEARS (GO TO ,~EXT NO.2 BI RTH),,r v NO . 2 220 219 IF LESS THAN 15 YRS. OF AGE: With whc~ does he/she Live? IF 15+: GO TO NEXT BIRTH. FATHER . 1 OTHER RELATIVE.2 SUMEORE ELSE.3 (C~3 NEXT BIRTH) FATHER . 1 OTHER RELATIVE.2 SUMEONE ELSE.3 (GO NEXT BIRTH) FATHER . I OTHER RELATIVE.Z SUMEONE ELSE.3 (DO NEXT BIRTH) FATHER . 1 OTHER RELATIVE.2 SUMEONE ELSE,,.3 (GO NEXT G(RTH) FATHER . t OTHER RELATIVE.2 SOMEONE ELSE.3 (GO NEXT BIRTH) FATHER . I OTHER RELATIVE.2 SUMEONE ELSE.3 (GO TO 221) COMPARE 208 WITH NUMBER Of BIRTHS IN HISTORY ABOVE AND MARK: NUMBERS [~] NUMBERS ARE ARE SAME ~ DIFFERENT ~ ~ (PROBE AND RECONCILE) v CHECK: FOR EACH BIRTH: YEAR OF BIRTH IS RECORDED. FOR EACH LIVING CHILD: CURRENT AGE IS RECORDED. F(~ EACH DE~ CHILD: AGE AT DEATH IS RECORDED. FOR AGE AT DEATH 12 MONTHS: PR(~SE TO DETERMINE EXACT NUMBER Of MONTHS. ZZO IF DEAD: How old was he/she when he/she died? If "I YR,", PROSE: How many months old WaS (NAME)? RECORD DAYS IF LESS THAN 1 MONTH,MONTHS IF LESS THAN T~,~3 YEARS, OR YEARS. m DAYS.( MORTHSlI2 YEARS.3 DAYS.( MONTHS.2 YEARS.,.3 DAYS.1 MONTRS.2 YEARS.3 DAYS.( MONTHS.2 YEARS.3 DATS.I MONTHS.2 YEARS,.3 DAYS.I MONTHS.2 TEARS.] 178 EB NO. I 223 I QUESTIONS AND FILTERS Are you pregnant now? SKIP I COOING CATEGORIES I TO I ,'ES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . i I 22, I ~o.oy.o,,, or.oo.o,.r.,oo, I 'o'T"s . ~1 I r,,E . 1 pregnant then, did you want to wait until later, LATER . 2 or did you noJ uant to become pregnant at all? NOT AT ALL . 3 226 When did your Last menstrual period start? DAYS AGO . 1 WEEKS AGO . 2 MONTHS AGO . 3 YEARS AGO . . . . . . . . . . . . . . . . 4 IN MENOPAUSE . 994 BEFORE LAST BIRTH . 995 NEVER NENSTRUATED . 996 227 I Between the first day of a woman's period and the | I first day of her next period, are there certain | times when she has a greater chance of becoming pregnant| than other times? I I YES . 1 | NO . 2 DK . 8~301 I 228 During which times of the monthly cycle does a woman have the greatest chance of becoming pregnant? DURING HER PERIO0 . 1 RIGHT AFTER HER PERIO0 HAS ENDED . 2 I~ THE MIDDLE OF THE C~CLE . 3 JUST BEFORE HER PERIO0 BEGINS,.4 OTHER 5 (SPECIFY) OK . . . . . . o . . . . . . . . . . . . . . . . . . . . . . ER 8 179 SECTION 3, CONTRACEPTION 301 I Now I Would like to talk about family planning - the various ways or methods that a couple can use to dw~lay or avoid a pregnancy. Which Ways or methcw~s have you heard about? CIRCLE CODE I IM 302 FOR EACH METHOD MENTIONED SPONTANEI~JSLY. THEN PROCEED DONS THE COLONS, READING THE NAME AND DESCRIPTION OF EACH METHOD NOT MENTIONED SPONTANEOUSLY. CIRCLE COOE 2 IF NETHOD IS RECOGNIZED, AND CODE 3 IF NOT RECOGNIZED. THEN, FOR EACH METHOD WITH CODE 1 OR 2 CIRCLED IN 30~, ASK 303"304 BEFORE PROCEED]NG TO TEE NEXT METHOD. IIII O~ PILL Wcx~en can take a pill every day. .• IUCD Weaken can have a Loop or coil placed inside them by a doctor or a nurse. INJECTIONS W~n can have an injection by a doctor or nurse which stops them from becoming pregnant For several months, O~ FOAMING TABLET/JELLY Worsen can place a sponge, suppository, diaphragm, jelly or cream in- side them before intercourse. CONDON Men can use a rub4)er sheath during sexual inter- course. FEMALE STERILIZATION Worn can have an operation to avoid having any more children. This is also called ,turning the wo(it)., MALE STERILIZATION Men can have an operation to avoid having any more ch i ld ren . O B J NATURAL FAMILY PLANNING Couples can avoid having sexual i n te rcourse on cer ta ln days o~ the menth when the w~n is mere Likely to bec~ pregnant. 09] WITHDRAWAL Men can be careful and pull out before climax. •j Have you heard of any other ways or methods that wo(nen or men can use tO avoid pregnancY? I (SPECIFY) 2 (SPECIFY) 3 (SPECIFY) V • 302 Have you ever heard of (NETH~O)? READ OESCRIPFION OF EACH METHOD YES/EPONT . 1 YES/PROBED . 2 NO . )l v YES/SPONT . I YES/PROBED . 2 NO . 3] v YES/SPONT . 1 YES/PROBED . 2 NO . 3] v YES/SPONT . 1 YES/PROBED . 2 NO . 31 v YES/SPONT . 1 YES/PROBED . NO . 3] v YES/SRONT . . . . . . . . . . . . . . . . . . . 1 YES/PROBED . 2 NO . 31 v YES/EPONT . 1 YES/PROBED . . . . . . . . . . . . . . . . . . 2 WO . 3] YES/SPONT . 1 ~ YES/PROBED . ~ NO . 31 V YES/SPONT . 1 YES/PROBED . 2 NO . 37 Y YES/SPOST . 1 NO . . . 3 303 Have you ever used (METHOO)? YES . 1 MO . . . . . . . . . . . . . . . . 2 304 Do you know where a person could g o to set (METHOD)? YES . 1 NO . 2 YES . I YES . . . . . . . . . . . . . . . . . . . . . . . . I NO . Z NO . 2 YES . I YES . 1 NO . 2 NO . 2 YES . 1 YES . 1 NO . 2 NO . 2 YES . . . . . . . . . . . . . . . 1 YES . . . . . . . . . . . . . . . . . . . . . . . . 1 NO . Z NO . 2 Save you ever had an operation to avoid having any more children? YES . 1 NO . 2 YES . . . . . . I NO . 2 YES . 1 NO . 2 YES . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . 2 YES .1 NO . 2 DO you know where a person can obtain advice on how to use natura l fami ly p lanDing? YES . 1 NO . . . . . . . . . . . . . . . . . . . . . . . . . 2 YES . 1 ; :: ::~:::: ~;:;; ;:;:::::: ; ::: :;; ; '~ : :: : : ; iiiiiiiii!i!ii~ii!i~iiiiiiiiiii!i~ii~iiii~iiiiiiiii~iii~:~i~iiiiiiiiiiiiiiii YES . I ~i~iiii~i~;iii~iiiiiiiiiiiiiiii~i~iii~i~i~iiiiiiii!iiii!i~!!~!i!~iii YES . I ~i~h~;;ii~[~)~h;~;h;;~iii~i~;~;~;~;;;~j~[~ NO . 2 iiii}iiiiiiiii~{i!i~!~iiiiiiiii}i}~!~!~!i~iii}iiii!iiiiiiiiiiiiiiii~ii~iiii AT LEAST ONE "YES" (EVER USED) [-~ SK]P TO 308 EN 180 SKIP NO. l QUESTIONS AND FILTERS l CODING CATEGORIES l TO +I +.+,+ -,o I ,+ . delay or avoid getting pregnant? NO . ~'~ ~324 ~°71 +" -+u++°r - ' I I CORRECT 303-305 (AND 302 IF NECESSARY). 308 l No~ I would Like To ask you about The time ~hen you ) first did something or used a method to avoid getting pregnant. HO~ many Living children did you have at that time. if any? IF HONE, RECORD IO0+, REVER USED NATURAL FAMILY PLANNING [~ +°"l YOU said that sometimes you have avoided having sexuBt intercourse on certain days of the month to avoid getting pregnant. Ho~ did you know which days to avoid sexual intercourse? CHECK E23: flOT PREGNANT OR UNSURE V~ CHECK 303: WQI4AN NOT STERILIZED V[~ l / Are you currently doing something or using any method to delay or avoid getting pregnant? HUNGER OF CHILDREN . . . . . . . . . I CALENDkR, CQUKTLNG DAYS . 1 CERVICAL NUCUS METHOD . 2 TOOK TEMPERATURE DAILY . 3 NUCUS AND TENPERATURE . . . . . . . . . . . 4 OTHER S (SPECIFY) PREGNANT ~--~ ~I4AH STERILIZED [--] l YES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . I N O . . . . + + . , . . . . . • . . . . . . . . . .+ . . . . . ~309 J I I I .324 312 312A Which method are you using? CIRCLE ~06: FOR FEHALE STERILIZAT]Ofl. PILL . 01 I lUO . . . . . . . . . . . . . . . . . . . . . . . . . . . . 02 INJECT[ORS . 03 DIAPHRAOR/FOAN/JELLY . O'y b CONDOI4 . OS 318 FENALE STERILIZATION . 06 HALE STERILIZATION . 07 NATURAL FAH]LY PLANNING . 08 WITHDRAWAL . 09~323 OTHER 10 ~ (SPECIFY) I "~ I '* +"+" +"r+* + '+ u+'n' +'P+'" °+° + I +E+ . '1 consult a doctor or B nurse? NO . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 DK . 8 +" I ~t the ' " Y°° (ast ' ° ' Pi l l" Oid + °°°+°(' " = '°*1 T" . '1 or a nurse? NO . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 315 Nay I see the package of pills you are using now? RECORD NAME OF SRA~D. . . . . . . . . . . . . 1 PACKAGE SEEN . . . . . . . . ~ - ' ~ 317 BRAND NAME PACKAGE NOT SEEN . 2 J 316 Do you know the brand name of the pills you are now using? RECORD NAHE OF BRAND. BRAND NAME [ ~ OK . . 98 317 I How much does one (packet~cycLe) of pills cost you? IcosT . l !11 FREE . 996 OK . 998 181 EH ~O NO. QUESTIONS AND FILTERS COOING CATEGORIES I I I I I I PUBL ~C SECTOR I 318 CHECK 312; GOVERNMENT HOSPITAL . 11 GOVERNMENT HEALTH CENTER . 12 SHE/HE STERILIZED [~ USING ANOTHER METHCO ~ F~ I V v Where did the Where did you obtain steriliz@tion take (METHO0) the last time? place? (NAME OF PLACE) RECORD MINES HOSPITAL OR CLINIC AS PRIVATE ('21~), SKIP I TO FIELD WORKER . 13 ~321 MEDICAL PRIVATE SECTOR PRIVATE HOSPITAL OR CLINIC.,.21 MISSION HOSPITAL OR CLINID.22 PHARMACY . 23 PRIVATE DOCTOR . 24 MOBILE CLINIC . 25~ FIELD WORKER . 2&~321 OTHER PRIVATE SECTOR J I SHOP . 31 OTHERFRIENDS/RELATIVES~_ . 413~- 321 O~ . 9 MINUTES . I ~ I HOURS . 2 DK . . . . . . . . . . . . . . . . . . . . . . . . . . . 9998 319 l How Long does it take to travel I from your ho~e to this place? IF LESS THAN 2 HOJR$, RECORD NINUTES. OTHERWISE, RECORD HOURS. 320 I Is it easy or difficult to get there? EASY . I DIFFICULF . 2 322 CHECK 312: SHE/HE ~ USING ANOTHER I STERILIZED METHO0 ~ ~323 MDNTH . 334 the sterikization o~ration ~rfor~? YEAR . I I . For how many months have you been using (CURRENT METHOD) continuously? 329 IF LESS THAN 1 MONTH, RECORD 'DO ' . 8 YEARS OR LONGER . 323 324 J Do you intend to use a ~ethod to delay or avoid m YES . 1 =326 I pregnancy mt any t~r~e in the future? [ NO . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Z J DK . 8 =330 325 What is the r~in reason you do not int(~qd to use a method? WANTS CHILDREN . Ol-- LACK OF KNOWLEDGE . 02 PARTNER OPPOSED . 03 COST TOU /HOCN . 04 SIDE EFFECTS . 05 HEALTH CONCERNS . 06 HARD TO GET METHDOS . 07 RELIGION . 08 OPPOSED TO FAMILY PLANNING . 09 FATAL IST IC . 10 OTHER PEOPLE OPPOSED . 11 INFREQUENT SEX . 12 DIFFICULT TO GET PREGNANT . 13 MENOPAUSAL/HAD HYSTERECTOMy.14 INCONVENIENT . 15 NOF MARRIED . 16 OTHER 17 (SPECIFY) DK . 9e,~ -330 32' I °°'°u'°'e" t° I YES . '1 within the next 12 months? NO . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 DK . B 327 When you use a methc~J, which rnethod woutd you prefer co use? PILL . 01 [UD . 02 INJECTIONS . 03 DIAPHRAGM/FOAM/JELLY . 04 CONDOM . OS FEMALE STERILIZATION . 06 MALE STERILIZATION . 07 NATURAL FAMILY PLANNING . O ~ WITHDRAWAL . 09 OTHER 1 330 (SPECIFY) EN 11 182 329 NO. QUESTIONS AND FILTERS 328 Uhere can you get (METHQO MENTIONED IN 3E?)? 330 (NAME OF PLACE) CHECK 312: USING NATURAL FAMILY PLANNING, UITHDRAMAL, E~ OTHER TRADITIONAL METHCO ¥ Do you know of a pLace ~here you can obtain a method of family planninQ? S~iP COOING CATEGORIES I TO PUBLIC SECTOR J GOVERNMENT HOSPITAL . 11 L332 GOVERNMENT HEALTH CENTER . 12 ~332 FIELD I~ORKER . 13 ~334 NEDICAL PRIVATE SECTOR J PRIVATE HOSPITAL OR CLINIC.,.21 NISSIOM HOSPITAL OR CLINIC,.22]-~33Z PHARMACY . 23 / PRIVATE DOCTOR . 24 NOQILE CLINIC . 25~ FIELD ~KER . 261.334 OTHER PRIVATE SECTOR m SHOP . 31 .33Z FRIENDS/RELATIVES . 32 OTHER 41-'-]-~334 (SPECIFY) OK . 98 ~330 I USING A I'K]OERN NETHO0 ~-~ .334 I I YES . 1 I I NO . 2 ~334 331 Where is that? (NAME OF PLACE) PUBLIC SECTOR I GOVERNMENT HOSPITAL . 11 GOVERNMENT HEALTH CENTER . 12 FIELD t/ORKER . 13 ~334 MEDICAL PRIVATE SECTOR PRIVATE HOSPITAL DR CLINIC.21 NISSION HOSPITAL DR CLINIC.22 PHARMACY . 23 PRIVATE DOCTOR . 24 MOBILE CLINIC . . . . . . . . . . . . . . . . . 25-- FIELD k~RKER . 2~334 OTHER PRIVATE SECTOR I I SH(~ ° . 31 FRIENDS/RELATIVES . 32 OTHERDK ~ 9 6 ~ - ~ 3 3 6 332 I Hou Long does it take to travel From your home to this plata? IF LESS THAN 2 HOURS, RECD~D MINUTES. OTHERMISE, RECORD HOURS. MINUTES . 1 I l i l HOURS . 2 OK . 9998 333 Is it easy or difficult to get there? I EASY . 1 DIFFICULT . 2 334 In the Last month, have you heard a mess=ge about FamiLy planning on: the radio? television? I YES NO I RAD%O . 1 2 TELEVISION . 1 2 335 Is it acceptabte to you for family planning information to be provided on: the radio? television? I YES NO I RADIO . 1 2 TELEVISION . 1 2 183 ~FI It. SECTION 4A. PREGNANCY AND GREASTF~EDING 402 I ENTER THE LINE NUMBER, NAME, AND SURVIVAL STATUS OF EACH BIRTH SINCE JANUARY 19G5* IN THE TABLE. [ ASK THE QUESTIONS AGCJJT ALL OF THESE BIRTHS. BEGIN WITH THE LAST BIRTH, (IF THERE ARE MORE THAN ] BIRTHS, USE ADDITIONAL FORMS). Now I wouLd Like to ask you some more questions about the health of all your children bern in the past five years. (We will talk about one child at a time.) i L,NE N GER FRON 0. 2,2, I l l J FROND. 212 403 J At the t i~ you became I pregnant with (NAME), did you want to bec~ pregnant then, did you want to wait until Late~ or did you want no (more) I children at all? LAST G%RTH NAME THEN . 1 ] (SKIP TO 4GS)e* / LATER . 2 NO h~DRE . (SKIP TO 4G5)4 / NEXT'TO'LAST GIRTH NAME THEN . . . . . . . . . . . . . . . . . . . . . 1 1 (SKIP TO 4OS)~ / LATER . 2 NO MORE . / (SKIP TO 40S)4 SECORD*FRDM-LAST BIRTH j NAME TGER . . . . . . . . . . . . . . . . . . . . . Ill (SKIP TO 4GS)4 J I LATER . 2 NO HONE . 31 (SKIP TO 40S)~ ] | 4G4 I How n~JCh Longer would you ] Like to have waited? MONTHS . . . . . . . . . . . . 1 IQONTHS . . . . . . . . . . . . 1 YEARS . . . . . . . . . . . . . 2 YEARS . 2 YEARS . 2 BK . 998 ON . 998 OK . 998 J 4OS When you were pregnant with (NAME), did you see anyone for antenatal care for this pregnancy? IF YES, WhcEn did you see? AnyOne else? RECORD ALL PERSONS SEEN. HEALTH PROFESSIONAL GOCTOR . A NURSE/MIDWIFE . g DLIN]CAL OFFICER . C OTHER PERSON TRAINED TRADITIONAL GIRTH ATTENDANT . . . . . . . . D TRADITIONAL GIRTH ATTENDANT . E OTHER F :HEALTH PROFESSIONAL DOCTOR . A NURSE/MIDWIFE . B CLIN]CAL OFFICER . C OTHER PERSON TRAINED TRADITIONAL BIRTB ATTENDAHT . . . . . . . . D TRADITIONAL BIRTH ATTENDANT . E OTHER F HEALTH PROFESSIONAL DOCTOR . A NURSE/M]BW[FE . B CLINICAL OFFICER . C OTHER PERSON TRAINED TRADITIONAL BIRTH ATTGNDANT . . . . . . . . D TRADITIONAL GIRTH ATTENDANT . E OTHER F (SPECIFY) (SPECIFY) (SPECIFY) NO ONE . G NO ONE . G- NO ONE . G (SKIP TO 409)4 (SKIP TO 409)4 (SKIP TO 4G9),- 406 | Were you given an YES . ( YES . I YES . 1 [ antenatal card for this pregnancy? NO . 2 NO . 2 NO . 2 DK . B BK . 8 OK . G 407 J H°w manY m°nths pregnant I I ] ~- ] [~ were you when you first RONTHS . NONTHS . MONTHS . saw someone for =n antenatal check on this pregnancy? BK . 98 BK . 98 OK . 98 408 IH°wWanY antenatal visits [ I J ~ did you have during NO. OF VISITS . NO. OF VISITS . NO. OF VISITS . this preg~ncy? OK . 98 BK . 98 OK . 98 409 When you were preg~nt with (NAHE) were you given YES . 1 YES . 1 YES . 1 an injection in the arm To oreveot The beOy NO . . . . . . . . . . . . . . . . . . . . . . . 21 NO . . . . . . . . . . . . . . . . . . . . . . . 21 NO . . . . . . . . . . . . . . . . . . . . . . . 21 gett~ng tetanus, that is, (SKIP TO 4T1)4 8~ DK (SKIP [0 411)4 8~ (SKZP TO 41( )~- convulsions after Birth? DK . DK . 410 During this pregnancy ~ ~ how many times did you Bet TIMES . TIRES . TIRES . this injection? OK . 8 DK . 8 OK . 8 EN 13 184 /.11 I i~here did you give !birth to (NAME)? LAST SIRTH NAME HONE YOUR H~4E . 11 OTHER HONE . 12 PUBLIC SECTOR GVT. HOSPITAL . 21 GVT. HEALTH CENTER . 22 PR J VATE SECTOR PVT. HOSP%TAL/CL]NiC,, ~31 MISSION HOSP./CLINIC.32 OTHER '1 (SPECIFY) NEXT'TO'LAST DISTH NAME HOME YOUR HQHE . 11 OTHER HONE . . . . . . . . . . . . . 12 >UDLIC SECTOR GVT. HOSPITAL . 21 GVT, HEALTH CENTER . 22 ~RIVATE SECTOR PVT. HOSPITAL/CLIMIC.~I MISSION HOSP,/CLINIC.,32 STHER '1 (SPECIFY) I SECO~- FR~4- LAST SIHTH gAME HONE YOUR HOME . 11 OTHER H(Xa~ . 12 PUBLIC SECTOR GVT. HOSPITAL . . . . . . . . . . 21 GVT. HEALTH CENTER . 22 PR[VATE SECTOR PVT. HOSP]TAL/CLLN]C.~1 MISSION HOSP,/CLIN]C.32 OTHER ~.1 (SPECIFY) /.12 Who assisted ~ith the detivery of (NAME)? Anyone e(se? PROBE FOR THE TYPE OF PERSON AND RECOND ALL PERSONS ASSISTZNG. HEALTH PROFESSZONAL DOCTOR . A NURSE/MIDMI FE . B CLINICAL OFFICER . C OTHER PERSO~ TRAINED TRADITIONAL BIRTH ATTEMOANT . D TRAOI T %OHAL BIRTH ATTENDANT . E SELAT IVE . E OTHER G IHEALTH PROFESSIONAL DOCTO~ . A MURSE/MiDMI FE . B CLINICAL OFFICER . C 3THER PERSON TRAINED TRADITIONAL BERTH ATTENDANT . D TRADITIONAL BIRTH ATTENDAHT . E RELATIVE . F DTHER G HEALTH PROFESSIONAL DOCTOR . A NURSE/MIDWIFE . H CLINICAL OFFICER . C OTHER PERSON TRAINED TRADITIONAL BIRTH ATTENDANT . 0 TRADITIOHAL BIRTH ATTENDANT . E RELATIVE . F OTHER G (SPECIFY) (SPEC%FY) (SPECIFY) NO ONE . H ~i0 ONE . H NO ONE . H ,13 m was (NAME) born ~ tim ON TIME . 1 OH TIME . 1 ON TIME . 1 m I I or pr~turel.y? PREKATURELY . 2 PREMATURELY . 2 PREMATURELT . Z DK . 8 OK . 8 DK . S . , i . a (HAME) .vered IYES . . . . . . . . . . . . . . . . . . . . . . i TES . . . . . . . . . . . . . . . . . . . . . . , I TES . . . . . . . . . . . . . . . . . . . . . . 1 I by caesarian sectio~? NO . 2 NO . 2 NO . 2 /.15 I ghen (NAME) was born, uas he/she: very large, VERY LARGE . 1 VERY LARGE . 1 VERY LARGE . 1 larger than average, LARGER THAN AVERAGE . 2 LARGER THAN AVERAGE . 2 LARGER THAN AVERAGE . E average, AVERAGE . 3 AVERAGE . 3 AVERAGE . . . . . . . . . . . . . . . . . . 3 smaller than average, SMALLER THAN AVERAGE . /* SMALLER THAN AVERAGE . 6, SMALLER THAN AVERAGE . 4 or very small? VERY SHALL . S VERY SHALL . S VERY SHALL . 5 DK . 8 OK . . . . . . . . . . . . . . . . . . . . . . . 8 DK . 8 J NO . 21 YESHO . . 1 1 /.16 atWas birth?[NAME) weighed NoYES . . 21 YES . 1 2] (SKIP TO /.181, ] [SK%P TO /* 91. (SKIP TO /.19), _ . . . . . . . . . . . . . . . . . . D'' OORA' . . . . . . . . . OK . 1.98 OK . 1.98 OK . 1.98 I I i 418 HaS your period returned YES . .1 ] iiiiii!ii!!i~ii[i[i!iii[iiiiiii Jiiiiiiiiii![!!!!!~iiiil]i[ii[iiii[!iiiii!iii Ji (SKIP TO /*Z1 )4 /.19 I Did~4~x,1~your)., =~pml~4.yrperi°d return between YES . 1 YES . 11 I dldffffii~ff~ff~ffff!ffff~ff~ff~hfflh]ffffiffliifffflfftiliffffff~ffffa[]~ ] (SKIp TO /*~3), | the birth of (NAME) did KONTHS . MONTHS . MONTHS . r~ F,~r,u~ OK . . . . . . . . . . . . . . . . . . . . . . 98 OK . . . . . . . . . . . . . . . . . . . . . . 98 OK . . . . . . . . . . . . . . . . . . . . . . 98 I ON UNSURE . ~'"" "~;~!"~"" ''r !"" """" ~ '; :~:~::::: :;:::::" :: : ~:~ ::::::: : (SKIP TO 422 | Have you resumed sexual I re(atio~s SJoCe The birth of (HAMS)? 423 | For hoN many months after I the birth of (NAME) did I you no~t have sexual relations? MONTHS . ~ 1 MONTHS . ~--~1 MONTHS . ['~1 oK . . . . . . . . . . . . . . . . . . . . . . 98 I OK . i,-'." I OK . ,G I EN 14 185 I 424 J Did you ever breastfeed (NAME)? LAST BIRTH NAME YES . . . . . . . . . . . . . . . . . . . . . . I (SKIP TO 426)4 ] RO . NEXT*TO-LAST BIRTH NAME YES . 1 (SKIP TO 4]3)4 ] NO . . . . . . . . . . . . . 2 SECOND-FROM-LAST BIRTH J NAME YES . ,]1 (SKIP TO 433)~ I NO . . . . . . . . . . . . . . . . . . . . . . . 2 425 Why did you not breastfeed (NAME)? MOTHER ILL/WEAR . 01- CHILD ILL/WEAK . 02 CHILD DIED . . . . . . . . . . . . . . O] NIPPLE/BREAST PRO~LEN.O4 INSUFFICIENT MILK . . . . . . . OS MOTHER ~KIRG . 06 CHILD REFUSED . 07 OTHER O& (SPECIFY) (SKIP TO 4]5)4 MOTHER ILL/WEAK . 01 CHILD ILL/WEAK . 02 CHILD DIED . 0] NIPPLE/BREAST PROBLEM.04 INSUFFICIENT MILK . OS MOTHER ~KIMG . 06 CHILD REFUSED . 07 OTHER .OR (SPECIFY) (SKIP TO 4]S)a MOTHER ILL/WEAK . 01 CHILD ILL/WEAK . 02 CHILD DIED . 03 RIPPLE/BREAST PROBLEN.04 INSUFFICIENT MILK . 05 MOTHER WORKING . O~ CHILD REFUSED . 07 OTHER O& (SPECIFY) (SKIP TO G]5)~ 426 HOW Long after birth did 428 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. Are you still breast- feeding (NAME)? IMMEDIATELY . F i )i iLffii~Lffff i!F!5 1! )~)) i~ ~ HOURS . . . . . . . . . . . . . . I DAYS . . . . . . . . . . . . . 2 ~ )~))i)i)l)[ii)i)~) ~[ ])i )i)) )][]~ ))l l~)i)) ))))]))i) )Fi)) ))) )))))) L) ););;);EH;I]H~););I;I;) ;) )) ;H ));~THil];i;iii)~i;~ff~;lff;i)::~:): i !)iLi[Z)[ii[~[[)Lff+~)i)ilESEii[iEi~)iF~ ) i ILS [) [ [[)i )) F H ) LJ [6)i iil)~Jff]EF! [ff 51~)6)L~i ~i~ ii!~i~ ff~ff15)i)i ) ] i)[ L/ [2)[i 16ill) ) ] )))F])]i))]i)) ) ) DEAD ? (SKIP TO 433) V YES . 1 NO . . . . . . . . . . . . . . . . . . . . . . . 2 (SKIP TO 4]])~ ] 429 J Now many times d id you I breastfeed last n ight between sunset and sunrise? IF ANSWER IS NOT NUMERIC, PROiBE FOR APPROXIMATE RUMBER. 430 | Now n~any t imes d id you I breastfeedyesterday during the daykight hours? IF ANSWER IS NOT NUMERIC, PROBE FO~ APPROXIMATE NUMBER. 431 AT any time yesterday or last night was (NAME) given any of the following?: Plain water? Sugar water? Juice? Tea? Baby forr~ta? I Fresh milk? Tinned or powdered milk? Other liquids? Any so l id o r ~shy Food? NU~4BER OF NIGHTTIME FEEDINGS HUMBER DF DAYLIGHT FEEDINGS !!!iiii)iiil)il)tiii)ilili!!!!!)! )) ) i ii i iiiii!iiiiiiiiiiii! ii iiiiiii!i iil)ii!i)i))!)ili!i!iiiii)ii)iiil)iiiiiii)i)ii!i)iiiiii!)iiii)iii!ii)iiiiiiil! i~i;i~i ;~i~;~L;;i~i~ Z ~i~i~ii~i]ii]iiii]i]]i]!!i!~!!~t;~ U ~!!! ! ~ ~ i i ~ '~ i~ ~:~iiii~i~+Ei~ )!)Li)))i!ili)i)!ii)i)ii)))ii))))i)i)!)ii)i)])i)!il)!)!)!;)!i!!il ii)i) ))i) il : :: :::::::::::::::::::::::::::::: : u : YES NO PLAIN WATER . 1 2 i SUGAR WATER . 1 21 JUICE . 1 2 I ) ;;~;;~;~) ~ ; ;;))H )ii)i])ii)ii)i)HH)iii)ii)ii TEA . 1 2 BABY FORMULA . 1 Z FREBH MILK . 1 2 ! OTHER LIQUIDS . 1 2 iiiiii)(]il)iilLi))))ii))ii)ii[]))])ii)(~J~U~)])!)U))i))i!)!))I)!)!))D! I J , iiii))))i)iiii~)F H L) ~)SVF j~[ ) ~ ~::) ~) )) ) L )) J) L! SOL ID /MUSNY FO~O . . . . . I Z ~Hil)ii~i)ilFi 6! ) )) ~ )) ~[iFi ii!li~ff= :~:h~ ~====~=:=~::::::: r::~:=:~ :m.:~.:.::=::=~:::: i)i ~i i ::::::::::::::::::::::::::::::::::: . . . . . . . . . . . . . . . CHECK 431: F~ OR LIQUID GIVEN YESTERDAY? "YES" TO ONE OR "RO" TO ALL @ v ¥ (SKIP TO 437) (SKIP TO 436 EN 15 186 G33 For how nw~y months d~d you breastfeed (NAME)? LAST BIRTH NAME NONTHS . . . . . . . . . . . . . . F ~ ;; ; ; ; i ; 9 NEXT'TO'LAST BIRTH NAME MONTHS. . . . . . . . . . . [ ~ NAMESECOND" FBOR- LAST BIRTH I 434 436 MOTHER ILLIUEAK. . . . . . . . . 01 CHILD l LLIUEAK . . . . . . . . . . 02 CHILD DIED, . . . . . . . . . . . . ,03 NIPPLE/BREAST PROBLEM.04 INSUFFICIENT MiLK . . . . . . . 05 MOTHER WORNI NG, . . . . . . . . . 06 CHILD REFUSED . . . . . . . . . . . 07 WEANING AGE. . . . . . . . . . . . .08 BECAME PREGNANT . . . . . . . . . 09 STARTED USING CORTRAGEPT [ ON . . . . . . . . . . 10 OTHER 11 (SPECIFY) YES. . . . . . . . . . . . . . . . . . . . . .1 NO . . . . . . MOTHER I LL/WEAN. . 01 CHILD ILL/WEAK . 82 CHILD DIED. . .03 NIPPLE/BREAST PROeLEM,, .04 INSUFFICIENT MILK . 85 MOTHER WORKING. . .06 CHILD REFUSED . 07 UEANI NG AGE . . . . . . . . . . . . . 08 BECAME PREGNANT . . . . . . . . . 09 STARTED USING CONTSACEPT ] ON . . . . . . . . . . 10 OTHER 11 (SPECIFY) ALIVE(sKI P 043,)I DERO NO . . . . . . YES" MOTHER l LL/WEAX . . . . . . . . . 01 CHILD I LL/UEAK . OZ CHILD DIED . 03 NIPPLE/BREAST PROBLEM.O4 INSUFFZCIENT M]LN, . .O5 MOTHER WORKING . . . . . . . . . . 06 CHILD REFUSED . 07 WEAN ZNG AGE . . . . . . . . . . . . . OB BECAME PREGNANT . . . . . . . . . 09 STARTED USING CONTRACEPTION . 1D OTHER 11 (SPECIFY) ALIVE(sK|P~TO 437) v DEAD ~v I 437 sterted giving the following on ~ regular basis?: FormuLa or milk other than breastmi L k? PLain water? Other L iquids? Any solid or mushy food? IF LESS THAN I k~BTH, RECORO ~00'. AGE IN MONTHS . J t J NOT GIVEN . 96 AGE IN MONTHS. J I J NOT GIVEN. . .96 AGE IN NO~TH$ . J [ J t401 GIVEN. . .96 AGE IN MONTHS . . . . . . . ] I I HOT GIVEN . .96 AGE IN MONTHS J I I NOT GIVEN . 96 AGE IN MONTHS . . . . . . . J I I NOT G[VEN . 96 AGE IN ~NTNS . I I I MOT GIVEN . ,96 AGE IN MONTHS J J J NOT GIVEN . . . . . . . 96 (SKIP TO 440) RGE IH MONTHS . i NOT GIVEN . 96 AGE IN MONTHS . . . . . . . I I l NOT GIVEN . .96 AGE IN MONTHS . J ] I NOT GIVEN . 96 AGE IN MONTHS . J I l NOT GIVEN . 96 (SKIP TO 440) 438 CREEK ~6: CHILD ALIVE? ~440 I GO RACK TO 403 FOR NEXT BIRTH; OR, IF NO NOSE BIRTHS, GO TO FIRST COLUMN OF 441 EN 16 187 441 442 SEETIOR 4B. JWP4UMIZATIOM AND HEALTH ENTER THE LIME NUMBER AND NAME OF EACH BIRTH SINCE JANUARY 1987 IN THE TABLE. ASK THE OUESTIONS ABOUT ALL OF THESE BIRTHS. BEGIN WITH THE LAST BIRTH. (IF THERE ARE MORE THAN ] BIRTHS, USE ADDITIONAL FORMS). LINE NUMBER FROM G, 212 Do you have • card where (MANE'S) vaccinations ~re written down? IF YES: May 1 see i t , p lease? IIJ LAST BIRTH NAME YES, SEEN . 1 (SKIP TO 444)4 / YES+ NOT SEEM . 2 1 (SKIP TO 446)4 / WO CARD . . . . . . . . . . . . . . . . . . ] II1 NEXT-TO-LAST BIRTH HA~E YES, SEEN . . . . . . . . . . . . . . . . 1 "'7 (SKIP TO 444)~ YES, MOT SEEM . 2] (SKIP TO 446)4 / MO CARD . . . . . . . . . . . . . . . . . . 3 SECOND-FROM-LAST BIRTH NAME YES, SEEN . 1 '1 (SKIP TO 444)~ J YES, NOT SEEN . 2 I (SKIP TO 446)~ J NO CARD . 3 ++1 °'°+'++'" + . '] + . !! . '] . vacc Jnat Jm card fo r (SKIP TO 446)+- - ! ! ! ! .P ~?.6!.4 (SKIP TO 446)+ (MANE)? NO . 2 NO . . . . . . . . . . . 2 MO . 444 (1) COPY VACCIMATIOR DATES FOR EACH VACCINE FRUM THE CARD. (2) WRITE '44' IN 'DAY I COLUMN F CARD SHOWS A VACCINE WAS GIVEN BUT NO DATE WAS RECORDED. 445 BOO POLIO 1 POLIO 2 POLIO 3 DPT 1 DPT 2 OPT 3 MEASLES Has (MANE) received any vaccinations that are not recorcleO on this carU? RECORD 'YES J ONLY IF RESPONDENT MENTIONS BCG, OPT 1"3, POLIO 1-3 AND/OR MEASLES VACCINE(S). DAY MO YR BCO Pl PZ P3 D1 02 03 MEA YES . 1 (PROBE FOR VACCINATIONS~ AND WRITE +c~6' IN THE CORRESPONDING DAY COLUMN IN 444) NO . i:i::::: ~2 OK . (SKIP TO 448 DAY 140 YR YES . 1 (PROBE FOR VACCINATIONM~ AND WRITE '6<~+ IN THE CORRESPONDING DAY COLUMN IN 444) NO . oK-'- i~;;%'i i i ; - 1 . DAY NO YR BOG Pl P2 P3 Dt D2 L-- D3 NEA 1 i CORRESPONDING DAY * HoODLuM. 1.+) ~1 OK:::::::::::::::::::::::8 (SKIP TO 44B +++I °+°+E++++" ++ . . . . . . . . . . . . . . . . . . . . . . i + . . . . . . . . . . . . . . . . . . . . . . i + . . . . . . . . . . . . . . . . . . . . . . il ~ny vacc i~t J~ To MO . . . . . . . . . . . . . . . . . . . . . . . 2 MO . . . . . . . . . . . . . . . . . . . . . . . 2 NO . . . . . . . . . . . . . . . . . . . . . . . 2 prevent him/her from DK (SKIP TO 4+8)+ OK (SKIP TO 448)+ DK (SKIP TO 44814 getting diseases? . 447 Ptease te t ( me if (MARE) (has) received eny of the fo[ Lowing vaccinations: A BCG vaccir~tion against tuberculosis, that is, an injection in the teft forearm that caused a scar? Polio vaccine, that is, drops in the mouth? IF YES: How many tin~s? OPT vaccine, given in the right thigh or buttock to prevent whooping cough? IF YES: How ~ny times? An injection against meas!es? CHECK 216: CHILD ALIVE? YES . 1 NO . 2 DK,., . B YES . 1 NO . 2 OK . 8 NUMBER OF TINES . ~'~ YES . 1 NO . 2 DK . B NUMBER OF TIMES . YES . 1 . 2 DK . 8 ALIVE @ (SKIP ToV450 ) [ GO BACK TO 4/*2 FOR NEXT MIRTH; OR, IF NO MORE BIRTHS, SKIP TO YES . I NO . 2 DK . B YES . . . . . . . . . . . . . . . . . . . . . . I NO . OK . 8 NUMBER OF TINES . YES . I NO . 2 DK . 8 NUMBER OF TIMES . YES . 1 NO . , . . . +.2 OK . B AL,VE (SKIP TO 450) 480. YES . . . . . . . . . . . . . . . . . . . . . . + NO . 2 DK . 8 YES . . . . . . . . . . . . . . . . . . . . . . I NO . . . . . . . . . . . . . . . . . . . . . . . OR . . . . . . . . . . . . . . . . . . . . . . . NUMBER OF TIMES . [~ YES . I NO . DK . NUI4BER OF TIMES . [-~ YES . 1 RO . 2 OK . 8 RLIVE (SKIP TO 450) m 188 EN I7 450 I LAST BIRTH NAME I Hes (gAME) been iLL with YES . I a fever at any time in NO . 2 the list Z weeks? OK . 8 NEXT" TO" LAST BIRTH NAME YES . 1 NO . 2 OR, . .,.8 SECOND-FRO~-LAST BIRTH I NAME YES . I | I HO . OK . 8 451 HiS (NAME)been ill with YES . I YES . 1 YES . 11 a cough at any time in NO . 21 NO . 21 NO . 2 The (as( 2 weeks? (SKIP TO 455)4 8J (SKIP TO 455)~ 8j (SKIP TO 455)4 DR . DK . DE . 452 m Has (NAME) been ill with YES . 1 YES . 1 YES . 1 m i a cough in the Last NO . 2 NO . 2 NO . 2 I 24 hours? OK . 8 OK . 8 OK . B 454 I~en (NAME) had the ! illness with a cough, did he/she breathe faster than usual with short, rapid breaths? m ~ 455 I CHECK 450 AND 451: I FEVER ON COUGH? 456 Was anything given to treat the fever/cough? YES . 1 / 1 NO . 2 DK . S "YES ~' IN EITHER OTHER 4so OR l-l.(sNIP 4s1 / TO 460) 1 l v ~ YES . 1 NO . 2 (SKIP TO 45B)~ J OK . .*. . 8J YES . 1 J [ NO . . . . . . . . . . . . . . . . . . . . . . . 2 DK . 8 "YES"IN EITHER OTHER 450 OR ~ ~].(SKIP 451 J TO 4601 I l v ~ YES . 1 NO . 2 (SKIP TO 45B)~ OK YES . 1 NO . 2 OK . S "YES" IN E I THER OT HER 650 OR [~ E-'],(SKIP 451 | TO 660) l v ~ NO . . . . . . . . . . . . . . . . . . . . . . . ~ DK (SKIP TO 458)q 457 What was given To treat the fever/cough? Anything ekse? RECORD ALL MENTIONED. INJECTION . A ANTIBIOTIC (PILL OR SYRUP) . B ANTIMALARIAL (PILL OR SYRUP) . C COUGH SYRUP . O OTHER PILL OR SYRUP . E UNKNONN PILL OR SYRUP.,F HONE REMEDY/ HERBAL MEDICINE . . . . . . . . . G OTHER H INJECTiON . A ANTIBiOTiC (PILL OR SYRUP) . B ANTIMALARIAL (PILL OR SYRUP) . C COUGH SYRUP . O OTHER P]LL OR SYRUP . E UNKNOWN PiLL OR $YRUP,.,,F HONE REMEDY/ HERBAL MEDICiNE . G OTHER H iNJECTION . A ANTiBIOTiC (PILL ON SYRUP) . B ANTIMALARIAL (PILL ON SYRUP) . C COUGH SYRUP . D OTHER PILL OR SYRUP . E UNKNOWN PILL OR SYHUP.F HONE REMEDY/ HERBAL MEDICINE . G OTHER H (SPECIFY) (SPECIFY) (SPECIFY) I (SKIP TO 460)~ YES . (SKIP TO 460). 1 YES . 1 I1 658 Did you seek advice or YES . 1 ] NO . 2 NO . 2 NO . 2 treatment for the fever/cough? (SKIP TO 460)u / 459 Where did you seek advice or treat~.-ntT Anywhere else? RECORD ALL MENTIONED, PUBLIC SECTOR GVT, HOSPITAL . A GVT. HEALTH CENTER . B CCM~4UNITY HEALTH WORKER.C MEDICAL PRIVATE SECTOR PVT. HOSP]TAL/CL]NZC,,,.D HISS[ON HOSP./CLIN]C.E PHARMACY . F PRIVATE DOCTOR . G OTHER PRIVATE SECTOR SHOP . H TRADITIONAL HEALER . 1 OTHER J (SPECIFY) PUBLIC SECTOR GVT. HOSPITAL . A OVT. HEALTH CENTER . B COMMUNITY HEALTH UOBKEB.C MEDICAL PRIVATE SECTOR PVT. HOSP]TAL/CLIN]C.D MISSION HOSP./CLINIC.E PHARMACY . F PRIVATE DOCTOR . G ITHER PR]VATE SECTOR SHOP . H TRADITIONAL HEALER . Z )THER J (SPECIFY) PUBLIC SECTOR GVT. HOSPITAL . A GVT. HEALTH CENTER . S CO~U4UBiTY HEALTH WOHKER.C MEDICAL PRIVATE SECTOR PVT. HOSPITAL/CL[NIC.D MISSION HOSP./CLINIC,,.E PHARMACY . F PRIVATE DOCTOR . G OTHER PRIVATE SECTOR SHOP . H TRADITIONAL HEALER . I OTHER J (SPECIFY) EH 18 189 46olH C.E dirre LYES . lIqEs . YE . . . . . . . . . . . . . . . . . . . . . . in the last two weeks? (SKIP TO 462), ] (SKIP TO 462)4 1 (SKIP TO 462)~ NO . 2 NO . 2 NO . 2 i ~ ~ ~ ~ D K . B OK . 8 DK . 8 461 J GO BACK TO 442 EOR NEXT BIRTH; OR, IF NO MORE BIRTHS, SKIP TO 480 462 m Has (WANE) had diarrhea YES . 1 YES . 1 YES . 1 I I in the Last 24 hours? NO . 2 NO . . . . . . . . . . . . . . . . . . . . . . . 2 NO . . . . . . . . . . . . . . . . . . . . . . . 2 I (] OR MORE WATERY STOOLS) DK . S DK . B DK . 8 4°3 For ho,--y dav, (ha, the FT1 diarrhea l~sted/did DAYS . DAYS . DAYS . the diarrhea Last)? IF LESS THAN I DAY, WRITE 'DO'. 46(5 | During (N#d4E)'s diarrhea, I did you change the frequency of breastfeeding? YES . I ~ ~ ~ :~ ]~ ~ ~ ~]]~ff~[~:~ NO . 2 (SKIP TO 4~I W~- iiiiiiiiiiiiiiiiiiiiiiiii~il]iiiiiil]iiiii~ii~ii[i~ii;iiiii ; i iil ili~ii I iiiiiiiii[iiiiiiiiiiiiiiii]iii[ii[!~ii~iiii~ii[iiiii;iiiiiiii i :iiiii~ii 467 I Did you increase the numloer of INCREASED . 1 ~ ~:~:::::~E~ . | I breastfeeds or reduce them, REDUCED . 2 I i i i![ ~i:[ ]ii[[ i[ii~iiiii i or did you stop complete(y? STOPPED C04PLETELY . 3 468 ] (Aside from breastmitk) I Was he/she given the same SAME . 1 SAME . 1 SAME . 1 an~unt to drink as before MORE . 2 MORE . 2 MORE . 2 the diarrhea, or more, or LESS . 3 LESS . 3 LESS . 3 less? OK . . . . . . . . . . . . . . . . . . . . . . . B DK . . . . . . . . . . . . . . . . . . . . . . . 8 DK . . . . . . . . . . . . . . . . . . . . . . . 8 469 IWas anything given to treat YES . i YES . i YES . i1 the diarrhea? NO . . . . . . . . . . . . . . . . . . . . . . . 2 NO . . . . . . . . . . . . . . . . . . . . . . . 2 NO . 2 DK (SKIP TO 471)-- (SKIP TO 471)~ DK (SKIP TO 47~). . UK . . . 470 What was given to treat the diarrhea? Anything else? RECORD ALL MENTIONED. FLUID FROM ORS PACKET.A HOMENADE SUGAR/SALT SOLUTION . B ANTIBIOTIC PILL OR SYRUP,C OTHER PILL OR SYRUP . D INJECTION . E (l.V.) INTRAVENOUS . F HOME REMEDIES/ HERBAL MEDICINES . O OTHER B FLUID FROM ORS PACKET.A HOREMADE SUGAR/SALT SOLUTION . B ANTIBIOTIC PILL OR SYRUP.C OTHER PILL OR SYRUP . D INJECF[ON . E (I.V.) INTRAVENOUS . F HOME REMEDIES/ HERBAL MEDICINES . G OTHER B FLUID FROM ORS PACKET.A HO~4EMADE SUC~R/SALT SOLUTION . E ANTIBIOTIC PILL OR SYRUP.C OTHER PILL OR SYRUP . O INJECTION . E ( I .V . ) INTRAVENOUS . F HOME REMEDIES/ HERBAL MEDICINES . G OTHER B (SPECIFY) (SPECIFY) (SPECIFY) l NO . 2] (SKIP TO 4~), l YES . 1 I 471 Did you seek advice or YES . 1 YES . 1 NO . 2 NO . 2 treatment for the diarrhea? SKIP TO 473)~ (SKIP TO 473), | 472 Where did you seek advice or treatment? Anywhere else? RECORD ALL MENTIONED. PUBLIC SECTOR GVT. HOSPITAL . A GVT. HEALTH CENTER . B COMPQJRITY HEALTH W()RKEB.C MEDICAL PRIVATE SECTOR PVT. HOSPITAL/CLIHIC.mmD MISSION HOBP./CLINIC.E PHARMACY . F PRIVATE DOCTOR . G OTHER PRIVATE SECTOR SHOP . H TRADITIONAL HEALER . I OTHER d (SPECIFY) PUBLIC SECTOR GVT. HOSPITAL . A GVT. HEALTH CENTER . B CO~4UN]TY HEALTH WORKER.C MEDICAL PRIVATE SECTOR PVT. HOSP[TAL/CL[NIC.D MISSION HOSP./CLINIC.E PHARMACY . F PRIVATE DOCTOR . G OTHER PR[VATE SECTOR SHOP . H TRADITIONAL HEALER . l OTHER J (SPECIFY) PUBLIC SECTOR GVT. HOSPITAL . A GVT, HEALTH CENTER . B CO~4MUMITY HEALTH WORKER.C MEDICAL PRIVATE SECTOR PVT. HOSPITAL/CLINIC.D MISSION HOSP./CLINIC.E PHARMACY . F PRIVATE DOCTOR . G OTHER PRIVATE SECTOR SHOP . . . . . . . . . . . . . . . . . . . . H TRADITIONAL HEALER . I UTHER J (SPECIFY) ER 19 190 4~ 474 CHECK 470: ORS FLUID FROg PACKET NEXTIONED? Was (MANE) given Nacizi a Noyo (or UNICEF ORS packet) when he/she had the diarrhea? LAST ~iRTH NANE NO, YES~ ORS FLUID ORS FLUID NOT MENT%ONED MENT]ORED v YES . 1 NO . 2 (SKIP TO 476)J | OK . 8J ~EXT'TO'kAST BIRTH NAHE NO, YES, ORS FLUID ORE FLUID NOT MENTIONED MENT ]ONED E~ (SKIP ~o 475) y YES . 1 No . . . .Z -1 (SK%P TO 476)4 DK. * . ~J SECOND-FR~%AST EIRIB MANE NO, YES, ORS FLUID ORS FLUID NOT MENTIONED NENT%OHED (SKIP To 475 V YES . 1 NO . 2 (SK%P TO 476)4 4~ 476 477 For ho~ eany days was (N~E) given N~z i a Noyo? IF LESS THAN I DAY, RECORD 'DO'. CHECK 470: HOMEMADE SUGAR/SALT SOLUTION MENTIONED? Was (NAME) given a homemade ftuid made fr~ stager, salt and water when he/she had the diarrhea? DAYS . OK . 98 gO, YES, HONE FLUZD HONE FLUID NOT MENT]ORED MENTIONED (SKIP TYro 478 V YES . 1 NO . 2 (SKIP TO 479)~ | 8J DK . DAYS . ~-~ DX . 9B NO, YES, HONE FLUID HONE FLUID NOT NENTIONED NEMTIORED (SKIP Tv~]Ok78) v DAYS . OK . 96 NO, YES, NONE FLUID HORE FLUID MOT MENTIONED NENTZONED (SKIP TV~O 478 V YES . 1 YES . 1 NO . . . . . . . . . . . . . . . . . . . . . . . 2 HO . 2 (SKIP TO 479)4 ~ DK . OK (SKIP TO 479)4 478 For how ~ny days was (NAI4E) given the fluid made from sugar, saLt and water? IF LESS THAN 1 DAY, WRUE 'DO'. DAYS . DK . 98 DAYS . OK . 98 GO BACK TO 442 FOR NEXT BIRTH; ON, IF NO MORE B%RTHS~ GO TO 480 DAYS . DK . 98 ER 20 191 NO. I QUESTIONS AND FILTERS m CODING CATEGORIES 48~ CHECK 470 AND 474 (ALL COLUMNS): ORS FLUID FROM PACKET GIVEN TO ANY CHILD F-l ORS FLUID FROM PACKET NOT GIVEN TO ANY CHILD OR 470 AND 474 NOT ASKED SKIP I (,84 I Nave you ever heard of a special product called Madzi a I YES . I I ,483 Moyo you can get for the treatment of diarrhea? I NO . 2 482 I Have Y°U ever seen a packet like this bef°re? I YEs . I I SH(~4 PACKET. NO . 2 ~487 483 I Have you ever prepared a solution with one of these I YES . 1 packets to treat diarrhea in yourself or someone else? I NO . 2 ~486 SHOW PACKET. I 484 | The last time you prepared Madzi a Moyo, did you I WHOLE PACKET AT ONCE . I I I prepare the whole packet at once or only part of I I the packet? PART OF PACKET . 2 ~486 I 485 How much water did you use to prepare Madzi a Moyo the last time you made it? I\2 LITER . 01 750 MLS . 02 I LITER . 03 1 1\2 LITERS . 04 2 LITERS . 05 FOLLOWED PACKAGE INSTRUCTIONS.06 OTHER 07 (SPECIFY) DK . 98 486 487 488 Where can you get Madzi a Moyo packet? PROBE: Anywhere else? RECORD ALL PLACES MENTIONED. CHECK 470 AND 477 (ALL COLUMNS): HOME-MADE FLUID F~ H~E'MADE LT--J NOT GIVEN TO ANY CHILD FLUID GIVEN I DR TO ANY CHILD 470 AND 477 HOT ASKED v Where did you Learn to prepare the ho~ fluid made from sugar, salt ar~:J water that was given to (NAME) when he/she had diarrhea? PUBLIC SECTOR GQVERNMENT HOSPITAL . A GOVERNMENT HEALTH CENTER . S COMMUNITY HEALTH WORKER . C MEDICAL PRIVATE SECTOR PRIVATE HOSPITAL/CLINIC . D MISSION HOSPITAL/CLINIC . E PHARMACY . F PRIVATE DOCTOR . G OTHER PRIVATE SECTOR SHOP . H TRADITIONAL PRACTICIANER . I OTHER J (SPECIFY) PUBLIC SECTOR GOVERNMENT HOSPITAL . 11 GOVERNMENT HEALTH CENTER . 12 COMMUNITY HEALTH WORKER . 13 MEDICAL PRIVATE SECTOR PRIVATE HOSPITAL/CLINIC . 21 MISSION HOSPITAL/CLINIC . 22 PHARMACY . 23 PRIVATE DOCTOR . 24 OTHER PRIVATE SECTOR SHOP . 31 TRADITIONAL HEALER . 32 OTHER 41 (SPECIFY) ~5011 192 EH 21 No. I 50, I SECTION 5. QUESTIONS AND FILTERS Rave you ever been married or lived with a man? MARRIAGE SKIP I CODING CATEGORIES I TO I YES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . I I NO . 2 ~512 501 reyouno r or vn h ran or reyounowI 0 . . 1 widowed, divorced, or no longer living together? LIVING TOGETHER . 2 WIDOWED . 3 1 DIVORCED 4 ~507 NO LONGER LIVING TOGETHER . 5 / 503 I Is y°ur husbar~/partner Living with Y°U n°w °r is elsewhere? I LIVING WITH HERSTAYING ELSEWHERE . . 21 I 50& I DOeSyourself?your husband/partner have any other wives besic~s I YES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 I I I NO . 2 ~507 I 505 How many other wives does he have? NUMgER . ~ I I OK . 9~ ~507 ~o61 ,r.,oo,,.,,~,, .oo~,.,,., I'" . . . . . . . . . . . . . . . . . . . . . . . ~1 507 Have you been married or lived with a man only once, ONCE . . . . . . . . . . . . . . . . . . . . 1 I or more than once? I MORE THAN ONCE . 2 508 In what month and year did you start living with your (first) husband/partner? MONTH . DK MONTH . 98 YEAR . ~ DK YEAR . 98 509 How old were you when you started living with him? AGE . F--~I DK AGE . 98 EN 22 193 NO, I QUESTIONS AND FILTERS I 510 i CHECK 508 AND 509: V ~ YEAR AND AGE YES GIVEN? 511 CHECK CONSISTENCY OF 508 AND 509: YEAR OF BIRTH (105) ~ 1 1 PLUS + AGE AT MARRIAGE (509) CALCULATED F ~ YEAR OF MARRIAGE [ I L I I NO COOING CATEGORIES IF NECESSARY, CALCULATE YEAR OF BIRTH CURRENT YEAR MINUS CURRENT AGE (106) CALCULATED YEAR OF BIRTH SKIP TO ~513 I 512 IS THE CALCULATED YEAR OF MARRIAGE WITRIN ORE YEAR OF THE REPORTED YEAR OF MARRIAGE (508) ? YES NO (SKIP TO 513) I I IF NEVER IN UNION: I Have you ever had sexual intercourse? F~ =PROBE AND CORRECT 508 AND 509. YES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . I NO . 2 ~517 513 Now we need some details about your sexual activity in order to get a better understanding of family planning and fertility. How many times did you have sexual intercourse in the last four weeks? TIMES . I 514 I HOW many times in a month do you usually have I sexual intercourse? I TIMES . F'~ I 515 When was the last time you had sexual intercourse? DAYS AGO . I WEEKS AGO . 2 MONTHS AGO . 3 YEARS AGO . 4 BEFORE LAST BIRTH . 996 517 I How old were you when you fiF)t had sexual intercourse? I PRESENCE OF OTHERS AT THIS POINT. I AGE . F~96 I FIRST TIME WHEN MARRIED . YES NO I CHILDREN UNDER 10 . I 2 HUSBAND . 1 2 OTHER MALES . 1 2 OTHER FEMALES . 1 2 194 EN 23 NO. 601 602 603 SECTION 6. FERTIL%TY PREFERENCES QUESTIONS AND FILTERS CHECK 312: NEITHER HE OR SHE STERILIZED ? STERILIZED CHECK 502: [-7 CURRENTLY MARRIED NOT MARRIED/ OR LIVING NOT LIVING TOGETHER 9 TOGETHER F-7 CHECK 223: MOT PREGNANT OR UNSURE J T v Now Z have some questions about the future. Would you like to have (e/another) child or would you prefer not to have any (more) children? PREGNANT 9 I V Now I have some questions about the future. After the child you are expecting, would you Like to have another child or would you prefer not to have any more children? COOING CATEGORIES HAVE k (ANOTHER) CHILD . 1 NO MORE/NONE . 2 SAYS SHE CAHIT GET PREGNANT . ] UNDECIDED OR DK . 8 SKIP I TO ,607 I ,614 I ~610 604 605 606 CHECK 223: NOT PREGNANT OR UNSURE [~ ! How tong would you tike to wait from no. before the birth of (a/another) child? CHECK 216 AND 22]: HAS LIVING CHILD(REN) YES OR PREGNANT? 9 V CHECK 223: NOT PREGNANT OR UNSURE I V How old would you Like your youngest child to be when your next child is born? PREGNANT 9 I V How tong would you like to wait after the birth of the child you are expecting before the birth of another child? NO PREGNANT 9 I V HOW old would you like the child you are expecting to be when your next child is born? OTHER 996 I (SPECIFY) DK . 998 I ~610 I AGE OF CHILD ~ l I 607 Given your present circumstances, if you had to do it over again, do you think (you/your husband) wo~ld make the same decision to have an operation not to have any more chitdren? I YES . 1 I I HO,.,,,,.,.° . ° . , . 2 195 EN z4 NO. I QUESTIONS AND FILTERS 608 | DO you regret that (you/your husband) had the operation I not to have any (more) children? SKIP l COOING CATEGORIES I TO YES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . , J NO . 2 ~614 609 J I '; Why do you regret it? RESPONDENT WANTS ANOTHER CHILD.1 PARTNER WANTS ANOTHER CHILD . 2 SIDE EFFECTS . 3 614 OTHER REASON 4 (SPECIFY) I ooyooth,k h your u - - /par net .roy or I APPROVE . . . . . . . . . . . . . . . . . . . . . . . . 1 I disapproves of couples using a ~thod to avoid DISAPPROVES . 2 pregnancy? DK . 8 family planning in the past year? OgCE OR TWICE . 2 MORE OFTEN . 3 6,2 J Have you a.d your husba.d/partner ever d i . c u s s e d t h e number of children you would like to have? t YESNO . . 21 1 number of children that you want, or does he want more MORE CHILDREN . 2 or fewer than you want? FEWER CHILDREN . 3 DK . 8 . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 I breastfeeding before starting to have sexua( relations again, or doesn't it matter? DOESN'T MATTER . 2 616 I In general, do you approve or disapprove of couples I APPROVE . 1 I using a ~¢hod to avoid getting pregnant? I DISAPPROVE . 2 617 CHECK 216: HAS LIVING CHILD(REN) ~] / I v If you could go back to the time you did not have any children and could choose exactly the nufftber of children to have in your whole life, how many would that be? NO LIVING CHILDREM~ I v if you could choose exactly the nun~oer of children to have in your whole life, how many would that be? RECORD SINGLE NUMBER OR OTHER ANSWER, NUMBER . . . . . . . . . . . . . . . . . . . . . OTHER ANSWER 96 (SPECIFY) ,181 What do you think is the best r~Jn~er of ~nths or years between the birth of one child ar~ the birth of the next child? I MONTHS . I YEARS . 2 OTHER 996 (SPECIFY) EN 25 196 NO, 701 702 SECTION 7. HUSBANDIS BACKGROUND AND WOMAN'S ~ORK QUEST IONS AND F ILTERS COOING CATEGORIES CHECK 501: EVER MARRIED NEVER MARRIED/ OR LIVED NEVER LIVED TOGETHER ~ TOGETHER ASK QUESTIONS ADGUT CURRENT OR MOST RECENT HUSBAND/PARTNER. Old your (last) husband/partner ever attend school? I YES . 1 I NO** , . . . . . . , o , , . . . . . , . . . . . . . . , . .2 SKIP TO I ~708 I L-70S 703 What was the highest level of school he attended: primary, seco~ry, or higher? I PRIMARY . . . . . . . . . . . . . . . . . . . . . . . . I | SECONDARY . . . . . . . . . . . . . . . . . . . . . . . 2 I HIGHER . . . . . . . . . . . . . . . . . . . . . . . . . . 3 DK . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8 ~7OS 704 Row many years did he co~olete at that level? C{)MMENT YEARS . ~-~ DK . 98 705 706 707 What kind of work does (did) your (last) husband/partner mainly do? CHECK 705: ~,K]RKS (WORKED) 9 IN AGRICULTURE v DOES (DID) ~-~ NOT ~ORK IN AGRICULTURE I (Does/did) your husband/partner work mainly on his | own lat,x~ or family tared, or (does/did) he rent land, I or (does/did) he work on someone else's Land? HIS/FAMILY LAND . 1 RENTED LAND . 2 SOMEONE ELSE'S LAND . 3 EH 26 ]97 NO. J 708 I QUESTIONS AND FILTERS Aside from your own housework, are you currently working? SKiP I COOING CATEGORIES I TO YES . 1 .710 NO . 2 709 As you know, some women take up jobs for which they are paid in cash or kind. Others seil 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? I YES . 1 I I NO . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 ~717 710 ~hat is your occupat ion, that i s , what kind of work do you do? I I 711 In your current work, do you work for a member of your FOR FAMILY MEMBER . 1 family, for someone else, or are you self-employed? FOR SOMEONE ELSE . 2 SELF-EMPLOYED . 3 712 Do you earn cash for this work? J YES . 1 ] I I PROBE: Do you make money for working? NO . 2 713 Do you do this work at home or away from home? 715 CHECK 215/216/218: HAS CHILD BORN SINCE JAN. 1987 AND LIVING AT HOME? YES I White you are working, do you usuaLly | have (NAME OF YOUNGEST CHILD AT HOME) with you, I sometimes have him/her with you, or never have him/her with you? HOME . 1 A~IAY . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 NO USUALLY . . . . . . . . . . . . . . . . . . . . . . . . . 1 SOMETIMES . . . . . . . . . . . . . . . . . . . . . . . 2 NEVER . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 ] II ~717 I I =717 I 716 Who usuaLLy takes care of (NAME OF YOUNGEST CHILD AT HOME) white you are working? RECORD THE TIME HUSBAND/PARTNER . . . . . . . . . . . . . . . . 01 OLDER CHILD(REN) . 02 OTHER RELATIVES . 03 NEIGHBORS . 04 FRIENDS . 05 SERVANTS/HIRED HELP . 06 CHILD IS IN SCHOOL . 07 INSTITUTIONAL CHILDCARE . 08 OTHER 09 (SPECIFY) HOUR . . . . . . . . . . . . . . . . . . . . . . . MINUTES . 198 EN 27 SECTION 8, AIDS KNOWLEDGE No. I QUESTIONS AND FILTERS I 801 I NOW I have a fe~ questions about a very important topic. I I Have you heard of an iLLness called AIDS? I SKIP CODING CATEGORIES I To YES . 1 I SECT NO . 2 ~ 9 802 From which sources of information or persons have you heard about AIDS in the Last month? CIRCLE ALL MENTIONED. RADIO . A T V . . o , , . . . . ° . o ° ° , , , ° ° . . . . . °° . . . . S NEWSPAPERS . C HEALTH WORKERS . D CHURCH . E FRIENDS/RELATIVES . F SCHOOLS/TEACHERS . G SLOGANS/P~MPHLETS/POSTERS . H COMMUNITY MEETINGS . [ OTHER J (SPECIFY) NONE . K 803 How is the AIDS virus transmitted? CIRCLE ALL MENTIONED. SEXUAL INTERCOURSE . A MEEOLES/BLADES/SK|M PUNCTURES.B MOTHER TO CHILD . C TRANSFUSION OF INFECTED gLOOO.O OTHER E (SPECIFY) DON'T KNOM . F 804 0o you think that you can get AIDS from shaking hands with someone who has AIDS? hugging someone who has AIDS? kissing someone who has AIDS? wearing the clothes of someone who has AIDS? sharing eeti~ utensils with someone who has AIDS? stepping on the urine or stool of s~one who has AIDS? ~squito, flea or bedbug bites? YES NO HANDSHAKING . 1 2 HUGGING . 1 2 KISSING . 1 2 SHARING CLOTHES . 1 2 SHARING EATING UTEMSLLS . 1 2 STEPPING ON URINE/STOOL . 1 2 MOSQUITO/FLEA/BEDBUG BITES.1 2 805 I Is it possible for a healthy looking person m YES . 1 | I to be carrying the AIDS virus? I NO . 2 I D~ . . . . ,. . . . . . . . . . . . . . . . . . . . . . , . . 8 806 | Is it possible for o w~n ~ho has the AIDS virus to | YES . 1 | I give birth to a child with the AIDS virus? J NO . 2 I OK . 8 807 I Can AIDS be prevented? I YES . 1 | NO . 2 ~809 OK . 8 ~809 808 Now con AIDS be prevented? CIRCLE ALL MENTIONED, STICK TO ONE PARTNER . A I I USE CONDO~S . B STERILIZE SYRINGES/NEEDLES . C OTHER O (SPECIFY) 809 ~hat do you suggest is the most im~rtant thing the government should do for people who have AIDS? PROVIDE MEDICAL TREATMENT . 1 I HELP RELATIVES PROVIDE CARE . 2 I ISOLATE/QUARANTINE/JAIL . 3 NOT BE INVOLVED . 4 OTHER S (SPECIFY) 810 If your relative is suffering with ALOE, who would you prefer to care for him/her? I RELATIVES/FRIENOS . 1 I GOVERNMENT . 2 RELIGIOUS ORG./NISSION . 3 NOBOOY/ABARDON . 4 OTHER 5 (SPECIFY) EN Z8 ]99 SECTION 9, HEIGHT AND WEIGHT CHECK 222: ONE OR 140~E BIRTHS ~ flO BIRTHS SINCE JAW. 1987 I~J SINCE JAN. 1987 I~ ~ END INTERVIEWER: IN 902 (COLUMNS 2-¢) RECORD THE LINE NUMBER FOR EACH CHILD BORN SINCE JANUARY 1987 AND STILL ALIVE. IN 903 AND 904 RECORD THE NAME AND BIRTH DATE FOR THE RESPONDENT AND FOR ALL LIVING CHILDREN BORN SINCE JANUARY 1967, IN 906 AND 908 RECORD HEIGHT AND WEIGHT OF THE RESPONDENT AND THE LIVING CHILDREN. (NOTE: ALL RESPONDENTS WITH ONE OR MORE BIRTHS SINCE JANUARY 1987 SHOULD BE WEIGHED AND MEASURED EVEN IF ALL OF THE CHILDREN HAVE DIED. IF THERE ARE MORE THAN 3 LIVING CHILDREN BONN SINCE JANUARY 19B7, 902 LiNE NO. FROM D.212 USE ADDITIONAL FORMS). 903 NAME FROM G.212 FOR CHILDREN 904 DATE OF BIRTH FROM 0.105 FOR RESPONDENT FROM Q.215 FOR CHILDREN, AND ASK FOR DAY OF BIRTH 905 BCG SCAR ON LEFT FOREARM 906 HEIGHT (in centJme£ers) 907 ~AS HEIGHT/LENGTH OF CHILD MEASURED LYING DO~fl OR STANOING UP? 908 WEIGHT (in kilograr~s) 909 DATE WEIGHED AND MEASURED 910 RESULT RESPONDENT iiii!!!!!!!!!~!iiiii!!!!i!~!~iii~!ii!!!i!ii!!iiiiil (NAME) L• YOUNGEST LIVING CHILD ( NAME ) YEAR . DAY . VK)~ T H . :::::::::::::::::::::::::::::::::: . : SCAR SEEN . 1 ::::::::::::::::::::::::::::::::::::::::::::::: ::::::::::::::::::::::::::::::::::::::::::::: . NO SCAR . 2 iiiiiiiiiii!iiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiii~ DAY . MONTH . YEAR . MEASURED . 1 NOT PRESENT.3 REFUSED . 4 OTHER . 6 (SPECIFY) LYING . 1 STANDING . 2 DAY . MONTH . YEAR . CHILD MEASURED.1 CHILD SICK . 2 CHILD NOT PRESENT . 3 CHILD REFUSED.,6 MOTHER REFUSED.5 OTHER . . . . . . . . . . 6 (SPECIFY) NEXT'TO" YOUNGEST LIVING CHILD (NAME) DAY . MONTH . YEAR . SCAR SEEN . 1 NO SCAR . 2 LYING . 1 STANDING . Z OAY . MONTH . YEAR . CHILD MEASURED.1 CHILD SICK . 2 CHILD NOT PRESENT . 3 CHILD REFUSED,.4 MOTHER REFUSED.5 OTHER . 6 (SPECIFY) L• SECOND'TO" YOUNGEST LIVING CHILD (NAME) DAY . [ ~ MONTH . YEAR . SCAR SEEN . 1 NO SCAR . 2 LYING . 1 STANDING . 2 DAY . ~ ] ~ MONTH . YEAR . CHILD MEASURED.1 CHILD SICK . 2 CHILD NOT PRESENT . 3 CHILD REFUSED,,4 MOTHER REFUSED,5 OTHER . 6 (SPECIFY) 911 NAME OF MEASURER: NAME OF ASSISTANT: EN 29 200 Comments About Respondent: INTERVIEWER'S OBSERVATIONS (To be fil led in after completing interview) Comments on Specific Questions: Any Other Comments: SUPERVISQ~'S OBSERVATION S Name of Supervisor: Date: EDITOR'S OBSERVATIONS EN 30 201 Front Matter Title Page Contact Information Table of Contents List of Tables List of Figures Preface Summary of Findings Map of Zambia Chapter 01 - Introduction Chapter 02 - Characteristics of Households and Respondents Chapter 03 - Fertility Chapter 04 - Fertility Regulation Chapter 05 - Other Proximate Determinants of Fertility Chapter 06 - Fertility Preferences Chapter 07 - Infant and Child Mortality Chapter 08 - Maternal and Child Health Chapter 09 - Infant Feeding and Childhood and Maternal Nutrition Chapter 10 - Knowledge of AIDS References Appendix A - Survey Design Appendix B - Estimates of Sampling Errors Appendix C - Data Quality Tables Appendix D - Persons Involved in The Zambia Demographic and Health Survey Appendix E - Survey Instruments (Questionnaires) Household Questionnaire Individual Questionnaire

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