Zambia - Demographic and Health Survey - 2015

Publication date: 2015

Zambia Demographic and Health Survey 2013-14 Zambia Demographic and Health Survey 2013-14 Central Statistical Office Lusaka, Zambia Ministry of Health Lusaka, Zambia University of Zambia Teaching Hospital, Virology Laboratory Lusaka, Zambia University of Zambia Department of Population Studies Lusaka, Zambia Tropical Diseases Research Centre Ndola, Zambia The DHS Program ICF International Rockville, Maryland, USA March 2015 This report summarises the findings of the 2013-14 Zambia Demographic and Health Survey (2013-14 ZDHS) carried out by the Central Statistical Office (CSO) in partnership with the Ministry of Health as well as the University Teaching Hospital (UTH)-Virology Laboratory, the Tropical Diseases Research Centre (TDRC), and the Department of Population Studies at the University of Zambia (UNZA) under the overall guidance of the National Steering Committee from August 2013 to April 2014. The government, through the Ministry of Health and the Ministry of Finance, provided funding for the survey. ICF International provided technical assistance as well as funding to the project through The DHS Program, a USAID-funded project providing support and technical assistance in the implementation of population and health surveys in countries worldwide. Additional funding for the ZDHS was provided by the United States Agency for International Development (USAID), the Centers for Disease Control and Prevention (CDC), the United Nations Population Fund (UNFPA), and the United Nations Children’s Fund (UNICEF). Additional information about the 2013-14 ZDHS may be obtained from the Central Statistical Office, P.O. Box 31908, Lusaka, Zambia; Telephone: (260-211) 251377/85 257604/05; Fax: (260-211) 1253468; E-mail: Info@ zamstats.gov.zm; Internet: http:www.zamstats gov.zm; Data Portal: http://zambia.africadata.org. Information about The DHS Program may be obtained from The DHS Program, ICF International, 530 Gaither Road, Suite 500, Rockville, MD, USA; Telephone: (301) 407-6500, Fax: (301) 407-6501, E-mail: reports@ dhsprogram.com; Internet: http://www.dhsprogram.com. Cover photos: Victoria Falls in Livingstone, Zambia, © 2008 Arturo Sanabria, courtesy of Photoshare; the Livingstone Health District Clinic in Zambia, © 1997 Michael Bailey, courtesy of Photoshare; a woman and her children after a family planning consultation at Kalingalinga Clinic in Lusaka, Zambia, © 2009 Arturo Sanabria, courtesy of Photoshare; and mothers shelter, © 2009 Mpongwe Baptist Association, used with permission. Suggested citation: Central Statistical Office (CSO) [Zambia], Ministry of Health (MOH) [Zambia], and ICF International. 2014. Zambia Demographic and Health Survey 2013-14. Rockville, Maryland, USA: Central Statistical Office, Ministry of Health, and ICF International. Contents • iii CONTENTS TABLES AND FIGURES . ix PREFACE . xv ACRONYMS . xvii MILLENNIUM DEVELOPMENT GOALS . xix MAP OF ZAMBIA . xx 1 INTRODUCTION . 1 1.1 History, Geography, and Economy . 1 1.1.1 History . 1 1.1.2 Geography . 1 1.1.3 Economy . 1 1.2 Population . 2 1.3 The Population Policy and National Population and Development Programme of Action . 3 1.4 Health Priorities and Programmes . 3 1.5 Strategic Framework to Combat the National HIV/AIDS Epidemic . 5 1.6 Objectives and Organisation of the Survey . 5 1.6.1 Objectives . 5 1.6.2 Organisation . 6 1.7 Sample Design . 7 1.8 Questionnaires . 7 1.9 HIV and CD4 Cell Count Testing . 8 1.9.1 CD4 Measurement and Blood Collection for HIV Incidence Testing . 8 1.9.2 HIV Prevalence Testing . 9 1.9.3 HIV Incidence Testing . 10 1.10 Pretest Activities . 11 1.11 Training of Field Staff . 12 1.12 Fieldwork . 12 1.13 Data Processing . 12 1.14 Response Rates . 13 2 HOUSING CHARACTERISTICS AND HOUSEHOLD POPULATION . 15 2.1 Household Characteristics . 15 2.1.1 Water and Sanitation . 15 2.1.2 Housing Characteristics . 17 2.1.3 Household Possessions . 19 2.2 Socioeconomic Status Index . 20 2.3 Hand Washing . 21 2.4 Household Population by Age and Sex . 22 2.5 Household Composition . 23 2.6 Birth Registration . 24 2.7 Children’s Living Arrangements, Orphanhood, and School Attendance . 25 2.8 Education of Household Population . 26 2.8.1 Educational Attainment of Household Population . 27 2.8.2 School Attendance Ratios . 29 3 CHARACTERISTICS OF RESPONDENTS . 33 3.1 Characteristics of Survey Respondents . 33 3.2 Educational Attainment . 35 3.3 Literacy . 37 3.4 Exposure to Mass Media . 39 3.5 Employment Status . 41 3.6 Occupation . 44 iv • Contents 3.7 Type of Employment . 46 3.8 Health Insurance Coverage . 48 3.9 Tobacco Use . 49 3.10 Knowledge and Attitudes Regarding Tuberculosis . 51 4 MARRIAGE AND SEXUAL ACTIVITY . 55 4.1 Current Marital Status . 55 4.2 Polygyny . 56 4.3 Age at First Marriage . 58 4.4 Median Age at First Marriage . 60 4.5 Age at First Sexual Intercourse . 60 4.6 Median Age at First Sexual Intercourse . 62 4.7 Recent Sexual Activity . 62 5 FERTILITY . 67 5.1 Current Fertility . 67 5.2 Fertility Differentials . 68 5.3 Fertility Trends . 69 5.4 Children Ever Born and Living . 71 5.5 Birth Intervals . 72 5.6 Postpartum Amenorrhoea, Abstinence, and Insusceptibility . 73 5.7 Menopause . 75 5.8 Age at First Birth . 75 5.9 Teenage Pregnancy and Motherhood . 76 6 FERTILITY PREFERENCES . 79 6.1 Desire for More Children . 79 6.2 Desire to Limit Childbearing by Background Characteristics. 80 6.3 Ideal Family Size . 82 6.4 Fertility Planning . 84 6.5 Wanted Fertility Rates . 85 7 FAMILY PLANNING . 87 7.1 Knowledge of Contraceptive Methods . 88 7.2 Current Use of Contraception . 89 7.3 Current Use of Contraception by Background Characteristics . 91 7.4 Trends in Current Use of Family Planning . 93 7.5 Source of Contraception . 93 7.6 Brands of Pills, Injectables, and Condoms Used . 94 7.7 Informed Choice . 97 7.8 Contraceptive Discontinuation Rates . 98 7.9 Reasons for Discontinuation of Contraceptive Use . 99 7.10 Knowledge of Fertile Period . 100 7.11 Need and Demand for Family Planning Services . 100 7.12 Future Use of Contraception . 102 7.13 Reasons for Not Intending to Use Contraception in the Future . 102 7.14 Preferred Method for Future Use . 103 7.15 Exposure to Family Planning Messages . 103 7.16 Contact of Nonusers with Family Planning Providers . 105 7.17 Husband/Partner’s Knowledge of Women’s Contraceptive Use . 106 8 INFANT AND CHILD MORTALITY . 109 8.1 Assessment of Data Quality . 110 8.2 Levels and Trends in Infant and Child Mortality . 111 8.3 Socioeconomic Differentials in Childhood Mortality . 112 8.4 Demographic Differentials in Mortality . 113 8.5 Perinatal Mortality . 114 8.6 High-risk Fertility Behaviour . 116 Contents • v 9 MATERNAL HEALTH . 119 9.1 Antenatal Care . 119 9.2 Components of Antenatal Care . 121 9.3 Birth Preparedness . 123 9.4 Tetanus Toxoid Vaccination . 124 9.5 Place of Delivery . 126 9.6 Assistance during Delivery . 127 9.7 Reasons for Not Delivering in a Health Facility . 128 9.8 Postnatal Care . 129 9.8.1 Timing of First Postnatal Checkup for the Mother . 129 9.8.2 Provider of First Postnatal Checkup for the Mother . 130 9.9 Newborn Care . 131 9.9.1 Timing of First Postnatal Checkup for the Newborn . 131 9.9.2 Provider of First Postnatal Checkup for the Newborn . 132 9.10 Problems in Accessing Health Care . 133 9.11 Knowledge of Fistula and Reporting of Fistula-Like Symptoms . 134 10 CHILD HEALTH . 137 10.1 Child’s Weight and Size at Birth . 138 10.2 Vaccination Coverage . 139 10.3 Vaccination by Background Characteristics . 140 10.4 Trends in Immunisation Coverage . 142 10.5 Acute Respiratory Infection . 143 10.6 Fever . 145 10.7 Diarrhoea. 146 10.8 Diarrhoea Treatment . 147 10.9 Feeding Practices during Diarrhoea . 149 10.10 Knowledge of ORS Packets . 149 10.11 Disposal of Children’s Stools. 152 11 NUTRITION OF CHILDREN AND WOMEN . 155 11.1 Nutritional Status of Children . 156 11.1.1 Measurement of Nutritional Status among Young Children . 156 11.1.2 Data Collection . 157 11.1.3 Measures of Child Nutritional Status . 157 11.1.4 Trends in Children’s Nutritional Status . 161 11.2 Breastfeeding and Complementary Feeding . 162 11.3 Breastfeeding Status by Age . 163 11.4 Duration of Breastfeeding . 166 11.5 Types of Complementary Foods . 167 11.6 Infant and Young Child Feeding (IYCF) Practices . 169 11.7 Micronutrient Intake among Children . 171 11.8 Presence of Iodised Salt in Households . 174 11.9 Nutritional Status of Women . 175 11.10 Micronutrient Intake among Mothers . 177 12 MALARIA . 181 12.1 Ownership of Mosquito Nets . 181 12.2 Indoor Residual Spraying . 183 12.3 Access to an Insecticide-Treated Net . 184 12.4 Use of Mosquito Nets . 185 12.4.1 Use of Mosquito Nets by Persons in the Household . 186 12.4.2 Use of Existing Mosquito Nets . 188 12.4.3 Use of Mosquito Nets by Children under Age 5 . 188 12.4.4 Use of Mosquito Nets by Pregnant Women . 190 12.5 Use of Intermittent Preventive Treatment of Malaria during Pregnancy . 192 12.6 Prevalence, Diagnosis, and Prompt Treatment of Children with Fever . 193 vi • Contents 13 HIV/AIDS-RELATED KNOWLEDGE, ATTITUDES, AND BEHAVIOUR . 197 13.1 HIV and AIDS Knowledge, Transmission, and Prevention Methods . 198 13.1.1 Knowledge of AIDS and Knowledge of HIV Prevention . 198 13.1.2 Comprehensive Knowledge about HIV and AIDS . 199 13.2 Knowledge about Mother-to-Child Transmission . 202 13.3 Perceived Risk of HIV Infection . 203 13.4 Knowledge of Antiretroviral Drugs . 204 13.5 Attitudes toward People Living with HIV and AIDS . 206 13.6 Attitudes toward Negotiating Safer Sexual Relations with Husbands . 208 13.7 Attitudes toward Condom Education for Young People . 209 13.8 Higher-Risk Sex . 210 13.8.1 Multiple Sexual Partners . 210 13.8.2 Point Prevalence and Cumulative Prevalence of Concurrent Sexual Partners . 213 13.9 Paid Sex . 214 13.10 Coverage of HIV Testing Services. 215 13.11 HIV Counselling and Testing during Pregnancy . 218 13.12 Disclosure of HIV Test Results From ANC Visit . 220 13.13 Male Circumcision . 221 13.14 Self-Reporting of Sexually Transmitted Infections . 221 13.15 Injections . 223 13.16 HIV- and AIDS-Related Knowledge and Behaviour among Young People . 224 13.16.1 Knowledge about HIV and AIDS and Source for Condoms . 224 13.16.2 First Sex . 225 13.16.3 Premarital Sex . 227 13.16.4 Multiple Sexual Partners among Youth . 228 13.16.5 Age-Mixing in Sexual Relationships among Youth . 230 13.16.6 Drunkenness during Sexual Intercourse among Youth . 230 13.16.7 HIV Testing among Youth . 231 14 HIV PREVALENCE . 233 14.1 Coverage Rates for HIV Testing . 234 14.2 HIV Prevalence . 236 14.2.1 HIV Prevalence by Socioeconomic Characteristics . 236 14.2.2 Trends in HIV Prevalence . 237 14.2.3 HIV Prevalence by Demographic Characteristics. 238 14.2.4 HIV Prevalence by Sexual Behaviour . 239 14.3 HIV Prevalence among Young People . 240 14.4 HIV Prevalence by Other Characteristics Related to HIV Risk . 242 14.5 HIV Prevalence among Couples . 244 15 ADULT AND MATERNAL MORTALITY . 247 15.1 Assessment of Data Quality . 248 15.2 Estimates of Adult Mortality . 249 15.3 Estimates of Maternal Mortality . 250 16 WOMEN’S EMPOWERMENT AND DEMOGRAPHIC AND HEALTH OUTCOMES . 253 16.1 Employment and Form of Earnings . 254 16.2 Control over Cash Earnings and Relative Magnitude of Earnings . 254 16.2.1 Women’s Control over Their Cash Earnings . 255 16.2.2 Control over Husband’s Cash Earnings . 256 16.2.3 Women’s Earnings Relative to Their Husband’s Earnings . 257 16.3 Women’s and Men’s Ownership of Selected Assets . 258 16.4 Women’s Participation in Decision Making . 260 16.5 Attitudes toward Wife Beating . 264 16.6 Women’s Attitude toward Refusing Sex with Their Husband . 266 16.7 Women’s Empowerment Indicators . 269 16.8 Current Use of Contraception by Women’s Status . 270 16.9 Ideal Family Size and Unmet Need by Women’s Status . 271 16.10 Reproductive Health Care and Women’s Empowerment . 272 Contents • vii 17 DOMESTIC VIOLENCE . 273 17.1 Measurement of Violence . 273 17.1.1 Use of Valid Measures of Violence . 273 17.1.2 Ethical Considerations in the 2013-14 ZDHS . 274 17.1.3 Subsample for the Violence Module . 275 17.2 Experience of Physical Violence . 275 17.3 Perpetrators of Physical Violence . 277 17.4 Experience of Sexual Violence . 277 17.5 Perpetrators of Sexual Violence . 279 17.6 Age at First Experience of Sexual Violence . 279 17.7 Experience of Different Forms of Violence . 280 17.8 Violence during Pregnancy . 280 17.9 Marital Control by Husband. 282 17.10 Forms of Spousal Violence . 283 17.11 Spousal Violence by Background Characteristics . 285 17.12 Violence by Spousal Characteristics and Women’s Empowerment Indicators . 286 17.13 Recent Spousal Violence . 288 17.14 Onset of Spousal Violence . 290 17.15 Physical Consequences of Spousal Violence . 290 17.16 Violence by Women against Their Husbands . 291 17.17 Help-Seeking Behaviour by Women Who Experience Violence . 294 REFERENCES . 297 APPENDIX A SAMPLE SELECTION . 303 A.1 Introduction . 303 A.2 Sampling Frame . 303 A.3 Sample Design and Sampling Procedure . 304 A.4 Sampling Probabilities . 305 APPENDIX B ESTIMATES OF SAMPLING ERRORS . 313 APPENDIX C DATA QUALITY TABLES . 345 APPENDIX D PARTICIPANTS IN THE 2013-14 ZAMBIA DEMOGRAPHIC AND HEALTH SURVEY . 351 APPENDIX E QUESTIONNAIRES . 361 Tables and Figures • ix TABLES AND FIGURES 1 INTRODUCTION . 1 Table 1.1 Demographic characteristics . 2 Table 1.2 Results of the household and individual interviews . 13 2 HOUSING CHARACTERISTICS AND HOUSEHOLD POPULATION . 15 Table 2.1 Household drinking water . 16 Table 2.2 Household sanitation facilities . 17 Table 2.3 Household characteristics . 18 Table 2.4 Household possessions . 19 Table 2.5 Wealth quintiles . 20 Table 2.6 Hand washing . 21 Table 2.7 Household population by age, sex, and residence. 22 Table 2.8 Household composition . 23 Table 2.9 Birth registration of children under age 5 . 24 Table 2.10 Children’s living arrangements and orphanhood . 25 Table 2.11 School attendance by survivorship of parents . 26 Table 2.12.1 Educational attainment of the female household population . 27 Table 2.12.2 Educational attainment of the male household population . 28 Table 2.13 School attendance ratios . 30 Figure 2.1 Population pyramid . 23 Figure 2.2 Age-specific attendance rates of the de facto population 5 to 24 years . 31 3 CHARACTERISTICS OF RESPONDENTS . 33 Table 3.1 Background characteristics of respondents . 34 Table 3.2.1 Educational attainment: Women . 36 Table 3.2.2 Educational attainment: Men . 37 Table 3.3.1 Literacy: Women . 38 Table 3.3.2 Literacy: Men . 39 Table 3.4.1 Exposure to mass media: Women . 40 Table 3.4.2 Exposure to mass media: Men . 41 Table 3.5.1 Employment status: Women . 43 Table 3.5.2 Employment status: Men . 44 Table 3.6.1 Occupation: Women . 45 Table 3.6.2 Occupation: Men . 46 Table 3.7.1 Type of employment: Women . 47 Table 3.7.2 Type of employment: Men . 47 Table 3.8.1 Health insurance coverage: Women . 48 Table 3.8.2 Health insurance coverage: Men . 49 Table 3.9.1 Use of tobacco: Women . 50 Table 3.9.2 Use of tobacco: Men . 51 Table 3.10.1 Knowledge and attitudes concerning tuberculosis: Women . 52 Table 3.10.2 Knowledge and attitudes concerning tuberculosis: Men . 53 Figure 3.1 Women’s employment status (past 12 months) . 42 4 MARRIAGE AND SEXUAL ACTIVITY . 55 Table 4.1 Current marital status . 56 Table 4.2.1 Number of women’s co-wives . 57 Table 4.2.2 Number of men’s wives . 58 Table 4.3 Age at first marriage . 59 x • Tables and Figures Table 4.4 Median age at first marriage by background characteristics . 60 Table 4.5 Age at first sexual intercourse . 61 Table 4.6 Median age at first sexual intercourse by background characteristics . 62 Table 4.7.1 Recent sexual activity: Women . 63 Table 4.7.2 Recent sexual activity: Men . 64 5 FERTILITY . 67 Table 5.1 Current fertility . 68 Table 5.2 Fertility by background characteristics . 69 Table 5.3.1 Trends in age-specific fertility rates . 69 Table 5.3.2 Trends in age-specific and total fertility rates, various sources . 70 Table 5.4 Children ever born and living . 71 Table 5.5 Birth intervals . 72 Table 5.6 Postpartum amenorrhoea, abstinence, and insusceptibility . 73 Table 5.7 Median duration of amenorrhoea, postpartum abstinence, and postpartum insusceptibility . 74 Table 5.8 Menopause . 75 Table 5.9 Age at first birth . 75 Table 5.10 Median age at first birth . 76 Table 5.11 Teenage pregnancy and motherhood . 77 Figure 5.1 Trends in total fertility rate, ZDHS 1992-2014 . 70 6 FERTILITY PREFERENCES . 79 Table 6.1 Fertility preferences by number of living children . 80 Table 6.2.1 Desire to limit childbearing: Women . 81 Table 6.2.2 Desire to limit childbearing: Men . 82 Table 6.3 Ideal number of children by number of living children . 83 Table 6.4 Mean ideal number of children . 84 Table 6.5 Fertility planning status . 85 Table 6.6 Wanted fertility rates . 85 7 FAMILY PLANNING . 87 Table 7.1 Knowledge of contraceptive methods . 88 Table 7.2 Current use of contraception by age . 90 Table 7.3.1 Current use of contraception by background characteristics . 92 Table 7.3.2 Trends in the current use of family planning . 93 Table 7.4 Source of modern contraception methods . 94 Table 7.5.1 Use of social marketing brand pills and injectables . 95 Table 7.5.2 Use of social marketing brand condoms: Women . 96 Table 7.5.3 Use of social marketing brand condoms: Men . 97 Table 7.6 Informed choice . 98 Table 7.7 Twelve-month contraceptive discontinuation rates . 99 Table 7.8 Reasons for discontinuation . 99 Table 7.9 Knowledge of fertile period . 100 Table 7.10 Need and demand for family planning among currently married women . 101 Table 7.11 Future use of contraception . 102 Table 7.12 Reason for not intending to use contraception in the future . 102 Table 7.13 Preferred method of contraception for future use . 103 Table 7.14 Exposure to family planning messages . 104 Table 7.15 Exposure to specific radio and television programmes . 105 Table 7.16 Contact of nonusers with family planning providers . 106 Table 7.17 Husband/partner’s knowledge of women’s use of contraception . 107 Figure 7.1 Trends in the contraceptive prevalence rate, ZDHS 1992-2014 . 93 Figure 7.2 Trends in the preferred method for future use, ZDHS 1992-2014 . 103 Tables and Figures • xi 8 INFANT AND CHILD MORTALITY . 109 Table 8.1 Early childhood mortality rates . 111 Table 8.2 Early childhood mortality rates by socioeconomic characteristics . 113 Table 8.3 Early childhood mortality rates by demographic characteristics . 114 Table 8.4 Perinatal mortality . 115 Table 8.5 High-risk fertility behaviour . 116 Figure 8.1 Trends in childhood mortality, ZDHS 1992-2014 . 112 9 MATERNAL HEALTH . 119 Table 9.1 Antenatal care . 120 Table 9.2 Number of antenatal care visits and timing of first visit . 121 Table 9.3 Components of antenatal care . 122 Table 9.4 Birth preparedness plan . 124 Table 9.5 Tetanus toxoid injections . 125 Table 9.6 Place of delivery . 126 Table 9.7 Assistance during delivery . 127 Table 9.8 Reasons for not delivering in a health facility . 129 Table 9.9 Timing of first postnatal checkup for the mother . 130 Table 9.10 Type of provider of first postnatal checkup for the mother . 131 Table 9.11 Timing of first postnatal checkup for the newborn . 132 Table 9.12 Type of provider of first postnatal checkup for the newborn . 133 Table 9.13 Problems in accessing health care . 134 Table 9.14 Knowledge of fistula and experience of fistula-like symptoms . 135 10 CHILD HEALTH . 137 Table 10.1 Child’s size and weight at birth . 139 Table 10.2 Vaccinations by source of information . 140 Table 10.3 Vaccinations by background characteristics . 141 Table 10.4 Vaccinations in first year of life. 142 Table 10.5 Trends in vaccination coverage among children age 12-23 months, Zambia 1992-2014 . 142 Table 10.6 Prevalence and treatment of symptoms of ARI . 144 Table 10.7 Prevalence and treatment of fever . 146 Table 10.8 Prevalence of diarrhoea . 147 Table 10.9 Diarrhoea treatment . 148 Table 10.10 Feeding practices during diarrhoea . 150 Table 10.11 Knowledge of ORS packets or pre-packaged liquids . 152 Table 10.12 Disposal of children’s stools . 153 11 NUTRITION OF CHILDREN AND WOMEN . 155 Table 11.1 Nutritional status of children . 159 Table 11.2 Initial breastfeeding . 163 Table 11.3 Breastfeeding status by age . 164 Table 11.4 Median duration of breastfeeding . 167 Table 11.5 Foods and liquids consumed by children in the day or night preceding the interview . 168 Table 11.6 Infant and young child feeding (IYCF) practices . 170 Table 11.7 Micronutrient intake among children . 173 Table 11.8 Presence of iodised salt in household . 175 Table 11.9 Nutritional status of women . 176 Table 11.10 Micronutrient intake among mothers . 178 Figure 11.1 Nutritional status of children by age . 161 Figure 11.2 Trends in nutritional status of children under age 5, Zambia 1992-2014 . 161 Figure 11.3 Infant feeding practices by age . 165 xii • Tables and Figures Figure 11.4 IYCF indicators on breastfeeding status . 166 Figure 11.5 IYCF indicators on minimum acceptable diet . 171 Figure 11.6 Trends in nutritional status of women age 15-49 . 177 12 MALARIA . 181 Table 12.1 Household possession of mosquito nets . 182 Table 12.2 Indoor residual spraying against mosquitoes . 184 Table 12.3 Access to an insecticide-treated net (ITN) . 185 Table 12.4 Use of mosquito nets by persons in the household . 186 Table 12.5 Use of existing ITNs . 188 Table 12.6 Use of mosquito nets by children. 189 Table 12.7 Use of mosquito nets by pregnant women . 191 Table 12.8 Use of intermittent preventive treatment (IPTp) by women during pregnancy . 193 Table 12.9 Prevalence, diagnosis, and prompt treatment of children with fever . 194 Table 12.10 Source of advice or treatment for children with fever . 195 Table 12.11 Type of antimalarial drugs used . 196 Figure 12.1 Percentage of the de facto population with access to an ITN in the household . 185 Figure 12.2 Ownership of, access to, and use of ITNs . 187 Figure 12.3 Trends in the percentage of children under age 5 who slept under a mosquito net on the night before the survey by type of net, Zambia 2001-2014 . 190 Figure 12.4 Trends in use of mosquito nets among pregnant women age 15-49, Zambia 2001-2014 . 192 13 HIV/AIDS-RELATED KNOWLEDGE, ATTITUDES, AND BEHAVIOUR . 197 Table 13.1 Knowledge of HIV prevention methods . 199 Table 13.2.1 Comprehensive knowledge about AIDS: Women . 200 Table 13.2.2 Comprehensive knowledge about AIDS: Men . 201 Table 13.3 Knowledge of prevention of mother-to-child transmission of HIV . 202 Table 13.4 Perceived risk of HIV infection . 204 Table 13.5 Knowledge of antiretroviral drugs . 205 Table 13.6.1 Accepting attitudes toward those living with HIV/AIDS: Women . 206 Table 13.6.2 Accepting attitudes toward those living with HIV/AIDS: Men . 207 Table 13.7 Attitudes toward negotiating safer sexual relations with husband . 209 Table 13.8 Adult support of education about condom use to prevent AIDS . 210 Table 13.9.1 Multiple sexual partners: Women . 211 Table 13.9.2 Multiple sexual partners: Men . 212 Table 13.10 Point prevalence and cumulative prevalence of concurrent sexual partners . 214 Table 13.11 Payment for sexual intercourse and condom use at last paid sexual intercourse . 215 Table 13.12.1 Coverage of prior HIV testing: Women . 216 Table 13.12.2 Coverage of prior HIV testing: Men . 217 Table 13.13 Pregnant women counselled and tested for HIV . 219 Table 13.14 Disclosure of HIV test results from ANC HIV test . 220 Table 13.15 Male circumcision . 221 Table 13.16 Self-reported prevalence of sexually transmitted infections (STIs) and STI symptoms . 222 Table 13.17 Prevalence of medical injections . 224 Table 13.18 Comprehensive knowledge about AIDS and of a source of condoms among youth . 225 Table 13.19 Age at first sexual intercourse among young people . 226 Table 13.20 Premarital sexual intercourse and condom use during premarital sexual intercourse among young people . 228 Table 13.21.1 Multiple sexual partners in the past 12 months among young people: Women . 229 Table 13.21.2 Multiple sexual partners in the past 12 months among young people: Men . 229 Table 13.22 Age-mixing in sexual relationships among women age 15-19 . 230 Tables and Figures • xiii Table 13.23 Drunkenness during sexual intercourse among youth . 231 Table 13.24 Recent HIV tests among young people . 232 Figure 13.1 Trends in coverage of prior HIV testing . 218 Figure 13.2 Women and men seeking advice or treatment for STIs . 223 Figure 13.3 Trends in age of first sexual intercourse . 227 14 HIV PREVALENCE . 233 Table 14.1 Coverage of HIV testing by residence and province . 234 Table 14.2 Coverage of HIV testing by selected background characteristics . 235 Table 14.3 HIV prevalence by socioeconomic characteristics . 236 Table 14.4 HIV prevalence by demographic characteristics. 238 Table 14.5 HIV prevalence by sexual behaviour . 240 Table 14.6 HIV prevalence among young people by background characteristics . 241 Table 14.7 HIV prevalence among young people by sexual behaviour . 242 Table 14.8 HIV prevalence by other characteristics . 243 Table 14.9 Prior HIV testing by current HIV status . 243 Table 14.10 HIV prevalence by male circumcision . 244 Table 14.11 HIV prevalence among couples . 245 Figure 14.1 HIV prevalence among adults age 15-49, and by sex, Zambia 2001 02, 2007, and 2013-14 . 237 15 ADULT AND MATERNAL MORTALITY . 247 Table 15.1 Adult mortality rates . 249 Table 15.2 Adult mortality probabilities . 250 Table 15.3 Maternal mortality . 251 Figure 15.1 Age-specific mortality rates by sex . 250 Figure 15.2 Maternal mortality ratios (MMR) with confidence intervals for the seven years preceding the 1996, 2001-02, 2007, and 2013-14 ZDHS surveys (per 100,000 live births) . 252 16 WOMEN’S EMPOWERMENT AND DEMOGRAPHIC AND HEALTH OUTCOMES . 253 Table 16.1 Employment and cash earnings of currently married women and men . 254 Table 16.2.1 Control over women’s cash earnings and relative magnitude of women’s cash earnings . 255 Table 16.2.2 Control over men’s cash earnings . 257 Table 16.3 Women’s control over their own earnings and over those of their husbands . 258 Table 16.4.1 Ownership of assets: Women . 259 Table 16.4.2 Ownership of assets: Men . 260 Table 16.5 Participation in decision making . 261 Table 16.6.1 Women’s participation in decision making by background characteristics . 262 Table 16.6.2 Men’s participation in decision making by background characteristics . 263 Table 16.7.1 Attitude toward wife beating: Women . 265 Table 16.7.2 Attitude toward wife beating: Men . 266 Table 16.8.1 Attitude toward refusing sexual intercourse with husband: Women . 267 Table 16.8.2 Attitude toward refusing sexual intercourse with husband: Men . 268 Table 16.9 Indicators of women’s empowerment . 269 Table 16.10 Current use of contraception by women’s empowerment . 270 Table 16.11 Ideal number of children and unmet need for family planning by women’s empowerment . 271 Table 16.12 Reproductive health care by women’s empowerment . 272 Figure 16.1 Number of decisions in which currently married women participate . 261 xiv • Tables and Figures 17 DOMESTIC VIOLENCE . 273 Table 17.1 Experience of physical violence . 276 Table 17.2 Persons committing physical violence . 277 Table 17.3 Experience of sexual violence . 278 Table 17.5 Age at first experience of sexual violence . 279 Table 17.6 Experience of different forms of violence . 280 Table 17.7 Experience of violence during pregnancy . 281 Table 17.8 Marital control exercised by husbands . 282 Table 17.9 Forms of spousal violence . 284 Table 17.10 Spousal violence by background characteristics . 286 Table 17.11 Spousal violence by husband’s characteristics and empowerment indicators . 287 Table 17.12 Physical or sexual violence in the past 12 months by any husband/partner . 289 Table 17.13 Experience of spousal violence by duration of marriage . 290 Table 17.14 Injuries to women due to spousal violence . 291 Table 17.15 Women’s violence against their spouse . 292 Table 17.16 Women’s violence against their spouse by husband’s characteristics and empowerment indicators . 293 Table 17.17 Help seeking to stop violence . 294 Table 17.18 Sources for help to stop the violence . 295 Figure 17.1 Percentage of ever-married women age 15-49 who have experienced specific types of spousal physical or sexual violence by the current/most recent husband/partner . 285 APPENDIX A SAMPLE SELECTION . 303 Table A.1 Population distribution by province and by residence from the 2010 Census of Population and Housing, Zambia 2013-14 . 304 Table A.2 Sample allocation of clusters and households, according to province and by type of residence, Zambia 2013-14 . 305 Table A.3 Sample allocation of eligible women and completed women’s interviews, according to province and by type of residence, Zambia 2013-14 . 305 Table A.4 Sample allocation of eligible men and completed men’s interviews, according to province and by type of residence, Zambia 2013-14 . 305 Table A.5 Sample implementation: Women . 307 Table A.6 Sample implementation: Men . 308 Table A.7 Coverage of HIV testing by social and demographic characteristics: Women . 309 Table A.8 Coverage of HIV testing by social and demographic characteristics: Men . 310 Table A.9 Coverage of HIV testing by sexual behaviour characteristics: Women . 311 Table A.10 Coverage of HIV testing by sexual behaviour characteristics: Men . 312 APPENDIX B ESTIMATES OF SAMPLING ERRORS . 313 Table B.1 List of indicators for sampling errors, Zambia DHS 2014 . 315 Table B.2 Sampling errors: Total sample, Zambia DHS 2014 . 317 Table B.3 Sampling errors: Urban sample, Zambia DHS 2014 . 319 Table B.4 Sampling errors: Rural sample, Zambia DHS 2014. 321 Table B.5 Sampling errors: Central sample, Zambia DHS 2014 . 323 Table B.6 Sampling errors: Copperbelt sample, Zambia DHS 2014 . 325 Table B.7 Sampling errors: Eastern sample, Zambia DHS 2014 . 327 Table B.8 Sampling errors: Luapula sample, Zambia DHS 2014 . 329 Table B.9 Sampling errors: Lusaka sample, Zambia DHS 2014 . 331 Table B.10 Sampling errors: Muchinga sample, Zambia DHS 2014 . 333 Table B.11 Sampling errors: Northern sample, Zambia DHS 2014 . 335 Table B.12 Sampling errors: North Western sample, Zambia DHS 2014 . 337 Table B.13 Sampling errors: Southern sample, Zambia DHS 2014 . 339 Table B.14 Sampling errors: Western sample, Zambia DHS 2014 . 341 Table B.15 Sampling errors for adult and maternal mortality rates, Zambia 2013-2014 . 343 Tables and Figures • xv APPENDIX C DATA QUALITY TABLES . 345 Table C.1 Household age distribution . 345 Table C.2.1 Age distribution of eligible and interviewed women . 346 Table C.2.2 Age distribution of eligible and interviewed men . 346 Table C.3 Completeness of reporting . 347 Table C.4 Births by calendar years . 347 Table C.5 Reporting of age at death in days . 348 Table C.6 Reporting of age at death in months . 348 Table C.7 Nutritional status of children based on the NCHS/CDC/WHO International Reference Population . 349 Table C.8 Completeness of information on siblings . 350 Table C.9 Sibship size and sex ratio of siblings . 350 Preface • xvii PREFACE he 2013-14 Zambia Demographic and Health Survey (ZDHS) is a national sample survey designed to provide up-to-date information on background characteristics of the respondents, fertility levels, nuptiality, sexual activity, fertility preferences, awareness and use of family planning methods, breastfeeding practices, nutritional status of mothers and young children, early childhood mortality and maternal mortality, maternal and child health, awareness and behaviours regarding HIV/AIDS and other sexually transmitted infections (STIs), and prevalence and incidence of HIV/AIDS and other STIs. The target groups were men age 15-59and women age 15-49 in randomly selected households across Zambia. Information about children age 0-5 was also collected, including data on weight and height. The survey collected blood samples for HIV testing in order to determine national and provincial prevalence and incidence rates. While significantly expanded in terms of household coverage and scope, the 2013-14 ZDHS is a follow-up to the 1992, 1996, 2001-02, and 2007 ZDHS surveys and provides updated estimates of basic demographic and health indicators covered in the earlier surveys. The 2013-14survey is the third ZDHS that includes collection of information on violence against women and HIV testing. Also, it is the first ZDHS to collect information on HIV incidence. In addition, data on malaria prevention and treatment were collected. The 2013-14 ZDHS was implemented by the Central Statistical Office (CSO) in partnership with the Ministry of Health (MoH), the University of Zambia Teaching Hospital (UTH) Virology Laboratory, the Tropical Diseases Research Centre (TDRC), and the Department of Population Studies at the University of Zambia (UNZA) under the overall guidance of the National Steering Committee. A technical committee provided technical guidance for the survey. TDRC and the UTH Virology Laboratory provided technical support in the implementation of HIV testing. The government of Zambia, through the Ministry of Health and the Ministry of Finance, provided funding for the survey. Cooperating partners, namely the U.S. Centers for Disease Control and Prevention (CDC), the United Nations Children’s Fund (UNICEF), and the United Nations Population Fund (UNFPA), provided additional funds. The Demographic and Health Surveys Program at ICF International, which is funded by the United States Agency for International Development (USAID), provided technical assistance in the areas of survey design, sample design, questionnaire design, interviewer training, fieldwork logistics, blood specimen collection, laboratory testing, and data processing and analysis. CDC provided technical assistance with protocol development, as well as technical support to TDRC and UTH during laboratory testing and reporting of HIV incidence. Key people in the implementation of the 2013-14 ZDHS were Dr. Peter Mwaba, former Permanent Secretary, Ministry of Health; Dr. Davies M. Chikamata, current Permanent Secretary Ministry of Health; Mr. William Mayaka, former Deputy Director, Social Statistics- Central Statistical Office; Mr. Iven Sikanyiti, current Deputy Director, Social Statistics- Central Statistical Office; Dr. Christopher Simoonga, Director of Policy and Planning, Ministry of Health; Mrs. Sheila S. Mudenda, Survey Coordinator, Central Statistical Office; and Mr. Chipalo Kaliki, Survey Coordinator, Ministry of Health. Also instrumental to the implementation of the survey were Ms. Dorothy S. Kaemba, Josephine Chewe, and Chola N. Daka from the Central Statistical Office; Ms. Gina Mulundu of the UTH Virology Laboratory; Dr. Webster Kasongo of TDRC; Jacob RS Malungo of UNZA; and the team from ICF International that provided technical assistance during the design, planning, and implementation of the survey and during data processing and analysis. T xviii • Preface Special appreciation goes to the trainers, field monitors, supervisors, editors, interviewers, nurses/nurse counsellors, laboratory technicians, regional statisticians, provincial directors of health, and drivers for their hard work and commitment. Gratitude also goes to the respondents for their patience and willingness in providing the required information and the blood samples. This survey would not have been a success without their cooperation. John Kalumbi Director Census and Statistics Acronyms • xix ACRONYMS ACT artemisinin-based combination therapy AIDS acquired immunodeficiency syndrome ANC antenatal care ARI acute respiratory infection ASFR age-specific fertility rate BCG Bacille Calmette-Guerin BMI body mass index CBD Community Based Distributors CDC Centers for Disease Control and Prevention CDD Control of Diarrhoeal Diseases CEDAW Convention on the Elimination of All Forms of Discrimination Against Women CPR Contraceptive Prevalence Rate CSO Central Statistical Office CSPro Census and Survey Processing System DBS dried blood spot DFID Department of International Development DTP diphtheria, pertussis, and tetanus EA enumeration area ELISA enzyme-linked immunosorbent assay EPI Expanded Programme on Immunisation GDP gross domestic product GPS Global Positioning System GRZ Government of the Republic of Zambia HIV human immunodeficiency virus HepB hepatitis B IMCI Integrated Management of Childhood Illnesses IPTp intermittent preventive treatment IRS indoor residual spraying ITN insecticide-treated net IUD intrauterine device IYCF Infant and Young Child Feeding LAM lactational amenorrhoea method LLIN long-lasting insecticidal net MCDMCH Ministry of Community Development Mother and Child Health MDG Millenium Development Goal MOFNP Ministry of Finance and National Planning MoH Ministry of Health MoJ Ministry of Justice NAC National AIDS Council NCDP National Commission for Development Planning NFNC National Food and Nutrition Commission NGO non-governmental organisation xx • Acronyms NHSP National Health Strategic Plan OPV oral polio vaccine ORS oral rehydration salt ORT oral rehydration therapy PAHO Pan American Health Organization PMTCT Prevention of Mother-to-Child Transmission POPIN United Nations Population Information Network RHF recommended home fluid SDM standard days method STI Sexually transmitted infection TDRC Tropical Diseases Research Centre TFR total fertility rate UNDP United Nations Development Programme UNFPA United Nations Population Fund UNICEF United Nations Children’s Fund UNZA University of Zambia USAID United States Agency for International Development UTH University Teaching Hospital VAD Vitamin A deficiency WHO World Health Organization ZDHS Zambia Demographic and Health Survey Millennium Development Goal Indicators • xxi MILLENNIUM DEVELOPMENT GOAL INDICATORS Millennium Development Goal Indicators Zambia 2013-14 Sex Total Indicator Male Female 1. Eradicate extreme poverty and hunger 1.8 Prevalence of underweight children under age 5 16.0 13.5 14.8 2. Achieve universal primary education 2.1 Net attendance ratio in primary education1 81.4 84.5 83.0 2.3 Literacy rate of 15 to 24-year-olds2 84.9a 77.3 81.1b 3. Promote gender equality and empower women 3.1 Ratio of girls to boys in primary, secondary ,and tertiary education 3.1a Ratio of girls to boys in primary education3 na na 1.0 3.1b Ratio of girls to boys in secondary education3 na na 1.1 3.1c Ratio of girls to boys in tertiary education3 na na 0.8 4. Reduce child mortality 4.1 Under-5 mortality rate4 87 74 75 4.2 Infant mortality rate4 53 43 45 4.3 Proportion of 1-year-old children immunized against measles 84.4 85.5 84.9 5. Improve maternal health 5.1 Maternal mortality ratio5 na na 398 5.2 Percentage of births attended by skilled health personnel6 na na 64.2 5.3 Contraceptive prevalence rate7 na 49.0 na 5.4 Adolescent birth rate8 na 141.2 na 5.5a Antenatal care coverage: at least one visit9 na 97.7 na 5.5b Antenatal care coverage: four or more visits10 na 55.5 na 5.6 Unmet need for family planning na 21.1 na 6. Combat HIV/AIDS, malaria, and other diseases 6.1 HIV prevalence among the population age 15-24 5.4 7.7 6.6 6.2 Condom use at last high-risk sex11 50.1 40.1 45.1 6.3 Percentage of the population age 15-24 with comprehensive correct knowledge of HIV/AIDS12 46.7 41.5 44.1 6.4 Ratio of school attendance of orphans to school attendance of non-orphans age 10-14 0.87 0.86 0.86 6.7 Percentage of children under 5 sleeping under insecticide-treated bed nets 40.5 40.6 40.6 6.8 Percentage of children under 5 with fever who are treated with appropriate antimalarial drugs13 41.2 38.5 39.9 Urban Rural Total 7. Ensure environmental sustainability 7.8 Percentage of population using an improved drinking water source14 89.2 46.9 63.1 7.9 Percentage of population with access to improved sanitation15 39.2 19.7 27.3 na = Not applicable 1 The ratio is based on reported attendance, not enrollment, in primary education among primary school age children (7-13 years). The rate also includes children of primary school age enrolled in secondary education. This is a proxy for MDG indicator 2.1, Net enrollment ratio. 2 Refers to respondents who attended secondary school or higher or who could read a whole sentence or part of a sentence 3 Based on reported net attendance, not gross enrollment, among 6-12-year-olds for primary, 13-17-year-olds for secondary, and 18-22-year- olds for tertiary education 4 Expressed in terms of deaths per 1,000 live births. Mortality by sex refers to a 10-year reference period preceding the survey. Mortality rates for males and females combined refer to the five-year period preceding the survey. 5 Expressed in terms of maternal deaths per 100,000 live births in the seven-year period preceding the survey 6 Among births in the five years preceding the survey 7 Percentage of currently married women age 15-49 using any method of contraception 8 Equivalent to the age-specific fertility rate for women age 15-19 for the three years preceding the survey, expressed in terms of births per 1,000 women age 15-19 9 With a skilled provider 10 With any health care provider 11 High-risk sex refers to sexual intercourse with a non-marital, non-cohabitating partner. Expressed as a percentage of men and women age 15- 24 who had higher-risk sex in the past 12 months. 12 Comprehensive knowledge means knowing that consistent use of a condom during sexual intercourse and having just one uninfected faithful partner can reduce the chance of getting the AIDS virus, knowing a healthy-looking person can have the AIDS virus, and rejecting the two most common local misconceptions about transmission or prevention of the AIDS virus. 13 Measured as the percentage of children age 0-59 months who were ill with a fever in the two weeks preceding the interview and who received any antimalarial drug 14 Percentage of de jure population whose main source of drinking water is a household connection (piped), public tap or standpipe, tubewell or borehole, protected dug well, protected spring, rainwater collection, or bottled water. 15 Percentage of de jure population whose household has a flush toilet, ventilated improved pit latrine, pit latrine with a slab, or composting toilet and does not share its facility with other households a Restricted to men in a subsample of households selected for the male interview b The total calculated as the simple arithmetic mean of the percentages in the columns for male and females xxii • Map of Zambia Introduction • 1 INTRODUCTION 1 1.1 HISTORY, GEOGRAPHY, AND ECONOMY 1.1.1 History Zambia was originally inhabited by Khoisan peoples, and in the 13th century it was occupied by Bantu-speaking horticulturalists. Following visits by European explorers in the 18th century, Zambia became the British protectorate of Northern Rhodesia toward the end of the 19th century. The country was governed by an administration appointed from London with the advice of the British South Africa Company. In 1924, the British Colonial Office assumed responsibility for administering the territory. 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. This federation was dissolved in 1963. On October 24, 1964, Zambia gained political independence and adopted a multiparty system of government. The country became a one-party state in 1972 before once again adopting the multiparty system of government in 1991, beginning a period of social-economic growth and government decentralisation. 1.1.2 Geography Zambia is a land-locked country in sub-Saharan Africa that borders the Democratic Republic of Congo to the north, Tanzania to the northeast, Malawi and Mozambique to the east, Zimbabwe and Botswana to the south, Namibia to the southwest, and Angola to the west. Zambia covers a land area of 752,612 square kilometres. Administratively, the country is divided into 10 provinces and 74 districts. Of the 10 provinces, two are predominantly urban, namely Lusaka and Copperbelt. The remaining provinces—Central, Eastern, Muchinga, Northern, Luapula, North Western, Western, and Southern—are predominantly rural. The capital city is Lusaka, in the south-central part of the country. Zambia lies between 8 and 18 degrees south latitude and between 20 and 35 degrees east longitude. It has a tropical climate and vegetation with three distinct seasons: the cool dry winter from May to August, a hot dry season during September and October, and a warm wet season from November to April. There are several major rivers in Zambia that are the main sources of water: the Zambezi, Kafue, Luangwa, and Luapula. The country also has major lakes such as Tanganyika, Mweru, Bangweulu, and the man-made Kariba. The northern part of the country has the highest rainfall, with an annual average ranging from 1,100 mm to over 1,400 mm. The southern and eastern parts of the country have the least rainfall, ranging from 600 mm to 1,100 mm annually, which sometimes result in droughts. 1.1.3 Economy Zambia has a mixed economy consisting of a rural agricultural sector and a modern urban sector that, geographically, follows the rail line. Currently, construction sector contributes 14 percent of the gross domestic product (GDP), agriculture contributes 9 percent of the GDP, manufacturing sector and mining each contribute 8 percent of the GDP (CSO, 2014). For many years, the modern sector was dominated by parastatal organisations, while private businesses dominated the construction and agriculture sectors. Historically, the country’s economy has been based on the copper mining industry, accounting for 95 percent of annual export earnings and contributing 45 percent of government revenues during the decade following independence (1965-1975). 2 • Introduction The country’s economy deteriorated in the mid-1970s after a sharp decline in copper prices and a sharp increase in oil prices. The creation of import substitution parastatals with the goal of minimising the country’s dependency on copper exports and diversifying the economy did not achieve the desired results. In the midst of a stagnating economy, Zambia began to implement vigorous structural adjustment programmes; however, these programmes failed to substantially alter the economy and led to increased levels of poverty for the majority of Zambians. In the mid-1990s, an economic recovery programme led to sustained positive economic growth and improved living standards. The performance of the Zambian economy improved further during the implementation of the Poverty Reduction Strategy Plan and the Transitional National Development Plan from 2002 to 2005. Both strategies serve as frameworks for economic and social development. Real GDP growth averaged 5 percent per year, up from an annual average of 2 percent in the preceding years. The subsequent development plan (2006-2010), the Fifth National Development Plan, arose from the need to institute a strategy that would focus on “broad-based wealth and job creation-.through citizenry participation and technological advancement.” The strategy was based on rising economic growth amidst high poverty levels (MoFNP, 2006). Annual average economic growth reached 6 percent during 2006- 2010 as a result of prudent macroeconomic management, market liberalisation, privatisation efforts, expansion of investments in the copper mining industry and related infrastructure, and a steep increase in copper prices (MoFNP, 2013). The Sixth National Development Plan (SNDP), covering the period 2011-2015, was partially implemented between 2011 and 2013 with the aim of achieving sustained economic growth and poverty reduction through infrastructure and human development (MoFNP, 2011). In its pursuit to improve the quality of life for all, the government of the Republic of Zambia is currently implementing the Revised Sixth National Development Plan (R-SNDP) for the period 2013-2016. The R-SNDP identifies primary growth areas, including skill development, agriculture, and infrastructural development, and focuses on enhancing the water and sanitation, education, and health sectors (MoFNP, 2014). According to the Living Conditions Monitoring Survey 2010, 60 percent of Zambians are classified as poor. In the Zambian context, poverty is defined as lack of access to income, employment opportunities, and entitlements, including freely determined consumption of goods and services, shelter, and other basic needs. As of 2010, poverty continued to be more prevalent among rural than urban residents (78 percent and 28 percent, respectively) (CSO, 2011). 1.2 POPULATION Table 1.1 presents selected demographic indicators from the 1980, 1990, 2000, and 2010 Zambia Population and Housing Censuses. The 2010 census reported a population of 13.1 million and a population growth rate of 3 percent per annum. The population increased steadily from 5.7 million in 1980 to 13.1 million in 2010. During the 2000-2010 intercensal period, growth rates varied by province, ranging from 2 percent in Western to 5 percent in Lusaka (CSO, 2012). The population density in Zambia increased from 8 people per square kilometre in 1980 to 17 in 2010. Average density by province in 2010 ranged from a high of 100 people per square kilometre in Lusaka to a low of six people per square kilometre in North Western. In addition to being the most densely populated provinces, Lusaka and Copperbelt are also the most urbanised. Table 1.1 Demographic characteristics Selected demographic indicators, Zambia 1980, 1990, 2000, and 2010 Census year Indicator 1980 1990 2000 2010 Population (millions) 5.7 7.8 9.9 13.1 Density (population/ km2) 7.5 10.4 13.1 17.4 Percent urban 39.9 38.0 35.0 39.5 Total fertility rate 7.2 6.7 6.0 5.9 Completed family size (women age 45-49) 6.6 7.1 6.9 6.0 Infant mortality rate 97 123 110 76 Life expectancy at birth Male 50.4 46.1 48.0 49.2 Female 52.5 47.6 52.0 53.4 Source: Central Statistical Office, 1985a, 1985b, 1995, 2002, 2003, 2012 Introduction • 3 The proportion of the population living in urban areas was 40 percent in 2010, an increase from 35 percent in 2000. The proportion of the urban population varies by province, from 13 percent in Eastern and Western to 85 percent in Lusaka (CSO, 2012). The estimated total fertility rate of 7.2 births per woman in 1980 declined steadily to 5.9 births per woman in 2010. The 2010 census reported a life expectancy at birth of 49 years for males and 53 years for females. Overall life expectancy at birth ranged from 45 years in Luapula to 56 years in Southern (CSO, 2012). 1.3 THE POPULATION POLICY AND NATIONAL POPULATION AND DEVELOPMENT PROGRAMME OF ACTION The results of the 1980 Population and Housing Census emphasised the rapidity with which the population was expanding and the implied adverse effect on development and individual welfare. This led the government to reappraise the role of population in national development efforts. In 1984, the then National Commission for Development Planning (NCDP) was given a mandate to initiate a draft population policy that would aim at achieving a population growth rate consistent with the growth rate of the economy (NCDP, 1991). The National Population Policy was accepted in May 1989. Since then, the country’s population growth rate has remained high and continues to be a serious impediment to sustainable development. The demographic factors and other emerging issues, such as rapid urbanisation, gender concerns, and HIV/AIDS, that began unfolding in the 1990s were major obstacles to ensuring improved quality of life among Zambia’s population. In an effort to address these issues, the process of revising the population policy commenced in December 1996, based on issues adopted by the 1994 Cairo International Conference on Population and Development. The new objectives of the policy took into account concerns regarding HIV and AIDS, poverty, reproductive health, the environment, unemployment, gender issues, and a global perspective on population and development. The National Population Policy was revised in 2007 with the vision of improving quality of life in Zambia through improved population trends and socioeconomic development. The main objectives of the policy are to: • Integrate population variables, reproductive health (including family planning), gender, and HIV/AIDS into development planning and programme implementation processes, especially in education, health, and agriculture. • Reduce the incidence of morbidity and mortality, particularly maternal, infant, and child mortality. • Reduce the high level of fertility, particularly adolescent fertility. • Improve sexual and reproductive health (including family planning) so as to encourage a manageable family size. • Improve and maintain the nation’s population database. • Achieve a more even distribution of the population between rural and urban areas and regulate international migration (MoFNP, 2007). 1.4 HEALTH PRIORITIES AND PROGRAMMES The high disease burden in Zambia is compounded by the high prevalence of HIV, high poverty levels, and the poor macroeconomic situation. The government of the Republic of Zambia is committed to 4 • Introduction improving the quality of life for all Zambians, and this commitment is demonstrated through the government’s efforts to improve health care delivery by reforming the health sector. In 1991, the government launched radical health policy reforms characterised by a move from a strongly centralised health system in which the central structures provided support and national guidance to the peripheral structures. An important component of health policy reform is the restructured primary health care programme. The government is committed to providing efficient and cost-effective quality basic health care services for common illnesses as close to the family as possible through implementation of the Basic Health Care Package (BHCP) at all levels of care. Currently, the following priority health service areas have been identified for inclusion in the BHCP: nutrition; environmental health; control and management of communicable diseases; malaria; tuberculosis (TB); epidemic and disaster prevention, preparedness, and response; school health; and oral health. The elements of the BHCP are selected on the basis of an epidemiological analysis of diseases and conditions that cause the highest burden of morbidity and mortality. Population-based and health facility-based surveys are regularly and consistently conducted to guide policy and planning. The Ministry of Health (MoH) has embarked on the 2011-2015 National Health Strategic Plan (NHSP), aimed at reducing the disease burden and accelerating the attainment of the Millennium Development Goals and other national priorities. The plan represents a major departure from past strategic plans. While it is recognised that all health care interventions are important and should continue to receive the necessary levels of support, prioritisation of interventions is of critical importance as the resources and capabilities available are significantly constrained. The NHSP places emphasis on addressing human resource crises; improving the state of the health care infrastructure; fostering multisectoral responses in key areas such as nutrition, HIV/AIDS, control of epidemics, and health education; and increasing access to basic environmental health facilities such as water and sanitation, electricity, and telecommunication. The plan includes an increased focus on establishing effective, strong, and sustainable partnerships among all key stakeholders involved in health service delivery in Zambia (MoH, 2011). The NHSP groups priority areas into four major categories: human resources, health service delivery interventions, clinical care and diagnostic service priority interventions, and priority integrated support systems. The objectives under these health priority areas are to: • Reduce the under-5 mortality rate from the current 119 deaths per 1,000 live births to 63 deaths per 1,000 live births by 2015. • Reduce the maternal mortality ratio from the current 591 deaths per 100,000 live births to 159 deaths per 100,000 live births by 2015. • Increase the proportion of rural residents living within 5 km of a health facility from 54 percent in 2004 to 70 percent by 2015. • Reduce the population/doctor ratio from the current 17,589 to 10,000 by 2015. • Reduce the population/nurse ratio from the current 1,864 to 700 by 2015. • Reduce the incidence of malaria from 252 cases per 1,000 population in 2008 to 75 by 2015. • Increase the percentage of deliveries assisted by skilled health personnel from 45 percent in 2008 to 65 percent by 2015. • Reduce the prevalence of non-communicable diseases associated with identifiable behaviours. Introduction • 5 1.5 STRATEGIC FRAMEWORK TO COMBAT THE NATIONAL HIV/AIDS EPIDEMIC Zambia, like many sub-Saharan countries, has been adversely affected by the HIV/AIDS pandemic. The first AIDS case in Zambia was diagnosed in 1984. For the last three decades, the government of the Republic of Zambia has been committed to responding to the HIV/AIDS epidemic, in collaboration with national and international partners. Several national plans have been developed to respond to the epidemic: (1) the Emergency Short-Term Plan, developed in 1987 to ensure safe blood and blood product supplies; (2) the MTP1 and MTP2 medium-term plans, covering the periods 1988-1992 and 1994-1998, respectively; (3) and the National HIV/AIDS Intervention Strategic Plan and National Monitoring and Evaluation Plan, covering the period 2002-2005. In December 2002, the Parliament established the National HIV/AIDS/STI/TB Council (NAC) to coordinate and support development, monitoring, and evaluation of the multisectoral national response to HIV/AIDS, sexually transmitted infections (STIs), and TB. In 2005, the National HIV/AIDS Policy was established to provide the directive and mandate for the national response. In 2006, the government created the National HIV/AIDS/STI/TB Monitoring and Evaluation Plan for 2006-2010. The plan was developed to prevent, halt, and begin to reverse the spread of HIV by 2010. The plan defines six themes describing priority action areas: (1) intensifying prevention; (2) expanding treatment, care, and support; (3) mitigating the socioeconomic impact of HIV/AIDS; (4) strengthening decentralised responses and mainstreaming HIV/AIDS; (5) improving monitoring of responses; and (6) integrating advocacy and coordination of multisectoral responses. To facilitate effective coordination, the NAC developed the National HIV/AIDS Monitoring and Evaluation System, allowing the country to track its progress toward the plan’s goals and objectives. In response to the high morbidity and mortality associated with HIV infection, the Ministry of Health began to distribute free antiretroviral drugs in two major public health care facilities in 2005 (MoH/NAC, 2008). Distribution of highly effective antiretroviral therapy (ART) has since been scaled up to include almost all of the districts in Zambia. A laboratory infrastructure for basic assessment and monitoring of HIV-positive patients has been set up in almost all provincial hospitals. The MoH has expanded quality services for prevention of mother-to-child transmission of HIV, voluntary HIV counselling and testing, ART, and other treatment and care services. The Ministry of Health also encourages joint implementation of TB-HIV programme activities, given the cross-cutting nature of the two conditions, including early and improved detection of TB, strengthening of TB diagnostic capacity, and surveillance for multidrug-resistant TB. The 2011-2015 National HIV and AIDS Strategic Framework, launched in 2010, emphasises a multisectoral and decentralised response to the AIDS epidemic. Four national priorities for tackling the epidemic have been identified. The first priority is to accelerate and intensify prevention in order to reduce annual rates of new HIV infections. The second is to accelerate universal access to comprehensive treatment, care, and support for people living with HIV/AIDS, as well as their caregivers and families. Comprehensive treatment and care for TB, STIs, and other opportunistic infections is emphasised. The third priority is to mitigate the socioeconomic impact of HIV/AIDS, especially among the most vulnerable groups (such as orphans and vulnerable children, people living with HIV/AIDS, and their caregivers and families). The final priority is to strength the capacity for a well-coordinated and sustainably managed multisectoral response to HIV/AIDS (MoH/NAC, 2010). 1.6 OBJECTIVES AND ORGANISATION OF THE SURVEY 1.6.1 Objectives The Zambia Demographic and Health Survey (ZDHS) is a nationally representative sample survey of women and men of reproductive age. The main objective is to provide information on levels and trends in fertility, childhood mortality, use of family planning methods, maternal and child health indicators 6 • Introduction including HIV/AIDS. This information is necessary for programme managers, policymakers, and implementers to monitor and evaluate the impact of existing programmes and to design new initiatives for health policies in Zambia. The primary objectives of the 2013-14 ZDHS are: • To collect up-to-date information on fertility, infant and child mortality, and family planning. • To collect information on health-related matters such as breastfeeding, antenatal care, children’s immunisations, and childhood diseases. • To assess knowledge of contraceptive practices among women. • To assess the nutritional status of mothers and children. • To improve understanding of variations in HIV seroprevalence levels according to social and economic characteristics and behavioural risk factors. • To estimate levels of HIV incidence in the general population of adults.1 • To estimate unmet need for antiretroviral treatment. In the case of HIV/AIDS, the testing component of the 2013-14 ZDHS was undertaken to provide information to address the monitoring and evaluation needs of government and nongovernmental programmes dealing with HIV/AIDS. It also provides programme managers and policymakers with the information they need to effectively plan and implement future interventions. The overall objective was to collect high-quality and representative data on knowledge, attitudes, and behaviours regarding HIV/AIDS and other STIs and on the prevalence and incidence of HIV among women and men. 1.6.2 Organisation The 2013-14 ZDHS was implemented by the Central Statistical Office in partnership with the Ministry of Health, the University of Zambia Teaching Hospital (UTH) Virology Laboratory, the Tropical Diseases Research Centre (TDRC), and the Department of Population Studies at the University of Zambia (UNZA) under the overall guidance of the National Steering Committee. A technical committee provided technical guidance to the survey. The TDRC and the UTH Virology Laboratory provided technical support in the implementation of HIV testing. The government of Zambia, through the Ministry of Health and the Ministry of Finance, provided funding for the survey. Cooperating partners, namely the U.S. Centers for Disease Control and Prevention (CDC), the United Nations Children’s Fund (UNICEF), and the United Nations Population Fund (UNFPA), provided additional funds. The Demographic and Health Surveys Program at ICF International, which is funded by the United States Agency for International Development (USAID), provided technical assistance in the areas of survey design, sample design, questionnaire design, interviewer training, fieldwork logistics, blood specimen collection, laboratory testing, and data processing and analysis. The CDC provided technical assistance with HIV protocol development, as well as technical support to the TDRC and the UTH Virology Laboratory during laboratory testing. While significantly expanded in size and content, the 2013-14 ZDHS is a follow-up to the 1992, 1996, 2001-02, and 2007 ZDHS surveys and provides updated estimates of basic demographic and health indicators covered in the earlier surveys. The 2013-14 survey is the third ZDHS to measure HIV prevalence in Zambia and the first to measure HIV incidence. It is also the third survey that includes information on violence against women. 1 The HIV incidence results are published in a separate addendum to this report. Introduction • 7 1.7 SAMPLE DESIGN The sample for the 2013-14 ZDHS was designed to provide estimates at the national and provincial levels, as well as for rural and urban areas within the provinces. This is the first time the ZDHS has been designed to provide estimates at such disaggregated levels for many of the survey indicators. The updated list of enumeration areas (EAs) for the 2010 Population and Housing Census provided the sampling frame for the survey. The frame comprises 25,631 EAs and 2,815,897 households. An EA is a convenient geographical area with an average size of 130 households or 600 people. For each EA, information is available on its location, type of residence (rural or urban), number of households, and total population. Each EA has a cartographical map with delimited boundaries and main landmarks of the area. A 2013-14 ZDHS cluster is essentially representative of an EA. A representative sample of 18,052 households was drawn for the 2013-14 ZDHS. The survey used a two-stage stratified cluster sample design, with EAs (or clusters) selected during the first stage and households selected during the second stage. In the first stage, 722 EAs (305 in urban areas and 417 in rural areas) were selected with probability proportional to size. Zambia is now administratively divided into 10 provinces (Central, Copperbelt, Eastern, Luapula, Lusaka, Muchinga,2 Northern, North Western, Southern, and Western). Stratification was achieved by separating each province into urban and rural areas. Therefore, the 10 provinces were stratified into 20 sampling strata. In the second stage, a complete list of households served as the sampling frame in the selection of households for enumeration. An average of 25 households was selected in each EA. It was during the second stage of selection that a representative sample of 18,052 households was selected. Prior to selection, EAs were stratified by province and then into urban and rural areas. A complete listing of households in each selected cluster, along with a mapping exercise, was conducted from November 2012 to January 2013 by listers and mappers from the CSO Geographic Information Branch. All private households were listed. The listing excluded people living in institutional dwelling units (such as army barracks, hospitals, police camps, and boarding schools). The listing teams recorded geographic coordinates for each sampled cluster (centroid) using Global Positioning System (GPS) receivers. All women age 15-49 and men age 15-59 who were either permanent residents of the households or visitors present in the households on the night before the survey were eligible to be interviewed. In addition, a subsample of one eligible woman in each household was randomly selected to be asked additional questions on domestic violence. All women and men who were eligible for interviews were asked if they would voluntarily give a finger prick blood sample to allow HIV prevalence estimation from dried blood spot (DBSs). If they consented to DBS collection, they were also offered home-based counselling and testing for HIV with rapid HIV tests. Venous blood was also collected for CD4 counts. Venous blood was processed in the field laboratory, and respondents were given their CD4 count results. Both DBS and venous blood samples were transferred to either the UTH Virology Laboratory or the TDRC laboratory for HIV testing. As a means of assessing nutritional status, height and weight measurements were taken for all children age 0-59 months and women age 15-49 who were usual residents of or visitors in the household. 1.8 QUESTIONNAIRES Three questionnaires were used in the 2013-14 ZDHS: the Household Questionnaire, the Woman’s Questionnaire, and the Man’s Questionnaire. The three instruments were based on the questionnaires developed by the Demographic and Health Surveys Program and adapted to Zambia’s specific data needs. The questionnaires were translated into seven major languages: Bemba, Kaonde, Lozi, 2 Muchinga is a new province in Zambia; some of the province’s districts were part of Northern and Eastern in the 2007 ZDHS. 8 • Introduction Lunda, Luvale, Nyanja, and Tonga. Questionnaires and field procedures were pretested prior to implementation of the main survey. The Household Questionnaire was used to collect data such as: • Age, sex, marital status, and education of all usual members and visitors • Current school attendance and survivorship of parents among children under age 18 • Characteristics of the structural dwelling/housing unit • Sanitation facilities and source of water • Ownership of durable goods, land, and livestock • Ownership and use of mosquito nets The Household Questionnaire was also used to record biomarker data, including height and weight data for children and women and HIV and CD4 testing information for women and men. Data on age and sex of household members were used to identify the women and men eligible for individual interviews. The Woman’s Questionnaire was used to collect information from all women age 15-49. Women were asked questions on the following main topics: • Background characteristics (age, religion, education, literacy, media exposure, etc.) • Reproductive history • Knowledge, use, and source of family planning methods • Fertility preferences • Maternal health (antenatal, delivery, and postnatal care) • Fistula prevalence • Breastfeeding and infant feeding practices • Child immunisation and childhood illnesses • Treatment of malaria • Child mortality • Marriage and sexual activity • Women’s work and husbands’ background characteristics • Awareness of AIDS and other STIs • Other health issues (e.g., tuberculosis, injection safety, and smoking) • Maternal mortality • Domestic violence The Man’s Questionnaire was administered to all men age 15-59. It collected much of the same information as the Woman’s Questionnaire but it did not contain a detailed reproductive history or questions on maternal and child health or nutrition. 1.9 HIV AND CD4 CELL COUNT TESTING In the 2013-14 ZDHS, dried blood spot (DBS) samples were collected for voluntary HIV testing for prevalence from all consenting, eligible women and men in all selected survey households. In addition, venous blood specimens were collected from consenting men and women who tested HIV-positive on a rapid diagnostic test (RDT) in the household. The protocol for blood specimen collection, CD4 measurement, and HIV testing was reviewed and approved by the TDRC Ethical Review Committee, the Institutional Review Board of ICF International, and the CDC. 1.9.1 CD4 Measurement and Blood Collection for HIV Incidence Testing A nurse/nurse counsellor and a laboratory technician were part of each of the 24 ZDHS field teams to provide testing and counselling for HIV in the household using rapid tests (among consenting Introduction • 9 men and women) and CD4 cell count measurement. The nurse/nurse counsellors and laboratory technicians were recruited through the Ministry of Health and had experience in venous blood collection and testing. According to the ZDHS protocol, rapid HIV testing was conducted in the field by the nurse counsellor, following the national HIV testing algorithm. To ascertain HIV infection status, a blood sample obtained from a fingertip using a retractable, safety lancet from consenting respondents was used for concurrent HIV testing with Determine™ HIV-1/2 (Alere Healthcare) and Uni-Gold™ HIV-1/2 (Trinity Biotechnology). Field rapid HIV testing was performed only among respondents who had also consented to provide a blood sample for HIV prevalence testing in a central laboratory, and who had agreed to the rapid HIV test in a separate consent statement. If a respondent consented to HIV testing and either of the rapid HIV tests was HIV reactive (positive), permission to conduct a venous blood draw for CD4 cell count measurement was requested. The blood specimens were given a bar code label unique to the respondent; this label was identical to the one attached to the individual’s questionnaire and to the filter paper card with the dried blood spots used for laboratory HIV prevalence testing. CD4 cell count testing was performed in a field laboratory using the PIMA Point of Care CD4 machine (Alere Healthcare, Waltham, Massachusetts, USA). HIV positive respondents were referred to the nearest health facility to present their CD4 cell count and for further assessment (if they were not already receiving treatment). Plasma was separated from the left-over venous whole blood samples that were collected from all HIV-positive blood samples, stored in cryo vials, and labelled with appropriate bar codes. The plasma samples were then frozen in liquid nitrogen tanks and transported to the CSO for logging in and, subsequently, the UTH Virology and the Tropical Diseases Research Centre (TDRC) laboratories for HIV incidence testing. 1.9.2 HIV Prevalence Testing The protocol for blood specimen collection and analysis was based on the anonymous linked protocol developed by ICF International. This protocol allows for the merging of HIV test results with sociodemographic data collected in the individual questionnaires, provided that information that could potentially identify an individual is destroyed before the linking takes place. Eligible women and men who consented to HIV testing were asked to voluntarily provide five drops of blood from a finger prick for anonymous testing. Interviewers explained the procedure, the confidentiality of the data, and the fact that the DBS- based HIV test results for prevalence would not be made available to the respondent. They also explained to respondents that they had the option of having their DBS sample stored for use in additional future testing. If a respondent consented to the testing, blood obtained from a finger prick was used to prepare five blood spots on a filter paper card labelled with a bar code unique to the respondent. If the respondent did not consent to additional testing using his or her sample, the words “no further testing” were written on the filter paper card. Each household, whether individuals consented to HIV testing or not, was given an information brochure on HIV/AIDS and a list of nearby sites providing voluntary counselling and testing services. Each DBS sample was given a bar code label, and a duplicate label was attached to the Woman’s or Man’s Questionnaire. A third copy of the bar code was affixed to the blood sample transmittal form to track the blood samples from the field to the laboratory. Blood spots prepared on pre-marked circles on filter paper cards were dried overnight, and the resulting DBS was packaged for storage the following morning. Samples were periodically collected in the field along with the completed questionnaires and transported to CSO headquarters in Lusaka to be logged in, checked, and then transported to the UTH Virology Laboratory in Lusaka (for testing of samples collected in Central, Eastern, Lusaka, Central, Southern, and Western provinces) or the Immunology Laboratory at the TDRC in Ndola (for testing of samples collected in Copperbelt, Luapula, Muchinga, Northern, and North Western provinces). 10 • Introduction The processing of DBS samples for HIV testing at the TDRC and UTH Virology laboratories was handled by 10 laboratory personnel. Each DBS sample was logged into the CSPro HIV Test Tracking System (CHTTS) database, assigned a unique laboratory number, and stored at -20˚C. HIV prevalence testing on all samples was conducted between April and October 2014. Testing followed the completion of data processing, ensuring that all unique identifiers other than the bar code number had been removed from the questionnaire file. Before commencement of HIV prevalence testing, laboratory staff were trained (by an HIV prevalence testing expert from ICF International) on DBS elution, enzyme-linked immunosorbent assay (ELISA) protocols, and Western blot HIV testing. During the HIV testing period, selected ELISA test results from the TDRC and UTH Virology laboratories were reviewed by the HIV prevalence testing expert. Fourth-generation ELISA HIV test kits were used for screening and confirmatory testing of the DBS samples. All samples were tested on the first assay, Vironostika® HIV Antigen/Antibody Combination Assay (Biomerieux). A negative result on the first test was considered negative and no further testing was done on the sample, unless it was selected for internal quality control. All samples with positive results on the first test were subjected to a second ELISA, Enzygnost® HIV Integral II Assay (Dade Behring), for confirmatory testing. Positive samples on the second test were considered positive.3 Ten percent of samples that were negative on Vironostika were rested on the Enzygnost. If the results of the first and second tests were discordant, the sample was retested on both the Vironostika and Enzygnost ELISA tests. If the results of both the repeated first and second tests were negative, the sample was rendered negative. If both were positive, the sample was rendered positive. If there was still a discrepancy in the results after the repeated tests, a third test, the Western Blot 2.2 (Abbott Labs), was used to resolve the discordance. The final result was rendered positive if the Western Blot 2.2 confirmed the result as positive, and it was rendered negative if the Western blot was negative. If the result of the Western blot was indeterminate, the final result of the sample was indeterminate. To ensure the quality and validity of the test results, positive and negative serum controls supplied by the manufacturer with the test kits were included on each plate of samples tested. In addition, known HIV-negative, low-positive, and high-positive DBS controls obtained from the CDC were included on each plate of samples tested. The HIV test results for the 2013-14 ZDHS were entered into a CHTTS database with the bar code as the unique identifier. Data from the HIV testing and linked demographic and health data are included in this report. 1.9.3 HIV Incidence Testing HIV Incidence Testing Although the “gold standard method” for HIV incidence testing is follow-up of a cohort of HIV- negative persons with periodic repeated testing, recent infection testing algorithms based on measuring a biomarker indicating recent HIV infection among individuals participating in a cross-sectional survey offer another way to estimate incidence. To distinguish recent from long-term HIV infections, plasma specimens were tested using the Sedia LAg-Avidity EIA (LAg). Respondents from whom plasma specimens were collected during the 2013-14 ZDHS were offered counselling and testing for HIV in the household using rapid tests based on the national HIV testing algorithm. The specimens were further tested at the central lab using Vironostika HIV 3 Since the time that the 2013-14 Zambia DHS HIV testing protocol was approved by MoH, concerns have been raised that ELISA tests may overestimate HIV prevalence and that a more specific third test be used to confirm all samples rendered positive by ELISA tests (CDC, 2014). To the extent that this concern is valid it would also apply to the 2001-02 and 2007 Zambia DHS surveys that included HIV testing based on the same protocol as the 2013-14 ZDHS. Introduction • 11 Antigen/Antibody Combination Assay to confirm the presence of HIV. Only those plasma specimens that were confirmed as HIV-1 positive were tested using the Sedia LAg-Avidity EIA. Classification of HIV-1 positive plasma specimens as recent or long-term HIV infection was dependent on the normalised optical density (ODn) from screening and confirmatory LAg testing. LAg- screened specimens with ODn greater than 2.0 were classified as long-term infection. LAg-screened specimens with ODn less than or equal to 2.0 were confirmed in triplicate. LAg-confirmed specimens with median ODn of less than or equal to 1.5 were classified as preliminary recent infection; those with median ODn greater than 1.5 were classified as long-term infection. Specimens whose screening and confirmatory LAg results were significantly discordant were retested in triplicate. The HIV serostatus of specimens with final ODn of less than or equal to 0.4 was confirmed by retesting the sample using Alere Determine™ HIV-1/2 because testing of HIV-negative specimens with the LAg test will result in misclassification of these specimens as recent HIV infections. Any HIV-negatives were moved to the HIV negative category for incidence calculation. Elite controllers and those on ART can potentially misclassify as recent HIV infection; for this reason, all confirmed HIV-1 positive specimens preliminarily classified as recent by LAg testing were further tested for HIV-1 viral load (COBAS AmpliPrep/COBASR TaqMan HIV-1 Test, Version 2.0). Those identified to have a viral load less than 1000 copies/mL may represent elite controllers or individuals on ART and were reclassified as long-term infection. Specimens with LAg ODn less than or equal to 1.5 and a viral load greater than or equal to 1000 copies/ml were finally classified as recent HIV infection. Annualised HIV incidence estimates (overall and by province) were computed using a modified Welte formula. To ensure the credibility of LAg testing, technicians at the TDRC and UTH Virology laboratories were trained for five days by an HIV incidence testing expert from the CDC. During the training, laboratory staff were assessed with respect to their competency and proficiency in LAg testing and data management. Additionally, all HIV incidence test results from the TDRC and UTH Virology laboratories were reviewed by incidence testing experts at the CDC. The HIV incidence results are published in a separate addendum to this report. 1.10 PRETEST ACTIVITIES The 2013-14 ZDHS was significantly expanded in content and included collection of samples for HIV prevalence testing as well as samples for HIV incidence testing and CD4 measurement. Venous blood samples for HIV incidence testing and CD4 measurement were collected only from consenting respondents who tested positive for HIV on an RDT performed at the household. A pretest was conducted to assess the survey instruments and procedures to be used in the main survey. The training and fieldwork for the pretest took place from November 4 to December 1, 2012. Fifteen interviewers (nine women and six men) were trained to administer the questionnaires, take anthropometric measurements, and collect blood samples for HIV testing. In addition, three laboratory technicians and three HIV nurse counsellors were trained to collect venous blood samples for CD4 measurement and HIV incidence testing. Representatives from the CDC and from the TDRC and UTH Virology laboratories assisted in training interviewers to perform finger pricks to collect samples for HIV testing. Furthermore, nurse counsellors were trained on proper handling and storage of dried blood spots and plasma prepared from venous blood. Resource personnel included professionals from the CDC, UNZA, CSO, MoH, Ministry of Gender, ICF International, National AIDS Council, TDRC, and Young Women’s Christian Association (YWCA). The pretest fieldwork was conducted in two urban and three rural clusters covering 104 households. Debriefing sessions were held with the pretest field staff, and modifications to the questionnaires were made based on lessons drawn from the exercise. 12 • Introduction 1.11 TRAINING OF FIELD STAFF The CSO and MoH recruited and trained 306 participants. The MoH provided nurses, HIV counsellors, and laboratory technicians, while the CSO provided non-medical interviewers and data processing staff. Training on the survey methodology was conducted over a five-week period in May and June 2013 by resource personnel from the CDC, CSO, MoH, TDRC, UTH Virology, and UNZA Population Studies. Prior to the training of field staff, a two-week training workshop was conducted for resource personnel (training of trainers). Field staff were trained to serve as supervisors, field editors, and interviewers. The training course consisted of instruction on interviewing techniques and field procedures, a detailed review of questionnaire items, instruction and practice in weighing and measuring children, mock interviews between participants in the classroom, and practice interviews with real respondents in areas outside the 2013-14 ZDHS sample clusters. Field practice in rapid HIV testing, CD4 measurement, and DBS specimen preparation for HIV testing was also conducted. During this period, field editors and team supervisors were provided with additional training in methods of field editing, data quality control procedures, and fieldwork coordination. Twenty-four supervisors, 24 editors, 72 female interviewers, 48 HIV counsellors, 24 laboratory technicians, and 48 male interviewers made up the 24 data collection teams (each comprising 10 people) for the 2013-14 ZDHS. 1.12 FIELDWORK The survey was undertaken by 24 field teams. The 24 interviewing teams carrying out data collection each consisted of one supervisor (team leader), one field editor, three female interviewers, two male interviewers, two nurses/nurse counsellors, one laboratory technician, and one driver. Four senior staff members from the CSO, assisted by seven other staff members, coordinated supervision of fieldwork activities. Three staff members from UNZA assisted in field supervision and monitoring. In addition, two ICF International staff members conducted field supervision activities. To monitor implementation of the 2013-14 ZDHS biomarker components, laboratory staff from the TDRC and UTH Virology periodically supervised and monitored field laboratory technicians with respect to their compliance with survey biomarker procedures. Data collection took place over an eight-month period, from August 2013 to April 2014. 1.13 DATA PROCESSING All questionnaires for the 2013-14 ZDHS were returned to the CSO headquarters in Lusaka for data processing, which consisted of office editing, coding of open-ended questions, data entry, and editing of computer-identified errors. Data processing staff included two data processing supervisors, 24 data entry clerks, five office editors, four secondary editors, one questionnaire administrator, and one biomarker administrator. The processing of the data began in September 2013, one month after data collection commenced, and continued concurrently with the fieldwork. This offered an advantage because data were consistently checked and feedback was given to field teams, thereby improving data quality. Before being sent to the data processing centre in Lusaka, completed questionnaires were edited in the field by the field editors and checked by the supervisors. At the processing centre, data were edited and coded by office editors. Data were then entered using the CSPro computer package. All data were entered twice for 100 percent verification. This double entry of data enabled easy comparisons and identification of errors and inconsistencies. Inconsistencies were resolved by tallying the data with the paper questionnaire entries. Further inconsistencies that were identified were resolved through secondary editing of the data. The data files (excluding HIV testing data) were finalised in June 2014 after data cleaning. Introduction • 13 1.14 RESPONSE RATES The household and individual response rates for the 2013-14 ZDHS are shown in Table 1.2. A total of 18,052 households were selected from 722 clusters, of which 16,258 were occupied at the time of the fieldwork. Of the occupied households, 15,920 were successfully interviewed, yielding a household response rate of 98 percent. In the interviewed households, a total of 17,064 women age 15-49 were identified as eligible for individual interviews, and 96 percent of these women were successfully interviewed. A total of 16,209 men age 15-59 were identified as eligible for interviews, and 91 percent were successfully interviewed. Individual response rates were slightly lower in urban areas than in rural areas. Table 1.2 Results of the household and individual interviews Number of households, number of interviews, and response rates, according to residence (unweighted), Zambia 2013-14 Residence Total Result Urban Rural Household interviews Households selected 7,637 10,415 18,052 Households occupied 7,063 9,195 16,258 Households interviewed 6,957 8,963 15,920 Household response rate1 98.5 97.5 97.9 Interviews with women age 15-49 Number of eligible women 8,212 8,852 17,064 Number of eligible women interviewed 7,871 8,540 16,411 Eligible women response rate2 95.8 96.5 96.2 Interviews with men age 15-59 Number of eligible men 7,660 8,549 16,209 Number of eligible men interviewed 6,828 7,945 14,773 Eligible men response rate2 89.1 92.9 91.1 1 Households interviewed/households occupied 2 Respondents interviewed/eligible respondents Housing Characteristics and Household Population • 15 HOUSING CHARACTERISTICS AND HOUSEHOLD POPULATION 2 his chapter provides an overview of demographic and socioeconomic characteristics of the household population, including information on housing facilities and characteristics, household assets, wealth status, and education; these data serve as a basis for understanding the socioeconomic status of households. The chapter also presents information on birth registration, children’s living arrangements, and children’s educational attainment, helping to provide an understanding of the general social environment in which children live. In the 2013-14 ZDHS, a household is defined as a person or a group of related and unrelated persons who usually live together in the same dwelling unit(s) or in connected premises, who acknowledge one adult member as the head of the household, and who have common cooking and eating arrangements. Information was collected from all usual residents of a selected household (de jure population) as well as persons who had stayed in the selected household the night before the interview (de facto population). The difference between these two populations is very small, and all tables in this report refer to the de facto population unless otherwise specified, to maintain comparability with other DHS reports. 2.1 HOUSEHOLD CHARACTERISTICS Access to basic utilities, sources of drinking water and water treatment practices, access to sanitation facilities, housing structure and crowdedness of dwelling spaces, and type of fuel used for cooking are physical characteristics of a household that are used to assess the general well-being and socioeconomic status of household members. Millennium Development Goal (MDG) 7, which focuses on environmental sustainability, is measured by the percentage of the population using solid fuels, the percentage with sustainable access to an improved water source, and the percentage with access to improved sanitation. This section provides information from the 2013-14 ZDHS on household drinking water and sanitation facilities, hand-washing practices, housing characteristics, and possession of basic amenities and utilities. 2.1.1 Water and Sanitation The basic determinants of better health, such as access to water, and sanitation, are still in a critical state in Zambia. Limited access to water and sanitation facilities accompanied by poor hygiene is associated with skin diseases, acute respiratory infections (ARIs), and diarrhoeal diseases, the leading preventable diseases. ARI and diarrhoeal diseases are among the leading causes of child deaths in Zambia (MoH, 2012a). T Key Findings • In Zambia, 65 percent of households have access to an improved source of drinking water. • Twenty-five percent of households have an improved toilet facility that is not shared with other households. • Twenty-eight percent of households have electricity. • Fourteen percent of households are exposed daily to secondhand smoke. • Half of the Zambian population is under age 15. 16 • Housing Characteristics and Household Population Table 2.1 presents the percent distribution of households and the de jure population, according to urban or rural setting, by source of drinking water, time taken to obtain drinking water, and water treatment practices adopted by households. Table 2.1 Household drinking water Percent distribution of households and de jure population by source of drinking water, time to obtain drinking water, and treatment of drinking water, according to residence, Zambia 2013-14 Households Population Characteristic Urban Rural Total Urban Rural Total Source of drinking water Improved source 89.5 46.6 64.5 89.2 46.9 63.4 Piped into dwelling/yard/plot 40.8 1.9 18.1 41.4 1.6 17.2 Public tap/standpipe 33.5 2.1 15.2 31.9 2.0 13.7 Tube well or borehole 7.4 32.5 22.1 8.0 32.9 23.2 Protected dug well 6.7 9.4 8.3 6.9 9.6 8.5 Protected spring 0.3 0.6 0.5 0.3 0.7 0.5 Rainwater 0.0 0.1 0.0 0.0 0.1 0.0 Bottled water 0.8 0.0 0.3 0.7 0.0 0.3 Non-improved source 8.5 53.2 34.5 8.7 53.0 35.7 Unprotected dug well 6.8 30.3 20.5 6.9 30.5 21.3 Unprotected spring 0.8 5.4 3.5 0.9 5.4 3.6 Tanker truck/cart with small tank 0.0 0.2 0.1 0.1 0.2 0.1 Surface water 0.8 17.3 10.4 0.9 16.9 10.6 Other 1.8 0.0 0.7 2.0 0.0 0.8 Total 100.0 100.0 100.0 100.0 100.0 100.0 Time to obtain drinking water (round trip) Water on premises 46.8 9.5 25.1 47.6 9.8 24.6 Less than 30 minutes 40.1 59.7 51.5 39.1 59.3 51.4 30 minutes or longer 12.5 28.2 21.7 12.7 28.6 22.3 Don’t know 0.6 2.3 1.6 0.6 2.1 1.6 Total 100.0 100.0 100.0 100.0 100.0 100.0 Method for storing water Does not store water 0.4 0.3 0.3 0.3 0.2 0.3 Closed container/jerry can 89.8 86.5 87.9 89.9 86.8 88.0 Open container/bucket 9.8 13.2 11.7 9.8 12.9 11.7 Total 100.0 100.0 100.0 100.0 100.0 100.0 Water treatment prior to drinking1 Boiled 25.3 7.6 15.0 25.5 7.6 14.6 Bleach/chlorine/chlorin added 33.2 16.7 23.6 35.4 17.3 24.4 Strained through cloth 0.1 0.2 0.2 0.2 0.2 0.2 Ceramic, sand or other filter 0.2 0.1 0.1 0.2 0.1 0.1 Other 1.2 0.8 1.0 1.2 0.8 0.9 No treatment 50.0 77.7 66.2 48.5 77.2 65.9 Percentage using an appropriate treatment method2 49.2 21.6 33.1 50.8 22.2 33.4 Number 6,640 9,280 15,920 31,977 49,698 81,675 Note: Totals may not sum to 100 percent because households with missing information have been deleted. 1 Respondents may report multiple treatment methods, so the sum of treatment may exceed 100 percent. 2 Appropriate water treatment methods include boiling, bleaching, filtering, and solar disinfecting. Most households in Zambia (65 percent) obtain drinking water from an improved source. Households in urban areas have greater access to an improved source of drinking water than households in rural areas (90 percent versus 47 percent). There has been a notable increase in the percentage of households with access to an improved source of drinking water from 24 percent in 2007 to 65 percent in 2013-14. The most common improved source of drinking water in urban areas is piped water. Water piped into a dwelling, yard, or plot was a source for 41 percent of households, while 34 percent accessed water from a public tap/standpipe. In contrast, a tube well or borehole is the most common improved source of drinking water in rural areas (33 percent). The most common non-improved source of drinking water is an unprotected dug well (21 percent). It is much more common in rural areas (30 percent) than in urban areas (7 percent). Fifty-two percent of households spend less than 30 minutes to obtain drinking water, while 22 percent of households spend 30 minutes or longer. Accessing drinking water takes longer in rural areas (28 percent) than urban areas (13 percent). Housing Characteristics and Household Population • 17 Households that do not treat drinking water account for 66 percent. Rural households are more likely not to treat water before drinking (78 percent) compared with urban areas (50 percent). Adding bleach/chlorine/chlorin is the most common treatment method (24 percent), followed by boiling water prior to drinking (15 percent). Ensuring adequate sanitation facilities is another MDG indicator that Zambia monitors like other countries. A household is classified as having an improved toilet if the toilet is used only by members of one household (i.e., it is not shared) and if the facility used by the household separates the waste from human contact (WHO/UNICEF Joint Monitoring Programme for Water Supply and Sanitation, 2012). Table 2.2 presents information on household sanitation facilities by type of toilet/latrine. Among households interviewed, one in four (25 percent) has access to an improved (not shared) facility; one in five (20 percent) has access to a shared toilet facility; while 55 percent have access to a non-improved facility. Sixteen percent of households still use a bush or open field for defecation, but this is an improvement since 2007, when one in four households had no toilet facility. Rural households are more likely than urban households not to have a toilet facility (27 percent versus 2 percent). Table 2.2 Household sanitation facilities Percent distribution of households and de jure population by type of toilet/latrine facilities, according to residence, Zambia 2013-14 Households Population Type of toilet/latrine facility Urban Rural Total Urban Rural Total Improved, not shared facility Flush/pour flush to piped sewer system 17.3 0.4 7.5 18.8 0.3 7.6 Flush/pour flush to septic tank 6.8 0.6 3.2 7.7 0.6 3.4 Flush/pour flush to pit latrine 0.6 0.1 0.3 0.7 0.1 0.3 Ventilated improved pit (VIP) latrine 3.1 9.2 6.7 3.6 10.1 7.5 Pit latrine with slab 7.2 8.1 7.7 8.3 8.6 8.5 Total 35.0 18.5 25.4 39.2 19.7 27.3 Shared facility1 Flush/pour flush to piped sewer system 6.3 0.2 2.7 6.0 0.1 2.4 Flush/pour flush to septic tank 2.6 0.1 1.2 2.4 0.1 1.0 Flush/pour flush to pit latrine 1.1 0.1 0.5 0.9 0.1 0.4 Ventilated improved pit (VIP) latrine 7.6 3.6 5.2 6.7 3.3 4.6 Pit latrine with slab 20.4 3.3 10.4 17.8 2.9 8.7 Total 38.0 7.2 20.1 33.9 6.5 17.2 Non-improved facility Flush/pour flush not to sewer/septic tank/pit latrine 0.2 0.0 0.1 0.3 0.0 0.1 Pit latrine without slab/open pit 25.2 47.1 37.9 25.1 47.8 38.9 Hanging toilet/hanging latrine 0.0 0.2 0.1 0.0 0.2 0.1 No facility/bush/field 1.5 26.8 16.2 1.4 25.7 16.2 Total 27.0 74.2 54.5 26.9 73.9 55.5 Total 100.0 100.0 100.0 100.0 100.0 100.0 Number 6,640 9,280 15,920 31,977 49,698 81,675 Note: Totals may not sum up 100 percent because households with missing information have been deleted. 1 Facilities that would be considered improved if they were not shared by two or more households. 2.1.2 Housing Characteristics Housing characteristics and household assets can be used as a measure of the socioeconomic status of household members. Cooking practices and cooking fuels also affect the health of family members and the environment. For example, use of biomass fuels exposes household members to indoor pollution, which has a direct bearing on their health and surroundings. 18 • Housing Characteristics and Household Population Table 2.3 presents information on the availability of electricity, type of flooring material, number of rooms for sleeping, type of fuel used for cooking, and place where cooking is done. The table shows that 28 percent of households in Zambia have access to electricity, an improvement since 2007, when only 19 percent of households had access to electricity. Access to electricity has increased in urban areas in the last six years, with 62 percent of urban households having electricity in 2013-14 compared with 48 percent in 2007. Access to electricity in rural areas has not improved much, however, in the last six years. Earth and sand are the most common flooring materials used in Zambian households (51 percent), and these materials are predominantly used in rural areas (78 percent). The use of cement has increased in the past six years from 35 percent to 41 percent, with increases seen in rural areas and a slight decline in urban areas. The number of rooms used for sleeping indicates the extent of crowding in households. Overcrowding increases the risk of contracting infectious diseases such as acute respiratory infections and skin diseases, which particularly affect children and the elderly. The proportion of households using one room for sleeping has decreased from 47 percent to 34 percent in the last six years. The presence and extent of indoor pollution depend on places used for cooking and types of fuel used. According to the 2013-14 ZDHS, 26 percent of households cook inside the house, while 35 percent cook in a separate building and 38 percent cook outdoors. The percentage of households that cook within the dwelling unit is higher in urban areas (50 percent) than in rural areas (10 percent). Fifty-seven percent of households in rural areas cook in a separate building. Almost all households use wood, charcoal, or electricity for cooking. Use of wood is more common in rural areas (82 percent) than in urban areas (6 percent). On the other hand, use of charcoal is much more common in urban (67 percent) than in rural areas (16 percent). There has been a sharp increase in the use of charcoal for cooking from 25 percent in 2007 to 37 percent in 2013-14. Electricity is used for cooking in only 27 percent of urban households despite its recent growth in availability to 62 percent of these households. A major concern for the government of Zambia is the effect of secondhand smoke on the health of children and neonates. The purpose of the Tobacco Act CAP 237 in Zambia is to control tobacco and tobacco-related product use and distribution (GRZ, 1994). Table 2.3 Household characteristics Percent distribution of households by housing characteristics, percentage using solid fuel for cooking, and percent distribution by frequency of smoking in the home, according to residence, Zambia 2013-14 Residence Total Housing characteristic Urban Rural Electricity Yes 61.5 3.8 27.9 No 38.5 96.0 72.0 Total 100.0 100.0 100.0 Flooring material Earth, sand 13.8 78.2 51.3 Dung 0.7 5.4 3.5 Wood/planks 0.1 0.0 0.1 Palm/bamboo/leeds 0.1 0.0 0.1 Parquet or polished wood 1.9 0.2 0.9 Vinyl or asphalt strips 0.5 0.0 0.2 Ceramic/terrazzo tiles 5.1 0.2 2.3 Concrete cement 76.8 15.7 41.2 Carpet 0.9 0.1 0.4 Total 100.0 100.0 100.0 Rooms used for sleeping One 30.3 36.7 34.0 Two 41.7 41.8 41.7 Three or more 27.4 20.7 23.5 Total 100.0 100.0 100.0 Place for cooking In the house 49.7 9.8 26.4 In a separate building 5.9 56.5 35.4 Outdoors 44.3 33.5 38.0 No food cooked in household 0.0 0.1 0.1 Other 0.0 0.1 0.1 Total 100.0 100.0 100.0 Cooking fuel Electricity 26.9 1.8 12.3 Charcoal 67.2 15.6 37.1 Wood 5.8 82.0 50.2 Straw/shrubs/grass 0.0 0.3 0.2 Animal dung 0.0 0.2 0.1 No food cooked in household 0.0 0.1 0.1 Total 100.0 100.0 100.0 Percentage using solid fuel for cooking1 73.0 98.1 87.6 Frequency of smoking in the home Daily 10.6 16.5 14.0 Weekly 2.4 3.4 3.0 Monthly 0.3 0.3 0.3 Less than monthly 0.8 0.9 0.8 Never 85.9 78.9 81.8 Total 100.0 100.0 100.0 Number 6,640 9,280 15,920 Note: Totals may not sum to 100 percent because households with missing information have been deleted. 1 Includes coal/lignite, wood/straw/shrubs/grass, and animal dung Housing Characteristics and Household Population • 19 Information on smoking was collected in the 2013-14 ZDHS to assess the percentage of households exposed to SHS, which is a risk factor for children and adults who do not smoke. Pregnant women who are exposed to SHS have a higher risk of giving birth to a low birth weight baby (Windham et al., 1999). Also, children who are exposed to SHS are at a higher risk of respiratory and ear infections and poor lung development (U.S. Department of Health and Human Services, 2006). Table 2.3 provides information on household exposure to SHS according to frequency of smoking, used here as a proxy for level of SHS exposure. Fourteen percent of households are exposed daily to SHS, and rural households (17 percent) are more likely to be exposed than urban households (11 percent). 2.1.3 Household Possessions Possession of durable consumer goods is another useful indicator of household socioeconomic status. The possession and use of household durable goods have multiple effects and implications. Having access to a radio or television exposes household members to updated daily events, information, and educational materials. Similarly, a refrigerator prolongs food storage and keeps food fresh and hygienic. A means of transportation allows greater access to services away from the local area and enhances social and economic activities. The 2013-14 ZDHS collected information on possession of durable commodities, means of transportation, and ownership of agricultural land and farm animals. Table 2.4 shows that radio and mobile telephones are very common information and communication devices possessed by most households. Possession of mobile phones has sharply increased from 28 percent in 2007 to 66 percent in 2013-14. Nearly 9 in 10 households in urban areas and half of households in rural areas possess mobile phones. Fifty-seven percent of households have a radio, with two-thirds of urban households and half of rural households having a radio. Thirty-seven percent of households have a television (66 percent urban and 16 percent rural). Ownership of a television has increased from 24 percent in 2007 to 37 percent. A refrigerator is available in 20 percent of households, with urban households more than 15 times as likely (44 percent) as rural households (3 percent) to own one. Bicycles continue to be the most common means of transportation in Zambia; 43 percent of households in Zambia use bicycles as a means of transport, with more households in rural areas (54 percent) than urban households (29 percent) using bicycles. Ownership of a car/truck is much more common in urban areas (13 percent) than in rural areas (3 percent). Zambia is predominantly agricultural, with a large proportion of the population engaged in this sector. The 2013-14 ZDHS data indicate that 62 percent of households own agricultural land, with rural households more likely to own land (88 percent) than urban households (25 percent). Forty-nine percent of households in the country possess farm animals; 72 percent in rural areas and 17 percent in urban areas. Table 2.4 Household possessions Percentage of households possessing various household effects, means of transportation, agricultural land and livestock/farm animals by residence, Zambia 2013-14 Residence Total Possession Urban Rural Household effects Radio 68.3 48.5 56.7 Television 66.0 16.1 36.9 Mobile telephone 89.3 50.0 66.4 Non-mobile telephone 3.0 0.4 1.5 Refrigerator 43.9 2.9 20.0 Bed 89.8 59.4 72.1 Chair 75.9 47.2 59.2 Table 77.5 46.5 59.4 Cupboard 57.3 16.4 33.4 Sofa 64.0 14.4 35.1 Clock 37.8 7.8 20.3 Fan 30.9 1.8 13.9 Sewing machine 9.0 3.6 5.9 Cassette player 18.1 13.2 15.3 Plough 3.5 21.5 14.0 VCR/DVD 48.9 9.4 25.9 Tractor 0.5 0.4 0.5 Hammer mill 0.6 1.3 1.0 Computer 11.2 1.0 5.3 Internet 11.8 1.1 5.5 Microwave 10.4 0.5 4.6 Means of transport Bicycle 28.9 53.6 43.3 Animal drawn cart 0.7 8.5 5.2 Motorcycle/scooter 1.4 1.7 1.6 Car/truck 13.2 2.5 7.0 Boat with a motor 0.3 0.2 0.2 Banana boat 0.6 4.6 2.9 Ownership of agricultural land 24.8 88.1 61.7 Ownership of farm animals1 16.5 72.0 48.8 Ownership of bank/savings account2 46.2 8.8 24.4 Number 6,640 9,280 15,920 1 Traditional cattle, dairy cattle, beef cattle, horses, donkeys, mules, goats, sheep, pigs, chickens, rabbits, or other poultry or livestock. 2 At least one household member has an account. 20 • Housing Characteristics and Household Population 2.2 SOCIOECONOMIC STATUS INDEX The wealth index used in this survey is a measure that has been used in many DHS and other country-level surveys to indicate inequalities in household characteristics, use of health care and other services, and health outcomes (Rutstein and Johnson, 2004). It serves as an indicator of level of wealth that is consistent with expenditure and income measures (Rutstein, 1999). The index was constructed using household asset data via a principal components analysis. In its current form, which takes better account of urban-rural differences in scores and indicators of wealth, the wealth index is created in three steps. In the first step, a subset of indicators common to urban and rural areas is used to create wealth scores for households in both areas. Categorical variables to be used are transformed into separate dichotomous (0-1) indicators. These indicators and those that are continuous are then examined using a principal components analysis to produce a common factor score for each household. In the second step, separate factor scores are produced for households in urban and rural areas using area-specific indicators. The third step combines the separate area-specific factor scores to produce a nationally applicable combined wealth index by adjusting area-specific scores through a regression on the common factor scores. This three-step procedure permits greater adaptability of the wealth index in both urban and rural areas. The resulting combined wealth index has a mean of zero and a standard deviation of one. Once the index is computed, national-level wealth quintiles (from lowest to highest) are obtained by assigning the household score to each de jure household member, ranking each person in the population by his or her score, and then dividing the ranking into five equal categories, each comprising 20 percent of the population. Table 2.5 presents distributions across the five wealth quintiles by place of urban or rural residence and by province. These distributions indicate the degree to which wealth is evenly (or unevenly) distributed, according to geographic area. Forty-eight percent of urban residents are from the richest quintile, while a much lower proportion of rural residents (2 percent) fall in the same category. Rural households are mostly distributed in the lowest, second, and middle wealth quintiles (33 percent, 31 percent, and 24 percent, respectively). One in two households in the more urban provinces of Lusaka (50 percent) and Copperbelt (46 percent) are in the highest wealth quintile. About one in two households (44 percent) in Western are in the lowest wealth quintile. Table 2.5 Wealth quintiles Percent distribution of the de jure population by wealth quintiles, and the Gini Coefficient, according to residence and province, Zambia 2013-14 Wealth quintile Total Number of persons Gini coefficient Residence/province Lowest Second Middle Fourth Highest Residence Urban 0.6 2.8 13.4 35.6 47.6 100.0 31,977 0.23 Rural 32.5 31.0 24.3 10.0 2.2 100.0 49,698 0.43 Province Central 16.3 26.1 29.0 18.8 9.8 100.0 7,873 0.49 Copperbelt 3.3 7.4 16.1 27.7 45.5 100.0 12,732 0.30 Eastern 31.5 26.8 22.6 14.9 4.2 100.0 10,271 0.49 Luapula 30.5 35.0 22.2 8.3 4.0 100.0 6,327 0.44 Lusaka 1.5 2.2 8.0 38.5 49.8 100.0 13,429 0.20 Muchinga 38.4 26.1 17.8 11.8 5.9 100.0 4,676 0.52 Northern 43.2 26.4 17.2 8.6 4.5 100.0 6,745 0.54 North Western 26.4 30.6 22.9 12.0 8.1 100.0 3,875 0.51 Southern 11.9 23.5 33.4 19.4 11.8 100.0 10,565 0.46 Western 44.0 26.9 15.6 8.7 4.8 100.0 5,181 0.54 Total 20.0 20.0 20.0 20.0 20.0 100.0 81,675 0.49 Table 2.5 also includes the Gini coefficient for each area, which indicates the level of concentration of wealth (0 being an equal distribution and 1 a totally unequal distribution). This ratio is expressed as a proportion between 0 and 1. Wealth inequality, as measured by the Gini coefficient, is Housing Characteristics and Household Population • 21 higher in rural than urban areas. Inequality in wealth is highest in Northern and Western (0.54) and lowest in Lusaka (0.20). 2.3 HAND WASHING Table 2.6 provides information on designated places for hand washing in households and the use of water and cleansing agents for washing hands according to place of residence, province, and wealth quintile. Interviewers were instructed to observe the place where household members usually washed their hands. They looked for regularity of water supply and observed whether households had cleansing agents near the place of hand washing. Only 40 percent of households were observed to have a place for washing hands. Table 2.6 Hand washing Percentage of households in which the place most often used for washing hands was observed, and among households in which the place for hand washing was observed, percent distribution by availability of water, soap, and other cleansing agents, Zambia 2013-14 Percentage of households where place for washing hands was observed Number of households Among households where place for hand washing was observed, percentage with: Number of households with place for hand washing observed Background characteristic Soap and water1 Water and cleansing agent2 other than soap only Water only Soap but no water3 Cleansing agent other than soap only2 No water, no soap, no other cleansing agent Missing Total Residence Urban 56.9 6,640 42.8 0.5 27.6 4.1 0.3 24.4 0.2 100.0 3,780 Rural 28.2 9,280 17.3 2.5 24.6 5.4 3.0 46.2 0.9 100.0 2,615 Province Central 23.1 1,472 29.8 0.6 39.9 0.9 0.5 27.2 1.1 100.0 339 Copperbelt 65.9 2,455 41.7 1.8 22.8 4.6 0.9 28.1 0.2 100.0 1,619 Eastern 30.1 1,938 20.9 0.9 44.7 1.4 0.3 30.3 1.4 100.0 583 Luapula 33.7 1,265 19.8 0.9 13.6 6.7 0.4 57.3 1.3 100.0 427 Lusaka 60.3 2,925 39.1 0.6 30.3 3.7 0.0 26.2 0.2 100.0 1,765 Muchinga 16.8 881 13.0 1.7 15.0 2.8 14.8 51.2 1.5 100.0 148 Northern 29.2 1,269 21.2 1.7 9.8 13.1 7.0 46.5 0.8 100.0 370 North Western 27.1 724 15.9 1.5 19.0 2.7 2.0 58.6 0.3 100.0 196 Southern 35.6 1,934 21.3 3.0 22.5 8.2 2.7 42.2 0.1 100.0 689 Western 24.6 1,057 48.1 0.3 31.5 1.3 0.0 17.8 0.9 100.0 260 Wealth quintile Lowest 23.0 3,514 10.3 1.4 23.0 4.4 3.0 56.6 1.2 100.0 808 Second 25.7 3,055 13.5 2.0 22.4 6.3 3.8 50.7 1.2 100.0 787 Middle 33.9 2,958 17.4 3.9 23.0 6.1 2.7 46.5 0.4 100.0 1,001 Fourth 47.0 3,252 26.3 0.8 31.6 5.1 0.6 35.5 0.1 100.0 1,529 Highest 72.3 3,141 57.5 0.2 27.0 3.2 0.0 11.7 0.3 100.0 2,270 Total 40.2 15,920 32.4 1.3 26.4 4.6 1.4 33.3 0.5 100.0 6,396 1 Soap includes soap or detergent in bar, liquid, powder, or paste form. This column includes households with soap and water only as well as those that had soap and water and another cleansing agent. 2 Cleansing agents other than soap include locally available materials such as ash, mud, or sand 3 Includes households with soap only as well as those with soap and another cleansing agent Among households that were observed to have a place for washing hands, 32 percent had soap and water at the place where household members washed their hands, 26 percent had water only, and 5 percent had soap but no water. Overall, one-third (33 percent) of households did not have either water or any other cleansing agent. Forty-three percent of households in urban areas had soap and water, compared with 17 percent of rural households. Western had the highest proportion of households that had soap and water (48 percent). Muchinga had the lowest percentage of households with soap and water (13 percent). Soap and water was most common (58 percent) among households in the highest wealth quintile and least common in households in the lowest wealth quintile (10 percent). 22 • Housing Characteristics and Household Population 2.4 HOUSEHOLD POPULATION BY AGE AND SEX Age and sex are important demographic variables and are the primary basis of demographic classification. They are also very important variables in the study of mortality, fertility, and nuptiality. Table 2.7 shows the distribution of the de facto household population by age and sex according to urban and rural residence. The 2013-14 ZDHS enumerated a total of 78,803 persons (40,628 females and 38,175 males). Half of the Zambian population (50 percent) is under age 15, and 17 percent of the population is under age 5. These proportions have remained the same over the last six years. Persons age 65 and older account for about 3 percent of the total population. There is a smaller proportion of children under age 5 in urban than rural areas. Table 2.7 Household population by age, sex, and residence Percent distribution of the de facto household population by five-year age groups, according to sex and residence, Zambia 2013-14 Urban Rural Total Age Male Female Total Male Female Total Male Female Total <5 15.7 14.0 14.8 19.4 18.2 18.7 17.9 16.5 17.2 5-9 15.5 14.5 15.0 19.4 18.3 18.8 17.9 16.8 17.3 10-14 13.6 14.1 13.9 17.5 15.5 16.5 16.0 15.0 15.5 15-19 10.8 11.1 11.0 8.9 8.2 8.5 9.7 9.4 9.5 20-24 8.9 9.8 9.4 5.4 6.5 6.0 6.8 7.8 7.3 25-29 7.2 8.5 7.9 4.7 6.2 5.5 5.7 7.1 6.4 30-34 7.1 7.3 7.2 4.8 5.6 5.2 5.7 6.3 6.0 35-39 5.8 5.8 5.8 4.4 4.8 4.6 5.0 5.2 5.1 40-44 4.8 3.7 4.2 3.7 3.7 3.7 4.1 3.7 3.9 45-49 3.1 2.7 2.9 2.9 2.6 2.7 3.0 2.6 2.8 50-54 2.2 2.7 2.5 2.0 2.8 2.4 2.1 2.8 2.5 55-59 1.3 1.9 1.6 1.5 1.9 1.7 1.4 1.9 1.7 60-64 1.8 1.4 1.6 1.7 1.6 1.7 1.8 1.5 1.6 65-69 0.9 1.0 1.0 1.2 1.5 1.3 1.1 1.3 1.2 70-74 0.6 0.8 0.7 0.8 1.0 0.9 0.7 0.9 0.8 75-79 0.3 0.4 0.3 0.7 0.8 0.8 0.6 0.6 0.6 80 + 0.3 0.4 0.4 0.8 0.9 0.8 0.6 0.7 0.6 Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 Number 14,921 16,181 31,102 23,254 24,447 47,701 38,175 40,628 78,803 Figure 2.1 illustrates the age structure of the household population in a population pyramid. A feature of population pyramids is their strength in illustrating whether a population is “young” or “old.” The broad base of the pyramid indicates that Zambia’s population is young. This scenario is typical of countries with higher fertility rates. The pyramid also shows that there are slightly more females than males, especially at age 15 and older. The overall sex ratio (the number of males per 100 females) is 94, slightly higher than the sex ratio in the 2007 ZDHS (93). The sex ratio also differs by residence. Rural areas have a higher sex ratio (95) than urban areas (92). Housing Characteristics and Household Population • 23 Figure 2.1 Population pyramid 2.5 HOUSEHOLD COMPOSITION Information on household composition is critical for understanding family size, household headship, and orphanhood and for implementing meaningful population-based policies and programmes. Household composition is also a determinant of health status and well-being. Female- headed households are, for example, typically poorer than male-headed households. Economic resources are often more limited in larger households. Moreover, where the size of the household is large, crowding can also lead to health problems. Table 2.8 presents information on household composition. The majority (73 percent) of households are headed by men, although the proportion of female-headed households has risen from 24 percent in 2007 to 27 percent in 2013-14, with the rise more marked in urban than rural areas. The average household size is 5.1 persons, as compared with 4.9 in 2007; household sizes are larger in rural (5.4) than urban (4.8) areas. This decrease in overall household size is consistent with findings from the 2010 Census of Population and Housing (CSO, 2013). The 2013-14 ZDHS also collected informa- tion on the presence in households of foster children and orphans. Foster children are children under age -10 -5 0 5 10 <5 5-9 10-14 15-19 20-24 25-29 30-34 35-39 40-44 45-49 50-54 55-59 60-64 65-69 70-74 75-79 80 + 10 8 6 4 2 0 2 4 6 8 10 ZDHS 2013-14 Age Male Female Table 2.8 Household composition Percent distribution of households by sex of head of household and by household size; mean size of household, and percentage of households with orphans and foster children under 18 years of age, according to residence, Zambia 2013-14 Residence Total Characteristic Urban Rural Household headship Male 73.7 73.2 73.4 Female 26.3 26.8 26.6 Total 100.0 100.0 100.0 Number of usual members 1 8.7 6.1 7.2 2 10.1 8.3 9.1 3 14.1 11.1 12.4 4 15.8 14.4 15.0 5 15.1 15.0 15.0 6 13.2 13.8 13.6 7 9.2 12.0 10.8 8 5.9 8.1 7.2 9+ 7.8 11.1 9.7 Total 100.0 100.0 100.0 Mean size of households 4.8 5.4 5.1 Percentage of households with orphans and foster children under 18 years of age Foster children1 30.4 29.0 29.6 Double orphans 4.9 3.8 4.2 Single orphans2 15.7 14.8 15.2 Foster and/or orphan children 35.8 33.9 34.7 Number of households 6,640 9,280 15,920 Note: Table is based on de jure household members, i.e., usual residents. 1 Foster children are those under age 18 living in households with neither their mother nor their father present. 2 Includes children with one dead parent and an unknown survival status of the other parent. 24 • Housing Characteristics and Household Population 18 living in households with neither their mother nor their father present; orphans are children with one (single orphans) or both parents (double orphans) dead. Foster children and orphans are of concern because they may be at increased risk of neglect or exploitation when their mothers, fathers, or both are not present to assist them. Overall, 35 percent of households have foster or orphan children. There is little difference in the distribution of foster children by rural and urban areas. Single orphans are present in 15 percent of households, whereas double orphans are present in 4 percent of households. 2.6 BIRTH REGISTRATION Birth registration is the formal inscription of the facts of a birth into an official log kept at the registrar’s office. A birth certificate is issued at the time of registration or later as proof of the registration of the birth. Birth registration is basic to ensuring a child’s legal status and, thus, basic rights and services (UNICEF, 2006; United Nations General Assembly, 2002). Although Zambia has a legal and administrative structure stipulating official registration of births, according to standard procedures, few births are registered officially. The practice of formally registering births is not widely adhered to in the country, even though the registration system was implemented more than 40 years ago and enforced with the Birth and Death Registration Act CAP 51 of the Laws of Zambia (GRZ, 1973). Table 2.9 presents the percentage of the de jure population under age 5 whose births are registered with the civil authorities, according to background characteristics. Birth registration information was solicited for children age 0-4. The table shows that only 11 percent of children age 0-4 are registered with the civil authority. Four percent of children under age 5 have a birth certificate. The table also shows that birth registration is much higher in urban (20 percent) than rural (7 percent) areas. It is highest in Copperbelt (24 percent), followed by Lusaka (21 percent), and lowest in Northern (2 percent). Children from the highest wealth quintile are six times more likely to have their births registered (29 percent) than children in the lowest quintile (5 percent). Table 2.9 Birth registration of children under age 5 Percentage of de jure children under age 5 whose births are registered with the civil authorities, according to background characteristics, Zambia 2013-14 Children whose births are registered Number of children Background characteristic Percentage who had a birth certificate Percentage who did not have a birth certificate Percentage registered Age <2 3.5 6.9 10.5 5,321 2-4 4.4 7.4 11.8 8,394 Sex Male 4.2 7.4 11.7 6,922 Female 3.9 7.0 10.9 6,793 Residence Urban 9.1 11.3 20.4 4,633 Rural 1.5 5.2 6.7 9,082 Province Central 2.2 2.4 4.6 1,333 Copperbelt 13.7 9.9 23.6 1,796 Eastern 3.2 10.2 13.4 1,731 Luapula 0.7 5.0 5.7 1,197 Lusaka 6.6 14.1 20.8 1,987 Muchinga 0.4 3.3 3.7 812 Northern 0.8 1.5 2.3 1,311 North Western 3.0 2.4 5.4 719 Southern 1.8 10.1 12.0 1,908 Western 1.9 0.7 2.6 922 Wealth quintile Lowest 1.2 3.7 4.9 3,323 Second 1.1 4.2 5.3 3,126 Middle 2.3 7.4 9.7 2,798 Fourth 5.4 8.8 14.2 2,370 Highest 14.1 15.2 29.2 2,099 Total 4.1 7.2 11.3 13,715 Housing Characteristics and Household Population • 25 2.7 CHILDREN’S LIVING ARRANGEMENTS, ORPHANHOOD, AND SCHOOL ATTENDANCE The 2013-14 ZDHS collected information on living arrangements of children with and without parents. Living arrangements should be monitored for both because of their significant effects on the comprehensive development of children. Table 2.10 shows the percent distribution of children under age 18 by living arrangements and survivorship of parents. The proportion of Zambian children under age 18 with one or both parents dead is 11 percent. Orphanhood increases with children’s age, from 2 percent of children under age 2 to 24 percent of children age 15-17. There are no marked differences in the proportion of orphans according to sex. The proportion of orphans is higher in urban areas (13 percent) than rural areas (10 percent). Copperbelt has the highest proportion of orphans (15 percent), while Eastern, Northern, North Western, and Southern have the lowest (10 percent). Orphanhood by wealth quintile shows no major variations. Table 2.10 Children’s living arrangements and orphanhood Percent distribution of de jure children under age 18 by living arrangements and survival status of parents, the percentage of children not living with a biological parent, and the percentage of children with one or both parents dead, according to background characteristics, Zambia 2013-14 Living with both parents Living with mother but not with father Living with father but not with mother Not living with either parent Total Percentage not living with a biological parent Percentage with one or both parents dead1 Number of children Background characteristic Father alive Father dead Mother alive Mother dead Both alive Only father alive Only mother alive Both dead Missing information on father/ mother Age 0-4 71.3 20.1 1.9 0.9 0.1 4.3 0.5 0.4 0.3 0.3 100.0 5.4 3.1 13,715 <2 74.2 22.5 1.4 0.2 0.0 1.1 0.3 0.0 0.0 0.3 100.0 1.4 1.7 5,321 2-4 69.4 18.7 2.2 1.3 0.1 6.3 0.6 0.6 0.5 0.3 100.0 7.9 4.1 8,394 5-9 62.5 13.4 4.2 3.2 0.5 10.8 1.3 2.2 1.5 0.4 100.0 15.7 9.7 13,901 10-14 51.1 10.8 6.3 4.9 1.0 15.1 2.3 4.3 3.4 0.8 100.0 25.0 17.3 12,477 15-17 44.1 8.8 8.6 4.6 1.1 16.4 3.2 5.4 5.3 2.5 100.0 30.3 23.7 4,767 Sex Male 60.9 14.2 4.5 3.5 0.6 9.6 1.3 2.6 2.1 0.7 100.0 15.6 11.1 22,459 Female 59.2 14.3 4.7 2.7 0.5 11.5 1.7 2.6 2.0 0.8 100.0 17.8 11.5 22,402 Residence Urban 55.1 14.9 5.3 3.5 0.6 12.3 1.7 2.9 2.8 0.9 100.0 19.6 13.4 15,789 Rural 62.7 13.9 4.2 2.9 0.5 9.7 1.4 2.4 1.7 0.6 100.0 15.1 10.2 29,071 Province Central 59.0 13.7 5.1 3.0 0.3 11.5 2.1 2.6 2.1 0.6 100.0 18.3 12.2 4,467 Copperbelt 54.2 14.1 5.6 3.8 0.8 12.3 2.0 3.2 3.0 1.1 100.0 20.5 14.6 6,386 Eastern 63.5 13.4 3.8 2.3 0.4 10.3 1.1 2.8 1.7 0.8 100.0 15.8 9.7 5,731 Luapula 57.7 19.3 4.7 3.1 0.2 7.9 1.3 2.5 2.9 0.4 100.0 14.6 11.6 3,777 Lusaka 58.7 13.9 4.9 2.9 0.4 12.2 1.4 2.4 2.3 0.8 100.0 18.3 11.6 6,522 Muchinga 67.8 11.6 4.4 1.5 0.8 7.8 1.5 2.0 1.9 0.6 100.0 13.2 10.8 2,678 Northern 68.8 12.4 3.9 1.7 0.3 7.1 1.4 2.4 1.6 0.4 100.0 12.5 9.7 4,040 North Western 58.2 16.8 4.1 3.2 0.5 11.9 1.2 1.9 1.8 0.5 100.0 16.9 9.5 2,268 Southern 63.1 11.2 3.7 4.3 0.9 11.1 1.3 2.2 1.5 0.7 100.0 16.0 9.7 6,074 Western 49.7 20.7 5.3 5.0 0.9 11.4 1.5 3.3 1.3 0.8 100.0 17.5 12.5 2,919 Wealth quintile Lowest 57.5 19.9 5.7 2.0 0.6 8.0 1.7 2.1 1.8 0.7 100.0 13.6 11.9 9,508 Second 66.2 12.4 4.6 2.8 0.4 7.9 1.2 2.3 1.7 0.5 100.0 13.1 10.3 9,638 Middle 61.8 13.8 4.2 3.1 0.5 10.9 1.1 2.3 1.8 0.7 100.0 16.0 9.8 9,474 Fourth 58.7 12.5 4.2 3.6 0.8 12.3 1.5 3.1 2.4 0.9 100.0 19.3 12.1 8,613 Highest 55.0 12.2 3.9 4.4 0.7 14.9 2.2 3.1 2.8 0.9 100.0 23.0 12.8 7,627 Total <15 62.0 14.9 4.1 2.9 0.5 9.9 1.3 2.2 1.7 0.5 100.0 15.1 9.8 40,093 Total <18 60.1 14.2 4.6 3.1 0.6 10.6 1.5 2.6 2.1 0.7 100.0 16.7 11.3 44,861 Note: Table is based on de jure members, i.e., usual residents. 1 Includes children with father dead, mother dead, both dead, and one parent dead but missing information on survival status of the other parent. About 60 percent of children younger than age 18 live with both of their parents. The proportion of children living with both parents decreases with age. Children who are younger than age 2 are more likely to live with both parents (74 percent) than children age 15-17 (44 percent). Children in rural areas (63 percent) are more likely to live with both parents than children in urban areas (55 percent). Only one in two children in Western (50 percent) lives with both parents, compared with two in three children in Northern (69 percent) and Muchinga (68 percent). The percentage of children living with both parents is highest in the second wealth quintile (66 percent) and lowest in the highest quintile (55 percent). 26 • Housing Characteristics and Household Population Table 2.10 also shows that the percentage of children not living with a biological parent increases with their age. Children age 15-17 (30 percent) are most likely not to live with a biological parent. The highest proportion of children not living with a biological parent is observed in Copperbelt (21 percent), while the lowest proportion is found in Northern and Muchinga (13 percent). Orphaned children may be at greater risk of dropping out of school than children with biological parents. This can happen for various reasons, such as the inability to pay school fees, the need to help with household chores, or the need to care for sick parents or younger siblings. Table 2.11 shows data on school attendance rates among children age 10-14 by survivorship of parents. Double orphans (i.e., children whose father and mother are dead) are less likely than children whose parents are both alive and living with at least one parent to be currently in school (79 percent and 91 percent, respectively). Table 2.11 School attendance by survivorship of parents For de jure children age 10-14, the percentage attending school by parental survival and the ratio of the percentage attending, by parental survival, according to background characteristics, Zambia 2013-14 Percentage attending school by survivorship of parents Ratio1 Background characteristic Both parents deceased Number Both parents alive and living with at least one parent Number Sex Male 78.7 220 90.5 4,286 0.87 Female 78.3 201 91.5 4,057 0.86 Residence Urban 86.2 182 95.0 2,670 0.91 Rural 72.6 238 89.1 5,673 0.81 Province Central (84.1) 43 90.9 837 0.93 Copperbelt 77.0 76 94.4 1,080 0.82 Eastern 47.2 45 80.9 1,168 0.58 Luapula 82.1 59 89.6 797 0.92 Lusaka (86.9) 58 94.9 1,113 0.92 Muchinga (81.6) 25 90.6 524 0.90 Northern (82.8) 31 90.8 810 0.91 North Western (85.9) 21 90.9 427 0.94 Southern (84.7) 46 96.2 1,115 0.88 Western * 16 89.7 472 0.82 Wealth quintile Lowest 66.6 92 79.3 1,666 0.84 Second 73.6 83 90.3 1,889 0.82 Middle 75.8 63 94.6 1,872 0.80 Fourth 79.2 98 94.0 1,619 0.84 Highest 97.5 84 97.9 1,297 1.00 Total 78.5 420 91.0 8,343 0.86 Note: Table is based only on children who usually live in the household. Figures in parentheses are based on 25-49 unweighted cases. An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. 1 Ratio of the percentage with both parents deceased to the percentage with both parents alive and living with a parent 2.8 EDUCATION OF HOUSEHOLD POPULATION Studies have shown that education is one of the major socioeconomic factors that influence a person’s behaviours and attitudes. In general, the higher the level of education of a woman, the more knowledgeable she is about the use of health facilities, family planning methods, and the health of her children. Zambia is addressing poor access to education through MDG 2. In 2002, the Ministry of Education enacted the Free Basic Education policy, which has subsequently led Zambia to dedicate substantially more domestic resources to education. From 2006 to 2010, funding to the education sector steadily increased from 3 percent to 4 percent of gross domestic product. Zambia improved school infrastructure, including water and sanitation. Teacher training programmes increased the supply of Housing Characteristics and Household Population • 27 teachers to match the expansion of school enrollment. The number of teachers in all schools increased from 79,874 in 2010 to 93,194 in 2013 (DFID, 2011). 2.8.1 Educational Attainment of Household Population Tables 2.12.1 and 2.12.2 show the percent distribution of the de facto female and male household population age 6 and older by level of education and background characteristics. Table 2.12.1 shows that, 16 percent of females have never been to school, 46 percent have some primary education, 11 percent have completed primary school, 19 percent have some secondary education, 4 percent have completed secondary education, and 3 percent have more than a secondary school education. The proportion of females with no education increases with age, indicating that older women are less likely to be educated than younger women. This trend also indicates improvement in the level of education over the last six decades. Table 2.12.2 shows a similar trend for males and also indicates that males are more educated than females. For example, more females than males have no education (16 percent and 13 percent respectively). Men are also twice as likely to complete secondary level schooling as women (8 percent and 4 percent, respectively). The median years of schooling for females is 4.3 years, while it is 5.1 years for males. The percentage of females and males with no education has decreased over the last six years from 20 percent to 16 percent of females and 14 percent to 13 percent of males. Table 2.12.1 Educational attainment of the female household population Percent distribution of the de facto female household population age six and over by highest level of schooling attended or completed and median years completed, according to background characteristics, Zambia 2013-14 Background characteristic No education Some primary Completed primary1 Some secondary Completed secondary2 More than secondary Don’t know/ missing Total Number Median years completed Age 6-9 38.1 61.1 0.0 0.0 0.0 0.0 0.7 100.0 5,649 0.0 10-14 4.6 84.6 4.4 6.1 0.1 0.0 0.4 100.0 6,083 3.4 15-19 2.5 27.8 14.3 50.1 4.7 0.3 0.3 100.0 3,803 7.0 20-24 5.4 23.2 12.6 38.4 15.9 4.5 0.1 100.0 3,178 7.7 25-29 10.0 30.7 15.3 24.0 11.2 8.4 0.4 100.0 2,900 6.6 30-34 10.3 34.6 17.7 22.2 6.3 8.6 0.3 100.0 2,544 6.3 35-39 11.5 35.8 20.0 22.2 4.7 5.5 0.3 100.0 2,105 6.1 40-44 13.8 36.0 20.9 19.9 3.8 5.2 0.4 100.0 1,510 6.0 45-49 15.7 33.1 26.1 16.0 3.3 5.5 0.3 100.0 1,061 6.0 50-54 17.9 31.6 24.5 16.2 2.9 6.1 0.9 100.0 1,128 6.0 55-59 22.2 33.8 21.4 15.8 1.3 4.0 1.5 100.0 765 4.7 60-64 34.3 36.8 10.4 11.9 1.1 4.8 0.7 100.0 609 2.9 65+ 55.1 33.1 3.6 3.7 0.6 2.2 1.8 100.0 1,417 0.0 Residence Urban 8.3 35.9 12.1 28.4 8.5 6.5 0.3 100.0 13,526 6.4 Rural 21.3 53.3 10.6 11.9 1.4 0.8 0.6 100.0 19,231 3.0 Province Central 17.3 48.0 12.1 16.2 3.7 2.3 0.3 100.0 3,180 3.9 Copperbelt 8.5 38.1 11.4 28.0 7.2 6.5 0.3 100.0 5,366 6.2 Eastern 24.4 52.0 8.8 10.9 1.8 0.9 1.3 100.0 4,081 2.6 Luapula 20.7 55.6 8.2 12.5 1.6 0.9 0.5 100.0 2,532 2.8 Lusaka 9.5 34.7 13.5 27.3 8.4 6.3 0.3 100.0 5,652 6.4 Muchinga 16.9 55.5 9.5 14.3 2.3 1.0 0.6 100.0 1,785 3.4 Northern 19.8 57.2 8.9 11.9 1.0 0.7 0.4 100.0 2,612 2.8 North Western 21.6 48.9 8.0 15.2 3.7 2.1 0.5 100.0 1,528 3.2 Southern 12.8 47.2 15.5 18.6 3.3 2.1 0.6 100.0 3,958 4.7 Western 24.8 46.7 10.2 13.0 3.3 1.8 0.2 100.0 2,063 3.1 Wealth quintile Lowest 30.6 54.3 7.9 6.3 0.2 0.0 0.7 100.0 6,515 1.6 Second 21.2 55.6 11.3 10.9 0.6 0.0 0.4 100.0 6,158 2.9 Middle 15.7 52.2 12.8 16.7 1.8 0.3 0.5 100.0 6,317 3.9 Fourth 9.7 43.2 14.4 25.3 5.0 1.8 0.5 100.0 6,670 5.6 Highest 4.1 27.9 9.9 32.4 13.0 12.4 0.3 100.0 7,096 7.8 Total 16.0 46.2 11.2 18.7 4.3 3.1 0.5 100.0 32,757 4.3 1 Completed 7th grade at the primary level 2 Completed 12th grade at the secondary level 28 • Housing Characteristics and Household Population Females and males in rural areas are less educated than their urban counterparts. The median years of schooling are 3.0 and 3.7 years for females and males, respectively, in rural areas compared with 6.4 and 7.2 years, respectively, in urban areas. One in four females in Western (25 percent) and Eastern (24 percent) has no education. Lusaka and Copperbelt have the lowest proportion of females with no education (10 percent and 9 percent, respectively). Twenty-three percent of males in Eastern have no education compared with 7 percent of males in Copperbelt and Lusaka. Wealth exerts a positive influence on educational attainment. Females from the highest wealth quintile are more likely to be educated than those from other quintiles. Females from the highest wealth quintile have completed at least 7.8 years of schooling compared with 1.6 years among females in the lowest wealth quintile. Similarly the median years of schooling among males in the highest wealth quintile is 8.7 years compared with 2.4 years among males in the lowest wealth quintile. Table 2.12.2 Educational attainment of the male household population Percent distribution of the de facto male household population age 6 and over by highest level of schooling attended or completed and median years completed, according to background characteristics, Zambia 2013-14 Background characteristic No education Some primary Completed primary1 Some secondary Completed secondary2 More than secondary Don’t know/ missing Total Number Median years completed Age 6-9 43.0 56.2 0.0 0.0 0.0 0.0 0.7 100.0 5,544 0.0 10-14 6.1 84.8 3.6 5.2 0.0 0.0 0.3 100.0 6,094 3.1 15-19 2.7 31.7 13.4 46.1 5.3 0.3 0.5 100.0 3,686 6.8 20-24 2.7 14.1 11.4 42.3 23.4 5.9 0.3 100.0 2,597 8.5 25-29 4.5 20.8 13.2 29.8 20.8 10.6 0.4 100.0 2,175 8.2 30-34 5.9 24.6 16.9 24.5 15.6 11.9 0.6 100.0 2,170 7.3 35-39 6.5 22.5 16.7 29.4 13.2 11.2 0.4 100.0 1,900 7.7 40-44 5.0 23.2 19.7 29.4 11.3 10.8 0.6 100.0 1,584 7.2 45-49 7.7 23.8 23.4 21.9 11.5 11.1 0.5 100.0 1,136 6.8 50-54 6.7 20.1 26.2 25.2 12.0 9.5 0.3 100.0 807 6.9 55-59 3.5 20.9 28.1 26.8 6.1 13.1 1.6 100.0 548 6.9 60-64 13.4 25.9 20.4 20.7 7.8 11.0 0.9 100.0 674 6.5 65+ 18.1 45.5 11.3 15.0 4.3 4.4 1.4 100.0 1,138 4.0 Province Urban 6.7 31.0 8.9 28.1 15.3 9.6 0.4 100.0 12,144 7.2 Rural 16.7 50.6 11.8 15.8 3.0 1.5 0.7 100.0 17,912 3.7 Province Central 12.2 48.0 11.9 18.7 6.1 2.9 0.2 100.0 2,809 4.7 Copperbelt 6.9 32.9 8.8 28.3 13.3 9.3 0.5 100.0 4,836 6.9 Eastern 22.9 47.5 9.5 13.3 3.9 1.8 1.1 100.0 3,873 3.2 Luapula 16.3 52.0 8.6 17.2 3.5 1.5 0.9 100.0 2,280 3.6 Lusaka 7.2 30.3 10.2 27.1 15.5 9.5 0.2 100.0 5,277 7.1 Muchinga 10.9 50.2 12.3 19.2 4.2 2.4 0.8 100.0 1,649 4.6 Northern 13.7 50.9 11.6 18.5 3.2 1.8 0.4 100.0 2,334 4.1 North Western 16.0 45.3 9.3 19.7 6.1 3.1 0.5 100.0 1,344 4.3 Southern 11.5 45.2 14.4 19.1 6.0 3.1 0.6 100.0 3,921 5.0 Western 18.8 50.4 9.4 14.3 3.6 3.0 0.4 100.0 1,734 3.3 Wealth quintile Lowest 23.2 53.7 10.8 10.3 1.0 0.1 0.9 100.0 5,357 2.4 Second 17.3 51.4 12.6 15.9 2.2 0.1 0.5 100.0 5,916 3.6 Middle 13.1 49.0 12.4 20.4 3.9 0.5 0.6 100.0 6,123 4.4 Fourth 8.0 36.5 11.7 28.1 11.1 4.1 0.4 100.0 6,336 6.4 Highest 3.7 25.4 5.7 27.1 19.9 17.9 0.4 100.0 6,324 8.7 Total 12.7 42.7 10.6 20.7 7.9 4.8 0.5 100.0 30,056 5.1 1 Completed 7th grade at the primary level 2 Completed 12th grade at the secondary level Housing Characteristics and Household Population • 29 2.8.2 School Attendance Ratios The net attendance ratio (NAR) indicates participation in primary schooling for the population age 7-13 and secondary schooling for the population age 14-18. The gross attendance ratio (GAR) measures participation at each level of schooling among those of any age from 5 to 24 years. The GAR is almost always higher than the NAR for the same level because the GAR includes participation by those who may be older or younger than the official age range for that level. A NAR of 100 percent would indicate that all of those in the official age range for that level are attending at that level. The GAR can exceed 100 percent if there is significant overage or underage participation at a given level of schooling. The gender parity index (GPI) assesses sex-related differences in school attendance rates and is calculated by dividing the GAR for females by the GAR for males. A GPI less than 1 indicates a gender disparity in favour of males (i.e., a higher proportion of males than females attends that level of schooling). A GPI greater than 1 indicates a gender disparity in favour of females. A GPI of 1 indicates parity or equality between the rates of participation for males and females. Table 2.13 provides data on net attendance ratios and gross attendance ratios by sex and level of schooling and gender parity index, according to background characteristics. The Net Attendance Ratio (NAR) at the primary level is 80 percent and is half that percentage (40 percent) at the secondary level. The NAR in rural areas is lower than in urban areas (79 percent versus 84 percent). The NAR at the primary level and secondary level is lowest in Eastern (70 percent and 22 percent, respectively). The NAR at the primary level is highest in Lusaka and Southern (85 percent), while the NAR at the secondary level is highest in Copperbelt (60 percent). The GAR is higher than the NAR for both males and females at the primary and secondary levels. The NAR at the primary level has remained the same since 2007 but the NAR at the secondary level has increased from 37 percent to 40 percent over the same period. Over the past six years, the rise in the NAR and GAR at the secondary level for females has been noticeable, with the NAR increasing from 35 percent in 2007 to 41 percent in 2013-14 and the GAR increasing from 46 percent in 2007 to 57 percent in 2013-14. Table 2.13 also shows the Gender Parity Index (GPI), which represents the ratio of the NAR and GAR for females to the NAR and GAR for males. The gender parity index shows the disparities in access to education between males and females. The index helps in addressing unequal access to education among females. It is a more precise indicator of gender differences in the schooling system. The indexes for NAR at the primary and secondary levels are slightly higher than one (1.04 and 1.05, respectively), indicating that more males than females attend primary and secondary school. The GPI for the GAR is slightly lower than 1, indicating more females are attending school than males. However, the gender gap in attendance has remained almost unchanged at the primary level but has narrowed over the past few years at the secondary level. 30 • Housing Characteristics and Household Population Table 2.13 School attendance ratios Net attendance ratios (NAR) and gross attendance ratios (GAR) for the de facto household population by sex and level of schooling; and the Gender Parity Index (GPI), according to background characteristics, Zambia 2013-14 Net attendance ratio1 Gross attendance ratio2 Background characteristic Male Female Total Gender Parity Index3 Male Female Total Gender Parity Index3 PRIMARY SCHOOL Residence Urban 82.8 84.3 83.6 1.02 105.2 103.5 104.3 0.98 Rural 76.8 80.3 78.5 1.05 101.4 98.5 99.9 0.97 Province Central 82.1 82.9 82.5 1.01 106.8 103.1 104.9 0.97 Copperbelt 79.4 82.5 81.1 1.04 100.4 100.7 100.5 1.00 Eastern 63.3 76.5 69.9 1.21 88.9 95.0 92.0 1.07 Luapula 78.8 75.9 77.4 0.96 97.9 92.5 95.2 0.95 Lusaka 84.5 85.9 85.2 1.02 110.2 105.3 107.6 0.96 Muchinga 81.6 81.8 81.7 1.00 107.7 101.7 104.8 0.94 Northern 77.5 80.3 78.9 1.04 101.4 97.2 99.2 0.96 North Western 83.0 80.8 81.8 0.97 108.5 100.0 104.1 0.92 Southern 82.5 87.9 85.2 1.07 109.5 106.8 108.2 0.98 Western 80.5 77.2 78.9 0.96 98.3 95.1 96.8 0.97 Wealth quintile Lowest 68.9 70.2 69.6 1.02 89.9 86.7 88.3 0.96 Second 76.1 81.6 78.8 1.07 101.8 97.8 99.8 0.96 Middle 80.0 85.8 82.8 1.07 105.2 106.9 106.0 1.02 Fourth 84.4 86.1 85.3 1.02 107.6 105.0 106.3 0.98 Highest 86.7 85.4 86.0 0.99 110.4 105.7 107.9 0.96 Total 78.8 81.7 80.3 1.04 102.7 100.3 101.5 0.98 SECONDARY SCHOOL Residence Urban 58.0 58.5 58.3 1.01 91.1 83.2 86.9 0.91 Rural 26.9 26.9 26.9 1.00 41.1 35.6 38.5 0.87 Province Central 34.5 35.8 35.2 1.04 53.6 47.8 50.6 0.89 Copperbelt 56.5 62.6 59.7 1.11 93.6 86.0 89.6 0.92 Eastern 19.5 25.5 22.3 1.31 36.2 36.1 36.2 1.00 Luapula 36.3 26.7 31.9 0.74 56.5 41.0 49.4 0.73 Lusaka 54.4 53.4 53.9 0.98 79.8 76.1 77.8 0.95 Muchinga 32.4 28.7 30.6 0.89 47.6 40.9 44.3 0.86 Northern 31.9 25.9 28.9 0.81 49.5 34.7 42.0 0.70 North Western 42.0 39.5 40.8 0.94 63.2 55.7 59.3 0.88 Southern 33.0 37.3 35.0 1.13 46.2 49.8 47.8 1.08 Western 35.6 33.8 34.6 0.95 55.3 44.1 49.1 0.80 Wealth quintile Lowest 15.0 13.3 14.1 0.89 27.4 16.6 21.7 0.60 Second 23.5 24.7 24.0 1.05 35.1 30.8 33.1 0.88 Middle 30.7 32.8 31.7 1.07 47.2 43.0 45.3 0.91 Fourth 50.5 47.4 49.0 0.94 75.0 68.2 71.6 0.91 Highest 67.8 70.6 69.3 1.04 107.8 100.8 104.0 0.94 Total 39.3 41.3 40.3 1.05 61.1 57.3 59.2 0.94 1 The NAR for primary school is the percentage of the primary-school age (7-13 years) population that is attending primary school. The NAR for secondary school is the percentage of the secondary-school age (14-18 years) population that is attending secondary school. By definition the NAR cannot exceed 100 percent. 2 The GAR for primary school is the total number of primary school students, expressed as a percentage of the official primary-school- age population. The GAR for secondary school is the total number of secondary school students, expressed as a percentage of the official secondary-school-age population. If there are significant numbers of overage and underage students at a given level of schooling, the GAR can exceed 100 percent. 3 The Gender Parity Index for primary school is the ratio of the primary school NAR (GAR) for females to the NAR (GAR) for males. The Gender Parity Index for secondary school is the ratio of the secondary school NAR (GAR) for females to the NAR (GAR) for males. Figure 2.2 shows the age-specific attendance rates (ASAR) for the population age 5 to 24 years—that is, the percentage of a given age cohort that attends school, regardless of the level attended (primary, secondary, or higher). The ASAR rises up to age 11 and then declines gradually, with steeper declines observed at older ages. Females are more likely than males to be in school up to age 13, after which males are substantially more likely to attend school than females. Housing Characteristics and Household Population • 31 Figure 2.2 Age-specific attendance rates of the de facto population 5 to 24 years 0 10 20 30 40 50 60 70 80 90 100 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 Percentage Age Male Female ZDHS 2013-14 Characteristics of Respondents • 33 CHARACTERISTICS OF RESPONDENTS 3 he purpose of this chapter is to create a demographic and socioeconomic profile of the respondents interviewed in the 2013-14 ZDHS. This information helps in the interpretation of findings presented later in the report and provides an indication of the representativeness of the survey. The chapter begins by describing basic background characteristics, including age, marital status, religion, ethnicity, and wealth status. It then provides more detailed information on education, media exposure, employment, and tobacco use. Throughout this report, numbers in tables reflect weighted numbers. Percentages based on 25 to 49 unweighted cases are shown in parentheses, and percentages based on fewer than 25 unweighted cases are suppressed and replaced with an asterisk, to caution readers when interpreting data that a percentage based on fewer than 50 cases may not be statistically reliable.1 3.1 CHARACTERISTICS OF SURVEY RESPONDENTS Table 3.1 shows the background characteristics of the 16,411 women and 13,530 men age 15-49 interviewed in the 2013-14 ZDHS. A high proportion of women (40 percent) and men (42 percent) are in the 15-24 age group. The proportion of women and men in each age group decreases with increasing age, reflecting the comparatively young age structure of the population in Zambia. The vast majority of women (80 percent) and men (78 percent) are Protestant. Eighteen percent of women and 20 percent of men are Catholic, and less than 1 percent each of women and men are Muslim. Table 3.1 shows that about three in ten women (28 percent) and more than four in ten men (44 percent) have never been married. The majority of women (60 percent) and men (51 percent) are currently married; less than 1 percent each are cohabiting with someone as if married. The data further show that female respondents are more likely than male respondents to be divorced or separated (9 percent versus 4 percent) or widowed (4 percent versus less than 1 percent). More than half of women and men (54 percent 1 Parentheses are used if mortality rates are based on 250 to 499 children exposed to the risk of mortality in any of the component rates; mortality rates are suppressed if they are based on fewer than 250 children exposed to the risk of mortality in any of the component rates. T Key Findings • Eight percent of women and 4 percent of men age 15-49 have no education, a slight decrease from the figures of 10 percent and 5 percent reported in the 2007 ZDHS. Forty-five percent of women and 57 percent of men have a secondary education or higher. • About seven in ten women (68 percent) and more than eight in ten men (83 percent) in Zambia are literate. • Twelve percent of women and 22 percent of men age 15-49 are exposed to three types of mass media (newspaper, television, and radio) at least once a week. Thirty-four percent of women and 22 percent of men are not exposed to any of these mass media. • Forty-nine percent of women and 73 percent of men age 15-49 were employed at the time of the survey. • The agricultural sector remains the primary employer in Zambia, with 48 percent of women and 49 percent of men engaged in agricultural occupations. 34 • Characteristics of Respondents and 53 percent, respectively) live in rural areas. By province, the largest proportion of female and male respondents (20 percent and 21 percent, respectively) live in Lusaka, while the smallest proportion reside in North Western (4 percent each). Only 8 percent of women and 4 percent of men age 15-49 in Zambia have no formal education (a slight decrease from 10 percent and 5 percent, respectively, in 2007). Forty-seven percent of women and 40 percent of men have a primary education, and 45 percent of women and 57 percent of men have a secondary education or higher. High dropout rates among girls at the secondary level may explain some of the differences in educational attainment between women and men. The government of Zambia has taken measures to enhance girls’ retention rates in school. One such measure allows girls who drop out of school due to pregnancy to return and continue their education after they have delivered. Table 3.1 Background characteristics of respondents Percent distribution of women and men age 15-49 by selected background characteristics, Zambia 2013-14 Women Men Background characteristic Weighted percent Weighted number Unweighted number Weighted percent Weighted number Unweighted number Age 15-19 22.1 3,625 3,686 24.6 3,337 3,344 20-24 18.3 3,006 3,040 17.2 2,335 2,306 25-29 17.1 2,813 2,789 14.3 1,944 1,934 30-34 15.1 2,475 2,435 14.2 1,927 1,894 35-39 12.2 2,009 1,975 12.3 1,664 1,671 40-44 8.9 1,464 1,466 10.2 1,384 1,387 45-49 6.2 1,018 1,020 7.1 970 994 Religion Catholic 18.2 2,988 2,895 19.7 2,671 2,650 Protestant 80.4 13,191 13,298 78.2 10,599 10,592 Muslim 0.6 101 79 0.8 105 96 Other 0.6 94 98 1.0 136 137 Missing 0.2 38 41 0.4 50 55 Marital status Never married 27.9 4,572 4,753 44.1 5,985 5,908 Married 59.5 9,759 9,552 51.4 6,965 7,020 Living together 0.6 100 97 0.5 70 80 Divorced/separated 8.6 1,406 1,438 3.6 488 476 Widowed 3.5 574 571 0.4 54 46 Residence Urban 46.2 7,585 7,871 46.6 6,326 6,337 Rural 53.8 8,826 8,540 53.4 7,235 7,193 Province Central 8.9 1,467 1,401 8.5 1,153 1,088 Copperbelt 17.3 2,836 1,770 17.7 2,395 1,488 Eastern 11.8 1,930 2,035 12.6 1,710 1,820 Luapula 7.0 1,143 1,585 6.3 855 1,259 Lusaka 19.9 3,266 1,913 21.0 2,844 1,722 Muchinga 5.3 868 1,455 5.0 680 1,144 Northern 7.3 1,200 1,580 6.9 929 1,301 North Western 4.3 713 1,570 4.1 557 1,234 Southern 12.2 2,007 1,732 13.1 1,771 1,548 Western 6.0 980 1,370 4.9 668 926 Education No education 8.4 1,375 1,360 3.7 500 492 Primary 46.8 7,685 7,658 39.6 5,365 5,376 Secondary 39.7 6,521 6,546 49.0 6,638 6,604 More than secondary 5.1 830 847 7.8 1,058 1,058 Wealth quintile Lowest 17.4 2,859 2,838 15.0 2,038 2,102 Second 17.4 2,861 3,000 18.1 2,448 2,606 Middle 18.8 3,077 3,491 18.8 2,547 2,834 Fourth 21.4 3,510 3,442 23.0 3,124 2,987 Highest 25.0 4,103 3,640 25.1 3,405 3,001 Total 15-49 100.0 16,411 16,411 100.0 13,561 13,530 50-59 na na na na 1,212 1,243 Total 15-59 na na na na 14,773 14,773 Note: Education categories refer to the highest level of education attended, whether or not that level was completed. na = Not applicable Characteristics of Respondents • 35 3.2 EDUCATIONAL ATTAINMENT Educational attainment is one of the most influential factors affecting people’s knowledge, attitudes, and behaviours in various facets of life. Tables 3.2.1 and 3.2.2 show the distribution of women and men age 15-49, respectively, by their educational attainment, according to background characteristics. Table 3.2.1 shows that 8 percent of women have no education, 31 percent have only some primary education, 16 percent have completed primary school, 32 percent have some secondary education, 8 percent have completed secondary school, and 5 percent have more than a secondary education. The proportion of women with no education increases steadily with age, from 2 percent among those age 15-19 to 16 percent among those age 45-49. Women who reside in rural areas are much more likely than urban women to have no education (13 percent versus 3 percent) or some primary education (43 percent versus 16 percent). By contrast, women in urban areas are six times as likely as those in rural areas to have a secondary education or higher (24 percent versus 4 percent). Among provinces, the percentage of women with no education is highest in Eastern (18 percent) and lowest in Copperbelt (3 percent). Conversely, Copperbelt has the highest percentage of women with more than a secondary education (10 percent), while Eastern and Northern have the lowest percentage (1 percent each). Women’s educational attainment is directly related to their economic status. For example, 21 percent of women in the highest wealth quintile have completed secondary school and 17 percent have more than a secondary education, as compared with 1 percent or less of women in the lowest two quintiles. Table 3.2.1 shows that women have completed a median of 6.6 years of schooling. Median number of years of schooling completed is higher among women age 15-19 (7.3) and age 20-24 (7.9) than among women age 40-49 (5.8). Urban women have completed a median of 8.2 years, as compared with 5.5 years among rural women. Median number of years of schooling is highest among women from Copperbelt (8.2) and lowest among women from Eastern (4.8). The median increases with increasing wealth, from 4.0 years in the lowest quintile to 9.0 years in the highest quintile. A similar educational attainment pattern is found among men (Table 3.2.2). However, men are more educated than women in all categories. Overall, 4 percent of men age 15-49 have no education, 23 percent have some primary education, 35 percent have some secondary education, and 22 percent have a secondary education or higher. Men age 45-49 are more likely to have no education (7 percent) than men age 15-24 (2 percent). Men from urban areas have higher levels of educational attainment than their rural counterparts. Thirty-seven percent of urban men have a secondary education or higher (as compared with 8 percent of rural men), and only 1 percent have no formal education (as compared with 6 percent of their rural counterparts). Overall, men age 15-49 have completed a median of 7.6 years of schooling. Median number of years of schooling is highest among men age 20-24 (8.7), urban men (8.9 years), men in Lusaka (8.9), and men in the highest wealth quintile (11.1). 36 • Characteristics of Respondents Table 3.2.1 Educational attainment: Women Percent distribution of women age 15-49 by highest level of schooling attended or completed, and median years completed, according to background characteristics, Zambia 2013-14 Highest level of schooling Total Median years completed Number of women Background characteristic No education Some primary Completed primary1 Some secondary Completed secondary2 More than secondary Age 15-24 3.1 23.6 13.6 46.2 11.0 2.5 100.0 7.5 6,631 15-19 1.9 23.8 14.8 52.9 6.3 0.4 100.0 7.3 3,625 20-24 4.6 23.3 12.1 38.2 16.7 5.1 100.0 7.9 3,006 25-29 9.9 32.5 13.9 24.9 10.6 8.2 100.0 6.5 2,813 30-34 10.8 35.2 17.3 22.3 6.0 8.4 100.0 6.2 2,475 35-39 12.2 38.8 18.4 21.4 3.8 5.3 100.0 5.9 2,009 40-44 14.5 37.3 21.4 18.6 3.2 4.9 100.0 5.8 1,464 45-49 16.2 35.6 24.0 16.2 3.3 4.7 100.0 5.8 1,018 Residence Urban 3.4 16.2 15.2 41.7 14.1 9.4 100.0 8.2 7,585 Rural 12.7 43.2 16.9 22.9 3.0 1.3 100.0 5.5 8,826 Province Central 8.8 31.4 18.4 30.4 7.2 3.9 100.0 6.5 1,467 Copperbelt 2.7 17.9 15.0 41.5 13.2 9.7 100.0 8.2 2,836 Eastern 18.2 42.7 13.2 20.5 4.0 1.4 100.0 4.8 1,930 Luapula 10.9 47.4 14.7 21.6 4.0 1.5 100.0 5.1 1,143 Lusaka 4.9 16.4 16.2 40.6 13.0 8.9 100.0 8.1 3,266 Muchinga 9.8 43.9 14.4 25.1 4.8 1.9 100.0 5.7 868 Northern 9.7 49.0 14.2 23.5 2.4 1.2 100.0 5.1 1,200 North Western 11.4 36.5 13.0 27.4 7.7 4.0 100.0 6.2 713 Southern 5.2 29.6 22.1 33.4 6.0 3.7 100.0 6.7 2,007 Western 15.0 35.5 17.1 22.9 6.4 3.0 100.0 5.9 980 Wealth quintile Lowest 19.4 53.3 14.2 12.8 0.3 0.0 100.0 4.0 2,859 Second 12.5 46.3 18.4 21.5 1.3 0.0 100.0 5.3 2,861 Middle 8.4 37.5 19.3 30.5 3.8 0.5 100.0 6.2 3,077 Fourth 4.6 22.5 19.3 41.3 9.4 3.0 100.0 7.2 3,510 Highest 1.1 6.0 10.8 44.3 20.5 17.3 100.0 9.0 4,103 Total 8.4 30.7 16.1 31.6 8.1 5.1 100.0 6.6 16,411 1 Completed 7th year at the primary level 2 Completed 12th year at the secondary level Characteristics of Respondents • 37 Table 3.2.2 Educational attainment: Men Percent distribution of men age 15-49 by highest level of schooling attended or completed, and median years completed, according to background characteristics, Zambia 2013-14 Highest level of schooling Total Median years completed Number of men Background characteristic No education Some primary Completed primary1 Some secondary Completed secondary2 More than secondary Age 15-24 1.7 20.9 14.5 46.2 13.4 3.3 100.0 7.8 5,672 15-19 1.6 26.8 16.0 49.1 6.1 0.4 100.0 7.1 3,337 20-24 1.9 12.5 12.2 42.1 24.0 7.4 100.0 8.7 2,335 25-29 4.0 21.1 13.6 29.2 21.7 10.4 100.0 8.2 1,944 30-34 5.1 26.3 16.6 25.9 13.6 12.4 100.0 7.2 1,927 35-39 5.7 26.8 16.9 27.5 11.3 11.9 100.0 7.0 1,664 40-44 4.6 26.6 19.9 29.8 9.5 9.6 100.0 6.9 1,384 45-49 6.8 24.6 25.5 23.8 8.7 10.5 100.0 6.7 970 Residence Urban 1.1 9.4 11.9 41.0 22.7 14.0 100.0 8.9 6,326 Rural 6.0 35.4 20.1 30.3 5.7 2.4 100.0 6.4 7,235 Province Central 2.7 27.6 19.8 33.4 11.2 5.4 100.0 6.9 1,153 Copperbelt 1.2 11.7 10.6 43.4 20.2 12.9 100.0 8.7 2,395 Eastern 11.7 39.9 14.6 24.1 6.9 2.8 100.0 5.8 1,710 Luapula 3.9 34.3 19.1 32.7 7.6 2.4 100.0 6.6 855 Lusaka 1.7 9.1 14.0 39.0 21.9 14.3 100.0 8.9 2,844 Muchinga 2.3 30.4 21.3 33.8 7.8 4.3 100.0 6.7 680 Northern 4.0 31.5 19.0 35.2 6.8 3.6 100.0 6.7 929 North Western 4.8 25.2 14.9 36.9 12.5 5.8 100.0 7.4 557 Southern 1.7 25.8 23.0 33.8 10.8 5.0 100.0 6.9 1,771 Western 7.4 34.2 15.7 30.0 8.3 4.4 100.0 6.5 668 Wealth quintile Lowest 9.9 45.3 21.8 20.6 2.3 0.1 100.0 5.6 2,038 Second 6.2 38.3 20.5 31.0 3.9 0.1 100.0 6.2 2,448 Middle 3.4 29.0 21.6 37.7 7.7 0.6 100.0 6.7 2,547 Fourth 1.4 13.9 15.9 44.7 18.0 6.1 100.0 8.3 3,124 Highest 0.4 3.6 6.3 36.7 28.0 24.9 100.0 11.1 3,405 Total 15-49 3.7 23.3 16.3 35.3 13.7 7.8 100.0 7.6 13,561 50-59 4.8 21.5 27.0 27.5 8.6 10.6 100.0 6.9 1,212 Total 15-59 3.8 23.1 17.2 34.7 13.2 8.0 100.0 7.5 14,773 1 Completed 7th grade at the primary level 2 Completed 12th grade at the secondary level 3.3 LITERACY The ability to read is an important personal asset allowing women and men increased opportunities in life. In addition, knowledge of the literacy level of the population can help programme managers, especially those working in health and family planning, decide how to reach women and men with their messages. In the 2013-14 ZDHS, the literacy status of respondents was determined by assessing their ability to read all or part of a simple sentence in any of Zambia’s seven major language groups.2 The literacy test was administered only to respondents who had less than a secondary education. The findings are shown in Tables 3.3.1 and 3.3.2 for women and men, respectively. Table 3.3.1 shows that about seven in ten women age 15-49 (68 percent) in Zambia are literate, an increase from the figure of 64 percent reported in the 2007 ZDHS. The level of literacy is higher among women age 15-24 (77 percent) than among women in the older age groups (59-63 percent), suggesting that younger women have more opportunities for learning. Literacy varies notably by place of residence. Eighty-three percent of women residing in urban areas are literate, as compared with only 54 percent of rural women. Literacy is highest among women in Copperbelt (84 percent) and lowest among those in Luapula (48 percent). Literacy increases substantially with increasing household wealth, ranging from 38 percent among women in the lowest wealth quintile to 93 percent among those in the highest quintile. This finding reaffirms the positive association between economic status and literacy. 2 The major language groups are Bemba, Kaonde, Lozi, Lunda, Luvale, Nyanja, and Tonga. 38 • Characteristics of Respondents Men are more likely to be literate than women (Table 3.3.2). Eighty-three percent of Zambian men age 15-49 are literate, a slight increase from the figure of 82 percent reported in 2007. Literacy patterns among men are similar to those observed for women. Literacy is highest among men age 15-24 (85 percent), urban men (93 percent), and men living in Lusaka (93 percent). Similar to educational attainment, literacy is positively associated with wealth, with men in the lowest quintile having the lowest rate (62 percent) and those in the highest quintile having the highest rate (98 percent). Table 3.3.1 Literacy: Women Percent distribution of women age 15-49 by level of schooling attended and level of literacy, and percentage literate, according to background characteristics, Zambia 2013-14 Secondary school or higher No schooling or primary school Missing Total Percentage literate1 Number of women Background characteristic Can read a whole sentence Can read part of a sentence Cannot read at all No card with required language Blind/ visually impaired Age 15-24 59.7 10.5 7.1 22.1 0.2 0.0 0.5 100.0 77.3 6,631 15-19 59.5 11.7 7.6 20.3 0.2 0.0 0.6 100.0 78.8 3,625 20-24 59.9 9.0 6.5 24.2 0.1 0.0 0.2 100.0 75.4 3,006 25-29 43.7 10.9 8.5 36.5 0.1 0.0 0.2 100.0 63.2 2,813 30-34 36.7 13.3 10.4 38.9 0.5 0.1 0.1 100.0 60.4 2,475 35-39 30.5 17.0 11.2 40.3 0.5 0.2 0.4 100.0 58.7 2,009 40-44 26.8 22.7 10.9 38.8 0.2 0.2 0.4 100.0 60.4 1,464 45-49 24.2 26.1 10.2 38.3 0.4 0.5 0.4 100.0 60.5 1,018 Residence Urban 65.2 9.9 7.7 16.5 0.4 0.0 0.2 100.0 82.8 7,585 Rural 27.3 17.2 9.9 44.9 0.2 0.1 0.5 100.0 54.3 8,826 Province Central 41.5 14.4 12.3 31.6 0.0 0.0 0.3 100.0 68.2 1,467 Copperbelt 64.4 12.5 6.7 15.8 0.4 0.1 0.1 100.0 83.7 2,836 Eastern 26.0 17.0 6.3 50.5 0.0 0.1 0.1 100.0 49.3 1,930 Luapula 27.0 6.7 14.3 51.2 0.1 0.1 0.5 100.0 48.1 1,143 Lusaka 62.5 8.0 9.6 18.9 0.7 0.0 0.3 100.0 80.1 3,266 Muchinga 31.9 15.9 6.7 44.8 0.4 0.1 0.3 100.0 54.4 868 Northern 27.1 13.6 8.4 50.4 0.0 0.1 0.3 100.0 49.1 1,200 North Western 39.1 11.3 10.6 37.9 0.1 0.1 1.0 100.0 60.9 713 Southern 43.1 21.0 7.9 26.7 0.2 0.2 0.8 100.0 72.0 2,007 Western 32.4 23.8 9.6 33.7 0.1 0.2 0.3 100.0 65.8 980 Wealth quintile Lowest 13.1 14.7 9.9 61.6 0.1 0.2 0.5 100.0 37.6 2,859 Second 22.8 18.0 10.9 47.5 0.3 0.1 0.4 100.0 51.7 2,861 Middle 34.8 19.5 10.6 34.4 0.2 0.1 0.4 100.0 64.9 3,077 Fourth 53.6 13.4 10.5 21.9 0.3 0.1 0.2 100.0 77.5 3,510 Highest 82.1 6.4 4.1 6.6 0.4 0.0 0.3 100.0 92.7 4,103 Total 44.8 13.8 8.9 31.8 0.3 0.1 0.3 100.0 67.5 16,411 1 Refers to women who attended secondary school or higher and women who can read a whole sentence or part of a sentence Characteristics of Respondents • 39 Table 3.3.2 Literacy: Men Percent distribution of men age 15-49 by level of schooling attended and level of literacy, and percentage literate, according to background characteristics, Zambia 2013-14 Secondary school or higher No schooling or primary school Missing Total Percentage literate1 Number of men Background characteristic Can read a whole sentence Can read part of a sentence Cannot read at all No card with required language Blind/ visually impaired Age 15-24 62.9 12.4 9.6 14.5 0.3 0.0 0.3 100.0 84.9 5,672 15-19 55.5 14.8 12.0 16.9 0.3 0.1 0.4 100.0 82.3 3,337 20-24 73.4 8.9 6.3 11.1 0.1 0.0 0.2 100.0 88.6 2,335 25-29 61.2 11.3 8.4 18.4 0.5 0.0 0.2 100.0 81.0 1,944 30-34 52.0 16.8 11.6 19.3 0.0 0.0 0.3 100.0 80.4 1,927 35-39 50.6 19.9 9.8 19.2 0.1 0.2 0.1 100.0 80.3 1,664 40-44 48.9 21.8 11.9 16.9 0.2 0.0 0.3 100.0 82.6 1,384 45-49 43.1 25.4 13.0 17.9 0.3 0.1 0.3 100.0 81.5 970 Residence Urban 77.6 8.7 6.9 6.2 0.2 0.1 0.3 100.0 93.2 6,326 Rural 38.5 21.8 13.2 26.0 0.3 0.0 0.3 100.0 73.4 7,235 Province Central 49.9 16.2 14.0 19.5 0.2 0.0 0.2 100.0 80.2 1,153 Copperbelt 76.5 9.4 5.1 8.2 0.6 0.1 0.2 100.0 90.9 2,395 Eastern 33.8 23.8 8.6 33.5 0.1 0.0 0.1 100.0 66.3 1,710 Luapula 42.7 9.7 25.7 21.4 0.3 0.0 0.2 100.0 78.1 855 Lusaka 75.2 8.4 9.5 6.5 0.0 0.0 0.3 100.0 93.2 2,844 Muchinga 46.0 21.1 9.0 23.6 0.0 0.0 0.3 100.0 76.1 680 Northern 45.6 23.5 6.6 23.9 0.0 0.2 0.2 100.0 75.6 929 North Western 55.1 12.5 16.2 15.2 0.0 0.0 1.0 100.0 83.8 557 Southern 49.6 21.7 10.0 17.8 0.5 0.0 0.5 100.0 81.3 1,771 Western 42.7 25.4 11.6 20.0 0.0 0.1 0.2 100.0 79.6 668 Wealth quintile Lowest 23.0 24.6 14.7 37.3 0.1 0.1 0.2 100.0 62.4 2,038 Second 35.0 21.7 15.0 27.5 0.4 0.0 0.5 100.0 71.6 2,448 Middle 45.9 20.9 12.5 19.9 0.5 0.0 0.3 100.0 79.3 2,547 Fourth 68.8 13.4 8.7 8.6 0.1 0.1 0.3 100.0 91.0 3,124 Highest 89.6 4.2 3.9 2.0 0.2 0.0 0.2 100.0 97.6 3,405 Total 15-49 56.8 15.7 10.2 16.8 0.2 0.0 0.3 100.0 82.7 13,561 50-59 46.7 29.2 11.2 11.9 0.5 0.3 0.2 100.0 87.1 1,212 Total 15-59 55.9 16.8 10.3 16.4 0.2 0.1 0.3 100.0 83.0 14,773 1 Refers to men who attended secondary school or higher and men who can read a whole sentence or part of a sentence 3.4 EXPOSURE TO MASS MEDIA In the 2013-14 ZDHS, exposure to media was assessed by asking respondents whether they listened to the radio, watched television, or read a newspaper or magazine at least once a week. This information is useful for programme managers and planners in determining which media are most effective in disseminating health-related information to targeted audiences. Tables 3.4.1 and 3.4.2 show the percentage of women and men who were exposed to different types of media at least once a week by background characteristics. Overall, 12 percent of women and 22 percent of men have access to all three types of media at least once a week. Radio is the most commonly used form of mass media among both women and men (51 percent and 67 percent, respectively), followed by television (40 percent and 46 percent, respectively). Twenty-two percent of women and 34 percent of men report reading a newspaper at least once a week. About one-third of women (34 percent) and one-fifth of men (22 percent) have no access to any of the three specified media at least once a week. 40 • Characteristics of Respondents Table 3.4.1 Exposure to mass media: Women Percentage of women age 15-49 who are exposed to specific media on a weekly basis, by background characteristics, Zambia 2013- 14 Background characteristic Reads a newspaper at least once a week Watches television at least once a week Listens to the radio at least once a week Accesses all three media at least once a week Accesses none of the three media at least once a week Number of women Age 15-19 25.8 43.1 49.1 11.7 30.9 3,625 20-24 23.4 43.5 51.6 12.5 32.0 3,006 25-29 21.0 41.7 52.3 11.8 33.6 2,813 30-34 19.7 39.8 52.1 11.7 34.8 2,475 35-39 18.7 37.4 50.8 10.9 37.2 2,009 40-44 18.6 34.2 51.4 10.3 38.0 1,464 45-49 19.8 31.7 50.3 10.6 39.9 1,018 Residence Urban 29.8 69.9 60.0 20.7 17.1 7,585 Rural 14.8 14.7 43.4 3.8 48.7 8,826 Province Central 22.9 25.1 51.9 7.5 36.3 1,467 Copperbelt 24.1 65.4 56.6 16.2 20.3 2,836 Eastern 25.9 22.0 53.1 8.4 36.6 1,930 Luapula 13.9 12.4 37.0 3.1 55.9 1,143 Lusaka 31.9 76.6 61.8 24.8 15.3 3,266 Muchinga 11.2 23.5 50.7 5.6 41.3 868 Northern 9.0 18.0 44.3 3.5 50.1 1,200 North Western 17.9 20.8 44.9 5.5 44.6 713 Southern 21.5 29.3 47.2 8.4 38.7 2,007 Western 8.1 15.8 31.5 2.5 60.1 980 Education No education 1.4 13.3 35.3 0.3 60.0 1,375 Primary 10.2 24.2 44.2 2.8 45.3 7,685 Secondary 33.4 58.5 59.6 19.0 19.4 6,521 More than secondary 70.4 89.9 73.9 53.0 2.9 830 Wealth quintile Lowest 7.0 3.2 23.3 0.4 72.0 2,859 Second 12.3 6.1 44.8 0.9 49.1 2,861 Middle 16.7 16.7 51.3 3.4 39.9 3,077 Fourth 22.1 56.7 56.7 11.8 22.0 3,510 Highest 42.0 93.4 69.8 32.8 3.3 4,103 Total 21.7 40.2 51.1 11.6 34.1 16,411 There are no major variations in mass media exposure by age among women. Among men, those in the youngest age group are less likely to be exposed to all three media weekly (15 percent) than those in the older age groups (22-25 percent). There are wide gaps in exposure to mass media by place of residence. For example, 21 percent of urban women are exposed to all three media at least once a week, as compared with only 4 percent of rural women. Women and men residing in Lusaka are most likely to be exposed to all three media on a weekly basis (25 percent and 41 percent, respectively). Women in Luapula and Western (3 percent each) and men in Northern and Western (4 percent each) are least likely to be exposed to all three media each week. Exposure to mass media increases with increasing educational attainment among both women and men. Less than 1 percent of women and men with no education are exposed to all three media at least once a week, as compared with 53 percent of women and 67 percent of men with more than a secondary education. A similar pattern is observed in the relationship between mass media exposure and wealth. For example, less than 1 percent of men in the lowest wealth quintile are exposed weekly to all three mass media, compared with 54 percent of men in the highest quintile. Characteristics of Respondents • 41 Table 3.4.2 Exposure to mass media: Men Percentage of men age 15-49 who are exposed to specific media on a weekly basis, by background characteristics, Zambia 2013-14 Background characteristic Reads a newspaper at least once a week Watches television at least once a week Listens to the radio at least once a week Accesses all three media at least once a week Accesses none of the three media at least once a week Number of men Age 15-19 27.8 46.3 60.2 15.3 24.7 3,337 20-24 37.1 52.4 67.6 24.9 20.2 2,335 25-29 36.0 45.9 67.7 23.3 23.0 1,944 30-34 34.7 47.1 67.6 22.8 21.5 1,927 35-39 36.0 44.3 71.1 24.6 20.4 1,664 40-44 33.2 41.0 68.9 21.7 23.2 1,384 45-49 33.8 39.9 71.7 22.7 22.1 970 Residence Urban 51.3 76.1 75.8 39.5 8.8 6,326 Rural 18.0 20.0 58.6 5.7 34.2 7,235 Province Central 28.6 38.2 67.4 16.8 22.7 1,153 Copperbelt 46.7 72.3 77.5 36.3 8.5 2,395 Eastern 33.5 27.4 65.1 10.9 23.8 1,710 Luapula 11.7 20.4 50.8 5.6 45.0 855 Lusaka 52.1 79.3 74.3 41.2 9.4 2,844 Muchinga 23.4 24.8 61.6 10.0 29.8 680 Northern 10.1 16.5 45.1 4.1 48.7 929 North Western 38.0 23.7 61.4 11.7 27.2 557 Southern 23.2 34.8 69.4 13.8 22.9 1,771 Western 10.5 17.7 50.4 3.9 43.8 668 Education No education 1.8 14.4 51.3 0.0 43.1 500 Primary 13.9 25.1 57.1 5.0 34.7 5,365 Secondary 44.0 58.5 72.7 29.1 14.1 6,638 More than secondary 82.3 90.3 84.3 67.2 1.8 1,058 Wealth quintile Lowest 12.1 6.1 37.2 0.5 55.4 2,038 Second 15.3 10.9 59.8 2.4 34.5 2,448 Middle 18.7 25.2 67.7 6.0 25.1 2,547 Fourth 40.5 64.7 75.5 27.0 11.2 3,124 Highest 64.2 94.2 80.3 54.2 1.9 3,405 Total 15-49 33.5 46.2 66.7 21.5 22.3 13,561 50-59 34.6 38.3 73.3 19.7 19.7 1,212 Total 15-59 33.6 45.5 67.2 21.3 22.1 14,773 3.5 EMPLOYMENT STATUS The 2013-14 ZDHS asked respondents a number of questions regarding their employment status, including whether they were working in the seven days preceding the survey and, if not, whether they had been employed in the 12 months preceding the survey. Accurate assessment of employment status can be difficult because certain types of work, especially on family farms, in family businesses, or in the informal sector, are often not perceived as employment and hence not reported as such. To avoid underestimating employment status, respondents were asked several questions to probe for their status and to ensure complete coverage of employment in both the formal and informal sectors. The results are shown in Tables 3.5.1 and 3.5.2 for women and men, respectively. Table 3.5.1 and Figure 3.1 show that 49 percent of women were employed at the time of the survey, 3 percent were not employed but had worked sometime in the past 12 months, and 48 percent were not employed during the 12 months preceding the survey. Current employment among women increases with age, from 19 percent among those age 15-19 to 69-70 percent among those age 40-49. Women who are divorced, separated, or widowed are most likely to be currently employed (69 percent), while women who have never been married are least likely to be employed (26 percent). The proportion of women who are currently employed increases steadily with number of living children, from 23 percent among those with no children to 65 percent among those with five or more children. With respect to residence, rural women were more likely than urban women to be employed at the time of the survey (53 percent versus 43 percent). There are variations by province, with current 42 • Characteristics of Respondents employment being highest among women in Northern (69 percent) and lowest among those in Eastern (38 percent). Among women, there is no consistent relationship between education and current employment. Women with more than a secondary education are most likely to be currently employed (70 percent) and those with a secondary education least likely (38 percent). The proportion of women who are currently employed decreases with increasing wealth, from 58 percent among those in the lowest wealth quintile to 41 percent among those in the highest quintile. Table 3.5.2 shows that about three-quarters of men age 15-49 (73 percent) were employed at the time of the survey, 7 percent were not employed but had worked at some time in the past 12 months, and 20 percent were not employed during the 12 months preceding the survey. Variations in men’s current employment by background characteristics are similar to those observed among women. The percentage of men employed at the time of the survey is lower among those age 15-19 (37 percent) and age 20-24 (65 percent) than among those in the older age groups (87-92 percent). Married or cohabiting men are most likely to be currently employed (91 percent), while men who have never been married are least likely to be employed (50 percent). Similar to women, men with no children are less likely to be currently employed (51 percent) than men with one or more children (90-92 percent). Current employment is higher among rural men than urban men (75 percent versus 70 percent). By province, current employment ranges from 53 percent in Eastern to 86 percent in Southern. Men with more than a secondary education are most likely to be currently employed (85 percent), and those with a secondary education are least likely (68 percent). Men in the highest wealth quintile are less likely to be currently employed (64 percent) than men in the lower quintiles (73-79 percent). Figure 3.1 Women’s employment status (past 12 months) ZDHS 2013-14 Currently employed 49% Not currently employed, but worked in last 12 months 3% Did not work in last 12 months 48% Characteristics of Respondents • 43 Table 3.5.1 Employment status: Women Percent distribution of women age 15-49 by employment status, according to background characteristics, Zambia 2013-14 Employed in the 12 months preceding the survey Not employed in the 12 months preceding the survey Total Number of women Background characteristic Currently employed1 Not currently employed Age 15-19 19.4 2.5 78.1 100.0 3,625 20-24 39.6 3.8 56.6 100.0 3,006 25-29 55.6 3.1 41.3 100.0 2,813 30-34 61.0 4.2 34.8 100.0 2,475 35-39 64.9 3.3 31.9 100.0 2,009 40-44 70.0 3.6 26.3 100.0 1,464 45-49 69.3 3.2 27.5 100.0 1,018 Marital status Never married 25.6 2.2 72.3 100.0 4,572 Married or living together 55.5 3.8 40.7 100.0 9,859 Divorced/separated/widowed 68.7 3.7 27.5 100.0 1,980 Number of living children 0 23.4 2.4 74.2 100.0 4,112 1-2 49.7 3.7 46.7 100.0 4,821 3-4 59.1 3.4 37.5 100.0 3,750 5+ 65.2 3.8 30.9 100.0 3,727 Residence Urban 43.4 2.1 54.5 100.0 7,585 Rural 53.4 4.4 42.2 100.0 8,826 Province Central 40.3 6.1 53.5 100.0 1,467 Copperbelt 40.6 2.0 57.4 100.0 2,836 Eastern 37.8 5.6 56.7 100.0 1,930 Luapula 66.0 0.9 33.0 100.0 1,143 Lusaka 41.3 1.5 57.2 100.0 3,266 Muchinga 58.0 3.9 38.1 100.0 868 Northern 68.8 2.3 28.8 100.0 1,200 North Western 56.5 6.6 36.8 100.0 713 Southern 52.2 5.0 42.8 100.0 2,007 Western 65.9 2.4 31.7 100.0 980 Education No education 55.5 4.9 39.6 100.0 1,375 Primary 54.3 3.5 42.2 100.0 7,685 Secondary 38.1 2.9 59.0 100.0 6,521 More than secondary 69.9 2.8 27.3 100.0 830 Wealth quintile Lowest 57.7 3.2 39.0 100.0 2,859 Second 55.0 4.7 40.3 100.0 2,861 Middle 50.8 4.3 44.9 100.0 3,077 Fourth 43.5 3.0 53.5 100.0 3,510 Highest 41.2 2.0 56.8 100.0 4,103 Total 48.8 3.3 47.9 100.0 16,411 1 “Currently employed” is defined as having done work in the past seven days. Includes persons who did not work in the past seven days but who are regularly employed and were absent from work for leave, illness, vacation, or any other such reason. 44 • Characteristics of Respondents Table 3.5.2 Employment status: Men Percent distribution of men age 15-49 by employment status, according to background characteristics, Zambia 2013-14 Employed in the 12 months preceding the survey Not employed in the 12 months preceding the survey Total Number of men Background characteristic Currently employed1 Not currently employed Age 15-19 36.5 9.0 54.5 100.0 3,337 20-24 65.1 9.2 25.7 100.0 2,335 25-29 87.1 6.3 6.6 100.0 1,944 30-34 92.2 5.0 2.9 100.0 1,927 35-39 91.2 5.1 3.7 100.0 1,664 40-44 91.9 5.5 2.4 100.0 1,384 45-49 91.9 4.8 3.3 100.0 970 Marital status Never married 50.0 8.4 41.6 100.0 5,985 Married or living together 91.4 5.7 2.9 100.0 7,035 Divorced/separated/widowed 85.4 7.3 7.3 100.0 542 Number of living children 0 50.8 8.6 40.6 100.0 6,083 1-2 89.7 5.8 4.4 100.0 2,689 3-4 92.1 4.7 3.1 100.0 2,146 5+ 91.0 6.1 2.9 100.0 2,644 Residence Urban 70.2 3.9 25.9 100.0 6,326 Rural 75.3 9.6 15.1 100.0 7,235 Province Central 76.4 1.5 22.1 100.0 1,153 Copperbelt 70.4 5.3 24.3 100.0 2,395 Eastern 52.8 27.4 19.8 100.0 1,710 Luapula 82.6 2.2 15.2 100.0 855 Lusaka 70.0 2.8 27.2 100.0 2,844 Muchinga 77.6 6.6 15.7 100.0 680 Northern 81.4 3.0 15.6 100.0 929 North Western 76.1 3.5 20.3 100.0 557 Southern 85.8 5.6 8.6 100.0 1,771 Western 74.1 5.6 20.2 100.0 668 Education No education 76.0 15.4 8.6 100.0 500 Primary 76.3 8.7 15.0 100.0 5,365 Secondary 68.0 5.6 26.4 100.0 6,638 More than secondary 85.2 2.6 12.2 100.0 1,058 Wealth quintile Lowest 73.4 11.8 14.8 100.0 2,038 Second 78.9 8.6 12.5 100.0 2,448 Middle 77.0 7.5 15.5 100.0 2,547 Fourth 73.9 5.4 20.7 100.0 3,124 Highest 64.3 3.8 31.8 100.0 3,405 Total 15-49 72.9 6.9 20.1 100.0 13,561 50-59 86.6 8.0 5.4 100.0 1,212 Total 15-59 74.0 7.0 18.9 100.0 14,773 1 “Currently employed” is defined as having done work in the past seven days. Includes persons who did not work in the past seven days but who are regularly employed and were absent from work for leave, illness, vacation, or any other such reason. 3.6 OCCUPATION Respondents who were currently employed or had worked in the 12 months preceding the survey were asked to specify their occupation. The results for women and men are presented in Table 3.6.1 and Table 3.6.2, respectively, according to background characteristics. The findings show that the agricultural sector remains the primary employer in Zambia, with 48 percent of women and 49 percent of men engaged in agricultural occupations. Sales and services are the second largest sector (40 percent of women and 18 percent of men). Six percent of women are in professional, technical, and managerial fields, and 2 percent are engaged in skilled or unskilled manual labour. Men are more likely than women to be employed as manual labourers; 15 percent are engaged in skilled manual labour and 6 percent in unskilled manual labour. Characteristics of Respondents • 45 Table 3.6.1 Occupation: Women Percent distribution of women age 15-49 employed in the 12 months preceding the survey by occupation, according to background characteristics, Zambia 2013-14 Background characteristic Professional/ technical/ managerial Clerical Sales and services Skilled manual Unskilled manual Agriculture Missing Total Number of women Age 15-19 1.2 0.2 27.6 0.9 0.0 68.7 1.5 100.0 794 20-24 3.2 1.4 41.1 1.6 0.2 49.6 3.0 100.0 1,303 25-29 7.4 1.9 42.1 1.9 0.4 44.1 2.2 100.0 1,651 30-34 8.9 2.1 41.6 2.2 0.0 41.6 3.6 100.0 1,614 35-39 5.5 1.2 43.7 2.7 0.0 42.5 4.5 100.0 1,369 40-44 5.2 0.9 39.5 2.8 0.5 48.5 2.6 100.0 1,078 45-49 4.8 0.5 37.1 2.9 0.5 50.4 3.9 100.0 738 Marital status Never married 9.3 3.5 40.4 2.3 0.0 40.9 3.5 100.0 1,268 Married or living together 5.1 0.8 37.5 2.2 0.2 51.6 2.7 100.0 5,846 Divorced/separated/widowed 4.5 1.8 49.9 1.9 0.5 37.2 4.2 100.0 1,434 Number of living children 0 8.9 3.3 38.2 2.7 0.0 43.6 3.3 100.0 1,060 1-2 8.7 2.3 42.9 1.7 0.4 40.5 3.4 100.0 2,571 3-4 5.7 0.6 45.3 2.5 0.1 42.7 3.2 100.0 2,344 5+ 1.2 0.3 33.0 2.0 0.2 60.8 2.5 100.0 2,574 Residence Urban 11.1 3.0 69.3 3.6 0.3 8.4 4.3 100.0 3,450 Rural 1.9 0.3 20.2 1.2 0.1 74.1 2.2 100.0 5,098 Province Central 4.2 1.5 43.1 1.9 0.0 46.6 2.6 100.0 681 Copperbelt 11.7 1.3 60.3 3.8 0.3 18.1 4.5 100.0 1,209 Eastern 2.4 0.9 24.1 1.7 0.0 66.6 4.3 100.0 836 Luapula 1.8 0.3 27.9 0.9 0.4 67.0 1.6 100.0 765 Lusaka 11.1 4.5 71.3 4.0 0.5 4.6 4.1 100.0 1,397 Muchinga 2.4 0.4 21.4 1.1 0.1 72.6 2.1 100.0 537 Northern 1.6 0.2 20.4 1.2 0.2 75.7 0.7 100.0 854 North Western 4.2 0.8 24.6 1.0 0.2 65.9 3.3 100.0 450 Southern 4.5 0.7 34.4 1.5 0.1 56.2 2.6 100.0 1,149 Western 4.0 0.2 28.4 1.3 0.2 62.5 3.4 100.0 669 Education No education 0.1 0.0 27.7 0.9 0.2 69.4 1.8 100.0 830 Primary 0.1 0.0 36.1 1.6 0.2 59.3 2.6 100.0 4,442 Secondary 3.2 1.8 56.1 3.3 0.2 31.8 3.5 100.0 2,673 More than secondary 64.8 10.7 14.3 2.3 0.6 0.9 6.3 100.0 603 Wealth quintile Lowest 0.0 0.1 14.4 0.7 0.0 82.4 2.3 100.0 1,742 Second 0.3 0.0 21.7 1.2 0.2 74.5 2.0 100.0 1,707 Middle 1.2 0.2 39.5 1.4 0.2 55.0 2.4 100.0 1,697 Fourth 5.5 0.7 67.0 2.2 0.1 20.9 3.6 100.0 1,632 Highest 20.8 5.6 58.2 5.1 0.5 4.8 5.0 100.0 1,771 Total 5.7 1.4 40.0 2.1 0.2 47.6 3.1 100.0 8,548 Type of occupation varies by background characteristics. Respondents age 15-19 (69 percent of women and 71 percent of men) are more likely to work in agriculture than older respondents. As expected, rural women and men are substantially more likely to work in agriculture (74 percent and 77 percent, respectively) than their urban counterparts (8 percent and 12 percent, respectively). The opposite is true for the other types of occupations, especially sales and services, the sector that employs the majority of urban women (69 percent) and men (32 percent). Similarly, a much higher percentage of respondents living in rural provinces such as Luapula and Northern work in agriculture, while respondents in urban provinces such as Copperbelt and Lusaka are more likely to work in other occupations such as sales and services, skilled manual labour, or professional, technical, or managerial jobs. Women and men with more than a secondary education (including a vocational or technical school education) are most likely to work in the professional, technical, and managerial sector (65 percent of women and 46 percent of men). By contrast, respondents with no education are most likely to work in the agricultural sector (69 percent of women and 75 percent of men). The reason is probably that women and men with no education have few employment opportunities other than in the agricultural sector, while it is easier for educated women and men to obtain employment in the nonagricultural sector. 46 • Characteristics of Respondents More than eight in ten employed women (82 percent) and men (85 percent) in the lowest wealth quintile work in agriculture, whereas only 5 percent of women and 8 percent of men in the highest quintile do so. Women and men in the highest wealth quintile are most likely to be employed in sales and services (58 percent and 27 percent, respectively). Table 3.6.2 Occupation: Men Percent distribution of men age 15-49 employed in the 12 months preceding the survey by occupation, according to background characteristics, Zambia 2013-14 Background characteristic Professional/ technical/ managerial Clerical Sales and services Skilled manual Unskilled manual Agriculture Missing Total Number of men Age 15-19 1.2 0.2 12.5 9.8 1.6 70.7 4.1 100.0 1,518 20-24 2.7 1.1 21.2 14.6 5.7 47.7 7.0 100.0 1,734 25-29 5.9 1.2 20.5 16.7 7.7 42.2 5.8 100.0 1,815 30-34 6.8 1.4 20.5 16.2 6.6 40.6 7.8 100.0 1,872 35-39 8.7 0.9 18.5 15.1 7.5 43.3 6.0 100.0 1,602 40-44 6.5 0.9 17.9 15.8 5.3 48.5 5.1 100.0 1,349 45-49 7.9 1.0 14.1 14.7 4.5 51.3 6.4 100.0 937 Marital status Never married 4.4 1.3 19.2 14.3 3.5 50.2 7.0 100.0 3,495 Married or living together 6.1 0.9 17.5 14.6 7.0 48.4 5.5 100.0 6,832 Divorced/separated/widowed 5.3 0.0 22.5 21.0 4.5 38.5 8.1 100.0 502 Number of living children 0 4.9 1.3 18.7 14.0 3.6 50.6 6.9 100.0 3,615 1-2 8.2 1.0 22.1 16.9 8.2 37.7 6.0 100.0 2,569 3-4 6.2 1.1 18.9 16.5 8.4 42.3 6.7 100.0 2,078 5+ 3.2 0.5 13.6 12.5 4.2 61.4 4.6 100.0 2,566 Residence Urban 9.1 2.0 32.0 24.0 10.6 11.9 10.3 100.0 4,686 Rural 2.8 0.2 7.9 7.7 2.0 76.5 2.9 100.0 6,143 Province Central 4.7 0.7 12.3 10.8 3.0 63.2 5.3 100.0 898 Copperbelt 7.9 1.2 25.2 22.5 9.8 22.1 11.3 100.0 1,812 Eastern 2.8 0.5 12.4 10.5 3.4 66.7 3.7 100.0 1,371 Luapula 2.4 0.2 7.5 5.0 2.2 80.9 1.7 100.0 725 Lusaka 8.9 2.2 33.8 23.0 11.6 12.5 8.1 100.0 2,070 Muchinga 4.5 0.7 10.4 10.7 2.7 67.3 3.6 100.0 573 Northern 4.0 0.7 10.5 8.9 1.4 72.5 1.9 100.0 784 North Western 4.0 0.6 12.1 15.3 5.1 58.9 4.0 100.0 444 Southern 4.9 0.6 13.1 11.5 3.4 59.9 6.6 100.0 1,619 Western 4.0 0.7 15.8 10.3 2.2 63.8 3.2 100.0 533 Education No education 0.2 0.0 13.3 6.4 3.2 74.6 2.3 100.0 458 Primary 0.7 0.1 13.9 11.9 2.7 66.6 4.0 100.0 4,560 Secondary 2.9 1.1 23.8 17.9 9.0 37.9 7.4 100.0 4,883 More than secondary 45.6 5.1 13.6 16.6 5.1 3.0 11.1 100.0 928 Wealth quintile Lowest 0.9 0.0 4.3 7.2 0.7 84.9 2.0 100.0 1,737 Second 0.9 0.1 9.2 8.4 1.5 77.1 2.8 100.0 2,141 Middle 1.2 0.2 15.3 13.4 2.6 61.5 5.9 100.0 2,153 Fourth 5.2 0.7 30.5 21.6 9.8 24.6 7.6 100.0 2,477 Highest 17.7 3.6 27.1 20.4 12.1 8.4 10.8 100.0 2,321 Total 15-49 5.5 1.0 18.3 14.8 5.7 48.5 6.1 100.0 10,829 50-59 7.6 0.8 13.5 13.2 3.8 56.6 4.6 100.0 1,146 Total 15-59 5.7 1.0 17.9 14.6 5.6 49.3 6.0 100.0 11,975 3.7 TYPE OF EMPLOYMENT Tables 3.7.1 and 3.7.2 show the percent distribution of women and men employed in the 12 months preceding the survey by type of earnings, type of employer (among women only), and continuity of employment, according to type of employment (agricultural or nonagricultural). More than six in ten women employed in agriculture (61 percent) are not paid for their work. By contrast, 85 percent of women who work in the nonagricultural sector are paid in cash, as compared with only 29 percent of women working in agriculture. Overall, more than one-third of employed women (35 percent) are not paid at all. Characteristics of Respondents • 47 Seventy-two percent of women employed in the agricultural sector and 63 percent of those who work in the nonagricultural sector are self-employed. As expected, the majority of women who work in agriculture (83 percent) are seasonally employed, and only 13 percent work all year. Among women who do nonagricultural work, the majority (72 percent) are employed all year. Table 3.7.1 Type of employment: Women Percent distribution of women age 15-49 employed in the 12 months preceding the survey by type of earnings, type of employer, and continuity of employment, according to type of employment (agricultural or nonagricultural), Zambia 2013-14 Employment characteristic Agricultural work Nonagricultural work Total Type of earnings Cash only 28.9 85.4 58.3 Cash and in-kind 8.2 3.1 5.5 In-kind only 1.8 0.2 1.0 Not paid 60.9 10.7 34.8 Total 100.0 100.0 100.0 Type of employer Employed by family member 23.5 4.5 13.4 Employed by nonfamily member 4.7 32.2 19.3 Self-employed 71.6 62.9 66.9 Total 100.0 100.0 100.0 Continuity of employment All year 13.1 72.0 43.7 Seasonal 83.2 16.4 48.4 Occasional 3.4 11.0 7.4 Total 100.0 100.0 100.0 Number of women employed during the past 12 months 4,067 4,220 8,548 Note: Totals may not sum up to 100 percent because women with missing information have been deleted. Table 3.7.2 Type of employment: Men Percent distribution of men age 15-49 employed in the 12 months preceding the survey by type of earnings, type of employer, and continuity of employment, according to type of employment (agricultural or nonagricultural), Zambia 2013-14 Employment characteristic Agricultural work Nonagricultural work Total Type of earnings Cash only 41.7 91.4 66.8 Cash and in-kind 17.4 2.8 10.0 In-kind only 1.4 0.5 1.0 Not paid 39.3 5.3 22.1 Total 100.0 100.0 100.0 Continuity of employment All year 24.9 75.2 50.1 Seasonal 68.3 11.7 40.0 Occasional 6.8 13.1 9.8 Total 100.0 100.0 100.0 Number of men employed during the past 12 months 5,903 5,359 11,975 Note: Totals may not sum up to 100 percent because men with missing information have been deleted. Table 3.7.2 shows that a lower percentage of employed men (22 percent) than employed women (35 percent) are not paid for their work. About four in ten men working in the agricultural sector (39 percent) are not paid at all for their work. On the other hand, the majority of men who work in the nonagricultural sector (91 percent) receive cash for their work; only 5 percent do not receive payment of any type. Sixty-eight percent of men who work in agriculture are seasonally employed, and 25 percent work throughout the year. Three-quarters of men in the nonagricultural sector are employed all year. 48 • Characteristics of Respondents 3.8 HEALTH INSURANCE COVERAGE Access to health care improves when individuals are covered by some form of health insurance. Tables 3.8.1 and 3.8.2 show the percentage of women and men age 15-49 by the specific health insurance coverage they carry, according to background characteristics. The vast majority of women and men in Zambia do not have any health insurance (97 percent each). Among women and men with health insurance, 2 percent have employer-based insurance and less than 1 percent has other types of health insurance such as social security, mutual health organisation or community-based coverage, or privately purchased commercial insurance. There are no major variations in health insurance coverage by background characteristics. Table 3.8.1 Health insurance coverage: Women Percentage of women age 15-49 with specific types of health insurance coverage, according to background characteristics, Zambia 2013-14 Background characteristic Employer- based insurance Mutual health organisation/ community- based insurance Privately purchased commercial insurance Low cost pre- payment scheme/standard High cost pre- payment scheme/premium None Number of women Age 15-19 0.6 0.2 0.1 0.2 0.3 98.6 3,625 20-24 1.3 0.1 0.1 0.1 0.2 98.1 3,006 25-29 2.5 0.2 0.2 0.2 0.6 96.4 2,813 30-34 2.1 0.3 0.2 0.3 0.5 96.5 2,475 35-39 1.9 0.3 0.3 0.3 0.4 96.8 2,009 40-44 1.7 0.1 0.3 0.4 0.5 97.1 1,464 45-49 2.1 0.3 0.3 0.3 0.4 96.6 1,018 Residence Urban 3.3 0.4 0.4 0.3 0.8 94.8 7,585 Rural 0.2 0.0 0.0 0.1 0.1 99.5 8,826 Province Central 1.1 0.1 0.0 0.0 0.3 98.5 1,467 Copperbelt 4.5 0.2 0.3 0.1 1.2 93.8 2,836 Eastern 0.4 0.1 0.1 0.0 0.0 99.3 1,930 Luapula 0.1 0.1 0.0 0.0 0.3 99.3 1,143 Lusaka 2.4 0.6 0.4 0.5 0.4 95.7 3,266 Muchinga 0.1 0.0 0.0 0.0 0.1 99.8 868 Northern 0.0 0.0 0.0 0.0 0.1 99.8 1,200 North Western 0.9 0.0 0.4 0.1 0.6 97.9 713 Southern 1.2 0.0 0.1 0.9 0.1 97.6 2,007 Western 0.3 0.0 0.4 0.0 0.1 99.2 980 Education No education 0.0 0.0 0.0 0.3 0.0 99.7 1,375 Primary 0.3 0.1 0.1 0.2 0.1 99.3 7,685 Secondary 2.0 0.3 0.2 0.2 0.4 96.9 6,521 More than secondary 14.2 0.5 2.4 0.3 4.2 78.6 830 Wealth quintile Lowest 0.0 0.0 0.0 0.0 0.0 100.0 2,859 Second 0.0 0.0 0.0 0.4 0.0 99.6 2,861 Middle 0.2 0.0 0.0 0.0 0.1 99.7 3,077 Fourth 0.6 0.1 0.1 0.3 0.1 98.8 3,510 Highest 5.9 0.6 0.8 0.5 1.3 90.9 4,103 Total 1.6 0.2 0.2 0.2 0.4 97.3 16,411 Characteristics of Respondents • 49 Table 3.8.2 Health insurance coverage: Men Percentage of men age 15-49 with specific types of health insurance coverage, according to background characteristics, Zambia 2013-14 Background characteristic Social security Employer- based insurance Mutual health organisation/ community- based insurance Privately purchased commercial insurance Low cost pre- payment scheme/ standard High cost pre- payment scheme/ premium Other None Number of men Age 15-19 0.0 0.4 0.1 0.2 0.1 0.1 0.1 99.1 3,337 20-24 0.1 0.4 0.2 0.2 0.0 0.4 0.0 98.7 2,335 25-29 0.1 1.4 0.3 0.3 0.0 0.0 0.0 97.8 1,944 30-34 0.1 3.1 0.2 0.2 0.4 0.2 0.1 95.7 1,927 35-39 0.1 2.7 0.4 0.3 0.2 0.5 0.2 95.7 1,664 40-44 0.0 1.4 0.8 0.5 0.6 0.5 0.0 96.2 1,384 45-49 0.1 2.5 0.5 0.5 0.6 0.6 0.5 94.9 970 Residence Urban 0.1 2.9 0.5 0.4 0.3 0.5 0.2 95.1 6,326 Rural 0.1 0.2 0.1 0.2 0.1 0.1 0.1 99.3 7,235 Province Central 0.2 0.7 0.2 0.2 0.2 0.3 0.0 98.2 1,153 Copperbelt 0.2 2.9 0.7 0.3 0.2 0.8 0.2 94.6 2,395 Eastern 0.1 0.2 0.1 0.1 0.2 0.1 0.2 99.1 1,710 Luapula 0.0 0.5 0.2 0.1 0.0 0.0 0.0 99.2 855 Lusaka 0.0 2.2 0.2 0.5 0.3 0.4 0.1 96.3 2,844 Muchinga 0.0 0.3 0.3 0.3 0.0 0.0 0.3 98.9 680 Northern 0.0 0.3 0.0 0.1 0.0 0.0 0.1 99.5 929 North Western 0.0 1.2 0.3 0.2 0.0 0.2 0.1 97.9 557 Southern 0.0 2.0 0.4 0.4 0.2 0.1 0.1 96.9 1,771 Western 0.0 0.3 0.1 0.2 0.0 0.0 0.0 99.4 668 Education No education 0.0 0.0 0.1 0.0 0.2 0.0 0.0 99.7 500 Primary 0.0 0.2 0.1 0.0 0.0 0.0 0.0 99.5 5,365 Secondary 0.0 1.2 0.2 0.2 0.2 0.2 0.1 97.9 6,638 More than secondary 0.5 10.3 1.6 2.0 1.0 2.5 0.7 81.8 1,058 Wealth quintile Lowest 0.0 0.1 0.1 0.0 0.0 0.0 0.0 99.8 2,038 Second 0.0 0.1 0.1 0.0 0.1 0.0 0.0 99.8 2,448 Middle 0.1 0.3 0.1 0.0 0.0 0.0 0.0 99.5 2,547 Fourth 0.1 0.6 0.3 0.4 0.1 0.1 0.1 98.4 3,124 Highest 0.2 4.9 0.6 0.8 0.5 1.1 0.3 91.6 3,405 Total 15-49 0.1 1.5 0.3 0.3 0.2 0.3 0.1 97.3 13,561 50-59 0.2 2.3 0.3 0.5 0.0 0.3 0.1 96.3 1,212 Total 15-59 0.1 1.5 0.3 0.3 0.2 0.3 0.1 97.3 14,773 3.9 TOBACCO USE Smoking and other forms of tobacco use can cause a wide variety of diseases and can lead to death. Smoking is a risk factor for cardiovascular disease, lung cancer, and other forms of cancer, and it contributes to the severity of pneumonia, emphysema, and chronic bronchitis symptoms. Also, secondhand smoke may adversely affect the health of children and aggravate childhood illnesses. In the 2013-14 ZDHS, women and men age 15-49 were asked whether they currently smoked cigarettes and, if so, how many cigarettes they had smoked in the past 24 hours. Those who reported not currently smoking cigarettes were asked whether they use any other forms of tobacco, such as a pipe, chewing tobacco, or snuff. Tables 3.9.1 and 3.9.2 show the percentage of women and men who smoke cigarettes or use other tobacco products according to background characteristics. Table 3.9.2 also shows the percent distribution of male cigarette smokers by number of cigarettes smoked in the preceding 24 hours. The majority of women (98 percent) do not use tobacco. Among the 76 women who smoke (weighted number), 9 percent reported that they smoked more than 10 cigarettes in the 24 hours before the survey (data not shown). 50 • Characteristics of Respondents Table 3.9.1 Use of tobacco: Women Percentage of women age 15-49 who smoke cigarettes or use other tobacco products, according to background characteristics and maternity status, Zambia 2013-14 Uses tobacco Does not use tobacco Number of women Background characteristic Cigarettes Other tobacco Age 15-19 0.1 0.0 99.9 3,625 20-24 0.3 0.2 99.5 3,006 25-29 0.3 1.2 98.6 2,813 30-34 0.5 1.0 98.5 2,475 35-39 0.4 2.1 97.7 2,009 40-44 0.9 3.3 96.0 1,464 45-49 2.1 3.8 94.8 1,018 Maternity status Pregnant 0.1 0.8 99.1 1,427 Breastfeeding (not pregnant) 0.4 1.0 98.6 4,297 Neither 0.5 1.3 98.3 10,687 Residence Urban 0.3 1.2 98.6 7,585 Rural 0.6 1.2 98.3 8,826 Province Central 0.6 0.5 98.9 1,467 Copperbelt 0.3 2.8 97.1 2,836 Eastern 0.9 0.5 98.9 1,930 Luapula 0.1 2.1 97.8 1,143 Lusaka 0.3 0.2 99.5 3,266 Muchinga 0.5 0.1 99.4 868 Northern 0.2 1.2 98.6 1,200 North Western 0.3 0.5 99.2 713 Southern 0.4 0.2 99.5 2,007 Western 1.3 5.0 94.3 980 Education No education 1.4 3.3 95.9 1,375 Primary 0.5 1.5 98.1 7,685 Secondary 0.3 0.5 99.2 6,521 More than secondary 0.2 0.2 99.6 830 Wealth quintile Lowest 1.1 2.7 96.5 2,859 Second 0.4 0.8 98.9 2,861 Middle 0.4 0.9 98.8 3,077 Fourth 0.3 0.8 99.0 3,510 Highest 0.3 0.9 98.8 4,103 Total 0.5 1.2 98.4 16,411 Tobacco use is more common among men. Table 3.9.2 shows that one in five men age 15-49 use tobacco, the majority of whom smoke cigarettes (19 percent of all men). The proportion of male cigarette smokers increases with age, from 3 percent in the 15-19 age group to 36 percent in the 45-49 age group. Men in rural areas are more likely to smoke cigarettes than men in urban areas (21 percent versus 17 percent). The percentage of men who smoke cigarettes ranges from 13 percent in Southern to 30 percent in Luapula. This percentage decreases with increasing education and wealth. Among men who smoke, 26 percent smoked 1-2 cigarettes in the 24 hours preceding the survey, 38 percent smoked 3-5 cigarettes, 13 percent s

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