Demographic and Health Survey - Zambia - 2018

Publication date: 2018

Zambia Demographic and Health Survey 2018 Zam bia 2018 D em ographic and H ealth S urvey GOVERNMENT OF ZAMBIA Zambia Demographic and Health Survey 2018 Zambia Statistics Agency (Formerly Central Statistical Office) Lusaka, Zambia Ministry of Health Lusaka, Zambia University Teaching Hospital Virology Laboratory Lusaka, Zambia The DHS Program ICF Rockville, Maryland, USA January 2020 The 2018 Zambia Demographic and Health Survey (2018 ZDHS) was implemented by the Zambia Statistics Agency in partnership with the Ministry of Health; the University Teaching Hospital Virology Laboratory (UTH-VL); and the Department of Population Studies at the University of Zambia (UNZA) under the overall guidance of the National Steering Committee. Data collection lasted from July 2018 to January 2019. Funding for the 2018 ZDHS was provided by the United States Agency for International Development (USAID). Additional funding was provided by the Global Fund, the Department for International Development (DFID), and the United Nations Population Fund (UNFPA). ICF provided technical assistance 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 information about the 2018 ZDHS may be obtained from the Zambia Statistics Agency, P.O. Box 31908, Lusaka, Zambia; telephone: (260-211) 251377/85 257604/05; fax: (260-211) 253468; email: Info@zamstats.gov.zm; internet: www.zamstats.gov.zm; data portal: http://zambia.opendataforafrica.org/. Information about The DHS Program may be obtained from ICF, 530 Gaither Road, Suite 500, Rockville, MD 20850, USA; telephone: +1-301-407-6500; fax: +1-301-407-6501; email: info@DHSprogram.com; internet: www.DHSprogram.com. Suggested citation: Zambia Statistics Agency, Ministry of Health (MOH) Zambia, and ICF. 2019. Zambia Demographic and Health Survey 2018. Lusaka, Zambia, and Rockville, Maryland, USA: Zambia Statistics Agency, Ministry of Health, and ICF. Contents • iii CONTENTS TABLES AND FIGURES . ix FOREWORD . xix ACRONYMS AND ABBREVIATIONS . xxi SUSTAINABLE DEVELOPMENT GOAL (SDG) INDICATORS . xxiii READING AND UNDERSTANDING TABLES FROM THE 2018 ZAMBIA DEMOGRAPHIC AND HEALTH SURVEY (ZDHS) . xxv MAP OF ZAMBIA . xxxii 1 INTRODUCTION AND SURVEY METHODOLOGY . 1 1.1 Survey Objectives . 1 1.2 Sample Design . 1 1.3 Questionnaires . 2 1.4 Anthropometry, Anaemia Testing, and HIV Testing . 3 1.4.1 Anthropometry Measurements . 3 1.4.2 Anaemia Testing . 4 1.4.3 HIV Testing . 4 1.5 Pretest . 5 1.6 Training of Field Staff . 6 1.7 Fieldwork . 7 1.8 Data Processing . 7 1.9 Response Rates . 7 2 HOUSING CHARACTERISTICS AND HOUSEHOLD POPULATION . 9 2.1 Housing Characteristics . 9 2.1.1 Drinking Water Sources and Treatment . 9 2.1.2 Sanitation . 10 2.1.3 Exposure to Smoke inside the Home . 11 2.1.4 Other Housing Characteristics . 11 2.1.5 Household Wealth . 12 2.1.6 Handwashing . 12 2.2 Household Population and Composition . 12 2.3 Children’s Living Arrangements and Parental Survival . 13 2.4 Birth Registration . 14 2.5 Education . 15 2.5.1 Educational Attainment . 15 2.5.2 School Attendance and Orphanhood . 16 3 CHARACTERISTICS OF RESPONDENTS . 33 3.1 Basic Characteristics of Survey Respondents . 33 3.2 Education and Literacy . 34 3.3 Mass Media Exposure . 35 3.4 Employment . 36 3.5 Occupation . 37 3.6 Health Insurance Coverage . 37 3.7 Tobacco Use . 37 3.8 Surgery . 38 iv • Contents 4 MARRIAGE AND SEXUAL ACTIVITY . 61 4.1 Marital Status . 61 4.2 Polygyny . 62 4.3 Age at First Marriage . 63 4.4 Age at First Sexual Intercourse . 63 4.5 Recent Sexual Activity . 64 5 FERTILITY . 73 5.1 Current Fertility . 73 5.2 Children Ever Born and Living . 74 5.3 Birth Intervals . 75 5.4 Insusceptibility to Pregnancy . 76 5.5 Menopause . 77 5.6 Age at First Birth . 77 5.7 Teenage Childbearing . 78 5.8 Sexual and Reproductive Behaviours before Age 15 . 78 6 FERTILITY PREFERENCES . 89 6.1 Desire for Another Child . 89 6.2 Ideal Family Size . 90 6.3 Fertility Planning Status . 91 6.4 Wanted Fertility Rates . 92 7 FAMILY PLANNING . 99 7.1 Contraceptive Knowledge and Use . 99 7.2 Source of Modern Contraceptive Methods . 101 7.3 Informed Choice . 101 7.4 Discontinuation of Contraceptives . 102 7.5 Demand for Family Planning . 102 7.5.1 Decision Making about Family Planning . 103 7.5.2 Future Use of Contraception . 104 7.5.3 Exposure to Family Planning Messages in the Media . 104 7.6 Contact of Nonusers with Family Planning Providers . 104 7.7 Exposure to Specific Radio and Television Programmes . 104 8 INFANT AND CHILD MORTALITY . 121 8.1 Infant and Child Mortality . 122 8.2 Biodemographic Risk Factors . 123 8.3 Perinatal Mortality . 124 8.4 High-risk Fertility Behaviour . 124 9 MATERNAL HEALTH CARE . 131 9.1 Antenatal Care Coverage and Content . 131 9.1.1 Skilled Providers . 131 9.1.2 Timing and Number of ANC Visits . 132 9.2 Components of ANC Visits . 133 9.3 Protection against Neonatal Tetanus . 133 9.4 Delivery Services . 134 9.4.1 Institutional Deliveries . 134 9.4.2 Skilled Assistance during Delivery . 135 9.4.3 Delivery by Caesarean . 136 Contents • v 9.5 Postnatal Care . 136 9.5.1 Postnatal Health Check for Mothers . 136 9.5.2 Postnatal Health Check for Newborns . 137 9.6 Problems in Accessing Health Care . 138 9.7 Obstetric Fistula . 139 10 CHILD HEALTH . 155 10.1 Birth Weight . 155 10.2 Vaccination of Children . 156 10.3 Symptoms of Acute Respiratory Infection . 158 10.4 Fever . 159 10.5 Diarrhoeal Disease . 159 10.5.1 Prevalence of Diarrhoea and Treatment-seeking Behaviour . 159 10.5.2 Feeding Practices . 160 10.5.3 Oral Rehydration Therapy and Other Treatments . 160 10.6 Treatment of Childhood Illness . 161 10.7 Disposal of Children’s Stools . 162 11 NUTRITION OF CHILDREN AND WOMEN . 177 11.1 Nutritional Status of Children . 177 11.1.1 Anthropometry Training and Data Collection . 179 11.1.2 Levels of Child Malnutrition . 179 11.2 Infant and Young Child Feeding Practices . 180 11.2.1 Early Initiation of Breastfeeding . 180 11.2.2 Exclusive Breastfeeding . 181 11.2.3 Median Duration of Breastfeeding . 182 11.2.4 Bottle Feeding . 183 11.2.5 Introduction of Complementary Foods . 183 11.2.6 Minimum Dietary Diversity, Minimum Meal Frequency, and Minimum Acceptable Diet . 183 11.3 Anaemia Prevalence in Children . 185 11.4 Micronutrient Intake and Supplementation among Children . 186 11.5 Anaemia Prevalence in Women. 187 11.6 Micronutrient Supplementation and Deworming During Pregnancy . 188 12 MALARIA . 201 12.1 Ownership of Insecticide-treated Nets . 202 12.2 Household Access to and Use of ITNs . 203 12.3 Use of ITNs by Children and Pregnant Women . 205 12.4 Indoor Residual Spraying . 206 12.5 Malaria in Pregnancy . 206 12.6 Case Management of Malaria in Children . 207 12.7 Prevalence of Low Haemoglobin in Children . 208 13 HIV/AIDS-RELATED KNOWLEDGE, ATTITUDES, AND BEHAVIOUR . 223 13.1 HIV/AIDS Knowledge, Transmission, and Prevention Methods . 223 13.2 Knowledge about Mother-to-Child Transmission . 224 13.3 Discriminatory Attitudes towards People Living with HIV . 225 13.4 Multiple Sexual Partners . 226 13.5 Paid Sex . 227 13.6 Coverage of HIV Testing Services . 227 13.6.1 Awareness of HIV Testing Services and Experience with HIV Testing . 228 13.6.2 HIV Testing of Pregnant Women . 228 vi • Contents 13.6.3 Disclosure of HIV Test Results . 229 13.6.4 HIV Self-testing . 229 13.7 Male Circumcision . 230 13.8 Self-reporting of Sexually Transmitted Infections . 230 13.9 HIV/AIDS-related Knowledge and Behaviour among Young People . 231 13.9.1 Knowledge . 231 13.9.2 First Sex . 232 13.9.3 Premarital Sex . 232 13.9.4 Multiple Sexual Partners . 232 13.9.5 Coverage of HIV Testing Services . 233 13.9.6 Age-mixing in Sexual Relationships . 233 13.9.7 Drunkenness and Sexual Intercourse among Young People . 233 14 HIV PREVALENCE . 259 14.1 Coverage Rates for HIV Testing . 259 14.2 HIV Prevalence . 260 14.2.1 HIV Prevalence by Age and Sex . 260 14.2.2 HIV Prevalence by Sexual Risk Behaviour . 262 14.2.3 HIV Prevalence among Young People . 263 14.2.4 HIV Prevalence by Other Characteristics Related to HIV Risk . 263 14.2.5 HIV Prevalence among Couples . 264 15 ADULT AND MATERNAL MORTALITY . 275 15.1 Data . 275 15.2 Direct Estimates of Adult Mortality . 276 15.3 Trends in Adult Mortality . 277 15.4 Direct Estimates of Maternal Mortality . 277 15.5 Trends in Pregnancy-related Mortality . 278 16 WOMEN’S EMPOWERMENT . 283 16.1 Married Women’s and Men’s Employment . 284 16.2 Control over Women’s Earnings . 284 16.3 Control over Men’s Earnings . 285 16.4 Women’s and Men’s Ownership of Assets . 286 16.4.1 Documentation of Ownership of Assets . 286 16.4.2 Bank Accounts and Mobile Phones . 286 16.5 Women’s Participation in Decision Making . 287 16.6 Attitudes toward Wife Beating . 287 16.7 Negotiating Sexual Relations . 288 16.8 Widows Dispossessed of Property . 289 17 DOMESTIC VIOLENCE . 311 17.1 Measurement of Violence . 312 17.2 Women’s Experience of Physical Violence . 312 17.2.1 Prevalence of Physical Violence . 312 17.2.2 Perpetrators of Physical Violence . 313 17.3 Experience of Sexual Violence . 313 17.3.1 Prevalence of Sexual Violence . 313 17.3.2 Perpetrators of Sexual Violence . 314 17.4 Experience of Different Forms of Violence . 314 17.5 Marital Control by Husband . 314 Contents • vii 17.6 Forms of Spousal Violence . 315 17.6.1 Prevalence of Spousal Violence . 315 17.6.2 Experience of Spousal Violence by Duration of Marriage . 317 17.7 Injuries to Women due to Spousal Violence . 317 17.8 Violence Initiated by Women against Husbands . 318 17.9 Help Seeking among Women Who Have Experienced Violence . 318 REFERENCES . 335 APPENDIX A SAMPLE DESIGN . 337 A.1 Introduction . 337 A.2 Sample Frame . 337 A.3 Sample Design and Implementation . 338 A.4 Sample Probabilities and Sampling Weights . 339 APPENDIX B ESTIMATES OF SAMPLING ERRORS . 347 APPENDIX C DATA QUALITY TABLES . 377 APPENDIX D CONTRIBUTORS TO THE 2018 ZDHS . 385 APPENDIX E QUESTIONNAIRES . 391 Tables and Figures • ix TABLES AND FIGURES 1 INTRODUCTION AND SURVEY METHODOLOGY . 1 Table 1.1 Results of the household and individual interviews . 8 Figure 1.1 2018 ZDHS HIV testing algorithm . 5 2 HOUSING CHARACTERISTICS AND HOUSEHOLD POPULATION . 9 Table 2.1.1 Household drinking water . 18 Table 2.1.2 Drinking water according to province and wealth . 19 Table 2.1.3 Treatment of household drinking water . 20 Table 2.2 Availability of water . 20 Table 2.3.1 Household sanitation facilities . 21 Table 2.3.2 Sanitation facility type according to province and wealth . 21 Table 2.4 Household characteristics . 22 Table 2.5 Household possessions . 23 Table 2.6 Wealth quintiles . 23 Table 2.7 Handwashing . 24 Table 2.8 Household population by age, sex, and residence . 25 Table 2.9 Household composition . 26 Table 2.10 Children’s living arrangements and orphanhood . 27 Table 2.11 Birth registration of children under age 5 . 28 Table 2.12.1 Educational attainment of the female household population . 29 Table 2.12.2 Educational attainment of the male household population . 30 Table 2.13 School attendance ratios . 31 Table 2.14 Children under age 5 by highest level of education . 32 Table 2.15 School attendance by survivorship of parents . 32 Figure 2.1 Household drinking water by residence . 10 Figure 2.2 Household toilet facilities by residence . 11 Figure 2.3 Population pyramid . 13 Figure 2.4 Orphanhood by household wealth . 14 Figure 2.5 Birth registration by province . 15 Figure 2.6 Secondary school attendance by household wealth . 16 3 CHARACTERISTICS OF RESPONDENTS . 33 Table 3.1 Background characteristics of respondents . 40 Table 3.2.1 Educational attainment: Women . 41 Table 3.2.2 Educational attainment: Men . 42 Table 3.3.1 Literacy: Women . 43 Table 3.3.2 Literacy: Men . 44 Table 3.4.1 Exposure to mass media: Women . 45 Table 3.4.2 Exposure to mass media: Men . 46 Table 3.5.1 Internet usage: Women . 47 Table 3.5.2 Internet usage: Men . 48 Table 3.6.1 Employment status: Women . 49 Table 3.6.2 Employment status: Men . 50 Table 3.7.1 Occupation: Women . 51 Table 3.7.2 Occupation: Men . 52 x • Tables and Figures Table 3.8.1 Type of employment: Women . 53 Table 3.8.2 Type of employment: Men . 53 Table 3.9.1 Health insurance coverage: Women . 54 Table 3.9.2 Health insurance coverage: Men . 55 Table 3.10.1 Tobacco smoking: Women . 56 Table 3.10.2 Tobacco smoking: Men . 57 Table 3.11 Average number of cigarettes smoked daily: Men . 58 Table 3.12 Smokeless tobacco use and any tobacco use . 59 Table 3.13 History of diabetes and hypertension . 59 Table 3.14 Use of surgery . 60 Figure 3.1 Education of survey respondents . 34 Figure 3.2 Secondary education by household wealth . 35 Figure 3.3 Exposure to mass media . 35 Figure 3.4 Employment status by residence . 36 Figure 3.5 Use of surgery by age group . 38 4 MARRIAGE AND SEXUAL ACTIVITY . 61 Table 4.1 Current marital status . 65 Table 4.2.1 Number of women’s co-wives . 65 Table 4.2.2 Number of men’s wives . 66 Table 4.3 Age at first marriage . 67 Table 4.4 Median age at first marriage by background characteristics . 68 Table 4.5 Age at first sexual intercourse . 69 Table 4.6 Median age at first sexual intercourse according to background characteristics . 70 Table 4.7.1 Recent sexual activity: Women . 71 Table 4.7.2 Recent sexual activity: Men . 72 Figure 4.1 Marital status . 62 Figure 4.2 Trends in polygyny . 62 Figure 4.3 Median age at first sex and first marriage . 63 5 FERTILITY . 73 Table 5.1 Current fertility . 80 Table 5.2 Fertility by background characteristics . 80 Table 5.3.1 Trends in age-specific fertility rates . 81 Table 5.3.2 Trends in age-specific and total fertility rates . 81 Table 5.4 Children ever born and living . 82 Table 5.5 Birth intervals . 83 Table 5.6 Postpartum amenorrhoea, abstinence, and insusceptibility . 84 Table 5.7 Median duration of amenorrhoea, postpartum abstinence, and postpartum insusceptibility . 84 Table 5.8 Menopause . 85 Table 5.9 Age at first birth . 85 Table 5.10 Median age at first birth . 86 Table 5.11 Teenage pregnancy and motherhood . 87 Table 5.12 Sexual and reproductive health behaviours before age 15 . 87 Figure 5.1 Trends in fertility by residence . 74 Figure 5.2 Fertility by province . 74 Figure 5.3 Birth intervals . 75 Figure 5.4 Median age at first birth by residence . 77 Figure 5.5 Teenage pregnancy and motherhood by residence . 78 Tables and Figures • xi 6 FERTILITY PREFERENCES . 89 Table 6.1 Fertility preferences according to number of living children . 93 Table 6.2.1 Desire to limit childbearing: Women . 93 Table 6.2.2 Desire to limit childbearing: Men . 94 Table 6.3 Ideal number of children according to number of living children . 95 Table 6.4 Mean ideal number of children according to background characteristics . 96 Table 6.5 Fertility planning status . 96 Table 6.6 Wanted fertility rates . 97 Figure 6.1 Trends in desire to limit childbearing . 90 Figure 6.2 Ideal family size . 90 Figure 6.3 Ideal family size by number of living children . 91 Figure 6.4 Trends in wanted and actual fertility . 92 7 FAMILY PLANNING . 99 Table 7.1 Knowledge of contraceptive methods . 106 Table 7.2 Knowledge of contraceptive methods according to background characteristics . 107 Table 7.3 Current use of contraception according to age . 108 Table 7.4 Current use of contraception according to background characteristics . 109 Table 7.5 Knowledge of fertile period . 110 Table 7.6 Knowledge of fertile period by age . 110 Table 7.7 Timing of sterilisation . 110 Table 7.8 Source of modern contraception methods . 111 Table 7.9 Use of social marketing brand pills and condoms . 112 Table 7.10 Informed choice . 113 Table 7.11 Twelve-month contraceptive discontinuation rates . 113 Table 7.12 Reasons for discontinuation . 114 Table 7.13.1 Need and demand for family planning among currently married women . 115 Table 7.13.2 Need and demand for family planning for all women and for sexually active unmarried women . 116 Table 7.14 Decision making about family planning . 117 Table 7.15 Future use of contraception . 118 Table 7.16 Exposure to family planning messages . 118 Table 7.17 Contact of nonusers with family planning providers . 119 Table 7.18 Exposure to specific radio and television programmes . 120 Figure 7.1 Contraceptive use . 100 Figure 7.2 Trends in contraceptive use . 100 Figure 7.3 Use of modern methods by residence . 100 Figure 7.4 Source of modern contraceptive methods . 101 Figure 7.5 Contraceptive discontinuation rates . 102 Figure 7.6 Demand for family planning . 103 Figure 7.7 Unmet need by residence . 103 Figure 7.8 Unmet need by province . 103 8 INFANT AND CHILD MORTALITY . 121 Table 8.1 Early childhood mortality rates . 126 Table 8.2 Five-year early childhood mortality rates according to background characteristics . 126 Table 8.3 Ten-year early childhood mortality rates according to additional characteristics . 127 Table 8.4 Perinatal mortality . 128 Table 8.5 High-risk fertility behaviour . 129 xii • Tables and Figures Figure 8.1 Trends in early childhood mortality rates . 122 Figure 8.2 Under-5 mortality by province . 123 Figure 8.3 Under-5 mortality by mother’s education . 123 Figure 8.4 Perinatal mortality by household wealth . 124 9 MATERNAL HEALTH CARE . 131 Table 9.1 Antenatal care . 140 Table 9.2 Number of antenatal care visits and timing of first visit . 141 Table 9.3 Components of antenatal care . 142 Table 9.4 Tetanus toxoid injections . 143 Table 9.5 Place of delivery . 144 Table 9.6 Assistance during delivery . 145 Table 9.7 Caesarean section . 146 Table 9.8 Duration of stay in health facility after birth . 146 Table 9.9 Timing of first postnatal check for the mother . 147 Table 9.10 Type of provider of first postnatal check for the mother . 148 Table 9.11 Timing of first postnatal check for the newborn . 149 Table 9.12 Type of provider of first postnatal check for the newborn . 150 Table 9.13 Content of postnatal care for newborns . 151 Table 9.14 Problems in accessing health care . 152 Table 9.15 Knowledge of fistula and experience of fistula-like symptoms . 153 Figure 9.1 Trends in antenatal care coverage . 132 Figure 9.2 Components of antenatal care . 133 Figure 9.3 Trends in place of birth . 134 Figure 9.4 Health facility births by province . 134 Figure 9.5 Health facility births by education . 135 Figure 9.6 Assistance during delivery . 135 10 CHILD HEALTH . 155 Table 10.1 Child’s size and weight at birth. 163 Table 10.2 Vaccinations by source of information . 164 Table 10.3 Vaccinations by background characteristics . 165 Table 10.4 Possession and observation of vaccination cards, according to background characteristics . 166 Table 10.5 Prevalence and treatment of symptoms of ARI . 167 Table 10.6 Source of advice or treatment for children with symptoms of ARI . 168 Table 10.7 Prevalence and treatment of fever . 169 Table 10.8 Prevalence and treatment of diarrhoea . 170 Table 10.9 Source of advice or treatment for children with diarrhoea . 171 Table 10.10 Feeding practices during diarrhoea . 172 Table 10.11 Oral rehydration therapy, zinc, and other treatments for diarrhoea . 173 Table 10.12 Knowledge of ORS packets . 174 Table 10.13 Disposal of children’s stools . 175 Figure 10.1 Childhood vaccinations . 157 Figure 10.2 Trends in childhood vaccinations . 158 Figure 10.3 Vaccination coverage by province . 158 Figure 10.4 Diarrhoea prevalence by age . 159 Figure 10.5 Feeding practices during diarrhoea . 160 Figure 10.6 Treatment of diarrhoea . 161 Figure 10.7 Prevalence and treatment of childhood illness . 161 Tables and Figures • xiii 11 NUTRITION OF CHILDREN AND WOMEN . 177 Table 11.1 Nutritional status of children . 190 Table 11.2 Initial breastfeeding . 191 Table 11.3 Breastfeeding status by age . 192 Table 11.4 Infant and young child feeding (IYCF) indicators on breastfeeding status . 192 Table 11.5 Median duration of breastfeeding . 193 Table 11.6 Foods and liquids consumed by children in the day or night preceding the interview . 194 Table 11.7 Minimum acceptable diet . 195 Table 11.8 Prevalence of anaemia in children . 196 Table 11.9 Micronutrient intake among children . 197 Table 11.10 Therapeutic foods . 198 Table 11.11 Prevalence of anaemia in women . 199 Table 11.12 Micronutrient intake among mothers . 200 Figure 11.1 Trends in nutritional status of children . 179 Figure 11.2 Stunting in children by province . 180 Figure 11.3 Stunting in children by mother’s education . 180 Figure 11.4 Breastfeeding practices by age . 182 Figure 11.5 Infant and young child feeding (IYCF) indicators on breastfeeding status . 182 Figure 11.6 IYCF indicators on minimum acceptable diet . 184 Figure 11.7 Anaemia in children by province . 186 12 MALARIA . 201 Table 12.1 Household possession of mosquito nets . 210 Table 12.2 Source of mosquito nets . 211 Table 12.3 Access to an insecticide-treated net (ITN) . 211 Table 12.4 Access to an ITN according to background characteristics . 212 Table 12.5 Use of mosquito nets by persons in the household . 213 Table 12.6 Use of existing ITNs . 214 Table 12.7 Use of mosquito nets by children . 215 Table 12.8 Use of mosquito nets by pregnant women . 216 Table 12.9 Indoor residual spraying against mosquitoes . 217 Table 12.10 Use of intermittent preventive treatment (IPTp) by women during pregnancy . 218 Table 12.11 Prevalence, diagnosis, and prompt treatment of children with fever . 219 Table 12.12 Source of advice or treatment for children with fever . 220 Table 12.13 Type of antimalarial drugs used . 221 Table 12.14 Haemoglobin <8.0 g/dl in children . 222 Figure 12.1 Trends in household ownership of ITNs . 202 Figure 12.2 ITN ownership by province . 202 Figure 12.3 Full household ITN coverage by household wealth . 203 Figure 12.4 Source of ITNs . 203 Figure 12.5 Trends in ITN access and use . 204 Figure 12.6 Access to and use of ITNs by residence . 204 Figure 12.7 ITN access by province . 205 Figure 12.8 ITN use . 205 Figure 12.9 Trends in IPTp use by pregnant women . 207 Figure 12.10 Low haemoglobin in children by age . 209 xiv • Tables and Figures 13 HIV/AIDS-RELATED KNOWLEDGE, ATTITUDES, AND BEHAVIOUR . 223 Table 13.1 Knowledge of HIV prevention methods . 235 Table 13.2.1 Comprehensive knowledge about HIV: Women . 236 Table 13.2.2 Comprehensive knowledge about HIV: Men . 237 Table 13.3 Knowledge of prevention of mother-to-child transmission of HIV . 238 Table 13.4 Discriminatory attitudes towards people living with HIV . 239 Table 13.5.1 Multiple sexual partners and higher-risk sexual intercourse in the past 12 months: Women . 240 Table 13.5.2 Multiple sexual partners and higher-risk sexual intercourse in the past 12 months: Men . 241 Table 13.6 Payment for sexual intercourse and condom use at last paid sexual intercourse . 242 Table 13.7.1 Coverage of prior HIV testing: Women . 243 Table 13.7.2 Coverage of prior HIV testing: Men . 244 Table 13.8 Pregnant women counselled and tested for HIV . 245 Table 13.9.1 Disclosure of HIV test results from ANC HIV test: Women . 246 Table 13.9.2 Disclosure of HIV test results from most recent test: Men . 247 Table 13.10 Knowledge and coverage of self-testing for HIV . 248 Table 13.11 Male circumcision . 249 Table 13.12 Self-reported prevalence of sexually transmitted infections (STIs) and STI symptoms . 250 Table 13.13 Women and men seeking treatment for STIs . 250 Table 13.14 Comprehensive knowledge about HIV among young people . 251 Table 13.15 Age at first sexual intercourse among young people . 251 Table 13.16 Premarital sexual intercourse among young people . 252 Table 13.17.1 Multiple sexual partners and higher-risk sexual intercourse in the past 12 months among young people: Women . 253 Table 13.17.2 Multiple sexual partners and higher-risk sexual intercourse in the past 12 months among young people: Men . 254 Table 13.18 Recent HIV tests among young people . 255 Table 13.19 Age-mixing in sexual relationships among women age 15-19 . 256 Table 13.20 Drunkenness during sexual intercourse among youth. 257 Figure 13.1 Trends in knowledge of mother-to-child transmission (MTCT) . 225 Figure 13.2 Discriminatory attitudes towards people living with HIV by education . 226 Figure 13.3 Sex and condom use with non-regular partners . 226 Figure 13.4 HIV testing . 228 Figure 13.5 Trends in recent HIV testing . 228 Figure 13.6 Trends in HIV testing during pregnancy . 228 Figure 13.7 Male circumcision by age . 230 Figure 13.8 Trends in comprehensive HIV knowledge among youth . 231 14 HIV PREVALENCE . 259 Table 14.1 Coverage of HIV testing by residence and province . 265 Table 14.2 Coverage of HIV testing according to selected background characteristics . 266 Table 14.3 HIV prevalence by age . 267 Table 14.4 HIV prevalence by socioeconomic characteristics . 268 Table 14.5 HIV prevalence by demographic characteristics . 269 Table 14.6 HIV prevalence by sexual behaviour . 270 Table 14.7 HIV prevalence among young people by background characteristics . 271 Table 14.8 HIV prevalence among young people by sexual behaviour . 272 Table 14.9 HIV prevalence by other characteristics . 272 Tables and Figures • xv Table 14.10 Prior HIV testing by current HIV status . 272 Table 14.11 HIV prevalence by male circumcision . 273 Table 14.12 HIV prevalence among couples . 274 Figure 14.1 Trends in HIV prevalence . 261 Figure 14.2 HIV prevalence by age . 261 Figure 14.3 HIV prevalence by residence and sex . 261 Figure 14.4 HIV prevalence by province . 262 Figure 14.5 HIV prevalence by marital status . 262 Figure 14.6 HIV prevalence by number of lifetime partners . 263 15 ADULT AND MATERNAL MORTALITY . 275 Table 15.1 Adult mortality rates . 280 Table 15.2 Adult mortality probabilities . 280 Table 15.3 Maternal mortality . 281 Table 15.4 Maternal mortality ratio . 281 Table 15.5 Pregnancy-related mortality trends . 281 Figure 15.1 Adult mortality rates by age . 276 Figure 15.2 Trends in the pregnancy-related mortality ratio (PRMR) with confidence intervals . 279 16 WOMEN’S EMPOWERMENT . 283 Table 16.1 Employment and cash earnings of currently married women and men . 291 Table 16.2.1 Control over women’s cash earnings and relative magnitude of women’s cash earnings . 292 Table 16.2.2 Control over men’s cash earnings . 293 Table 16.3 Women’s control over their own earnings and over those of their husbands . 294 Table 16.4.1 Ownership of assets: Women . 294 Table 16.4.2 Ownership of assets: Men . 295 Table 16.5.1 Ownership of title or deed for house: Women . 296 Table 16.5.2 Ownership of title or deed for house: Men . 297 Table 16.6.1 Ownership of title or deed for land: Women . 298 Table 16.6.2 Ownership of title or deed for land: Men . 299 Table 16.7.1 Ownership and use of bank accounts and mobile phones: Women . 300 Table 16.7.2 Ownership and use of bank accounts and mobile phones: Men . 301 Table 16.8 Participation in decision making . 302 Table 16.9.1 Women’s participation in decision making by background characteristics . 302 Table 16.9.2 Men’s participation in decision making by background characteristics . 303 Table 16.10.1 Attitude toward wife beating: Women . 304 Table 16.10.2 Attitude toward wife beating: Men . 305 Table 16.11 Attitudes toward negotiating safer sexual relations with husband . 306 Table 16.12 Ability to negotiate sexual relations with husband . 307 Table 16.13 Indicators of women’s empowerment . 307 Table 16.14 Current use of contraception by women’s empowerment . 308 Table 16.15 Ideal number of children and unmet need for family planning by women’s empowerment . 308 Table 16.16 Reproductive health care by women’s empowerment . 309 Table 16.17 Early childhood mortality rates by indicators of women’s empowerment . 309 Table 16.18 Widows dispossessed of property . 310 xvi • Tables and Figures Figure 16.1 Employment by age . 284 Figure 16.2 Control over women’s earnings . 285 Figure 16.3 Ownership of assets . 286 Figure 16.4 Attitudes towards wife beating . 288 17 DOMESTIC VIOLENCE . 311 Table 17.1 Experience of physical violence . 320 Table 17.2 Persons committing physical violence . 321 Table 17.3 Experience of sexual violence. 322 Table 17.4 Age at first experience of sexual violence . 323 Table 17.5 Persons committing sexual violence . 323 Table 17.6 Experience of different forms of violence . 323 Table 17.7 Experience of violence during pregnancy . 324 Table 17.8 Marital control exercised by husbands . 325 Table 17.9 Forms of spousal violence . 326 Table 17.10 Spousal violence by background characteristics . 327 Table 17.11 Spousal violence by husband’s characteristics and empowerment indicators . 328 Table 17.12 Violence by any husband/partner in the last 12 months. 329 Table 17.13 Experience of spousal violence by duration of marriage . 330 Table 17.14 Injuries to women due to spousal violence . 330 Table 17.15 Violence by women against their husband by women’s background characteristics . 331 Table 17.16 Violence by women against their husband by husband’s characteristics and empowerment indicators . 332 Table 17.17 Help seeking to stop violence . 333 Table 17.18 Sources for help to stop the violence . 334 Figure 17.1 Women’s experience of violence by marital status . 313 Figure 17.2 Forms of spousal violence . 316 Figure 17.3 Spousal violence by husband’s alcohol consumption . 317 Figure 17.4 Help seeking by type of violence experienced . 319 APPENDIX A SAMPLE DESIGN. 337 Table A.1 Distribution of residential households by provinces and type of residence . 338 Table A.2 Distribution of SEAs and their average size in number of households by provinces and type of residence . 338 Table A.3 The 2018 ZDHS sample allocation of SEAs and households by provinces and type of residence . 339 Table A.4 The 2018 ZDHS sample allocation of expected completed women and men interviews by province and type of residence . 339 Table A.5 Sample implementation: Women . 341 Table A.6 Sample implementation: Men . 342 Table A.7 Coverage of HIV testing by social and demographic characteristics: Women . 343 Table A.8 Coverage of HIV testing by social and demographic characteristics: Men . 344 Table A.9 Coverage of HIV testing by sexual behaviour characteristics: Women . 345 Table A.10 Coverage of HIV testing by sexual behaviour characteristics: Men . 346 APPENDIX B ESTIMATES OF SAMPLING ERRORS . 347 Table B.1 List of selected variables for sampling errors, Zambia DHS 2018 . 349 Table B.2 Sampling errors: Total sample, Zambia DHS 2018 . 351 Table B.3 Sampling errors: Urban sample, Zambia DHS 2018 . 353 Table B.4 Sampling errors: Rural sample, Zambia DHS 2018 . 355 Tables and Figures • xvii Table B.5 Sampling errors: Central sample, Zambia DHS 2018 . 357 Table B.6 Sampling errors: Copperbelt sample, Zambia DHS 2018 . 359 Table B.7 Sampling errors: Eastern sample, Zambia DHS 2018 . 361 Table B.8 Sampling errors: Luapula sample, Zambia DHS 2018 . 363 Table B.9 Sampling errors: Lusaka sample, Zambia DHS 2018 . 365 Table B.10 Sampling errors: Muchinga sample, Zambia DHS 2018 . 367 Table B.11 Sampling errors: Northern sample, Zambia DHS 2018 . 369 Table B.12 Sampling errors: North Western sample, Zambia DHS 2018 . 371 Table B.13 Sampling errors: Southern sample, Zambia DHS 2018 . 373 Table B.14 Sampling errors: Western sample, Zambia DHS 2018 . 375 APPENDIX C DATA QUALITY TABLES . 377 Table C.1 Household age distribution . 377 Table C.2.1 Age distribution of eligible and interviewed women . 378 Table C.2.2 Age distribution of eligible and interviewed men . 378 Table C.3 Completeness of reporting . 379 Table C.4 Births by calendar years . 379 Table C.5 Reporting of age at death in days . 380 Table C.6 Reporting of age at death in months . 380 Table C.7 Completeness of information on siblings . 381 Table C.8 Sibship size and sex ratio of siblings . 381 Table C.9 Height and weight data completeness and quality for children . 382 Table C.10 Number of enumeration areas completed by month, according to province, Zambia DHS 2018 . 383 Foreword • xix FOREWORD he Government of Zambia, through the Zambia Statistics Agency and the Ministry of Health together with its cooperating partners, conducted the 2018 Zambia Demographic and Health Survey (2018 ZDHS). This study is the sixth in a series of Demographic and Health Surveys in Zambia. Previous surveys were conducted in 1992, 1996, 2001-02, 2007, and 2013-14. The ZDHS provides an opportunity to inform policy and provide data for planning, implementation, and monitoring and evaluation of national health programmes. It is designed to provide up-to-date information on health indicators, including fertility levels, nuptiality, sexual activity, fertility preferences, awareness and use of family planning methods, breastfeeding practices, nutritional status of children, early childhood and maternal mortality, maternal and child health, awareness and behaviours regarding HIV/AIDS and other sexually transmitted infections, and prevalence of HIV. The Zambia Statistics Agency wishes to express its appreciation to those involved in the implementation of the 2018 ZDHS through financial and technical support. Particular thanks go to the following: ▪ The U.S. Agency for International Development in Zambia, for providing the funding for organising and conducting the 2018 Zambia DHS; ▪ The Global Fund, the Department for International Development (DFID), and the United Nations Population Fund (UNFPA), Zambia Country Office, for providing additional funds; ▪ The University Teaching Hospital Virology Laboratory (UTH-VL) and the Tropical Diseases Research Centre (TDRC), for providing technical support in the implementation of biomarker collection and HIV testing; and ▪ ICF, for providing technical support, training of fieldwork staff, consultations, recommendations, and analyses of the data collected. The survey would not have been possible without the good work and dedication of the project staff at various levels. In particular, we wish to express our appreciation to the provincial coordinators, supervisors, interviewers, biomarker technicians, and drivers for their active participation in and contribution to this work. Above all, we appreciate the cooperation of all of the survey respondents countrywide who have made the 2018 ZDHS a success. Mulenga J.J Musepa Interim Statistician General Zambia Statistics Agency T Acronyms and Abbreviations • xxi ACRONYMS AND ABBREVIATIONS ACT Artemisinin-based combination therapy AIDS Acquired immune deficiency syndrome ANC Antenatal care ARI Acute respiratory infection ART Antiretroviral therapy ARVs Antiretroviral drugs BCG Bacille Calmette-Guérin CAPI Computer-assisted personal interviewing CDC Centers for Disease Control and Prevention CI Confidence interval CPH Census of Population and Housing CPR Contraceptive prevalence rate CSAs Census supervisory areas CSO Central Statistical Office CSPro Censuses and Survey Processing DBS Dried blood spot DFID Department for International Development DHS Demographic and Health Survey DPT Diphtheria, pertussis, and tetanus vaccine EA Enumeration area EIA Enzyme immunoassay ELISA Enzyme-linked immunosorbent assay eMTCT Elimination of mother-to-child transmission EPI Expanded Programme on Immunisation GAR Gross attendance ratio GBV Gender-based violence GF Global Fund GFR General fertility rate GPI Gender parity index HepB Hepatitis B Hib Haemophilus influenzae type b HIV Human immunodeficiency virus ICF ICF (originally, Inner City Fund) IMCI Integrated management of childhood illnesses IPTp Intermittent preventive treatment for malaria in pregnancy IPV Inactivated polio vaccine IQC Internal quality control IRBs Institutional review boards IRS Indoor residual spraying ITN Insecticide-treated net IUD Intrauterine device IYCF Infant and young child feeding xxii • Acronyms and Abbreviations LAM Lactational amenorrhoea LLIN Long-lasting insecticidal net LPG Liquid petroleum gas MGCD Ministry of Gender and Child Development MHA Ministry of Home Affairs MMR Maternal mortality ratio MNDP Ministry of National Development Planning MOH Ministry of Health MR Measles and rubella MTCT Mother-to-child transmission MWDSEP Ministry of Water Development, Sanitation, and Environmental Protection NAC National AIDS Council NAR Net attendance ratio NMEC National Malaria Elimination Centre OPV Oral polio vaccine ORS Oral rehydration salts ORT Oral rehydration therapy PCV Pneumococcal vaccine PEPFAR U.S. President’s Emergency Plan for AIDS Relief PLHIV People living with HIV PRMR Pregnancy-related mortality ratio RDT Rapid diagnostic testing RHF Government-recommended homemade fluids RR Risk ratio RV Rotavirus vaccine SD Standard deviation SDGs Sustainable Development Goals SDM Standard days method SE Standard error SEA Standard enumeration areas SP Sulfadoxine-pyrimethamine STI Sexually transmitted infection TDRC Tropical Diseases Research Centre TFR Total fertility rate TOT Training of trainers UNAIDS Joint United Nations Programme on HIV and AIDS UNFPA United Nations Population Fund UNZA University of Zambia USAID United States Agency for International Development UTH-VL University Teaching Hospital Virology Laboratory VAD Vitamin A deficiency VIP Ventilated improved pit latrine WHO World Health Organization ZAMSTATS Zambia Statistics Agency (formerly CSO) ZDHS Zambia Demographic and Health Survey Sustainable Development Goals Indicators • xxiii SUSTAINABLE DEVELOPMENT GOAL INDICATORS Zambia DHS 2018 Sex Total DHS table number Indicator Male Female 2. Zero hunger 2.2.1 Prevalence of stunting among children under 5 years of age 38.3 31.0 34.6 11.1 2.2.2 Prevalence of malnutrition among children under 5 years of age 10.2 8.7 9.5a na a) Prevalence of wasting among children under 5 years of age 4.8 3.7 4.2a 11.1 b) Prevalence of overweight among children under 5 years of age 5.4 5.0 5.2a 11.1 3. Good health and well-being 3.1.1 Maternal mortality ratio1 na na 252 15.4 3.1.2 Proportion of births attended by skilled health personnel na na 80.4 9.6 3.2.1 Under-5 mortality rate2 67 53 61 8.2 3.2.2 Neonatal mortality rate2 33 22 27 8.2 3.7.1 Proportion of women of reproductive age (aged 15-49 years) who have their need for family planning satisfied with modern methods na 66.2 na 7.13.2 3.7.2 Adolescent birth rates per 1,000 women 5.1 a) Girls aged 10-14 years3 na 3 na 5.1 b) Women aged 15-19 years4 na 135 na 5.1 3.a.1 Age-standardized prevalence of current tobacco use among persons aged 15 years and older5 18.5 0.9 9.7a 3.10.1, 3.10.2 3.b.1 Proportion of the target population covered by all vaccines included in their national programme a) Coverage of DPT containing vaccine (3rd dose)6 91.6 92.6 92.1 10.3 b) Coverage of measles containing vaccine (2nd dose)7 66.5 61.2 63.8 10.3 c) Coverage of pneumococcal conjugate vaccine (last dose in schedule)8 89.7 89.9 89.8 10.3 5. Gender equality 5.2.1 Proportion of ever-partnered women and girls aged 15 years and older subjected to physical, sexual or psychological violence by a current or former intimate partner in the previous 12 months9,10 na 32.3 na 17.12 a) Physical violence na 21.1 na 17.12 b) Sexual violence na 10.8 na 17.12 c) Psychological violence na 22.6 na 17.12 5.3.1 Proportion of women aged 20-24 years who were married or in a union before age 15 and before age 18 4.3 a) Before age 15 na 5.2 na 4.3 b) Before age 18 na 29.0 na 4.3 5.6.1 Proportion of women aged 15-49 years who make their own informed decisions regarding sexual relations, contraceptive use and reproductive health care11 na 46.5 na na 5.b.1 Proportion of individuals who own a mobile telephone12 65.7 53.0 59.3a 15.7.1, 15.7.2 Residence Urban Rural Total 7. Affordable clean energy 7.1.1 Proportion of population with access to electricity 70.6 8.1 32.8 2.4 7.1.2 Proportion of population with primary reliance on clean fuels and technology13 18.0 1.5 8.0 2.4 Sex Male Female Total 8. Decent work and economic growth 8.10.2 Proportion of adults (15 years and older) with an account at a bank or other financial institution or with a mobile-money-service provider14 17.6 10.8 14.2a 15.7.1, 15.7.2 16. Peace, justice, and strong institutions 16.9.1 Proportion of children under 5 years of age whose births have been registered with a civil authority 14.1 14.0 14.0 2.11 17. Partnerships for the goals 17.8.1 Proportion of individuals using the Internet15 26.0 12.1 19.0a 3.5 na = Not applicable 1 Expressed in terms of maternal deaths per 100,000 live births in the 7-year period preceding the survey 2 Expressed in terms of deaths per 1,000 live births for the 5-year period preceding the survey 3 Equivalent to the age-specific fertility rate for girls age 10-14 for the 3-year period preceding the survey, expressed in terms of births per 1,000 girls age 10-14 4 Equivalent to the age-specific fertility rate for women age 15-19 for the 3-year period preceding the survey, expressed in terms of births per 1,000 women age 15-19 5 Data are not age-standardized and are available for women and men age 15-49 only. 6 The percentage of children age 12-23 months who received three doses of DPT-HepB-Hib 7 The percentage of children age 24-35 months who received two doses of measles and rubella vaccine 8 The percentage of children age 12-23 months who received three doses of pneumococcal vaccine 9 Data are available for women age 15-49 who have ever been in union only. 10 In the DHS, psychological violence is termed emotional violence. 11 Data are available for currently married women who are not pregnant only. 12 Data are available for women and men age 15-49 only. 13 Measured as the percentage of the population using clean fuel for cooking. 14 Data are available for women and men age 15-49 who have and use an account at a bank or other financial institution; information on use of a mobile-money- service provider is not available. 15 Data are available for women and men age 15-49 who have used the internet in the past 12 months. a The total is calculated as the simple arithmetic mean of the percentages in the columns for males and females. Reading and Understanding Tables from the 2018 ZDHS • xxv READING AND UNDERSTANDING TABLES FROM THE 2018 ZAMBIA DEMOGRAPHIC AND HEALTH SURVEY (ZDHS) he new format of the 2018 ZDHS final report is based on approximately 200 tables of data. For quick reference, they are located at the end of each chapter and can be accessed through links in the pertinent text (electronic version). Additionally, this more reader-friendly version features about 90 figures that clearly highlight trends, subnational patterns, and background characteristics. Large colourful maps display breakdowns for provinces in Zambia. The text has been simplified to highlight key points in bullets and to clearly identify indicator definitions in boxes. While the text and figures featured in each chapter highlight some of the most important findings from the tables, not every finding can be discussed or displayed graphically. For this reason, ZDHS data users should be comfortable reading and interpreting tables. The following pages provide an introduction to the organization of ZDHS tables, the presentation of background characteristics, and a brief summary of sampling and understanding denominators. In addition, this section provides some exercises for users as they practice their new skills in interpreting ZDHS tables. T xxvi • Reading and Understanding Tables from the 2018 ZDHS Example 1 – Exposure to Mass Media: Women A Question Asked of All Survey 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, according to background characteristics, Zambia DHS 2018 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 12.4 36.8 29.5 4.8 47.5 3,000 20-24 10.1 37.9 33.1 4.3 46.0 2,733 25-29 10.4 40.4 37.6 5.2 43.3 2,237 30-34 10.4 43.2 38.4 6.0 42.1 1,862 35-39 10.1 37.3 35.9 5.3 46.2 1,697 40-44 9.2 35.2 36.0 5.4 48.6 1,253 45-49 11.3 28.5 34.9 4.9 52.5 900 Residence Urban 14.8 67.0 43.6 9.1 23.8 6,374 Rural 7.1 12.4 26.6 1.5 65.4 7,309 Province Central 11.1 30.7 38.6 4.0 46.7 1,165 Copperbelt 14.5 62.8 42.2 8.3 25.4 2,201 Eastern 16.6 19.0 33.7 3.6 51.6 1,605 Luapula 6.2 22.3 43.3 2.6 47.8 1,071 Lusaka 15.2 72.9 43.1 10.7 21.4 2,733 Muchinga 7.5 17.3 31.2 1.7 61.7 754 Northern 4.1 15.4 24.6 1.5 68.4 1,054 North Western 1.0 18.9 11.8 0.4 77.4 718 Southern 5.3 22.8 27.0 2.3 60.9 1,574 Western 9.4 14.4 19.7 2.3 70.7 808 Education No education 0.3 12.5 21.9 0.0 72.0 1,054 Primary 4.6 20.4 26.5 0.9 60.9 6,059 Secondary 15.0 54.0 42.0 7.2 31.1 5,816 Higher 40.5 88.5 59.1 28.9 5.8 755 Wealth quintile Lowest 4.7 3.3 16.6 0.3 79.0 2,442 Second 6.0 4.6 25.3 0.4 69.8 2,387 Middle 7.3 11.6 30.4 1.3 62.8 2,477 Fourth 8.9 54.1 39.1 4.2 32.1 3,011 Highest 22.4 91.2 52.9 15.4 5.4 3,367 Total 10.7 37.8 34.5 5.1 46.0 13,683 Step 1: Read the title and subtitle, highlighted in orange in the table above. They tell you the topic and the specific population group being described. In this case, the table is about women age 15-49 and their exposure to different types of media. All eligible female respondents age 15-49 were asked these questions. Step 2: Scan the column headings—highlighted in green in Example 1. They describe how the information is categorized. In this table, the first three columns of data show different types of media that women access at least once a week. The fourth column shows women who access all three types of media, while the fifth column shows women who do not access any of the three types of media on a weekly basis. The last column lists the number of women age 15-49 interviewed in the survey. Step 3: Scan the row headings—the first vertical column highlighted in blue in Example 1. These show the different ways the data are divided into categories based on population characteristics. In this case, the table presents women’s exposure to media by age, urban-rural residence, province, level of education, and wealth quintile. Most of the tables in the ZDHS report will be divided into these same categories. Step 4: Look at the row at the bottom of the table highlighted in red. These percentages represent the totals of all women age 15-49 and their weekly access to different types of media. In this case, 10.7%* of women age 15-49 read a newspaper at least once a week, 37.8% watch television at least weekly, and 34.5% listen to the radio on a weekly basis. 1 2 3 4 5 Reading and Understanding Tables from the 2018 ZDHS • xxvii Step 5: To find out what percentage of women with higher education listen to the radio on a weekly basis, draw two imaginary lines, as shown on the table. This shows that 59.1% of women age 15-49 with higher education listen to the radio at least once a week. By looking at patterns by background characteristics, we can see how exposure to mass media varies across Zambia. Mass media are often used to communicate health messages. Knowing how mass media exposure varies among different groups can help programme planners and policymakers determine how to most effectively reach their target populations. *For the purpose of this document data are presented exactly as they appear in the table including decimal places. However, the text in the remainder of this report rounds data to the nearest whole percentage point. Practice: Use the table in Example 1 to answer the following questions: a) What percentage of women in Zambia do not access any of the three media at least once a week? b) Which age group of women is most likely to watch television at least once a week? c) Compare women in urban areas to women in rural areas—which group is more likely to read a newspaper at least once a week? d) What are the lowest and highest percentages (range) of women who do not access any of the three media at least once a week by province? e) Is there a clear relationship in exposure to newspapers on a weekly basis by education level? f) Is there a clear relationship in exposure to television on a weekly basis by wealth quintile? Answers: a) 46.0% b) Women age 30-34: 43.2% of women in this age group watch television on a weekly basis. c) Women in urban areas; 14.8% of urban women read the newspaper at least once a week, compared to 7.1% of rural women. d) Women with no exposure to media ranges from a low of 21.4% in Lusaka province to a high of 77.4% in North Western province. e) Yes. Women’s exposure to newspapers on a weekly basis increases as a woman’s level of education increases; 0.3% of women with no education read the newspaper at least once a week, compared to 40.5% of women with higher education. f) Yes. Women’s exposure to television on a weekly basis increases with household wealth, from 3.3% of women in the poorest households to 91.2% of women in the wealthiest households. xxviii • Reading and Understanding Tables from the 2018 ZDHS Example 2 – Prevalence and Treatment of Symptoms of ARI A Question Asked of a Subgroup of Survey Respondents Table 10.5 Prevalence and treatment of symptoms of ARI Among children under age 5, percentage who had symptoms of acute respiratory infection (ARI) in the 2 weeks preceding the survey, and among children with symptoms of ARI in the 2 weeks preceding the survey, percentage for whom advice or treatment was sought, according to background characteristics, Zambia DHS 2018 Among children under age 5: Among children under age 5 with symptoms of ARI: Background characteristic Percentage with symptoms of ARI1 Number of children Percentage for whom advice or treatment was sought2 Percentage for whom treatment was sought same or next day Number of children Age in months <6 1.1 1,036 * * 11 6-11 2.3 924 * * 21 12-23 2.8 1,891 (78.4) (39.8) 52 24-35 2.0 1,862 (83.0) (57.1) 38 36-47 1.3 1,866 (74.9) (47.5) 23 48-59 0.9 1,782 * * 15 Sex Male 1.6 4,666 81.1 38.8 75 Female 1.8 4,695 71.6 41.8 86 Mother’s smoking status Smokes cigarettes/ tobacco 9.1 70 * * 6 Does not smoke 1.7 9,291 76.2 40.7 155 Cooking fuel Electricity 0.8 646 * * 5 Solar power (0.0) 26 * * 0 Kerosene * 0 * * 0 Coal/lignite * 2 * * 0 Charcoal 1.2 3,516 (91.4) (47.5) 43 Wood 2.2 5,169 69.1 36.9 113 Animal dung * 0 * * 0 Other * 1 * * 0 Residence Urban 1.2 3,307 (88.9) (53.7) 39 Rural 2.0 6,054 71.9 36.1 122 Province Central 1.5 819 * * 12 Copperbelt 0.9 1,166 * * 10 Eastern 1.4 1,266 * * 17 Luapula 2.3 877 * * 21 Lusaka 0.3 1,446 * * 5 Muchinga 0.8 569 * * 5 Northern 3.8 846 (56.9) (27.8) 32 North Western 0.0 517 * * 0 Southern 3.2 1,242 * * 39 Western 3.3 613 (84.2) (33.9) 20 Mother’s education No education 2.1 951 * * 20 Primary 1.6 4,763 64.4 26.5 78 Secondary 1.8 3,276 (87.7) (52.7) 59 Higher 1.2 371 * * 5 Wealth quintile Lowest 2.4 2,343 69.4 35.5 57 Second 1.9 2,079 (79.7) (41.0) 40 Middle 1.2 1,735 (59.7) (28.9) 21 Fourth 1.4 1,733 * * 25 Highest 1.2 1,469 * * 18 Total 1.7 9,361 76.0 40.4 161 Note: Figures in parentheses are based on 25-49 unweighted cases. An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. 1 Symptoms of ARI include short, rapid breathing that is chest-related and/or difficult breathing that is chest-related. 2 Includes advice or treatment from the public and private health sectors, pharmacies, shops, markets, and itinerant drug seller. Excludes advice or treatment from a traditional practitioner. Step 1: Read the title and subtitle. In this case, the table is about two separate groups of children: all children under age 5 (a) and children under age 5 with symptoms of acute respiratory infection (ARI) in the 2 weeks before the survey (b). 2 1 a b 4 3 Reading and Understanding Tables from the 2018 ZDHS • xxix Step 2: Identify the two panels. First, identify the columns that refer to all children under age 5 (a), and then isolate the columns that refer only to children under age 5 with symptoms of ARI in the 2 weeks before the survey (b). Step 3: Look at the first panel. What percentage of children under age 5 had symptoms of ARI in the 2 weeks before the survey? It’s 1.7%. Now look at the second panel. How many children under age 5 are there who had symptoms of ARI in the 2 weeks before the survey? It’s 161 children, or 1.7% of the 9,361 children under age 5 (with rounding). The second panel is a subset of the first panel. Step 4: Only 1.7% of children under 5 had symptoms of ARI in the 2 weeks before the survey. Once these children are further divided into the background characteristic categories, there may be too few cases for the percentages to be reliable. • Among children under age 5 with symptoms of ARI in the 2 weeks before the survey in urban areas, what percentage of children under age 5 had treatment or advice sought? It’s 88.9%. This percentage is in parentheses because there are between 25 and 49 cases (unweighted) in this category. Readers should use this number with caution—it may not be reliable. (For more information on weighted and unweighted numbers, see Example 3.) • Among children under age 5 with symptoms of ARI in the 2 weeks before the survey, what percentage of children in Central province had treatment or advice sought? There is no number in this cell—only an asterisk. This is because fewer than 25 children under age 5 who had recent symptoms of ARI in Central province had advice or treatment sought. Results for this group are not reported. The subgroup is too small, and therefore the data are not reliable. Note: When parentheses or asterisks are used in a table, the explanation will be noted under the table. If there are no parentheses or asterisks in a table, you can proceed with confidence that enough cases were included in all categories that the data are reliable. xxx • Reading and Understanding Tables from the 2018 ZDHS Example 3 – Understanding Sampling Weights in ZDHS Tables A sample is a group of people who have been selected for a survey. In the ZDHS, the sample is designed to represent the national population age 15-49. In addition to national data, most countries want to collect and report data on smaller geographical or administrative areas. However, doing so requires a large enough sample size in each area. For the 2018 ZDHS, the survey sample is representative at the national and provincial levels, and for urban and rural areas. To generate statistics that are representative of the country as a whole and the 10 provinces, the number of women surveyed in each province should contribute to the size of the total (national) sample in proportion to size of the province. However, if some provinces have small populations, then a sample allocated in proportion to each province’s population may not include sufficient women from each province for analysis. To solve this problem, provinces with small populations are oversampled. For example, let’s say that you have enough money to interview 13,683 women and want to produce results that are representative of Zambia as a whole and its provinces (as in modified Table 3.1). However, the total population of Zambia is not evenly distributed among the provinces: some provinces, such as Lusaka, are heavily populated while others, such as North Western, are not. Thus, North Western must be oversampled. A sampling statistician determines how many women should be interviewed in each province in order to get reliable statistics. The blue column (1) in the table at the right shows the actual number of women interviewed in each province. Within the provinces, the number of women interviewed ranges from 1,081 in North Western to 1,775 in Lusaka. The number of interviews is sufficient to get reliable results in each province. With this distribution of interviews, some provinces are overrepresented and some provinces are underrepresented. For example, the population in Lusaka is about 20% of the population in Zambia, while North Western’s population contributes only 5% of the population in Zambia. But as the blue column shows, the number of women interviewed in Lusaka accounts for only about 13% of the total sample of women interviewed (1,775/13,683) and the number of women interviewed in North Western accounts for 8% of women interviewed (1,081/13,683). This unweighted distribution of women does not accurately represent the population. In order to get statistics that are representative of Zambia, the distribution of the women in the sample needs to be weighted (or mathematically adjusted) such that it resembles the true distribution in the country. Women from a small province, like North Western, should only contribute a small amount to the national total. Women from a large province, like Lusaka, should contribute much more. Therefore, DHS statisticians mathematically calculate a “weight” that is used to adjust the number of women from each province so that each province’s contribution to the total is proportional to the actual population of the province. The numbers in the purple column (2) represent the “weighted” values. The weighted values can be smaller or larger than the unweighted values at province level. The total national sample size of 13,683 women has not changed after weighting, but the distribution of the women in the provinces has been changed to represent their contribution to the total population size. How do statisticians weight each category? They take into account the probability that a woman was selected in the sample. If you were to compare the green column (3) to the actual population distribution Table 3.1 Background characteristics of respondents Percent distribution of women age 15-49 by selected background characteristics, Zambia DHS 2018 Women Background characteristic Weighted percent Weighted number Unweighted number Province Central 8.5 1,165 1,397 Copperbelt 16.1 2,201 1,615 Eastern 11.7 1,605 1,536 Luapula 7.8 1,071 1,414 Lusaka 20.0 2,733 1,775 Muchinga 5.5 754 1,183 Northern 7.7 1,054 1,239 North Western 5.2 718 1,081 Southern 11.5 1,574 1,347 Western 5.9 808 1,096 Total 15-49 100.0 13,683 13,683 1 2 3 Reading and Understanding Tables from the 2018 ZDHS • xxxi of Zambia, you would see that women in each province are contributing to the total sample with the same weight that they contribute to the population of the country. The weighted number of women in the survey now accurately represents the proportion of women who live in Lusaka and the proportion of women who live in North Western. With sampling and weighting, it is possible to interview enough women to provide reliable statistics at national and provincial levels. In general, only the weighted numbers are shown in each of the ZDHS tables, so don’t be surprised if these numbers seem low: they may actually represent a larger number of women interviewed. xxxii • Map of Zambia Introduction and Survey Methodology • 1 INTRODUCTION AND SURVEY METHODOLOGY 1 he 2018 Zambia Demographic and Health Survey (ZDHS) was implemented by the Zambia Statistics Agency (ZamStats) in collaboration with the Ministry of Health (MOH). Data collection took place from 18 July 2018 to 24 January 2019. ICF provided technical assistance through The DHS Program, which is funded by the United States Agency for International Development (USAID) and offers financial support and technical assistance for population and health surveys in countries worldwide. Other agencies and organisations that facilitated the successful implementation of the survey through technical or financial support were the Global Fund (GF), the Department for International Development (DFID) in Zambia, and the United Nations Population Fund (UNFPA). 1.1 SURVEY OBJECTIVES The primary objective of the 2018 ZDHS was to provide up-to-date estimates of basic demographic and health indicators. Specifically, the ZDHS collected information on: ▪ Fertility levels and preferences; contraceptive use; maternal and child health; infant, child, and neonatal mortality levels; maternal mortality; and gender, nutrition, and awareness regarding HIV/AIDS and other health issues relevant to the achievement of the Sustainable Development Goals (SDGs) ▪ Ownership and use of mosquito nets as part of the national malaria eradication programmes ▪ Health-related matters such as breastfeeding, maternal and childcare (antenatal, delivery, and postnatal), children’s immunisations, and childhood diseases ▪ Anaemia prevalence among women age 15-49 and children age 6-59 months ▪ Nutritional status of children under age 5 (via weight and height measurements) ▪ HIV prevalence among men age 15-59 and women age 15-49 and behavioural risk factors related to HIV ▪ Assessment of situation regarding violence against women The information collected through the ZDHS is intended to assist policymakers and programme managers in evaluating and designing programmes and strategies for improving the health of the country’s population. 1.2 SAMPLE DESIGN The sampling frame used for the 2018 ZDHS is the Census of Population and Housing (CPH) of the Republic of Zambia, conducted in 2010 by ZamStats. Zambia is divided into 10 provinces. Each province is subdivided into districts, each district into constituencies, and each constituency into wards. In addition to these administrative units, during the 2010 CPH each ward was divided into convenient areas called census supervisory areas (CSAs), and in turn each CSA was divided into enumeration areas (EAs). An enumeration area is a geographical area assigned to an enumerator for the purpose of conducting a census count; according to the Zambian census frame, each EA consists of an average of 110 households. The current version of the EA frame for the 2010 CPH was updated to accommodate some changes in districts and constituencies that occurred between 2010 and 2017. The list of EAs incorporates census T 2 • Introduction and Survey Methodology information on households and population counts. Each EA has a cartographic map delineating its boundaries, with identification information and a measure of size, which is the number of residential households enumerated in the 2010 CPH. This list of EAs was used as the sampling frame for the 2018 ZDHS. The 2018 ZDHS followed a stratified two-stage sample design. The first stage involved selecting sample points (clusters) consisting of EAs. EAs were selected with a probability proportional to their size within each sampling stratum. A total of 545 clusters were selected. The second stage involved systematic sampling of households. A household listing operation was undertaken in all of the selected clusters. During the listing, an average of 133 households were found in each cluster, from which a fixed number of 25 households were selected through an equal probability systematic selection process, to obtain a total sample size of 13,625 households. Results from this sample are representative at the national, urban and rural, and provincial levels. All women age 15-49 and men age 15-59 who were either permanent residents of the selected households or visitors who stayed in the households the night before the survey were eligible to be interviewed. 1.3 QUESTIONNAIRES Four questionnaires were used in the 2018 ZDHS: the Household Questionnaire, the Woman’s Questionnaire, the Man’s Questionnaire, and the Biomarker Questionnaire. The questionnaires, based on The DHS Program’s Model Questionnaires, were adapted to reflect the population and health issues relevant to Zambia. Input on questionnaire content was solicited from various stakeholders representing government ministries and agencies, nongovernmental organisations, and international cooperating partners. After all questionnaires were finalised in English, they were translated into seven local languages: Bemba, Kaonde, Lozi, Lunda, Luvale, Nyanja, and Tonga. In addition, information about the fieldworkers for the survey was collected through a self-administered Fieldworker Questionnaire. The Household Questionnaire listed all members of and visitors to selected households. Basic demographic information was collected on each person listed, including age, sex, marital status, education, and relationship to the head of the household. For children under age 18, parents’ survival status was determined. The data on age and sex of household members were used to identify women and men eligible for individual interviews. The Household Questionnaire also collected information on characteristics of the household, such as source of water; type of toilet facilities; materials used for flooring, external walls, and roofing; ownership of various household goods; and ownership and use of mosquito nets. In addition, all households were eligible to have their salt tested for the presence of iodine. However, due to an uneven distribution of the two types of salt test kits among the fieldworkers, the tests were not uniformly applied, thus compromising the reliability of the results. Accordingly, the results are not included in this report. The Woman’s Questionnaire was used to collect information from all eligible women age 15-49. These women were asked questions on the following topics: ▪ Background characteristics (including age, education, and media exposure) ▪ Reproduction and child mortality ▪ Contraception ▪ Antenatal, delivery, and postnatal care ▪ Vaccinations and childhood illnesses ▪ Maternal and child health and nutrition ▪ Marriage and sexual activity ▪ Fertility preferences ▪ Women’s work and husbands’ background characteristics ▪ Knowledge, awareness, and behaviour regarding HIV/AIDS and other sexually transmitted infections (STIs) Introduction and Survey Methodology • 3 ▪ Knowledge, attitudes, and behaviour related to other health issues (e.g., injections, smoking, childhood illnesses, and pregnancy and childbirth) ▪ Fistula ▪ Adult and maternal mortality ▪ Domestic violence ▪ Women’s empowerment The Man’s Questionnaire was used to collect information from all eligible men age 15-59. These men were asked questions on the following topics: ▪ Background characteristics ▪ Reproduction ▪ Contraception ▪ Marriage and sexual activity ▪ Fertility preferences ▪ Employment and gender roles ▪ HIV/AIDS ▪ Other health issues The Biomarker Questionnaire was used to record the results of anthropometry measurements and haemoglobin and HIV testing. The signature of the fieldworker (biomarker technician) who conducted the testing was included on the questionnaire. The Fieldworker Questionnaire collects data on the basic characteristics of fieldworkers and can serve as a tool in conducting analyses of data quality. Fieldworkers filled out a two-page self-administered questionnaire on their general background characteristics. ZamStats distributed and collected this questionnaire before the fieldworkers entered the field. No personal identifiers were attached to the ZDHS fieldworkers’ data files. The Household, Woman’s, and Man’s Questionnaires were programmed into tablet computers to facilitate computer-assisted personal interviewing (CAPI) for data collection purposes, with the capability to choose any of the eight specified languages for each questionnaire. The Biomarker Questionnaire was completed on paper during data collection and then entered into the CAPI system in the field before the data collection teams completed each cluster. The protocols for survey methodology, biomarker measurements, and all instruments were approved by institutional review boards (IRBs) at ICF and the Tropical Diseases Research Centre (TDRC) in Zambia. Both IRBs approved the protocols before the commencement of data collection activities. 1.4 ANTHROPOMETRY, ANAEMIA TESTING, AND HIV TESTING The 2018 ZDHS incorporated three biomarkers: anthropometry, haemoglobin testing, and HIV testing. All data related to the coverage of the anthropometric measures and the results of the haemoglobin and HIV testing were recorded in the Biomarker Questionnaire. HIV testing was conducted via two methods: rapid diagnostic testing (RDT), which provided respondents with immediate feedback regarding their HIV status, and collection of dried blood spot (DBS) samples. After collection, the DBS samples were sent to a central laboratory for testing, where they were used to produce a national HIV prevalence estimate. 1.4.1 Anthropometry Measurements In all households, height and weight measurements were recorded for children age 0-59 months. Weight measurements were obtained using lightweight, electronic SECA 878 scales with a digital screen and the mother and child function. Height measurements were carried out with measuring boards made by Shorr 4 • Introduction and Survey Methodology Productions. Children younger than age 24 months were measured while lying down (recumbent) on the board, while standing height was measured for children older than 24 months. 1.4.2 Anaemia Testing Blood specimens were collected from all children age 6-59 months and women age 15-49 who consented to testing for anaemia. A consent statement was read to all eligible respondents. This statement explained the purpose of the test, informed them that the results would be made available as soon as the test was completed, and requested permission for the test to be carried out. For young women age 15-17 who had never been married, the consent of a parent or guardian was sought first, followed by their assent. For children age 6-59 months, consent was provided by a parent or guardian. Blood samples were drawn from a finger prick (or a heel prick for young children with small fingers or children less than 12 months old) by pricking the finger or heel with a retractable, safety lancet and the third blood drop was collected in a microcuvette for haemoglobin measurement. Haemoglobin analysis was carried out on-site using a battery-operated portable HemoCue 201+ analyser, which produces a result in less than 1 minute. Results were given verbally and in writing to the child’s parents/guardians. Parents of children with a haemoglobin level below 7 g/dl were given a referral form with the haemoglobin level indicated and advised to take the child to a health facility for follow-up care. Likewise, non-pregnant women and pregnant women were also given referral forms and referred for follow-up care at a health facility if their haemoglobin levels were below 7 g/dl and 9 g/dl, respectively. All households in which anthropometry measurements, anaemia testing, or both were conducted were given a brochure explaining the causes of and ways to prevent anaemia. Lancets and other supplies and equipment used during sample collection (a HemoCue microcuvette, gloves, gauze, alcohol swab, bandage packaging, and waste collection bag) were disposed of safely, usually by taking the materials to a nearby health facility that uses proper protocols for the disposal of biohazardous waste. 1.4.3 HIV Testing All women and men interviewed with the individual questionnaires were eligible for HIV testing. The survey featured a parallel system for HIV testing in which a rapid diagnostic testing algorithm was performed in the household for respondents who wished to be informed of their status, and DBS specimens were collected and transported to a central lab for anonymised testing. HIV prevalence for the survey was based on the laboratory test results. The national RDT algorithm in Zambia at the time of the 2018 ZDHS implementation consisted of a screening test (Determine® HIV 1/2) followed by confirmation of reactive specimens with a second rapid test (Uni-gold HIV 1/2). To test respondents via RDT, a blood sample was collected directly from a finger prick using a sample collection device supplied with the RDT kit. Dedicated nurse counsellors who provided pre- and post-test counselling conducted the HIV rapid testing. Pre-test counselling included explanations of HIV infection and transmission, the meaning of test results, risks associated with sexual behaviours, and how to prevent and treat HIV and other sexually transmitted infections. Post-test counselling messages were tailored to participants’ HIV results and risk profiles. Testing and delivery of results at home were done after creating conditions that would guarantee the confidentiality of respondents. All participants with HIV-seropositive or indeterminate results were referred to the nearest health facility for further care and treatment. For the purposes of HIV testing in the central lab using DBS samples, at the time of collection of the blood sample, a unique and random barcoded identification number was assigned to each participant who consented to testing. Sheets of peel-off labels with the unique barcodes were pre-printed for use in the Introduction and Survey Methodology • 5 field. Matching barcode labels were affixed to the Biomarker Questionnaire, a fresh filter paper card, and a blood sample transmittal sheet. Respondents were also asked whether they would consent to having the laboratory store their blood sample for future testing. If respondents did not consent to additional testing of their blood sample in the future, their refusal was recorded on the Biomarker Questionnaire and on the filter paper card. Blood samples were dried overnight and packaged for storage the following morning. Approximately every 2 weeks, or more frequently, all DBS samples and transmittal sheets from the clusters were collected from teams in the field by fieldwork monitors or provincial coordinators and transported to the University Teaching Hospital Virology Laboratory (UTH-VL) for registration and processing. Each specimen was then assigned a unique serial laboratory number during the registration process at the laboratory before being stored in a freezer at a temperature of at least -20°C. Before samples were tested, all personal identifiers were removed from the data file. Laboratory HIV testing of DBS samples was guided by the testing algorithm shown in Figure 1.1, which was agreed upon by ICF and the laboratory. Enzyme immunoassay (EIA) kits were obtained from different manufacturers and had different antigen preparations. The first testing assay was Bioelisa HIV-1+2 Ag/Ab (Biokit, Spain); the second was Genscreen ULTRA HIV Ag/Ab (Bio-Rad, France). The Geenius HIV 1/2 Supplemental Assay (Bio-Rad, France) was used to confirm the HIV status of all double-EIA positive samples. Five percent of the samples which tested negative on the first assay were retested as part of the internal quality control (IQC). Figure 1.1 2018 ZDHS HIV testing algorithm 1.5 PRETEST Thirty participants took part in a training session to pretest the ZDHS survey questionnaires both on paper and via CAPI over a 4-week period from 3-28 April 2018 outside of Lusaka District. An additional eight participants attended the biomarker training portion of the pretest, which ran from 16-28 April. The training utilised a variety of different learning tools such as formal lectures, informal discussions on various practice scenarios, videos, and hands-on demonstrations. In addition to the aforementioned training, the biomarker technicians participated in an anthropometry standardisation exercise and a health clinic visit. From 25-27 April, interviewers and biomarker technicians conducted practice fieldwork to solidify skills learned during pretest training and to provide a simulated fieldwork experience to test survey materials. A1 A2 A1-A2- A1-A2+ NEGATIVE NEGATIVE A2 A1+ A2- A1+ A2+ A1+ A2- (A1-A2+) A1- A2- A1+ A2+ NEGATIVE INCONCLUSIVE A3 A1+ A2+ A3+ A1+ A2+ A3- A1+ A2+ A3 IND POSITIVE A1- A1+ NEGATIVE 5% IQC REPEAT A1 & A2 IN PARALLEL NEGATIVE A3 A1+ A2- A3+ (A1-A2+A3+) A1+ A2- A3- (A1-A2+A3-) A1+ A2- A3 IND (A1-A2+A3 IND) INCONCLUSIVE INDETERMINATE 6 • Introduction and Survey Methodology The practice occurred in two EAs, one urban and one rural, that were both near the training venue. Each area had 26 selected households, but these were divided in half to create four practice clusters (one for each team) of 13 households. To complete the fieldwork, each interviewer had to complete at least one household interview per day. While the interviewers recorded responses on tablet computers using CAPI, the Biomarker Questionnaires were first filled out on paper and later entered into the CAPI system by the interviewers. At the end of each day, both during and after the pretest fieldwork, debriefing sessions were held and questionnaires were modified based on lessons drawn from the exercise. 1.6 TRAINING OF FIELD STAFF A training of trainers (TOT) to prepare the master trainers for the main training was conducted from 11-12 June 2018. Fifteen trainers were selected. The trainers, employed through the ZamStats and the MOH, later served as the team supervisors and provincial coordinators during the ZDHS data collection. ZamStats recruited 123 people, including 24 supervisors and 99 interviewers, to attend the training on the questionnaire content. The training consisted of lectures, demonstrations, and practice interviews. Fifty- three biomarker technicians attended a parallel training course on conducting biomarker tests. The main fieldwork training, conducted from 13 June to 9 July 2018, was led by the master trainers and backstopped by staff from The DHS Program. Sessions discussed concepts, procedures, and methodologies related to conducting the survey, and participants were guided through the questionnaires both on paper and in CAPI. The training included presentations, lectures, hands-on exercises, mock interviews, role- plays, group work, and quizzes. In addition, subject specialists from the MOH were invited to make short presentations on programmes in Zambia that provide services in the areas of family planning and reproductive health, HIV/AIDS and other STIs, childhood immunisation, child health and nutrition, and fistula. The biomarker classroom portion of the training commenced on 18 June and continued through 9 July. This training was led by staff from The DHS Program with the assistance of staff members from ZamStats, MOH, TDRC, and UTH-VL. Biomarker training included classroom instruction that focused on anthropometry measurements, anaemia and HIV testing, appropriate procedures for obtaining informed consent, recording of information in the Biomarker Questionnaire, reporting test results back to respondents with referrals as needed, and pre- and post-test HIV counselling. The facilitators used learning tools similar to those used during the pretest, including an anthropometry standardisation exercise, a health clinic visit, and 3 days of field practice. Throughout the training, each individual’s performance was evaluated. Those determined to be capable of successfully conducting the tests were placed on teams as supervisors, interviewers, or biomarker technicians. The supervisors received additional training covering their roles and responsibilities, including how they should organise fieldwork, monitor interviews, and conduct quality control checks on both paper and CAPI questionnaires. From 6-8 July, interviewers and biomarker technicians conducted practice fieldwork to solidify skills learned during the training and provide a simulated fieldwork experience to test the survey materials. The practice occurred in six EAs, three in the urban locality of Chawama and three in the rural locality of Shimabala. Each area contained 52 selected households, but areas were divided into four mini-clusters of 13 households (creating 24 mini-clusters). To complete the practice fieldwork, each interviewer had to complete at least one household per day. All of the interviewers and supervisors had the opportunity to practice household and individual interviews, while the biomarker technicians practiced testing and measuring eligible household members. Introduction and Survey Methodology • 7 1.7 FIELDWORK Data collection was carried out from 17 July 2018 to 24 January 2019 by 22 teams, with each team consisting of seven members typically featuring the following composition: one supervisor, three female interviewers, one male interviewer, and two biomarker technicians. Fieldwork monitoring was an integral part of the ZDHS. Senior technical staff from ZamStats, the Department of Population Studies at the University of Zambia (UNZA), UTH-VL, and TDRC visited teams regularly to review their work and monitor data quality. ZamStats organised three groups of fieldwork monitors. The first group consisted of 10 provincial coordinators, each responsible for supervising the work of the teams in one province. They helped teams resolve any issues that arose in accessing clusters or while conducting their work, and they supported the technical work of the interviewers. The second group consisted of five biomarker monitors, each responsible for two provinces, who supervised the work of the biomarker technicians. The final supervisory group consisted of three information technology (IT) staff, who were deployed to teams on an as-needed basis to resolve CAPI- related issues. Three staff members from The DHS Program each independently visited teams to monitor data collection and biomarker collection. These visits occurred 17-21 July, 17 September-1 October, and 2-5 October 2018. During field visits, monitors provided the teams they visited with critical feedback to improve their performance. All monitors used the ZDHS field-check tables, based on data from the completed clusters, to illustrate problems specific to each team visited. 1.8 DATA PROCESSING All electronic data files were transferred via a secure internet file streaming system to the ZamStats central office in Lusaka, where they were stored on a password-protected computer. The data processing operation included secondary editing, which required resolution of computer-identified inconsistencies and coding of open-ended questions. The data were processed by two IT specialists and one secondary editor who took part in the main fieldwork training; they were supervised remotely by staff from The DHS Program. Data editing was accomplished using CSPro software. During the fieldwork, field-check tables were generated to check various data quality parameters, and specific feedback was given to the teams to improve performance. Secondary editing and data processing were initiated in July 2018 and completed in March 2019. 1.9 RESPONSE RATES Table 1.1 shows response rates for the 2018 ZDHS. Of the 13,595 households in the sample, 12,943 were occupied. Of these occupied households, 12,831 were successfully interviewed, yielding a response rate of 99%. In the interviewed households, 14,189 women age 15-49 were identified as eligible for individual interviews; 13,683 women were interviewed, yielding a response rate of 96% (the same rate achieved in the 2013-14 survey). A total of 13,251 men were eligible for individual interviews; 12,132 of these men were interviewed, producing a response rate of 92% (a 1 percentage point increase from the previous survey). Of the households successfully interviewed, 12,505 were interviewed in 2018 and 326 in 2019. As the large majority of households were interviewed in 2018 and the year for reference indicators is 2018, this report is considered the 2018 ZDHS. 8 • Introduction and Survey Methodology Table 1.1 Results of the household and individual interviews Number of households, number of interviews, and response rates, according to residence (unweighted), Zambia DHS 2018 Residence Total Result Urban Rural Household interviews Households selected 4,944 8,651 13,595 Households occupied 4,768 8,175 12,943 Households interviewed 4,714 8,117 12,831 Household response rate1 98.9 99.3 99.1 Interviews with women age 15-49 Number of eligible women 5,766 8,423 14,189 Number of eligible women interviewed 5,513 8,170 13,683 Eligible women response rate2 95.6 97.0 96.4 Interviews with men age 15-59 Number of eligible men 5,078 8,173 13,251 Number of eligible men interviewed 4,498 7,634 12,132 Eligible men response rate2 88.6 93.4 91.6 1 Households interviewed/households occupied 2 Respondents interviewed/eligible respondents Housing Characteristics and Household Population • 9 HOUSING CHARACTERISTICS AND HOUSEHOLD POPULATION 2 Key Findings ▪ Drinking water: In Zambia, 72% of households have access to an improved water source. ▪ Sanitation: Fifty-four percent of households have access to improved sanitation. ▪ Electricity: Thirty-four percent of households have electricity (69% in urban areas and 8% in rural areas). ▪ Household population and composition: The Zambian population is relatively young; almost half of the population (48%) is age 0-14, while only 3% is age 65 or older. nformation on the socioeconomic characteristics of the household population in the 2018 ZDHS provides a context to interpret demographic and health indicators and can furnish an approximate indication of the representativeness of the survey. In addition, this information sheds light on the living conditions of the population. This chapter presents information on sources of drinking water, sanitation, exposure to smoke inside the home, wealth, handwashing, household population and composition, educational attainment, school attendance, birth registration, and family living arrangements. 2.1 HOUSING CHARACTERISTICS 2.1.1 Drinking Water Sources and Treatment Improved sources of drinking water Include piped water, public taps, standpipes, tube wells, boreholes, protected dug wells and springs, rainwater, water delivered via a tanker truck or a cart with a small tank, and bottled water. Sample: Households In Zambia, 72% of households have access to an improved water source, although access is more predominant in urban (92%) than rural (58%) households (Table 2.1.1). The most common sources of drinking water in urban households are water piped into the household’s dwelling, yard, or plot (41%); water from a public tap or standpipe (16%); and water piped to a neighbour (15%). Rural households obtain their drinking water mainly from tube wells or boreholes (36%), followed by protected dug wells (14%). Figure 2.1 shows that 42% of rural households obtain their drinking water from an unimproved water source, as compared with 8% of urban households. The percentage of households with an unimproved source of drinking water decreases with increasing wealth (Table 2.1.2). Trends: The percentage of households with an improved source of drinking water has increased over time, from 63% in 1992 to 72% in 2018. I 10 • Housing Characteristics and Household Population Figure 2.1 Household drinking water by residence Basic drinking water service Is from an improved source, provided either water is on the premises or round- trip collection time is 30 minutes or less. Sample: De jure population Limited drinking water service Is from an improved source, provided round-trip collection time is more than 30 minutes. Sample: De jure population Sixty-four percent of Zambia’s population has basic drinking water service, while 6% has limited drinking water service (Table 2.1.2). Access to basic drinking water service varies widely by province, from 36% in Northern to 91% in Lusaka. Access to basic drinking water service increases with rising wealth; however, there is no clear association between household wealth and limited drinking water service. Table 2.1.3 shows that 65% of de jure residents do not treat their drinking water (45% in urban areas and 78% in rural areas). Thirty-five percent of residents (54% in urban areas and 22% in rural areas) use an appropriate treatment method such as boiling, bleaching, filtering, and solar disinfecting. 2.1.2 Sanitation Improved toilet facilities Is a flush/pour flush toilets that flushes the water and waste to a piped sewer system, septic tank, pit latrine, or an unknown destination; a ventilated improved pit (VIP) latrine; a pit latrine with a slab; or a composting toilet Sample: Households Basic sanitation service Use of improved facilities that are not shared with other households. Sample: De jure population Limited sanitation service Use of improved facilities shared by 2 or more households Sample: De jure population 19 41 3 7 15 1 8 16 3 24 7 36 13 12 15 <1 <1 <1 28 8 42 Total Urban Rural Percent distribution of households by source of drinking water Unimproved source Bottled water Protected well or spring Tube well or borehole Public tap/ standpipe Piped to neighbour Piped water into dwelling/yard/plot Housing Characteristics and Household Population • 11 In Zambia, the Ministry of Water Development, Sanitation and Environmental Protection (MWDSEP) has embarked on the 2018-2021 strategy to improve access to water and sanitation services and improve good hygiene practices among all segments of the population. To that end, MWDSEP will strengthen the implementation of the National Urban and Rural Water Supply and Sanitation Programmes, which involves water supply and sanitation infrastructure development, water quality monitoring, and sanitation and hygiene promotion. The target of these efforts is to provide access to basic sanitation to 70% of the urban population and 55% of the rural population by December 2021 (MWDSEP 2018). The 2018 ZDHS results showed that 33% of the population has basic sanitation service, 41% in urban areas and 28% in rural areas (Table 2.3.1). Fifty-four percent of households have access to an improved sanitation facility, with the most commonly used facility being a pit latrine with a slab (37%). Patterns by background characteristics ▪ By province, the proportion of the population with improved sanitation facilities varies from a high of 80% in Lusaka to a low of 6% in Western. The proportion of the population engaging in open defection is highest in Western (50%) and lowest in Copperbelt, Lusaka, and Northern (1% each) (Table 2.3.2). ▪ Eighteen percent of the population in the lowest wealth quintile has basic sanitation service, as compared with 65% of the population in the highest wealth quintile. Figure 2.2 compares the availability of sanitation facilities nationally and by residence. The figure shows that urban households are more likely than rural households to have either improved or shared toilet facilities, while rural households are more likely to have unimproved facilities or no facilities. Overall, 16% of rural households have no toilet facility, as compared with 1% of urban households. Trends: The proportion of the population with access to improved sanitation increased from 27% in 2013-14 to 54% in 2018. 2.1.3 Exposure to Smoke inside the Home Exposure to smoke inside the home, from either cooking with solid fuels or smoking tobacco, has potentially harmful health effects. In Zambia, 25% of households cook inside the home, and 91% use solid fuel for cooking; only 9% of households use clean fuel for cooking. Tobacco is smoked in the home daily in 12% of households (Table 2.4). 2.1.4 Other Housing Characteristics The 2018 ZDHS also collected data on access to electricity, flooring materials, and the number of rooms used for sleeping. Only one in three (34%) households in Zambia have access to electricity (69% of urban households and 8% of rural households). The flooring materials most commonly used are earth or sand (45%) and cement (48%). Usage of these materials varies widely by residence, with 69% of rural households using earth or sand and 81% of urban households using cement (Table 2.4). Figure 2.2 Household toilet facilities by residence 54 78 37 24 42 11 36 21 47 10 1 16 Total Urban Rural Percent distribution of households by type of toilet facilities No facility/ bush/field Unimproved facility Shared facility Improved facility 12 • Housing Characteristics and Household Population 2.1.5 Household Wealth Household Durable Goods Wealth can be measured by number of household durable consumer goods. Table 2.5 shows information on various household effects, means of transportation, agricultural land, and livestock/farm animals. Urban households are generally more likely to own household effects; for example, 66% of urban households own television sets, as compared with 15% of rural households. However, rural households are more likely to own agricultural land (79%) and farm animals (63%) than urban households (16% and 13%, respectively). Wealth Index Wealth index Households are given scores based on the number and kinds of consumer goods they own, ranging from a television to a bicycle or car, and housing characteristics such as source of drinking water, toilet facilities, and flooring materials. These scores are derived using principal component analysis. National wealth quintiles are compiled by assigning the household score to each usual (de jure) household member, ranking each person in the household population by their score, and then dividing the distribution into five equal categories, each with 20% of the population. Sample: Households Table 2.6 presents wealth quintiles according to urban-rural residence and province. The table also includes the Gini coefficient, a measure of disparity in wealth. The Gini coefficient ranges from 0-1, with 0 implying an equal distribution of wealth and 1 implying a totally unequal distribution. Forty-six percent of the population in urban areas are in the highest wealth quintile, as compared with 3% of the population in rural areas. Nearly two-thirds of the rural population is in either the lowest (33%) or the second lowest (31%) wealth quintile. By province, Western has the highest percentage of the population in the lowest wealth quintile (47%). Conversely, Lusaka (51%) and Copperbelt (39%) have the highest percentages of the population in the highest wealth quintile (Table 2.6). 2.1.6 Handwashing The interviewers observed the places most often used for handwashing. Twenty-five percent of the de jure population have a fixed place for handwashing, although this is more common among urban (33%) than rural (19%) populations. Among the observed places of handwashing, 66% of the de jure population had water, 42% had soap, and 4% had cleansing agents other than soap (Table 2.7). 2.2 HOUSEHOLD POPULATION AND COMPOSITION Household A person or group of related or unrelated persons who live together in the same dwelling unit(s), who acknowledge one adult male or female as the head of the household, who share the same housekeeping arrangements, and who are considered a single unit. Housing Characteristics and Household Population • 13 De facto population All persons who stayed in the selected households the night before the interview (whether usual residents or visitors). De jure population All persons who are usual residents of the selected households, whether or not they stayed in the household the night before the interview. How data are calculated All tables are based on the de facto population, unless specified otherwise. The 2018 ZDHS included a total of 62,191 de facto household members, among whom 29,673 were male and 32,517 were female.1 Forty-eight percent of household members are age 0-14 and 49% are age 15-64; only 3% of household members are age 65 and above (Table 2.8). Table 2.9 shows that women head 27% of households in Zambia. The table also shows that urban households are slightly smaller (4.7 persons) than rural households (5.2 persons). Overall, 32% of households in Zambia are caring for foster and/or orphaned children. Figure 2.3 shows the de facto household population by 5-year age groups according to sex. The broad base of the pyramid indicates that Zambia’s population is largely young. Almost half (48%) of the population is under age 15. This kind of distribution is characteristic of developing countries with high fertility and low life expectancy. Trends: Overall, the age composition of the de facto population has remained relatively constant since 1992. 2.3 CHILDREN’S LIVING ARRANGEMENTS AND PARENTAL SURVIVAL Orphan A child with one or both parents who are dead. Sample: Children under age 18 1 The sex-specific numbers do not sum to the total due to rounding in the number of weighted cases. Figure 2.3 Population pyramid 10 6 2 2 6 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+ Age Percent distribution of the household population Male Female 2610 14 • Housing Characteristics and Household Population Sixteen percent of children under age 18 are not living with a biological parent, and 10% of these children are orphans (i.e., one or both parents are dead). By province, the percentage of children with one or both parents dead is lowest in Eastern, North Western, and Southern (8% each) and highest in Copperbelt (13%). Twenty-one percent of children not living with a biological parent are from households in the highest wealth quintile (Table 2.10). Figure 2.4 shows that there is little variation in the percentages of children with one or both parents dead according to wealth. Ten percent of children from households in the lowest wealth quintile and 11% from households in the highest quintile are orphans. Trends: The percentage of children under age 18 who do not live with a biological parent has declined only slightly since 2007, from 19% to 16%. 2.4 BIRTH REGISTRATION Registered birth Child has a birth certificate or child does not have a birth certificate, but his/her birth is registered with the civil authorities. Sample: De jure children under age 5 The global concern regarding the need to have all births registered by 2030 is evident in targets 16.9 and 17.19 of the SDGs. This is important given the need to protect all children because a child who is not registered is in danger of being shut out of society—denied the right to an official identity, a recognised name, and a nationality. In this regard the Zambian government, under the Department of National Registration, Passport and Citizenship, has drawn a roadmap to scale up birth registration in the country (MHA, 2017). Figure 2.4 Orphanhood by household wealth 10 9 9 12 11 Lowest Second Middle Fourth Highest Percentage of children under age 18 with one or both parents dead Poorest Wealthiest Housing Characteristics and Household Population • 15 Table 2.11 presents information on birth registration of children under age 5. Fourteen percent of children’s births are registered with the civil authorities. There is no variation by age or sex in the percentage of births registered. However, 25% of urban children are registered, as compared with only 8% of rural children. Furthermore, the percentage of registered births rises with increasing wealth, from 4% in the lowest quintile to 32% in the highest quintile. Figure 2.5 shows large variations by province in the percentage of children whose births are registered with the civil authorities. Copperbelt (29%) has the highest percentage of registered births, while Northern (3%) has the lowest. Trends: The percentage of children under age 5 whose births are registered with the civil authorities increased from 11% in 2013-14 to 14% in 2018. 2.5 EDUCATION 2.5.1 Educational Attainment Median educational attainment Half of the population has completed less than the median number of years of schooling, and half of the population has completed more than the median number of years of schooling. Sample: De facto household population age 6 and older The majority of Zambians have either no formal education or only some primary education. Specifically, 60% of females and 54% of males age 6 and over have no education or only some primary education (Tables 2.12.1 and 2.12.2). Women have completed a median of 4.6 years of schooling, while men have completed a median of 5.3 years. Trends: The percentage of females age 6 or above with no education declined from 24% in 1992 to 16% in 2013-14 and remained at 16% in 2018. Patterns by background characteristics ▪ Urban residents are better educated than rural residents. Only 9% of females age 6 and older in urban areas have no education, as compared with 21% in rural areas. The corresponding percentages among males are 8% and 18% (Tables 2.12.1 and 2.12.2). ▪ Among both women and men, median number of years of education increases with increasing wealth. ▪ Men and women in the highest wealth quintile (18% and 14%, respectively) are more likely than their counterparts to attain a higher education. Figure 2.5 Birth registration by province Percentage of de jure children under age 5 whose births are registered with the civil authorities 16 • Housing Characteristics and Household Population 2.5.2 School Attendance and Orphanhood School Attendance Ratios Net attendance ratios (NAR) Percentage of the school-age population that attends primary or secondary school. Sample: Children age 7-13 for primary school NAR and children age 14-18 for secondary school NAR Gross attendance ratios (GAR) The total number of children attending primary school divided by the official primary school-age population and the total number of children attending secondary school divided by the official secondary school-age population. Sample: Children age 7-13 for primary school GAR and children age 14-18 for secondary school GAR In Zambia, the primary school net attendance ratio (NAR) for the population age 7-13 is 79% (81% for girls and 77% for boys). The secondary school NAR drops drastically to 40% (38% for girls and 42% for boys). The variation in secondary school NARs by residence is large, with a difference of 27 percentage points between urban (56%) and rural (29%) areas (Table 2.13). Figure 2.6 shows the secondary school NAR among children age 14-18 by wealth quintile. Sixty-two percent of girls in the highest wealth quintile attend secondary school, as compared with 10% of those in the lowest wealth quintile. Boys follow a similar trajectory (73% in the highest quintile and 13% in the lowest). Across nearly all wealth quintiles, the secondary school NAR is higher among boys. The gross attendance ratio (GAR) is similar for boys and girls at both the primary level (97% and 98%, respectively) and the secondary level (60% and 55%, respectively). Gender Parity Indices (GPI) The ratio of female to male students attending primary school and the ratio of female to male students attending secondary school. The index reflects the magnitude of the gender gap. Sample: Primary school students and secondary school students Patterns by background characteristics ▪ The disparity in attendance between females and males at the primary level is minimal in all provinces other than Eastern (1.27), Central (1.07), and Luapula (1.07). Orphanhood Orphaned children may be at greater risk of dropping out of school than children with biological parents. This can occur for various reasons, such as the inability to pay school fees, the need to help with household chores, and the need to care for sick parents or younger siblings. Table 2.15 presents data on school attendance rates among children age 10-14 by survivorship of parents. Double orphans (i.e., children Figure 2.6 Secondary school attendance by household wealth 10 22 37 48 62 13 28 37 51 73 Lowest Second Middle Fourth Highest Net attendance ratio for secondary school among children age 14-18 Girls Boys WealthiestPoorest Housing Characteristics and Household Population • 17 whose father and mother are dead) are less likely to currently be in school than children whose parents are both alive and who are living with at least one parent (79% and 88%, respectively). LIST OF TABLES For more information on household population and housing characteristics, see the following tables: ▪ Table 2.1.1 Household drinking water ▪ Table 2.1.2 Drinking water according to province and wealth ▪ Table 2.1.3 Treatment of household drinking water ▪ Table 2.2 Availability of water ▪ Table 2.3.1 Household sanitation facilities ▪ Table 2.3.2 Sanitation facility type according to province and wealth ▪ Table 2.4 Household characteristics ▪ Table 2.5 Household possessions ▪ Table 2.6 Wealth quintiles ▪ Table 2.7 Handwashing ▪ Table 2.8 Household population by age, sex, and residence ▪ Table 2.9 Household composition ▪ Table 2.10 Children’s living arrangements and orphanhood ▪ Table 2.11 Birth registration of children under age 5 ▪ Table 2.12.1 Educational attainment of the female household population ▪ Table 2.12.2 Educational attainment of the male household population ▪ Table 2.13 School attendance ratios ▪ Table 2.14 Children under age 5 by highest level of education ▪ Table 2.15 School attendance by survivorship of parents 18 • Housing Characteristics and Household Population Table 2.1.1 Household drinking water Percent distribution of households and de jure population by source of drinking water and by time to obtain drinking water, percentage of households and de jure population with basic drinking water service, and percentage with limited drinking water service, according to residence, Zambia DHS 2018 Households Population Characteristic Urban Rural Total Urban Rural Total Source of drinking water Improved source 91.8 58.0 72.3 91.1 57.4 70.7 Piped into dwelling/yard/plot 41.1 2.9 19.1 41.3 2.3 17.7 Piped to neighbour 15.4 1.1 7.2 14.3 1.0 6.3 Public tap/standpipe 16.2 2.5 8.3 15.6 2.4 7.6 Tube well or borehole 6.9 36.4 23.9 7.1 36.1 24.7 Protected dug well 11.4 14.0 12.9 11.8 14.6 13.5 Protected spring 0.2 0.7 0.5 0.2 0.7 0.5 Rainwater 0.0 0.3 0.2 0.0 0.2 0.1 Tanker truck/cart with small tank 0.0 0.0 0.0 0.0 0.0 0.0 Bottled water 0.7 0.1 0.3 0.7 0.0 0.3 Unimproved source 8.2 42.0 27.7 8.9 42.6 29.3 Unprotected dug well 6.6 25.1 17.2 7.2 25.8 18.4 Unprotected spring 0.8 4.2 2.8 0.9 4.1 2.9 Surface water 0.5 12.7 7.6 0.6 12.6 7.9 Other 0.2 0.0 0.1 0.2 0.0 0.1 Total 100.0 100.0 100.0 100.0 100.0 100.0 Time to obtain drinking water (round trip) Water on premises1 66.2 14.6 36.5 65.8 14.5 34.8 30 minutes or less 29.5 69.6 52.6 29.6 68.9 53.4 More than 30 minutes 3.8 14.8 10.1 4.2 15.6 11.1 Don’t know/missing 0.4 1.1 0.8 0.4 1.0 0.7 Total 100.0 100.0 100.0 100.0 100.0 100.0 Method for storing water Closed container/jerry can 93.5 90.0 91.5 93.1 90.3 91.4 Open container/bucket 6.1 9.8 8.2 6.5 9.6 8.4 Does not store water 0.4 0.2 0.3 0.4 0.2 0.2 Other 0.1 0.0 0.0 0.0 0.0 0.0 Total 100.0 100.0 100.0 100.0 100.0 100.0 Percentage with basic drinking water service2 88.2 49.6 66.0 87.2 48.5 63.8 Percentage with limited drinking water service3 3.2 7.6 5.7 3.5 8.2 6.4 Number of households/ population 5,441 7,390 12,831 25,346 38,746 64,092 1 Includes water piped to a neighbour and those reporting a roundtrip collection time of zero minutes 2 Defined as drinking water from an improved source, provided either water is on the premises or round-trip collection time is 30 minutes or less. Includes safely managed drinking water, which is not shown separately. 3 Drinking water from an improved source, provided round-trip collection time is more than 30 minutes Housing Characteristics and Household Population • 19 Table 2.1.2 Drinking water according to province and wealth Percent distribution of de jure population by drinking water source, percentage of de jure population with basic drinking water service, and percentage with limited drinking water service, according to province and wealth quintile, Zambia DHS 2018 Background characteristic Improved source of drinking water1 Unimproved source of drinking water2 Total Percentage with basic drinking water service2 Percentage with limited drinking water service3 Number of persons Province Central 73.7 26.3 100.0 65.9 7.8 5,730 Copperbelt 80.8 19.2 100.0 78.0 2.7 9,074 Eastern 79.2 20.8 100.0 68.4 8.3 8,357 Luapula 58.1 41.9 100.0 49.8 7.6 5,526 Lusaka 98.0 2.0 100.0 91.2 6.5 10,700 Muchinga 52.3 47.7 100.0 46.3 6.1 3,676 Northern 39.9 60.1 100.0 36.2 3.5 5,502 North Western 65.5 34.5 100.0 60.4 4.2 3,477 Southern 66.2 33.8 100.0 56.4 9.8 7,811 Western 44.5 55.5 100.0 38.2 5.9 4,237 Wealth quintile Lowest 42.6 57.4 100.0 36.1 5.5 12,813 Second 58.3 41.7 100.0 48.9 8.5 12,820 Middle 67.8 32.2 100.0 56.6 10.6 12,822 Fourth 87.5 12.5 100.0 82.2 4.9 12,819 Highest 97.4 2.6 100.0 95.2 2.3 12,818 Total 70.7 29.3 100.0 63.8 6.4 64,092 1 See Table 2.1.1 for definition of an improved source. 2 See Table 2.1.1 for definition of an unimproved source. 3 Defined as drinking water from an improved source, provided either water is on the premises or round-trip collection time is 30 minutes or less. Includes safely managed drinking water, which is not shown separately. 4 Drinking water from an improved source, provided round-trip collection time is more than 30 minutes 20 • Housing Characteristics and Household Population Table 2.1.3 Treatment of household drinking water Percentage of households and de jure population using various methods to treat drinking water, and percentage using an appropriate treatment method, according to residence, Zambia DHS 2018 Households Population Water treatment method Urban Rural Total Urban Rural Total Boil 24.0 8.7 15.2 24.2 8.0 14.4 Bleach/chlorine added 35.2 15.2 23.7 37.7 15.4 24.2 Strain through cloth 0.0 0.1 0.1 0.0 0.1 0.1 Ceramic, sand, or other filter 0.1 0.1 0.1 0.0 0.1 0.1 Solar disinfection 0.1 0.1 0.1 0.1 0.1 0.1 Let stand and settle 0.2 0.2 0.2 0.2 0.3 0.3 Other 0.3 0.0 0.2 0.3 0.0 0.2 No treatment 47.1 77.5 64.6 45.1 78.0 65.0 Percentage using an appropriate treatment method1 52.4 22.1 35.0 54.4 21.6 34.5 Number of households/population 5,441 7,390 12,831 25,346 38,746 64,092 Note: Respondents may report multiple treatment methods, so the sum of treatment may exceed 100%. 1 Appropriate water treatment methods include boiling, bleaching, filtering, and solar disinfecting. Table 2.2 Availability of water Percent distribution of households and de jure population using piped water or water from a tube well or borehole, by availability of water in the last 2 weeks, according to residence, Zambia DHS 2018 Availability of water in last 2 weeks Households Population Urban Rural Total Urban Rural Total Not available for at least 1 day 43.1 9.2 28.8 43.1 9.1 27.9 Available with no interruption of at least 1 day 55.3 90.7 70.2 56.0 90.7 71.5 Don’t know/missing 1.6 0.1 1.0 0.9 0.3 0.6 Total 100.0 100.0 100.0 100.0 100.0 100.0 Number of households/ population using piped water or water from a tube well1 4,364 3,173 7,537 20,023 16,197 36,219 1 Includes households/population reporting piped water or water from a tube well or borehole as their main source of drinking water and households/population reporting bottled water as their main source of drinking water if their main source of water for cooking and handwashing is piped water or water from a tube well or borehole Housing Characteristics and Household Population • 21 Table 2.3.1 Household sanitation facilities Percent distribution of households and de jure population by type of toilet/latrine facilities, percent distribution of households and de jure population with a toilet/latrine facility by location of the facility, percentage of households and de jure population with basic sanitation services, and percentage with limited sanitation services, according to residence, Zambia DHS 2018 Households Population Type and location of toilet/latrine facility Urban Rural Total Urban Rural Total Improved sanitation facility 77.7 37.2 54.4 79.0 37.7 54.0 Flush/pour flush to piped sewer system 17.2 0.6 7.6 17.2 0.5 7.1 Flush/pour flush to septic tank 13.6 1.8 6.8 14.4 1.4 6.6 Flush/pour flush to pit latrine 3.9 0.2 1.8 3.9 0.1 1.6 Flush/pour flush, don’t know where 0.4 0.1 0.2 0.5 0.1 0.2 Ventilated improved pit (VIP) latrine 0.8 0.7 0.8 0.8 0.8 0.8 Pit latrine with slab 41.8 33.9 37.2 42.2 34.8 37.7 Composting toilet 0.0 0.0 0.0 0.0 0.0 0.0 Unimproved facility Unimproved sanitation facility 20.8 46.5 35.6 20.0 46.8 36.2 Flush/pour flush not to sewer/septic tank/pit latrine 0.7 0.0 0.3 0.7 0.0 0.3 Pit latrine without slab/open pit 20.0 46.4 35.2 19.2 46.7 35.8 Hanging toilet/hanging latrine 0.0 0.0 0.0 0.0 0.0 0.0 Other 0.1 0.1 0.1 0.1 0.0 0.1 Open defecation (no facility/bush/ field) 1.4 16.2 10.0 1.0 15.5 9.8 Total 100.0 100.0 100.0 100.0 100.0 100.0 Number of households/population 5,441 7,390 12,831 25,346 38,746 64,092 Location of toilet facility In own dwelling 20.3 4.4 11.8 21.6 4.0 11.6 In own yard/plot 73.4 81.3 77.7 72.7 83.4 78.8 Elsewhere 6.3 14.3 10.6 5.7 12.6 9.6 Total 100.0 100.0 100.0 100.0 100.0 100.0 Number of households/population with a toilet/latrine facility 5,363 6,191 11,554 25,090 32,729 57,819 Percentage with basic sanitation service1 35.4 26.4 30.2 40.6 27.8 32.9 Percentage with limited sanitation service2 42.2 10.9 24.2 38.3 9.8 21.1 Number of households/population 5,441 7,390 12,831 25,346 38,746 64,092 1 Defined as use of improved facilities that are not shared with other households. Includes safely managed sanitation service, which is not shown separately. 2 Defined as use of improved facilities shared by 2 or more households Table 2.3.2 Sanitation facility type according to province and wealth Percent distribution of de jure population by type of sanitation, percentage of de jure population with basic sanitation service, and percentage with limited sanitation service, according to province and wealth quintile, Zambia DHS 2018 Type of sanitation Total Percentage with basic sanitation service3 Percentage with limited sanitation service4 Number of persons Background characteristic Improved sanitation facility1 Unimproved sanitation facility2 Open defecation Province Central 38.9 54.4 6.8 100.0 26.6 12.3 5,730 Copperbelt 76.7 22.3 1.0 100.0 46.2 30.5 9,074 Eastern 39.2 44.5 16.3 100.0 25.3 13.9 8,357 Luapula 48.8 46.8 4.4 100.0 39.4 9.3 5,526 Lusaka 80.0 18.8 1.2 100.0 34.3 45.5 10,700 Muchinga 52.0 42.6 5.4 100.0 40.5 11.4 3,676 Northern 55.8 43.4 0.9 100.0 45.5 10.3 5,502 North Western 47.7 49.2 3.1 100.0 30.1 17.6 3,477 Southern 51.4 28.2 20.4 100.0 27.5 23.9 7,811 Western 6.2 43.8 50.0 100.0 4.9 1.3 4,237 Wealth quintile Lowest 25.8 48.1 26.1 100.0 17.5 8.2 12,813 Second 35.3 51.4 13.3 100.0 26.2 9.1 12,820 Middle 42.1 49.5 8.4 100.0 27.7 14.3 12,822 Fourth 72.7 26.2 1.2 100.0 28.2 44.4 12,819 Highest 94.3 5.6 0.1 100.0 64.8 29.5 12,818 Total 54.0 36.2 9.8 100.0 32.9 21.1 64,092 1 See Table 2.3.1 for definition of an improved facility. 2 See Table 2.3.1 for definition of an unimproved facility. 3 Defined as use of improved facilities that are not shared with other households. Includes safely managed sanitation service, which is not shown separately. 4 Defined as use of improved facilities shared by 2 or more households 22 • Housing Characteristics and Household Population Table 2.4 Household characteristics Percent distribution of households and de jure population by housing characteristics, percentage using solid fuel for cooking, percentage using clean fuel for cooking, and percent distribution by frequency of smoking in the home, according to residence, Zambia DHS 2018 Households Population Housing characteristic Urban Rural Total Urban Rural Total Electricity Yes 69.1 8.4 34.2 70.6 8.1 32.8 No 30.9 91.6 65.8 29.4 91.9 67.2 Total 100.0 100.0 100.0 100.0 100.0 100.0 Flooring material Earth, sand 11.3 69.4 44.7 10.7 68.3 45.5 Dung 1.3 5.7 3.8 1.4 5.7 4.0 Wood/planks 0.0 0.1 0.0 0.0 0.0 0.0 Palm/bamboo/reeds 0.0 0.1 0.1 0.0 0.1 0.1 Parquet or polished wood 0.2 0.0 0.1 0.2 0.0 0.1 Vinyl or asphalt strips 0.3 0.1 0.2 0.4 0.0 0.2 Ceramic tiles/terrazzo tiles 5.4 0.3 2.5 5.8 0.2 2.4 Cement 80.7 24.0 48.1 81.0 25.2 47.2 Carpet 0.6 0.1 0.3 0.5 0.1 0.3 Other 0.1 0.2 0.2 0.1 0.3 0.2 Total 100.0 100.0 100.0 100.0 100.0 100.0 Rooms used for sleeping One 35.9 31.5 33.4 23.4 21.8 22.4 Two 37.9 41.4 39.9 40.0 41.7 41.0 Three or more 26.2 27.1 26.7 36.6 36.5 36.5 Total 100.0 100.0 100.0 100.0 100.0 100.0 Place for cooking In the house 44.5 9.8 24.5 44.6 8.3 22.7 In a separate building 5.1 48.2 29.9 5.5 51.7 33.4 Outdoors 50.4 42.0 45.5 49.8 40.0 43.9 Other 0.0 0.0 0.0 0.0 0.0 0.0 Total 100.0 100.0 100.0 100.0 100.0 100.0 Cooking fuel Electricity 18.4 2.0 9.0 17.8 1.5 7.9 Solar power 0.1 0.3 0.2 0.0 0.3 0.2 LPG/natural gas/biogas 0.3 0.1 0.2 0.2 0.1 0.1 Kerosene 0.0 0.0 0.0 0.0 0.0 0.0 Coal/lignite 0.1 0.0 0.0 0.1 0.0 0.0 Charcoal 75.4 18.1 42.4 75.7 16.6 40.0 Wood 5.8 79.3 48.1 6.2 81.4 51.7 Straw/shrubs/grass 0.0 0.2 0.1 0.0 0.2 0.1 Agricultural crop 0.0 0.0 0.0 0.0 0.0 0.0 Animal dung 0.0 0.0 0.0 0.0 0.0 0.0 Other 0.0 0.0 0.0 0.0 0.0 0.0 Total 100.0 100.0 100.0 100.0 100.0 100.0 Percentage using solid fuel for cooking1 81.3 97.5 90.6 82.0 98.2 91.8 Percentage using clean fuel for cooking2 18.7 2.1 9.1 18.0 1.5 8.0 Frequency of smoking in the home Daily 8.9 13.6 11.6 9.1 13.8 12.0 Weekly 5.2 6.1 5.7 5.3 6.0 5.7 Monthly 0.6 0.5 0.6 0.7 0.5 0.6 Less than once a month 1.1 2.0 1.6 1.3 2.1 1.8 Never 84.2 77.8 80.5 83.6 77.6 80.0 Total 100.0 100.0 100.0 100.0 100.0 100.0 Number of households/ population 5,441 7,390 12,831 25,346 38,746 64,092 LPG = Liquefied petroleum gas 1 Includes coal/lignite, charcoal, wood, straw/shrubs/grass, agricultural crops, and animal dung 2 Includes electricity, LPG/natural gas/biogas, and solar power Housing Characteristics and Household Population • 23 Table 2.5 Household possessions Percentage of households possessing various household effects, means of transportation, agricultural land, and livestock/farm animals, by residence, Zambia DHS 2018 Residence Total Possession Urban Rural Household effects Radio 60.3 37.4 47.1 Television 66.3 14.8 36.6 Computer 14.8 2.3 7.6 Refrigerator 45.8 4.3 21.9 Internet 14.3 2.1 7.3 Bed 89.3 56.0 70.1 Table 71.3 49.9 59.0 Sofa 65.3 19.8 39.1 Washing machine 2.3 0.5 1.2 Air conditioner 4.0 0.5 2.0 Generator 2.1 1.0 1.4 Microwave 9.0 0.7 4.3 Geyser 4.3 0.6 2.2 Grain grinder 0.7 1.4 1.1 Plough 1.4 17.6 10.7 Tractor 0.3 0.4 0.4 Hammer mill 0.4 1.3 0.9 Watch 36.9 11.8 22.4 Mobile phone 90.0 61.7 73.7 Means of transport Bicycle 24.3 47.7 37.8 Animal-drawn cart 0.7 7.6 4.7 Motorcycle/scooter 1.6 3.4 2.6 Car/truck 11.7 3.0 6.7 Boat with a motor 0.2 0.4 0.3 Banana boat 0.8 3.0 2.0 Ownership of agricultural land 16.3 79.4 52.7 Ownership of farm animals1 13.4 63.3 42.2 Ownership of a bank account 42.1 9.1 23.1 Number 5,441 7,390 12,831 1 Traditional cattle, dairy cattle, beef cattle, horses, donkeys, mules, goats, sheep, chickens, pigs, or rabbits/other poultry Table 2.6 Wealth quintiles Percent distribution of the de jure population by wealth quintiles, and the Gini coefficient, according to residence and province, Zambia DHS 2018 Residence/ province Wealth quintile Total Number of persons Gini coefficient Lowest Second Middle Fourth Highest Residence Urban 0.4 2.7 12.4 38.7 45.7 100.0 25,346 0.19 Rural 32.8 31.3 25.0 7.7 3.2 100.0 38,746 0.41 Province Central 15.9 21.9 28.9 18.5 14.8 100.0 5,730 0.44 Copperbelt 2.2 7.8 14.6 36.3 39.0 100.0 9,074 0.25 Eastern 31.3 29.7 25.1 7.4 6.5 100.0 8,357 0.47 Luapula 28.7 35.6 19.1 8.6 7.9 100.0 5,526 0.44 Lusaka 1.6 3.4 8.4 36.0 50.5 100.0 10,700 0.19 Muchinga 38.3 26.4 20.7 9.8 4.8 100.0 3,676 0.47 Northern 39.5 25.4 21.0 8.7 5.5 100.0 5,502 0.46 North Western 25.5 27.4 22.1 13.0 12.1 100.0 3,477 0.52 Southern 11.1 21.6 32.0 24.8 10.4 100.0 7,811 0.38 Western 47.0 24.3 14.1 6.8 7.8 100.0 4,237 0.51 Total 20.0 20.0 20.0 20.0 20.0 100.0 64,092 0.44 24 • Housing Characteristics and Household Population Table 2.7 Handwashing Percentage of the de jure population for whom the place most often used for washing hands was observed, by whether the location was fixed or mobile; total percentage of the de jure population for whom the place for handwashing was observed; among the de jure population for whom the place for handwashing was observed, percentage with water available, percentage with soap available, and percentage with a cleansing agent other than soap available; percentage of the de jure population with a basic handwashing facility; and percentage with a limited handwashing facility, according to background characteristics, Zambia DHS 2018 Percentage of de jure population for whom place for washing hands was observed: Number of persons Place for handwashing observed and: Number of persons for whom place for hand- washing was observed Percentage of de jure population with a basic hand- washing facility3 Percentage of de jure population with a limited hand- washing facility4 Number of persons for whom a place for hand- washing was observed or with no place for hand- washing in the dwelling, yard, or plot Background characteristic Place for hand- washing was a fixed place Place for hand- washing was mobile Total Water available Soap available1 Cleansing agent other than soap available2 Residence Urban 32.9 33.1 66.0 25,346 72.9 51.8 1.5 16,729 36.2 41.4 21,545 Rural 19.4 26.4 45.8 38,746 58.4 32.9 6.7 17,742 15.3 38.0 33,236 Province Central 28.8 32.0 60.8 5,730 71.0 51.7 4.9 3,486 30.9 36.7 5,155 Copperbelt 27.8 48.6 76.4 9,074 62.3 45.1 0.8 6,929 33.6 55.8 7,749 Eastern 24.1 16.5 40.6 8,357 63.8 43.7 4.4 3,391 17.2 23.8 8,264 Luapula 21.6 36.1 57.7 5,526 55.8 33.9 7.3 3,188 19.3 42.5 5,153 Lusaka 33.3 28.9 62.3 10,700 81.6 56.0 1.4 6,664 39.9 35.0 8,904 Muchinga 21.4 23.2 44.6 3,676 61.8 16.0 4.4 1,639 10.1 55.9 2,483 Northern 19.2 19.6 38.8 5,502 62.5 36.5 12.1 2,136 15.8 30.8 4,579 North Western 24.6 24.1 48.6 3,477 56.7 20.1 0.7 1,691 9.3 44.1 3,162 Southern 17.5 18.5 36.0 7,811 48.3 22.9 7.3 2,809 7.5 45.3 5,320 Western 20.2 39.8 59.9 4,237 68.1 49.8 7.6 2,539 26.6 36.7 4,013 Wealth quintile Lowest 16.5 26.0 42.5 12,813 57.0 29.3 8.5 5,441 12.8 35.9 11,185 Second 16.9 27.7 44.6 12,820 53.6 29.1 6.8 5,712 13.2 38.9 10,970 Middle 19.4 27.8 47.2 12,822 54.8 34.8 5.8 6,047 16.2 40.2 10,720 Fourth 19.3 40.2 59.5 12,819 63.2 40.0 2.0 7,625 24.2 47.9 10,562 Highest 51.7 23.6 75.3 12,818 85.7 63.2 0.9 9,646 50.5 34.5 11,344 Total 24.7 29.0 53.8 64,092 65.5 42.1 4.2 34,471 23.5 39.4 54,782 1 Soap includes soap or detergent in bar, liquid, powder, or paste form. 2 Cleansing agents other than soap include locally available materials such as ash, mud, or sand. 3 The availability of a handwashing facility on premises with soap and water 4 The availability of a handwashing facility on premises without soap and/or water Housing Characteristics and Household Population • 25 Table 2.8 Household population by age, sex, and residence Percent distribution of the de facto household population by various age groups and percentage of the de facto household population age 10-19, according to sex and residence, Zambia DHS 2018 Urban Rural Male Female Total Age Male Female Total Male Female Total <5 14.8 13.3 14.0 18.0 17.0 17.5 16.7 15.5 16.1 5-9 15.3 13.6 14.4 18.6 17.2 17.9 17.3 15.8 16.5 10-14 14.5 14.0 14.3 17.4 16.1 16.7 16.3 15.2 15.7 15-19 10.4 10.6 10.5 10.2 9.4 9.8 10.3 9.9 10.1 20-24 9.2 10.6 9.9 6.6 7.8 7.2 7.6 8.9 8.3 25-29 7.8 9.0 8.4 5.2 6.2 5.7 6.2 7.3 6.8 30-34 6.2 7.4 6.8 4.7 5.0 4.9 5.3 6.0 5.7 35-39 5.9 6.3 6.1 4.1 4.9 4.5 4.8 5.5 5.1 40-44 5.2 4.3 4.7 3.7 3.9 3.8 4.3 4.1 4.2 45-49 3.2 2.7 2.9 3.1 2.9 3.0 3.2 2.8 3.0 50-54 2.1 2.7 2.4 2.3 2.5 2.4 2.2 2.6 2.4 55-59 1.2 1.6 1.4 1.4 1.8 1.6 1.3 1.7 1.5 60-64 1.8 1.4 1.6 1.6 1.5 1.6 1.7 1.5 1.6 65-69 0.6 0.8 0.7 1.0 1.2 1.1 0.8 1.0 0.9 70-74 0.6 0.8 0.7 0.7 1.1 0.9 0.7 1.0 0.8 75-79 0.4 0.5 0.4 0.6 0.7 0.6 0.5 0.6 0.5 80+ 0.5 0.4 0.4 0.7 0.7 0.7 0.6 0.6 0.6 Don’t know/missing 0.3 0.1 0.2 0.2 0.1 0.1 0.2 0.1 0.2 Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 Dependency age groups 0-14 44.6 40.9 42.6 54.0 50.4 52.1 50.3 46.5 48.3 15-64 53.0 56.5 54.9 42.9 45.9 44.5 46.9 50.2 48.6 65+ 2.1 2.5 2.3 2.9 3.6 3.3 2.6 3.2 2.9 Don’t know/missing 0.3 0.1 0.2 0.2 0.1 0.1 0.2 0.1 0.2 Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 Child and adult populations 0-17 50.5 46.8 48.5 59.9 55.8 57.8 56.2 52.1 54.1 18+ 49.2 53.1 51.3 40.0 44.1 42.1 43.5 47.8 45.7 Don’t know/missing 0.3 0.1 0.2 0.2 0.1 0.1 0.2 0.1 0.2 Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 Adolescents 10-19 24.9 24.7 24.8 27.6 25.5 26.5 26.5 25.2 25.8 Number of persons 11,535 13,254 24,789 18,138 19,264 37,401 29,673 32,517 62,191 26 • Housing Characteristics and Household Population Table 2.9 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 age 18, according to residence, Zambia DHS 2018 Residence Total Characteristic Urban Rural Household headship Male 71.9 74.2 73.2 Female 28.1 25.8 26.8 Total 100.0 100.0 100.0 Number of usual members 1 9.6 6.8 8.0 2 10.3 7.6 8.8 3 16.0 12.6 14.0 4 15.9 15.3 15.6 5 15.3 15.0 15.1 6 12.7 13.3 13.1 7 8.0 10.9 9.7 8 5.1 8.2 6.9 9+ 7.0 10.3 8.9 Total 100.0 100.0 100.0 Mean size of households 4.7 5.2 5.0 Percentage of households with orphans and foster children under age 18 Double orphans 3.0 2.6 2.8 Single orphans1 14.5 13.8 14.1 Foster children2 25.7 28.2 27.1 Foster and/or orphan children 31.1 32.9 32.1 Number of households 5,441 7,390 12,831 Note: Table is based on de jure household members, i.e., usual residents. 1 Includes children with one dead parent and an unknown survival status of the other parent 2 Foster children are those under age 18 living in households with neither their mother nor their father present, and the mother and/or the father are alive. Housing Characteristics and Household Population • 27 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, percentage of children not living with a biological parent, and percentage of children with one or both parents dead, according to background characteristics, Zambia DHS 2018 Living with both parents Living with mother but not with father Living with father but not with mother Not living with either parent Total Percent- age not living with a bio- logical parent Percent- age 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 informa- tion on father/ mother Age 0-4 66.1 25.0 2.0 0.9 0.1 4.7 0.4 0.3 0.2 0.3 100.0 5.5 3.0 10,077 <2 68.7 28.1 1.5 0.1 0.0 1.1 0.3 0.1 0.0 0.2 100.0 1.4 1.8 3,977 2-4 64.4 23.0 2.4 1.4 0.2 7.0 0.5 0.4 0.3 0.4 100.0 8.2 3.8 6,100 5-9 58.2 18.3 4.0 3.0 0.5 11.5 1.3 1.8 1.0 0.4 100.0 15.6 8.7 10,392 10-14 49.7 14.9 5.9 4.4 1.1 15.4 2.3 3.5 2.1 0.6 100.0 23.3 15.0 9,984 15-17 43.5 12.6 7.2 5.1 1.2 16.9 2.8 5.6 4.1 1.0 100.0 29.4 21.3 3,721 Sex Male 57.1 18.7 4.5 3.5 0.8 10.0 1.4 2.2 1.4 0.5 100.0 14.9 10.3 16,939 Female 55.8 18.7 4.1 2.5 0.5 12.4 1.6 2.4 1.4 0.5 100.0 17.8 10.1 17,235 Residence Urban 53.0 19.8 5.1 3.3 0.9 11.3 1.6 2.8 1.8 0.5 100.0 17.5 12.3 12,082 Rural 58.3 18.1 3.9 2.9 0.5 11.1 1.4 2.0 1.2 0.5 100.0 15.7 9.1 22,092 Province Central 54.2 18.7 3.8 2.9 0.5 13.8 1.5 2.5 1.7 0.5 100.0 19.4 10.0 3,086 Copperbelt 52.8 19.0 4.9 3.2 0.8 11.6 1.7 3.5 2.2 0.3 100.0 18.9 13.0 4,364 Eastern 63.6 15.9 3.4 2.6 0.7 9.8 1.1 1.4 0.9 0.5 100.0 13.3 7.7 4,566 Luapula 56.9 18.5 5.5 2.0 0.4 10.2 2.0 2.3 1.8 0.4 100.0 16.3 12.1 3,125 Lusaka 54.1 20.5 5.0 2.7 0.7 11.0 1.6 2.4 1.6 0.4 100.0 16.5 11.3 5,151 Muchinga 63.2 15.6 4.5 3.5 0.2 8.4 1.4 2.0 1.1 0.3 100.0 12.8 9.1 2,095 Northern 62.1 15.3 4.2 2.3 0.5 10.2 1.5 1.5 1.9 0.5 100.0 15.1 9.7 3,127 North Western 53.1 23.0 3.6 3.3 0.1 11.7 1.3 2.2 1.0 0.6 100.0 16.2 8.3 1,959 Southern 55.9 18.4 3.2 3.7 1.2 13.2 1.0 2.0 0.7 0.7 100.0 16.9 8.4 4,319 Western 47.2 23.8 5.5 4.8 0.8 11.4 2.1 2.7 1.1 0.5 100.0 17.3 12.2 2,382 Wealth quintile Lowest 56.6 22.9 5.3 2.4 0.3 7.8 1.5 1.6 1.1 0.4 100.0 12.1 10.0 7,486 Second 59.4 17.7 4.4 2.7 0.5 10.5 1.4 1.5 1.4 0.5 100.0 14.8 9.3 7,350 Middle 58.2 16.3 3.4 3.1 0.6 12.6 1.4 2.4 1.4 0.6 100.0 17.8 9.4 7,115 Fourth 52.3 20.1 4.9 3.5 1.2 11.6 1.3 3.1 1.6 0.5 100.0 17.6 12.2 6,419 Highest 54.9 15.8 3.5 3.8 0.7 14.4 1.8 3.0 1.7 0.5 100.0 20.8 10.7 5,803 Total <15 58.0 19.4 4.0 2.8 0.6 10.5 1.3 1.9 1.1 0.4 100.0 14.8 8.9 30,453 Total <18 56.4 18.7 4.3 3.0 0.7 11.2 1.5 2.3 1.4 0.5 100.0 16.4 10.2 34,174 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 28 • Housing Characteristics and Household Population Table 2.11 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 DHS 2018 Percentage of children whose births are registered and who: Number of children Background characteristic Had a birth certificate Did not have a birth certificate Total percentage of children whose births are registered Age <2 4.8 8.9 13.8 3,977 2-4 6.6 7.6 14.2 6,100 Sex Male 6.3 7.8 14.1 4,993 Female 5.5 8.5 14.0 5,084 Residence Urban 10.5 14.8 25.3 3,445 Rural 3.5 4.7 8.2 6,632 Province Central 0.8 21.5 22.4 878 Copperbelt 14.2 14.8 29.0 1,273 Eastern 6.8 4.6 11.4 1,380 Luapula 4.4 4.0 8.3 968 Lusaka 7.9 13.5 21.3 1,491 Muchinga 11.4 2.5 14.0 589 Northern 1.1 1.6 2.6 902 North Western 4.8 4.1 8.9 574 Southern 2.9 5.1 7.9 1,337 Western 1.3 3.0 4.4 684 Wealth quintile Lowest 1.8 1.8 3.6 2,523 Second 3.8 4.5 8.3 2,251 Middle 5.0 8.7 13.7 1,921 Fourth 7.8 13.0 20.8 1,824 Highest 14.4 17.4 31.8 1,557 Total 5.9 8.2 14.0 10,077 Housing Characteristics and Household Population • 29 Table 2.12.1 Educational attainment of the female household population Percent distribution of the de facto female household population age 6 and over by highest level of schooling attended or completed and median years completed, according to background characteristics, Zambia DHS 2018 Background characteristic No education Some primary Completed primary1 Some secondary Completed secondary2 Higher Don’t know/ missing Total Number Median years completed Age 6-9 45.7 54.3 0.0 0.0 0.0 0.0 0.0 100.0 4,190 0.0 10-14 6.0 83.7 4.0 6.2 0.0 0.0 0.0 100.0 4,959 3.1 15-19 3.7 30.1 13.5 46.6 5.6 0.3 0.2 100.0 3,222 6.9 20-24 4.1 21.9 13.0 36.4 19.4 5.1 0.2 100.0 2,895 7.9 25-29 6.0 23.9 14.2 31.4 15.6 8.6 0.3 100.0 2,384 7.4 30-34 10.9 30.9 13.4 23.5 11.0 9.8 0.6 100.0 1,940 6.6 35-39 11.2 33.7 17.6 23.2 6.0 7.4 1.0 100.0 1,773 6.2 40-44 11.0 34.5 20.0 21.2 6.5 5.7 1.1 100.0 1,319 6.2 45-49 14.7 38.1 19.7 18.1 3.6 4.5 1.2 100.0 920 5.7 50-54 17.7 35.8 21.5 14.4 3.3 5.9 1.4 100.0 843 5.6 55-59 24.4 34.6 18.5 14.1 2.2 4.7 1.4 100.0 558 4.5 60-64 23.2 39.1 21.1 10.9 1.1 3.6 1.0 100.0 481 3.8 65+ 45.7 37.8 5.4 6.9 0.7 1.4 2.1 100.0 1,028 0.2 Don’t know/ missing (35.5) (19.2) (9.3) (6.9) (6.0) (5.2) (18.0) 100.0 31 (2.7) Residence Urban 9.1 33.0 10.8 28.1 11.8 6.7 0.6 100.0 11,170 6.6 Rural 20.5 52.0 10.4 13.8 1.9 1.0 0.4 100.0 15,374 3.2 Province Central 16.2 42.0 13.6 19.6 5.6 2.5 0.4 100.0 2,432 4.8 Copperbelt 9.6 34.6 12.2 25.6 11.6 5.6 0.8 100.0 3,972 6.4 Eastern 22.2 55.5 6.6 11.2 2.2 1.7 0.6 100.0 3,259 2.7 Luapula 19.7 51.8 9.4 13.5 2.9 1.7 1.0 100.0 2,191 3.2 Lusaka 10.6 32.6 10.4 27.8 10.8 7.4 0.4 100.0 4,715 6.5 Muchinga 21.3 50.0 11.1 13.8 2.5 1.0 0.2 100.0 1,535 3.4 Northern 20.6 54.4 8.4 12.8 2.1 1.2 0.6 100.0 2,233 3.0 North Western 15.9 46.6 5.7 21.8 6.4 3.4 0.2 100.0 1,384 4.2 Southern 11.9 43.7 15.4 22.7 4.2 2.1 0.1 100.0 3,098 5.4 Western 20.8 47.7 9.5 16.4 3.6 1.6 0.3 100.0 1,723 3.4 Wealth quintile Lowest 29.2 54.7 8.2 7.1 0.4 0.0 0.3 100.0 5,113 1.8 Second 21.4 54.2 10.2 12.6 1.0 0.1 0.5 100.0 5,089 3.1 Middle 14.6 49.4 13.2 19.4 2.6 0.3 0.5 100.0 5,172 4.3 Fourth 10.3 37.1 13.1 29.5 7.8 1.7 0.5 100.0 5,454 6.2 Highest 4.7 27.0 8.2 28.6 17.1 13.9 0.6 100.0 5,716 8.1 Total 15.7 44.0 10.6 19.8 6.1 3.4 0.5 100.0 26,544 4.6 Note: Figures in parentheses are based on 25-49 unweighted cases. 1 Completed grade 7 at the primary level 2 Completed grade 12 at the secondary level 30 • Housing Characteristics and Household Population 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 DHS 2018 Background characteristic No education Some primary Completed primary1 Some secondary Completed secondary2 Higher Don’t know/ missing Total Number Median years completed Age 6-9 49.6 50.4 0.0 0.0 0.0 0.0 0.0 100.0 4,174 0.0 10-14 9.9 81.9 3.5 4.7 0.0 0.0 0.0 100.0 4,827 2.9 15-19 3.8 33.3 11.3 47.1 4.1 0.2 0.1 100.0 3,049 6.7 20-24 4.0 15.6 11.0 38.4 25.3 5.1 0.5 100.0 2,258 8.5 25-29 3.1 15.4 11.6 34.6 23.0 11.6 0.7 100.0 1,835 8.5 30-34 4.7 18.3 13.7 26.8 22.1 12.4 2.0 100.0 1,573 8.4 35-39 6.3 18.8 15.9 27.3 16.0 13.2 2.4 100.0 1,417 7.8 40-44 5.9 23.6 16.5 28.0 13.7 10.0 2.4 100.0 1,274 7.3 45-49 6.8 26.6 17.1 25.3 11.1 11.0 2.1 100.0 936 6.8 50-54 5.4 25.8 22.6 21.3 11.8 8.6 4.5 100.0 668 6.7 55-59 3.4 22.2 28.7 19.3 13.0 11.7 1.7 100.0 393 6.8 60-64 9.6 20.8 25.7 22.6 10.5 7.6 3.1 100.0 502 6.7 65+ 14.6 38.5 14.4 18.0 5.7 5.9 2.8 100.0 771 5.4 Don’t know/ missing 7.6 12.4 18.5 40.2 10.1 1.2 10.1 100.0 65 (8.3) Residence Urban 8.0 30.3 8.3 26.3 16.8 9.2 1.0 100.0 9,472 7.2 Rural 18.0 46.3 10.6 18.0 4.3 1.8 0.9 100.0 14,268 3.9 Province Central 14.0 39.2 11.9 21.1 8.6 4.3 0.8 100.0 2,179 5.4 Copperbelt 8.9 31.4 8.3 26.5 16.0 7.9 0.9 100.0 3,372 6.9 Eastern 23.9 45.7 7.6 14.7 4.5 2.5 1.0 100.0 3,127 3.1 Luapula 19.1 42.8 8.6 18.5 5.7 2.7 2.5 100.0 1,990 3.9 Lusaka 8.2 31.7 9.8 24.5 15.9 8.8 1.1 100.0 4,073 6.8 Muchinga 13.8 47.8 10.5 20.8 4.6 2.1 0.4 100.0 1,379 4.5 Northern 14.7 44.9 12.5 20.8 4.5 1.9 0.7 100.0 2,023 4.5 North Western 11.6 45.4 5.3 23.0 8.3 5.7 0.7 100.0 1,255 4.9 Southern 13.3 39.0 12.9 22.5 8.0 3.8 0.5 100.0 2,918 5.7 Western 16.9 50.7 7.7 16.2 5.8 2.2 0.5 100.0 1,424 3.5 Wealth quintile Lowest 25.1 49.2 10.7 12.3 1.7 0.0 1.0 100.0 4,333 2.5 Second 18.9 48.7 9.9 17.8 3.2 0.3 1.2 100.0 4,652 3.5 Middle 13.9 43.6 12.2 22.2 6.6 0.8 0.7 100.0 4,959 4.8 Fourth 9.1 33.5 10.2 28.3 14.0 3.9 1.1 100.0 4,901 6.6 Highest 4.6 26.2 5.6 24.9 19.8 18.1 0.8 100.0 4,894 8.6 Total 14.0 39.9 9.7 21.3 9.3 4.8 1.0 100.0 23,740 5.3 Note: Figures in parentheses are based on 25-49 unweighted cases. 1 Completed grade 7 at the primary level 2 Completed grade 12 at the secondary level Housing Characteristics and Household Population • 31 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 DHS 2018 Net attendance ratio1 Gross attendance ratio2 Background characteristic Male Female Total Gender Parity Index3 Male Female Total Gender Parity Index3 PRIMARY SCHOOL Residence Urban 83.2 82.7 82.9 0.99 101.8 102.1 102.0 1.00 Rural 73.8 79.2 76.5 1.07 94.6 96.1 95.3 1.02 Province Central 71.2 76.2 73.8 1.07 87.9 91.5 89.7 1.04 Copperbelt 79.7 81.8 80.8 1.03 97.7 101.3 99.6 1.04 Eastern 61.7 78.5 70.2 1.27 82.6 95.7 89.1 1.16 Luapula 69.3 74.0 71.5 1.07 87.4 92.1 89.7 1.05 Lusaka 85.2 82.3 83.7 0.97 105.5 100.5 103.0 0.95 Muchinga 80.2 80.6 80.4 1.01 106.8 98.0 102.4 0.92 Northern 78.0 78.2 78.1 1.00 97.4 100.6 99.0 1.03 North Western 82.4 83.0 82.7 1.01 103.3 103.3 103.3 1.00 Southern 82.8 85.8 84.4 1.04 105.4 100.8 103.0 0.96 Western 83.3 82.5 82.9 0.99 102.5 98.0 100.2 0.96 Wealth quintile Lowest 65.7 72.0 68.9 1.10 84.3 87.1 85.7 1.03 Second 72.5 78.8 75.7 1.09 94.4 96.4 95.4 1.02 Middle 79.2 83.8 81.5 1.06 99.4 101.9 100.7 1.03 Fourth 83.9 84.6 84.2 1.01 104.1 100.5 102.3 0.97 Highest 86.1 83.6 84.8 0.97 105.3 106.2 105.8 1.01 Total 77.0 80.5 78.8 1.04 97.1 98.2 97.7 1.01 SECONDARY SCHOOL Residence Urban 59.2 53.1 55.9 0.90 84.1 77.9 80.8 0.93 Rural 31.3 26.0 28.7 0.83 44.3 36.2 40.4 0.82 Province Central 35.2 37.6 36.4 1.07 50.8 52.9 51.8 1.04 Copperbelt 55.1 48.8 51.7 0.88 77.0 70.6 73.5 0.92 Eastern 22.7 19.9 21.3 0.88 33.9 26.1 30.2 0.77 Luapula 33.8 22.7 28.2 0.67 50.0 34.0 41.9 0.68 Lusaka 58.5 51.7 55.0 0.88 79.8 79.4 79.6 0.99 Muchinga 32.7 29.3 31.0 0.90 45.0 39.5 42.2 0.88 Northern 43.2 31.7 37.3 0.73 63.9 43.4 53.3 0.68 North Western 52.6 45.9 48.9 0.87 77.9 65.9 71.3 0.85 Southern 41.0 39.5 40.4 0.96 57.6 57.0 57.4 0.99 Western 38.7 34.8 36.7 0.90 53.8 46.5 50.1 0.86 Wealth quintile Lowest 12.7 10.1 11.3 0.79 21.1 13.7 17.1 0.65 Second 27.6 21.9 24.8 0.79 37.8 29.1 33.6 0.77 Middle 37.2 36.5 36.8 0.98 50.1 48.3 49.2 0.96 Fourth 51.0 48.3 49.7 0.95 70.6 69.7 70.2 0.99 Highest 73.0 61.9 67.0 0.85 107.2 94.8 100.6 0.88 Total 42.3 37.9 40.0 0.90 59.9 54.5 57.2 0.91 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 100.0 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. 32 • Housing Characteristics and Household Population Table 2.14 Children under age 5 by highest level of education Percent distribution of children under age 5 by highest level of education attended, according to age, residence, and province, Zambia DHS 2018 Sex Total Male Female Background characteristic Never attended school Highest level attended pre-K Total Number of children Never attended school Highest level attended pre-K Total Number of children Never attended school Highest level attended pre-K Total Number of children Residence Urban 71.5 28.5 100.0 1,020 72.9 27.1 100.0 1,081 72.2 27.8 100.0 2,101 Rural 95.1 4.9 100.0 1,958 93.3 6.7 100.0 1,959 94.2 5.8 100.0 3,917 Province Central 90.8 9.2 100.0 262 85.9 14.1 100.0 270 88.3 11.7 100.0 532 Copperbelt 72.1 27.9 100.0 409 78.4 21.6 100.0 379 75.1 24.9 100.0 788 Eastern 93.0 7.0 100.0 361 90.2 9.8 100.0 404 91.5 8.5 100.0 764 Luapula 94.4 5.6 100.0 296 92.7 7.3 100.0 291 93.6 6.4 100.0 587 Lusaka 70.9 29.1 100.0 443 68.5 31.5 100.0 494 69.7 30.3 100.0 937 Muchinga 96.6 3.4 100.0 193 95.7 4.3 100.0 182 96.1 3.9 100.0 375 Northern 96.4 3.6 100.0 279 92.3 7.7 100.0 265 94.4 5.6 100.0 545 North Western 90.5 9.5 100.0 160 86.0 14.0 100.0 161 88.2 11.8 100.0 322 Southern 91.1 8.9 100.0 397 91.9 8.1 100.0 395 91.5 8.5 100.0 792 Western 94.7 5.3 100.0 177 97.3 2.7 100.0 201 96.0 4.0 100.0 378 Total 87.0 13.0 100.0 2,977 86.0 14.0 100.0 3,041 86.5 13.5 100.0 6,018 Table 2.15 School attendance by survivorship of parents Among de jure children age 10-14, the percentage attending school and the ratio of the percentage attending, by parental survival, according to background characteristics, Zambia DHS 2018 Percentage attending school by survivorship of parents Background characteristic Both parents deceased Number Both parents alive and living with at least one parent Number Ratio1 Sex Male 77.4 102 84.9 3,489 0.9 Female 80.4 107 90.4 3,407 0.9 Residence Urban 89.7 73 93.1 2,365 1.0 Rural 73.1 136 84.8 4,531 0.9 Province Central (77.5) 28 84.1 604 0.9 Copperbelt (98.1) 30 91.6 809 1.1 Eastern * 15 79.0 991 0.7 Luapula (66.1) 29 81.5 630 0.8 Lusaka * 30 93.2 1,050 1.0 Muchinga * 12 87.5 469 0.8 Northern (57.3) 26 87.0 641 0.7 North Western * 13 90.9 403 1.1 Southern * 13 92.5 834 1.0 Western * 15 88.4 465 1.0 Wealth quintile Lowest 65.4 45 76.5 1,472 0.9 Second 69.3 48 85.4 1,483 0.8 Middle 80.1 42 88.6 1,514 0.9 Fourth (95.1) 38 92.2 1,281 1.0 Highest (90.5) 35 98.2 1,145 0.9 Total 78.9 209 87.6 6,896 0.9 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 Characteristics of Respondents • 33 CHARACTERISTICS OF RESPONDENTS 3 Key Findings ▪ Literacy: Two-thirds (66%) of women and 82% of men age 15-49 are literate. ▪ Exposure to mass media: Only 5% of women and 13% of men have access to three specified types of mass media (newspaper, television, and radio) on a weekly basis. ▪ Internet use: Overall, 12% of women and 26% of men age 15-49 have used the internet in the past 12 months. ▪ Employment: Forty-five percent of women are currently employed, as compared with 75% of men age 15-49. Among those employed in the 12 months preceding the survey, 34% of women and 31% of men work in agriculture. ▪ Health insurance: Health insurance coverage is low, with only 2% of women and 3% of men age 15-49 having any type of health insurance. ▪ Tobacco: One percent of women and 19% of men age 15-49 smoke tobacco. his chapter presents information on the demographic and socioeconomic characteristics of the survey respondents such as age, education, place of residence, marital status, employment, and wealth status. This information is useful for understanding the factors that affect use of reproductive health services, contraceptive use, and other health behaviours. 3.1 BASIC CHARACTERISTICS OF SURVEY RESPONDENTS A total of 13,683 women age 15-49 and 12,132 men age 15-59 were interviewed in the 2018 ZDHS. Table 3.1 shows the distribution of women and men age 15-49 interviewed by background characteristics. For the most part, the female and male populations have similar distributions. In both populations, 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. A majority of women (81%) and men (80%) are Protestant. Seventeen percent of women and 19% of men are Catholic, while 1% of women and less than 1% of men are Muslim. Table 3.1 shows that about 3 in 10 women (31%) and more than 4 in 10 men (46%) have never been married. More than half of women (55%) and 50% of men are currently married; 1% of women and less than 1% of men are living with someone as if married. The data further show that female respondents are more likely than male respondents to be divorced or separated (10% versus 4%) or widowed (3% versus less than 1%). More than half of women and men (53% and 55%, respectively) live in rural areas. By province, the largest proportion of female and male respondents (20% and 19%, respectively) live in Lusaka, while the T 34 • Characteristics of Respondents smallest proportion of women (5%) reside in North Western and the smallest proportion of men reside in North Western, Western, and Muchinga (5% each). 3.2 EDUCATION AND LITERACY Literacy Respondents who have attended higher than secondary school are assumed to be literate. All other respondents, shown a typed sentence to read aloud, are considered literate if they could read all or part of the sentence. Sample: Women and men age 15-49 Education is an important factor influencing an individual’s attitudes and opportunities. Tables 3.2.1 and 3.2.2 show that men have slightly greater educational attainment than women; the median number of years of schooling completed among men is 6.9, as compared with 6.8 among women. In addition, 8% of women have no formal education, compared with only 4% of men. Forty-four percent of women and 38% of men have attended or completed primary school, and 43% of women and 50% of men have attended or completed secondary school. Higher education is relatively rare; only 6% of women and 8% of men have attended or completed a higher education (Figure 3.1). Literacy follows a similar pattern, with only 66% of women being literate, as compared with 82% of men (Tables 3.3.1 and 3.3.2). Trends: The percentage of women with a secondary or higher education increased from 28% in 1996 to 48% in 2018, with a corresponding increase among men (from 44% to 58%). The percentage of women (8%) and men (4%) with no education has remained constant since 2013-14. Patterns by background characteristics ▪ Urban women have on average completed more years of education (8.4) than their rural counterparts (5.7). A similar pattern is observed between urban (8.0) and rural (6.3) men. ▪ There is considerable provincial variation in educational attainment. The largest proportion of women with no education is found in Muchinga (15%), while the largest proportion of men with no education is found in Eastern (13%). Figure 3.1 Education of survey respondents 8 4 29 23 15 14 32 35 11 16 6 8 Women Men Percent distribution of women and men age 15-49 by highest level of schooling attended or completed Higher Completed secondary Some secondary Primary complete Primary incomplete No education Characteristics of Respondents • 35 ▪ The proportion of respondents who have completed secondary school or higher increases with increasing wealth. Forty-five percent of women and 55% of men in the highest wealth quintile have completed secondary school or higher, as compared with 1% of women and 3% of men in the lowest wealth quintile (Figure 3.2). ▪ Literacy among women generally decreases with age, from 76% among those age 15-19 to 58% among those age 45-49 (Table 3.3.1). ▪ Respondents living in urban areas are more likely to be literate than those living in rural areas, although the gap in literacy rates between urban and rural populations is higher among women than among men. Eighty-one percent of urban women and 91% of urban men are literate, as compared with 54% of rural women and 74% of rural men. 3.3 MASS MEDIA EXPOSURE Exposure to mass media Respondents were asked how often they read a newspaper, listened to the radio, or watched television. Those who responded at least once a week are considered regularly exposed to that form of media. Sample: Women and men age 15-49 Access to information is essential in increasing people’s knowledge and awareness of important issues. Data on women’s and men’s exposure to mass media are especially crucial in the development of health education programmes and the dissemination of information, particularly on family planning, nutrition, HIV/AIDS, and other essential topics. Radio is the dominant medium of information for men, whereas television is the most dominant medium for women: 56% of men age 15-49 listen to the radio and 38% of women watch television at least once a week (Tables 3.4.1 and 3.4.2). Men are more likely (13%) than women (5%) to access all three forms of media (newspaper, television, and radio) on a weekly basis. Forty-six percent of women and 31% of men do not access any of the three media on a weekly basis (Figure 3.3). The internet is also a critical tool through which people access and share information. Internet use includes accessing web pages, email, and social media. Among all women and men age 15-49, 12% and 26% have used the internet in the last 12 months, respectively. Of those who have accessed the internet in the past 12 months, a greater percentage of women (55%) than men (47%) use the internet on a daily basis (Tables 3.5.1 and 3.5.2). Figure 3.2 Secondary education by household wealth Figure 3.3 Exposure to mass media 1 2 5 16 45 3 7 14 27 55 Lowest Second Middle Fourth Highest Percentage of women and men age 15-49 with secondary education complete or higher Women Men WealthiestPoorest 11 38 35 5 46 22 43 56 13 31 Reads news- paper Watches television Listens to radio All three media None of these media Percentage of women and men age 15-49 who are exposed to media on a weekly basis Women Men 36 • Characteristics of Respondents Trends: The percentage of women age 15-49 with no weekly access to mass media increased from 33% in 2007 and 34% in 2013-14 to 46% in 2018. Among men, the percentage increased from 19% in 2007 and 22% in 2013-14 to 31% in 2018. Patterns by background characteristics ▪ Both men and women in urban areas are more likely to have accessed all three forms of mass media in the last week than those in rural areas (9% versus 2% among women and 22% versus 5% among men) (Table 3.4.1 and 3.4.2). ▪ Exposure to the three forms of mass media increases with increasing education. The proportion of women with exposure to all three forms of media rises from less than 1% among those with no education to 29% among those with a higher education. Among men, the corresponding increase is from less than 1% to 45%. ▪ Internet use in the last 12 months is more common in urban areas (22% of women and 44% of men) than in rural areas (3% of women and 11% of men) (Tables 3.5.1 and 3.5.2). ▪ Internet usage among women and men generally increases with increasing education and household wealth. Seventy-nine percent of women and 89% of men with a higher education used the internet in the past 12 months, as compared with 1% of women and 6% of men with no education. Similarly, 38% of women and 65% of men in the highest wealth quintile used the internet during the past 12 months, compared with less than 1% of women and 3% of men in the lowest wealth quintile. 3.4 EMPLOYMENT Currently employed Respondents who were employed in the 7 days before the survey. Sample: Women and men age 15-49 Men are more likely (75%) to be currently employed than women (45%) (Tables 3.6.1 and 3.6.2). Twenty- one percent of men and 48% of women were not employed in the 12 months preceding the survey. Trends: The percentage of women who are currently employed decreased from 46% in 1996 to 45% in 2018. Among men, however, the percentage increased from 62% to 75% over the same period. Patterns by background characteristics ▪ The percentage of men who are currently employed is highest in Muchinga (81%) and lowest in North Western (65%). Conversely, the percentage of women who are employed is highest in Luapula (57%) and lowest in Muchinga (33%). ▪ There are minor differences between urban and rural areas in the percentages of women and men who are currently employed (46% versus 45% for women and 73% versus 76% for men) (Figure 3.4). Figure 3.4 Employment status by residence 45 46 45 75 73 76 Total Urban Rural Percentage of women and men age 15-49 who are currently employed Women Men Characteristics of Respondents • 37 3.5 OCCUPATION Occupation Categorised as professional/technical/managerial, clerical, sales and services, skilled manual, unskilled manual, domestic service, agriculture, and other occupations. Sample: Women and men age 15-49 who were currently employed or had worked in the 12 months before the survey Roughly one in three women (34%) and men (31%) age 15-49 work in the agriculture sector. Among men, 20% work in skilled manual occupations and another 20% work in unskilled manual occupations (Tables 3.7.1 and 3.7.2). Thirty-five percent of women are engaged in sales and services, while 8% work in professional/technical/managerial jobs. Nineteen percent of employed women in Zambia are not paid for the work they do. Women engaged in agricultural work are more likely (37%) than women not working in agriculture (9%) to not be paid for their work. Sixty-three percent of women who worked in the past year are self-employed (Table 3.8.1). Among men, 16% are not paid for their work. Similar to women, men engaged in agricultural work are more likely to not be paid (26%) than those not working in agriculture (11%) (Table 3.8.2). Trends: The proportion of women employed in agriculture declined from 58% in 2001-2002 to 34% in 2018; the corresponding decrease among men was from 52% to 31%. The proportion of women and men working in professional, technical, and managerial occupations increased between 1996 and 2018 (from 5% to 8% among women and from 7% to 9% among men). Patterns by background characteristics ▪ Urban women are more likely to work in sales and services (50%) than women in rural areas (22%), while urban men are more likely to be engaged in skilled manual occupations (31%) and sales and services (20%) than rural men (11% and 7%, respectively). In rural areas, however, the highest percentage of women and men work in agriculture (59% of women and 50% of men) (Tables 3.7.1 and 3.7.2). ▪ The proportion of women and men working in professional, technical, and managerial occupations rises sharply between the secondary and higher levels of education. 3.6 HEALTH INSURANCE COVERAGE Only 2% of women and 3% of men age 15-49 have any type of health insurance (Tables 3.9.1 and 3.9.2). Trends: The percentage of women without health insurance increased slightly from 97% in 2013-14 to 98% in 2018, while the percentage among men was 97% in both 2013-14 and 2018. 3.7 TOBACCO USE One percent of women age 15-49 smoke any kind of tobacco (Table 3.10.1), as compared with 19% of men age 15-49 (Table 3.10.2). Fourteen percent of men smoke daily, and 5% are occasional smokers. Forty-nine percent of men who are daily smokers reported that they smoke on average less than five cigarettes per day (Table 3.11). Trends: The percentage of men age 15-49 who smoke cigarettes increased from 15% in 2000-01 to 23% in 2007 before declining to 19% in both 2013-14 and 2018. 38 • Characteristics of Respondents Patterns by background characteristics ▪ The proportion of men who smoke any type of tobacco generally increases with age; only 3% of men age 15-19 smoke tobacco, as compared with 33% of those age 45-49. ▪ Men in Luapula are most likely to smoke cigarettes (25%), while those in Southern are least likely to do so (12%). ▪ Cigarette smoking among men decreases with increasing education, from 26% among those with no education to 8% among those with a higher education. 3.8 SURGERY The Lancet Commission on Global Surgery was created in 2013 with the objective of bringing to the forefront the issue of global surgery and anaesthesia as an integral part of universal access to health services. Its vision is centred on universal access to safe, affordable surgical and anaesthesia care when needed. Four dimensions of access are considered: timeliness, surgical capacity, safety, and affordability (Lancet Commission 2015). Two of the indicators identified by the Lancet Commission were access to timely essential surgery and surgical volume. To collect data informing these indicators, five questions were added to the 2018 ZDHS for both women and men. In this report, information from only the first two questions is analysed. In the first question, respondents were asked “Have you ever undergone a surgical operation in the past 5 years?” If they responded yes, they were asked “What type of operation(s) were they?” The results, presented in Table 3.14, show that 5% of women and 2% of men age 15-49 had an operation in the last 5 years. Among women, caesarean sections (C-sections) represented nearly four out of five surgeries undergone. Patterns by background characteristics ▪ Across all age groups, the percentage of women who had surgery is higher than the percentage among men, peaking at age 30-34 (7%), when C-sections are particularly common. However, when excluding C- sections, the percentages of men and women converge (Figure 3.5). This demonstrates that the greater use of surgery among women is largely due to C-sections. ▪ More women in urban areas (6%) reported having surgery in the last 5 years than women in rural areas (4%). A similar pattern is observed by men (3% and 1%, respectively) (Table 3.14). ▪ The percentage of women who have undergone surgery differs by province, ranging from a high of 7% in Eastern to a low of 3% in Western. Among men, provincial differences are small. Figure 3.5 Use of surgery by age group 0 1 2 3 4 5 6 7 8 9 10 15-19 20-24 25-29 30-34 35-39 40-44 45-49 Age group Percentage of women and men age 15-49 who underwent surgery in the last 5 years by age Total women Women excluding C-section Women only including C-section Total men Characteristics of Respondents • 39 ▪ The higher a woman’s educational level, the more likely she is to have had surgery in the last 5 years. Thirteen percent of women with a higher education had surgery, as compared with 4% of women with no education or a primary education. The pattern among men is similar. ▪ Both women (7%) and men (4%) in the highest wealth quintile are more likely to have had surgery than those in the lowest quintile (3% and 1%, respectively). LIST OF TABLES For more information on the characteristics of survey respondents, see the following tables: ▪ Table 3.1 Background characteristics of respondents ▪ Table 3.2.1 Educational attainment: Women ▪ Table 3.2.2 Educational attainment: Men ▪ Table 3.3.1 Literacy: Women ▪ Table 3.3.2 Literacy: Men ▪ Table 3.4.1 Exposure to mass media: Women ▪ Table 3.4.2 Exposure to mass media: Men ▪ Table 3.5.1 Internet usage: Women ▪ Table 3.5.2 Internet usage: Men ▪ Table 3.6.1 Employment status: Women ▪ Table 3.6.2 Employment status: Men ▪ Table 3.7.1 Occupation: Women ▪ Table 3.7.2 Occupation: Men ▪ Table 3.8.1 Type of employment: Women ▪ Table 3.8.2 Type of employment: Men ▪ Table 3.9.1 Health insurance coverage: Women ▪ Table 3.9.2 Health insurance coverage: Men ▪ Table 3.10.1 Tobacco smoking: Women ▪ Table 3.10.2 Tobacco smoking: Men ▪ Table 3.11 Average number of cigarettes smoked daily: Men ▪ Table 3.12 Smokeless tobacco use and any tobacco use ▪ Table 3.13 History of diabetes and hypertension ▪ Table 3.14 Use of surgery 40 • Characteristics of Respondents Table 3.1 Background characteristics of respondents Percent distribution of women and men age 15-49 by selected background characteristics, Zambia DHS 2018 Women Men Background characteristic Weighted percent Weighted number Unweighted number Weighted percent Weighted number Unweighted number Age 15-19 21.9 3,000 3,112 24.9 2,781 2,852 20-24 20.0 2,733 2,687 18.2 2,032 1,994 25-29 16.4 2,237 2,166 15.4 1,721 1,630 30-34 13.6 1,862 1,864 12.4 1,383 1,357 35-39 12.4 1,697 1,622 11.5 1,280 1,282 40-44 9.2 1,253 1,280 9.8 1,097 1,096 45-49 6.6 900 952 7.9 883 893 Religion Catholic 17.2 2,354 2,351 18.7 2,089 2,048 Protestant 81.1 11,098 11,138 79.8 8,917 8,889 Muslim 0.5 64 61 0.4 48 54 Other 1.2 167 133 1.1 123 113 Marital status Never married 31.2 4,272 4,321 46.0 5,142 5,129 Married 55.4 7,580 7,544 49.6 5,545 5,497 Living together 0.5 68 53 0.2 27 37 Divorced/separated 10.0 1,370 1,366 3.7 418 404 Widowed 2.9 392 399 0.4 45 37 Residence Urban 46.6 6,374 5,513 44.8 5,013 4,191 Rural 53.4 7,309 8,170 55.2 6,165 6,913 Province Central 8.5 1,165 1,397 8.8 979 1,211 Copperbelt 16.1 2,201 1,615 15.5 1,727 1,313 Eastern 11.7 1,605 1,536 13.2 1,476 1,346 Luapula 7.8 1,071 1,414 7.6 849 1,140 Lusaka 20.0 2,733 1,775 19.4 2,166 1,415 Muchinga 5.5 754 1,183 5.4 599 968 Northern 7.7 1,054 1,239 7.7 855 976 North Western 5.2 718 1,081 5.0 556 847 Southern 11.5 1,574 1,347 12.5 1,395 1,117 Western 5.9 808 1,096 5.1 574 771 Education No education 7.7 1,054 1,145 4.0 446 450 Primary 44.3 6,059 6,217 37.6 4,206 4,399 Secondary 42.5 5,816 5,556 50.3 5,618 5,387 Higher 5.5 755 765 8.1 907 868 Wealth quintile Lowest 17.8 2,442 2,844 16.3 1,827 2,133 Second 17.4 2,387 2,677 17.5 1,952 2,214 Middle 18.1 2,477 2,683 19.8 2,218 2,391 Fourth 22.0 3,011 2,559 22.8 2,552 2,090 Highest 24.6 3,367 2,920 23.5 2,629 2,276 Total 15-49 100.0 13,683 13,683 100.0 11,177 11,104 50-59 na na na na 955 1,028 Total 15-59 na na na na 12,132 12,132 Note: Education categories refer to the highest level of education attended, whether or not that level was completed. na = Not applicable Characteristics of Respondents • 41 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 DHS 2018 Highest level of schooling Total Median years completed Number of women Background characteristic No education Some primary Completed primary1 Some secondary Completed secondary2 Higher Age 15-24 3.6 25.6 13.4 42.3 12.5 2.6 100.0 7.3 5,733 15-19 3.3 28.8 14.0 47.5 6.1 0.3 100.0 7.0 3,000 20-24 3.9 22.2 12.7 36.7 19.4 5.1 100.0 7.9 2,733 25-29 6.6 23.5 14.2 31.7 14.9 9.1 100.0 7.4 2,237 30-34 10.9 31.6 13.9 24.0 10.4 9.3 100.0 6.5 1,862 35-39 11.8 35.1 17.4 23.2 5.5 7.0 100.0 6.2 1,697 40-44 12.6 36.2 19.8 20.4 5.5 5.5 100.0 6.1 1,253 45-49 15.4 38.6 21.3 16.8 3.3 4.7 100.0 5.6 900 Residence Urban 3.3 14.0 13.9 40.6 18.5 9.7 100.0 8.4 6,374 Rural 11.5 42.2 16.3 24.6 3.5 1.8 100.0 5.7 7,309 Province Central 6.2 26.0 19.1 34.3 10.4 4.0 100.0 6.9 1,165 Copperbelt 2.7 15.9 16.2 38.2 18.5 8.5 100.0 8.3 2,201 Eastern 13.2 51.0 9.9 19.5 3.5 2.9 100.0 4.9 1,605 Luapula 11.0 43.1 13.3 24.3 5.0 3.3 100.0 5.6 1,071 Lusaka 4.6 14.4 13.9 40.0 16.8 10.3 100.0 8.3 2,733 Muchinga 15.4 36.6 16.9 24.5 4.7 1.9 100.0 5.8 754 Northern 10.9 48.1 13.0 21.9 3.8 2.2 100.0 5.2 1,054 North Western 7.8 31.6 7.7 35.5 11.3 6.0 100.0 6.7 718 Southern 4.4 23.7 23.9 36.7 7.6 3.6 100.0 6.9 1,574 Western 13.3 33.2 15.2 28.4 7.0 2.8 100.0 6.2 808 Wealth quintile Lowest 19.1 53.0 14.3 12.9 0.7 0.0 100.0 4.1 2,442 Second 11.6 45.9 17.2 23.4 1.9 0.0 100.0 5.5 2,387 Middle 6.2 33.8 19.6 35.0 5.0 0.4 100.0 6.4 2,477 Fourth 4.0 18.0 17.9 44.4 13.1 2.7 100.0 7.6 3,011 Highest 1.2 6.3 8.7 38.8 25.4 19.6 100.0 10.2 3,367 Total 7.7 29.1 15.2 32.0 10.5 5.5 100.0 6.8 13,683 1 Completed grade 7 at the primary level 2 Completed grade 12 at the secondary level 42 • Characteristics of Respondents 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 DHS 2018 Highest level of schooling Total Median years completed Number of men Background characteristic No education Some primary Completed primary1 Some secondary Completed secondary2 Higher Age 15-24 3.0 25.2 13.0 42.6 13.3 2.9 100.0 6.7 4,813 15-19 2.7 32.5 13.7 46.7 4.2 0.2 100.0 6.3 2,781 20-24 3.5 15.1 12.1 37.0 25.8 6.6 100.0 7.6 2,032 25-29 2.5 14.9 12.6 35.1 22.3 12.6 100.0 7.5 1,721 30-34 5.6 19.9 13.9 26.9 21.3 12.4 100.0 7.2 1,383 35-39 5.7 22.7 15.6 28.2 15.1 12.7 100.0 6.8 1,280 40-44 5.3 27.5 19.3 26.0 10.8 11.2 100.0 6.7 1,097 45-49 5.5 29.0 19.1 24.5 11.3 10.6 100.0 6.6 883 Residence Urban 1.5 10.0 11.1 38.9 24.4 14.2 100.0 8.0 5,013 Rural 6.0 33.9 17.1 31.5 8.3 3.2 100.0 6.3 6,165 Province Central 2.8 23.3 18.8 33.6 14.2 7.4 100.0 6.9 979 Copperbelt 1.6 12.7 10.0 39.5 23.7 12.6 100.0 7.8 1,727 Eastern 13.1 39.4 11.4 23.3 8.6 4.0 100.0 5.5 1,476 Luapula 4.2 32.7 14.9 32.8 10.4 5.0 100.0 6.4 849 Lusaka 1.6 10.8 13.9 36.5 23.0 14.1 100.0 7.8 2,166 Muchinga 3.4 31.2 16.2 37.8 8.4 3.0 100.0 6.4 599 Northern 3.5 30.7 18.1 35.7 8.6 3.4 100.0 6.5 855 North Western 2.5 22.8 8.8 40.0 15.9 10.0 100.0 6.9 556 Southern 2.2 20.1 19.6 38.8 13.3 6.0 100.0 6.8 1,395 Western 5.6 34.0 15.3 28.8 12.2 4.0 100.0 6.3 574 Wealth quintile Lowest 10.6 45.2 17.6 23.2 3.3 0.0 100.0 5.4 1,827 Second 5.2 38.3 17.2 32.4 6.4 0.5 100.0 6.1 1,952 Middle 3.6 25.6 19.1 37.7 12.4 1.5 100.0 6.6 2,218 Fourth 2.1 13.5 14.5 43.3 20.6 5.9 100.0 7.3 2,552 Highest 0.6 4.0 6.2 33.8 28.3 27.1 100.0 10.2 2,629 Total 15-49 4.0 23.2 14.4 34.8 15.5 8.1 100.0 6.9 11,177 50-59 4.8 27.0 27.1 22.9 8.6 9.7 100.0 6.6 955 Total 15-59 4.1 23.5 15.4 33.8 14.9 8.2 100.0 6.8 12,132 1 Completed grade 7 at the primary level 2 Completed grade 12 at the secondary level Characteristics of Respondents • 43 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 DHS 2018 Higher than secondary schooling No schooling, primary or secondary school 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 2.6 53.0 17.5 26.8 0.0 0.0 100.0 73.1 5,733 15-19 0.3 57.1 18.3 24.2 0.0 0.0 100.0 75.7 3,000 20-24 5.1 48.6 16.5 29.7 0.0 0.1 100.0 70.2 2,733 25-29 9.1 42.2 16.0 32.7 0.0 0.0 100.0 67.2 2,237 30-34 9.3 36.0 16.7 38.0 0.0 0.0 100.0 62.0 1,862 35-39 7.0 34.3 15.8 42.8 0.0 0.1 100.0 57.1 1,697 40-44 5.5 37.6 16.1 40.6 0.2 0.1 100.0 59.1 1,253 45-49 4.7 39.7 13.9 41.5 0.0 0.3 100.0 58.3 900 Residence Urban 9.7 51.1 19.7 19.4 0.0 0.1 100.0 80.5 6,374 Rural 1.8 38.4 13.8 45.8 0.0 0.1 100.0 54.1 7,309 Province Central 4.0 49.4 20.4 26.1 0.0 0.0 100.0 73.9 1,165 Copperbelt 8.5 51.6 17.0 22.8 0.0 0.1 100.0 77.1 2,201 Eastern 2.9 35.6 11.2 50.1 0.0 0.1 100.0 49.7 1,605 Luapula 3.3 34.6 12.4 49.6 0.0 0.0 100.0 50.4 1,071 Lusaka 10.3 43.1 26.6 19.9 0.1 0.0 100.0 80.0 2,733 Muchinga 1.9 35.2 15.2 47.3 0.3 0.2 100.0 52.2 754 Northern 2.2 34.6 10.4 52.6 0.0 0.2 100.0 47.3 1,054 North Western 6.0 46.8 11.7 35.6 0.0 0.0 100.0 64.4 718 Southern 3.6 56.1 12.5 27.7 0.0 0.1 100.0 72.2 1,574 Western 2.8 47.5 13.0 36.7 0.0 0.0 100.0 63.3 808 Wealth quintile Lowest 0.0 24.7 12.2 63.1 0.0 0.0 100.0 36.9 2,442 Second 0.0 36.8 13.9 49.1 0.1 0.1 100.0 50.8 2,387 Middle 0.4 48.6 16.8 34.1 0.0 0.1 100.0 65.8 2,477 Fourth 2.7 50.9 21.7 24.6 0.1 0.1 100.0 75.3 3,011 Highest 19.6 54.9 16.8 8.6 0.0 0.1 100.0 91.3 3,367 Total 5.5 44.3 16.5 33.5 0.0 0.1 100.0 66.4 13,683 1 Refers to women who attended schooling higher than the secondary level and women who can read a whole sentence or part of a sentence 44 • Characteristics of Respondents 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 DHS 2018 Higher than secondary schooling No schooling, primary or secondary school 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 2.9 61.1 18.5 17.4 0.0 0.0 100.0 82.5 4,813 15-19 0.2 61.1 20.0 18.6 0.0 0.0 100.0 81.4 2,781 20-24 6.6 61.0 16.5 15.8 0.1 0.1 100.0 84.0 2,032 25-29 12.6 56.4 16.9 13.8 0.3 0.0 100.0 86.0 1,721 30-34 12.4 53.6 15.5 18.3 0.1 0.1 100.0 81.6 1,383 35-39 12.7 50.1 17.3 18.5 1.0 0.4 100.0 80.2 1,280 40-44 11.2 50.1 16.3 22.4 0.0 0.0 100.0 77.6 1,097 45-49 10.6 51.8 15.1 22.2 0.0 0.3 100.0 77.5 883 Residence Urban 14.2 62.3 14.5 8.6 0.4 0.0 100.0 91.0 5,013 Rural 3.2 51.5 19.5 25.6 0.0 0.1 100.0 74.3 6,165 Province Central 7.4 34.4 35.9 22.4 0.0 0.0 100.0 77.6 979 Copperbelt 12.6 63.0 14.3 10.0 0.0 0.2 100.0 89.8 1,727 Eastern 4.0 46.6 16.0 33.2 0.1 0.1 100.0 66.7 1,476 Luapula 5.0 62.1 13.2 19.5 0.0 0.2 100.0 80.4 849 Lusaka 14.1 60.8 14.7 10.0 0.3 0.0 100.0 89.6 2,166 Muchinga 3.0 52.9 20.7 23.2 0.0 0.2 100.0 76.6 599 Northern 3.4 61.6 17.9 16.8 0.0 0.3 100.0 83.0 855 North Western 10.0 57.3 13.4 19.4 0.0 0.0 100.0 80.6 556 Southern 6.0 58.7 18.3 16.1 0.8 0.1 100.0 83.0 1,395 Western 4.0 63.4 10.6 22.0 0.0 0.1 100.0 77.9 574 Wealth quintile Lowest 0.0 43.2 20.5 36.1 0.1 0.1 100.0 63.7 1,827 Second 0.5 52.6 19.9 26.9 0.0 0.2 100.0 72.9 1,952 Middle 1.5 59.2 19.5 19.7 0.0 0.1 100.0 80.2 2,218 Fourth 5.9 63.0 19.6 10.9 0.5 0.0 100.0 88.6 2,552 Highest 27.1 59.6 9.0 4.0 0.2 0.1 100.0 95.7 2,629 Total 15-49 8.1 56.4 17.3 17.9 0.2 0.1 100.0 81.8 11,177 50-59 9.7 56.5 16.6 17.0 0.0 0.2 100.0 82.8 955 Total 15-59 8.2 56.4 17.2 17.9 0.2 0.1 100.0 81.9 12,132 1 Refers to men who attended schooling higher than the secondary level and men who can read a whole sentence or part of a sentence Characteristics of Respondents • 45 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, according to background characteristics, Zambia DHS 2018 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 12.4 36.8 29.5 4.8 47.5 3,000 20-24 10.1 37.9 33.1 4.3 46.0 2,733 25-29 10.4 40.4 37.6 5.2 43.3 2,237 30-34 10.4 43.2 38.4 6.0 42.1 1,862 35-39 10.1 37.3 35.9 5.3 46.2 1,697 40-44 9.2 35.2 36.0 5.4 48.6 1,253 45-49 11.3 28.5 34.9 4.9 52.5 900 Residence Urban 14.8 67.0 43.6 9.1 23.8 6,374 Rural 7.1 12.4 26.6 1.5 65.4 7,309 Province Central 11.1 30.7 38.6 4.0 46.7 1,165 Copperbelt 14.5 62.8 42.2 8.3 25.4 2,201 Eastern 16.6 19.0 33.7 3.6 51.6 1,605 Luapula 6.2 22.3 43.3 2.6 47.8 1,071 Lusaka 15.2 72.9 43.1 10.7 21.4 2,733 Muchinga 7.5 17.3 31.2 1.7 61.7 754 Northern 4.1 15.4 24.6 1.5 68.4 1,054 North Western 1.0 18.9 11.8 0.4 77.4 718 Southern 5.3 22.8 27.0 2.3 60.9 1,574 Western 9.4 14.4 19.7 2.3 70.7 808 Education No education 0.3 12.5 21.9 0.0 72.0 1,054 Primary 4.6 20.4 26.5 0.9 60.9 6,059 Secondary 15.0 54.0 42.0 7.2 31.1 5,816 Higher 40.5 88.5 59.1 28.9 5.8 755 Wealth quintile Lowest 4.7 3.3 16.6 0.3 79.0 2,442 Second 6.0 4.6 25.3 0.4 69.8 2,387 Middle 7.3 11.6 30.4 1.3 62.8 2,477 Fourth 8.9 54.1 39.1 4.2 32.1 3,011 Highest 22.4 91.2 52.9 15.4 5.4 3,367 Total 10.7 37.8 34.5 5.1 46.0 13,683 46 • Characteristics of Respondents 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, according to background characteristics, Zambia DHS 2018 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 15.8 42.0 48.5 7.3 35.2 2,781 20-24 20.9 43.2 53.0 10.1 32.7 2,032 25-29 23.7 44.1 58.0 12.9 28.7 1,721 30-34 26.6 43.4 59.3 16.7 29.1 1,383 35-39 27.2 46.9 63.1 17.9 25.8 1,280 40-44 24.2 42.4 62.0 15.9 28.2 1,097 45-49 24.4 40.8 59.0 14.9 30.6 883 Residence Urban 30.0 72.7 65.1 22.3 15.2 5,013 Rural 15.7 19.3 48.4 4.5 43.6 6,165 Province Central 24.4 35.8 61.0 10.0 28.7 979 Copperbelt 27.4 65.0 60.7 18.8 19.0 1,727 Eastern 24.8 24.5 48.1 7.6 41.1 1,476 Luapula 23.6 27.3 61.5 10.2 31.5 849 Lusaka 33.9 79.0 68.5 26.9 11.9 2,166 Muchinga 24.4 16.3 50.5 8.2 45.9 599 Northern 6.4 23.7 58.3 2.7 35.1 855 North Western 6.7 27.3 21.7 2.5 62.3 556 Southern 10.0 34.7 56.8 6.0 32.9 1,395 Western 13.6 20.2 30.5 3.9 57.2 574 Education No education 3.5 16.4 36.5 0.3 56.5 446 Primary 11.8 23.5 46.9 3.9 44.5 4,206 Secondary 25.8 52.7 61.4 14.7 22.8 5,618 Higher 56.1 89.3 73.0 44.6 4.9 907 Wealth quintile Lowest 11.4 6.2 34.8 1.3 59.9 1,827 Second 16.3 10.0 47.5 3.0 46.4 1,952 Middle 16.3 22.8 55.5 4.9 37.1 2,218 Fourth 23.5 62.7 63.2 16.0 19.3 2,552 Highest 37.4 91.9 70.2 30.3 5.1 2,629 Total 15-49 22.1 43.2 55.9 12.5 30.9 11,177 50-59 24.8 34.1 60.0 13.2 31.2 955 Total 15-59 22.3 42.5 56.2 12.5 30.9 12,132 Characteristics of Respondents • 47 Table 3.5.1 Internet usage: Women Percentage of women age 15-49 who have ever used the internet and percentage who have used the internet in the past 12 months, and among women who have used the internet in the past 12 months, percent distribution by frequency of internet use in the past month, according to background characteristics, Zambia DHS 2018 Ever used the internet Used the internet in the past 12 months Number Among respondents who have used the internet in the past 12 months, percentage who, in the past month, used the internet: Background characteristic Almost every day At least once a week Less than once a week Not at all Missing Total Number Age 15-19 10.5 9.2 3,000 39.6 34.2 24.1 2.1 0.0 100.0 275 20-24 19.2 17.5 2,733 55.7 29.1 11.8 3.4 0.0 100.0 478 25-29 17.6 15.7 2,237 59.3 28.5 10.3 1.9 0.0 100.0 351 30-34 14.7 13.6 1,862 58.6 23.1 15.4 2.9 0.0 100.0 253 35-39 10.1 9.4 1,697 60.1 25.7 13.7 0.5 0.0 100.0 159 40-44 7.8 7.1 1,253 52.1 28.3 17.2 2.4 0.0 100.0 89 45-49 5.4 4.9 900 (72.6) (16.8) (6.9) (3.7) (0.0) (100.0) 44 Residence Urban 24.4 22.2 6,374 56.5 28.1 13.2 2.2 0.0 100.0 1,418 Rural 3.8 3.2 7,309 44.8 28.8 22.2 4.3 0.0 100.0 231 Province Central 11.4 10.5 1,165 63.3 22.1 12.4 2.2 0.0 100.0 123 Copperbelt 22.9 20.7 2,201 56.2 28.0 12.3 3.5 0.0 100.0 454 Eastern 4.9 4.4 1,605 54.7 19.6 16.3 9.5 0.0 100.0 71 Luapula 6.4 6.0 1,071 58.3 26.5 9.2 6.0 0.0 100.0 64 Lusaka 24.4 22.1 2,733 58.5 25.8 14.8 0.9 0.0 100.0 604 Muchinga 6.0 5.5 754 39.1 52.5 6.6 1.8 0.0 100.0 42 Northern 5.1 3.6 1,054 29.3 54.5 11.7 4.5 0.0 100.0 38 North Western 13.6 11.8 718 50.4 23.2 25.9 0.6 0.0 100.0 85 Southern 7.4 7.0 1,574 37.0 41.7 19.2 2.1 0.0 100.0 111 Western 7.7 7.1 808 54.8 26.6 16.9 1.7 0.0 100.0 57 Education No education 0.5 0.5 1,054 * * * * * * 5 Primary 1.0 0.8 6,059 (32.9) (29.0) (38.1) (0.0) (0.0) (100.0) 47 Secondary 19.7 17.3 5,816 45.0 34.2 17.6 3.2 0.0 100.0 1,004 Higher 81.1 78.5 755 73.2 18.3 7.0 1.5 0.0 100.0 593 Wealth quintile Lowest 0.5 0.4 2,442 * * * * * * 10 Second 1.2 0.7 2,387 * * * * * * 16 Middle 3.6 3.1 2,477 26.7 50.6 15.6 7.1 0.0 100.0 76 Fourth 10.4 9.2 3,011 41.4 39.2 15.2 4.3 0.0 100.0 276 Highest 41.1 37.8 3,367 60.3 24.3 13.8 1.7 0.0 100.0 1,272 Total 13.4 12.1 13,683 54.9 28.2 14.4 2.5 0.0 100.0 1,649 Note: Figures in parentheses are based on 25-49 unweighted cases. An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. 48 • Characteristics of Respondents Table 3.5.2 Internet usage: Men Percentage of men age 15-49 who have ever used the internet and percentage who have used the internet in the past 12 months, and among men who have used the internet in the past 12 months, percent distribution by frequency of internet use in the past month, according to background characteristics, Zambia DHS 2018 Ever used the internet Used the internet in the past 12 months Number Among respondents who have used the internet in the past 12 months, percentage who, in the past month, used the internet: Background characteristic Almost every day At least once a week Less than once a week Not at all Missing Total Number Age 15-19 22.9 20.3 2,781 34.7 37.8 23.9 3.5 0.0 100.0 565 20-24 39.5 36.8 2,032 45.9 33.5 16.2 4.4 0.0 100.0 747 25-29 35.1 32.3 1,721 51.8 35.0 10.2 2.9 0.0 100.0 556 30-34 29.0 27.0 1,383 51.6 32.1 12.7 3.7 0.0 100.0 374 35-39 25.7 24.5 1,280 54.8 30.9 11.6 2.8 0.0 100.0 313 40-44 19.3 18.0 1,097 51.4 31.8 14.2 2.6 0.0 100.0 198 45-49 17.7 16.6 883 50.2 41.2 7.6 1.1 0.0 100.0 147 Residence Urban 47.6 44.2 5,013 51.4 33.2 11.8 3.6 0.0 100.0 2,215 Rural 12.3 11.1 6,165 33.4 38.4 25.4 2.8 0.0 100.0 686 Province Central 30.6 28.6 979 40.8 45.4 13.3 0.5 0.0 100.0 280 Copperbelt 38.2 35.5 1,727 45.7 40.5 12.1 1.7 0.0 100.0 613 Eastern 11.4 11.0 1,476 38.8 41.9 17.5 1.9 0.0 100.0 162 Luapula 12.1 10.4 849 35.0 45.8 18.1 1.1 0.0 100.0 88 Lusaka 54.0 50.0 2,166 55.4 26.6 12.5 5.6 0.0 100.0 1,084 Muchinga 7.5 6.7 599 34.8 32.4 28.9 3.8 0.0 100.0 40 Northern 13.3 12.2 855 31.9 30.7 33.5 3.9 0.0 100.0 104 North Western 27.4 24.0 556 42.7 23.7 24.2 9.3 0.0 100.0 133 Southern 24.5 22.7 1,395 43.9 37.0 18.8 0.4 0.0 100.0 316 Western 15.1 14.0 574 44.6 42.9 8.7 3.7 0.0 100.0 80 Education No education 6.0 6.0 446 * * * * * * 27 Primary 5.6 5.0 4,206 14.9 38.7 37.9 8.5 0.0 100.0 211 Secondary 36.6 33.0 5,618 39.5 39.8 16.9 3.8 0.0 100.0 1,857 Higher 90.5 88.9 907 72.2 21.3 5.2 1.3 0.0 100.0 807 Wealth quintile Lowest 3.0 2.5 1,827 (6.6) (56.0) (35.3) (2.1) (0.0) (100.0) 46 Second 7.0 5.6 1,952 16.7 44.0 34.3 5.0 0.0 100.0 110 Middle 14.4 12.6 2,218 31.4 40.6 25.6 2.3 0.0 100.0 279 Fourth 32.7 29.5 2,552 38.9 38.1 17.7 5.3 0.0 100.0 754 Highest 68.3 65.1 2,629 56.3 30.6 10.3 2.7 0.0 100.0 1,712 Total 15-49 28.1 26.0 11,177 47.1 34.4 15.0 3.4 0.0 100.0 2,901 50-59 13.4 12.9 955 54.6 27.6 17.2 0.6 0.0 100.0 123 Total 15-59 26.9 24.9 12,132 47.4 34.2 15.1 3.3 0.0 100.0 3,023 Note: Figures in parentheses are based on 25-49 unweighted cases. An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. Characteristics of Respondents • 49 Table 3.6.1 Employment status: Women Percent distribution of women age 15-49 by employment status, according to background characteristics, Zambia DHS 2018 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 17.4 4.3 78.2 100.0 3,000 20-24 35.9 8.5 55.6 100.0 2,733 25-29 50.0 7.6 42.4 100.0 2,237 30-34 59.2 7.4 33.4 100.0 1,862 35-39 63.2 6.6 30.3 100.0 1,697 40-44 63.5 8.4 28.1 100.0 1,253 45-49 63.5 9.5 27.0 100.0 900 Marital status Never married 25.6 5.4 69.0 100.0 4,272 Married or living together 51.2 7.6 41.2 100.0 7,648 Divorced/separated/ widowed 65.7 9.2 25.2 100.0 1,762 Number of living children 0 22.5 5.2 72.4 100.0 3,489 1-2 46.5 7.0 46.4 100.0 4,427 3-4 56.0 8.4 35.6 100.0 2,945 5+ 59.2 8.3 32.5 100.0 2,821 Residence Urban 45.7 5.3 49.0 100.0 6,374 Rural 44.5 8.7 46.8 100.0 7,309 Province Central 42.4 9.2 48.5 100.0 1,165 Copperbelt 39.6 5.3 55.1 100.0 2,201 Eastern 44.1 16.0 39.9 100.0 1,605 Luapula 57.1 5.0 37.9 100.0 1,071 Lusaka 47.6 4.4 48.0 100.0 2,733 Muchinga 33.3 7.7 59.0 100.0 754 Northern 47.5 4.0 48.5 100.0 1,054 North Western 38.8 6.2 55.1 100.0 718 Southern 48.3 6.1 45.6 100.0 1,574 Western 48.3 9.3 42.4 100.0 808 Education No education 43.1 11.0 45.9 100.0 1,054 Primary 47.5 8.0 44.5 100.0 6,059 Secondary 40.0 5.6 54.4 100.0 5,816 Higher 66.8 5.8 27.5 100.0 755 Wealth quintile Lowest 44.5 10.6 44.9 100.0 2,442 Second 43.4 9.0 47.6 100.0 2,387 Middle 47.3 6.4 46.2 100.0 2,477 Fourth 43.3 5.7 51.0 100.0 3,011 Highest 46.6 5.0 48.5 100.0 3,367 Total 45.0 7.1 47.8 100.0 13,683 1 “Currently employed” is defined as having done work in the past 7 days. Includes persons who did not work in the past 7 days but who are regularly employed and were absent from work for leave, illness, vacation, or any other such reason. 50 • Characteristics of Respondents Table 3.6.2 Employment status: Men Percent distribution of men age 15-49 by employment status, according to background characteristics, Zambia DHS 2018 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 35.6 6.2 58.2 100.0 2,781 20-24 71.4 5.6 23.0 100.0 2,032 25-29 89.1 3.1 7.8 100.0 1,721 30-34 94.3 2.1 3.6 100.0 1,383 35-39 94.0 2.1 4.0 100.0 1,280 40-44 94.4 2.8 2.8 100.0 1,097 45-49 92.0 3.0 5.0 100.0 883 Marital status Never married 51.7 5.8 42.5 100.0 5,142 Married or living together 94.6 2.4 3.0 100.0 5,572 Divorced/separated/ widowed 85.6 5.0 9.3 100.0 463 Number of living children 0 51.8 5.5 42.7 100.0 5,028 1-2 91.1 3.5 5.4 100.0 2,523 3-4 94.9 2.2 2.9 100.0 1,678 5+ 94.3 2.6 3.1 100.0 1,948 Residence Urban 72.5 4.6 23.0 100.0 5,013 Rural 76.2 3.7 20.2 100.0 6,165 Province Central 71.6 2.0 26.4 100.0 979 Copperbelt 73.5 3.4 23.1 100.0 1,727 Eastern 70.5 5.2 24.2 100.0 1,476 Luapula 79.0 1.5 19.4 100.0 849 Lusaka 75.4 5.9 18.7 100.0 2,166 Muchinga 81.2 3.5 15.3 100.0 599 Northern 75.4 4.4 20.2 100.0 855 North Western 64.8 4.6 30.7 100.0 556 Southern 78.0 3.5 18.5 100.0 1,395 Western 75.6 4.6 19.8 100.0 574 Education No education 77.7 4.2 18.1 100.0 446 Primary 75.6 4.0 20.5 100.0 4,206 Secondary 71.6 4.5 23.9 100.0 5,618 Higher 86.2 2.0 11.8 100.0 907 Wealth quintile Lowest 80.7 4.0 15.4 100.0 1,827 Second 76.6 4.2 19.1 100.0 1,952 Middle 74.8 3.5 21.7 100.0 2,218 Fourth 76.3 3.3 20.4 100.0 2,552 Highest 66.7 5.2 28.1 100.0 2,629 Total 15-49 74.5 4.1 21.4 100.0 11,177 50-59 86.5 3.1 10.4 100.0 955 Total 15-59 75.5 4.0 20.5 100.0 12,132 1 “Currently employed” is defined as having done work in the past 7 days. Includes persons who did not work in the past 7 days but who are regularly employed and were absent from work for leave, illness, vacation, or any other such reason. Characteristics of Respondents • 51 Table 3.7.1 Occupation: Women Percent distribution of women age 15-49 employed in the 12 months preceding the survey by occupation, according to background characteristics, Zambia DHS 2018 Background characteristic Profes- sional/ technical/ managerial Clerical Sales and services Skilled manual Unskilled manual Domestic service Agriculture Missing Total Number of women Age 15-19 1.9 0.0 23.4 1.3 10.9 9.4 53.1 0.0 100.0 653 20-24 4.4 1.1 36.6 0.8 12.2 8.5 35.4 1.0 100.0 1,212 25-29 10.4 1.3 37.6 1.7 12.0 8.1 29.0 0.0 100.0 1,290 30-34 11.2 1.4 36.9 1.6 12.4 8.1 28.3 0.0 100.0 1,241 35-39 8.5 0.9 36.0 2.3 12.2 10.7 29.5 0.0 100.0 1,183 40-44 8.1 0.9 34.3 3.4 10.8 7.3 35.2 0.0 100.0 901 45-49 5.8 1.1 30.8 2.9 11.5 6.0 42.0 0.0 100.0 657 Marital status Never married 12.1 2.5 36.1 1.7 11.1 11.1 25.5 0.0 100.0 1,323 Married or living together 6.9 0.7 33.9 1.7 10.7 6.4 39.4 0.3 100.0 4,495 Divorced/separated/ widowed 6.1 0.8 35.9 2.9 16.4 12.5 25.3 0.0 100.0 1,319 Number of living children 0 13.0 2.8 33.9 1.9 10.9 9.7 27.9 0.0 100.0 963 1-2 10.3 1.2 36.5 1.6 12.0 10.1 27.8 0.5 100.0 2,371 3-4 7.7 0.9 36.8 2.0 12.5 8.3 31.8 0.0 100.0 1,897 5+ 1.8 0.1 30.7 2.2 11.4 5.9 47.9 0.0 100.0 1,905 Residence Urban 13.0 2.1 49.6 2.8 12.3 14.6 5.3 0.3 100.0 3,251 Rural 3.3 0.1 22.2 1.1 11.4 3.3 58.5 0.0 100.0 3,885 Province Central 7.7 0.7 29.7 0.7 9.9 5.4 45.8 0.0 100.0 600 Copperbelt 12.7 1.2 47.3 3.4 11.4 12.4 11.5 0.0 100.0 988 Eastern 4.6 0.4 19.1 1.8 19.9 2.9 51.2 0.1 100.0 965 Luapula 4.3 0.2 25.2 0.9 7.8 2.9 58.6 0.0 100.0 666 Lusaka 13.9 2.7 45.7 2.9 15.3 16.0 3.6 0.0 100.0 1,422 Muchinga 2.6 0.6 28.9 2.0 5.5 3.1 57.3 0.0 100.0 309 Northern 4.1 0.2 28.2 1.3 7.1 3.3 55.8 0.0 100.0 543 North Western 7.7 1.3 32.4 1.9 9.7 2.9 44.2 0.0 100.0 322 Southern 4.0 0.6 40.8 1.0 8.5 14.4 29.4 1.3 100.0 857 Western 3.9 0.2 28.6 1.4 11.0 2.4 52.5 0.0 100.0 465 Education No education 0.8 0.0 22.5 2.2 15.0 7.0 52.6 0.0 100.0 570 Primary 0.6 0.2 29.3 1.5 12.0 7.6 48.5 0.4 100.0 3,363 Secondary 6.3 0.9 48.1 2.2 12.4 11.2 18.8 0.0 100.0 2,655 Higher 65.7 8.0 15.4 3.0 4.5 1.2 2.2 0.0 100.0 548 Wealth quintile Lowest 0.5 0.0 12.7 1.5 13.4 1.9 69.8 0.1 100.0 1,344 Second 1.0 0.0 23.5 0.9 12.3 2.0 60.3 0.0 100.0 1,250 Middle 2.1 0.1 34.6 1.5 9.2 10.2 41.5 0.8 100.0 1,332 Fourth 4.4 0.9 55.3 2.1 11.0 16.2 10.0 0.0 100.0 1,475 Highest 25.2 3.4 42.4 3.1 13.0 10.1 2.8 0.0 100.0 1,735 Total 7.7 1.0 34.7 1.9 11.8 8.4 34.2 0.2 100.0 7,136 52 • Characteristics of Respondents Table 3.7.2 Occupation: Men Percent distribution of men age 15-49 employed in the 12 months preceding the survey by occupation, according to background characteristics, Zambia DHS 2018 Background characteristic Profes- sional/ technical/ managerial Clerical Sales and services Skilled manual Unskilled manual Domestic service Agriculture Missing Total Number of men Age 15-19 2.5 0.7 8.2 9.3 36.4 7.8 34.9 0.2 100.0 1,164 20-24 5.3 0.3 14.8 16.5 26.1 7.9 29.1 0.0 100.0 1,565 25-29 11.2 0.9 14.5 23.8 16.2 8.2 24.9 0.1 100.0 1,588 30-34 10.5 0.8 13.1 23.3 16.1 7.0 28.7 0.5 100.0 1,332 35-39 11.1 0.8 14.3 22.9 14.3 6.2 30.5 0.0 100.0 1,230 40-44 10.8 0.3 12.2 22.4 16.4 3.5 34.4 0.0 100.0 1,066 45-49 10.1 0.2 10.2 23.1 15.6 3.5 37.3 0.0 100.0 839 Marital status Never married 8.5 0.8 13.2 15.6 27.7 9.3 24.8 0.1 100.0 2,957 Married or living together 8.9 0.5 12.4 22.1 16.3 5.1 34.6 0.1 100.0 5,406 Divorced/separated/ widowed 8.0 0.1 14.8 26.2 20.6 7.6 22.2 0.4 100.0 420 Number of living children 0 7.9 0.6 13.3 15.0 27.8 9.4 25.8 0.1 100.0 2,882 1-2 11.3 1.0 13.7 24.6 18.8 6.0 24.3 0.3 100.0 2,386 3-4 9.4 0.3 12.5 24.5 14.5 5.7 33.0 0.0 100.0 1,629 5+ 6.1 0.2 11.1 18.6 15.9 3.9 44.2 0.0 100.0 1,887 Residence Urban 14.6 1.1 20.1 31.3 17.1 8.9 6.7 0.2 100.0 3,862 Rural 4.1 0.2 7.0 11.4 22.9 4.8 49.5 0.0 100.0 4,921 Province Central 7.4 0.7 9.2 14.9 21.5 7.8 38.5 0.0 100.0 721 Copperbelt 11.4 0.3 14.7 32.3 20.6 8.3 12.4 0.0 100.0 1,327 Eastern 5.3 0.4 10.3 14.9 21.6 11.1 36.4 0.0 100.0 1,118 Luapula 5.9 0.1 10.2 7.7 14.9 3.6 57.7 0.0 100.0 684 Lusaka 15.8 1.4 22.2 29.0 15.2 9.9 6.0 0.5 100.0 1,760 Muchinga 3.9 0.3 10.2 12.2 15.6 3.3 54.2 0.3 100.0 508 Northern 3.5 0.2 6.8 8.6 13.4 3.6 63.9 0.0 100.0 683 North Western 10.2 2.2 10.3 24.4 12.2 3.2 37.6 0.0 100.0 385 Southern 6.8 0.2 9.6 19.5 28.6 3.1 32.1 0.0 100.0 1,137 Western 5.0 0.1 8.6 14.6 44.0 0.5 27.2 0.0 100.0 461 Education No education 1.1 0.0 7.3 10.4 27.6 6.2 47.3 0.0 100.0 366 Primary 1.0 0.1 8.4 14.2 24.7 6.9 44.7 0.1 100.0 3,345 Secondary 6.1 0.6 16.3 26.4 19.4 7.6 23.4 0.2 100.0 4,273 Higher 58.6 2.7 15.1 16.1 3.5 0.7 3.3 0.0 100.0 800 Wealth quintile Lowest 0.6 0.0 3.4 8.8 23.2 3.4 60.4 0.1 100.0 1,546 Second 1.3 0.1 5.8 9.8 24.6 5.0 53.3 0.1 100.0 1,578 Middle 2.5 0.3 11.7 17.1 23.2 6.7 38.4 0.1 100.0 1,738 Fourth 9.3 0.7 18.9 30.9 19.8 11.2 9.0 0.1 100.0 2,030 Highest 26.5 1.6 20.7 29.3 12.3 5.6 3.8 0.2 100.0 1,892 Total 15-49 8.7 0.6 12.8 20.1 20.3 6.6 30.7 0.1 100.0 8,784 50-59 9.0 1.0 10.8 18.4 14.6 1.8 44.2 0.2 100.0 856 Total 15-59 8.7 0.6 12.6 20.0 19.8 6.2 31.9 0.1 100.0 9,639 Characteristics of Respondents • 53 Table 3.8.1 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 DHS 2018 Employment characteristic Agricultural work Non- agricultural work Missing Total Type of earnings Cash only 29.1 81.7 * 63.5 Cash and in-kind 30.5 8.9 * 16.3 In-kind only 3.7 0.4 * 1.5 Not paid 36.7 9.0 * 18.7 Total 100.0 100.0 100.0 100.0 Type of employer Employed by family member 25.4 4.8 * 11.9 Employed by non-family member 2.9 36.6 * 25.0 Self-employed 71.7 58.6 * 63.1 Total 100.0 100.0 100.0 100.0 Continuity of employment All year 22.1 69.6 * 53.2 Seasonal 75.9 20.2 * 39.3 Occasional 1.9 10.2 * 7.5 Total 100.0 100.0 100.0 100.0 Number of women employed during the last 12 months 2,443 4,681 12 7,136 Note: Total includes women with missing information on type of employment who are not shown separately. An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. Table 3.8.2 Type of employment: Men Percent distribution of men age 15-49 employed in the 12 months preceding the survey by type of earnings, and continuity of employment, according to type of employment (agricultural or nonagricultural), Zambia DHS 2018 Employment characteristic Agricultural work Non- agricultural work Missing Total Type of earnings Cash only 34.0 81.8 * 67.1 Cash and in-kind 37.9 6.5 * 16.1 In-kind only 2.4 0.6 * 1.2 Not paid 25.8 11.0 * 15.5 Total 100.0 100.0 100.0 100.0 Continuity of employment All year 35.8 61.9 * 53.9 Seasonal 62.0 20.0 * 32.9 Occasional 2.2 18.1 * 13.2 Total 100.0 100.0 100.0 100.0 Number of women employed during the last 12 months 2,696 6,078 10 8,784 Note: Total includes men with missing information on type of employment who are not shown separately. An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. 54 • Characteristics of Respondents Table 3.9.1 Health insurance coverage: Women Percentage of women age 15-49 with specific types of health insurance coverage, and percentage with any health insurance, according to background characteristics, Zambia DHS 2018 Background characteristic Social security Other employer- based insurance Mutual health organisation/ community- based insurance Privately purchased commercial insurance Other None Any health insurance Number of women Age 15-19 0.0 0.7 0.0 0.0 0.2 99.1 0.9 3,000 20-24 0.0 0.5 0.2 0.3 0.2 98.9 1.1 2,733 25-29 0.0 1.3 0.3 0.2 0.6 97.7 2.3 2,237 30-34 0.1 2.7 0.3 0.2 0.5 96.2 3.8 1,862 35-39 0.0 2.7 0.1 0.1 0.4 96.7 3.3 1,697 40-44 0.0 1.8 0.0 0.2 0.5 97.8 2.2 1,253 45-49 0.0 1.5 0.1 0.2 0.4 97.9 2.1 900 Residence Urban 0.0 2.7 0.3 0.3 0.7 96.1 3.9 6,374 Rural 0.0 0.3 0.0 0.0 0.1 99.6 0.4 7,309 Province Central 0.0 1.2 0.0 0.2 0.1 98.5 1.5 1,165 Copperbelt 0.0 2.2 0.1 0.2 1.1 96.5 3.5 2,201 Eastern 0.0 0.4 0.0 0.0 0.1 99.5 0.5 1,605 Luapula 0.0 0.4 0.0 0.0 0.3 99.2 0.8 1,071 Lusaka 0.1 3.2 0.5 0.4 0.4 95.4 4.6 2,733 Muchinga 0.0 0.0 0.0 0.1 0.1 99.8 0.2 754 Northern 0.0 0.2 0.0 0.0 0.0 99.8 0.2 1,054 North Western 0.1 1.8 0.6 0.1 0.1 97.3 2.7 718 Southern 0.0 0.6 0.0 0.0 0.2 99.2 0.8 1,574 Western 0.0 0.8 0.0 0.1 0.5 98.7 1.3 808 Education No education 0.0 0.0 0.0 0.0 0.0 100.0 0.0 1,054 Primary 0.0 0.0 0.0 0.0 0.0 99.9 0.1 6,059 Secondary 0.0 1.3 0.1 0.1 0.4 98.1 1.9 5,816 Higher 0.1 14.8 2.2 1.7 3.5 78.2 21.8 755 Wealth quintile Lowest 0.0 0.0 0.0 0.0 0.0 100.0 0.0 2,442 Second 0.0 0.0 0.0 0.0 0.0 100.0 0.0 2,387 Middle 0.0 0.0 0.0 0.0 0.1 99.9 0.1 2,477 Fourth 0.1 0.4 0.0 0.0 0.2 99.4 0.6 3,011 Highest 0.0 5.4 0.6 0.6 1.3 92.3 7.7 3,367 Total 0.0 1.4 0.2 0.1 0.4 97.9 2.1 13,683 Characteristics of Respondents • 55 Table 3.9.2 Health insurance coverage: Men Percentage of men age 15-49 with specific types of health insurance coverage, and percentage with any health insurance, according to background characteristics, Zambia DHS 2018 Background characteristic Social security Other employer- based insurance Mutual health organisation/ community- based insurance Privately purchased commercial insurance Other None Any health insurance Number of men Age 15-19 0.0 0.1 0.2 0.1 0.0 99.6 0.4 2,781 20-24 0.0 0.8 0.2 1.0 0.0 97.9 2.1 2,032 25-29 0.1 2.7 0.0 0.5 0.1 96.9 3.1 1,721 30-34 0.1 3.5 0.3 0.7 0.0 95.8 4.2 1,383 35-39 0.0 3.9 0.6 0.4 0.2 95.0 5.0 1,280 40-44 0.0 2.6 0.4 0.3 0.0 96.7 3.3 1,097 45-49 0.2 4.8 0.9 0.7 0.0 93.5 6.5 883 Residence Urban 0.1 4.1 0.7 1.0 0.1 94.3 5.7 5,013 Rural 0.0 0.5 0.0 0.1 0.0 99.4 0.6 6,165 Province Central 0.0 1.2 0.1 0.7 0.0 98.0 2.0 979 Copperbelt 0.1 4.1 0.0 0.5 0.1 95.4 4.6 1,727 Eastern 0.1 0.8 0.0 0.1 0.0 99.1 0.9 1,476 Luapula 0.0 1.2 0.2 0.2 0.0 98.3 1.7 849 Lusaka 0.0 4.3 1.4 0.9 0.0 93.6 6.4 2,166 Muchinga 0.0 0.5 0.1 0.0 0.0 99.4 0.6 599 Northern 0.0 0.0 0.0 0.0 0.0 100.0 0.0 855 North Western 0.0 2.6 0.0 0.3 0.1 97.0 3.0 556 Southern 0.0 1.0 0.0 1.0 0.1 97.9 2.1 1,395 Western 0.0 0.8 0.1 0.3 0.2 98.6 1.4 574 Education No education 0.3 0.6 0.0 2.6 0.0 96.6 3.4 446 Primary 0.0 0.2 0.1 0.0 0.0 99.7 0.3 4,206 Secondary 0.0 1.3 0.2 0.2 0.0 98.4 1.6 5,618 Higher 0.4 17.0 2.4 3.7 0.2 77.4 22.6 907 Wealth quintile Lowest 0.0 0.0 0.0 0.0 0.0 100.0 0.0 1,827 Second 0.0 0.0 0.0 0.0 0.0 99.9 0.1 1,952 Middle 0.0 0.1 0.0 0.0 0.0 99.8 0.2 2,218 Fourth 0.0 1.4 0.1 0.5 0.0 98.0 2.0 2,552 Highest 0.2 7.5 1.2 1.6 0.1 89.8 10.2 2,629 Total 15-49 0.0 2.1 0.3 0.5 0.0 97.1 2.9 11,177 50-59 0.1 3.5 0.0 1.8 0.0 94.6 5.4 955 Total 15-59 0.0 2.2 0.3 0.6 0.0 96.9 3.1 12,132 56 • Characteristics of Respondents Table 3.10.1 Tobacco smoking: Women Percentage of women age 15-49 who smoke various tobacco products, according to background characteristics and maternity status, Zambia DHS 2018 Percentage who smoke:1 Number of women Background characteristic Cigarettes2 Other type of tobacco3 Any type of tobacco Age 15-19 0.0 0.0 0.0 3,000 20-24 0.6 0.0 0.6 2,733 25-29 1.3 0.0 1.3 2,237 30-34 1.1 0.1 1.1 1,862 35-39 0.8 0.0 0.8 1,697 40-44 1.7 0.0 1.7 1,253 45-49 2.0 0.0 2.0 900 Residence Urban 1.0 0.0 1.0 6,374 Rural 0.8 0.0 0.8 7,309 Province Central 0.3 0.0 0.3 1,165 Copperbelt 1.2 0.0 1.2 2,201 Eastern 0.5 0.0 0.5 1,605 Luapula 0.7 0.0 0.7 1,071 Lusaka 1.0 0.1 1.0 2,733 Muchinga 1.3 0.1 1.3 754 Northern 0.6 0.0 0.6 1,054 North Western 0.2 0.0 0.2 718 Southern 0.4 0.0 0.4 1,574 Western 2.9 0.0 2.9 808 Education No education 2.5 0.0 2.5 1,054 Primary 0.7 0.0 0.7 6,059 Secondary 0.7 0.0 0.7 5,816 Higher 1.2 0.0 1.2 755 Wealth quintile Lowest 1.3 0.0 1.3 2,442 Second 0.6 0.0 0.6 2,387 Middle 0.7 0.0 0.7 2,477 Fourth 0.9 0.0 0.9 3,011 Highest 1.0 0.1 1.0 3,367 Total 0.9 0.0 0.9 13,683 1 Includes daily and occasional (less than daily) use 2 Cigarettes include kreteks. 3 Includes pipes full of tobacco, cigars, cigarillos, and water pipes Characteristics of Respondents • 57 Table 3.10.2 Tobacco smoking: Men Percentage of men age 15-49 who smoke various tobacco products, and percent distribution of men by smoking frequency, according to background characteristics, Zambia DHS 2018 Percentage who smoke:1 Smoking frequency Total Number of men Background characteristic Cigarettes2 Other type of tobacco3 Any type of tobacco Daily smoker Occasional smoker4 Non- smoker Age 15-19 2.9 0.2 2.9 1.7 1.2 97.0 100.0 2,781 20-24 15.1 1.2 15.1 9.6 5.7 84.7 100.0 2,032 25-29 24.4 1.2 24.5 18.0 7.0 75.1 100.0 1,721 30-34 24.7 1.1 24.7 17.6 7.3 75.1 100.0 1,383 35-39 25.3 0.8 25.6 21.2 4.8 74.0 100.0 1,280 40-44 28.1 0.3 28.2 23.7 4.8 71.5 100.0 1,097 45-49 32.5 1.1 32.5 27.2 6.0 66.8 100.0 883 Residence Urban 17.2 1.4 17.4 12.4 5.2 82.3 100.0 5,013 Rural 19.5 0.3 19.5 15.3 4.5 80.2 100.0 6,165 Province Central 19.6 0.2 19.8 13.2 6.6 80.2 100.0 979 Copperbelt 21.8 2.1 21.8 13.9 8.5 77.6 100.0 1,727 Eastern 19.7 0.4 19.7 16.2 3.7 80.1 100.0 1,476 Luapula 24.6 0.2 24.8 24.0 1.2 74.8 100.0 849 Lusaka 15.9 1.4 16.0 12.5 3.9 83.6 100.0 2,166 Muchinga 17.1 0.1 17.2 14.5 3.0 82.5 100.0 599 Northern 18.1 0.2 18.2 13.6 5.0 81.4 100.0 855 North Western 19.4 1.0 19.4 13.2 6.4 80.4 100.0 556 Southern 12.3 0.2 12.3 8.5 3.8 87.7 100.0 1,395 Western 20.2 0.2 20.2 15.5 5.0 79.5 100.0 574 Education No education 25.7 0.5 25.7 23.2 3.3 73.5 100.0 446 Primary 22.9 0.4 22.9 18.8 4.5 76.7 100.0 4,206 Secondary 16.2 1.1 16.3 11.1 5.4 83.4 100.0 5,618 Higher 8.3 0.9 8.4 5.3 3.2 91.5 100.0 907 Wealth quintile Lowest 28.2 0.2 28.3 22.8 5.9 71.3 100.0 1,827 Second 21.2 0.5 21.3 17.4 4.0 78.5 100.0 1,952 Middle 17.9 0.5 18.0 12.7 5.5 81.8 100.0 2,218 Fourth 16.5 1.0 16.6 12.0 4.8 83.2 100.0 2,552 Highest 12.1 1.4 12.2 8.4 4.1 87.5 100.0 2,629 Total 15-49 18.5 0.8 18.5 14.0 4.8 81.2 100.0 11,177 50-59 31.9 0.3 31.9 27.1 5.0 67.9 100.0 955 Total 15-59 19.5 0.8 19.6 15.0 4.8 80.1 100.0 12,132 1 Includes daily and occasional (less than daily) use 2 Includes manufactured cigarettes, hand-rolled cigarettes, and kreteks 3 Includes pipes full of tobacco, cigars, cigarillos, and water pipes 4 Occasional refers to less often than daily use. 58 • Characteristics of Respondents Table 3.11 Average number of cigarettes smoked daily: Men Among men age 15-49 who smoke cigarettes daily, percent distribution by average number of cigarettes smoked per day, according to background characteristics, Zambia DHS 2018 Average number of cigarettes smoked per day1 Total Number of respondents who smoke cigarettes daily1 Background characteristic <5 5-9 10-14 15-24 ≥25 Don’t know/ missing Age 15-19 (72.6) (16.5) (8.2) (2.8) (0.0) (0.0) (100.0) 46 20-24 57.2 27.7 10.3 4.4 0.5 0.0 100.0 195 25-29 53.5 31.2 8.1 6.6 0.6 0.0 100.0 290 30-34 46.9 31.4 16.2 3.1 2.5 0.0 100.0 242 35-39 45.3 32.3 13.6 7.4 1.4 0.0 100.0 265 40-44 41.7 31.1 17.4 7.3 2.5 0.0 100.0 257 45-49 45.6 36.4 11.9 3.6 2.5 0.0 100.0 237 Residence Urban 40.3 34.6 16.2 7.4 1.4 0.0 100.0 599 Rural 54.4 29.2 10.5 4.2 1.7 0.0 100.0 933 Province Central 50.1 35.6 9.2 4.4 0.7 0.0 100.0 127 Copperbelt 38.5 34.3 20.4 6.6 0.2 0.0 100.0 237 Eastern 46.4 36.7 12.7 3.3 0.9 0.0 100.0 238 Luapula 71.6 18.3 5.9 3.1 1.1 0.0 100.0 198 Lusaka 36.1 37.0 15.7 9.1 2.1 0.0 100.0 263 Muchinga 43.9 28.0 16.8 8.0 3.3 0.0 100.0 86 Northern 71.4 16.8 8.9 2.9 0.0 0.0 100.0 114 North Western 44.5 31.6 6.1 8.5 9.4 0.0 100.0 73 Southern 45.6 30.8 13.5 6.9 3.3 0.0 100.0 107 Western 52.3 37.2 9.8 0.4 0.4 0.0 100.0 89 Education No education 54.1 35.2 8.0 1.5 1.1 0.0 100.0 104 Primary 49.8 31.1 12.3 5.3 1.4 0.0 100.0 766 Secondary 48.0 31.4 13.4 5.3 1.9 0.0 100.0 615 Higher (34.0) (24.1) (21.4) (18.4) (2.0) (0.0) (100.0) 47 Wealth quintile Lowest 57.1 28.1 10.5 3.1 1.2 0.0 100.0 413 Second 51.2 31.7 10.6 4.9 1.6 0.0 100.0 337 Middle 51.7 29.5 10.2 6.2 2.4 0.0 100.0 277 Fourth 37.8 34.9 17.4 8.2 1.7 0.0 100.0 290 Highest 40.9 34.4 17.4 6.2 1.1 0.0 100.0 216 Total 15-49 48.9 31.3 12.8 5.4 1.6 0.0 100.0 1,533 50-59 45.6 34.8 10.7 6.0 2.9 0.0 100.0 257 Total 15-59 48.4 31.8 12.5 5.5 1.8 0.0 100.0 1,790 Note: Figures in parentheses are based on 25-49 unweighted cases. 1 Includes manufactured cigarettes, hand-rolled cigarettes, and kreteks Characteristics of Respondents • 59 Table 3.12 Smokeless tobacco use and any tobacco use Percentage of women and men age 15-49 who currently use smokeless tobacco, according to type of tobacco product, and percentage who use any type of tobacco, Zambia DHS 2018 Tobacco product Women Men Snuff, by mouth 0.2 0.4 Snuff, by nose 0.9 0.2 Chewing tobacco 0.0 0.0 Other type of smokeless tobacco 0.0 0.0 Any type of smokeless tobacco1 1.1 0.5 Any type of tobacco2 2.7 19.2 Number 13,683 11,177 Note: Table includes women and men who use smokeless tobacco daily or occasionally (less than daily). 1 Includes snuff by mouth, snuff by nose, and chewing tobacco 2 Includes all types of smokeless tobacco shown in this table along with cigarettes, pipes, cigars, cigarillos, and water pipes Table 3.13 History of diabetes and hypertension Percent distribution of women age 15-49 by history of diabetes and hypertension, Zambia DHS 2018 History of diabetes and hypertension Total History of diabetes Told had diabetes by medical practitioner 0.5 Number of women 13,683 Received treatment for diabetes Receiving treatment1 36.3 Not receiving treatment 63.7 Total 100.0 Number of women with diabetes 68 History of hypertension Told blood pressure was high 8.8 Number of women 13,683 Received treatment for hypertension Receiving treatment2 21.0 Not receiving treatment 79.0 Total 100.0 Number of women with high blood pressure 1,198 1 Has taken medication for diabetes prescribed by a doctor or other health worker in the 2 weeks prior to the interview 2 Has taken medication for hypertension prescribed by a doctor or other health worker in the 2 weeks prior to the interview 60 • Characteristics of Respondents Table 3.14 Use of surgery Percentage of women and men age 15-49 who underwent surgery in the 5 years preceding the survey, and percentage of women age 15-49 who underwent surgery in the 5 years preceding the survey excluding C-sections, according to background characteristics, Zambia DHS 2018 Women Men Background characteristic Percentage who have undergone surgery in the last 5 years Percentage who have undergone surgery in the last 5 years excluding C-sections Number of women Percentage who have undergone surgery in the last 5 years Number of men Age 15-19 1.7 0.2 3,000 1.6 2,781 20-24 4.2 0.5 2,733 2.3 2,032 25-29 5.7 0.9 2,237 2.0 1,721 30-34 6.7 1.3 1,862 1.0 1,383 35-39 6.3 1.0 1,697 2.4 1,280 40-44 6.2 1.9 1,253 2.5 1,097 45-49 5.1 1.9 900 2.6 883 Residence Urban 6.0 1.3 6,374 3.1 5,013 Rural 3.7 0.6 7,309 1.0 6,165 Province Central 3.9 0.7 1,165 0.6 979 Copperbelt 5.0 0.7 2,201 3.3 1,727 Eastern

View the publication

You are currently offline. Some pages or content may fail to load.