Zimbabwe - Demographic and Health Survey - 2016

Publication date: 2016

Zimbabwe Demographic and Health Survey 2015 Zim babw e 2015 D em ographic and H ealth S urvey GOVERNMENT OF ZIMBABWE Zimbabwe Demographic and Health Survey 2015 Final Report Zimbabwe National Statistics Agency Harare, Zimbabwe The DHS Program ICF International Rockville, Maryland, USA November 2016 The 2015 Zimbabwe Demographic and Health Survey (2015 ZDHS) was implemented by the Zimbabwe National Statistics Agency in July through December 2015. The HIV testing component was implemented by the National Microbiology Reference Laboratory (NMRL). The funding for the ZDHS was provided by the Government of Zimbabwe, the United States Agency for International Development (USAID), the United Nations Population Fund (UNFPA), the United Nations Development Programme (UNDP), the United Nations Children’s Fund (UNICEF), the United Kingdom Department for International Development (DFID), the Royal Danish Embassy, the Australian Agency for International Development (AusAID), the European Union (EU), the Swedish International Development Cooperation (SIDA), and Irish Aid. ICF International 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 2015 ZDHS may be obtained from the Zimbabwe National Statistics Agency (ZIMSTAT), P.O. Box CY 342, Causeway, Harare, Zimbabwe; Telephone +263-4-793-971/2 and 794-757; Fax: +263-4-728-529 and 708-854; E-mail: dg@zimstat.co.zw. Information about The DHS Program may be obtained from ICF International, 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. Cover photo of Victoria Falls ©2016 by Ali Yuhas. Used under Creative Commons license. Recommended citation: Zimbabwe National Statistics Agency and ICF International. 2016. Zimbabwe Demographic and Health Survey 2015: Final Report. Rockville, Maryland, USA: Zimbabwe National Statistics Agency (ZIMSTAT) and ICF International. Contents • iii CONTENTS TABLES AND FIGURES . ix PREFACE . xix ADDITIONAL DHS PROGRAM RESOURCES . xxi ACRONYMS AND ABBREVIATIONS . xxiii MAP OF ZIMBABWE . xxvi 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 1.5 Training of Field Staff . 4 1.6 Fieldwork . 5 1.7 Data Processing . 5 1.8 Response Rates . 5 2 HOUSING CHARACTERISTICS AND HOUSEHOLD POPULATION . 7 2.1 Drinking Water Sources and Treatment . 8 2.2 Sanitation Facilities and Waste Disposal . 9 2.3 Exposure to Smoke Inside the Home and Other Housing Characteristics . 10 2.4 Household Wealth . 11 2.5 Hand Washing . 12 2.6 Household Population and Composition . 13 2.7 Birth Registration . 14 2.8 Children’s Living Arrangements, School Attendance, and Parental Survival . 14 2.9 Education . 15 2.9.1 Educational Attainment . 15 2.9.2 School Attendance . 15 3 CHARACTERISTICS OF RESPONDENTS . 35 3.1 Basic Characteristics of Survey Respondents . 35 3.2 Education and Literacy . 36 3.4 Exposure to Mass Media and Internet Usage . 37 3.5 Employment Status . 38 3.6 Occupation . 39 3.7 Health Insurance Coverage . 40 3.8 Tobacco Use . 40 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 iv • Contents 5 FERTILITY . 75 5.1 Current Fertility . 76 5.2 Children Ever Born and Living . 77 5.3 Birth Intervals . 78 5.4 Insusceptibility to Pregnancy . 78 5.5 Age at First Birth . 80 5.6 Teenage Childbearing . 80 6 FERTILITY PREFERENCES . 95 6.1 Desire for Another Child . 95 6.2 Ideal Number of Children . 97 6.3 Fertility Planning Status . 98 6.4 Wanted Fertility Rates . 99 7 FAMILY PLANNING . 109 7.1 Contraceptive Knowledge and Use . 110 7.2 Source of Modern Contraceptive Methods . 112 7.3 Informed Choice . 113 7.4 Discontinuation of Contraceptives . 113 7.5 Demand for Family Planning . 113 7.6 Future Use of Contraception . 115 7.7 Exposure to Family Planning Messages in the Media . 115 7.8 Contact of Non-users with Family Planning Providers . 116 8 INFANT AND CHILD MORTALITY . 131 8.1 Infant and Child Mortality . 132 8.2 Biodemographic Risk Factors . 133 8.3 Perinatal Mortality . 134 8.4 Higher-risk Fertility Behaviour . 134 9 MATERNAL HEALTH CARE . 141 9.1 Antenatal Care Coverage and Content . 142 9.1.1 Skilled Providers . 142 9.1.2 Timing and Number of ANC Visits . 142 9.1.3 Components of ANC Visits . 143 9.2 Protection Against Neonatal Tetanus . 143 9.3 Place of Delivery . 144 9.4 Skilled Assistance during Delivery . 145 9.5 Delivery by Caesarean . 146 9.6 Postnatal Care . 146 9.6.1 Postnatal Health Check for Mothers . 146 9.6.2 Postnatal Health Checks for Newborns . 147 9.6.3 Content of Postnatal Care for Newborns . 147 9.7 Problems in Accessing Health Care . 148 9.8 Prevention of Cervical Cancer . 148 10 CHILD HEALTH . 165 10.1 Birth Weight . 165 10.2 Vaccination of Children . 166 10.3 Symptoms of Acute Respiratory Infection . 168 10.4 Fever . 168 Contents • v 10.5 Diarrhoeal Disease . 169 10.5.1 Prevalence of Diarrhoea . 169 10.5.2 Treatment of Diarrhoea . 169 10.5.3 Feeding Practices . 170 10.5.4 Knowledge of ORS Packets . 171 10.6 Disposal of Children’s Stools . 171 11 NUTRITION OF CHILDREN AND ADULTS . 185 11.1 Nutritional Status of Children . 185 11.1.1 Measurement of Nutritional Status among Young Children . 186 11.1.2 Data Collection . 187 11.1.3 Prevalence of Malnutrition in Children . 187 11.2 Infant and Young Child Feeding Practices . 188 11.2.1 Initiation of Breastfeeding . 188 11.2.2 Exclusive Breastfeeding . 189 11.2.3 Median Duration of Breastfeeding . 190 11.2.4 Complementary Feeding . 191 11.2.5 Minimum Acceptable Diet . 191 11.3 Anaemia Prevalence in Children . 193 11.4 Vitamin A Supplementation and Deworming in Children . 194 11.5 Presence of Iodised Salt in Households . 195 11.6 Adults’ Nutritional Status . 195 11.6.1 Nutritional Status of Women . 195 11.6.2 Nutritional Status of Men . 197 11.7 Anaemia Prevalence in Adults . 197 11.8 Maternal Iron and Folate Supplementation . 198 12 MALARIA . 217 12.1 Mosquito Nets and Indoor Residual Spraying . 218 12.1.1 Ownership of Insecticide-Treated Nets . 218 12.1.2 Access to Insecticide-Treated Nets (ITNs) . 219 12.1.3 Source of Mosquito Nets . 220 12.1.4 Indoor Residual Spraying (IRS) . 221 12.1.5 Use of Mosquito Nets among the De Facto Household Population . 222 12.1.6 Use of Mosquito Nets by Children . 223 12.1.7 Use of Mosquito Nets by Pregnant Women . 224 12.2 Prevalence, Diagnosis, and Prompt Treatment of Fever among Young Children . 225 13 HIV/AIDS-RELATED KNOWLEDGE, ATTITUDES, AND BEHAVIOUR . 237 13.1 HIV/AIDS Knowledge, Transmission, and Prevention Methods . 238 13.2 Knowledge about Mother-to-Child Transmission . 239 13.3 HIV/AIDS Attitudes . 240 13.3.1 Discriminatory Attitudes towards People Living with HIV. 240 13.3.2 Attitudes towards Negotiating Safer Sexual Relations with Husbands . 241 13.4 Multiple Sexual Partners and Condom Use . 241 13.5 Paid Sex . 242 13.6 Coverage of HIV Testing Services . 242 13.6.1 Awareness of HIV Testing Services and Experience with HIV Testing . 242 13.6.2 HIV Testing of Pregnant Women . 244 13.7 Male Circumcision . 244 13.8 Self-reporting of Sexually Transmitted Infections . 245 13.9 Injections . 245 vi • Contents 13.10 HIV/AIDS-related Knowledge and Behaviour among Young People . 245 13.10.1 Knowledge about HIV/AIDS and Source for Condoms . 245 13.10.2 First Sex . 246 13.10.3 Premarital Sex . 247 13.10.4 Multiple Sexual Partners and Condom Use . 247 13.10.5 Age-mixing in Sexual Relationships . 247 13.10.6 Coverage of HIV Testing Services . 247 14 HIV PREVALENCE . 273 14.1 Coverage Rates for HIV Testing . 273 14.2 HIV Prevalence . 274 14.2.1 HIV Prevalence among Women and Men . 274 14.2.2 HIV Prevalence among Children . 275 14.2.3 HIV Prevalence among Women and Men by Background Characteristics . 276 14.2.4 HIV Prevalence by Sexual Risk Behaviour . 277 14.2.5 HIV Prevalence among Young People . 277 14.2.6 HIV Prevalence by Other Characteristics Related to HIV Risk . 278 14.2.7 HIV Prevalence among Couples . 279 15 WOMEN’S EMPOWERMENT . 295 15.1 Married Women’s and Men’s Employment . 295 15.2 Control over Women’s Earnings . 296 15.3 Control over Men’s Earnings . 297 15.4 Women’s and Men’s Ownership of Assets . 297 15.5 Women’s Participation in Decision Making . 299 15.6 Attitudes towards Wife Beating . 300 16 DOMESTIC VIOLENCE . 315 16.1 Measurement of Violence . 316 16.1.1 The Use of Valid Measures of Violence . 316 16.1.2 Ethical Considerations . 317 16.1.3 Subsample for the Violence Module . 317 16.2 Experience of Physical Violence . 318 16.3 Experience of Sexual Violence . 319 16.4 Experience of Different Forms of Violence . 319 16.5 Violence during Pregnancy . 320 16.6 Marital Control . 320 16.7 Spousal Violence . 321 16.7.1 Prevalence of Spousal Violence . 321 16.7.2 Recent Spousal Violence . 322 16.8 Duration of Marriage and Spousal Violence . 323 16.9 Injuries due to Spousal Violence . 323 16.10 Violence Initiated by Women against Their Husbands/Partners . 323 16.11 Response to Violence . 324 16.11.1 Help-Seeking among Women Who Have Experienced Violence . 324 16.11.2 Sources for Help . 324 17 ADULT AND MATERNAL MORTALITY . 343 17.1 Data . 343 17.2 Direct Estimates of Adult Mortality . 344 17.3 Trends in Adult Mortality . 345 17.4 Direct Estimation of Maternal Mortality . 346 Contents • vii REFERENCES . 351 APPENDIX A SAMPLE DESIGN AND IMPLEMENTATION . 353 APPENDIX B HIV TESTING METHODOLOGY . 365 APPENDIX C ESTIMATES OF SAMPLING ERRORS . 371 APPENDIX D DATA QUALITY TABLES . 389 APPENDIX E SURVEY PERSONNEL . 397 APPENDIX F QUESTIONNAIRES . 399 Tables and Figures • ix TABLES AND FIGURES 1 INTRODUCTION AND SURVEY METHODOLOGY . 1 Table 1.1 Results of the household and individual interviews . 5 2 HOUSING CHARACTERISTICS AND HOUSEHOLD POPULATION . 7 Table 2.1 Household drinking water . 19 Table 2.2 Availability of water . 20 Table 2.3 Household sanitation facilities . 21 Table 2.4 Household characteristics . 22 Table 2.5 Wealth quintiles . 23 Table 2.6 Household possessions . 24 Table 2.7 Hand washing . 25 Table 2.8 Household population by age, sex, and residence . 26 Table 2.9 Household composition . 27 Table 2.10 Birth registration of children under age 5 . 28 Table 2.11 Children’s living arrangements and orphanhood . 29 Table 2.12 School attendance by survivorship of parents . 30 Table 2.13.1 Educational attainment of the female household population . 31 Table 2.13.2 Educational attainment of the male household population . 32 Table 2.14 School attendance ratios . 33 Table 2.15 Age-specific attendance rates of the de facto population 5 to 24 years . 34 Figure 2.1 Households with improved water source . 8 Figure 2.2 Household drinking water by residence . 8 Figure 2.3 Availability of water in the last 2 weeks before the survey . 9 Figure 2.4 Household toilet facilities by residence . 10 Figure 2.5 Household wealth by residence. 12 Figure 2.6 Population pyramid . 13 Figure 2.7 Secondary school attendance by wealth quintile . 16 Figure 2.8 Age-specific attendance rates of the de facto population 5 to 24 years . 17 3 CHARACTERISTICS OF RESPONDENTS . 35 Table 3.1 Background characteristics of respondents . 42 Table 3.2.1 Educational attainment: Women . 43 Table 3.2.2 Educational attainment: Men . 44 Table 3.3.1 Literacy: Women . 45 Table 3.3.2 Literacy: Men . 46 Table 3.4.1 Exposure to mass media: Women . 47 Table 3.4.2 Exposure to mass media: Men . 48 Table 3.5.1 Internet usage: Women . 49 Table 3.5.2 Internet usage: Men . 50 Table 3.6.1 Employment status: Women . 51 Table 3.6.2 Employment status: Men . 52 Table 3.7.1 Occupation: Women . 53 Table 3.7.2 Occupation: Men . 54 Table 3.8 Type of employment: Women . 55 Table 3.9.1 Health insurance coverage: Women . 56 Table 3.9.2 Health insurance coverage: Men . 57 x • Tables and Figures Table 3.10.1 Tobacco smoking: Women . 58 Table 3.10.2 Tobacco smoking: Men . 59 Table 3.11 Average number of cigarettes smoked daily: Men . 60 Figure 3.1 Education of survey respondents . 36 Figure 3.2 Education by wealth . 37 Figure 3.3 Women’s employment status . 38 Figure 3.4 Men’s employment status . 38 Figure 3.5 Employment status by residence . 39 4 MARRIAGE AND SEXUAL ACTIVITY . 61 Table 4.1 Current marital status . 66 Table 4.2.1 Number of women’s co-wives . 67 Table 4.2.2 Number of men’s wives . 68 Table 4.3 Age at first marriage . 69 Table 4.4 Median age at first marriage by background characteristics . 70 Table 4.5 Age at first sexual intercourse . 71 Table 4.6 Median age at first sexual intercourse by background characteristics . 72 Table 4.7.1 Recent sexual activity: Women . 73 Table 4.7.2 Recent sexual activity: Men . 74 Figure 4.1 Marital status . 62 5 FERTILITY . 75 Table 5.1 Current fertility . 82 Table 5.2 Fertility by background characteristics . 83 Table 5.3.1 Trends in age-specific fertility rates . 84 Table 5.3.2 Trends in age-specific and total fertility rates, 1985-2015 . 85 Table 5.4 Children ever born and living . 86 Table 5.5 Birth intervals . 87 Table 5.6 Postpartum amenorrhoea, abstinence, and insusceptibility . 88 Table 5.7 Median duration of amenorrhoea, postpartum abstinence, and postpartum insusceptibility . 89 Table 5.8 Menopause . 90 Table 5.9 Age at first birth . 91 Table 5.10 Median age at first birth . 92 Table 5.11 Teenage pregnancy and motherhood . 93 Figure 5.1 Trends in total fertility rate (TFR) . 76 Figure 5.2 Total fertility rate by province . 76 Figure 5.3 Trends in age-specific fertility rates . 77 Figure 5.4 Total fertility rate by wealth quintile . 77 Figure 5.5 Birth interval distribution . 78 Figure 5.6 Percentage of menopausal women by age . 79 Figure 5.7 Teenage childbearing by province . 81 6 FERTILITY PREFERENCES . 95 Table 6.1 Fertility preferences by number of living children . 101 Table 6.2.1 Desire to limit childbearing: Women . 102 Table 6.2.2 Desire to limit childbearing: Men . 103 Table 6.3 Ideal number of children by number of living children . 104 Table 6.4 Mean ideal number of children . 105 Table 6.5 Fertility planning status . 106 Table 6.6 Wanted fertility rates . 107 Tables and Figures • xi Figure 6.1 Trends in desire to limit childbearing . 96 Figure 6.2 Trends in ideal family size . 97 Figure 6.3 Ideal family size by number of living children . 98 Figure 6.4 Fertility planning status . 99 Figure 6.5 Trends in wanted and actual fertility . 99 7 FAMILY PLANNING . 109 Table 7.1 Knowledge of contraceptive methods . 118 Table 7.2 Knowledge of contraceptive methods by background characteristics . 119 Table 7.3 Current use of contraception by age . 120 Table 7.4 Current use of contraception by background characteristics . 121 Table 7.5 Source of modern contraception methods . 122 Table 7.6 Informed choice . 123 Table 7.7 Twelve-month contraceptive discontinuation rates . 124 Table 7.8 Reasons for discontinuation . 124 Table 7.9.1 Need and demand for family planning among currently married women . 125 Table 7.9.2 Need and demand for family planning for all women and for women who are not currently married . 126 Table 7.10 Future use of contraception . 128 Table 7.11 Exposure to family planning messages . 128 Table 7.12 Contact of non-users with family planning providers . 129 Figure 7.1 Contraceptive use . 110 Figure 7.2 Trends in contraceptive use . 111 Figure 7.3 Modern contraceptive use by province . 111 Figure 7.4 Modern contraceptive use by education . 112 Figure 7.5 Sources of modern contraceptive methods . 112 Figure 7.6 Demand for family planning . 114 Figure 7.7 Trends in total demand for family planning . 114 Figure 7.8 Unmet need for family planning by province . 115 8 INFANT AND CHILD MORTALITY . 131 Table 8.1 Early childhood mortality rates . 136 Table 8.2 Early childhood mortality rates according to socioeconomic characteristics . 136 Table 8.3 Early childhood mortality rates according to demographic characteristics . 137 Table 8.4 Perinatal mortality . 138 Table 8.5 High-risk fertility behaviour . 139 Figure 8.1 Trends in childhood mortality . 132 Figure 8.2 Under-5 mortality by province . 133 Figure 8.3 Under-5 mortality by mother’s education . 133 Figure 8.4 Perinatal mortality by province . 134 9 MATERNAL HEALTH CARE . 141 Table 9.1 Antenatal care . 150 Table 9.2 Number of antenatal care visits and timing of first visit . 151 Table 9.3 Components of antenatal care . 152 Table 9.4 Tetanus toxoid injections . 153 Table 9.5 Place of delivery . 154 Table 9.6 Assistance during delivery . 155 Table 9.7 Caesarean section . 156 Table 9.8 Timing of first postnatal check for the mother . 157 Table 9.9 Type of provider of first postnatal check for the mother . 158 xii • Tables and Figures Table 9.10 Timing of first postnatal check for the newborn . 159 Table 9.11 Type of provider of first postnatal check for the newborn . 160 Table 9.12 Content of postnatal care for newborns . 161 Table 9.13 Problems in accessing health care . 162 Table 9.14 Knowledge and prevention of cervical cancer . 163 Figure 9.1 Antenatal care coverage trends . 142 Figure 9.2 Trends in place of delivery . 144 Figure 9.3 Institutional deliveries by province . 144 Figure 9.4 Institutional deliveries by mother’s education . 145 Figure 9.5 Delivery assistance. 145 Figure 9.6 Delivery assistance by wealth quintile . 146 10 CHILD HEALTH . 165 Table 10.1 Child’s size and weight at birth. 173 Table 10.2 Vaccinations by source of information . 174 Table 10.3 Vaccinations by background characteristics . 175 Table 10.4 Possession and observation of vaccination cards, according to background characteristics . 176 Table 10.5 Prevalence and treatment of symptoms of ARI . 177 Table 10.6 Prevalence and treatment of fever . 178 Table 10.7 Prevalence of diarrhoea . 179 Table 10.8 Feeding practices during diarrhoea . 180 Table 10.9 Diarrhoea treatment . 181 Table 10.10 Knowledge of ORS packets or pre-packaged liquids. 182 Table 10.11 Disposal of children’s stools . 183 Figure 10.1 Childhood vaccinations . 167 Figure 10.2 Trends in childhood vaccinations . 167 Figure 10.3 Vaccination coverage by province . 168 Figure 10.4 Diarrhoea prevalence by age . 169 Figure 10.5 Treatment of diarrhoea . 170 Figure 10.6 Feeding practices during diarrhoea . 171 Figure 10.7 Prevalence and treatment of childhood illnesses . 171 11 NUTRITION OF CHILDREN AND ADULTS . 185 Table 11.1 Nutritional status of children . 200 Table 11.2 Initial breastfeeding . 202 Table 11.3 Breastfeeding status according to age . 203 Table 11.4 Median duration of breastfeeding . 204 Table 11.5 Foods and liquids consumed by children in the day or night preceding the interview . 205 Table 11.6 Infant and young child feeding (IYCF) practices . 206 Table 11.7 Prevalence of anaemia in children . 207 Table 11.8 Micronutrient intake among children . 208 Table 11.9 Presence of iodised salt in household . 209 Table 11.10.1 Nutritional status of women . 210 Table 11.10.2 Nutritional status of men . 211 Table 11.11.1 Prevalence of anaemia in women . 212 Table 11.11.2 Prevalence of anaemia in men . 213 Table 11.12 Micronutrient intake among mothers . 214 Table 11.13 Mothers living in households with iodised salt . 215 Tables and Figures • xiii Figure 11.1 Nutritional status of children . 187 Figure 11.2 Trends in nutritional status of children . 187 Figure 11.3 Stunting by province . 188 Figure 11.4 Breastfeeding practices by age . 189 Figure 11.5 IYCF breastfeeding indicators . 190 Figure 11.6 IYCF indicators on minimum acceptable diet . 192 Figure 11.7 Trends in anaemia status among children . 193 Figure 11.8 Anaemia in children by province . 194 Figure 11.9 Trends in nutritional status among women . 196 Figure 11.10 Trends in nutritional status among men . 197 Figure 11.11 Trends in anaemia status among women . 198 12 MALARIA . 217 Table 12.1 Household possession of mosquito nets . 227 Table 12.2 Access to an insecticide-treated net (ITN) . 227 Table 12.3 Source of mosquito nets . 228 Table 12.4 Indoor residual spraying against mosquitoes . 229 Table 12.5 Use of mosquito nets by persons in the household . 230 Table 12.6 Use of existing ITNs . 231 Table 12.7 Use of mosquito nets by children . 232 Table 12.8 Use of mosquito nets by pregnant women . 233 Table 12.9 Prevalence, diagnosis, and prompt treatment of children with fever . 234 Table 12.10 Source of advice or treatment for children with fever . 235 Figure 12.1 Malaria Annual Parasite Incidence (API), Zimbabwe 2015 . 217 Figure 12.2 2013 LLIN Coverage . 218 Figure 12.3 Trends in ownership of ITNs . 219 Figure 12.4 Differentials in household ownership of ITNs . 219 Figure 12.5 Percentage of the de facto population with access to an ITN in the household . 220 Figure 12.6 Trends in IRS household coverage . 221 Figure 12.7 Coverage of ITN and/or IRS by province . 222 Figure 12.8 Trends in ITN ownership, access, and use . 223 Figure 12.9 Trends in net use among children under age 5 . 224 Figure 12.10 Trends in net use among pregnant women . 224 13 HIV/AIDS-RELATED KNOWLEDGE, ATTITUDES, AND BEHAVIOUR . 237 Table 13.1 Knowledge of HIV or AIDS . 249 Table 13.2 Knowledge of HIV prevention methods . 250 Table 13.3.1 Comprehensive knowledge about HIV: Women . 251 Table 13.3.2 Comprehensive knowledge about HIV: Men . 252 Table 13.4 Knowledge of prevention of mother-to-child transmission of HIV . 253 Table 13.5 Discriminatory attitudes towards people living with HIV . 254 Table 13.6 Attitudes toward negotiating safer sexual relations with husband . 255 Table 13.7.1 Multiple sexual partners and higher-risk sexual intercourse in the past 12 months: Women . 256 Table 13.7.2 Multiple sexual partners and higher-risk sexual intercourse in the past 12 months: Men . 257 Table 13.8 Payment for sexual intercourse and condom use at last paid sexual intercourse . 258 Table 13.9.1 Coverage of prior HIV testing: Women . 259 Table 13.9.2 Coverage of prior HIV testing: Men . 260 Table 13.10 Pregnant women counselled and tested for HIV . 261 Table 13.11 Male circumcision . 262 xiv • Tables and Figures Table 13.12 Self-reported prevalence of sexually-transmitted infections (STIs) and STIs symptoms . 263 Table 13.13 Prevalence of medical injections . 264 Table 13.14 Comprehensive knowledge about HIV and of a source of condoms among young people . 265 Table 13.15 Age at first sexual intercourse among young people . 266 Table 13.16 Premarital sexual intercourse and condom use during premarital sexual intercourse among young people . 267 Table 13.17.1 Multiple sexual partners and higher-risk sexual intercourse in the past 12 months among young people: Women . 268 Table 13.17.2 Multiple sexual partners and higher-risk sexual intercourse in the past 12 months among young people: Men . 269 Table 13.18 Age-mixing in sexual relationships among women age 15-19 . 270 Table 13.19 Recent HIV tests among young people . 271 Figure 13.1 Trends in HIV knowledge . 238 Figure 13.2 Comprehensive knowledge of HIV by education . 239 Figure 13.3 Trends in knowledge of mother-to-child transmission of HIV . 240 Figure 13.4 Higher-risk sexual partners and condom use . 241 Figure 13.5 Trends in HIV testing . 243 Figure 13.6 Recent HIV testing by province . 243 Figure 13.7 Trends in male circumcision by age . 244 Figure 13.8 STI advice or treatment seeking behaviour . 245 Figure 13.9 Age at first sex among young people . 246 Figure 13.10 Premarital sex and condom use among young people . 247 14 HIV PREVALENCE . 273 Table 14.1.1 Coverage of HIV testing by residence and province: Women and men age 15-49 . 280 Table 14.1.2 Coverage of HIV testing by residence and province: Children age 0-14 . 281 Table 14.2.1 Coverage of HIV testing by selected background characteristics: Women and men age 15-49 . 282 Table 14.2.2 Coverage of HIV testing by age : Children age 0-14 . 283 Table 14.3.1 HIV prevalence among women age 15-49 and men age 15-54, by age . 284 Table 14.3.2 HIV prevalence among children age 0-14 years, by age . 284 Table 14.4 HIV prevalence among children age 0-14 by socioeconomic characteristics . 285 Table 14.5 HIV prevalence among children age 0-14, by orphanhood and serological status of the mother . 285 Table 14.6 HIV prevalence by socioeconomic characteristics . 286 Table 14.7 HIV prevalence by demographic characteristics . 287 Table 14.8 HIV prevalence by sexual behaviour . 288 Table 14.9 HIV prevalence among young people by background characteristics . 289 Table 14.10 HIV prevalence among young people by sexual behaviour . 290 Table 14.11 HIV prevalence by other characteristics . 290 Table 14.12 Prior HIV testing by current HIV status . 291 Table 14.13 HIV prevalence by male circumcision . 292 Table 14.14 HIV prevalence among couples . 293 Figure 14.1 HIV prevalence by age . 275 Figure 14.2 HIV prevalence among children, by province . 275 Figure 14.3 HIV prevalence by residence and sex . 276 Figure 14.4 HIV prevalence among adults, by province . 276 Tables and Figures • xv 15 WOMEN’S EMPOWERMENT . 295 Table 15.1 Employment and cash earnings of currently married women and men . 302 Table 15.2.1 Control over women’s cash earnings and relative magnitude of women’s cash earnings . 303 Table 15.2.2 Control over men’s cash earnings . 304 Table 15.3 Women’s control over their own earnings and over those of their husbands . 305 Table 15.4.1 Ownership of assets: Women . 306 Table 15.4.2 Ownership of assets: Men . 307 Table 15.5 Participation in decision making . 308 Table 15.6.1 Women’s participation in decision making by background characteristics . 308 Table 15.6.2 Men’s participation in decision making by background characteristics . 309 Table 15.7.1 Attitude toward wife beating: Women . 310 Table 15.7.2 Attitude toward wife beating: Men . 311 Table 15.8 Indicators of women’s empowerment . 312 Table 15.9 Current use of contraception by women’s empowerment . 312 Table 15.10 Ideal number of children and unmet need for family planning by women’s empowerment . 313 Table 15.11 Reproductive health care by women’s empowerment . 313 Figure 15.1 Women’s and men’s employment by age . 296 Figure 15.2 Control over women’s earnings . 297 Figure 15.3 House and land ownership . 298 Figure 15.4 Women’s participation in decision making. 299 Figure 15.5 Attitude towards wife beating . 300 16 DOMESTIC VIOLENCE . 315 Table 16.1 Experience of physical violence . 326 Table 16.2 Persons committing physical violence . 327 Table 16.3 Experience of sexual violence. 328 Table 16.4 Persons committing sexual violence . 329 Table 16.5 Age at first experience of sexual violence . 329 Table 16.6 Experience of different forms of violence . 329 Table 16.7 Experience of violence during pregnancy . 330 Table 16.8 Marital control exercised by husbands . 331 Table 16.9 Forms of spousal violence . 333 Table 16.10 Spousal violence according to background characteristics . 334 Table 16.11 Spousal violence by husband’s characteristics and empowerment indicators . 335 Table 16.12 Frequency of physical or sexual violence . 336 Table 16.13 Experience of spousal violence by duration of marriage . 337 Table 16.14 Injuries to women due to spousal violence . 337 Table 16.15 Women’s violence against their spouse according to background characteristics . 338 Table 16.16 Women’s violence against their spouse according to husband’s characteristics . 339 Table 16.17 Help seeking to stop violence . 340 Table 16.18 Sources for help to stop the violence . 341 Figure 16.1 Trends in physical violence . 318 Figure 16.2 Women’s experience of physical or sexual violence by marital status . 319 Figure 16.3 Types of spousal violence . 321 Figure 16.4 Spousal violence by husband’s alcohol consumption . 322 Figure 16.5 Help seeking by type of violence experienced . 324 xvi • Tables and Figures 17 ADULT AND MATERNAL MORTALITY . 343 Table 17.1 Completeness of information on siblings . 348 Table 17.2 Adult mortality rates . 348 Table 17.3 Adult mortality probabilities . 348 Table 17.4 Maternal mortality . 349 Figure 17.1 Adult mortality rates among women and men age 15-49 . 345 Figure 17.2 Trends in maternal mortality ratios with confidence intervals . 347 APPENDIX A SAMPLE DESIGN AND IMPLEMENTATION . 353 Table A.1 Population distribution of the 2012 census population by province and residence, Zimbabwe . 354 Table A.2 Household distribution of the 2012 census population by province and residence, Zimbabwe . 354 Table A.3 Distribution of enumeration areas (EAs) and their average size in number of households, Zimbabwe . 354 Table A.4 Sample allocation of clusters and households by province and residence, Zimbabwe 2015 . 355 Table A.5 Sample allocation of expected completed interviews with men and women by province and residence, Zimbabwe 2015 . 356 Table A.6 Number of expected HIV tests for women 15-49 and the expected precision by province, Zimbabwe 2015. 356 Table A.7 Number of expected HIV tests for men 15-54 and the expected precision by province, Zimbabwe 2015 . 357 Table A.8 Number of children 0-14 eligible for the HIV testing by province and residence, Zimbabwe 2015 . 357 Table A.9 Sample implementation: Women . 359 Table A.10 Sample implementation: Men . 360 Table A.11 Coverage of HIV testing by social and demographic characteristics: Women . 361 Table A.12 Coverage of HIV testing by social and demographic characteristics: Men . 362 Table A.13 Coverage of HIV testing by sexual behaviour characteristics: Women . 363 Table A.14 Coverage of HIV testing by sexual behaviour characteristics: Men . 364 APPENDIX B HIV TESTING METHODOLOGY . 365 Table B.1 HIV prevalence according to final and original HIV testing algorithms, by age . 368 Table B.2 HIV prevalence according to final and original HIV testing algorithms, by socioeconomic characteristics . 369 Figure B.1 Original HIV testing algorithm, participants age 2 years and older . 366 Figure B.2 Final HIV testing algorithm, participants age 2 years and older . 367 Figure B.3 Trends in HIV prevalence . 370 APPENDIX C ESTIMATES OF SAMPLING ERRORS . 371 Table C.1 List of indicators for sampling errors, 2015 Zimbabwe DHS . 373 Table C.2 Sampling errors: Total sample, 2015 Zimbabwe DHS . 374 Table C.3 Sampling errors: Urban sample, 2015 Zimbabwe DHS . 375 Table C.4 Sampling errors: Rural sample, 2015 Zimbabwe DHS . 376 Table C.5 Sampling errors: Manicaland sample, 2015 Zimbabwe DHS . 377 Table C.6 Sampling errors: Mashonaland Central sample, 2015 Zimbabwe DHS . 378 Table C.7 Sampling errors: Mashonaland East sample, 2015 Zimbabwe DHS . 379 Table C.8 Sampling errors: Mashonaland West sample, 2015 Zimbabwe DHS . 380 Table C.9 Sampling errors: Matabeleland North sample, 2015 Zimbabwe DHS . 381 Tables and Figures • xvii Table C.10 Sampling errors: Matabeleland South sample, 2015 Zimbabwe DHS . 382 Table C.11 Sampling errors: Midlands sample, 2015 Zimbabwe DHS . 383 Table C.12 Sampling errors: Masvingo sample, 2015 Zimbabwe DHS . 384 Table C.13 Sampling errors: Harare sample, 2015 Zimbabwe DHS . 385 Table C.14 Sampling errors: Bulawayo sample, 2015 Zimbabwe DHS . 386 Table C.15 Sampling errors for adult and maternal mortality rates, Zimbabwe 2015 . 387 APPENDIX D DATA QUALITY TABLES . 389 Table D.1 Household age distribution . 389 Table D.2.1 Age distribution of eligible and interviewed women . 390 Table D.2.2 Age distribution of eligible and interviewed men . 390 Table D.3 Completeness of reporting . 391 Table D.4 Births by calendar years . 391 Table D.5 Reporting of age at death in days . 392 Table D.6 Reporting of age at death in months . 392 Table D.7 Nutritional status of children based on the NCHS/CDC/WHO International Reference Population . 393 Table D.8 Completeness of information on siblings . 395 Table D.9 Sibship size and sex ratio of siblings . 395 Preface • xix PREFACE he 2015 Zimbabwe Demographic and Health Survey (2015 ZDHS) presents the major findings of a nationally representative survey with a sample of more than 11,000 households. The ZDHS was conducted by the Zimbabwe National Statistics Agency (ZIMSTAT) in collaboration with the Ministry of Health and Child Care (MoHCC) and the United Nations Population Fund (UNFPA), from July through December 2015. The 2015 ZDHS is the sixth such survey to be conducted in Zimbabwe as a follow-up to the 1988, 1994, 1999, 2005-06, and 2010-11 surveys and provides basic demographic and health indicators. Pursuant to the global trend on the use of modern technology in data collection, the 2010-11 survey, adopted the use of personal digital assistants (PDAs) rather than paper questionnaires for recording responses during interviews. In the 2015 survey, Asus tablets operating on Windows 8.1 software were used during data collection and these offer more features that the PDAs. A Key Indicators report was published in May 2016 and presents at a glance some selected findings of the survey. The primary objective of the 2015 ZDHS survey is to provide current demographic and health information for use by policymakers, planners, researchers and programme managers. Specific topics covered in the survey include: respondent demographic characteristics, reproductive and contraceptive history, fertility preferences, family planning methods, infant and child mortality, knowledge and attitudes about sexually transmitted infections, maternal health, breastfeeding and complementary feeding, anaemia prevalence in children and women, ownership of mosquito nets, knowledge of HIV prevention methods, comprehensive knowledge of HIV prevention among young people, multiple sexual partners, coverage of prior HIV testing, male circumcision, prevention of cervical cancer, domestic violence and maternal mortality. ZIMSTAT is appreciative of the significant funding and material provisions availed to the Agency by the Government of Zimbabwe, various development partners and the donor community that facilitated the successful implementation of the survey. Specific mention is due to the following: Ministry of Health and Child Care (MoHCC), United Nations Population Fund (UNFPA), National Microbiology Reference Laboratory (NMRL), the Zimbabwe National Family Planning Council (ZNFPC), United Nations Development Programme (UNDP), United Nations Children’s Fund (UNICEF), United Kingdom Department for International Development (DFID), Royal Danish Embassy, Australian Agency for International Development (AusAID), the European Union (EU), the Swedish International Development Cooperation (SIDA), and Irish Aid. ICF International provided technical assistance through The DHS Program, a USAID-funded project that provides support and technical assistance for the implementation of population and health surveys in countries worldwide. Finally, ZIMSTAT would also like to thank all field personnel for their dedication to duty and commitment to high quality work as well as the general public for the patience and cooperation during data collection. M. Dzinotizei Director General—Zimbabwe National Statistics Agency Harare, October 2016 T Additional DHS Program Resources • xxi ADDITIONAL DHS PROGRAM RESOURCES The DHS Program Website – Download free DHS reports, standard documentation, key indicator data, and training tools, and view announcements. DHSprogram.com STATcompiler – Build custom tables, graphs, and maps with data from 90 countries and thousands of indicators. Statcompiler.com DHS Program Mobile App – Access key DHS indicators for 90 countries on your mobile device (Apple, Android, or Windows). Search DHS Program in your iTunes or Google Play store DHS Program User Forum – Post questions about DHS data, and search our archive of FAQs. userforum.DHSprogram.com Tutorial Videos – Watch interviews with experts and learn DHS basics, such as sampling and weighting, downloading datasets, and How to Read DHS Tables. www.youtube.com/DHSProgram Datasets – Download DHS datasets for analysis. DHSprogram.com/Data Spatial Data Repository – Download geographically linked health and demographic data for mapping in a geographic information system (GIS). spatialdata.DHSprogram.com Social Media – Follow The DHS Program and join the conversation. Stay up to date through: Facebook www.facebook.com/DHSprogram Twitter www.twitter.com/ DHSprogram Pinterest www.pinterest.com/ DHSprogram LinkedIn www.linkedin.com/ company/dhs-program YouTube www.youtube.com/DHSprogram Blog Blog.DHSprogram.com Acronyms and Abbreviations • xxiii ACRONYMS AND ABBREVIATIONS AIDS acquired immunodeficiency syndrome ANC antenatal care API annual parasite incidence ARI acute respiratory infection ART antiretroviral therapy ASAR age-specific attendance rate AUSAID Australian Agency for International Development BMI body mass index CAPI computer-assisted personal interviewing CBD community-based distributor CBR crude birth rate CDC Centers for Diseases Control and Prevention CHTTS CSPro HIV Test Tracking System CPR contraceptive prevalence rate CSPro Census and Survey Processing System DBS dried blood spots DEFT design effect DFID United Kingdom Department of International Development DHS Demographic and Health Surveys EA enumeration area ELISA enzyme-linked immunosorbent assay EPI Expanded Programme on Immunization EU European Union GAR gross attendance ratio GFR general fertility rate GIS geographic information system GoZ Government of Zimbabwe GPI gender parity index HIV human immunodeficiency virus IFSS internet file streaming system IRS indoor residual spraying ITN insecticide-treated net IUCD intrauterine contraceptive device IYCF infant and young child feeding LAM lactational amenorrhoea method LLIN long-lasting insecticidal net LPG liquid petroleum gas xxiv • Acronyms and Abbreviations MAD minimum acceptable diet MDG Millennium Development Goal MoHCC Ministry of Health and Child Care MMR maternal mortality ratio MRCZ Medical Research Council of Zimbabwe MTCT mother-to-child transmission MUAC mid-upper-arm circumference NAR net attendance ratio NCD noncommunicable disease NGO non-governmental organisation NMRL National Microbiology Reference Laboratory ORS oral rehydration salts ORT oral rehydration therapy PDA personal digital assistant PEPFAR U.S. President’s Emergency Plan for AIDS Relief PMTCT prevention of mother-to-child transmission PPS probability proportional to size PSU primary sampling unit PY person-years RHF recommended home fluids SD standard deviation SDGs Sustainable Development Goals SE standard error SIDA Swedish International Development Cooperation STI sexually transmitted infection TB tuberculosis TFR total fertility rate TOT training of trainers UNDP United National Development Programme UNFPA United Nations Population Fund UNICEF United Nations Children’s Fund USAID United States Agency for International Development VAD vitamin A deficiency VIP ventilated improved pit VMMC voluntary male medical circumcision WHO World Health Organization ZDHS Zimbabwe Demographic and Health Survey ZIM Asset Zimbabwe Agenda for Sustainable Socio-Economic Transformation ZIMSTAT Zimbabwe National Statistics Agency ZNFPC Zimbabwe National Family Planning Council xxvi • Map of Zimbabwe Introduction and Survey Methodology • 1 INTRODUCTION AND SURVEY METHODOLOGY 1 he 2015 Zimbabwe Demographic and Health Survey (ZDHS) was implemented by the Zimbabwe National Statistics Agency (ZIMSTAT) from July through December 2015, with a nationally representative sample of over 11,000 households. Women age 15-49 and men age 15-54 in these households were eligible for individual interviews. The 2015 ZDHS is a follow-up survey to the 1988, 1994, 1999, 2005-06, and 2010-11 ZDHS surveys that provides updated estimates of basic demographic and health indicators. Other agencies and organizations that facilitated the successful implementation of the survey with technical or financial support were the Government of Zimbabwe, the United States Agency for International Development (USAID), the United Nations Population Fund (UNFPA), the United Nations Development Programme (UNDP), the United Nations Children’s Fund (UNICEF), the United Kingdom Department for International Development (DFID), the Royal Danish Embassy, the Australian Agency for International Development (AusAID), the European Union (EU), the Swedish International Development Cooperation Agency (SIDA), and Irish Aid. ICF International provided technical assistance through The DHS Program, a USAID-funded project that provides support and technical assistance for the implementation of population and health surveys in countries around the world. 1.1 SURVEY OBJECTIVES The primary objective of the 2015 ZDHS survey is to provide current estimates of basic demographic and health indicators. The ZDHS collected information on fertility levels, marriage, sexual activity, fertility preferences, awareness and use of family planning methods, breastfeeding practices, nutritional status of mothers and young children, early childhood mortality, maternal mortality, maternal and child health, knowledge and behaviour related to HIV/AIDS and other sexually transmitted infections (STIs), smoking, knowledge of cervical cancer, and male circumcision. In addition, the 2015 ZDHS provides estimates of anaemia prevalence among children age 6-59 months, women age 15-49, and men age 15-54, and HIV prevalence for all females age 0-49 and all males age 0-54. The information collected through the ZDHS will assist policy makers and programme managers in evaluating and designing programmes and strategies for improving the health of the country’s population. 1.2 SAMPLE DESIGN The 2015 ZDHS sample was designed to yield representative information for most indicators for the country as a whole, for urban and rural areas, and for each of Zimbabwe’s ten provinces: Manicaland, Mashonaland Central, Mashonaland East, Mashonaland West, Matabeleland North, Matabeleland South, Midlands, Masvingo, Harare, and Bulawayo. The 2012 Zimbabwe Population Census was used as the sampling frame for the 2015 ZDHS. Administratively, each province in Zimbabwe is divided into districts, and each district is divided into smaller administrative units called wards. During the 2012 Zimbabwe Population Census, each ward was subdivided into convenient areas, which are called census enumeration areas (EAs). The 2015 ZDHS sample was selected with a stratified, two-stage cluster design, with EAs as the sampling units for the first stage. The 2015 ZDHS sample included 400 EAs—166 in urban areas and 234 in rural areas. The second stage of sampling included the listing exercises for all households in the survey sample. A complete listing of households was conducted for each of the 400 selected EAs in March 2015. Maps were drawn for each of the clusters and all private households were listed. The listing excluded institutional living arrangements such as army barracks, hospitals, police camps, and boarding schools. A representative sample of 11,196 households was selected for the 2015 ZDHS. T 2 • Introduction and Survey Methodology Women age 15-49 and men age 15-54 who were either permanent residents of the selected households or visitors who stayed in the household the night before the survey were eligible for interviewing. Anaemia testing was performed in all households among eligible women age 15-49 and men age 15-54 who consented to testing. With the parent’s or guardian’s consent, children age 6-59 months were also tested for anaemia in these households. With consent from the respondent or parental or guardian consent for minors, blood samples were collected in all households for HIV testing in the laboratory for females age 0- 49 and males age 0-54. In addition, a sub-sample of one eligible woman in each household was randomly selected to be asked additional questions about domestic violence. 1.3 QUESTIONNAIRES Four questionnaires were used for the 2015 ZDHS: the Household Questionnaire, the Woman’s Questionnaire, the Man’s Questionnaire, and the Biomarker Questionnaire. These questionnaires were adapted from model survey instruments developed for The DHS Program to reflect the population and health issues relevant to Zimbabwe. Issues were identified at a series of meetings with various stakeholders from government ministries and agencies, research and training institutions, non-governmental organisations (NGOs), and development partners. In addition to English, the questionnaires were translated into two major languages, Shona and Ndebele. All four questionnaires were programmed into tablet computers to facilitate computer assisted personal interviewing (CAPI) for data collection, with the option to choose English, Shona, or Ndebele for each questionnaire. The Household Questionnaire listed the usual members and visitors of the selected households. Basic information was collected on the characteristics of each person listed, including age, sex, education, and relationship to the head of the household. For children under age 18, survival status of the parents was determined. Data on the age and sex of household members obtained in the Household Questionnaire was used to identify women age 15-49 and men age 15-54 who were eligible for the individual interview, anthropometry measurement, and haemoglobin and HIV testing. The Household Questionnaire was also used to identify children age 0-14 for HIV testing and children age 6-59 months for anaemia testing and age 0-59 months for anthropometry measurement. In addition, the Household Questionnaire collected information on characteristics of the household’s dwelling unit such as the source of water, type of toilet facilities, materials used for the floor, ownership of various durable goods, and ownership and use of mosquito nets (to assess the coverage of malaria prevention programmes). The Woman’s Questionnaire was used to collect information from women age 15-49 years on the following topics:  Background characteristics (age, education, media exposure, etc.)  Birth history and childhood mortality  Knowledge and use of family planning methods  Fertility preferences  Antenatal, delivery, and postnatal care  Breastfeeding and infant feeding practices  Vaccinations and childhood illnesses  Marriage and sexual activity  Women’s work and husband’s background characteristics  Malaria prevention and treatment  Awareness and behaviour related to HIV/AIDS and other sexually transmitted infections (STIs)  Adult mortality, including maternal mortality  Domestic violence The Man’s Questionnaire was administered to men age 15-54 in all households in the 2015 ZDHS sample. The Man’s Questionnaire collected much of the same information as in the Woman’s Questionnaire, but was shorter because it did not contain a detailed reproductive history or questions on maternal and child health. Introduction and Survey Methodology • 3 The Biomarker Questionnaire recorded the results of the anthropometry measurements, haemoglobin testing results, and HIV sample collection for testing in the laboratory, as well as the signatures of the fieldworker and the respondent who gave consent. Separate consent forms were administered, signed, and archived to record each respondent’s consent and signature. For this survey, interviewers used tablet computers to record all questionnaire responses during the interviews. The tablet computers were equipped with Bluetooth® technology to enable remote electronic transfer of files, such as assignment sheets from the team supervisor to the interviewers, Household Questionnaires among survey team members, and completed questionnaires from interviewers to the team supervisors. The tablet computer programming was created using the Census and Survey Processing System (CSPro) by The DHS Program, in collaboration with the U.S. Census Bureau. 1.4 ANTHROPOMETRY, ANAEMIA TESTING, AND HIV TESTING The 2015 ZDHS incorporated three “biomarkers” that included anthropometry, anaemia testing, and HIV testing. Data related to the coverage of the biomarker component, the anthropometric measures and the result of the anaemia testing were directly recorded using the tablet. The protocol for anaemia testing and for the blood specimen collection for HIV testing was reviewed and approved by the Medical Research Council of Zimbabwe (MRCZ), the Institutional Review Board of ICF International, and the Centers for Disease Control and Prevention (CDC) in Atlanta. Anthropometry Measurements: In all households, height and weight measurements were recorded for children age 0-59 months, women age 15-49, and men age 15-54. Anaemia Testing: Blood specimens were collected for anaemia testing from all children age 6-59 months, women age 15-49 and men age 15-54 who voluntarily consented to the testing. Blood samples were drawn from a drop of blood taken from a finger prick (or a heel prick for young children with small fingers) and collected in a microcuvette. Haemoglobin analysis was conducted on site with a battery-operated portable HemoCue® analyser, which produces a result in less than one minute. Results were provided verbally and in writing. Parents of children with a haemoglobin level below 7 g/dL were instructed to take the child to a health facility for follow-up care. Non-pregnant women, pregnant women, and men were referred for follow-up care if their haemoglobin level was below 7 g/dL, 9 g/dL and 9 g/dL, respectively. All households in which anthropometry and/or anaemia testing was conducted were given a brochure that explained the causes and prevention of anaemia. HIV Testing: Blood specimens for HIV testing in the laboratory were collected from females age 0-49 and males age 0-54 who consented to the testing. The protocol for the blood specimen collection and analysis was based on the anonymous linked protocol developed for The DHS Program. This protocol allows for the merging of the HIV test results with the socio-demographic data collected in the individual questionnaires after all information that could potentially identify an individual have been destroyed. The ZDHS biomarker interviewers explained the blood collection procedure, the confidentiality of the data, and the fact that the test results would not be made available to the respondent. For women age 18-49 and men age 18-54, informed consent was sought directly from the respondent. For children age 0-6 years, informed consent for HIV testing was sought from parents or guardians. In accordance with human subjects practices in Zimbabwe, for children/youth age 7-17 years parental/guardian consent and youth assent were sought for HIV testing. Minors age 13-17 who have ever been married, or who live in households in which no household members are 18 years of age or above, are considered emancipated and were able to consent to participate in the HIV test without the permission of a parent or guardian. Biomarker interviewers read informed consent statements aloud to participants and their parents or guardians and provided printed copies of the consent statements. Adults, emancipated minors, and parents or guardians provided written consent, and unemancipated minors age 7-17 provided written assent. Each household, whether individuals consented to HIV testing or not, was given an informational brochure on HIV/AIDS and a list of fixed sites providing voluntary counselling and testing services in surrounding districts within the province. 4 • Introduction and Survey Methodology If a respondent consented to the HIV testing, five blood spots from the finger prick were collected on a filter paper card to which a barcode label unique to the respondent was affixed. Respondents were asked whether they consented to having the laboratory store their blood sample for future unspecified testing. If the respondent did not consent to additional testing using their sample, it was indicated on the Biomarker Questionnaire and the Blood Sample Transmittal Form that the respondent refused additional tests using their specimen; “no additional testing” was also written on the filter paper card. Each blood sample had a barcode label, and the barcode number was entered into the Biomarker Questionnaire. A third copy of the same barcode was affixed to the Blood Sample Transmittal Form to track the blood samples from the field to the laboratory. Blood samples were dried overnight and packaged for storage the following morning. Samples were periodically collected from the field teams, along with the Blood Sample Transmittal Forms, and transported to ZIMSTAT in Harare to be logged in, and checked. Blood samples were then transported to the National Microbiology Reference Laboratory (NMRL) in Harare. Upon arrival at NMRL, each blood sample was logged into the CSPro HIV Test Tracking System (CHTTS) database, given a laboratory number, and stored at -20°C until tested. The HIV testing protocol stipulates that testing of blood can only be conducted after the questionnaire data entry is completed, verified, and cleaned, and all unique identifiers are removed from the questionnaire file except the anonymous barcode number. The original testing algorithm calls for testing all samples on the first assay test, an ELISA, the Vironostika® HIV Ag/Ab (fourth generation) (Biomerieux). A negative result is rendered negative. All samples with positive results are subjected to a second ELISA, the Enzygnost® HIV Integral II (fourth generation) (Siemens). Samples with positive results on the second test are rendered positive. If the first and second tests are discordant, the samples are re-tested on the first and second assay. If the samples are still discordant, a third confirmatory test, the INNO-LIA™ HIV I/II Score Blot Assay (Fujirebio, Zwignaard, Belgium), is administered. The final result will be rendered positive if the INNO-LIA confirms the result to be positive and rendered negative if the INNO-LIA confirms it to be negative. If the INNO-LIA results are indeterminate, the sample will be rendered indeterminate. In accordance with new recommendations, released after the 2015 ZDHS survey protocol was finalized (see UNAIDS/WHO, 2015), a decision was taken to add an additional test to the algorithm. To reduce the risk of false-positive results, all specimens that were rendered positive in the original HIV testing algorithm for the survey were tested on a highly specific confirmatory assay, Geenius HIV 1/2 (Bio-Rad, France). Further discussion on the final testing algorithm is presented in Appendix B. 1.5 TRAINING OF FIELD STAFF The ZDHS technical team, composed of ZIMSTAT staff and experts from the Ministry of Health and Child Care (MoHCC), Zimbabwe National Family Planning Council (ZNFPC), the Medical Research Council of Zimbabwe (MRCZ), UNFPA, USAID and ICF International, participated in a 3-day training of trainers (TOT), which was conducted April 20-22, 2015. Immediately following the TOT, the pretest training took place from April 23 to May 6, 2015. The pretest fieldwork was conducted May 7-9, 2015. During a 2-week period, the 15-member ZDHS technical team and 3 ICF technical specialists trained 27 participants to administer paper and electronic questionnaires with tablet computers. The ICF biomarker specialist trained the technical team and pretest participants to take anthropometric measurements, collect finger prick blood samples for haemoglobin measurement and HIV testing, and properly store the dried blood spot (DBS) specimens for HIV testing. The pretest fieldwork was conducted over 3 days, covering approximately 150 households. The ZDHS technical team conducted debriefing sessions with the pretest field staff on May 10, 2015; modifications to the questionnaires were made based on lessons learned from the exercise. ZIMSTAT recruited and trained 120 individuals (52 females and 68 males) to serve as supervisors, interviewers, biomarker interviewers, and reserve interviewers for the main fieldwork. Field staff training for the main survey was conducted June 1-24, 2015. The training course included instruction on interviewing techniques and field procedures, a detailed review of the questionnaire content, and mock interviews between participants in the classroom. The biomarker interviewers (21 females and 24 males) Introduction and Survey Methodology • 5 received additional training, including instruction in anthropometry and finger prick blood collection for haemoglobin measurement and HIV testing. Main training participants conducted practice interviews and biomarker collection with respondents in households located outside the 2015 ZDHS sample EAs. Team supervisors were trained in methods of data quality control procedures, fieldwork coordination, and the use of special programmes for the tablet computers. 1.6 FIELDWORK Fifteen interviewing teams conducted data collection for the 2015 ZDHS. Each team included one team supervisor, four interviewers, three biomarker interviewers, and one driver. Electronic data files were transferred each day from each interviewer’s tablet computer to the team supervisor’s tablet computer. The field supervisors transferred data to the central data processing office. To facilitate communication and monitoring, each field worker was assigned a unique identification number. Senior technical staff members from ZIMSTAT coordinated and supervised fieldwork activities. An ICF International technical specialist, a biomarker specialist, two data processing staff, and representatives from NMRL, MoHCC, ZNFPC, MRCZ, UNFPA, and USAID supported the fieldwork monitoring activities. Data collection took place over a 6-month period from July 6 to December 20, 2015. 1.7 DATA PROCESSING CSPro was used for data editing, weighting, cleaning, and tabulation. In ZIMSTAT’s central office, data received from the supervisor’s tablets were registered and checked for inconsistencies and outliers. Data editing and cleaning included structure and internal consistency checks to ensure the completeness of work in the field. Any anomalies were communicated to the respective team through the technical team and the team supervisor. The corrected results were then re-sent to the central office. 1.8 RESPONSE RATES Table 1.1 shows the household and individual response rates for the 2015 ZDHS. A total of 11,196 households were selected for inclusion in the 2015 ZDHS and of these, 10,657 were found to be occupied. A total of 10,534 households were successfully interviewed, yielding a response rate of 99 percent. In the interviewed households, 10,351 women were identified as eligible for the individual interview, and 96 percent of them were successfully interviewed. For men, 9,132 were identified as eligible for interview, with 92 percent successfully interviewed. The 2015 ZDHS achieved a higher response rates than the 2010-11 ZDHS for households, women, and men. The increase in the response rates is particularly notable in urban areas. Table 1.1 Results of the household and individual interviews Number of households, number of interviews, and response rates, according to residence (unweighted), Zimbabwe 2015 Residence Total Result Urban Rural Household interviews Households selected 4,646 6,550 11,196 Households occupied 4,423 6,234 10,657 Households interviewed 4,341 6,193 10,534 Household response rate1 98.1 99.3 98.8 Interviews with women age 15-49 Number of eligible women 4,753 5,598 10,351 Number of eligible women interviewed 4,521 5,434 9,955 Eligible women response rate2 95.1 97.1 96.2 Interviews with men age 15-54 Number of eligible men 3,917 5,215 9,132 Number of eligible men interviewed 3,456 4,940 8,396 Eligible men response rate2 88.2 94.7 91.9 1 Households interviewed/households occupied 2 Respondents interviewed/eligible respondents Housing Characteristics and Household Population • 7 HOUSING CHARACTERISTICS AND HOUSEHOLD POPULATION 2 Key Findings  Drinking water: Access to an improved source of drinking water is 97 percent in urban households and 69 percent in rural households.  Availability of water: Among households using piped water or water from a tube well or borehole, 72 percent of households have water available to them without an interruption of at least 1 day.  Sanitation: An improved sanitation facility is used by 37 percent of Zimbabwean households.  Household characteristics: Thirty-four percent of Zimbabwean households use electricity as a source of energy, and 68 percent of Zimbabwean households use wood as cooking fuel.  Household possessions: Eighty-seven percent of Zimbabwean households own mobile phones, up from 62 percent in the 2010-11 ZDHS. Ten percent of Zimbabwean households own computers.  Orphans: Sixteen percent of Zimbabwean children under age 18 are orphaned (single or both parents), 12 percent in urban areas and 17 percent in rural areas. Twenty-six percent of children do not live with either parent.  Birth registration: Births are registered with civil authorities for 44 percent of children under age 5; only one-third of children had a birth certificate.  School attendance: Ninety-one percent of females and 94 percent of males have ever attended school. his chapter presents information on demographic and socioeconomic characteristics of the household population such as age, sex, education, and place of residence. The environmental profile of households included in the 2015 ZDHS sample is also examined. Taken together, these descriptive data provide a context for the interpretation of demographic and health indices and furnish an approximate indication of the representativeness of the survey. In the 2015 ZDHS, a household refers to a person or group of related and unrelated persons who live together in the same dwelling unit(s), acknowledge one adult male or female as the head of the household, share the same housekeeping arrangements, and are considered a single unit. Information was collected from all usual residents of each selected household and visitors who stayed in the selected household the night before the interview. Those persons who stayed in the selected household the night before the interview (whether usual residents or visitors) represent the de facto population; usual residents alone constitute the de jure population. To maintain comparability with other ZDHS surveys, all tables in this report refer to the de facto population unless otherwise specified. T 8 • Housing Characteristics and Household Population 2.1 DRINKING WATER SOURCES AND TREATMENT Improved sources of drinking water Include piped water, public taps, standpipes, tube wells, boreholes, protected dug wells and springs, and rainwater. Because the quality of bottled water is not known, households using bottled water for drinking are classified as using an improved source only if their water source for cooking and handwashing are from an improved source. Sample: Households The majority of households in Zimbabwe (78 percent) have access to an improved source of water: 97 percent in urban areas and 69 percent in rural areas (Table 2.1). Improved sources protect against outside contamination so that water is more likely to be safe to drink. Figure 2.1 presents data on improved water source among the provinces. Twenty-four percent of households have water piped into the dwelling, yard, or plot, while 30 percent of households use a tube well or borehole, 17 percent a protected dug well, and 6 percent a public tap or standpipe. More than half of urban households (58 percent) drink water that is piped into the dwelling, yard, or plot compared with 6 percent rural households (Figure 2.2). In rural areas, tube wells or boreholes are the main source of drinking water (35 percent), followed by protected and unprotected dug wells (19 percent and 16 percent, respectively). In 72 percent of urban households and 20 percent of rural households, water is available on premises, within the dwelling or plot (Table 2.1). In 8 in 10 rural households obtain water from a source not on the premises; 39 percent of rural households report that it takes 30 minutes or longer (round trip) to access drinking water. Figure 2.1 Households with improved water source Figure 2.2 Household drinking water by residence 58 6 24 6 5 6 18 35 30 12 19 17 3 32 22 Urban Rural Total Unimproved source Protected dug well Tube well or borehole Public tap/standpipe Piped into dwelling/yard plot Percent distribution of households by source of drinking water Housing Characteristics and Household Population • 9 Most households (86 percent) do not treat their drinking water: 80 percent among urban households and 88 percent among rural households. In Zimbabwe, 6 percent of households boil their water, and 8 percent use bleach or chlorine. Overall, 14 percent of households in Zimbabwe are using an appropriate treatment method: 19 percent in urban areas and 11 percent in rural areas. Figure 2.3 presents information on the proportion of households using piped water or water from a tube well or borehole who reported availability of water in the last 2 weeks. Seventy-two percent of households in Zimbabwe reported having water, with no interruption of at least a single day in the last two weeks (Table 2.2). Urban households are more likely to report non- availability of water for at least one day compared with rural households (40 percent and 17 percent, respectively). Trends: The proportion of households using an improved source of water remains similar between the 2010-11 ZDHS (79 percent) and the 2015 ZDHS (78 percent). Fewer households treat their drinking water. In 2010-11, 22 percent of households used an appropriate water treatment method compared with 14 percent in 2015. 2.2 SANITATION FACILITIES AND WASTE DISPOSAL Improved toilet facilities Include any non-shared toilet of the following types: flush or pour flush into a piped sewer system, septic tank, or pit latrine; ventilated improved pit (VIP) latrines or Blair toilets; and pit latrines with a slab. Sample: Households Table 2.3 presents information on the proportion of households with access to hygienic sanitation facilities by type of toilet or latrine. Figure 2.3 Availability of water in the last 2 weeks before the survey 40 17 28 59 83 72 Urban Rural Total Available with no interruption of at least one day Not available for at least one day Percent distribution of households by water availability 10 • Housing Characteristics and Household Population Nearly 4 in 10 households in Zimbabwe usually use improved toilet facilities, which are defined as non-shared facilities that prevent people from coming into contact with human waste, and reduce the risk of transmitting cholera, typhoid, and other diseases. Shared toilet facilities, which are otherwise considered improved facilities, are especially common in urban areas (Figure 2.4). Overall, the most commonly used improved toilet facility among households in Zimbabwe is a pit latrine with a slab (13 percent). Thirty percent of Zimbabwean households have shared facilities. Urban households are more than twice as likely to have a shared facility as rural households (49 percent and 20 percent, respectively). Twenty-three percent of households do not use any toilet facility. Rural households are more likely to have an unimproved toilet facility or have no toilet at all when compared with urban households (48 percent and 5 percent, respectively). Among households in Zimbabwe that use a toilet facility, one-third (32 percent) use a toilet facility in their own dwelling, 58 percent use a toilet facility in their own yard or plot, and 10 percent use toilet facility elsewhere. Urban households are much more likely than rural households to use a facility in their own dwelling (65 percent and 7 percent, respectively). Rural households are more likely than urban households to use toilets in their yard or plot (79 percent and 31 percent, respectively). Trends: Thirty-four percent of households in rural areas have no toilet facility, a slightly lower proportion than that reported in the 2010-11 ZDHS (39 percent). The proportion of households with improved facilities is similar between the two surveys: 36 percent in 2010-11 and 37 percent in 2015. 2.3 EXPOSURE TO SMOKE INSIDE THE HOME AND OTHER HOUSING CHARACTERISTICS Table 2.4 presents information on a number of household dwelling characteristics along with the percentage of households using various types of fuel for cooking and the exposure to smoke inside the home. Information on type of fuel used for cooking and place for cooking was obtained to assess the extent to which household members may be exposed to the potentially harmful effects of smoke from cooking with solid fuels such as coal, plant materials, and animal waste. About 7 of 10 households in Zimbabwe use some type of solid fuel, a figure that is unchanged since the 2010-11 ZDHS (69 percent). Almost all households that use solid fuels cook with wood (68 percent). In rural areas, 93 percent of households use wood for cooking, compared with 18 percent in urban areas. The potential for exposure to harmful effects of smoke from using solid fuels for cooking is increased if cooking occurs within the home itself rather than outdoors or in a separate building. Forty-six percent of households in Zimbabwe cook in the house and 54 percent cook in a separate building or outdoors. Eleven percent of Zimbabwean households report that someone smokes at the home daily, a decrease from 17 percent in 2010-11 ZDHS. Someone smokes at least once a week in 4 percent of households. In 81 percent of households, smoking never occurs in the home. Overall, smoking inside the home is less frequent in urban areas than in rural areas. The survey also collected data on access to electricity, flooring materials, and the number of rooms used for sleeping. Thirty-four percent of households in Zimbabwe have access to electricity (81 percent in urban Figure 2.4 Household toilet facilities by residence 46 32 37 49 20 30 4 14 10 1 34 23 Urban Rural All No facility/bush/field Unimproved facility Shared facility Improved facility Percent distribution of households by type of toilet facilities Housing Characteristics and Household Population • 11 areas and 10 percent in rural areas), which is a slight decrease from 37 percent in the 2010-11 ZDHS. A majority of urban households use electricity for cooking (66 percent); in contrast, only 5 percent of rural households use electricity for this purpose. The most commonly used flooring material, cement, has remained at 67 percent since the previous ZDHS, followed by earth or sand (15 percent) and dung (10 percent). In urban areas, 79 percent of households have cement floors, compared with 61 percent in rural areas. Earth, sand, or dung floors are found in 37 percent of rural dwelling units. Thirty-six percent of households have one room that is used for sleeping and another 36 percent have two rooms, while 28 percent have three or more rooms. More households in urban areas (41 percent) compared with rural areas (33 percent) use one room for sleeping. 2.4 HOUSEHOLD WEALTH 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 a car, plus 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 percent of the population. Thus, throughout this report, wealth quintiles are expressed in terms of quintiles of individuals in the overall population rather than quintiles of individuals at risk for any one health or population indicator. Sample: Households Table 2.5 presents wealth quintiles by urban-rural residence and province. Also included in the table is the Gini coefficient, which indicates the level of concentration of wealth, with 0 being an equal distribution and 1 a totally unequal distribution. 12 • Housing Characteristics and Household Population All of the urban population is represented in the two highest wealth quintiles (100 percent), while almost 6 in 10 households in rural areas are in the two lowest wealth quintiles (Figure 2.5). The wealth quintile distribution among provinces shows large variations. The two urban provinces, Bulawayo and Harare, have the largest proportions in the highest wealth quintile (67 percent and 58 percent, respectively). In contrast, Matabeleland North and Masvingo have the largest proportions in the lowest wealth quintile (44 percent and 31 percent, respectively). Household Durable Goods Information on household effects, means of transportation, agricultural land, and farm animals is presented in Table 2.6, by residence. Nationally, 43 percent of households have a radio, 37 percent a television, 25 percent a refrigerator, and 10 percent a computer. Urban households are more likely than rural households to own household effects that are powered by electricity, such as a television (73 percent and 19 percent, respectively), a refrigerator (61 percent and 7 percent, respectively), and a computer (24 percent and 3 percent, respectively). The most common means of transportation owned by households in both urban and rural areas is a bicycle (17 percent in urban areas and 26 percent in rural areas). Animal drawn carts, owned by 10 percent of urban households and 26 percent of rural households, are also a common means of transport. Urban households are five times more likely than rural households to own a car or truck (26 percent and 5 percent, respectively). A small proportion (2 percent) of households in both urban and rural areas owns a motorcycle or scooter. The majority of households in Zimbabwe own agricultural land (65 percent), and 66 percent own farm animals. Among urban households, 31 percent own agricultural land, compared with 82 percent in rural areas. Trends: Eight-seven percent have a mobile telephone, which is an increase from 62 percent in the 2010-11 ZDHS. Ownership of mobile telephones in rural households has risen sharply from 48 percent in 2010-11 to 82 percent in 2015. Ten percent of households in Zimbabwe own a computer, which is an increase from 4 percent in the 2010-11 ZDHS. 2.5 HAND WASHING Hand washing with soap and water is ideal. However, hand washing with a non-soap cleansing agent such as ash or sand is an improvement over not using any cleansing agent. To obtain hand-washing information, interviewers asked respondents to see the place where members of the household most often wash their hands. Table 2.7 shows that interviewers observed the place most often used for hand washing in 98 percent of households. Among households where the hand washing place was observed, the most common hand washing agent was soap and water (39 percent), followed by water only (36 percent). In 19 percent of the households, no water, soap, or any other cleansing agent was observed at the hand washing place. Lack of water and a cleansing agent decreases with an increase in household wealth. Trends: The proportion of households with soap and water observed for hand washing has decreased from what was observed in the 2010-11 ZDHS to the 2015 ZDHS from 44 percent to 39 percent. An Figure 2.5 Household wealth by residence 29 29 29 40 11 60 2 Urban Rural Percent distribution of de jure population by wealth quintiles Highest Fourth Middle Second Lowest Housing Characteristics and Household Population • 13 increase was observed in the proportion of households with water only, 33 percent in 2010-11 and 36 percent in 2015. There is an increase in the proportion of households with no water, soap, or other cleansing agent observed for hand washing from 17 percent to 19 percent in the same period. 2.6 HOUSEHOLD POPULATION AND COMPOSITION Household A person or group of related or unrelated persons who live together in the same dwelling unit(s), who acknowledged one adult male or female as the head of the household, who share the same housekeeping arrangements, and who are considered a single unit 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 households the night before the interview Table 2.8 shows the distribution of the 2015 ZDHS household population by age groups, according to sex and residence. A total of 42,586 individuals stayed overnight in 10,534 sample households in the 2015 ZDHS. Fifty-three percent (22,404) of household residents were female and 47 percent (20,181) were male. Figure 2.6 shows their distribution by five-year age groups and sex. The broad base of the pyramid indicates that Zimbabwe’s population is young, a scenario typical of countries with high fertility rates. The proportion of children under age 15 remains at 43 percent since the 2010-11 ZDHS. Half of the population in Zimbabwe is below age 18, while 5 percent are age 65 or older. Table 2.9 shows that 59 percent of households are headed by males and 41 percent are headed by females. There is no significant difference in household headship between rural and urban residence. Urban households are, on average, slightly smaller (3.7 persons) than rural households (4.3 persons). Overall, 35 percent of households in Zimbabwe are caring for foster or orphaned children. Twenty-one percent of households are caring for orphans (5 percent double orphans and 16 percent single orphans). Rural households are more likely than urban households to be caring for foster or orphaned children (41 percent versus 25 percent, respectively). Figure 2.6 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 Trends: The average household size has remained at 4.1 individuals since the 2010-11 ZDHS. The proportion of female headed households decreased slightly from 45 percent in the 2010-11 ZDHS to 41 percent. 2.7 BIRTH REGISTRATION Registered birth Child has a birth certificate or his/her birth has been registered with the civil authority. Sample: De jure children under 5 Table 2.10 shows the percentage of de jure children under age 5 whose births were officially registered and the percentage with a birth certificate. At the time of the survey, 44 percent of children under age 5 had their births registered with the civil authority; 33 percent of children had a birth certificate and 10 percent had their birth registered but did not have a birth certificate. There are rural and urban differences in birth certification, with children in urban areas more than twice as likely as children in rural areas to have a birth certificate (57 percent versus 24 percent, respectively); overall, two-thirds (67 percent) of children in urban areas have had their birth registered compared with one-third (34 percent) of children in rural areas. Birth registration does not vary by sex, but varies widely by province, ranging from a low of 27 percent in Manicaland to a high of 68 percent in Harare. The proportion of children whose birth has been registered increases dramatically with wealth, ranging from 24 percent in the lowest wealth quintile to 79 percent in the highest wealth quintile. Trends: The proportion of de jure children whose births were registered has decreased during the last 10 years. According to the 2005-06 ZDHS, 74 percent of children’s births were registered, but this dropped to 49 percent in the 2010-11 ZDHS, and 44 percent in the 2015 ZDHS. 2.8 CHILDREN’S LIVING ARRANGEMENTS, SCHOOL ATTENDANCE, AND PARENTAL SURVIVAL Orphan A child with one or both parents dead Sample: De jure children under 18 Table 2.11 presents the proportion of de jure children under age 18 who are not living with one or both parents, either because the parent(s) died or for other reasons. Twenty-six percent of Zimbabwean children under age 18 are not living with a biological parent. Sixteen percent of children under age 18 have lost one or both parents (single or double orphans). Rural children (17 percent) are more likely to be orphans than urban children (12 percent). There are notable disparities across provinces. Table 2.12 presents data on school attendance rates and parental survivorship among de jure children age 10-14. The school attendance ratio in the final column of the table allows an assessment of the extent to which orphaned children are disadvantaged in terms of access to education. Ratios below 1.0 indicate that access to education is more limited for double orphans. Ninety-two percent of the proportion of de jure children age 10-14, who have both parents deceased, are currently attending school; 96 percent of children with both parents alive and who are living with a least one parent are attending school. Housing Characteristics and Household Population • 15 2.9 EDUCATION 2.9.1 Educational Attainment Median educational attainment Half the population has completed less than the median number of years of schooling and half 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 Zimbabweans have attained some education. Overall, 94 percent of males age 6 and older have ever attended school, compared with 91 percent of females (Tables 2.13.1 and 2.13.2). The median number of years of educational attainment is similar for males (6.7 years) and females (6.5 years). Educational attainment rises with wealth quintile, and peaks in the highest wealth quintile for both sexes. As expected, regardless of sex, educational attainment is higher among urban than rural residents. Among both males and females, the median number of years of schooling is highest in Harare (9.8 for females and 10.2 for males). Trends: During the last 10 years, educational attainment at the household level has increased. The proportion of females and males with more than a secondary level education in surveyed households has increased from 2 percent of women and 4 percent of men in the 2005-06 ZDHS to 5 percent of women and 6 percent of men in the 2015 ZDHS. Likewise, over the same period, the proportion of women and men with no education has decreased from 12 percent of women and 9 percent of men in 2005-06 to 9 percent of women and 6 percent of men in 2015. 2.9.2 School Attendance Net attendance ratio (NAR) Percentage of school-age population that attends primary or secondary school Sample: Children age 6-12 for primary school NAR and children age 13-18 for secondary school NAR Table 2.14 shows that 91 percent of children age 6-12 attend primary school and 50 percent of children age 13-18 attend secondary school. Patterns by background characteristics  Few differences are observed in the net attendance ratios (NARs) for girls and boys at either the primary or secondary school level.  At the primary school level, the NAR in urban areas is slightly higher than in rural areas (93 percent and 91 percent, respectively); there is a much wider gap in the NAR between urban and rural areas at the secondary school level (64 percent and 45 percent, respectively). 16 • Housing Characteristics and Household Population  By province, no notable differences in NARs are observed at the primary school level. At the secondary school level, there is a greater variation in NARs. Harare (62 percent) has the highest NAR and Matabeleland South the lowest (39 percent).  The NARs increase with household wealth at both the primary and secondary school levels. Girls and boys in the highest wealth quintile are about two times more likely to attend secondary school than those in the lowest wealth quintile (Figure 2.7). Other Measures of School Attendance Gross attendance ratio (GAR) The total number of students attending primary and secondary school— regardless of age—expressed as a percentage of the official primary school- age population Sample: All children in primary school, regardless of age, for primary school GAR. All children in secondary school, regardless of age, for secondary school GAR. Gender Parity Index (GPI) The ratio of female to male attendance rates at the primary and secondary levels that indicates the magnitude of the gender gap Sample: Children age 6-12 for primary school, and children age 13-18 for secondary school The ZDHS education data allow the calculation of two more education indicators: the gross attendance ratio (GAR), and the gender parity index (GPI) (Table 2.14). At the primary school level, the GAR is 108 percent. This figure exceeds the primary school NAR (91 percent) by 17 percentage points, indicating that a number of children outside the official school age population are attending primary school. At the secondary school level, the GAR is also higher (58 percent) than the NAR (50 percent), which indicates that there are children outside of the official school age population who are attending secondary school. The Gender Parity Index (GPI) measures sex-related differences in school attendance ratios, and is the ratio of female to male attendance. A GPI of 1 indicates parity or equality between the school participation ratios for males and females. A GPI lower than 1 indicates a gender disparity in favour of males, with a higher proportion of males than females attending that level of schooling. A GPI higher than 1 indicates a gender disparity in favour of females. At the primary level, the GPIs for the NAR and GAR are 1.01 and 0.96, respectively. At the secondary level, the GPIs for the NAR and GAR are 1.03 and 1.02, respectively. This indicates that there is relatively Figure 2.7 Secondary school attendance by wealth quintile 31 43 46 58 73 50 35 44 53 56 64 51 Lowest Second Middle Fourth Highest Total Female Male RichestPoorest Net attendance ratio for secondary school among children age 13-18 Housing Characteristics and Household Population • 17 little difference in overall school attendance by girls and boys at either the primary or secondary school level. Patterns by background characteristics At the primary school level, the GPI for the GAR did not differ much by area of residence (0.97 for urban and 0.95 rural); by province, the GPI ranges from a low of 0.92 in Masvingo and Matebeleland South to a high of 1.01 in Manicaland.  The GPI for the GAR shows that the fewer girls than boys attend secondary school in urban areas (GPI=0.84), while more girls than boys attend secondary school (GPI=1.08) in rural areas.  By province, the GPI for the GAR is widest in Matebeleland South (1.49), followed by Matebeleland North (1.38) and Masvingo (1.33), with more girls than boys attending secondary school. The GPI for the GAR is lowest in Bulawayo (0.76) and Harare (0.81) with fewer girls attending secondary school than boys.  By wealth quintile, the GPI for the secondary school GAR shows no clear pattern, but the gender gap is greatest in the highest (0.88) and middle (1.12) wealth quintiles. Age-specific attendance rate Children in any specific age group attending school, irrespective of whether they are attending the appropriate stages in the school Sample: De facto household population age 5-24 years attending school Age-specific attendance rates (ASARs) for the population age 5 to 24 are presented in Figure 2.8 by age and sex. The ASARs indicate participation in schooling at any level, from primary to higher levels of education. The trends are generally the same for males and females. Approximately half of children attend school by age 6. In the age groups 6-7 and 9-13, the ASARs are higher for females than for males. In the 8-13 age group, more than 90 percent of children attend school. The attendance rate declines rapidly from age 14 to 19, with a slower decline observed from age 20 to 24. The decline in ASARs is more rapid for females than males from age 16 and older. Figure 2.8 Age-specific attendance rates of the de facto population 5 to 24 years 0 10 20 30 40 50 60 70 80 90 100 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 Female Male Age Percent 18 • Housing Characteristics and Household Population LIST OF TABLES For detailed information on household population and housing characteristics, see the following tables:  Table 2.1 Household drinking water  Table 2.2 Availability of water  Table 2.3 Household sanitation facilities  Table 2.4 Household characteristics  Table 2.5 Wealth quintiles  Table 2.6 Household possessions  Table 2.7 Hand washing  Table 2.8 Household population by age, sex, and residence  Table 2.9 Household composition  Table 2.10 Birth registration of children under age 5  Table 2.11 Children’s living arrangements and orphanhood  Table 2.12 School attendance by survivorship of parents  Table 2.13.1 Educational attainment of the female household population  Table 2.13.2 Educational attainment of the male household population  Table 2.14 School attendance ratios  Table 2.15 Age-specific attendance rates Housing Characteristics and Household Population • 19 Table 2.1 Household drinking water Percent distribution of households and de jure population by source of drinking water, time to obtain drinking water, and treatment of drinking water, according to residence, Zimbabwe 2015 Households Population Characteristic Urban Rural Total Urban Rural Total Source of drinking water Improved source 97.2 68.5 78.1 97.1 67.2 76.3 Piped into dwelling/yard/plot 58.3 5.9 23.5 57.6 4.9 20.9 Piped to neighbour 1.2 1.1 1.1 1.1 1.0 1.1 Public tap/standpipe 6.3 5.1 5.5 6.5 4.2 4.9 Tube well or borehole 18.2 35.3 29.6 18.5 35.8 30.6 Protected dug well 11.5 19.3 16.7 11.9 19.4 17.1 Protected spring 0.6 1.7 1.3 0.6 1.7 1.4 Rain water 0.0 0.1 0.0 0.0 0.0 0.0 Bottled water, improved source for cooking/handwashing1 1.2 0.1 0.4 1.0 0.0 0.3 Unimproved source 2.6 31.4 21.8 2.6 32.8 23.6 Unprotected dug well 1.7 15.5 10.9 1.7 16.1 11.7 Unprotected spring 0.3 4.8 3.3 0.3 4.9 3.5 Tanker truck/cart with small tank 0.4 0.2 0.3 0.3 0.1 0.2 Surface water 0.2 10.8 7.3 0.3 11.7 8.2 Bottled water, unimproved source for cooking/handwashing1 0.0 0.1 0.0 0.0 0.0 0.0 Other 0.2 0.1 0.1 0.3 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 premises2 72.0 20.3 37.6 71.1 18.9 34.8 Less than 30 minutes 19.2 40.4 33.3 19.5 39.7 33.5 30 minutes or longer 8.1 38.9 28.6 8.8 41.2 31.4 Don’t know 0.7 0.4 0.5 0.6 0.2 0.3 Total 100.0 100.0 100.0 100.0 100.0 100.0 Water treatment prior to drinking3 Boiled 9.4 3.9 5.8 8.9 4.0 5.5 Bleach/chlorine added 10.7 7.2 8.4 11.3 7.3 8.5 Strained through cloth 0.1 0.3 0.2 0.1 0.3 0.2 Ceramic, sand or other filter 0.5 0.2 0.3 0.5 0.3 0.3 Let it stand and settle 0.1 1.1 0.8 0.1 1.0 0.8 Other 0.1 0.1 0.1 0.1 0.1 0.1 No treatment 80.4 88.0 85.5 80.3 88.0 85.6 Percentage using an appropriate treatment method4 19.3 10.7 13.6 19.4 10.8 13.4 Number 3,531 7,003 10,534 13,034 29,856 42,890 1 Because the quality of bottled water is not known, households using bottled water for drinking are classified as using an improved or unimproved source according to their water source for cooking and handwashing. 2 Includes water piped to neighbour 3 Respondents may report multiple treatment methods, so the sum of treatment may exceed 100 percent. 4 Appropriate water treatment methods include boiling, bleaching, filtering, and solar disinfecting. 20 • Housing Characteristics and Household Population Table 2.2 Availability of water Among households and de jure population using piped water or water from a tube well or borehole, percentage with lack of availability of water in the last 2 weeks, according to residence, Zimbabwe 2015 Availability of water in last 2 weeks Households Population Urban Rural Total Urban Rural Total Not available for at least one day 40.0 17.1 28.0 40.7 17.6 27.9 Available with no interruption of at least one day 59.1 82.7 71.5 58.6 82.2 71.7 Don’t know 0.9 0.2 0.5 0.7 0.2 0.4 Total 100.0 100.0 100.0 100.0 100.0 100.0 Number using piped water or water from a tube well1 3,002 3,321 6,324 11,025 13,723 24,748 1 Households reporting piped water or water from a tube well or borehole as their main source of drinking water. Households reporting bottled water as their main source of drinking water are also included 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 Household sanitation facilities Percent distribution of households and de jure population by type and location of toilet/latrine facilities, according to residence, Zimbabwe 2015 Type and location of toilet/latrine facility Households Population Urban Rural Total Urban Rural Total Improved facility 46.4 32.2 37.0 52.3 34.5 39.9 Flush/pour flush to piped sewer system 35.6 0.7 12.4 40.3 0.8 12.8 Flush/pour flush to septic tank 6.6 1.5 3.2 7.6 1.3 3.2 Flush/pour flush to pit latrine 1.0 0.1 0.4 0.9 0.2 0.4 Ventilated improved pit (VIP) latrine 0.6 11.9 8.1 0.8 12.3 8.8 Pit latrine with slab 2.6 17.9 12.8 2.7 19.8 14.6 Shared facility1 48.8 20.1 29.8 43.3 16.6 24.7 Flush/pour flush to piped sewer system 39.5 0.6 13.7 35.3 0.5 11.1 Flush/pour flush to septic tank 4.7 0.6 2.0 3.8 0.5 1.5 Flush/pour flush to pit latrine 1.4 0.2 0.6 1.4 0.2 0.5 Ventilated improved pit (VIP) latrine 0.3 7.1 4.8 0.2 5.5 3.9 Pit latrine with slab 2.9 11.6 8.7 2.6 9.9 7.7 Unimproved facility 4.7 47.6 33.2 4.4 49.0 35.5 Flush/pour flush not to sewer/septic tank/pit latrine 1.2 0.1 0.5 1.0 0.1 0.4 Pit latrine without slab/open pit 1.9 13.5 9.6 1.8 14.4 10.6 Bucket 0.7 0.0 0.3 0.8 0.0 0.3 No facility/bush/field 0.8 33.8 22.7 0.6 34.4 24.1 Other 0.1 0.1 0.1 0.2 0.1 0.1 Total 100.0 100.0 100.0 100.0 100.0 100.0 Number 3,531 7,003 10,534 13,034 29,856 42,890 Location of toilet facility In own dwelling 65.4 6.9 32.1 66.0 6.8 30.4 In own yard/plot 31.1 79.0 58.4 30.7 81.2 61.1 Elsewhere 3.4 14.2 9.6 3.2 12.0 8.5 Total 100.0 100.0 100.0 100.0 100.0 100.0 Number of households/population with a toilet/latrine facility 3,504 4,637 8,141 12,960 19,583 32,543 1 Facilities that would be considered improved if they were not shared by two or more households. 22 • Housing Characteristics and Household Population Table 2.4 Household characteristics Percent distribution of households by housing characteristics, percentage using solid fuel for cooking, and percent distribution by frequency of smoking in the home, according to residence, Zimbabwe 2015 Residence Total Housing characteristic Urban Rural Electricity Yes 81.2 9.7 33.7 No 18.8 90.3 66.3 Total 100.0 100.0 100.0 Flooring material Earth/sand 1.1 21.7 14.8 Dung 0.2 15.5 10.4 Wood planks 1.1 0.0 0.4 Parquet or polished wood 1.4 0.0 0.5 Vinyl or asphalt strips 0.2 0.0 0.1 Ceramic tiles 13.8 0.9 5.2 Cement 79.2 61.4 67.4 Carpet 2.5 0.2 1.0 Other 0.5 0.1 0.2 Total 100.0 100.0 100.0 Rooms used for sleeping One 41.0 33.4 35.9 Two 33.0 37.8 36.2 Three or more 25.9 28.8 27.9 Total 100.0 100.0 100.0 Place for cooking In the house 80.2 28.0 45.5 In a separate building 3.1 56.5 38.6 Outdoors 16.6 15.3 15.7 No food cooked in household 0.1 0.1 0.1 Other 0.0 0.1 0.1 Total 100.0 100.0 100.0 Cooking fuel Electricity 66.3 5.2 25.7 LPG/natural gas/biogas 7.9 0.9 3.3 Kerosene/paraffin 6.5 0.8 2.7 Coal/lignite 0.1 0.0 0.0 Charcoal 0.5 0.1 0.2 Wood 18.4 92.6 67.7 Straw/shrubs/grass 0.0 0.2 0.1 Animal dung 0.0 0.1 0.1 Other 0.0 0.0 0.0 No food cooked in household 0.1 0.1 0.1 Total 100.0 100.0 100.0 Percentage using solid fuel for cooking1 19.1 93.0 68.2 Frequency of smoking in the home Daily 6.0 13.3 10.8 Weekly 2.8 5.0 4.3 Monthly 1.1 2.3 1.9 Less than once a month 1.6 2.5 2.2 Never 88.5 76.9 80.8 Total 100.0 100.0 100.0 Number 3,531 7,003 10,534 LPG = Liquefied petroleum gas 1 Includes coal/lignite, charcoal, wood, straw/shrubs/grass, and animal dung Housing Characteristics and Household Population • 23 Table 2.5 Wealth quintiles Percent distribution of the de jure population by wealth quintiles, and the Gini coefficient, according to residence and province, Zimbabwe 2015 Wealth quintile Total Number of persons Gini coefficient Residence/province Lowest Second Middle Fourth Highest Residence Urban 0.0 0.0 0.0 39.7 60.3 100.0 13,034 0.19 Rural 28.7 28.7 28.7 11.4 2.4 100.0 29,856 0.33 Province Manicaland 20.5 25.2 30.0 17.1 7.2 100.0 6,168 0.36 Mashonaland Central 28.7 28.7 26.0 12.3 4.2 100.0 4,139 0.38 Mashonaland East 12.3 26.1 32.3 19.4 10.0 100.0 4,367 0.31 Mashonaland West 23.1 22.8 18.7 20.1 15.3 100.0 5,117 0.40 Matabeleland North 44.3 27.5 14.5 7.8 5.8 100.0 2,248 0.49 Matabeleland South 21.1 25.5 28.6 16.9 7.8 100.0 2,086 0.42 Midlands 24.9 21.6 19.8 18.4 15.3 100.0 5,388 0.42 Masvingo 30.7 22.3 22.1 10.6 14.3 100.0 5,290 0.44 Harare 0.0 0.5 2.0 39.6 57.9 100.0 6,095 0.08 Bulawayo 0.0 0.0 0.0 32.7 67.3 100.0 1,992 0.19 Total 20.0 20.0 20.0 20.0 20.0 100.0 42,890 0.38 24 • Housing Characteristics and Household Population Table 2.6 Household possessions Percentage of households possessing various household effects, means of transportation, agricultural land, and livestock/farm animals by residence, Zimbabwe 2015 Residence Total Possession Urban Rural Household effects Radio 44.3 42.0 42.8 Television 73.4 19.2 37.4 Mobile phone 96.5 82.1 86.9 Computer 24.1 3.2 10.2 Non-mobile telephone 8.5 0.6 3.3 Refrigerator 61.0 6.6 24.8 Means of transport Bicycle 17.4 26.2 23.2 Animal drawn cart 10.0 26.0 20.7 Motorcycle/scooter 1.6 1.7 1.7 Car/truck 25.9 5.3 12.2 Boat with a motor 0.8 0.3 0.5 Ownership of agricultural land 30.8 81.5 64.5 Ownership of farm animals1 37.0 80.9 66.2 Number 3,531 7,003 10,534 1 Cattle, horses, donkeys, mules, goats, sheep, chickens or other poultry, rabbits, and pigs Housing Characteristics and Household Population • 25 Table 2.7 Hand washing Percentage of households in which the place most often used for washing hands was observed, and among households in which the place for hand washing was observed, percent distribution by availability of water, soap and other cleansing agents, Zimbabwe 2015 Percentage of households in which place for washing hands was observed1 Number of households Among households where place for hand washing was observed, percentage with: Number of households with place for hand washing observed Background characteristic Soap and water2 Water and cleansing agent3 other than soap only Water only Soap but no water4 Cleansing agent other than soap only3 No water, no soap, no other cleansing agent Total Residence Urban 96.4 3,531 49.8 0.2 30.1 4.6 0.1 15.3 100.0 3,404 Rural 98.0 7,003 32.9 1.5 39.6 4.2 0.6 21.3 100.0 6,863 Province Manicaland 99.5 1,484 32.2 0.9 52.7 2.7 0.2 11.3 100.0 1,477 Mashonaland Central 98.5 952 56.8 1.3 23.6 3.8 0.0 14.6 100.0 938 Mashonaland East 98.3 1,171 40.8 0.5 46.2 4.6 0.4 7.5 100.0 1,151 Mashonaland West 98.9 1,209 53.3 0.7 33.1 2.7 0.4 9.8 100.0 1,195 Matabeleland North 99.4 527 27.0 4.6 35.2 5.2 0.1 27.8 100.0 524 Matabeleland South 94.3 530 28.6 2.1 45.5 1.4 0.3 22.1 100.0 500 Midlands 98.5 1,271 24.7 1.2 21.0 5.5 1.6 46.1 100.0 1,251 Masvingo 96.9 1,244 26.7 1.4 40.0 5.9 0.4 25.7 100.0 1,205 Harare 92.7 1,604 37.9 0.2 34.6 6.8 0.1 20.4 100.0 1,486 Bulawayo 99.2 542 66.5 0.0 26.5 1.2 0.0 5.7 100.0 538 Wealth quintile Lowest 98.4 1,996 25.0 2.2 41.5 4.8 1.1 25.5 100.0 1,965 Second 97.6 1,983 31.5 1.7 39.3 4.4 0.6 22.4 100.0 1,934 Middle 97.9 2,000 33.8 1.0 41.3 3.7 0.1 20.2 100.0 1,957 Fourth 96.4 2,398 39.3 0.5 36.5 4.2 0.2 19.3 100.0 2,312 Highest 97.2 2,158 61.0 0.1 24.4 4.5 0.1 10.0 100.0 2,097 Total 97.5 10,534 38.5 1.1 36.4 4.3 0.4 19.3 100.0 10,266 1 Includes fixed and mobile place 2 Soap includes soap or detergent in bar, liquid, powder or paste form. This column includes households with soap and water only, as well as those that had soap and water and another cleansing agent. 3 Cleansing agents other than soap include locally available materials such as ash, mud or sand 4 Includes households with soap only as well as those with soap and another cleansing agent 26 • Housing Characteristics and Household Population Table 2.8 Household population by age, sex, and residence Percent distribution of the de facto household population by age groups, according to sex and residence, Zimbabwe 2015 Urban Rural Male Female Total Age Male Female Total Male Female Total <5 15.1 14.1 14.5 16.6 15.7 16.1 16.1 15.2 15.6 5-9 12.7 10.8 11.7 16.6 14.3 15.4 15.4 13.2 14.3 10-14 10.5 10.0 10.2 16.0 13.8 14.8 14.3 12.6 13.4 15-19 9.3 10.2 9.8 11.8 9.7 10.7 11.1 9.9 10.4 20-24 9.0 10.7 9.9 6.6 7.0 6.8 7.3 8.2 7.8 25-29 8.5 9.8 9.2 5.3 6.4 5.9 6.3 7.5 6.9 30-34 8.8 9.7 9.3 5.1 6.1 5.6 6.2 7.2 6.7 35-39 7.2 7.4 7.3 4.2 5.3 4.8 5.1 6.0 5.6 40-44 6.1 4.8 5.4 3.7 4.0 3.8 4.4 4.2 4.3 45-49 4.1 2.8 3.4 2.7 2.5 2.6 3.1 2.6 2.9 50-54 2.3 3.3 2.8 1.9 3.3 2.6 2.0 3.3 2.7 55-59 2.5 2.2 2.4 2.3 3.2 2.8 2.3 2.9 2.6 60-64 2.0 1.5 1.7 1.9 2.5 2.2 2.0 2.2 2.1 65-69 1.0 1.1 1.0 1.6 2.1 1.8 1.4 1.8 1.6 70-74 0.4 0.6 0.5 1.1 1.4 1.3 0.9 1.2 1.0 75-79 0.5 0.4 0.4 1.1 1.1 1.1 0.9 0.8 0.9 80 + 0.4 0.5 0.4 1.3 1.8 1.6 1.0 1.4 1.2 Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 Dependency age groups 0-14 38.2 34.9 36.4 49.1 43.7 46.3 45.9 41.0 43.3 15-64 59.6 62.5 61.2 45.7 49.9 47.9 49.8 53.9 52.0 65+ 2.2 2.6 2.4 5.2 6.3 5.8 4.3 5.1 4.7 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 43.5 40.9 42.1 57.1 50.2 53.5 53.0 47.2 50.0 18+ 56.5 59.1 57.9 42.9 49.8 46.5 47.0 52.8 50.0 Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 Number of persons 6,011 7,077 13,088 14,170 15,328 29,498 20,181 22,404 42,586 Housing Characteristics and Household Population • 27 Table 2.9 Household composition Percent distribution of households by sex of head of household and by household size; mean size of households; and percentage of households with orphans and foster children under age 18, according to residence, Zimbabwe 2015 Residence Total Characteristic Urban Rural Household headship Male 61.7 58.3 59.4 Female 38.3 41.7 40.6 Total 100.0 100.0 100.0 Number of usual members 0 0.1 0.1 0.1 1 14.5 11.3 12.4 2 15.4 12.4 13.4 3 19.6 16.7 17.7 4 18.6 18.1 18.3 5 15.3 15.5 15.4 6 8.6 10.6 9.9 7 4.5 6.4 5.8 8 2.1 3.8 3.2 9+ 1.4 5.0 3.8 Total 100.0 100.0 100.0 Mean size of households 3.7 4.3 4.1 Percentage of households with orphans and foster children under 18 years of age Double orphans 2.9 6.2 5.1 Single orphans1 10.5 18.4 15.8 Foster children2 20.9 36.3 31.2 Foster and/or orphan children 24.7 40.8 35.4 Number of households 3,531 7,003 10,534 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. 28 • Housing Characteristics and Household Population Table 2.10 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, Zimbabwe 2015 Children whose births are registered Number of children Background characteristic Percentage who had a birth certificate Percentage who did not have birth certificate Percentage registered Age <2 25.3 11.7 37.0 2,425 2-4 37.8 9.4 47.2 4,190 Sex Male 33.1 9.7 42.8 3,224 Female 33.4 10.7 44.1 3,390 Residence Urban 57.2 9.5 66.7 1,876 Rural 23.8 10.5 34.3 4,739 Province Manicaland 24.5 2.6 27.2 1,026 Mashonaland Central 26.2 24.6 50.8 631 Mashonaland East 33.5 12.7 46.1 613 Mashonaland West 25.2 18.9 44.2 839 Matabeleland North 34.9 8.6 43.5 341 Matabeleland South 30.2 10.3 40.5 310 Midlands 28.5 3.7 32.2 874 Masvingo 30.8 4.7 35.6 849 Harare 55.4 12.6 68.0 870 Bulawayo 61.1 5.3 66.4 260 Wealth quintile Lowest 13.4 10.8 24.2 1,581 Second 19.5 11.4 30.9 1,378 Middle 29.2 10.2 39.4 1,211 Fourth 42.2 12.1 54.3 1,384 Highest 73.6 5.4 79.0 1,060 Total 33.2 10.2 43.5 6,614 Housing Characteristics and Household Population • 29 Table 2.11 Children’s living arrangements and orphanhood Percent distribution of de jure children under age 18 by living arrangements and survival status of parents, the percentage of children not living with a biological parent, and the percentage of children with one or both parents dead, according to background characteristics, Zimbabwe 2015 Living with both parents Living with mother but not with father Living with father but not with mother Not living with either parent Missing informa- tion on father/ mother 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 Age 0-4 55.6 26.3 1.7 1.2 0.1 11.9 0.5 0.9 0.3 1.5 100.0 13.6 3.6 6,614 <2 61.1 31.5 1.5 0.4 0.0 4.3 0.1 0.2 0.0 0.8 100.0 4.6 1.9 2,425 2-4 52.4 23.3 1.9 1.6 0.2 16.3 0.8 1.3 0.4 1.8 100.0 18.7 4.6 4,190 5-9 43.5 20.4 3.7 2.6 0.5 19.2 1.7 4.1 1.2 3.0 100.0 26.2 11.5 6,074 10-14 35.4 16.5 6.7 3.3 1.7 17.9 2.8 6.6 5.3 3.8 100.0 32.5 23.9 5,714 15-17 26.5 12.4 8.6 2.7 1.7 20.6 4.3 9.7 9.8 3.7 100.0 44.4 34.8 2,815 Sex Male 42.2 20.4 4.7 2.7 0.8 16.6 2.0 4.3 3.3 2.8 100.0 26.3 15.7 10,689 Female 43.4 19.8 4.3 2.0 0.9 16.9 1.9 4.7 3.0 2.9 100.0 26.5 15.3 10,528 Residence Urban 51.8 20.0 3.7 2.9 1.0 12.7 1.7 2.7 2.1 1.4 100.0 19.2 11.5 5,430 Rural 39.7 20.2 4.8 2.2 0.9 18.1 2.0 5.2 3.5 3.4 100.0 28.8 16.9 15,788 Province Manicaland 38.3 22.3 6.4 2.4 1.0 17.5 2.1 5.2 2.9 1.9 100.0 27.7 18.1 3,284 Mashonaland Central 54.4 13.6 3.8 2.0 0.9 14.9 1.9 4.0 2.5 1.9 100.0 23.4 13.4 2,108 Mashonaland East 42.8 20.5 4.1 2.9 1.7 15.2 1.3 4.9 3.3 3.3 100.0 24.8 15.9 2,115 Mashonaland West 49.3 15.9 5.2 3.1 0.7 13.8 2.3 3.6 3.9 2.2 100.0 23.5 15.9 2,568 Matabeleland North 34.7 21.1 3.8 2.2 0.5 20.3 1.7 6.1 4.4 5.1 100.0 32.5 17.3 1,181 Matabeleland South 20.1 24.9 4.9 2.0 0.6 27.2 2.5 7.5 3.4 7.0 100.0 40.6 19.6 1,088 Midlands 42.8 20.5 4.6 2.2 0.7 17.0 2.0 4.0 2.8 3.5 100.0 25.8 14.4 2,749 Masvingo 33.9 24.7 4.0 2.2 0.7 19.6 2.0 5.7 3.7 3.5 100.0 30.9 16.6 2,836 Harare 59.1 17.1 3.3 2.1 1.0 10.7 1.6 1.8 2.3 1.0 100.0 16.4 10.2 2,460 Bulawayo 35.0 24.5 4.5 2.8 0.4 20.2 2.6 4.9 2.6 2.4 100.0 30.3 16.1 829 Wealth quintile Lowest 43.6 21.7 7.3 1.4 0.9 12.6 1.7 4.0 3.4 3.4 100.0 21.7 17.8 4,828 Second 40.2 20.2 3.8 1.9 0.6 18.4 2.4 5.4 3.5 3.6 100.0 29.6 16.2 4,653 Middle 34.5 18.5 4.5 2.2 1.0 23.3 1.9 6.8 3.7 3.5 100.0 35.7 18.4 4,439 Fourth 47.0 22.0 3.5 3.0 0.9 14.0 2.0 3.1 2.7 1.9 100.0 21.7 12.5 3,862 Highest 51.3 17.8 2.9 3.9 1.1 15.0 1.8 2.7 2.2 1.2 100.0 21.8 11.0 3,436 Total <15 45.3 21.3 3.9 2.3 0.8 16.2 1.6 3.7 2.1 2.7 100.0 23.6 12.5 18,402 Total <18 42.8 20.1 4.5 2.4 0.9 16.7 2.0 4.5 3.2 2.9 100.0 26.4 15.5 21,218 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. 30 • Housing Characteristics and Household Population Table 2.12 School attendance by survivorship of parents For de jure children age 10-14, the percentage attending school by parental survival, and the ratio of the percentage attending, by parental survival, according to background characteristics, Zimbabwe 2015 Percentage attending school by survivorship of parents Ratio1 Background characteristic Both parents deceased Number of children Both parents alive and living with at least one parent Number of children Sex Male 90.6 166 95.7 1,614 0.95 Female 93.6 137 97.1 1,542 0.96 Residence Urban 89.0 50 98.5 877 0.90 Rural 92.5 253 95.5 2,279 0.97 Province Manicaland (81.4) 42 96.9 484 (0.84) Mashonaland Central * 22 95.4 354 * Mashonaland East (96.0) 36 97.0 345 (0.99) Mashonaland West (92.7) 45 97.2 395 (0.95) Matabeleland North (90.6) 24 95.0 158 (0.95) Matabeleland South (92.7) 16 93.6 118 (0.99) Midlands (97.2) 35 96.7 391 (1.01) Masvingo (97.6) 47 93.9 390 (1.04) Harare * 29 97.6 411 * Bulawayo * 6 99.1 110 * Wealth quintile Lowest 91.8 79 91.9 690 1.00 Second 89.1 73 95.1 680 0.94 Middle 95.7 78 98.4 600 0.97 Fourth (87.4) 40 97.4 584 (0.90) Highest (95.2) 33 99.8 602 (0.95) Total 91.9 303 96.3 3,156 0.95 Notes: Table is based 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 attending school for children with both parents deceased to the percentage attending school with both parents alive and living with at least one parent Housing Characteristics and Household Population • 31 Table 2.13.1 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, Zimbabwe 2015 Background characteristic No education Some primary Completed primary1 Some secondary Completed secondary2 More than secondary Don’t know/ missing Total Number Median years completed Age 6-9 21.6 78.2 0.0 0.1 0.0 0.0 0.1 100.0 2,278 0.2 10-14 0.7 77.4 7.6 14.3 0.0 0.0 0.0 100.0 2,824 4.4 15-19 0.5 10.9 11.4 75.4 1.0 0.7 0.2 100.0 2,212 8.4 20-24 1.1 9.5 12.9 65.4 3.6 6.8 0.6 100.0 1,830 9.9 25-29 0.9 10.1 15.5 62.1 2.4 8.8 0.1 100.0 1,674 9.7 30-34 1.5 8.6 16.7 60.6 1.9 10.4 0.4 100.0 1,616 10.0 35-39 2.5 11.6 17.4 57.5 1.1 9.3 0.5 100.0 1,345 9.2 40-44 3.6 13.2 16.1 55.8 0.8 9.6 0.9 100.0 946 8.8 45-49 5.3 19.3 12.5 52.4 1.0 8.5 0.8 100.0 583 8.7 50-54 19.6 29.0 21.1 20.8 0.3 7.8 1.4 100.0 739 6.0 55-59 26.4 33.1 19.9 14.0 0.5 4.4 1.8 100.0 648 4.4 60-64 24.6 38.4 19.0 12.4 0.3 3.7 1.6 100.0 485 4.0 65+ 38.1 42.8 9.0 5.8 0.2 1.4 2.7 100.0 1,152 1.8 Residence Urban 3.0 20.9 7.4 54.0 2.7 11.3 0.7 100.0 5,894 9.7 Rural 11.1 39.9 14.0 32.8 0.3 1.4 0.5 100.0 12,436 5.8 Province Manicaland 12.1 37.6 13.6 33.2 0.7 2.4 0.5 100.0 2,529 6.0 Mashonaland Central 11.9 43.4 12.8 29.5 0.1 2.2 0.2 100.0 1,674 5.3 Mashonaland East 9.2 34.9 13.7 37.8 0.7 2.6 1.1 100.0 1,916 6.3 Mashonaland West 8.4 35.5 10.9 39.8 0.4 4.1 0.9 100.0 2,092 6.4 Matabeleland North 9.0 40.2 18.0 30.5 0.3 1.8 0.2 100.0 935 6.0 Matabeleland South 9.0 37.5 15.7 34.0 1.1 2.4 0.4 100.0 909 6.2 Midlands 7.7 33.2 12.9 41.4 0.7 3.8 0.3 100.0 2,285 6.6 Masvingo 10.6 37.5 10.0 37.0 0.6 3.8 0.5 100.0 2,337 6.1 Harare 2.6 20.2 7.4 55.0 3.3 10.5 1.0 100.0 2,712 9.8 Bulawayo 3.5 21.6 8.8 51.5 3.0 11.5 0.1 100.0 940 9.5 Wealth quintile Lowest 16.3 44.6 14.8 24.0 0.0 0.1 0.2 100.0 3,497 4.7 Second 11.9 42.2 14.0 31.1 0.1 0.1 0.6 100.0 3,589 5.5 Middle 8.9 38.2 14.5 36.6 0.3 0.8 0.7 100.0 3,630 6.1 Fourth 4.1 26.5 10.3 53.1 1.0 4.3 0.6 100.0 3,665 8.3 Highest 2.1 19.1 6.4 51.6 3.7 16.4 0.7 100.0 3,949 10.1 Total 8.5 33.8 11.9 39.7 1.1 4.6 0.6 100.0 18,330 6.5 1 Completed grade 7 at the primary level 2 Completed grade 6 at the secondary level 32 • Housing Characteristics and Household Population Table 2.13.2 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, Zimbabwe 2015 Background characteristic No education Some primary Completed primary1 Some secondary Completed secondary2 More than secondary Don’t know/ missing Total Number Median years completed Age 6-9 25.1 74.8 0.0 0.1 0.0 0.0 0.0 100.0 2,369 0.0 10-14 1.1 82.8 6.0 9.9 0.0 0.1 0.1 100.0 2,895 4.1 15-19 0.4 15.9 12.9 68.8 1.0 0.7 0.3 100.0 2,237 8.1 20-24 0.4 9.8 10.9 65.1 5.3 8.0 0.5 100.0 1,480 10.1 25-29 0.5 8.7 12.8 59.7 5.8 12.2 0.3 100.0 1,264 10.2 30-34 0.5 7.1 12.7 61.6 4.2 13.3 0.6 100.0 1,252 10.3 35-39 0.2 7.9 11.8 62.3 2.1 15.3 0.5 100.0 1,033 10.3 40-44 1.7 7.7 12.6 58.9 3.8 14.2 1.3 100.0 889 10.3 45-49 1.1 7.4 10.7 59.0 2.4 17.3 2.0 100.0 633 10.3 50-54 6.3 16.4 15.5 44.6 1.0 15.3 0.9 100.0 404 8.9 55-59 9.1 30.0 21.9 26.5 1.9 8.7 1.9 100.0 473 6.5 60-64 9.5 34.6 22.7 23.9 0.2 6.4 2.7 100.0 394 6.2 65+ 18.1 43.9 16.6 13.5 0.6 4.8 2.4 100.0 863 4.4 Residence Urban 2.5 22.2 4.7 49.9 4.7 15.3 0.7 100.0 4,925 10.1 Rural 7.3 41.7 12.5 34.8 0.8 2.4 0.6 100.0 11,261 6.1 Province Manicaland 7.3 40.0 9.8 37.7 1.2 3.3 0.7 100.0 2,346 6.2 Mashonaland Central 8.1 41.8 10.4 35.6 0.9 3.1 0.1 100.0 1,596 6.0 Mashonaland East 6.3 33.3 12.7 40.9 1.3 4.5 1.0 100.0 1,690 6.7 Mashonaland West 4.8 35.7 11.8 39.5 1.2 6.1 0.8 100.0 1,980 6.7 Matabeleland North 5.7 44.5 20.3 25.7 1.0 2.4 0.3 100.0 827 5.9 Matabeleland South 7.6 44.0 14.0 29.9 1.2 2.7 0.7 100.0 793 5.7 Midlands 4.9 37.7 10.6 39.3 1.9 5.1 0.6 100.0 1,965 6.6 Masvingo 8.5 41.9 8.2 35.1 1.3 4.9 0.2 100.0 1,910 5.9 Harare 2.1 20.7 4.6 51.3 5.1 15.1 1.0 100.0 2,325 10.2 Bulawayo 3.5 23.6 6.8 48.0 3.4 14.7 0.1 100.0 754 9.7 Wealth quintile Lowest 11.1 50.7 13.7 23.8 0.2 0.2 0.3 100.0 2,919 4.6 Second 8.4 42.4 13.4 34.6 0.4 0.3 0.6 100.0 3,207 5.9 Middle 5.3 40.6 12.2 39.1 0.7 1.5 0.6 100.0 3,420 6.3 Fourth 3.4 25.6 8.4 51.6 2.8 7.4 0.8 100.0 3,237 8.9 Highest 1.6 21.6 3.9 45.9 5.3 21.1 0.6 100.0 3,404 10.3 Total 5.8 35.8 10.2 39.4 1.9 6.3 0.6 100.0 16,186 6.7 1 Completed grade 7 at the primary level 2 Completed grade 6 at the secondary level Housing Characteristics and Household Population • 33 Table 2.14 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, Zimbabwe 2015 Net attendance ratio1 Gross attendance ratio2 Background characteristic Male Female Total Gender Parity Index3 Male Female Total Gender Parity Index3 PRIMARY SCHOOL Residence Urban 93.1 92.3 92.7 0.99 107.8 104.3 106.0 0.97 Rural 89.9 91.0 90.5 1.01 111.4 106.4 109.0 0.95 Province Manicaland 89.1 91.4 90.1 1.03 110.7 111.6 111.1 1.01 Mashonaland Central 91.9 91.9 91.9 1.00 113.6 105.7 109.6 0.93 Mashonaland East 90.4 90.6 90.5 1.00 105.6 103.5 104.6 0.98 Mashonaland West 90.2 91.2 90.7 1.01 108.7 104.6 106.7 0.96 Matabeleland North 93.3 92.2 92.8 0.99 113.1 108.5 110.8 0.96 Matabeleland South 89.9 89.4 89.7 1.00 107.2 99.1 103.3 0.92 Midlands 90.9 92.2 91.6 1.01 114.5 110.0 112.3 0.96 Masvingo 88.4 90.6 89.5 1.02 112.1 103.6 107.8 0.92 Harare 93.9 91.4 92.6 0.97 106.3 100.7 103.4 0.95 Bulawayo 92.5 93.9 93.2 1.02 116.6 111.8 114.1 0.96 Wealth quintile Lowest 87.1 89.5 88.2 1.03 109.8 106.0 108.0 0.97 Second 89.5 91.0 90.2 1.02 111.0 107.8 109.4 0.97 Middle 91.7 91.7 91.7 1.00 113.8 106.8 110.4 0.94 Fourth 91.0 92.4 91.7 1.02 105.0 104.5 104.7 1.00 Highest 95.7 92.9 94.3 0.97 112.1 103.3 107.7 0.92 Total 90.7 91.4 91.0 1.01 110.6 105.9 108.3 0.96 SECONDARY SCHOOL Residence Urban 68.9 59.4 63.5 0.86 82.0 69.2 74.8 0.84 Rural 43.7 47.3 45.4 1.08 49.8 53.7 51.6 1.08 Province Manicaland 45.6 45.5 45.5 1.00 53.1 47.6 50.5 0.90 Mashonaland Central 42.8 41.5 42.2 0.97 47.0 45.5 46.3 0.97 Mashonaland East 54.5 50.0 52.2 0.92 61.7 59.0 60.3 0.96 Mashonaland West 52.0 53.2 52.5 1.02 59.4 61.8 60.5 1.04 Matabeleland North 35.3 48.8 41.9 1.38 40.8 56.2 48.3 1.38 Matabeleland South 32.9 45.8 38.8 1.39 36.0 53.5 44.0 1.49 Midlands 49.6 49.3 49.4 0.99 55.6 54.6 55.1 0.98 Masvingo 47.0 60.4 53.4 1.29 54.2 72.1 62.6 1.33 Harare 68.6 57.4 62.4 0.84 83.9 68.3 75.2 0.81 Bulawayo 67.7 54.3 60.1 0.80 84.9 64.3 73.1 0.76 Wealth quintile Lowest 30.6 35.4 33.0 1.16 33.4 37.3 35.4 1.11 Second 43.1 43.7 43.4 1.01 49.0 50.9 49.9 1.04 Middle 45.5 52.8 48.8 1.16 52.2 58.6 55.1 1.12 Fourth 57.6 55.7 56.6 0.97 67.0 64.2 65.6 0.96 Highest 73.3 64.3 68.4 0.88 87.5 77.1 81.9 0.88 Total 49.7 51.1 50.4 1.03 57.4 58.5 58.0 1.02 1 The NAR for primary school is the percentage of the primary-school age (6-12 years) population that is attending primary school. The NAR for secondary school is the percentage of the secondary-school age (13-18 years) population that is attending secondary school. By definition the NAR cannot exceed 100 percent. 2 The GAR for primary school is the total number of primary school students, expressed as a percentage of the official primary-school- age population. The GAR for secondary school is the total number of secondary school students, expressed as a percentage of the official secondary-school-age population. If there are significant numbers of overage and underage students at a given level of schooling, the GAR can exceed 100 percent. 3 The Gender Parity Index for primary school is the ratio of the primary school NAR (GAR) for females to the NAR (GAR) for males. The Gender Parity Index for secondary school is the ratio of the secondary school NAR (GAR) for females to the NAR (GAR) for males. 34 • Housing Characteristics and Household Population Table 2.15 Age-specific attendance rates of the de facto population 5 to 24 years Percentage of the de facto household population age 5-24 years attending school, by age and sex, Zimbabwe 2015 Age Percent attending N de facto MALE 5 11.4 744 6 45.0 5,634 7 84.3 623 8 95.3 582 9 96.6 600 10 96.7 602 11 97.3 562 12 93.4 592 13 93.6 551 14 87.5 588 15 79.3 505 16 74.8 466 17 64.8 472 18 43.7 434 19 33.5 360 20 20.7 389 21 17.9 311 22 13.8 265 23 12.4 260 24 5.6 255 FEMALE 5 10.2 678 6 50.5 549 7 86.3 598 8 94.0 558 9 97.2 572 10 98.7 574 11 98.8 534 12 98.5 581 13 95.5 565 14 86.4 569 15 79.7 498 16 68.8 488 17 53.9 420 18 34.7 434 19 19.1 372 20 11.3 402 21 10.0 358 22 9.1 326 23 8.8 373 24 5.9 372 Characteristics of Respondents • 35 CHARACTERISTICS OF RESPONDENTS 3 Key Findings  Education: Most adults have at least some secondary education—73 percent of women age 15-49 and 77 percent of men age 15-49 have attended or completed secondary school or higher.  Literacy: Literacy is nearly universal with 94 percent of women and men able to read.  Exposure to mass media: Almost half of women and a third of men do not regularly access mass media.  Employment: Forty-one percent of women and 65 percent of men age 15-49 are currently employed.  Health insurance: Eighty-nine percent of women and 88 percent of men do not have health insurance.  Tobacco use: Ninety-nine percent of women and 83 percent of men age 15-49 reported that they do not use tobacco. his chapter presents information on 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 the use of reproductive health services, contraceptive use, and other health behaviours, as they provide a context for the interpretation of demographic and health indices. 3.1 BASIC CHARACTERISTICS OF SURVEY RESPONDENTS A total of 9,955 women age 15-49 and 8,396 men age 15-54 were interviewed in the 2015 ZDHS (Table 3.1). The distribution of respondents by age shows a similar pattern for men and women. The proportion of respondents in each age group declines with increasing age for both sexes. The majority of respondents are Christians with the highest proportion in the Apostolic Sect (42 percent of women and 32 percent of men). A quarter of women have never married while 45 percent of men report themselves as having never married. Among the 15-49 age group, women are much more likely than men to be either currently or previously married. Fifty-eight percent of women are currently married compared with 49 percent of men. Three percent of women and 1 percent of men are living together (as if married). Nine percent of women are divorced or separated, compared with 4 of men. Four percent of women are widows, while less than 1 percent of men are widowers. The majority of women and men age 15-49 live in the rural areas (62 and 64 percent, respectively). The largest proportions of both women and men live in Harare (18 percent each) and the smallest proportions live in Matabeleland South (4 percent each). T 36 • Characteristics of Respondents 3.2 EDUCATION AND LITERACY Literacy Respondents who attended higher than secondary school are assumed to be literate. All other respondents were given a sentence to read, and they were considered to be literate if they could read all or part of the sentence. Sample: Women and men age 15-49 Education is an important factor which has an influence on an individual’s attitude and outlook on various aspects of life. Educational attainment in Zimbabwe is high (Tables 3.2.1 and 3.2.2). Most adults have at least some secondary education. Seventy-three percent of women and 77 percent of men have attended secondary school or higher, while only 1 percent of both women and men have never attended school (Figure 3.1). Literacy is nearly universal with 94 percent of women and men able to read (Tables 3.3.1 and 3.3.2). Trends: Since 2010-11, the median number of years of schooling completed has changed slightly. In 2010-11, women completed 9.0 years of education compared with 9.1 years in 2015. For men, the median number of years of school was 10.0 in 2010- 11 and 9.8 in 2015. Literacy among women (94 percent) remains constant since 2010-11. For men, literacy has decreased slightly from 96 percent in 2010-11 to 94 percent in 2015. Patterns by background characteristics  Younger respondents are more likely to be educated and to have reached higher levels of education than older respondents. For example, the proportion of women with no education ranges from less than 1 percent among those age 15-19 to 6 percent among those age 45-49 (Tables 3.2.1 and 3.2.2).  Rural respondents are less educated than their urban counterparts. Only 62 percent of rural women have attended secondary school or higher compared with 90 percent of urban women; similarly, 69 percent of rural women have attended secondary school or higher compared with 94 percent of urban men.  Harare and Bulawayo, which are predominantly urban, have the most educated populations with more than 9 in 10 women and men having attended secondary school or higher. Mashonaland Central (55 percent) and Matabeleland North (52 percent) have the lowest proportions of women and men with at least some secondary schooling. Figure 3.1 Education of survey respondents 1 1 26 22 66 67 7 11 Women Men Percent distribution of women and men age 15-49 by highest level of schooling attended or completed More than secondary Secondary Primary No education Characteristics of Respondents • 37  Higher wealth status is associated with greater educational attainment. The proportion of women who have attended secondary school or higher increases from 44 percent in the lowest quintile to 94 percent in the highest (Figure 3.2).  The literacy rate varies from 89 percent among women age 45-49 to 95 percent among women age 15-34. For men the rate varies from 91 percent among those age 15-19 to 96 percent among men age 30-44 (Tables 3.2.1 and 3.2.2).  There is not much variation in literacy by residence or province. Bulawayo and Harare have the highest literacy rates for both women and men while Mashonaland Central has the lowest for women and Matabeleland North for men.  As with educational attainment, literacy correlates positively with increasing wealth. 3.4 EXPOSURE TO MASS MEDIA AND INTERNET USAGE 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 to be regularly exposed to that form of media. Respondents were also asked if and how often they use the Internet. Sample: Women and men age 15-49 Mass media often convey messages on family planning, HIV/AIDS awareness, and other health topics. Radio and television are the most commonly accessed forms of media, although almost half of women and a third of men do not regularly access any mass media. Thirty-five percent of women and 49 percent of men listen to the radio at least once a week. However, significant proportions of women and men do not access any of the three media on a weekly basis; 45 percent of women and 34 percent of men do not access any of the media types at least once a week (Tables 3.4.1 and 3.4.2). Overall, 26 percent of women and 41 percent of men age 15-49 have ever used the internet; 24 percent of women and 38 percent of men have used the internet in the past 12 months (Tables 3.5.1 and 3.5.2). Among women and men who have used the internet in the past 12 months, seven in 10 report that they have used it nearly every day in the past month. Patterns by background characteristics  Urban residents are much more likely to be exposed to all forms of mass media than rural residents (Table 3.4.1 and 3.4.2).  Seventy-nine percent of women with no education report that they are not exposed to any mass media, compared with 15 percent of women with more than a secondary education. A similar pattern is seen among men. Figure 3.2 Education by wealth  44 59 70 84 94 49 65 74 87 97 Lowest Second Middle Fourth Highest Percent distribution by wealth quintile of men and women with secondary education or higher Women Men 38 • Characteristics of Respondents  Media exposure among women and men is also associated with wealth. Thirty-five percent of women in the highest wealth quintile read a newspaper at least once a week, compared with only 3 percent of women in the lowest wealth quintile.  Internet usage is more common in urban areas than rural areas. In urban areas, 48 percent and 71 percent women and men, respectively, have used the internet in the past 12 months compared to 9 percent and 19 percent women and men respectively in the rural areas.  Internet use rises sharply with increasing education and wealth. For example, in the past 12 months, only 1 percent of women with no education have used the internet compared with 86 percent of women with more than secondary education. Similarly, only 2 percent of women in the lowest wealth quintile have used the internet in the past 12 months compared with 57 percent in the highest wealth quintile. 3.5 EMPLOYMENT STATUS Currently employed Respondents who were employed in the seven days before the survey Sample: Women and men age 15-49 Men are more likely to be employed than women; 41 percent of women age 15-49 are currently employed, compared with 65 percent of men age 15-49 (Figures 3.3 and 3.4 and Tables 3.6.1 and 3.6.2). An additional 9 percent of men and 10 percent of women reported working in the past 12 months even though they were not currently employed. Trends: Since 2010-11, current employment levels have improved. Among women, 37 percent were currently employed in 2010-11 compared with 41 percent in 2015; among men, the percentage has increased from 61 percent to 65 percent. Patterns by background characteristics  Employment for women and men generally increases with age (Tables 3.6.1 and 3.6.2).  Currently or formerly married women and men are more likely to be employed compared with those who have never married.  A higher proportion of urban women and men are currently employed than their rural counterparts (Figure 3.5).  The proportion of women and men who are currently employed generally increases with increasing wealth quintile. Figure 3.3 Women’s employment status Figure 3.4 Men’s employment status Currently employed 41% Not currently employed but worked in last 12 months 10% Not employed in last 12 months 49% Percentage of women age 15-49 employed in the past 12 months Currently employed 65% Not currently employed but worked in last 12 months 9% Not employed in last 12 months 26% Percentage of men age 15-49 employed in the past 12 months Characteristics of Respondents • 39 Figure 3.5 Employment status by residence 3.6 OCCUPATION Occupation Categorised as professional/technical/managerial, clerical, sales and services, skilled manual, unskilled manual, domestic service and agriculture Sample: Women and men age 15-49 who were currently employed or had worked in the 12 months before the survey Most women are employed in sales and services (49 percent), followed by agriculture (18 percent). Men age 15-49 are most commonly employed in skilled manual labour (27 percent), agriculture (25 percent), and sales and services (24 percent) (Tables 3.7.1 and 3.7.2). Most women who worked in the past 12 months:  did non-agricultural work (70 percent);  were paid only in cash (78 percent);  were self-employed (56 percent); and  were employed throughout the year (57 percent) (Table 3.8). Trends: The percentage of women employed in the sales and services sector has increased over the last decade, from 31 percent in 2005-06, to 36 percent in 2010-11, to 49 percent in 2015. The percentage of women working in agriculture has decreased over time, from 34 percent in 2005-06, to 21 percent 2010- 11, to 18 percent in 2015. Similarly, the percentage of men engaged in agriculture has decreased from 34 percent in 2005-06, to 29 percent in 2010, to 25 percent in 2015. Patterns by background characteristics  Both urban women and rural women are most likely to be employed in sales and services sector (51 percent and 47 percent, respectively). However, urban women are much less likely than rural women to work in agriculture (3 percent and 32 percent, respectively).  Occupation varies with level of education. More than half of all women and men with more than a secondary education are employed in the professional, technical, and managerial sector compared with less than 1 percent of women with only a primary education. 34 62 52 71 Women Men Rural Urban Percentage of women and men age 15-49 who are currently employed by residence 40 • Characteristics of Respondents  Employed women and men in the lowest wealth quintiles are concentrated in agricultural occupations: between 32 and 39 percent of women and 40 to 43 percent of men in the lowest three wealth quintiles work in agriculture. The percentage of women and men working in the sales and services sector is consistent across all wealth quintiles. Women and men in the highest wealth quintile are most commonly employed in the professional/technical/managerial sector. 3.7 HEALTH INSURANCE COVERAGE The majority of women (89 percent) and men (88 percent) do not have health insurance. The most common source of insurance is through one’s employer (Table 3.9.1 and Table 3.9.2). Trends: The percentage of women who have insurance has increased slightly from 7 percent in 2010-11 to 11 percent in 2015. Similarly, the percentage of men with health insurance has increased from 9 percent in 2010-11 to 12 percent in 2015. 3.8 TOBACCO USE Tobacco use is rare among women age 15-49 with less than 1 percent reporting that they currently smoke cigarettes (Table 3.10.1). Among men age 15-49, 17 percent currently smoke tobacco. Among men who smoke cigarettes, the majority smoke cigarettes on a daily basis (Table 3.10.2). Trends: The percentage of men age 15-49 who do not smoke tobacco has increased from 78 percent in 2010-11 to 82 percent in 2015. Patterns by background characteristics  Among men, tobacco smoking is lowest among those under age 19 where 2 percent are current smokers, and highest among men age 30-34 where 29 percent are current smokers (Table 3.10.2).  Tobacco use among men generally decreases with increasing education levels and wealth.  Among men age 15-54 who smoke cigarettes every day, 38 percent smoke fewer than five cigarettes (<5) per day and 25 percent smoke an average between 5 and 9 cigarettes per day (Table 3.11). Characteristics of Respondents • 41 LIST OF TABLES For detailed information on respondents’ characteristics, 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 Type of employment: Women  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 42 • Characteristics of Respondents Table 3.1 Background characteristics of respondents Percent distribution of women and men age 15-49 by selected background characteristics, Zimbabwe 2015 Women Men Background characteristic Weighted percent Weighted number Unweighted number Weighted percent Weighted number Unweighted number Age 15-19 22.1 2,199 2,156 26.4 2,126 2,065 20-24 17.0 1,697 1,782 16.5 1,330 1,376 25-29 16.6 1,657 1,656 14.3 1,148 1,166 30-34 16.3 1,619 1,591 13.9 1,120 1,104 35-39 12.4 1,236 1,209 11.4 917 932 40-44 9.7 965 966 10.1 809 797 45-49 5.9 582 595 7.4 591 578 Religion Traditional 0.6 64 60 2.6 208 202 Roman Catholic 6.7 666 670 8.0 645 652 Protestant 15.7 1,560 1,618 15.4 1,237 1,204 Pentecostal 25.2 2,506 2,679 17.6 1,413 1,486 Apostolic sect 41.8 4,165 3,829 32.1 2,585 2,432 Other Christian 4.6 461 589 6.1 487 578 Muslim 0.4 38 30 0.7 59 50 None 4.9 489 471 17.4 1,397 1,405 Other 0.1 6 9 0.1 10 9 Marital status Never married 25.2 2,511 2,666 45.1 3,624 3,617 Married 58.7 5,841 5,700 49.1 3,948 3,931 Living together 3.1 310 315 0.8 62 68 Divorced/separated 8.6 855 844 4.4 354 350 Widowed 4.4 438 430 0.7 53 52 Residence Urban 38.5 3,829 4,521 36.1 2,900 3,297 Rural 61.5 6,126 5,434 63.9 5,140 4,721 Province Manicaland 12.7 1,266 1,019 13.3 1,072 852 Mashonaland Central 8.9 882 993 10.0 806 944 Mashonaland East 9.6 952 910 10.0 807 759 Mashonaland West 11.7 1,160 1,054 12.5 1,004 888 Matabeleland North 4.7 465 849 4.6 366 698 Matabeleland South 4.2 419 829 4.2 335 634 Midlands 12.7 1,263 1,062 12.3 986 850 Masvingo 11.9 1,187 1,046 10.5 843 747 Harare 17.9 1,783 1,235 17.6 1,412 954 Bulawayo 5.8 577 958 5.1 409 692 Education No education 1.3 126 106 0.5 38 38 Primary 25.8 2,571 2,385 22.4 1,803 1,726 Secondary 65.6 6,527 6,637 66.5 5,349 5,359 More than secondary 7.3 731 827 10.6 849 895 Wealth quintile Lowest 17.1 1,704 1,499 15.1 1,212 1,121 Second 17.0 1,693 1,452 18.0 1,448 1,294 Middle 17.6 1,748 1,549 19.4 1,558 1,419 Fourth 23.2 2,307 2,558 23.0 1,852 1,993 Highest 25.1 2,503 2,897 24.5 1,970 2,191 Total 15-49 100.0 9,955 9,955 100.0 8,041 8,018 50-54 na na na na 355 378 Total 15-54 na na na na 8,396 8,396 Note: Education categories refer to the highest level of education attended, whether or not that level was completed. na = Not applicable Characteristics of Respondents • 43 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, Zimbabwe 2015 Highest level of schooling Total Median years completed Number of women Background characteristic No education Some primary Completed primary1 Some secondary Completed secondary2 More than secondary Age 15-24 0.3 10.4 11.5 72.1 2.1 3.6 100.0 8.9 3,895 15-19 0.2 11.4 10.5 76.3 1.0 0.8 100.0 8.5 2,199 20-24 0.4 9.1 12.8 66.8 3.5 7.4 100.0 9.9 1,697 25-29 0.9 10.6 16.6 60.2 2.2 9.5 100.0 9.5 1,657 30-34 1.0 8.8 16.8 61.7 1.7 10.0 100.0 9.9 1,619 35-39 1.7 12.0 17.0 58.1 0.8 10.4 100.0 9.3 1,236 40-44 2.6 13.9 17.7 55.9 0.2 9.7 100.0 8.7 965 45-49 6.4 20.4 12.4 51.7 0.8 8.2 100.0 8.5 582 Residence Urban 0.3 2.6 6.8 72.0 3.2 15.1 100.0 10.3 3,829 Rural 1.9 16.7 19.4 58.9 0.6 2.5 100.0 8.0 6,126 Province Manicaland 3.0 15.4 17.9 58.5 1.1 4.2 100.0 8.1 1,266 Mashonaland Central 1.9 25.1 18.3 51.2 0.3 3.2 100.0 7.1 882 Mashonaland East 0.8 10.8 15.8 66.8 1.4 4.5 100.0 8.8 952 Mashonaland West 1.9 15.5 12.7 63.2 0.5 6.3 100.0 8.6 1,160 Matabeleland North 1.2 16.4 26.7 51.5 0.8 3.4 100.0 7.4 465 Matabeleland South 1.0 8.1 20.3 63.8 2.1 4.6 100.0 8.7 419 Midlands 0.7 9.6 18.0 64.5 0.9 6.4 100.0 9.0 1,263 Masvingo 1.6 11.7 14.8 64.8 1.0 6.2 100.0 8.9 1,187 Harare 0.2 2.6 6.1 73.4 4.2 13.5 100.0 10.3 1,783 Bulawayo 0.3 1.3 7.5 70.2 2.7 18.0 100.0 10.4 577 Wealth quintile Lowest 3.5 26.2 26.4 43.8 0.0 0.1 100.0 6.7 1,704 Second 1.4 19.0 20.4 58.5 0.3 0.3 100.0 7.5 1,693 Middle 1.6 11.4 17.3 67.6 0.7 1.4 100.0 8.5 1,748 Fourth 0.4 5.3 9.9 76.6 1.5 6.3 100.0 10.0 2,307 Highest 0.2 1.3 4.8 67.2 4.4 22.2 100.0 10.5 2,503 Total 1.3 11.3 14.5 63.9 1.6 7.3 100.0 9.1 9,955 Note: In Zimbabwe, primary level is referred to as grades 1-7. Secondary level is referred to as forms 1-6. With the primary and secondary levels combined, there is a total of 13 years of schooling. 1 Completed 7th grade at the primary level 2 Completed 6th grade at the secondary level 44 • 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, Zimbabwe 2015 Highest level of schooling Total Median years completed Number of men Background characteristic No education Some primary Completed primary1 Some secondary Completed secondary2 More than secondary Age 15-24 0.3 12.9 11.1 68.9 3.0 3.7 100.0 8.8 3,456 15-19 0.3 14.7 11.8 71.3 1.2 0.6 100.0 8.2 2,126 20-24 0.4 10.1 10.1 64.9 5.9 8.6 100.0 10.1 1,330 25-29 0.4 9.8 13.9 57.0 6.4 12.5 100.0 10.1 1,148 30-34 0.3 7.6 12.8 61.9 3.0 14.5 100.0 10.2 1,120 35-39 0.3 8.0 13.8 57.9 2.0 18.0 100.0 10.2 917 40-44 1.1 8.2 12.2 59.4 2.3 16.8 100.0 10.3 809 45-49 1.1 7.7 10.5 59.7 1.7 19.3 100.0 10.3 591 Residence Urban 0.1 2.2 3.6 65.5 6.6 22.0 100.0 10.6 2,900 Rural 0.7 14.9 16.9 62.1 1.3 4.1 100.0 8.5 5,140 Province Manicaland 0.8 10.0 12.7 68.1 2.1 6.3 100.0 9.2 1,072 Mashonaland Central 0.6 19.8 14.7 58.5 1.5 4.9 100.0 8.3 806 Mashonaland East 1.0 6.7 14.7 69.6 2.3 5.7 100.0 9.5 807 Mashonaland West 0.5 10.5 12.8 63.1 2.6 10.5 100.0 9.4 1,004 Matabeleland North 1.1 17.5 29.8 45.0 2.0 4.6 100.0 6.9 366 Matabeleland South 0.1 15.4 20.2 57.0 1.6 5.7 100.0 8.4 335 Midlands 0.0 13.1 13.5 62.8 2.1 8.4 100.0 9.3 986 Masvingo 1.0 14.2 10.9 61.5 2.6 9.8 100.0 9.2 843 Harare 0.0 1.8 3.8 66.5 6.8 21.0 100.0 10.6 1,412 Bulawayo 0.1 3.0 4.1 63.6 6.4 22.7 100.0 10.5 409 Wealth quintile Lowest 1.3 26.4 23.2 48.1 0.5 0.4 100.0 6.8 1,212 Second 0.6 15.4 19.4 63.3 0.7 0.6 100.0 8.1 1,448 Middle 0.5 11.2 14.7 70.3 1.1 2.1 100.0 8.9 1,558 Fourth 0.1 4.9 7.9 71.9 4.3 10.9 100.0 10.2 1,852 Highest 0.2 1.0 1.9 59.0 7.4 30.5 100.0 10.8 1,970 Total 15-49 0.5 10.3 12.1 63.3 3.2 10.6 100.0 9.8 8,041 50-54 6.0 17.4 16.4 43.2 1.2 15.9 100.0 8.7 355 Total 15-54 0.7 10.6 12.3 62.5 3.1 10.8 100.0 9.8 8,396 Note: In Zimbabwe, primary level is referred to as grades 1-7. Secondary level is referred to as forms 1-6. With the primary and secondary levels combined, there is a total of 13 years of schooling. 1 Completed 7th grade at the primary level 2 Completed 6th grade at the secondary level Characteristics of Respondents • 45 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, Zimbabwe 2015 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 3.6 84.0 6.9 5.3 0.1 0.1 100.0 94.5 3,895 15-19 0.8 85.9 7.5 5.6 0.2 0.1 100.0 94.2 2,199 20-24 7.4 81.5 6.1 4.9 0.1 0.1 100.0 94.9 1,697 25-29 9.5 78.7 7.2 4.4 0.1 0.1 100.0 95.4 1,657 30-34 10.0 79.0 6.1 4.8 0.0 0.0 100.0 95.1 1,619 35-39 10.4 76.8 7.2 5.4 0.0 0.2 100.0 94.3 1,236 40-44 9.7 73.9 10.7 5.6 0.1 0.2 100.0 94.2 965 45-49 8.2 71.3 9.4 10.1 0.0 1.0 100.0 88.9 582 Residence Urban 15.1 78.2 5.1 1.5 0.0 0.0 100.0 98.5 3,829 Rural 2.5 80.6 8.8 7.8 0.1 0.2 100.0 91.8 6,126 Province Manicaland 4.2 79.7 9.6 6.5 0.0 0.0 100.0 93.5 1,266 Mashonaland Central 3.2 76.3 8.1 12.1 0.0 0.2 100.0 87.7 882 Mashonaland East 4.5 82.7 7.8 4.7 0.1 0.2 100.0 95.0 952 Mashonaland West 6.3 79.3 3.9 10.1 0.0 0.4 100.0 89.5 1,160 Matabeleland North 3.4 81.3 8.2 6.6 0.3 0.1 100.0 93.0 465 Matabeleland South 4.6 70.9 14.5 8.1 1.4 0.5 100.0 90.0 419 Midlands 6.4 83.9 6.9 2.6 0.0 0.3 100.0 97.1 1,263 Masvingo 6.2 82.0 7.6 4.2 0.0 0.1 100.0 95.7 1,187 Harare 13.5 79.4 5.2 1.8 0.0 0.0 100.0 98.2 1,783 Bulawayo 18.0 72.1 8.8 1.1 0.0 0.0 100.0 98.9 577 Wealth quintile Lowest 0.1 74.2 12.2 12.8 0.4 0.4 100.0 86.5 1,704 Second 0.3 80.1 10.8 8.6 0.0 0.2 100.0 91.2 1,693 Middle 1.4 87.2 5.9 5.4 0.1 0.1 100.0 94.5 1,748 Fourth 6.3 84.9 6.2 2.5 0.1 0.1 100.0 97.4 2,307 Highest 22.2 73.1 3.8 0.9 0.0 0.1 100.0 99.0 2,503 Total 7.3 79.7 7.4 5.4 0.1 0.2 100.0 94.4 9,955 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 46 • 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, Zimbabwe 2015 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 3.7 76.5 11.9 7.8 0.0 0.0 100.0 92.2 3,456 15-19 0.6 78.7 11.7 8.9 0.1 0.0 100.0 91.0 2,126 20-24 8.6 73.0 12.4 6.0 0.0 0.0 100.0 94.0 1,330 25-29 12.5 70.4 12.1 4.9 0.0 0.2 100.0 95.0 1,148 30-34 14.5 70.9 10.9 3.6 0.0 0.1 100.0 96.3 1,120 35-39 18.0 68.5 8.9 4.4 0.1 0.1 100.0 95.5 917 40-44 16.8 70.0 9.2 3.6 0.3 0.1 100.0 96.0 809 45-49 19.3 70.5 6.1 3.5 0.0 0.5 100.0 95.9 591 Residence Urban 22.0 72.0 4.4 1.4 0.0 0.1 100.0 98.5 2,900 Rural 4.1 73.3 14.3 8.1 0.1 0.1 100.0 91.8 5,140 Province Manicaland 6.3 77.4 11.1 5.1 0.0 0.2 100.0 94.7 1,072 Mashonaland Central 4.9 71.4 14.9 8.7 0.0 0.1 100.0 91.2 806 Mashonaland East 5.7 78.3 11.4 4.6 0.0 0.0 100.0 95.4 807 Mashonaland West 10.5 68.6 14.5 6.3 0.0 0.0 100.0 93.7 1,004 Matabeleland North 4.6 74.7 6.1 14.5 0.0 0.1 100.0 85.4 366 Matabeleland South 5.7 68.5 13.0 11.9 0.9 0.0 100.0 87.2 335 Midlands 8.4 72.4 12.5 6.4 0.0 0.3 100.0 93.3 986 Masvingo 9.8 70.0 13.5 6.7 0.0 0.1 100.0 93.2 843 Harare 21.0 72.6 5.4 0.9 0.1 0.0 100.0 99.0 1,412 Bulawayo 22.7 73.0 2.8 1.2 0.0 0.3 100.0 98.5 409 Wealth quintile Lowest 0.4 66.7 19.8 12.4 0.1 0.5 100.0 86.9 1,212 Second 0.6 74.6 15.8 8.9 0.1 0.0 100.0 91.0 1,448 Middle 2.1 78.5 13.2 6.2 0.0 0.0 100.0 93.8 1,558 Fourth 10.9 79.0 6.9 3.2 0.1 0.0 100.0 96.7 1,852 Highest 30.5 65.2 3.2 1.0 0.0 0.1 100.0 98.9 1,970 Total 15-49 10.6 72.8 10.8 5.7 0.1 0.1 100.0 94.2 8,041 50-54 15.9 63.9 11.7 8.2 0.0 0.3 100.0 91.5 355 Total 15-54 10.8 72.5 10.8 5.8 0.1 0.1 100.0 94.1 8,396 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 • 47 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, Zimbabwe 2015 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 15.2 30.4 31.7 5.0 47.0 2,199 20-24 15.7 34.4 35.5 7.0 43.8 1,697 25-29 14.9 32.7 35.9 6.0 44.3 1,657 30-34 18.2 33.9 37.8 7.1 42.9 1,619 35-39 15.7 29.8 35.7 5.4 45.7 1,236 40-44 17.7 29.0 35.3 6.2 46.7 965 45-49 12.4 26.4 33.8 3.5 48.7 582 Residence Urban 29.8 62.1 37.7 12.6 23.8 3,829 Rural 7.2 12.5 33.3 1.7 58.6 6,126 Province Manicaland 13.3 20.4 38.6 5.7 51.2 1,266 Mashonaland Central 8.4 13.7 41.7 2.3 49.4 882 Mashonaland East 12.4 18.8 44.9 3.6 43.0 952 Mashonaland West 12.8 30.0 42.3 3.0 39.7 1,160 Matabeleland North 8.5 14.1 20.9 1.7 66.7 465 Matabeleland South 9.4 19.8 20.9 2.8 66.3 419 Midlands 11.0 28.3 27.6 3.3 53.1 1,263 Masvingo 9.0 23.6 22.1 2.4 60.2 1,187 Harare 31.6 58.7 40.5 14.7 25.9 1,783 Bulawayo 31.5 70.5 33.3 13.2 20.2 577 Education No education 0.3 5.7 17.7 0.0 79.0 126 Primary 2.3 11.9 30.6 0.5 62.2 2,571 Secondary 17.0 35.8 36.4 6.1 41.3 6,527 More than secondary 56.3 68.0 41.1 24.4 14.8 731 Wealth quintile Lowest 2.8 2.8 23.2 0.3 74.3 1,704 Second 5.4 5.4 32.0 0.7 63.6 1,693 Middle 7.1 11.2 39.9 1.4 53.8 1,748 Fourth 19.1 41.2 38.8 7.0 36.2 2,307 Highest 35.1 74.2 38.2 15.5 15.5 2,503 Total 15.9 31.6 35.0 5.9 45.2 9,955 48 • 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, Zimbabwe 2015 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 16.1 26.3 41.6 5.6 43.1 2,126 20-24 26.9 33.9 51.1 11.6 33.2 1,330 25-29 30.3 33.6 50.3 13.6 32.6 1,148 30-34 31.7 33.1 53.6 13.5 28.8 1,120 35-39 38.0 34.7 48.5 14.2 28.6 917 40-44 37.0 35.9 56.1 16.3 24.7 809 45-49 37.0 36.0 49.6 16.0 30.4 591 Residence Urban 57.6 62.2 53.5 26.1 12.6 2,900 Rural 11.6 15.2 46.3 3.5 45.4 5,140 Province Manicaland 16.2 18.2 51.4 5.5 38.2 1,072 Mashonaland Central 15.5 15.7 60.4 5.0 32.1 806 Mashonaland East 17.5 20.8 56.3 6.5 34.6 807 Mashonaland West 24.7 30.6 55.3 10.0 29.7 1,004 Matabeleland North 12.5 15.3 20.1 3.7 68.0 366 Matabeleland South 16.2 22.6 38.0 6.5 49.1 335 Midlands 22.5 31.6 38.5 8.2 41.7 986 Masvingo 15.2 24.1 26.0 3.3 53.0 843 Harare 61.5 59.9 60.3 27.9 10.1 1,412 Bulawayo 64.1 73.0 56.9 35.9 9.1 409 Education No education (2.4) (13.4) (38.0) (2.4) (59.2) 38 Primary 3.6 10.2 40.7 1.1 54.4 1,803 Secondary 28.8 33.8 51.1 11.5 30.6 5,349 More than secondary 77.8 69.6 52.8 35.8 7.1 849 Wealth quintile Lowest 4.0 3.5 35.6 0.4 61.7 1,212 Second 6.9 8.9 45.1 1.3 49.8 1,448 Middle 10.4 13.1 52.7 2.8 41.7 1,558 Fourth 38.6 41.3 53.4 14.8 22.2 1,852 Highest 63.2 73.5 52.7 30.3 8.5 1,970 Total 15-49 28.2 32.2 48.9 11.7 33.6 8,041 50-54 29.2 35.5 51.8 16.0 34.7 355 Total 15-54 28.3 32.3 49.0 11.8 33.6 8,396 Note: Figures in parentheses are based on 25-49 unweighted cases. Characteristics of Respondents • 49 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, Zimbabwe 2015 Ever used the internet Used the internet in the past 12 months Number Among women 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 Total Number Age 15-19 18.4 16.2 2,199 52.7 26.2 14.3 6.7 100.0 355 20-24 33.7 31.7 1,697 74.0 12.9 8.6 4.5 100.0 538 25-29 31.4 29.5 1,657 76.3 12.9 6.3 4.5 100.0 489 30-34 29.8 27.6 1,619 74.4 11.9 9.0 4.7 100.0 448 35-39 24.9 23.5 1,236 75.5 12.5 7.5 4.5 100.0 290 40-44 20.6 19.2 965 77.7 16.3 3.7 2.3 100.0 185 45-49 17.5 15.5 582 75.3 14.3 8.6 1.8 100.0 91 Residence Urban 50.2 47.5 3,829 75.4 14.2 6.6 3.8 100.0 1,818 Rural 10.8 9.4 6,126 61.0 17.3 14.6 7.1 100.0 579 Province Manicaland 10.8 10.3 1,266 60.8 19.7 15.3 4.2 100.0 130 Mashonaland Central 11.0 9.6 882 49.7 21.8 9.1 19.4 100.0 84 Mashonaland East 22.4 20.6 952 67.9 16.9 8.0 7.2 100.0 196 Mashonaland West 22.3 20.2 1,160 71.8 13.5 12.6 2.1 100.0 234 Matabeleland North 16.9 15.4 465 74.1 9.9 7.6 8.5 100.0 72 Matabeleland South 24.8 22.8 419 73.6 14.0 2.7 9.7 100.0 96 Midlands 21.0 19.4 1,263 68.9 11.9 16.1 3.2 100.0 245 Masvingo 16.4 14.3 1,187 65.6 20.6 11.8 1.9 100.0 170 Harare 50.8 47.9 1,783 77.2 14.5 5.8 2.6 100.0 854 Bulawayo 57.6 54.6 577 75.5 13.2 4.8 6.5 100.0 315 Education No education 1.0 1.0 126 * * * * * 1 Primary 4.7 3.8 2,571 59.9 15.2 16.6 8.3 100.0 98 Secondary 28.0 25.5 6,527 69.0 15.9 9.3 5.8 100.0 1,667 More than secondary 87.3 86.1 731 81.6 12.3 5.2 0.9 100.0 630 Wealth quintile Lowest 2.2 1.6 1,704 (61.0) (21.9) (2.1) (15.0) (100.0) 28 Second 6.2 5.2 1,693 52.6 16.2 24.4 6.8 100.0 88 Middle 11.0 9.3 1,748 60.5 11.3 21.1 7.1 100.0 162 Fourth 32.2 29.7 2,307 71.6 14.3 7.9 6.3 100.0 685 Highest 60.3 57.3 2,503 74.7 15.5 6.6 3.2 100.0 1,434 Total 26.0 24.1 9,955 71.9 15.0 8.5 4.6 100.0 2,396 Notes: 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. 50 • 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, Zimbabwe 2015 Ever used the internet Used the internet in the past 12 months Number Among men who have used the internet in the past 12 months, percentage who, in the past month, used internet: Background characteristic Almost every day At least once a week Less than once a week Not at all Total Number Age 15-19 28.9 26.2 2,126 54.0 24.9 12.7 8.4 100.0 557 20-24 51.8 49.0 1,330 68.9 14.5 7.6 9.0 100.0 652 25-29 45.0 42.8 1,148 72.8 14.6 4.4 8.3 100.0 492 30-34 46.0 42.0 1,120 76.3 12.4 6.1 5.2 100.0 470 35-39 42.6 40.4 917 77.5 13.2 5.4 3.9 100.0 370 40-44 40.2 37.8 809 73.1 15.9 5.5 5.5 100.0 306 45-49 35.4 32.6 591 73.0 15.3 7.5 4.2 100.0 193 Residence Urban 73.9 71.3 2,900 76.3 13.3 4.9 5.5 100.0 2,069 Rural 21.7 18.9 5,140 55.6 22.1 12.4 9.9 100.0 971 Province Manicaland 26.6 23.6 1,072 61.1 24.1 8.6 6.3 100.0 253 Mashonaland Central 19.6 18.1 806 53.7 24.6 13.0 8.7 100.0 146 Mashonaland East 34.2 29.9 807 67.5 18.1 10.1 4.3 100.0 241 Mashonaland West 31.0 29.5 1,004 64.6 21.3 6.9 7.2 100.0 296 Matabeleland North 24.3 22.2 366 59.3 16.4 14.8 9.4 100.0 81 Matabeleland South 34.3 30.7 335 61.2 20.7 6.0 12.1 100.0 103 Midlands 38.0 34.1 986 67.2 18.7 6.4 7.6 100.0 336 Masvingo 30.8 27.4 843 58.4 18.7 11.3 11.6 100.0 231 Harare 75.7 73.5 1,412 78.5 10.0 4.8 6.7 100.0 1,037 Bulawayo 79.0 77.1 409 77.5 13.5 6.7 2.3 100.0 315 Education No education (4.3) (4.3) 38 * * * * * 2 Primary 8.2 6.4 1,803 51.2 20.6 15.4 12.9 100.0 115 Secondary 43.5 40.3 5,349 65.4 18.3 8.0 8.4 100.0 2,155 More than secondary 92.4 90.4 849 84.5 9.3 4.2 2.0 100.0 768 Wealth quintile Lowest 8.4 5.9 1,212 42.5 28.5 14.4 14.6 100.0 72 Second 13.4 11.2 1,448 51.0 21.0 18.2 9.9 100.0 162 Middle 23.6 20.3 1,558 48.8 26.0 13.5 11.8 100.0 317 Fourth 53.8 50.3 1,852 68.2 17.1 6.2 8.5 100.0 931 Highest 81.2 79.1 1,970 78.0 12.5 5.2 4.3 100.0 1,559 Total 15-49 40.5 37.8 8,041 69.7 16.1 7.3 6.9 100.0 3,040 50-54 25.6 23.2 355 72.1 16.4 8.6 2.9 100.0 82 Total 15-54 39.9 37.2 8,396 69.7 16.1 7.3 6.8 100.0 3,122 Notes: An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. Characteristics of Respondents • 51 Table 3.6.1 Employment status: Women Percent distribution of women age 15-49 by employment status, according to background characteristics, Zimbabwe 2015 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 15.3 6.7 78.0 100.0 2,199 20-24 34.6 12.4 53.0 100.0 1,697 25-29 47.6 12.6 39.8 100.0 1,657 30-34 51.9 10.3 37.8 100.0 1,619 35-39 55.5 8.6 35.9 100.0 1,236 40-44 55.1 9.4 35.5 100.0 965 45-49 57.9 9.0 33.1 100.0 582 Marital status Never married 24.8 7.8 67.5 100.0 2,511 Married or living together 44.1 10.6 45.3 100.0 6,151 Divorced/separated/ widowed 60.1 10.4 29.5 100.0 1,292 Number of living children 0 23.6 8.2 68.1 100.0 2,710 1-2 47.1 10.6 42.3 100.0 3,668 3-4 50.5 10.3 39.2 100.0 2,664 5+ 43.7 10.4 45.9 100.0 912 Residence Urban 52.4 8.5 39.0 100.0 3,829 Rural 34.3 10.7 55.0 100.0 6,126 Province Manicaland 33.3 11.7 55.0 100.0 1,266 Mashonaland Central 34.9 13.9 51.2 100.0 882 Mashonaland East 44.2 11.5 44.3 100.0 952 Mashonaland West 46.9 10.6 42.5 100.0 1,160 Matabeleland North 22.3 6.0 71.7 100.0 465 Matabeleland South 29.8 9.1 61.2 100.0 419 Midlands 43.2 9.0 47.8 100.0 1,263 Masvingo 34.1 6.8 59.1 100.0 1,187 Harare 54.1 9.6 36.3 100.0 1,783 Bulawayo 47.3 8.1 44.6 100.0 577 Education No education 35.8 7.3 56.8 100.0 126 Primary 37.4 10.0 52.6 100.0 2,571 Secondary 38.9 10.0 51.1 100.0 6,527 More than secondary 77.6 8.5 14.0 100.0 731 Wealth quintile Lowest 26.6 9.6 63.9 100.0 1,704 Second 32.1 11.2 56.7 100.0 1,693 Middle 35.7 12.1 52.2 100.0 1,748 Fourth 49.1 9.4 41.6 100.0 2,307 Highest 54.3 8.1 37.7 100.0 2,503 Total 41.3 9.9 48.9 100.0 9,955 1 “Currently employed” is defined as having done work in the past seven days. Includes persons who did not work in the past seven days but who are regularly employed and were absent from work for leave, illness, vacation, or any other such reason. 52 • Characteristics of Respondents Table 3.6.2 Employment status: Men Percent distribution of men age 15-49 by employment status, according to background characteristics, Zimbabwe 2015 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 32.3 7.3 60.4 100.0 2,126 20-24 62.3 11.6 26.1 100.0 1,330 25-29 79.4 9.4 11.2 100.0 1,148 30-34 81.1 7.2 11.6 100.0 1,120 35-39 82.9 7.3 9.8 100.0 917 40-44 82.3 8.5 9.2 100.0 809 45-49 78.5 9.1 12.4 100.0 591 Marital status Never married 45.7 8.6 45.7 100.0 3,624 Married or living together 81.6 8.2 10.2 100.0 4,010 Divorced/separated/ widowed 73.0 11.6 15.4 100.0 407 Number of living children 0 48.0 8.8 43.2 100.0 3,969 1-2 81.5 8.8 9.7 100.0 1,957 3-4 83.3 7.6 9.1 100.0 1,523 5+ 77.1 8.6 14.3 100.0 591 Residence Urban 70.5 7.1 22.4 100.0 2,900 Rural 61.9 9.4 28.8 100.0 5,140 Province Manicaland 62.5 14.0 23.4 100.0 1,072 Mashonaland Central 59.7 9.4 30.9 100.0 806 Mashonaland East 62.4 7.8 29.8 100.0 807 Mashonaland West 74.6 5.1 20.3 100.0 1,004 Matabeleland North 61.6 12.0 26.4 100.0 366 Matabeleland South 58.4 14.0 27.6 100.0 335 Midlands 63.7 6.4 29.9 100.0 986 Masvingo 61.6 5.3 33.0 100.0 843 Harare 70.7 9.1 20.2 100.0 1,412 Bulawayo 61.7 5.1 33.2 100.0 409 Education No education (69.1) (9.6) (21.3) 100.0 38 Primary 63.3 10.0 26.7 100.0 1,803 Secondary 62.9 8.4 28.7 100.0 5,349 More than secondary 81.7 6.2 12.1 100.0 849 Wealth quintile Lowest 57.7 12.3 30.0 100.0 1,212 Second 60.2 10.2 29.6 100.0 1,448 Middle 60.4 8.4 31.2 100.0 1,558 Fourth 72.6 6.6 20.8 100.0 1,852 Highest 69.5 6.9 23.6 100.0 1,970 Total 15-49 65.0 8.6 26.5 100.0 8,041 50-54 79.4 9.2 11.4 100.0 355 Total 15-54 65.6 8.6 25.8 100.0 8,396 Note: Figures in parentheses are based on 25-49 unweighted cases. 1 “Currently employed” is defined as having done work in the past seven days. Includes persons who did not work in the past seven days but who are regularly employed and were absent from work for leave, illness, vacation, or any other such reason. Characteristics of Respondents • 53 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, Zimbabwe 2015 Background characteristic Profes- sional/ technical/ managerial Clerical Sales and services Skilled manual Unskilled manual Domestic service Agriculture Other Missing Total Number of women Age 15-19 2.6 1.0 42.6 3.4 0.1 34.5 13.9 1.8 0.0 100.0 484 20-24 9.6 3.9 50.6 3.9 0.9 14.9 13.8 1.7 0.7 100.0 797 25-29 10.1 3.6 51.9 2.8 0.0 8.6 20.3 2.3 0.3 100.0 998 30-34 13.4 3.4 50.5 5.3 0.9 6.6 16.9 1.7 1.1 100.0 1,007 35-39 14.2 1.6 51.3 6.7 0.5 5.5 17.6 2.0 0.6 100.0 792 40-44 14.3 2.1 45.4 6.4 0.2 5.8 22.1 3.1 0.6 100.0 623 45-49 12.5 4.2 41.9 7.9 0.4 3.9 26.4 2.3 0.5 100.0 390 Marital status Never married 15.0 5.6 37.7 3.4 0.4 30.2 4.2 3.2 0.2 100.0 817 Married or living together 10.6 2.4 51.3 5.4 0.4 3.8 23.7 1.7 0.6 100.0 3,363 Divorced/separated/ widowed 10.6 2.5 49.9 4.8 0.6 17.3 10.9 2.5 0.9 100.0 911 Number of living children 0 14.7 5.4 39.4 3.7 0.1 27.3 5.9 3.3 0.2 100.0 863 1-2 12.7 3.4 52.0 4.2 0.6 9.8 14.5 2.0 0.6 100.0 2,115 3-4 10.1 1.7 50.3 6.2 0.5 5.0 24.1 1.6 0.5 100.0 1,619 5+ 3.2 0.5 47.4 6.1 0.3 1.9 37.0 2.3 1.4 100.0 493 Residence Urban 17.1 5.4 51.3 5.3 0.7 14.3 2.6 2.7 0.7 100.0 2,334 Rural 6.4 0.8 46.9 4.7 0.3 7.3 31.6 1.6 0.5 100.0 2,757 Province Manicaland 7.7 0.5 55.6 2.9 0.4 7.0 22.7 2.6 0.6 100.0 570 Mashonaland Central 7.4 0.6 45.7 4.9 0.2 3.5 36.1 1.7 0.0 100.0 430 Mashonaland East 6.3 1.0 44.3 2.6 0.0 7.9 35.0 2.4 0.5 100.0 531 Mashonaland West 7.5 1.7 42.4 7.7 0.3 6.7 32.3 1.2 0.3 100.0 667 Matabeleland North 15.8 3.1 52.1 3.1 0.1 18.7 5.3 1.6 0.2 100.0 131 Matabeleland South 11.5 4.0 49.2 3.3 1.3 25.4 3.4 1.8 0.2 100.0 163 Midlands 9.3 1.6 50.9 4.8 0.8 9.3 21.1 2.1 0.1 100.0 659 Masvingo 13.9 3.2 53.9 5.8 0.1 6.6 13.2 1.2 2.1 100.0 485 Harare 16.2 5.7 50.9 5.6 0.7 15.9 2.2 2.2 0.6 100.0 1,135 Bulawayo 20.0 7.7 42.1 5.5 1.2 16.2 1.6 4.6 1.2 100.0 320 Education No education (0.0) (0.0) (31.9) (5.5) (0.0) (10.6) (45.0) (3.3) (3.7) 100.0 54 Primary 1.1 0.1 43.1 5.0 0.3 13.7 34.9 1.3 0.4 100.0 1,218 Secondary 5.7 2.2 57.4 5.6 0.5 11.2 14.8 2.0 0.4 100.0 3,190 More than secondary 60.2 12.1 18.3 1.6 0.3 0.4 1.3 4.4 1.5 100.0 629 Wealth quintile Lowest 1.4 0.0 42.6 6.7 0.4 7.6 38.9 0.8 1.6 100.0 615 Second 2.9 0.4 45.0 6.2 0.3 7.3 36.3 1.3 0.4 100.0 732 Middle 4.3 0.6 50.7 2.5 0.4 7.3 31.5 2.3 0.3 100.0 836 Fourth 10.1 1.6 61.3 5.7 0.5 10.0 8.4 1.9 0.4 100.0 1,348 Highest 23.9 7.6 41.5 4.4 0.6 15.2 3.2 3.1 0.6 100.0 1,560 Total 11.3 2.9 48.9 5.0 0.5 10.5 18.3 2.1 0.6 100.0 5,091 Note: Figures in parentheses are based on 25-49 unweighted cases. 54 • 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, Zimbabwe 2015 Background characteristic Profes- sional/ technical/ managerial Clerical Sales and services Skilled manual Unskilled manual Domestic service Agriculture Other Missing Total Number of men Age 15-19 3.6 0.1 23.9 12.7 1.5 7.8 43.0 7.1 0.1 100.0 842 20-24 8.7 0.7 23.2 26.4 4.2 4.8 27.5 4.3 0.2 100.0 983 25-29 11.7 1.3 23.8 31.8 3.1 3.7 20.2 4.2 0.2 100.0 1,019 30-34 13.4 1.3 25.6 29.4 3.1 3.1 19.5 4.5 0.2 100.0 990 35-39 14.3 1.5 23.0 31.5 2.7 2.4 20.4 3.6 0.6 100.0 827 40-44 13.9 0.2 23.9 29.1 1.7 2.2 22.3 6.2 0.4 100.0 734 45-49 19.8 1.6 19.3 26.4 2.1 3.0 22.6 5.1 0.0 100.0 518 Marital status Never married 9.5 0.7 24.3 20.0 2.6 5.6 31.1 6.0 0.1 100.0 1,967 Married or living together 13.3 1.1 22.7 30.2 2.6 3.0 22.1 4.6 0.4 100.0 3,601 Divorced/separated/ widowed 7.5 0.6 27.4 32.5 4.9 3.7 21.0 2.0 0.4 100.0 344 Number of living children 0 9.3 0.9 24.0 21.6 2.8 5.1 30.4 5.7 0.1 100.0 2,255 1-2 14.0 0.8 23.1 31.0 3.8 2.9 19.5 4.5 0.3 100.0 1,767 3-4 13.9 1.2 23.6 30.5 1.5 4.1 20.3 4.5 0.4 100.0 1,385 5+ 8.0 0.9 22.8 26.5 2.4 1.7 33.2 4.2 0.4 100.0 506 Residence Urban 22.0 1.7 29.4 31.3 3.4 3.4 2.7 5.8 0.1 100.0 2,250 Rural 5.3 0.5 19.9 24.2 2.3 4.3 38.8 4.4 0.4 100.0 3,662 Province Manicaland 6.0 0.9 23.6 29.7 0.6 4.0 32.1 3.1 0.0 100.0 820 Mashonaland Central 5.6 0.7 14.3 18.9 2.9 2.8 49.8 4.6 0.2 100.0 557 Mashonaland East 6.7 0.3 26.8 24.1 2.9 2.5 32.4 4.2 0.0 100.0 566 Mashonaland West 10.5 0.3 20.2 27.2 0.5 8.4 31.3 1.6 0.0 100.0 801 Matabeleland North 7.0 0.5 32.1 19.9 1.9 5.3 22.5 10.5 0.3 100.0 270 Matabeleland South 10.1 0.8 34.6 24.5 3.1 1.3 22.9 2.6 0.3 100.0 243 Midlands 10.3 1.0 19.7 25.6 7.2 2.7 27.3 6.0 0.2 100.0 691 Masvingo 12.1 1.6 16.8 26.2 1.4 2.5 29.4 8.2 1.8 100.0 565 Harare 21.3 1.2 29.5 33.0 3.4 3.8 2.1 5.8 0.0 100.0 1,127 Bulawayo 23.8 3.1 25.6 29.0 4.1 3.9 3.9 6.3 0.4 100.0 273 Education No education (1.6) (0.0) (30.7) (14.1) (8.5) (2.1) (35.8) (7.2) (0.0) 100.0 30 Primary 1.3 0.0 21.8 22.7 2.5 6.2 42.3 2.6 0.6 100.0 1,322 Secondary 7.2 1.0 26.3 29.9 3.0 3.8 23.5 5.2 0.2 100.0 3,814 More than secondary 53.1 2.4 12.2 20.0 1.7 0.7 1.9 7.7 0.3 100.0 746 Wealth quintile Lowest 0.7 0.1 18.8 28.9 2.9 3.9 40.2 3.6 0.9 100.0 848 Second 2.1 0.0 20.5 23.9 2.2 3.9 42.7 4.7 0.0 100.0 1,019 Middle 3.2 0.4 22.1 21.6 1.9 5.1 40.9 4.4 0.3 100.0 1,072 Fourth 13.5 0.8 27.8 29.9 4.6 4.4 14.3 4.6 0.2 100.0 1,467 Highest 28.6 2.6 25.0 28.7 1.8 2.8 3.8 6.6 0.1 100.0 1,506 Total 15-49 11.7 0.9 23.5 26.9 2.7 3.9 25.0 4.9 0.3 100.0 5,913 50-54 16.9 0.1 19.4 29.5 2.0 2.6 27.2 2.4 0.0 100.0 315 Total 15-54 11.9 0.9 23.3 27.1 2.7 3.9 25.2 4.8 0.3 100.0 6,228 Note: Figures in parentheses are based on 25-49 unweighted cases. Characteristics of Respondents • 55 Table 3.8 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), Zimbabwe 2015 Employment characteristic Agricultural work Nonagricultural work Total Type of earnings Cash only 63.6 81.5 78.1 Cash and in-kind 22.9 13.5 15.1 In-kind only 3.1 1.3 1.7 Not paid 10.4 3.8 5.1 Total 100.0 100.0 100.0 Type of employer Employed by family member 3.2 4.5 4.2 Employed by nonfamily member 21.5 43.4 39.7 Self-employed 75.2 52.1 56.1 Total 100.0 100.0 100.0 Continuity of employment All year 41.9 60.1 57.0 Seasonal 50.8 19.7 25.3 Occasional 7.3 20.2 17.7 Total 100.0 100.0 100.0 Number of women employed during the last 12 months 931 4,023 5,091 Note: Total includes women with missing information on type of employment who are not shown separately. 56 • Characteristics of Respondents Table 3.9.1 Health insurance coverage: Women Percentage of women age 15-49 with specific types of health insurance coverage, according to background characteristics, Zimbabwe 2015 Background characteristic Social security Health insurance through employer Mutual Health Organization/ community based insurance Privately purchased commercial insurance Other None Number of women Age 15-19 0.2 4.3 0.4 1.5 0.0 93.6 2,199 20-24 0.3 4.8 0.9 2.9 0.0 91.1 1,697 25-29 0.1 6.9 0.8 2.7 0.0 89.5 1,657 30-34 0.2 10.2 1.0 3.3 0.1 85.4 1,619 35-39 0.2 9.7 1.0 3.5 0.3 85.5 1,236 40-44 0.3 10.4 1.0 3.2 0.0 85.0 965 45-49 0.4 9.2 1.3 2.2 0.2 86.9 582 Residence Urban 0.5 14.3 1.6 6.1 0.2 77.5 3,829 Rural 0.0 3.0 0.3 0.6 0.0 96.1 6,126 Province Manicaland 0.0 3.1 0.7 1.4 0.0 94.7 1,266 Mashonaland Central 0.0 5.0 0.1 0.5 0.0 94.5 882 Mashonaland East 0.1 3.9 1.7 1.7 0.0 92.8 952 Mashonaland West 0.8 6.7 0.2 2.0 0.1 90.1 1,160 Matabeleland North 0.4 3.9 0.9 0.8 0.0 94.1 465 Matabeleland South 0.3 2.5 1.2 1.7 0.0 94.3 419 Midlands 0.0 5.0 0.2 2.8 0.0 91.9 1,263 Masvingo 0.4 9.1 1.4 0.4 0.0 88.7 1,187 Harare 0.1 14.7 0.5 7.6 0.4 77.2 1,783 Bulawayo 0.2 12.1 3.1 3.3 0.2 81.2 577 Education No education 0.0 1.7 0.0 0.0 0.0 98.3 126 Primary 0.0 0.6 0.0 0.1 0.0 99.3 2,571 Secondary 0.2 6.5 0.7 2.2 0.1 90.4 6,527 More than secondary 1.1 39.3 5.1 17.1 0.4 37.7 731 Wealth quintile Lowest 0.0 0.2 0.1 0.0 0.0 99.7 1,704 Second 0.0 0.4 0.1 0.0 0.0 99.5 1,693 Middle 0.0 1.7 0.2 0.1 0.0 98.0 1,748 Fourth 0.3 6.9 0.7 2.3 0.2 89.7 2,307 Highest 0.7 21.3 2.4 8.5 0.2 67.3 2,503 Total 0.2 7.3 0.8 2.7 0.1 88.9 9,955 Characteristics of Respondents • 57 Table 3.9.2 Health insurance coverage: Men Percentage of men age 15-49 with specific types of health insurance coverage, according to background characteristics, Zimbabwe 2015 Background characteristic Social security Health insurance through employer Mutual Health Organization/ community based insurance Privately purchased commercial insurance Other None Number of men Age 15-19 0.1 2.7 0.4 2.1 0.1 94.5 2,126 20-24 0.1 2.3 1.1 4.8 0.8 90.9 1,330 25-29 0.0 6.5 1.0 2.3 0.7 89.8 1,148 30-34 0.5 7.1 1.1 4.7 0.3 86.3 1,120 35-39 0.6 11.6 1.3 4.8 0.5 81.6 917 40-44 0.5 10.2 1.8 5.0 0.7 82.4 809 45-49 0.9 14.6 1.2 5.3 0.9 77.3 591 Residence Urban 0.6 13.5 2.1 8.5 1.2 74.5 2,900 Rural 0.1 2.5 0.4 1.1 0.1 95.8 5,140 Province Manicaland 0.5 3.2 0.8 0.8 0.1 94.6 1,072 Mashonaland Central 0.2 3.0 0.1 0.9 0.2 95.6 806 Mashonaland East 0.3 3.5 1.6 2.0 0.1 92.6 807 Mashonaland West 0.2 6.3 1.2 2.1 0.1 90.2 1,004 Matabeleland North 0.3 5.1 0.3 0.9 0.0 93.4 366 Matabeleland South 0.3 4.0 0.4 1.3 0.1 94.1 335 Midlands 0.3 5.2 0.2 4.8 0.0 89.6 986 Masvingo 0.3 7.5 2.7 2.7 1.2 85.8 843 Harare 0.2 11.8 1.1 10.1 1.9 75.5 1,412 Bulawayo 0.8 13.4 0.8 7.7 0.0 77.8 409 Education No education (0.0) (1.2) (0.0) (1.9) (0.0) (96.9) 38 Primary 0.0 0.5 0.0 0.1 0.0 99.4 1,803 Secondary 0.2 4.4 0.7 3.0 0.2 91.5 5,349 More than secondary 1.6 32.0 4.9 16.9 3.2 42.5 849 Wealth quintile Lowest 0.0 0.2 0.0 0.0 0.0 99.8 1,212 Second 0.0 0.2 0.1 0.3 0.0 99.4 1,448 Middle 0.2 1.0 0.1 0.5 0.0 98.2 1,558 Fourth 0.3 7.0 1.0 4.2 0.6 87.1 1,852 Highest 0.8 18.6 3.1 10.9 1.4 65.6 1,970 Total 15-49 0.3 6.4 1.0 3.8 0.5 88.1 8,041 50-54 0.3 9.2 3.7 6.9 0.3 79.6 355 Total 15-54 0.3 6.6 1.1 3.9 0.5 87.8 8,396 Note: Figures in parentheses are based on 25-49 unweighted cases. 58 • Characteristics of Respondents Table 3.10.1 Tobacco smoking: Women Percentage of women age 15-49 who smoke cigarettes, according to background characteristics, Zimbabwe 2015 Background characteristic Percentage who smoke cigarettes1,2 Number of women Age 15-19 0.2 2,199 20-24 0.3 1,697 25-29 0.2 1,657 30-34 0.5 1,619 35-39 0.1 1,236 40-44 0.4 965 45-49 0.7 582 Residence Urban 0.6 3,829 Rural 0.1 6,126 Province Manicaland 0.3 1,266 Mashonaland Central 0.0 882 Mashonaland East 0.1 952 Mashonaland West 0.3 1,160 Matabeleland North 0.2 465 Matabeleland South 0.5 419 Midlands 0.0 1,263 Masvingo 0.2 1,187 Harare 0.6 1,783 Bulawayo 0.9 577 Education No education 0.8 126 Primary 0.1 2,571 Secondary 0.4 6,527 More than secondary 0.5 731 Wealth quintile Lowest 0.2 1,704 Second 0.0 1,693 Middle 0.1 1,748 Fourth 0.3 2,307 Highest 0.7 2,503 Total 0.3 9,955 1 Includes daily and occasional (less than daily) use 2 Includes manufactured cigarettes and hand-rolled cigarettes Characteristics of Respondents • 59 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, Zimbabwe 2015 Percentage who smoke:1 Smoking frequency Number of men Background characteristic Cigarettes2 Other type of tobacco3 Any type of tobacco Daily smoker Occasional smoker4 Non- smoker Total Age 15-19 1.9 0.4 2.1 0.8 1.5 97.7 100.0 2,126 20-24 14.0 1.9 14.5 8.8 6.7 84.5 100.0 1,330 25-29 26.4 2.3 27.0 18.8 9.0 72.2 100.0 1,148 30-34 29.1 2.2 29.4 23.0 7.3 69.7 100.0 1,120 35-39 23.9 1.3 23.9 17.2 7.2 75.6 100.0 917 40-44 20.8 0.6 21.0 16.9 5.5 77.6 100.0 809 45-49 18.7 0.5 18.9 14.3 5.5 80.2 100.0 591 Residence Urban 15.4 1.6 15.8 10.9 5.2 83.9 100.0 2,900 Rural 17.6 1.1 17.9 13.0 5.8 81.2 100.0 5,140 Province Manicaland 15.7 1.2 16.1 11.6 5.3 83.1 100.0 1,072 Mashonaland Central 24.3 1.5 24.4 16.8 8.3 75.0 100.0 806 Mashonaland East 17.2 1.1 17.5 14.5 3.9 81.6 100.0 807 Mashonaland West 16.6 1.7 17.3 12.6 4.8 82.6 100.0 1,004 Matabeleland North 17.9 2.8 18.3 12.2 7.8 80.0 100.0 366 Matabeleland South 19.7 0.8 19.8 15.5 6.9 77.7 100.0 335 Midlands 12.9 0.3 12.9 8.4 5.8 85.9 100.0 986 Masvingo 14.2 0.9 14.5 10.6 4.8 84.7 100.0 843 Harare 16.7 1.2 16.9 11.7 5.2 83.1 100.0 1,412 Bulawayo 16.5 2.7 17.2 12.1 5.9 81.9 100.0 409 Education No education (27.0) (1.8) (27.0) (27.1) (3.1) (69.8) (100.0) 38 Primary 22.0 1.5 22.5 16.7 6.9 76.4 100.0 1,803 Secondary 16.0 1.4 16.3 11.3 5.6 83.1 100.0 5,349 More than secondary 10.4 0.5 10.4 8.0 2.9 89.1 100.0 849 Wealth quintile Lowest 23.5 1.4 23.8 17.9 6.8 75.3 100.0 1,212 Second 19.5 1.6 19.8 14.0 6.9 79.0 100.0 1,448 Middle 14.8 1.0 15.1 11.0 5.0 84.0 100.0 1,558 Fourth 18.0 1.6 18.4 13.3 5.5 81.2 100.0 1,852 Highest 11.3 1.0 11.4 7.5 4.5 88.1 100.0 1,970 Total 15-49 16.8 1.3 17.1 12.3 5.6 82.1 100.0 8,041 50-54 29.5 0.8 29.9 22.6 8.7 68.7 100.0 355 Total 15-54 17.4 1.3 17.7 12.7 5.7 81.6 100.0 8,396 Note: Figures in parentheses are based on 25-49 unweighted cases. 1 Includes daily and occasional (less than daily) use 2 Includes manufactured cigarettes and hand-rolled cigarettes 3 Includes pipes and other types of tobacco 4 Occasional refers to less often than daily use 60 • 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, Zimbabwe 2015 Average number of cigarettes smoked per day1 Number of respondents who smoke cigarettes daily1 Background characteristic <5 5-9 10-14 15-24 ≥25 Don’t know Total Age 15-19 * * * * * * * 15 20-24 40.3 34.3 8.8 12.0 4.6 0.0 100.0 114 25-29 43.9 26.1 15.7 11.6 2.6 0.0 100.0 211 30-34 34.5 23.4 20.4 16.1 5.0 0.7 100.0 256 35-39 32.8 24.2 20.4 17.8 4.9 0.0 100.0 155 40-44 36.0 24.1 20.8 12.8 6.4 0.0 100.0 130 45-49 35.4 29.8 16.8 9.5 8.5 0.0 100.0 83 Residence Urban 31.1 30.3 21.3 14.0 2.8 0.6 100.0 312 Rural 40.8 23.7 15.9 13.8 5.8 0.0 100.0 652 Province Manicaland 29.8 35.3 11.4 20.4 3.2 0.0 100.0 122 Mashonaland Central 49.9 20.8 12.4 13.1 3.8 0.0 100.0 131 Mashonaland East 32.1 27.8 22.4 13.5 4.2 0.0 100.0 113 Mashonaland West 53.6 15.3 19.5 4.1 7.5 0.0 100.0 126 Matabeleland North 49.8 17.8 21.5 8.1 2.8 0.0 100.0 44 Matabeleland South 30.8 25.2 14.9 15.8 13.4 0.0 100.0 50 Midlands 41.2 18.5 24.3 10.5 5.4 0.0 100.0 80 Masvingo 37.9 23.8 11.5 19.8 7.0 0.0 100.0 84 Harare 27.7 31.5 20.7 16.8 2.2 1.0 100.0 165 Bulawayo 19.1 42.8 20.1 15.1 3.0 0.0 100.0 48 Education No education * * * * * * * 9 Primary 43.1 25.5 15.1 10.8 5.6 0.0 100.0 293 Secondary 36.0 26.5 17.4 15.3 4.5 0.3 100.0 597 More than secondary 29.7 23.2 30.4 12.8 3.9 0.0 100.0 65 Wealth quintile Lowest 50.0 19.9 16.9 8.4 4.9 0.0 100.0 212 Second 34.2 23.2 16.3 20.8 5.5 0.0 100.0 199 Middle 37.8 26.9 14.7 15.1 5.5 0.0 100.0 165 Fourth 33.3 28.0 21.2 12.7 4.1 0.7 100.0 246 Highest 31.5 33.3 17.9 13.2 4.2 0.0 100.0 142 Total 15-49 37.7 25.8 17.6 13.9 4.8 0.2 100.0 964 50-54 37.9 20.1 24.4 12.1 3.8 1.7 100.0 78 Total 15-54 37.7 25.4 18.1 13.8 4.7 0.3 100.0 1,042 Note: An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. 1 Includes manufactured cigarettes and hand-rolled cigarettes Marriage and Sexual Activity • 61 MARRIAGE AND SEXUAL ACTIVITY 4 Key Findings  Age at first marriage: Marriage is almost universal in Zimbabwe. The median age at marriage among women age 25-49 is 19.8 years and among men age 30-54 is 25.6 years.  Polygyny: Eleven percent of married women reported that their husband has more than one wife.  Sexual initiation: The median age at first sexual intercourse for women age 25-49 is about 1 year younger than the median age at first marriage, indicating that women engage in sex before marriage.  Widowhood: More than one in five (23 percent) of women age 45-49 are widowed. arriage and sexual activity help determine the extent to which women are exposed to the risk of pregnancy. Thus, they are important determinants of fertility levels. However, the timing and circumstances of marriage and sexual activity also have profound consequences for women’s and men’s lives. This chapter also presents information on marital status, polygyny, age at first marriage, and age at first sexual intercourse for both women and men. 4.1 MARITAL STATUS Currently married Women and men who report being married or living together with a partner as if married at the time of the survey Sample: Women and men age 15-49 Marriage is nearly universal in Zimbabwe. By age 45-49, only 4 percent and 2 percent of women and men, respectively, have never been married (Table 4.1). Sixty-two percent of women and 50 percent of men age 15-49 are currently married or living together with a partner as though married (Figure 4.1). Although nearly all men eventually marry, they tend to marry later than women; thus, a higher percentage of men than women age 15-49 have never married (45 percent compared with 25 percent). Women are more likely than men to be widowed (4 percent compared with 1 percent), while the proportion of women who are divorced or separated is more than twice that of men (9 percent and 4 percent, respectively). The percentage widowed increases with increasing age, especially among women (Table 4.1). M 62 • Marriage and Sexual Activity Figure 4.1 Marital status Percent distribution of women and men age 15-49 by current marital status Trends: The percentage of women age 15-49 who are married or living together has remained at 62 percent since 2010-11. The proportion of men married or living together is also similar, 50 percent in 2010-11 and 49 percent in 2015. Over this same time period, the proportion of men who were widowed has remained constant at less than 1 percent. 4.2 POLYGYNY Polygyny Women who report that their husband or partner has other wives are considered to be in a polygynous marriage. Sample: Currently married women and men age 15-49 Polygyny has implications for the frequency of exposure to sexual activity and therefore fertility. The extent of polygyny in Zimbabwe was measured by asking all women currently married or living with a man the question: “Does your husband/partner have other wives, does he live with other women as if married, or does he maintain a small house?” In Zimbabwe, the term “small house” is used to refer to a woman having an extramarital relationship with a married man. The majority of married women report their husband or partner has no other wives (88 percent). Eleven percent of women report their husbands have more than one wife, while 1 percent don’t know if their husbands have other wives (Table 4.2.1). Interestingly, a higher percentage of men age 15-49 report that they have only one wife compared with women (95 percent versus 88 percent), and only 5 percent report that they have multiple wives (Table 4.2.2). Trends: The percentage of women and men who report polygyny has remained consistent over the past decade, at 11 percent among currently married women and 5 percent among currently married men. Patterns by background characteristics  The percentage of women who report that their husbands or partners have multiple wives increases with an increase in age, from 8 percent for women age 15-24 to 16-18 percent for women age 40-49.  Women in rural areas are more than twice as likely as their urban counterparts to report that their husband or partner has multiple wives (14 percent and 6 percent, respectively).  The proportion of women who report having co-wives is highest in Manicaland (16 percent). Never married 25% Married 59% Living together 3% Divorced 5% Separated 4% Widowed 4% Women Never married 45% Married 49%Living together 1% Divorced 2% Separated 3% Widowed 1% Men Marriage and Sexual Activity • 63  There is an inverse relationship between education and wealth, and polygyny; women who have no education are the most likely to report having co-wives (20 percent) and those with more than a secondary education are the least likely (3 percent). Similarly, 15 percent of women in the lowest wealth quintile report that their husbands or partners have multiple wives compared with 4 percent of women in the highest wealth quintile. 4.3 AGE AT FIRST MARRIAGE Median age at first marriage Age by which half of respondents have been married Sample: Women age 20-49 and age 25-29, and men age 30-54 For most societies, marriage marks the point in a woman’s life when childbearing first becomes socially acceptable. On average, women who marry early will have longer exposure to pregnancy and a greater number of lifetime births. The median age at marriage among women 25-49 is 19.8 years and the majority of women are married by age 25 (83 percent) (Table 4.3). Men get married later than women; median age at marriage among men 30-54 is 25.6 years and 46 percent of men age 30-54 get married by the age of 25. Trends: During the 16-year period between 1999 and 2015, the median age at marriage among women has increased slowly but steadily, from 19.3 years in 1999 and 2005 to 19.8 years in 2015. A similar trend is observed among men over the same period. Patterns by background characteristics  Urban women marry later than rural women. The median age at first marriage is about 2 years older among urban than among rural women age 25-49 (21.2 years compared with 19.1 years) (Table 4.4).  By province, the median age at first marriage for women ranges from 18.4 years in Mashonaland Central to 22.4 years in Bulawayo.  Educated women marry much later. There is a 6.3-year difference in the median age at first marriage between women with no education and those with more than a secondary education (17.2 years compared with 23.6 years).  The median age at first marriage for women increases steadily with household wealth, from18.5 years in the lowest wealth quintile to 21.6 years in the highest wealth quintile. 4.4 AGE AT FIRST SEXUAL INTERCOURSE Median age at first sexual intercourse Age by which half of respondents have had sexual intercourse Sample: Women age 20-49 and age 25-29, and men age 25-49 and 25-54 Age at first marriage can be used as a proxy for the beginning of exposure to the risk of pregnancy. However, because some women are sexually active before marriage, the age at which women initiate sexual intercourse more precisely marks the beginning of their exposure to reproductive risks. The median age at first intercourse for women age 25-49 in Zimbabwe is 18.7 years (Table 4.5). Six percent of women age 25-49 have had sexual intercourse before age 15 and 40 percent before age 18. By age 20, 66 percent of Zimbabwean women have had sexual intercourse. 64 • Marriage and Sexual Activity Zimbabwean men have an older median age at first intercourse compared with women. Among men age 25-49, the median age at first intercourse is 20.5 years, compared with 18.7 years among women the same age. Four percent of men age 25-49 have had sexual intercourse before age 15 and 24 percent before age 18. By age 20, more than four in ten men have initiated sexual intercourse (44 percent). A comparison of the median age at first intercourse with the median age at first marriage can be used as a measure of whether respondents engage in sex before marriage. The median age at first intercourse for women age 25-49 in Zimbabwe is about 1 year younger than the median age at first marriage of women the same age (18.7 years versus 19.8 years). This indicates that many women engage in sex before marriage. Thus, women in Zimbabwe may be exposed to the risk of pregnancy and begin childbearing at an earlier age than indicated by the median age at first marriage. Trends: Since 1999, the median age at first sexual intercourse among women age 25-49 has remained constant at 18.7 years. Among men age 25-49 it has increased from 19.7 years in 1999 to 20.5 years in 2015. Over the same 16-year period, women age 25-49 engaging in sex by age 18 has remained steady at about 4 in 10 women. However, among men age 25-49, the proportion that has initiated sexual intercourse by age 18 has decreased from 29 percent in 1999 to 24 percent in 2015. Patterns by background characteristics  The median age at first sex for women age 25-49 is 1.8 years younger among rural than among urban women (18.1 years versus 19.9 years) (Table 4.6).  The median age at first sexual intercourse for women age 25-49 ranges from 17.7 years in Matabeleland North to 20.0 years in Harare.  More educated women wait longer before having sex. Among women age 25-49, there is an almost 6- year difference in the median age at first sex between women with no education and those with more than a secondary education (16.4 years compared with 22.1 years).  Age at first sexual intercourse increases steadily with household wealth. The median age at first sex for women in the lowest quintile is about 3 years younger than for women in the highest wealth quintile (17.6 years versus 20.3 years). 4.5 RECENT SEXUAL ACTIVITY In the absence of effective contraception, the probability of becoming pregnant is highly dependent upon the frequency of intercourse. Therefore, information on sexual activity can be used to refine measures of exposure to pregnancy. Men and women who have ever had sex were asked how long ago they most recently had sexual intercourse. More than half of respondents age 15-49 (54 percent of women and 52 percent of men) reported having sexual intercourse within the four weeks before the survey (Tables 4.7.1 and 4.7.2). Nine percent of women age 15-49 have not had sexual intercourse for one or more years, and 19 percent have never had sexual intercourse. Among men age 15-49, 7 percent have not been sexually active for one or more years and 24 percent have never had sexual intercourse. For more information on recent sexual activity, see Tables 4.7.1 and 4.7.2. Trends: Since 2010-11, there was a slight increase in the percentage of women and men age 15-49 who reported having had sexual intercourse within the four weeks preceding the interview from 50 percent to 54 percent for women and from 51 percent to 52 percent for men. Marriage and Sexual Activity • 65 LIST OF TABLES For more information on marriage and sexual activity, see the following tables:  Table 4.1 Current marital status  Table 4.2.1 Number of women’s co-wives  Table 4.2.2 Number of men’s wives  Table 4.3 Age at first marriage  Table 4.4 Median age at first marriage by background characteristics  Table 4.5 Age at first sexual intercourse  Table 4.6 Median age at first sexual intercourse by background characteristics  Table 4.7.1 Recent sexual activity: Women  Table 4.7.2 Recent sexual activity: Men 66 • Marriage and Sexual Activity Table 4.1 Current marital status Percent distribution of women and men age 15-49 by current marital status, according to age, Zimbabwe 2015 Marital status Total Percentage of respondents currently in union Number of respondents Age Never married Married Living together Divorced Separated Widowed WOMEN 15-19 77.2 17.0 2.6 1.2 1.8 0.1 100.0 19.6 2,199 20-24 29.1 57.4 4.2 4.3 4.7 0.2 100.0 61.6 1,697 25-29 9.5 73.8 3.3 6.4 5.3 1.7 100.0 77.1 1,657 30-34 5.0 78.9 3.5 6.4 2.9 3.4 100.0 82.3 1,619 35-39 2.7 76.1 2.8 6.4 4.7 7.4 100.0 78.9 1,236 40-44 2.4 71.1 2.2 8.0 3.3 13.0 100.0 73.3 965 45-49 4.3 63.1 2.4 6.2 1.4 22.6 100.0 65.5 582 Total 15-49 25.2 58.7 3.1 5.0 3.6 4.4 100.0 61.8 9,955 MEN 15-19 99.0 0.8 0.0 0.0 0.2 0.0 100.0 0.9 2,126 20-24 73.7 21.0 1.0 1.0 3.2 0.0 100.0 22.0 1,330 25-29 30.9 60.2 1.8 2.9 3.9 0.3 100.0 62.1 1,148 30-34 10.9 81.4 1.3 2.1 3.8 0.5 100.0 82.7 1,120 35-39 3.8 88.2 0.7 3.5 3.0 0.8 100.0 88.9 917 40-44 2.1 88.7 0.7 3.4 2.7 2.4 100.0 89.4 809 45-49 1.7 88.1 0.3 4.4 2.6 3.0 100.0 88.4 591 Total 15-49 45.1 49.1 0.8 1.9 2.5 0.7 100.0 49.9 8,041 50-54 0.4 88.4 1.0 4.4 2.0 3.7 100.0 89.4 355 Total 15-54 43.2 50.8 0.8 2.0 2.5 0.8 100.0 51.5 8,396 Marriage and Sexual Activity • 67 Table 4.2.1 Number of women’s co-wives Percent distribution of currently married women age 15-49 by number of co-wives, according to background characteristics, Zimbabwe 2015 Background characteristic Number of co-wives Total Number of women 0 1 2+ Don’t know Age 15-19 91.5 4.0 3.8 0.8 100.0 432 20-24 91.0 6.1 1.7 1.3 100.0 1,045 25-29 89.7 6.7 2.7 0.9 100.0 1,278 30-34 88.9 7.9 2.1 1.0 100.0 1,333 35-39 85.4 8.9 4.0 1.7 100.0 975 40-44 80.1 12.2 5.7 2.0 100.0 707 45-49 81.7 11.9 4.2 2.2 100.0 381 Residence Urban 91.7 5.4 1.0 1.9 100.0 2,100 Rural 85.4 9.3 4.2 1.0 100.0 4,051 Province Manicaland 82.7 7.4 8.4 1.5 100.0 857 Mashonaland Central 86.9 10.9 2.0 0.2 100.0 638 Mashonaland East 86.9 8.8 3.3 1.1 100.0 622 Mashonaland West 86.2 9.6 3.9 0.3 100.0 774 Matabeleland North 86.9 8.2 1.4 3.5 100.0 279 Matabeleland South 94.4 4.1 1.0 0.4 100.0 214 Midlands 87.5 8.5 3.3 0.7 100.0 794 Masvingo 87.5 8.3 2.2 2.0 100.0 740 Harare 90.5 6.1 0.8 2.6 100.0 976 Bulawayo 96.2 3.2 0.3 0.4 100.0 258 Education No education 79.6 11.5 8.9 0.0 100.0 88 Primary 81.4 11.6 6.0 1.1 100.0 1,826 Secondary 89.9 6.8 1.9 1.4 100.0 3,813 More than secondary 95.2 2.4 0.4 2.0 100.0 424 Wealth quintile Lowest 83.6 9.7 5.6 1.1 100.0 1,193 Second 86.4 9.0 3.8 0.8 100.0 1,191 Middle 85.6 9.4 4.5 0.5 100.0 1,073 Fourth 87.7 8.3 2.0 1.9 100.0 1,402 Highest 93.9 3.8 0.3 2.0 100.0 1,292 Total 87.6 8.0 3.1 1.3 100.0 6,151 68 • Marriage and Sexual Activity Table 4.2.2 Number of men’s wives Percent distribution of currently married men age 15-49 by number of wives, according to background characteristics, Zimbabwe 2015 Background characteristic Number of wives Total Number of men 1 2+ Age 15-19 * * 100.0 18 20-24 98.3 1.7 100.0 293 25-29 97.6 2.4 100.0 713 30-34 96.1 3.9 100.0 926 35-39 94.7 5.3 100.0 815 40-44 92.0 8.0 100.0 723 45-49 89.6 10.4 100.0 523 Residence Urban 97.6 2.4 100.0 1,485 Rural 93.0 7.0 100.0 2,525 Province Manicaland 92.9 7.1 100.0 493 Mashonaland Central 90.8 9.2 100.0 462 Mashonaland East 95.1 4.9 100.0 418 Mashonaland West 93.5 6.5 100.0 533 Matabeleland North 95.5 4.5 100.0 169 Matabeleland South 97.2 2.8 100.0 128 Midlands 93.0 7.0 100.0 519 Masvingo 95.7 4.3 100.0 410 Harare 98.1 1.9 100.0 712 Bulawayo 98.3 1.7 100.0 168 Education No education * * 100.0 19 Primary 92.7 7.3 100.0 887 Secondary 94.4 5.6 100.0 2,545 More than secondary 98.9 1.1 100.0 560 Wealth quintile Lowest 91.6 8.4 100.0 715 Second 93.1 6.9 100.0 715 Middle 93.2 6.8 100.0 674 Fourth 96.1 3.9 100.0 943 Highest 97.9 2.1 100.0 964 Total 15-49 94.7 5.3 100.0 4,010 50-54 90.7 9.3 100.0 318 Total 15-54 94.4 5.6 100.0 4,328 Note: An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. Marriage and Sexual Activity • 69 Table 4.3 Age at first marriage Percentage of women and men age 15-49 who were first married by exact ages and median age at first marriage, according to current age, Zimbabwe 2015 Percentage first married by exact age: Percentage never married Number of respondents Median age at first marriage Current age 15 18 20 22 25 WOMEN 15-19 2.7 na na na na 77.2 2,199 a 20-24 3.7 32.4 55.3 na na 29.1 1,697 19.5 25-29 4.5 30.5 54.8 71.4 85.6 9.5 1,657 19.6 30-34 3.1 28.7 51.3 66.9 81.8 5.0 1,619 19.9 35-39 4.1 27.6 52.1 69.1 83.2 2.7 1,236 19.8 40-44 6.4 28.0 51.1 68.4 82.8 2.4 965 19.9 45-49 8.0 31.8 49.4 67.7 81.9 4.3 582 20.1 20-49 4.5 29.9 52.9 na na 10.5 7,756 19.7 25-49 4.7 29.1 52.2 68.9 83.3 5.3 6,060 19.8 MEN 15-19 0.0 na na na na 99.0 2,126 a 20-24 0.1 1.2 8.6 na na 73.7 1,330 a 25-29 0.9 2.5 9.7 23.4 49.9 30.9 1,148 a 30-34 0.4 3.3 10.6 22.7 50.1 10.9 1,120 25.0 35-39 1.0 2.4 8.2 19.9 47.2 3.8 917 25.4 40-44 0.9 2.7 7.3 19.0 45.4 2.1 809 25.6 45-49 0.8 3.6 9.4 21.8 41.8 1.7 591 26.3 20-49 0.6 2.5 9.0 na na 25.7 5,914 a 25-49 0.8 2.8 9.2 21.5 47.6 11.7 4,584 a 20-54 0.6 2.5 9.0 na na 24.3 6,270 a 30-54 0.7 2.9 8.9 20.3 45.7 4.9 3,792 25.6 Note: The age at first marriage is defined as the age at which the respondent began living with her/his first spouse/partner. na = Not applicable due to censoring a = Omitted because less than 50 percent of the women or men began living with their spouse or partner for the first time before reaching the beginning of the age group 70 • Marriage and Sexual Activity Table 4.4 Median age at first marriage by background characteristics Median age at first marriage among women age 20-49 and age 25-49, and median age at first marriage among men age 20-54 and 30-54, according to background characteristics, Zimbabwe 2015 Background characteristic Women age Men age 20-49 25-49 25-54 30-54 Residence Urban a 21.2 a 26.2 Rural 18.9 19.1 24.8 25.1 Province Manicaland 19.2 19.4 24.9 25.0 Mashonaland Central 18.3 18.4 24.4 24.6 Mashonaland East 19.3 19.4 a 25.4 Mashonaland West 18.6 18.7 a 25.8 Matabeleland North 19.8 19.9 a 26.1 Matabeleland South a 21.2 a 26.9 Midlands 19.5 19.7 a 25.5 Masvingo 19.8 19.9 a 25.7 Harare a 21.2 a 25.6 Bulawayo a 22.4 a 27.5 Education No education 17.0 17.2 a a Primary 17.9 18.0 24.5 24.8 Secondary a 20.1 a 25.3 More than secondary a 23.6 a 27.1 Wealth quintile Lowest 18.3 18.5 24.4 24.8 Second 18.6 18.7 24.6 24.8 Middle 19.3 19.4 25.0 25.1 Fourth a 20.2 a 25.6 Highest a 21.6 a 26.6 Total 19.7 19.8 a 25.6 Note: The age at first marriage is defined as the age at which the respondent began living with her/his first spouse/partner. a = Omitted because less than 50 percent of the respondents began living with their spouse/partners for the first time before reaching the beginning of the age group Marriage and Sexual Activity • 71 Table 4.5 Age at first sexual intercourse Percentage of women and men age 15-49 who had first sexual intercourse by exact ages, percentage who never had sexual intercourse, and median age at first sexual intercourse, according to current age, Zimbabwe 2015 Current age Percentage who had first sexual intercourse by exact age: Percentage who never had intercourse Number of respondents Median age at first intercourse 15 18 20 22 25 WOMEN 15-19 4.7 na na na na 66.9 2,199 a 20-24 4.4 40.9 68.7 na na 16.0 1,697 18.6 25-29 5.7 41.1 67.8 82.7 93.8 2.9 1,657 18.6 30-34 4.9 39.0 64.2 80.4 91.2 1.3 1,619 18.8 35-39 4.4 39.9 66.5 83.2 93.8 1.2 1,236 18.7 40-44 8.1 38.9 65.1 81.8 93.4 0.9 965 18.8 45-49 7.0 42.7 66.3 81.6 92.0 1.3 582 18.6 20-49 5.4 40.3 66.6 na na 4.8 7,756 18.7 25-49 5.7 40.1 66.0 81.9 92.9 1.6 6,060 18.7 15-24 4.6 na na na na 44.7 3,895 a MEN 15-19 5.8 na na na na 72.9 2,126 a 20-24 5.0 26.4 55.5 na na 22.6 1,330 19.6 25-29 4.0 27.3 47.4 67.2 86.5 4.9 1,148 20.2 30-34 4.4 24.6 45.6 66.2 84.6 1.9 1,120 20.3 35-39 4.9 25.1 46.7 63.8 79.8 0.9 917 20.3 40-44 4.7 21.9 37.8 59.7 76.6 0.6 809 20.9 45-49 3.8 20.3 39.7 59.0 75.8 0.5 591 20.8 20-49 4.5 24.8 46.7 na na 6.7 5,914 a 25-49 4.4 24.4 44.1 63.9 81.6 2.0 4,584 20.5 15-24 5.5 na na na na 53.5 3,456 a 20-54 4.4 24.6 46.5 na na 6.3 6,270 a 25-54 4.2 24.2 44.1 63.7 81.3 1.9 4,940 20.5 na = Not applicable due to censoring a = Omitted because less than 50 percent of the respondents had sexual intercourse for the first time before reaching the beginning of the age group 72 • Marriage and Sexual Activity Table 4.6 Median age at first sexual intercourse by background characteristics Median age at first sexual intercourse among women age 20-49 and age 25-49, and median age at first sexual intercourse among men age 20-54 and age 25-54, according to background characteristics, Zimbabwe 2015 Background characteristic Women age Men age 20-49 25-49 20-54 25-54 Residence Urban 19.8 19.9 a 20.5 Rural 18.1 18.1 a 20.5 Province Manicaland 18.5 18.5 a 20.7 Mashonaland Central 17.9 17.9 a 20.7 Mashonaland East 18.6 18.6 a 20.7 Mashonaland West 18.1 18.1 a 20.7 Matabeleland North 17.7 17.7 19.1 19.4 Matabeleland South 18.1 18.2 18.9 19.1 Midlands 18.5 18.6 a 20.6 Masvingo 18.9 18.9 a 20.3 Harare a 20.0 a 20.4 Bulawayo 19.8 19.9 19.8 20.0 Education No education 16.3 16.4 a (20.3) Primary 17.1 17.2 a 20.2 Secondary 19.1 19.1 a 20.4 More than secondary a 22.1 a 21.5 Wealth quintile Lowest 17.5 17.6 a 20.4 Second 17.8 17.8 a 20.5 Middle 18.4 18.4 a 20.4 Fourth 19.0 19.1 a 20.3 Highest a 20.3 a 20.7 Total 18.7 18.7 a 20.5 Note: Figures in parentheses are based on 25-49 unweighted cases. a = Omitted because less than 50 percent of the respondents had intercourse for the first time before reaching the beginning of the age group Marriage and Sexual Activity • 73 Table 4.7.1 Recent sexual activity: Women Percent distribution of women age 15-49 by timing of last sexual intercourse, according to background characteristics, Zimbabwe 2015 Timing of last sexual intercourse Never had sexual intercourse Total Number of women Background characteristic Within the past 4 weeks Within 1 year1 One or more years Missing Age 15-19 17.7 11.5 3.8 0.1 66.9 100.0 2,199 20-24 55.7 20.2 7.8 0.3 16.0 100.0 1,697 25-29 67.7 20.6 8.2 0.6 2.9 100.0 1,657 30-34 71.8 19.8 6.3 0.8 1.3 100.0 1,619 35-39 69.7 18.5 10.0 0.6 1.2 100.0 1,236 40-44 61.7 18.1 18.7 0.7 0.9 100.0 965 45-49 57.3 14.0 26.0 1.5 1.3 100.0 582 Marital status Never married 5.3 12.6 8.4 0.4 73.3 100.0 2,511 Married or living together 82.4 15.4 1.9 0.3 0.0 100.0 6,151 Divorced/separated/ widowed 16.0 37.1 45.0 1.9 0.0 100.0 1,292 Marital duration2 0-4 years 79.6 18.9 1.3 0.2 0.0 100.0 1,292 5-9 years 85.4 12.8 1.4 0.4 0.0 100.0 1,264 10-14 years 81.6 16.3 1.8 0.2 0.0 100.0 1,002 15-19 years 82.9 14.0 2.6 0.5 0.0 100.0 788 20-24 years 80.9 15.4 3.3 0.5 0.0 100.0 503 25+ years 81.5 15.1 3.3 0.1 0.0 100.0 339 Married more than once 83.8 14.3 1.8 0.1 0.0 100.0 963 Residence Urban 52.6 15.4 9.4 0.9 21.8 100.0 3,829 Rural 55.5 18.8 9.0 0.3 16.4 100.0 6,126 Province Manicaland 53.3 18.3 11.7 0.8 15.9 100.0 1,266 Mashonaland Central 64.9 13.5 6.8 0.1 14.8 100.0 882 Mashonaland East 57.3 16.4 9.0 0.4 16.9 100.0 952 Mashonaland West 62.0 13.0 7.2 0.0 17.8 100.0 1,160 Matabeleland North 51.2 24.5 9.2 0.4 14.9 100.0 465 Matabeleland South 42.7 33.4 9.4 0.2 14.3 100.0 419 Midlands 56.4 17.0 7.8 0.1 18.7 100.0 1,263 Masvingo 48.2 20.1 10.2 0.5 21.0 100.0 1,187 Harare 52.5 13.7 9.7 1.6 22.6 100.0 1,783 Bulawayo 45.2 22.8 10.2 0.2 21.6 100.0 577 Education No education 59.5 19.0 18.1 2.9 0.5 100.0 126 Primary 61.6 18.1 10.6 0.0 9.6 100.0 2,571 Secondary 51.0 17.3 8.3 0.6 22.7 100.0 6,527 More than secondary 57.2 16.4 10.4 1.0 15.0 100.0 731 Wealth quintile Lowest 57.0 20.2 10.3 0.2 12.3 100.0 1,704 Second 56.3 20.1 7.8 0.3 15.6 100.0 1,693 Middle 53.0 18.5 9.7 0.2 18.6 100.0 1,748 Fourth 57.4 16.7 8.2 0.7 17.0 100.0 2,307 Highest 49.3 13.9 9.7 1.0 26.0 100.0 2,503 Total 54.3 17.5 9.1 0.5 18.5 100.0 9,955 1 Excludes women who had sexual intercourse within the last 4 weeks 2 Excludes women who are not currently married 74 • Marriage and Sexual Activity Table 4.7.2 Recent sexual activity: Men Percent distribution of men age 15-49 by timing of last sexual intercourse, according to background characteristics, Zimbabwe 2015 Timing of last sexual intercourse Never had sexual intercourse Total Number of men Background characteristic Within the past 4 weeks Within 1 year1 One or more years Missing Age 15-19 5.4 14.2 7.6 0.0 72.9 100.0 2,126 20-24 32.8 32.7 11.9 0.0 22.6 100.0 1,330 25-29 64.8 23.1 7.2 0.0 4.9 100.0 1,148 30-34 82.5 11.8 3.9 0.0 1.9 100.0 1,120 35-39 84.7 10.5 3.9 0.0 0.9 100.0 917 40-44 83.1 9.7 6.4 0.2 0.6 100.0 809 45-49 81.0 12.0 6.5 0.0 0.5 100.0 591 Marital status Never married 10.4 24.5 11.5 0.0 53.6 100.0 3,624 Married or living together 91.2 8.1 0.6 0.0 0.0 100.0 4,010 Divorced/separated/ widowed 27.2 40.6 32.1 0.0 0.0 100.0 407 Marital duration2 0-4 years 92.1 7.9 0.0 0.0 0.0 100.0 254 5-9 years 90.9 8.9 0.3 0.0 0.0 100.0 220 10-14 years 93.3 5.6 1.1 0.0 0.0 100.0 160 15-19 years 87.3 11.0 1.7 0.0 0.0 100.0 149 20-24 years 97.0 3.0 0.0 0.0 0.0 100.0 92 25+ years (90.7) (9.3) (0.0) (0.0) (0.0) 100.0 32 Married more than once 91.1 8.2 0.6 0.0 0.0 100.0 3,104 Residence Urban 54.2 19.5 6.0 0.1 20.2 100.0 2,900 Rural 50.1 15.8 7.7 0.0 26.4 100.0 5,140 Province Manicaland 46.2 16.5 8.9 0.0 28.5 100.0 1,072 Mashonaland Central 57.6 11.1 9.4 0.0 21.9 100.0 806 Mashonaland East 52.9 15.3 7.3 0.0 24.4 100.0 807 Mashonaland West 53.8 14.7 7.1 0.0 24.4 100.0 1,004 Matabeleland North 51.5 21.4 6.6 0.0 20.4 100.0 366 Matabeleland South 50.2 24.3 5.2 0.0 20.4 100.0 335 Midlands 52.6 16.2 5.9 0.0 25.2 100.0 986 Masvingo 46.7 16.2 6.7 0.0 30.4 100.0 843 Harare 52.9 21.0 6.0 0.1 20.1 100.0 1,412 Bulawayo 49.2 22.1 7.2 0.0 21.4 100.0 409 Education No education (44.2) (22.3) (14.0) (0.0) (19.5) 100.0 38 Primary 50.5 16.5 7.8 0.0 25.2 100.0 1,803 Secondary 49.5 17.2 7.0 0.0 26.4 100.0 5,349 More than secondary 67.2 18.4 6.0 0.2 8.3 100.0 849 Wealth quintile Lowest 58.5 13.0 6.9 0.0 21.7 100.0 1,212 Second 49.0 16.9 8.2 0.0 25.9 100.0 1,448 Middle 45.5 16.5 8.0 0.0 30.0 100.0 1,558 Fourth 53.0 19.0 6.7 0.0 21.3 100.0 1,852 Highest 52.5 18.7 6.2 0.1 22.5 100.0 1,970 Total 15-49 51.5 17.2 7.1 0.0 24.2 100.0 8,041 50-54 81.4 11.6 6.6 0.1 0.4 100.0 355 Total 15-54 52.8 16.9 7.1 0.0 23.2 100.0 8,396 Note: Figures in parentheses are based on 25-49 unweighted cases. 1 Excludes men who had sexual intercourse within the last 4 weeks 2 Excludes men who are not currently married Fertility • 75 FERTILITY 5 Key Findings  Total fertility rate: The current total fertility rate in Zimbabwe is 4.0 children per woman, a slight decline from 4.1 children per woman in the 2010-11 ZDHS (4.1 children).  Patterns of fertility: Fertility levels are markedly lower among urban women, highly educated women, and women in wealthy households compared with other women.  Birth intervals: The median birth interval in Zimbabwe has decreased in Zimbabwe from 47.1 months in 2010- 11 to 43.5 months in 2015.  Age at first birth: The median age at first birth among women age 25-49 is 20.3. n the 2015 ZDHS, data were collected on current and completed fertility. The birth histories of women interviewed in the survey contribute to a description of level and differentials in current fertility. The number of children that a woman bears depends on many factors, including the age she begins childbearing, how long she waits between births, and her fecundity. Postponing first births and extending the interval between births have played a role in reducing fertility levels in many countries. These factors also have positive health consequences. In contrast, short birth intervals (of less than 24 months) can lead to harmful outcomes for both newborns and their mothers, such as preterm birth, low birth weight, and death. Childbearing at a very young age is associated with an increased risk of complications during pregnancy and childbirth and higher rates of neonatal mortality. This chapter describes the current level of fertility in Zimbabwe and some of its proximate determinants. It presents information on the total fertility rate, birth intervals, insusceptibility to pregnancy (due to postpartum amenorrhoea, postpartum abstinence, or menopause), age at first birth, and teenage childbearing. The chapter also shows trends in fertility, including an examination of age-specific fertility rates in periods dating back 15 to 20 years. The fertility indicators presented in this chapter are based on reports of reproductive histories provided by women age 15-49. As in the previous ZDHS surveys, each woman was asked to provide information on the total number of sons and daughters to whom she had given birth and who were living with her, the number of children living elsewhere, and the number who had died. These data were used to obtain the total number of live births. In the birth history, women reported the details of each live birth separately, including information such as name, month, year of birth, sex, and survival status. Information on age at death was collected for children who had died. I 76 • Fertility 5.1 CURRENT FERTILITY Total fertility rate The average number of children a woman would have by the end of her childbearing years if she bore children at the current age-specific fertility rates. Age-specific fertility rates are calculated for the 3 years before the survey, based on detailed birth histories provided by women. Sample: Women age 15-49 The total fertility rate (TFR) in Zimbabwe is 4.0 children per woman (Table 5.1). Childbearing peaks at age 20-24 (204 births per 1,000 women), and drops steadily thereafter. Rural women have 1.7 more children, on average, than urban women (TFR of 4.7 versus 3.0 children). Trends: Since 1988, the TFR has declined by 1.4 births, from 5.4 to 4.0 children (Figure 5.1). However, the decline has not been linear; TFR declined between 1988 and 2005-06 from 5.4 to 3.8 children per woman. It increased to 4.1 children per woman in 2010-11, and declined slightly to 4.0 children per woman in 2015. Patterns by background characteristics  The total fertility rate ranges from a low of 2.7 children in Bulawayo to a high of 5.0 children in Manicaland (Figure 5.2).  The number of children a woman bears generally decreases as her education level increases. Women with some primary education have, on average, 2.8 more children than women with more than secondary education (Table 5.2). Figure 5.1 Trends in total fertility rate (TFR) Figure 5.2 Total fertility rate by province TFR for the 3 years before the survey 5.4 4.3 4.0 3.8 4.1 4.0 3.8 3.1 3.0 2.6 3.1 3.0 6.2 4.9 4.6 4.6 4.8 4.7 1988 1994 1999 2005-06 2010-11 2015 TFR for the 3 years before each survey Rural Total Urban Fertility • 77  Women in the lowest wealth quintile have, on average, 3.2 more children than women in the highest quintile (5.6 versus 2.4 children) (Figure 5.3). More information on trends in age- specific fertility rates for this survey is found in Table 5.3.1, and more information on trends in age- specific and total fertility rates across ZDHS surveys is found in Table 5.3.2 and Figure 5.4. Figure 5.4 Total fertility rate by wealth quintile 5.2 CHILDREN EVER BORN AND LIVING The survey also collected data on the number of children ever born to women age 15-49 and those still living. Of the 4.0 average children ever born to women age 45-49, 2.0 survived to the time of the survey. For complete information on children ever born and living, by mother’s age, see Table 5.4. 5.6 4.9 4.5 3.7 2.4 4.0 Lowest Second Middle Fourth Highest Total Poorest Richest TFR for the 3 years before the survey Figure 5.3 Trends in age-specific fertility rates 0 50 100 150 200 250 300 15-19 20-24 25-29 30-34 35-39 40-44 45-49 1988 1994 1999 2005-06 2010-11 2015 Births per 1,000 women Age at birth 78 • Fertility 5.3 BIRTH INTERVALS Median birth interval Number of months since the preceding birth by which half of children are born Sample: Non-first births in the 5 years before the survey The median birth interval in Zimbabwe is 43.7 months. Eleven percent of children in Zimbabwe are born after a short interval (less than 24 months) (Table 5.5 and Figure 5.5). Short birth intervals place newborns and their mothers at greater health risks. Trends: Birth intervals have decreased over the last decade in Zimbabwe, with the median interval decreasing by over 3 months between 2010-11 and 2015 (from 47.1 to 43.7 months). Patterns by background characteristics  Births to older women have longer intervals than births to younger women. The median birth interval is nearly 2 years longer among women age 40-49 than women age 20-29 (59.7 months versus 37.9 months) (Table 5.5).  The median birth interval in urban areas is more than 7 months longer than in rural areas (49.3 months versus 41.8 months).  The median birth interval ranges from 39.9 months in Manicaland to 49.2 months in Harare.  Birth intervals are longer by about 8 months for births to women with more than secondary education compared with births to women with no education (50.1 months versus 41.8 months).  Births to women in wealthier households have longer birth intervals. The median birth interval in the highest wealth quintile is more than 12 months longer than in the lowest quintile (51.0 months versus 38.4 months). 5.4 INSUSCEPTIBILITY TO PREGNANCY Median duration of postpartum amenorrhoea Number of months after childbirth by which time half of women have begun menstruating Sample: Women who gave birth in the 3 years before the survey Median duration of postpartum insusceptibility Number of months after childbirth by which time half of women are no longer protected against pregnancy either by postpartum amenorrhoea or abstinence from sex Sample: Women who gave birth in the 3 years before the survey Figure 5.5 Birth interval distribution Percent distribution of non-first births in the five years preceding the survey by number of months since preceding birth 7-23 months 11% 24-35 months 24% 36-47 months 21% 48-59 months 16% 60+ months 27% Fertility • 79 Almost all women are insusceptible to pregnancy during the first 2 months after a birth; and continued postpartum amenorrhoea and abstinence from sexual intercourse may protect them from pregnancy for longer periods. In Zimbabwe, for births in the 3 years preceding the survey, the median duration of postpartum amenorrhoea is 12.5 months, and women abstain from sexual intercourse for a median of 2.1 months after giving birth. Women are insusceptible to pregnancy after childbirth (either because they are amenorrhoeic or because they are still abstaining from sex after birth) for a median of 13.7 months (Table 5.6). Trends: From 2010-11 to 2015, the median duration of postpartum amenorrhoea has increased, from 11.6 months in 2010-11 to 12.5 months in 2015. The duration of postpartum abstinence has remained similar at 2.3 months 2010-11 and 2.1 months in 2015. Postpartum insusceptibility to pregnancy increased from 12.7 months in 2010-11 to 13.7 months in 2015. Patterns by background characteristics  Older women have a longer duration of postpartum amenorrhoea: 14.7 months among women age 30- 49 versus 9.9 months among women age 15-29. However, older women have a similar duration of postpartum abstinence as younger women (2.3 and 2.1 months, respectively) (Table 5.7).  Urban women remain amenorrhoeic longer than rural women (12.8 versus 12.4 months). The duration of postpartum abstinence is similar among urban and rural women (1.8 months and 2.2 months, respectively).  The duration of postpartum amenorrhoea and insusceptibility is highest in the highest wealth quintile (13.7 and 14.9 months, respectively). With the exception of the highest wealth quintile, the duration of postpartum amenorrhoea generally decreases as wealth increases, from 13.9 months in the lowest quintile to 10.0 months in the fourth quintile. The duration of postpartum insusceptibility also generally decreases with increasing wealth, from 15.1 months in the lowest quintile to 10.6 months in the fourth quintile. Menopause Women are considered to have reached menopause if they are neither pregnant nor postpartum amenorrhoeic and have not had a menstrual period in the 6 months before the survey, or if they report being menopausal. Sample: Women age 30-49 Once women reach menopause, they are no longer able to become pregnant. Overall, 8 percent of women age 30-49 are menopausal. This proportion increases with age, from 3 percent among women age 30-34 to 32 percent among women age 48-49 (Table 5.8 and Figure 5.6). Figure 5.6 Percentage of menopausal women by age 3 4 7 10 19 25 32 30-34 35-39 40-41 42-43 44-45 46-47 48-49 Age group 80 • Fertility 5.5 AGE AT FIRST BIRTH Median age at first birth Age by which half of women have had their first child. Sample: Women age 20-49 and 25-49 The median age at first birth in Zimbabwe is 20.3 years among women age 25-49 (Table 5.9). The median age at first birth in Zimbabwe has remained similar to that observed in the 2010-11 ZDHS (20.2 years). Patterns by background characteristics  Women in urban areas begin childbearing 2 years later, on average, than rural women (21.6 versus 19.6 years) (Table 5.10).  Highly educated women have their first child later than other women. Women with more than secondary education begin childbearing about 6 years later than women with no education (24.0 versus 18.1 years).  Women in the lowest wealth quintile have their first birth 3 years earlier, on average, than women in the highest quintile (19.2 versus 22.2 years). 5.6 TEENAGE CHILDBEARING Teenage childbearing Percentage of women age 15-19 who have given birth or are pregnant with their first child. Sample: Women age 15-19 In Zimbabwe, 22 percent of women age 15-19 have begun childbearing: 17 percent have given birth, and an additional 5 percent are pregnant with their first child (Table 5.11). Trends: Teenage childbearing has declined slightly over the last 5 years from 19 percent in 2010-11 to 17 percent in 2015. Patterns by background characteristics  Teenagers in rural areas are almost three times as likely their urban peers to begin childbearing: 27 percent of rural teenagers have begun childbearing, compared with 10 percent of urban teenagers (Table 5.11). Fertility • 81  Some provinces have much higher rates of teenage childbearing than others. The percentage of teenagers who have begun childbearing ranges from a low of 10 percent in Harare to a high of 31 percent in Mashonaland Central (Figure 5.7).  Teenage childbearing is less common among young women in the wealthiest households. Teenagers in the lowest wealth quintile are almost six times more likely to have started childbearing by age 19 as those in the highest quintile (34 percent versus 6 percent, respectively). LIST OF TABLES For more information on fertility levels and some of the determinants of fertility, see the following tables:  Table 5.1 Current fertility  Table 5.2 Fertility by background characteristics  Table 5.3.1 Trends in age-specific fertility rates  Table 5.3.2 Trends in age-specific and total fertility rates, 1988-2015  Table 5.4 Children ever born and living  Table 5.5 Birth intervals  Table 5.6 Postpartum amenorrhoea, abstinence, and insusceptibility  Table 5.7 Median duration of amenorrhoea, postpartum abstinence, and postpartum insusceptibility  Table 5.8 Menopause  Table 5.9 Age at first birth  Table 5.10 Median age at first birth  Table 5.11 Teenage pregnancy and motherhood Figure 5.7 Teenage childbearing by province Percentage of women age 15-19 who have begun childbearing 82 • Fertility Table 5.1 Current fertility Age-specific and total fertility rates, general fertility rate, and crude birth rate for the 3 years preceding the survey, according to residence, Zimbabwe 2015 Residence Total Age group Urban Rural 15-19 63 138 110 20-24 153 243 204 25-29 171 222 201 30-34 118 167 147 35-39 77 118 102 40-44 15 44 34 45-49 3 8 6 TFR (15-49) 3.0 4.7 4.0 GFR 110 166 144 CBR 31.1 32.7 32.0 Notes: Age-specific fertility rates are per 1,000 women. Rates for age group 45-49 may be slightly biased due to truncation. Rates are for the period 1-36 months prior to interview. TFR: Total fertility rate expressed per woman GFR: General fertility rate expressed per 1,000 women age 15-44 CBR: Crude birth rate, expressed per 1,000 population Fertility • 83 Table 5.2 Fertility by background characteristics Total fertility rate for the 3 years preceding the survey, percentage of women age 15-49 currently pregnant, and mean number of children ever born to women age 40-49 years, according to background characteristics, Zimbabwe 2015 Background characteristic Total fertility rate Percentage of women age 15-49 currently pregnant Mean number of children ever born to women age 40-49 Residence Urban 3.0 5.3 3.2 Rural 4.7 7.0 4.7 Province Manicaland 5.0 7.5 4.6 Mashonaland Central 4.4 9.1 4.5 Mashonaland East 4.3 6.4 4.3 Mashonaland West 4.3 6.8 4.2 Matabeleland North 4.4 5.2 5.0 Matabeleland South 3.5 6.4 4.1 Midlands 4.2 5.8 4.4 Masvingo 4.4 5.9 4.4 Harare 2.8 5.5 3.2 Bulawayo 2.7 4.2 2.9 Education No education 4.7 5.7 5.7 Primary 5.0 7.3 5.2 Secondary 3.8 6.2 3.7 More than secondary 2.2 4.5 2.5 Wealth quintile Lowest 5.6 7.9 5.5 Second 4.9 7.6 4.7 Middle 4.5 5.9 4.6 Fourth 3.7 6.8 3.6 Highest 2.4 4.4 3.0 Total 4.0 6.3 4.2 Note: Total fertility rates are for the period 1-36 months prior to interview. 84 • Fertility Table 5.3.1 Trends in age-specific fertility rates Age-specific fertility rates for five-year periods preceding the survey, by mother’s age at the time of the birth, Zimbabwe 2015 Mother’s age at birth Number of years preceding survey 0-4 5-9 10-14 15-19 15-19 112 118 114 109 20-24 213 207 204 225 25-29 207 183 178 201 30-34 155 157 153 [176] 35-39 111 104 [111] 40-44 37 [52] 45-49 [7] Note: Age-specific fertility rates are per 1,000 women. Estimates in brackets are truncated. Rates exclude the month of interview. Fertility • 85 Table 5.3.2 Trends in age-specific and total fertility rates, 1985-2015 Age-specific and total fertility rates (TFR) for the three-year period preceding several surveys, according to mother’s age at the time of the birth, Zimbabwe 1985-2015 Mother’s age at birth 1988 ZDHS (1985-88) 1994 ZDHS (1991-94) 1999 ZDHS (1996-99) 2005-06 ZDHS (2002-03 - 2005-06) 2010-11 ZDHS (2007-08 - 2010-11) 2015 ZDHS (2012-15) 15-19 102 99 112 99 115 110 20-24 251 210 199 205 212 204 25-29 250 194 180 172 194 201 30-34 212 172 135 144 149 147 35-39 158 117 108 86 104 102 40-44 80 52 46 42 35 34 45-49 32 14 15 13 12 6 TFR 15-49 5.4 4.3 4.0 3.8 4.1 4.0 Note: Age-specific fertility rates are per 1,000 women. Rates for age group 45-49 may be slightly biased due to truncation. 86 • Fertility Table 5.4 Children ever born and living Percent distribution of all women and currently married women age 15-49 by number of children ever born, mean number of children ever born, and mean number of living children, according to age group, Zimbabwe 2015 Age group Number of children ever born Total Number of women Mean number of children ever born Mean number of living children 0 1 2 3 4 5 6 7 8 9 10+ ALL WOMEN 15-19 83.2 15.4 1.4 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 100.0 2,199 0.18 0.17 20-24 29.7 37.2 25.2 6.5 1.3 0.1 0.0 0.0 0.0 0.0 0.0 100.0 1,697 1.13 1.05 25-29 8.7 18.3 34.4 26.0 8.9 2.7 0.6 0.3 0.0 0.0 0.0 100.0 1,657 2.20 2.04 30-34 4.7 9.2 23.8 29.0 20.3 8.1 3.7 0.8 0.2 0.1 0.0 100.0 1,619 2.96 2.75 35-39 2.5 5.2 16.2 26.6 21.4 15.7 7.9 2.5 1.2 0.4 0.3 100.0 1,236 3.63 3.33 40-44 3.6 5.3 12.9 20.9 20.5 14.2 10.1 5.5 3.2 1.6 2.3 100.0 965 4.10 3.68 45-49 4.3 4.5 11.6 16.2 24.3 14.4 10.9 6.0 2.7 2.2 2.9 100.0 582 4.25 3.88 Total 26.6 15.7 18.1 16.4 11.1 5.9 3.3 1.4 0.7 0.3 0.4 100.0 9,955 2.18 2.00 CURRENTLY MARRIED WOMEN 15-19 41.7 52.2 6.1 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 100.0 432 0.64 0.60 20-24 10.2 43.7 34.6 9.2 2.2 0.1 0.0 0.0 0.0 0.0 0.0 100.0 1,045 1.50 1.39 25-29 3.4 15.8 36.5 29.3 10.4 3.4 0.8 0.4 0.0 0.0 0.0 100.0 1,278 2.43 2.24 30-34 2.1 7.2 22.5 31.7 21.6 9.1 4.3 1.0 0.3 0.1 0.0 100.0 1,333 3.15 2.93 35-39 0.6 3.4 14.3 27.0 22.8 17.6 9.2 3.0 1.5 0.5 0.2 100.0 975 3.87 3.55 40-44 2.4 2.9 10.4 20.7 20.8 16.2 11.6 6.3 3.5 2.2 2.9 100.0 707 4.44 3.99 45-49 1.6 1.8 8.0 15.4 26.8 17.2 11.9 6.5 3.9 3.2 3.5 100.0 381 4.72 4.33 Total 6.3 16.9 22.7 22.1 14.9 8.4 4.6 1.9 0.9 0.5 0.6 100.0 6,151 2.90 2.67 Fertility • 87 Table 5.5 Birth intervals Percent distribution of non-first births in the 5 years preceding the survey by number of months since preceding birth, and median number of months since preceding birth, according to background characteristics, Zimbabwe 2015 Background characteristic Months since preceding birth Total Number of non-first births Median number of months since preceding birth 7-17 18-23 24-35 36-47 48-59 60+ Age 15-19 (11.9) (21.9) (50.7) (14.5) (0.0) (0.9) 100.0 29 (27.1) 20-29 5.9 8.7 30.8 25.7 15.9 13.0 100.0 2,085 37.9 30-39 2.9 6.0 20.0 18.4 17.1 35.7 100.0 2,204 49.6 40-49 1.6 4.4 14.7 15.9 14.0 49.4 100.0 429 59.7 Sex of preceding birth Male 3.9 7.0 23.2 21.8 16.4 27.7 100.0 2,389 44.5 Female 4.3 7.3 25.7 20.9 16.0 25.8 100.0 2,358 42.8 Survival of preceding birth Living 2.2 6.1 24.3 22.4 17.0 28.0 100.0 4,270 44.5 Dead 23.7 18.0 26.0 12.1 7.4 12.8 100.0 435 26.5 Birth order 2-3 4.1 6.3 23.7 21.5 16.3 28.1 100.0 2,928 44.9 4-6 4.1 8.3 24.2 20.8 16.0 26.6 100.0 1,600 42.8 7+ 4.3 10.4 35.9 24.0 15.3 10.0 100.0 219 35.8 Residence Urban 4.1 7.1 20.2 16.5 17.0 35.1 100.0 1,421 49.3 Rural 4.2 7.1 26.3 23.4 15.8 23.2 100.0 3,326 41.8 Province Manicaland 3.5 8.5 30.1 22.9 15.3 19.8 100.0 742 39.9 Mashonaland Central 3.0 6.0 20.1 23.3 18.0 29.5 100.0 486 46.2 Mashonaland East 4.8 6.3 25.3 22.4 19.1 22.1 100.0 453 43.5 Mashonaland West 5.5 5.5 25.7 21.6 15.7 26.0 100.0 666 41.9 Matabeleland North 3.3 7.2 21.3 22.0 16.3 29.9 100.0 208 45.9 Matabeleland South 5.2 5.2 23.4 21.3 15.9 29.0 100.0 157 44.0 Midlands 4.8 10.7 22.3 22.6 16.3 23.4 100.0 622 41.9 Masvingo 3.0 6.3 29.3 21.3 13.2 26.8 100.0 568 41.7 Harare 4.4 6.0 19.6 17.7 16.7 35.6 100.0 682 49.2 Bulawayo 3.8 9.4 20.8 14.9 15.6 35.6 100.0 164 49.0 Education No education 1.4 1.6 23.2 37.8 18.7 17.2 100.0 74 41.8 Primary 4.6 7.2 26.8 23.3 16.1 22.0 100.0 1,615 41.4 Secondary 4.1 7.3 23.4 20.3 16.2 28.7 100.0 2,813 44.7 More than secondary 2.3 6.3 21.7 15.8 15.0 38.8 100.0 245 50.1 Wealth quintile Lowest 4.5 8.7 29.9 22.8 16.7 17.4 100.0 1,170 38.4 Second 4.6 6.3 27.1 25.2 15.6 21.2 100.0 969 41.5 Middle 3.4 6.6 24.2 24.2 14.2 27.4 100.0 805 43.4 Fourth 5.0 7.2 20.6 17.3 16.8 33.1 100.0 1,064 47.9 Highest 2.6 6.3 18.1 16.8 17.3 39.0 100.0 739 51.0 Total 4.1 7.1 24.4 21.4 16.2 26.8 100.0 4,747 43.7 Notes: First-order births are excluded. The interval for multiple births is the number of months since the preceding pregnancy that ended in a live birth. Figures in parentheses are based on 25-49 unweighted cases. 88 • Fertility Table 5.6 Postpartum amenorrhoea, abstinence, and insusceptibility Percentage of births in the 3 years preceding the survey for which mothers are postpartum amenorrhoeic, abstaining, and insusceptible, according to number of months since birth, and median and mean durations, Zimbabwe 2015 Months since birth Percentage of births for which the mother is: Number of births Amenorrhoeic Abstaining Insusceptible1 <2 80.9 80.2 94.5 207 2-3 58.8 27.6 67.4 237 4-5 64.0 17.1 66.9 190 6-7 61.3 14.4 66.3 195 8-9 60.4 13.2 66.3 214 10-11 57.5 7.7 60.4 178 12-13 48.9 9.5 54.5 223 14-15 45.5 9.4 51.1 213 16-17 28.0 9.8 34.5 221 18-19 18.9 6.1 23.5 208 20-21 17.5 6.9 23.1 201 22-23 4.8 5.8 10.7 197 24-25 5.7 7.7 13.4 210 26-27 2.8 4.2 7.0 207 28-29 1.2 2.5 3.7 246 30-31 1.3 5.1 6.3 187 32-33 1.3 2.7 4.0 220 34-35 1.9 5.3 7.2 189 Total 31.0 13.1 36.6 3,742 Median 12.5 2.1 13.7 na Mean 11.6 5.0 13.5 na Note: Estimates are based on status at the time of the survey. na = Not applicable 1 Includes births for which mothers are either still amenorrhoeic or still abstaining (or both) following birth Fertility • 89 Table 5.7 Median duration of amenorrhoea, postpartum abstinence, and postpartum insusceptibility Median number of months of postpartum amenorrhoea, postpartum abstinence, and postpartum insusceptibility following births in the 3 years preceding the survey, according to background characteristics, Zimbabwe 2015 Background characteristic Postpartum amenorrhoea Postpartum abstinence Postpartum insusceptibility1 Mother’s age 15-29 9.9 2.1 12.7 30-49 14.7 2.3 15.2 Residence Urban 12.8 1.8 13.8 Rural 12.4 2.2 13.6 Province Manicaland 13.9 (2.5) 15.0 Mashonaland Central 14.5 * 15.2 Mashonaland East 13.3 * 13.3 Mashonaland West 12.0 (2.2) 12.3 Matabeleland North 10.3 (3.5) 15.6 Matabeleland South (8.7) 2.9 (12.2) Midlands 8.8 (1.8) 10.0 Masvingo 6.6 * 8.8 Harare 13.7 * 14.8 Bulawayo (8.4) * (12.9) Education Primary 13.6 2.6 14.2 Secondary 11.4 2.0 13.1 More than secondary * * (14.8) Wealth quintile Lowest 13.9 (2.1) 15.1 Second 12.7 (2.4) 14.3 Middle 12.7 (2.1) 13.4 Fourth 10.0 2.2 10.6 Highest 13.7 (1.7) 14.9 Total 12.5 2.1 13.7 Notes: Medians are based on the status at the time of the survey (current status). Figures in parentheses are based on 25-49 unweighted cases. An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. 1 Includes births for which mothers are either still amenorrhoeic or still abstaining (or both) following birth 90 • Fertility Table 5.8 Menopause Percentage of women age 30-49 who are menopausal, according to age, Zimbabwe 2015 Age Percentage menopausal1 Number of women 30-34 2.7 1,619 35-39 4.0 1,236 40-41 7.2 461 42-43 9.7 386 44-45 18.6 276 46-47 24.9 255 48-49 32.2 170 Total 7.6 4,402 1 Percentage of all women who are not pregnant and not postpartum amenorrhoeic whose last menstrual period occurred six or more months preceding the survey Fertility • 91 Table 5.9 Age at first birth Percentage of women age 15-49 who gave birth by specific exact ages, percentage who have never given birth, and median age at first birth, according to current age, Zimbabwe 2015 Percentage who gave birth by exact age Percentage who have never given birth Number of women Median age at first birth Current age 15 18 20 22 25 15-19 0.6 na na na na 83.2 2,199 a 20-24 1.2 22.0 50.5 na na 29.7 1,697 20.0 25-29 1.5 21.9 49.5 69.7 86.2 8.7 1,657 20.0 30-34 1.6 22.2 46.0 67.2 84.6 4.7 1,619 20.3 35-39 2.1 19.3 48.5 68.3 87.9 2.5 1,236 20.1 40-44 3.1 21.8 43.6 65.9 84.6 3.6 965 20.5 45-49 2.5 23.8 43.8 65.3 81.9 4.3 582 20.6 20-49 1.8 21.7 47.7 na na 10.5 7,756 a 25-49 2.0 21.6 46.9 67.7 85.5 5.2 6,060 20.3 na = Not applicable due to censoring a = Omitted because less than 50 percent of women had a birth before reaching the beginning of the age group 92 • Fertility Table 5.10 Median age at first birth Median age at first birth among women age 20-49 and 25-49 years, according to background characteristics, Zimbabwe 2015 Background characteristic Women age 20-49 25-49 Residence Urban a 21.6 Rural 19.5 19.6 Province Manicaland 19.9 20.1 Mashonaland Central 19.3 19.4 Mashonaland East 19.9 19.9 Mashonaland West 19.3 19.5 Matabeleland North 19.4 19.5 Matabeleland South 19.7 19.9 Midlands 19.9 20.1 Masvingo a 20.6 Harare a 21.7 Bulawayo a 21.9 Education No education 17.9 18.1 Primary 18.6 18.7 Secondary a 20.6 More than secondary a 24.0 Wealth quintile Lowest 19.1 19.2 Second 19.3 19.3 Middle 19.8 19.9 Fourth a 20.7 Highest a 22.2 Total a 20.3 a = Omitted because less than 50 percent of the women had a birth before reaching the beginning of the age group Fertility • 93 Table 5.11 Teenage pregnancy and motherhood Percentage of women age 15-19 who have had a live birth or who are pregnant with their first child, and percentage who have begun childbearing, by background characteristics, Zimbabwe 2015 Percentage of women age 15-19 who: Percentage who have begun childbearing Number of women Background characteristic Have had a live birth Are pregnant with first child Age 15 1.8 1.4 3.2 487 16 6.7 2.6 9.4 472 17 15.7 5.7 21.4 435 18 22.9 8.1 31.0 384 19 40.9 7.4 48.3 421 Residence Urban 7.1 3.3 10.3 724 Rural 21.6 5.6 27.2 1,475 Province Manicaland 18.8 8.8 27.7 291 Mashonaland Central 24.0 6.9 30.9 199 Mashonaland East 20.5 4.9 25.3 220 Mashonaland West 18.2 2.2 20.4 244 Matabeleland North 22.6 3.5 26.1 109 Matabeleland South 23.8 6.5 30.3 99 Midlands 18.5 5.4 23.9 302 Masvingo 14.4 3.2 17.6 287 Harare 6.6 3.2 9.9 323 Bulawayo 8.7 3.6 12.2 126 Education No education * * * 4 Primary 32.3 5.5 37.8 480 Secondary 12.6 4.7 17.3 1,698 More than secondary * * * 17 Wealth quintile Lowest 27.1 6.5 33.6 360 Second 20.7 6.4 27.2 398 Middle 21.2 4.8 26.0 479 Fourth 14.2 5.8 20.0 458 Highest 4.5 1.5 6.1 504 Total 16.8 4.8 21.6 2,199 Note: An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. Fertility Preferences • 95 FERTILITY PREFERENCES 6 Key Findings  Desire for another child: Nineteen percent of currently married women age 15-49 want to have another child soon, but a higher percentage, 35 percent, want to wait at least 2 years.  Limiting childbearing: Women are more likely than men to want no more children, no matter how many children they already have. Overall, 41 percent of women and 31 percent of men do not want another child. Almost 3 in 10 women with two living children (28 percent) and half of women with three living children (50 percent) do not want any more children.  Ideal family size: Over the last decade, the ideal family size has dropped slightly for both women and men. Women currently want 3.9 children, on average, while men want 4.5 children.  Unwanted births: Of all births in the past 5 years and current pregnancies, 68 percent were wanted at the time of conception, 27 percent were mistimed, and 7 percent were unwanted. nformation on fertility preferences is important to family planning programme planners because it allows for an assessment of the need for contraception, whether for spacing or limiting births, and of the extent of unwanted and mistimed pregnancies. Data on fertility preferences can also be useful as an indicator of the direction of future fertility patterns. The 2015 ZDHS respondents were asked whether they wanted more children and, if so, how long they would prefer to wait before the next child. They were also asked, if they could start again, how many children they would want. This chapter presents information on whether and when married women and men want more children, ideal family size, whether the last birth was wanted at that time, and the theoretical fertility rate if all unwanted births were prevented. 6.1 DESIRE FOR ANOTHER CHILD Desire for another child Women and men were asked whether they wanted more children and, if so, how long they would prefer to wait before the next child. Women and men who are sterilised are assumed not to want any more children. Sample: Currently married women and men age 15-49 Table 6.1 presents fertility preferences among currently married women and men by the number of living children. In classifying individuals according to their fertility preferences, the desired timing of the next I 96 • Fertility Preferences birth is taken into account. More than half (55 percent) of currently married women in Zimbabwe would like to have another child. Among women who want another child, 19 percent want a child within the next 2 years, 35 percent would prefer to wait 2 or more years before having their next birth, and 1 percent want another child, but are undecided about the timing. Four in ten currently married women want no more children, and 1 percent are sterilised. Thus, the majority of women (76 percent) want to either delay their next birth (for 2 or more years) or end childbearing altogether, inclusive of sterilisation. As expected, the desire for more children decreases noticeably as the number of living children increases. Eighty-six percent of married women with no children want to have a child soon (within 2 years), while fewer than 1 in 10 women with four or more children want to have another soon. Among women with three or more children, the desire to limit childbearing predominates. The proportion of women who do not want another child increases from 49 percent among those with three children to 82 percent among women with six or more children. The proportion of currently married men who want no more children also increases with the increasing number of children, but it is lower than the respective proportion of women at every parity, expect for men who have no living children. Men are generally more likely than women to want to have another child, no matter how many children they already have. Tables 6.2.1 and 6.2.2 present the percentages of currently married women and men who want no more children, by number of living children and selected background characteristics. Overall, 41 percent of married women and 31 percent of married men age 15-49 want no more children. Trends: The proportion of currently married women who want no more children increased steadily from 35 percent in the 1988 ZDHS to 44 percent in the 2005-06 ZDHS, and then it decreased and stabilized at 40-41 percent in the 2010-11 and 2015 ZDHS surveys (Figure 6.1). Similar patterns are observed in trends over time among men, although smaller proportions of men want no more children when compared with women. Patterns by background characteristics  The proportion of currently married women and men who want no more children is higher in urban (46 percent and 38 percent respectively) than in rural areas (38 percent and 26 percent respectively). A larger proportion of urban than rural residents want no more children at each parity, with the exception of women with no children For example, 66 percent of urban women with three children do not want another child, compared with 41 percent of rural women (Tables 6.2.1 and 6.2.2).  More than 5 in 10 currently married women in Matabeleland South and Bulawayo (52 percent each) want no more children, compared with 32 percent of married women in Manicaland.  The desire to limit childbearing is positively associated with wealth for both women and men. For example, 43 percent of men in the highest wealth quintile want to limit childbearing compared with 21 percent of men in the lowest quintile. Figure 6.1 Trends in desire to limit childbearing 35 38 41 44 40 41 32 32 36 28 31 1988 1994 1999 2005-06 2010-11 2015 Men Women Percentage of currently married women and men age 15-49 who want no more children Fertility Preferences • 97 6.2 IDEAL NUMBER OF CHILDREN Ideal family size Respondents with no children were asked, “If you could choose exactly the number of children to have in your whole life, how many would that be?” Respondents who had children were asked: “If you could go back to the time when you did not have any children and could choose exactly the number of children to have in your whole life, how many would that be?” Sample: Women and men age 15-49 If women could choose their family size, they would choose to have 3.9 children, on average, while men would choose to have 4.5 children (Table 6.3). The mean ideal number is higher among the currently married population. Overall, 60 percent of women and 64 percent of men want four or more children. The data in the top portion of each panel in Table 6.3 indicate that the vast majority of women and men age 15- 49 were able to give a numeric answer to this hypothetical question. Less than 1 percent of women and 1 percent of men gave a nonnumeric answer such as “it is up to God,” “any number,” or “I do not know.” When interpreting the findings in Table 6.3, it is important to remember that the actual and stated ideal number of children tend to be related. There are several reasons for this. First, to the extent that women are able to implement their fertility desires, women who want large families will achieve large families. Second, because women with large families are, on average, older women, they may prefer a greater number of children because of the attitudes towards childbearing to which they were exposed during the early stages of their reproductive lives. Finally, some women may have difficulty admitting that they would prefer fewer children than they currently have if they could begin childbearing again. Such women are likely to report their actual number as their preferred number. Indeed, women who have fewer children do report a smaller ideal number of children than women with more children. Trends: The mean ideal number of children among all women age 15-49 decreased from 4.3 children in 1994 to 3.9 in 1999 and to 3.8 children in 2005-06 and 2010-11, and it increased only slightly to 3.9 children in 2015. Among all men age 15-49, the ideal family size has increased slightly over time from 4.2 children in 1999 to 4.5 children in 2015 (Figure 6.2). Patterns by background characteristics  The more children respondents already have, the more children they consider ideal. For example, the average ideal number of children among all men with one child is 4.1 compared with 8.2 among men with six or more children. Similarly, the mean ideal number of children among all women with one child is 3.5, compared with 6.5 among all women with six or more children (Figure 6.3).  Older women want larger families. The ideal family size increases from 3.3 children among women age 15-19 to 5.2 children among women age 45-49 (Table 6.4).  Women in rural areas want a larger family (4.3 children) than women in urban areas (3.4 children).  Across provinces, women in Bulawayo want a smaller family size (3.2 children) compared with women in Mashonaland Central (4.6 children). Figure 6.2 Trends in ideal family size 4.3 3.9 3.8 3.8 3.9 4.2 4 4.5 4.3 4.5 1994 1999 2005-06 2010-11 2015 Women Men Mean ideal number of children among women and men age 15-49 98 • Fertility Preferences  The ideal family size decreases with an increase in education and wealth, Women with no education prefer an ideal family size of 6.3 children compared with 3.1 children of women with more than secondary education. Similarly, women in the lowest wealth quantile prefer an ideal family size of 4.8 children compared with 3.3 children for women in the highest wealth quantile. 6.3 FERTILITY PLANNING STATUS Planning status of birth Women reported whether their most recent birth was wanted at the time (planned birth), at a later time (mistimed birth), or not at all (unwanted birth). Sample: Current pregnancies and births in the 5 years before the survey to women age 15-49 The issue of unplanned and unwanted fertility was investigated in the 2015 ZDHS by asking women who had births during the five years before the survey whether the births were wanted at the time (planned), wanted at a later time (mistimed), or not wanted at all (unwanted). The responses to those questions provide a measure of the degree to which Zimbabwean couples have been successful in controlling childbearing. In addition, the information can be used to estimate the effect on fertility if unwanted pregnancies had been prevented. The questions on the planning status of recent births required the female respondent to recall accurately her wishes at one or more points in the past five years and report them honestly. These questions are subject to recall and accuracy bias for the woman remembering how she felt about a particular pregnancy. The respondent also may not be willing to admit that she had not wanted a child at its conception. Conversely, if the child has become an economic or health burden, she may now claim that it was unwanted. Despite these potential problems of comprehension, recall, and truthfulness, results from previous surveys have yielded plausible responses, with the most probable effect of biases in the answers being a net underestimation of the level of unwanted fertility. Figure 6.3 Ideal family size by number of living children 3.2 3.5 3.8 4.8 5.3 6.5 4.0 4.1 4.2 5.2 6.3 8.2 0 1 2 4 5 6+ Mean ideal number of children among women and men age 15-49 Women Men Fertility Preferences • 99 Overall, 68 percent of all births were wanted at the time of conception, 25 percent were reported as mistimed (wanted later), and 7 percent were unwanted (Figure 6.4). Trends: Over the past two decades, the proportion of births wanted at the time of conception has increased steadily from 56 percent in 1994 to 68 percent in 2015. The proportion of births that were mistimed has decreased from 34 percent in 1994 to 25 percent in 2015. The proportion of unwanted births has also declined from 10 percent in 1994 to 7 percent in 2010-11 and 2015, although it peaked at 13 percent in 2005-06. Patterns by background characteristics  The more children a woman has, the more likely it is that her last birth was unwanted. Less than 1 percent of first births were unwanted, compared with 7 percent of third births and 17 percent of fourth or higher order births (Table 6.5).  The proportion of births that were mistimed decreases with the mother’s age, ranging from 36 percent of births to women less than age 20 to 10 percent of births to women age 40-44. 6.4 WANTED FERTILITY RATES Wanted fertility rate The number of children the average woman would have over the course of her lifetime if she bore children at current age-specific fertility rates, excluding unwanted births. A birth is considered wanted if the number of living children at the time of conception is lower than the ideal number of children currently reported by the respondent. Sample: Births to women age 15-49 during the 3 years before the survey The wanted fertility rate reflects the level of fertility that would result if all unwanted births were prevented. The wanted fertility rate in Zimbabwe is 3.6 children, compared with the actual fertility rate of 4.0 children (Table 6.6). In other words, Zimbabwean women are currently having an average of 0.4 children more than they actually want. Trends: The total wanted fertility rate in Zimbabwe decreased from 4.4 to 3.5 children between 1988 and 1994, and it has remained fairly constant over the last two decades between 3.3 and 3.6 children (Figure 6.5). However, the gap between wanted and actual fertility has decreased over the same period from 0.8 in 1994 to 0.4 children in 2015. Figure 6.4 Fertility planning status Figure 6.5 Trends in wanted and actual fertility Wanted then 68% Wanted later 25% Wanted no more 7% Percent distribution of births to women age 15-49 in the five years before the survey (including current pregnancies) by planning status of births 4.4 3.5 3.4 3.3 3.5 3.6 1.0 0.8 0.6 0.5 0.6 0.4 5.4 4.3 4.0 3.8 4.1 4.0 1988 1994 1999 2005-06 2010-11 2015 Total wanted fertility Difference TFR Wanted and actual number of children per woman 100 • Fertility Preferences Patterns by background characteristics  The total wanted fertility rate is consistently lower than the actual total fertility rate, although the size of the gap varies by women’s background characteristics (Table 6.6).  The gap between wanted and actual fertility is twice as large in rural areas (4.7 − 4.1 = 0.6) as in urban areas (3.0 − 2.7 = 0.3).  Women in Matabeleland North and Matabeleland South have the largest gap between their actual and wanted fertility (0.7 children), while women in Harare have the smallest gap of 0.1 child.  Women with higher levels of education and those in the highest wealth quintile are the most successful in achieving their fertility goals when compared with their counterparts. The gap between wanted and actual fertility narrows as women’s education and wealth increase. LIST OF TABLES For more information on fertility preferences, see the following tables:  Table 6.1 Fertility preferences by number of living children  Table 6.2.1 Desire to limit childbearing: Women  Table 6.2.2 Desire to limit childbearing: Men  Table 6.3 Ideal number of children by number of living children  Table 6.4 Mean ideal number of children  Table 6.5 Fertility planning status  Table 6.6 Wanted fertility rates Fertility Preferences • 101 Table 6.1 Fertility preferences by number of living children Percent distribution of currently married women and currently married men age 15-49 by desire for children, according to number of living children, Zimbabwe 2015 Number of living children Total 15-49 Total 15-54 Desire for children 0 1 2 3 4 5 6+ WOMEN1 Have another soon2 86.3 27.2 18.9 12.3 9.7 6.2 7.9 18.9 na Have another later3 4.9 63.6 45.3 30.5 18.7 12.5 6.3 34.7 na Have another, undecided when 0.6 1.1 2.0 1.1 0.3 0.6 0.0 1.1 na Undecided 1.8 1.6 4.6 5.3 3.3 3.1 1.8 3.6 na Want no more 2.4 5.7 27.9 49.2 65.2 76.4 81.9 40.0 na Sterilised4 0.0 0.0 0.3 1.1 2.4 0.9 1.4 0.8 na Declared infecund 4.0 0.8 0.9 0.6 0.4 0.3 0.7 0.8 na Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 na Number of women 274 1,133 1,587 1,403 916 475 363 6,151 na MEN5 Have another soon2 82.0 33.8 22.5 16.9 11.2 10.7 15.3 22.8 22.2 Have another later3 10.7 60.6 52.2 39.6 28.9 26.5 26.1 41.3 38.8 Have another, undecided when 1.8 1.0 2.1 0.6 1.1 1.3 0.4 1.2 1.2 Undecided 0.8 0.5 3.2 6.4 5.9 5.9 2.7 3.9 3.7 Want no more 4.8 3.9 19.6 36.1 52.4 55.6 55.1 30.5 33.6 Sterilised4 0.0 0.2 0.0 0.3 0.4 0.0 0.0 0.2 0.2 Declared infecund 0.0 0.0 0.3 0.0 0.2 0.0 0.3 0.1 0.3 Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 Number of men 190 695 990 891 617 279 348 4,010 4,328 na = Not applicable 1 The number of living children includes the current pregnancy 2 Wants next birth within 2 years 3 Wants to delay next birth for 2 or more years 4 Includes both female and male sterilisation 5 The number of living children includes one additional child if respondent’s wife is pregnant (or if any wife is pregnant for men with more than one current wife). 102 • Fertility Preferences Table 6.2.1 Desire to limit childbearing: Women Percentage of currently married women age 15-49 who want no more children, by number of living children, according to background characteristics, Zimbabwe 2015 Background characteristic Number of living children Total 0 1 2 3 4 5 6+ Residence Urban 2.1 8.2 39.1 65.9 85.1 90.5 (92.3) 46.3 Rural 2.5 4.2 19.9 41.1 60.9 74.6 82.2 38.0 Province Manicaland (3.7) 4.4 18.1 35.8 51.5 69.0 (81.2) 32.4 Mashonaland Central (3.7) 3.6 20.5 38.6 61.6 77.9 (71.3) 36.4 Mashonaland East * 5.2 24.9 56.2 67.4 88.5 (93.9) 45.4 Mashonaland West * 5.2 27.9 47.5 64.7 68.3 (74.8) 40.9 Matabeleland North * 5.1 28.4 49.2 63.7 (78.3) (92.6) 43.5 Matabeleland South * 18.0 35.3 67.3 87.8 (92.6) * 52.1 Midlands (0.0) 3.7 24.7 55.7 71.8 81.6 (90.8) 42.2 Masvingo (3.5) 6.5 23.4 43.3 65.4 (71.7) (78.8) 38.6 Harare (0.0) 6.2 37.2 58.5 81.7 (81.1) * 42.6 Bulawayo * 10.5 50.8 74.9 (89.7) * * 52.2 Education No education * * * * * * * 54.0 Primary 2.4 2.4 21.7 36.7 60.9 74.0 82.0 41.9 Secondary 2.6 5.9 27.4 52.3 72.0 80.5 84.5 39.0 More than secondary * 14.6 46.4 77.6 (79.9) * * 50.3 Wealth quintile Lowest (2.5) 3.3 18.7 29.9 48.8 65.7 77.9 34.2 Second (0.0) 5.2 17.6 41.5 62.6 75.4 73.4 38.0 Middle 5.3 3.2 20.0 44.2 66.7 78.8 95.2 40.3 Fourth 2.4 7.8 30.4 56.8 79.9 82.8 (92.3) 41.3 Highest 1.8 7.6 43.2 69.3 87.7 97.2 (97.3) 49.7 Total 2.4 5.7 28.2 50.3 67.5 77.3 83.3 40.9 Notes: Women who have been sterilized are considered to want no more children. 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 The number of living children includes the current pregnancy. Fertility Preferences • 103 Table 6.2.2 Desire to limit childbearing: Men Percentage of currently married men age 15-49 who want no more children, by number of living children, according to background characteristics, Zimbabwe 2015 Number of living children1 Total Background characteristic 0 1 2 3 4 5 6+ Residence Urban 6.8 6.8 27.6 44.9 67.9 57.7 84.2 37.8 Rural 3.9 2.5 13.8 29.7 43.8 54.9 49.3 26.4 Province Manicaland * 1.9 16.4 33.2 39.8 (40.3) (37.6) 24.0 Mashonaland Central * 4.7 8.3 24.6 43.2 (53.8) 48.0 24.5 Mashonaland East * 0.5 23.6 38.8 56.0 (68.5) (70.7) 33.6 Mashonaland West * 7.5 15.0 37.3 50.2 (45.8) (46.8) 29.2 Matabeleland North * 6.6 18.8 39.4 (45.8) * (50.0) 30.7 Matabeleland South (22.2) 0.0 32.1 (28.3) (42.7) * * 31.7 Midlands (9.5) 4.9 18.8 36.3 59.7 (57.4) (42.5) 30.9 Masvingo * 6.8 13.1 37.5 39.7 (61.0) (70.2) 30.1 Harare * 3.7 24.7 39.4 68.8 (51.0) * 35.6 Bulawayo * 4.5 43.0 50.7 (66.5) * * 43.3 Education No education * * * * * * * * Primary 8.3 1.4 11.0 22.9 40.2 51.6 47.9 23.3 Secondary 3.7 4.1 19.0 35.9 52.3 51.7 56.3 30.1 More than secondary * 9.2 31.3 53.3 79.3 (80.1) * 44.3 Wealth quintile Lowest (8.6) 1.3 13.8 18.0 33.7 (37.8) 40.3 21.1 Second (1.6) 4.7 11.9 26.3 41.2 67.9 42.4 26.2 Middle (2.5) 1.3 11.4 31.2 53.1 46.5 55.7 26.3 Fourth (3.4) 3.3 20.1 37.2 62.4 47.4 75.9 31.3 Highest (7.9) 8.9 32.5 52.4 69.2 72.1 89.2 43.4 Total 15-49 4.8 4.1 19.6 36.4 52.8 55.6 55.1 30.7 50-54 * * (89.5) 83.3 75.4 67.1 72.2 74.0 Total 15-54 5.9 5.1 21.0 38.8 55.2 57.3 59.2 33.8 Notes: Men who have been sterilized or who state in response to the question about desire for children that their wife has been sterilized are considered to want no more children. 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 The number of living children includes one additional child if respondent’s wife is pregnant (or if any wife is pregnant for men with more than one current wife). 104 • Fertility Preferences Table 6.3 Ideal number of children by number of living children Percent distribution of women and men 15-49 by ideal number of children, and mean ideal number of children for all respondents and for currently married respondents, according to the number of living children, Zimbabwe 2015 Number of living children Total Ideal number of children 0 1 2 3 4 5 6+ WOMEN1 Ideal number of children 0 2.0 0.7 0.7 1.0 1.1 0.9 0.8 1.1 1 2.8 4.1 2.0 1.7 1.0 0.2 1.3 2.3 2 26.2 21.0 14.2 8.8 7.1 5.3 2.8 15.8 3 31.2 29.5 18.5 14.6 5.8 5.7 3.6 20.3 4 25.4 26.8 44.9 38.5 34.5 23.6 15.1 32.2 5 8.4 9.8 12.6 22.1 18.6 21.0 13.0 13.8 6+ 3.7 7.8 7.0 12.9 31.4 41.7 62.4 14.2 Non-numeric responses 0.3 0.2 0.1 0.3 0.4 1.5 1.0 0.3 Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 Number of women 2,520 1,729 2,001 1,673 1,083 531 417 9,955 Mean ideal number of children for women 15-49:2 All women 3.2 3.5 3.8 4.2 4.8 5.3 6.5 3.9 Number of women 2,513 1,725 1,999 1,668 1,079 523 413 9,920 Currently married women 3.8 3.6 3.8 4.2 4.8 5.3 6.4 4.3 Number of currently married women 274 1,130 1,585 1,401 912 470 359 6,132 MEN3 Ideal number of children 0 0.3 0.0 0.5 0.3 0.6 0.1 3.4 0.4 1 1.6 1.0 1.5 0.7 0.2 0.0 0.3 1.2 2 15.1 13.7 9.9 6.1 5.5 3.3 2.4 11.4 3 28.2 27.8 19.8 16.8 8.4 6.5 5.1 22.3 4 25.3 30.7 36.8 32.4 29.0 14.9 10.1 27.5 5 17.6 14.6 20.3 24.6 22.9 29.9 7.7 18.9 6+ 11.3 11.9 10.4 18.2 32.5 44.7 67.4 17.4 Non-numeric responses 0.6 0.4 0.8 0.9 0.8 0.6 3.6 0.8 Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 Number of men 3,848 894 1,073 943 640 288 354 8,041 Mean ideal number of children for men 15-49:2 All men 4.0 4.1 4.2 4.7 5.2 6.3 8.2 4.5 Number of men 3,823 890 1,064 935 635 287 341 7,976 Currently married men 4.2 4.1 4.1 4.7 5.2 6.3 8.2 4.9 Number of currently married men 190 691 982 883 612 277 336 3,970 Mean ideal number of children for men 15-54:2 All men 4.0 4.1 4.2 4.7 5.1 6.2 7.9 4.5 Number of men 3,833 908 1,090 986 713 336 454 8,321 Currently married men 4.2 4.1 4.1 4.7 5.1 6.3 7.9 5.0 Number of currently married men 196 704 1,003 928 686 322 442 4,280 1 The number of living children includes current pregnancy for women. 2 Means are calculated excluding respondents who gave non-numeric responses. 3 The number of living children includes one additional child if respondent’s wife is pregnant (or if any wife is pregnant for men with more than one current wife). Fertility Preferences • 105 Table 6.4 Mean ideal number of children Mean ideal number of children for all women age 15-49 by background characteristics, Zimbabwe 2015 Background characteristic Mean Number of women1 Age 15-19 3.3 2,197 20-24 3.6 1,695 25-29 3.9 1,648 30-34 4.0 1,614 35-39 4.3 1,233 40-44 4.8 958 45-49 5.2 575 Residence Urban 3.4 3,820 Rural 4.3 6,100 Province Manicaland 4.4 1,253 Mashonaland Central 4.6 881 Mashonaland East 4.1 947 Mashonaland West 4.2 1,159 Matabeleland North 3.9 464 Matabeleland South 3.3 419 Midlands 3.8 1,257 Masvingo 4.2 1,187 Harare 3.5 1,779 Bulawayo 3.2 576 Education No education 6.3 124 Primary 4.7 2,559 Secondary 3.7 6,509 More than secondary 3.1 728 Wealth quintile Lowest 4.8 1,697 Second 4.4 1,688 Middle 4.1 1,740 Fourth 3.6 2,298 Highest 3.3 2,497 Total 3.9 9,920 1 Number of women who gave a numeric response 106 • Fertility Preferences Table 6.5 Fertility planning status Percent distribution of births to women age 15-49 in the five years preceding the survey (including current pregnancies), by planning status of the birth, according to birth order and mother’s age at birth, Zimbabwe 2015 Planning status of birth Total Number of births Birth order and mother’s age at birth Wanted then Wanted later Wanted no more Birth order 1 71.5 27.5 0.9 100.0 1,849 2 70.0 27.4 2.6 100.0 1,753 3 70.8 21.8 7.4 100.0 1,453 4+ 59.0 24.3 16.7 100.0 1,995 Mother’s age at birth <20 62.4 36.1 1.5 100.0 1,176 20-24 68.2 29.7 2.0 100.0 1,908 25-29 71.1 24.1 4.7 100.0 1,865 30-34 70.8 19.2 10.0 100.0 1,242 35-39 62.3 13.8 24.0 100.0 686 40-44 51.0 9.9 39.1 100.0 158 45-49 * * * 100.0 13 Total 67.5 25.4 7.1 100.0 7,050 Note: An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. Fertility Preferences • 107 Table 6.6 Wanted fertility rates Total wanted fertility rates and total fertility rates for the three years preceding the survey, by background characteristics, Zimbabwe 2015 Background characteristic Total wanted fertility rates Total fertility rate Residence Urban 2.7 3.0 Rural 4.1 4.7 Province Manicaland 4.5 5.0 Mashonaland Central 4.1 4.4 Mashonaland East 3.7 4.3 Mashonaland West 3.9 4.3 Matabeleland North 3.7 4.4 Matabeleland South 2.8 3.5 Midlands 3.6 4.2 Masvingo 3.9 4.4 Harare 2.7 2.8 Bulawayo 2.2 2.7 Education No education 4.2 4.7 Primary 4.4 5.0 Secondary 3.4 3.8 More than secondary 2.0 2.2 Wealth quintile Lowest 4.9 5.6 Second 4.3 4.9 Middle 4.0 4.5 Fourth 3.3 3.7 Highest 2.1 2.4 Total 3.6 4.0 Note: Rates are calculated based on births to women age 15-49 in the period 1-36 months preceding the survey. The total fertility rates are the same as those presented in Table 5.2. Family Planning • 109 FAMILY PLANNING 7 Key Findings  Knowledge of contraception: Knowledge of modern contraception is nearly universal in Zimbabwe; 99 percent of all women and 100 percent of all men report knowing at least one modern contraceptive method.  Contraceptive use: Sixty-seven percent of currently married women report current use of a family planning method, and 66 percent use a modern method. The most popular contraceptive method is the pill, currently used by 41 percent of currently married women.  Contraceptive discontinuation: The leading reasons for method discontinuation are the desire to become pregnant (37 percent), method- related health concerns or side effects (21 percent), and method failure (12 percent).  Percentage of demand for family planning satisfied: Demand for family planning satisfied by the use of modern methods among currently married women is 85 percent.  Unmet need for family planning: Unmet need for family planning among currently married women has decreased from 15 percent in 2010-11 to 10 percent in 2015. If all currently married women with an unmet need for family planning were to use a contraceptive method, the contraceptive prevalence rate in Zimbabwe would increase from 67 to 77 percent. amily planning refers to a couple’s conscious effort to limit or space the number of children they want through the use of contraceptive methods. Information about the knowledge of family planning methods was collected from female and male respondents by asking them if they had heard of specific methods by which a couple can delay or avoid a pregnancy. Respondents were also asked if they were currently using a method and if so, which method they were using. Contraceptive methods are classified as modern or traditional. Modern methods include female sterilisation, male sterilisation, the pill, intrauterine contraceptive device (IUCD), injectables, implants, male condom, female condom, and lactational amenorrhoea method (LAM). Methods such as rhythm (periodic abstinence) and withdrawal are classified as traditional. This chapter presents results from the 2015 ZDHS on aspects of contraception that include knowledge of specific contraceptive methods, attitudes and behaviour towards contraceptive use, current use, and informed choice of methods. The chapter focuses on women who are sexually active because these women have the greatest risk of exposure to pregnancy and the need for regulating their fertility. The results of interviews with men are presented with the women’s interview results because men play an equally important role in reproductive health and family planning decisions and behaviour. F 110 • Family Planning In Zimbabwe, family planning is part of the Sexual and Reproductive Health Programme of the Ministry of Health and Child Care (MoHCC) and is an important part of the Zimbabwe Agenda for Sustainable Socio- Economic Transformation (Zim Asset) October 2013-December 2018 (Government of Zimbabwe 2014). 7.1 CONTRACEPTIVE KNOWLEDGE AND USE Knowledge of contraceptive methods is almost universal in Zimbabwe, with 99 percent of all women age 15-49 and 100 percent of all men age 15-49 knowing at least one method of contraception (Table 7.1). Zimbabwean women and men age 15-49 know a mean of 8 contraceptive methods. More than 90 percent of women and men age 15-49 know about pills, male condoms, and female condoms. Emergency contraception is the least-known modern contraceptive method among women and men (28 percent and 33 percent, respectively). Knowledge of contraceptive methods does not significantly vary by background characteristics (Table 7.2). Contraceptive prevalence rate (CPR) Percentage who use any contraceptive method Sample: All women age 15-49, currently married women age 15-49, and sexually active unmarried women age 15-49 Overall, 67 percent of currently married women report current use of a contraceptive method and 66 percent use a modern method (Table 7.3). Modern contraceptive use among currently married women is highest (73 percent) among women age 35-39. Among sexually active, unmarried women age 15-49, 68 percent use a contraceptive method and 66 percent use a modern method. Modern methods Include male and female sterilisation, injectables, intrauterine contraceptive devices (IUCDs), contraceptive pills, implants, female and male condoms, and emergency contraception. The most commonly used methods among currently married women are the pill (41 percent), and injectables and implants (10 percent each). Four percent of currently married women use male condoms and 1 percent each have been sterilised or use IUCD. One percent of currently married women use a traditional method, mostly withdrawal (Figure 7.1). Among sexually active unmarried women, male condoms are by far the most commonly used method (27 percent), followed by pills (16 percent) and implants (14 percent) (Table 7.3). Figure 7.1 Contraceptive use 67 66 41 10 10 4 1 1 1 Any method Any modern method Pill Injectables Implants Male condom Female sterilisation IUCD Traditional method Percentage of currently married women age 15-49 currently using a contraceptive method Family Planning • 111 Trends: Between 1988 and 2015, use of modern contraceptive methods among currently married women in Zimbabwe has increased substantially from 36 percent to 66 percent in 2015 (Figure 7.2). Most notably, pill use increased from 31 percent in 1988 to 41 percent in 2015, and the implants from less than 1 percent in 1994 to 10 percent in 2015 (data not shown). The use of traditional contraceptive methods declined from 7 percent in 1988 to less than 1 percent in 2015. Patterns by background characteristics  Modern contraceptive use increases with age reaching a peak at 71 percent at age 30-39, and then it declines to 54 percent among women age 45- 49 (Table 7.3).  Urban married women are more likely to use modern contraceptives than rural married women (71 percent versus 63 percent) (Table 7.4).  By province, modern contraceptive use among currently married women ranges from 57 percent in Manicaland to 71 percent in Mashonaland West and Bulawayo (Figure 7.3). Figure 7.2 Trends in contraceptive use Figure 7.3 Modern contraceptive use by province Percentage of currently married women age 15-49 currently using a modern contraceptive method 66 5758 50 4236 <11134 7 20152010-112005-06199919941988 Percentage of currently married women currently using a contraceptive method Traditional methods Any modern method 112 • Family Planning  Modern contraceptive use among currently married women increases with an increase in education from 49 percent of women with no education to 75 percent of those with more than a secondary education (Figure 7.4).  By household wealth, the modern contraceptive use among currently married women increases from 62 percent in the lowest wealth quintile to 72 percent in the highest wealth quintile (Table 7.4). 7.2 SOURCE OF MODERN CONTRACEPTIVE METHODS Source of modern contraceptives Place where the modern method currently being used was obtained the last time it was acquired Sample: Women age 15-49 currently using a modern contraceptive method The information on where women obtain their contraceptive methods is useful for family planning programme planning and implementation. In the 2015 ZDHS, all women who reported that they were currently using any modern contraceptive method at the time of the survey were asked where they obtained the method the last time they acquired it. The majority of contraceptive users most recently obtained their method of choice them from the public sector (73 percent) (Figure 7.5). Twenty-two percent obtained contraceptives from the private medical sector, and 5 percent from other sources (primarily retail outlets). However, the proportion of each source varies according to the method.  Injectables, implants, and pills: Almost 9 in 10 women obtain injectables (89 percent) and more than 8 in 10 women obtain implants (82 percent) from the public sector. Seven in 10 women obtain pills (70 percent) from the public sector (Table 7.5).  Male condoms: The predominant sources for male condoms are the public sector (52 percent) and other sources (34 percent), especially supermarkets or tuck shops (23 percent).  Female sterilisation: The public sector is the most common source for female sterilisation (63 percent). Thirty-five percent of female sterilisations occur in the private sector, predominantly in a private hospital or clinic (26 percent). Figure 7.4 Modern contraceptive use by education Figure 7.5 Sources of modern contraceptive methods 49 61 68 75 No education Primary Secondary More than secondary Percentage of currently married women age 15-49 currently using a modern contraceptive method Public sector 73% Private medical sector 22% Other source 5% Percent distribution of current users of modern methods by most recent source of method Family Planning • 113 7.3 INFORMED CHOICE Informed choice Informed choice consists of women being informed at the time they started the current episode of method use about side effects of the method, what to do if they experience side effects, and other methods they could use. Sample: Women age 15-49 who are currently using selected modern contraceptive methods and who started the last episode of use within the 5 years before the survey Sixty-three percent of all current users of modern contraceptive methods were informed about side effects of the method used and 55 percent were informed about what to do if they experienced side effects. About three-fourths of women were informed of other methods they could use (Table 7.6). 7.4 DISCONTINUATION OF CONTRACEPTIVES Contraceptive discontinuation rate Percentage of contraceptive use episodes discontinued within 12 months Sample: Episodes of contraceptive use in the 5 years before the survey for women who are currently age 15-49 Couples can realise their sexual and reproductive goals only when they consistently use reliable methods of contraception. Of particular concern to family planning programmes is the rate at which users discontinue contraceptive methods and the reasons for such discontinuation. Armed with this information, family planning service providers will be able to better advice potential users of the advantages and disadvantages of each contraceptive method, which will allow women to make a more informed decision and choice about the method that best suits their needs. Among all methods, 22 percent of episodes of contraceptive use were discontinued within 12 months (Table 7.7). The male condom was most often discontinued (38 percent), followed by injectables (30 percent), and the pill (21 percent). The reason for discontinuation varies greatly by method (Table 7.8). For example, while 55 percent of episodes of implant use were discontinued because of health concerns/side effects, only 16 percent of episodes of pill use were discontinued for this reason. Across all contraceptive methods, the most common reason for discontinuation was the desire to become pregnant (37 percent), followed by concern over health concerns or side effects (21 percent) and method failure (12 percent). 7.5 DEMAND FOR FAMILY PLANNING Unmet need for family planning Proportion of women who (1) are not pregnant and not postpartum amenorrhoeic and are considered fecund and want to postpone their next birth for 2 or more years or stop childbearing altogether but are not using a contraceptive method, or (2) have a mistimed or unwanted current pregnancy, or (3) are postpartum amenorrhoeic and their last birth in the last 2 years was mistimed or unwanted. Sample: All women age 15-49, currently married women age 15-49, and sexually active unmarried women age 15-49 114 • Family Planning Demand for family planning: Unmet need for family planning + Current contraceptive use (any method) Proportion of demand satisfied: Current contraceptive use (any method) Unmet need + current contraceptive use (any method) Proportion of demand satisfied by modern methods: Current contraceptive use (any modern method) Unmet need + current contraceptive use (any method) Ten percent of currently married women have an unmet need for family planning services: 6 percent for spacing and 4 percent for limiting births (Table 7.9.1, Figure 7.6). Sixty-seven percent of married women are currently using a contraceptive method and therefore have met their need for family planning. However, 77 percent have a demand for family planning. Therefore, 87 percent of the potential demand for family planning is being met. Thus, if all married women who said they want to space or limit their children were to use family planning methods, the contraceptive prevalence rate would increase from 67 percent to 77 percent. Demand for family planning satisfied by the use of modern methods among currently married women is 85 percent. Trends: Figure 7.7 shows that the total demand for family planning among currently married women age 15-49 in Zimbabwe has generally increased over time, rising from 66 percent in 1994, to 75 percent in 2005-06, before decreasing to 73 percent in 2010-11. However, the demand increased to 77 percent in 2015. Contraceptive use has also increased over time resulting in the decrease in unmet need for family planning among married women from 19 percent in 1994, to 15 percent in 2010-11, and further to 10 percent in 2015. Patterns by background characteristics  Unmet need for spacing is high among younger women, while unmet need for limiting childbearing is high among older women (Table 7.9.1).  There is little difference in unmet need between rural and urban areas, with urban areas at 9 percent and rural areas at 11 percent. Figure 7.6 Demand for family planning Figure 7.7 Trends in total demand for family planning Unmet need for spacing 6% Unmet need for limiting 4% Met need for spacing 37% Met need for limiting 30% No need for family planning 23% Percent distribution of currently married women age 15-49 by need for family planning 0 10 20 30 40 50 60 70 80 90 100 1994 1999 2005-06 2010-11 2015 Percentage of currently married women age 15-49 with unmet need, met need, and total demand for family planning Unmet need Met need, traditional methods Met need, modern methods 66 70 75 Total demand73 77 Family Planning • 115  Matabeleland South has the highest unmet need (16 percent), and Mashonaland West has the lowest unmet need (7 percent) (Figure 7.8).  Unmet need is inversely associated with a woman’s education, and is lower among women with more than secondary education (5 percent) than among those with primary education (22 percent).  Unmet need is also inversely associated with a woman’s wealth status. Among women in the lowest two wealth quintiles, unmet need is 12 percent and 14 percent, respectively, compared with 7 percent among their counterparts in the highest wealth quintile. For additional information on the need and demand for family planning among all women and among women who are not currently married, see Table 7.9.2. 7.6 FUTURE USE OF CONTRACEPTION An important indicator of the changing demand for family planning is the extent to which non-users plan to use contraceptive methods in the future, as this is a forecast of potential demand for such services. Seventy-one percent of the currently married non-users indicated that they intend to use family planning methods in the future, while 27 percent said that they do not intend to use a method (Table 7.10). The proportion of women who intend to use a method is highest among women with one to two children (77-78 percent) and lowest among those with at least four children (59 percent). 7.7 EXPOSURE TO FAMILY PLANNING MESSAGES IN THE MEDIA Radio, television, newspapers and/or magazines, mobile phones, and pamphlets and/or posters are the major sources of information about family planning in the media in Zimbabwe. Information on the level of public exposure to a particular type of media allows policymakers to ensure the use of the most effective media for various target groups. To assess the effectiveness of such media on the dissemination of family planning information, women and men in the 2015 ZDHS were asked whether they had heard messages about family planning on various media during the few months preceding the survey. Table 7.11 offers information on exposure to family planning messages in the media among women and men age 15-49. Women reported hearing or seeing a family planning message in the past few months on the radio (28 percent), in pamphlets or posters (21 percent), in newspapers or magazines (20 percent), on television (18 percent), and on mobile phones (9 percent). The proportion of men who were exposed to family planning messages exceeded that for women for each type of media: 35 percent of men were exposed to family planning messages on the radio, 30 percent in newspapers or magazines, 27 percent in pamphlets or posters, 20 percent on television, and 12 percent on mobile phones. The proportion of women and men who were exposed to family planning messages on each of the five media is higher in urban than in rural areas. There are variations in exposure to family planning messages Figure 7.8 Unmet need for family planning by province Percentage of currently married women age 15-49 with unmet need for family planning 116 • Family Planning though the media by province. For example, exposure of women to family planning messages on the radio varies from 15 percent, each, in Matabeleland North and Matabeleland South to 39 percent in Mashonaland East. Similarly, the proportion of women exposed to family planning information through television ranges from 10 percent, each, in Manicaland, Mashonaland Central, and Matabeleland North to 47 percent in Bulawayo. Exposure to family planning messages increases with an increase in the respondents’ educational level and wealth status. 7.8 CONTACT OF NON-USERS WITH FAMILY PLANNING PROVIDERS Contact of non-users with family planning providers Respondent discussed family planning in the 12 months before the survey with a fieldworker or during a visit to a health facility. Sample: Women age 15-49 who are not currently using any contraceptive methods Seventy-seven percent of non-users did not discuss family planning with either a fieldworker or with someone at a health facility (Table 7.12). Eleven percent of non-users reported discussing family planning when visited by a fieldworker. Fifteen percent of non-users reported that they had visited a health facility and discussed family planning, while 29 percent of the non-users had visited a health facility but did not discuss family planning. Patterns by background characteristics  Women age 20-44 are more likely to discuss family planning with a fieldworker or staff at health facilities compared with younger women age 15-19 or older women age 45-49 (Table 7.12).  Urban women are somewhat less likely than rural women to visit a health facility and discuss family planning (13 percent versus 16 percent), and they are equally likely to visit a health facility but not discuss family planning (29 percent).  The proportion of non-users who visited a health facility and discussed family planning is highest in Masvingo (19 percent) and is lowest in Harare (11 percent).  Women in lower wealth quintiles are more likely to visit a health facility and discuss family planning with a provider than women in higher wealth quintiles. Family Planning • 117 LIST OF TABLES For detailed information on family planning, see the following tables:  Table 7.1 Knowledge of contraceptive methods  Table 7.2 Knowledge of contraceptive methods by background characteristics  Table 7.3 Current use of contraception by age  Table 7.4 Current use of contraception by background characteristics  Table 7.5 Source of modern contraception methods  Table 7.6 Informed choice  Table 7.7 Twelve-month contraceptive discontinuation rates  Table 7.8 Reasons for discontinuation  Table 7.9.1 Need and demand for family planning among currently married women  Table 7.9.2 Need and demand for family planning for all women and for women who are not currently married  Table 7.10 Future use of contraception  Table 7.11 Exposure to family planning messages  Table 7.12 Contact of non-users with family planning providers 118 • Family Planning Table 7.1 Knowledge of contraceptive methods Percentage of all respondents, currently married respondents, and sexually active unmarried respondents age 15-49 who know any contraceptive method, by specific method, Zimbabwe 2015 Women Men Method All women Currently married women Sexually active unmarried women1 All men Currently married men Sexually active unmarried men1 Any method 99.0 99.8 99.6 99.5 100.0 100.0 Any modern method 99.0 99.7 99.6 99.5 99.9 100.0 Female sterilisation 59.0 60.4 64.5 56.3 63.0 56.4 Male sterilisation 37.0 38.5 37.3 44.6 49.0 46.8 Pill 97.1 99.3 98.7 93.4 99.1 95.1 IUCD 74.1 80.2 88.0 53.7 66.3 48.0 Injectables 94.9 98.1 97.1 88.0 97.2 91.8 Implants 90.3 95.1 95.6 71.9 87.2 75.8 Male condom 97.1 98.6 99.6 98.9 99.7 99.6 Female condom 92.0 95.0 95.9 90.9 96.8 96.3 Emergency contraception 27.9 26.2 47.5 33.4 34.5 48.5 Lactational amenorrhoea (LAM) 42.9 49.4 47.0 26.6 36.7 25.6 Other modern method 0.1 0.1 0.0 0.1 0.1 0.0 Any traditional method 76.5 84.6 85.1 79.9 90.0 85.3 Rhythm 42.7 44.8 51.3 56.2 66.3 59.7 Other 2.7 2.9 6.6 2.0 3.1 2.2 Mean number of methods known by respondents 15-49 8.3 8.7 9.1 7.9 8.8 8.3 Number of respondents 9,955 6,151 349 8,041 4,010 498 Mean number of methods known by respondents 15-54 na na na 7.9 8.9 8.3 Number of respondents na na na 8,396 4,328 504 na = Not applicable 1 Had last sexual intercourse within 30 days preceding the survey Family Planning • 119 Table 7.2 Knowledge of contraceptive methods by background characteristics Percentage of currently married women and currently married men age 15-49 who have heard of at least one contraceptive method and who have heard of at least one modern method, by background characteristics, Zimbabwe 2015 Women Men Background characteristic Heard of any method Heard of any modern method1 Number of women Heard of any method Heard of any modern method1 Number of men Age 15-19 99.4 99.4 432 * * 18 20-24 99.4 99.2 1,045 100.0 100.0 293 25-29 99.9 99.9 1,278 100.0 99.9 713 30-34 100.0 99.9 1,333 100.0 100.0 926 35-39 100.0 100.0 975 100.0 100.0 815 40-44 99.7 99.7 707 99.8 99.8 723 45-49 99.6 99.6 381 100.0 100.0 523 Residence Urban 99.9 99.9 2,100 100.0 100.0 1,485 Rural 99.7 99.6 4,051 99.9 99.9 2,525 Province Manicaland 99.8 99.4 857 100.0 100.0 493 Mashonaland Central 100.0 100.0 638 99.7 99.5 462 Mashonaland East 99.3 99.2 622 100.0 100.0 418 Mashonaland West 99.9 99.9 774 100.0 100.0 533 Matabeleland North 100.0 100.0 279 100.0 100.0 169 Matabeleland South 99.7 99.7 214 100.0 100.0 128 Midlands 100.0 100.0 794 100.0 100.0 519 Masvingo 99.4 99.4 740 100.0 100.0 410 Harare 99.8 99.8 976 100.0 100.0 712 Bulawayo 100.0 100.0 258 100.0 100.0 168 Education No education 98.5 98.5 88 * * 19 Primary 99.5 99.3 1,826 100.0 100.0 887 Secondary 99.9 99.9 3,813 99.9 99.9 2,545 More than secondary 100.0 100.0 424 100.0 100.0 560 Wealth quintile Lowest 99.6 99.6 1,193 100.0 100.0 715 Second 99.8 99.7 1,191 99.8 99.8 715 Middle 99.6 99.6 1,073 100.0 99.9 674 Fourth 99.8 99.7 1,402 100.0 100.0 943 Highest 100.0 100.0 1,292 100.0 100.0 964 Total 15-49 99.8 99.7 6,151 100.0 99.9 4,010 50-54 na na na 100.0 100.0 318 Total 15-54 na na na 100.0 99.9 4,328 Note: An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. na = Not applicable 1 Female sterilisation, male sterilisation, pill, IUCD, injectables, implants, male condom, female condom, emergency contraception, lactational amenorrhoea method (LAM), and other modern methods 12 0 • F am ily P la nn in g Ta bl e 7. 3 C ur re nt u se o f c on tr ac ep tio n b y ag e P er ce nt d is tri bu tio n of a ll w om en , c ur re nt ly m ar rie d w om en , a nd s ex ua lly a ct iv e un m ar rie d w om en a ge 1 5- 49 b y co nt ra ce pt iv e m et ho d cu rr en tly u se d, a cc or di ng to a ge , Z im ba bw e 20 15 A ge A ny m et ho d A ny m od er n m et ho d M od er n m et ho d A ny tr ad i- tio na l m et ho d Tr ad iti on al m et ho d N ot cu rr en tly us in g To ta l N um be r of w om en Fe m al e st er ili - sa tio n M al e st er ili - sa tio n P ill IU C D In je ct - ab le s Im pl an ts M al e co nd om Fe m al e co nd om E m er - ge nc y co nt ra - ce pt io n LA M R hy th m W ith - dr aw al O th er A LL W O M E N 15 -1 9 12 .3 12 .1 0. 0 0. 0 7. 0 0. 0 2. 2 1. 5 1. 3 0. 0 0. 0 0. 0 0. 2 0. 0 0. 2 0. 0 87 .7 10 0. 0 2, 19 9 20 -2 4 48 .9 48 .6 0. 0 0. 0 27 .8 0. 1 7. 7 9. 4 3. 0 0. 1 0. 3 0. 3 0. 3 0. 2 0. 2 0. 0 51 .1 10 0. 0 1, 69 7 25 -2 9 62 .6 61 .9 0. 2 0. 0 35 .3 0. 8 10 .3 10 .5 4. 2 0. 1 0. 0 0. 5 0. 8 0. 0 0. 7 0. 0 37 .4 10 0. 0 1, 65 7 30 -3 4 66 .8 66 .0 0. 3 0. 0 38 .3 0. 7 9. 6 12 .4 4. 2 0. 0 0. 0 0. 4 0. 9 0. 0 0. 9 0. 0 33 .2 10 0. 0 1, 61 9 35 -3 9 65 .4 64 .2 0. 6 0. 0 38 .5 0. 4 7. 9 10 .7 5. 7 0. 2 0. 0 0. 1 1. 2 0. 2 1. 0 0. 0 34 .6 10 0. 0 1, 23 6 40 -4 4 57 .4 56 .4 2. 2 0. 0 28 .3 0. 7 9. 1 8. 1 7. 6 0. 3 0. 0 0. 0 0. 9 0. 1 0. 9 0. 0 42 .6 10 0. 0 96 5 45 -4 9 43 .1 41 .7 3. 3 0. 2 18 .9 0. 6 4. 7 4. 5 8. 9 0. 6 0. 0 0. 0 1. 3 0. 2 0. 8 0. 3 56 .9 10 0. 0 58 2 To ta l 48 .6 47 .9 0. 6 0. 0 27 .0 0. 4 7. 2 8. 1 4. 2 0. 1 0. 0 0. 2 0. 7 0. 1 0. 6 0. 0 51 .4 10 0. 0 9, 95 5 C U R R E N TL Y M A R R IE D W O M E N 15 -1 9 45 .8 44 .9 0. 0 0. 0 31 .7 0. 1 8. 1 3. 6 1. 5 0. 0 0. 0 0. 0 0. 9 0. 0 0. 9 0. 0 54 .2 10 0. 0 43 2 20 -2 4 64 .2 63 .8 0. 0 0. 0 41 .7 0. 1 10 .1 9. 9 1. 7 0. 0 0. 0 0. 3 0. 4 0. 2 0. 2 0. 0 35 .8 10 0. 0 1, 04 5 25 -2 9 69 .3 68 .5 0. 3 0. 0 43 .1 0. 9 11 .5 9. 6 2. 4 0. 1 0. 0 0. 5 0. 8 0. 0 0. 8 0. 0 30 .7 10 0. 0 1, 27 8 30 -3 4 71 .5 70 .6 0. 3 0. 0 44 .4 0. 9 9. 6 11 .7 3. 3 0. 0 0. 0 0. 4 0. 9 0. 0 0. 9 0. 0 28 .5 10 0. 0 1, 33 3 35 -3 9 72 .9 71 .4 0. 7 0. 0 45 .9 0. 3 8. 5 10 .8 4. 7 0. 2 0. 0 0. 2 1. 5 0. 2 1. 3 0. 0 27 .1 10 0. 0 97 5 40 -4 4 67 .4 66 .1 2. 8 0. 0 35 .4 1. 0 9. 6 9. 5 7. 6 0. 2 0. 0 0. 0 1. 3 0. 1 1. 2 0. 0 32 .6 10 0. 0 70 7 45 -4 9 55 .8 53 .8 3. 6 0. 4 26 .6 0. 8 6. 3 5. 9 9. 3 0. 9 0. 0 0. 0 2. 0 0. 3 1. 2 0. 5 44 .2 10 0. 0 38 1 To ta l 66 .8 65 .8 0. 8 0. 0 40 .9 0. 6 9. 6 9. 6 3. 8 0. 1 0. 0 0. 3 1. 0 0. 1 0. 9 0. 0 33 .2 10 0. 0 6, 15 1 S E X U A LL Y A C TI V E U N M A R R IE D W O M E N 1 15 -1 9 38 .7 38 .7 0. 0 0. 0 9. 0 0. 0 4. 9 6. 5 18 .2 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 61 .3 10 0. 0 48 20 -2 4 70 .6 69 .4 0. 0 0. 0 9. 3 0. 0 10 .2 16 .9 29 .2 0. 9 2. 8 0. 0 1. 2 1. 2 0. 0 0. 0 29 .4 10 0. 0 72 25 -2 9 73 .3 72 .6 0. 0 0. 0 16 .3 0. 0 10 .3 19 .9 26 .0 0. 0 0. 0 0. 0 0. 7 0. 7 0. 0 0. 0 26 .7 10 0. 0 67 30 -3 4 73 .5 69 .2 0. 0 0. 0 16 .0 0. 5 16 .8 19 .2 16 .8 0. 0 0. 0 0. 0 4. 3 0. 0 4. 3 0. 0 26 .5 10 0. 0 57 35 -3 9 (7 1. 3) (7 1. 3) (0 .6 ) (0 .0 ) (2 1. 0) (0 .0 ) (0 .0 ) (1 2. 2) (3 7. 4) (0 .0 ) (0 .0 ) (0 .0 ) (0 .0 ) (0 .0 ) (0 .0 ) (0 .0 ) (2 8. 7) 10 0. 0 48 40 -4 4 (8 3. 5) (8 3. 5) (0 .0 ) (0 .0 ) (3 4. 6) (0 .0 ) (6 .1 ) (1 0. 6) (3 2. 3) (0 .0 ) (0 .0 ) (0 .0 ) (0 .0 ) (0 .0 ) (0 .0 ) (0 .0 ) (1 6. 5) 10 0. 0 32 45 -4 9 (5 6. 6) (5 6. 6) (0 .0 ) (0 .0 ) (1 4. 8) (0 .0 ) (4 .5 ) (5 .0 ) (3 2. 3) (0 .0 ) (0 .0 ) (0 .0 ) (0 .0 ) (0 .0 ) (0 .0 ) (0 .0 ) (4 3. 4) 10 0. 0 25 To ta l 67 .5 66 .4 0. 1 0. 0 16 .0 0. 1 8. 4 14 .4 26 .7 0. 2 0. 6 0. 0 1. 1 0. 4 0. 7 0. 0 32 .5 10 0. 0 34 9 N ot es : I f m or e th an o ne m et ho d is u se d, o nl y th e m os t e ffe ct iv e m et ho d is c on si de re d in th is ta bu la tio n. F ig ur es in p ar en th es es a re b as ed o n 25 -4 9 un w ei gh te d ca se s. na = N ot a pp lic ab le LA M = L ac ta tio na l a m en or rh oe a m et ho d 1 W om en w ho h av e ha d se xu al in te rc ou rs e w ith in 3 0 da ys p re ce di ng th e su rv ey Fa m ily P la nn in g • 1 21 Ta bl e 7. 4 C ur re nt u se o f c on tr ac ep tio n b y ba ck gr ou nd c ha ra ct er is tic s P er ce nt d is tri bu tio n of c ur re nt ly m ar rie d w om en a ge 1 5- 49 b y co nt ra ce pt iv e m et ho d cu rr en tly u se d, a cc or di ng to b ac kg ro un d ch ar ac te ris tic s, Z im ba bw e 20 15 A ny m et ho d A ny m od er n m et ho d M od er n m et ho d A ny tr ad i- tio na l m et ho d Tr ad iti on al m et ho d N ot cu rr en tly us in g To ta l N um be r o f w om en B ac kg ro un d ch ar ac te ris tic Fe m al e st er ili - sa tio n M al e st er ili - sa tio n P ill IU C D In je ct - ab le s Im pl an ts M al e co nd om Fe m al e co nd om LA M R hy th m W ith - dr aw al O th er N um be r of li vi ng ch ild re n 0 6. 8 5. 9 0. 0 0. 0 2. 7 0. 0 0. 8 0. 3 2. 0 0. 0 0. 0 1. 0 0. 4 0. 5 0. 0 93 .2 10 0. 0 42 6 1- 2 68 .8 68 .2 0. 1 0. 1 45 .4 0. 6 9. 6 8. 3 3. 8 0. 1 0. 2 0. 6 0. 1 0. 5 0. 0 31 .2 10 0. 0 2, 68 8 3- 4 75 .5 74 .4 1. 6 0. 0 45 .7 0. 4 10 .3 12 .0 3. 9 0. 1 0. 3 1. 1 0. 0 1. 1 0. 0 24 .5 10 0. 0 2, 23 4 5+ 67 .3 65 .3 1. 2 0. 0 32 .6 1. 5 12 .3 12 .6 4. 3 0. 5 0. 4 2. 0 0. 2 1. 5 0. 2 32 .7 10 0. 0 80 3 R es id en ce U rb an 71 .5 70 .7 1. 4 0. 1 44 .1 1. 0 6. 6 12 .0 5. 3 0. 0 0. 3 0. 8 0. 2 0. 6 0. 0 28 .5 10 0. 0 2, 10 0 R ur al 64 .3 63 .2 0. 5 0. 0 39 .2 0. 4 11 .2 8. 4 3. 1 0. 2 0. 3 1. 1 0. 0 1. 0 0. 0 35 .7 10 0. 0 4, 05 1 P ro vi nc e M an ic al an d 58 .7 56 .7 0. 7 0. 0 34 .3 0. 9 10 .4 7. 8 2. 6 0. 2 0. 0 2. 0 0. 0 1. 8 0. 2 41 .3 10 0. 0 85 7 M as ho na la nd C en tra l 66 .4 65 .2 0. 4 0. 0 46 .5 0. 4 7. 5 7. 2 2. 8 0. 3 0. 2 1. 2 0. 1 1. 1 0. 0 33 .6 10 0. 0 63 8 M as ho na la nd E as t 69 .9 69 .1 0. 6 0. 0 43 .1 0. 6 11 .3 10 .0 3. 6 0. 0 0. 0 0. 8 0. 0 0. 8 0. 0 30 .1 10 0. 0 62 2 M as ho na la nd W es t 71 .7 71 .0 0. 6 0. 0 48 .1 0. 4 8. 5 9. 1 4. 2 0. 0 0. 2 0. 7 0. 1 0. 5 0. 0 28 .3 10 0. 0 77 4 M at ab el el an d N or th 67 .0 66 .3 1. 3 0. 0 29 .3 0. 5 18 .6 10 .6 6. 0 0. 0 0. 0 0. 8 0. 1 0. 7 0. 0 33 .0 10 0. 0 27 9 M at ab el el an d S ou th 59 .8 59 .7 0. 9 0. 1 26 .7 0. 1 13 .4 13 .7 4. 7 0. 0 0. 0 0. 1 0. 0 0. 1 0. 0 40 .2 10 0. 0 21 4 M id la nd s 68 .2 67 .2 0. 7 0. 0 39 .6 0. 2 11 .9 10 .7 2. 8 0. 2 1. 1 1. 0 0. 1 0. 8 0. 0 31 .8 10 0. 0 79 4 M as vi ng o 61 .2 60 .5 0. 4 0. 0 37 .7 0. 5 11 .4 8. 1 2. 1 0. 4 0. 0 0. 7 0. 0 0. 7 0. 0 38 .8 10 0. 0 74 0 H ar ar e 71 .1 70 .4 0. 9 0. 1 46 .8 1. 1 4. 4 10 .6 6. 0 0. 0 0. 4 0. 7 0. 2 0. 5 0. 0 28 .9 10 0. 0 97 6 B ul aw ay o 72 .4 70 .8 3. 2 0. 2 36 .9 1. 7 5. 8 16 .2 6. 4 0. 0 0. 5 1. 6 0. 6 1. 0 0. 0 27 .6 10 0. 0 25 8 E du ca tio n N o ed uc at io n 49 .3 49 .3 0. 7 0. 0 29 .4 0. 0 5. 0 2. 8 9. 5 1. 9 0. 0 0. 0 0. 0 0. 0 0. 0 50 .7 10 0. 0 88 P rim ar y 61 .8 60 .7 0. 4 0. 0 36 .9 0. 6 10 .5 8. 1 3. 7 0. 2 0. 3 1. 1 0. 0 1. 1 0. 0 38 .2 10 0. 0 1, 82 6 S ec on da ry 68 .4 67 .5 0. 8 0. 0 42 .5 0. 6 9. 7 9. 9 3. 8 0. 1 0. 3 0. 9 0. 1 0. 7 0. 1 31 .6 10 0. 0 3, 81 3 M or e th an s ec on da ry 76 .8 75 .4 2. 7 0. 3 46 .4 0. 9 5. 7 15 .7 3. 3 0. 4 0. 0 1. 4 0. 2 1. 2 0. 0 23 .2 10 0. 0 42 4 W ea lth q ui nt ile Lo w es t 62 .8 61 .8 0. 2 0. 0 38 .5 0. 2 12 .5 7. 3 2. 6 0. 2 0. 4 1. 0 0. 0 0. 8 0. 2 37 .2 10 0. 0 1, 19 3 S ec on d 62 .8 61 .5 0. 5 0. 0 37 .8 0. 5 9. 9 8. 6 3. 8 0. 2 0. 3 1. 2 0. 1 1. 1 0. 0 37 .2 10 0. 0 1, 19 1 M id dl e 64 .1 63 .1 0. 6 0. 0 37 .2 0. 4 12 .2 9. 0 3. 6 0. 0 0. 0 1. 0 0. 0 1. 0 0. 0 35 .9 10 0. 0 1, 07 3 Fo ur th 69 .4 68 .7 0. 7 0. 0 44 .9 0. 4 7. 4 10 .7 4. 2 0. 2 0. 2 0. 7 0. 0 0. 7 0. 0 30 .6 10 0. 0 1, 40 2 H ig he st 73 .4 72 .3 1. 9 0. 2 44 .7 1. 4 6. 8 12 .2 4. 7 0. 0 0. 4 1. 1 0. 4 0. 7 0. 0 26 .6 10 0. 0 1, 29 2 To ta l 66 .8 65 .8 0. 8 0. 0 40 .9 0. 6 9. 6 9. 6 3. 8 0. 1 0. 3 1. 0 0. 1 0. 9 0. 0 33 .2 10 0. 0 6, 15 1 N ot e: If m or e th an o ne m et ho d is u se d, o nl y th e m os t e ffe ct iv e m et ho d is c on si de re d in th is ta bu la tio n. LA M = L ac ta tio na l a m en or rh oe a m et ho d. 122 • Family Planning Table 7.5 Source of modern contraception methods Percent distribution of users of modern contraceptive methods age 15-49 by most recent source of method, according to method, Zimbabwe 2015 Source Female sterilisation Pill IUCD Injectables Implants Male condom Total Public sector 62.6 69.9 (73.3) 88.5 81.9 51.6 73.0 Government hospital/clinic 60.1 8.4 (6.4) 12.7 15.1 9.4 10.8 Municipal clinic 0.0 9.9 (14.9) 15.2 15.5 17.2 12.2 ZNFPC clinic 1.2 2.7 (15.4) 1.4 7.2 0.1 3.1 Rural health centre 0.0 40.0 (24.8) 56.5 42.3 20.5 40.5 Village health worker 0.0 4.8 (0.0) 0.0 0.0 3.1 3.0 MoHCC mobile clinic 0.0 3.6 (11.8) 2.4 1.4 0.7 2.8 ZNFPC CBD/depot holder 0.0 0.4 (0.0) 0.0 0.3 0.6 0.3 Other public sector 1.3 0.2 (0.0) 0.2 0.2 0.0 0.2 Private sector 35.1 27.5 (26.7) 11.0 17.7 14.1 22.3 Mission hospital/clinic 9.4 1.7 (0.0) 2.7 3.1 2.5 2.3 Pharmacy 0.0 21.6 (0.0) 0.7 0.4 10.7 13.5 Private medical hospital/clinic 25.7 2.1 (4.7) 3.8 6.7 0.5 3.3 Private doctor 0.0 0.8 (3.0) 2.1 2.9 0.0 1.3 CBD 0.0 0.2 (0.0) 0.0 0.0 0.2 0.1 Private outreach clinic 0.0 0.4 (3.7) 0.7 1.7 0.1 0.7 Other private medical sector 0.0 0.5 (15.2) 1.0 2.9 0.2 1.1 Other source 0.0 2.5 (0.0) 0.1 0.1 33.9 4.5 General dealer 0.0 0.5 (0.0) 0.0 0.0 2.0 0.4 Supermarket/tuck shop 0.0 0.7 (0.0) 0.0 0.0 22.5 2.4 Service station 0.0 0.0 (0.0) 0.0 0.0 0.6 0.1 Bottle store/bar 0.0 0.0 (0.0) 0.0 0.0 1.1 0.1 Other retail 0.0 0.1 (0.0) 0.0 0.0 0.0 0.0 Friend/relative 0.0 0.4 (0.0) 0.0 0.0 5.0 0.7 Public toilet 0.0 0.0 (0.0) 0.0 0.0 0.0 0.0 Street vendor 0.0 0.6 (0.0) 0.0 0.0 0.0 0.3 Workplace 0.0 0.2 (0.0) 0.1 0.1 2.7 0.4 Other 1.0 0.1 (0.0) 0.4 0.3 0.4 0.2 Missing 1.3 0.0 (0.0) 0.0 0.0 0.0 0.0 Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 Number of women 56 2,690 43 719 804 415 4,745 Note: Total excludes lactational amenorrhoea method (LAM), but includes 2 users of male sterilisation, 11 users of female condoms, and 4 users of emergency contraception. Figures in parentheses are based on 25-49 unweighted cases. ZNFPC = Zimbabwe National Family Planning Council MoHCC = Ministry of Health and Child Care CBD = Community-Based Distributor Family Planning • 123 Table 7.6 Informed choice Among current users of modern methods age 15-49 who started the last episode of use within the 5 years preceding the survey, percentage who were informed about possible side effects or problems of that method, percentage who were informed about what to do if they experienced side effects, and percentage who were informed about other methods they could use, according to method and initial source, Zimbabwe 2015 Among women who started last episode of modern contraceptive method within 5 years preceding the survey: Method/source Percentage who were informed about side effects or problems of method used Percentage who were informed about what to do if side effects experienced Percentage who were informed by a health or family planning worker of other methods that could be used Number of women Method Female sterilisation (52.8) (52.8) (77.7) 27 Pill 56.1 46.7 71.5 2,267 IUCD (83.8) (74.9) (95.3) 38 Injectables 62.5 53.0 73.5 643 Implants 85.3 78.4 82.9 761 Initial source of method1 Public sector 64.3 55.6 76.1 3,044 Central hospital * * * 7 Provincial hospital * * * 7 District hospital 68.8 61.5 80.7 565 ZNFPC clinic 76.0 61.9 82.7 112 Rural health centre 63.2 53.9 74.5 1,699 Village health worker 44.8 38.1 58.6 62 MoHCC mobile clinic 55.0 51.3 84.0 71 Government hospital/clinic 64.2 55.8 75.6 506 Other public sector * * * 14 Private medical sector 61.3 52.4 68.0 632 Mission hospital/clinic 62.3 57.2 73.8 102 Pharmacy 46.2 36.7 55.4 309 Private hospital/clinic 76.7 68.0 79.7 116 Private doctor (84.3) (72.8) (93.7) 38 CBD * * * 4 Private outreach clinic (82.7) (79.4) (84.5) 25 Other private medical sector (94.3) (78.4) (84.7) 37 Other source 38.9 22.4 56.8 54 Total 63.4 54.6 74.4 3,736 Notes: Table includes users of only the methods listed individually. 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. ZNFPC = Zimbabwe National Family Planning Council MoHCC = Ministry of Health and Child Care CBD = Community-Based Distributor 1 Source at start of current episode of use 124 • Family Planning Table 7.7 Twelve-month contraceptive discontinuation rates Among women age 15-49 who started an episode of contraceptive use within the 5 years preceding the survey, the percentage of episodes discontinued within 12 months, by reason for discontinuation and specific method, Zimbabwe 2015 Reason for discontinuation Method Method failure Desire to become pregnant Other fertility related reasons2 Side effects/ health concerns Wanted more effective method Other method related reasons3 Other reasons Any reason4 Switched to another method5 Number of episodes of use6 Pill 2.7 5.6 1.8 4.9 3.0 1.8 0.7 20.5 5.3 4,477 Injectables 1.2 4.7 2.0 15.6 1.9 3.0 1.6 30.0 12.3 1,182 Implants 0.6 0.5 0.0 4.5 0.2 0.0 0.5 6.1 1.7 898 Male condom 2.3 8.7 9.3 0.7 8.9 2.6 6.0 38.4 11.3 600 Other1 4.3 4.3 3.4 2.0 8.5 2.4 1.5 26.5 11.6 289 All methods 2.3 5.1 2.3 6.0 3.2 1.9 1.3 22.0 6.7 7,446 Note: Figures are based on life table calculations using information on episodes of use that began 3-62 months preceding the survey. 1 Includes LAM and female condom. 2 Includes infrequent sex/husband away, difficult to get pregnant/menopausal, and marital dissolution/separation 3 Includes lack of access/too far, costs too much, and inconvenient to use 4 Reasons for discontinuation are mutually exclusive and add to the total given in this column 5 The episodes of use included in this column are a subset of the discontinued episodes included in the discontinuation rate. A woman is considered to have switched to another method if she used a different method in the month following discontinuation or if she gave “wanted a more effective method” as the reason for discontinuation and started another method within two months of discontinuation. 6 Number of episodes of use includes both episodes of use that were discontinued during the period of observation and episodes of use that were not discontinued during the period of observation Table 7.8 Reasons for discontinuation Percent distribution of discontinuations of contraceptive methods in the five years preceding the survey by main reason stated for discontinuation, according to specific method, Zimbabwe 2015 Reason Pill Injectables Implants Male condom LAM Other modern1 Withdrawal Other2 All methods Became pregnant while using 14.8 5.3 6.5 8.7 (2.6) 10.6 16.6 * 12.2 Wanted to become pregnant 42.8 28.3 23.0 24.4 (3.5) 14.4 41.8 * 37.2 Husband/partner disapproved 1.5 2.6 1.2 10.2 (0.0) 5.3 3.0 * 2.5 Wanted a more effective method 8.4 6.4 3.1 16.0 (57.8) 12.9 20.2 * 9.0 Health concerns/side effects 16.2 40.2 55.3 2.1 (8.8) 23.5 0.3 * 20.7 Lack of access/too far 2.0 3.7 0.4 2.2 (2.9) 0.0 0.0 * 2.2 Cost too much 1.1 2.9 0.3 0.5 (0.0) 1.9 0.0 * 1.3 Inconvenient to use 3.4 2.0 3.2 4.8 (12.2) 6.7 0.0 * 3.3 Up to God/fatalistic 0.0 0.0 0.0 0.4 (0.0) 0.0 1.6 * 0.1 Difficult to get pregnant/ menopausal 0.4 0.1 0.0 0.2 (0.0) 0.0 0.0 * 0.3 Infrequent sex/husband away 5.3 4.2 2.0 18.6 (3.7) 16.5 13.0 * 6.3 Marital dissolution/separation 1.6 1.0 0.6 5.5 (0.0) 0.9 1.5 * 1.8 Other 2.2 2.8 4.4 5.5 (8.4) 4.7 1.3 * 2.7 Don’t know 0.2 0.1 0.0 0.9 (0.0) 2.5 0.7 * 0.3 Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 Number of discontinuations 3,431 883 263 451 33 50 88 11 5,211 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. LAM = Lactational amenorrhoea method 1 Includes IUCD, female condom, and emergency contraception 2 Includes rhythm method, periodic abstinence, and other traditional methods Family Planning • 125 Table 7.9.1 Need and demand for family planning among currently married women Percentage of currently married women age 15-49 with unmet need for family planning, percentage with met need for family planning, total demand for family planning, and percentage of the demand for contraception that is satisfied, according to background characteristics, Zimbabwe 2015 Background characteristic Unmet need for family planning Met need for family planning (currently using) Total demand for family planning1 Percentage of demand satisfied2 Percentage of demand satisfied by modern methods3 Number of women For spacing For limiting Total For spacing For limiting Total For spacing For limiting Total Age 15-19 12.2 0.5 12.6 44.1 1.8 45.8 56.2 2.2 58.5 78.4 76.8 432 20-24 8.4 1.7 10.1 57.1 7.1 64.2 65.4 8.8 74.2 86.5 86.0 1,045 25-29 8.0 1.9 10.0 52.1 17.2 69.3 60.2 19.1 79.3 87.4 86.4 1,278 30-34 5.4 3.2 8.6 40.0 31.4 71.5 45.4 34.6 80.0 89.3 88.2 1,333 35-39 4.3 6.8 11.1 21.1 51.8 72.9 25.4 58.6 83.9 86.8 85.0 975 40-44 2.0 10.3 12.3 5.9 61.5 67.4 7.8 71.9 79.7 84.6 83.0 707 45-49 0.2 11.4 11.6 0.8 55.0 55.8 1.0 66.4 67.4 82.8 79.9 381 Residence Urban 4.8 4.6 9.4 35.2 36.3 71.5 40.0 40.9 80.9 88.3 87.3 2,100 Rural 6.6 4.3 10.9 37.0 27.3 64.3 43.6 31.6 75.2 85.5 84.1 4,051 Province Manicaland 6.7 3.4 10.1 36.0 22.7 58.7 42.7 26.1 68.8 85.3 82.4 857 Mashonaland Central 5.9 2.5 8.4 39.4 27.0 66.4 45.4 29.5 74.9 88.7 87.2 638 Mashonaland East 5.6 3.8 9.3 35.2 34.8 69.9 40.7 38.5 79.3 88.2 87.2 622 Mashonaland West 4.0 2.5 6.5 38.5 33.2 71.7 42.5 35.7 78.2 91.7 90.8 774 Matabeleland North 5.4 7.1 12.5 36.4 30.6 67.0 41.8 37.7 79.5 84.3 83.3 279 Matabeleland South 7.6 8.6 16.2 24.8 35.0 59.8 32.4 43.5 75.9 78.7 78.6 214 Midlands 7.2 4.2 11.4 37.2 30.9 68.2 44.5 35.1 79.6 85.7 84.4 794 Masvingo 7.9 7.3 15.2 35.9 25.4 61.2 43.7 32.7 76.4 80.1 79.2 740 Harare 5.2 4.6 9.9 37.0 34.1 71.1 42.2 38.8 81.0 87.8 87.0 976 Bulawayo 4.4 4.4 8.9 32.2 40.2 72.4 36.6 44.6 81.3 89.1 87.1 258 Education No education 8.1 14.2 22.3 25.0 24.3 49.3 33.1 38.5 71.6 68.8 68.8 88 Primary 7.6 5.8 13.4 33.2 28.6 61.8 40.8 34.4 75.1 82.2 80.8 1,826 Secondary 5.6 3.8 9.4 38.5 30.0 68.4 44.1 33.7 77.8 87.9 86.8 3,813 More than secondary 2.6 1.9 4.5 33.5 43.3 76.8 36.1 45.1 81.2 94.5 92.8 424 Wealth quintile Lowest 8.7 5.4 14.1 40.7 22.1 62.8 49.4 27.5 76.9 81.7 80.4 1,193 Second 6.9 4.9 11.8 35.5 27.3 62.8 42.4 32.2 74.6 84.1 82.5 1,191 Middle 5.5 3.5 9.0 34.5 29.7 64.1 40.0 33.1 73.1 87.7 86.4 1,073 Fourth 6.2 4.3 10.5 38.0 31.4 69.4 44.2 35.8 80.0 86.8 85.9 1,402 Highest 3.0 3.7 6.7 33.0 40.4 73.4 35.9 44.2 80.1 91.6 90.3 1,292 Total 6.0 4.4 10.4 36.4 30.4 66.8 42.4 34.8 77.2 86.5 85.2 6,151 Note: Numbers in this table correspond to the revised definition of unmet need described in Bradley et al., 2012. 1 Total demand is the sum of unmet need and met need. 2 Percentage of demand satisfied is met need divided by total demand. 3 Modern methods include female sterilisation, male sterilisation, pill, IUCD, injectables, implants, male condom, female condom, emergency contraception, and lactational amenorrhoea method (LAM), and other modern methods. 126 • Family Planning Table 7.9.2 Need and demand for family planning for all women and for women who are not currently married Percentage of all women and women not currently married age 15-49 with unmet need for family planning, percentage with met need for family planning, total demand for family planning, and percentage of the demand for contraception that is satisfied, according to background characteristics, Zimbabwe 2015 Unmet need for family planning Met need for family planning (currently using) Total demand for family planning1 Percentage of demand satisfied2 Percentage of demand satisfied by modern methods3 Number of women Background characteristic For spacing For limiting Total For spacing For limiting Total For spacing For limiting Total ALL WOMEN Age 15-19 4.4 0.2 4.6 11.0 1.2 12.3 15.4 1.5 16.9 72.7 71.7 2,199 20-24 7.0 1.3 8.3 42.2 6.7 48.9 49.2 8.1 57.3 85.5 84.9 1,697 25-29 7.1 2.0 9.2 46.5 16.1 62.6 53.7 18.1 71.8 87.2 86.2 1,657 30-34 4.7 3.2 7.9 36.8 30.0 66.8 41.6 33.2 74.8 89.4 88.3 1,619 35-39 3.7 6.4 10.0 18.1 47.3 65.4 21.8 53.7 75.5 86.7 85.1 1,236 40-44 1.4 8.0 9.4 6.3 51.0 57.4 7.7 59.0 66.7 85.9 84.6 965 45-49 0.1 8.8 8.9 0.9 42.1 43.1 1.0 50.9 51.9 82.9 80.4 582 Residence Urban 3.6 3.2 6.7 24.3 23.8 48.1 27.9 27.0 54.8 87.7 86.7 3,829 Rural 5.4 3.2 8.7 27.5 21.3 48.8 32.9 24.6 57.5 84.9 83.6 6,126 Province Manicaland 5.5 2.9 8.3 25.7 17.6 43.3 31.1 20.5 51.6 83.9 81.3 1,266 Mashonaland Central 4.9 2.1 6.9 30.9 22.3 53.3 35.8 24.4 60.2 88.5 87.1 882 Mashonaland East 4.3 2.6 6.9 26.9 25.7 52.6 31.2 28.3 59.5 88.4 87.2 952 Mashonaland West 3.5 2.3 5.8 28.0 25.6 53.6 31.5 27.9 59.5 90.2 89.5 1,160 Matabeleland North 5.1 4.7 9.8 28.6 23.4 52.0 33.7 28.1 61.9 84.1 83.1 465 Matabeleland South 7.6 5.7 13.3 20.4 25.1 45.5 28.0 30.8 58.9 77.3 77.2 419 Midlands 5.7 2.8 8.5 27.4 23.2 50.6 33.1 26.0 59.1 85.7 84.6 1,263 Masvingo 5.4 4.9 10.3 24.1 18.1 42.2 29.5 23.0 52.5 80.4 79.6 1,187 Harare 3.5 3.2 6.7 24.9 22.5 47.5 28.4 25.7 54.2 87.6 86.7 1,783 Bulawayo 3.8 2.9 6.7 24.3 22.8 47.2 28.2 25.7 53.9 87.5 85.8 577 Education No education 6.8 11.5 18.3 20.2 20.3 40.4 27.0 31.8 58.8 68.8 68.8 126 Primary 6.6 4.7 11.4 26.8 24.3 51.1 33.4 29.1 62.5 81.8 80.6 2,571 Secondary 4.2 2.7 6.8 26.0 20.8 46.9 30.2 23.5 53.7 87.3 86.1 6,527 More than secondary 2.3 1.4 3.7 27.5 28.4 55.9 29.8 29.8 59.6 93.8 92.3 731 Wealth quintile Lowest 7.6 4.4 12.0 31.2 18.1 49.3 38.8 22.5 61.3 80.5 79.4 1,704 Second 5.5 3.8 9.3 27.7 22.2 49.9 33.2 26.0 59.3 84.3 82.7 1,693 Middle 4.6 2.4 7.0 24.0 22.3 46.3 28.6 24.8 53.4 86.8 85.7 1,748 Fourth 4.6 3.4 8.0 27.6 24.0 51.5 32.2 27.3 59.5 86.5 85.4 2,307 Highest 2.4 2.4 4.8 22.4 23.6 45.9 24.7 25.9 50.7 90.6 89.5 2,503 Total 4.7 3.2 7.9 26.3 22.3 48.6 31.0 25.5 56.5 86.0 84.8 9,955 Continued… Family Planning • 127 Table 7.9.2—Continued Unmet need for family planning Met need for family planning (currently using) Total demand for family planning1 Percentage of demand satisfied2 Percentage of demand satisfied by modern methods3 Number of women Background characteristic For spacing For limiting Total For spacing For limiting Total For spacing For limiting Total SEXUALLY ACTIVE UNMARRIED WOMEN4 Age 15-19 38.3 1.3 39.6 29.1 9.5 38.7 67.4 10.9 78.3 49.4 49.4 48 20-24 14.2 2.5 16.7 59.5 11.1 70.6 73.7 13.6 87.3 80.9 79.5 72 25-29 9.8 4.3 14.1 54.5 18.8 73.3 64.3 23.1 87.4 83.8 83.1 67 30-34 6.8 10.1 16.9 35.6 37.9 73.5 42.4 48.0 90.4 81.3 76.6 57 35-39 (4.7) (19.3) (24.0) (20.7) (50.6) (71.3) (25.4) (69.9) (95.3) (74.8) (74.8) 48 40-44 (0.0) (5.8) (5.8) (24.8) (58.7) (83.5) (24.8) (64.5) (89.3) (93.5) (93.5) 32 45-49 (0.0) (30.3) (30.3) (9.0) (47.6) (56.6) (9.0) (77.9) (86.9) (65.1) (65.1) 25 Residence Urban 11.7 10.8 22.5 40.2 24.2 64.4 51.9 35.0 86.9 74.1 72.3 187 Rural 12.0 5.9 17.9 36.3 34.7 71.0 48.3 40.6 88.9 79.9 79.3 163 Province Manicaland * * * * * * * * * * * 17 Mashonaland Central (2.2) (1.5) (3.7) (34.3) (52.7) (87.1) (36.6) (54.2) (90.8) (95.9) (95.9) 19 Mashonaland East * * * * * * * * * * * 21 Mashonaland West (15.4) (9.0) (24.4) (31.1) (39.9) (71.0) (46.5) (48.9) (95.3) (74.4) (74.4) 36 Matabeleland North (7.7) (3.2) (10.8) (53.3) (29.6) (82.9) (61.0) (32.8) (93.7) (88.5) (85.1) 28 Matabeleland South 21.1 10.9 32.0 36.7 22.0 58.8 57.9 32.9 90.8 64.7 64.7 35 Midlands (17.2) (4.5) (21.8) (28.4) (34.9) (63.3) (45.6) (39.4) (85.1) (74.4) (74.4) 49 Masvingo * * * * * * * * * * * 19 Harare (9.3) (13.1) (22.4) (41.7) (27.4) (69.1) (51.0) (40.5) (91.5) (75.5) (72.1) 77 Bulawayo 13.5 6.2 19.6 48.8 20.2 69.0 62.3 26.4 88.7 77.8 76.8 49 Education No education * * * * * * * * * * * 9 Primary 12.2 8.6 20.8 31.4 37.9 69.3 43.6 46.5 90.1 76.9 75.9 97 Secondary 11.6 9.9 21.5 37.4 27.7 65.1 49.0 37.6 86.6 75.1 73.7 194 More than secondary 11.4 0.0 11.4 58.4 16.3 74.7 69.8 16.3 86.1 86.8 85.7 50 Wealth quintile Lowest (11.8) (14.1) (25.9) (28.1) (32.3) (60.4) (39.9) (46.5) (86.3) (70.0) (70.0) 44 Second (6.4) (1.9) (8.3) (50.2) (33.2) (83.4) (56.6) (35.1) (91.7) (90.9) (88.0) 32 Middle 13.9 4.7 18.7 27.8 44.8 72.6 41.8 49.5 91.2 79.6 79.6 54 Fourth 9.9 9.9 19.8 33.8 33.2 67.0 43.6 43.2 86.8 77.2 74.6 110 Highest 14.5 8.5 23.0 49.1 14.5 63.5 63.5 23.0 86.6 73.4 72.9 108 Total 11.9 8.5 20.3 38.4 29.1 67.5 50.2 37.6 87.8 76.8 75.6 349 Notes: Numbers in this table correspond to the revised definition of unmet need described in Bradley et al., 2012. 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 Total demand is the sum of unmet need and met need. 2 Percentage of demand satisfied is met need divided by total demand. 3 Modern methods include female sterilisation, male sterilisation, pill, IUCD, injectables, implants, male condom, female condom, emergency contraception, and lactational amenorrhoea method (LAM), and other modern methods. 4 Women who have had sexual intercourse within 30 days preceding the survey 128 • Family Planning Table 7.10 Future use of contraception Percent distribution of currently married women age 15-49 who are not using a contraceptive method by intention to use in the future, according to number of living children, Zimbabwe 2015 Number of living children1 Total Intention to use in the future 0 1 2 3 4+ Intends to use 77.2 77.6 77.9 69.5 58.9 71.2 Unsure 0.9 2.1 2.3 1.2 1.4 1.6 Does not intend to use 21.9 20.3 19.8 29.4 39.6 27.2 Total 100.0 100.0 100.0 100.0 100.0 100.0 Number of women 245 421 448 396 534 2,045 1 Includes current pregnancy Table 7.11 Exposure to family planning messages Percentage of women and men age 15-49 who heard or saw a family planning message on radio, on television, or in a newspaper or magazine in the past few months, according to background characteristics, Zimbabwe 2015 Women Men Background characteristic Radio Tele- vision News- paper/ maga- zine Pamph- lets or posters Mobile phone None of these five media sources Number of women Radio Tele- vision News- paper/ maga- zine Pamph- lets or posters Mobile phone None of these five media sources Number of men Age 15-19 18.3 11.7 14.1 10.7 4.6 65.1 2,199 21.1 11.1 13.7 13.8 5.4 60.9 2,126 20-24 27.7 17.1 19.0 20.0 9.6 51.0 1,697 35.7 18.4 24.8 21.1 9.9 43.0 1,330 25-29 30.3 17.7 19.3 23.0 8.1 50.4 1,657 36.0 17.8 28.2 24.6 13.2 40.4 1,148 30-34 31.5 20.4 23.8 27.7 10.6 45.1 1,619 39.3 20.6 35.0 32.3 13.8 33.8 1,120 35-39 31.5 20.0 22.5 25.1 11.5 47.2 1,236 43.8 28.5 43.5 40.2 19.5 29.0 917 40-44 33.5 23.0 25.8 26.5 9.4 44.3 965 47.3 33.1 47.5 41.7 20.2 24.5 809 45-49 33.2 21.2 21.9 23.9 6.8 46.8 582 44.5 30.4 48.5 44.0 16.6 27.1 591 Residence Urban 33.2 33.8 35.7 33.2 13.4 34.2 3,829 39.7 36.9 50.3 38.1 18.0 24.4 2,900 Rural 24.8 7.6 10.3 13.7 5.4 62.6 6,126 32.5 10.7 18.4 21.0 9.2 51.0 5,140 Province Manicaland 27.4 10.4 13.1 14.2 6.3 59.3 1,266 35.7 13.8 23.3 20.0 9.7 45.8 1,072 Mashonaland Central 30.5 9.5 12.3 12.5 6.7 58.4 882 43.2 12.5 23.4 27.8 13.6 39.8 806 Mashonaland East 38.8 13.0 16.5 20.5 7.4 46.2 952 42.9 13.4 26.2 23.9 12.8 41.7 807 Mashonaland West 30.0 12.4 12.1 20.5 5.6 53.8 1,160 38.0 15.8 27.0 23.5 9.2 42.9 1,004 Matabeleland North 14.5 10.2 11.0 13.9 4.1 69.5 465 16.5 9.2 10.2 27.9 4.7 58.5 366 Matabeleland South 15.0 11.8 14.2 24.4 5.6 61.6 419 21.6 13.0 21.4 33.9 9.8 51.5 335 Midlands 20.4 10.8 12.9 16.0 4.9 64.2 1,263 26.2 16.3 21.7 19.6 10.7 52.8 986 Masvingo 18.9 15.2 16.4 18.9 8.1 59.1 1,187 16.9 16.3 18.5 22.7 9.4 56.9 843 Harare 35.3 33.3 39.1 30.9 15.3 32.2 1,783 43.6 34.5 54.3 38.9 18.7 22.1 1,412 Bulawayo 37.5 47.0 44.4 41.9 16.6 25.2 577 53.1 59.9 58.8 40.7 20.3 12.9 409 Education No education 15.4 5.0 1.8 5.9 1.3 75.1 126 (18.7) (3.8) (3.8) (8.8) (0.0) (77.9) 38 Primary 21.3 4.9 4.7 8.8 3.2 69.3 2,571 27.6 5.6 7.5 11.7 4.8 62.4 1,803 Secondary 29.7 19.7 22.1 22.9 9.8 48.0 6,527 36.6 20.4 31.5 28.0 13.6 38.7 5,349 More than secondary 39.1 47.2 58.5 51.3 16.5 18.3 731 42.5 50.5 69.0 55.8 20.9 12.4 849 Wealth quintile Lowest 16.6 1.6 4.0 9.4 2.8 75.0 1,704 25.0 2.9 8.6 13.8 5.0 64.0 1,212 Second 23.7 4.5 7.7 10.9 4.5 66.5 1,693 31.7 7.2 14.5 18.5 8.6 54.5 1,448 Middle 29.9 8.1 11.0 15.1 5.7 56.9 1,748 37.4 10.5 20.4 21.6 10.9 47.0 1,558 Fourth 32.7 21.8 24.8 25.7 11.2 43.6 2,307 38.4 24.2 37.7 31.9 15.1 33.6 1,852 Highest 33.1 40.5 41.3 36.2 14.5 29.7 2,503 38.9 44.4 54.6 41.7 18.1 20.9 1,970 Total 15-49 28.0 17.7 20.0 21.2 8.5 51.7 9,955 35.1 20.2 29.9 27.2 12.3 41.4 8,041 50-54 na na na na na na 0 48.2 36.1 38.6 36.7 16.2 28.3 355 Total 15-54 na na na na na na 0 35.7 20.9 30.3 27.6 12.5 40.9 8,396 Note: Figures in parentheses are based on 25-49 unweighted cases. na = Not applicable Family Planning • 129 Table 7.12 Contact of non-users with family planning providers Among women age 15-49 who are not using contraception, percentage who during the past 12 months were visited by a fieldworker who discussed family planning, percentage who visited a health facility and discussed family planning, percentage who visited a health facility but did not discuss family planning, and percentage who did not discuss family planning either with a fieldworker or at a health facility, according to background characteristics, Zimbabwe 2015 Percentage of women who were visited by fieldworker who discussed family planning Percentage of women who visited a health facility in the past 12 months and who: Percentage of women who did not discuss family planning either with fieldworker or at a health facility Number of women Background characteristic Discussed family planning Did not discuss family planning Age 15-19 8.4 4.0 25.4 88.2 1,929 20-24 9.7 15.8 31.9 77.7 866 25-29 9.0 24.9 32.0 68.6 619 30-34 13.5 24.6 31.6 66.7 537 35-39 14.6 25.1 27.9 65.2 427 40-44 16.2 25.0 36.7 66.6 412 45-49 12.2 14.1 30.0 75.7 332 Residence Urban 9.0 12.9 29.4 80.1 1,987 Rural 11.6 15.9 29.3 75.6 3,134 Province Manicaland 12.1 15.9 23.3 75.5 718 Mashonaland Central 8.8 15.9 30.7 77.8 412 Mashonaland East 11.5 15.6 34.2 76.0 451 Mashonaland West 12.1 12.4 37.4 77.7 538 Matabeleland North 6.8 15.4 31.4 79.0 223 Matabeleland South 4.7 14.0 20.2 82.7 228 Midlands 12.4 14.1 33.3 77.6 623 Masvingo 13.1 18.9 26.8 71.6 686 Harare 8.7 11.2 27.8 81.4 937 Bulawayo 9.7 16.3 28.6 77.0 305 Education No education 9.3 18.3 30.2 72.4 75 Primary 10.2 16.4 24.9 76.6 1,256 Secondary 10.7 13.7 29.7 78.1 3,468 More than secondary 11.5 18.9 43.2 72.6 322 Wealth quintile Lowest 9.6 18.6 25.1 73.7 863 Second 11.4 14.7 29.6 76.6 848 Middle 12.2 15.9 28.9 76.1 938 Fourth 11.5 14.2 31.7 77.2 1,119 Highest 8.9 12.0 30.3 81.0 1,354 Total 10.6 14.8 29.4 77.3 5,121 Infant and Child Mortality • 131 INFANT AND CHILD MORTALITY 8 Key Findings  Current levels: For the 5-year period preceding the survey, the under-5 mortality rate is 69 deaths per 1,000 live births, and the infant mortality rate is 50 deaths per 1,000 live births. About one in 15 children in Zimbabwe dies before his or her fifth birthday, and about 70 percent of these deaths occur during infancy.  Trends: Under-5 mortality peaked in the five years before the 1999 ZDHS. Under-5 mortality increased from 1988 (71 deaths per 1,000 live births) to 1999 (102 deaths per 1000 live births) and then declined (69 deaths per 1,000 live births in 2015).  Provincial differences: Large differences in perinatal mortality are seen among the provinces. The perinatal mortality rate ranges from a low of 17 deaths per 1,000 pregnancies in Matabeleland South to a high of 43 deaths per 1,000 pregnancies in Manicaland. nformation on infant and child mortality is relevant to a demographic assessment of the population, and is an important indicator of the country’s socioeconomic development and quality of life. This information can help identify children who may be at higher risk of death and can lead to strategies to reduce this risk, such as promoting birth spacing. Estimates of infant and child mortality are also used for population projections, particularly if the level of adult mortality is known from another source or can be inferred with reasonable confidence. This chapter presents information on levels, trends, and differentials in neonatal, infant, child, and under-5 mortality rates. The chapter also examines biodemographic factors and fertility behaviours that increase mortality risks for infants and children. The information is collected as part of a retrospective birth history, in which female respondents list all of the children they have borne, along with each child’s date of birth, survivorship status, and current age, or age at death. The quality of mortality estimates calculated from birth histories depends upon the mother’s ability to recall all children she has given birth to, as well as their birth dates and ages at death. Potential data quality problems include:  The selective omission from the birth histories of those births that did not survive, which can result in underestimation of childhood mortality.  The displacement of birth dates, which can distort mortality trends. This can occur if an interviewer knowingly records a birth as occurring in a different year than the one in which it occurred. This may happen if an interviewer is trying to reduce his or her overall work load, because live births that occur during the 5 years before the interview are the subject of a lengthy set of additional questions. In the 2015 ZDHS questionnaire, the cut-off year for these questions was 2010. Appendix Table D.4 shows I 132 • Infant and Child Mortality that the rates of completeness of birth dates to be greater than 99 percent in this interval. The sex ratio at birth in Table D.4 shows a high level of accuracy in female-male birth reporting.  Table D.5 shows the distribution of reported deaths under age 1 month by age at death in days and the percentage of neonatal deaths reported to occur at age 0-6 days, for the 5-year periods preceding the survey. For all infant deaths reported in days, for the period 0-4 years preceding the survey, 76 percent were neonatal deaths that occurred in the first week of life. For all infant deaths reported in days for the 20 years preceding the survey, 76 percent were neonatal deaths.  The quality of reporting of age at death. Misreporting the child’s age at death may distort the age pattern of mortality, especially if the net effect of the age misreporting is to transfer deaths from one age bracket to another. To minimise errors in reporting age at death, ZDHS interviewers were instructed to record age at death in days if the death took place in the month following the birth, in months if the child died before age 2, and in years if the child was at least age 2. Interviewers were also asked to probe for deaths reported at age 1 to determine a more precise age at death in terms of months. Appendix Table D.6 shows that, for the five years preceding the survey, the number of reported deaths at age 12 months, or 1 year, is fewer than the number of deaths reported at 11 months and comparable with the number reported at 13 months. This indicates that there is no apparent distortion of the infant mortality rate.  Any method of measuring childhood mortality that relies on the mothers’ reports (e.g., birth histories) assumes that female adult mortality is not high, or if it is high, that there is little or no correlation between the mortality risks of the mothers and those of their children. In countries like Zimbabwe with high rates of female adult mortality, primarily due to the HIV epidemic (see Chapter 14), these assumptions may not hold, and the resulting childhood mortality rates will be understated to some degree. 8.1 INFANT AND CHILD MORTALITY Neonatal, postneonatal, infant, child, and under-5 mortality rates Neonatal, infant, and under-5 mortality are direct estimates of the risk of dying within 1 month, 1 year, and 5 years after birth, respectively. Postneonatal mortality is the arithmetic difference between infant and neonatal mortality while child mortality is the probability of dying between exact age 1 and the fifth birthday. All rates are expressed as deaths per 1,000 live births, except child mortality, which is expressed as deaths per 1,000 children surviving to the first birthday. Sample: Live births to women age 15-49 For the 5-year period preceding the survey, the under-5 mortality rate is 69 deaths per 1,000 live births, and the infant mortality rate is 50 deaths per 1,000 live births (Table 8.1). In other words, about one in 15 children in Zimbabwe dies before his or her fifth birthday, and about 70 percent of these deaths occur during infancy. The neonatal mortality rate was 29 deaths per 1,000 live births, meaning that about 4 in 10 childhood deaths took place in the first month of life. Figure 8.1 Trends in childhood mortality 27 24 29 24 31 29 49 53 65 60 57 50 71 77 102 82 84 69 1988 1994 1999 2005-06 2010-11 2015 Deaths per 1,000 live births in the 5-year period before the survey Under-5 mortality Infant mortality Neonatal mortality Infant and Child Mortality • 133 Trends: Under-5 mortality increased from 1988 (71 deaths per 1,000 live births) to 1999 (102 deaths per 1000 live births) and then declined such that the rate in 2015 (69 deaths per 1,000 live births) is just slightly lower than the 1988 rate (Figure 8.1). Similar patterns are observed for infant and neonatal mortality rates. Infant mortality was 49 deaths per 1,000 live births in 1988 and rose to 65 deaths per 1,000 live births in 1999 before declining to 50 deaths per 1,000 live births in 2015. Although differences in neonatal mortality rates are smaller, notably neonatal mortality rates also peaked in 1999 (40 deaths per 1,000 live births). Patterns by background characteristics Mortality estimates by background characteristics are calculated for the 10-year period before the survey to ensure that there are sufficient cases to produce statistically reliable estimates (Table 8.2).  Under-5 mortality is higher in rural areas than in urban areas (92 deaths per 1,000 live births versus 60 deaths per 1,000 live births).  Among the provinces, under-5 mortality ranges from a low of 50 deaths per 1,000 live births in Bulawayo to a high of 112 deaths per 1,000 live births in Manicaland (Figure 8.2).  Neonatal mortality ranges from a low of 16 deaths per 1,000 live births in Matabeleland South to a high of 46 deaths per 1,000 live births in Mashonaland West.  Under-5 mortality declines with the level of education of the mother (Figure 8.3).  Under-5 mortality generally decreases with household wealth, from 102 deaths per 1,000 live births in the lowest wealth quintile to 52 deaths per 1,000 live births in the highest wealth quintile. 8.2 BIODEMOGRAPHIC RISK FACTORS Researchers have identified multiple risk factors for infant and child mortality based on the characteristics of the mother and child, and the circumstances of the birth. Table 8.3 illustrates the relationship between these risk factors and neonatal, post-neonatal, infant, child, and under-5 mortality. Figure 8.2 Under-5 mortality by province Deaths per 1,000 live births in the 10-year period before the survey Figure 8.3 Under-5 mortality by mother’s education 106 73 26 Primary education Secondary education More than secondary education Deaths per 1,000 live births for the 10-year period before the survey 134 • Infant and Child Mortality Patterns by background characteristics  Boys are more likely to die in childhood than girls. The gender gap is seen across all mortality rates.  The relationship between childhood mortality and mother’s age at birth shows the expected U-shape pattern for all the childhood mortality indicators except postneonatal mortality.  Infant mortality is much higher for children who were small or very small at birth compared with those who were average or larger than average (68 deaths per 1,000 live births compared with 44 deaths per 1,000 live births). 8.3 PERINATAL MORTALITY Perinatal mortality rate Perinatal deaths comprise stillbirths (pregnancy loss that occurs after 7 months of gestation) and early neonatal deaths (deaths of live births within the first 7 days of life). The perinatal mortality rate is calculated as the number of perinatal deaths per 1,000 pregnancies of 7 or more months’ duration. Sample: Number of pregnancies of 7 or more months’ duration to women age 15-49 in the five years before the survey. The causes of stillbirths and early neonatal deaths are closely linked, and it can be difficult to ascertain whether a death is one or the other. Because the perinatal mortality rate encompasses both stillbirths and early neonatal deaths, it offers a better measure of the level of mortality around delivery. During the 5 years before the survey, the perinatal mortality rate in Zimbabwe was 34 deaths per 1,000 pregnancies (Table 8.4). Patterns by background characteristics  Perinatal mortality rates are highest among the oldest mothers.  Differences by province are large. Perinatal mortality ranges from a low of 17 deaths per 1,000 pregnancies in Matabeleland South to a high of 43 deaths per 1,000 pregnancies in Manicaland (Figure 8.4). 8.4 HIGHER-RISK FERTILITY BEHAVIOUR Typically, infants and young children have a higher risk of dying if they are born to very young mothers or older mothers, if they are born after a short interval, or if their mothers have already had many children. In the following analysis, mothers are classified as too young if they are less than age 18 at the time of birth of the child and too old if they are age 35 or more at the time of the birth. A short birth interval is defined as less than 24 months, and a high- order birth is defined as occurring after 3 or more previous births (i.e., birth order >3). A birth may be at an elevated risk of dying from a combination of characteristics. The first column of Table 8.5 shows the percent of births in the five years before the survey classified by various risk categories. Overall, 41 percent of births are in at least one avoidable high-risk category; 28 percent are in a single high-risk category, and 13 percent have multiple high-risk characteristics. Figure 8.4 Perinatal mortality by province 43 42 42 32 32 17 24 33 29 30 Manicaland Mashonaland Central Mashonaland East Mashonaland West Matabeleland North Matabeleland South Midlands Masvingo Harare Bulawayo Deaths per 1,000 pregnancies of 7 or more months duration for the 5-year period before the survey Infant and Child Mortality • 135 The second column in Table 8.5 presents risk ratios, which represent the increased risk of mortality among births in various high-risk categories relative to births without any high-risk characteristics. The primary factor leading to heightened mortality risk in Zimbabwe is the mother’s age less than 18 (risk ratio of 1.58). The largest percentage of high-risk births in Zimbabwe are of high birth order (16 percent). Notably, however, these births actually exhibit a modest decreased risk of mortality (0.94). This acts to reduce the risk ratios in the overall single high-risk category (risk ratio of 1.15) and in the overall multiple high-risk category (risk ratio of 1.32). The third column in Table 8.5 shows the distribution of currently married women by the risk category into which a birth conceived at the time of the survey would fall. The data in the table show that 25 percent of women are not in any elevated mortality risk category, and 5 percent are only at risk of having their first birth between ages 18 and 34, which is considered to be an unavoidable risk. Among those who are in an elevated mortality risk category (71 percent of women), 32 percent have a single high risk and 38 percent have multiple risks. LIST OF TABLES For detailed information on infant and child mortality, see the following tables:  Table 8.1 Early childhood mortality rates  Table 8.2 Early childhood mortality rates by socioeconomic characteristics  Table 8.3 Early childhood mortality rates by demographic characteristics  Table 8.4 Perinatal mortality  Table 8.5 High-risk fertility behaviour 136 • Infant and Child Mortality Table 8.1 Early childhood mortality rates Neonatal, postneonatal, infant, child, and under-5 mortality rates for five-year periods preceding the survey, Zimbabwe 2015 Years preceding the survey Approximate time period of estimated rates Neonatal mortality (NN) Post- neonatal mortality (PNN)1 Infant mortality (1q0) Child mortality (4q1) Under-5 mortality (5q0) 0-4 2010-2015 29 22 50 20 69 5-9 2005-2010 32 37 69 32 99 10-14 2000-2005 23 25 48 29 76 Note: Estimates are for deaths per 1,000 live births except for child mortality, which is deaths per 1,000 children age 12-59 months. 1 Computed as the difference between the infant and neonatal mortality rates Table 8.2 Early childhood mortality rates according to socioeconomic characteristics Neonatal, postneonatal, infant, child, and under-5 mortality rates for the 10-year period preceding the survey, according to background characteristics, Zimbabwe 2015 Background characteristic Neonatal mortality (NN) Post- neonatal mortality (PNN)1 Infant mortality (1q0) Child mortality (4q1) Under-5 mortality (5q0) Residence Urban 27 20 46 14 60 Rural 32 32 64 30 92 Province Manicaland 35 43 78 37 112 Mashonaland Central 28 36 64 28 90 Mashonaland East 34 35 68 36 102 Mashonaland West 46 25 71 32 101 Matabeleland North 25 21 46 23 67 Matabeleland South 16 29 46 21 65 Midlands 32 28 60 13 72 Masvingo 22 22 44 22 65 Harare 23 20 42 16 58 Bulawayo 26 14 40 10 50 Mother’s education None * * * * * Primary 38 37 74 34 106 Secondary 28 24 52 22 73 More than secondary 14 10 24 2 26 Wealth quintile Lowest 32 35 68 37 102 Second 35 30 65 27 90 Middle 33 38 72 26 96 Fourth 28 18 46 23 68 Highest 22 21 43 9 52 Note: An asterisk indicates that a rate is based on fewer than 250 person-years of exposure to the risk of death and has been suppressed. 1 Computed as the difference between the infant and neonatal mortality rates Infant and Child Mortality • 137 Table 8.3 Early childhood mortality rates according to demographic characteristics Neonatal, postneonatal, infant, child, and under-5 mortality rates for the 10-year period preceding the survey, according to demographic characteristics, Zimbabwe 2015 Demographic characteristic Neonatal mortality (NN) Post- neonatal mortality (PNN)1 Infant mortality (1q0) Child mortality (4q1) Under-5 mortality (5q0) Child’s sex Male 35 29 63 27 88 Female 26 28 54 23 76 Mother’s age at birth <20 38 31 69 29 96 20-29 26 28 54 23 76 30-39 35 26 61 29 88 40-49 * * * * * Birth order 1 35 27 62 22 82 2-3 26 27 52 24 75 4-6 32 29 62 28 88 7+ (42) (60) (102) * * Previous birth interval2 <2 years 60 59 119 49 162 2 years 32 32 63 27 88 3 years 15 23 38 23 60 4+ years 25 22 47 22 68 Birth size3 Small/very small 41 27 68 na na Average or larger 26 18 44 na na Notes: Figures in parentheses are based on 250-499 unweighted person-years of exposure to the risk of death. An asterisk indicates that a figure is based on fewer than 250 unweighted person-years exposure to the risk of death and has been suppressed. na = Not available 1 Computed as the difference between the infant and neonatal mortality rates 2 Excludes first-order births 3 Rates for the five-year period before the survey 138 • Infant and Child Mortality Table 8.4 Perinatal mortality Number of stillbirths and early neonatal deaths, and the perinatal mortality rate for the five-year period preceding the survey, according to background characteristics, Zimbabwe 2015 Background characteristic Number of stillbirths1 Number of early neonatal deaths2 Perinatal mortality rate3 Number of pregnancies of 7+ months duration Mother’s age at birth <20 19 32 47 1,085 20-29 21 57 23 3,449 30-39 24 49 42 1,745 40-49 12 3 95 158 Previous pregnancy interval in months4 First pregnancy 20 39 37 1,564 <15 10 19 46 619 15-26 8 13 22 977 27-38 8 22 33 914 39+ 32 47 33 2,364 Residence Urban 19 39 29 2,020 Rural 57 101 36 4,417 Province Manicaland 11 31 43 972 Mashonaland Central 16 11 42 639 Mashonaland East 13 13 42 621 Mashonaland West 8 20 32 850 Matabeleland North 2 7 32 286 Matabeleland South 2 2 17 237 Midlands 3 17 24 859 Masvingo 10 15 33 766 Harare 9 18 29 944 Bulawayo 2 6 30 262 Mother’s education No education 0 2 28 73 Primary 17 50 33 2,038 Secondary 57 84 35 3,986 More than secondary 2 3 17 340 Wealth quintile Lowest 13 35 32 1,473 Second 24 33 45 1,262 Middle 12 23 32 1,108 Fourth 19 30 32 1,507 Highest 10 19 26 1,087 Total 77 140 34 6,437 1 Stillbirths are foetal deaths in pregnancies lasting seven or more months. 2 Early neonatal deaths are deaths at age 0-6 days among live-born children. 3 The sum of the number of stillbirths and early neonatal deaths divided by the number of pregnancies of seven or more months’ duration, expressed per 1,000. 4 Categories correspond to birth intervals of <24 months, 24-35 months, 36-47 months, and 48+ months. Infant and Child Mortality • 139 Table 8.5 High-risk fertility behaviour Percent distribution of children born in the five years preceding the survey by category of elevated risk of mortality and the risk ratio, and percent distribution of currently married women by category of risk if they were to conceive a child at the time of the survey, Zimbabwe 2015 Births in the 5 years preceding the survey Percentage of currently married women1 Risk category Percentage of births Risk ratio Not in any high risk category 38.6 1.00 24.5 Unavoidable risk category First order births between ages 18 and 34 years 20.0 1.10 5.0 Single high-risk category Mother’s age <18 6.1 1.58 0.9 Mother’s age >34 2.0 1.25 5.9 Birth interval <24 months 4.4 1.26 9.7 Birth order >3 15.5 0.94 16.0 Subtotal 28.1 1.15 32.3 Multiple high-risk category Age <18 and birth interval <24 months2 0.3 * 0.4 Age >34 and birth interval <24 months 0.2 * 0.3 Age >34 and birth order >3 9.2 1.27 26.4 Age >34 and birth interval <24 months and birth order >3 0.6 (0.00) 3.2 Birth interval <24 months and birth order >3 3.0 1.82 7.9 Subtotal 13.3 1.32 38.3 In any avoidable high-risk category 41.4 1.21 70.6 Total 100.0 na 100.0 Number of births/women 6,360 na 6,151 Notes: Risk ratio is the ratio of the proportion dead among births in a specific high- risk category to the proportion dead among births not in any high-risk category. Ratios in parentheses are based on 25-49 unweighted cases. An asterisk indicates that a ratio is based on fewer than 25 unweighted cases and has been suppressed. na = Not applicable 1 Women are assigned to risk categories according to the status they would have at the birth of a child if they were to conceive at the time of the survey: current age less than 17 years and 3 months or older than 34 years and 2 months, latest birth less than 15 months ago, or latest birth being of order 3 or higher. 2 Includes the category age <18 and birth order >3 a Includes sterilised women Maternal Health Care • 141 MATERNAL HEALTH CARE 9 Key Findings  Antenatal care coverage: Ninety-three percent of women age 15-49 who gave birth in the 5 years preceding the survey received antenatal care (ANC) from a skilled provider during pregnancy for their most recent birth. However, only 39 percent received any antenatal care during their first trimester.  Components of antenatal care: Nearly all women who received ANC had their blood pressure measured (97 percent) and a blood sample taken (98 percent).  Protection against neonatal tetanus: Fifty-four percent of the women who gave birth in the 5 years preceding the survey had sufficient tetanus toxoid injections to ensure that their most recent birth was protected against neonatal tetanus.  Delivery: Seventy-seven percent of live births in the 5 years preceding the survey took place in a health facility.  Caesarean section: Six percent of births in the past 5 years were delivered via Caesarean section.  Maternal postnatal checks: Among women who gave birth in the 2 years preceding the survey, 57 percent received a postnatal check-up in the first 2 days after birth.  Newborn postnatal checks: Among newborns born in the 2 years preceding the survey, 73 percent received a postnatal check-up in the first 2 days after birth. he health care services that a mother receives during pregnancy, childbirth, and the immediate postnatal period are important for the survival and wellbeing of both the mother and the infant. The 2015 ZDHS obtained information on the extent to which women in Zimbabwe receive care during each of these stages. These findings are important to those who design policy and implement programmes that improve maternal and child health care services. The first part of this chapter presents information on ANC providers, the number and timing of ANC visits, and various components of care. The second part focuses on childbirth and presents information on the place of delivery, assistance during delivery, and caesarean deliveries. The third section focuses on postnatal care and presents information on postnatal health checks for mothers and newborns. The conclusion examines the barriers that women may face when seeking care during pregnancy, delivery, and the postnatal period. T 142 • Maternal Health Care 9.1 ANTENATAL CARE COVERAGE AND CONTENT 9.1.1 Skilled Providers Antenatal care (ANC) from a skilled provider Pregnancy care received from skilled providers, i.e., doctors, nurses, and nurse midwives. Sample: Women age 15-49 who had a live birth in the 5 years before the survey Ninety-three percent of women age 15-49 received ANC from a skilled provider during the pregnancy of their most recent birth (Table 9.1). The majority of women received ANC from a nurse (64 percent), while 17 percent received ANC from a nurse midwife and 12 percent from a doctor. Trends: The proportion of women age 15-49 in Zimbabwe who received ANC from a skilled provider increased slightly from 90 percent in 2010-11 to 93 percent in 2015, returning to 2005-06 ZDHS levels (Figure 9.1). Patterns by background characteristics  Higher-order births are less likely to receive ANC than lower-order births (Table 9.1). Eighty percent of women giving birth to their sixth or higher-order child received ANC from a skilled provider, compared with 96 percent of women giving birth to their first child.  ANC coverage from a skilled provider is somewhat higher in urban areas than in rural areas (96 percent and 92 percent, respectively). It is noteworthy that urban women are four times more likely than rural women to receive ANC from a doctor (24 percent versus 6 percent).  ANC coverage from a skilled provider is highest in Matabeleland North (98 percent) and lowest in Manicaland (86 percent).  Women in the highest wealth quintile are more than six times as likely as women in the lowest two wealth quintiles to receive ANC from a doctor (32 percent versus 5 percent). 9.1.2 Timing and Number of ANC Visits Ninety-three percent of women who had a live birth in the five years preceding the survey had at least one ANC visit (Table 9.2, Figure 9.1). Three-quarters of women (76 percent) had four or more visits and only 7 percent did not receive any ANC. There are no major differences by place of residence in the number of visits made by women. Overall, 39 percent of women were in their first trimester of pregnancy at the time of their first ANC visit, as recommended. However, it must be noted that a relatively high percentage of women (35 percent) were four to five months pregnant when they first had an ANC visit and 17 percent delayed until sixth or seventh month. Figure 9.1 Antenatal care coverage trends 94 71 27 90 64 19 93 76 39 Received any ANC from a skilled provider Had 4+ ANC visits Had ANC in first trimester (<4 months) Percentage of women age 15-49 who had a live birth in the 5 years before the survey (for the most recent birth) 2005-06 2010-11 2015 Maternal Health Care • 143 Trends: The proportion of women who received the recommended four or more ANC visits has increased from 71 percent since 2005-06 to 76 percent in 2015 (Figure 9.1), while the proportion of women receiving no ANC has decreased from 10 percent to 7 percent. The median number of months pregnant at the first ANC visit has decreased gradually, from 5.0 months in 2005-06 to 4.4 months in 2015. 9.1.3 Components of ANC Visits Among women who received ANC, 98 percent had a blood sample taken, 97 percent had their blood pressure measured, and 68 percent had a urine sample taken (Table 9.3). Among women with a live birth in the past 5 years, 83 percent took iron tablets or syrup and only 3 percent of women took intestinal parasite drugs. Trends: There have been fluctuations in coverage of each of the three ANC components between 2005-06 and 2015 ZDHS surveys. The proportion of pregnant women who had their blood pressure measured decreased from 93 percent in 2005-06 to 88 percent in 2010-11, and then it increased to 97 percent in 2015. Blood samples were taken from 68 percent of pregnant women in 2005-06 compared with 84 percent in 2010-11 and 98 percent in 2015. Urine sample collection fluctuated from 69 percent in 2005-06 to 60 percent in 2010-11 and to 68 percent in 2015. Other Components of ANC The 2015 ZDHS also collected data on other components of care important to maternal and newborn health outcomes. Eighty-three percent of women took iron tablets or syrup during the pregnancy of their last birth. For complete information on these components of ANC, see Table 9.3. 9.2 PROTECTION AGAINST NEONATAL TETANUS Protection against neonatal tetanus The number of tetanus toxoid injections needed to protect a baby from neonatal tetanus depends on the mother’s vaccinations. A birth is protected against neonatal tetanus if the mother has received any of the following:  Two tetanus toxoid injections during that pregnancy  Two or more injections, the last one within 3 years of the birth  Three or more injections, the last one within 5 years of the birth  Four or more injections, the last one within 10 years of the birth  Five or more injections at any time prior to the birth Sample: Last live births in the 5 years before the survey to women age 15-49 Depending on whether and when a pregnant woman has been vaccinated against tetanus before the most recent pregnancy, the woman may need as many as two tetanus toxoid injections during her pregnancy to protect her baby against neonatal tetanus. Fifty-four percent of women’s last births were protected against neonatal tetanus (Table 9.4). Trends: The proportion of births in the 5 years before the survey protected against neonatal tetanus decreased from 59 percent in 2005-06 to 54 percent in 2010-11 and in 2015. Patterns by background characteristics  First-order births (49 percent) and births of sixth or higher order (46 percent) are more likely to be protected against neonatal tetanus when compared with other births (55 to 58 percent).  Mashonaland West has the highest proportion of births protected against neonatal tetanus (67 percent), while Harare has the lowest proportion (45 percent). 144 • Maternal Health Care 9.3 PLACE OF DELIVERY Institutional deliveries Deliveries that take place in a health facility Sample: All live births in the 5 years before the survey Seventy-seven percent of live births in the 5 years before the survey took place in a health facility, while 20 percent were delivered at home. Most institutional deliveries took place at public sector health facilities (65 percent) (Table 9.5). Trends: Institutional deliveries in Zimbabwe declined from 72 percent in 1999, to 68 percent in 2005-06, and 65 percent in 2010-11, and then substantially increased to 77 percent in 2015. Over the same period, home deliveries increased from 23 percent in 1999, to 31 percent in 2005-06, and 34 percent in 2011-10, and then decreased notably to 20 percent in 2015 (Figure 9.2). Patterns by background characteristics  Higher-order births (6+) are more likely to be delivered at home (43 percent) compared with 13 percent of first-order births (Table 9.5).  Only 21 percent of live births to women who received no ANC services took place in a health facility compared with 86 percent of live births to women who received four or more visits.  Nine in ten births in Harare and Bulawayo were delivered in a health facility, compared with 66 percent in Mashonaland West (Figure 9.3).  Births to mothers with more than a secondary education are much more likely to take place in a health facility than births to mothers with no education (99 percent and 52 percent, respectively) (Figure 9.4). Figure 9.2 Trends in place of delivery Figure 9.3 Institutional deliveries by province Percentage of live births in the 5 years before the survey that were delivered at a health facility 72 68 65 77 23 31 34 20 1999 2005-06 2010-11 2015 Percentage of live births in the 5 years before the survey Delivered in health facility Delivered at home Maternal Health Care • 145 Figure 9.4 Institutional deliveries by mother’s education 9.4 SKILLED ASSISTANCE DURING DELIVERY Skilled assistance during delivery Births delivered with the assistance of doctors, nurses and nurse/midwives. Sample: All live births in the 5 years before the survey In Zimbabwe, about 8 in 10 deliveries are assisted by a skilled provider, the majority by a nurse or nurse midwife (66 percent). Unskilled persons, such as traditional birth attendants, village health workers and relatives/friends, assist in 20 percent, while 3 percent of births receive no assistance (Figure 9.5). Trends: Since 1999, skilled assistance at delivery in Zimbabwe decreased from 72 percent in 1999 to 69 percent in 2005-06 and to 66 percent in 2010-11. However, as has been observed with other maternal health indicators, delivery assistance in 2015 shows significant improvement, with 78 percent of births in the last five years having been assisted by a skilled provider. Patterns by background characteristics  First-order births are the most likely to receive assistance from a skilled provider (86 percent), while sixth or higher-order births are the least likely to do so (56 percent) (Table 9.6).  In urban areas, 93 percent of births were assisted by a skilled provider compared with 71 percent in rural areas.  More than 9 in 10 deliveries in Harare (91 percent) and Bulawayo (95 percent) were assisted by a skilled provider, compared with fewer than 7 in 10 (67 percent) of births in Mashonaland West. Manicaland has the highest percentage of deliveries by traditional birth attendants (18 percent). 52 64 82 99 77 No education Primary Secondary More than secondary Total Percentage of live births in the 5 years preceding the survey that were delivered at a health facility Figure 9.5 Delivery assistance Village health worker 2% No one 3% Traditional Birth Attendant 8% Doctor 12% Relative/Other 10% Nurse 42% Nurse midwife 25% Percent distribution of births in the 5 years before the survey 146 • Maternal Health Care  All births to women with more than a secondary education received assistance from a skilled provider during delivery compared with half of women with no education.  Births to women in the highest wealth quintile were much more likely to receive assistance at delivery from a skilled provider (96 percent) compared with births to women in the lowest wealth quintile (62 percent) (Figure 9.6). 9.5 DELIVERY BY CAESAREAN Access to caesarean sections can reduce maternal and neonatal mortality and complications such as obstetric fistula. However, use of caesarean section without a medical need can put women at risk of short- and long-term health problems. The WHO advises that caesarean sections should only be done when medically necessary, and does not recommend a target rate for countries to achieve at the population level. Research conducted by WHO has found that increases in countries’ caesarean section rates up to 10 percent are associated with a decline in maternal and neonatal mortality. However, increases in caesarean section rates beyond 10 percent are not associated with reductions in maternal and newborn mortality rates (WHO 2015). The 2015 ZDHS found that caesarean deliveries accounted for 6 percent of all births in the 5 years before the survey (Table 9.7). Trends: In 1999, 7 percent of births were delivered via caesarean section. This percentage decreased to 5 percent in 2005-06 and 2010-11, and increased slightly to 5 percent in 2015. Patterns by background characteristics  Caesarean deliveries are most common among first births (8 percent) when compared with higher- order births (ranging from 2 to 6 percent) (Table 9.7).  The caesarean delivery rate is higher in urban than in rural areas (11 percent versus 4 percent).  Among provinces, Mashonaland Central has the lowest caesarean rate (2 percent) while Bulawayo has the highest rate (15 percent).  Higher educated women are notably more likely to undergo caesarean deliveries; 22 percent of women with more than a secondary education undergo caesarean deliveries compared with just 3 percent of women with no education.  The caesarean rate among births to women in the highest wealth quintile is eight times higher than the rate for women in the lowest wealth quintile (15 percent versus 2 percent). 9.6 POSTNATAL CARE 9.6.1 Postnatal Health Check for Mothers Safe motherhood programs recommend that women receive a postnatal health check within two days after delivery. In Zimbabwe, 68 percent of mothers received a postnatal check, but only 57 percent had a check in the first two days after delivery (Table 9.8). One in three mothers (32 percent) did not have any postnatal health check. Figure 9.6 Delivery assistance by wealth quintile 62 70 78 89 96 78 Lowest Second Third Fourth Highest TOTAL Percent distribution of births in the 5 years before the survey RichestPoorest Maternal Health Care • 147 Trends: The proportion of mothers who received a postnatal check in the first 2 days after delivery has increased dramatically, from 28 percent in 2010-11 to 57 percent in 2015. Patterns by background characteristics  Women who delivered in a health facility were more than three times as likely to receive a postnatal health check within 2 days of delivery as those who delivered elsewhere (65 percent versus 19 percent) (Table 9.8).  There are marked differences in postnatal care for mothers by province. Mothers are most likely to have a timely postnatal health check in Matabeleland South (81 percent) and least likely in Masvingo (44 percent).  Mothers with more than a secondary education (82 percent) and those in the wealthiest households (69 percent) are more likely to receive timely postnatal care when compared with women with less education and those in the poorer households. Type of Provider Forty-three percent of women received a postnatal health check in the first 2 days after delivery from a doctor or nurse and 13 percent received it from a nurse midwife (Table 9.9). 9.6.2 Postnatal Health Checks for Newborns Postnatal care services for newborns should start as soon as possible after birth because many neonatal deaths occur within the first 48 hours of life. Among newborns born in the 2 years before the survey, 73 percent received a postnatal check within 2 days after birth. However, almost one in five (18 percent) did not receive any postnatal health check (Table 9.10). Patterns by background characteristics  Newborns delivered in a health facility are almost three times as likely to receive a postnatal health check within 2 days of birth as those delivered elsewhere (84 percent versus 29 percent) (Table 9.10).  By province, the percentage of newborns who receive a postnatal health check within 2 days ranges from 60 percent in Manicaland to 87 percent in Matabeleland South.  There is a clear correlation between a mother’s education and the likelihood of a timely postnatal health check for newborns. The proportion of births in which the baby received a postnatal check within the first two days ranges from 63 percent among women with primary education to 86 percent among women with more than a secondary education. Type of Provider Fifty-five percent of newborns received a postnatal health check in the first 2 days after delivery from a doctor or nurse and 17 percent received it from a nurse midwife (Table 9.11). 9.6.3 Content of Postnatal Care for Newborns Forty-eight percent of births have all six signal functions performed during the 2 days after birth— umbilical cord examined, temperature measured, counselling on danger signs, breastfeeding counselling, breastfeeding observation, weight measured (Table 9.12). Approximately 7 in 10 of newborns had their cord examined (74 percent) and temperature measured (71 percent), and 85 percent were weighed 2 days after birth. Mothers of about three-fourths of newborns received breastfeeding counselling and were observed breastfeeding. 148 • Maternal Health Care Patterns by background characteristics  Performance of all six signals functions during the first 2 days decreases with birth order from 52 percent for first births to 32 percent for sixth or higher-order births (Table 9.12).  Performance of all six signals functions during the first 2 days of life is higher in urban than in rural areas (58 percent versus 44 percent).  Among provinces, Matabeleland South has the highest rate of performance of all six signals functions in the 2 days after birth (73 percent), while Mashonaland West has the lowest rate (25 percent).  Newborns of mothers with more than a secondary education are more likely to have had all six signal functions performed within the first 2 days (67 percent) compared with newborns of mothers with primary education (37 percent).  Performance of all six signals functions during the first 2 days of life increases with wealth. 9.7 PROBLEMS IN ACCESSING HEALTH CARE Problems in accessing health care Women were asked whether each of the following factors is a big problem in seeking medical advice or treatment for themselves when they are sick:  getting permission to go to the doctor  getting money for advice or treatment  distance to a health facility  not wanting to go alone Sample: Women age 15-49 Almost two-thirds of women (59 percent) in Zimbabwe report at least one of the problems associated with accessing health care for themselves. This proportion ranges from 45 percent in Harare and Bulawayo to 70 percent each in Manicaland and Mashonaland Central (Table 9.13). The most commonly reported problems are obtaining money to pay for treatment (43 percent) and distance to the health facility (33 percent). Fewer women say that not wanting to go alone (14 percent) or needing permission to go for treatment (5 percent) are big problems in seeking medical advice or treatment. 9.8 PREVENTION OF CERVICAL CANCER Cervical cancer is one of the leading causes of deaths among women. Cervical cancer screening via the Papanicolau (Pap) test or the Visual Inspection with Acetic Acid and Camera (VIAC) are effective for detecting early abnormal or cancer cells in the cervix and uterus. The Pap and VIAC tests are recommended for women from the time they become sexually active. In the 2015 ZDHS, women age 15-49 were asked if they had heard of cervical cancer and whether they had ever been screened for cervical cancer. Women who ever had a cervical screening were asked about the timing of their last cervical exam. Nationally, 79 percent of women report that they have heard of cervical cancer (Table 9.14). However, only 13 percent of women have ever had a cervical exam. Among those who report having a cervical exam, 90 percent report having the exam in the last 3 years and 66 percent had their cervical exam within the last 12 months. Women in urban areas are three times more likely than their rural counterparts to report ever having a cervical exam (21 percent and 7 percent, respectively). Women in Harare (24 percent) and Bulawayo (21 Maternal Health Care • 149 percent) have the highest percentages who report ever having a cervical exam, and women in Manicaland have the lowest percentage (6 percent). As education and wealth increases, so does the likelihood of a woman having a cervical exam. LIST OF TABLES For detailed information on maternal health care, see the following tables:  Table 9.1 Antenatal care  Table 9.2 Number of antenatal care visits and timing of first visit  Table 9.3 Components of antenatal care  Table 9.4 Tetanus toxoid injections  Table 9.5 Place of delivery  Table 9.6 Assistance during delivery  Table 9.7 Caesarean section  Table 9.8 Timing of first postnatal check for the mother  Table 9.9 Type of provider of first postnatal check for the mother  Table 9.10 Timing of first postnatal check for the newborn  Table 9.11 Type of provider of first postnatal check for the newborn  Table 9.12 Content of postnatal care for newborns  Table 9.13 Problems in accessing health care  Table 9.14 Knowledge and prevention of cervical cancer 150 • Maternal Health Care Table 9.1 Antenatal care Percent distribution of women age 15-49 who had a live birth in the 5 years preceding the survey by antenatal care (ANC) provider during pregnancy for the most recent birth and percentage receiving ANC from a skilled provider for the most recent birth, according to background characteristics, Zimbabwe 2015 Antenatal care provider No ANC Total Percentage receiving antenatal care from a skilled provider1 Number of women Background characteristic Doctor Nurse Nurse midwife Traditional birth attendant Village health worker Mother’s age at birth <20 10.3 68.8 15.5 0.0 0.0 5.1 100.0 94.6 775 20-34 12.0 63.4 17.6 0.2 0.0 6.7 100.0 93.0 3,535 35-49 13.5 62.8 16.8 0.2 0.0 6.7 100.0 93.1 677 Birth order 1 14.3 67.5 14.4 0.0 0.0 3.7 100.0 96.2 1,206 2-3 12.7 63.2 19.1 0.1 0.0 4.8 100.0 95.0 2,308 4-5 10.2 63.7 17.3 0.4 0.0 8.3 100.0 91.3 1,093 6+ 5.1 60.5 13.9 0.4 0.0 20.1 100.0 79.5 381 Residence Urban 23.6 52.9 19.3 0.0 0.0 4.1 100.0 95.7 1,637 Rural 6.3 69.7 16.2 0.2 0.0 7.6 100.0 92.1 3,351 Province Manicaland 8.2 51.8 26.5 0.6 0.0 13.0 100.0 86.4 709 Mashonaland Central 6.4 82.9 4.4 0.2 0.0 6.1 100.0 93.7 492 Mashonaland East 6.9 75.0 12.3 0.0 0.0 5.9 100.0 94.1 473 Mashonaland West 12.8 55.6 25.0 0.0 0.0 6.4 100.0 93.4 638 Matabeleland North 5.8 69.7 22.8 0.0 0.0 1.6 100.0 98.4 234 Matabeleland South 12.3 80.9 3.0 0.0 0.0 3.5 100.0 96.2 200 Midlands 7.3 81.1 7.0 0.0 0.0 4.6 100.0 95.4 678 Masvingo 8.9 66.0 17.9 0.5 0.0 6.7 100.0 92.8 583 Harare 25.2 42.4 26.4 0.0 0.0 5.7 100.0 94.1 762 Bulawayo 27.7 60.7 8.0 0.4 0.0 3.2 100.0 96.4 220 Education No education (6.4) (64.9) (21.8) (0.0) (0.0) (6.9) 100.0 (93.1) 57 Primary 5.8 68.4 15.5 0.4 0.0 9.8 100.0 89.6 1,530 Secondary 11.9 64.4 18.2 0.1 0.0 5.3 100.0 94.5 3,125 More than secondary 47.8 37.5 14.2 0.0 0.0 0.4 100.0 99.6 275 Wealth quintile Lowest 5.3 67.7 17.0 0.8 0.0 9.2 100.0 90.0 1,082 Second 5.3 73.2 13.4 0.0 0.0 8.0 100.0 91.9 956 Middle 5.7 71.6 16.0 0.0 0.0 6.7 100.0 93.3 860 Fourth 12.9 61.2 19.2 0.0 0.0 6.5 100.0 93.3 1,183 Highest 31.5 47.3 19.8 0.1 0.0 1.3 100.0 98.6 908 Total 12.0 64.2 17.2 0.2 0.0 6.5 100.0 93.3 4,988 Notes: If more than one source of ANC was mentioned, only the provider with the highest qualifications is considered in this tabulation. Figures in parentheses are based on 25-49 unweighted cases. 1 Skilled provider includes doctor, nurse, and nurse midwife. Maternal Health Care • 151 Table 9.2 Number of antenatal care visits and timing of first visit Percent distribution of women age 15-49 who had a live birth in the 5 years preceding the survey by number of antenatal care (ANC) visits for the most recent live birth, and by the timing of the first visit, and among women with ANC, median months pregnant at first visit, according to residence, Zimbabwe 2015 Residence Total Number and timing of ANC visits Urban Rural Number of ANC visits None 4.1 7.6 6.5 1 2.2 1.3 1.6 2-3 16.0 15.9 15.9 4+ 77.4 74.9 75.7 Don’t know/missing 0.3 0.3 0.3 Total 100.0 100.0 100.0 Number of months pregnant at time of first ANC visit No antenatal care 4.1 7.6 6.5 <4 33.9 40.7 38.5 4-5 34.4 35.0 34.8 6-7 22.8 14.6 17.3 8+ 4.6 2.0 2.9 Don’t know/missing 0.3 0.1 0.2 Total 100.0 100.0 100.0 Number of women 1,637 3,351 4,988 Median months pregnant at first visit (for those with ANC) 4.8 4.3 4.4 Number of women with ANC 1,570 3,096 4,666 152 • Maternal Health Care Table 9.3 Components of antenatal care Among women age 15-49 with a live birth in the 5 years preceding the survey, percentages who took iron tablets or syrup and drugs for intestinal parasites during the pregnancy of the most recent birth; and among women receiving antenatal care (ANC) for the most recent live birth in the 5 years preceding the survey, percentage receiving specific antenatal services, according to background characteristics, Zimbabwe 2015 Among women with a live birth in the past 5 years, percentage who during the pregnancy of their last birth: Among women who received antenatal care for their most recent birth in the past 5 years, percentage with the selected services Number of women with ANC for their most recent birth Background characteristic Took iron tablets or syrup Took intestinal parasite drugs Number of women with a live birth in the past 5 years Blood pressure measured Urine sample taken Blood sample taken Mother’s age at birth <20 87.5 4.3 775 95.4 58.8 98.0 736 20-34 83.0 3.1 3,535 97.2 69.3 98.6 3,298 35-49 80.0 3.6 677 97.2 73.4 97.3 632 Birth order 1 86.8 3.5 1,206 96.5 68.6 99.1 1,160 2-3 84.9 3.3 2,308 97.7 68.1 98.3 2,198 4-5 80.9 3.2 1,093 95.8 68.8 98.0 1,002 6+ 69.7 4.1 381 97.0 66.0 96.2 305 Residence Urban 82.6 2.2 1,637 98.6 81.0 99.2 1,570 Rural 83.7 3.9 3,351 96.1 61.7 97.9 3,096 Province Manicaland 80.1 4.5 709 93.9 66.7 96.8 617 Mashonaland Central 84.5 5.1 492 97.0 60.5 97.4 462 Mashonaland East 85.0 3.3 473 97.1 69.0 98.6 445 Mashonaland West 84.5 3.0 638 96.1 55.2 98.5 597 Matabeleland North 81.2 1.9 234 97.6 53.6 98.9 230 Matabeleland South 86.5 1.0 200 97.5 71.3 99.3 193 Midlands 85.7 2.0 678 97.1 61.7 98.6 646 Masvingo 85.2 7.6 583 97.2 76.5 97.5 545 Harare 79.3 1.4 762 99.1 84.3 99.7 718 Bulawayo 85.2 0.3 220 97.8 81.4 98.7 212 Education No education (83.8) (4.0) 57 (87.5) (48.3) (93.6) 53 Primary 80.6 3.7 1,530 95.3 57.5 96.8 1,380 Secondary 84.5 3.3 3,125 97.6 71.5 99.0 2,959 More than secondary 85.0 2.5 275 99.6 90.3 99.6 274 Wealth quintile Lowest 81.9 4.5 1,082 94.4 54.1 96.2 982 Second 84.0 3.0 956 96.2 60.2 98.2 880 Middle 85.7 3.9 860 96.7 63.6 98.8 802 Fourth 81.0 2.7 1,183 98.6 78.5 99.0 1,106 Highest 85.0 2.8 908 98.6 83.1 99.4 896 Total 83.3 3.4 4,988 96.9 68.2 98.3 4,666 Note: Figures in parentheses are based on 25-49 unweighted cases. Maternal Health Care • 153 Table 9.4 Tetanus toxoid injections Among mothers age 15-49 with a live birth in the 5 years preceding the survey, percentage receiving two or more tetanus toxoid injections during the pregnancy for the last live birth and percentage whose last live birth was protected against neonatal tetanus, according to background characteristics, Zimbabwe 2015 Background characteristic Percentage receiving two or more injections during last pregnancy Percentage whose last birth was protected against neonatal tetanus1 Number of mothers Mother’s age at birth <20 44.4 51.1 775 20-34 39.8 55.4 3,535 35-49 36.3 52.2 677 Birth order 1 42.7 49.0 1,206 2-3 41.8 58.1 2,308 4-5 36.1 55.0 1,093 6+ 32.0 46.3 381 Residence Urban 34.2 50.2 1,637 Rural 42.9 56.3 3,351 Province Manicaland 36.0 45.7 709 Mashonaland Central 51.4 59.4 492 Mashonaland East 45.2 59.7 473 Mashonaland West 38.3 67.0 638 Matabeleland North 41.8 58.1 234 Matabeleland South 48.3 66.2 200 Midlands 41.4 51.6 678 Masvingo 45.1 54.3 583 Harare 30.6 44.8 762 Bulawayo 27.0 49.0 220 Education No education (28.1) (38.4) 57 Primary 40.4 53.6 1,530 Secondary 41.0 55.4 3,125 More than secondary 29.8 49.2 275 Wealth quintile Lowest 39.9 52.5 1,082 Second 46.3 61.2 956 Middle 44.3 57.8 860 Fourth 34.6 48.9 1,183 Highest 36.5 53.0 908 Total 40.0 54.3 4,988 Note: Figures in parentheses are based on 25-49 unweighted cases. 1 Includes mothers with two injections during the pregnancy of her last birth, or two or more injections (the last within 3 years of the last live birth), or three or more injections (the last within 5 years of the last birth), or four or more injections (the last within 10 years of the last live birth), or five or more injections at any time prior to the last birth. 154 • Maternal Health Care Table 9.5 Place of delivery Percent distribution of live births in the 5 years preceding the survey by place of delivery and percentage delivered in a health facility, according to background characteristics, Zimbabwe 2015 Health facility Home Other Total Percentage delivered in a health facility Number of births Background characteristic Public medical sector Private medical sector Mission hospital or clinic Mother’s age at birth <20 66.5 1.2 9.3 20.8 2.2 100.0 77.0 1,074 20-34 66.2 5.5 6.0 19.2 3.1 100.0 77.7 4,572 35-49 56.0 7.5 9.4 24.7 2.4 100.0 72.9 772 Birth order 1 71.0 4.6 9.3 13.2 1.9 100.0 84.9 1,671 2-3 68.0 6.1 4.8 18.2 3.0 100.0 78.8 2,928 4-5 59.0 4.4 7.9 25.2 3.5 100.0 71.3 1,353 6+ 42.9 1.2 9.4 42.6 3.9 100.0 53.5 466 Antenatal care visits1 None 20.0 0.2 0.6 73.0 6.1 100.0 20.9 322 1-3 68.8 1.4 5.0 21.7 3.2 100.0 75.1 874 4+ 71.3 6.5 8.0 12.0 2.2 100.0 85.7 3,777 Residence Urban 78.9 11.3 1.8 6.5 1.5 100.0 92.1 2,027 Rural 58.7 2.1 9.3 26.4 3.5 100.0 70.0 4,392 Province Manicaland 57.3 2.7 9.6 28.1 2.4 100.0 69.5 966 Mashonaland Central 56.9 1.0 10.5 26.8 4.7 100.0 68.5 629 Mashonaland East 62.7 2.2 8.5 21.5 5.0 100.0 73.4 609 Mashonaland West 59.3 3.1 3.4 31.3 3.0 100.0 65.7 847 Matabeleland North 67.5 2.0 13.5 14.5 2.5 100.0 83.0 288 Matabeleland South 78.9 1.5 3.0 13.5 3.1 100.0 83.4 238 Midlands 65.2 5.1 10.4 17.1 2.0 100.0 80.8 866 Masvingo 62.1 8.2 7.7 18.4 3.6 100.0 78.0 764 Harare 78.4 12.2 0.5 8.6 0.3 100.0 91.1 949 Bulawayo 81.6 6.2 2.5 4.7 5.0 100.0 90.3 262 Mother’s education No education 42.3 0.0 9.2 43.9 4.6 100.0 51.5 76 Primary 54.9 1.0 7.9 32.4 3.9 100.0 63.7 2,038 Secondary 71.4 4.3 6.7 15.1 2.5 100.0 82.4 3,962 More than secondary 57.3 38.1 4.0 0.1 0.5 100.0 99.4 342 Wealth quintile Lowest 53.1 0.0 7.7 35.3 3.9 100.0 60.8 1,477 Second 58.7 0.5 9.1 27.0 4.8 100.0 68.3 1,252 Middle 63.3 1.7 11.1 21.3 2.5 100.0 76.2 1,098 Fourth 79.4 3.9 4.3 10.6 1.8 100.0 87.6 1,504 Highest 70.6 21.9 2.8 3.6 1.2 100.0 95.2 1,087 Total 65.1 5.0 6.9 20.1 2.9 100.0 77.0 6,418 Note: Total includes 10 cases with missing information on number of antenatal care visits. 1 Includes only the most recent birth in the 5 years preceding the survey Maternal Health Care • 155 Table 9.6 Assistance during delivery Percent distribution of live births in the 5 years preceding the survey by person providing assistance during delivery, percentage of birth assisted by a skilled provider, according to background characteristics, Zimbabwe 2015 Person providing assistance during delivery Total Percentage delivered by a skilled provider1 Number of births Background characteristic Doctor Nurse Nurse midwife Traditional birth attendant Village health worker Relative/ other No one Mother’s age at birth <20 10.9 43.2 23.0 9.7 1.8 10.0 1.3 100.0 77.2 1,074 20-34 12.3 41.6 25.0 7.3 1.5 9.5 2.8 100.0 78.9 4,572 35-49 12.7 38.6 23.4 8.1 1.7 11.0 4.5 100.0 74.7 772 Birth order 1 16.1 44.1 25.5 5.2 1.2 6.8 1.0 100.0 85.7 1,671 2-3 12.5 41.3 25.9 7.4 1.3 9.5 2.1 100.0 79.8 2,928 4-5 9.6 40.8 22.3 9.3 2.3 11.1 4.6 100.0 72.7 1,353 6+ 2.5 35.5 18.4 15.1 2.2 18.2 8.1 100.0 56.3 466 Antenatal care visits2 None 3.0 11.1 8.8 39.9 1.3 28.1 7.9 100.0 22.9 322 1-3 9.6 42.0 24.1 6.0 1.9 12.3 4.2 100.0 75.6 874 4+ 14.1 45.0 27.6 3.7 1.4 6.5 1.8 100.0 86.6 3,777 Place of delivery Health facility 15.5 53.3 30.8 0.2 0.0 0.2 0.1 100.0 99.5 4,941 Elsewhere 0.7 2.2 3.6 33.2 6.7 41.9 11.7 100.0 6.5 1,477 Residence Urban 23.9 37.1 31.9 2.7 0.8 2.1 1.5 100.0 92.9 2,027 Rural 6.7 43.6 21.1 10.1 1.9 13.3 3.4 100.0 71.3 4,392 Province Manicaland 8.1 30.1 31.7 17.7 1.5 8.8 2.1 100.0 69.9 966 Mashonaland Central 5.1 50.9 13.0 12.8 2.1 13.0 3.1 100.0 69.1 629 Mashonaland East 7.2 48.3 18.9 9.9 1.0 10.9 3.9 100.0 74.3 609 Mashonaland West 11.0 32.3 23.9 4.8 3.4 19.0 5.6 100.0 67.2 847 Matabeleland North 8.4 38.0 37.8 4.7 1.4 7.5 2.2 100.0 84.2 288 Matabeleland South 10.8 46.6 30.9 4.4 0.3 5.7 1.3 100.0 88.3 238 Midlands 11.2 54.8 15.2 4.6 1.9 9.9 2.5 100.0 81.2 866 Masvingo 8.6 49.7 21.8 5.2 0.7 11.5 2.5 100.0 80.2 764 Harare 25.4 31.1 34.8 3.7 1.2 2.0 1.8 100.0 91.3 949 Bulawayo 28.4 44.5 21.8 3.2 0.2 1.8 0.0 100.0 94.8 262 Mother’s education No education 1.8 33.8 14.1 14.4 3.2 21.8 10.9 100.0 49.7 76 Primary 6.5 40.0 19.4 11.8 2.2 16.2 3.9 100.0 65.8 2,038 Secondary 12.3 43.7 27.1 6.2 1.3 7.1 2.3 100.0 83.1 3,962 More than secondary 45.4 26.9 27.7 0.1 0.0 0.0 0.0 100.0 99.9 342 Wealth quintile Lowest 3.3 40.3 18.1 12.3 2.5 19.4 4.1 100.0 61.7 1,477 Second 7.2 43.4 19.6 10.5 1.9 13.0 4.4 100.0 70.1 1,252 Middle 7.8 45.9 23.9 9.1 1.0 10.1 2.2 100.0 77.6 1,098 Fourth 15.5 42.9 30.2 4.5 1.4 3.7 1.9 100.0 88.6 1,504 Highest 29.5 34.8 31.6 1.7 0.7 1.1 0.7 100.0 95.8 1,087 Total 12.1 41.5 24.5 7.8 1.6 9.8 2.8 100.0 78.1 6,418 Notes: If the respondent mentioned more than one person attending during delivery, only the most qualified person is considered in this tabulation. Total includes 10 cases with missing information on number of antenatal care visits. 1 Skilled provider includes doctor, nurse, and nurse midwife. 2 Includes only the most recent birth in the 5 years preceding the survey 156 • Maternal Health Care Table 9.7 Caesarean section Percentage of live births in the 5 years preceding the survey delivered by caesarean section (C-section), percentage delivered by C-section that was planned before the onset of labour pains, and percentage delivered by C-section that was decided after the onset of labour pains, according to background characteristics, Zimbabwe 2015 Percentage delivered by C-section Timing of decision to conduct C-section Number of births Background characteristic Decided before onset of labour pains Decided after onset of labour pains Mother’s age at birth <20 5.1 1.0 4.1 1,074 20-34 5.6 1.9 3.6 4,572 35-49 8.5 4.3 4.2 772 Birth order 1 8.1 1.3 6.8 1,671 2-3 5.9 2.9 3.0 2,928 4-5 4.3 1.8 2.5 1,353 6+ 1.9 0.4 1.6 466 Antenatal care visits1 None 1.6 1.2 0.3 322 1-3 3.7 1.0 2.7 874 4+ 7.0 2.7 4.3 3,777 Place of delivery Public sector 6.3 2.1 4.2 4,176 Central hospital 21.8 8.0 13.8 497 Provincial hospital 19.3 5.7 13.6 426 District hospital 5.9 2.5 3.4 839 Rural hospital 3.4 0.6 2.7 447 Urban municipal clinic 0.8 0.1 0.7 663 Other public * * * 4 Rural health centre 0.3 0.0 0.3 1,300 Private sector 24.4 10.3 14.1 320 Private hospital/clinic 24.1 10.6 13.5 311 Other private sector * * * 10 Mission hospital / clinic 7.3 2.4 4.9 445 Residence Urban 10.6 4.7 5.8 2,027 Rural 3.7 0.8 2.8 4,392 Province Manicaland 5.0 1.6 3.4 966 Mashonaland Central 2.2 0.8 1.4 629 Mashonaland East 2.7 1.1 1.6 609 Mashonaland West 5.3 1.8 3.6 847 Matabeleland North 4.8 1.2 3.5 288 Matabeleland South 7.3 2.6 4.6 238 Midlands 5.5 2.4 3.1 866 Masvingo 7.0 1.9 5.1 764 Harare 8.4 3.0 5.4 949 Bulawayo 15.3 6.3 8.9 262 Mother’s education No education 2.7 0.0 2.7 76 Primary 3.4 0.8 2.6 2,038 Secondary 5.8 2.2 3.6 3,962 More than secondary 21.7 8.6 13.1 342 Wealth quintile Lowest 1.8 0.6 1.2 1,477 Second 4.1 0.8 3.3 1,252 Middle 4.6 0.8 3.8 1,098 Fourth 5.6 2.5 3.1 1,504 Highest 15.0 6.1 8.9 1,087 Total 5.8 2.1 3.8 6,418 Note: Total includes 10 cases with missing information on number of antenatal care visits. 1 Includes only the most recent birth in the 5 years preceding the survey Maternal Health Care • 157 Table 9.8 Timing of first postnatal check for the mother Among women age 15-49 giving birth in the 2 years preceding the survey, percent distribution of the mother’s first postnatal check-up for the last live birth by time after delivery, and percentage of women with a live birth in the 2 years preceding the survey who received a postnatal check in the first 2 days after giving birth, according to background characteristics, Zimbabwe 2015 Time after delivery of mother’s first postnatal check1 No postnatal check2 Total Percentage of women with a postnatal check in the first 2 days after birth1 Number of women Background characteristic Less than 4 hours 4-23 hours 1-2 days 3-6 days 7-41 days Don’t know/ missing Mother’s age at birth <20 36.8 11.8 6.8 5.7 5.6 0.2 33.0 100.0 55.5 451 20-34 38.6 11.0 7.9 5.8 5.5 0.5 30.7 100.0 57.5 1,723 35-49 34.2 11.4 6.9 4.7 6.4 1.2 35.2 100.0 52.4 279 Birth order 1 39.2 13.1 8.8 6.4 6.1 0.5 25.8 100.0 61.1 658 2-3 39.1 11.4 7.8 5.1 5.4 0.6 30.5 100.0 58.3 1,096 4-5 38.0 9.3 5.5 5.9 5.3 0.3 35.7 100.0 52.9 507 6+ 24.4 8.7 7.7 5.7 5.7 0.8 47.1 100.0 40.8 192 Place of delivery Health facility 43.6 13.1 8.6 5.2 5.7 0.6 23.2 100.0 65.3 1,987 Elsewhere 13.0 3.2 3.3 7.7 5.4 0.1 67.4 100.0 19.4 467 Residence Urban 41.4 16.3 9.0 7.2 5.5 0.7 19.9 100.0 66.7 689 Rural 36.3 9.2 7.1 5.1 5.6 0.5 36.2 100.0 52.6 1,765 Province Manicaland 26.6 8.5 9.3 4.3 2.3 0.4 48.6 100.0 44.5 396 Mashonaland Central 31.1 12.5 5.4 5.9 3.8 0.0 41.3 100.0 49.0 246 Mashonaland East 43.0 12.2 3.0 6.3 3.6 0.9 31.1 100.0 58.1 244 Mashonaland West 39.5 11.5 7.8 6.6 8.1 0.0 26.5 100.0 58.8 298 Matabeleland North 58.1 6.9 11.0 2.9 5.0 0.6 15.5 100.0 75.9 117 Matabeleland South 64.9 7.0 8.6 1.6 2.1 0.0 15.7 100.0 80.5 99 Midlands 45.4 11.1 7.0 7.5 6.1 0.7 22.2 100.0 63.5 338 Masvingo 32.2 4.8 6.8 5.4 9.3 0.5 41.0 100.0 43.8 299 Harare 30.1 19.2 11.4 4.4 7.7 1.1 26.2 100.0 60.6 324 Bulawayo 45.9 19.0 4.2 13.3 5.7 1.1 10.7 100.0 69.1 92 Education No education * * * * * * * 100.0 * 32 Primary 30.1 8.7 5.7 5.1 6.1 0.7 43.6 100.0 44.5 787 Secondary 41.1 12.0 8.5 6.1 5.5 0.3 26.4 100.0 61.6 1,534 More than secondary 50.8 21.4 9.4 2.6 4.2 2.8 8.8 100.0 81.6 101 Wealth quintile Lowest 31.9 8.4 6.7 3.8 5.1 0.4 43.6 100.0 47.1 610 Second 38.4 6.7 6.8 4.9 6.7 0.9 35.8 100.0 51.8 504 Middle 37.2 10.6 8.3 6.4 6.1 0.1 31.3 100.0 56.1 441 Fourth 40.5 17.7 6.0 6.7 5.0 0.4 23.6 100.0 64.2 550 Highest 43.5 13.2 12.0 7.5 5.0 1.2 17.6 100.0 68.7 349 Total 37.7 11.2 7.6 5.7 5.6 0.5 31.6 100.0 56.6 2,454 Note: An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. 1 Includes women who received a check from a doctor, midwife, nurse, community health worker, or traditional birth attendant. 2 Includes women who received a check after 41 days 158 • Maternal Health Care Table 9.9 Type of provider of first postnatal check for the mother Among women age 15-49 giving birth in the 2 years preceding the survey, percent distribution by type of provider of the mother’s first postnatal health check in the 2 days after the last live birth, according to background characteristics, Zimbabwe 2015 Type of health provider of mother’s first postnatal check No postnatal check in the first 2 days after birth1 Total Number of women Background characteristic Doctor/nurse Nurse midwife Traditional birth attendant Village health worker Mother’s age at birth <20 43.3 11.9 0.0 0.3 44.5 100.0 451 20-34 43.3 13.9 0.3 0.1 42.5 100.0 1,723 35-49 42.4 9.0 0.5 0.5 47.6 100.0 279 Birth order 1 47.8 13.4 0.0 0.0 38.9 100.0 658 2-3 44.8 12.9 0.3 0.2 41.7 100.0 1,096 4-5 37.4 14.9 0.2 0.3 47.1 100.0 507 6+ 33.3 6.7 0.8 0.0 59.2 100.0 192 Place of delivery Health facility 50.2 15.1 0.0 0.0 34.7 100.0 1,987 Elsewhere 13.3 3.9 1.4 0.8 80.6 100.0 467 Residence Urban 51.5 15.2 0.0 0.0 33.3 100.0 689 Rural 40.0 12.1 0.4 0.2 47.4 100.0 1,765 Province Manicaland 27.9 16.2 0.4 0.0 55.5 100.0 396 Mashonaland Central 43.6 5.1 0.4 0.0 51.0 100.0 246 Mashonaland East 49.8 8.3 0.0 0.0 41.9 100.0 244 Mashonaland West 39.9 17.8 0.8 0.4 41.2 100.0 298 Matabeleland North 44.5 30.7 0.7 0.0 24.1 100.0 117 Matabeleland South 62.8 16.8 1.0 0.0 19.5 100.0 99 Midlands 52.6 10.6 0.0 0.3 36.5 100.0 338 Masvingo 32.9 10.3 0.0 0.5 56.2 100.0 299 Harare 48.0 12.6 0.0 0.0 39.4 100.0 324 Bulawayo 60.5 8.6 0.0 0.0 30.9 100.0 92 Education No education * * * * * 100.0 32 Primary 33.2 10.4 0.5 0.3 55.5 100.0 787 Secondary 47.6 13.8 0.2 0.1 38.4 100.0 1,534 More than secondary 59.1 22.6 0.0 0.0 18.4 100.0 101 Wealth quintile Lowest 36.5 9.7 0.5 0.5 52.9 100.0 610 Second 39.3 12.1 0.4 0.0 48.2 100.0 504 Middle 42.5 13.0 0.3 0.3 43.9 100.0 441 Fourth 47.5 16.7 0.0 0.0 35.8 100.0 550 Highest 54.7 14.0 0.0 0.0 31.3 100.0 349 Total 43.2 13.0 0.3 0.2 43.4 100.0 2,454 Note: An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. 1 Includes women who received a check after 41 days Maternal Health Care • 159 Table 9.10 Timing of first postnatal check for the newborn Percent distribution of last births in the 2 years preceding the survey by time after birth of first postnatal check, and percentage of births with a postnatal check in the first 2 days after birth, according to background characteristics, Zimbabwe 2015 Time after birth of newborn’s first postnatal check1 No postnatal check2 Total Percentage of births with a postnatal check in the first 2 days after birth1 Number of births Background characteristic Less than 1 hour 1-3 hours 4-23 hours 1-2 days 3-6 days Don’t know/ missing Mother’s age at birth <20 26.8 26.1 9.4 8.0 10.0 0.9 19.0 100.0 70.2 451 20-34 30.3 24.3 11.1 8.7 6.3 1.8 17.7 100.0 74.3 1,723 35-49 34.3 17.0 10.2 11.6 5.2 0.6 21.0 100.0 73.2 279 Birth order 1 30.5 27.1 10.9 8.1 7.3 1.7 14.3 100.0 76.7 658 2-3 32.3 24.0 10.9 8.5 6.3 1.7 16.2 100.0 75.7 1,096 4-5 29.5 21.9 10.3 10.1 7.2 0.9 20.2 100.0 71.8 507 6+ 17.9 16.2 9.1 10.6 6.9 0.9 38.4 100.0 53.7 192 Place of delivery Health facility 35.8 26.8 12.0 9.4 5.8 1.8 8.5 100.0 83.9 1,987 Elsewhere 5.8 11.1 5.0 6.8 11.1 0.0 60.1 100.0 28.8 467 Residence Urban 30.6 25.7 14.2 10.2 6.2 2.5 10.6 100.0 80.6 689 Rural 29.9 23.1 9.3 8.4 7.0 1.1 21.3 100.0 70.6 1,765 Province Manicaland 26.9 15.4 8.4 9.4 5.2 1.7 33.1 100.0 60.0 396 Mashonaland Central 28.0 20.3 12.8 9.1 14.3 0.0 15.4 100.0 70.3 246 Mashonaland East 43.2 19.3 11.1 2.3 6.6 1.6 15.7 100.0 76.0 244 Mashonaland West 28.2 21.6 12.7 9.0 7.3 0.0 21.2 100.0 71.5 298 Matabeleland North 47.5 19.8 4.3 14.7 3.1 1.4 9.1 100.0 86.4 117 Matabeleland South 29.2 42.8 7.1 8.2 2.5 0.3 9.9 100.0 87.3 99 Midlands 15.6 43.0 11.3 10.4 5.5 0.7 13.4 100.0 80.4 338 Masvingo 39.3 15.7 5.7 7.4 8.2 2.2 21.4 100.0 68.1 299 Harare 23.9 25.6 15.8 12.3 5.2 4.6 12.5 100.0 77.7 324 Bulawayo 44.8 22.0 13.8 3.4 8.1 0.0 7.9 100.0 84.1 92 Mother’s education No education * * * * * * * 100.0 * 32 Primary 23.2 21.0 9.3 9.2 8.7 1.2 27.5 100.0 62.7 787 Secondary 33.2 25.5 11.3 8.6 6.0 1.5 14.0 100.0 78.6 1,534 More than secondary 38.7 25.6 10.6 11.1 3.8 4.1 6.0 100.0 86.0 101 Wealth quintile Lowest 27.1 20.9 8.4 8.3 7.3 0.9 27.0 100.0 64.8 610 Second 29.8 25.3 7.7 8.4 5.7 0.8 22.3 100.0 71.2 504 Middle 32.2 22.3 10.7 8.4 8.3 1.4 16.7 100.0 73.6 441 Fourth 29.2 25.3 15.5 8.8 7.7 2.0 11.6 100.0 78.8 550 Highest 34.5 26.3 10.9 11.4 4.2 2.8 9.9 100.0 83.1 349 Total 30.1 23.8 10.6 8.9 6.8 1.5 18.3 100.0 73.4 2,454 Note: An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. 1 Includes newborns who received a check from a doctor, midwife, nurse, community health worker, or traditional birth attendant. 2 Includes newborns who received a check after the first week of life 160 • Maternal Health Care Table 9.11 Type of provider of first postnatal check for the newborn Percent distribution of last births in the 2 years preceding the survey by type of provider of the newborn’s first postnatal health check during the 2 days after the birth, according to background characteristics, Zimbabwe 2015 Type of health provider of newborn’s first postnatal check No postnatal check in the first 2 days after birth Total Number of births Background characteristic Doctor/nurse Nurse midwife Village health worker Traditional birth attendant Mother’s age at birth <20 54.4 15.3 0.3 0.2 29.8 100.0 451 20-34 55.4 18.0 0.3 0.6 25.7 100.0 1,723 35-49 54.8 16.5 0.0 1.9 26.8 100.0 279 Birth order 1 59.2 17.3 0.0 0.2 23.3 100.0 658 2-3 56.8 17.8 0.6 0.5 24.3 100.0 1,096 4-5 51.5 18.9 0.0 1.4 28.2 100.0 507 6+ 41.2 10.4 0.0 2.2 46.3 100.0 192 Place of delivery Health facility 63.9 20.0 0.1 0.0 16.1 100.0 1,987 Elsewhere 18.1 6.1 0.9 3.7 71.2 100.0 467 Residence Urban 62.8 17.5 0.3 0.0 19.4 100.0 689 Rural 52.2 17.2 0.2 1.0 29.4 100.0 1,765 Province Manicaland 32.1 26.6 0.5 0.8 40.0 100.0 396 Mashonaland Central 61.4 7.6 0.0 1.4 29.7 100.0 246 Mashonaland East 60.9 14.1 0.0 1.0 24.0 100.0 244 Mashonaland West 48.5 21.9 0.4 0.8 28.5 100.0 298 Matabeleland North 48.7 37.7 0.0 0.0 13.6 100.0 117 Matabeleland South 71.8 14.8 0.0 0.8 12.7 100.0 99 Midlands 70.3 9.2 0.3 0.5 19.6 100.0 338 Masvingo 49.1 18.0 0.0 0.9 31.9 100.0 299 Harare 61.8 15.1 0.6 0.1 22.3 100.0 324 Bulawayo 74.7 9.4 0.0 0.0 15.9 100.0 92 Mother’s education No education * * * * * 100.0 32 Primary 45.3 15.3 0.4 1.7 37.3 100.0 787 Secondary 59.8 18.4 0.2 0.3 21.4 100.0 1,534 More than secondary 65.6 20.4 0.0 0.0 14.0 100.0 101 Wealth quintile Lowest 49.6 13.9 0.2 1.1 35.2 100.0 610 Second 51.4 18.4 0.0 1.4 28.8 100.0 504 Middle 54.0 18.2 0.7 0.7 26.4 100.0 441 Fourth 58.0 20.7 0.0 0.0 21.2 100.0 550 Highest 67.1 15.4 0.6 0.0 16.9 100.0 349 Total 55.1 17.3 0.3 0.7 26.6 100.0 2,454 Note: An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. Maternal Health Care • 161 Table 9.12 Content of postnatal care for newborns Among last births in the 2 years preceding the survey, percentage for whom selected functions were performed within 2 days after birth and percentage with at least two signal functions performed within 2 days after birth, according to background characteristics, Zimbabwe 2015 Among last births in the 2 years preceding the survey, percentage for whom the selected function was performed within 2 days after birth: Percentage with all six signal functions performed during the 2 days after birth Number of births Background characteristic Cord examined Temperatur e measured Counselling on danger signs Counselling on breast- feeding Observation of breast- feeding Weighed1 Mother’s age at birth <20 69.7 71.4 55.8 75.8 74.6 86.5 42.4 451 20-34 75.7 71.4 64.6 76.6 73.4 85.5 48.8 1,723 35-49 73.5 65.6 62.4 73.3 74.1 82.5 47.7 279 Birth order 1 76.3 78.3 63.9 81.8 80.5 91.4 51.9 658 2-3 76.9 74.1 65.5 76.7 73.5 88.1 49.0 1,096 4-5 73.1 62.2 60.8 73.5 70.0 80.8 44.5 507 6+ 56.7 47.9 48.4 60.2 61.2 60.6 31.5 192 Place of delivery Health facility 82.3 80.4 70.0 85.3 81.8 98.7 55.7 1,987 Elsewhere 40.5 29.5 31.9 36.9 39.3 28.2 12.3 467 Residence Urban 84.0 82.3 73.6 87.8 83.2 96.5 57.7 689 Rural 70.6 66.2 58.5 71.5 70.0 81.0 43.5 1,765 Province Manicaland 67.7 57.4 56.8 73.1 69.8 74.3 37.7 396 Mashonaland Central 59.7 60.4 48.6 61.7 64.4 83.6 39.2 246 Mashonaland East 75.8 71.5 50.4 69.8 72.6 83.6 38.6 244 Mashonaland West 56.0 46.0 39.5 51.8 53.6 75.8 24.8 298 Matabeleland North 83.6 85.0 79.1 89.6 90.6 94.5 63.7 117 Matabeleland South 85.5 93.0 86.5 92.0 89.9 95.2 73.4 99 Midlands 85.9 76.8 76.3 86.2 75.9 88.9 54.7 338 Masvingo 80.6 85.1 71.8 82.0 78.7 85.4 60.3 299 Harare 82.3 80.5 72.4 89.4 83.5 96.8 56.8 324 Bulawayo 82.9 87.9 74.5 85.8 85.7 96.9 58.7 92 Mother’s education No education * * * * * * * 32 Primary 64.7 59.6 54.7 66.8 63.5 74.4 37.4 787 Secondary 78.8 75.6 66.6 80.7 78.5 90.5 52.0 1,534 More than secondary 86.8 88.5 77.3 91.9 86.5 100.0 66.6 101 Wealth quintile Lowest 66.8 63.6 55.2 68.4 68.2 74.1 41.1 610 Second 71.4 64.2 57.3 69.4 68.6 80.5 41.4 504 Middle 70.3 67.2 60.8 75.1 73.7 85.0 45.9 441 Fourth 80.6 77.4 70.5 84.6 79.4 94.5 54.2 550 Highest 87.1 86.5 73.9 87.2 81.6 97.9 58.6 349 Total 74.4 70.7 62.7 76.1 73.7 85.3 47.5 2,454 Note: An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. 1 Captures newborns who were weighed "at birth". May exclude some newborns who were weighed during the 2 days after birth. 162 • Maternal Health Care Table 9.13 Problems in accessing health care Percentage of women age 15-49 who reported that they have serious problems in accessing health care for themselves when they are sick, by type of problem, according to background characteristics, Zimbabwe 2015 Problems in accessing health care Number of women Background characteristic Getting permission to go to the doctor Getting money for treatment Distance to health facility Not wanting to go alone At least one problem accessing health care Age 15-19 6.8 34.2 31.1 19.7 55.8 2,199 20-34 4.9 42.3 32.6 12.9 57.6 4,973 35-49 4.8 51.3 36.2 12.1 62.6 2,783 Number of living children 0 5.9 32.7 26.6 18.3 52.7 2,710 1-2 5.1 41.8 30.3 11.8 55.8 3,668 3-4 4.6 48.3 37.6 12.5 62.2 2,664 5+ 6.3 62.6 52.6 16.6 77.1 912 Marital status Never married 4.8 31.7 25.3 18.1 51.1 2,511 Married or living together 5.7 44.4 36.6 13.2 59.9 6,151 Divorced/separated/widowed 4.2 58.3 33.0 11.5 66.9 1,292 Employed last 12 months Not employed 5.8 45.4 38.3 16.4 62.8 4,864 Employed for cash 4.7 40.4 27.3 12.0 54.3 4,746 Employed not for cash 6.5 45.4 45.6 13.4 59.5 346 Residence Urban 3.7 32.6 10.1 10.6 41.9 3,829 Rural 6.3 49.5 47.8 16.5 69.1 6,126 Province Manicaland 6.5 56.0 44.2 14.3 69.6 1,266 Mashonaland Central 8.7 47.6 49.2 18.5 69.7 882 Mashonaland East 4.8 42.5 34.1 16.4 57.1 952 Mashonaland West 5.1 46.4 36.1 14.2 63.1 1,160 Matabeleland North 5.1 41.5 36.8 17.6 57.8 465 Matabeleland South 10.3 43.7 50.9 27.5 65.0 419 Midlands 2.2 32.6 32.9 5.6 51.4 1,263 Masvingo 5.6 49.8 41.9 16.2 68.4 1,187 Harare 4.1 35.7 12.2 11.4 44.9 1,783 Bulawayo 5.1 33.5 10.1 14.8 45.0 577 Education No education 9.4 68.2 59.6 15.0 77.8 126 Primary 8.7 55.7 50.3 18.8 74.5 2,571 Secondary 4.2 40.9 28.7 12.8 55.5 6,527 More than secondary 1.7 12.1 10.3 10.1 27.3 731 Wealth quintile Lowest 8.5 61.4 60.8 21.0 81.0 1,704 Second 7.6 52.5 53.0 18.4 74.8 1,693 Middle 4.7 47.9 40.1 13.1 64.5 1,748 Fourth 4.9 39.8 20.0 11.1 52.7 2,307 Highest 2.3 23.5 8.7 10.3 33.7 2,503 Total 5.3 43.0 33.3 14.2 58.6 9,955 Maternal Health Care • 163 Table 9.14 Knowledge and prevention of cervical cancer Percentage of women age 15-49 who have ever heard of cervical cancer, have had a cervical screening (Pap test) ever or in the last 12 months and the last 3 years, by background characteristics, Zimbabwe 2015 Have heard of cervical cancer Have ever been screened for cervical cancer Number of women Among women who have had a cervical exam Background characteristic Had cervical exam in the last 12 months Had cervical exam in the last 3 years Number of women Age 15-19 57.1 1.5 2,199 (82.9) (97.0) 33 20-24 77.0 4.8 1,697 84.8 98.8 81 25-29 83.6 13.9 1,657 71.6 94.4 231 30-34 88.2 19.0 1,619 60.1 89.7 308 35-39 89.2 19.3 1,236 68.5 94.0 238 40-44 88.2 22.7 965 61.2 84.4 219 45-49 85.9 24.1 582 56.6 81.5 140 Residence Urban 88.4 21.1 3,829 64.9 89.2 806 Rural 72.6 7.2 6,126 67.5 92.3 444 Province Manicaland 73.4 6.4 1,266 52.5 84.2 80 Mashonaland Central 79.8 9.4 882 66.2 91.3 83 Mashonaland East 82.0 11.9 952 71.9 93.0 114 Mashonaland West 82.9 10.4 1,160 65.5 93.3 121 Matabeleland North 65.4 8.1 465 79.2 93.1 38 Matabeleland South 61.5 8.2 419 59.7 84.9 35 Midlands 72.6 8.4 1,263 66.6 90.6 106 Masvingo 73.0 10.5 1,187 74.8 94.1 125 Harare 90.8 23.9 1,783 65.9 88.5 426 Bulawayo 85.0 21.2 577 56.6 91.0 122 Marital status Never married 64.3 2.4 2,511 70.9 98.4 60 Married 83.2 16.0 5,841 64.0 89.3 932 Living together 83.8 10.2 310 (71.8) (96.7) 31 Divorced/separated 83.9 16.3 855 69.5 91.0 139 Widowed 86.7 19.9 438 74.3 92.5 87 Education No education 59.2 8.9 126 * * 11 Primary 66.4 7.5 2,571 71.4 88.9 192 Secondary 81.7 12.4 6,527 68.2 91.1 812 More than secondary 97.7 32.0 731 54.6 88.4 234 Wealth quintile Lowest 65.1 5.3 1,726 54.6 90.0 91 Second 71.9 5.2 1,660 71.4 94.2 86 Middle 74.9 6.9 1,733 70.0 94.6 120 Fourth 84.2 16.7 2,269 71.7 90.6 379 Highest 89.7 22.4 2,567 62.0 88.7 575 Total 15-49 78.7 12.6 9,955 65.8 90.3 1,250 Notes: 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. Child Health • 165 CHILD HEALTH 10 Key Findings  Vaccination: Seventy-six percent of children age 12-23 months had received all basic vaccinations at the time of the survey, up from 65 percent in 2010-11.  Symptoms of acute respiratory infection (ARI): Four percent of children under age 5 experienced symptoms of an acute respiratory infection (ARI) in the 2 weeks preceding the survey. Half of these children (51 percent) were taken for advice or treatment to a health facility or provider.  Fever: Fourteen percent of children under age 5 had a fever within the 2 weeks preceding the survey. Forty-five percent of children with a fever were taken to a health facility or provider for advice or treatment.  Diarrhoea: Seventeen percent of children under age 5 had diarrhoea in the 2 weeks preceding the survey. Thirty-nine percent of children with diarrhoea were taken to a health facility or provider. Among children with diarrhoea, 78 percent were treated with oral rehydration therapy (ORT), oral rehydration salts (ORS), recommended home fluids (RHF), or increased fluids. One in five children with diarrhoea (20 percent) did not receive any type of treatment. his chapter presents findings about child health and survival, including characteristics of the neonate (birth weight and size), the vaccination status of young children, and healthcare treatment practices—particularly contact with health services—among children suffering from three childhood illnesses: acute respiratory infection (ARI), fever, and diarrhoea. Because appropriate sanitary practices can help prevent and reduce the severity of diarrhoeal disease, information is also provided on how children’s faecal matter is disposed. Findings in this chapter are expected to assist policymakers and program managers as they formulate appropriate strategies and interventions to improve children’s health in Zimbabwe. 10.1 BIRTH WEIGHT Low birth weight Percentage of births with a reported birth weight <2.5 kilograms regardless of gestational age Sample: Live births in the 5 years before the survey that have a reported birth weight, either from a written record or mother’s report T 166 • Child Health Birth weight is an important indicator when assessing a child’s health in terms of early exposure to childhood morbidity and mortality. Children who weigh less than 2.5 kilograms or are reported to be very small or smaller than average, are considered to have a higher-than-average risk of early childhood death. In the 2015 ZDHS, for births in the 5 years preceding the survey, birth weight was recorded in the Woman’s Questionnaire based on either a written record or the mother’s report. The mother’s estimate of the infant’s size at birth was also obtained because birth weight may be unknown for many infants. Although the mother’s estimate of size is subjective, it can be a useful proxy for the child’s weight. Birth weight is reported for 82 percent of the live births that occurred in the five years preceding the survey; 10 percent of these infants had low birth weights (less than 2.5 kg) (Table 10.1). Reported birth weights were the least available for sixth- or higher-order births (59 percent). By residence, birth weights were less available for births in rural areas (76 percent) than in urban areas (96 percent). Across provinces, births weights were less available in Mashonaland West (71 percent) and in Manicaland (70 percent), compared with other provinces. Birth weights were also less available for children born to women with no education (60 percent) and births in the lowest wealth quintile (68 percent). Therefore, the pattern of birth weights by background characteristics may be biased due to underrepresentation, and should be interpreted with caution. Table 10.1 also includes information on the mother’s estimate of the infant’s size at birth. Although the mother’s estimate of size is subjective, it can be a useful proxy for the child’s weight. Four percent of births are reported as very small, and 11 percent as smaller than average. Patterns by background characteristics  Births to older mothers age 35-49 are slightly more likely to be less than 2.5 kg than births to younger mothers (Table 10.1).  First-order births (11 percent) are slightly more likely than subsequent births to be less than 2.5 kg.  Among the provinces, Masvingo has the lowest proportion of low birth weight infants (7 percent) and Bulawayo and Mashonaland Central have the highest proportions (11 percent each). 10.2 VACCINATION OF CHILDREN All basic vaccinations coverage Percentage of children age 12-23 months who received specific vaccines at any time before the survey (according to a vaccination card or the mother’s report). To have received all basic vaccinations, a child must receive at least:  one dose of BCG vaccine, which protects against tuberculosis  three doses of DPT, which protects against diphtheria, pertussis (whooping cough), and tetanus; or three doses of pentavalent (DPT- HepB-Hib) vaccine, which protects against DPT, hepatitis B, and Haemophilus influenzae type B  three doses of polio vaccine  one dose of measles vaccine Sample: Living children age 12-23 months According to WHO, a child is considered to have received all basic vaccinations if he or she has received a BCG vaccination against tuberculosis; three doses of DPT vaccine to prevent diphtheria, pertussis, and tetanus (or three doses of pentavalent, which includes DPT and vaccines against both hepatitis B and Haemophilus influenza type B); at least three doses of polio vaccine; and one dose of measles vaccine. These vaccinations should be received during the first year of life. The 2015 ZDHS collected information Child Health • 167 on the coverage of these vaccinations among all children born in the 3 years preceding the survey. The 2015 ZDHS also collected information on the coverage of three doses of pneumococcal vaccine (introduced in July 2012) and two doses of the rotavirus vaccine (introduced in August 2014) because these vaccines are included in the routine immunisations for children in Zimbabwe. Seventy-six percent of children age 12-23 months received all the basic vaccinations at any time before the survey: 90 percent received the BCG vaccine, 83 percent received three doses of DPT or pentavalent vaccine, 82 percent received three doses of polio vaccine, and 82 percent received one dose of the measles vaccine (Table 10.2 and Figure 10.1). Eighty-two percent of children completed three doses of the pneumococcal vaccine and 50 percent completed two doses of the rotavirus vaccine. Ten percent of children age 12-23 months did not receive any vaccinations. The coverage of the first dose of pentavalent and polio vaccines is very high (90 percent each). However, 83 percent of children received the third dose of pentavalent, while 82 percent received the third dose of the polio vaccine. This represents a dropout rate between the first and third dose of 7 percentage points for the pentavalent vaccine and 8 percentage points for the polio vaccine. Figure 10.1 Childhood vaccinations Table 10.2 also presents vaccination coverage for each vaccination which was given by the time the child reached age 12 months, which provides information on the percentage of children receiving vaccines on time. Sixty-nine percent of children age 12-23 months received all the basic vaccinations by age 12 months. Trends: Figure 10.2 presents vaccination coverage trends for children age 12-23 months between the 1988 and 2015 ZDHS surveys. Although coverage for all basic vaccinations among children age 12-23 months in Zimbabwe decreased steadily between 1994 and 2005-06 (from 80 to 53 percent), coverage increased to 65 percent in 2010-11 and 76 percent in 2015. Accordingly, the percentage of children with no vaccinations has followed the opposite trend. Patterns by background characteristics  Female children are somewhat less likely to have received all basic vaccinations than male children (75 and 77 percent, respectively) (Table 10.3). 90 90 88 83 90 88 82 82 76 88 87 82 55 50 10 BCG 1 2 3 1 2 3 All basic 1 2 3 1 2 None Percentage of children age 12-23 months vaccinated at any time before the survey Measles PolioDPT/ Pentavalent Pneumococcal Rotavirus Figure 10.2 Trends in childhood vaccinations 67 80 64 53 65 76 23 4 12 21 12 10 1988 1994 1999 2005-06 2010-11 2015 Percentage of children age 12-23 months who received all basic vaccinations at any time before the survey No vaccinations All basic vaccinations 168 • Child Health  Birth order is generally negatively associated with vaccination coverage. Seventy- eight percent of first-order births received all basic vaccinations compared with only 60 percent of sixth- or higher-order births. Higher- order births were also more likely to not have received any vaccinations (25 percent) than other births.  Coverage of all basic vaccinations ranges from a high of 91 percent in Matabeleland North to a low of 62 percent in Masvingo (Figure 10.3).  Mother’s education level is positively associated with children’s coverage with all basic vaccinations (Table 10.3). Vaccination card ownership and availability Vaccination cards are a critical tool in ensuring that a child receives all recommended vaccinations on schedule. Ninety-three percent of children age 12-23 months have had a vaccination card at some point in time; 78 percent of children had vaccination cards that were observed by survey interviewers (Table 10.4). 10.3 SYMPTOMS OF ACUTE RESPIRATORY INFECTION Treatment of ARI symptoms Children with ARI symptoms for whom advice or treatment was sought from a health facility or provider. The symptoms of ARI include cough accompanied by (1) short, rapid breathing that is chest-related, and/or (2) difficult breathing that is chest-related. Sample: Children under age 5 with symptoms of ARI in the 2 weeks before the survey Mothers reported that 4 percent of children under age 5 experienced ARI symptoms within the 2-week period before the interview (Table 10.5). About half of children with ARI symptoms (51 percent) were taken to a health facility or health provider for advice or treatment. Forty percent of children with symptoms received antibiotics (data not shown). Trends: While percentage of children with ARI symptoms who were taken for advice or treatment at a health facility or health provider has remained constant between the 2010-11 and 2015 ZDHS surveys, the percentage who were given antibiotics has increased from 31 percent to 40 percent. 10.4 FEVER Fever is a symptom of numerous illnesses including pneumonia, the common cold, influenza, and malaria. Mothers reported that 14 percent of children under age 5 were ill with fever in the 2 weeks before the Figure 10.3 Vaccination coverage by province Percentage of children age 12-23 months who received all basic vaccinations at any time before the survey Child Health • 169 survey. The proportion of children with fever peaks at 20 percent among children age 6-11 months (Table 10.6). Treatment of fever Children with fever for whom advice or treatment was sought from a health facility or provider Sample: Children under age 5 with fever in the 2 weeks before the survey Forty-five percent of children with fever were taken to a health facility or provider for advice or treatment. One percent received antimalarial drugs and 34 percent received an antibiotic. Trends: Health-seeking behaviour for fever has increased slightly from 37 percent in 2010-11 to 42 percent in 2015. 10.5 DIARRHOEAL DISEASE 10.5.1 Prevalence of Diarrhoea Mothers report that 17 percent of children under age 5 had a diarrhoeal episode in the 2 weeks preceding the survey (Table 10.7). The prevalence of diarrhoea increases from 10 percent among children less than age 6 months to a peak of 31 percent among those age 6-11 months (Figure 10.4). Prevalence remains high at age 12-23 months (30 percent), about the time when children start to walk and are at increased risk of contamination from the environment. The introduction of other liquids and foods at the time of weaning can also facilitate the spread of disease- causing microbes. Patterns by background characteristics  Diarrhoea is slightly more prevalent among children whose households do not have an improved source of drinking water (18 percent) compared with children from households that do (16 percent) (Table 10.7).  Similarly, the prevalence of diarrhoea is higher among children whose households do not have an improved toilet facility (17 percent) or who share a facility with other households (20 percent), compared with households that have an improved, unshared toilet facility (14 percent).  The prevalence of diarrhoea varies by province; it is highest in Mashonaland West (23 percent) and lowest in Matabeleland South (9 percent). 10.5.2 Treatment of Diarrhoea Thirty-nine percent of the children suffering from diarrhoea were taken for advice or treatment was sought from a health facility or provider for (Table 10.8). Figure 10.4 Diarrhoea prevalence by age 10 31 30 17 10 7 17 <6 6-11 12-23 24-35 36-47 48-59 Total Percentage of children under age 5 who had diarrhoea in the 2 weeks preceding the survey Age in months 170 • Child Health Oral rehydration therapy (ORT) Children with diarrhoea are given a fluid made from a special packet of oral rehydration salts (ORS) or government-recommended homemade fluids (RHF). Sample: Children under age 5 with diarrhoea in the 2 weeks before the survey Oral rehydration therapy (ORT) is a simple and effective way to reduce dehydration caused by diarrhoea. The majority of children with diarrhoea (78 percent) receive some form of ORT, 59 percent were given increased fluids, 48 percent were given RHF, and 41 percent were given fluid from ORS sachets (Figure 10.5). Twenty percent of children were given zinc supplements, and 7 percent of children were given antibiotics (Table 10.8). One in five children with diarrhoea did not receive any treatment. Trends: Use of ORS sachets has almost doubled from 21 percent in 2010-11 to 41 percent in 2015. Treatment with zinc supplements has also increased from less than 1 percent and 2010-11 to 20 percent in 2015, while use of RHF has decreased from 55 percent to 48 percent over the same period. The percentage of children who received no treatment for diarrhoea has remained at 20 percent since 2010-11. Patterns by background characteristics  Percentage of children with diarrhoea who were taken to a health facility or provider for treatment or advice is highest in Matabeleland North (62 percent) and lowest in Midlands (27 percent).  Children who have diarrhoea are more likely to be taken to a health facility or provider if they are from households in the highest quintile (35 percent), compared with children in other wealth quintiles. 10.5.3 Feeding Practices Appropriate feeding practices Children with diarrhoea are given more liquids than usual, and as much food or more than usual. Sample: Children under age 5 with diarrhoea in the 2 weeks before the survey When a child has diarrhoea, mothers are encouraged to continue feeding their child the same amount of food as they would if the child did not have diarrhoea, and also to increase the child’s fluid intake. These practices help to reduce dehydration and minimise the adverse consequences of diarrhoea on the child’s nutritional status. Figure 10.5 Treatment of diarrhoea 20 7 59 78 48 41 39 No treatment Antibiotics ORS or increased fluids ORT (ORS, RHF, or increased fluids) Recommended homemade fluids (RHF) Fluid from ORS packet Taken to a health provider Percentage of children under age 5 with diarrhoea in the 2 weeks before the survey Child Health • 171 As recommended, 34 percent of children with diarrhoea in the 2 weeks preceding the survey were given more liquids than usual, and another 34 percent were given the same amount of liquids as usual (Figure 10.6). It is a concern that 32 percent of the children were given less than the usual amount of liquids or no liquids at all during the diarrhoea episode. With regard to food intake during a diarrhoea episode, 35 percent of children were given the same amount of food or more than usual, as recommended. Forty-eight percent of children are given less food than usual, while 11 percent received no food during diarrhoea. For additional information on feeding practices during diarrhoea, see Table 10.9. 10.5.4 Knowledge of ORS Packets Women were asked whether they had heard of a special product called an ORS sachet that can be used to treat diarrhoea. Among women with a live birth in the last five years, 72 percent had heard of ORS sachets (Table 10.10). Knowledge of ORS tends to increase with women’s age. This knowledge is higher among urban women (79 percent), those living in Mashonaland West (84 percent), women with more than a secondary education (90 percent), and women in the highest wealth quintile (81 percent). Knowledge of ORS has increased substantially from 49 percent in 2010-11 to 72 percent in 2015. Treatment of Childhood Illness In summary, during the 2 weeks before the survey, diarrhoea was the most common illness reported among children under age 5. However, children with ARI symptoms were more likely to be taken for advice or treatment (51 percent) (Figure 10.7). Professional advice is sought less often for children with diarrhoea (39 percent) or fever (45 percent). 10.6 DISPOSAL OF CHILDREN’S STOOLS Safe disposal of children’s stools The child’s last stools were put in or rinsed into a toilet or latrine, buried, or the child used a toilet or latrine. Sample: Youngest child under age 2 living with the mother The proper disposal of children’s faeces is important in preventing the spread of disease. Seventy-five percent of children had their last stool disposed of safely (Table 10.11). Figure 10.6 Feeding practices during diarrhoea Figure 10.7 Prevalence and treatment of childhood illnesses 7 34 29 34 48 30 11 2 5Food given Liquids given Percentage of children under age 5 with diarrhoea in the 2 weeks before the survey More Same Less None Never gave (compared to usual) (compared to usual) 4 14 17 51 45 39 ARI Fever Diarrhoea ARI Fever Diarrhoea Percentage of children under age 5 with symptoms in the 2 weeks before the survey Among those with illness, percentage from whom advice or treatment was sought from a health facility or provider 172 • Child Health Patterns by background characteristics  Eighty-two percent of children who had access to an improved, non-shared toilet facility had their last stool disposed of safely compared with 64 percent of children who did not.  No major differences are observed between children in rural and urban areas.  There are differences in the disposal of children’s stools by province. The proportion of children whose last stool was safely disposed of ranges from a low of 60 percent in Bulawayo to 81 percent in Manicaland. LIST OF TABLES For detailed information on low birth weight, vaccinations, childhood illness, and disposal of children’s stools, see the following tables:  Table 10.1 Child’s size and weight at birth  Table 10.2 Vaccinations by source of information  Table 10.3 Vaccinations by background characteristics  Table 10.4 Possession and observation of vaccination cards, according to background characteristics  Table 10.5 Prevalence and treatment of symptoms of ARI  Table 10.6 Prevalence and treatment of fever  Table 10.7 Prevalence of diarrhoea  Table 10.8 Diarrhoea treatment  Table 10.9 Feeding practices during diarrhoea  Table 10.10 Knowledge of ORS packets or pre-packaged liquids  Table 10.11 Disposal of children’s stools Child Health • 173 Table 10.1 Child’s size and weight at birth Percent distribution of live births in the 5 years preceding the survey by mother’s estimate of baby’s size at birth, percentage of live births in the 5 years preceding the survey that have a reported birth weight, and among live births in the 5 years preceding the survey with a reported birth weight, percentage less than 2.5 kg, according to background characteristics, Zimbabwe 2015 Percent distribution of births by size of child at birth Percentage of births that have a reported birth weight1 Number of births Births with a reported birth weight1 Background characteristic Very small Smaller than average Average or larger Don’t know/ missing Total Percentage less than 2.5 kg Number of births Mother’s age at birth <20 5.0 12.3 82.2 0.5 100.0 80.7 1,074 9.3 867 20-34 3.5 10.2 85.9 0.3 100.0 83.0 4,572 9.4 3,796 35-49 5.9 11.1 82.1 0.8 100.0 79.2 772 10.1 611 Birth order 1 4.6 13.3 81.8 0.2 100.0 87.8 1,671 10.8 1,467 2-3 3.5 9.9 86.2 0.4 100.0 84.8 2,928 9.1 2,484 4-5 4.9 9.5 85.1 0.5 100.0 77.6 1,353 9.2 1,050 6+ 3.6 9.8 85.9 0.7 100.0 58.6 466 7.1 273 Mother’s smoking status Smokes cigarettes/ tobacco * * * * 100.0 * 11 * 10 Does not smoke 4.0 10.7 84.8 0.4 100.0 82.2 6,407 9.4 5,264 Residence Urban 4.0 9.8 85.8 0.3 100.0 95.9 2,027 10.0 1,944 Rural 4.1 11.1 84.4 0.5 100.0 75.8 4,392 9.1 3,330 Province Manicaland 2.7 12.9 84.1 0.3 100.0 70.0 966 9.7 676 Mashonaland Central 8.5 7.2 84.2 0.2 100.0 77.0 629 10.6 484 Mashonaland East 3.0 10.5 86.2 0.3 100.0 80.2 609 9.9 488 Mashonaland West 4.6 12.0 83.4 0.0 100.0 71.0 847 9.7 601 Matabeleland North 5.6 11.2 83.0 0.3 100.0 88.9 288 9.3 256 Matabeleland South 5.5 7.2 86.2 1.2 100.0 94.1 238 8.8 224 Midlands 4.2 11.8 84.0 0.0 100.0 84.3 866 9.5 730 Masvingo 2.3 11.2 84.6 1.8 100.0 84.9 764 7.0 649 Harare 3.4 8.2 88.1 0.4 100.0 96.6 949 9.9 917 Bulawayo 3.7 13.9 82.4 0.0 100.0 94.9 262 10.5 249 Mother’s education No education 14.8 6.2 77.4 1.6 100.0 59.9 76 (14.5) 45 Primary 5.1 10.7 83.7 0.5 100.0 71.3 2,038 10.1 1,454 Secondary 3.4 10.7 85.5 0.4 100.0 86.7 3,962 9.2 3,433 More than secondary 3.5 11.8 84.7 0.0 100.0 99.8 342 8.9 342 Wealth quintile Lowest 4.8 11.6 82.8 0.8 100.0 68.2 1,477 10.5 1,007 Second 4.7 10.2 84.9 0.3 100.0 75.1 1,252 8.6 940 Middle 3.3 11.1 85.1 0.4 100.0 80.5 1,098 8.0 884 Fourth 3.9 10.0 85.8 0.3 100.0 92.2 1,504 9.8 1,387 Highest 3.4 10.7 85.8 0.2 100.0 97.1 1,087 10.0 1,056 Total 4.1 10.7 84.8 0.4 100.0 82.2 6,418 9.5 5,274 Note: An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. 1 Based on either a written record or the mother’s recall 174 • Child Health Table 10.2 Vaccinations by source of information Percentage of children age 12-23 months who received specific vaccines at any time before the survey, by source of information (vaccination card or mother's report), and percentage who received vaccines by appropriate age, Zimbabwe 2015 Vaccinated at any time before the survey according to: Vaccinated by appropriate age2,3 Source of information Vaccination card1 Mother's report Either source BCG 77.7 12.2 89.9 89.4 DPT-HepB-Hib 1 77.7 11.8 89.5 89.2 2 76.9 11.2 88.1 87.9 3 74.6 8.9 83.4 82.0 Polio 1 77.6 11.9 89.5 89.2 2 76.1 11.7 87.9 87.6 3 73.3 9.0 82.3 81.0 Pneumococcal4 1 77.0 10.9 88.0 87.7 2 76.2 10.7 86.9 86.7 3 73.5 8.7 82.2 80.9 Rotavirus5 1 46.5 8.9 55.4 55.0 2 41.7 7.8 49.5 48.6 Measles 72.1 9.9 81.9 76.2 All basic vaccinations6 69.1 6.9 76.0 69.0 All age appropriate vaccinations7 37.6 4.5 42.1 38.8 No vaccinations 0.0 9.8 9.8 na Number of children 948 268 1,216 1,216 na = Not applicable BCG = Bacille Calmette-Guérin DPT = Diphtheria-pertussis-tetanus HepB = Hepatitis B Hib = Haemophilus influenzae type b 1 Vaccination card, booklet or other home-based record 2 Received by age 12 months 3 For children whose vaccination information is based on the mother’s report, date of vaccination is not collected. The proportions of vaccinations given during the first and second years of life are assumed to be the same as for children with a written record of vaccination. 4 In Zimbabwe, the pneumococcal vaccine was introduced as part of the routine immunisations in July 2012. 5 In Zimbabwe, the rotavirus vaccine was introduced as part of the routine immunisations in August 2014. 6 BCG, three doses of DPT-HepB-Hib (pentavalent), three doses of oral polio vaccine, and one dose of measles vaccine 7 BCG, three doses of DPT-HepB-Hib (pentavalent), three doses of oral polio vaccine, three doses of pneumococcal vaccine, two doses of rotavirus vaccine, and one dose of measles vaccine C hi ld H ea lth • 1 75 Ta bl e 10 .3 V ac ci na tio ns b y ba ck gr ou nd c ha ra ct er is tic s P er ce nt ag e of c hi ld re n ag e 12 -2 3 m on th s w ho r ec ei ve d sp ec ifi c va cc in es a t an y tim e be fo re t he s ur ve y (a cc or di ng t o a va cc in at io n ca rd o r th e m ot he r’s r ep or t), p er ce nt ag e w ith a ll ba si c va cc in at io ns , a nd p er ce nt ag e w ith a ll ag e ap pr op ria te v ac ci na tio ns , a cc or di ng to b ac kg ro un d ch ar ac te ris tic s, Z im ba bw e 20 15 B ac kg ro un d ch ar ac te ris tic B C G D P T- H ep B -H ib (P en ta va le nt ) P ol io P ne um oc oc ca l R ot av iru s M ea sl es A ll ba si c va cc in a- tio ns 1 A ll ag e ap pr op ri- at e va cc in a- tio ns 2 N o va cc in a- tio ns N um be r of c hi ld re n 1 2 3 1 2 3 1 2 3 1 2 S ex M al e 88 .4 88 .3 86 .8 83 .0 88 .2 86 .5 81 .5 86 .3 84 .9 81 .2 55 .6 49 .9 80 .4 74 .8 42 .4 11 .4 61 5 Fe m al e 91 .4 90 .7 89 .4 83 .9 90 .9 89 .2 83 .0 89 .7 89 .0 83 .1 55 .1 49 .0 83 .5 77 .3 41 .9 8. 3 60 1 B ir th o rd er 1 91 .8 91 .6 90 .0 86 .2 91 .4 90 .3 84 .3 89 .5 88 .5 85 .2 61 .8 55 .7 84 .7 77 .7 47 .2 7. 7 28 8 2- 3 93 .3 93 .0 91 .9 87 .9 93 .2 91 .4 86 .6 91 .0 90 .3 86 .5 54 .9 48 .9 86 .5 81 .1 42 .2 6. 4 56 9 4- 5 85 .8 85 .2 83 .6 76 .5 85 .2 83 .1 76 .6 84 .8 83 .1 76 .2 55 .1 48 .9 74 .8 69 .1 42 .1 14 .2 26 2 6+ 75 .2 73 .7 72 .3 68 .0 73 .7 72 .3 66 .2 73 .7 72 .3 63 .5 40 .1 35 .7 66 .5 60 .3 26 .6 24 .8 97 R es id en ce U rb an 93 .9 94 .0 92 .3 87 .6 94 .0 91 .9 87 .7 92 .1 90 .6 85 .4 54 .5 49 .5 87 .3 80 .5 43 .5 5. 7 35 5 R ur al 88 .2 87 .6 86 .3 81 .7 87 .7 86 .2 80 .0 86 .2 85 .4 80 .8 55 .7 49 .5 79 .7 74 .2 41 .6 11 .6 86 1 P ro vi nc e M an ic al an d 84 .4 84 .0 83 .4 75 .5 84 .8 84 .2 75 .0 83 .6 82 .9 76 .7 54 .7 52 .2 78 .5 71 .7 43 .6 14 .4 18 4 M as ho na la nd C en tra l 94 .9 93 .8 92 .7 89 .5 93 .8 92 .0 85 .2 91 .6 91 .6 86 .1 55 .4 48 .4 86 .9 80 .3 39 .5 5. 1 12 9 M as ho na la nd E as t 92 .1 92 .4 91 .3 89 .4 92 .4 90 .9 87 .7 92 .0 92 .0 90 .6 62 .9 62 .0 88 .9 83 .0 54 .0 7. 6 11 9 M as ho na la nd W es t 86 .2 85 .4 83 .9 81 .5 85 .4 83 .9 81 .5 85 .4 83 .9 81 .5 55 .5 48 .8 81 .5 77 .6 44 .7 13 .8 14 7 M at ab el el an d N or th 10 0. 0 10 0. 0 97 .7 96 .4 99 .0 96 .5 94 .0 96 .2 95 .2 94 .0 66 .2 59 .1 94 .4 90 .7 54 .2 0. 0 58 M at ab el el an d S ou th 98 .4 98 .4 95 .5 91 .9 98 .4 93 .1 89 .1 94 .3 90 .5 85 .0 55 .9 49 .2 91 .5 85 .9 44 .1 1. 6 45 M id la nd s 89 .6 89 .0 85 .4 79 .6 89 .0 86 .2 78 .1 87 .9 84 .4 79 .6 52 .4 38 .2 72 .6 67 .2 28 .3 10 .0 16 4 M as vi ng o 79 .3 79 .3 78 .9 72 .7 79 .3 78 .4 72 .0 76 .3 76 .3 70 .4 51 .6 48 .2 67 .9 61 .5 39 .7 20 .7 15 9 H ar ar e 97 .5 97 .2 97 .0 90 .8 97 .2 96 .4 92 .2 96 .2 96 .2 88 .7 54 .8 49 .8 91 .7 85 .4 44 .2 2. 5 16 5 B ul aw ay o 92 .8 91 .3 88 .5 88 .5 91 .3 87 .0 83 .9 87 .0 84 .4 81 .5 49 .7 42 .7 87 .3 78 .4 38 .3 7. 2 44 M ot he r’ s ed uc at io n N o ed uc at io n * * * * * * * * * * * * * * * * 12 P rim ar y 85 .4 84 .3 82 .1 77 .6 84 .5 82 .5 76 .1 83 .7 81 .7 77 .1 52 .5 45 .0 74 .1 68 .8 36 .7 14 .6 38 9 S ec on da ry 91 .9 91 .7 90 .8 85 .7 91 .7 90 .1 84 .5 89 .6 89 .1 83 .8 57 .5 52 .1 84 .9 78 .6 44 .7 7. 8 76 4 M or e th an s ec on da ry 94 .1 95 .0 92 .5 92 .5 95 .0 93 .9 93 .9 95 .0 93 .9 93 .2 50 .7 48 .3 94 .9 90 .3 47 .4 3. 7 50 W ea lth q ui nt ile Lo w es t 88 .0 86 .7 84 .5 79 .4 86 .5 84 .9 79 .1 85 .7 84 .5 80 .4 50 .7 45 .7 76 .5 70 .7 38 .6 12 .0 30 5 S ec on d 84 .2 83 .0 82 .3 75 .9 83 .6 81 .3 72 .7 81 .4 80 .5 74 .0 56 .2 48 .8 76 .2 69 .1 40 .1 15 .8 24 2 M id dl e 92 .4 92 .9 92 .3 91 .5 92 .9 92 .6 88 .8 91 .9 91 .3 88 .8 61 .7 56 .0 87 .7 85 .0 48 .7 6. 8 21 2 Fo ur th 93 .8 93 .7 91 .6 86 .0 93 .7 91 .6 86 .6 92 .5 91 .0 84 .7 53 .8 47 .9 84 .5 78 .3 40 .2 6. 0 27 5 H ig he st 91 .9 92 .1 91 .4 86 .9 92 .1 90 .3 86 .0 88 .8 88 .2 84 .3 57 .2 51 .4 88 .3 80 .4 46 .2 7. 5 18 1 To ta l 89 .9 89 .5 88 .1 83 .4 89 .5 87 .9 82 .3 88 .0 86 .9 82 .2 55 .4 49 .5 81 .9 76 .0 42 .1 9. 8 1, 21 6 N ot es : C hi ld re n ar e co ns id er ed to h av e re ce iv ed th e va cc in e if it w as e ith er w rit te n on th e ch ild ’s v ac ci na tio n ca rd o r re po rte d by th e m ot he r. Fo r ch ild re n w ho se v ac ci na tio n in fo rm at io n is ba se d on th e m ot he r’s r ep or t, da te o f v ac ci na tio n is n ot c ol le ct ed . T he p ro po rti on s of v ac ci na tio ns g iv en d ur in g th e fir st a nd s ec on d ye ar s of li fe a re a ss um ed to b e th e sa m e as fo r ch ild re n w ith a w rit te n re co rd o f v ac ci na tio n. A n as te ris k in di ca te s th at a fi gu re is b as ed o n fe w er th an 2 5 un w ei gh te d ca se s an d ha s be en s up pr es se d. 1 B C G , t hr ee d os es o f D P T- H ep B -H ib (p en ta va le nt ), th re e do se s of o ra l p ol io v ac ci ne , a nd o ne d os e of m ea sl es v ac ci ne 2 B C G , t hr ee d os es o f D P T- H ep B -H ib (p en ta va le nt ), th re e do se s of o ra l p ol io v ac ci ne , t hr ee d os es o f p ne um oc oc ca l v ac ci ne , t w o do se s of ro ta vi ru s va cc in e, a nd o ne d os e of m ea sl es v ac ci ne 176 • Child Health Table 10.4 Possession and observation of vaccination cards, according to background characteristics Percentage of children age 12-23 months who ever had a vaccination card, and percentage with a vaccination card seen, according to background characteristics, Zimbabwe 2015 Background characteristic Percentage who ever had a vaccination card1 Percentage with a vaccination card seen1 Number of children Sex Male 92.3 75.8 615 Female 92.9 80.1 600 Birth order 1 96.1 75.8 307 2-3 95.4 82.4 556 4-5 87.9 75.8 257 6+ 77.6 64.6 95 Residence Urban 98.1 76.8 355 Rural 90.3 78.4 861 Province Manicaland 86.0 74.5 184 Mashonaland Central 93.2 82.0 129 Mashonaland East 92.9 82.4 119 Mashonaland West 92.7 77.9 147 Matabeleland North 99.6 85.5 58 Matabeleland South 98.4 81.4 45 Midlands 95.0 76.9 164 Masvingo 86.2 74.9 159 Harare 99.0 78.1 165 Bulawayo 92.3 69.0 44 Mother’s education No education * * 12 Primary 86.9 75.8 389 Secondary 94.9 79.0 764 More than secondary 100.0 74.8 50 Wealth quintile Lowest 87.1 78.7 305 Second 88.7 73.7 242 Middle 95.1 84.9 212 Fourth 98.1 78.4 275 Highest 95.9 73.4 181 Total 92.6 77.9 1,216 Note: An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. 1 Vaccination card, booklet or other home-based record Child Health • 177 Table 10.5 Prevalence and treatment of symptoms of ARI Among children under age 5, the percentage who had symptoms of acute respiratory infection (ARI) in the 2 weeks preceding the survey; and among children with symptoms of ARI, the percentage for whom advice or treatment was sought from a health facility or provider, according to background characteristics, Zimbabwe 2015 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 sought from a health facility or provider2 Number of children Age in months <6 4.3 624 * 27 6-11 3.7 572 * 21 12-23 4.4 1,216 (56.0) 53 24-35 4.6 1,191 (46.0) 54 36-47 3.6 1,223 (46.9) 43 48-59 2.5 1,230 (62.1) 31 Sex Male 4.3 2,950 47.3 126 Female 3.4 3,105 55.3 104 Mother’s smoking status Smokes cigarettes/ tobacco * 10 * 3 Does not smoke 3.8 6,045 50.8 227 Cooking fuel Electricity or gas 2.9 1,545 (75.3) 44 Kerosene 1.1 165 * 2 Coal/lignite * 4 * 0 Charcoal * 13 * 0 Wood/straw3 4.2 4,322 44.7 184 Animal dung * 4 * 0 Other fuel * 0 * 0 No food cooked in household * 2 * 0 Residence Urban 2.8 1,937 69.1 55 Rural 4.2 4,118 45.2 175 Province Manicaland 3.9 893 (39.7) 34 Mashonaland Central 1.1 590 * 6 Mashonaland East 4.4 574 * 25 Mashonaland West 4.5 783 (48.9) 35 Matabeleland North 2.4 275 * 6 Matabeleland South 2.8 230 * 7 Midlands 5.9 821 (38.2) 48 Masvingo 5.1 731 (57.6) 37 Harare 2.7 910 * 25 Bulawayo 2.0 249 * 5 Mother’s education No education 11.7 70 * 8 Primary 3.9 1,884 34.1 73 Secondary 3.8 3,767 57.1 144 More than secondary 1.2 335 * 4 Wealth quintile Lowest 4.0 1,381 (43.2) 55 Second 5.2 1,179 (43.0) 61 Middle 3.7 1,016 (53.6) 38 Fourth 2.9 1,428 (54.7) 41 Highest 3.3 1,052 (70.0) 34 Total 3.8 6,055 50.9 230 Notes: 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 (cough accompanied by short, rapid breathing which was chest-related and/or by difficult breathing which was chest-related) is considered a proxy for pneumonia 2 Excludes pharmacy, shop, and traditional practitioner 3 Includes grass, shrubs, and crop residues 178 • Child Health Table 10.6 Prevalence and treatment of fever Among children under age 5, the percentage who had a fever in the 2 weeks preceding the survey; and among children with fever, the percentage for whom advice or treatment was sought from a health facility or provider, the percentage who took antimalarial drugs, and the percentage who received antibiotics as treatment, according to background characteristics, Zimbabwe 2015 Among children under age 5: Percentage for whom advice or treatment was sought from a health facility or provider1 Among children under age 5 with fever: Background characteristic Percentage with fever Number of children Percentage who took antimalarial drugs Percentage who took antibiotic drugs Number of children Age in months <6 11.1 624 41.6 0.0 28.8 69 6-11 20.0 572 46.3 1.2 32.8 114 12-23 16.7 1,216 46.7 1.1 36.5 203 24-35 15.4 1,193 46.4 1.7 35.5 184 36-47 11.1 1,223 46.7 0.7 37.5 136 48-59 10.5 1,228 39.6 0.4 28.8 129 Sex Male 13.3 2,950 40.5 1.6 31.5 391 Female 14.3 3,105 49.1 0.4 36.4 444 Residence Urban 14.1 1,937 55.8 2.0 42.1 273 Rural 13.7 4,118 39.8 0.4 30.3 563 Province Manicaland 11.2 893 35.1 3.0 27.0 100 Mashonaland Central 8.4 590 64.2 1.0 37.3 50 Mashonaland East 15.9 574 34.8 1.1 29.5 92 Mashonaland West 23.9 783 40.3 0.0 36.2 188 Matabeleland North 15.4 275 56.5 0.0 36.4 42 Matabeleland South 13.3 230 55.5 1.9 41.2 31 Midlands 9.6 821 52.7 0.0 32.1 79 Masvingo 12.4 731 33.3 0.0 24.9 90 Harare 15.0 910 52.2 1.4 39.8 136 Bulawayo 11.6 249 64.4 4.0 51.2 29 Mother’s education No education 19.5 70 * * * 14 Primary 13.5 1,884 39.3 0.3 23.6 254 Secondary 13.9 3,767 46.6 1.3 37.5 525 More than secondary 12.7 335 (64.3) (0.8) (63.1) 42 Wealth quintile Lowest 14.3 1,381 41.9 0.3 29.4 197 Second 14.2 1,179 34.1 0.0 24.1 167 Middle 12.3 1,016 43.4 1.5 29.6 125 Fourth 13.9 1,428 47.0 0.8 33.0 198 Highest 14.1 1,052 60.5 2.8 57.0 149 Total 13.8 6,055 45.1 1.0 34.1 835 Notes: 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 Excludes pharmacy, shop, market, and traditional practitioner Child Health • 179 Table 10.7 Prevalence of diarrhoea Percentage of children under age 5 who had diarrhoea in the 2 weeks preceding the survey according to background characteristics, Zimbabwe 2015 Background characteristic Percentage with diarrhoea Number of children Age in months <6 9.7 624 6-11 31.0 572 12-23 30.4 1,216 24-35 17.2 1,193 36-47 9.6 1,223 48-59 6.8 1,228 Sex Male 18.2 2,950 Female 15.4 3,105 Source of drinking water1 Improved 16.1 4,184 Not improved 18.4 1,521 Other/missing 17.6 350 Toilet facility2 Improved, not shared 13.7 1,946 Shared3 19.5 1,734 Non-improved 17.2 2,375 Residence Urban 16.6 1,937 Rural 16.8 4,118 Province Manicaland 16.7 893 Mashonaland Central 18.9 590 Mashonaland East 12.2 574 Mashonaland West 22.5 783 Matabeleland North 11.7 275 Matabeleland South 9.4 230 Midlands 16.8 821 Masvingo 17.1 731 Harare 17.4 910 Bulawayo 13.3 249 Mother’s education No education 23.6 70 Primary 17.7 1,884 Secondary 17.0 3,767 More than secondary 7.2 335 Wealth quintile Lowest 18.4 1,381 Second 16.3 1,179 Middle 16.3 1,016 Fourth 17.6 1,428 Highest 14.1 1,052 Total 16.7 6,055 1 See Table 2.1 for definition of categories. 2 See Table 2.2 for definition of categories. 3 Facilities that would be considered improved if they were not shared by two or more households 18 0 • C hi ld H ea lth Ta bl e 10 .8 F ee di ng p ra ct ic es d ur in g di ar rh oe a P er ce nt d is tri bu tio n of c hi ld re n un de r ag e 5 w ho h ad d ia rr ho ea in th e 2 w ee ks p re ce di ng th e su rv ey b y am ou nt o f l iq ui ds a nd fo od o ffe re d co m pa re d w ith n or m al p ra ct ic e, a cc or di ng to b ac kg ro un d ch ar ac te ris tic s, Z im ba bw e 20 15 A m ou nt o f l iq ui ds g iv en A m ou nt o f f oo d gi ve n N um be r o f ch ild re n w ith di ar rh oe a B ac kg ro un d ch ar ac te ris tic M or e S am e as us ua l S om ew ha t le ss M uc h le ss N on e D on ’t kn ow / m is si ng To ta l M or e S am e as us ua l S om ew ha t le ss M uc h le ss N on e N ev er g av e fo od D on ’t kn ow / m is si ng To ta l A ge in m on th s <6 20 .2 55 .0 9. 1 8. 9 6. 6 0. 0 10 0. 0 0. 0 20 .1 17 .3 8. 5 0. 3 53 .8 0. 0 10 0. 0 60 6- 11 33 .9 34 .2 21 .2 9. 8 0. 9 0. 0 10 0. 0 7. 9 29 .1 24 .8 18 .8 13 .5 5. 9 0. 0 10 0. 0 17 7 12 -2 3 30 .3 34 .9 21 .2 11 .3 1. 8 0. 5 10 0. 0 4. 6 23 .9 32 .0 20 .7 15 .9 2. 5 0. 5 10 0. 0 36 9 24 -3 5 40 .6 31 .6 16 .6 8. 5 2. 0 0. 7 10 0. 0 9. 5 36 .9 28 .4 17 .7 6. 2 1. 2 0. 0 10 0. 0 20 6 36 -4 7 35 .4 29 .4 22 .1 9. 8 1. 8 1. 4 10 0. 0 8. 0 32 .8 40 .1 13 .3 4. 0 0. 2 1. 4 10 0. 0 11 8 48 -5 9 36 .2 22 .6 25 .8 8. 6 3. 6 3. 3 10 0. 0 7. 7 30 .2 31 .6 22 .5 7. 6 0. 0 0. 5 10 0. 0 83 S ex M al e 32 .4 36 .0 20 .7 8. 5 2. 1 0. 4 10 0. 0 7. 5 31 .3 28 .0 15 .6 11 .3 6. 1 0. 4 10 0. 0 53 6 Fe m al e 34 .8 31 .0 19 .3 11 .6 2. 2 1. 2 10 0. 0 5. 5 26 .0 32 .4 21 .4 9. 6 4. 7 0. 4 10 0. 0 47 8 B re as tf ee di ng s ta tu s B re as tfe ed in g 28 .5 38 .2 20 .3 10 .9 2. 2 0. 0 10 0. 0 5. 5 21 .6 25 .7 18 .8 16 .1 12 .3 0. 0 10 0. 0 42 6 N ot b re as tfe ed in g 37 .2 30 .3 19 .9 9. 2 2. 1 1. 3 10 0. 0 7. 3 34 .0 33 .2 18 .0 6. 4 0. 5 0. 7 10 0. 0 58 7 R es id en ce U rb an 36 .6 32 .3 14 .5 12 .5 2. 6 1. 6 10 0. 0 4. 5 31 .1 30 .6 19 .6 9. 5 4. 0 0. 7 10 0. 0 32 1 R ur al 32 .1 34 .3 22 .6 8. 7 1. 9 0. 4 10 0. 0 7. 5 27 .7 29 .8 17 .7 11 .0 6. 1 0. 3 10 0. 0 69 3 P ro vi nc e M an ic al an d 41 .2 30 .2 8. 5 19 .8 0. 4 0. 0 10 0. 0 12 .7 26 .6 16 .4 34 .6 5. 7 4. 0 0. 0 10 0. 0 14 9 M as ho na la nd C en tra l 37 .4 35 .8 22 .6 2. 6 1. 6 0. 0 10 0. 0 7. 3 29 .7 22 .9 7. 2 24 .1 8. 7 0. 0 10 0. 0 11 1 M as ho na la nd E as t 24 .4 33 .0 35 .2 4. 8 0. 0 2. 5 10 0. 0 2. 1 19 .3 49 .7 11 .6 5. 6 9. 2 2. 5 10 0. 0 70 M as ho na la nd W es t 31 .5 31 .0 23 .4 10 .3 3. 0 0. 8 10 0. 0 4. 9 33 .4 29 .3 12 .7 14 .9 4. 9 0. 0 10 0. 0 17 6 M at ab el el an d N or th 36 .3 29 .6 26 .9 1. 5 3. 6 2. 1 10 0. 0 2. 1 23 .7 45 .6 6. 5 11 .9 10 .1 0. 0 10 0. 0 32 M at ab el el an d S ou th (2 6. 9) (1 7. 3) (2 8. 6) (2 4. 4) (2 .8 ) (0 .0 ) 10 0. 0 (5 .5 ) (1 8. 6) (3 3. 7) (2 2. 2) (1 5. 1) (4 .9 ) (0 .0 ) 10 0. 0 22 M id la nd s 37 .6 39 .3 13 .7 7. 0 2. 5 0. 0 10 0. 0 9. 4 40 .5 28 .7 10 .3 5. 5 5. 7 0. 0 10 0. 0 13 8 M as vi ng o 23 .4 38 .4 30 .5 4. 2 3. 5 0. 0 10 0. 0 3. 8 26 .8 34 .7 22 .7 5. 7 6. 2 0. 0 10 0. 0 12 5 H ar ar e 33 .0 33 .4 15 .6 13 .0 2. 8 2. 1 10 0. 0 5. 2 19 .8 36 .3 24 .4 10 .9 2. 5 1. 1 10 0. 0 15 8 B ul aw ay o 41 .2 31 .4 9. 6 16 .6 0. 0 1. 3 10 0. 0 4. 1 44 .6 18 .8 23 .7 5. 8 1. 8 1. 3 10 0. 0 33 M ot he r’ s ed uc at io n N o ed uc at io n * * * * * * 10 0. 0 * * * * * * * 10 0. 0 16 P rim ar y 31 .8 31 .0 24 .4 8. 9 3. 4 0. 5 10 0. 0 6. 9 28 .8 28 .9 16 .7 10 .7 7. 5 0. 5 10 0. 0 33 3 S ec on da ry 33 .6 34 .4 18 .7 10 .7 1. 6 0. 9 10 0. 0 6. 5 28 .5 30 .6 19 .7 10 .4 3. 9 0. 3 10 0. 0 64 0 M or e th an s ec on da ry (4 4. 9) (4 3. 3) (8 .0 ) (3 .8 ) (0 .0 ) (0 .0 ) 10 0. 0 (2 .5 ) (3 0. 4) (2 8. 6) (1 0. 0) (7 .1 ) (2 1. 4) (0 .0 ) 10 0. 0 24 W ea lth q ui nt ile Lo w es t 33 .1 34 .5 23 .8 7. 7 0. 6 0. 3 10 0. 0 6. 1 25 .9 30 .2 19 .8 10 .5 7. 4 0. 0 10 0. 0 25 4 S ec on d 33 .2 29 .4 25 .9 8. 5 2. 9 0. 0 10 0. 0 7. 3 29 .0 30 .1 13 .7 12 .4 7. 5 0. 0 10 0. 0 19 3 M id dl e 31 .8 36 .7 18 .6 8. 4 3. 5 1. 1 10 0. 0 9. 0 26 .2 29 .5 17 .0 12 .5 4. 7 1. 1 10 0. 0 16 6 Fo ur th 31 .1 35 .6 15 .3 14 .0 2. 7 1. 3 10 0. 0 6. 1 34 .8 28 .7 21 .1 6. 0 2. 6 0. 7 10 0. 0 25 2 H ig he st 40 .6 30 .9 15 .8 10 .3 1. 1 1. 3 10 0. 0 4. 2 26 .0 32 .7 18 .5 13 .3 5. 1 0. 3 10 0. 0 14 9 To ta l 33 .5 33 .6 20 .0 9. 9 2. 1 0. 8 10 0. 0 6. 5 28 .8 30 .0 18 .3 10 .5 5. 4 0. 4 10 0. 0 1, 01 4 N ot es : I t i s re co m m en de d th at c hi ld re n sh ou ld b e gi ve n m or e liq ui ds to d rin k du rin g di ar rh oe a an d fo od s ho ul d no t b e re du ce d. F ig ur es in p ar en th es es a re b as ed o n 25 -4 9 un w ei gh te d ca se s. A n as te ris k in di ca te s th at a fi gu re is b as ed o n fe w er th an 2 5 un w ei gh te d ca se s an d ha s be en s up pr es se d. C hi ld H ea lth • 1 81 Ta bl e 10 .9 D ia rr ho ea tr ea tm en t A m on g ch ild re n un de r a ge 5 w ho h ad d ia rr ho ea in th e 2 w ee ks p re ce di ng th e su rv ey , p er ce nt ag e fo r w ho m a dv ic e or tr ea tm en t w as s ou gh t f ro m a h ea lth fa ci lit y or p ro vi de r; pe rc en ta ge g iv en fl ui d fro m a n O R S p ac ke t o r p re - pa ck ag ed O R S fl ui d, r ec om m en de d ho m em ad e flu id s (R H F) , O R S o r R H F, z in c, O R S a nd z in c, O R S o r in cr ea se d flu id s, o ra l r eh yd ra tio n th er ap y (O R T) , c on tin ue d fe ed in g an d O R T, a nd o th er tr ea tm en ts ; a nd p er ce nt ag e gi ve n no tr ea tm en t, ac co rd in g to b ac kg ro un d ch ar ac te ris tic s, Z im ba bw e 20 15 B ac kg ro un d ch ar ac te ris tic P er ce nt ag e of ch ild re n w ith di ar rh oe a fo r w ho m ad vi ce o r t re at m en t w as s ou gh t f ro m a he al th fa ci lit y or pr ov id er 1 P er ce nt ag e of c hi ld re n w ith d ia rr ho ea w ho w er e gi ve n: P er ce nt ag e gi ve n no tre at m en t N um be r o f ch ild re n w ith di ar rh oe a Fl ui d fro m O R S p ac ke t or p re - pa ck ag ed O R S fl ui d R ec om - m en de d ho m em ad e flu id s (R H F) E ith er O R S or R H F Zi nc O R S a nd zi nc O R S o r in cr ea se d flu id s O R T (O R S , R H F, o r in cr ea se d flu id s) C on tin ue d fe ed in g an d O R T2 O th er tr ea tm en ts A nt ib io tic dr ug s A nt i-m ot ili ty dr ug s In tra ve no us so lu tio n A ge in m on th s <6 27 .4 15 .5 26 .7 39 .1 9. 4 7. 5 29 .2 48 .9 19 .4 3. 7 3. 4 0. 0 48 .0 60 6- 11 32 .0 34 .6 40 .8 60 .5 12 .5 9. 4 57 .4 73 .1 41 .0 5. 6 0. 0 1. 2 26 .3 17 7 12 -2 3 43 .3 44 .0 50 .9 73 .6 23 .7 18 .2 61 .2 82 .6 49 .7 7. 5 1. 0 2. 4 15 .7 36 9 24 -3 5 45 .7 49 .7 53 .6 77 .9 24 .2 19 .2 68 .5 83 .6 61 .4 8. 3 1. 0 1. 1 14 .6 20 6 36 -4 7 40 .0 40 .5 44 .8 67 .7 22 .3 14 .2 60 .5 77 .0 66 .9 8. 7 0. 9 2. 6 19 .3 11 8 48 -5 9 31 .0 32 .7 57 .2 73 .9 13 .1 9. 5 52 .8 79 .2 52 .9 4. 8 0. 0 0. 3 18 .1 83 S ex M al e 38 .6 39 .8 45 .8 68 .7 19 .7 16 .1 56 .9 76 .4 50 .6 7. 6 1. 1 1. 6 22 .3 53 6 Fe m al e 40 .4 41 .3 50 .6 70 .3 20 .2 13 .9 62 .1 80 .2 51 .4 6. 4 0. 7 1. 7 17 .2 47 8 R es id en ce U rb an 40 .6 46 .4 50 .9 72 .0 17 .2 13 .4 65 .4 80 .6 53 .0 7. 3 0. 3 1. 5 17 .5 32 1 R ur al 38 .9 37 .8 46 .7 68 .3 21 .2 15 .8 56 .5 77 .1 50 .1 6. 9 1. 2 1. 7 21 .0 69 3 P ro vi nc e M an ic al an d 37 .1 36 .7 43 .2 66 .2 25 .0 16 .9 62 .0 82 .2 43 .0 12 .3 3. 5 4. 2 15 .0 14 9 M as ho na la nd C en tra l 44 .9 40 .5 55 .7 69 .6 33 .6 23 .8 62 .5 79 .8 47 .5 8. 9 0. 0 2. 8 15 .9 11 1 M as ho na la nd E as t 40 .6 33 .8 41 .0 62 .2 12 .2 7. 8 53 .3 69 .9 53 .2 8. 6 0. 6 0. 4 23 .1 70 M as ho na la nd W es t 37 .0 36 .1 49 .8 69 .7 18 .1 13 .9 55 .4 74 .7 50 .3 6. 6 0. 0 0. 0 23 .6 17 6 M at ab el el an d N or th 61 .5 60 .3 41 .3 85 .7 29 .9 27 .1 66 .8 85 .7 62 .1 4. 5 0. 0 1. 7 14 .3 32 M at ab el el an d S ou th (5 2. 2) (5 6. 5) (6 5. 9) (8 0. 9) (1 3. 9) (1 2. 5) (6 7. 3) (8 2. 3) (4 4. 7) (0 .0 ) (0 .0 ) (0 .0 ) (1 7. 7) 22 M id la nd s 26 .9 38 .7 33 .5 61 .0 14 .4 10 .2 60 .4 75 .1 60 .5 3. 3 2. 0 0. 4 23 .3 13 8 M as vi ng o 39 .1 35 .1 47 .8 67 .2 16 .6 13 .6 46 .8 74 .8 48 .8 4. 5 0. 0 2. 4 25 .2 12 5 H ar ar e 41 .7 49 .4 55 .0 76 .0 15 .3 12 .9 66 .2 81 .3 50 .8 7. 6 0. 0 0. 3 18 .5 15 8 B ul aw ay o 54 .8 50 .3 72 .8 87 .8 28 .7 24 .9 68 .5 91 .6 60 .3 5. 5 2. 1 7. 2 7. 2 33 M ot he r’ s ed uc at io n N o ed uc at io n * * * * * * * * * * * * * 16 P rim ar y 32 .5 32 .8 41 .3 61 .3 17 .9 13 .9 52 .0 72 .7 46 .4 5. 3 0. 5 0. 3 24 .6 33 3 S ec on da ry 42 .3 44 .7 52 .0 74 .3 20 .6 15 .3 62 .9 81 .5 53 .6 7. 7 1. 2 2. 0 17 .3 64 0 M or e th an s ec on da ry (4 9. 7) (4 3. 1) (2 7. 1) (5 3. 0) (2 3. 7) (2 1. 7) (6 5. 3) (6 7. 7) (4 4. 1) (1 7. 6) (0 .0 ) (6 .7 ) (2 7. 3) 24 W ea lth q ui nt ile Lo w es t 34 .7 29 .7 49 .5 65 .9 20 .0 14 .2 51 .7 76 .4 46 .8 6. 0 0. 0 2. 0 21 .6 25 4 S ec on d 40 .1 37 .0 42 .9 66 .9 22 .1 15 .6 52 .9 74 .4 49 .0 6. 2 1. 6 2. 0 24 .2 19 3 M id dl e 38 .8 44 .2 43 .0 68 .8 20 .0 14 .2 65 .5 79 .7 52 .8 7. 4 2. 9 1. 5 17 .0 16 6 Fo ur th 38 .1 49 .5 51 .6 74 .9 16 .9 14 .4 64 .3 81 .7 56 .3 6. 6 0. 0 0. 6 16 .7 25 2 H ig he st 49 .6 44 .2 51 .9 70 .5 22 .0 17 .9 65 .4 78 .6 49 .8 10 .2 0. 7 2. 5 19 .8 14 9 To ta l 39 .4 40 .5 48 .1 69 .5 19 .9 15 .1 59 .3 78 .2 51 .0 7. 0 0. 9 1. 6 19 .9 1, 01 4 N ot es : O R T in cl ud es f lu id p re pa re d fro m o ra l r eh yd ra tio n sa lt (O R S ) pa ck et s, p re -p ac ka ge d O R S f lu id , an d re co m m en de d ho m e flu id s (R H F) . Fi gu re s in p ar en th es es a re b as ed o n 25 -4 9 un w ei gh te d ca se s. A n as te ris k in di ca te s th at a fi gu re is b as ed o n fe w er th an 2 5 un w ei gh te d ca se s an d ha s be en s up pr es se d. 1 E xc lu de s ph ar m ac y, s ho p an d tra di tio na l p ra ct iti on er 2 C on tin ue d fe ed in g in cl ud es c hi ld re n w ho w er e gi ve n m or e, s am e as u su al , o r s om ew ha t l es s fo od d ur in g th e di ar rh oe a ep is od e. 182 • Child Health Table 10.10 Knowledge of ORS packets or pre- packaged liquids Percentage of women age 15-49 with a live birth in the 5 years preceding the survey who know about ORS packets or ORS pre-packaged liquids for treatment of diarrhoea, according to background characteristics, Zimbabwe 2015 Background characteristic Percentage of women who know about ORS packets or ORS pre- packaged liquids Number of women Age 15-19 56.0 369 20-24 69.4 1,136 25-34 74.9 2,443 35-49 73.2 1,039 Residence Urban 79.3 1,637 Rural 68.2 3,351 Province Manicaland 72.7 709 Mashonaland Central 55.4 492 Mashonaland East 80.4 473 Mashonaland West 84.1 638 Matabeleland North 74.5 234 Matabeleland South 54.2 200 Midlands 71.6 678 Masvingo 64.1 583 Harare 78.1 762 Bulawayo 65.7 220 Education No education (59.8) 57 Primary 60.0 1,530 Secondary 76.3 3,125 More than secondary 90.3 275 Wealth quintile Lowest 62.6 1,082 Second 68.9 956 Middle 71.7 860 Fourth 75.7 1,183 Highest 81.2 908 Total 71.9 4,988 ORS = Oral rehydration salts Child Health • 183 Table 10.11 Disposal of children’s stools Percent distribution of youngest children under age 2 living with the mother by the manner of disposal of the child’s last faecal matter, and percentage of children whose stools are disposed of safely, according to background characteristics, Zimbabwe 2015 Manner of disposal of children’s stools Total Percentage of children whose stools are disposed of safely1 Number of children Background characteristic Child used toilet or latrine Put/rinsed into toilet or latrine Buried Put/rinsed into drain or ditch Thrown into garbage Left in the open Other Age of child in months 0-1 7.2 50.5 11.2 9.4 14.8 4.7 2.2 100.0 68.9 201 2-3 8.2 47.9 8.6 10.8 13.2 7.5 3.8 100.0 64.7 228 4-5 7.4 57.3 13.3 9.1 8.5 2.3 2.1 100.0 78.0 181 6-8 9.6 49.3 10.3 9.6 14.9 5.2 1.0 100.0 69.3 283 9-11 6.9 53.0 14.5 7.0 7.4 6.9 4.4 100.0 74.4 276 12-17 8.1 52.4 17.4 7.6 8.1 4.5 1.9 100.0 77.9 609 18-23 11.2 47.1 20.5 4.1 8.0 6.6 2.5 100.0 78.8 532 6-23 9.1 50.3 16.7 6.7 9.1 5.7 2.4 100.0 76.2 1,699 Toilet facility2 Improved, not shared 12.7 67.0 2.5 3.2 11.4 1.1 2.0 100.0 82.2 687 Shared3 12.0 65.8 4.5 4.1 10.3 1.6 1.7 100.0 82.3 671 Unimproved 3.6 28.3 31.8 13.0 8.6 11.4 3.3 100.0 63.7 954 Residence Urban 13.3 59.8 0.7 3.3 20.1 0.1 2.7 100.0 73.7 647 Rural 7.0 47.1 20.8 9.2 6.0 7.6 2.4 100.0 74.9 1,664 Province Manicaland 10.3 63.9 7.3 6.2 3.7 2.9 5.8 100.0 81.4 367 Mashonaland Central 1.2 61.3 13.4 11.1 3.6 9.4 0.0 100.0 76.0 234 Mashonaland East 13.8 46.3 17.4 8.1 4.1 7.7 2.7 100.0 77.5 227 Mashonaland West 5.0 55.0 18.7 10.9 6.8 3.1 0.4 100.0 78.7 286 Matabeleland North 3.9 25.7 37.2 14.9 9.8 7.2 1.3 100.0 66.8 111 Matabeleland South 18.6 36.3 24.0 4.7 9.1 6.6 0.7 100.0 78.9 93 Midlands 12.5 43.6 17.1 5.5 9.3 8.1 3.9 100.0 73.2 324 Masvingo 3.1 34.3 28.1 8.9 13.6 9.6 2.4 100.0 65.4 282 Harare 9.3 65.3 0.0 2.7 22.7 0.0 0.0 100.0 74.6 303 Bulawayo 19.8 38.4 1.4 4.7 26.2 0.7 8.8 100.0 59.6 83 Mother’s education No education * * * * * * * 100.0 * 29 Primary 5.3 44.7 22.1 9.2 7.0 8.2 3.5 100.0 72.1 732 Secondary 10.4 53.9 12.4 7.2 9.8 4.4 1.8 100.0 76.7 1,453 More than secondary 11.1 47.3 0.9 0.9 35.7 0.0 4.1 100.0 59.3 97 Wealth quintile Lowest 3.3 26.4 34.3 13.0 7.9 12.6 2.6 100.0 63.9 578 Second 9.0 43.4 21.4 9.3 5.4 8.6 2.9 100.0 73.8 475 Middle 7.5 69.1 9.1 6.4 3.3 2.9 1.8 100.0 85.7 416 Fourth 13.6 71.1 2.2 3.1 7.4 0.2 2.3 100.0 86.9 513 Highest 11.8 48.8 0.4 3.8 32.2 0.2 2.8 100.0 61.1 329 Total 8.7 50.7 15.2 7.5 9.9 5.5 2.5 100.0 74.6 2,311 Note: An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. 1 Children’s stools are considered to be disposed of safely if the child used a toilet or latrine, if the faecal matter was put or rinsed into a toilet or latrine, or if it was buried. 2 See Table 2.2 for definition of categories. 3 Facilities that would be considered improved if they were not shared by two or more households Nutrition of Children and Adults • 185 NUTRITION OF CHILDREN AND ADULTS 11 Key Findings  Nutritional status of children: Just over a quarter (27 percent) of children under age 5 are stunted (short for their age); 3 percent are wasted (thin for their height); 8 percent are underweight (thin for their age); and 6 percent are overweight (heavy for their height).  Breastfeeding: Almost all children (98 percent) have been breastfed at some point in their life with almost two- thirds (58 percent) initiating breastfeeding within one hour of birth. Forty-eight percent of infants under age 6 months are exclusively breastfed. The median duration of any breastfeeding is 17.3 months, while the median duration for exclusive breastfeeding is 2.3 months.  Complementary feeding: Thirty-five percent of children age 6-23 months ate meals the recommended number of times per day while 8 percent were fed a minimum acceptable diet.  Anaemia: More than a third of children aged 6-59 months (37 percent) are anaemic while 27 percent of women and 15 percent of men age 15-49 are anaemic.  Adult nutritional status: Thirty-five percent of women age 15-49 are overweight or obese; 13 percent are obese. Thirteen percent of men age 15-49 years are overweight or obese; 2 percent are obese.  Salt iodisation: Ninety-five percent of households use iodised salt for cooking. his chapter focuses on the nutritional status of children under age 5 and that of women and men age 15-49. The chapter also describes infant and young feeding practices including breastfeeding, complementary feeding, minimum meal frequency, and the minimum dietary diversity for children below age 24 months. Also discussed is vitamin A, iron and iodine-rich or fortified food consumption for children below age 2 years, and vitamin A supplementation status in children age 6-59 months. Finally, the anaemia status of children 6-59 months and women and men age 15-49 are also presented in this chapter. 11.1 NUTRITIONAL STATUS OF CHILDREN In the 2015 ZDHS, children under age 5 had their height and weight measured to assess their nutritional status. This aids in the identification of population subgroups at risk of mortality and morbidity from malnutrition. T 186 • Nutrition of Children and Adults 11.1.1 Measurement of Nutritional Status among Young Children Weight and recumbent length were measured for children age 0-23 months. Weight and standing height were also measured for children age 24-59 months from the sampled households regardless of whether the mother was interviewed in the survey. SECA digital electronic scales were used to measure weight; ShorrBoards® were used to measure height and length. Children’s height/length, weight, and age data were used to calculate three indices: height-for-age, weight- for-height, and weight-for-age. Each of these indices is expressed in terms of standard deviations from the median (Z-scores) of the WHO reference population (WHO 2006). Each indices provides different information about growth and body composition for assessing nutritional status. As indicated below, stunting, or low height-for-age, is a sign of chronic undernutrition that reflects failure to receive adequate nutrition over a long period. Stunting can also be affected by recurrent and chronic illness. Wasting, or low weight-for-height, is a measure of acute undernutrition and represents the failure to receive adequate nutrition in the period immediately before the survey. Wasting may result from inadequate food intake or from a recent episode of illness that caused weight loss. The opposite of wasting is overweight (high weight-for-height), which is a measure of overnutrition. Weight-for-age is a composite index of weight- for-height and height-for-age that includes both acute (wasting) and chronic (stunting) undernutrition and is an indicator of overall undernutrition. Stunting, or height-for-age Height-for-age is a measure of linear growth retardation and cumulative growth deficits. Children whose height-for-age Z-score is below minus two standard deviations (-2 SD) from the median of the reference population are considered short for their age (stunted), or chronically undernourished. Children who are below minus three standard deviations (-3 SD) are considered severely stunted. Sample: Children under age 5 Wasting, or weight-for-height The weight-for-height index measures body mass in relation to body height or length and describes current nutritional status. Children whose Z-score is below minus two standard deviations (-2 SD) from the median of the reference population are considered thin (wasted), or acutely undernourished. Children whose weight-for-height Z-score is below minus three standard deviations (-3 SD) from the median of the reference population are considered severely wasted. Sample: Children under age 5 Underweight, or weight-for-age Weight-for-age is a composite index of height-for-age and weight-for-height. It takes into account both acute and chronic undernutrition. Children whose weight-for-age Z-score is below minus two standard deviations (-2 SD) from the median of the reference population are classified as underweight. Children whose weight-for-age Z-score is below minus three standard deviations (-3 SD) from the median are considered severely underweight. Sample: Children under age 5 Overweight in children Children whose weight-for-height Z-score is more than 2 standard deviations (+2 SD) above the median of the reference population are considered overweight. Sample: Children under age 5 Nutrition of Children and Adults • 187 The means of the Z-scores for height-for-age, weight-for-height, and weight-for-age are also calculated as summary statistics that represent the nutritional status of children in a population. These mean scores describe the nutritional status of the entire population of children without the use of a cutoff point. A mean Z-score of less than 0 (a negative mean value for stunting, wasting, or underweight) suggests a downward shift in the entire sample population’s nutritional status relative to the reference population. The farther away the mean Z-scores are from 0, the higher the prevalence of undernutrition. 11.1.2 Data Collection Height and weight measurements were obtained for 6,511 children under age 5 who were present in the 2015 ZDHS sample households at the time of the survey. The following analysis is based on the 93 percent for whom complete, credible anthropometric and age data were collected. 11.1.3 Prevalence of Malnutrition in Children The 2015 ZDHS data show that 27 percent of children are stunted, 3 percent are wasted, 8 percent are underweight, and 6 percent are overweight Table 11.1 and Figure 11.1. Trends: From 1988 to 2005-06, the prevalence of children who were stunted, underweight, and wasted increased slightly; since 2005-06, the prevalence of stunting, underweight, and wasting have gradually declined to levels below or comparable to 1988 (Figure 11.2). Over the same time period, the proportion of overweight children rose from 2 percent in 1988 to 10 percent in 1999 before declining to 6 percent in 2010-11, where it remains in 2015. Figure 11.1 Nutritional status of children Figure 11.2 Trends in nutritional status of children 18 2 6 6 9 1 2 Stunting Wasting Underweight Overweight Percentage of children under age 5 classified as malnourished Moderate Severe 3 8 27 31 29 34 35 32 27 2 6 8 7 3 3 8 11 10 13 10 8 5 7 10 8 6 6 1988 1994 1999 2005-06 2010-11 2015 Percentage of children under age 5 classified as malnourished Stunting Underweight Overweight Wasting 188 • Nutrition of Children and Adults Patterns by background characteristics:  Stunting generally increases with a child’s age, rising from 13 percent of children age 6-8 months to a peak of 39 percent of children age 24-35 months, before declining to 18 percent of children age 48-59 months.  Boys have a higher proportion of stunting than girls (30 percent versus 24 percent).  Stunting, wasting, and underweight are higher in rural areas than in urban areas, whereas the proportion of overweight children is higher in urban areas than rural areas.  Stunting varies by province: stunting is highest in Matebeleland South (31 percent) and lowest in Bulawayo (19 percent) (Figure 11.3).  The prevalence of stunting is highest among children whose mothers have no education (45 percent) and lowest among children whose mothers have more than a secondary education (9 percent). In contrast, the prevalence of overweight is lowest among children whose mothers have no education (3 percent) and highest among those whose mothers have more than secondary education (9 percent).  The prevalence of stunting, wasting, and underweight generally decreases with increasing household wealth. In contrast the prevalence of overweight increases with increasing wealth. 11.2 INFANT AND YOUNG CHILD FEEDING PRACTICES Optimal infant and young child feeding (IYCF) during the first 2 years of life lowers morbidity and mortality and reduces the risk of chronic disease. The recommended practices that promote appropriate nutrition include early initiation of breastfeeding within 1 hour of birth, exclusive breastfeeding for the first 6 months of life, introduction of nutritionally adequate, safe, complementary foods (solid and semisolid) at 6 months, and gradual increases in the amount of food given and frequency of feeding as the child gets older together with continued breastfeeding through age 2 years. It is also important for young children to receive a diverse diet, i.e., eating foods from different food groups to take care of the growing micronutrient needs (WHO 2008). 11.2.1 Initiation of Breastfeeding Early initiation of breastfeeding is important for both mother and child. The first breast milk contains colostrum, which is highly nutritious and contains antibodies that protect the newborn from diseases. Early initiation of breastfeeding encourages bonding between the mother and her newborn, facilitates the production of regular breast milk, and reduces the risk of maternal postpartum haemorrhage. Thus, it is recommended that children be put to the breast immediately or within 1 hour after birth, and that prelacteal feeding (feeding newborns anything other than breast milk before breast milk is regularly given) be discouraged. Globally, suboptimal breastfeeding results in more than 800,000 child deaths annually (Oot et al. 2015). Figure 11.3 Stunting by province Percentage of children under age 5 who are stunted Nutrition of Children and Adults • 189 Early breastfeeding Initiation of breastfeeding within 1 hour of birth Sample: Last born children who were born in the 2 years before the survey Table 11.2 shows that 58 percent of last-born children who were born in the 2 years before the survey were breastfed within 1 hour of birth and that 93 percent started breastfeeding within 1 day of birth. Ninety-eight percent of last-born children born were breastfed at some point in their life. Trends: The percentage of infants breastfed within an hour of birth has steadily decreased from 68 percent in 2005-06 to 65 percent in 2010-11, and then to 58 percent in 2015. Since 1988, the percentage of children who were ever breastfed has held steady (99-97 percent) Patterns by background characteristics  The proportion of children breastfed within 1 hour of birth was higher among those delivered in a health facility (61 percent) than those born at home (44 percent).  Matabeleland South (81 percent) has the highest percentage of children breastfed within 1 hour of birth, and Manicaland (43 percent) has the lowest percentage. The practice of giving prelacteal feeds limit the frequency of suckling by the infant and exposes the baby to the risk of infection. Overall, 13 percent of infants received a prelacteal feeding. 11.2.2 Exclusive Breastfeeding Infants should receive only breast milk (exclusive breastfeed) in the first 6 months of life. It is not necessary to give other liquids (including water) or solids because breast milk contains all the nutrients that an infant needs in the first 6 months of their life. Exclusive breastfeeding for 6 months confers many benefits to the infant and the mother. Chief among these is breastfeeding’s protective effect against gastrointestinal infections. In the context of HIV, introducing other milks, foods, or liquids significantly increases the risk of HIV transmission through breast milk, and reduces an infant’s chances of HIV-free survival. For the mother, exclusive breastfeeding can delay the return of fertility. Table 11.3 and Figure 11.4 show breastfeeding practices by the child’s age. Forty-eight percent of infants under the age of 6 months in Zimbabwe are exclusively breastfed. The proportion of children exclusively breastfed rapidly drops from 74 percent among infants age 0-1 month to 46 percent among children age 2-3 months. Contrary to the recommendation that children under 6 months be exclusively breastfed, many infants consume other liquids such as plain water (21 percent), and 28 percent consume complementary foods in addition to breast milk. Figure 11.4 Breastfeeding practices by age 0 10 20 30 40 50 60 70 80 90 100 <2 2-3 4-5 6-7 8-9 10-11 12-13 14-15 16-17 18-19 20-21 22-23 Age in months Percent distribution of children under age 2 Breastfeeding and complementary foods Not breastfeeding Exclusive breastfeeding Breastfeeding and water only Breastfeeding and other liquids 190 • Nutrition of Children and Adults Trends: The proportion of exclusively breastfed children below age 6 months has gradually increased over the last decade. In 2005-06, 22 percent of children age 0-5 months were exclusive breastfed; this increased to 31 percent in 2010-11 and 48 percent in 2015. Patterns by background characteristics  At age 4-5 months, only one in five children (20 percent) are benefiting from exclusive breastfeeding.  Ninety percent of children age 6-9 months receive timely complementary foods, and 77 percent of children are no longer breastfed by the age 18-23 months.  The proportion of children below age 24 months who were fed using a bottle with a nipple is 8 percent (Figure 11.5). The prevalence of bottle- feeding is highest among children age 6-8 months (14 percent). A summary of IYCF breastfeeding indicators is shown in Figure 11.5. 11.2.3 Median Duration of Breastfeeding Breastfeeding reduces the risk of many perinatal infections, acute lower respiratory infections, and diarrhoea in infants age 23 months and younger; and continues to make an important contribution to the health and well-being of mother and children up to the age 2 and beyond (Lamberti, et al. 2013). Longer durations of breastfeeding reduce the risk of ovarian and breast cancer in women. Continued, frequent breastfeeding also protects a child’s health by delaying maternal fertility postpartum, increasing birth space, and reducing the child’s risk of morbidity and mortality. Table 11.4 shows that the median duration of any breastfeeding is 17.3 months. This means that half of Zimbabwean children were breastfed for 17.3 months or less, and half were breastfed for 17.3 months or more. Overall, the median duration of exclusive breastfeeding for Zimbabwean children is 2.3 months, while the median duration of predominant breastfeeding (the period in which an infant receives only water or other non-milk liquids in addition to breast milk) is 3.8 months. Ninety-one percent of children continue breastfeeding at 1 year, while 14 percent continue breastfeeding at 2 years (Figure 11.5). Trends: Over the last decade, the median duration for exclusive breastfeeding has increased from 0.6 months in 2005-06 to 2.3 months in 2015. During the same period the median duration of predominant breastfeeding has increased from 1.6 months in 2005-06 to 3.8 months in 2015. Patterns by background characteristics  The median duration of any breastfeeding is about a month longer for girls than the boys (17.8 months versus 16.9 months).  On average, urban children are breastfed for a period 2 months shorter than rural children (16.0 months versus 18.0 months). Exclusive breastfeeding is of shorter duration in urban areas (1.9 months) compared with rural (2.4 months).  The median duration of any breastfeeding increases with decreasing wealth, ranging from 18.3 months in the lowest and second wealth quintiles to 15.5 months in highest wealth quintile. Figure 11.5 IYCF breastfeeding indicators 8 60 14 91 91 69 20 48 Bottle feeding (0-23 months) Age-appropriate breastfeeding** (0-23 months) Continued breastfeeding at 2 years Continued breastfeeding at 1 year Introduction of solid, semisolid, or soft foods at 6-8 months Predominant breastfeeding* (0-5 months) Exclusive breastfeeding at 4-5 months of age Exclusive breastfeeding under 6 months of age Percentage of children * Predominant breastfeeding includes exclusive breastfeeding, breastfeeding plus plain water, and breastfeeding plus non-milk liquids/juice ** Age appropriate breastfeeding = Children age 0-5 months who are exclusively breastfed + children age 6-23 months who receive breastmilk and complementary foods Nutrition of Children and Adults • 191 11.2.4 Complementary Feeding At 6 months of age, when an infant’s need for energy and nutrients begins to exceed what is provided by breast milk, complementary foods are necessary to meet those needs. The transition from exclusive breastfeeding to family foods is referred to as complementary feeding. This is the most critical period for children because during this transition, children are most vulnerable to becoming undernourished. Complementary feeding should be timely, with all infants receiving foods in addition to breast milk starting at 6 months of age. In the 2015 ZDHS, women who had at least one child living with them who was born in 2013 or later were asked questions about the types of liquids and foods the child had consumed during the day or night before the interview. Mothers who had more than one child born in 2013 or later were asked question about the youngest child living with them. Among the youngest children living with their mother, 91 percent age 6-8 months are receiving complementary foods (Figure 11.5). Appropriate complementary feeding should include feeding children a variety of foods to ensure that requirements for nutrients are met. Fruits and vegetables rich in vitamin A should be consumed daily. Eating a range of fruits and vegetables, in addition to those rich in vitamin A, is also important. Studies have shown that plant-based complementary foods alone are insufficient to meet the needs for certain micronutrients. Therefore, it has been recommended that meat, poultry, fish, or eggs should be part of the daily diet, and eaten as often as possible (WHO 1998). Vitamin A-rich foods include liver, fish, egg yolk, dark yellow or orange fruits, dark green leafy vegetables, and orange or dark yellow-fleshed vegetables, roots, and tubers. Iron-rich foods include meat, fish, and poultry. Table 11.5 shows that the type of foods and liquids given to children during the day and night before the survey depend on the child’s age and breastfeeding status. Overall, food made from grains is by far the most commonly consumed item followed by fruits and vegetables rich in vitamin. Among breastfeeding children age 6-23 months, 90 percent consumed foods made from grains and 53 percent consumed fruits and vegetables rich in Vitamin A; among nonbreastfeeding children age 6-23 months, 86 percent consumed foods made from grains and 67 percent consumed fruits and vegetables rich in Vitamin A. Patterns by background characteristics  The majority of children who are less than age 1 are breastfeed and complementary foods are introduced as the child gets older. The proportions of children who consume vitamin A-rich and iron- rich foods increase with age. Fifty-three percent of breastfeeding children age 6-23 months consumed vitamin-rich fruits and vegetables compared with 67 percent of nonbreastfeeding children in the same age group (Table 11.5).  Half (52 percent) of nonbreastfeeding children and 36 percent of breastfeeding children age 6-23 months consumed meat, fish, or poultry.  One in five (20 percent) nonbreastfeeding children age 6-23 months consumed eggs compared with one in seven (14 percent) of breastfeeding children.  Twenty-six percent of nonbreastfeeding children age 6-23 months consumed foods made from legumes and nuts, and 19 percent consumed cheese, yogurt, and other milk products. Among breastfeeding children in the same age group, 16 percent consumed foods made from legumes and nuts, and 14 percent consumed cheese, yogurt, and other milk products. 11.2.5 Minimum Acceptable Diet Infant and young children should be fed a minimum acceptable diet (MAD) to ensure appropriate growth and development. Without adequate diversity and meal frequency, infants and young children are vulnerable to undernutrition, especially stunting and micronutrient deficiencies, and increased morbidity and mortality. The WHO minimum acceptable diet recommendation, which is a combination of dietary 192 • Nutrition of Children and Adults diversity and minimum meal frequency, is different for breastfed and nonbreastfed children. The definition of the composite indicator of a minimum acceptable diet for all children 6-23 months is indicated in the box below. Dietary diversity is a proxy for adequate micronutrient-density of foods. Minimum dietary diversity requires feeding the child food from at least four food groups. A minimum of four food groups is associated with better quality diets for both breastfed and nonbreastfed children. Children who consume food from at least four food groups have a high likelihood of consuming at least one animal food source and at least one fruit or vegetable in addition to a staple food such as grains, roots, or tubers (WHO 2008). The four food groups should come from the seven available food groups: grains, roots, and tubers; legumes and nuts; dairy products (milk yogurt, cheese); flesh foods (meat, fish, poultry, and liver/organ meat); eggs; vitamin A-rich fruits and vegetables; and other fruits and vegetables. Minimum meal frequency is a proxy for a child’s energy requirements. For infants and young children, the indicator is based on the child’s energy needs and, if the child is breastfed, the amount of energy needs not met by breast milk. Breastfed children are considered to be consuming minimum meal frequency if they receive solid, semi-solid, or soft foods at least twice a day for infants age 6-8 months and at least three times a day for children age 9-23 months. Nonbreastfed children age 6-23 months are considered to be fed with a minimum meal frequency if they receive solid, semi-solid, or soft foods at least four times a day. Minimum acceptable diet Proportion of children age 6-23 months who receive a minimum acceptable diet (apart from breast milk). This composite indicator is calculated from the following two fractions: Breastfed children age 6-23 months who had at least the minimum dietary diversity and the minimum meal frequency during the previous day ——————————————————————————— Breastfed children age 6-23 months and Nonbreastfed children age 6-23 months who received at least two milk feedings and had at least the minimum dietary diversity (not including milk feeds) and the minimum meal frequency during the previous day ——————————————————————————— Nonbreastfed children age 6-23 months Table 11.6 shows that overall 72 percent of children age 6-23 months received breast milk, milk, or milk products (2+ times) during the day or night before the interview. Twenty-eight percent had an adequately diverse diet— that is, they had been given foods from the appropriate number of food groups—and 35 percent had been fed the minimum number of times appropriate for their age. The feeding practices of only 8 percent of children age 6-23 months met the minimum standards with respect to all three IYCF feeding practices. The IYCF indicators for minimum acceptable diet by breastfeeding status among children age 6-23 months are summarised in Figure 11.6. Figure 11.6 IYCF indicators on minimum acceptable diet 23 39 10 41 25 3 28 35 8 Minimum dietary diversity Minimum meal frequency Minimum acceptable diet Percentage of children age 6-23 months Breastfed Nonbreastfed All children 6-23 months Nutrition of Children and Adults • 193 Trends: The proportion of all children age 6-23 months who met all three IYCF practices for a minimal acceptable diet decreased from 11 percent in 2010-11 to 8 percent in 2015. Patterns by background characteristics:  Urban children are more than twice as likely as rural children to consume a minimum acceptable diet (13 percent versus 6 percent).  Bulawayo (23 percent) and Harare (15 percent) have highest proportion of children fed a minimum acceptable diet, while Mashonaland West (4 percent) had the lowest proportion. 11.3 ANAEMIA PREVALENCE IN CHILDREN Anaemia is a condition marked by low levels of haemoglobin in the blood. Iron is a key component of haemoglobin, and iron deficiency is estimated to be responsible for half of all anaemia globally. Other causes of anaemia include malaria, hookworm and other helminths, other nutritional deficiencies, chronic infections, and genetic conditions. Anaemia is a serious concern in children because it can impair cognitive development, increase morbidity from infectious diseases, and stunt growth. Anaemia prevalence Any anaemia in children is defined as a blood haemoglobin level below 11.0 g/dL. In the 2015 ZDHS, severe anaemia is defined as <7.0 g/dL, and moderate anaemia is defined as 7.0-9.9 g/dL. Sample: Children 6-59 months Haemoglobin testing was carried out on children age 6-59 months. (The methodology used to measure haemoglobin levels is described in the first chapter of this report.) Overall, 37 percent of children are anaemic. Twenty-two percent of the children are mildly anaemic, 15 percent are moderately anaemic, and less than 1 percent are severely anaemic (Table 11.7). Trends: The prevalence of anaemia in children age 6-59 months decreased slightly between 2005-06 and2010-11 (from 58 percent to 56 percent), but has decreased markedly between 2010-11 and 2015 (from 56 percent to 37 percent) (Figure 11.7). Figure 11.7 Trends in anaemia status among children 28 27 22 30 29 15 1 1 0 2005-06 2010-11 2015 Percentage of children age 6-59 months 58 56 37 Severe Moderate Mild 194 • Nutrition of Children and Adults Patterns by background characteristics  Anaemia prevalence is inversely proportional to age, with the highest prevalence among children age 6-8 months (66 percent). The proportion of children with anaemia gradually decreases to a low of 22 percent among children age 48-59 months.  Anaemia prevalence for children varies by province, from a low of 29 percent in Masvingo to a high of 42 percent in Harare (Figure 11.8).  The prevalence of anaemia is similar for children in urban and rural areas (38 percent and 37 percent, respectively). There is also little difference by gender; 38 percent of boys are anaemic compared with 36 percent of girls. 11.4 VITAMIN A SUPPLEMENTATION AND DEWORMING IN CHILDREN Micronutrient deficiency is a major contributor to childhood morbidity and mortality. Micronutrients are available in foods and can also be provided through direct supplementation. Breastfeeding children benefit from supplements given to the mother. The information collected on food consumption among the youngest children under age 2 is useful in assessing the extent to which children are consuming food groups rich in two key micronutrients—vitamin A and iron—in their daily diet. Iron deficiency is one of the primary causes of anaemia, which has serious health consequences for both women and children. Vitamin A is an essential micronutrient for the immune system and plays an important role in maintaining the epithelial tissue in the body. Severe vitamin A deficiency (VAD) can cause eye damage and is the leading cause of childhood blindness. In addition, VAD also increases the severity of infections such as measles and diarrheal disease in children and slows recovery from illness. VAD is common in dry environments where fresh fruits and vegetables are not readily available. Infants and children have increased vitamin A requirements because vitamin A is necessary for rapid growth and combating infections. In addition, roundworms can cause significant vitamin A malabsorption, which can aggravate malnutrition in children. In Zimbabwe, high-dose vitamin A supplementation is provided to infants and children age 6-59 months twice per year to reduce child morbidity and mortality. In endemic districts, mass deworming is also conducted for children age 1 and older. The 2015 ZDHS also included questions designed to ascertain whether young children had received vitamin A or deworming medication in the 6 months before the survey. Vitamin A supplementation is an important intervention in preventing VAD among young children. Seventy-two percent of children age 6-23 months ate foods rich in vitamin A in the day or night preceding the interview, and 46 percent consumed iron-rich foods (Table 11.8). As expected, intake of both vitamin A-rich and iron-rich foods increases as children are weaned. Nonbreastfeeding children are more likely Figure 11.8 Anaemia in children by province Percentage of children under age 5 who are anaemic Nutrition of Children and Adults • 195 than breastfeeding children to consume foods rich in vitamin A (83 percent versus 67 percent) and iron (57 percent versus 42 percent). In the 6 months before the survey, 67 percent of children age 6-59 months received a vitamin A supplement and 18 percent received deworming medication. Ninety-five percent of children age 6-59 months live in households with iodized salt. Trends: The proportion of children 6-59 months of age who received vitamin A supplementation increased from 47 percent in 2005-06 to 66 percent in 2010-11, and 67 percent in 2015, while the proportion children who received deworming medication increased six-fold from 3 percent in 2010-11 to 18 percent in 2015. 11.5 PRESENCE OF IODISED SALT IN HOUSEHOLDS Poor iodine intake results in a series of abnormalities characterized as iodine deficiency disorders (IDD). Iodine deficiency disorders present as goitre, hypothyroidism, and impaired mental and physical development. Food rich in iodine is the only source of iodine for humans. Salt iodisation is recognized as the most sustainable approach to ensure iodine availability in the diet. In 1989, Zimbabwe recognised IDD as a public health problem and regulated the fortification of all household salt with potassium iodate at 25- 55 mg/kg. Fortification to this level ensures a range of 15-35 ppm of iodine at consumption, assuming about 40 percent loss during production and cooking. Globally, it is recommended that the proportion of households using adequately iodized salt of at least 15 ppm be above 90 percent. The 2015 ZDHS tested household salt for the presence of potassium iodate using MBI rapid salt test kits that rely on colour change to detect the presence iodine. Overall, salt was tested in 77 percent of households (Table 11.9). Among households in which salt was tested, 95 percent had iodised salt. It should be noted that household salt was tested for the presence or absence of iodine only; the iodine content in the salt was not measured. Trends: The proportion of households consuming iodised salt in 2010-11 (94 percent) is nearly identical to what is observed in 2015 (95 percent). Patterns by background characteristics:  The proportion of households with iodised salt across all provinces varies little, and in all instances meets the recommended target (above 90 percent of households are using iodised salt). 11.6 ADULTS’ NUTRITIONAL STATUS 11.6.1 Nutritional Status of Women The 2015 ZDHS collected anthropometric data on height and weight for 94 percent of women age 15-49 interviewed in the survey. These data were used to calculate several measures of nutritional status, specifically maternal height and body mass index (BMI). Maternal height is an outcome of nutrition during childhood and adolescence. Small stature is associated with small pelvis size, and thus maternal height is useful in predicting risk of difficult delivery. The risk of low birthweight babies is also higher for short women (defined as less than 145 cm). BMI is used to classify adults as underweight, normal weight, overweight, or obese. Elevated BMI is associate with an increased incidence of morbidity and mortality. 196 • Nutrition of Children and Adults Body mass index (BMI) BMI is calculated by dividing weight in kilograms by height in metres squared (kg/m2). A BMI of less than 18.5 indicates that the respondents are too thin for their height (that is, that they have a chronic energy deficiency). At the other end of the BMI scale, women and men are considered overweight if their BMI falls between 25.0 and 29.9 and are obese if their BMI is greater than or equal to 30.0. Sample: Women age 15-49 who are not pregnant and who have not had a birth in the 2 months before the survey and men age 15-49 Table 11.10.1 shows that 35 percent of women age 15-49 in Zimbabwe are overweight or obese. Six percent of women are thin, and 59 percent have a BMI in the normal range. One percent of women are shorter than 145 cm. Trends: The percentage of women who are thin (indicative of undernutrition) has remained fairly constant over the last two decades, peaking at 9 percent in 2005-06 (Figure 11.9). In contrast, the proportion of women who are overweight or obese (indicative of overnutrition) has gradually increased from 23 percent in 1994 to 35 percent in 2015. Patterns by background characteristics  The proportion of overweight or obese women increases with age, ranging from 13 percent among women age 15-19 to 54 percent among women age 40-49.  Matebeleland South and Matebeleland North have the highest proportion of thin women (12 and 11 percent, respectively).  Women living in urban areas were much more likely to be overweight or obese when compared with their rural counterparts (46 percent and 28 percent, respectively). Nearly half the women in Bulawayo and Harare are overweight or obese (46 and 48 percent, respectively).  Overweight and obesity increases with wealth and generally with education. For example, 19 percent of women in the lowest wealth quintile are overweight or obese compared with 50 percent of women in the highest wealth quintile. Figure 11.9 Trends in nutritional status among women 5 6 9 7 6 23 27 25 31 35 1994 1999 2005-06 2010-11 2015 Percentage of women age 15-49 Underweight Overweight/obese Nutrition of Children and Adults • 197 11.6.2 Nutritional Status of Men The ZDHS collected anthropometric data on height and weight for 89 percent of men age 15-49 interviewed in the survey. Overall, 75 percent of men age 15-49 have a BMI in the normal range, 13 percent are thin, and 12 percent are overweight or obese (Table 11.10.2). Trends: The percentage of men age 15-49 who are thin has declined in the last 5 years from 15 percent in 2010-11 to 13 percent in 2015, while percentage who are overweight or obese has increased from 9 percent in 2010-11 to 12 percent in 2015 (Figure 11.10). Patterns by background characteristics  The proportion of men who are thin (BMI below 18.5) is highest among those age 15-19 years (31 percent).  Men from Harare province (7 percent) are less likely to be thin compared with men from other provinces (12-20 percent).  Overweight and obesity increases with age, ranging from 1 percent among men age 15-49 to 24 percent among men age 40-49.  The prevalence of overweight or obesity is higher among urban men than rural men (21 percent and 7 percent, respectively). Similar to the pattern observed for women, overweight and obesity increase with education and wealth. 11.7 ANAEMIA PREVALENCE IN ADULTS Anaemia is a multi-factorial disorder caused primarily by iron deficiency and infections including helminths, malaria, tuberculosis, and HIV. Iron deficiency anaemia contributes to maternal mortality, foetal growth retardation, and perinatal mortality. Women are at greater risk of iron deficiency than men due to monthly loss of iron-rich blood during menstruation. Anaemia among women and men was measured using similar procedures used for testing children age 6- 59 months, except that capillary blood was collected exclusively from a finger prick. Haemoglobin levels were successfully measured for 90 percent of women and 84 percent of men who were interviewed. Anaemia results are adjusted for pregnancy status, altitude, and smoking status. Figure 11.10 Trends in nutritional status among men 15 13 9 12 2010-11 2015 Percentage of men age 15-49 Underweight Overweight/obese 198 • Nutrition of Children and Adults Anaemia prevalence Any anaemia is defined as a blood haemoglobin level below 11.0 g/dL in pregnant women; below 12.0 g/dL in nonpregnant women; and below 13.0 g/dL for men. The cutoffs are adjusted for altitude for enumeration areas above 1,000 metres and for cigarette smoking for women and men. Sample: Women age 15-49 and men age 15-49 Over one-quarter (27 percent) of women in Zimbabwe are anaemic (Table 11.11.1). Twenty percent of women are classified as mildly anaemic, 6 percent are moderately anaemic, and 1 percent are severely anaemic. Fifteen percent of men age 15-49 are anaemic (Table 11.11.2). Trends: Anaemia prevalence for women dropped from 38 percent in 2005-06 to 28 percent in 2010-11 and to 27 percent in 2015 (Figure 11.11). Among men, the prevalence of any anaemia dropped from 22 percent in 2005-06 to 14 percent in 2010-11; however, between 2010-11 and 2015, the prevalence of anaemia in men has changed little (14 percent and 15 percent, respectively). Patterns by background characteristics  Among adults age 15-49, the prevalence of anaemia is higher among women age than men (27 percent versus15 percent).  Anaemia prevalence is highest in women and men in Matebeleland South (43 and 25 percent, respectively).  Women living in urban areas are slightly more likely to be anaemic their counterparts in rural areas (29 percent and 26 percent, respectively). In contrast, men in rural areas are more likely to be anaemic than their counterparts in urban areas (17 percent and 11 percent, respectively). 11.8 MATERNAL IRON AND FOLATE SUPPLEMENTATION Improving iron and folate nutrition influences safe motherhood and birth outcomes. Pregnant women should take daily oral iron and folic acid supplementation for at least 90 days, and eat an iron-rich diet to reduce the risk of low birth weight, maternal anaemia, and iron deficiency. The 2015 ZDHS included questions to ascertain whether mothers received iron and folic acid (IFA) supplements during pregnancy. Eighty-three percent of women who gave birth in the 5 years before the survey took IFA supplements, and 3 percent of women took deworming medication during the pregnancy for their last birth. Forty percent of women took IFA supplements for 90 days or more, as recommended; and 17 percent did not take iron supplements (Table 11.12). Table 11.13 shows that 95 percent of women with a birth in the last 5 years live in households with iodised salt. Trends: There has been a remarkable increase in the proportion of pregnant women taking iron supplements for at least 90 days; in both 2005-06 and 2010-11, only 5 percent of women reported taking Figure 11.11 Trends in anaemia status among women 27 20 20 9 7 6 1 1 1 2005-06 2010-11 2015 Percentage of women age 15-49 38 2728 Mild Moderate Severe Nutrition of Children and Adults • 199 iron tablets for 90 or more days during the pregnancy of their last birth in the past 5 years compared with 40 percent in 20151. Patterns by background characteristics  A greater percentage of rural women (44 percent) took IFA supplements for 90 or more days during their last pregnancy compared with urban women (30 percent).  Harare (19 percent) has the lowest proportion of women taking IFA supplements for at least 90 days and Mashonaland Central (55 percent) has the highest. LIST OF TABLES For more information on nutrition of children and adults, see the following tables:  Table 11.1 Nutritional status of children  Table 11.2 Initial breastfeeding  Table 11.3 Breastfeeding status according to age  Table 11.4 Median duration of breastfeeding  Table 11.5 Foods and liquids consumed by children in the day or night preceding the interview  Table 11.6 Infant and young child feeding (IYCF) practices  Table 11.7 Prevalence of anaemia in children  Table 11.8 Micronutrient intake among children  Table 11.9 Presence of iodised salt in household  Table 11.10.1 Nutritional status of women  Table 11.10.2 Nutritional status of men  Table 11.11.1 Prevalence of anaemia in women  Table 11.11.2 Prevalence of anaemia in men  Table 11.12 Micronutrient intake among mothers  Table 11.13 Mothers living in households with iodised salt 1 Note that the 2005-06 ZDHS and the 2010-11 ZDHS asked respondents about taking iron supplements during their last pregnancy in the past 5 years rather than iron and folic acid supplements. 20 0 • N ut rit io n of C hi ld re n an d A du lts Ta bl e 11 .1 N ut ri tio na l s ta tu s of c hi ld re n P er ce nt ag e of c hi ld re n un de r ag e 5 c la ss ifi ed a s m al no ur is he d ac co rd in g to t hr ee a nt hr op om et ric i nd ic es o f nu tri tio na l s ta tu s: h ei gh t- fo r- ag e, w ei gh t-f or -h ei gh t, an d w ei gh t-f or -a ge , ac co rd in g to b ac kg ro un d ch ar ac te ris tic s, Zi m ba bw e 20 15 H ei gh t-f or -a ge 1 W ei gh t-f or -h ei gh t W ei gh t-f or -a ge B ac kg ro un d ch ar ac te ris tic P er ce nt ag e be lo w -3 S D P er ce nt ag e be lo w -2 S D 2 M ea n Z- sc or e (S D ) N um be r o f ch ild re n P er ce nt ag e be lo w -3 S D P er ce nt ag e be lo w -2 S D 2 P er ce nt ag e ab ov e +2 S D M ea n Z- sc or e (S D ) N um be r o f ch ild re n P er ce nt ag e be lo w -3 S D P er ce nt ag e be lo w -2 S D 2 P er ce nt ag e ab ov e +2 S D M ea n Z- sc or e (S D ) N um be r o f ch ild re n A ge in m on th s <6 6. 4 17 .0 -0 .6 55 8 1. 9 4. 7 18 .8 0. 6 54 1 0. 8 4. 1 5. 1 0. 0 56 9 6- 8 6. 1 13 .0 -0 .5 27 5 0. 8 5. 0 8. 0 0. 2 27 2 1. 4 7. 5 4. 1 -0 .2 27 8 9- 11 4. 0 15 .1 -0 .8 26 8 1. 4 9. 5 4. 6 -0 .0 26 8 0. 8 11 .2 2. 3 -0 .4 26 9 12 -1 7 8. 7 28 .0 -1 .1 60 8 2. 5 6. 4 4. 5 -0 .0 60 2 1. 3 12 .1 1. 9 -0 .6 61 6 18 -2 3 14 .8 37 .3 -1 .6 60 4 1. 7 4. 2 6. 5 0. 2 60 2 3. 1 12 .4 1. 7 -0 .7 60 7 24 -3 5 14 .4 38 .7 -1 .7 1, 27 9 0. 3 1. 7 5. 1 0. 4 1, 26 9 2. 0 9. 2 1. 7 -0 .6 1, 28 7 36 -4 7 8. 0 28 .5 -1 .4 1, 34 4 0. 9 1. 9 3. 4 0. 2 1, 33 5 1. 4 7. 2 0. 7 -0 .7 1, 35 0 48 -5 9 4. 6 17 .8 -1 .1 1, 37 1 0. 5 1. 7 2. 8 0. 0 1, 36 6 1. 1 6. 5 0. 5 -0 .7 1, 37 5 S ex M al e 10 .5 29 .6 -1 .3 3, 12 5 1. 2 3. 2 6. 1 0. 2 3, 10 1 1. 8 8. 6 1. 7 -0 .6 3, 15 6 Fe m al e 7. 3 24 .0 -1 .2 3, 18 0 0. 8 3. 2 5. 1 0. 2 3, 15 4 1. 3 8. 1 1. 6 -0 .5 3, 19 6 B ir th in te rv al in m on th s3 Fi rs t b irt h4 7. 9 24 .3 -1 .2 1, 22 5 0. 6 3. 7 6. 7 0. 2 1, 21 8 1. 1 8. 4 2. 2 -0 .5 1, 23 8 <2 4 11 .6 27 .3 -1 .3 37 5 1. 8 2. 6 5. 3 0. 2 37 2 0. 7 7. 7 0. 9 -0 .6 37 8 24 -4 7 9. 5 31 .9 -1 .4 1, 81 7 1. 2 3. 1 6. 2 0. 2 1, 79 7 1. 9 8. 7 1. 7 -0 .6 1, 83 4 48 + 6. 0 21 .3 -1 .0 1, 70 2 1. 2 4. 2 5. 1 0. 2 1, 68 6 1. 3 7. 2 1. 5 -0 .5 1, 70 8 S iz e at b ir th 3 V er y sm al l 18 .6 45 .8 -1 .9 19 9 2. 5 7. 7 3. 8 -0 .2 19 8 5. 6 23 .1 0. 7 -1 .2 20 4 S m al l 11 .3 37 .1 -1 .6 56 3 1. 2 4. 1 3. 2 -0 .1 55 8 1. 6 14 .3 0. 4 -0 .9 56 2 A ve ra ge o r l ar ge r 7. 2 23 .9 -1 .1 4, 34 2 1. 0 3. 3 6. 3 0. 2 4, 30 3 1. 2 6. 6 2. 0 -0 .5 4, 37 7 D on ’t K no w * * * 14 * * * * 14 * * * * 15 M ot he r’ s in te rv ie w s ta tu s In te rv ie w ed 8. 1 26 .2 -1 .2 5, 11 9 1. 1 3. 6 5. 9 0. 2 5, 07 4 1. 4 8. 1 1. 7 -0 .5 5, 15 9 N ot in te rv ie w ed b ut in h ou se ho ld 6. 3 25 .1 -1 .1 17 8 1. 0 2. 8 3. 6 0. 3 17 7 0. 6 5. 4 2. 1 -0 .4 17 9 N ot in te rv ie w ed a nd n ot in th e ho us eh ol d5 13 .2 29 .8 -1 .4 1, 00 8 0. 6 1. 3 4. 5 0. 2 1, 00 4 2. 2 10 .3 1. 3 -0 .7 1, 01 4 M ot he r’ s nu tr iti on al s ta tu s6 Th in (B M I < 18 .5 ) 10 .9 32 .0 -1 .3 19 3 3. 1 10 .2 1. 6 -0 .5 19 1 4. 0 20 .4 1. 2 -1 .1 19 9 N or m al (B M I 1 8. 5- 24 .9 ) 8. 1 27 .5 -1 .3 2, 87 1 1. 2 3. 8 4. 2 0. 1 2, 85 0 1. 6 9. 2 1. 7 -0 .7 2, 89 8 O ve rw ei gh t/o be se (B M I ≥ 25 ) 6. 3 22 .0 -1 .1 1, 60 0 0. 7 2. 3 7. 2 0. 4 1, 58 4 0. 8 4. 7 1. 6 -0 .3 1, 60 4 C on tin ue d… N ut rit io n of C hi ld re n an d A du lts • 2 01 Ta bl e 11 .1 — C o n ti n u e d H ei gh t-f or -a ge 1 W ei gh t-f or -h ei gh t W ei gh t-f or -a ge B ac kg ro un d ch ar ac te ris tic P er ce nt ag e be lo w -3 S D P er ce nt ag e be lo w -2 S D 2 M ea n Z- sc or e (S D ) N um be r o f ch ild re n P er ce nt ag e be lo w -3 S D P er ce nt ag e be lo w -2 S D 2 P er ce nt ag e ab ov e +2 S D M ea n Z- sc or e (S D ) N um be r o f ch ild re n P er ce nt ag e be lo w -3 S D P er ce nt ag e be lo w -2 S D 2 P er ce nt ag e ab ov e +2 S D M ea n Z- sc or e (S D ) N um be r o f ch ild re n R es id en ce U rb an 7. 2 22 .1 -1 .1 1, 71 6 0. 8 2. 4 7. 6 0. 4 1, 69 8 0. 6 6. 0 1. 8 -0 .3 1, 72 8 R ur al 9. 5 28 .5 -1 .3 4, 58 9 1. 1 3. 5 4. 9 0. 1 4, 55 7 1. 9 9. 2 1. 6 -0 .6 4, 62 5 P ro vi nc e M an ic al an d 9. 9 30 .3 -1 .4 99 7 0. 9 2. 4 5. 0 0. 2 99 2 1. 8 8. 6 1. 0 -0 .6 1, 00 4 M as ho na la nd C en tra l 8. 5 28 .7 -1 .4 59 7 0. 9 2. 8 3. 1 0. 1 59 3 1. 2 7. 3 0. 6 -0 .7 60 3 M as ho na la nd E as t 6. 8 24 .5 -1 .2 59 2 1. 2 3. 7 4. 2 0. 1 58 6 0. 5 7. 9 2. 4 -0 .5 59 2 M as ho na la nd W es t 9. 6 27 .7 -1 .3 79 2 1. 1 4. 0 5. 6 0. 1 78 6 2. 1 9. 9 0. 5 -0 .7 79 3 M at ab el el an d N or th 6. 6 23 .5 -1 .1 32 4 1. 7 5. 0 3. 6 0. 0 32 1 1. 7 9. 7 1. 1 -0 .6 32 5 M at ab el el an d S ou th 13 .0 31 .1 -1 .3 29 6 1. 1 3. 7 6. 1 0. 1 29 2 2. 6 13 .5 2. 4 -0 .7 30 0 M id la nd s 10 .5 27 .4 -1 .1 85 9 1. 7 4. 8 6. 5 0. 2 85 5 2. 4 9. 4 3. 0 -0 .5 86 7 M as vi ng o 7. 8 26 .8 -1 .2 81 6 0. 7 2. 8 5. 8 0. 2 81 1 1. 7 7. 5 2. 3 -0 .5 82 7 H ar ar e 8. 2 23 .0 -1 .2 78 0 0. 4 1. 0 8. 4 0. 5 76 7 0. 7 6. 1 1. 8 -0 .3 78 6 B ul aw ay o 6. 5 18 .8 -0 .9 25 3 0. 5 2. 2 6. 5 0. 3 25 1 0. 0 4. 6 1. 9 -0 .3 25 4 M ot he r’ s ed uc at io n7 N o ed uc at io n 11 .5 45 .3 -1 .6 82 0. 0 2. 7 2. 7 -0 .1 78 1. 4 12 .7 4. 4 -0 .7 82 P rim ar y 9. 5 31 .0 -1 .4 1, 69 9 1. 3 4. 6 4. 9 0. 1 1, 69 0 2. 0 9. 8 1. 6 -0 .7 1, 71 3 S ec on da ry 7. 7 24 .6 -1 .2 3, 24 7 1. 1 3. 0 6. 1 0. 2 3, 21 6 1. 2 7. 4 1. 5 -0 .5 3, 27 1 M or e th an s ec on da ry 1. 8 8. 7 -0 .6 26 7 0. 2 3. 1 9. 1 0. 5 26 4 0. 2 2. 4 4. 8 0. 1 27 0 M is si ng * * * 2 * * * * 2 * * * * 2 W ea lth q ui nt ile Lo w es t 11 .0 33 .0 -1 .4 1, 51 3 1. 4 4. 1 5. 1 0. 1 1, 50 0 2. 4 10 .7 1. 7 -0 .7 1, 52 0 S ec on d 9. 5 28 .8 -1 .3 1, 33 9 1. 3 3. 9 4. 9 0. 1 1, 33 0 2. 3 9. 0 2. 0 -0 .7 1, 35 3 M id dl e 8. 0 25 .4 -1 .2 1, 18 9 1. 0 2. 8 4. 8 0. 1 1, 18 2 1. 3 7. 7 1. 0 -0 .6 1, 20 0 Fo ur th 8. 8 26 .3 -1 .2 1, 29 5 0. 8 2. 9 6. 4 0. 3 1, 28 0 0. 8 7. 8 1. 4 -0 .5 1, 30 2 H ig he st 5. 8 16 .6 -0 .9 97 0 0. 4 1. 6 7. 2 0. 4 96 3 0. 5 5. 2 2. 3 -0 .2 97 7 To ta l 8. 9 26 .8 -1 .2 6, 30 5 1. 0 3. 2 5. 6 0. 2 6, 25 5 1. 5 8. 4 1. 7 -0 .6 6, 35 2 N ot es : E ac h of t he in di ce s is e xp re ss ed in s ta nd ar d de vi at io n un its ( S D ) fro m t he m ed ia n of t he W H O C hi ld G ro w th S ta nd ar ds . A n as te ris k in di ca te s th at a f ig ur e is b as ed o n fe w er t ha n 25 u nw ei gh te d ca se s an d ha s be en su pp re ss ed . 1 R ec um be nt le ng th is m ea su re d fo r c hi ld re n un de r a ge 2 ; s ta nd in g he ig ht is m ea su re d fo r a ll ot he r c hi ld re n. 2 In cl ud es c hi ld re n w ho a re b el ow - 3 st an da rd d ev ia tio ns (S D ) f ro m th e W H O C hi ld G ro w th S ta nd ar ds p op ul at io n m ed ia n 3 E xc lu de s ch ild re n w ho se m ot he rs w er e no t i nt er vi ew ed 4 Fi rs t-b or n tw in s (tr ip le ts , e tc .) ar e co un te d as fi rs t b irt hs b ec au se th ey d o no t h av e a pr ev io us b irt h in te rv al . 5 In cl ud es c hi ld re n w ho se m ot he rs a re d ec ea se d 6 E xc lu de s ch ild re n w ho se m ot he rs w er e no t w ei gh ed a nd m ea su re d, c hi ld re n w ho se m ot he rs w er e no t i nt er vi ew ed , a nd c hi ld re n w ho se m ot he rs a re p re gn an t o r g av e bi rth w ith in th e pr ec ed in g 2 m on th s. M ot he r’s n ut rit io na l s ta tu s in te rm s of B M I ( B od y M as s In de x) is p re se nt ed in T ab le 1 1. 10 .1 . 7 Fo r w om en w ho a re n ot in te rv ie w ed , i nf or m at io n is ta ke n fro m th e H ou se ho ld Q ue st io nn ai re . E xc lu de s ch ild re n w ho se m ot he rs a re n ot li st ed in th e H ou se ho ld Q ue st io nn ai re . 202 • Nutrition of Children and Adults Table 11.2 Initial breastfeeding Among last-born children who were born in the 2 years preceding the survey, the percentage who were ever breastfed, and the percentages who started breastfeeding within one hour and within one day of birth; and among last-born children born in the 2 years preceding the survey who were ever breastfed, the percentage who received a prelacteal feed, according to background characteristics, Zimbabwe 2015 Among last-born children born in the past 2 years: Among last-born children born in the past 2 years who were ever breastfed: Background characteristic Percentage ever breastfed Percentage who started breastfeeding within 1 hour of birth Percentage who started breastfeeding within 1 day of birth1 Number of last-born children Percentage who received a prelacteal feed2 Number of last-born children ever breastfed Sex Male 97.7 56.7 92.0 1,242 11.2 1,214 Female 98.6 58.6 94.5 1,212 13.9 1,194 Assistance at delivery Health professional3 98.3 61.1 95.0 2,007 10.6 1,973 Traditional birth attendant 96.6 37.9 79.4 153 33.3 148 Other 97.6 42.9 88.2 244 17.0 238 No one (97.4) (52.0) (89.3) 50 (6.8) 49 Place of delivery Health facility 98.4 61.0 94.9 1,987 10.5 1,954 At home 97.2 43.9 85.3 397 22.1 386 Other 97.3 40.9 90.9 70 16.8 68 Residence Urban 97.6 54.1 90.8 689 13.4 672 Rural 98.4 59.0 94.2 1,765 12.2 1,736 Province Manicaland 96.7 43.4 90.0 396 15.5 384 Mashonaland Central 99.8 60.1 94.2 246 12.1 246 Mashonaland East 98.0 56.1 93.7 244 16.7 239 Mashonaland West 98.5 56.8 93.3 298 15.2 294 Matabeleland North 99.3 75.8 96.5 117 4.0 116 Matabeleland South 96.6 80.6 95.3 99 4.2 96 Midlands 98.9 66.5 94.6 338 14.4 334 Masvingo 98.3 59.4 95.7 299 7.5 294 Harare 97.7 51.9 92.0 324 11.5 316 Bulawayo 97.2 52.5 87.5 92 15.0 89 Mother’s education No education * * * 32 * 32 Primary 97.6 59.8 92.2 787 14.3 768 Secondary 98.4 56.5 94.1 1,534 11.3 1,510 More than secondary 97.1 57.8 89.6 101 16.3 98 Wealth quintile Lowest 98.5 60.1 93.4 610 11.8 600 Second 98.1 57.5 93.7 504 12.3 494 Middle 98.6 58.9 95.3 441 14.4 435 Fourth 98.2 56.9 93.8 550 12.7 540 Highest 97.1 52.9 88.6 349 11.7 339 Total 98.1 57.6 93.2 2,454 12.6 2,408 Notes: Table is based on last-born children born in the 2 years preceding the survey regardless of whether the children are living or dead at the time of interview. Figures in parentheses are based on 25-49 unweighted cases. An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. 1 Includes children who started breastfeeding within one hour of birth 2 Children given something other than breast milk during the first 3 days of life. 3 Doctor, nurse, or nurse midwife Nutrition of Children and Adults • 203 Table 11.3 Breastfeeding status according to age Percent distribution of youngest children under age 2 who are living with their mother, by breastfeeding status and the percentage currently breastfeeding; and the percentage of all children under age 2 using a bottle with a nipple, according to age in months, Zimbabwe 2015 Breastfeeding status Total Percentage currently breast- feeding Number of youngest child under age 2 living with their mother Percentage using a bottle with a nipple Number of all children under age 2 Age of child in months Not breast- feeding Exclusively breast- feeding Breast- feeding and consuming plain water only Breast- feeding and consuming non-milk liquids1 Breast- feeding and consuming other milk Breast- feeding and consuming comple- mentary foods 0-1 2.4 74.2 14.1 0.0 1.1 8.1 100.0 97.6 203 4.3 211 2-3 1.9 46.1 21.9 1.0 1.2 27.8 100.0 98.1 228 6.4 230 4-5 0.6 19.8 26.6 1.7 0.8 50.5 100.0 99.4 181 10.8 185 6-8 1.7 2.9 5.1 0.6 0.0 89.7 100.0 98.3 283 14.1 289 9-11 4.8 0.0 4.4 0.4 0.7 89.6 100.0 95.2 276 8.7 284 12-17 17.3 0.8 1.2 0.8 0.0 79.9 100.0 82.7 609 8.2 629 18-23 77.3 0.0 0.5 0.0 0.0 22.2 100.0 22.7 532 4.8 587 0-3 2.2 59.4 18.2 0.5 1.2 18.5 100.0 97.8 431 5.4 441 0-5 1.7 47.7 20.7 0.9 1.1 28.0 100.0 98.3 612 7.0 625 6-9 1.9 2.1 5.1 0.4 0.4 90.0 100.0 98.1 390 13.7 399 12-15 8.9 1.2 1.8 1.0 0.0 87.1 100.0 91.1 410 7.0 422 12-23 45.3 0.4 0.9 0.4 0.0 53.0 100.0 54.7 1,141 6.5 1,216 20-23 85.8 0.0 0.7 0.0 0.0 13.5 100.0 14.2 346 3.8 384 Note: Breastfeeding status refers to a “24-hour” period (yesterday and last night). Children who are classified as breastfeeding and consuming plain water only consumed no liquid or solid supplements. The categories of not breastfeeding, exclusively breastfeeding, breastfeeding and consuming plain water, non-milk liquids, other milk, and complementary foods (solids and semi-solids) are hierarchical and mutually exclusive, and their percentages add to 100 percent. Thus children who receive breast milk and non-milk liquids and who do not receive other milk and who do not receive complementary foods are classified in the non-milk liquid category even though they may also drink plain water. Any children who receive complementary food are classified in that category as long as they are breastfeeding as well. 1 Non-milk liquids include juice, juice drinks, clear broth, or other liquids. 204 • Nutrition of Children and Adults Table 11.4 Median duration of breastfeeding Median duration of any breastfeeding, exclusive breastfeeding, and predominant breastfeeding among children born in the 3 years preceding the survey, according to background characteristics, Zimbabwe 2015 Median duration (months) of breastfeeding among children born in the past 3 years1 Background characteristic Any breast- feeding Exclusive breastfeeding Predominant breastfeeding2 Sex Male 16.9 2.3 3.6 Female 17.8 2.2 4.0 Residence Urban 16.0 1.9 3.5 Rural 18.0 2.4 4.0 Province Manicaland 18.3 (1.8) 3.9 Mashonaland Central 18.2 * 4.0 Mashonaland East 17.3 * 3.3 Mashonaland West 16.6 (2.3) 4.6 Matabeleland North 18.8 (3.1) (4.3) Matabeleland South (15.0) 3.7 4.1 Midlands 16.9 2.9 3.7 Masvingo 18.5 3.0 4.1 Harare 15.9 * 2.9 Bulawayo (17.6) * (3.6) Mother’s education No education * * * Primary 18.2 2.6 3.6 Secondary 17.1 2.3 4.1 More than secondary * a * Wealth quintile Lowest 18.3 (2.3) 3.8 Second 18.3 2.8 4.4 Middle 17.6 (2.2) 4.1 Fourth 16.5 2.0 3.9 Highest 15.5 (2.2) 3.0 Total 17.3 2.3 3.8 Mean for all children 17.3 3.5 5.0 Notes: Median and mean durations are based on the distributions at the time of the survey of the proportion of births by months since birth. Includes children living and deceased at the time of the survey. 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. a = omitted because less than 50 percent of the children in this group were exclusively or predominantly breastfeeding 1 It is assumed that non-last-born children and last-born children not currently living with the mother are not currently breastfeeding. 2 Either exclusively breastfed or received breast milk and plain water, and/or non-milk liquids only N ut rit io n of C hi ld re n an d A du lts • 2 05 Ta bl e 11 .5 Fo od s an d liq ui ds c on su m ed b y ch ild re n in th e da y or n ig ht p re ce di ng th e in te rv ie w P er ce nt ag e of y ou ng es t c hi ld re n un de r a ge 2 w ho a re li vi ng w ith th e m ot he r b y ty pe o f f oo ds c on su m ed in th e da y or n ig ht p re ce di ng th e in te rv ie w , a cc or di ng to b re as tfe ed in g st at us a nd a ge , Z im ba bw e 20 15 Li qu id s S ol id o r s em i-s ol id fo od s A ny s ol id o r se m i-s ol id fo od N um be r o f ch ild re n un de r a ge 2 A ge o f c hi ld in m on th s In fa nt fo rm ul a O th er m ilk 1 O th er liq ui ds 2 Fo rti fie d ba by fo od s Fo od m ad e fro m g ra in s3 Fr ui ts a nd ve ge ta bl es ric h in vi ta m in A 4 O th er fr ui ts an d ve ge - ta bl es Fo od m ad e fro m ro ot s an d tu be rs Fo od m ad e fro m le gu m es an d nu ts M ea t, fis h, po ul try E gg s C he es e, yo gu rt, o th er m ilk p ro du ct In se ct s B R E A S TF E E D IN G C H IL D R E N 0- 1 1. 2 1. 5 0. 6 1. 8 3. 8 0. 9 0. 6 0. 0 0. 0 0. 0 0. 0 0. 4 0. 9 8. 4 19 7 2- 3 4. 1 0. 5 2. 1 8. 9 19 .1 1. 1 0. 8 0. 0 0. 0 0. 8 0. 0 0. 2 0. 0 28 .4 22 3 4- 5 1. 9 0. 9 7. 4 9. 5 40 .1 4. 4 1. 3 4. 6 3. 1 4. 5 1. 2 4. 1 0. 4 50 .8 18 0 6- 8 2. 7 3. 5 40 .7 20 .4 83 .2 29 .0 15 .6 9. 8 10 .1 17 .0 6. 3 13 .7 0. 0 91 .2 27 8 9- 11 2. 7 3. 3 49 .3 12 .0 90 .8 42 .0 21 .4 12 .9 14 .6 28 .1 10 .1 10 .1 1. 2 94 .2 26 2 12 -1 7 0. 5 4. 7 58 .3 7. 7 93 .3 69 .4 26 .9 14 .8 20 .3 47 .4 18 .6 16 .4 2. 3 96 .7 50 3 18 -2 3 0. 0 6. 9 55 .2 4. 9 87 .7 63 .1 36 .5 15 .0 18 .9 53 .1 20 .8 16 .6 5. 3 97 .6 12 1 6- 23 1. 4 4. 3 51 .8 11 .4 89 .7 52 .9 24 .0 13 .2 16 .4 36 .4 14 .0 14 .4 1. 8 94 .9 1, 16 5 To ta l 1. 8 3. 2 35 .2 9. 8 66 .1 35 .6 16 .1 9. 2 11 .2 24 .6 9. 3 9. 9 1. 3 72 .3 1, 76 7 N O N B R E A S TF E E D IN G C H IL D R E N 0- 11 (2 8. 5) (2 1. 4) (3 2. 9) (1 5. 2) (6 0. 8) (3 7. 9) (1 7. 1) (1 9. 5) (2 6. 4) (1 4. 5) (1 4. 5) (1 2. 3) (0 .0 ) (6 2. 9) 28 12 -1 7 3. 2 17 .6 68 .8 15 .6 95 .2 63 .6 32 .5 21 .2 33 .3 66 .7 18 .5 24 .6 1. 1 99 .7 10 5 18 -2 3 0. 2 9. 2 63 .1 7. 1 95 .4 78 .4 36 .1 21 .5 27 .4 56 .9 21 .9 19 .7 0. 9 98 .3 41 1 6- 23 1. 9 11 .7 63 .8 9. 4 95 .1 74 .9 35 .1 21 .7 29 .1 57 .7 21 .3 20 .7 0. 9 98 .4 53 5 To ta l 2. 3 11 .5 62 .6 9. 2 93 .6 73 .5 34 .4 21 .3 28 .5 56 .6 20 .9 20 .3 0. 9 96 .7 54 5 N ot es : B re as tfe ed in g st at us a nd fo od c on su m ed re fe r t o a “2 4- ho ur ” p er io d (y es te rd ay a nd la st n ig ht ). Fi gu re s in p ar en th es es a re b as ed o n 25 -4 9 un w ei gh te d ca se s. 1 O th er m ilk in cl ud es fr es h, ti nn ed , a nd p ow de re d co w o r o th er a ni m al m ilk . 2 D oe s no t i nc lu de p la in w at er . I nc lu de s ju ic e, ju ic e dr in ks , c le ar b ro th , o r o th er n on -m ilk li qu id s. 3 In cl ud es fo rti fie d ba by fo od 4 In cl ud es p um pk in ; o ra ng e or y el lo w y am s; b ut te rn ut o r o th er s qu as h; c ar ro ts ; d ar k gr ee n le af y ve ge ta bl es s uc h as s pi na ch , c ov o, p um pk in le av es , c as sa va le av es , o kr a le av es , o r n ye vh e; m an go es , p aw p aw , m az ja nj e, m at un du ru , o r m as aw u; a nd o th er lo ca lly g ro w n fru its a nd v eg et ab le s th at a re ri ch in v ita m in A . 20 6 • N ut rit io n of C hi ld re n an d A du lts Ta bl e 11 .6 In fa nt a nd y ou ng c hi ld fe ed in g (IY C F) p ra ct ic es P er ce nt ag e of y ou ng es t c hi ld re n ag e 6- 23 m on th s liv in g w ith th ei r m ot he r w ho a re fe d ac co rd in g to th re e IY C F fe ed in g pr ac tic es b as ed o n br ea st fe ed in g st at us , n um be r of fo od g ro up s, a nd ti m es th ey a re fe d du rin g th e da y or n ig ht p re ce di ng th e su rv ey , a cc or di ng to b ac kg ro un d ch ar ac te ris tic s, Z im ba bw e 20 15 A m on g br ea st fe d ch ild re n ag e 6- 23 m on th s, pe rc en ta ge fe d: N um be r o f br ea st fe d ch ild re n 6- 23 m on th s A m on g no n- br ea st fe d ch ild re n ag e 6- 23 m on th s, pe rc en ta ge fe d: N um be r o f no n- br ea st fe d ch ild re n 6- 23 m on th s A m on g al l c hi ld re n ag e 6- 23 m on th s, pe rc en ta ge fe d: N um be r o f a ll ch ild re n 6- 23 m on th s B ac kg ro un d ch ar ac te ris tic 4+ fo od gr ou ps 1 M in im um m ea l fre qu en cy 2 B ot h 4+ fo od gr ou ps a nd m in im um m ea l fre qu en cy M ilk o r m ilk pr od uc ts 3 4+ fo od gr ou ps 1 M in im um m ea l fre qu en cy 4 W ith 3 IY C F pr ac tic es 5 B re as t m ilk , m ilk , o r m ilk pr od uc ts 6 4+ fo od gr ou ps 1 M in im um m ea l fre qu en cy 7 W ith 3 IY C F pr ac tic es A ge in m on th s 6- 8 13 .6 51 .4 7. 9 27 8 * * * * 5 99 .1 13 .8 51 .3 8. 0 28 3 9- 11 14 .6 29 .6 5. 9 26 2 * * * * 13 97 .0 16 .7 30 .4 6. 6 27 6 12 -1 7 29 .7 36 .7 11 .6 50 3 14 .0 52 .8 29 .7 3. 0 10 5 85 .1 33 .7 35 .5 10 .1 60 9 18 -2 3 31 .4 39 .4 19 .7 12 1 7. 3 37 .3 23 .2 2. 5 41 1 28 .4 36 .0 26 .8 6. 4 53 2 S ex M al e 23 .4 35 .0 9. 0 58 0 8. 9 42 .6 26 .3 2. 2 28 0 70 .4 29 .6 32 .2 6. 8 86 0 Fe m al e 21 .9 42 .7 11 .5 58 4 10 .7 38 .8 24 .1 4. 2 25 5 72 .9 27 .0 37 .1 9. 3 83 9 R es id en ce U rb an 37 .3 42 .2 17 .4 28 0 17 .4 59 .0 35 .4 7. 5 18 8 66 .8 46 .0 39 .5 13 .4 46 9 R ur al 18 .0 37 .8 8. 0 88 5 5. 6 30 .8 19 .7 0. 8 34 6 73 .5 21 .6 32 .7 6. 0 1, 23 1 P ro vi nc e M an ic al an d 14 .8 50 .9 7. 7 19 6 2. 2 22 .3 12 .5 0. 0 74 73 .2 16 .9 40 .4 5. 6 27 0 M as ho na la nd C en tra l 23 .7 25 .6 8. 4 12 5 6. 6 47 .9 25 .7 1. 3 52 72 .4 30 .8 25 .7 6. 3 17 8 M as ho na la nd E as t 26 .1 25 .1 7. 5 12 0 2. 1 31 .7 9. 1 0. 8 54 69 .6 27 .8 20 .1 5. 4 17 5 M as ho na la nd W es t 11 .3 32 .1 5. 7 13 1 5. 5 30 .2 15 .9 1. 0 74 65 .7 18 .2 26 .2 4. 0 20 5 M at ab el el an d N or th 16 .0 53 .1 13 .6 66 (8 .7 ) (2 7. 2) (2 8. 5) (0 .0 ) 17 81 .3 18 .3 48 .0 10 .8 83 M at ab el el an d S ou th 7. 2 71 .0 5. 8 38 23 .0 25 .1 42 .1 4. 3 26 68 .6 14 .5 59 .2 5. 2 64 M id la nd s 24 .0 35 .2 7. 5 16 1 13 .3 35 .9 31 .1 5. 4 75 72 .6 27 .8 33 .9 6. 8 23 6 M as vi ng o 23 .0 35 .7 9. 1 15 5 (1 1. 2) (4 9. 3) (3 6. 9) (4 .4 ) 54 77 .1 29 .8 36 .0 7. 9 20 9 H ar ar e 42 .3 37 .1 21 .5 13 3 15 .8 67 .8 29 .4 6. 3 89 66 .2 52 .5 34 .0 15 .4 22 2 B ul aw ay o 37 .9 65 .5 29 .2 39 (2 2. 3) (6 2. 4) (5 5. 9) (9 .8 ) 18 75 .3 45 .7 62 .4 23 .1 57 M ot he r’ s ed uc at io n N o ed uc at io n * * * 19 * * * * 5 * * * * 24 P rim ar y 16 .1 31 .6 5. 9 41 3 6. 5 29 .9 15 .2 1. 6 14 8 75 .4 19 .8 27 .3 4. 8 56 2 S ec on da ry 25 .8 41 .8 12 .2 69 6 9. 6 42 .0 26 .9 2. 5 35 0 69 .7 31 .3 36 .8 8. 9 1, 04 7 M or e th an s ec on da ry (4 4. 0) (7 1. 1) (2 8. 4) 36 (2 8. 5) (7 6. 3) (5 9. 2) (1 8. 5) 31 67 .1 58 .8 65 .7 23 .8 67 W ea lth q ui nt ile Lo w es t 13 .3 32 .7 3. 4 32 5 3. 4 27 .9 12 .3 0. 0 12 0 74 .0 17 .2 27 .2 2. 5 44 4 S ec on d 17 .6 36 .1 7. 5 25 2 10 .2 24 .2 20 .9 0. 1 95 75 .4 19 .4 31 .9 5. 5 34 6 M id dl e 20 .6 40 .9 10 .8 20 8 5. 6 32 .6 25 .5 2. 3 93 70 .8 24 .3 36 .2 8. 2 30 0 Fo ur th 29 .6 42 .8 13 .6 23 3 9. 2 48 .3 24 .4 3. 7 13 1 67 .3 36 .4 36 .1 10 .1 36 4 H ig he st 43 .6 48 .4 24 .0 14 8 21 .9 70 .5 46 .5 10 .1 96 69 .2 54 .2 47 .7 18 .5 24 4 To ta l 22 .6 38 .9 10 .3 1, 16 5 9. 7 40 .8 25 .2 3. 1 53 5 71 .6 28 .3 34 .6 8. 0 1, 69 9 N ot es : F ig ur es in p ar en th es es a re b as ed o n 25 -4 9 un w ei gh te d ca se s. A n as te ris k in di ca te s th at a fi gu re is b as ed o n fe w er th an 2 5 un w ei gh te d ca se s an d ha s be en s up pr es se d. 1 Fo od g ro up s: a . i nf an t f or m ul a, m ilk o th er th an b re as t m ilk , c he es e or y og ur t o r o th er m ilk p ro du ct s; b . f oo ds m ad e fro m g ra in s, r oo ts , a nd tu be rs , i nc lu di ng p or rid ge a nd fo rti fie d ba by fo od fr om g ra in s; c . v ita m in A -r ic h fru its a nd v eg et ab le s; d . o th er fru its a nd v eg et ab le s; e . e gg s; f. m ea t, po ul try , f is h, a nd s he llf is h (a nd o rg an m ea ts ); g. le gu m es a nd n ut s. 2 Fo r b re as tfe d ch ild re n, m in im um m ea l f re qu en cy is re ce iv in g so lid o r s em i-s ol id fo od a t l ea st tw ic e a da y fo r i nf an ts 6 -8 m on th s an d at le as t t hr ee ti m es a d ay fo r c hi ld re n 9- 23 m on th s. 3 In cl ud es tw o or m or e fe ed in gs o f c om m er ci al in fa nt fo rm ul a, fr es h, ti nn ed , a nd p ow de re d an im al m ilk , a nd y og ur t. 4 Fo r n on br ea st fe d ch ild re n ag e 6- 23 m on th s, m in im um m ea l f re qu en cy is re ce iv in g so lid o r s em i-s ol id fo od o r m ilk fe ed s at le as t f ou r t im es a d ay . 5 N on br ea st fe d ch ild re n ag e 6- 23 m on th s ar e co ns id er ed to b e fe d w ith a m in im um s ta nd ar d of th re e In fa nt a nd Y ou ng C hi ld F ee di ng P ra ct ic es (I Y C F) if th ey re ce iv e ot he r m ilk o r m ilk p ro du ct s at le as t t w ic e a da y, re ce iv e th e m in im um m ea l f re qu en cy , an d re ce iv e so lid o r s em i-s ol id fo od s fro m a t l ea st fo ur fo od g ro up s no t i nc lu di ng th e m ilk o r m ilk p ro du ct s fo od g ro up . 6 B re as tfe ed in g, o r n ot b re as tfe ed in g an d re ce iv in g tw o or m or e fe ed in gs o f c om m er ci al in fa nt fo rm ul a, fr es h, ti nn ed a nd p ow de re d an im al m ilk , a nd y og ur t. 7 C hi ld re n ar e fe d th e m in im um re co m m en de d nu m be r o f t im es p er d ay a cc or di ng to th ei r a ge a nd b re as tfe ed in g st at us a s de sc rib ed in fo ot no te s 2 an d 4. Nutrition of Children and Adults • 207 Table 11.7 Prevalence of anaemia in children Percentage of children age 6-59 months classified as having anaemia, according to background characteristics, Zimbabwe 2015 Anaemia status by haemoglobin level Number of children Background characteristic Any anaemia (<11.0 g/dL) Mild anaemia (10.0-10.9 g/dL) Moderate anaemia (7.0-9.9 g/dL) Severe anaemia (<7.0 g/dL) Age in months 6-8 66.1 35.2 29.4 1.5 240 9-11 58.8 31.8 26.6 0.4 243 12-17 56.4 27.4 28.0 1.0 567 18-23 49.3 25.6 22.9 0.8 563 24-35 36.6 22.8 13.4 0.4 1,206 36-47 28.2 18.7 9.3 0.2 1,248 48-59 21.7 15.8 5.9 0.0 1,308 Sex Male 37.6 22.0 15.1 0.5 2,692 Female 35.9 21.8 13.8 0.3 2,684 Mother’s interview status Interviewed 38.2 22.4 15.4 0.5 4,273 Not interviewed but in household 34.5 17.9 16.7 0.0 146 Not interviewed and not in the household1 30.5 20.3 10.0 0.1 957 Residence Urban 37.5 20.1 16.7 0.6 1,440 Rural 36.5 22.5 13.6 0.4 3,936 Province Manicaland 39.5 25.7 13.3 0.5 784 Mashonaland Central 33.6 18.0 15.1 0.4 523 Mashonaland East 36.4 22.5 13.4 0.5 500 Mashonaland West 38.0 23.3 14.8 0.0 681 Matabeleland North 38.2 23.0 14.7 0.6 294 Matabeleland South 39.2 24.1 15.1 0.0 270 Midlands 37.5 22.7 14.3 0.4 728 Masvingo 29.2 17.7 10.8 0.6 720 Harare 41.9 21.1 20.1 0.6 657 Bulawayo 33.6 20.5 12.3 0.8 219 Mother’s education2 No education 31.0 16.8 14.2 0.0 72 Primary 38.8 23.4 14.9 0.5 1,415 Secondary 38.5 21.9 16.1 0.5 2,723 More than secondary 31.4 20.2 11.0 0.3 207 Missing * * * * 2 Wealth quintile Lowest 39.9 25.4 14.0 0.6 1,292 Second 32.4 19.3 12.6 0.6 1,149 Middle 36.4 22.6 13.8 0.0 1,037 Fourth 39.1 21.3 17.5 0.3 1,104 Highest 35.0 19.9 14.5 0.6 794 Total 36.8 21.9 14.5 0.4 5,376 Notes: Table is based on children who stayed in the household on the night before the interview and who were tested for anaemia. Prevalence of anaemia, based on haemoglobin levels, is adjusted for altitude using formulas in CDC, 1998. Haemoglobin in grams per decilitre (g/dL). An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. 1 Includes children whose mothers are deceased 2 For women who are not interviewed, information is taken from the Household Questionnaire. Excludes children whose mothers are not listed in the Household Questionnaire. 208 • Nutrition of Children and Adults Table 11.8 Micronutrient intake among children Among youngest children age 6-23 months who are living with their mother, the percentages who consumed vitamin A-rich and iron-rich foods in the 24 hours preceding the survey; among all children 6-59 months, the percentages who were given vitamin A supplements in the 6 months preceding the survey, and who were given deworming medication in the 6 months preceding the survey, and among all children age 6-59 months who live in households in which salt was tested for iodine, the percentage who live in households with iodised salt, according to background characteristics, Zimbabwe 2015 Among youngest children age 6-23 months living with the mother: Among all children age 6-59 months: Among children age 6-59 months living in households in which salt was tested: Background characteristic Percentage who consumed foods rich in vitamin A in past 24 hours1 Percentage who consumed foods rich in iron in past 24 hours2 Number of children Percentage given vitamin A supplements in past 6 months3 Percentage given deworming medication in past 6 months3,4 Number of children Percentage living in households with iodised salt5 Number of children Age in months 6-8 38.8 19.7 283 62.4 6.3 289 95.8 227 9-11 58.0 32.6 276 81.0 8.5 284 92.6 216 12-17 85.0 56.6 609 80.8 14.0 629 96.3 485 18-23 82.6 56.0 532 80.8 19.9 587 95.3 462 24-35 na na na 70.1 17.8 1,191 94.3 962 36-47 na na na 59.4 20.1 1,223 94.5 950 48-59 na na na 56.7 22.0 1,228 94.0 980 Sex Male 72.7 48.6 860 68.2 17.1 2,647 95.2 2,078 Female 71.6 44.1 839 66.3 18.7 2,783 94.0 2,204 Breastfeeding status Breastfeeding 67.1 41.6 1,165 76.8 11.2 1,204 95.5 931 Not breastfeeding 83.3 56.8 535 64.5 19.9 4,226 94.3 3,351 Mother’s age 15-19 69.7 41.0 183 74.8 14.7 269 94.5 189 20-29 72.3 47.7 909 68.0 17.6 2,751 94.7 2,168 30-39 74.1 46.6 532 66.1 18.1 2,032 94.5 1,616 40-49 64.2 41.2 75 61.9 21.9 378 94.4 309 Residence Urban 75.2 64.2 469 66.0 18.9 1,756 94.4 1,470 Rural 71.1 39.6 1,231 67.8 17.5 3,674 94.7 2,812 Province Manicaland 76.7 40.8 270 66.5 20.7 794 93.0 581 Mashonaland Central 77.0 42.7 178 67.5 27.7 532 93.0 434 Mashonaland East 65.7 39.4 175 75.8 19.6 521 98.2 476 Mashonaland West 73.6 46.6 205 67.8 22.2 698 96.0 521 Matabeleland North 58.9 34.0 83 73.7 9.7 247 96.7 221 Matabeleland South 51.1 28.3 64 60.9 2.1 201 93.1 148 Midlands 72.9 46.9 236 60.2 15.2 731 94.1 618 Masvingo 73.6 46.0 209 68.0 12.3 655 93.1 456 Harare 75.2 66.4 222 64.3 19.1 828 94.1 712 Bulawayo 73.9 64.6 57 76.9 12.7 223 97.1 114 Mother’s education No education * * 24 65.0 11.5 62 (91.1) 51 Primary 68.9 36.6 562 62.9 17.1 1,713 95.2 1,353 Secondary 73.7 50.4 1,047 69.5 18.3 3,349 94.7 2,635 More than secondary 79.3 74.6 67 66.5 20.0 306 90.9 243 Wealth quintile Lowest 73.2 34.9 444 61.3 12.3 1,246 93.8 984 Second 68.3 34.9 346 68.4 17.5 1,046 96.6 791 Middle 70.2 44.4 300 71.8 20.8 899 93.4 654 Fourth 72.7 57.6 364 67.0 20.4 1,277 95.4 1,053 Highest 77.6 69.0 244 69.6 19.9 962 93.5 799 Total 72.2 46.4 1,699 67.2 18.0 5,430 94.6 4,282 Notes: Information on vitamin A is based on both mother’s recall and the immunization card (where available). Information on iron supplements and deworming medication is based on the mother’s recall. Figures in parentheses are based on 25-49 unweighted cases. An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. na = Not applicable 1 Includes meat (and organ meat), fish, poultry, eggs, pumpkin, red or yellow yams or squash, carrots, red sweet potatoes, dark green leafy vegetables, mango, papaya, and other locally grown fruits and vegetables that are rich in vitamin A. 2 Includes meat (including organ meat), fish, poultry, and eggs 3 Based on mother's recall 4 Deworming for intestinal parasites is commonly done for helminths and for schistosomiasis. 5 Excludes children in households in which salt was not tested Nutrition of Children and Adults • 209 Table 11.9 Presence of iodised salt in household Among all households, the percentage with salt tested for iodine content and the percentage with no salt in the household; and among households with salt tested, the percentage with iodised salt, according to background characteristics, Zimbabwe 2015 Among all households, the percentage Among households with tested salt: Background characteristic With salt tested With no salt in the household Salt not tested Number of households Percentage with iodised salt Number of households Residence Urban 80.2 1.3 18.5 3,531 94.4 2,831 Rural 74.6 1.4 23.9 7,003 95.3 5,225 Province Manicaland 71.6 1.3 27.1 1,484 93.8 1,062 Mashonaland Central 82.0 2.0 16.1 952 93.8 781 Mashonaland East 89.9 0.9 9.2 1,171 97.0 1,053 Mashonaland West 70.5 0.6 28.9 1,209 97.3 852 Matabeleland North 89.8 2.9 7.3 527 95.9 473 Matabeleland South 66.1 3.3 30.6 530 94.0 350 Midlands 80.9 1.4 17.7 1,271 95.0 1,028 Masvingo 67.8 0.9 31.3 1,244 94.6 844 Harare 83.4 1.9 14.7 1,604 93.7 1,337 Bulawayo 50.8 0.2 49.1 542 95.7 275 Wealth quintile Lowest 78.1 2.2 19.7 1,996 95.0 1,558 Second 73.5 1.6 24.9 1,983 96.0 1,458 Middle 70.7 1.0 28.3 2,000 94.8 1,414 Fourth 78.8 1.5 19.6 2,398 95.1 1,890 Highest 80.4 0.8 18.8 2,158 94.3 1,736 Total 76.5 1.4 22.1 10,534 95.0 8,056 210 • Nutrition of Children and Adults Table 11.10.1 Nutritional status of women Among women age 15-49, the percentage with height under 145 cm, mean Body Mass Index (BMI), and the percentage with specific BMI levels, according to background characteristics, Zimbabwe 2015 Height Body Mass Index1 Mean Body Mass Index (BMI) Normal Thin Overweight/obese Number of women Background characteristic Percentage below 145 cm Number of women 18.5-24.9 (Total normal) <18.5 (Total thin) 17.0-18.4 (Mildly thin) <17 (Mode- rately and severely thin) ≥25.0 (Total over- weight or obese) 25.0-29.9 (Over- weight) ≥30.0 (Obese) Age 15-19 1.4 2,149 21.8 74.2 12.5 10.0 2.4 13.3 11.5 1.8 2,011 20-29 0.6 3,276 23.8 66.0 4.6 3.9 0.7 29.4 20.8 8.6 2,901 30-39 0.3 2,766 25.7 48.8 4.1 3.1 1.0 47.1 28.3 18.8 2,542 40-49 0.7 1,502 26.5 42.6 3.6 2.8 0.8 53.8 29.6 24.3 1,473 Residence Urban 0.5 3,650 25.7 49.6 4.1 3.4 0.6 46.4 26.3 20.1 3,415 Rural 0.8 6,043 23.5 65.0 7.3 5.8 1.5 27.7 19.8 7.9 5,511 Province Manicaland 1.5 1,251 24.2 64.7 4.3 3.1 1.2 31.1 20.9 10.2 1,131 Mashonaland Central 0.4 872 23.7 66.4 4.9 4.2 0.7 28.8 20.2 8.6 775 Mashonaland East 0.5 928 24.0 57.1 9.8 7.8 2.0 33.1 22.5 10.7 865 Mashonaland West 0.5 1,137 23.8 60.6 7.9 6.5 1.4 31.6 20.4 11.2 1,041 Matabeleland North 1.7 460 23.2 60.6 11.3 9.2 2.1 28.1 19.3 8.8 427 Matabeleland South 1.6 405 23.4 59.6 11.5 8.2 3.3 28.9 19.8 9.1 372 Midlands 0.6 1,224 24.0 61.1 7.1 5.7 1.5 31.8 21.5 10.3 1,126 Masvingo 0.3 1,157 24.0 64.9 3.8 3.0 0.8 31.3 20.9 10.4 1,076 Harare 0.6 1,701 25.8 49.1 3.0 2.8 0.2 47.9 27.8 20.1 1,587 Bulawayo 0.5 557 25.9 49.4 5.0 4.3 0.7 45.6 23.9 21.6 527 Education No education 2.7 120 23.8 61.6 6.0 1.6 4.4 32.4 23.2 9.2 113 Primary 1.2 2,525 23.5 65.4 6.7 5.5 1.2 27.9 20.0 8.0 2,294 Secondary 0.6 6,356 24.3 58.7 6.2 5.0 1.2 35.2 22.6 12.5 5,861 More than secondary 0.0 692 27.1 40.5 2.7 2.5 0.2 56.8 27.5 29.4 658 Wealth quintile Lowest 1.3 1,673 22.6 72.4 8.3 6.6 1.6 19.3 16.0 3.4 1,512 Second 0.6 1,672 23.1 67.5 8.2 6.0 2.2 24.4 18.1 6.3 1,503 Middle 0.8 1,732 23.7 61.6 7.7 6.1 1.6 30.7 21.8 8.9 1,610 Fourth 0.6 2,227 25.0 54.2 4.8 4.4 0.4 41.0 26.0 15.0 2,038 Highest 0.4 2,389 26.3 47.3 3.1 2.5 0.6 49.7 26.4 23.3 2,263 Total 0.7 9,693 24.3 59.1 6.0 4.9 1.2 34.9 22.3 12.6 8,926 Note: The Body Mass Index (BMI) is expressed as the ratio of weight in kilograms to the square of height in meters (kg/m2). 1 Excludes pregnant women and women with a birth in the preceding 2 months Nutrition of Children and Adults • 211 Table 11.10.2 Nutritional status of men Among men age 15-49, mean Body Mass Index (BMI), and the percentage with specific BMI levels, according to background characteristics, Zimbabwe 2015 Body Mass Index Mean Body Mass Index (BMI) Normal Thin Overweight/obese Number of men Background characteristic 18.5-24.9 (Total normal) <18.5 (Total thin) 17.0-18.4 (Mildly thin) <17 (Mode- rately and severely thin) ≥25.0 (Total over- weight or obese) 25.0-29.9 (Over- weight) ≥30.0 (Obese) Age 15-19 19.7 68.0 30.7 19.4 11.3 1.4 1.2 0.2 2,069 20-29 21.6 86.1 6.1 5.4 0.7 7.7 6.7 1.0 2,385 30-39 22.6 73.1 6.8 5.8 1.1 20.0 16.2 3.8 1,935 40-49 22.9 67.6 8.0 6.3 1.7 24.4 18.8 5.6 1,333 Residence Urban 22.6 69.7 9.4 7.2 2.3 20.9 16.0 4.9 2,683 Rural 21.0 77.5 15.2 10.6 4.6 7.3 6.3 0.9 5,038 Province Manicaland 21.4 79.6 11.7 8.4 3.2 8.8 7.2 1.6 1,050 Mashonaland Central 21.0 79.0 14.1 10.3 3.8 6.9 6.2 0.8 786 Mashonaland East 21.1 76.9 14.8 10.8 4.0 8.3 7.1 1.2 771 Mashonaland West 21.2 73.1 17.3 12.0 5.2 9.7 8.1 1.5 967 Matabeleland North 20.8 74.2 18.1 11.3 6.7 7.7 6.4 1.3 357 Matabeleland South 20.9 71.8 19.5 12.2 7.3 8.7 6.8 1.9 316 Midlands 21.6 73.2 14.1 9.7 4.4 12.7 10.9 1.9 934 Masvingo 21.8 74.9 11.7 8.7 3.0 13.4 11.0 2.4 821 Harare 22.6 72.6 7.3 5.9 1.4 20.1 15.1 4.9 1,327 Bulawayo 22.1 67.9 14.0 9.6 4.4 18.1 13.6 4.5 392 Education No education (21.3) (83.1) (14.6) (14.6) (0.0) (2.3) (2.3) (0.0) 38 Primary 20.7 77.9 17.4 12.2 5.2 4.7 4.5 0.2 1,758 Secondary 21.5 76.3 12.7 9.0 3.7 10.9 9.1 1.9 5,143 More than secondary 24.2 57.5 6.8 5.4 1.4 35.7 25.8 10.0 782 Wealth quintile Lowest 20.7 78.8 16.7 11.9 4.8 4.5 4.3 0.2 1,186 Second 20.8 80.4 15.3 10.4 4.9 4.3 3.7 0.6 1,411 Middle 20.8 76.7 17.1 11.8 5.3 6.1 5.5 0.6 1,530 Fourth 21.9 76.7 9.7 7.5 2.2 13.7 11.4 2.3 1,769 Highest 23.1 64.4 9.5 6.9 2.6 26.1 19.6 6.4 1,824 Total 15-49 21.6 74.8 13.2 9.4 3.8 12.0 9.7 2.3 7,721 50-54 22.8 65.0 9.9 7.6 2.3 25.1 18.9 6.2 341 Total 15-54 21.6 74.4 13.1 9.3 3.7 12.5 10.1 2.5 8,062 Note: The Body Mass Index (BMI) is expressed as the ratio of weight in kilograms to the square of height in meters (kg/m2). Figures in parentheses are based on 25-49 unweighted cases. 212 • Nutrition of Children and Adults Table 11.11.1 Prevalence of anaemia in women Percentage of women age 15-49 with anaemia, by background characteristics, Zimbabwe 2015 Anaemia status by haemoglobin level Number of women Background characteristic Any Mild Moderate Severe Not pregnant <12.0 g/dL 10.0-11.9 g/dL 7.0-9.9 g/dL <7.0 g/dL Pregnant <11.0 g/dL 10.0-10.9 g/dL 7.0-9.9 g/dL <7.0 g/dL Age 15-19 26.5 20.5 5.5 0.4 2,061 20-29 25.6 19.3 6.0 0.4 3,124 30-39 26.9 20.4 5.9 0.6 2,625 40-49 29.5 20.8 7.7 1.0 1,425 Number of children ever born 0 28.9 20.8 7.4 0.8 2,448 1 28.0 20.7 6.8 0.6 1,473 2-3 25.3 19.8 5.1 0.4 3,196 4-5 25.1 19.2 5.5 0.5 1,592 6+ 27.7 20.8 6.1 0.7 527 Maternity status Pregnant 33.1 18.5 14.2 0.4 579 Breastfeeding 23.3 19.1 3.8 0.5 1,636 Neither 27.1 20.5 6.0 0.6 7,020 Using IUD Yes (32.9) (23.3) (7.2) (2.3) 37 No 26.8 20.1 6.1 0.5 9,199 Smoking status Smokes cigarettes/ tobacco (35.2) (18.4) (16.9) (0.0) 29 Does not smoke 26.8 20.1 6.1 0.6 9,206 Residence Urban 28.7 20.4 7.8 0.4 3,465 Rural 25.6 19.9 5.1 0.6 5,770 Province Manicaland 21.7 17.9 3.3 0.5 1,151 Mashonaland Central 23.5 18.5 4.1 0.8 848 Mashonaland East 22.3 16.5 5.0 0.8 867 Mashonaland West 25.9 20.1 5.4 0.4 1,073 Matabeleland North 25.9 18.5 6.4 1.0 452 Matabeleland South 43.1 30.7 10.4 2.0 400 Midlands 31.2 23.3 7.5 0.4 1,177 Masvingo 23.1 17.5 5.5 0.1 1,125 Harare 29.9 21.4 8.3 0.2 1,597 Bulawayo 29.4 21.5 6.8 1.0 545 Education No education 23.4 20.0 3.4 0.0 117 Primary 28.4 21.9 5.7 0.8 2,378 Secondary 26.0 19.4 6.2 0.5 6,099 More than secondary 28.4 20.2 7.7 0.5 642 Wealth quintile Lowest 27.1 21.6 5.0 0.5 1,596 Second 23.0 17.4 4.9 0.7 1,589 Middle 26.7 20.8 5.4 0.6 1,662 Fourth 28.6 21.0 7.1 0.5 2,141 Highest 27.6 19.7 7.4 0.5 2,248 Total 26.8 20.1 6.1 0.5 9,235 Notes: Figures in parentheses are based on 25-49 unweighted cases. Prevalence is adjusted for altitude and for smoking status if known using formulas in CDC, 1998. Nutrition of Children and Adults • 213 Table 11.11.2 Prevalence of anaemia in men Percentage of men age 15-49 with anaemia, by background characteristics, Zimbabwe 2015 Background characteristic Any anaemia <13.0 g/dL Number of men Age 15-19 20.4 1,977 20-29 11.3 2,247 30-39 10.9 1,826 40-49 17.3 1,225 Smoking status Smokes cigarettes/ tobacco 15.3 1,318 Does not smoke 14.5 5,957 Residence Urban 10.9 2,508 Rural 16.6 4,767 Province Manicaland 11.4 952 Mashonaland Central 13.3 760 Mashonaland East 12.9 707 Mashonaland West 14.6 909 Matabeleland North 19.0 348 Matabeleland South 25.3 314 Midlands 22.8 894 Masvingo 14.8 775 Harare 10.9 1,236 Bulawayo 8.9 381 Education No education (20.7) 36 Primary 19.4 1,674 Secondary 14.2 4,842 More than secondary 6.6 722 Wealth quintile Lowest 19.0 1,136 Second 15.9 1,330 Middle 17.2 1,446 Fourth 12.8 1,669 Highest 10.5 1,694 Total 15-49 14.6 7,275 50-54 20.1 331 Total 15-54 14.9 7,606 Notes: Prevalence is adjusted for altitude and for smoking status, if known, using formulas in CDC, 1998. Figures in parentheses are based on 25-49 unweighted cases. 214 • Nutrition of Children and Adults Table 11.12 Micronutrient intake among mothers Among women age 15-49 with a child born in the 5 years preceding the survey, the percentage who took deworming medication during the pregnancy of last child; the percentage who took iron tablets during the pregnancy of last child, and the percent distribution by number of days they took iron tablets during the pregnancy of the last child, according to background characteristics, Zimbabwe 2015 Background characteristic Among women with a child born on the past 5 years: Number of women Percentage of women who took deworming medication during pregnancy of last birth Percentage of women who took iron tablets during pregnancy of last birth Number of days women took iron and folic acid (IFA) tablets during pregnancy of last birth None <60 60-89 90+ Don’t know Total Age 15-19 4.0 90.6 9.4 24.6 13.9 51.0 1.1 100.0 369 20-29 3.5 83.7 16.1 30.7 9.4 41.3 2.4 100.0 2,429 30-39 3.1 82.5 17.5 34.1 10.1 35.6 2.7 100.0 1,815 40-49 3.2 77.3 22.7 27.9 8.4 37.6 3.5 100.0 374 Residence Urban 2.2 82.6 17.4 41.4 7.7 30.1 3.5 100.0 1,637 Rural 3.9 83.7 16.3 26.3 11.0 44.4 2.0 100.0 3,351 Province Manicaland 4.5 80.1 19.6 29.3 7.1 40.5 3.5 100.0 709 Mashonaland Central 5.1 84.5 15.5 19.2 9.9 55.2 0.2 100.0 492 Mashonaland East 3.3 85.0 15.0 22.0 13.3 45.9 3.8 100.0 473 Mashonaland West 3.0 84.5 15.5 30.6 12.4 39.8 1.7 100.0 638 Matabeleland North 1.9 81.2 18.8 28.8 5.8 43.9 2.7 100.0 234 Matabeleland South 1.0 86.5 13.5 39.5 6.3 38.1 2.5 100.0 200 Midlands 2.0 85.7 14.3 34.8 14.3 35.9 0.7 100.0 678 Masvingo 7.6 85.2 14.8 23.2 10.7 47.9 3.4 100.0 583 Harare 1.4 79.3 20.7 49.6 6.2 19.1 4.4 100.0 762 Bulawayo 0.3 85.2 14.6 29.1 9.8 46.3 0.3 100.0 220 Education No education (4.0) (83.8) (16.2) (26.4) (11.7) (42.9) (2.8) (100.0) 57 Primary 3.7 80.6 19.4 26.8 9.8 42.3 1.7 100.0 1,530 Secondary 3.3 84.5 15.4 32.8 9.9 39.1 2.7 100.0 3,125 More than secondary 2.5 85.0 14.8 39.2 10.7 30.4 4.9 100.0 275 Wealth quintile Lowest 4.5 81.9 18.1 24.5 11.3 44.2 1.9 100.0 1,082 Second 3.0 84.0 16.0 26.4 11.1 44.7 1.8 100.0 956 Middle 3.9 85.7 14.0 27.5 10.4 46.2 1.9 100.0 860 Fourth 2.7 81.0 19.0 36.9 7.8 32.7 3.6 100.0 1,183 Highest 2.8 85.0 14.9 40.7 9.4 31.9 3.1 100.0 908 Total 3.4 83.3 16.6 31.3 9.9 39.7 2.5 100.0 4,988 Note: Figures in parentheses are based on 25-49 unweighted cases. 1 In the first 2 months after delivery of last birth Nutrition of Children and Adults • 215 Table 11.13 Mothers living in households with iodised salt Among women age 15-49 with a child born in the 5 years preceding the survey and who live in households that were tested for iodised salt, the percentage who live in households with iodised salt, according to background characteristics, Zimbabwe 2015 Among women with a child born in the past 5 years, who live in households in which salt was tested: Background characteristic Percentage living in households with iodised salt1 Number of women Age 15-19 95.2 271 20-29 94.7 1,901 30-39 94.4 1,443 40-49 95.1 301 Residence Urban 94.8 1,348 Rural 94.6 2,567 Province Manicaland 92.8 522 Mashonaland Central 92.5 404 Mashonaland East 97.6 436 Mashonaland West 96.3 470 Matabeleland North 96.5 213 Matabeleland South 93.5 146 Midlands 94.7 568 Masvingo 93.2 403 Harare 94.7 646 Bulawayo 95.7 106 Education No education (92.5) 47 Primary 94.7 1,212 Secondary 94.9 2,441 More than secondary 92.5 215 Wealth quintile Lowest 93.7 861 Second 96.3 731 Middle 93.6 620 Fourth 95.9 953 Highest 93.6 750 Total 94.7 3,915 Note: Figures in parentheses are based on 25-49 unweighted cases. 1 Excludes women in households where salt was not tested. Malaria • 217 MALARIA 12 Key Findings  Net possession: Insecticide-treated net (ITN) ownership by households increased from 9 percent in 2006-06 to 25 percent in 2010-11 and 48 percent in 2015.  Indoor residual spraying: Twenty-one percent of households reported that they had received indoor residual spraying during the past 12 months.  Net utilization: There was a general decrease in net use by children under age 5 and pregnant women in households that possess at least one ITN. Use by children under age 5 decreased from 30 percent in 2010- 11 to 18 percent in 2015; use by pregnant women decreased from 30 percent to 13 percent during the same period.  Treatment of children with fever: Fourteen percent of the children under age 5 had fever in the two weeks preceding the survey. Advice and treatment were sought for 50 percent of children who had fever; 13 percent had blood taken from heel or finger for testing. alaria is one of the leading causes of morbidity and mortality in sub-Saharan Africa. In Zimbabwe, malaria transmission is generally seasonal, starting in November and lasting until the end of May, with a peak between March and May. Malaria is a common cause of hospital admissions for all age groups in moderate to high transmission areas during the peak transmission period. In recent years, the burden of malaria has been reduced significantly in the central parts of the country, with most of the burden remaining in the border districts. There are areas in the country with no malaria transmission. Figure 12.1 graphically displays the annual Figure 12.1 Malaria Annual Parasite Incidence (API), Zimbabwe 2015 Source: WHO 2016 M 218 • Malaria parasite incidence (API1) in 2015. Malaria prevention and control interventions are deployed only in areas with malaria transmission. This factor should be taken into account when reviewing the data on malaria indicators described in this chapter, because they relate to the prevalence of fever and treatment among children reported to have had fever in the two weeks before the survey. The 2015 ZDHS obtained data on topics related to malaria prevention and treatment, such as household mosquito net ownership, use of mosquito nets by children and pregnant women, , and the prevalence and treatment of fever among children under age 5. The survey also obtained information on the use of indoor residual spraying (IRS). 12.1 MOSQUITO NETS AND INDOOR RESIDUAL SPRAYING Insecticide-treated nets (ITN) are one of the integrated vector control management tools recommended for the prevention and control of malaria in Zimbabwe. Since 2010, Zimbabwe has distributed long- lasting insecticidal nets (LLIN) exclusively, and distribution has focused only on districts with moderate to high malaria transmission. The mass distribution strategy targets one net per sleeping space. Figure 12.2 details the areas of the 2013 net distribution campaign. 12.1.1 Ownership of Insecticide-Treated Nets All households in the 2015 ZDHS were asked whether they owned any mosquito nets and, if so, how many they owned and what type. Ownership of insecticide-treated nets Households that have at least one insecticide-treated net (ITN). An ITN is defined as: (1) a factory-treated net that does not require any further treatment (long-lasting insecticidal net or LLIN) or (2) a net that has been soaked with insecticide within the past 12 months. In Zimbabwe, all ITNs are LLINs. Sample: Households Full household ITN coverage Percentage of households with at least one ITN for every two people. Sample: Households Table 12.1 presents the percentage of households with at least one mosquito net (treated or untreated), and insecticide-treated net (ITN)/long-lasting insecticidal net (LLIN); average number of nets and ITNs/LLINs 1 The API is defined as the number of confirmed cases of malaria during one year divided by the population under surveillance times 1,000. Figure 12.2 2013 LLIN Coverage Source: NMCP 2013 Malaria • 219 per household; and the percentage of households with at least one net and one ITN/LLIN per two persons who stayed in the household the previous night, by background characteristics and by state. Figure 12.3 presents differentials in ITN household ownership for the background characteristics. Sixty-one percent of households have at least one mosquito net, and 48 percent have at least one ITN. Because all ITNs in Zimbabwe are LLINs, this means that 48 percent of households have at least one LLIN. (Most mosquito net indicators focus on ITNs not LLINs, and prior to 2010, not all ITNs in Zimbabwe were LLINs. For the sake of simplicity, the remainder of this chapter will use the term ITN only.) The average number of ITNs per household is 0.9. Thirty-three percent of households have at least one net for every two persons in the household, and 26 percent of households have achieved full household ITN coverage, meaning that they have an ITN for every two persons. Trends: Figure 12.3 shows trend data for ITN ownership from the 2005-06 ZDHS, 2010-11 ZDHS and 2015 ZDHS surveys. Household ITN ownership has substantially increased during the past ten years from only 9 percent in 2005-06 to 29 percent in 2010-11 and 48 percent in 2015. Patterns by background characteristics  Rural households (63 percent) are more likely than urban households (56 percent) to have a mosquito net (treated or untreated). More than half of rural households own at least one ITN (56 percent), compared with one-third of urban households (32 percent).  Household ownership of at least one ITN varies from a low of 17 percent of households in Harare (non-malaria transmission area) to a high of 71 percent in Matabeleland North (Figure 12.4).  More than half of households in the lowest, second, and middle wealth quintiles own at least one ITN, compared with about four in ten households in the fourth and highest wealth quintiles. 12.1.2 Access to Insecticide-Treated Nets (ITNs) Access to an ITN Percentage of the population that could sleep under an ITN if each ITN in the household were used by up to two people. Sample: De facto household population The access indicator for ITNs is considered an indication of typical net usage, and is a key indicator of the effectiveness of Zimbabwe’s malaria programme. Table 12.2 shows the percent distribution of the de facto Figure 12.3 Trends in ownership of ITNs Figure 12.4 Differentials in household ownership of ITNs 9 11 7 29 23 32 48 32 56 Total Urban Rural Percentage of households owning at least one insecticide-treated net (ITN) 2005-06 2010-11 2015 38 38 59 55 53 30 17 55 47 40 71 67 53 49 57 32 56 48 Highest Fourth Middle Second Lowest WEALTH QUINTILE Bulawayo Harare Masvingo Midlands Matabeleland South Matabeleland North Mashonaland West Mashonaland East Mashonaland Central Manicaland PROVINCE Urban Rural RESIDENCE Total 220 • Malaria household population (the individuals who are listed in the household schedule, including usual members and visitors who slept in the household the night before the interview) by the number of ITNs the household owns, and the percentage with access to an ITN, according to the number of persons who stayed in the household the night before the survey. Nationally, 37 percent of the de facto population had access to an ITN. Although ownership of ITNs increases as household size increases, access to an ITN generally decreases as household size increases. For example, 45 percent of the household population in which two people stayed in the household the night before the survey have access to an ITN compared with 33 percent of the household population in which eight or more people stayed in the household. Figure 12.5 shows data for the percentage of the de facto household population with access to an ITN, by residence, province, and wealth quintile. 12.1.3 Source of Mosquito Nets During the survey, several questions were asked separately about each mosquito net owned by the household. For each mosquito net, the respondent for the Household Questionnaire was asked where the net was obtained. There are several ways to procure or obtain a mosquito net in Zimbabwe. Individuals may obtain nets from a government health facility, during mass distribution campaigns, ANC and immunisation visits; and nets can be purchased directly through various sources. The percent distribution of nets by source, according to background characteristics, is shown in Table 12.3. Over one-third of the 12,306 mosquito nets found in households were obtained from a government health facility (37 percent), and 22 percent through mass net distribution campaigns. Other sources of nets include shops or markets (15 percent), immunisation visits (7 percent), and ANC visits (5 percent). One percent of the nets were obtained from private health facility, 1 percent from schools, and 1 percent from community health workers. Patterns by background characteristics  In rural areas, 24 percent of nets are obtained through mass distribution campaigns, 46 percent from government health facilities, and only 5 percent from a shop or market. However, in urban areas, 43 percent of nets are obtained from a shop or market, 17 percent through mass distribution campaigns, and 12 percent from government health facilities.  In Bulawayo and Harare, the most nets are obtained in shops or markets, in contrast to other provinces where the most nets are obtained from a government health facility or mass distribution campaigns.  Interestingly, about one in four nets is obtained through mass distribution campaigns for households in the lowest, second, and middle wealth quintiles. About half of the nets for households in these same wealth quintiles are obtained from government health facilities. Figure 12.5 Percentage of the de facto population with access to an ITN in the household 29 30 47 43 38 20 11 40 38 32 58 53 43 34 46 23 44 37 Highest Fourth Middle Second Lowest WEALTH QUINTILE Bulawayo Harare Masvingo Midlands Matabeleland South Matabeleland North Mashonaland West Mashonaland East Mashonaland Central Manicaland PROVINCE Urban Rural RESIDENCE Total Note: Percentage of the de facto household population who could sleep inside an ITN if each ITN in the household were used by up to two people Malaria • 221 12.1.4 Indoor Residual Spraying (IRS) Vector control intervention: Indoor residual spraying (IRS) in the past 12 months Indoor residual spraying (IRS) is defined as spraying of the interior walls of dwellings with insecticide to protect against mosquitoes during the 12-month period before the survey. This does not include self-applied insecticides, only those applied by professionals as part of an organized malaria prevention program. Sample: Households Indoor residual spraying (IRS) is a major malaria vector control strategies used in Zimbabwe since 1949. During the 12-month period before the survey, IRS was implemented in the 47 districts with malaria transmission. To obtain information on the coverage of IRS, all households interviewed in the 2015 ZDHS were asked whether the interior walls of their dwellings had been sprayed against mosquitoes during the 12-month period before the survey and, if so, who had sprayed the dwelling. Nationally, 21 percent of households report that their households received IRS in the past 12 months (Table 12.4). Fifty-five percent of households surveyed in the 2015 ZDHS have at least one ITN and/or have had IRS in the last 12 months, while 39 percent have at least one ITN for every two persons and/or IRS in the past 12 months. Eighty-five percent of households sprayed were sprayed by government workers or a government-sponsored programme, and 7 percent were sprayed by a private company (data not shown). Trends: Nationally, IRS household coverage increased from 15 percent in the ZDHS 2005-06 to 21 percent in the ZDHS 2015. Over the same 10-year period, IRS coverage among rural households increased from 19 percent to 30 percent, while it has dropped from 8 percent to 4 percent among urban households (Figure 12.6). This observation is consistent with fact that the IRS programme has focused on rural areas, where higher malaria transmission is found, rather than urban areas. Patterns by background characteristics  IRS varies markedly by residence. Rural households are more than seven times as likely as urban households to receive IRS (30 percent and 4 percent, respectively). Figure 12.6 Trends in IRS household coverage 15 17 21 8 4 4 19 24 30 2005-06 2010-11 2015 Total Rural Urban 222 • Malaria  By province, the coverage of IRS varies from 2 percent in Bulawayo and Harare to 44 percent in Matabeleland North.  Figure 12.7 presents data on ITN and/or IRS household coverage by province. Coverage is highest in Matabeleland North (81 percent).  Households in the lower wealth quintiles were more likely to have received IRS than households in the higher wealth quintiles. 12.1.5 Use of Mosquito Nets among the De Facto Household Population The 2015 ZDHS asked about the use of mosquito nets by household members during the night before the survey. Use of nets during the night before the survey is taken as typical of net usage. However, caution should be exercised in interpreting the results because the survey was conducted during the low malaria transmission period. In Zimbabwe, the prevalence of mosquitoes varies according to season and other climatic conditions; therefore, net usage on the night before the survey may not be representative of the patterns of usage during periods of high malaria transmission. Use of ITNs Percentage of population that slept under an ITN the night before the survey. Sample: De facto household population Table 12.5 shows that 11 percent of the household population slept under any net the night before the survey, while 9 percent slept under an ITN. Among households with at least one ITN, 17 percent of members of households slept under an ITN the night before the survey. Twenty-nine percent of the population slept under an ITN or in a dwelling sprayed during IRS in the past 12 months. Table 12.6 presents the percentages of ITNs used by anyone in the household the night before the survey. Among the observed 9,985 ITNs found in the sampled households, 19 percent were used by someone the night before the survey. Figure 12.7 Coverage of ITN and/or IRS by province Percentage of households with at least one ITN and/or IRS in the past 12 months Malaria • 223 Trends: The proportion of the household population that slept under any mosquito net increased from 6 percent in the 2005-06 ZDHS to 12 percent in the 2010-11 ZDHS and is 11 percent in the 2015 ZDHS. The proportion that slept under an ITN the night before increased from 2 percent in the 2005-06 ZDHS to 9 percent in the 2010-11 ZDHS, where it remains in the 2015 ZDHS. Figure 12.8 presents trends in ITN ownership and use for the 2005-06, 2010-11, and 2015 ZDHS surveys. Patterns by background characteristics  Rural residents are more likely than their urban counterparts to have slept under an ITN the night before the survey (10 and 6 percent, respectively).  Among the provinces, the percentage of the household population that slept under an ITN ranges from a low of 2 percent in Harare to a high of 14 percent in Matabeleland North.  Among households with at least one ITN, Bulawayo has the highest proportion of the household population that slept under an ITN the night before the survey (26 percent) and Harare has the lowest (12 percent). 12.1.6 Use of Mosquito Nets by Children Children under age 5 are at considerably higher risk of contracting malaria and developing severe disease than the general population because they have not developed acquired immunity to malaria. This vulnerability to malaria makes it especially important for children under age 5 to sleep under ITNs to prevent malaria transmission and reduce malaria-related morbidity and mortality. Table 12.7 presents data on the extent to which children under age 5 slept under various types of nets on the night before the interview. Overall, 11 percent of children slept under a mosquito net, 9 percent under an ITN, and 30 percent slept under an ITN or in a dwelling that was treated with IRS. Figure 12.8 Trends in ITN ownership, access, and use 9 48 27 9 3 29 38 28 37 24 48 19 17 55 39 Percent of households with at least one ITN Percent of existing ITNs used last night Percent of the household population who slept under an ITN last night among those living in a household with at least one ITN Percent of households with at least one ITN and/or IRS in past 12 months Percent of households with at least one ITN for every two persons and/or IRS in the past 12 months 2005-06 2010-11 2015 224 • Malaria Trends: The proportion of children under age 5 who slept under any net increased from 7 percent in the 2005-06 ZDHS to the 14 percent in the 2010-11 ZDHS before declining slightly in the 2015 ZDHS (11 percent). Over the same period, ITN usage was lower than any net usage, but followed a similar pattern (Figure 12.9). Patterns by background characteristics  Younger children age 0-23 months are more likely than other children to have slept under any net (14 percent) or an ITN (11 percent) the night before the survey.  There are small differentials in ITN usual by urban-rural residence (10 percent of rural children and 8 percent or urban children slept under an ITN). Among children who live in households that possess an ITN, 21 percent of children in urban areas slept under an ITN, compared with 17 percent of children in rural areas.  The ITN usage among children living in households with an ITN is lowest in Harare and Midlands (14 percent each) and highest in Bulawayo (29 percent). 12.1.7 Use of Mosquito Nets by Pregnant Women In malaria-endemic areas, adults usually have acquired some degree of immunity to severe, life-threatening malaria. However, pregnancy reduces immunity which increases the risk of malaria and development of severe disease, especially in women who are pregnant for the first time. Malaria among pregnant women may be asymptomatic, and is a major contributor to spontaneous abortion, low birth weight, premature delivery, stillbirth, maternal anaemia, and maternal mortality. Consistent use of ITNs by pregnant women is one of the effective ways to reduce the risk of malaria in pregnancy. Table 12.8 presents data on the use of mosquito nets (treated or untreated) by pregnant women, by background characteristics. Overall, 8 percent of women slept under any net and 6 percent slept under an ITN. Twenty-seven percent of women slept under an ITN the night before the survey or in a dwelling prayed with IRS in the past 12 months. Thirteen percent of pregnant women living in households that possess an ITN slept under an ITN the night before the survey. Trends: Over the past decade, the proportion of pregnant women who slept under any mosquito net increased from 7 percent in the 2005-06 ZDHS to 15 percent in the 2010-11 ZDHS before declining to 8 percent in the 2015 ZDHS (8 percent). Use of ITNs followed a similar pattern over the same period (Figure 12.10). Patterns by background characteristics  The likelihood of sleeping under a net generally decreases with increasing level of education.  Pregnant women in urban areas were more likely to have slept under any net the night before the survey than their rural counterparts (10 and 7 percent, respectively). However, rural pregnant women Figure 12.9 Trends in net use among children under age 5 Figure 12.10 Trends in net use among pregnant women 7 14 11 3 10 9 2005-06 2010-11 2015 Percentage of children using an ITN the night before the survey ITN Any net 7 15 8 3 10 6 2005-06 2010-11 2015 Percentage of pregnant women using an ITN the night before the survey ITN Any net Malaria • 225 are more likely to have slept under an ITN than their urban counterparts (7 and 5 percent, respectively). 12.2 PREVALENCE, DIAGNOSIS, AND PROMPT TREATMENT OF FEVER AMONG YOUNG CHILDREN Care seeking for children under 5 with fever Percentage of children under 5 with a fever in the two weeks before the survey for whom advice or treatment was sought from a health provider, a health facility or a pharmacy. Sample: Children under 5 with a fever in the two weeks before the survey Diagnosis of malaria in children under 5 with fever Percentage of children under 5 with a fever in the two weeks before the survey who had blood taken from a finger or heel for testing. This is a proxy measure of diagnostic testing for malaria. Sample: Children under 5 with a fever in the two weeks before the survey Fever is a major manifestation of malaria in young children, although it also accompanies other illnesses. The malaria treatment policy stipulates that every suspected malaria case should have a parasitological test with a rapid diagnostic test (RDT) or microscopy. Only malaria positive cases are treated with antimalarial medicines. Malaria testing and treatment should be accessed within 24 hours of symptoms to prevent progression to severe disease which is life threatening. As discussed in Chapter 10, mothers were asked whether their children under age 5 had a fever in the two weeks preceding the survey and, if so, what was done to treat the fever. Table 12.9 shows the percentage of children under 5 who had a fever in the two weeks preceding the survey and, among those who had a fever, the percentage for whom advice or treatment was sought and the percentage who had blood taken from a finger or heel , by background characteristics. Table 12.10 shows the source of advice or treatment for children with fever. Table 12.9 shows that 14 percent of children under age 5 had a fever in the two weeks preceding the survey. Among children with fever, 50 percent of the mothers with children with fever sought advice or treatment. Thirteen percent had blood taken from a finger or heel for testing. The public sector was the main source of advice or treatment for 36 percent of the children with fever; the Rural Health Centre was the main source of advice or treatment (22 percent). Only 10 percent sought advice or treatment from the private sector (Table 12.10). Patterns by background characteristics  The proportion of children under age 5 who had a fever in the two weeks preceding the survey was highest among children age 0-35 months (16 percent).  The prevalence of fever in children in the two weeks preceding the survey was the same for urban and rural children (14 percent). However, among those children who had a fever, the percentage of who had blood taken from a finger or heel for testing was higher among those in rural areas than urban areas (15 percent versus 9 percent).  The prevalence of fever in children in the two weeks preceding the survey was higher among children of mothers with no education (20 percent) than those whose mothers had some education (13-14 percent).Children in the Mashonaland West province were more likely to have experienced fever (24 percent) than those in the other provinces (16 percent or lower). 226 • Malaria Data are not presented for treatment patterns because there were too few cases (10 unweighted cases) reported for children who were given antimalarials. LIST OF TABLES For detailed information on the malaria section, see the following tables:  Table 12.1 Household possession of mosquito nets  Table 12.2 Access to an insecticide-treated net (ITN)  Table 12.3 Source of mosquito nets  Table 12.4 Indoor residual spraying against mosquitoes  Table 12.5 Use of mosquito nets by persons in the household  Table 12.6 Use of existing ITNs  Table 12.7 Use of mosquito nets by children  Table 12.8 Use of mosquito nets by pregnant women  Table 12.9 Prevalence, diagnosis, and prompt treatment of children with fever  Table 12.10 Source of advice or treatment for children with fever Malaria • 227 Table 12.1 Household possession of mosquito nets Percentage of households with at least one mosquito net (treated or untreated) and insecticide-treated net (ITN), and long-lasting insecticidal net (LLIN); average number of nets and ITNs/ LLINs per household; and percentage of households with at least one net and ITN/LLIN per two persons who stayed in the household last night, according to background characteristics, Zimbabwe 2015 Percentage of households with at least one mosquito net Average number of nets per household Number of households Percentage of households with at least one net for every two persons who stayed in the household last night Number of households with at least one person who stayed in the household last night Background characteristic Any mosquito net Insecticide- treated mosquito net (ITN)/long- lasting insecticidal net (LLIN)1 Any mosquito net ITN/LLIN1 Any mosquito net ITN/LLIN1 Residence Urban 55.8 32.4 0.9 0.5 3,531 27.6 16.5 3,499 Rural 63.0 55.7 1.3 1.2 7,003 35.4 31.4 6,916 Province Manicaland 66.9 57.3 1.4 1.2 1,484 38.9 32.9 1,463 Mashonaland Central 64.3 48.5 1.2 0.9 952 32.0 23.8 939 Mashonaland East 60.7 53.1 1.1 1.0 1,171 36.8 32.6 1,162 Mashonaland West 71.9 66.6 1.5 1.4 1,209 38.1 35.4 1,200 Matabeleland North 79.4 70.9 1.8 1.6 527 51.8 46.4 510 Matabeleland South 47.7 40.1 1.0 0.9 530 31.0 26.8 525 Midlands 58.6 47.1 1.1 1.0 1,271 29.1 23.5 1,256 Masvingo 59.6 55.0 1.2 1.1 1,244 33.1 30.6 1,234 Harare 45.1 17.0 0.7 0.2 1,604 18.1 6.6 1,584 Bulawayo 58.5 30.2 1.0 0.4 542 31.5 15.0 542 Wealth quintile Lowest 57.0 52.7 1.1 1.0 1,996 29.0 26.8 1,965 Second 61.3 54.6 1.2 1.1 1,983 32.3 28.9 1,964 Middle 66.8 58.6 1.4 1.3 2,000 39.3 34.9 1,980 Fourth 57.4 38.1 1.0 0.7 2,398 31.6 22.1 2,365 Highest 61.2 38.2 1.2 0.7 2,158 31.9 20.3 2,141 Total 60.6 47.9 1.2 0.9 10,534 32.8 26.4 10,415 1 An insecticide-treated net (ITN) is (1) a factory-treated net that does not require any further treatment (LLIN) or (2) a net that has been soaked with insecticide within the past 12 months. All ITNs in the 2015 ZDHS are LLINs. Table 12.2 Access to an insecticide-treated net (ITN) Percent distribution of the de facto household population by number of ITNs the household owns, and percentage with access to an ITN, according to number of persons who stayed in the household the night before the survey, Zimbabwe 2015 Number of persons who stayed in the household the night before the survey Total Number of ITNs 1 2 3 4 5 6 7 8+ Number of ITNs1 0 59.9 55.0 55.3 51.5 49.9 45.9 47.0 43.6 49.6 1 28.0 22.3 20.7 19.1 16.4 13.5 12.7 13.0 16.8 2 9.7 16.2 16.0 18.7 17.8 19.6 15.6 13.5 16.6 3 1.8 4.7 6.6 8.1 12.1 15.6 16.5 13.5 11.1 4 0.6 1.1 1.2 2.3 2.8 3.1 5.8 9.1 3.8 5 0.0 0.6 0.0 0.2 0.9 1.1 1.6 3.5 1.2 6 0.0 0.0 0.1 0.1 0.2 1.1 0.4 2.1 0.6 7 0.0 0.0 0.1 0.1 0.0 0.1 0.4 1.7 0.4 Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 Number 1,344 2,868 5,484 7,422 7,678 6,031 4,245 7,513 42,586 Percent with access to an ITN1,2 40.1 45.0 37.8 39.0 36.7 38.5 34.9 32.5 37.2 1 An insecticide-treated net (ITN) is (1) a factory-treated net that does not require any further treatment (LLIN) or (2) a net that has been soaked with insecticide within the past 12 months. All ITNs in the 2015 ZDHS are LLINs. 2 Percentage of the de facto household population who could sleep under an ITN if each ITN in the household were used by up to two individuals. 228 • Malaria Table 12.3 Source of mosquito nets Percent distribution of mosquito nets by source of net, according to background characteristics, Zimbabwe 2015 Background characteristic Mass distri- bution campaign ANC visit Immuni- sation visit Govern- ment health facility Private health facility Phar- macy Shop/ market Com- munity health worker Mission Hospital School Other Don’t know Total Number of mosquito nets Type of net ITN1 24.2 5.0 8.2 41.2 1.6 0.2 7.7 0.9 0.6 1.7 7.9 0.8 100.0 9,985 Other2 14.3 2.5 2.9 18.3 0.8 0.6 48.4 0.3 0.1 0.3 9.1 2.4 100.0 2,321 Residence Urban 17.3 3.4 6.0 11.6 1.6 0.8 43.4 0.5 0.2 0.7 12.3 2.3 100.0 3,235 Rural 24.1 4.9 7.7 45.9 1.4 0.1 5.4 0.9 0.7 1.7 6.6 0.7 100.0 9,071 Province Manicaland 29.9 5.7 5.2 41.0 1.1 0.0 7.5 0.9 1.5 0.1 6.2 0.8 100.0 2,031 Mashonaland Central 29.2 3.7 3.2 50.6 0.1 0.1 5.6 0.7 0.0 0.3 6.3 0.2 100.0 1,130 Mashonaland East 15.3 11.1 4.1 42.5 0.1 0.2 12.7 0.0 0.2 1.5 10.9 1.5 100.0 1,319 Mashonaland West 19.0 1.9 10.1 47.7 0.7 0.4 12.1 0.8 0.1 1.4 5.7 0.2 100.0 1,802 Matabeleland North 8.4 5.7 5.0 59.7 1.1 0.0 3.0 4.3 2.1 7.2 3.2 0.4 100.0 956 Matabeleland South 16.9 1.9 2.7 56.4 0.7 0.1 13.8 0.0 0.0 2.9 3.4 1.2 100.0 549 Midlands 20.4 1.7 15.8 29.6 1.0 0.5 16.5 0.0 0.8 0.6 11.6 1.5 100.0 1,458 Masvingo 32.9 3.7 10.9 21.8 5.8 0.0 9.7 1.1 0.0 1.3 11.2 1.4 100.0 1,478 Harare 23.6 3.9 3.6 4.7 0.5 0.3 46.2 0.1 0.0 0.7 12.9 3.4 100.0 1,065 Bulawayo 9.8 6.0 4.0 6.1 4.0 2.2 59.5 0.4 0.3 0.9 6.2 0.6 100.0 519 Wealth quintile Lowest 24.8 6.1 8.7 48.0 0.3 0.1 2.1 1.1 0.8 1.6 5.9 0.5 100.0 2,123 Second 25.2 5.1 8.8 48.5 0.2 0.1 2.6 0.8 0.8 2.1 5.4 0.4 100.0 2,465 Middle 23.8 5.0 8.1 46.3 0.7 0.1 6.7 0.8 0.4 1.6 6.1 0.7 100.0 2,844 Fourth 20.3 3.7 5.5 28.6 1.6 0.2 24.4 0.7 0.5 1.0 11.6 1.9 100.0 2,378 Highest 17.5 2.8 5.1 13.1 4.3 0.9 40.6 0.7 0.3 0.8 11.8 2.0 100.0 2,496 Total 22.3 4.5 7.2 36.9 1.4 0.3 15.4 0.8 0.5 1.4 8.1 1.1 100.0 12,306 ANC = Antenatal care 1 An insecticide-treated net (ITN) is (1) a factory-treated net that does not require any further treatment (LLIN) or (2) a net that has been soaked with insecticide within the past 12 months. All ITNs in the 2015 ZDHS are LLINs. 2 Any net that is not an ITN Malaria • 229 Table 12.4 Indoor residual spraying against mosquitoes Percentage of households in which someone has come into the dwelling to spray the interior walls against mosquitoes (IRS) in the past 12 months, the percentage of households with at least one ITN and/or IRS in the past 12 months, and the percentage of households with at least one ITN for every two persons and/or IRS in the past 12 months, by background characteristics, Zimbabwe 2015 Background characteristic Percentage of households with IRS1 in the past 12 months Percentage of households with at least one ITN2 and/or IRS1 in the past 12 months Percentage of households with at least one ITN2 for every two persons and/or IRS1 in the past 12 months Number of households Residence Urban 4.0 33.9 18.8 3,531 Rural 30.1 65.4 49.8 7,003 Province Manicaland 31.9 68.5 54.5 1,484 Mashonaland Central 41.0 68.2 54.8 952 Mashonaland East 23.7 58.9 44.9 1,171 Mashonaland West 18.6 71.1 45.0 1,209 Matabeleland North 43.8 80.6 67.2 527 Matabeleland South 18.1 43.2 34.0 530 Midlands 18.0 53.2 35.2 1,271 Masvingo 22.8 61.8 43.9 1,244 Harare 2.0 18.4 8.4 1,604 Bulawayo 2.0 31.4 16.8 542 Wealth quintile Lowest 37.6 68.2 52.7 1,996 Second 29.7 63.4 48.0 1,983 Middle 24.7 65.2 48.2 2,000 Fourth 9.4 40.7 26.9 2,398 Highest 8.7 40.9 25.1 2,158 Total 21.3 54.9 39.4 10,534 1 Indoor residual spraying (IRS) is limited to spraying conducted by a government, private, or non- governmental organization. The total excludes 185 households which reported that they had been sprayed in the past 12 months, but either did not know the organization which conducted the spraying or reported it was not applied by professionals during an organized campaign. 2 An insecticide-treated net (ITN) is (1) a factory-treated net that does not require any further treatment (LLIN), or (2) a net that has been soaked with insecticide within the past 12 months. All ITNs in the 2015 ZDHS are LLINs. 230 • Malaria Table 12.5 Use of mosquito nets by persons in the household Percentage of the de facto household population who slept the night before the survey under a mosquito net (treated or untreated), under an insecticide-treated net (ITN) and under an ITN or in a dwelling in which the interior walls have been sprayed against mosquitoes (IRS) in the past 12 months; and among the de facto household population in households with at least one ITN, the percentage who slept under an ITN the night before the survey, by background characteristics, Zimbabwe 2015 Household population Household population in households with at least one ITN1 Background characteristic Percentage who slept under any mosquito net last night Percentage who slept under an ITN1 last night Percentage who slept under an ITN1 last night or in a dwelling sprayed with IRS2 in the past 12 months Number of persons Percentage who slept under an ITN1 last night Number of persons Age <5 11.4 9.0 29.5 6,640 17.5 3,404 5-14 8.1 6.8 30.3 11,795 12.7 6,304 15-34 9.6 7.5 25.7 13,579 15.9 6,415 35-49 15.4 12.0 28.7 5,433 23.7 2,746 50+ 13.3 11.1 31.4 5,138 21.9 2,606 Sex Male 10.3 8.2 28.8 20,181 16.1 10,254 Female 11.0 8.9 28.5 22,404 17.7 11,221 Residence Urban 10.7 6.3 9.8 13,088 18.7 4,395 Rural 10.6 9.5 37.0 29,498 16.5 17,081 Province Manicaland 13.7 11.1 41.1 6,084 18.7 3,622 Mashonaland Central 11.2 9.2 46.9 4,041 18.5 2,010 Mashonaland East 10.8 9.5 29.8 4,376 17.3 2,416 Mashonaland West 12.4 11.5 27.1 5,091 16.3 3,600 Matabeleland North 15.1 13.7 52.3 2,173 18.8 1,583 Matabeleland South 6.8 6.3 23.8 2,085 15.5 848 Midlands 9.6 8.1 27.4 5,343 15.5 2,787 Masvingo 8.4 8.1 29.7 5,288 14.9 2,855 Harare 5.9 2.2 4.1 6,089 11.7 1,143 Bulawayo 18.2 8.0 9.8 2,015 26.4 610 Wealth quintile Lowest 10.5 9.8 43.5 8,337 18.1 4,484 Second 11.1 10.1 38.2 8,518 17.7 4,875 Middle 11.1 9.9 32.1 8,535 16.3 5,195 Fourth 9.7 6.4 15.5 8,525 15.6 3,486 Highest 10.9 6.6 14.4 8,671 16.6 3,435 Total 10.7 8.5 28.6 42,586 16.9 21,475 1 An insecticide-treated net (ITN) is (1) a factory-treated net that does not require any further treatment (LLIN) or (2) a net that has been soaked with insecticide within the past 12 months. All ITNs in the 2015 ZDHS are LLINs. 2 Indoor residual spraying (IRS) is limited to spraying conducted by a government, private, or non-governmental organization. Malaria • 231 Table 12.6 Use of existing ITNs Percentage of insecticide-treated nets (ITNs) that were used by anyone the night before the survey, by background characteristics, Zimbabwe 2015 Background characteristic Percentage of existing ITNs1 used last night Number of ITNs1 Residence Urban 23.1 1,905 Rural 17.8 8,080 Province Manicaland 19.3 1,739 Mashonaland Central 23.2 837 Mashonaland East 18.6 1,173 Mashonaland West 17.9 1,683 Matabeleland North 19.1 845 Matabeleland South 17.0 473 Midlands 17.3 1,211 Masvingo 15.9 1,383 Harare 16.9 399 Bulawayo 38.3 243 Wealth quintile Lowest 20.1 1,971 Second 19.4 2,208 Middle 17.5 2,517 Fourth 17.7 1,693 Highest 19.8 1,596 Total 18.8 9,985 1 An insecticide-treated net (ITN) is (1) a factory-treated net that does not require any further treatment (LLIN) or (2) a net that has been soaked with insecticide within the past 12 months. All ITNs in the 2015 ZDHS are LLINs. 232 • Malaria Table 12.7 Use of mosquito nets by children Percentage of children under age 5 who, the night before the survey, slept under a mosquito net (treated or untreated), under an insecticide-treated net (ITN), and under an ITN or in a dwelling in which the interior walls have been sprayed against mosquitoes (IRS) in the past 12 months; and among children under age 5 five in households with at least one ITN, the percentage who slept under an ITN the night before the survey, according to background characteristics, Zimbabwe 2015 Children under age 5 in all households Children under age 5 in households with at least one ITN1 Background characteristic Percentage who slept under any mosquito net last night Percentage who slept under an ITN1 last night Percentage who slept under an ITN1 last night or in a dwelling sprayed with IRS2 in the past 12 months Number of children Percentage who slept under an ITN1 last night Number of children Age in months <12 14.3 10.9 31.3 1,175 21.1 607 12-23 14.1 11.4 30.5 1,258 22.5 639 24-35 10.1 7.5 29.1 1,363 14.9 685 36-47 10.3 8.5 29.4 1,376 16.3 720 48-59 8.9 7.2 27.7 1,468 14.0 752 Sex Male 11.6 9.3 30.2 3,257 18.2 1,669 Female 11.1 8.6 28.8 3,383 16.9 1,735 Residence Urban 13.1 7.7 10.9 1,898 21.1 690 Rural 10.7 9.5 36.9 4,742 16.6 2,714 Province Manicaland 15.0 12.5 41.5 1,018 22.0 578 Mashonaland Central 10.9 9.0 45.9 619 18.3 304 Mashonaland East 10.5 8.7 28.1 625 16.2 335 Mashonaland West 12.1 11.1 27.3 850 15.6 607 Matabeleland North 17.8 15.8 52.1 329 22.8 228 Matabeleland South 7.3 6.7 27.2 317 14.7 144 Midlands 8.9 7.6 27.7 905 14.3 482 Masvingo 9.1 8.9 31.4 844 15.9 473 Harare 7.5 2.6 4.6 867 13.6 165 Bulawayo 23.2 9.5 11.2 265 28.5 89 Wealth quintile Lowest 10.1 9.5 42.2 1,545 18.0 811 Second 10.9 10.1 35.6 1,391 18.3 769 Middle 11.3 9.9 32.9 1,232 16.1 760 Fourth 12.3 7.4 16.7 1,395 17.5 593 Highest 12.7 7.7 16.0 1,078 17.7 472 Total 11.4 9.0 29.5 6,640 17.5 3,404 Note: Table is based on children who stayed in the household the night before the interview. 1 An insecticide-treated net (ITN) is (1) a factory-treated net that does not require any further treatment (LLIN) or (2) a net that has been soaked with insecticide within the past 12 months. All ITNs in the 2015 ZDHS are LLINs. 2 Indoor residual spraying (IRS) is limited to spraying conducted by a government, private, or non-governmental organization. Malaria • 233 Table 12.8 Use of mosquito nets by pregnant women Percentage of pregnant women age 15-49 who, the night before the survey, slept under a mosquito net (treated or untreated), under an insecticide-treated net (ITN), and under an ITN or in a dwelling in which the interior walls have been sprayed against mosquitoes (IRS) in the past 12 months; and among pregnant women age 15-49 in households with at least one ITN, the percentage who slept under an ITN the night before the survey, by background characteristics, Zimbabwe 2015 Among pregnant women age 15-49 in all households Among pregnant women age 15-49 in households with at least one ITN1 Background characteristic Percentage who slept under any mosquito net last night Percentage who slept under an ITN1 last night Percentage who slept under an ITN1 last night or in a dwelling sprayed with IRS2 in the past 12 months Number of women Percentage who slept under an ITN1 last night Number of women Residence Urban 10.2 4.6 8.0 201 14.1 66 Rural 7.0 6.8 35.1 436 12.9 230 Province Manicaland 3.0 3.0 38.6 94 (7.9) 36 Mashonaland Central 13.9 12.6 48.5 83 (23.0) 46 Mashonaland East 4.6 4.6 25.3 60 (8.7) 32 Mashonaland West 11.3 10.2 24.9 80 (14.2) 57 Matabeleland North (9.3) (8.4) (45.7) 24 (11.5) 17 Matabeleland South 14.4 13.1 26.8 27 (28.5) 13 Midlands 4.5 4.5 22.6 74 (9.9) 34 Masvingo 4.5 4.5 27.7 73 (7.7) 43 Harare 7.3 0.6 0.6 98 * 14 Bulawayo (20.9) (7.2) (7.2) 24 * 4 Education No education * * * 9 * 3 Primary 9.4 8.5 39.7 190 16.5 97 Secondary 8.0 5.5 22.0 406 12.0 187 More than secondary (3.3) (0.7) (2.0) 33 * 8 Wealth quintile Lowest 7.0 7.0 35.7 135 13.9 68 Second 9.3 8.4 44.3 130 14.8 74 Middle 4.0 4.0 26.1 106 (7.0) 60 Fourth 8.5 6.0 15.2 155 17.1 54 Highest 11.1 4.3 10.8 111 12.3 38 Total 8.0 6.1 26.5 638 13.1 295 Notes: Table is based on women who stayed in the household the night before the interview. 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 An insecticide-treated net (ITN) is (1) a factory-treated net that does not require any further treatment (LLIN) or (2) a net that has been soaked with insecticide within the past 12 months. All ITNs in the 2015 ZDHS are LLINs. 2 Indoor residual spraying (IRS) is limited to spraying conducted by a government, private, or non-governmental organization. 234 • Malaria Table 12.9 Prevalence, diagnosis, and prompt treatment of children with fever Percentage of children under age 5 with fever in the 2 weeks preceding the survey; and among children under age 5 with fever, the percentage for whom advice or treatment was sought and the percentage who had blood taken from a finger or heel for testing, according to background characteristics, Zimbabwe 2015 Children under age 5 Children under age 5 with fever Background characteristic Percentage with fever in the 2 weeks preceding the survey Number of children Percentage for whom advice or treatment was sought1 Percentage who had blood taken from a finger or heel for testing Number of children Age in months <12 15.3 1,196 46.5 11.6 184 12-23 16.7 1,216 51.1 12.0 203 24-35 15.5 1,191 50.0 19.5 184 36-47 11.1 1,223 52.0 11.9 136 48-59 10.5 1,228 49.0 6.6 129 Sex Male 13.3 2,950 45.9 13.7 391 Female 14.3 3,106 52.9 11.8 444 Residence Urban 14.1 1,937 60.4 8.7 273 Rural 13.7 4,118 44.4 14.7 563 Province Manicaland 11.2 893 36.7 9.0 100 Mashonaland Central 8.4 590 67.2 19.1 50 Mashonaland East 15.9 575 37.5 15.3 92 Mashonaland West 23.9 783 46.8 8.7 188 Matabeleland North 15.4 275 62.7 21.8 42 Matabeleland South 13.3 230 60.8 23.9 31 Midlands 9.6 821 60.9 19.4 79 Masvingo 12.4 731 38.6 16.9 90 Harare 15.0 910 54.5 4.0 136 Bulawayo 11.6 249 71.2 17.2 29 Mother’s education No education 19.5 70 * * 14 Primary 13.5 1,884 45.7 13.6 254 Secondary 13.9 3,767 50.2 11.2 525 More than secondary 12.7 335 (68.7) (25.1) 43 Wealth quintile Lowest 14.3 1,381 48.1 16.2 197 Second 14.2 1,179 40.7 12.5 167 Middle 12.3 1,016 45.1 12.8 125 Fourth 13.9 1,428 51.1 9.2 198 Highest 14.1 1,052 63.7 12.9 149 Total 13.8 6,055 49.7 12.7 835 Notes: 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 Excludes advice or treatment from a friend/relative and other non-medical and non-retail sources Malaria • 235 Table 12.10 Source of advice or treatment for children with fever Percentage of children under age 5 with fever in the 2 weeks preceding the survey for whom advice or treatment was sought from specific sources; and among children under age 5 with fever in the 2 weeks preceding the survey for whom advice or treatment was sought, the percentage for whom advice or treatment was sought from specific sources, Zimbabwe 2015 Percentage for whom advice or treatment was sought from each source: Background characteristic Among children with fever Among children with fever for whom advice or treatment was sought Any public sector source 35.5 70.0 Government hospital 2.4 4.6 Rural health centre 21.8 43.0 Municipal clinic 9.5 18.7 Village health worker 0.8 1.6 MOHCC mobile clinic 0.2 0.4 Mission hospital 1.3 2.6 Any private sector source 9.9 19.4 Private hospital/clinic 4.7 9.2 Pharmacy 3.1 6.1 Private doctor 1.1 2.1 CBD 0.5 1.1 Private outreach clinic 0.1 0.2 Other private medical sector 0.4 0.8 Any other source 5.9 11.6 General dealer/supermarket 3.1 6.0 Tuck shop/service station/bottle store/bar 0.8 1.7 Other retail 0.2 0.4 Church 0.7 1.4 Friend/relative 0.2 0.3 Other 0.9 1.7 Number of children 835 424 CBD = Community-based distribution HIV/AIDS-related Knowledge Attitudes, and Behaviour • 237 HIV/AIDS-RELATED KNOWLEDGE, ATTITUDES, AND BEHAVIOUR 13 Key Findings  Knowledge of HIV prevention methods: Fifty-five percent of women and 56 percent of men age 15-49 have “comprehensive knowledge” about the modes of HIV transmission and prevention, as do 46 percent of young women and 47 percent of young men age 15-24.  Knowledge of prevention of mother-to-child transmission of HIV: Eighty-two percent of women and 75 percent of men know that HIV can be transmitted by breastfeeding. Among women and men, 91 percent and 86 percent, respectively, know that the risk of mother-to- child transmission is reduced by a mother taking special drugs.  Sexual partners and condom use: One percent of women and 14 percent of men had sexual intercourse with two or more partners in the past 12 months. Among respondents who had sex with a non-marital, non- cohabitating partner in the past 12 months, 67 percent of women and 85 percent of men reported that they used a condom during their most recent sexual intercourse with that partner.  HIV tests: Ninety-four percent of women and 95 percent of men know where to get an HIV test. Eighty percent of women and 62 percent of men have been tested for HIV and have received the results of their last test. Forty-nine percent of women and 36 percent of men were tested in the past 12 months and received the results for their last test.  Male circumcision: Overall, 14 percent of men age 15- 49 are circumcised. The percentage of men age 15-19 who are circumcised has increased four-fold since the 2010-11 ZDHS, from 5 percent to 23 percent in 2015. imbabwe continues to experience one of the highest levels of HIV prevalence in sub-Saharan Africa. As of 2014, an estimated 1.5 million adults and children in the country were living with HIV (MoHCW 2015). In response to the increased burden of disease due to HIV infections, Zimbabwe has continued to scale up prevention, care, and treatment programmes that combat the disease, and has also strengthened monitoring and evaluation systems for these programmes. Measuring changes in HIV risk behaviours is important for successful tracking of the drivers of HIV transmission in generalized epidemics such as that in Zimbabwe. The principal mode of HIV transmission in Zimbabwe is heterosexual intercourse, which accounts for 97 percent of all new HIV infections in the country (NAC 2010). The second most important mode of HIV Z 238 • HIV/AIDS-related Knowledge Attitudes, and Behaviour transmission in Zimbabwe is perinatal transmission in which a mother passes HIV to her child during pregnancy, childbirth, or breastfeeding. The prevention of mother-to-child transmission of HIV (PMTCT) programme is a priority in the fight against HIV in children in Zimbabwe. The PMTCT programme seeks to prevent paediatric HIV infection through primary prevention of HIV infection in the childbearing population; prevention of unintended pregnancies; PMTCT through a combined three-drug (Option B+) regimen; and provision of care and follow-up psychosocial support. This chapter presents the prevalence of relevant knowledge, perceptions, and behaviours at the national level and within geographic and socioeconomic subpopulations. In this way, the sexually transmitted infection (STI), HIV, and AIDS programme in Zimbabwe can target those groups of individuals who are most in need of information and most at risk of HIV infection. To facilitate comparisons between sexes, findings in this chapter refer to the age 15-49 group unless otherwise noted. The chapter concludes with a discussion of the findings for young individuals age 15-24. 13.1 HIV/AIDS KNOWLEDGE, TRANSMISSION, AND PREVENTION METHODS Knowledge of HIV or AIDS is almost universal in Zimbabwe—99 percent of women and men age 15-49 have heard of HIV or AIDS (Table 13.1). Eighty-four percent of women and 88 percent of men know that consistent condom use reduces HIV transmission. Similarly, 92 percent of women and 94 percent of men recognise that the risk of getting HIV can be reduced by limiting sexual intercourse to one uninfected partner (Table 13.2). Seventy-nine percent of women and 85 percent of men know both prevention methods. Trends: Between the 2005-06 and the 2015 ZDHS surveys, the proportion of respondents knowing both prevention methods increased from 65 percent to 79 percent for women, and from 71 percent to 85 percent for men (Figure 13.1). Patterns by background characteristics  Knowledge of prevention methods varies by province, especially for men. For example, 88 percent of men in Harare and Mashonaland East recognise that using condoms and limiting sexual intercourse to one uninfected partner are ways to avoid getting HIV, compared with 76 percent of men in Masvingo (Table 13.2).  Knowledge of HIV increases with education. Seventy-two percent of women and 74 percent of men with primary education know these two prevention methods, compared with 92 percent of women and men with more than a secondary education. To assess HIV knowledge, the 2015 ZDHS obtained information on several common misconceptions about HIV transmission. Respondents were asked whether they think it is possible for a healthy-looking person to have HIV, for mosquitoes to transmit HIV, for HIV to be transmitted by supernatural means, or for HIV to be transmitted by sharing food with a person with HIV. The survey results show that misconceptions about HIV are still held by some women and men in Zimbabwe. Eighty-five percent of women and 87 percent of men agreed that a healthy-looking person can Figure 13.1 Trends in HIV knowledge 65 71 44 47 77 79 56 53 79 85 55 56 Women Men Women Men 2005-06 2010-11 2015 Percentage of women and men age 15-49 Know that HIV can be prevented by using condoms and limiting sex to one uninfected partner Has comprehensive knowledge of HIV HIV/AIDS-related Knowledge Attitudes, and Behaviour • 239 have HIV (Tables 13.3.1 and 13.3.2). A smaller proportion of women (79 percent) and men (76 percent) said HIV cannot be transmitted by mosquitoes. Ninety-one percent of women and 89 percent of men said a person cannot become infected by sharing food with a person who has HIV. Comprehensive knowledge of HIV Knowing that consistent use of condoms during sexual intercourse and having just one uninfected, faithful partner can reduce the chances of getting HIV, knowing that a healthy-looking person can have HIV, and rejecting the two most common local misconceptions about transmission or prevention of HIV Sample: Women and men age 15-49 Comprehensive knowledge of HIV is a composite measure and indicates that an individual knows that consistent condom use and limiting sexual intercourse to one uninfected partner can reduce the risk HIV transmission, that a healthy-looking person can have HIV, and rejects the two most common local misconceptions about the transmission of HIV. In Zimbabwe, the two most common misconceptions are that HIV can be transmitted through mosquitoes and that a person can become infected with HIV by sharing food with a person who has HIV. Nationally, only 55 percent of women and 56 percent of men have comprehensive knowledge of HIV prevention and transmission (Tables 13.3.1 and 13.3.2). Trends: Between the 2005-06 and the 2010-11 ZDHS surveys, the proportion of women and men with comprehensive knowledge of HIV/AIDS increased from 44 percent to 56 percent for women and from 47 percent to 53 percent for men. However, between the 2010-11 and 2015 surveys, a smaller increase was observed in comprehensive knowledge among men (from 53 to 56 percent), and the proportion of women with comprehensive knowledge remained similar (56 percent and 55 percent, respectively) (Figure 13.1). Patterns by background characteristics  Rural women (49 percent) and men (50 percent) are less likely to have comprehensive knowledge of HIV than urban women (64 percent) and men (67 percent) (Tables 13.3.1 and 13.3.2).  Among both women and men, comprehensive knowledge of HIV increases with education and wealth quintile. The difference by education among men is particularly striking; only 33 percent of men with primary education have comprehensive knowledge of HIV, compared with 81 percent of men with more than a secondary education (Figure 13.2). 13.2 KNOWLEDGE ABOUT MOTHER-TO-CHILD TRANSMISSION Increasing the level of general knowledge about transmission of HIV from mother to child and reducing the risk of transmission with antiretroviral drugs are critical in reducing mother-to-child transmission (MTCT) of HIV. To assess MTCT knowledge, respondents were asked whether HIV can be transmitted from mother to child through breastfeeding and whether a mother with HIV can reduce the risk of transmission to her baby by taking special drugs. Awareness is higher among women than men that HIV can be transmitted through breastfeeding (82 percent versus 75 percent) and that the risk of MTCT can be reduced by taking special drugs (91 percent versus 86 percent) (Table 13.4). Overall, 78 percent of women and 68 percent of men are aware that HIV can be transmitted through breastfeeding and that this risk can be reduced by taking special drugs. Figure 13.2 Comprehensive knowledge of HIV by education 27 40 58 83 32 33 60 81 No education Primary Secondary More than secondary Women Men Percentage of women and men age 15-49 Note: The percentage of men with no education who have comprehensive knowledge of HIV is based on 25-49 unweighted cases. 240 • HIV/AIDS-related Knowledge Attitudes, and Behaviour Trends: Knowledge that HIV can be transmitted from mother to child during breastfeeding has remained roughly the same among women, and decreased slightly among men, across the past three ZDHS surveys. By contrast, knowledge that MTCT can be reduced by a mother taking special drugs has increased markedly between the 2005-06 and the 2015 ZDHS surveys—from 57 percent to 91 percent among women, and from 46 percent to 86 percent among men (Figure 13.3). Patterns by background characteristics  Knowledge of both MTCT facts ranges from 65 percent in Manicaland to 86 percent in Masvingo for women, and from 60 percent in Matabeleland South to 72 percent in Mashonaland Central for men (Table 13.4).  Knowledge of MTCT increases with education, especially among men. Only 63 percent of men with primary education know both MTCT facts compared with 77 percent of men with more than a secondary education. 13.3 HIV/AIDS ATTITUDES 13.3.1 Discriminatory Attitudes towards People Living with HIV Widespread stigma and discrimination in a population can adversely affect an individual’s willingness to be tested and one’s adherence to antiretroviral therapy (ART). Thus, the reduction of stigma and discrimination in a population is an important indicator of the success of programmes that target HIV/AIDS prevention and control. Discriminatory attitudes towards people living with HIV Women and men are asked two questions to assess the level of stigma towards people living with HIV. Respondents who indicate that (1) they would not buy fresh vegetables from a shopkeeper who has HIV; or (2) they do not think children living with HIV should be allowed to attend school with children who are HIV negative are considered to have discriminatory attitudes. Sample: Women and men age 15-49 Among respondents who have heard of HIV or AIDS, 22 percent of women and 20 percent of men have discriminatory attitudes towards people living with HIV. Six percent of women and 9 percent of men do not think that children living with HIV should be allowed to attend school with children who are HIV negative. Nineteen percent of women would not buy fresh vegetables from a shopkeeper who has HIV, compared with 16 percent of men (Table 13.5). Trends: This is a new indicator not measured in prior ZDHS surveys. Figure 13.3 Trends in knowledge of mother-to-child transmission of HIV 80 80 57 46 86 78 86 7682 75 91 86 Women Men Women Men 2005-06 2010-11 2015 Percentage of women and men age 15-49 Know that HIV can be transmitted by breastfeeding Know that risk of MTCT can be reduced by the mother taking special drugs HIV/AIDS-related Knowledge Attitudes, and Behaviour • 241 Patterns by background characteristics  Interestingly, discriminatory attitudes towards people living with HIV appear to be more common among younger respondents. For example, the percentage of men with discriminatory attitudes decreases from 32 percent among men age 15-19 to 15 percent or less among those age 30-49 (Table 13.5).  By province, the percentage of respondents with discriminatory attitudes ranges from 16 percent in Harare to 30 percent in Manicaland among women, and from 13 percent in Harare to 36 percent in Matabeleland South among men.  Discriminatory attitudes towards people living with HIV are more prevalent among respondents with lower levels of education and wealth. 13.3.2 Attitudes towards Negotiating Safer Sexual Relations with Husbands Knowledge about ways to prevent HIV transmission is not useful if people are not able to negotiate safer sex practices with their partners. To assess attitudes towards negotiating safer sexual relations with husbands, women and men were asked whether they thought that a wife is justified in refusing to have sexual intercourse with her husband if she knows he has engaged in sex with other women or asking that he use a condom if she knows he has an STI. Table 13.6 shows that 63 percent of women and 69 percent of men believe a woman has a right to refuse sexual intercourse with her husband if she knows he has sex with other women, and 87 percent of women and 85 percent of men believe that a wife is justified in asking her husband to use a condom if she knows he has an STI. 13.4 MULTIPLE SEXUAL PARTNERS AND CONDOM USE Given that most HIV infections in Zimbabwe are contracted through heterosexual contact, information on sexual behaviour is important in designing and monitoring intervention programmes that control the spread of the epidemic. The 2015 ZDHS included questions on respondents’ sexual partners during their lifetimes and over the 12 months preceding the survey. Information was collected on women’s and men’s use of condoms, and men were also asked if they have paid for sex. These questions are sensitive, and some respondents may have been reluctant to provide information on recent sexual behaviour. It is important to remember when interpreting the results in this section that respondents’ answers may be subject to some reporting bias. One percent of women and 14 percent of men reported that they had two or more sexual partners in the year before the survey. Among women and men who had 2 or more partners in the preceding year, 50 percent and 37 percent, respectively, reported using a condom during their most recent sexual intercourse (Tables 13.7.1 and 13.7.2). Tables 13.7.1 and 13.7.2 also show that among respondents who had sexual intercourse in the past 12 months, 14 percent of women and 37 percent of men had sexual intercourse with a non-marital, non- cohabitating partner (higher-risk sexual partners). Two-thirds of women (67 percent) and more than 8 in 10 men (85 percent) used a condom at last intercourse with such a partner (Figure 13.4). On average, women have 1.8 lifetime sexual partners, while men have 6.1. Figure 13.4 Higher-risk sexual partners and condom use 14 67 37 85 Percentage who had sexual intercourse with a non-marital, non-cohabitating partner in the past 12 months Percentage who used a condom during last sex with non-marital, non-cohabitating partner (among those with such a partner in the past 12 months) Among women and men age 15-49 who had sexual intercourse in the past 12 months Women Men 242 • HIV/AIDS-related Knowledge Attitudes, and Behaviour Patterns by background characteristics  Among provinces, the proportion of men having sex with two or more partners in the past 12 months is highest in Matabeleland South and Harare (17 percent) and lowest in Manicaland (11 percent) (Table 13.7.2).  Condom use with non-marital, non-cohabitating partners is lower among women age 15-24 and among men age 15-19 than among their older counterparts. Condom use with such partners is also lower among respondents in rural areas, and among those with lower education and wealth. Overall, men are more likely than women to report condom use with non-marital, non-cohabitating partners, with the variation across background characteristics greater among women than men (Tables 13.7.1 and 13.7.2).  Among women and men, the average number of lifetime sexual partners increases with education. Women and men with more than a secondary education have an average of 1.9 and 7.0 lifetime partners, respectively. 13.5 PAID SEX The act of paying for sex introduces an uneven negotiating ground for safer sexual intercourse. Eighteen percent of men age 15-49 reported ever having paid for sex, and 4 percent paid for sex in the past 12 months. Among those who paid for sex in the past 12 months, 9 in 10 said that they used a condom the last time they paid for sex (Table 13.8). Trends: There has been little change in these behaviours over time, with levels of payment for sex in the past 12 months and condom use at last paid sex reported in the 2015 ZDHS similar to those observed in the 2005-06 and 2010-11 ZDHS surveys. 13.6 COVERAGE OF HIV TESTING SERVICES Knowledge of HIV status helps HIV-negative individuals make specific decisions about reducing risks and increasing safer sex practices so they can remain disease free. Among those who are living with HIV, knowledge of their status allows them to take action to protect their sexual partners, access care, and receive treatment. 13.6.1 Awareness of HIV Testing Services and Experience with HIV Testing To assess awareness and coverage of HIV testing services, ZDHS respondents were asked whether they had ever been tested for HIV. If they had been tested, they were asked whether they had received the result of their last test. If they had never been tested, they were asked whether they knew a place where they could go to be tested. HIV/AIDS-related Knowledge Attitudes, and Behaviour • 243 Over 9 in 10 respondents know where they can go to get tested for HIV (Tables 13.9.1 and 13.9.2). Eighty percent of women and 62 percent of men age 15-49 have ever been tested for HIV and received the result of their last HIV test. Less than 2 percent of women and men said they had been tested but did not receive the test result. Almost half of women (49 percent) and more than one-third of men (36 percent) were tested for HIV and received the test result in the past 12 months. Trends: Coverage of HIV testing has increased dramatically in Zimbabwe over the past 10 years. As shown in Figure 13.5, the percentage of women who have ever been tested for HIV and received the result of their last test has increased sharply from 22 percent in the 2005-06 ZDHS to 57 percent in the 2010-11 ZDHS, and further to 80 percent in the 2015 ZDHS. Although men are less likely than women to have ever been tested for HIV, percentage of men who have been tested and received the results increased from 16 percent in the 2005-06 ZDHS to 62 percent in the 2015 ZDHS. The percentage of respondents who have been tested in the past 12 months and received the test result has also increased, although the pace of increase between the 2010-11 and 2015 surveys is a little slower than between the 2005-06 and 2010-11 surveys. Patterns by background characteristics  In general, the percentage of respondents who have been tested ever and in the past 12 months and received the results follows a U-shape pattern. It increases with age through age 30-39 for ever tested and 25-29 for recently tested, and then it decreases thereafter (Tables 13.9.1 and 13.9.2). For example, the percentage of women who have ever been tested for HIV and received the result increases from 46 percent among women age 15-19 to 92 percent among women age 30-39, and then decreases to 86 percent among women age 40-49.  Coverage of HIV testing is remarkably similar among women in urban and rural areas. Women in rural areas are slightly more likely than their urban counterparts to have been tested for HIV and to have received the result in the past 12 months (50 percent versus 47 percent). However, among men, coverage of HIV testing is slightly higher in urban areas (38 percent versus 35 percent).  There is variation in testing coverage by province (Figure 13.6). The percentage who have ever been tested for HIV and received the result ranges from 73 percent in Manicaland to 85 percent in Matabeleland North among women, and from 55 percent in Manicaland to 67 percent in Harare among men. The percentage who were tested and received the results in the past 12 months is also lowest in Figure 13.5 Trends in HIV testing Figure 13.6 Recent HIV testing by province 22 7 16 7 57 34 36 21 80 49 62 36 Ever tested for HIV and received the result Tested in 12 months before the survey and received the result of the last test Ever tested for HIV and received the result Tested in 12 months before the survey and received the result of the last test 2005-06 2010-11 2015 Percentage of women and men age 15-49 who have been tested for HIV and received the test result Women Men 45 55 46 47 51 52 54 50 46 48 29 40 37 40 32 40 38 32 37 34 Manicaland Mashonaland Central Mashonaland East Mashonaland West Matabeleland North Matabeleland South Midlands Masvingo Harare Bulawayo Percentage of women and men age 15-49 who were tested for HIV in the 12 months before the survey and received the results Women Men 244 • HIV/AIDS-related Knowledge Attitudes, and Behaviour Manicaland among both women and men. The range across provinces spans roughly 10 percentage points among both sexes.  Coverage of HIV testing, ever-tested and tested in the past 12 months, increases with education among both women and men. HIV testing coverage also increases by wealth quintile among men. However, among women, testing coverage is fairly even across wealth quintiles (Tables 13.9.1 and 13.9.2). 13.6.2 HIV Testing of Pregnant Women Testing for HIV during pregnancy is a key component of preventing mother-to-child transmission. Table 13.10 shows that 73 percent of women who gave birth in the 2 years preceding the survey received counselling on HIV during antenatal care (ANC). Overall, 90 percent of women received an HIV test during pregnancy—72 percent received the test result and post-test counselling, 17 percent received the test result but no post-test counselling, and 1 percent were tested but were not given their test result. There were a few women who were tested in labour but not during ANC, as the percentage of women tested during ANC or labour is almost exactly the same as the percentage who were tested during ANC. Trends: Coverage of testing and counselling of pregnant women during ANC has increased. The percentage of women who gave birth in the 2 years preceding the survey who were counselled about HIV, were tested for HIV, and received the result was 23 percent in the 2005-06 ZDHS survey. This figure increased to 59 percent in the 2010-11 ZDHS and to 71 percent in the 2015 ZDHS. 13.7 MALE CIRCUMCISION Male circumcision has been associated with lower risk of transmission of HIV from women to men (WHO and UNAIDS 2007). In the 2015 ZDHS, male respondents were asked whether or not they were circumcised. Overall, 14 percent of men age 15-49 are circumcised (Table 13.11). Trends: The percentage of men circumcised has increased from 9 percent in the 2010-11 ZDHS to 14 percent in the 2015 ZDHS. Almost all of this increase is due to the increase in circumcision among men 15-24. As shown in Figure 13.7, the percentage of men circumcised has increased more than four- fold, from 5 percent to 23 percent, among young men age 15-19, and from 8 percent to 13 percent among young men age 20-24. Patterns by background characteristics  Male circumcision is highest in Bulawayo (33 percent) and lowest in Mashonaland Central (7 percent) (Table 13.11).  By religion, male circumcision is highest among men of the Muslim faith, two-thirds of whom (67 percent) are circumcised. Circumcision in other religious groups or men with no religion ranges from 10 to 22 percent. Figure 13.7 Trends in male circumcision by age 9 5 8 11 11 12 14 23 13 10 12 10 Total 15-49 15-19 20-24 25-29 30-39 40-49 Percentage of men 2010-11 2015 HIV/AIDS-related Knowledge Attitudes, and Behaviour • 245 13.8 SELF-REPORTING OF SEXUALLY TRANSMITTED INFECTIONS Sexually transmitted infections (STIs) and symptoms Respondents who have ever had sex are asked whether they had an STI or symptoms of an STI (a bad-smelling, abnormal discharge from the vagina/penis or a genital sore or ulcer) in the 12 months before the survey. Sample: Women and men age 15-49 In the 2015 ZDHS, respondents who ever had sex were asked whether they had a sexually transmitted infection (STI) or symptoms of an STI in the 12 months preceding the survey. Women and men were equally likely to report an STI or symptoms ofan STI in the 12 months preceding the survey (2 percent and 3 percent, respectively) (Table 13.12). Four to five percent of women and men who ever had sexual intercourse reported having a bad smelling or abnormal genital discharge and a genital sore or ulcer, while 8 percent overall reported having either an STI or symptoms of an STI. Among respondents who reported having an STI or symptoms of an STI, 48 percent of women and 55 percent of men sought no advice or treatment. Among those who did seek advice or treatment, most consulted a clinic, hospital, private doctor, or other health professional (Figure 13.8). 13.9 INJECTIONS Overuse of injections can contribute to the transmission of blood-borne pathogens because it amplifies the effect of unsafe practices such as reuse of injection equipment. The ZDHS respondents were asked whether they had received any injections from a health worker in the 12 months before the survey, and if so, whether their last injection was administered with a syringe from a new, unopened package. It should be noted that self-administered medical injections such as insulin injections for diabetics were not included in the calculations. Thirty percent of women and 16 percent of men received an injection from a health worker in the 12 months preceding the survey (Table 13.13). Ninety-eight percent of women and 97 percent of men reported that for their last injection, the syringe and needle were removed from a new, unopened package. 13.10 HIV/AIDS-RELATED KNOWLEDGE AND BEHAVIOUR AMONG YOUNG PEOPLE This section addresses HIV/AIDS-related knowledge among young people age 15-24 and also assesses the extent to which Zimbabwean young people are engaged in behaviours that may place them at risk of acquiring HIV. 13.10.1 Knowledge about HIV/AIDS and Source for Condoms Knowledge of how HIV is transmitted is crucial to enabling individuals to avoid HIV infection. This is especially true for young people, who are often at greater risk because they may have shorter relationships with more partners or may engage in other risky behaviours. In Zimbabwe, 46 percent of young women and 47 percent of young men have comprehensive knowledge of HIV (defined as knowing that both Figure 13.8 STI advice or treatment seeking behaviour 48 1 3 48 37 2 7 55 Clinic/hospital/ private doctor/other health professional Advice or medicine from shop/ pharmacy Advice or treatment from any other source No advice or treatment Percentage of women and men age 15-49 with an STI or STI symptoms Women Men 246 • HIV/AIDS-related Knowledge Attitudes, and Behaviour consistent condom use and limiting sexual intercourse to one uninfected partner are HIV prevention methods, knowing that a healthy-looking person can have HIV, and rejecting the two most common local misconceptions about HIV transmission) (Table 13.14). Among both sexes, the proportion with comprehensive knowledge increases with age and educational attainment. Urban young people are more likely than rural young people to have comprehensive knowledge of HIV/AIDS. Although fewer than half of young people have comprehensive knowledge of HIV, knowledge of a source for condoms is relatively high. Forty-eight percent of young women and 86 percent of young men know a place where they can obtain a condom. 13.10.2 First Sex Young people who initiate sex at an early age are typically at higher risk of becoming pregnant or acquiring an STI than young people who initiate sex later. Consistent condom use can reduce such risks. In Zimbabwe, 5 percent women and 6 percent men age 15-24 reported having sex before age 15 (Table 13.15 and Figure 13.9). Among those age 18-24, 40 percent of young women and 29 percent of young men report having sex by age 18. Trends: The percentage of young women and men age 15-19 who had sex by age 15 has remained fairly stable across the past three ZDHS surveys, varying between 4 and 5 percent for women and 4 and 6 percent for men. The percentage of young women and men age 18-19 who had sex by age 18 has also changed very little over this time. This varied between 36 and 39 percent for women and 30 and 32 percent for men. Patterns by background characteristics  Rural young women and men are more likely than their urban counterparts to have had sex before age 15 or age 18 (Table 13.15).  Variations by education level are vast among young women but not young men: 72 percent of women age 18-24 with primary education had sexual intercourse before the age of 18, compared with 6 percent of women with more than a secondary education. Among men, in contrast, the differences observed by education level are less pronounced. Figure 13.9 Age at first sex among young people 5 40 6 29 Sex by age 15 Sex by age 18 Percentage of women and men age 15-24 who had sex by age 15 and percentage of women and men age 18-24 who had sex by age 18 Women Men HIV/AIDS-related Knowledge Attitudes, and Behaviour • 247 13.10.3 Premarital Sex The 2015 ZDHS also collected information on the patterns of sexual activity among never-married young people age 15-24 in Zimbabwe. Seventy-nine percent of never-married young women and 60 percent of never-married young men age 15-24 reported that they have never engaged in sexual intercourse (Table 13.16). Fifteen percent of never- married young women reported that they had sexual intercourse in the past 12 months compared with 30 percent of never-married young men (Figure 13.10). Among never-married young people who had intercourse in the past 12 months, condom use at last sexual intercourse was much lower among young women than young men (50 percent versus 81 percent). Condom use at last sexual intercourse is more common among never-married young women and men in urban areas (57 percent and 87 percent, respectively) than among those in rural areas (43 percent and 78 percent, respectively). Condom use at last sexual intercourse generally increases with age and education. 13.10.4 Multiple Sexual Partners and Condom Use One percent of young women and 9 percent of young men report having multiple sexual partners in the 12 months before the survey (Tables 13.17.1 and 13.17.2). Among respondents with multiple partners in the past 12 months, 44 percent of young women and 66 percent of young men reported that they used a condom during their most recent sexual intercourse. Among those who had sexual intercourse in the past 12 months, 21 percent of young women and 80 percent of young men had sex with a non-marital, non- cohabitating partner. Condom use with non-marital, non-cohabitating partners is higher among young men than young women—84 percent of young men used a condom at last sex with this type of partner, compared with 57 percent of young women. 13.10.5 Age-mixing in Sexual Relationships In many societies, young women have sexual relationships with men who are considerably older. This practice contributes to the spread of HIV and other STIs because a younger, uninfected partner having sex with an older, infected partner can introduce the virus into the younger, uninfected cohort. In Zimbabwe, 17 percent of young women age 15-19 who had sexual intercourse in the past 12 months had sex with a man 10 or more years older than them (Table 13.18). None of young men age 15-19 who had sexual intercourse in the past 12 months and who were interviewed in the 2015 ZDHS reported having a partner 10 or more years older (data not shown). 13.10.6 Coverage of HIV Testing Services Seeking an HIV test may be more difficult for young people than adults because many young people lack experience in accessing health services; and there are often barriers to young people obtaining services. In Zimbabwe, among women and men who have been sexually active in the past 12 months, 63 percent of young women and 39 percent of young men have been tested for HIV in the past 12 months and received the results of the test (Table 13.19). Coverage of HIV testing is fairly even across urban and rural areas. Among both young women and men, HIV testing generally increases with age and level of education. Figure 13.10 Premarital sex and condom use among young people 15 50 30 81 Percent who had sexual intercourse in past 12 months Percent who used a condom at last sex (among those who had sexual intercourse in past 12 months) Percentage of never-married women and men age 15-24 Women Men 248 • HIV/AIDS-related Knowledge Attitudes, and Behaviour Trends: Coverage of HIV testing services among young people has improved dramatically over the past five years. Among young women who were sexually active in the past 12 months, the percentage who were tested for HIV in the past 12 months and received the result increased from 45 percent in the 2010-11 ZDHS to 63 percent in the 2015 ZDHS. Among men, this figure increased from 24 percent to 39 percent. LIST OF TABLES For detailed information on HIV/AIDS-related knowledge, attitudes, and behaviour, see the following tables:  Table 13.1 Knowledge of HIV or AIDS  Table 13.2 Knowledge of HIV prevention methods  Table 13.3.1 Comprehensive knowledge about HIV: Women  Table 13.3.2 Comprehensive knowledge about HIV: Men  Table 13.4 Knowledge of prevention of mother-to-child transmission of HIV  Table 13.5 Discriminatory attitudes towards people living with HIV  Table 13.6 Attitudes towards negotiating safer sexual relations with husband  Table 13.7.1 Multiple sexual partners and higher-risk sexual intercourse in the past 12 months: Women  Table 13.7.2 Multiple sexual partners and higher-risk sexual intercourse in the past 12 months: Men  Table 13.8 Payment for sexual intercourse and condom use at last paid sexual intercourse  Table 13.9.1 Coverage of prior HIV testing: Women  Table 13.9.2 Coverage of prior HIV testing: Men  Table 13.10 Pregnant women counselled and tested for HIV  Table 13.11 Male circumcision  Table 13.12 Self-reported prevalence of sexually transmitted infections (STIs) and STI symptoms  Table 13.13 Prevalence of medical injections  Table 13.14 Comprehensive knowledge about HIV/AIDS and of a source of condoms among young people  Table 13.15 Age at first sexual intercourse among young people  Table 13.16 Premarital sexual intercourse and condom use during premarital sexual intercourse among young people  Table 13.17.1 Multiple sexual partners and higher-risk sexual intercourse in the past 12 months among young people: Women  Table 13.17.2 Multiple sexual partners and higher-risk sexual intercourse in the past 12 months among young people: Men  Table 13.18 Age-mixing in sexual relationships among women age 15-19  Table 13.19 Recent HIV tests among young people HIV/AIDS-related Knowledge Attitudes, and Behaviour • 249 Table 13.1 Knowledge of HIV or AIDS Percentage of women and men age 15-49 who have heard of HIV or AIDS, by background characteristics, Zimbabwe 2015 Women Men Background characteristic Has heard of HIV or AIDS Number of women Has heard of HIV or AIDS Number of men Age 15-24 98.4 3,895 98.7 3,456 15-19 97.8 2,199 98.1 2,126 20-24 99.1 1,697 99.6 1,330 25-29 99.4 1,657 99.8 1,148 30-39 99.6 2,855 99.7 2,036 40-49 99.5 1,548 99.7 1,400 Marital status Never married 98.3 2,511 98.7 3,624 Ever had sex 98.9 670 99.8 1,680 Never had sex 98.1 1,841 97.8 1,943 Married/living together 99.3 6,151 99.7 4,010 Divorced/separated/ widowed 99.7 1,292 99.6 407 Residence Urban 99.7 3,829 99.8 2,900 Rural 98.7 6,126 98.9 5,140 Province Manicaland 99.4 1,266 99.4 1,072 Mashonaland Central 98.4 882 99.2 806 Mashonaland East 97.7 952 99.3 807 Mashonaland West 99.3 1,160 99.7 1,004 Matabeleland North 98.1 465 99.2 366 Matabeleland South 99.2 419 99.4 335 Midlands 99.1 1,263 98.9 986 Masvingo 99.1 1,187 97.7 843 Harare 99.9 1,783 99.8 1,412 Bulawayo 99.5 577 100.0 409 Education No education 94.9 126 (90.3) 38 Primary 97.9 2,571 97.9 1,803 Secondary 99.5 6,527 99.7 5,349 More than secondary 100.0 731 99.8 849 Wealth quintile Lowest 97.7 1,704 98.5 1,212 Second 98.2 1,693 98.3 1,448 Middle 99.6 1,748 99.2 1,558 Fourth 99.7 2,307 99.9 1,852 Highest 99.7 2,503 99.9 1,970 Total 15-49 99.1 9,955 99.3 8,041 50-54 na na 99.6 355 Total 15-54 na na 99.3 8,396 na = Not applicable 250 • HIV/AIDS-related Knowledge Attitudes, and Behaviour Table 13.2 Knowledge of HIV prevention methods Percentage of women and men age 15-49 who, in response to prompted questions, say that people can reduce the risk of getting HIV by using condoms every time they have sexual intercourse, and by having one sex partner who is not infected and has no other partners, according to background characteristics, Zimbabwe 2015 Women Men Background characteristic Using condoms1 Limiting sexual intercourse to one uninfected partner2 Using condoms and limiting sexual intercourse to one uninfected partner1,2 Number of women Using condoms1 Limiting sexual intercourse to one uninfected partner2 Using condoms and limiting sexual intercourse to one uninfected partner1,2 Number of men Age 15-24 75.9 87.4 70.6 3,895 83.9 89.6 78.1 3,456 15-19 71.3 85.3 66.0 2,199 81.0 86.6 73.6 2,126 20-24 81.9 90.1 76.5 1,697 88.4 94.5 85.3 1,330 25-29 87.4 92.1 83.1 1,657 91.7 94.8 87.6 1,148 30-39 89.9 95.4 87.1 2,855 91.5 97.4 89.8 2,036 40-49 87.4 94.2 83.6 1,548 91.9 96.8 90.1 1,400 Marital status Never married 74.9 88.0 70.6 2,511 84.6 90.0 78.9 3,624 Ever had sex 79.9 91.4 76.2 670 88.7 92.6 83.5 1,680 Never had sex 73.1 86.8 68.6 1,841 81.1 87.8 74.9 1,943 Married/living together 86.1 92.7 82.1 6,151 91.5 96.6 89.3 4,010 Divorced/separated/ widowed 88.7 92.5 83.9 1,292 89.5 95.9 87.7 407 Residence Urban 87.4 94.4 84.2 3,829 90.6 96.0 88.1 2,900 Rural 81.2 89.7 76.5 6,126 87.0 92.2 82.4 5,140 Province Manicaland 78.7 88.0 73.1 1,266 89.3 95.8 87.2 1,072 Mashonaland Central 84.4 90.7 79.8 882 88.0 90.8 81.7 806 Mashonaland East 78.9 86.4 72.9 952 91.7 93.9 87.5 807 Mashonaland West 84.2 93.5 81.4 1,160 89.5 94.5 85.5 1,004 Matabeleland North 80.1 91.2 76.4 465 84.8 93.6 81.5 366 Matabeleland South 82.2 91.3 78.5 419 86.3 94.2 82.5 335 Midlands 85.0 95.1 82.6 1,263 87.9 91.9 84.0 986 Masvingo 85.0 90.6 79.9 1,187 81.4 89.7 76.3 843 Harare 87.6 95.0 84.7 1,783 90.3 95.3 87.6 1,412 Bulawayo 85.7 88.5 78.7 577 89.9 96.0 86.4 409 Education No education 75.8 80.2 67.6 126 (75.8) (80.7) (74.5) 38 Primary 77.4 86.3 72.1 2,571 80.7 87.9 74.3 1,803 Secondary 85.2 93.0 81.2 6,527 90.2 95.0 86.9 5,349 More than secondary 92.8 98.4 91.8 731 93.3 97.4 91.5 849 Wealth quintile Lowest 79.1 87.2 73.7 1,704 84.4 91.8 80.1 1,212 Second 80.4 88.7 75.0 1,693 85.4 91.9 81.3 1,448 Middle 81.8 92.0 78.4 1,748 87.7 91.7 82.6 1,558 Fourth 86.6 93.0 82.6 2,307 90.0 94.9 86.5 1,852 Highest 87.4 94.7 84.2 2,503 91.8 96.1 89.2 1,970 Total 15-49 83.6 91.5 79.4 9,955 88.3 93.6 84.5 8,041 50-54 na na na na 88.8 92.9 85.6 355 Total 15-54 na na na na 88.3 93.5 84.5 8,396 na = Not applicable. 1 Using condoms every time they have sexual intercourse. 2 Partner who has no other partners. HIV/AIDS-related Knowledge Attitudes, and Behaviour • 251 Table 13.3.1 Comprehensive knowledge about HIV: Women Percentage of women age 15-49 who say that a healthy-looking person can have HIV and who, in response to prompted questions, correctly reject local misconceptions about transmission or prevention of HIV, and the percentage with a comprehensive knowledge about HIV, according to background characteristics, Zimbabwe 2015 Percentage of women who say that: Percentage who say that a healthy looking person can have HIV and who reject the two most common local miscon- ceptions1 Percentage with a comprehensive knowledge about HIV2 Number of women Background characteristic A healthy-looking person can have HIV HIV cannot be transmitted by mosquito bites HIV cannot be transmitted by supernatural means A person cannot become infected by sharing food with a person who has HIV Age 15-24 78.9 79.3 91.4 89.1 60.1 46.3 3,895 15-19 74.3 78.7 89.6 87.9 56.4 41.4 2,199 20-24 84.8 80.1 93.6 90.6 64.9 52.8 1,697 25-29 86.2 81.5 92.1 90.7 66.9 57.9 1,657 30-39 90.2 79.7 93.5 93.2 69.7 62.9 2,855 40-49 90.1 75.1 91.7 89.9 64.7 56.3 1,548 Marital status Never married 78.2 81.8 90.8 90.4 63.0 49.1 2,511 Ever had sex 84.2 80.8 90.8 91.5 67.5 55.4 670 Never had sex 76.1 82.2 90.8 90.0 61.4 46.8 1,841 Married/living together 86.9 78.5 92.7 90.8 65.1 56.0 6,151 Divorced/separated/ widowed 90.0 77.1 92.2 90.5 66.2 58.1 1,292 Residence Urban 90.4 84.2 93.6 94.3 73.9 64.1 3,829 Rural 81.8 76.0 91.2 88.4 59.0 48.6 6,126 Province Manicaland 83.8 77.7 94.6 89.9 62.1 49.0 1,266 Mashonaland Central 77.7 83.1 91.2 92.6 62.4 53.3 882 Mashonaland East 78.7 74.4 87.5 87.9 57.6 46.3 952 Mashonaland West 89.5 77.2 91.6 89.4 65.5 56.5 1,160 Matabeleland North 81.9 71.9 89.8 85.9 53.7 43.7 465 Matabeleland South 80.8 73.5 89.6 85.5 56.0 46.3 419 Midlands 87.5 80.1 93.6 91.1 66.8 58.2 1,263 Masvingo 83.6 79.8 91.1 87.9 63.3 54.3 1,187 Harare 90.5 81.6 94.3 95.1 72.4 62.9 1,783 Bulawayo 87.5 86.8 92.9 95.0 74.0 60.0 577 Education No education 76.6 45.6 73.7 66.7 35.0 27.3 126 Primary 78.5 69.0 87.5 82.9 49.9 39.9 2,571 Secondary 86.4 82.1 93.9 93.4 68.3 57.7 6,527 More than secondary 97.4 94.2 95.8 97.2 89.7 82.9 731 Wealth quintile Lowest 79.4 70.4 88.9 83.4 51.4 41.4 1,704 Second 78.8 74.9 91.5 87.7 56.6 45.6 1,693 Middle 84.0 79.0 92.1 91.1 63.5 52.8 1,748 Fourth 88.2 80.5 93.6 93.4 68.6 59.3 2,307 Highest 91.2 86.8 93.5 94.8 76.6 66.4 2,503 Total 15-49 85.1 79.1 92.1 90.7 64.7 54.6 9,955 1 Two most common local misconceptions: HIV can be transmitted by mosquito bites and by sharing food with a person who has HIV 2 Comprehensive knowledge means knowing that consistent use of condoms during sexual intercourse and having just one uninfected faithful partner can reduce the chance of getting HIV, knowing that a healthy-looking person can have HIV, and rejecting the two most common local misconceptions about HIV transmission or prevention. 252 • HIV/AIDS-related Knowledge Attitudes, and Behaviour Table 13.3.2 Comprehensive knowledge about HIV: Men Percentage of men age 15-49 who say that a healthy-looking person can have HIV and who, in response to prompted questions, correctly reject local misconceptions about transmission or prevention of HIV, and the percentage with a comprehensive knowledge about HIV, according to background characteristics, Zimbabwe 2015 Percentage of men who say that: Percentage who say that a healthy looking person can have HIV and who reject the two most common local miscon- ceptions1 Percentage with a comprehensive knowledge about HIV2 Number of men Background characteristic A healthy-looking person can have HIV HIV cannot be transmitted by mosquito bites HIV cannot be transmitted by supernatural means A person cannot become infected by sharing food with a person who has HIV Age 15-24 80.3 73.4 89.8 86.3 55.3 46.6 3,456 15-19 75.5 73.2 88.1 84.2 51.1 41.4 2,126 20-24 87.9 73.7 92.4 89.8 62.2 54.9 1,330 25-29 90.7 74.9 93.5 91.0 65.4 58.4 1,148 30-39 93.5 79.5 93.8 91.5 71.8 65.1 2,036 40-49 91.9 78.1 91.9 91.1 68.7 63.2 1,400 Marital status Never married 81.5 74.3 89.5 86.4 57.3 48.7 3,624 Ever had sex 88.1 72.4 90.4 87.9 60.8 53.3 1,680 Never had sex 75.8 76.0 88.7 85.1 54.2 44.8 1,943 Married/living together 91.7 77.7 93.8 91.5 68.4 62.0 4,010 Divorced/separated/ widowed 91.3 74.2 90.1 90.5 65.8 59.0 407 Residence Urban 91.8 82.8 93.2 94.1 73.8 66.5 2,900 Rural 84.5 72.1 90.8 86.4 57.3 49.9 5,140 Province Manicaland 85.8 80.6 96.1 89.9 65.6 59.1 1,072 Mashonaland Central 84.0 75.6 88.8 89.3 60.0 51.2 806 Mashonaland East 89.7 75.8 90.6 90.6 65.5 59.5 807 Mashonaland West 85.3 79.7 94.1 91.7 65.4 57.5 1,004 Matabeleland North 86.1 64.8 87.8 82.8 50.9 44.3 366 Matabeleland South 89.6 60.1 87.8 77.5 48.4 41.6 335 Midlands 86.2 68.0 90.0 85.2 55.2 48.9 986 Masvingo 83.5 73.1 89.9 85.6 58.7 48.7 843 Harare 91.0 82.2 93.3 94.4 73.3 66.4 1,412 Bulawayo 91.3 82.2 91.4 91.8 70.9 63.0 409 Education No education (72.8) (53.9) (79.1) (67.7) (33.6) (32.1) 38 Primary 79.3 61.5 85.8 78.0 42.6 33.4 1,803 Secondary 88.5 78.1 93.2 91.9 66.5 59.6 5,349 More than secondary 95.8 94.0 95.6 96.3 88.1 81.3 849 Wealth quintile Lowest 84.4 67.4 88.1 84.4 52.7 44.9 1,212 Second 81.7 69.7 91.7 84.4 53.5 46.5 1,448 Middle 84.0 73.3 91.0 86.7 58.2 51.1 1,558 Fourth 89.8 78.8 93.3 91.5 67.8 60.0 1,852 Highest 92.7 85.3 93.1 95.2 76.7 69.4 1,970 Total 15-49 87.1 76.0 91.7 89.1 63.3 55.9 8,041 50-54 92.0 69.2 91.9 84.9 59.1 52.2 355 Total 15-54 87.3 75.7 91.7 89.0 63.1 55.7 8,396 1 Two most common local misconceptions: HIV can be transmitted by mosquito bites and by sharing food with a person who has HIV 2 Comprehensive knowledge means knowing that consistent use of condoms during sexual intercourse and having just one uninfected faithful partner can reduce the chance of getting HIV, knowing that a healthy-looking person can have HIV, and rejecting the two most common local misconceptions about HIV transmission or prevention. HIV/AIDS-related Knowledge Attitudes, and Behaviour • 253 Table 13.4 Knowledge of prevention of mother-to-child transmission of HIV Percentage of women and men age 15-49 who know that HIV can be transmitted from mother to child by breastfeeding and that the risk of mother-to-child transmission (MTCT) of HIV can be reduced by mother taking special drugs during pregnancy, according to background characteristics, Zimbabwe 2015 Women Men Background characteristic HIV can be transmitted by breastfeeding Risk of MTCT can be reduced by mother taking special drugs HIV can be transmitted by breastfeeding and risk of MTCT can be reduced by mother taking special drugs Number of women HIV can be transmitted by breastfeeding Risk of MTCT can be reduced by mother taking special drugs HIV can be transmitted by breastfeeding and risk of MTCT can be reduced by mother taking special drugs Number of men Age 15-24 75.2 86.3 70.3 3,895 69.0 79.4 59.0 3,456 15-19 68.8 82.1 62.8 2,199 64.1 75.0 52.9 2,126 20-24 83.6 91.8 80.0 1,697 76.8 86.3 68.7 1,330 25-29 87.3 94.3 84.7 1,657 80.3 87.8 73.1 1,148 30-39 86.4 95.3 84.4 2,855 80.9 92.2 76.9 2,036 40-49 81.8 93.9 79.4 1,548 79.4 91.4 74.6 1,400 Marital status Never married 71.5 84.3 65.9 2,511 69.0 79.2 58.9 3,624 Ever had sex 81.9 89.2 78.2 670 75.9 83.6 65.7 1,680 Never had sex 67.8 82.5 61.4 1,841 63.0 75.3 52.9 1,943 Married/living together 84.9 93.7 82.2 6,151 80.8 91.7 76.3 4,010 Divorced/separated/ widowed 84.6 94.6 82.5 1,292 79.3 88.2 72.3 407 Currently pregnant Pregnant 81.5 91.6 77.4 632 na na na na Not pregnant or not sure 81.5 91.4 78.2 9,323 na na na na Residence Urban 83.6 93.6 81.0 3,829 76.5 89.0 70.0 2,900 Rural 80.1 90.0 76.3 6,126 74.8 84.2 67.3 5,140 Province Manicaland 72.1 86.4 65.3 1,266 73.1 86.9 68.0 1,072 Mashonaland Central 83.8 93.2 82.0 882 75.8 88.6 72.0 806 Mashonaland East 72.5 89.8 70.2 952 77.6 88.5 70.9 807 Mashonaland West 83.1 91.5 79.6 1,160 75.7 90.0 70.7 1,004 Matabeleland North 80.7 89.2 75.6 465 79.9 78.3 65.8 366 Matabeleland South 83.2 88.0 79.8 419 69.5 81.3 59.5 335 Midlands 83.3 91.3 79.5 1,263 73.6 80.8 63.5 986 Masvingo 87.9 94.0 86.3 1,187 76.7 81.6 69.1 843 Harare 84.4 93.9 81.8 1,783 75.6 88.3 68.5 1,412 Bulawayo 82.9 93.5 80.5 577 77.4 86.5 68.5 409 Education No education 76.5 83.8 70.6 126 (80.4) (74.6) (71.5) 38 Primary 78.1 86.5 73.2 2,571 72.8 78.9 63.4 1,803 Secondary 82.0 92.7 79.1 6,527 75.5 87.2 68.5 5,349 More than secondary 88.8 98.2 88.1 731 80.1 93.3 76.6 849 Wealth quintile Lowest 81.6 87.0 76.2 1,704 76.8 81.7 67.4 1,212 Second 78.4 89.7 74.5 1,693 73.5 83.9 67.2 1,448 Middle 79.4 92.0 76.5 1,748 73.0 83.6 65.1 1,558 Fourth 83.4 93.4 81.1 2,307 76.1 88.2 69.4 1,852 Highest 83.1 93.4 80.4 2,503 77.2 89.7 71.1 1,970 Total 15-49 81.5 91.4 78.1 9,955 75.4 85.9 68.3 8,041 50-54 na na na na 80.4 90.8 76.8 355 Total 15-54 na na na na 75.6 86.1 68.6 8,396 na = Not applicable 254 • HIV/AIDS-related Knowledge Attitudes, and Behaviour Table 13.5 Discriminatory attitudes towards people living with HIV Among women and men age 15-49 who have heard of HIV or AIDS, percentage who do not think that children living with HIV should be able to attend school with children who are HIV negative, percentage who would not buy fresh vegetables from a shopkeeper who has HIV, and percentage with discriminatory attitudes towards people living with HIV, according to background characteristics, Zimbabwe 2015 Women Men Background characteristic Percentage who do not think that children living with HIV should be able to attend school with children who are HIV negative Percentage who would not buy fresh vegetables from a shopkeeper who as HIV Percentage with discriminatory attitudes towards people living with HIV1 Number of women who have heard of HIV or AIDS Percentage who do not think that children living with HIV should be able to attend school with children who are HIV negative Percentage who would not buy fresh vegetables from a shopkeeper who as HIV Percentage with discriminatory attitudes towards people living with HIV1 Number of men who have heard of HIV or AIDS Age 15-24 8.4 25.4 28.5 3,833 11.9 22.6 27.3 3,410 15-19 9.8 27.9 31.5 2,151 14.0 26.7 32.0 2,085 20-24 6.7 22.2 24.8 1,681 8.6 16.2 19.9 1,325 25-29 5.3 17.3 19.5 1,648 6.7 12.4 15.5 1,145 30-39 4.4 14.2 15.9 2,844 5.4 10.5 13.8 2,030 40-49 5.9 15.7 18.2 1,539 6.2 11.0 14.5 1,396 Marital status Never married 8.0 22.5 25.7 2,469 11.6 22.2 26.6 3,576 Ever had sex 7.7 17.0 20.0 663 10.9 18.9 23.4 1,677 Never had sex 8.1 24.5 27.8 1,806 12.2 25.0 29.5 1,900 Married/living together 5.9 18.7 20.9 6,106 5.9 10.8 14.2 3,999 Divorced/separated/ widowed 5.0 16.3 18.4 1,289 7.5 13.1 17.4 405 Residence Urban 4.0 15.3 17.1 3,818 4.9 10.9 13.8 2,895 Rural 7.8 21.9 24.7 6,045 10.5 18.9 23.5 5,085 Province Manicaland 11.0 26.4 29.8 1,258 5.9 18.6 20.4 1,065 Mashonaland Central 5.1 22.0 23.4 868 7.4 16.9 19.4 799 Mashonaland East 8.9 20.9 25.1 930 8.9 12.8 17.5 801 Mashonaland West 4.5 17.8 20.3 1,152 6.9 11.8 16.1 1,001 Matabeleland North 11.9 20.9 25.9 456 20.6 26.5 34.0 363 Matabeleland South 10.7 20.9 23.3 416 20.4 29.2 36.3 333 Midlands 4.4 16.7 18.0 1,251 11.3 15.7 21.7 976 Masvingo 4.3 18.4 20.1 1,176 10.5 20.6 25.8 824 Harare 2.4 15.7 16.4 1,782 3.6 11.0 13.0 1,409 Bulawayo 10.5 16.9 22.9 574 6.6 13.2 15.9 409 Education No education 18.3 28.2 34.2 119 (20.2) (31.2) (37.9) 35 Primary 10.7 29.4 32.5 2,516 17.0 27.0 34.2 1,766 Secondary 5.0 16.8 19.1 6,497 6.6 13.8 17.1 5,333 More than secondary 1.3 5.4 6.6 731 2.1 6.3 7.7 847 Wealth quintile Lowest 9.3 26.3 29.7 1,665 11.8 21.5 26.8 1,194 Second 8.3 23.8 26.5 1,662 12.0 18.1 23.6 1,424 Middle 7.4 20.0 22.8 1,742 10.1 20.1 24.0 1,546 Fourth 4.9 16.9 18.9 2,299 7.2 13.4 16.7 1,849 Highest 3.7 13.4 15.2 2,496 4.0 10.5 13.0 1,968 Total 15-49 6.3 19.3 21.8 9,864 8.5 16.0 19.9 7,981 50-54 na na na na 8.5 20.7 22.2 354 Total 15-54 na na na na 8.5 16.2 20.0 8,335 na = Not applicable 1 Percentage who do not think that children living with HIV should be able to attend school with children who are HIV negative or would not buy fresh vegetables from a shopkeeper who has HIV HIV/AIDS-related Knowledge Attitudes, and Behaviour • 255 Table 13.6 Attitudes toward negotiating safer sexual relations with husband Percentage of women and men age 15-49 who believe that a woman is justified in refusing to have sexual intercourse with her husband if she knows that he has sexual intercourse with other women, and percentage who believe that a woman is justified in asking that they use a condom if she knows that her husband has a sexually transmitted infection (STI), according to background characteristics, Zimbabwe 2015 Women Men Background characteristic Percentage who believe that a woman is justified in refusing to have sexual intercourse with her husband if she knows he has sex with other women Percentage who believe that a woman is justified in asking that they use a condom if she knows that her husband has an STI Number of women Percentage who believe that a woman is justified in refusing to have sexual intercourse with her husband if she knows he has sex with other women Percentage who believe that a woman is justified in asking that they use a condom if she knows that her husband has an STI Number of men Age 15-24 64.8 81.3 3,895 66.0 78.3 3,456 15-19 64.2 77.7 2,199 66.0 75.0 2,126 20-24 65.7 85.9 1,697 65.9 83.5 1,330 25-29 58.9 89.0 1,657 67.6 88.1 1,148 30-39 62.3 91.2 2,855 70.1 91.3 2,036 40-49 62.3 90.2 1,548 76.5 91.4 1,400 Marital status Never married 68.8 80.3 2,511 68.2 79.2 3,624 Ever had sex 73.0 85.2 670 70.8 83.2 1,680 Never had sex 67.2 78.6 1,841 66.0 75.8 1,943 Married/living together 61.1 88.6 6,151 70.6 90.7 4,010 Divorced/separated/ widowed 58.8 90.5 1,292 61.0 85.0 407 Residence Urban 72.1 91.0 3,829 78.3 92.4 2,900 Rural 56.9 84.1 6,126 63.8 81.2 5,140 Province Manicaland 58.8 84.2 1,266 65.3 83.3 1,072 Mashonaland Central 54.8 89.8 882 56.9 80.9 806 Mashonaland East 55.3 83.8 952 70.0 84.6 807 Mashonaland West 56.5 89.4 1,160 67.8 84.1 1,004 Matabeleland North 65.3 79.1 465 71.2 82.8 366 Matabeleland South 67.3 74.1 419 77.8 84.2 335 Midlands 61.1 87.3 1,263 65.1 84.9 986 Masvingo 63.0 85.3 1,187 65.8 80.4 843 Harare 70.9 91.2 1,783 78.1 91.4 1,412 Bulawayo 80.5 91.6 577 79.9 95.8 409 Education No education 53.8 82.6 126 (46.4) (72.4) 38 Primary 50.7 81.8 2,571 56.9 74.0 1,803 Secondary 65.2 87.8 6,527 70.5 87.2 5,349 More than secondary 84.7 96.0 731 86.8 97.4 849 Wealth quintile Lowest 52.0 80.9 1,704 60.0 77.8 1,212 Second 57.9 84.0 1,693 62.5 80.9 1,448 Middle 56.0 84.6 1,748 64.4 81.1 1,558 Fourth 64.8 90.6 2,307 71.4 88.2 1,852 Highest 76.0 90.7 2,503 81.0 93.5 1,970 Total 15-49 62.7 86.8 9,955 69.1 85.3 8,041 50-54 na na na 70.0 89.6 355 Total 15-54 na na na 69.1 85.4 8,396 na = Not applicable 25 6 • H IV /A ID S -r el at ed K no w le dg e A tti tu de s, a nd B eh av io ur Ta bl e 13 .7 .1 M ul tip le s ex ua l p ar tn er s an d hi gh er -r is k se xu al in te rc ou rs e in th e pa st 1 2 m on th s: W om en A m on g al l w om en a ge 1 5- 49 , p er ce nt ag e w ho h ad s ex ua l i nt er co ur se w ith m or e th an o ne s ex ua l p ar tn er in t he p as t 1 2 m on th s; a m on g th os e ha vi ng m or e th an o ne p ar tn er in t he p as t 12 m on th s, p er ce nt ag e re po rti ng t ha t a co nd om w as u se d du rin g la st in te rc ou rs e; a m on g w om en w ho h ad s ex ua l i nt er co ur se in t he p as t 12 m on th s, p er ce nt ag e w ho h ad in te rc ou rs e in t he p as t 12 m on th s w ith a n on -m ar ita l, no n- co ha bi ta tin g pa rtn er ; a m on g w om en a ge 1 5- 49 w ho h ad s ex ua l i nt er co ur se in th e pa st 1 2 m on th s w ith a n on -m ar ita l, no n- co ha bi ta tin g pa rtn er , p er ce nt ag e w ho u se d a co nd om d ur in g la st s ex ua l i nt er co ur se w ith su ch a p ar tn er ; a nd a m on g w om en w ho e ve r h ad s ex ua l i nt er co ur se , m ea n nu m be r o f s ex ua l p ar tn er s du rin g th ei r l ife tim e, a cc or di ng to b ac kg ro un d ch ar ac te ris tic s, Z im ba bw e 20 15 A ll w om en W om en w ho h ad 2 + pa rtn er s in th e pa st 1 2 m on th s W om en w ho h ad s ex ua l in te rc ou rs e in th e pa st 1 2 m on th s W om en w ho h ad in te rc ou rs e in th e pa st 1 2 m on th s w ith a n on - m ar ita l, no n- co ha bi ta tin g pa rtn er 1 W om en w ho e ve r h ad s ex ua l in te rc ou rs e2 B ac kg ro un d ch ar ac te ris tic P er ce nt ag e w ho ha d 2+ p ar tn er s in th e pa st 1 2 m on th s N um be r o f w om en P er ce nt ag e w ho re po rte d us in g a co nd om d ur in g la st se xu al in te rc ou rs e N um be r o f w om en P er ce nt ag e w ho ha d in te rc ou rs e in th e pa st 1 2 m on th s w ith a n on -m ar ita l, no n- co ha bi ta tin g pa rtn er 1 N um be r o f w om en P er ce nt ag e w ho re po rte d us in g a co nd om d ur in g la st se xu al in te rc ou rs e w ith a n on -m ar ita l, no n- co ha bi ta tin g pa rtn er 1 N um be r o f w om en M ea n nu m be r o f se xu al p ar tn er s in lif et im e N um be r o f w om en A ge 15 -2 4 1. 3 3, 89 5 44 .2 52 21 .3 1, 93 0 56 .5 41 2 1. 5 2, 15 2 15 -1 9 0. 8 2, 19 9 * 18 28 .1 64 2 47 .0 18 0 1. 3 72 8 20 -2 4 2. 0 1, 69 7 (4 7. 3) 34 18 .0 1, 28 8 63 .8 23 1 1. 6 1, 42 3 25 -2 9 1. 2 1, 65 7 (5 2. 0) 20 12 .2 1, 46 3 77 .9 17 9 1. 8 1, 59 7 30 -3 9 1. 1 2, 85 5 (6 3. 8) 32 11 .3 2, 57 3 71 .2 29 2 1. 9 2, 80 3 40 -4 9 0. 5 1, 54 8 * 8 10 .9 1, 18 5 73 .6 13 0 1. 9 1, 52 7 M ar ita l s ta tu s N ev er m ar rie d 1. 5 2, 51 1 (5 7. 0) 37 99 .0 44 9 56 .3 44 4 2. 3 66 4 M ar rie d/ liv in g to ge th er 0. 6 6, 15 1 (9 .7 ) 35 0. 9 6, 01 7 53 .4 57 1. 5 6, 13 7 D iv or ce d/ se pa ra te d/ w id ow ed 3. 1 1, 29 2 (7 8. 2) 40 74 .4 68 6 77 .2 51 0 2. 8 1, 27 8 R es id en ce U rb an 1. 8 3, 82 9 58 .1 68 19 .4 2, 60 3 70 .6 50 6 2. 0 2, 97 3 R ur al 0. 7 6, 12 6 (3 6. 4) 44 11 .1 4, 54 8 62 .8 50 6 1. 6 5, 10 6 P ro vi nc e M an ic al an d 0. 3 1, 26 6 * 4 7. 4 90 6 63 .3 67 1. 5 1, 06 1 M as ho na la nd C en tra l 0. 6 88 2 * 5 7. 1 69 1 60 .7 49 1. 5 75 2 M as ho na la nd E as t 0. 6 95 2 * 6 10 .3 70 2 73 .3 72 1. 7 79 0 M as ho na la nd W es t 1. 4 1, 16 0 * 17 10 .7 87 0 69 .9 93 1. 7 95 2 M at ab el el an d N or th 0. 9 46 5 * 4 20 .6 35 2 54 .4 72 2. 3 39 3 M at ab el el an d S ou th 2. 0 41 9 * 8 33 .9 31 9 63 .1 10 8 2. 4 35 9 M id la nd s 1. 4 1, 26 3 * 17 13 .6 92 8 67 .2 12 7 1. 8 1, 01 9 M as vi ng o 0. 6 1, 18 7 * 7 9. 0 81 1 69 .4 73 1. 4 93 6 H ar ar e 1. 5 1, 78 3 * 27 18 .3 1, 18 0 71 .2 21 6 1. 9 1, 36 7 B ul aw ay o 2. 7 57 7 (5 4. 3) 16 34 .1 39 2 65 .1 13 4 2. 4 45 1 E du ca tio n N o ed uc at io n 1. 4 12 6 * 2 11 .1 99 * 11 1. 6 12 3 P rim ar y 1. 1 2, 57 1 (5 1. 3) 28 11 .7 2, 05 1 65 .2 24 1 1. 8 2, 31 8 S ec on da ry 1. 1 6, 52 7 47 .6 72 14 .4 4, 46 3 66 .6 64 1 1. 7 5, 02 3 M or e th an s ec on da ry 1. 4 73 1 * 11 22 .1 53 8 71 .5 11 9 1. 9 61 4 W ea lth q ui nt ile Lo w es t 0. 4 1, 70 4 * 7 9. 7 1, 31 6 54 .7 12 8 1. 6 1, 49 4 S ec on d 1. 0 1, 69 3 * 16 9. 6 1, 29 3 61 .6 12 5 1. 6 1, 42 9 M id dl e 1. 0 1, 74 8 * 17 13 .2 1, 25 0 65 .9 16 5 1. 7 1, 41 9 Fo ur th 1. 4 2, 30 7 (5 8. 5) 32 17 .1 1, 70 9 67 .4 29 2 2. 0 1, 89 1 H ig he st 1. 6 2, 50 3 (5 9. 3) 39 19 .1 1, 58 3 73 .6 30 2 1. 9 1, 84 6 To ta l 1 5- 49 1. 1 9, 95 5 49 .6 11 2 14 .1 7, 15 1 66 .7 1, 01 1 1. 8 8, 07 9 N ot e: F ig ur es in p ar en th es es a re b as ed o n 25 -4 9 un w ei gh te d ca se s. A n as te ris k in di ca te s th at a fi gu re is b as ed o n fe w er th an 2 5 un w ei gh te d ca se s an d ha s be en s up pr es se d. 1 A p er so n w ho w as n ot h er h us ba nd a nd d id n ot li ve w ith h er 2 M ea ns a re c al cu la te d ex cl ud in g re sp on de nt s w ho g av e no n- nu m er ic re sp on se s. H IV /A ID S -r el at ed K no w le dg e A tti tu de s, a nd B eh av io ur • 2 57 Ta bl e 13 .7 .2 M ul tip le s ex ua l p ar tn er s an d hi gh er -r is k se xu al in te rc ou rs e in th e pa st 1 2 m on th s: M en A m on g al l m en a ge 1 5- 49 , p er ce nt ag e w ho h ad s ex ua l i nt er co ur se w ith m or e th an o ne s ex ua l p ar tn er in th e pa st 1 2 m on th s; a m on g th os e ha vi ng m or e th an o ne p ar tn er in th e pa st 1 2 m on th s, p er ce nt ag e re po rti ng th at a c on do m w as u se d du rin g la st in te rc ou rs e; a m on g m en w ho h ad s ex ua l i nt er co ur se in th e pa st 1 2 m on th s, p er ce nt ag e w ho h ad in te rc ou rs e in th e pa st 1 2 m on th s w ith a n on -m ar ita l, no n- co ha bi ta tin g pa rtn er ; am on g m en a ge 1 5- 49 w ho h ad s ex ua l i nt er co ur se in th e pa st 1 2 m on th s w ith a n on -m ar ita l, no n- co ha bi ta tin g pa rtn er , p er ce nt ag e w ho u se d a co nd om d ur in g la st s ex ua l i nt er co ur se w ith s uc h a pa rtn er ; a nd a m on g m en w ho e ve r h ad s ex ua l i nt er co ur se , m ea n nu m be r o f s ex ua l p ar tn er s du rin g th ei r l ife tim e, a cc or di ng to b ac kg ro un d ch ar ac te ris tic s, Z im ba bw e 20 15 A ll m en M en w ho h ad 2 + pa rtn er s in th e pa st 1 2 m on th s M en w ho h ad s ex ua l i nt er co ur se in th e pa st 1 2 m on th s M en w ho h ad in te rc ou rs e in th e pa st 1 2 m on th s w ith a n on -m ar ita l, no n- co ha bi ta tin g pa rtn er 1 M en w ho e ve r h ad s ex ua l in te rc ou rs e2 B ac kg ro un d ch ar ac te ris tic P er ce nt ag e w ho ha d 2+ p ar tn er s in th e pa st 1 2 m on th s N um be r o f m en P er ce nt ag e w ho re po rte d us in g a co nd om d ur in g la st se xu al in te rc ou rs e N um be r o f m en P er ce nt ag e w ho ha d in te rc ou rs e in th e pa st 1 2 m on th s w ith a n on -m ar ita l, no n- co ha bi ta tin g pa rtn er 1 N um be r o f m en P er ce nt ag e w ho re po rte d us in g a co nd om d ur in g la st se xu al in te rc ou rs e w ith a n on -m ar ita l, no n- co ha bi ta tin g pa rtn er 1 N um be r o f m en M ea n nu m be r o f se xu al p ar tn er s in lif et im e N um be r o f m en A ge 15 -2 4 9. 3 3, 45 6 65 .7 32 2 79 .6 1, 28 7 84 .1 1, 02 4 4. 0 1, 59 9 15 -1 9 3. 9 2, 12 6 71 .1 82 96 .6 41 5 78 .8 40 1 2. 7 57 5 20 -2 4 18 .0 1, 33 0 63 .8 24 0 71 .5 87 2 87 .5 62 3 4. 7 1, 02 3 25 -2 9 20 .0 1, 14 8 35 .2 23 0 42 .1 1, 00 9 86 .5 42 4 6. 3 1, 07 2 30 -3 9 19 .0 2, 03 6 23 .9 38 7 23 .0 1, 92 8 86 .6 44 4 7. 2 1, 94 9 40 -4 9 14 .7 1, 40 0 20 .3 20 5 12 .7 1, 30 1 87 .0 16 5 6. 8 1, 34 4 M ar ita l s ta tu s N ev er m ar rie d 9. 4 3, 62 4 80 .7 34 0 10 0. 0 1, 26 4 84 .8 1, 26 4 4. 5 1, 66 0 M ar rie d/ liv in g to ge th er 17 .9 4, 01 0 12 .4 71 9 14 .1 3, 98 4 85 .7 56 3 6. 3 3, 91 5 D iv or ce d/ se pa ra te d/ w id ow ed 21 .1 40 7 73 .8 86 83 .5 27 6 87 .4 23 1 10 .4 38 9 R es id en ce U rb an 16 .6 2, 90 0 46 .4 48 2 41 .7 2, 13 9 89 .3 89 1 7. 2 2, 23 8 R ur al 12 .9 5, 14 0 30 .6 66 3 34 .5 3, 38 6 82 .3 1, 16 7 5. 4 3, 72 6 P ro vi nc e M an ic al an d 11 .0 1, 07 2 44 .9 11 7 33 .2 67 2 86 .4 22 3 4. 9 75 5 M as ho na la nd C en tra l 13 .3 80 6 16 .9 10 7 25 .9 55 4 89 .0 14 3 4. 6 61 7 M as ho na la nd E as t 13 .3 80 7 35 .7 10 7 33 .4 55 0 87 .1 18 4 5. 3 58 9 M as ho na la nd W es t 15 .0 1, 00 4 32 .4 15 1 33 .9 68 8 85 .8 23 4 6. 1 75 8 M at ab el el an d N or th 15 .4 36 6 36 .1 57 47 .1 26 7 78 .2 12 6 5. 8 28 6 M at ab el el an d S ou th 17 .0 33 5 44 .9 57 57 .5 25 0 76 .8 14 3 7. 9 26 1 M id la nd s 15 .1 98 6 29 .2 14 9 35 .3 67 9 86 .0 24 0 6. 9 73 5 M as vi ng o 11 .9 84 3 34 .7 10 1 33 .5 53 0 79 .7 17 8 5. 4 57 6 H ar ar e 17 .1 1, 41 2 44 .3 24 2 42 .5 1, 04 3 89 .6 44 3 7. 4 1, 06 8 B ul aw ay o 13 .7 40 9 65 .8 56 49 .5 29 2 84 .7 14 4 6. 6 31 8 E du ca tio n N o ed uc at io n (0 .5 ) 38 * 0 (2 7. 9) 26 * 7 (5 .3 ) 31 P rim ar y 13 .3 1, 80 3 31 .3 24 0 36 .4 1, 20 8 80 .1 44 0 5. 0 1, 33 0 S ec on da ry 14 .4 5, 34 9 38 .2 77 2 38 .4 3, 56 5 86 .8 1, 36 8 6. 3 3, 85 3 M or e th an s ec on da ry 15 .6 84 9 43 .0 13 3 33 .4 72 6 87 .1 24 3 7. 0 75 0 W ea lth q ui nt ile Lo w es t 12 .3 1, 21 2 18 .7 14 9 25 .1 86 5 75 .3 21 7 5. 0 94 1 S ec on d 12 .1 1, 44 8 31 .6 17 5 33 .2 95 5 82 .4 31 7 5. 3 1, 06 1 M id dl e 13 .4 1, 55 8 31 .9 20 8 39 .7 96 6 84 .2 38 4 5. 5 1, 07 3 Fo ur th 15 .4 1, 85 2 43 .4 28 5 41 .0 1, 33 4 86 .5 54 7 6. 7 1, 41 4 H ig he st 16 .6 1, 97 0 46 .8 32 7 42 .2 1, 40 4 90 .3 59 2 7. 2 1, 47 6 To ta l 1 5- 49 14 .2 8, 04 1 37 .3 1, 14 4 37 .3 5, 52 4 85 .3 2, 05 8 6. 1 5, 96 4 50 -5 4 15 .6 35 5 33 .0 56 16 .1 33 1 85 .0 53 10 .7 33 1 To ta l 1 5- 54 14 .3 8, 39 6 37 .1 1, 20 0 36 .1 5, 85 5 85 .3 2, 11 1 6. 3 6, 29 5 N ot e: F ig ur es in p ar en th es es a re b as ed o n 25 -4 9 un w ei gh te d ca se s. A n as te ris k in di ca te s th at a fi gu re is b as ed o n fe w er th an 2 5 un w ei gh te d ca se s an d ha s be en s up pr es se d. 1 A p er so n w ho w as n ot h is w ife a nd d id n ot li ve w ith h im 2 M ea ns a re c al cu la te d ex cl ud in g re sp on de nt s w ho g av e no n- nu m er ic re sp on se s. 258 • HIV/AIDS-related Knowledge, Attitudes, and Behaviour Table 13.8 Payment for sexual intercourse and condom use at last paid sexual intercourse Percentage of men age 15-49 who ever paid for sexual intercourse and percentage reporting payment for sexual intercourse in the past 12 months, and among them, the percentage reporting that a condom was used the last time they paid for sexual intercourse, according to background characteristics, Zimbabwe 2015 Among all men: Among men who paid for sex in the past 12 months: Background characteristic Percentage who ever paid for sexual intercourse Percentage who paid for sexual intercourse in the past 12 months Number of men Percentage reporting condom use at last paid sexual intercourse Number of men Age 15-24 6.1 2.6 3,456 91.0 90 15-19 1.6 1.0 2,126 * 20 20-24 13.3 5.2 1,330 94.4 69 25-29 22.1 4.7 1,148 95.2 54 30-39 29.2 5.0 2,036 83.9 103 40-49 29.9 2.9 1,400 (94.8) 40 Marital status Never married 7.8 3.7 3,624 87.8 134 Married/living together 25.7 2.5 4,010 90.2 102 Divorced/separated/ widowed 40.3 12.2 407 (94.4) 49 Residence Urban 22.9 4.1 2,900 90.4 118 Rural 15.8 3.3 5,140 89.4 168 Province Manicaland 19.6 4.3 1,072 (94.0) 46 Mashonaland Central 16.2 2.9 806 (93.9) 24 Mashonaland East 17.8 3.1 807 * 25 Mashonaland West 20.0 3.6 1,004 (94.7) 37 Matabeleland North 9.6 2.3 366 * 9 Matabeleland South 15.7 3.4 335 (89.2) 11 Midlands 15.6 3.2 986 (87.7) 32 Masvingo 14.1 3.2 843 * 27 Harare 26.5 4.1 1,412 (100.0) 58 Bulawayo 14.1 4.3 409 (65.8) 18 Education No education (21.5) (6.5) 38 * 2 Primary 15.7 4.3 1,803 86.0 77 Secondary 19.0 3.6 5,349 91.8 192 More than secondary 20.3 1.7 849 * 14 Wealth quintile Lowest 15.7 2.9 1,212 (73.9) 35 Second 16.5 4.5 1,448 87.0 65 Middle 14.9 2.4 1,558 (100.0) 37 Fourth 22.6 3.9 1,852 95.6 73 Highest 20.3 3.9 1,970 89.1 76 Total 15-49 18.4 3.6 8,041 89.8 286 50-54 44.1 2.9 355 * 10 Total 15-54 19.5 3.5 8,396 90.2 296 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. HIV/AIDS-related Knowledge, Attitudes, and Behaviour • 259 Table 13.9.1 Coverage of prior HIV testing: Women Percentage of women age 15-49 who know where to get an HIV test, percent distribution of women age 15-49 by testing status and by whether they received the results of the last test, percentage of women ever tested, and percentage of women age 15-49 who were tested in the past 12 months and received the results of the last test, according to background characteristics, Zimbabwe 2015 Percentage who know where to get an HIV test Percent distribution of women by testing status and by whether they received the results of the last test Total Percentage ever tested Percentage who have been tested for HIV in the past 12 months and received the results of the last test Number of women Background characteristic Ever tested and received results Ever tested, did not receive results Never tested1 Age 15-24 90.2 62.7 1.2 36.1 100.0 63.9 42.0 3,895 15-19 87.0 46.3 1.6 52.1 100.0 47.9 29.8 2,199 20-24 94.3 84.0 0.7 15.2 100.0 84.8 57.8 1,697 25-29 95.1 91.2 0.8 7.9 100.0 92.1 60.7 1,657 30-39 96.7 92.4 1.0 6.6 100.0 93.4 54.1 2,855 40-49 97.8 85.8 1.0 13.2 100.0 86.8 43.4 1,548 Marital status Never married 88.9 47.8 1.2 51.0 100.0 49.0 27.0 2,511 Ever had sex 95.5 80.5 1.2 18.3 100.0 81.7 53.8 670 Never had sex 86.5 35.9 1.2 62.9 100.0 37.1 17.2 1,841 Married/living together 95.3 90.0 1.0 9.0 100.0 91.0 56.5 6,151 Divorced/separated/ widowed 98.0 91.4 1.0 7.5 100.0 92.5 54.3 1,292 Residence Urban 96.0 80.1 0.9 19.0 100.0 81.0 46.8 3,829 Rural 92.9 79.2 1.1 19.6 100.0 80.4 50.0 6,126 Province Manicaland 89.9 72.8 1.4 25.8 100.0 74.2 44.5 1,266 Mashonaland Central 93.5 78.8 1.3 19.9 100.0 80.1 54.7 882 Mashonaland East 91.4 77.8 2.1 20.1 100.0 79.9 45.8 952 Mashonaland West 95.1 82.1 0.2 17.7 100.0 82.3 47.1 1,160 Matabeleland North 95.8 84.8 0.8 14.4 100.0 85.6 51.1 465 Matabeleland South 94.5 81.4 0.6 18.0 100.0 82.0 51.6 419 Midlands 95.8 83.5 0.4 16.1 100.0 83.9 54.2 1,263 Masvingo 94.6 79.0 1.6 19.4 100.0 80.6 50.3 1,187 Harare 94.8 79.8 1.2 19.0 100.0 81.0 45.7 1,783 Bulawayo 97.4 79.3 0.6 20.1 100.0 79.9 47.9 577 Education No education 90.2 76.4 0.0 23.6 100.0 76.4 38.8 126 Primary 89.8 77.6 1.5 20.8 100.0 79.2 46.6 2,571 Secondary 95.2 79.2 0.9 19.9 100.0 80.1 49.5 6,527 More than secondary 99.4 90.1 1.0 8.9 100.0 91.1 51.5 731 Wealth quintile Lowest 90.3 79.0 1.2 19.8 100.0 80.2 48.3 1,704 Second 92.4 78.9 1.4 19.8 100.0 80.2 49.2 1,693 Middle 94.0 79.2 1.3 19.5 100.0 80.5 50.3 1,748 Fourth 95.2 81.5 0.7 17.8 100.0 82.2 52.1 2,307 Highest 96.7 78.8 0.9 20.2 100.0 79.8 44.7 2,503 Total 15-49 94.1 79.6 1.1 19.4 100.0 80.6 48.8 9,955 1 Includes ‘don’t know/missing’ 260 • HIV/AIDS-related Knowledge, Attitudes, and Behaviour Table 13.9.2 Coverage of prior HIV testing: Men Percentage of men age 15-49 who know where to get an HIV test, percent distribution of men age 15-49 by testing status and by whether they received the results of the last test, percentage of men ever tested, and percentage of men age 15-49 who were tested in the past 12 months and received the results of the last test, according to background characteristics, Zimbabwe 2015 Percentage who know where to get an HIV test Percent distribution of men by testing status and by whether they received the results of the last test Total Percentage ever tested Percentage who have been tested for HIV in the past 12 months and received the results of the last test Number of men Background characteristic Ever tested and received results Ever tested, did not receive results Never tested1 Age 15-24 90.6 45.3 2.1 52.5 100.0 47.5 26.4 3,456 15-19 86.8 35.0 2.7 62.4 100.0 37.6 19.4 2,126 20-24 96.8 61.9 1.3 36.8 100.0 63.2 37.7 1,330 25-29 98.2 74.3 1.1 24.6 100.0 75.4 50.1 1,148 30-39 98.6 77.1 1.2 21.7 100.0 78.3 42.7 2,036 40-49 98.8 73.4 1.7 24.9 100.0 75.1 37.7 1,400 Marital status Never married 90.7 45.2 1.9 52.9 100.0 47.1 25.3 3,624 Ever had sex 96.8 58.9 1.4 39.7 100.0 60.3 34.1 1,680 Never had sex 85.5 33.4 2.3 64.3 100.0 35.7 17.7 1,943 Married/living together 98.7 76.9 1.4 21.7 100.0 78.3 44.7 4,010 Divorced/separated/ widowed 98.7 72.6 2.4 25.0 100.0 75.0 42.9 407 Residence Urban 98.1 68.6 1.0 30.5 100.0 69.5 37.9 2,900 Rural 93.5 58.9 2.1 39.0 100.0 61.0 34.7 5,140 Province Manicaland 96.0 55.4 1.7 42.9 100.0 57.1 29.2 1,072 Mashonaland Central 93.8 60.3 2.8 36.9 100.0 63.1 39.6 806 Mashonaland East 95.3 64.3 0.7 35.1 100.0 64.9 36.6 807 Mashonaland West 96.6 67.1 1.5 31.4 100.0 68.6 40.4 1,004 Matabeleland North 94.8 58.4 2.6 38.9 100.0 61.1 31.6 366 Matabeleland South 92.5 62.0 2.1 35.9 100.0 64.1 40.0 335 Midlands 92.7 60.9 1.7 37.5 100.0 62.5 38.2 986 Masvingo 90.4 56.7 2.2 41.1 100.0 58.9 31.8 843 Harare 98.4 67.4 1.1 31.5 100.0 68.5 36.5 1,412 Bulawayo 98.5 72.0 1.8 26.2 100.0 73.8 34.3 409 Education No education (78.4) (46.5) (0.0) (53.5) 100.0 (46.5) (22.8) 38 Primary 88.6 48.0 3.1 48.9 100.0 51.1 28.7 1,803 Secondary 96.8 64.1 1.3 34.6 100.0 65.4 37.0 5,349 More than secondary 99.4 83.1 1.0 16.0 100.0 84.0 44.8 849 Wealth quintile Lowest 91.8 57.5 2.6 39.9 100.0 60.1 32.4 1,212 Second 93.4 58.0 2.2 39.8 100.0 60.2 35.1 1,448 Middle 93.6 58.3 2.0 39.7 100.0 60.3 34.7 1,558 Fourth 96.9 66.0 1.1 32.9 100.0 67.1 37.9 1,852 Highest 98.0 68.6 1.0 30.4 100.0 69.6 37.5 1,970 Total 15-49 95.1 62.4 1.7 35.9 100.0 64.1 35.9 8,041 50-54 98.2 76.0 2.2 21.8 100.0 78.2 36.4 355 Total 15-54 95.3 63.0 1.7 35.3 100.0 64.7 35.9 8,396 Note: Figures in parentheses are based on 25-49 unweighted cases. 1 Includes ‘don’t know/missing’ HIV/AIDS-related Knowledge, Attitudes, and Behaviour • 261 Table 13.10 Pregnant women counselled and tested for HIV Among all women age 15-49 who gave birth in the 2 years preceding the survey, the percentage who received HIV pretest counseling, the percentage who received an HIV test during antenatal care for their most recent birth by whether they received their results and post-test counseling, and percentage who received an HIV test at the time during ANC or labor for their most recent birth by whether they received their test results, according to background characteristics, Zimbabwe 2015 Percentage who received counseling on HIV during antenatal care1 Percentage who were tested for HIV during antenatal care and who: Percentage who received counseling on HIV and an HIV test during ANC, and the results Percentage who had an HIV test during ANC or labor and who: Number of women who gave birth in the past 2 years2 Background characteristic Received results and received post- test counseling Received results and did not receive post-test counseling Did not receive results Received results Did not receive results Age 15-24 67.9 71.4 18.2 1.0 66.7 91.3 0.9 966 15-19 62.1 69.2 19.5 2.6 59.8 90.9 2.8 310 20-24 70.6 72.4 17.6 0.3 70.0 91.5 0.0 656 25-29 72.2 69.5 18.2 0.8 71.3 89.4 0.7 651 30-39 79.3 75.5 14.1 0.6 77.5 90.7 0.5 740 40-49 69.9 69.4 12.5 0.0 69.9 83.6 0.0 96 Marital status Never married 70.8 76.6 16.9 0.5 70.8 95.3 0.5 130 Married or living together 72.5 71.7 16.8 0.7 71.4 89.9 0.5 2,126 Divorced/separated/ widowed 74.4 72.0 15.5 2.4 70.9 90.9 3.4 198 Residence Urban 79.5 73.4 18.8 0.9 78.0 94.8 1.0 689 Rural 69.9 71.5 15.9 0.8 68.7 88.6 0.6 1,765 Province Manicaland 71.0 68.7 12.1 0.7 70.2 82.4 0.3 396 Mashonaland Central 61.9 66.3 19.9 1.3 60.5 86.8 1.2 246 Mashonaland East 71.1 69.7 15.9 1.6 68.3 87.0 1.0 244 Mashonaland West 59.3 71.6 19.6 0.0 58.7 91.4 0.0 298 Matabeleland North 82.7 85.1 9.5 1.1 80.9 95.1 0.6 117 Matabeleland South 87.5 89.0 4.1 0.0 86.9 94.5 0.0 99 Midlands 81.7 81.8 12.4 0.0 80.7 95.6 0.0 338 Masvingo 70.4 65.5 23.6 0.8 69.8 91.3 0.8 299 Harare 77.0 66.8 22.7 1.7 74.7 93.1 2.3 324 Bulawayo 83.3 77.8 16.5 0.7 82.5 95.7 0.0 92 Education No education * * * * * * * 32 Primary 62.3 64.2 17.1 1.5 60.3 83.1 1.3 787 Secondary 76.7 75.9 16.1 0.5 75.7 93.5 0.4 1,534 More than secondary 89.8 75.3 23.4 0.3 88.8 99.2 0.0 101 Wealth quintile Lowest 66.3 68.3 15.2 1.2 64.7 85.3 0.9 610 Second 70.2 72.1 15.7 0.5 68.9 88.2 0.2 504 Middle 70.9 72.2 17.2 0.8 70.0 90.2 0.8 441 Fourth 77.0 71.8 18.7 1.0 75.7 93.5 1.4 550 Highest 82.0 78.7 17.2 0.3 80.9 97.3 0.0 349 Total 15-49 72.6 72.0 16.7 0.8 71.3 90.3 0.7 2,454 Note: An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. 1 In this context, “pretest counseling” means that someone talked with the respondent about all three of the following topics: 1) babies getting the AIDS virus from their mother, 2) preventing the virus, and 3) getting tested for the virus 2 Denominator for percentages includes women who did not receive antenatal care for their last birth in the past 2 years 262 • HIV/AIDS-related Knowledge, Attitudes, and Behaviour Table 13.11 Male circumcision Percentage of men age 15-49 who report having been circumcised, by background characteristics, Zimbabwe 2015 Background characteristic Percentage circumcised Number of men Age 15-24 18.8 3,456 15-19 22.6 2,126 20-24 12.8 1,330 25-29 10.0 1,148 30-39 11.6 2,036 40-49 10.4 1,400 Residence Urban 18.0 2,900 Rural 12.2 5,140 Province Manicaland 10.4 1,072 Mashonaland Central 6.8 806 Mashonaland East 9.5 807 Mashonaland West 10.5 1,004 Matabeleland North 18.2 366 Matabeleland South 26.4 335 Midlands 14.5 986 Masvingo 17.3 843 Harare 15.5 1,412 Bulawayo 33.4 409 Religion Traditional 10.3 208 Roman Catholic 13.8 645 Protestant 14.9 1,237 Pentecostal 17.6 1,413 Apostolic sect 11.2 2,585 Other Christian 21.8 487 Muslim 66.5 59 None 12.2 1,397 Other Christian 21.8 487 Total 15-49 14.3 8,041 50-54 14.3 355 Total 15-54 14.3 8,396 HIV/AIDS-related Knowledge, Attitudes, and Behaviour • 263 Table 13.12 Self-reported prevalence of sexually-transmitted infections (STIs) and STIs symptoms Among women and men age 15-49 who ever had sexual intercourse, the percentage reporting having an STI and/or symptoms of an STI in the past 12 months, by background characteristics, Zimbabwe 2015 Women Men Percentage of women who reported having in the past 12 months: Percentage of men who reported having in the past 12 months: Background characteristic STI Bad smelling/ abnormal genital discharge Genital sore/ulcer STI/genital discharge/ sore or ulcer Number of women who ever had sexual intercourse STI Bad smelling/ abnormal discharge from penis Genital sore/ulcer STI/ abnormal discharge from penis/ sore or ulcer Number of men who ever had sexual intercourse Age 15-24 1.9 5.4 4.4 9.2 2,154 2.1 6.6 5.7 11.1 1,606 15-19 1.5 6.5 4.5 10.3 728 0.7 6.7 5.1 10.3 576 20-24 2.2 4.8 4.3 8.7 1,426 2.8 6.5 6.0 11.5 1,030 25-29 2.5 5.5 4.3 9.3 1,610 3.2 3.9 5.9 9.0 1,092 30-39 2.2 4.5 3.7 7.3 2,819 3.0 2.9 3.9 7.5 2,007 40-49 2.3 3.8 3.8 7.1 1,532 1.8 2.2 4.4 6.1 1,392 Marital status Never married 2.2 5.6 3.8 8.9 670 2.2 5.7 5.2 9.9 1,680 Married/living together 2.0 4.6 3.8 7.8 6,151 2.3 2.7 4.4 7.1 4,010 Divorced/separated/ widowed 3.2 5.3 5.1 9.5 1,292 5.5 8.3 7.7 15.5 407 Male circumcision Circumcised na na na na na 2.3 3.1 4.5 7.9 777 Not circumcised na na na na na 2.5 4.0 4.9 8.5 5,313 Residence Urban 2.2 4.6 3.5 7.6 2,995 2.1 3.5 5.2 8.5 2,315 Rural 2.2 4.9 4.3 8.5 5,119 2.7 4.2 4.7 8.4 3,782 Province Manicaland 2.9 5.2 3.0 7.1 1,065 3.7 3.4 3.8 7.1 766 Mashonaland Central 1.5 5.8 5.0 10.0 752 2.5 4.0 8.4 10.5 629 Mashonaland East 2.0 4.3 5.1 9.4 791 2.2 2.4 3.6 5.6 610 Mashonaland West 1.6 5.7 6.3 11.2 954 2.7 3.1 3.3 6.5 760 Matabeleland North 4.0 4.6 4.3 9.8 396 2.6 4.1 2.7 7.3 291 Matabeleland South 2.3 3.8 3.4 6.5 359 4.6 4.5 6.0 9.7 267 Midlands 2.7 4.5 3.5 7.1 1,027 2.9 6.2 3.3 9.3 738 Masvingo 2.6 4.0 2.5 6.2 937 1.3 3.4 5.1 8.5 587 Harare 1.4 4.7 3.7 7.1 1,381 1.1 3.6 5.4 8.5 1,128 Bulawayo 2.5 4.9 3.6 9.1 452 4.4 5.5 8.9 14.2 321 Education No education 1.0 4.3 1.0 4.3 125 (0.0) (2.3) (0.0) (2.3) 31 Primary 2.4 5.2 4.9 9.6 2,324 2.4 4.5 6.0 9.5 1,348 Secondary 2.2 4.9 3.9 8.1 5,044 2.8 4.1 4.8 8.7 3,939 More than secondary 1.8 2.4 2.5 4.8 621 1.3 1.6 3.2 5.2 779 Wealth quintile Lowest 2.4 5.5 4.4 10.0 1,495 1.9 3.6 4.5 7.7 949 Second 2.4 5.0 4.6 8.5 1,429 3.8 5.4 4.6 9.5 1,073 Middle 2.0 4.1 4.1 7.7 1,423 2.8 4.6 5.6 9.3 1,091 Fourth 2.4 5.6 4.6 8.8 1,915 2.4 3.8 4.9 8.2 1,458 Highest 1.8 3.8 2.6 6.2 1,852 1.9 2.6 4.6 7.6 1,527 Total 15-49 2.2 4.8 4.0 8.2 8,114 2.5 3.9 4.9 8.4 6,097 50-54 na na na na na 2.2 1.8 2.7 5.0 354 Total 15-54 na na na na na 2.5 3.8 4.7 8.2 6,451 Note: Figures in parentheses are based on 25-49 unweighted cases. Total includes 7 men for whom information on circumcision is missing. na = Not applicable 264 • HIV/AIDS-related Knowledge, Attitudes, and Behaviour Table 13.13 Prevalence of medical injections Percentage of women and men age 15-49 who received at least one medical injection in the past 12 months, the average number of medical injections per person in the past 12 months, and among those who received a medical injection, percentage of last medical injections for which the syringe and needle were taken from a new, unopened package, according to background characteristics, Zimbabwe 2015 Women Men Background characteristic Percentage who received a medical injection in the past 12 months Average number of medical injections per person in the past 12 months Number of women For last injection, syringe and needle taken from a new, unopened package Number of women receiving medical injections in the past 12 months Percentage who received a medical injection in the past 12 months Average number of medical injections per person in the past 12 months Number of men For last injection, syringe and needle taken from a new, unopened package Number of men receiving medical injections in the past 12 months Age 15-24 27.5 0.5 3,895 97.8 1,070 16.6 0.4 3,456 95.2 574 15-19 24.0 0.4 2,199 97.7 529 18.7 0.4 2,126 95.9 397 20-24 31.9 0.6 1,697 98.0 542 13.2 0.3 1,330 93.7 176 25-29 34.9 0.8 1,657 98.6 579 13.2 0.4 1,148 98.0 151 30-39 30.8 0.7 2,855 98.5 880 16.4 0.5 2,036 98.7 335 40-49 26.4 0.7 1,548 97.8 409 13.9 0.5 1,400 97.1 195 Marital status Never married 21.1 0.4 2,511 97.7 529 16.4 0.4 3,624 95.4 595 Ever had sex 30.3 0.6 670 99.0 203 16.0 0.3 1,680 93.9 269 Never had sex 17.7 0.3 1,841 96.9 326 16.8 0.4 1,943 96.6 326 Married/living together 33.1 0.7 6,151 98.2 2,033 15.2 0.5 4,010 98.0 611 Divorced/separated/ widowed 29.1 0.7 1,292 98.8 376 12.0 0.3 407 98.0 49 Residence Urban 27.3 0.6 3,829 98.4 1,046 16.4 0.5 2,900 97.8 476 Rural 30.9 0.6 6,126 98.1 1,892 15.1 0.4 5,140 96.2 778 Province Manicaland 28.4 0.6 1,266 98.2 360 13.8 0.3 1,072 96.0 148 Mashonaland Central 28.6 0.7 882 98.1 252 14.2 0.4 806 95.2 114 Mashonaland East 39.1 0.8 952 96.9 372 20.0 0.4 807 99.6 161 Mashonaland West 29.5 0.6 1,160 97.9 342 11.6 0.2 1,004 97.9 116 Matabeleland North 39.3 0.7 465 99.5 183 18.4 0.5 366 94.3 67 Matabeleland South 31.2 0.5 419 99.5 131 34.0 1.0 335 93.2 114 Midlands 28.3 0.7 1,263 98.3 358 11.4 0.3 986 100.0 113 Masvingo 27.1 0.6 1,187 96.9 321 13.8 0.2 843 96.3 116 Harare 26.6 0.6 1,783 99.3 474 17.1 0.6 1,412 97.0 242 Bulawayo 25.2 0.5 577 98.6 145 15.1 0.4 409 95.3 62 Education No education 21.8 0.4 126 * 27 (9.6) (0.9) 38 * 4 Primary 28.3 0.5 2,571 97.8 728 15.2 0.4 1,803 93.8 275 Secondary 29.9 0.7 6,527 98.3 1,949 15.0 0.4 5,349 98.0 803 More than secondary 32.0 0.9 731 98.3 234 20.4 0.6 849 96.0 173 Wealth quintile Lowest 29.8 0.5 1,704 97.7 508 12.6 0.3 1,212 96.7 152 Second 29.9 0.6 1,693 98.3 505 13.9 0.3 1,448 97.6 201 Middle 32.2 0.7 1,748 98.1 563 15.8 0.4 1,558 94.3 247 Fourth 28.8 0.6 2,307 97.6 665 16.1 0.6 1,852 97.6 298 Highest 27.9 0.7 2,503 99.1 697 18.1 0.4 1,970 97.4 356 Total 15-49 29.5 0.6 9,955 98.2 2,938 15.6 0.4 8,041 96.8 1,254 50-54 na na na na na 14.8 0.4 355 98.8 53 Total 15-54 na na na na na 15.6 0.4 8,396 96.9 1,307 Notes: Medical injections are those given by a doctor, nurse, pharmacist, dentist, or other health worker. Figures in parentheses are based on 25-49 unweighted cases. An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. na = Not applicable HIV/AIDS-related Knowledge, Attitudes, and Behaviour • 265 Table 13.14 Comprehensive knowledge about HIV and of a source of condoms among young people Percentage of young women and young men age 15-24 with comprehensive knowledge about HIV and percentage with knowledge of a source of condoms, according to background characteristics, Zimbabwe 2015 Women Men Background characteristic Percentage with comprehensive knowledge of HIV1 Percentage who know a condom source2 Number of women Percentage with comprehensive knowledge of HIV1 Percentage who know a condom source2 Number of men Age 15-19 41.4 26.4 2,199 41.4 80.6 2,126 15-17 37.1 14.8 1,394 38.5 75.8 1,352 18-19 48.7 46.6 805 46.5 89.0 774 20-24 52.8 76.3 1,697 54.9 95.6 1,330 20-22 50.6 72.5 1,034 54.3 94.9 889 23-24 56.1 82.2 663 56.2 97.0 442 Marital status Never married 47.1 18.0 2,192 46.7 85.2 3,085 Ever had sex 50.3 87.6 451 50.2 96.3 1,235 Never had sex 46.3 0.0 1,741 44.4 77.8 1,850 Ever married 45.3 87.0 1,703 45.7 95.9 371 Residence Urban 55.7 42.6 1,452 60.0 92.9 1,070 Rural 40.8 51.5 2,443 40.6 83.4 2,387 Education No education * * 11 * * 12 Primary 28.7 60.0 851 26.4 77.4 831 Secondary 49.9 44.7 2,891 51.7 88.8 2,485 More than secondary 80.9 47.7 142 80.1 99.5 128 Total 46.3 48.2 3,895 46.6 86.4 3,456 Note: An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. 1 Comprehensive knowledge means knowing that consistent use of condoms during sexual intercourse and having just one uninfected faithful partner can reduce the chance of getting HIV, knowing that a healthy-looking person can have HIV, and rejecting the two most common local misconceptions about HIV transmission or prevention of HIV. The components of comprehensive knowledge are presented in Tables 13.2, 13.3.1 and 13.3.2. 2 For this table, the following responses are not considered a source for condoms: friends, family members, and home. 266 • HIV/AIDS-related Knowledge, Attitudes, and Behaviour Table 13.15 Age at first sexual intercourse among young people Percentage of young women and young men age 15-24 who had sexual intercourse before age 15 and percentage of young women and young men age 18-24 who had sexual intercourse before age 18, according to background characteristics, Zimbabwe 2015 Women age 15-24 Women age 18-24 Men age 15-24 Men age 18-24 Background characteristic Percentage who had sexual intercourse before age 15 Number of women Percentage who had sexual intercourse before age 18 Number of women Percentage who had sexual intercourse before age 15 Number of men Percentage who had sexual intercourse before age 18 Number of men Age 15-19 4.7 2,199 na na 5.8 2,126 na na 15-17 4.6 1,394 na na 5.8 1,352 na na 18-19 4.8 805 38.8 805 5.9 774 32.3 774 20-24 4.4 1,697 40.9 1,697 5.0 1,330 26.4 1,330 20-22 4.4 1,034 39.5 1,034 4.7 889 24.3 889 23-24 4.5 663 43.1 663 5.7 442 30.4 442 Marital status Never married 1.7 2,192 13.3 974 5.3 3,085 26.5 1,734 Ever married 8.3 1,703 57.3 1,528 7.0 371 38.3 370 Knows condom source1 Yes 7.4 1,876 52.4 1,670 6.1 2,985 29.4 1,960 No 2.0 2,019 15.7 832 1.7 472 17.0 144 Residence Urban 2.0 1,452 26.6 1,034 4.5 1,070 26.4 749 Rural 6.1 2,443 49.8 1,467 6.0 2,387 29.7 1,355 Education No education * 11 * 9 * 12 * 6 Primary 13.6 851 72.4 521 8.6 831 36.2 423 Secondary 2.0 2,891 33.3 1,834 4.4 2,485 27.0 1,549 More than secondary 0.0 142 6.1 139 6.4 128 21.8 127 Total 4.6 3,895 40.2 2,502 5.5 3,456 28.5 2,104 Note: An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. na = Not available 1 For this table, the following responses are not considered a source for condoms: friends, family members, and home. HIV/AIDS-related Knowledge, Attitudes, and Behaviour • 267 Table 13.16 Premarital sexual intercourse and condom use during premarital sexual intercourse among young people Among never-married women and men age 15-24, percentage who have never had sexual intercourse, percentage who had sexual intercourse in the past 12 months, and, among those who had premarital sexual intercourse in the past 12 months, percentage who used a condom at the last sexual intercourse, by background characteristics, Zimbabwe 2015 Never-married women age 15-24 Never-married men age 15-24 Background characteristic Percentage who have never had sexual intercourse Percentage who had sexual intercourse in the past 12 months Number of women Women who had sexual intercourse in the past 12 months Percentage who have never had sexual intercourse Percentage who had sexual intercourse in the past 12 months Number of men Men who had sexual intercourse in the past 12 months Percentage who used a condom at last sexual intercourse Number of women Percentage who used a condom at last sexual intercourse Number of men Age 15-19 86.6 9.6 1,698 47.0 163 73.6 18.7 2,104 75.6 393 15-17 91.4 6.3 1,219 48.6 77 82.9 11.4 1,351 71.7 154 18-19 74.2 18.0 480 45.6 86 57.0 31.7 753 78.2 239 20-24 54.9 31.8 494 52.7 157 30.6 54.2 981 85.1 532 20-22 57.8 29.3 356 51.4 104 33.4 50.1 722 84.9 361 23-24 47.2 38.2 138 55.3 53 22.8 65.8 259 85.4 171 Knows condom source1 Yes 0.0 74.2 395 51.6 293 54.7 34.1 2,629 81.2 896 No 96.9 1.5 1,797 (30.2) 27 90.0 6.5 456 (75.1) 30 Residence Urban 77.9 15.9 973 57.4 154 55.0 35.1 993 86.9 349 Rural 80.7 13.6 1,220 42.7 166 62.3 27.6 2,092 77.5 577 Education No education * * 3 * 3 * * 12 * 4 Primary 73.1 19.3 314 37.7 61 61.1 29.5 718 72.1 212 Secondary 81.7 12.7 1,761 51.2 223 61.1 28.6 2,233 83.7 639 More than secondary 63.5 29.1 114 (60.4) 33 33.2 57.7 122 85.3 70 Total 79.4 14.6 2,192 49.8 320 60.0 30.0 3,085 81.0 925 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 For this table, the following responses are not considered a source for condoms: friends, family members, and home. 268 • HIV/AIDS-related Knowledge, Attitudes, and Behaviour Table 13.17.1 Multiple sexual partners and higher-risk sexual intercourse in the past 12 months among young people: Women Among all young women age 15-24, percentage who had sexual intercourse with more than one sexual partner in the past 12 months; among those having more than one partner in the past 12 months, percentage reporting that a condom was used during last intercourse; among young women age 15-24 who had sexual intercourse in the past 12 months, percentage who had intercourse in the past 12 months with a non-marital, non-cohabitating partner; and among young women age 15-24 who had sexual intercourse in the past 12 months with a non-marital, non-cohabitating partner, percentage who used a condom during last sexual intercourse with such a partner, according to background characteristics, Zimbabwe 2015 Women age 15-24 Women age 15-24 who had 2+ partners in the past 12 months Women age 15-24 who had sexual intercourse in the past 12 months Women age 15-24 who had intercourse in the past 12 months with a non-marital, non-cohabiting partner1 Background characteristic Percentage who had 2+ partners in the past 12 months Number of women Percentage who reported using a condom during last intercourse Number of women Percentage who had intercourse in the past 12 months with a non-marital, non- cohabitating partner1 Number of women Percentage who reported using a condom during last sexual intercourse with a non- marital, non- cohabitating partner1 Number of women Age 15-19 0.8 2,199 * 18 28.1 642 47.0 180 15-17 0.8 1,394 * 12 33.7 246 54.0 83 18-19 0.7 805 * 6 24.6 396 41.1 97 20-24 2.0 1,697 (47.3) 34 18.0 1,288 63.8 231 20-22 2.2 1,034 (39.2) 22 19.9 739 61.7 147 23-24 1.8 663 * 12 15.3 549 67.5 84 Marital status Never married 1.2 2,192 (44.6) 25 99.4 320 52.9 318 Ever married 1.6 1,703 (43.8) 27 5.8 1,610 68.5 93 Residence Urban 2.2 1,452 (52.2) 32 32.3 613 64.6 198 Rural 0.8 2,443 * 20 16.2 1,318 48.9 214 Education No education * 11 * 0 * 11 * 4 Primary 1.4 851 * 12 16.2 557 51.3 90 Secondary 1.2 2,891 (43.9) 35 21.7 1,303 56.3 283 More than secondary 3.1 142 * 4 58.4 60 (70.6) 35 Total 15-24 1.3 3,895 44.2 52 21.3 1,930 56.5 412 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 A person who was not her husband and did not live with her HIV/AIDS-related Knowledge, Attitudes, and Behaviour • 269 Table 13.17.2 Multiple sexual partners and higher-risk sexual intercourse in the past 12 months among young people: Men Among all young men age 15-24, percentage who had sexual intercourse with more than one sexual partner in the past 12 months; among those having more than one partner in the past 12 months, percentage reporting that a condom was used during last intercourse; among young men age 15-24 who had sexual intercourse in the past 12 months, percentage who had intercourse in the past 12 months with a non-marital, non-cohabitating partner; and among young men age 15-24 who had sexual intercourse in the past 12 months with a non-marital, non-cohabitating partner, percentage who used a condom during last sexual intercourse with such a partner, according to background characteristics, Zimbabwe 2015 Men age 15-24 Men age 15-24 who had 2+ partners in the past 12 months Men age 15-24 who had sexual intercourse in the past 12 months Men age 15-24 who had intercourse in the past 12 months with a non-marital, non-cohabitating partner1 Background characteristic Percentage who had 2+ partners in the past 12 months Number of men Percentage who reported using a condom at last intercourse Number of men Percentage who had intercourse in the past 12 months with a non-marital, non- cohabitating partner1 Number of men Percentage who reported using a condom during last sexual intercourse with a non- marital, non- cohabitating partner1 Number of men Age 15-19 3.9 2,126 71.1 82 96.6 415 78.8 401 15-17 1.4 1,352 * 19 99.3 156 73.7 154 18-19 8.2 774 76.1 63 95.0 260 82.0 246 20-24 18.0 1,330 63.8 240 71.5 872 87.5 623 20-22 15.1 889 69.1 134 77.0 524 87.3 403 23-24 24.0 442 57.2 106 63.2 348 87.8 220 Marital status Never married 7.7 3,085 79.6 239 100.0 925 83.8 925 Ever married 22.5 371 25.8 83 27.2 362 86.6 99 Residence Urban 11.9 1,070 75.2 127 88.1 423 90.5 373 Rural 8.2 2,387 59.4 195 75.4 864 80.4 651 Education No education * 12 * 0 * 4 * 4 Primary 8.4 831 48.8 70 76.0 321 76.9 244 Secondary 9.1 2,485 69.7 227 79.4 887 86.2 704 More than secondary 19.3 128 (77.1) 25 95.1 75 89.1 71 Total 15-24 9.3 3,456 65.7 322 79.6 1,287 84.1 1,024 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 A person who was not his wife and did not live with him 270 • HIV/AIDS-related Knowledge, Attitudes, and Behaviour Table 13.18 Age-mixing in sexual relationships among women age 15-19 Among women age 15-19 who had sexual intercourse in the past 12 months, percentage who had sexual intercourse with a partner who was 10 or more years older than themselves, by background characteristics, Zimbabwe 2015 Background characteristic Percentage who had sexual intercourse with a man 10+ years older Number of women age 15-19 who had sexual intercourse in the past 12 months Age 15-17 17.0 246 18-19 17.0 396 Marital status Never married 6.8 163 Ever married 20.5 479 Knows condom source1 Yes 15.2 520 No 24.7 122 Residence Urban 22.0 132 Rural 15.7 510 Education No education * 4 Primary 20.2 230 Secondary 15.3 402 More than secondary * 6 Total 17.0 642 Note: Among men age 15-19 who had sexual intercourse in the past 12 months, none reported having a partner who was 10 or more years older than himself. An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. 1 For this table, the following responses are not considered a source for condoms: friends, family members and home. HIV/AIDS-related Knowledge, Attitudes, and Behaviour • 271 Table 13.19 Recent HIV tests among young people Among young women and young men age 15-24 who have had sexual intercourse in the past 12 months, percentage who were tested for HIV in the past 12 months and received the results of the last test, according to background characteristics, Zimbabwe 2015 Women age 15-24 who have had sexual intercourse in the past 12 months: Men age 15-24 who have had sexual intercourse in the past 12 months: Background characteristic Percentage who have been tested for HIV in the past 12 months and received the results of the last test Number of women Percentage who have been tested for HIV in the past 12 months and received the results of the last test Number of men Age 15-19 59.6 642 27.8 415 15-17 49.5 246 22.0 156 18-19 65.9 396 31.2 260 20-24 64.7 1,288 44.9 872 20-22 66.1 739 42.2 524 23-24 62.8 549 49.0 348 Marital status Never married 54.7 320 34.0 925 Ever married 64.7 1,610 53.1 362 Knows condom source1 Yes 66.4 1,696 39.8 1,242 No 38.6 235 (28.0) 45 Residence Urban 64.1 613 40.9 423 Rural 62.6 1,318 38.6 864 Education No education * 11 * 4 Primary 54.7 557 32.5 321 Secondary 66.7 1,303 40.7 887 More than secondary 71.6 60 52.8 75 Total 63.0 1,930 39.4 1,287 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 For this table, the following responses are not considered a source for condoms: friends, family members, and home. HIV Prevalence • 273 HIV PREVALENCE 14 Key Findings  HIV prevalence: HIV prevalence is 13.8 percent among women and men age 15-49, 16.7 percent among women and 10.5 among men.  HIV prevalence among young people: HIV prevalence is 6.7 percent among young women and 2.9 percent among young men age 15-24.  HIV prevalence among children: HIV prevalence among children age 0-14 years is 1.8 percent. Prevalence increases from 1.1 percent among children age 0-4 years to 2.7 percent among children age 10-14 years.  HIV prevalence by province: HIV prevalence among women and men age 15-49 ranges from 10.5 percent in Manicaland to 21.5 percent in Matabeleland South.  HIV testing by current HIV status: 93 percent of women who are living with HIV and 83 percent of men who are living with HIV have ever been tested for HIV and received the test result. he 2015 ZDHS included HIV prevalence testing for females age 0-49 and males age 0-54. This is the first Zimbabwe DHS to include HIV testing of children under the age of 15. The specimen collection and HIV testing procedures are described in Appendix B. 14.1 COVERAGE RATES FOR HIV TESTING Among the household population age 15-49, 85 percent were interviewed, consented to be tested for HIV, and had a blood specimen collected and tested for HIV (Table 14.1.1). Among those not tested for HIV, 6 percent were not interviewed, 6 percent agreed to the interview but refused the HIV test, 2 percent were absent after repeated attempts to contact them, and 2 percent could not be tested or no final test result could be obtained for technical or logistical reasons. Participation is higher among women than men (88 percent versus 81 percent). T 274 • HIV Prevalence HIV testing response rate Percentage of women and men who are tested for HIV as part of the DHS survey Sample: Women and men who are in households selected for HIV testing and are within the eligible age range for HIV testing based on information collected in the household questionnaire. The HIV testing response rate is calculated as follows: Women age 15-49 and men age 15-54 who were interviewed and whose blood sample underwent the complete HIV testing algorithm with a final result of positive, negative, or indeterminate ————————————————————————————————— All women age 15-49 and men age 15-54 in households selected for HIV testing Among children age 0-14, the overall coverage of HIV testing was 86 percent (Table 14.1.2). For 8 percent of children, the HIV test was refused, and 4 percent of children were absent despite repeated visits. Coverage of HIV testing was similar among boys and girls (86 percent and 87 percent, respectively). Trends: Participation in the survey HIV test is higher in the 2015 ZHDS than in the 2010-11 ZDHS, with coverage increasing from 75 percent to 85 percent overall. Participation increased from 80 percent to 88 percent among women and, notably, from 69 percent to 81 percent among men. Patterns by background characteristics  Participation in the survey HIV test is higher in rural than urban areas (89 percent versus 79 percent). By province, participation in HIV testing ranges from 78 percent in Harare to 89 percent in Matabeleland North (Table 14.1.1). Patterns in participation in HIV testing among children under age 15 were similar to those of adults.  By age, women and men age 15-34 were somewhat more likely to participate in the survey HIV test than those age 35-49 (Table 14.2.1).  Patterns in participation by education and wealth were similar for women and men (Table 14.2.1). Those in the middle education categories were more likely to participate in the ZDHS HIV test than those in the lowest and highest categories. Those in the lowest three wealth quintiles were somewhat more likely to participate than those in the highest two.  Participation of children in the survey HIV test is lowest among children in the 0-5 month age group. Only 70 percent of girls and 68 percent of boys age 0-5 months participated in the HIV test. Participation is also slightly below average in the 6-11 month age group (80 percent for girls and boys) (Table 14.2.2). 14.2 HIV PREVALENCE 14.2.1 HIV Prevalence among Women and Men HIV prevalence Percentage of women and men testing positive for HIV as part of the DHS survey. See testing methodology in Appendix B. Sample: Women and men age 15-49 who are tested for HIV as part of the survey HIV Prevalence • 275 HIV prevalence among women and men age 15-49 is 13.8 percent (Table 14.3.1). Prevalence is higher among women (16.7 percent) than men (10.5 percent). During adolescence, HIV prevalence increases more rapidly among young women than young men. From the 15-19 year age group to the 20-24 age group, HIV prevalence increases from 4.0 percent to 10.3 percent among women, and from 2.5 percent to 3.7 percent among men (Figure 14.1). HIV prevalence reaches a peak in the 40-44 age group among women (31.3 percent) and in the 50-54 age group among men (28.9 percent). Trends: HIV prevalence among women and men age 15-49 has decreased from 18.1 percent in the 2005- 06 ZDHS, to 15.2 percent the 2010-11 ZDHS, and to 13.8 percent the 2015 ZDHS. Most of this decrease appears to reflect change in the population over time. However, it should be noted that some of the decrease between the 2010-11 ZDHS and the 2015 ZDHS can be attributed to a change in the HIV testing algorithm between these two surveys. See Appendix B for further details. Further, this finding should be interpreted with caution given that the HIV epidemic is aging, and these figures do not account for a potential increase in HIV prevalence among the population age 50 and older. For example, the HIV prevalence among men age 50-54 increased from 19.5 percent in the 2010-11 ZDHS to 28.9 percent in the 2015 ZDHS. 14.2.2 HIV Prevalence among Children Overall HIV prevalence among children age 0-14 is 1.8 percent (Table 14.3.2). HIV prevalence is similar among girls and boys (2.0 percent and 1.7 percent, respectively). HIV prevalence is generally less than 1 percent among children age 0-11 months, and varies between 1 and 2 percent among children age 1-9 years. HIV prevalence starts gradually increasing around age 10-14 years. Figure 14.2 shows provincial data for the total HIV prevalence for children age 0-14. Patterns by socioeconomic characteristics  There is little variation in the prevalence of HIV among children age 0-14 by urban/rural residence or wealth (Table 14.4).  Matabeleland North has the highest HIV prevalence among children. In this province, 3.3 percent of girls age 0-14 and 3.2 percent of boys age 0-14 are living with HIV. Figure 14.1 HIV prevalence by age Figure 14.2 HIV prevalence among children, by province 0 5 10 15 20 25 30 35 15-19 20-24 25-29 30-34 35-39 40-44 45-49 50-54 Men Women 276 • HIV Prevalence Patterns by orphanhood and HIV serostatus of the mother  Table 14.5 shows differentials in HIV prevalence among children by orphanhood status and HIV serostatus of the mother, according to age group.  Among all three age groups, children with at least one deceased parent are more likely than children with both parents living to have HIV. The percentage of children with at least one dead parent who are HIV positive increases steadily from 1.5 percent among children age 0-4, to 4.5 percent among children age 5-9, and 7.0 percent among children age 10-14.  Not surprisingly, children whose mothers have HIV are more likely to be HIV positive themselves than are children whose mother is HIV negative. In Table 14.5, HIV status of both mother and child is based on the 2015 ZDHS blood test. Among children of HIV positive mothers, 6.4 percent of children age 0-4, 10.7 percent of children age 5-9, and 8.8 percent of children age 10-14 years are HIV positive themselves. 14.2.3 HIV Prevalence among Women and Men by Background Characteristics Patterns by socioeconomic characteristics  HIV prevalence is slightly higher in urban than in rural areas, though the difference is small. Among women and men age 15-49, HIV prevalence is 14.3 percent in urban areas compared with 13.5 percent in rural areas (Table 14.6). There is very little difference between the urban and rural prevalence among women (Figure 14.3).  By province, among women and men age 15-49, HIV prevalence ranges from 10.5 percent in Manicaland to 21.5 percent in Matabeleland South. Among men, HIV prevalence ranges from 7.9 percent in Manicaland to 14.7 percent in Matabeleland South. Among women, HIV prevalence ranges from 12.9 percent in Manicaland to 27.3 percent in Matabeleland South. In fact, the HIV prevalence among women in Matabeleland South is almost 6 percentage points higher than in the next-highest province (Matabeleland North, 21.6 percent) (Figure 14.4).  By education, HIV prevalence is higher among women with primary education than among those with no education or with higher educational attainment. HIV prevalence among men varies little by education. Figure 14.3 HIV prevalence by residence and sex Figure 14.4 HIV prevalence among adults, by province 16.7 10.5 16.8 11.3 16.6 10.1 Women 15-49 Men 15-49 Total Urban Rural HIV Prevalence • 277 Patterns by other sociodemographic and health characteristics  HIV prevalence varies notably by marital status (Table 14.7). Over half (58.0 percent) of women and men who are widowed are living with HIV, followed by 28.0 percent of those who are divorced or separated. HIV prevalence is 15.8 percent among respondents who are married or living with someone, and 3.1 percent among those who report they have never had sex. Fifteen percent of women who have never married but have ever had sex are living with HIV.  HIV prevalence is slightly lower among women who report they are currently pregnant (14.7 percent) compared with those who say that they are not pregnant or not sure (16.8 percent). 14.2.4 HIV Prevalence by Sexual Risk Behaviour HIV prevalence by sexual behaviour characteristics among respondents who have ever had sexual intercourse are presented in Table 14.8. These findings have a number of limitations—for example, respondents may not accurately report their risk behaviours, recent behaviours may not accurately reflect lifetime risk, and it is not possible to know the sequence of these behaviours with reference to exposure to HIV infection.  Among women there is a clear association between younger age at first sex and having HIV. Twenty- two percent of women who first had sex before the age of 16 are living with HIV compared with 18.6 percent of women who first had sex at the age of 20 or older. By contrast, men who first had sex before age 16 are less likely to be HIV positive than their counterparts who initiated sexual activity at older ages.  HIV prevalence increases with number of lifetime sexual partners among men from 4.3 percent among men with 1 lifetime sexual partner to 18.6 percent among those with 10 or more. Among women, the relationship is less linear; however, women with 3 or more lifetime sexual partners are much more likely to have HIV than those with 1 or 2 lifetime partners.  Women and men who used a condom during last sexual intercourse in the past 12 months are more likely to be HIV positive (29.3 percent) than those who did not use a condom (11.6 percent).  Men who paid for sex in the past 12 months are more likely than those who did not to have HIV (15.8 percent versus 12.7 percent). 14.2.5 HIV Prevalence among Young People Tables 14.9 and 14.10 show HIV prevalence among young people age 15-24 according to background characteristics and sexual risk behaviours. Patterns by background characteristics and sexual risk behaviour  Among young women, HIV prevalence increases steadily with age, from 2.7 percent of women age 15-17 to 13.9 percent of women age 23-24. Among young men, HIV prevalence holds steady at around 2.5 percent until the age of 23-24 when it increases to 6.0 percent (Table 14.9).  Young women and men who are divorced, separated, or widowed are more likely than their currently married and never-married counterparts to have HIV. By marital status, the group with the next highest HIV prevalence differs for women and men. For women, those who have never been married but have ever had sex have the next-highest HIV prevalence (10.9 percent), whereas among young men, the next-highest group is those who are married or living together (5.5 percent).  Young women who are pregnant (10.1 percent) are more likely than those who are not pregnant or not sure (6.5 percent) to be living with HIV. 278 • HIV Prevalence  As observed for the 15-49 age group, HIV prevalence is highest among young women and men in Matabeleland South. Ten percent of young women and men in Matabeleland South are living with HIV, compared with 3.7 to 6.1 percent of young people in other provinces. Among young women, the HIV prevalence in Matabeleland South (16.1 percent) is roughly twice as high as in the next highest provinces, Bulawayo (8.2 percent) and Midlands (8.0 percent).  Among young people, HIV prevalence is lower among those with more years of schooling, and is fairly consistent across wealth quintiles. The difference by education is particularly stark among young women—9.2 percent of young women with primary education are living with HIV compared with 2.8 percent of those with more than secondary.  When looking at women and men separately, those with two or more partners in the past 12 months are more likely to be HIV positive than their counterparts with fewer sexual partners. Young women who used a condom at last sex are much more likely to have HIV than those who did not (18.0 percent versus 8.2 percent), though HIV status does not appear to have a strong association with condom use among men (Table 14.10). 14.2.6 HIV Prevalence by Other Characteristics Related to HIV Risk This chapter also examines the associations between HIV prevalence and history of sexually transmitted infections (STIs), prior history of HIV testing, and male circumcision.  As shown in Table 14.11, women and men who had an STI or symptoms of an STI in the past 12 months are more likely to be HIV positive than those who did not—29.6 percent compared with 18.9 percent among women, and 18.1 percent compared with 12.4 percent among men.  Respondents who have ever been tested for HIV are more likely to be HIV positive than those who have never been tested. For example, 20.2 percent of women who have ever been tested for HIV and received the test result are HIV positive compared with 14.2 percent of women who have never been tested for HIV.  Table 14.12 examines prior HIV testing history according to current HIV status. Among women who are HIV positive, 93 percent have ever been tested for HIV and received the result of their most recent test, including 48 percent of HIV positive women who were tested for HIV and received the result in the past 12 months and 45 percent of HIV positive women who were tested more than 12 months ago. Only 1 percent of HIV positive women said they had been tested for HIV but did not receive the result of their most recent test, and 6 percent of HIV positive women have never been tested for HIV. Eighty-three percent of HIV positive men have ever been tested for HIV and received the result of their most recent test, including 42 percent who were tested in the past 12 months and 41 percent who were tested more than 12 months ago. Fifteen percent of HIV positive men have never been tested for HIV. Using the percentage of HIV positive respondents who were tested and received the result in the past 12 months as a lower bound and the percentage who have ever been tested for HIV and received the result as an upper bound, between 46 percent and 89 percent of people living with HIV in Zimbabwe are likely to have been diagnosed.  Results on HIV prevalence by male circumcision are shown in Table 14.13. Overall, HIV prevalence is 7.6 percent among men age 15-49 who have been circumcised and 11.0 percent among men who have not been circumcised. In looking at the source of circumcision, a stronger association between medical male circumcision and lower HIV prevalence emerges. HIV prevalence is only 4.9 percent among men who say that they were circumcised by a health worker or health professional, compared with 21.5 percent among circumcised men who say that their circumcision was performed by a traditional practitioner, family member, or friend. HIV Prevalence • 279 14.2.7 HIV Prevalence among Couples Among the women and men interviewed in the 2015 ZDHS there are 3,151 cohabitating couples. Twenty percent of couples are HIV affected, that is, one or both members are HIV positive. Specifically, in 10.9 percent of couples, both members are HIV positive; in 5.0 percent of couples, the man is HIV positive and the woman is HIV negative; and in 3.8 percent of couples, the woman is HIV positive and the man is HIV negative (Table 14.14). Patterns by background characteristics  The likelihood that both members of a couple have HIV increases with the age of both the female and male partners.  In looking at the age difference between the man and woman, couples in which the woman is older than the man or in which the man is 15 or more years older than the woman are more likely than other couples to be affected by HIV.  Couples in Matabeleland North and Matabeleland South are most likely to be affected by HIV. The percentage of couples in which both members are HIV positive is highest in these two provinces (16.2 percent and 17.8 percent of couples, respectively). These two provinces also have the highest percentage of couples in which the women is positive and the man is negative. The province with the highest percentage of couples in which with man is positive and the woman is negative is Bulawayo (11.9 percent of couples). LIST OF TABLES For detailed information on HIV prevalence, see the following tables:  Table 14.1.1 Coverage of HIV testing by residence and province: Women and men age 15-49  Table 14.1.2 Coverage of HIV testing by residence and province: Children age 0-14  Table 14.2.1 Coverage of HIV testing by selected background characteristics: Women and men age 15-49  Table 14.2.2 Coverage of HIV testing by age: Children age 0-14  Table 14.3.1 HIV prevalence among women age 15-49 and men age 15-54, by age  Table 14.3.2 HIV prevalence among children age 0-14, by age  Table 14.4 HIV prevalence among children age 0-14, by background characteristics  Table 14.5 HIV prevalence among children age 0-14, by orphanhood and serological status of the mother  Table 14.6 HIV prevalence by socioeconomic characteristics  Table 14.7 HIV prevalence by demographic characteristics  Table 14.8 HIV prevalence by sexual behaviour  Table 14.9 HIV prevalence among young people by background characteristics  Table 14.10 HIV prevalence among young people by sexual behaviour  Table 14.11 HIV prevalence by other characteristics  Table 14.12 Prior HIV testing by current HIV status  Table 14.13 HIV prevalence by male circumcision  Table 14.14 HIV prevalence among couples 280 • HIV Prevalence Table 14.1.1 Coverage of HIV testing by residence and province: Women and men age 15-49 Percent distribution of women and men age 15-49 and eligible for HIV testing by testing status, according to residence and region (unweighted), Zimbabwe 2015 Testing status Total Number DBS Tested1 Refused to provide blood Absent at the time of blood collection Other/missing2 Residence and province Inter- viewed Inter- viewed Not inter- viewed Inter- viewed Not inter- viewed Inter- viewed Not inter- viewed WOMEN AGE 15-49 Residence Urban 83.7 7.2 1.7 2.1 2.6 2.1 0.5 100.0 4,753 Rural 90.6 4.5 0.8 0.6 1.6 1.3 0.5 100.0 5,598 Province Manicaland 86.3 9.0 1.4 0.6 1.8 0.5 0.5 100.0 1,058 Mashonaland Central 90.9 3.4 1.6 0.7 1.4 1.5 0.7 100.0 1,030 Mashonaland East 82.6 9.6 1.4 1.8 2.3 1.9 0.4 100.0 949 Mashonaland West 88.7 5.9 1.0 0.6 1.6 1.6 0.6 100.0 1,089 Matabeleland North 90.8 2.6 1.0 1.0 2.6 1.6 0.3 100.0 884 Matabeleland South 90.4 4.1 0.7 1.6 1.5 1.3 0.4 100.0 851 Midlands 86.7 4.9 0.8 2.7 2.3 2.1 0.5 100.0 1,102 Masvingo 89.7 4.5 0.7 1.1 1.8 1.8 0.4 100.0 1,077 Harare 82.5 8.8 2.0 1.5 2.6 2.2 0.5 100.0 1,302 Bulawayo 87.9 3.5 1.5 1.4 2.9 2.2 0.7 100.0 1,009 Total 15-49 87.5 5.7 1.2 1.3 2.1 1.7 0.5 100.0 10,351 MEN AGE 15-49 Residence Urban 73.8 8.5 2.8 4.2 8.6 1.5 0.6 100.0 3,744 Rural 86.7 5.5 0.9 1.2 3.8 1.3 0.5 100.0 4,980 Province Manicaland 79.8 10.0 1.4 2.2 5.8 0.3 0.5 100.0 924 Mashonaland Central 86.8 4.7 0.7 1.9 3.9 1.3 0.6 100.0 996 Mashonaland East 74.8 12.8 1.7 3.0 5.1 2.0 0.6 100.0 820 Mashonaland West 84.1 5.8 0.6 1.5 6.2 1.6 0.3 100.0 956 Matabeleland North 87.8 5.0 1.0 1.2 3.7 0.8 0.5 100.0 736 Matabeleland South 81.5 3.3 2.3 4.7 6.2 1.4 0.6 100.0 697 Midlands 79.8 5.7 1.9 4.6 5.9 1.4 0.5 100.0 928 Masvingo 84.4 6.3 1.1 1.6 4.3 1.8 0.5 100.0 794 Harare 72.5 9.3 4.7 2.5 8.8 1.8 0.4 100.0 1,108 Bulawayo 83.0 4.1 1.2 1.8 7.8 1.6 0.5 100.0 765 Total 15-49 81.2 6.8 1.7 2.5 5.9 1.4 0.5 100.0 8,724 Total 15-54 81.3 6.8 1.8 2.5 5.8 1.4 0.5 100.0 9,132 TOTAL (WOMEN AND MEN AGE 15-49) Residence Urban 79.4 7.8 2.2 3.0 5.2 1.8 0.5 100.0 8,497 Rural 88.8 5.0 0.9 0.9 2.7 1.3 0.5 100.0 10,578 Province Manicaland 83.2 9.4 1.4 1.3 3.7 0.4 0.5 100.0 1,982 Mashonaland Central 88.9 4.0 1.1 1.3 2.6 1.4 0.6 100.0 2,026 Mashonaland East 79.0 11.1 1.5 2.4 3.6 1.9 0.5 100.0 1,769 Mashonaland West 86.6 5.8 0.8 1.0 3.7 1.6 0.5 100.0 2,045 Matabeleland North 89.4 3.7 1.0 1.1 3.1 1.2 0.4 100.0 1,620 Matabeleland South 86.4 3.7 1.4 3.0 3.6 1.4 0.5 100.0 1,548 Midlands 83.5 5.3 1.3 3.6 3.9 1.8 0.5 100.0 2,030 Masvingo 87.4 5.3 0.9 1.3 2.8 1.8 0.4 100.0 1,871 Harare 77.9 9.0 3.2 2.0 5.5 2.0 0.5 100.0 2,410 Bulawayo 85.8 3.7 1.4 1.6 5.0 1.9 0.6 100.0 1,774 Total 15-49 84.6 6.2 1.5 1.9 3.8 1.5 0.5 100.0 19,075 1 Includes all Dried Blood Spot (DBS) specimens tested at the lab and for which there is a final result, i.e., positive, negative, or indeterminate. Indeterminate means that the sample went through the entire algorithm, but the final result was inconclusive. 2 Includes: 1) other results of blood collection (e.g., technical problem in the field), 2) lost specimens, 3) non corresponding bar codes, and 4) other lab results such as blood not tested for technical reason, not enough blood to complete the algorithm, etc. HIV Prevalence • 281 Table 14.1.2 Coverage of HIV testing by residence and province: Children age 0-14 Percent distribution of children aged 0-14 eligible for HIV testing by testing status, according to residence and region (unweighted), Zimbabwe 2015 Testing status Total Number Residence and province DBS Tested1 Refused to provide blood Absent at the time of blood collection Other/ missing2 FEMALES 0-14 YEARS Residence Urban 78.5 13.1 6.2 2.3 100.0 2,933 Rural 89.1 6.3 3.2 1.4 100.0 5,940 Province Manicaland 82.7 13.9 2.3 1.1 100.0 1,035 Mashonaland Central 89.1 5.7 4.3 1.0 100.0 934 Mashonaland East 80.8 12.0 5.5 1.7 100.0 839 Mashonaland West 85.5 8.5 3.8 2.3 100.0 976 Matabeleland North 93.0 3.1 3.3 0.6 100.0 859 Matabeleland South 90.4 4.6 3.6 1.3 100.0 822 Midlands 81.6 7.4 8.0 3.1 100.0 1,003 Masvingo 88.4 6.7 2.4 2.6 100.0 962 Harare 77.8 16.5 4.7 1.0 100.0 834 Bulawayo 88.0 5.6 4.4 2.0 100.0 609 Total 0-14 85.6 8.5 4.2 1.7 100.0 8,873 MALES 0-14 YEARS Residence Urban 80.7 11.1 5.5 2.7 100.0 2,835 Rural 89.7 5.9 2.8 1.6 100.0 6,114 Province Manicaland 85.6 11.3 1.8 1.3 100.0 1,089 Mashonaland Central 89.0 6.3 3.4 1.3 100.0 972 Mashonaland East 80.7 11.5 5.9 1.8 100.0 814 Mashonaland West 86.5 7.4 4.0 2.1 100.0 979 Matabeleland North 93.4 2.4 2.8 1.4 100.0 861 Matabeleland South 92.4 4.2 2.6 0.8 100.0 857 Midlands 82.8 7.9 6.1 3.1 100.0 995 Masvingo 89.4 5.4 2.7 2.5 100.0 1,014 Harare 80.2 13.0 4.1 2.7 100.0 754 Bulawayo 88.3 5.7 3.7 2.3 100.0 614 Total 0-14 86.9 7.5 3.7 1.9 100.0 8,949 TOTAL 0-14 YEARS Residence Urban 79.6 12.1 5.8 2.5 100.0 5,768 Rural 89.4 6.1 3.0 1.5 100.0 12,054 Province Manicaland 84.2 12.6 2.1 1.2 100.0 2,124 Mashonaland Central 89.0 6.0 3.8 1.2 100.0 1,906 Mashonaland East 80.8 11.8 5.7 1.8 100.0 1,653 Mashonaland West 86.0 7.9 3.9 2.2 100.0 1,955 Matabeleland North 93.2 2.8 3.0 1.0 100.0 1,720 Matabeleland South 91.4 4.4 3.1 1.1 100.0 1,679 Midlands 82.2 7.7 7.1 3.1 100.0 1,998 Masvingo 88.9 6.0 2.5 2.5 100.0 1,976 Harare 79.0 14.9 4.4 1.8 100.0 1,588 Bulawayo 88.1 5.6 4.1 2.1 100.0 1,223 Total 0-14 86.2 8.0 3.9 1.8 100.0 17,822 1 Includes all Dried Blood Spot (DBS) specimens tested at the lab and for which there is a final result, i.e., positive, negative, or indeterminate. Indeterminate means that the sample went through the entire algorithm, but the final result was inconclusive. 2 Includes: 1) other results of blood collection (e.g., technical problem in the field), 2) lost specimens, 3) non corresponding bar codes, and 4) other lab results such as blood not tested for technical reason, not enough blood to complete the algorithm, etc. 282 • HIV Prevalence Table 14.2.1 Coverage of HIV testing by selected background characteristics: Women and men age 15-49 Percent distribution of women and men age 15-49 eligible for HIV testing by testing status, according to selected background characteristics (unweighted), Zimbabwe 2015 Testing status Total Number DBS Tested1 Refused to provide blood Absent at the time of blood collection Other/missing2 Background characteristic Interviewed Interviewed Not inter- viewed Interviewed Not inter- viewed Interviewed Not inter- viewed WOMEN 15-49 Age 15-19 88.2 4.6 0.5 1.2 2.6 2.1 0.8 100.0 2,242 20-24 87.6 4.9 1.4 1.3 2.4 1.7 0.6 100.0 1,863 25-29 88.5 5.8 1.1 1.1 1.6 1.6 0.3 100.0 1,711 30-34 87.6 6.3 1.6 1.4 1.5 1.4 0.3 100.0 1,644 35-39 85.0 7.2 2.0 1.3 2.7 1.3 0.4 100.0 1,276 40-44 88.4 6.7 1.2 0.8 1.1 1.1 0.7 100.0 997 45-49 84.8 6.1 1.1 2.8 2.4 2.4 0.3 100.0 618 Education No education 67.9 5.0 11.4 1.4 5.7 1.4 7.1 100.0 140 Primary 89.9 5.6 0.6 0.7 1.3 1.1 0.7 100.0 2,451 Secondary 88.1 5.4 1.1 1.3 2.1 1.7 0.3 100.0 6,873 More than secondary 79.8 8.7 2.5 3.3 2.9 2.5 0.3 100.0 877 Missing 0.0 0.0 10.0 0.0 80.0 0.0 10.0 100.0 10 Wealth quintile Lowest 90.1 4.7 0.8 0.4 2.4 1.2 0.4 100.0 1,556 Second 90.1 4.6 0.9 0.8 1.5 1.2 0.8 100.0 1,501 Middle 92.0 3.7 0.5 0.5 1.3 1.6 0.4 100.0 1,583 Fourth 88.1 5.4 0.9 1.7 1.8 1.7 0.4 100.0 2,639 Highest 81.9 8.2 2.2 2.1 2.9 2.1 0.6 100.0 3,072 Total 15-49 87.5 5.7 1.2 1.3 2.1 1.7 0.5 100.0 10,351 MEN 15-49 Age 15-19 87.9 5.3 1.0 1.7 2.4 1.2 0.6 100.0 2,148 20-24 82.4 6.4 1.1 2.1 6.4 1.2 0.4 100.0 1,496 25-29 78.1 7.5 1.9 2.8 7.7 1.9 0.2 100.0 1,293 30-34 79.1 6.1 2.1 2.7 8.2 1.4 0.6 100.0 1,239 35-39 77.6 7.9 2.4 3.6 6.6 1.3 0.7 100.0 1,030 40-44 76.5 8.3 2.8 3.4 7.1 1.2 0.8 100.0 893 45-49 78.2 9.4 2.1 2.4 5.3 2.2 0.3 100.0 625 Education No education 59.6 3.5 12.3 0.0 10.5 3.5 10.5 100.0 57 Primary 86.2 5.1 1.1 1.4 4.1 1.5 0.5 100.0 1,832 Secondary 81.3 6.8 1.5 2.5 6.1 1.4 0.4 100.0 5,826 More than secondary 73.5 10.4 3.1 4.9 6.5 1.2 0.3 100.0 994 Missing 0.0 0.0 33.3 0.0 60.0 0.0 6.7 100.0 15 Wealth quintile Lowest 87.8 4.2 1.0 1.0 4.8 1.1 0.2 100.0 1,192 Second 85.8 5.8 0.8 1.7 3.3 1.8 0.7 100.0 1,360 Middle 87.1 5.8 0.9 0.9 3.6 1.2 0.4 100.0 1,492 Fourth 78.2 6.4 1.9 3.2 8.2 1.6 0.6 100.0 2,231 Highest 74.5 9.7 2.9 4.0 7.1 1.3 0.5 100.0 2,449 Total 15-49 81.2 6.8 1.7 2.5 5.9 1.4 0.5 100.0 8,724 1 Includes all Dried Blood Spot (DBS) specimens tested at the lab and for which there is a final result, i.e., positive, negative, or indeterminate. Indeterminate means that the sample went through the entire algorithm, but the final result was inconclusive. 2 Includes: 1) other results of blood collection (e.g., technical problem in the field), 2) lost specimens, 3) non corresponding bar codes, and 4) other lab results such as blood not tested for technical reason, not enough blood to complete the algorithm, etc. HIV Prevalence • 283 Table 14.2.2 Coverage of HIV testing by age : Children age 0-14 Percent distribution of children aged 0-14 eligible for HIV testing by testing status, according to selected background characteristics (unweighted), Zimbabwe 2015 Testing status Total Number Age DBS Tested1 Refused to provide blood Absent at the time of blood collection Other/missing2 FEMALES 0-14 YEARS 0-4 years 83.8 10.6 3.1 2.6 100.0 3,273 0-5 months 69.8 21.9 1.6 6.7 100.0 315 6-11 months 79.7 12.8 2.7 4.7 100.0 296 12-17 months 82.5 11.2 2.6 3.6 100.0 303 18-23 months 87.5 8.3 2.0 2.3 100.0 303 2-4 years 86.1 8.8 3.6 1.6 100.0 2,056 5-9 years 87.2 7.5 4.4 1.0 100.0 2,892 10-14 years 86.1 7.2 5.5 1.3 100.0 2,708 Total 0-14 85.6 8.5 4.2 1.7 100.0 8,873 MALES 0-14 YEARS 0-4 years 85.6 9.4 2.4 2.7 100.0 3,235 0-5 months 67.9 19.5 3.6 9.1 100.0 308 6-11 months 80.4 13.9 1.1 4.6 100.0 280 12-17 months 84.2 8.7 2.9 4.2 100.0 310 18-23 months 87.4 8.9 2.0 1.7 100.0 302 2-4 years 88.9 7.4 2.4 1.3 100.0 2,035 5-9 years 88.0 6.6 3.8 1.6 100.0 2,951 10-14 years 87.2 6.4 5.1 1.4 100.0 2,763 Total 0-14 86.9 7.5 3.7 1.9 100.0 8,949 1 Includes all Dried Blood Spot (DBS) specimens tested at the lab and for which there is a final result, i.e., positive, negative, or indeterminate. Indeterminate means that the sample went through the entire algorithm, but the final result was inconclusive. 2 Includes: 1) other results of blood collection (e.g., technical problem in the field), 2) lost specimens, 3) non corresponding bar codes, and 4) other lab results such as blood not tested for technical reason, not enough blood to complete the algorithm, etc. 284 • HIV Prevalence Table 14.3.1 HIV prevalence among women age 15-49 and men age 15-54, by age Among the de facto women age 15-49 and men age 15-54 who were interviewed and tested, the percentage HIV positive, according to age, Zimbabwe 2015 Women Men Total Age Percentage HIV positive Number Percentage HIV positive Number Percentage HIV positive Number 15-19 4.0 1,917 2.5 2,018 3.2 3,935 20-24 10.3 1,489 3.7 1,257 7.3 2,745 25-29 15.5 1,453 7.5 1,052 12.1 2,505 30-34 21.9 1,408 13.1 1,049 18.2 2,457 35-39 28.0 1,064 18.0 831 23.6 1,895 40-44 31.3 847 27.0 737 29.3 1,585 45-49 24.3 489 23.2 532 23.7 1,021 50-54 na na 28.9 333 na na Total 15-49 16.7 8,667 10.5 7,475 13.8 16,142 Total 15-54 na na 11.3 7,808 na na na = Not applicable Table 14.3.2 HIV prevalence among children age 0-14 years, by age Among the de facto children age 0-14 years who were tested, the percentage HIV positive, according to age, Zimbabwe 2015 Females Males Total Age Percentage HIV positive Number Percentage HIV positive Number Percentage HIV positive Number 0-5 months 0.3 213 1.5 204 0.9 417 6-11 months 0.7 217 0.0 233 0.3 450 12-23 months 1.2 547 1.7 548 1.4 1,095 24-35 months 1.3 576 1.5 611 1.4 1,187 36-47 months 1.0 633 0.4 599 0.7 1,232 48-59 months 1.6 648 1.2 635 1.4 1,283 5-9 years 2.0 2,579 1.7 2,670 1.8 5,250 10-14 years 2.9 2,407 2.5 2,516 2.7 4,924 Total 0-4 years 1.1 2,833 1.1 2,831 1.1 5,664 Total 0-14 years 2.0 7,820 1.7 8,018 1.8 15,837 HIV Prevalence • 285 Table 14.4 HIV prevalence among children age 0-14 by socioeconomic characteristics Percentage HIV positive among children aged 0-14 who were tested, according to socioeconomic characteristics, Zimbabwe 2015 Females 0-14 years Males 0-14 years Total Background characteristic Percentage HIV positive Number Percentage HIV positive Number Percentage HIV positive Number Residence Urban 2.1 1,905 1.8 1,826 2.0 3,732 Rural 1.9 5,914 1.7 6,191 1.8 12,106 Province Manicaland 1.8 1,172 1.0 1,300 1.4 2,471 Mashonaland Central 0.9 788 1.1 816 1.0 1,603 Mashonaland East 2.1 766 2.5 760 2.3 1,527 Mashonaland West 2.7 949 1.5 952 2.1 1,901 Matabeleland North 3.3 470 3.2 464 3.2 935 Matabeleland South 2.1 430 2.4 462 2.2 892 Midlands 2.0 1,004 2.5 1,008 2.2 2,012 Masvingo 1.5 1,059 1.6 1,137 1.5 2,196 Harare 2.4 866 1.2 799 1.9 1,666 Bulawayo 0.6 316 1.7 319 1.1 634 Wealth quintile Lowest 2.0 1,812 1.9 1,948 2.0 3,760 Second 1.2 1,732 1.5 1,821 1.4 3,552 Middle 2.8 1,638 1.6 1,768 2.2 3,406 Fourth 1.9 1,528 1.9 1,328 1.9 2,856 Highest 1.8 1,110 1.7 1,153 1.8 2,263 Total 2.0 7,820 1.7 8,018 1.8 15,837 na = Not applicable Table 14.5 HIV prevalence among children age 0-14, by orphanhood and serological status of the mother Among children age 0-14 years who were tested, percentage HIV positive by orphanhood status and HIV serostatus of the mother, according to 5-year age groups, Zimbabwe 2015 0-4 years 5-9 years 10-14 years Background characteristic Percentage HIV positive Number Percentage HIV positive Number Percentage HIV positive Number Orphanhood Mother or father dead 1.5 222 4.5 619 7.0 1,196 Mother and father alive 1.1 5,361 1.5 4,478 1.3 3,571 Survival status of either parent missing 0.8 80 1.0 153 1.9 157 HIV serostatus of the mother1 Mother HIV+ 6.4 659 10.7 500 8.8 460 Mother HIV- 0.1 3,851 0.2 2,744 0.4 1,887 Missing2 1.4 1,154 1.8 2,005 3.3 2,576 Total 1.1 5,664 1.8 5,250 2.7 4,924 1 Based on the survey blood test 2 Includes children whose mothers were not tested for HIV because the mother is deceased, does not live in the household, was absent at the time of blood collection, or refused the survey HIV test 286 • HIV Prevalence Table 14.6 HIV prevalence by socioeconomic characteristics Percentage HIV positive among women and men age 15-49 who were tested, according to socioeconomic characteristics, Zimbabwe 2015 Women Men Total Background characteristic Percentage HIV positive Number Percentage HIV positive Number Percentage HIV positive Number Religion Traditional 10.1 61 16.8 193 15.2 254 Roman Catholic 17.0 576 11.5 611 14.2 1,187 Protestant 14.6 1,365 8.2 1,184 11.6 2,549 Pentecostal 17.4 2,247 8.4 1,352 14.0 3,599 Apostolic sect 16.4 3,548 10.2 2,306 14.0 5,854 Other Christian 14.7 404 10.0 453 12.2 857 Muslim * 29 (22.0) 56 25.2 85 None 22.2 433 13.4 1,310 15.6 1,743 Other * 6 * 9 * 15 Employment (last 12 months) Not employed 13.7 4,258 6.9 1,984 11.5 6,243 Employed 19.5 4,409 11.8 5,490 15.2 9,900 Residence Urban 16.8 3,334 11.3 2,698 14.3 6,031 Rural 16.6 5,334 10.1 4,777 13.5 10,111 Province Manicaland 12.9 1,102 7.9 996 10.5 2,099 Mashonaland Central 13.7 768 10.0 748 11.9 1,517 Mashonaland East 18.0 829 12.0 750 15.2 1,579 Mashonaland West 16.3 1,010 9.8 933 13.2 1,943 Matabeleland North 21.6 405 12.8 340 17.6 745 Matabeleland South 27.3 365 14.7 313 21.5 678 Midlands 17.8 1,100 11.6 919 15.0 2,018 Masvingo 16.2 1,033 8.4 784 12.9 1,818 Harare 16.5 1,553 10.5 1,312 13.8 2,865 Bulawayo 15.1 502 13.3 379 14.3 881 Education No education 16.4 107 (9.0) 36 14.5 143 Primary 20.5 2,217 11.7 1,679 16.7 3,896 Secondary 15.7 5,737 10.2 4,998 13.1 10,735 More than secondary 11.5 607 9.9 762 10.6 1,368 Wealth quintile Lowest 17.9 1,472 11.8 1,135 15.2 2,606 Second 15.3 1,467 11.2 1,320 13.4 2,787 Middle 17.7 1,540 9.6 1,457 13.8 2,997 Fourth 19.5 2,046 11.5 1,753 15.8 3,798 Highest 13.2 2,143 9.0 1,810 11.3 3,953 Total 15-49 16.7 8,667 10.5 7,475 13.8 16,142 50-54 na na 28.9 333 na na Total 15-54 na na 11.3 7,808 na na Notes: Figures in parentheses are based on 25-49 unweighted cases. An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. na = Not applicable HIV Prevalence • 287 Table 14.7 HIV prevalence by demographic characteristics Percentage HIV positive among women and men age 15-49 who were tested, according to demographic characteristics, Zimbabwe 2015 Women Men Total Demographic characteristic Percentage HIV positive Number Percentage HIV positive Number Percentage HIV positive Number Marital status Never married 6.3 2,205 3.4 3,407 4.6 5,612 Ever had sexual intercourse 15.2 598 3.8 1,583 6.9 2,182 Never had sexual intercourse 3.0 1,607 3.1 1,824 3.1 3,431 Married/living together 15.9 5,326 15.6 3,687 15.8 9,013 Divorced or separated 31.9 764 19.0 332 28.0 1,096 Widowed 57.5 373 (61.7) 48 58.0 421 Type of union In polygynous union 17.9 500 13.8 156 16.9 656 In non-polygynous union 15.6 4,755 15.7 3,532 15.6 8,286 Not currently in union 17.9 3,342 5.5 3,787 11.3 7,129 Times slept away from home in past 12 months None 16.6 3,659 10.1 3,102 13.6 6,761 1-2 16.9 2,583 10.5 1,797 14.2 4,380 3-4 15.3 952 11.3 905 13.4 1,856 5+ 17.2 1,473 10.9 1,671 13.9 3,145 Time away in past 12 months Away for more than 1 month 15.7 1,329 10.3 1,058 13.3 2,386 Away for less than 1 month 17.0 3,680 10.9 3,315 14.2 6,994 Not away 16.6 3,659 10.1 3,102 13.6 6,761 Currently pregnant Pregnant 14.7 539 na na na na Not pregnant or not sure 16.8 8,129 na na na na ANC for last birth in the last 3 years ANC provided by the public sector 14.8 2,711 na na na na ANC provided by other than the public sector 11.7 185 na na na na No ANC/No birth in past 3 years 17.7 5,770 na na na na Missing * 2 na na na na Total 15-49 16.7 8,667 10.5 7,475 13.8 16,142 50-54 na na 28.9 333 na na Total 15-54 na na 11.3 7,808 na na Notes: Total includes 71 women missing information on type of union. Figures in parentheses are based on 25-49 unweighted cases. na = Not applicable 288 • HIV Prevalence Table 14.8 HIV prevalence by sexual behaviour Percentage HIV positive among women and men age 15-49 who ever had sex and were tested for HIV, according to sexual behaviour characteristics, Zimbabwe 2015 Women Men Total Sexual behaviour characteristic Percentage HIV positive Number Percentage HIV positive Number Percentage HIV positive Number Age at first sexual intercourse <16 21.5 1,221 10.6 750 17.3 1,971 16-17 20.1 1,982 13.1 1,074 17.6 3,056 18-19 19.2 1,925 12.8 1,286 16.6 3,210 20+ 18.6 1,886 13.5 2,424 15.7 4,310 Missing (30.5) 47 14.8 117 19.3 164 Number of lifetime partners 1 10.7 4,309 4.3 1,039 9.5 5,347 2 28.0 1,647 9.9 959 21.3 2,606 3-4 43.5 853 13.1 1,519 24.0 2,372 5-9 39.5 175 17.2 1,177 20.1 1,352 10+ 46.7 55 18.6 841 20.3 896 Missing (27.2) 22 26.3 116 26.5 138 Multiple sexual partners in the past 12 months 0 31.4 803 11.5 535 23.4 1,339 1 18.0 6,117 13.3 4,085 16.1 10,202 2+ 31.0 102 12.1 1,030 13.8 1,133 Non-marital, non-cohabitating partners in the past 12 months1 0 39.0 1,928 15.1 3,705 23.3 5,634 1 12.3 5,066 8.7 1,503 11.4 6,569 2+ (31.1) 28 9.1 442 10.4 470 Condom use at last sexual intercourse in past 12 months Used condom 44.2 1,141 18.6 1,588 29.3 2,729 Did not use condom 12.3 5,078 10.5 3,527 11.6 8,605 No sexual intercourse in last 12 months 31.4 842 11.5 535 23.7 1,377 Condom use at last sexual intercourse with a non-marital, non-cohabitating partner in past in past 12 months1 Used condom 37.1 578 8.7 1,607 16.2 2,185 Did not use condom 21.4 323 9.0 337 15.1 660 No sexual intercourse with any non-marital, non-cohabitating partners in past 12 months 18.0 6,160 15.0 3,707 16.9 9,866 Paid for sexual intercourse in past 12 months Yes na na 15.8 264 na na Used condom na na 15.9 236 na na Did not use condom na na (15.4) 28 na na No (No paid sexual intercourse/ no sexual intercourse in last 12 months) na na 12.7 5,387 na na Total 15-49 19.8 7,061 12.9 5,651 16.7 12,711 50-54 na na 29.1 332 na na Total 15-54 na na 13.8 5,982 na na Notes: Total includes 38 cases with information missing on number of sexual partners in the past 12 months and 38 cases with information missing on number of non-marital, non-cohabitating partners in the past 12 months. Figures in parentheses are based on 25-49 unweighted cases. na = Not applicable 1 Any partner who was not a spouse and did not live with the respondent HIV Prevalence • 289 Table 14.9 HIV prevalence among young people by background characteristics Percentage HIV positive among women and men age 15-24 who were tested for HIV, according to background characteristics, Zimbabwe 2015 Women Men Total Background characteristic Percentage HIV positive Number Percentage HIV positive Number Percentage HIV positive Number Age 15-19 4.0 1,917 2.5 2,018 3.2 3,935 15-17 2.7 1,211 2.5 1,286 2.6 2,497 18-19 6.1 706 2.5 732 4.2 1,439 20-24 10.3 1,489 3.7 1,257 7.3 2,745 20-22 8.0 908 2.5 845 5.4 1,752 23-24 13.9 581 6.0 412 10.6 993 Marital status Never married 4.6 1,929 2.6 2,925 3.4 4,855 Ever had sex 10.9 409 1.8 1,184 4.1 1,593 Never had sex 2.9 1,521 3.1 1,741 3.0 3,262 Married/living together 8.9 1,272 5.5 292 8.3 1,564 Divorced/separated/ widowed 13.2 204 8.1 57 12.0 261 Currently pregnant Pregnant 10.1 234 na na na na Not pregnant or not sure 6.5 3,172 na na na na Residence Urban 6.6 1,287 2.8 1,031 4.9 2,318 Rural 6.8 2,119 3.0 2,243 4.8 4,362 Province Manicaland 5.4 427 2.9 482 4.1 909 Mashonaland Central 5.0 288 2.4 300 3.7 587 Mashonaland East 5.1 315 3.3 312 4.2 627 Mashonaland West 5.3 371 2.8 403 4.0 774 Matabeleland North 7.4 162 3.6 169 5.5 331 Matabeleland South 16.1 172 4.4 163 10.4 335 Midlands 8.0 473 2.6 406 5.5 879 Masvingo 6.4 396 2.0 375 4.3 770 Harare 6.0 584 3.4 497 4.8 1,081 Bulawayo 8.2 218 3.3 168 6.1 387 Education No education * 9 * 12 * 21 Primary 9.2 721 3.2 787 6.1 1,509 Secondary 6.2 2,556 2.9 2,364 4.6 4,920 More than secondary 2.8 120 2.0 111 2.4 231 Wealth quintile Lowest 7.0 537 2.3 441 4.9 978 Second 5.6 602 3.9 592 4.8 1,194 Middle 7.8 635 3.3 793 5.3 1,427 Fourth 8.2 768 2.6 725 5.5 1,492 Highest 5.3 865 2.6 724 4.0 1,589 Total 15-24 6.7 3,406 2.9 3,275 4.9 6,680 Note: An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. na = Not applicable 290 • HIV Prevalence Table 14.10 HIV prevalence among young people by sexual behaviour Percentage HIV positive among women and men age 15-24 who have ever had sex and were tested for HIV, according to sexual behaviour, Zimbabwe 2015 Women Men Total Sexual behaviour characteristic Percentage HIV positive Number Percentage HIV positive Number Percentage HIV positive Number Multiple sexual partners in the past 12 months 0 10.2 197 2.6 303 5.6 501 1 9.7 1,637 2.5 929 7.1 2,566 2+ 14.4 46 3.5 301 5.0 346 Non-marital, non- cohabitating partners in the past 12 months1 0 14.9 474 3.5 552 8.8 1,025 1 8.2 1,395 2.4 732 6.2 2,127 2+ * 12 2.0 250 2.0 261 Condom use at last sexual intercourse in past 12 months Used condom 18.0 281 2.4 780 6.5 1,060 Did not use condom 8.2 1,402 3.4 450 7.0 1,852 No sexual intercourse in past 12 months 10.0 202 2.6 303 5.6 506 Total 15-24 9.8 1,885 2.7 1,533 6.7 3,418 Notes: Total includes 5 cases with missing information on number of sexual partners in the past 12 months, and 5 cases with information missing on number of non-marital, non-cohabitating partners in the past 12 months. An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. 1 Any partner who was not a spouse and did not live with the respondent Table 14.11 HIV prevalence by other characteristics Percentage HIV positive among women and men age 15-49 who have ever had sex and were tested for HIV, according to whether they had an STI in the past 12 months and prior testing for HIV, Zimbabwe 2015 Women Men Total Characteristic Percentage HIV positive Number Percentage HIV positive Number Percentage HIV positive Number Sexually transmitted infection in past 12 months Had STI or STI symptoms 29.6 583 18.1 481 24.4 1,064 No STI, no symptoms 18.9 6,453 12.4 5,163 16.0 11,616 Prior HIV testing Ever tested 20.3 6,555 14.9 4,207 18.2 10,762 Received results 20.2 6,491 15.0 4,116 18.2 10,607 Did not received results 23.1 64 11.2 91 16.1 155 Never tested 13.1 506 7.1 1,444 8.6 1,950 Total 15-49 19.8 7,061 12.9 5,651 16.7 12,711 Note: Total includes 31 cases with information missing on history of STI or STI symptoms and 153 cases with information missing on prior HIV testing. HIV Prevalence • 291 Table 14.12 Prior HIV testing by current HIV status Percent distribution of women and men age 15-49 who tested HIV positive and who tested HIV negative according to HIV testing status prior to the survey, Zimbabwe 2016 Women Men Total HIV testing prior to the survey HIV positive HIV negative HIV positive HIV negative HIV positive HIV negative Ever tested for HIV and received the result of the most recent test 92.8 79.3 83.1 61.0 89.4 70.5 Tested in the past 12 months and received the result1 47.6 50.5 42.1 35.8 45.7 43.4 Tested 12 or more months ago and received the result1 45.2 28.8 41.0 25.2 43.7 27.1 Ever tested for HIV and did not receive the result of the most recent test 1.4 1.1 1.9 1.7 1.6 1.4 Not previously tested 5.8 19.6 15.0 37.2 9.1 28.1 Missing2 1.1 1.9 0.0 0.0 0.7 1.0 Total 100.0 100.0 100.0 100.0 100.0 100.0 Number 1,444 7,223 785 6,690 2,229 13,913 1 Of the most recent HIV test 2 There were 153 women with missing information on prior HIV testing. 292 • HIV Prevalence Table 14.13 HIV prevalence by male circumcision Among men age 15-49 who were tested for HIV, the percentage HIV positive according to whether circumcised, according to background characteristics, Zimbabwe 2015 Circumcised by health worker/ professional Circumcised by traditional practitioner/family/friend All circumcised1 Uncircumcised Background characteristic Percentage HIV positive Number Percentage HIV positive Number Percentage HIV positive Number Percentage HIV positive Number Age 15-19 1.5 438 * 22 1.7 465 2.7 1,553 20-24 6.4 154 * 9 6.8 165 3.2 1,092 25-29 2.9 72 * 26 6.5 105 7.7 947 30-34 2.9 82 (13.7) 31 5.3 124 14.2 925 35-39 12.6 60 (40.7) 24 20.6 95 17.7 736 40-44 (16.5) 55 * 22 16.2 80 28.2 658 45-49 (27.1) 22 (30.9) 36 28.5 65 22.5 467 Religion Traditional * 18 * 2 * 20 18.6 173 Roman Catholic 2.5 69 * 18 7.0 90 12.3 521 Protestant 3.6 162 * 19 4.3 183 8.9 1,001 Pentecostal 5.3 207 (21.8) 24 6.9 244 8.7 1,107 Apostolic sect 4.1 207 (21.9) 41 7.1 260 10.6 2,046 Other Christian 7.9 86 * 17 8.6 104 10.5 349 Muslim * 15 * 20 (20.9) 38 * 18 None 6.2 119 (30.7) 28 10.5 157 13.8 1,153 Other * 0 * 0 * 0 * 9 Residence Urban 6.0 401 22.4 77 8.9 504 11.8 2,194 Rural 4.0 482 20.7 92 6.5 594 10.6 4,183 Province Manicaland 4.7 89 * 18 6.8 107 8.1 889 Mashonaland Central 1.5 47 * 3 1.4 51 10.6 697 Mashonaland East 4.4 62 * 8 7.3 74 12.5 675 Mashonaland West 0.0 87 * 12 4.5 103 10.4 830 Matabeleland North 10.1 55 * 6 10.1 63 13.4 276 Matabeleland South 1.2 74 * 7 5.2 83 18.1 230 Midlands 6.5 90 (24.8) 34 11.7 137 11.6 781 Masvingo 4.0 98 (10.9) 31 5.3 136 9.1 648 Harare 7.9 168 * 37 9.8 213 10.6 1,099 Bulawayo 5.7 114 * 14 8.1 129 16.0 250 Education No education * 0 * 3 * 3 (9.8) 33 Primary 8.8 121 (21.2) 46 11.5 178 11.7 1,501 Secondary 4.6 635 21.1 96 6.8 761 10.8 4,238 More than secondary 3.0 128 * 24 7.1 156 10.7 605 Wealth quintile Lowest 5.4 80 (20.8) 34 9.2 124 12.1 1,011 Second 2.0 132 * 22 4.6 158 12.2 1,162 Middle 5.0 160 * 24 6.5 188 10.1 1,269 Fourth 3.9 217 (25.0) 48 7.6 276 12.2 1,477 Highest 6.8 295 (20.6) 41 9.0 352 8.9 1,458 Total 15-49 4.9 883 21.5 169 7.6 1,098 11.0 6,377 50-54 * 20 * 22 23.0 47 29.9 286 Total 15-54 5.3 904 22.0 191 8.2 1,144 11.8 6,663 Notes: Figures in parentheses are based on 25-49 unweighted cases. An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. 1 Includes all men who report they are circumcised, including men circumcised by medical or traditional practitioners. Also includes those circumcised by other practitioners, those who don’t know what practitioner performed their circumcision, and those who did not report a practitioner of circumcision, not shown separately. HIV Prevalence • 293 Table 14.14 HIV prevalence among couples Percent distribution of couples living in the same household, both of whom were tested for HIV, by HIV status, according to background characteristics, Zimbabwe 2015 Background characteristic Both HIV positive Man HIV positive, woman HIV negative Woman HIV positive, man HIV negative Both HIV negative Total Number of couples Woman’s age 15-19 3.3 6.1 1.3 89.3 100.0 223 20-29 8.0 3.4 3.1 85.4 100.0 1,288 30-39 13.7 6.0 4.9 75.4 100.0 1,172 40-49 15.2 6.4 4.3 74.0 100.0 469 Man’s age 15-19 * * * * 100.0 13 20-29 4.7 2.8 3.1 89.3 100.0 722 30-39 9.2 5.2 3.8 81.7 100.0 1,340 40-49 16.2 6.8 4.3 72.6 100.0 878 50-54 20.3 4.2 4.5 71.1 100.0 198 Age difference between partners Woman older 15.0 11.2 11.5 62.3 100.0 165 Same age/man older by 0-4 years 8.6 5.1 3.7 82.6 100.0 1,293 Man older by 5-9 years 10.3 3.7 2.5 83.4 100.0 1,185 Man older by 10-14 years 12.9 5.6 3.2 78.3 100.0 372 Man older by 15+ years 26.7 7.1 8.5 57.8 100.0 137 Type of union Non-polygynous 11.1 5.0 3.6 80.3 100.0 2,919 Polygynous 7.6 4.9 6.5 81.1 100.0 199 Multiple partners in past 12 months1 Both no 11.2 4.8 3.7 80.3 100.0 2,620 Man yes, woman no 9.4 5.3 4.1 81.2 100.0 509 Woman yes, man no * * * * 100.0 11 Both yes * * * * 100.0 5 Residence Urban 10.7 5.5 3.8 80.0 100.0 1,079 Rural 10.9 4.8 3.8 80.4 100.0 2,072 Province Manicaland 10.3 2.8 2.1 84.8 100.0 401 Mashonaland Central 9.1 4.0 3.5 83.4 100.0 396 Mashonaland East 10.6 5.8 4.2 79.3 100.0 324 Mashonaland West 10.3 3.9 2.3 83.6 100.0 438 Matabeleland North 16.2 6.4 7.8 69.6 100.0 140 Matabeleland South 17.8 6.5 8.4 67.3 100.0 83 Midlands 14.5 5.4 4.7 75.4 100.0 407 Masvingo 8.9 5.4 4.1 81.6 100.0 327 Harare 9.4 5.3 3.5 81.8 100.0 519 Bulawayo 9.6 11.9 5.6 72.8 100.0 116 Woman’s education No education (1.8) (4.5) (1.4) (92.4) 100.0 42 Primary 13.0 5.7 3.5 77.8 100.0 938 Secondary 10.7 4.8 4.1 80.4 100.0 1,964 More than secondary 4.9 4.1 3.0 88.0 100.0 207 Man’s education No education * * * * 100.0 24 Primary 11.8 5.4 3.9 78.9 100.0 743 Secondary 11.2 4.9 3.7 80.2 100.0 1,987 More than secondary 7.4 5.0 4.0 83.6 100.0 398 Wealth quintile Lowest 10.1 5.6 4.7 79.6 100.0 610 Second 11.5 4.3 3.2 80.9 100.0 607 Middle 12.5 5.4 4.2 77.9 100.0 539 Fourth 12.0 5.7 3.4 78.9 100.0 723 Highest 8.4 4.2 3.7 83.7 100.0 673 Total 10.9 5.0 3.8 80.3 100.0 3,151 Notes: The table is based on couples for which a valid test result (positive or negative) is available for both partners. Total includes 32 couples with missing information on type of union, and 6 couples with missing information for number of sexual partners in the past 12 months. Notes: 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 A respondent is considered to have had multiple sexual partners in the past 12 months if he or she had sexual intercourse with two or more people during this time period. (Respondents with multiple partners include polygynous men who had sexual intercourse with two or more wives.) Women’s Empowerment • 295 WOMEN’S EMPOWERMENT 15 Key Findings  Employment and control over earnings: More than half of currently married women age 15-49 (55 percent) are employed compared with 9 in 10 (90 percent) of currently married men. Almost one-third of currently married women who receive cash earnings decide for themselves how their earnings will be used; 62 percent decide jointly with their husbands.  Ownership of assets: About 4 in 10 women and men (37 percent each) own a house. Among women, 3 in 10 (30 percent) own land, and among men one-third (34 percent) own land.  Participation in decision making: Seventy-two percent of currently married women make decisions, either alone or jointly with their husbands, about their own health care, family visits, and major household purchases.  Attitudes toward wife beating: Thirty-nine percent of women and 33 percent of men age 15-49 believe that a husband is justified in beating his wife in at least one of five specified circumstances. his chapter explores women’s empowerment in terms of employment, earnings, control over earnings, and magnitude of earnings relative to those of their partners. In addition, this chapter explores women’s empowerment in terms of employment, earnings, control over earnings, and magnitude of earnings relative to those of their partners. In addition, responses to specific questions are used to define two different indicators of women’s empowerment: women’s participation in household decision making and women’s attitudes towards wife beating. The extent to which women’s empowerment influences maternal health, contraceptive use, and child mortality is also examined. 15.1 MARRIED WOMEN’S AND MEN’S EMPLOYMENT Employment Respondents are considered to be employed if they have done any work other than their housework in the 12 months before the survey. Sample: Currently married women and men age 15-49 Earning cash for employment Respondents are asked if they are paid for their labour in cash or in kind. Only those who receive payment in cash only or in cash and in kind are considered to earn cash for their employment. Sample: Currently married women and men age 15-49 employed in the 12 months before the survey T 296 • Women’s Empowerment Men are more likely to be employed than women. More than half of married women age 15-49 (55 percent) reported being employed at any time in the 12 months before the survey compared with 9 in 10 (90 percent) of currently married men age 15-49 (Table 15.1). Not all women and men receive earnings for the work they do. However, among those who do receive earnings, cash only is the most common form of payment (75 percent of employed women and 77 percent of employed men paid in cash only for their work). Five percent of women and 11 percent of men do not receive any form of earnings for their work. Trends: Among married women, employment increased from 45 percent in 2005 to 55 percent in 2015. The proportion of women receiving only cash earnings increased steadily from 60 percent in 2005 to 68 percent in 2010-11 and 75 percent in 2015, while the proportion who did not receive any earnings for their work decreased from 27 percent in 2005 to 5 percent in 2015. Among currently married men, the percentage employed fluctuated from 90 percent in 2005 to 85 percent in 2010-11 and back to 90 percent in 2015. The proportion of men who receive cash earnings alone increased from 69 percent in 2005 to 76 percent in 2010-11 and 77 percent in 2015. The proportion who did not receive any earnings for their work decreased from 20 percent in 2005 to 11 percent in 2015. Patterns by background characteristics  Employment increases with age among currently married women, peaking at 65 percent in the 45- 49 age group. Variation of employment among currently married men does not follow a clear pattern by age. However, it ranges between 82 and 92 percent across the age groups (Figure 15.1).  Among women, the percentage not paid for work generally increases with age. For men, the youngest (20-24) and oldest (45-49) age groups are the most likely to not be paid (15 percent and 13 percent, respectively). 15.2 CONTROL OVER WOMEN’S EARNINGS Control over one’s own cash earnings Respondents are considered to have control over their own earnings if they participate in decisions alone or jointly with their husband about how their own earnings will be used. Sample: Currently married women age 15-49 who received cash earnings for employment during the 12 months before the survey Figure 15.1 Women’s and men’s employment by age 29 43 55 60 61 62 65 82 91 90 91 92 89 15-19 20-24 25-29 30-34 35-39 40-44 45-49 Percentage of currently married women and men who were employed at any time in the past 12 months Age in years Currently married men Currently married women Women’s Empowerment • 297 To assess women’s autonomy, currently married women who earned cash for their work in the 12 months before the survey were asked who the main decision maker was with regard to the use of their earnings. Women gain direct access to economic resources when they are paid for work in cash and have autonomy to make decisions about how to spend this earned cash. About one-third (32 percent) of currently married women who receive cash earnings report deciding for themselves how their earnings are used, while 62 percent indicate that the decision is made jointly with their husband (Table 15.2.1, Figure 15.2). Only 5 percent of women report that mainly their husband decides how their earnings are used. Sixty-eight percent of women earn less than their husbands and 13 percent earn more. Trends: Since 2005, women’s ability to make independent decisions about the use of their earnings has been constant at about 32 percent, as has their ability to make decisions either independently or jointly with their husbands on the use of their earnings (about 94 percent). Patterns by background characteristics  Percentage of women who make independent decisions about how to use their earnings increases with number of living children (Table 15.2.1).  Married women’s decision-making about the use of their earnings differs across provinces. The proportion of women whose husbands mainly make decisions on the use of their own cash earnings ranges from 2 percent in Matabeleland North to 10 percent in Matabeleland South.  Women with no education or with primary education are more likely to independently control their cash earnings (35 percent) than women with more than a secondary education (24 percent). 15.3 CONTROL OVER MEN’S EARNINGS Among married men age 15-49 who receive cash earnings, 83 percent report that they decide jointly with their wives how to spend those earnings (Table 15.2.2). Only 9 percent of men indicated that they decide alone how to spend their earnings. Married women were also asked who decides how their husband’s earnings are used; 71 percent report that this is a joint decision, while 15 percent report that it was mainly the husband who makes the decision. For information on women’s control over their own earnings and over those of their husbands’ by women’s earnings relative to their husband’s earnings, see Table 15.3. 15.4 WOMEN’S AND MEN’S OWNERSHIP OF ASSETS Ownership of a house or land Respondents who own a house or land, whether alone or jointly with someone else Sample: Women and men age 15-49 Figure 15.2 Control over women’s earnings Mainly wife 32% Wife and husband jointly 62% Mainly husband 5% Percent distribution of currently married women with cash earnings in the last 12 months 298 • Women’s Empowerment Thirty-seven percent of women own a house, either alone, jointly with someone, or both alone and jointly. Similarly, 30 percent of women own land, either alone, jointly, or both alone and jointly (Table 15.4.1, Figure 15.3). Joint ownership of these assets is more common among women than is sole ownership: 29 percent and 25 percent of women, respectively, own a house or land jointly with someone. The proportion of men age 15-49 who own a house is the same as for women (37 percent). However, a slightly higher proportion of men than women own land (34 percent versus 30 percent) (Table 15.4.2). Similar to women, joint ownership of either asset is more common among men than sole ownership. Patterns by background characteristics  House and land ownership, either alone or jointly, increases with age for both women and men. Eight percent of women age 15-19 own a house and 6 percent own land compared with 67 percent and 59 percent, respectively, of women age 45-49. A similar pattern is observed among men (Tables 15.4.1 and 15.4.2).  Women’s and men’s ownership of a house, either alone or jointly, is more common in rural areas than in urban areas. For example, 46 percent of rural women own a house compared with 23 percent of urban women. Similarly, 40 percent of rural women own land compared with 15 percent of urban women. A similar pattern is observed among men, whereby  Women and men in the lowest wealth quintile are more likely to own a house or land compared with respondents in other wealth quintiles. Figure 15.3 House and land ownership 11 4 11 6 19 25 21 29 4 2 5 2 66 70 64 63 Men Women LAND Men Women HOUSE Percent distribution of women and men age 15-49 by house and land ownership Alone Jointly Alone and jointly Do not ownOwn: Women’s Empowerment • 299 15.5 WOMEN’S PARTICIPATION IN DECISION MAKING Participation in major household decisions Women are considered to participate in household decisions if they make decisions alone or jointly with their husband in all three of the following areas: (1) the woman’s own health care, (2) major household purchases, and (3) visits to the woman’s family or relatives. Sample: Currently married women age 15-49 The 2015 ZDHS sought information from currently married women on their participation in three types of household decisions: the respondent’s own health care, major household purchases, and visits to family or relatives (Table 15.5). More than 8 in 10 women participate in each individual decision. Seventy-two percent of women participate in all three decisions, while only 3 percent participate in none of the three decisions (Table 15.6.1, Figure 15.4). Patterns by background characteristics  Women’s participation in all three decisions, either solely or jointly with their husbands, increases with age from 60 percent of women age 15-19 to a peak of 77 percent of women age 35-39, then it declines somewhat thereafter (Table 15.6.1).  Urban women are more likely than rural women to participate in all three decisions, either alone or jointly with their husbands (80 percent and 68 percent, respectively).  Women’s participation in decision making, either alone or jointly with their husbands, increases with education and wealth; 63 percent of women with no education participate in all three decisions compared with 88 percent of women with more than a secondary education. Women in the wealthiest households are more likely to participate in all three decisions than women in the poorest households (82 percent versus 64 percent). The 2015 ZDHS also collected information from married men about their participation in two types of household decisions: their own health care and making major household purchases. Information on men’s participation in decision making is shown in Table 15.5 and Table 15.6.2. Figure 15.4 Women’s participation in decision making 85 87 88 72 3 Woman's own health care Major household purchases Visits to family or relatives Participate in all 3 decisions Participate in none of these decisions Percentage of currently married women age 15-49 participating in select decisions 300 • Women’s Empowerment 15.6 ATTITUDES TOWARDS WIFE BEATING Attitudes toward wife beating Respondents are asked if they agree that a husband is justified in hitting or beating his wife under each of the following five circumstances: she burns the food, she argues with him, she goes out without telling him, she neglects the children, and she refuses to have sex with him. If respondents answer ‘yes’ in at least one circumstance, they are considered to have attitudes that justify wife beating. Sample: Women and men age 15-49 In Zimbabwe, 39 percent of women believe that a husband is justified in beating his wife for at least one of five specified circumstances (Table 15.7.1). The comparable figure among men is 33 percent (Table 15.7.2, Figure 15.5). In addition, for each of the specified circumstances, men were less likely as women to agree that wife beating was justified. Trends: Tolerance of wife beating appears to have declined over time among women and men. The proportion of women who agree that wife beating is justified in at least one of five specified circumstances has decreased from 48 percent in 2005 to 39 percent in 2015. Among men, the proportion has decreased from 37 percent in 2005 to 33 percent in 2015. Patterns by background characteristics  Tolerance for wife beating is higher among never-married women than among ever-married women; 45 percent of never-married women agree that wife beating is justified in at least one of the five specified circumstances compared with 37 percent of currently married women and 33 percent of formerly married women (Table 15.7.1).  Wife beating is more acceptable in rural areas than urban areas; 45 percent of women and 37 percent of men in rural areas agree that wife beating is justified in at least one of the five specified circumstances compared with 29 percent of women and 25 percent of men in urban areas (Tables 15.7.1 and 15.7.2).  Respondents’ tolerance of wife beating decreases steadily with education. For example, 55 percent of women with no education agree with wife beating in at least one of five specified circumstances compared with only 10 percent of women with more than a secondary education.  For both women and men, tolerance of wife beating decreases steadily with wealth. For instance, more than half (51 percent) of women in the lowest wealth quintile agree with wife beating in at least one of five specified circumstances, compared with about one-fourth (26 percent) of women in the highest wealth quintile do so. For additional information on indicators of women’s empowerment and variation of selected health indicators by women’s empowerment, see Tables 15.8, 15.9, 15.10, and 15.11. Figure 15.5 Attitude towards wife beating 8 17 23 21 15 39 6 14 18 18 6 33 Burns the food Argues with him Goes out without telling him Neglects the children Refuses sexual intercourse Any of these reasons Percentage of women and men age 15-49 who agree that a husband is justified in beating his wife for specific reasons Women Men Women’s Empowerment • 301 LIST OF TABLES For detailed information on women’s empowerment and demographic and health outcomes, see the following tables:  Table 15.1 Employment and cash earnings of currently married women and men  Table 15.2.1 Control over women’s cash earnings and relative magnitude of women’s cash earnings  Table 15.2.2 Control over men’s cash earnings  Table 15.3 Women’s control over their own earnings and over those of their husbands  Table 15.4.1 Ownership of assets: Women  Table 15.4.2 Ownership of assets: Men  Table 15.5 Participation in decision making  Table 15.6.1 Women’s participation in decision making by background characteristics  Table 15.6.2 Men’s participation in decision making by background characteristics  Table 15.7.1 Attitude towards wife beating: Women  Table 15.7.2 Attitude towards wife beating: Men  Table 15.8 Indicators of women’s empowerment  Table 15.9 Current use of contraception by women’s empowerment  Table 15.10 Ideal number of children and unmet need for family planning by women’s empowerment  Table 15.11 Reproductive health care by women’s empowerment 302 • Women’s Empowerment Table 15.1 Employment and cash earnings of currently married women and men Percentage of currently married women and men age 15-49 who were employed at any time in the past 12 months and the percent distribution of currently married women and men employed in the past 12 months by type of earnings, according to age, Zimbabwe 2015 Among currently married respondents: Percent distribution of currently married respondents employed in the past 12 months, by type of earnings Total Number of respondents Age Percentage employed in past 12 months Number of respondents Cash only Cash and in- kind In-kind only Not paid WOMEN 15-19 29.4 432 81.9 12.2 2.8 3.0 100.0 127 20-24 42.7 1,045 75.7 16.5 3.0 4.8 100.0 447 25-29 55.4 1,278 72.6 20.3 2.2 4.9 100.0 708 30-34 60.0 1,333 77.8 16.3 1.5 4.4 100.0 799 35-39 60.9 975 75.8 16.0 2.4 5.8 100.0 593 40-44 62.1 707 74.0 19.4 1.1 5.6 100.0 439 45-49 65.4 381 70.2 21.6 2.0 6.2 100.0 249 Total 54.7 6,151 75.2 17.8 2.0 5.0 100.0 3,363 MEN 15-19 * 18 * * * * * 11 20-24 81.9 293 73.6 9.2 2.0 15.1 100.0 240 25-29 90.8 713 75.8 12.9 0.6 10.7 100.0 647 30-34 89.9 926 76.0 14.8 0.2 9.0 100.0 833 35-39 91.4 815 79.6 11.3 0.1 8.9 100.0 745 40-44 91.5 723 75.5 13.6 0.2 10.7 100.0 662 45-49 88.9 523 76.5 10.8 0.1 12.5 100.0 464 Total 15-49 89.8 4,010 76.6 12.6 0.4 10.5 100.0 3,601 50-54 90.6 318 74.2 13.9 1.0 10.9 100.0 288 Total 15-54 89.9 4,328 76.4 12.7 0.4 10.5 100.0 3,889 Note: An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. Women’s Empowerment • 303 Table 15.2.1 Control over women’s cash earnings and relative magnitude of women’s cash earnings Percent distribution of currently married women age 15-49 who received cash earnings for employment in the 12 months preceding the survey by person who decides how wife’s cash earnings are used and by whether she earned more or less than her husband, according to background characteristics, Zimbabwe 2015 Person who decides how the wife’s cash earnings are used: Total Wife’s cash earnings compared with husband’s cash earnings: Total Number of women Background characteristic Mainly wife Wife and husband Mainly husband Other More Less About the same Husband has no earnings Don’t know/ missing Age 15-19 28.6 60.5 9.1 1.8 100.0 11.8 68.9 10.1 5.9 3.3 100.0 119 20-24 33.3 59.9 5.3 1.4 100.0 6.0 77.1 12.8 2.7 1.4 100.0 412 25-29 33.1 59.9 6.6 0.3 100.0 11.2 71.4 13.6 3.1 0.7 100.0 658 30-34 28.2 66.4 5.3 0.2 100.0 12.9 64.6 17.9 3.2 1.4 100.0 752 35-39 34.1 63.2 2.5 0.0 100.0 15.9 65.3 15.3 3.1 0.5 100.0 544 40-44 33.9 62.9 3.1 0.0 100.0 14.7 64.1 15.3 4.3 1.6 100.0 410 45-49 38.4 53.5 7.5 0.1 100.0 15.7 63.1 13.2 5.9 2.1 100.0 229 Number of living children 0 29.7 64.5 4.0 1.5 100.0 9.1 68.5 14.5 4.0 4.0 100.0 177 1-2 30.9 63.4 5.1 0.6 100.0 11.1 71.0 13.7 3.4 0.9 100.0 1,358 3-4 32.8 61.9 5.2 0.1 100.0 14.8 64.7 16.8 2.6 1.1 100.0 1,212 5+ 38.0 56.4 5.3 0.0 100.0 12.4 66.0 13.2 6.8 1.6 100.0 378 Residence Urban 32.4 63.9 3.4 0.3 100.0 14.4 70.3 12.4 2.3 0.7 100.0 1,361 Rural 32.5 60.5 6.5 0.4 100.0 11.2 65.9 16.8 4.5 1.7 100.0 1,764 Province Manicaland 45.2 48.9 4.7 1.3 100.0 11.0 71.6 8.5 4.7 4.2 100.0 389 Mashonaland Central 22.6 73.1 4.4 0.0 100.0 8.7 65.0 22.9 2.7 0.6 100.0 295 Mashonaland East 31.6 64.0 4.4 0.0 100.0 15.3 57.4 22.6 2.5 2.2 100.0 358 Mashonaland West 32.5 61.0 6.5 0.0 100.0 13.5 65.8 17.7 3.0 0.0 100.0 463 Matabeleland North 40.0 57.2 2.0 0.0 100.0 17.9 63.5 10.9 6.8 0.9 100.0 75 Matabeleland South 28.8 59.3 10.4 0.0 100.0 7.6 69.4 13.3 8.1 1.5 100.0 67 Midlands 29.9 62.7 6.4 0.9 100.0 14.3 63.6 18.2 2.7 1.3 100.0 372 Masvingo 26.6 67.2 6.2 0.0 100.0 9.9 68.4 14.2 6.3 1.1 100.0 290 Harare 32.7 62.6 4.1 0.5 100.0 12.8 77.1 8.0 1.7 0.5 100.0 658 Bulawayo 34.8 61.7 3.5 0.0 100.0 14.1 64.3 14.5 7.1 0.0 100.0 157 Education No education (35.1) (54.1) (10.8) (0.0) (100.0) (3.4) (69.4) (18.6) (8.6) (0.0) 100.0 35 Primary 34.9 58.3 6.6 0.0 100.0 11.4 66.7 15.1 5.2 1.7 100.0 761 Secondary 33.2 61.2 5.0 0.6 100.0 12.5 70.2 12.7 3.2 1.3 100.0 1,953 More than secondary 23.5 74.1 2.4 0.0 100.0 15.9 57.4 25.3 1.4 0.1 100.0 376 Wealth quintile Lowest 38.1 52.4 9.3 0.0 100.0 7.7 69.4 14.6 7.1 1.2 100.0 379 Second 33.4 60.9 5.1 0.4 100.0 13.9 63.2 17.1 3.2 2.6 100.0 491 Middle 30.9 61.0 7.2 0.9 100.0 13.7 63.0 16.6 4.9 1.8 100.0 530 Fourth 33.2 62.1 4.1 0.6 100.0 12.6 73.4 10.7 2.4 0.8 100.0 831 Highest 29.7 67.2 3.1 0.0 100.0 13.2 67.2 16.6 2.3 0.6 100.0 893 Total 32.4 62.0 5.1 0.4 100.0 12.6 67.8 14.9 3.5 1.3 100.0 3,125 Note: Figures in parentheses are based on 25-49 unweighted cases. 304 • Women’s Empowerment Table 15.2.2 Control over men’s cash earnings Percent distributions of currently married men age 15-49 who receive cash earnings and of currently married women age 15-49 whose husbands receive cash earnings, by person who decides how husband’s cash earnings are used, according to background characteristics, Zimbabwe 2015 Men Women Person who decides how husband’s cash earnings are used: Total Number of men Person who decides how husband’s cash earnings are used: Background characteristic Mainly wife Husband and wife jointly Mainly husband Mainly wife Husband and wife jointly Mainly husband Other Don’t know/ missing Total Number of women Age 15-19 * * * 100.0 9 13.0 68.6 17.6 0.9 0.0 100.0 405 20-24 7.0 78.7 14.3 100.0 199 16.4 69.5 14.1 0.0 0.0 100.0 999 25-29 10.9 79.6 9.3 100.0 574 12.7 73.3 13.6 0.4 0.0 100.0 1,219 30-34 5.4 86.8 7.8 100.0 756 12.0 74.4 13.4 0.2 0.0 100.0 1,278 35-39 8.3 84.3 7.3 100.0 677 12.5 71.6 15.1 0.8 0.1 100.0 919 40-44 9.4 83.4 7.3 100.0 589 13.4 68.6 17.7 0.3 0.0 100.0 657 45-49 8.9 82.1 9.0 100.0 406 14.4 66.3 18.5 0.5 0.3 100.0 349 Number of living children 0 9.2 78.1 12.7 100.0 225 15.7 67.5 16.1 0.6 0.2 100.0 409 1-2 8.4 83.4 8.1 100.0 1,389 13.1 73.9 12.7 0.3 0.0 100.0 2,567 3-4 7.6 85.0 7.3 100.0 1,179 12.6 71.4 15.7 0.3 0.0 100.0 2,120 5+ 9.1 80.2 10.7 100.0 417 14.9 64.4 19.8 0.9 0.1 100.0 730 Residence Urban 8.0 83.5 8.5 100.0 1,399 13.9 74.3 11.4 0.3 0.0 100.0 2,063 Rural 8.5 83.1 8.4 100.0 1,811 13.0 69.7 16.8 0.4 0.0 100.0 3,763 Province Manicaland 5.9 85.2 8.9 100.0 432 12.8 65.5 20.9 0.8 0.0 100.0 812 Mashonaland Central 5.6 84.4 9.7 100.0 301 7.9 77.8 14.2 0.0 0.0 100.0 613 Mashonaland East 11.3 79.2 9.5 100.0 328 12.2 69.0 18.3 0.5 0.0 100.0 602 Mashonaland West 4.4 91.4 4.2 100.0 448 10.8 73.2 15.8 0.2 0.0 100.0 748 Matabeleland North 5.7 89.6 4.7 100.0 125 18.6 66.2 14.9 0.0 0.3 100.0 243 Matabeleland South 18.3 71.4 10.3 100.0 116 24.1 61.3 13.9 0.1 0.5 100.0 199 Midlands 9.5 80.4 10.2 100.0 352 16.4 68.7 14.1 0.7 0.0 100.0 715 Masvingo 12.9 78.6 8.5 100.0 268 10.1 78.5 11.2 0.2 0.0 100.0 686 Harare 8.0 81.8 10.2 100.0 686 14.6 72.9 12.0 0.4 0.0 100.0 964 Bulawayo 9.3 85.1 5.7 100.0 156 19.9 69.9 10.2 0.0 0.0 100.0 244 Education No education * * * 100.0 11 22.8 64.4 10.5 2.4 0.0 100.0 76 Primary 9.3 80.2 10.4 100.0 627 15.3 63.9 20.2 0.5 0.1 100.0 1,680 Secondary 8.8 82.6 8.6 100.0 2,046 12.9 73.5 13.3 0.3 0.0 100.0 3,651 More than secondary 4.9 89.5 5.6 100.0 526 8.0 84.0 7.7 0.3 0.0 100.0 419 Wealth quintile Lowest 8.7 82.3 8.8 100.0 434 13.3 66.1 20.0 0.5 0.1 100.0 1,067 Second 8.9 84.0 7.1 100.0 487 12.8 68.7 18.1 0.4 0.1 100.0 1,112 Middle 7.4 85.2 7.4 100.0 516 12.3 72.2 14.9 0.6 0.0 100.0 1,002 Fourth 8.8 81.1 10.1 100.0 857 15.5 72.0 12.2 0.3 0.0 100.0 1,374 Highest 7.7 84.2 8.1 100.0 916 12.3 76.7 10.7 0.2 0.0 100.0 1,270 Total 15-49 8.3 83.2 8.5 100.0 3,210 13.3 71.4 14.9 0.4 0.0 100.0 5,825 50-54 9.9 83.5 6.7 100.0 254 na na na na na na na Total 15-54 8.4 83.3 8.3 100.0 3,464 na na na na na na na Note: An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. na = Not applicable Women’s Empowerment • 305 Table 15.3 Women’s control over their own earnings and over those of their husbands Percent distribution of currently married women age 15-49 with cash earnings in the last 12 months by person who decides how the wife’s cash earnings are used; and percent distribution of currently married women age 15-49 whose husbands have cash earnings by person who decides how the husband’s cash earnings are used, according to the relation between wife’s and husband’s cash earnings, Zimbabwe 2015 Person who decides how the wife’s cash earnings are used: Total Number of women Person who decides how husband’s cash earnings are used: Total Number of women Women’s earnings relative to husband’s earnings Mainly wife Wife and husband jointly Mainly husband Other Mainly wife Wife and husband jointly Mainly husband Other More than husband1 34.3 61.3 3.8 0.6 100.0 392 16.0 67.1 16.1 0.8 100.0 392 Less than husband 35.6 58.5 5.6 0.3 100.0 2,118 13.2 68.7 17.9 0.3 100.0 2,118 Same as husband 13.3 82.2 4.5 0.0 100.0 465 8.4 84.1 7.5 0.0 100.0 465 Husband has no cash earnings or did not work 32.1 64.4 3.5 0.0 100.0 110 na na na na na Woman worked but has no cash earnings na na na na na 11.5 72.5 15.3 0.7 100.0 196 Woman did not work na na na na na 14.1 72.2 13.3 0.4 100.0 2,615 Total1 32.4 62.0 5.1 0.4 100.0 3,125 13.3 71.4 14.9 0.4 100.0 5,825 Note: Total includes 36 cases for whom information on women’s earnings relative to husband’s earnings is missing. na = Not applicable 1 Includes cases in which a woman does not know whether she earned more or less than her husband 306 • Women’s Empowerment Table 15.4.1 Ownership of assets: Women Percent distribution of women age 15-49 by ownership of housing and land, according to background characteristics, Zimbabwe 2015 Percentage who own a house: Percentage who do not own a house Total Percentage who own land: Percentage who do not own land Total Number of women Background characteristic Alone Jointly Alone and jointly Alone Jointly Alone and jointly Age 15-19 0.9 6.2 0.4 92.6 100.0 0.4 5.2 0.3 94.0 100.0 2,199 20-24 2.3 20.8 0.7 76.1 100.0 1.1 17.7 1.1 80.1 100.0 1,697 25-29 4.2 34.3 1.7 59.8 100.0 2.5 29.0 1.2 67.3 100.0 1,657 30-34 4.3 40.5 2.7 52.6 100.0 3.1 34.5 2.5 59.9 100.0 1,619 35-39 9.2 41.9 3.7 45.3 100.0 5.4 36.2 3.8 54.5 100.0 1,236 40-44 13.4 44.6 3.0 39.0 100.0 10.0 35.6 1.8 52.6 100.0 965 45-49 20.6 43.4 2.7 33.2 100.0 17.1 40.3 1.5 41.1 100.0 582 Residence Urban 4.0 15.7 2.7 77.5 100.0 1.7 11.0 1.9 85.4 100.0 3,829 Rural 6.6 37.7 1.3 54.4 100.0 5.2 33.6 1.4 59.8 100.0 6,126 Province Manicaland 10.9 30.8 1.1 57.2 100.0 8.3 25.9 0.7 65.1 100.0 1,266 Mashonaland Central 4.4 43.4 1.9 50.2 100.0 3.7 40.7 1.4 54.2 100.0 882 Mashonaland East 3.7 31.5 0.4 64.4 100.0 3.1 26.3 0.4 70.1 100.0 952 Mashonaland West 7.4 34.8 0.7 57.1 100.0 5.0 28.3 0.9 65.8 100.0 1,160 Matabeleland North 6.2 35.3 3.0 55.5 100.0 5.9 29.5 2.7 61.9 100.0 465 Matabeleland South 5.2 23.9 1.6 69.3 100.0 3.4 16.7 1.4 78.5 100.0 419 Midlands 4.8 31.4 2.0 61.7 100.0 2.8 27.8 2.4 66.9 100.0 1,263 Masvingo 5.3 37.2 2.2 55.4 100.0 4.1 36.3 1.9 57.7 100.0 1,187 Harare 4.0 16.2 2.3 77.5 100.0 1.6 10.8 1.7 86.0 100.0 1,783 Bulawayo 2.9 7.6 4.6 84.9 100.0 0.9 5.4 3.9 89.8 100.0 577 Education No education 16.3 41.6 1.8 40.3 100.0 17.5 36.0 0.0 46.5 100.0 126 Primary 8.0 38.5 1.6 51.8 100.0 6.1 34.5 1.7 57.7 100.0 2,571 Secondary 4.3 25.8 1.6 68.3 100.0 2.8 22.1 1.6 73.5 100.0 6,527 More than secondary 7.6 25.1 4.9 62.5 100.0 3.1 14.8 1.4 80.7 100.0 731 Wealth quintile Lowest 8.9 45.7 1.6 43.8 100.0 7.7 39.5 1.7 51.1 100.0 1,704 Second 5.6 40.9 1.2 52.3 100.0 4.1 37.9 1.4 56.7 100.0 1,693 Middle 6.3 31.7 1.3 60.8 100.0 4.9 28.8 1.4 64.9 100.0 1,748 Fourth 4.2 18.0 1.2 76.6 100.0 2.3 14.5 1.2 82.0 100.0 2,307 Highest 4.3 18.8 3.4 73.5 100.0 1.8 13.1 2.2 82.9 100.0 2,503 Total 5.6 29.3 1.8 63.3 100.0 3.9 24.9 1.6 69.6 100.0 9,955 Women’s Empowerment • 307 Table 15.4.2 Ownership of assets: Men Percent distribution of men age 15-49 by ownership of housing and land, according to background characteristics, Zimbabwe 2015 Percentage who own a house: Percentage who do not own a house Total Percentage who own land: Percentage who do not own land Total Number of men Background characteristic Alone Jointly Alone and jointly Alone Jointly Alone and jointly Age 15-19 2.5 2.9 0.0 94.5 100.0 2.5 2.6 0.2 94.6 100.0 2,126 20-24 9.9 8.0 1.2 81.0 100.0 7.7 6.7 1.1 84.5 100.0 1,330 25-29 13.4 19.6 3.8 63.1 100.0 13.5 19.6 3.4 63.6 100.0 1,148 30-34 12.9 31.1 7.6 48.5 100.0 14.6 28.1 5.9 51.4 100.0 1,120 35-39 16.2 36.5 9.7 37.6 100.0 16.9 33.2 7.9 42.0 100.0 917 40-44 16.0 41.9 10.7 31.4 100.0 16.7 37.3 8.9 37.0 100.0 809 45-49 19.9 41.7 13.1 25.3 100.0 21.5 36.8 8.8 32.9 100.0 591 Residence Urban 7.1 12.4 4.7 75.7 100.0 8.2 11.8 3.0 76.9 100.0 2,900 Rural 13.1 25.3 5.1 56.5 100.0 12.7 22.7 4.5 60.1 100.0 5,140 Province Manicaland 14.9 24.0 1.8 59.3 100.0 13.3 21.8 1.5 63.4 100.0 1,072 Mashonaland Central 13.4 32.8 2.3 51.5 100.0 13.7 29.4 1.9 55.0 100.0 806 Mashonaland East 8.5 23.5 9.9 58.2 100.0 9.6 20.2 8.8 61.5 100.0 807 Mashonaland West 10.9 20.4 11.1 57.7 100.0 10.9 17.4 9.5 62.2 100.0 1,004 Matabeleland North 14.1 38.5 2.0 45.5 100.0 8.4 35.5 1.1 55.0 100.0 366 Matabeleland South 13.9 13.2 1.2 71.7 100.0 9.5 14.3 0.8 75.4 100.0 335 Midlands 11.2 23.2 4.8 60.7 100.0 11.0 20.8 3.2 65.1 100.0 986 Masvingo 13.9 16.5 2.0 67.6 100.0 17.1 13.5 2.1 67.3 100.0 843 Harare 5.4 11.9 6.3 76.4 100.0 7.3 13.0 4.6 75.0 100.0 1,412 Bulawayo 7.9 5.7 1.0 85.4 100.0 7.9 4.8 0.5 86.9 100.0 409 Education No education (17.1) (22.3) (4.8) (55.8) 100.0 (13.0) (20.8) (7.9) (58.3) 100.0 38 Primary 13.2 25.4 4.2 57.3 100.0 11.9 22.4 4.6 61.1 100.0 1,803 Secondary 10.0 18.9 4.8 66.3 100.0 10.9 17.9 3.8 67.5 100.0 5,349 More than secondary 12.0 21.5 7.4 59.1 100.0 10.5 16.6 3.6 69.2 100.0 849 Wealth quintile Lowest 17.1 35.2 5.8 41.9 100.0 15.1 32.1 5.2 47.7 100.0 1,212 Second 13.8 27.1 5.7 53.4 100.0 12.4 23.9 5.7 58.0 100.0 1,448 Middle 10.7 20.6 4.5 64.2 100.0 11.9 18.5 3.6 65.9 100.0 1,558 Fourth 7.9 13.7 3.9 74.6 100.0 8.5 11.7 3.3 76.5 100.0 1,852 Highest 8.2 13.5 5.2 73.0 100.0 9.3 13.7 2.9 74.1 100.0 1,970 Total 15-49 10.9 20.7 4.9 63.5 100.0 11.1 18.8 4.0 66.2 100.0 8,041 50-54 22.2 47.6 9.7 20.5 100.0 23.2 38.9 9.9 28.0 100.0 355 Total 15-54 11.4 21.8 5.1 61.6 100.0 11.6 19.6 4.2 64.6 100.0 8,396 Note: Figures in parentheses are based on 25-49 unweighted cases. 308 • Women’s Empowerment Table 15.5 Participation in decision making Percent distribution of currently married women and currently married men age 15-49 by person who usually makes decisions about various issues, Zimbabwe 2015 Decision Mainly wife Wife and husband jointly Mainly husband Someone else Other Total Number of women WOMEN Own health care 34.2 50.5 14.3 0.9 0.1 100.0 6,151 Major household purchases 27.5 59.3 12.7 0.3 0.2 100.0 6,151 Visits to her family or relatives 26.9 61.2 11.4 0.3 0.2 100.0 6,151 MEN Own health care 8.6 74.8 15.9 0.7 0.0 100.0 4,010 Major household purchases 20.1 70.4 9.3 0.2 0.1 100.0 4,010 Table 15.6.1 Women’s participation in decision making by background characteristics Percentage of currently married women age 15-49 who usually make specific decisions either by themselves or jointly with their husband, according to background characteristics, Zimbabwe 2015 Specific decisions All three decisions None of the three decisions Number of women Background characteristic Woman’s own health care Making major household purchases Visits to her family or relatives Age 15-19 72.7 81.5 78.0 59.7 8.2 432 20-24 83.0 85.8 87.2 69.1 2.9 1,045 25-29 84.2 85.5 87.7 70.9 4.0 1,278 30-34 86.6 88.3 89.2 74.2 2.4 1,333 35-39 88.9 88.6 90.3 77.2 2.5 975 40-44 87.0 86.9 90.3 74.4 2.8 707 45-49 83.4 89.2 90.2 73.2 3.1 381 Employment (last 12 months) Not employed 84.8 85.5 86.5 71.3 4.0 2,788 Employed for cash 84.3 88.1 89.7 72.5 2.7 3,125 Employed not for cash 90.1 84.5 86.1 74.8 4.0 238 Number of living children 0 75.7 86.1 81.9 64.9 7.0 426 1-2 84.8 87.4 88.8 72.5 2.9 2,688 3-4 86.8 87.8 90.2 75.2 2.7 2,234 5+ 83.8 82.2 83.5 65.7 4.6 803 Residence Urban 88.6 91.9 93.1 79.9 1.6 2,100 Rural 82.8 84.1 85.5 68.0 4.2 4,051 Province Manicaland 73.3 79.8 83.9 60.9 7.8 857 Mashonaland Central 88.1 88.9 88.4 73.3 1.4 638 Mashonaland East 80.4 81.7 86.9 65.2 4.2 622 Mashonaland West 80.2 88.0 87.9 70.1 3.6 774 Matabeleland North 87.8 80.0 82.4 63.3 2.2 279 Matabeleland South 83.6 85.3 79.6 69.3 6.5 214 Midlands 87.8 90.9 89.1 77.8 2.8 794 Masvingo 91.9 86.2 90.5 77.4 1.9 740 Harare 88.8 91.6 93.0 79.5 1.5 976 Bulawayo 90.8 92.6 89.6 79.4 1.4 258 Education No education 77.2 83.1 82.5 63.3 7.7 88 Primary 80.9 80.4 82.8 63.7 5.5 1,826 Secondary 85.8 88.9 89.9 74.5 2.5 3,813 More than secondary 93.7 96.3 95.9 88.2 0.6 424 Wealth quintile Lowest 82.6 80.9 81.4 64.1 5.4 1,193 Second 81.7 83.4 84.6 66.1 4.6 1,191 Middle 82.2 85.9 88.7 70.7 3.5 1,073 Fourth 86.0 89.4 90.8 75.9 2.4 1,402 Highest 90.2 93.2 94.2 81.9 1.1 1,292 Total 84.7 86.8 88.1 72.1 3.3 6,151 Women’s Empowerment • 309 Table 15.6.2 Men’s participation in decision making by background characteristics Percentage of currently married men age 15-49 who usually make specific decisions either alone or jointly with their wife, according to background characteristics, Zimbabwe 2015 Specific decisions Both decisions Neither of the two decisions Number of men Background characteristic Man’s own health Making major household purchases Age 15-19 * * * * 18 20-24 88.7 78.9 72.2 4.6 293 25-29 89.4 79.1 73.7 5.2 713 30-34 91.8 80.5 76.3 4.0 926 35-39 91.2 78.3 73.1 3.6 815 40-44 91.1 81.3 76.9 4.5 723 45-49 89.9 79.2 74.3 5.3 523 Employment (last 12 months) Not employed 89.0 80.7 75.5 5.8 409 Employed for cash 91.2 79.5 74.8 4.1 3,210 Employed not for cash 87.6 79.7 72.7 5.3 391 Number of living children 0 87.5 79.4 72.7 5.7 311 1-2 90.3 78.5 73.6 4.8 1,676 3-4 91.7 80.7 75.9 3.6 1,447 5+ 90.8 80.4 76.1 4.8 575 Residence Urban 91.3 77.6 73.4 4.5 1,485 Rural 90.3 80.8 75.4 4.4 2,525 Province Manicaland 92.1 73.2 68.4 3.1 493 Mashonaland Central 89.3 78.5 72.5 4.6 462 Mashonaland East 88.9 83.1 75.7 3.7 418 Mashonaland West 96.1 89.8 87.6 1.7 533 Matabeleland North 89.7 84.2 80.8 6.9 169 Matabeleland South 81.2 76.4 66.5 8.9 128 Midlands 88.0 80.5 73.9 5.4 519 Masvingo 90.1 78.3 74.8 6.3 410 Harare 91.5 75.0 70.8 4.3 712 Bulawayo 91.6 77.7 74.7 5.3 168 Education No education * * * * 19 Primary 89.2 80.6 75.4 5.6 887 Secondary 90.6 78.7 73.5 4.2 2,545 More than secondary 93.4 82.8 79.5 3.3 560 Wealth quintile Lowest 90.7 79.0 74.5 4.7 715 Second 89.7 82.0 76.1 4.4 715 Middle 90.1 82.4 76.6 4.1 674 Fourth 91.4 76.7 72.3 4.2 943 Highest 91.0 79.2 74.8 4.6 964 Total 15-49 90.7 79.6 74.7 4.4 4,010 50-54 90.7 77.4 72.8 4.8 318 Total 15-54 90.7 79.4 74.6 4.4 4,328 Note: An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. 310 • Women’s Empowerment Table 15.7.1 Attitude toward wife beating: Women Percentage of all women age 15-49 who agree that a husband is justified in hitting or beating his wife for specific reasons, according to background characteristics, Zimbabwe 2015 Husband is justified in hitting or beating his wife if she: Percentage who agree with at least one specified reason Number of women Background characteristic Burns the food Argues with him Goes out without telling him Neglects the children Refuses to have sexual intercourse with him Age 15-19 13.7 23.1 31.2 29.9 15.2 53.5 2,199 20-24 7.6 19.3 24.5 24.2 16.1 42.1 1,697 25-29 6.6 16.7 23.5 20.4 14.6 38.0 1,657 30-34 6.9 12.8 19.7 17.2 13.4 31.7 1,619 35-39 5.3 11.1 15.7 15.6 13.0 28.6 1,236 40-44 5.5 12.6 16.7 15.7 14.6 30.0 965 45-49 5.8 14.3 18.7 17.2 13.2 30.0 582 Employment (last 12 months) Not employed 9.9 18.6 25.4 23.6 15.6 42.8 4,864 Employed for cash 6.2 14.7 20.1 18.8 13.2 34.5 4,746 Employed not for cash 8.9 18.1 24.3 24.8 17.2 39.0 346 Number of living children 0 10.6 18.4 25.9 26.0 12.7 45.7 2,710 1-2 7.2 16.9 21.9 19.9 14.5 36.4 3,668 3-4 6.4 13.4 20.2 17.9 14.3 33.4 2,664 5+ 9.4 20.8 25.3 23.7 20.4 42.3 912 Marital status Never married 10.6 17.6 24.8 25.2 11.6 44.6 2,511 Married or living together 7.6 17.0 22.8 20.1 15.8 37.4 6,151 Divorced/separated/widowed 5.8 13.5 19.5 19.8 13.9 33.2 1,292 Residence Urban 4.2 10.7 14.2 16.7 8.6 28.8 3,829 Rural 10.5 20.4 28.3 24.3 18.2 44.9 6,126 Province Manicaland 8.4 18.0 26.8 20.1 14.2 39.6 1,266 Mashonaland Central 13.9 23.7 29.6 31.5 22.3 50.0 882 Mashonaland East 7.9 14.5 26.7 22.8 18.5 42.4 952 Mashonaland West 8.4 17.8 27.8 22.5 13.3 43.5 1,160 Matabeleland North 7.3 25.5 22.1 27.2 10.6 43.3 465 Matabeleland South 6.8 22.1 16.5 22.6 9.9 33.7 419 Midlands 7.2 18.5 19.5 17.7 13.3 36.1 1,263 Masvingo 12.5 17.4 29.7 25.2 22.7 46.8 1,187 Harare 4.5 8.8 15.0 15.3 9.5 27.3 1,783 Bulawayo 3.4 12.7 10.2 17.8 7.0 27.4 577 Education No education 17.0 26.4 35.0 33.3 28.5 55.2 126 Primary 12.1 25.5 31.2 26.3 22.1 48.9 2,571 Secondary 7.1 14.7 21.6 21.1 12.4 37.6 6,527 More than secondary 1.1 2.4 2.9 4.6 3.9 10.0 731 Wealth quintile Lowest 13.5 26.9 31.5 29.4 22.4 50.6 1,704 Second 9.8 20.8 29.8 22.9 18.6 46.9 1,693 Middle 9.2 17.8 26.5 23.0 15.6 41.4 1,748 Fourth 7.0 14.3 20.1 20.4 12.1 35.2 2,307 Highest 3.5 8.4 12.2 14.6 7.9 26.3 2,503 Total 8.1 16.7 22.8 21.4 14.5 38.7 9,955 Women’s Empowerment • 311 Table 15.7.2 Attitude toward wife beating: Men Percentage of all men age 15-49 who agree that a husband is justified in hitting or beating his wife for specific reasons, according to background characteristics, Zimbabwe 2015 Husband is justified in hitting or beating his wife if she: Percentage who agree with at least one specified reason Number of men Background characteristic Burns the food Argues with him Goes out without telling him Neglects the children Refuses to have sexual intercourse with him Age 15-19 12.0 21.9 24.6 28.0 9.7 48.9 2,126 20-24 5.8 14.2 21.2 19.1 5.4 37.3 1,330 25-29 5.1 12.3 15.4 14.9 5.3 28.9 1,148 30-34 3.2 10.2 14.7 16.7 4.0 25.8 1,120 35-39 2.2 11.6 14.1 13.2 4.7 23.4 917 40-44 2.2 7.0 11.8 11.7 3.7 19.8 809 45-49 1.6 8.2 9.3 7.9 3.5 17.6 591 Employment (last 12 months) Not employed 8.6 15.5 18.3 22.0 7.0 38.5 2,128 Employed for cash 4.3 12.6 16.5 16.1 5.2 29.0 5,013 Employed not for cash 8.2 17.5 23.4 21.7 7.5 40.3 900 Number of living children 0 9.1 17.7 21.7 22.9 7.7 41.6 3,969 1-2 3.5 11.6 15.2 15.2 4.1 26.8 1,957 3-4 1.8 8.8 12.5 12.2 4.0 21.9 1,523 5+ 2.5 9.5 13.2 12.5 5.2 21.8 591 Marital status Never married 9.3 18.2 21.8 23.2 7.8 42.4 3,624 Married or living together 3.1 10.2 14.2 13.8 4.4 24.6 4,010 Divorced/separated/widowed 3.3 12.4 16.3 18.3 4.7 28.8 407 Residence Urban 2.3 8.8 11.8 15.0 3.7 25.0 2,900 Rural 7.9 16.8 21.0 20.1 7.2 37.2 5,140 Province Manicaland 7.7 12.3 21.7 18.3 7.1 32.3 1,072 Mashonaland Central 8.7 15.8 19.1 22.6 8.3 37.6 806 Mashonaland East 6.9 12.5 18.9 14.9 6.0 32.0 807 Mashonaland West 6.9 15.2 19.9 20.7 5.8 35.7 1,004 Matabeleland North 4.2 28.3 18.4 23.6 4.8 41.0 366 Matabeleland South 4.1 16.9 14.7 13.8 4.1 28.9 335 Midlands 5.8 14.4 16.6 18.8 4.2 34.6 986 Masvingo 8.0 18.1 22.0 19.9 8.8 39.2 843 Harare 1.5 7.9 12.5 15.8 4.5 24.9 1,412 Bulawayo 5.0 10.5 10.9 13.1 4.1 24.4 409 Education No education (9.4) (22.0) (37.8) (30.5) (16.2) (45.4) 38 Primary 8.9 19.8 23.2 23.6 8.6 40.1 1,803 Secondary 5.6 13.5 17.8 18.0 5.5 33.3 5,349 More than secondary 1.3 4.3 4.7 8.2 2.9 13.7 849 Wealth quintile Lowest 9.1 21.0 23.2 24.2 8.2 42.1 1,212 Second 8.0 16.7 20.8 18.4 7.2 36.4 1,448 Middle 8.8 16.4 22.0 21.3 7.4 37.6 1,558 Fourth 4.1 11.6 16.9 17.7 4.5 31.0 1,852 Highest 1.7 7.8 9.5 12.6 3.7 22.3 1,970 Total 15-49 5.9 13.9 17.7 18.3 5.9 32.8 8,041 50-54 2.0 9.7 13.1 10.9 5.5 22.0 355 Total 15-54 5.7 13.8 17.5 17.9 5.9 32.3 8,396 Note: Figures in parentheses are based on 25-49 unweighted cases. 312 • Women’s Empowerment Table 15.8 Indicators of women’s empowerment Percentage of currently married women age 15-49 who participate in all decision making and the percentage who disagree with all of the reasons justifying wife-beating, according to value on each of the indicators of women’s empowerment, Zimbabwe 2015 Empowerment indicator Percentage who participate in all decision making Percentage who disagree with all the reasons justifying wife- beating Number of women Number of decisions in which women participate1 0 na 56.2 205 1-2 na 53.9 1,513 3 na 65.8 4,433 Number of reasons for which wife- beating is justified2 0 75.8 na 3,850 1-2 67.5 na 1,494 3-4 63.2 na 631 5 60.5 na 176 na = Not applicable 1 See Table 15.6.1 for the list of decisions. 2 See Table 15.7.1 for the list of reasons. Table 15.9 Current use of contraception by women’s empowerment Percent distribution of currently married women age 15-49 by current contraceptive method, according to selected indicators of women’s status, Zimbabwe 2015 Any method Any modern method Modern methods Any traditional method Not currently using Total Number of women Empowerment indicator Female sterili- sation Male sterili- sation Temporary modern female methods1 Male condom Number of decisions in which women participate2 0 48.1 45.6 0.8 0.0 42.7 2.0 2.5 51.9 100.0 205 1-2 62.3 61.1 0.7 0.0 57.4 2.9 1.1 37.7 100.0 1,513 3 69.2 68.3 0.8 0.0 63.3 4.2 0.9 30.8 100.0 4,433 Number of reasons for which wife-beating is justified3 0 68.9 67.9 1.1 0.1 62.1 4.6 1.0 31.1 100.0 3,850 1-2 64.1 63.0 0.2 0.0 60.3 2.5 1.1 35.9 100.0 1,494 3-4 62.6 61.8 0.2 0.0 59.5 2.1 0.8 37.4 100.0 631 5 57.0 57.0 0.0 0.0 54.1 2.9 0.0 43.0 100.0 176 Total 66.8 65.8 0.8 0.0 61.1 3.8 1.0 33.2 100.0 6,151 Note: If more than one method is used, only the most effective method is considered in this tabulation. 1 Pill, IUD, injectables, implants, female condom, emergency contraception, and lactational amenorrhea method 2 See Table 15.6.1 for the list of decisions. 3 See Table 15.7.1 for the list of reasons. Women’s Empowerment • 313 Table 15.10 Ideal number of children and unmet need for family planning by women’s empowerment Mean ideal number of children for women 15-49 and percentage of currently married women age 15-49 with an unmet need for family planning, according to indicators of women’s empowerment, Zimbabwe 2015 Empowerment indicator Mean ideal number of children1 Number of women Percentage of currently married women with an unmet need for family planning2 Number of currently married women For spacing For limiting Total Number of decisions in which women participate3 0 4.8 202 11.3 4.7 16.0 205 1-2 4.5 1,508 7.3 3.9 11.1 1,513 3 4.2 4,421 5.4 4.6 9.9 4,433 Number of reasons for which wife- beating is justified4 0 3.9 6,076 5.0 4.5 9.5 3,850 1-2 3.9 2,583 7.0 4.3 11.3 1,494 3-4 4.3 1,010 9.1 3.7 12.8 631 5 4.3 252 10.1 4.4 14.5 176 Total 3.9 9,920 6.0 4.4 10.4 6,151 1 Mean excludes respondents who gave non-numeric responses 2 See Table 7.12.1 for the definition of unmet need for family planning. 3 Restricted to currently married women. See Table 15.6.1 for the list of decisions. 4 See Table 15.7.1 for the list of reasons. Table 15.11 Reproductive health care by women’s empowerment Percentage of women age 15-49 with a live birth in the 5 years preceding the survey who received antenatal care, delivery assistance, and postnatal care from health personnel for the most recent birth, according to indicators of women’s empowerment, Zimbabwe 2015 Empowerment indicator Percentage receiving antenatal care from a skilled provider1 Percentage receiving delivery care from a skilled provider1 Number of women with a child born in the last 5 years Received postnatal care from health personnel within the first 2 days since delivery2 Number of women with a child born in the last 5 years Number of decisions in which women participate3 0 77.5 64.2 138 60.2 84 1-2 89.3 74.3 1,073 69.6 573 3 95.1 83.6 3,007 76.8 1,469 Number of reasons for which wife- beating is justified4 0 94.4 83.8 3,033 75.9 1,422 1-2 91.9 77.1 1,252 72.1 677 3-4 92.7 75.2 545 68.3 269 5 85.6 63.9 157 58.8 85 Total 93.3 80.6 4,988 73.4 2,454 1 ‘Skilled provider’ includes doctor, nurse, or nurse midwife. 2 Includes women who received a postnatal check from a doctor, nurse, midwife, community health worker or traditional birth attendant (TBA) in the first two days after the birth. Includes women who gave birth in a health facility and those who did not give birth in a health facility 3 Restricted to currently married women. See Table 15.6.1 for the list of decisions. 4 See Table 15.7.1 for the list of reasons. Domestic Violence • 315 DOMESTIC VIOLENCE 16 Key Findings  Physical violence: Thirty-five percent of women age 15- 49 experienced physical violence since age 15; 15 percent of women have experienced physical violence within the past 12 months.  Sexual violence: Fourteen percent of women age 15-49 experienced sexual violence at least once in their lifetime, and 8 percent experienced sexual violence in the past 12 months.  Emotional violence: Thirty-two percent of ever-married women have experienced spousal emotional violence; 24 percent experienced spousal emotional violence in the 12 months preceding the survey.  Violence during pregnancy: Six percent of women who have ever been pregnant experienced violence during one or more of their pregnancies.  Spousal violence: Overall, 35 percent of ever-married women age 15-49 experienced physical or sexual violence from a spouse, and of these women, 37 percent reported experiencing physical injuries.  Seeking to stop violence: Thirty-nine percent of women who have ever experienced physical or sexual violence have sought help. ender-based violence against women has been acknowledged worldwide as a violation of basic human rights. An increasing amount of research has highlighted the health burdens, intergenerational effects, and demographic consequences of such violence (United Nations 2006). The WHO defines this violence as “the intentional use of physical force or power, threatened or actual, against oneself, another person, or against a group or community, that either results in or has a high likelihood of resulting in injury, death, psychological harm, maldevelopment, or deprivation” (Krug et al. 2002). This chapter focuses on domestic violence, a form of gender-based violence, which is defined here as any act of violence that results in physical, sexual, or psychological harm or suffering to women, girls, and men, including threats of such acts, coercion, or arbitrary deprivation of liberty. In Zimbabwe, domestic violence is widely acknowledged as a great concern, not only from a human rights perspective but also from an economic and health perspective. In 2006, Zimbabwe enacted the Domestic Violence Act “to make provision for the protection and relief of victims of domestic violence” (Domestic Violence Act [Chapter 5:16] Act 14/2006). Despite the new legislation and ongoing efforts to protect women and vulnerable populations against violence, there is widespread recognition in Zimbabwe that much remains to be done to protect victims. In addition, reliable data are needed to further inform and educate the population about the problem. G 316 • Domestic Violence To collect such data, the 2015 ZDHS questionnaire included the domestic violence module, which was also included in the 2005-06 and 2010-11 ZDHS surveys. The series of questions focuses on specific aspects of domestic and interpersonal violence. The module addresses women’s experiences of acts of physical and sexual violence. Information is collected on both domestic violence (also known as spousal violence or intimate partner violence) and violence by other family members or unrelated individuals. This chapter presents the findings for women age 15-49 who have experienced interpersonal physical or sexual violence, and describes from whom they sought help. The chapter also provides detailed information from ever-married women on their experience of spousal emotional, physical, and sexual violence, at any time in their lives and in the past 12 months, the physical consequences of the violence, and when the violence first began in the relationship. Information is also included on women’s perpetration of spousal violence. 16.1 MEASUREMENT OF VIOLENCE Collecting valid, reliable, and ethical data on intimate partner violence poses particular challenges, because (1) what constitutes violence or abuse varies across cultures and individuals, and (2) a “culture of silence” can create sensitivity and affect reporting. Assuring the respondents’ and interviewers’ safety when asking questions about domestic violence in a familial setting and protecting those women who disclose violence raise ethical concerns. One woman age 15-49 in each household was randomly selected to be administered the domestic violence module. All female interviewers were trained to obtain complete privacy before asking questions in the domestic violence module. If the interviewer could not obtain complete privacy with the respondent, this fact was noted in the questionnaire and the interviewer did not proceed with administering the domestic violence module. 16.1.1 The Use of Valid Measures of Violence The 2015 ZDHS measured violence committed by spouses and by other household members. Accordingly, information was obtained from ever-married women on violence by spouses and others, and from never- married women on violence by anyone, including boyfriends. International research on violence shows that intimate partner violence is one of the most common forms of violence against women. Spousal or partner violence was measured in more detail than violence by other perpetrators through the use of a shortened, modified Conflict Tactics Scale (CTS) (Straus 1990). Specifically, spousal violence by the husband or partner for currently married women, and the most recent husband or partner for formerly married women was measured by asking all ever-married women the following set of questions: Did your (last) husband/partner ever: a) Say or do something to humiliate you in front of others? b) Threaten to hurt or harm you or someone you care about? c) Insult you or make you feel bad about yourself? Did your (last) husband/partner ever do any of the following things to you: d) Push you, shake you, or throw something at you? e) Slap you? f) Twist your arm or pull your hair? g) Punch you with his fist or with something that could hurt you? h) Kick you, drag you, or beat you up? i) Try to choke you or burn you on purpose? j) Threaten or attack you with a knife, gun, or any other weapon? k) Physically force you to have sexual intercourse with him even when you did not want to? l) Physically force you to perform any other sexual acts you did not want to? m) Force you with threats or in any other way to perform any sexual acts you did not want to? Domestic Violence • 317 When the answer to any of these questions was “yes,” women were asked about the frequency of the act in the 12 months preceding the survey. A “yes” answer to one or more of items (a) to (c) above constitutes evidence of emotional violence, a “yes” answer to one or more of items (d) to (j) constitutes evidence of physical violence, and a “yes” answer to items (k) to (m) constitutes evidence of sexual violence. This approach of asking about specific acts to measure different forms of violence has the advantage of not being affected by different understandings of what constitutes a summary term like violence. By including a wide range of acts, the approach also has the advantage of giving the respondent multiple opportunities to disclose any experience of violence. In addition to these questions asked only of ever-married women, all women were asked about physical violence perpetrated by others with the question: From the time you were 15 years old, has anyone [other than your current (last) husband/partner] hit, slapped, kicked, or done anything else to hurt you physically? Respondents who answered this question in the affirmative were asked who had done this to them. A similar question asked women who had ever been pregnant about violence during pregnancy. Women were also asked about sexual violence by anyone other than the current husband/partner with the following question: At any time in your life, as a child or as an adult, has anyone ever forced you in any way to have sexual intercourse or perform any other sexual acts? Although this approach to questioning is generally considered optimal, the possibility of underreporting of violence exists in any survey. 16.1.2 Ethical Considerations Three specific protections were built into the questionnaire in accordance with the WHO’s ethical and safety recommendations for research on domestic violence (WHO 2001). Only one eligible woman in each household was administered the questions on violence. The DHS Program protocol specifies that the domestic violence module can only be administered to one randomly selected woman per household. Therefore, in households with more than one eligible woman, the respondent for the module was selected with a CSPro random generation function. Interviewing only one woman in each household for the domestic violence module provides assurance to the selected respondent that other respondents in the household will not know about the questions the selected respondent was asked. Informed consent for the survey was obtained from the respondent at the beginning of the individual interview. In addition, at the beginning of the domestic violence section, respondents were read an additional statement informing them that the subsequent questions could be sensitive and reassuring them of the confidentiality of their responses. The domestic violence module was implemented only if privacy could be obtained. If privacy could not be obtained, the interviewer was instructed to skip the module, thank the respondent, and end the interview. Complete privacy is also essential for ensuring the security of the respondent and the interviewer. Asking about or reporting violence, especially in households where the perpetrator may be present at the time of interview, carries the risk of further violence. In addition, collection of such sensitive information requires the establishment of rapport between the interviewer and the respondent. Accordingly, interviewers were provided with specific training for implementing the domestic violence module to enable the field staff to collect violence data in a secure, confidential, and ethical manner. 16.1.3 Subsample for the Violence Module In accordance with the ethical requirements, only one woman per household was selected for the module. In total 7,233 women were selected and interviewed with the module. Less than one percent of eligible 318 • Domestic Violence women who were selected for the module were not interviewed because complete privacy could not be obtained. Specially constructed weights were used to adjust for the selection of only one woman per household and to ensure that the domestic violence subsample was nationally representative. 16.2 EXPERIENCE OF PHYSICAL VIOLENCE Physical violence by anyone Percentage of women who have experienced any physical violence (committed by a husband or anyone else) since age 15 and in the 12 months preceding the survey. Sample: Women age 15-49 This section provides information on women’s experience of physical violence since age 15, and describes the perpetrators of the violence. In Zimbabwe, women from all socioeconomic and cultural backgrounds are subject to violence. Table 16.1 shows the percentage of women age 15-49 who have ever experienced any form of physical violence since age 15, by background characteristics. The table also presents data on women who experienced physical violence 12 months preceding the survey. Thirty-five percent of women in Zimbabwe have experience physical violence since age 15, and 15 percent have experienced physical violence within the past 12 months. Among women age 15-49 who have experienced physical violence since age 15, 54 percent report their current husband/partner was a perpetrator, 23 percent report a former husband/partner, and 7 percent report other relatives (Table 16.2). Among every-married women who experienced violence since age 15, 64 percent report their current husband/partner committed acts of physical violence and 27 percent report former husbands or partners. Among never-married women, 22 percent report that the persons who committed acts of physical violence against them are other relatives, 19 percent report teachers, and 24 percent report other persons. Trends: Women’s experience with physical violence has changed little over the past decade: 36 percent of women age 15-49 reported having ever experienced physical violence since age 15 in the 2005-06 ZDHS, 30 percent in the 2010-11 ZDHS, and 35 percent in the 2015 ZDHS (Figure 16.1). In all three surveys, women most commonly reported that the person committing the physical violence is a current husband/partner, followed by a former husband/partner. Patterns by background characteristics  Women’s experience of physical violence since age 15 varies by age, ranging from a low of 28 percent among women age 15-19 to a peak of 42 percent among women age 25-29, and then decreasing among women age 30 and older (Table 16.1).  There is little variation in women’s experience of physical violence by urban-rural residence; however, the prevalence of physical violence since age 15 varies greatly by province, ranging from 23 percent in Matabeleland South to 45 percent in Mashonaland East. Figure 16.1 Trends in physical violence 32 29 34 39 31 3536 30 35 2005-06 2010-11 2015 Percentage of women who have ever experienced physical violence since age 15 Urban Rural Total Domestic Violence • 319  Women who have never married are much less likely than currently married women to have experienced physical violence (23 percent versus 37 percent, respectively). Almost half of divorced, separated, or widowed women (48 percent) report that they have experienced physical violence (Figure 16.2).  Currently employed women, whether employed for cash or not, have experienced higher rates of violence than women who are not employed (40 percent compared with 30 percent).  Women’s experience of violence declines sharply with education, from 38 percent with no education or primary education only to 22 percent among women with more than secondary education).  Approximately one-third of all women have experienced physical violence, regardless of wealth quintile, although the proportion is lowest among women in the highest wealth quintile (29 percent). 16.3 EXPERIENCE OF SEXUAL VIOLENCE Sexual violence Percentage of women who have experienced any sexual violence (committed by a husband or anyone else) ever and in the 12 months preceding the survey. Sample: Women age 15-49 Table 16.3 shows that 14 percent of women age 15-49 reported that they have experienced sexual violence at some point in their lives, and 8 percent experienced sexual violence in the past 12 months. The variation in women’s experience of sexual violence by most background characteristics is similar to the variation in their experience of physical violence, with a few notable exceptions. Unlike physical violence, the percentage of women who have experienced sexual violence varies little by education. Among women age 15-49 who ever experienced sexual violence, 55 percent reported that the perpetrator was their current husband/partner and 30 reported their former husband/partner (Table 16.4). Among all women age 15-49, 5 percent first experienced sexual violence by age 18, and 8 percent experienced sexual violence by age 22 (Table 16.5). 16.4 EXPERIENCE OF DIFFERENT FORMS OF VIOLENCE Table 16.6 presents data by current age on the percentage of women age 15-49 who report having experienced physical violence, sexual violence, or both. Thirty-nine percent of women report that they have experienced either physical or sexual violence at some point in their lives; 26 percent experienced physical violence only, 5 percent experienced sexual violence only, and 9 experienced both physical and Figure 16.2 Women’s experience of physical or sexual violence by marital status 23 6 37 14 48 24 Percentage who have ever experienced physical violence since age 15 Percentage who have ever experienced sexual violence Never married Married or living together Divorced/separated/widowed 320 • Domestic Violence sexual violence. Experience of physical or sexual violence is highest among women age 25-29 (48 percent). 16.5 VIOLENCE DURING PREGNANCY Experiencing violence during pregnancy not only affects the health of the woman, but also can have serious consequences for the unborn child. In the 2015 ZDHS, women who had ever been pregnant were asked whether they had experienced any type of physical violence during any of their pregnancies and who was the perpetrator of the violence. Table 16.7 presents findings on violence during pregnancy according to background characteristics. Overall, 6 percent of women report that they have experienced violence during pregnancy. Trends: Violence against women during pregnancy decreased from 8 percent in 2005-06 to 5 percent in 2010-11, and was 6 percent in 2015. Patterns by background characteristics  By age, violence during pregnancy is highest among women age 15-19 (11 percent).  The prevalence of violence during pregnancy varies little by urban-rural residence but shows greater variation by province. Prevalence of violence during pregnancy was highest among women in Mashonaland East (8 percent) and lowest among women in Matabeleland South (2 percent).  By marital status, the category of women who have the highest prevalence of violence during pregnancy is divorced, separated, or widowed women (11 percent). 16.6 MARITAL CONTROL Marital control Percentage of women whose current husband/partner (if currently married) or most recent husband/partner (if formerly married) demonstrates at least one of the following sets of controlling behaviors: is jealous or angry if she talks to other men; frequently accuses her of being unfaithful; does not permit her to meet her female friends; tries to limit her contact with her family; and insists on knowing where she is at all times. Sample: Ever-married women age 15-49 Attempts by husbands or partners to closely control and monitor their wives’ behaviour are important early warning signs and correlates of violence in a relationship. A series of questions were included in the 2015 ZDHS to elicit the degree of marital control exercised by the husband/partner over the respondent. Controlling behaviours most often manifest themselves as extreme possessiveness, jealousy, and attempts to isolate the woman from her family and friends. Because the concentration of such behaviours is more significant than the display of any single behaviour, the proportion of women whose husbands display at least three of the specified behaviours is highlighted. To examine the degree of marital control by husbands of their wives, ever-married women were asked whether they experienced any of the following five controlling behaviours by their husbands: (1) he is jealous or angry if she talks to other men; (2) he frequently accuses her of being unfaithful; (3) he does not permit her to meet her female friends; (4) he tries to limit contact with her family; and (5) he insists on knowing where she is at all times. Table 16.8 presents the percentage of ever-married women whose husbands or partners display each of the listed behaviours, by background characteristics. Domestic Violence • 321 Fifty-one percent of ever-married women report that their husband/partner is jealous or angry if she talks to other men, and 50 percent report that he insists on knowing where she is at all times. Twenty-three percent report that their husbands frequently accuse them of being unfaithful, 16 percent say that he does not permit her to meet her female friends, and 12 percent report that their husbands try to limit their contact with their families. Twenty-four percent of ever-married women report that their current or past husband/partner has displayed three or more of the behaviours described above. 16.7 SPOUSAL VIOLENCE Spousal violence Percentage of women who have experienced any of the specified acts of physical, sexual, or emotional violence committed by their current husband/partner (if currently married) or most recent husband/partner (if formerly married), ever and in the 12 months preceding the survey. Sample: Ever-married women age 15-49 Emotional violence A woman experiences emotional violence when someone says or does something to humiliate her in front of others, or when someone threatened to hurt or harm her or someone she cares about, or when someone insulted her or made her feel bad about herself. Sample: Ever-married women age 15-49 16.7.1 Prevalence of Spousal Violence Table 16.9 shows the percentage of ever-married women by their experience with spousal violence (emotional, physical, or sexual). It should be noted that different types of violence are not mutually exclusive, and women may report multiple forms of violence. Overall, 45 percent of ever-married women reported ever experiencing physical, sexual, or emotional violence by their current or most recent partner. Thirty percent reported experiencing spousal violence in the past 12 months either sometimes (21 percent) or often (9 percent). Thirty-one percent of ever-married women experienced physical violence by their current of most recent partner. Slapping was the most common act of physical violence, reported by 26% of women. Ten percent of women have been pushed, shaken, or had something thrown at them and 10 percent have been punched (Figure 16.3). Figure 16.3 Types of spousal violence 3 9 10 2 3 8 10 5 26 10 2 6 7 1 2 5 5 3 12 6 Forced her with threats or in any other way to perform sexual acts she did not want to Physically forced her to perform any other sexual acts she did not want to Physically forced her to have sexual intercourse with him when she did not want to Threatened her or attacked her with a knife, gun, or other weapon Tried to choke her or burn her on purpose Kicked her, dragged her, or beat her up Punched her with his fist or with something that could hurt her Twisted her arm or pulled her hair Slapped her Pushed her, shook her, or threw something at her Percentage of ever-married women age 15-49 who have ever experienced specfic acts of violence by their husband/partner Last 12 months Ever 322 • Domestic Violence Thirteen percent of ever-married women have experienced one or more acts of sexual violence by their current or most recent partner, the most common being physically forced to have sexual intercourse by their spouse when they did not want to (10 percent). Thirty-two percent of women reported ever experiencing emotional violence; 27 percent reported that their husband/partner had insulted them or made them feel bad about themselves. Among women who have been married more than once, spousal violence could have been perpetrated by an earlier husband/partner. To capture the totality of women’s experience of spousal physical or sexual violence, ever-married women were also asked about physical and sexual violence committed by their former husband/partner. Overall, 38 percent of ever-married women have experienced physical or sexual violence by any husband/partner, and 20 percent experienced such violence in the 12 months preceding the survey. Patterns by background characteristics  Experience of spousal violence does not differ by urban-rural residence (45 percent each). However, does vary by province, ranging from a low of 30 percent in Matebeleland North to a high of 53 percent in Mashonaland West (Table 16.10).  Spousal violence is higher among women who are divorced, separated, or widowed (51 percent) than among currently married women (44 percent).  Spousal violence decreases with education. Fifty percent of women with no education have experienced spousal violence compared with 30 percent with more than secondary education. Patterns by husband’s characteristics and empowerment indicators  Women whose husbands/partners have more than a secondary education are less likely than women with less educated husbands to have experienced physical, sexual, or emotional spousal violence (33 percent compared with 43-49 percent) (Table 16.11).  Three-quarters of women (75 percent) whose husbands become drunk very frequently report have experienced physical, sexual, or emotional spousal violence (Figure 16.4).  The likelihood of spousal violence increases substantially with the number of marital control behaviours the husband/partner displays; experience of spousal violence is more than two times as common among women whose husband/partner displays five controlling behaviours (95 percent) as among women whose husband/partner displays one or two controlling behaviours (43 percent).  Spousal violence is also substantially more common among women who are afraid of their husband/partner. Differences in the experience of spousal violence according to women’s decision-making capacity and attitudes toward wife beating are less striking. 16.7.2 Recent Spousal Violence Table 16.12 shows that 20 percent of ever-married women have experienced physical or sexual violence committed by their spouse in the past 12 months. Figure 16.4 Spousal violence by husband’s alcohol consumption 38 35 52 75 Does not drink Drinks/never gets drunk Gets drunk sometimes Gets drunk very often Percentage of ever-married women who have ever experienced spousal (physical, sexual, or emotional) violence Domestic Violence • 323 Patterns by background characteristics  Experience with the spousal violence in the past 12 months varies inversely with age—the older the women, the less likely they are to have experienced recent spousal violence.  Women who are employed but do not receive payment in cash (25 percent) are more likely to have experienced spousal violence than women who are employed and paid in cash or not employed (20 percent each).  Women with more than secondary education are much less likely to have experienced recent spousal violence than women with less education (10 percent versus 19-22 percent). 16.8 DURATION OF MARRIAGE AND SPOUSAL VIOLENCE To study the timing of the onset of marital violence, the 2015 ZDHS asked ever-married women who experienced physical or sexual spousal violence when the first episode of violence took place after marriage. Table 16.13 shows the interval between marriage and the first episode of spousal physical or sexual violence among women who have been married only once. One percent of women report that spousal physical or sexual violence started before they were married. Fifteen percent of women report that violence initiated by 2 years of marriage, while 24 percent report that it started after they were married for 5 years. Twenty-nine percent of women said that spousal violence initiated after 10 years of marriage. 16.9 INJURIES DUE TO SPOUSAL VIOLENCE Injuries due to spousal violence Percentage of women who have the following types of injuries from spousal violence: cuts, bruises, or aches; eye injuries, sprains, dislocations, or burns; or deep wounds, broken bones, broken teeth, or any other serious injury. Sample: Ever-married women age 15-49 who have experienced physical or sexual violence committed by their current husband/partner (if currently married) or most recent husband/partner (if formerly married) Table 16.14 presents information on the types of injuries ever-married women have endured as a result of spousal violence. Thirty-four percent of women who have ever experienced spousal physical or sexual violence received cuts, bruises, or aches; 10 percent had eye injuries, sprains, dislocations, or burns; and 7 percent had deep wounds, broken bones, broken teeth, or other serious injuries as a result of the violence. Overall, 37 percent of women who have ever experienced spousal physical or sexual violence have experienced one or more of these injuries, and 41 percent of women who have experienced spousal physical or sexual violence in the past month have experienced one or more injuries. 16.10 VIOLENCE INITIATED BY WOMEN AGAINST THEIR HUSBANDS/PARTNERS In domestic violence, either person can be the instigator of violent behaviour. In the 2015 ZDHS, ever- married women were asked about instances when they were the instigator of spousal violence. Specifically, all ever-married women were asked if they had ever tried to instigate physical violence against their husband when he was not already hitting or beating them. Tables 16.15 presents the percentages of ever- married women who have committed physical violence against their husband or partner when he was not already harming them, by background characteristics. Four percent of ever-married women report that they have instigated physical violence against their current or most recent husband, and 2 percent report that they have done so in the past year. Women who have 324 • Domestic Violence themselves experienced spousal violence are more likely to report ever initiating violence against their husband/partner (7 percent) than those who have not experienced violence (2 percent). Additional information on women’s violence against their spouse by their husband’s characteristics and by empowerment indicators are presented in Table 16.16. 16.11 RESPONSE TO VIOLENCE 16.11.1 Help-Seeking among Women Who Have Experienced Violence Table 16.17 presents information on help-seeking behaviour among women who have ever experienced violence, by type of violence experienced and background characteristics. Less than half of women (39 percent) who have experienced physical or sexual violence from anyone have sought help from any source. Another 19 percent have not sought help but have told someone that they were victims of violence. Four in ten women (42 percent) have never sought help or told anyone. Trends: Among women who have ever experienced physical or sexual violence, the percentage who sought help increased from 31 percent in the 2005-06 ZDHS to 37 percent in the 2010-11 ZDHS, and to 38 percent in the 2015 ZDHS. Patterns by background characteristics  Women who experienced both physical and sexual violence were more likely to have sought help (51 percent) than women who experienced only physical violence (36 percent) or only sexual violence (30 percent) (Figure 16.5)  Women living in rural areas are more likely that their counterparts in urban areas to have sought help (41 percent versus 35 percent).  By province, help seeking is most common in Mashonaland West (52 percent) and least common in Harare (30 percent).  Divorced or separated women are more likely to have sought help (44 percent) than never-married women (36 percent) or married women (38 percent).  Help seeking for violence declines with increasing wealth, from above 44 percent of women in the lowest wealth quintile to 36 percent of women in the highest wealth quintile. 16.11.2 Sources for Help Table 16.18 presents information on the sources of help by type of violence. The majority of women who have experienced any form of violence and sought help did so from a member of their own family (54 percent), while 37 percent sought help from their husband’s family. Twenty-one percent of women sought help from the police, and 8 percent from a friend. Trends: Among women who have ever experienced physical or sexual violence and sought help, the percentage who sought help from police increased from 10 percent in the 2005-06 ZDHS to 13 percent in the 2010-11 ZDHS, and to 21 percent in the 2015 ZDHS. Figure 16.5 Help seeking by type of violence experienced 36 30 51 Physical only Sexual only Physical and sexual Percentage of women age 15-49 who have experienced physical or sexual violence who sought help Domestic Violence • 325 LIST OF TABLES For more information on domestic violence, see the following tables:  Table 16.1 Experience of physical violence  Table 16.2 Persons committing physical violence  Table 16.3 Experience of sexual violence  Table 16.4 Persons committing sexual violence  Table 16.5 Age at first experience of sexual violence  Table 16.6 Experience of different forms of violence  Table 16.7 Experience of violence during pregnancy  Table 16.8 Marital control exercised by husbands  Table 16.9 Forms of spousal violence  Table 16.10 Spousal violence according to background characteristics  Table 16.11 Spousal violence by husband’s characteristics and empowerment indicators  Table 16.12 Frequency of physical or sexual violence  Table 16.13 Experience of spousal violence by duration of marriage  Table 16.14 Injuries to women due to spousal violence  Table 16.15 Women’s violence against their spouse according to background characteristics  Table 16.16 Women’s violence against their spouse according to husband’s characteristics  Table 16.17 Help seeking to stop violence  Table 16.18 Sources for help to stop the violence 326 • Domestic Violence Table 16.1 Experience of physical violence Percentage of women age 15-49 who have ever experienced physical violence since age 15 and percentage who have experienced violence during the 12 months preceding the survey, according to background characteristics, Zimbabwe 2015 Percentage who have ever experienced physical violence since age 151 Percentage who have experienced physical violence in the past 12 months Number of women Background characteristic Often Sometimes Often or sometimes2 Age 15-19 27.9 2.3 13.5 15.9 1,537 20-24 34.8 3.6 13.3 16.8 1,190 25-29 42.4 4.1 14.3 18.5 1,205 30-39 36.7 2.9 10.4 13.3 2,110 40-49 32.7 2.0 6.2 8.1 1,181 Religion Traditional (25.9) (2.3) (0.0) (2.3) 41 Roman Catholic 31.8 1.6 7.6 9.2 466 Protestant 31.4 2.8 9.1 12.0 1,169 Pentecostal 32.9 2.3 11.5 13.8 1,793 Apostolic sect 36.9 3.2 12.4 15.7 3,039 Other Christian 31.5 3.9 9.5 13.5 315 Muslim * * * * 27 None 45.3 4.8 19.0 24.0 367 Other * * * * 6 Residence Urban 34.2 2.5 11.6 14.2 2,739 Rural 35.2 3.2 11.4 14.6 4,484 Province Manicaland 34.3 3.4 13.4 16.8 909 Mashonaland Central 34.5 2.7 12.3 15.0 647 Mashonaland East 45.1 2.1 14.2 16.4 691 Mashonaland West 38.6 2.4 10.4 13.0 850 Matabeleland North 27.3 1.4 9.6 11.0 335 Matabeleland South 23.3 2.9 7.8 10.7 311 Midlands 36.5 3.8 10.9 14.7 921 Masvingo 29.3 4.1 9.9 14.0 881 Harare 35.8 2.4 12.6 15.1 1,262 Bulawayo 31.4 2.9 9.2 12.2 415 Marital status Never married 22.9 1.3 9.2 10.5 1,729 Married or living together 36.8 3.3 13.0 16.3 4,593 Divorced/separated/widowed 47.6 4.2 8.4 12.7 902 Number of living children 0 25.0 1.9 10.6 12.6 1,859 1-2 38.2 3.6 12.8 16.5 2,656 3-4 37.8 2.9 10.7 13.7 2,026 5+ 39.9 3.1 11.1 14.2 681 Employment Employed for cash 39.5 3.0 11.7 14.7 3,458 Employed not for cash 39.6 4.6 15.2 19.8 253 Not employed 29.9 2.7 11.1 13.8 3,512 Education No education 37.8 1.7 15.0 16.6 96 Primary 37.5 3.8 12.3 16.1 1,910 Secondary 35.1 2.8 11.8 14.6 4,680 More than secondary 21.9 1.4 5.2 6.7 537 Wealth quintile Lowest 36.4 3.8 11.6 15.3 1,260 Second 37.5 3.6 12.4 16.1 1,239 Middle 34.9 2.9 11.4 14.4 1,270 Fourth 37.4 2.9 13.9 16.9 1,680 Highest 29.4 1.9 8.6 10.4 1,775 Total 34.8 2.9 11.5 14.5 7,223 Note: Figures in parentheses are based on 25-49 unweighted cases. An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. 1 Includes violence in the past 12 months. For women who were married before age 15 and who reported physical violence by a spouse, the violence could have occurred before age 15. 2 Includes women for whom frequency in the past 12 months is not known. Domestic Violence • 327 Table 16.2 Persons committing physical violence Among women age 15-49 who have experienced physical violence since age 15, percentage who report specific persons who committed the violence, according to the respondent’s current marital status, Zimbabwe 2015 Marital status Total Person Ever- married Never married Current husband/partner 64.0 na 53.9 Former husband/partner 26.9 na 22.6 Current boyfriend 0.3 2.9 0.7 Former boyfriend 2.9 5.1 3.3 Father/step-father 2.9 10.6 4.1 Mother/step-mother 2.5 14.0 4.3 Sister/brother 3.3 12.7 4.8 Daughter/son 0.1 0.7 0.2 Other relative 4.0 21.5 6.7 Mother-in-law 0.1 na 0.1 Father-in-law 0.1 na 0.1 Other in-law 0.4 na 0.4 Teacher 1.4 18.6 4.1 Employer/someone at work 0.4 0.1 0.4 Police/soldier 0.1 0.0 0.1 Other 6.0 23.9 8.8 Number women who have experienced physical violence since age 15 2,120 395 2,515 Note: Women can report more than one person who committed the violence. na = Not applicable 328 • Domestic Violence Table 16.3 Experience of sexual violence Percentage of women age 15-49 who have ever experienced sexual violence and percentage who have experienced sexual violence in the 12 months preceding the survey, according to background characteristics, Zimbabwe 2015 Percentage who have experienced sexual violence: Number of women Background characteristic Ever1 In past 12 months Age 15-19 9.5 4.7 1,537 20-24 13.7 8.0 1,190 25-29 14.9 9.0 1,205 30-39 15.9 9.4 2,110 40-49 13.0 5.8 1,181 Religion Traditional (7.1) (3.2) 41 Roman Catholic 13.9 6.6 466 Protestant 11.9 5.9 1,169 Pentecostal 12.8 6.1 1,793 Apostolic sect 15.2 9.3 3,039 Other Christian 9.3 4.0 315 Muslim * * 27 None 12.9 9.4 367 Other * * 6 Residence Urban 13.1 6.8 2,739 Rural 13.8 8.0 4,484 Province Manicaland 15.9 10.7 909 Mashonaland Central 14.8 8.9 647 Mashonaland East 15.0 7.7 691 Mashonaland West 18.2 8.8 850 Matabeleland North 8.2 3.2 335 Matabeleland South 5.1 2.7 311 Midlands 13.4 6.8 921 Masvingo 11.2 8.0 881 Harare 13.0 7.3 1,262 Bulawayo 11.6 3.9 415 Marital status Never married 5.8 1.1 1,729 Married or living together 14.4 9.7 4,593 Divorced/separated/widowed 24.1 8.6 902 Employment Employed for cash 15.9 8.5 3,458 Employed not for cash 11.9 8.1 253 Not employed 11.4 6.5 3,512 Number of living children 0 7.6 2.7 1,859 1-2 15.9 9.3 2,656 3-4 15.2 8.8 2,026 5+ 15.5 9.6 681 Education No education 13.7 9.2 96 Primary 15.6 9.2 1,910 Secondary 12.9 7.1 4,680 More than secondary 11.4 5.0 537 Wealth quintile Lowest 15.6 9.8 1,260 Second 15.0 8.9 1,239 Middle 11.9 5.8 1,270 Fourth 15.5 9.0 1,680 Highest 10.4 4.7 1,775 Total 13.5 7.5 7,223 Note: Figures in parentheses are based on 25-49 unweighted cases. An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. 1 Includes violence in the past 12 months Domestic Violence • 329 Table 16.4 Persons committing sexual violence Among women age 15-49 who have experienced sexual violence, percentage who report specific persons who committed the violence according to the respondent’s current marital status, Zimbabwe 2015 Marital status Total Person Ever- married1 Never married Current husband/partner 60.8 na 54.6 Former husband/partner 29.6 na 26.5 Current/former boyfriend 4.5 43.8 8.6 Father/step-father 0.1 3.6 0.5 Brother/step-brother 0.5 1.3 0.6 Other relative 4.0 17.0 5.3 In-law 0.9 na 0.9 Own friend/acquaintance 0.6 5.4 1.1 Family friend 0.4 4.1 0.8 Teacher 0.0 0.2 0.0 Employer/someone at work 0.2 1.5 0.4 Police/soldier 0.2 0.0 0.2 Stranger 4.8 14.4 5.8 Other 1.3 7.8 2.0 Number women who have experienced sexual violence 878 100 978 1 Women can report more than one person who committed the violence. na = Not applicable Table 16.5 Age at first experience of sexual violence Percentage of women age 15-49 who experienced sexual violence by specific exact ages, according to current age and current marital status, Zimbabwe 2015 Percentage who first experienced sexual violence by exact age: Percentage who have not experienced sexual violence Number of women Background characteristic 10 12 15 18 22 Current age 15-19 0.3 0.6 3.2 na na 90.5 1,537 20-24 1.4 1.8 2.6 6.5 na 86.3 1,190 25-29 1.7 1.7 2.3 4.8 8.4 85.1 1,205 30-39 1.4 1.5 1.8 3.5 6.5 84.1 2,110 40-49 0.9 1.2 1.8 3.5 5.3 87.0 1,181 Marital status Never married 0.6 0.6 2.2 4.5 5.1 94.2 1,729 Ever married 1.3 1.6 2.3 5.4 8.9 84.0 5,494 Total 1.1 1.4 2.3 5.2 8.0 86.5 7,223 na = Not applicable Table 16.6 Experience of different forms of violence Percentage of women age 15-49 who have ever experienced different forms of violence by current age, Zimbabwe 2015 Age Physical violence only Sexual violence only Physical and sexual violence Physical or sexual violence Number of women 15-19 21.8 3.4 6.1 31.3 1,537 15-17 21.8 2.9 5.8 30.5 976 18-19 21.8 4.3 6.7 32.8 561 20-24 25.9 4.8 8.9 39.6 1,190 25-29 32.9 5.4 9.5 47.8 1,205 30-39 25.7 4.8 11.1 41.6 2,110 40-49 23.9 4.3 8.7 36.9 1,181 Total 25.8 4.5 9.0 39.4 7,223 330 • Domestic Violence Table 16.7 Experience of violence during pregnancy Among women age 15-49 who have ever been pregnant, percentage who have ever experienced physical violence during pregnancy, according to background characteristics, Zimbabwe 2015 Background characteristic Percentage who experienced violence during pregnancy Number of women who have ever been pregnant Age 15-19 11.4 363 20-24 6.0 928 25-29 5.8 1,115 30-39 4.9 2,052 40-49 4.3 1,145 Religion Traditional (0.0) 30 Roman Catholic 5.7 352 Protestant 4.7 800 Pentecostal 5.1 1,321 Apostolic sect 6.2 2,509 Other Christian 4.4 236 Muslim * 20 None 5.2 327 Other * 6 Residence Urban 5.2 2,010 Rural 5.7 3,593 Province Manicaland 5.1 723 Mashonaland Central 5.0 541 Mashonaland East 8.0 543 Mashonaland West 6.6 692 Matabeleland North 5.0 275 Matabeleland South 2.1 237 Midlands 6.9 725 Masvingo 5.0 674 Harare 4.6 923 Bulawayo 4.6 269 Marital status Never married 4.5 245 Married or living together 4.6 4,478 Divorced/separated/widowed 10.5 880 Number of living children 0 7.9 239 1-2 5.5 2,656 3-4 5.0 2,026 5+ 6.5 681 Education No education 2.9 91 Primary 6.3 1,663 Secondary 5.6 3,432 More than secondary 2.7 417 Wealth quintile Lowest 5.1 1,080 Second 7.8 997 Middle 5.2 987 Fourth 5.7 1,335 Highest 4.2 1,204 Total 5.5 5,603 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. D om es tic V io le nc e • 3 31 T a b le 1 6 .8 M a ri ta l c o n tr o l e x e rc is e d b y h u s b a n d s P er ce nt ag e of e ve r- m ar rie d w om en a ge 1 5- 49 w ho se h us ba nd s or p ar tn er s ha ve e ve r de m on st ra te d sp ec ifi c ty pe s of c on tro lli ng b eh av io ur s, a cc or di ng t o ba ck gr ou nd c ha ra ct er is tic s, Zi m ba bw e 20 15 P er ce nt ag e of w om en w ho se h us ba nd /p ar tn er : N um be r o f e ve r- m ar rie d w om en B ac kg ro un d ch ar ac te ris tic Is je al ou s or an gr y if sh e ta lk s to o th er m en Fr eq ue nt ly ac cu se s he r o f be in g un fa ith fu l D oe s no t p er m it he r t o m ee t h er fe m al e fri en ds Tr ie s to li m it he r co nt ac t w ith h er fa m ily In si st s on kn ow in g w he re sh e is a t a ll tim es D is pl ay s 3 or m or e of th e sp ec ifi c be ha vi ou rs D is pl ay s no ne o f th e sp ec ifi c be ha vi ou rs A ge 15 -1 9 54 .5 29 .7 21 .3 15 .6 54 .6 29 .7 28 .7 35 0 20 -2 4 54 .3 23 .4 20 .0 14 .1 56 .1 27 .0 29 .1 89 0 25 -2 9 54 .6 26 .2 17 .9 12 .3 54 .5 28 .3 31 .0 1, 08 2 30 -3 9 49 .0 22 .1 15 .2 11 .1 47 .5 21 .7 35 .4 2, 03 2 40 -4 9 46 .7 17 .8 12 .6 10 .8 42 .0 19 .4 38 .1 1, 14 0 R el ig io n Tr ad iti on al (4 1. 2) (1 2. 3) (6 .4 ) (6 .2 ) (5 8. 7) (2 .9 ) (2 5. 8) 31 R om an C at ho lic 48 .0 21 .2 15 .2 9. 6 47 .5 21 .3 34 .2 33 6 P ro te st an t 50 .3 21 .1 15 .9 10 .0 45 .9 23 .2 37 .1 77 6 P en te co st al 55 .0 21 .6 16 .5 11 .0 51 .2 24 .6 31 .9 1, 29 3 A po st ol ic s ec t 49 .3 23 .0 16 .1 13 .5 49 .2 23 .7 34 .2 2, 48 5 O th er C hr is tia n 47 .1 21 .6 16 .6 11 .9 51 .8 20 .9 32 .3 22 4 M us lim * * * * * * * 22 N on e 52 .3 30 .9 20 .0 12 .3 54 .1 30 .3 30 .1 32 3 O th er * * * * * * * 5 R es id en ce U rb an 54 .3 21 .4 18 .5 12 .0 48 .3 24 .5 32 .9 1, 95 6 R ur al 48 .9 23 .4 15 .2 12 .1 50 .3 23 .6 34 .0 3, 53 8 P ro vi nc e M an ic al an d 48 .9 21 .9 15 .9 14 .5 58 .0 26 .2 29 .8 73 2 M as ho na la nd C en tra l 52 .8 25 .3 19 .0 11 .5 48 .8 25 .2 31 .7 55 0 M as ho na la nd E as t 52 .9 24 .9 16 .7 15 .6 48 .6 26 .7 34 .4 54 7 M as ho na la nd W es t 50 .5 23 .9 14 .0 11 .5 57 .9 23 .6 29 .3 69 1 M at ab el el an d N or th 37 .2 17 .2 12 .2 7. 0 43 .1 19 .4 46 .9 24 9 M at ab el el an d S ou th 33 .2 16 .9 11 .2 8. 3 32 .8 15 .0 54 .0 19 8 M id la nd s 47 .8 23 .2 16 .0 12 .2 46 .2 23 .1 34 .5 70 8 M as vi ng o 53 .1 22 .2 14 .4 10 .9 44 .4 20 .6 35 .4 67 5 H ar ar e 56 .4 22 .8 20 .7 12 .0 47 .0 26 .1 33 .3 90 5 B ul aw ay o 58 .2 20 .7 16 .7 10 .4 57 .5 24 .2 23 .9 24 0 M ar ita l s ta tu s M ar rie d or li vi ng to ge th er 48 .8 21 .3 14 .6 10 .5 48 .1 21 .9 35 .5 4, 59 3 D iv or ce d/ se pa ra te d/ w id ow ed 61 .2 29 .9 25 .3 20 .0 57 .1 34 .4 24 .3 90 2 N um be r of li vi ng c hi ld re n 0 55 .6 21 .2 19 .4 11 .4 53 .4 23 .4 29 .9 33 9 1- 2 53 .8 24 .1 17 .9 13 .0 52 .1 26 .3 30 .7 2, 46 1 3- 4 47 .1 21 .2 14 .3 10 .8 46 .5 21 .5 37 .4 2, 01 7 5+ 48 .7 23 .0 15 .4 12 .6 47 .3 22 .6 34 .7 67 8 (C on tin ue d… ) 33 2 • D om es tic V io le nc e T ab le 1 6. 8— C o n ti n u e d P er ce nt ag e of w om en w ho se h us ba nd /p ar tn er : N um be r o f e ve r- m ar rie d w om en B ac kg ro un d ch ar ac te ris tic Is je al ou s or an gr y if sh e ta lk s to o th er m en Fr eq ue nt ly ac cu se s he r o f be in g un fa ith fu l D oe s no t p er m it he r t o m ee t h er fe m al e fri en ds Tr ie s to li m it he r co nt ac t w ith h er fa m ily In si st s on kn ow in g w he re sh e is a t a ll tim es D is pl ay s 3 or m or e of th e sp ec ifi c be ha vi ou rs D is pl ay s no ne o f th e sp ec ifi c be ha vi ou rs E m pl oy m en t E m pl oy ed fo r c as h 53 .1 23 .2 17 .6 12 .8 51 .4 25 .2 31 .4 2, 94 8 E m pl oy ed n ot fo r c as h 49 .4 21 .3 13 .7 8. 5 50 .7 18 .8 33 .2 21 9 N ot e m pl oy ed 48 .1 22 .2 15 .0 11 .4 47 .1 22 .8 36 .6 2, 32 7 E du ca tio n N o ed uc at io n 44 .2 23 .5 14 .2 13 .3 42 .1 24 .4 39 .2 90 P rim ar y 48 .7 26 .8 16 .8 13 .3 50 .4 25 .4 33 .5 1, 64 4 S ec on da ry 52 .3 21 .7 16 .2 11 .7 49 .7 23 .8 33 .1 3, 35 9 M or e th an s ec on da ry 48 .2 14 .4 16 .2 9. 5 46 .4 18 .5 37 .7 40 1 W ea lth q ui nt ile Lo w es t 47 .0 26 .3 15 .8 11 .9 46 .8 23 .4 35 .9 1, 05 0 S ec on d 48 .0 21 .8 14 .1 12 .9 50 .2 22 .1 34 .8 99 3 M id dl e 48 .6 25 .4 14 .7 11 .3 52 .5 24 .9 33 .3 96 4 Fo ur th 55 .2 22 .7 20 .1 14 .2 53 .3 28 .0 30 .9 1, 31 3 H ig he st 53 .5 18 .1 16 .0 9. 7 44 .9 20 .6 34 .0 1, 17 5 W om an a fr ai d of h us ba nd /p ar tn er M os t o f t he ti m e af ra id 72 .8 51 .9 47 .2 39 .8 76 .3 59 .7 13 .3 44 4 S om et im es a fra id 64 .3 38 .7 27 .1 21 .7 66 .7 41 .1 19 .0 95 8 N ev er a fra id 45 .3 15 .8 10 .5 6. 8 42 .6 16 .0 39 .3 4, 09 2 To ta l 50 .8 22 .7 16 .4 12 .0 49 .5 23 .9 33 .6 5, 49 4 N ot es : H us ba nd /p ar tn er r ef er s to t he c ur re nt h us ba nd /p ar tn er f or c ur re nt ly m ar rie d w om en a nd t he m os t re ce nt h us ba nd /p ar tn er f or d iv or ce d, s ep ar at ed , or w id ow ed w om en . Fi gu re s in pa re nt he se s ar e ba se d on 2 5- 49 u nw ei gh te d ca se s. A n as te ris k in di ca te s th at a fi gu re is b as ed o n fe w er th an 2 5 un w ei gh te d ca se s an d ha s be en s up pr es se d. Domestic Violence • 333 Table 16.9 Forms of spousal violence Percentage of ever-married women age 15-49 who have experienced various forms of violence ever or in the 12 months preceding the survey, committed by their husbands/partners, Zimbabwe 2015 Ever In the past 12 months Type of violence Often Sometimes Often or sometimes SPOUSAL VIOLENCE COMMITTED BY CURRENT OR MOST RECENT HUSBAND/PARTNER Physical violence Any physical violence 30.7 3.3 11.9 15.2 Pushed her, shook her, or threw something at her 10.3 1.6 4.2 5.8 Slapped her 26.3 2.2 10.0 12.2 Twisted her arm or pulled her hair 5.0 1.0 1.9 2.8 Punched her with his fist or with something that could hurt her 10.0 1.5 3.8 5.3 Kicked her, dragged her, or beat her up 8.1 1.3 3.2 4.6 Tried to choke her or burn her on purpose 2.5 0.5 1.4 1.9 Threatened her or attacked her with a knife, gun, or other weapon 2.1 0.3 0.8 1.1 Sexual violence Any sexual violence 12.7 2.4 6.9 9.3 Physically forced her to have sexual intercourse with him when she did not want to 9.8 1.9 5.2 7.0 Physically forced her to perform any other sexual acts she did not want to 8.5 1.6 4.6 6.2 Forced her with threats or in any other way to perform sexual acts she did not want to 3.3 0.9 1.3 2.2 Emotional violence Any emotional violence 31.5 7.2 16.3 23.5 Said or did something to humiliate her in front of others 12.4 3.0 5.9 9.0 Threatened to hurt or harm her or someone she cared about 11.8 2.1 6.0 8.1 Insulted her or made her feel bad about herself 26.7 5.6 14.6 20.3 Any form of physical and/or sexual violence 35.4 4.8 15.1 19.8 Any form of emotional and/or physical and/or sexual violence 45.0 9.0 21.1 30.1 SPOUSAL VIOLENCE COMMITTED BY ANY HUSBAND/PARTNER Physical violence 32.9 na na 15.3 Sexual violence 13.6 na na 9.3 Physical and/or sexual violence 37.6 na na 19.9 Number of ever-married women 5,494 5,494 5,494 5,494 na = Not available 334 • Domestic Violence Table 16.10 Spousal violence according to background characteristics Percentage of ever-married women age 15-49 who have ever experienced emotional, physical or sexual violence committed by their husband/partner, according to background characteristics, Zimbabwe 2015 Background characteristic Emotional violence Physical violence Sexual violence Physical and sexual Physical and sexual and emotional Physical or sexual Physical or sexual or emotional Number of ever-married women Age 15-19 31.9 31.1 18.4 11.0 10.0 38.6 45.2 350 20-24 31.1 32.5 13.2 8.5 7.0 37.2 45.9 890 25-29 35.5 35.9 12.3 7.7 6.3 40.5 50.9 1,082 30-39 32.5 30.6 13.4 8.6 7.1 35.4 45.7 2,032 40-49 26.4 24.5 9.6 5.9 5.2 28.3 37.5 1,140 Religion Traditional (15.0) (23.4) (9.3) (9.3) (5.1) (23.4) (30.3) 31 Roman Catholic 22.5 24.9 12.4 8.4 6.9 28.9 36.9 336 Protestant 30.6 27.5 10.7 6.8 6.0 31.5 41.5 776 Pentecostal 29.6 29.2 12.1 7.4 6.6 33.9 43.4 1,293 Apostolic sect 33.1 32.0 14.1 8.8 7.2 37.3 46.9 2,485 Other Christian 33.8 31.0 9.6 6.0 5.3 34.5 43.5 224 Muslim * * * * * * * 22 None 37.7 41.5 12.4 8.3 6.4 45.6 54.9 323 Other * * * * * * * 5 Residence Urban 32.0 30.0 12.1 7.5 6.6 34.6 45.0 1,956 Rural 31.3 31.1 13.0 8.2 6.8 35.9 45.0 3,538 Province Manicaland 32.9 31.8 16.0 9.4 7.3 38.5 47.8 732 Mashonaland Central 30.4 26.1 13.9 8.4 7.1 31.6 41.1 550 Mashonaland East 29.1 37.6 11.7 8.4 6.6 40.8 48.7 547 Mashonaland West 33.3 37.9 18.2 10.9 8.5 45.1 52.5 691 Matabeleland North 22.5 17.3 5.5 2.8 2.5 19.9 29.9 249 Matabeleland South 26.0 23.2 5.5 4.3 3.3 24.4 32.4 198 Midlands 36.8 33.1 11.1 7.8 7.0 36.5 48.8 708 Masvingo 28.0 27.7 11.3 7.7 7.1 31.3 38.7 675 Harare 32.3 29.3 12.4 7.5 6.9 34.2 44.5 905 Bulawayo 35.9 28.8 9.1 4.8 3.9 33.1 49.7 240 Marital status Married or living together 29.9 29.2 11.5 6.6 5.5 34.0 43.7 4,593 Divorced/separated/widowed 39.8 38.5 18.9 14.9 13.0 42.5 51.4 902 Education No education 36.0 31.7 10.8 7.1 7.1 35.4 49.8 90 Primary 33.3 34.3 14.0 9.3 7.5 39.0 48.4 1,644 Secondary 31.6 30.4 12.5 7.6 6.4 35.3 45.0 3,359 More than secondary 22.5 18.2 9.6 6.0 5.9 21.8 29.9 401 Wealth quintile Lowest 33.1 31.6 14.2 9.9 8.2 35.9 46.3 1,050 Second 30.7 32.8 14.0 9.8 7.9 37.0 45.3 993 Middle 31.9 32.2 11.8 6.6 5.5 37.3 47.2 964 Fourth 33.8 32.8 14.0 8.4 7.6 38.5 46.7 1,313 Highest 27.9 24.7 9.5 5.5 4.4 28.7 39.8 1,175 Total 31.5 30.7 12.7 8.0 6.7 35.4 45.0 5,494 Notes: Husband/partner refers to the current husband/partner for currently married women and the most recent husband/partner for divorced, separated, or widowed women. 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. Domestic Violence • 335 Table 16.11 Spousal violence by husband’s characteristics and empowerment indicators Percentage of ever-married women age 15-49 who have ever experienced emotional, physical, or sexual violence committed by their husband/partner, by husband’s characteristics and empowerment indicators, Zimbabwe 2015 Background characteristic Emotional violence Physical violence Sexual violence Physical and sexual Physical and sexual and emotional Physical or sexual Physical or sexual or emotional Number of ever- married women Husband’s/partner’s education1 No education 27.3 31.3 18.4 12.1 8.7 37.6 42.8 71 Primary 35.7 33.6 13.3 9.0 7.5 37.8 49.2 977 Secondary 29.6 29.4 11.4 6.3 5.2 34.6 43.9 2,991 More than secondary 20.6 18.6 7.4 3.5 2.8 22.5 32.5 482 Don’t know/missing 27.9 29.4 9.7 4.5 4.5 34.7 38.1 73 Husband’s/partner’s alcohol consumption Does not drink alcohol 26.3 24.9 10.3 5.9 5.2 29.3 37.9 3,299 Drinks alcohol but is never drunk 22.1 19.6 5.6 2.5 1.3 22.8 35.2 86 Is drunk sometimes 34.4 36.3 13.3 8.5 6.3 41.1 52.0 1,687 Is drunk very often 63.0 55.9 30.5 23.2 21.3 63.2 74.6 422 Spousal education difference Husband has more education 30.9 30.7 10.6 5.8 4.7 35.6 45.2 2,152 Wife has more education 32.6 30.5 13.3 9.7 8.0 34.0 44.4 960 Both have equal education 26.5 25.9 11.4 5.7 4.8 31.6 41.3 1,395 Neither has any education * * * * * * * 13 Don’t know/missing 38.9 37.8 18.2 14.2 12.4 41.9 50.4 975 Spousal age difference1 Wife older 31.3 30.4 13.2 6.6 5.0 37.0 45.2 148 Wife is same age 27.0 30.2 8.4 6.1 4.9 32.5 41.9 186 Wife is 1-4 years younger 30.1 32.0 12.1 7.8 6.4 36.2 45.2 1,621 Wife is 5-9 years younger 30.6 29.3 12.3 6.5 5.6 35.2 44.5 1,678 Wife is 10 or more years younger 28.6 24.0 9.3 5.0 3.8 28.3 40.2 958 Missing * * * * * * * 1 Number of marital control behaviours displayed by husband/partner2 0 12.0 15.3 3.8 2.1 1.5 17.1 22.2 1,848 1-2 27.4 26.9 10.6 4.8 3.2 32.7 43.8 2,332 3-4 60.7 55.7 24.8 18.6 16.7 61.8 74.8 1,036 5 86.9 72.4 44.5 34.9 33.8 82.0 95.2 278 Number of decisions in which women participate3 0 37.2 31.3 17.5 8.6 6.1 40.1 54.6 144 1-2 36.4 36.2 13.0 8.2 6.4 40.9 52.0 1,128 3 27.4 26.7 10.7 6.0 5.1 31.4 40.5 3,320 Number of reasons for which wife beating is justified4 0 29.5 27.8 10.5 6.7 6.0 31.5 41.3 3,506 1-2 34.6 34.1 15.2 9.0 7.4 40.3 50.3 1,312 3-4 35.2 37.4 19.9 12.5 8.7 44.9 53.1 524 5 40.4 46.8 16.9 14.1 10.8 49.7 56.8 153 Woman’s father beat her mother Yes 38.2 38.0 17.7 11.5 9.4 44.2 54.4 1,919 No 27.5 26.0 9.8 5.9 5.1 29.9 38.7 3,117 Don’t know 31.2 32.7 11.4 7.7 6.1 36.3 48.6 458 Woman afraid of husband/partner Most of the time afraid 64.3 62.9 34.7 27.4 24.9 70.2 76.0 444 Sometimes afraid 56.5 52.7 24.7 17.9 15.4 59.6 72.8 958 Never afraid 22.1 22.1 7.5 3.6 2.7 26.0 35.1 4,092 Total 31.5 30.7 12.7 8.0 6.7 35.4 45.0 5,494 Notes: Husband/partner refers to the current husband/partner for currently married women and the most recent husband/partner for divorced, separated, or widowed women. Figures in parentheses are based on 25-49 unweighted cases. An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. 1 Includes only currently married women. 2 According to the wife’s report. See Table 16.8 for list of behaviours. 3 According to the wife’s report. Includes only currently married women. See Table 15.6.1 for list of decisions. 4 According to the wife’s report. See Table 15.7.1 for list of reasons. 336 • Domestic Violence Table 16.12 Frequency of physical or sexual violence Percentage of ever-married women who have experienced physical or sexual violence by any husband/partner in the past 12 months, according to background characteristics, Zimbabwe 2015 Background characteristic Percentage of women who have experienced physical or sexual violence in the past 12 months from any husband/partner Number of ever-married women Age 15-19 31.5 350 20-24 25.3 890 25-29 24.7 1,082 30-39 18.2 2,032 40-49 10.7 1,140 Religion Traditional (7.1) 31 Roman Catholic 12.5 336 Protestant 17.5 776 Pentecostal 19.4 1,293 Apostolic sect 21.3 2,485 Other Christian 16.6 224 Muslim * 22 None 28.9 323 Other * 5 Residence Urban 19.9 1,956 Rural 20.0 3,538 Province Manicaland 23.6 732 Mashonaland Central 19.3 550 Mashonaland East 20.2 547 Mashonaland West 21.7 691 Matabeleland North 12.2 249 Matabeleland South 15.6 198 Midlands 17.9 708 Masvingo 20.8 675 Harare 20.5 905 Bulawayo 18.0 240 Marital status Married or living together 21.0 4,593 Divorced/separated/widowed 14.4 902 Employment Employed for cash 19.8 2,948 Employed not for cash 25.1 219 Not employed 19.7 2,327 Number of living children 0 21.9 339 1-2 21.6 2,461 3-4 18.0 2,017 5+ 18.8 678 Education No education 19.4 90 Primary 21.7 1,644 Secondary 20.3 3,359 More than secondary 9.9 401 Wealth quintile Lowest 20.3 1,050 Second 20.9 993 Middle 19.6 964 Fourth 24.4 1,313 Highest 14.2 1,175 Woman afraid of husband/partner Most of the time afraid 44.5 444 Sometimes afraid 39.5 958 Never afraid 12.7 4,092 Total 19.9 5,494 Notes: Any husband/partner includes all current, most recent, and former husbands/partners. 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. Domestic Violence • 337 Table 16.13 Experience of spousal violence by duration of marriage Among currently married women age 15-49 who have been married only once, the percentage who first experienced physical or sexual violence committed by their current husband/partner by specific exact years since marriage according to marital duration, Zimbabwe 2015 Percentage who first experienced spousal physical or sexual violence by exact marital duration: Percentage who have not experienced spousal sexual or physical violence Number of currently married women who have been married only once Years since marriage Before marriage 2 years 5 years 10 years <2 1.6 na na na 76.2 415 2-4 0.9 21.6 na na 66.7 495 5-9 0.3 15.7 30.7 na 62.3 969 10+ 0.7 11.5 18.9 25.7 66.1 1,991 Total 0.7 14.9 24.0 29.0 66.3 3,869 na = Not applicable Table 16.14 Injuries to women due to spousal violence Percentage of ever-married women age 15-49 who have experienced specific types of spousal violence by types of injuries resulting from the violence, according to the type of violence and whether they experienced the violence ever and in the 12 months preceding the survey, Zimbabwe 2015 Type of violence Cuts, bruises, or aches Eye injuries, sprains, dislocations, or burns Deep wounds, broken bones, broken teeth, or any other serious injury Any of these injuries Number of women Experienced physical violence1 Ever2 38.2 11.4 8.5 41.4 1,688 In the past 12 months 45.4 13.1 10.9 49.2 837 Experienced sexual violence Ever2 35.8 12.8 10.0 38.5 697 In the past 12 months 35.3 11.6 8.9 37.8 511 Experienced physical or sexual violence1 Ever2 34.1 9.9 7.4 36.9 1,947 In the past 12 months 38.1 10.8 8.6 41.3 1,091 Note: Husband/partner refers to the current husband/partner for currently married women and the most recent husband/partner for divorced, separated or widowed women. 1 Excludes women who reported violence only in response to a direct question on violence during pregnancy 2 Includes in the past 12 months 338 • Domestic Violence Table 16.15 Women’s violence against their spouse according to background characteristics Percentage of ever-married women age 15-49 who have committed physical violence against their current or most recent husband/partner when he was not already beating or physically hurting her, ever and in the past 12 months, according to women’s own experience of spousal violence and background characteristics, Zimbabwe 2015 Percentage who have committed physical violence against their husband/partner Number of ever- married women Background characteristic Ever1 In the past 12 months Woman’s experience of spousal physical violence Ever1 6.6 2.7 1,688 In the past 12 months 6.5 4.9 837 Never 2.2 0.9 3,806 Age 15-19 2.1 1.2 350 20-24 3.1 1.7 890 25-29 3.3 1.7 1,082 30-39 4.1 1.6 2,032 40-49 3.7 0.9 1,140 Religion Traditional (0.0) (0.0) 31 Roman Catholic 3.7 2.5 336 Protestant 4.0 1.7 776 Pentecostal 4.5 1.9 1,293 Apostolic sect 3.3 1.1 2,485 Other Christian 1.9 1.0 224 Muslim * * 22 None 2.2 0.8 323 Other * * 5 Residence Urban 5.2 2.2 1,956 Rural 2.7 1.0 3,538 Province Manicaland 2.6 1.1 732 Mashonaland Central 2.2 1.1 550 Mashonaland East 3.2 1.6 547 Mashonaland West 3.3 0.7 691 Matabeleland North 1.1 0.2 249 Matabeleland South 5.1 3.3 198 Midlands 4.5 1.2 708 Masvingo 2.5 1.9 675 Harare 5.0 2.0 905 Bulawayo 7.3 2.9 240 Marital status Married or living together 3.2 1.5 4,593 Divorced/separated/widowed 5.5 1.4 902 Employment Employed for cash 4.3 1.5 2,948 Employed not for cash 2.0 0.6 219 Not employed 2.7 1.5 2,327 Number of living children 0 3.1 2.0 339 1-2 4.0 1.6 2,461 3-4 3.3 1.4 2,017 5+ 2.8 0.7 678 Wealth quintile Lowest 2.0 0.5 1,050 Second 3.0 1.6 993 Middle 2.4 1.1 964 Fourth 4.9 2.1 1,313 Highest 4.9 1.8 1,175 Total 3.6 1.5 5,494 Notes: Husband/partner refers to the current husband/partner for currently married women and the most recent husband/partner for divorced, separated, or widowed women. Figures in parentheses are based on 25-49 unweighted cases. An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. 1 Includes in the past 12 months Domestic Violence • 339 Table 16.16 Women’s violence against their spouse according to husband’s characteristics Percentage of ever-married women age 15-49 who have committed physical violence against their current or most recent husband/partner when he was not already beating or physically hurting her, ever and in the past 12 months, according their husband’s characteristics, Zimbabwe 2015 Percentage who have committed physical violence against their husband/partner Number of ever- married women Background characteristic Ever1 In the past 12 months Husband’s/partner’s education2 No education 3.0 0.8 71 Primary 1.4 0.6 977 Secondary 3.7 1.8 2,991 More than secondary 3.5 1.5 482 Don’t know/missing 2.9 1.7 73 Husband’s/partner’s alcohol consumption Does not drink alcohol 2.5 1.1 3,299 Drinks alcohol but is never drunk 4.7 1.6 86 Is drunk sometimes 4.3 1.6 1,687 Is drunk very often 8.6 3.4 422 Spousal education difference2 Husband has more education 3.0 1.5 2,152 Wife has more education 3.2 1.1 960 Both have equal education 3.5 1.7 1,395 Neither has any education * * 13 Don’t know/missing 5.3 1.4 975 Spousal age difference2 Wife older 4.8 2.2 148 Wife is same age 3.6 2.9 186 Wife is 1-4 years younger 3.3 1.7 1,621 Wife is 5-9 years younger 3.3 1.2 1,678 Wife is 10 or more years younger 2.4 1.1 958 Missing * * 1 Number of marital control behaviours displayed by husband/partner3 0 1.4 0.4 1,848 1-2 4.2 1.6 2,332 3-4 5.1 2.7 1,036 5 6.4 2.0 278 Number of decisions in which women participate2,4 0 1.0 0.6 144 1-2 3.4 1.8 1,128 3 3.2 1.4 3,320 Number of reasons for which wife-beating is justified5 0 3.7 1.3 3,506 1-2 3.6 1.8 1,312 3-4 2.8 1.5 524 5 2.8 1.5 153 Woman’s father beat her mother Yes 4.8 1.9 1,919 No 2.7 1.3 3,117 Don’t know 3.7 0.8 458 Woman afraid of husband/partner Most of the time afraid 4.4 1.8 444 Sometimes afraid 4.4 2.3 958 Never afraid 3.3 1.2 4,092 Total 3.6 1.5 5,494 Notes: Husband/partner refers to the current husband/partner for currently married women and the most recent husband/partner for divorced, separated, or widowed women. Figures in parentheses are based on 25-49 unweighted cases. An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. 1 Includes in the past 12 months 2 Includes only currently married women 3 According to the wife’s report. See Table 16.8 for list of behaviours. 4 According to the wife’s report. Includes only currently married women. See Table 15.6.1 for list of decisions. 5 According to the wife’s report. See Table 15.7.1 for list of reasons. 340 • Domestic Violence Table 16.17 Help seeking to stop violence Percent distribution of women age 15-49 who have ever experienced physical or sexual violence by their help-seeking behaviour according to type of violence and background characteristics, Zimbabwe 2015 Background characteristic Sought help to stop violence Never sought help but told someone Never sought help, never told anyone Total Number of women who have ever experienced any physical or sexual violence Type of violence experienced Physical only 36.2 20.7 43.1 100.0 1,864 Sexual only 29.8 12.9 57.3 100.0 327 Physical and sexual 50.8 17.2 32.0 100.0 651 Age 15-19 39.7 19.1 41.1 100.0 481 20-24 38.7 17.8 43.5 100.0 472 25-29 37.6 21.1 41.3 100.0 576 30-39 37.5 20.1 42.4 100.0 877 40-49 42.0 15.2 42.8 100.0 436 Religion Traditional * * * 100.0 10 Roman Catholic 34.1 20.1 45.8 100.0 163 Protestant 37.5 19.9 42.6 100.0 419 Pentecostal 40.1 22.0 37.9 100.0 673 Apostolic sect 40.0 17.0 42.9 100.0 1,274 Other Christian 33.2 17.9 48.8 100.0 107 Muslim * * * 100.0 12 None 35.5 18.9 45.6 100.0 180 Other * * * 100.0 3 Residence Urban 35.0 25.8 39.3 100.0 1,075 Rural 41.1 14.9 44.0 100.0 1,768 Province Manicaland 33.4 16.6 49.9 100.0 366 Mashonaland Central 33.7 27.5 38.7 100.0 253 Mashonaland East 39.1 13.6 47.3 100.0 337 Mashonaland West 51.6 5.5 42.9 100.0 377 Matabeleland North 32.1 27.3 40.6 100.0 102 Matabeleland South 35.5 23.4 41.2 100.0 77 Midlands 48.2 9.7 42.2 100.0 374 Masvingo 42.6 15.8 41.6 100.0 292 Harare 30.4 33.9 35.6 100.0 514 Bulawayo 31.4 26.9 41.6 100.0 151 Marital status Never married 36.2 22.7 41.2 100.0 443 Married or living together 38.2 17.7 44.2 100.0 1,925 Divorced/separated/widowed 43.8 20.9 35.3 100.0 474 Number of living children 0 36.7 21.7 41.6 100.0 523 1-2 39.0 18.9 42.0 100.0 1,156 3-4 38.9 19.7 41.4 100.0 856 5+ 41.1 12.7 46.2 100.0 308 Employment Employed for cash 41.0 19.1 39.9 100.0 1,544 Employed not for cash 46.8 8.4 44.8 100.0 108 Not employed 35.2 19.8 45.0 100.0 1,190 Education No education (44.0) (10.0) (46.0) 100.0 40 Primary 41.7 14.9 43.4 100.0 812 Secondary 37.6 20.8 41.6 100.0 1,844 More than secondary 36.6 21.1 42.3 100.0 147 Wealth quintile Lowest 43.5 15.4 41.1 100.0 510 Second 40.1 15.6 44.3 100.0 513 Middle 39.7 13.8 46.4 100.0 500 Fourth 36.6 21.1 42.3 100.0 714 Highest 35.5 26.7 37.8 100.0 606 Total 38.8 19.0 42.2 100.0 2,842 Note: Women can report more than one source from which they sought help. 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. Domestic Violence • 341 Table 16.18 Sources for help to stop the violence Percentage of women age 15-49 who have experienced physical or sexual violence and sought help by sources from which they sought help, according to the type of violence that women reported, Zimbabwe 2015 Type of violence experienced Total Source Physical only Sexual only Physical and sexual Own family 53.1 64.6 51.9 53.8 Husband’s/partner’s family 38.8 17.5 39.8 37.2 Husband/partner 0.4 0.0 2.5 1.0 Boyfriend 0.3 0.0 0.0 0.2 Friend 4.9 13.7 11.9 7.8 Neighbour 3.2 4.3 7.0 4.4 Religious leader 3.4 2.3 4.9 3.8 Doctor/medical personnel 3.6 4.7 4.6 4.0 Police 19.8 6.5 27.2 20.8 Lawyer 0.1 0.0 1.7 0.6 Social work organization 1.1 2.2 2.0 1.5 Other 5.8 9.5 4.3 5.7 Number of women who have experienced violence and sought help 674 97 331 1,102 Note: Women can report more than one source from which they sought help. Adult and Maternal Mortality • 343 ADULT AND MATERNAL MORTALITY 17 Key Findings  Adult mortality: For women and men who have reached age 15, the probability of dying before age 50 is 28 percent and 30 percent, respectively.  Maternal mortality ratio: The maternal mortality ratio is 651 maternal deaths per 100,000 live births for the 7-year period before the survey.  Lifetime risk of maternal death: Current levels of fertility and mortality indicate that 1 in 37 women will die from pregnancy or childbearing. dult and maternal mortality indicators can be used to assess the health status of a population, especially in developing countries such as Zimbabwe. Estimation of mortality rates requires complete and accurate data on adult deaths, including maternal deaths. In the 2015 ZDHS, data were collected from women on the survival of their sisters and brothers to obtain an estimate of adult mortality. The inclusion of questions to determine whether any of the sisters’ deaths were maternity-related permits estimation of maternal mortality, a key indicator of maternal health and well-being. The term maternal mortality, used in this chapter, corresponds to pregnancy-related mortality, which is defined in the latest version of the International Classification of Diseases (ICD-10). The ICD-10 definition of a pregnancy-related death is “the death of a woman while pregnant or within 42 days of termination of pregnancy, irrespective of the cause of death” (WHO 2011). In keeping with this definition, the sibling survival module used in the DHS surveys measures only the timing of death and not the cause of death. The data collected in the ZDHS questionnaire refer to deaths within 2 months following a birth rather than 42 days following a birth. This chapter includes results estimated from sibling history data that were collected in the sibling survival module (commonly referred to as the maternal mortality module) that is part of the Woman’s Questionnaire. In addition to adult mortality rates for 5-year age groups, the chapter includes a summary measure (35q15) that represents the probability of dying between exact ages 15 and 50 – that is, between the 15th and 50th birthdays. 17.1 DATA To obtain a sibling history, each female respondent was initially asked to provide the total number of her mother’s live births. The respondent was then asked to provide a list of all her brothers and sisters born to her mother, starting with the first-born child. The respondent was asked whether each sibling was still alive at the survey date. For living siblings, the current age was recorded; for deceased siblings, the age at death and number of years since death were recorded. Interviewers were instructed that, when a respondent could not provide precise information on the age at death or years since death, approximate quantitative answers were acceptable. For sisters who died at age 12 or above, three questions were used to determine whether the death was maternity-related: “Was [NAME] pregnant when she died?” and, if not, “Did [NAME] die A 344 • Adult and Maternal Mortality during childbirth?” and, if not, “Did [NAME] die within two months after the end of a pregnancy or childbirth?” Estimation of adult and maternal mortality requires reasonably accurate reporting of the number of sisters and brothers the respondent ever had, the number who have died, and for maternal mortality, the number of sisters who have died from maternity related causes. Table 17.1 shows the number of living and dead siblings reported by the respondents and the completeness of data reported on current age, age at death, and years since death. There is no definitive procedure for establishing the completeness or accuracy of retrospective data on sibling survivorship. However, overall, the sibling history data collected in the 2015 ZDHS are complete and do not show any obvious defects that would indicate poor data quality or systematic underreporting:  For 100 percent of deceased siblings, both age at death and years since death were reported.  There were very few siblings for whom survival status was not reported (15 siblings).  Among surviving siblings, current age was reported for all of the 37,509 siblings.  The sex ratio for enumerated siblings (the ratio of brothers to sisters multiplied by 100) is 99.7 (Appendix D, Table D.9). 17.2 DIRECT ESTIMATES OF ADULT MORTALITY Adult mortality rate The number of adult deaths per 1,000 population age 15-49. Adult mortality rates by 5-year age groups are calculated as follows: the number of deaths to respondent’s siblings in each age group are divided by the number of person- years of exposure to the risk of dying in that age group during a specified period prior to the survey. The number of deaths is the number of siblings (brothers or sisters) reported as having died within the specified period. The person-years of exposure in each age group are calculated for both surviving and dead siblings based on their current age (living siblings) or age at death and years since death (dead siblings). Sample: Siblings (both living and dead) who were age 15-49 in the specified 7-year period preceding the survey by sex and 5-year age groups. One way to assess the quality of the data used to estimate maternal mortality is to evaluate the plausibility and stability of overall adult mortality. It is reasoned that if estimated rates of overall adult mortality are implausible, rates based on a subset of deaths (maternal deaths in particular) are unlikely to be free of serious problems. Levels and trends in overall adult mortality have very important implications for health and social programmes in Zimbabwe, especially in the context of the HIV/AIDS epidemic. Adult and Maternal Mortality • 345 The reported ages at death and years since death of the respondents’ brothers and sisters are used to make direct estimates of adult mortality. Because of the differentials in exposure to the risk of dying, age- and sex-specific death rates are presented in this report. Table 17.2 and Figure 17.1 show age- specific mortality rates among women and men age 15-49 for the 7 years before the 2015 ZDHS. To ensure a sufficiently large number of adult deaths to generate a robust estimate, the rates are calculated for the 7-year period before the survey (approximately late-2008 to late-2015). Nevertheless, age-specific mortality rates obtained in this manner are subject to considerable sampling variation. Use of this 7- year period is a compromise between the desire for the most recent data and the need to minimise the sampling error.  Overall, adult mortality is nearly identical among women (7.6 deaths per 1,000 population) and men (7.5 deaths per 1,000 population).  Mortality levels rise rapidly with age. Mortality rates are higher among women than men in the younger age groups (between ages 25 and 39), while the reverse is true in the older age groups (age 40 to 49). 17.3 TRENDS IN ADULT MORTALITY Adult mortality, summarised here by the age-adjusted rate for ages 15-49, decreased since the 2010-11 ZDHS. The rate decreased from 12.7 deaths to 7.6 deaths per 1,000 population among women and from 13.3 deaths to 7.5 deaths per 1,000 population among men. Age-specific assessments of mortality rates indicate a decrease among all age groups. Table 17.3 provides an alternative summary, the probability of dying between exact ages 15 and 50, 35q15. That is, the probability of a 15-year-old woman or man dying before age 50, if experiencing the age- specific death rates in Table 17.2. The 2015 ZDHS data show that women and men have similar probabilities: 282 of 1,000 women age 15, and 300 of 1,000 men age 15 would be expected to die before reaching age 50. Reviewing trends since the 1994 ZDHS, the probability of dying among adults was lowest in the 1994 ZDHS (142 of 1,000 women age 15, and 202 of 1000 men age 15 would be expected to die before reaching age 50) and highest in the 2005-06 ZDHS (443 of 1,000 women age 15, and 494 of 1000 men age 15 would be expected to die before reaching age 50). In the 5 years between the 2010-11 ZDHS and 2015 ZDHS, the probability of dying between exact ages 15 and 50 decreased from 395 to 282 among women and 428 to 300 among men. Confidence intervals for the 35q15 estimates are presented in Appendix Table C.14 and indicate that the change between the 2010-11 ZDHS and 2015 ZDHS are statistically significant. Figure 17.1 Adult mortality rates among women and men age 15-49 0 5 10 15 20 25 30 15-19 20-24 25-29 30-34 35-39 40-44 45-49 Deaths per 1,000 population Age Women Men 346 • Adult and Maternal Mortality 17.4 DIRECT ESTIMATION OF MATERNAL MORTALITY Maternal mortality rate The number of maternal deaths per 1,000 women age 15-49. Maternal mortality rates by 5-year age groups are calculated by dividing the number of maternal deaths to female siblings of respondents in each age group by the total person-years of exposure of the sisters to the risk of dying in that age group during the 7 years prior to the survey. The number of deaths is the number of sisters reported as having died during pregnancy or delivery, or in the 2 months following the delivery in the specified period by their age group at the time of death. The person-years of exposure in each age group are calculated for both surviving and dead sisters based on their reported current age (living sisters) or age at death and years since death (dead sisters). Sample: Sisters (both living and dead) age 15-49 in the specified period, by 5-year age groups. Maternal mortality ratio The number of maternal deaths per 100,000 live births. The maternal mortality ratio is calculated by dividing the age-standardised maternal mortality rate for women age 15-49 for the specified period by the general fertility rate (GFR) for the same time period. Maternal deaths are a subset of all female deaths, and are defined as any deaths that occur during pregnancy or childbirth, or within 2 months after the birth or termination of a pregnancy. Estimates of maternal mortality are therefore based solely on the timing of the death in relationship to the pregnancy. Two methods are generally used to estimate maternal mortality in developing countries: the indirect sisterhood method (Graham et al. 1989) and a direct variant of the sisterhood method (Rutenberg and Sullivan 1991; Stanton et al. 1997). In this report, the direct estimation procedure is applied. Age-specific estimates of maternal mortality from reported survivorship of sisters are shown in Table 17.4 for the 7- year period before the 2015 survey.  The maternal mortality rate among women age 15-49 is 0.9 deaths per 1,000 woman-years of exposure.  By 5-year age groups, the maternal mortality rate is highest among women age 40-44 (1.6) and lowest among women age 15-19 (0.4).  The percentage of female deaths that are maternal deaths varies by age and ranges from 5 percent among women age 45-49 to 31 percent among women age 20-24.  The estimated age-specific mortality rates display a plausible pattern, being generally higher during the peak childbearing ages than in the younger and older age groups. However, the age-specific pattern should be interpreted with caution because of the small number of events: only 99 maternal deaths were reported among women of all ages, which represented 12 percent of female deaths.  The maternal mortality ratio (MMR) is estimated at 651 deaths per 100,000 live births during the 7- year period before the survey. In other words, for every 1,000 live births in Zimbabwe during the 7 years before the 2015 ZDHS, slightly more than six women died during pregnancy, during childbirth, or within 2 months after childbirth.  The lifetime risk of maternal death (0.027) indicates that in the 7-year period before the survey, about 3 percent of women died during pregnancy or childbirth, or within 2 months after childbirth. Adult and Maternal Mortality • 347 Maternal mortality is a difficult indicator to measure because of the large sample sizes required to calculate an accurate estimate. This is evidenced by the fact that the MMR is expressed per 100,000 live births, which demonstrates that it is a relatively rare event. As a result, maternal mortality estimates are subject to large sampling errors. Table 17.4 and Figure 17.2 show the confidence intervals surrounding the MMRs in the 2015, 2010-11, and 2005-06 ZDHS surveys. The decrease in the estimated MMR between the 2010-11 ZDHS (960) and the 2015 ZDHS (651) is statistically significant. Likewise, the increase in the estimated MMR between the 2005-06 ZDHS MMR (612) and the 2010-11 ZDHS (960) is also statistically significant. However, the difference between the MMR estimates from the 2005-06 ZDHS (612) and the 2015 ZDHS (651) is not statistically significant. Therefore, it appears that maternal mortality has returned to levels observed in the 2005-06 ZDHS with an increase in between. LIST OF TABLES For detailed information on adult and maternal mortality, see the following tables:  Table 17.1 Completeness of information on siblings  Table 17.2 Adult mortality rates  Table 17.3 Adult mortality probabilities  Table 17.4 Maternal mortality Figure 17.2 Trends in maternal mortality ratios with confidence intervals 458 778 473 612 960 651 767 1142 829 0 200 400 600 800 1000 1200 1998-2006 2003-2011 2008-2015 Maternal deaths per 100,000 live births (7 years preceding the 2010-11 ZDHS) (7 years preceding the 2015 ZDHS) (7 years preceding the 2005-06 ZDHS) 348 • Adult and Maternal Mortality Table 17.1 Completeness of information on siblings Completeness of data on survival status of sisters and brothers reported by interviewed women, age of living siblings, and age at death (AD) and years since death (YSD) of dead siblings (unweighted), Zimbabwe 2015 Sisters Brothers All siblings Number Percent Number Percent Number Percent All siblings 22,283 100.0 22,151 100.0 44,434 100.0 Living 18,869 84.7 18,640 84.1 37,509 84.4 Dead 3,405 15.3 3,505 15.8 6,910 15.6 Survival status unknown 9 0.0 6 0.0 15 0.0 Living siblings 18,869 100.0 18,640 100.0 37,509 100.0 Age reported 18,869 100.0 18,640 100.0 37,509 100.0 Dead siblings 3,405 100.0 3,505 100.0 6,910 100.0 AD and YSD reported 3,405 100.0 3,505 100.0 6,910 100.0 Missing only AD nc 0.0 nc 0.0 nc 0.0 Missing only YSD nc 0.0 nc 0.0 nc 0.0 Missing AD and YSD nc 0.0 nc 0.0 nc 0.0 nc = no cases Table 17.2 Adult mortality rates Direct estimates of female and male mortality rates for the 7 years preceding the survey, by five-year age groups, Zimbabwe 2015 Age Deaths Exposure years Mortality rates1 FEMALES 15-19 31 16,199 1.88 20-24 51 20,326 2.49 25-29 116 23,096 5.02 30-34 217 20,182 10.75 35-39 184 13,497 13.64 40-44 126 8,248 15.23 45-49 85 4,953 17.10 15-49 808 106,502 7.6a MALES 15-19 26 15,691 1.68 20-24 54 20,388 2.65 25-29 96 22,139 4.33 30-34 172 20,070 8.56 35-39 176 14,458 12.17 40-44 130 8,273 15.72 45-49 116 4,442 26.20 15-49 770 105,461 7.50a 1 Expressed per 1,000 population a Age-adjusted rate Table 17.3 Adult mortality probabilities The probability of dying between the ages of 15 and 50 for women and men for the 7 years preceding the survey, Zimbabwe 2015 Women Men Survey 35q151 35q151 2015 ZDHS 282 300 2010-11 ZDHS 395 428 2005-06 ZDHS 443 494 1999 ZDHS 289 382 1994 ZDHS 142 202 1 The probability of dying between exact ages 15 and 50, expressed per 1,000 persons at age 15 Adult and Maternal Mortality • 349 Table 17.4 Maternal mortality Direct estimates of maternal mortality rates for the 7 years preceding the survey, by five-year age groups, Zimbabwe 2015 Age Percentage of female deaths that are maternal Maternal deaths Exposure years Maternal mortality rate1 15-19 20.2 6 16,199 0.38 20-24 31.0 16 20,326 0.77 25-29 16.2 19 23,096 0.81 30-34 10.7 23 20,182 1.15 35-39 9.7 18 13,497 1.32 40-44 10.6 13 8,248 1.62 45-49 4.5 4 4,953 0.77 15-49 12.2 99 106,502 0.90a General fertility rate GFR2 139a Maternal mortality ratio MMR3 651 CI: (473, 829) Lifetime risk of maternal death4 0.027 2010-11 ZDHS Maternal mortality ratio MMR3 960 CI: (778, 1,142) 2005-06 ZDHS Maternal mortality ratio MMR3 612 CI: (458, 767) CI: Confidence interval 1 Expressed per 1,000 woman-years of exposure 2 Expressed per 1,000 woman age 15-49 3 Expressed per 100,000 live births; calculated as the age-adjusted maternal mortality rate times 100 divided by the age-adjusted general fertility rate 4 Calculated as 1-(1-MMR)TFR where TFR represents the total fertility rate for the 7 years preceding the survey a Age-adjusted rate References • 351 REFERENCES Central Statistical Office (CSO) [Zimbabwe]. 2002. 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World Health Organization (WHO) Multicentre Growth Reference Study Group. 2006. WHO Child Growth Standards: Length/Height-for-Age, Weight-for-Age, Weight-for-Length, Weight-for-Height and Body Mass Index-for-Age: Methods and Development. Geneva: WHO. Zimbabwe Ministry of Health and Child Welfare (MoHCC) and UNAIDS. 2015. Global AIDS Response Progress Report 2015. Harare, Zimbabwe. http://www.unaids.org/sites/default/files/country/documents/ZWE_narrative_report_2015.pdf Zimbabwe National AIDS Council. 2010. Zimbabwe Analysis of HIV Epidemic, Response and Modes of Transmission. Harare, Zimbabwe. https://www.k4health.org/sites/default/files/Zimbabwe%20Analysis%20of%20the%20HIV%20Epidemic %20Response%20and%20Mode%20of%20Transmission.pdf Zimbabwe National Statistics Agency (ZIMSTAT) and ICF International. 2012. Zimbabwe Demographic and Health Survey 2010-11. Calverton, Maryland: ZIMSTAT and ICF International. Zimbabwe National Statistics Agency (ZIMSTAT). 2013. 2012 Zimbabwe Census Population National Report. Harare, Zimbabwe. Appendix A • 353 SAMPLE DESIGN AND IMPLEMENTATION Appendix A A.1 INTRODUCTION The 2015 Zimbabwe Demographic and Health Survey (2015 ZDHS) is the sixth in a series of Demographic and Health Surveys conducted in Zimbabwe. As with prior surveys, the main objective of the 2015 ZDHS is to provide up-to-date information on fertility and child mortality levels; maternal mortality; fertility preferences and contraceptive use; utilization of maternal and child health services; women’s and children’s nutrition status; knowledge, attitudes and behaviours related to HIV/AIDS and other sexually transmitted diseases; and domestic violence. All women age 15-49 and all men age 15-54 who are usual members of the selected households and those who spent the night before the survey in the selected households were eligible to be interviewed and for anaemia and HIV testing. All children age 6-59 months were eligible for anaemia testing, and children age 0-14 for HIV testing. In all households, height and weight measurements were recorded for children age 0-59 months, women age 15-49, and men age 15- 54. The domestic violence module was administered to one selected woman selected in each of surveyed households. The 2015 ZDHS sample is designed to yield representative information for most indicators for the country as a whole, for urban and rural areas, and for each of Zimbabwe’s ten provinces (Manicaland, Mashonaland Central, Mashonaland East, Mashonaland West, Matabeleland North, Matebeleland South, Midlands, Masvingo, Harare, and Bulawayo). A.2 SAMPLING FRAME The sampling frame used for the 2015 ZDHS is the frame of the 2012 Zimbabwe Census Population, provided by the Zimbabwe National Statistics Agency (ZIMSTAT). The census frame is a complete list of all census enumeration areas (EA) created for the 2012 population census. Zimbabwe is divided into ten administrative provinces, with each province divided into districts and each district into smaller administrative units called wards. Table A.1 shows the distribution of population at the time of the 2012 census by the geographic domains of interest for the ZDHS, i.e., province and urban-rural areas. The proportion of population varies by province from 5.3 percent, in Matabeleland South or in Bulawayo, to 16.6 percent in Harare. In Zimbabwe, 33.1 percent of the population live in urban areas and 66.9 percent in rural areas. As presented in Table A.2, the household distribution is similar to the population distribution. In Zimbabwe, 35.9 percent of the households live in urban areas. Table A.3 shows the distribution of EAs and their average size in number of households by province and type of residence. In total, there are 29,365 EAs (excluding the institutional EAs), with 10,475 located in urban areas and 18,890 in rural areas. The average EA size is about 101 households whether in for urban or rural areas. The EA size is an adequate size for the primary sampling unit (PSU) with a sample take of 28 households per EA. The EAs’ small size and the availability of sketch maps and other materials used to delimitate their geographic boundaries made census EAs an ideal unit for use as the frame for the first stage of the ZDHS sample selection. 354 • Appendix A Table A.1 Population distribution of the 2012 census population by province and residence, Zimbabwe Population in frame Percent of total population Percent urban Province Urban Rural Total Manicaland 269,784 1,433,139 1,702,923 13.8 15.8 Mashonaland Central 61,898 1,033,336 1,095,234 8.9 5.7 Mashonaland East 179,210 1,129,572 1,308,783 10.6 13.7 Mashonaland West 337,691 1,004,323 1,342,014 10.9 25.2 Matabeleland North 63,643 621,763 685,406 5.5 9.3 Matabeleland South 82,623 574,569 657,192 5.3 12.6 Midlands 376,605 1,037,403 1,414,007 11.4 26.6 Masvingo 135,134 1,317,084 1,452,218 11.8 9.3 Harare 1,938,469 109,818 2,048,287 16.6 94.6 Bulawayo 649,835 na 649,835 5.3 100.0 Zimbabwe 4,094,891 8,261,007 12,355,898 100.0 33.1 na = Not applicable Source: The 2012 Zimbabwe Census Population, provided by the Zimbabwe National Statistics Agency (ZIMSTAT) Table A.2 Household distribution of the 2012 census population by province and residence, Zimbabwe Households in frame Percent of total households Percent urban Province Urban Rural Total Manicaland 72,809 341,345 414,154 13.9 17.6 Mashonaland Central 15,904 244,161 260,065 8.7 6.1 Mashonaland East 45,763 277,871 323,634 10.9 14.1 Mashonaland West 84,546 230,769 315,315 10.6 26.8 Matabeleland North 18,616 142,999 161,615 5.4 11.5 Matabeleland South 21,187 126,627 147,814 5.0 14.3 Midlands 97,268 221,502 318,770 10.7 30.5 Masvingo 37,364 293,692 331,056 11.1 11.3 Harare 509,799 28,564 538,363 18.1 94.7 Bulawayo 165,332 na 165,332 5.6 100.0 Zimbabwe 1,068,588 1,907,531 2,976,119 100.0 35.9 na = Not applicable Source: The 2012 Zimbabwe Census Population, provided by the Zimbabwe National Statistics Agency (ZIMSTAT) Table A.3 Distribution of enumeration areas (EAs) and their average size in number of households, Zimbabwe Number of EAs Average EA size Province Urban Rural Total Urban Rural Total Manicaland 673 3,340 4,013 108 102 103 Mashonaland Central 162 2,451 2,613 98 100 100 Mashonaland East 463 2,843 3,306 99 98 98 Mashonaland West 839 2,298 3,137 101 100 101 Matabeleland North 165 1,343 1,508 113 106 107 Matabeleland South 218 1,280 1,498 97 99 99 Midlands 981 2,230 3,211 99 99 99 Masvingo 372 2,907 3,279 100 101 101 Harare 4,920 198 5,118 104 144 105 Bulawayo 1,682 0 1,682 98 0 98 Zimbabwe 10,475 18,890 29,365 102 101 101 Source: The 2012 Zimbabwe Census Population, provided by the Zimbabwe National Statistics Agency (ZIMSTAT). Appendix A • 355 A.3 SAMPLE ALLOCATION AND SAMPLING PROCEDURES The sample for the 2015 ZDHS was a stratified sample selected in two stages from the sampling frame. Stratification was achieved by separating each province into urban and rural areas. In total, 19 sampling strata were created because there are no rural areas in Bulawayo. Samples were selected independently in each sampling stratum, by a two-stage selection process. In the first stage, 400 EAs were selected with a probability proportional to size (PPS) selection procedure according to the sample allocation shown in Table A.4. The EA size is the number of residential households in the EA based on the 2012 Zimbabwe Census Population. Implicit stratification with proportional allocation was achieved at each of the lower administrative unit levels by sorting the EA frame before the sample selection according to a certain geographical order within each of the explicit stratum, and by using a PPS selection procedure. After the selection of EAs and before the main survey, a household listing operation was implemented in all selected EAs. The household listing operation consists of visiting each of the 400 selected EAs; drawing a location map and a detailed sketch map; and recording on the household listing forms all the occupied residential households found in the EA with the address and the name of the head of the household. The resulting list of households served as a sampling frame for the selection of households in the second stage. Some selected EAs were large in size. To limit the work load during household listing, selected EAs with more than 200 households (estimated by the listing team in the field) were segmented by the listing team in the field before the household listing exercise. Only one segment was selected for the survey with probability proportional to the segment size. The household listing was then conducted only in the selected segment (see detailed instructions for segmentation in the Manual for Household Listing). Thus, a 2015 ZDHS cluster is either an EA or a segment of an EA. In the second stage of selection, a fixed number of 28 households was selected in every cluster, by an equal probability systematic sampling based on the newly updated household listing. The allocation of the sampled households is shown in Table A.4. A total of 11,200 households were sampled, with 4,648 households in urban areas and 6,552 households in rural areas. A spreadsheet detailing the selected household numbers for each cluster was prepared. The survey interviewers then interviewed only the pre- selected households. In an effort to prevent bias, no replacements and no changes of the pre-selected households were allowed in the implementation stages. Table A.4 Sample allocation of clusters and households by province and residence, Zimbabwe 2015 Allocation of clusters Allocation of households Province Urban Rural Total Urban Rural Total Manicaland 14 30 44 392 840 1,232 Mashonaland Central 9 31 40 252 868 1,120 Mashonaland East 12 29 41 336 812 1,148 Mashonaland West 15 26 41 420 728 1,148 Matabeleland North 10 26 36 280 728 1,008 Matabeleland South 11 25 36 308 700 1,008 Midlands 16 25 41 448 700 1,148 Masvingo 12 30 42 336 840 1,176 Harare 32 12 44 896 336 1,232 Bulawayo 35 0 35 980 0 980 Zimbabwe 166 234 400 4,648 6,552 11,200 Table A.5 shows the sample allocation of expected number of interviews with women and men. The sample allocation of women featured a power allocation with small adjustment because a proportional allocation did not meet the minimum number of 800 women interviews per survey domain required for a DHS survey. The expected numbers of completed interviews for women and men in Table A.5 are based on the households’ allocation in Table A.4 after considering the households, the non-response rates for women and the men, and the average number of women 15-49 and men 15-54 per household. 356 • Appendix A Table A.5 Sample allocation of expected completed interviews with men and women by province and residence, Zimbabwe 2015 Women 15-49 Men 15-54 Province Urban Rural Total Urban Rural Total Manicaland 362 677 1,039 268 583 851 Mashonaland Central 233 701 934 172 603 775 Mashonaland East 311 655 966 229 564 793 Mashonaland West 388 587 975 287 506 793 Matabeleland North 258 587 845 191 506 697 Matabeleland South 284 565 849 210 487 697 Midlands 414 565 979 306 487 793 Masvingo 311 677 988 229 583 812 Harare 829 271 1,100 612 233 845 Bulawayo 907 0 907 670 0 670 Zimbabwe 4,297 5,285 9,582 3,174 4,552 7,726 The above sample allocation was calculated on the facts obtained from the 2010-11 ZDHS. There were 1.15 and 0.94 women age 15-49, and 0.98 and 0.85 men age 15-54 per household in urban and rural areas, respectively. The household response rates were 89.4 percent and 90.5 percent in urban and rural areas, respectively. The women response rates were 90.3 percent and 95.2 percent in urban and rural areas, respectively; and the men individual response rates were 78.1 percent and 90.3 percent in urban and rural areas, respectively. A.4 HIV TESTING AND EXPECTED PRECISION As HIV prevalence is a key indicator for the 2015 ZDHS, Tables A.6 and A.7 show the number of expected HIV tests for women 15-49 and men 15-54 and the corresponding precision of the HIV prevalence estimates by province. These estimates were calculated based on response rates obtained in the 2010-11 ZDHS, with 85.6 percent of the interviewed women and 80.8 percent of the interviewed men tested for HIV. In Tables A.6 and A.7, the HIV prevalence and the design effect (deft) are obtained from the 2010-11 ZDHS. Table A.8 shows the expected number of children 0-14 years eligible for the HIV testing. Table A.6 Number of expected HIV tests for women 15-49 and the expected precision by province, Zimbabwe 2015 Women 15-49 Relative standard error and the 95% confidence limits Province Number of tests HIV prevalence Deft RSE Lower limit Upper limit Manicaland 890 0.179 1.202 0.086 0.148 0.210 Mashonaland Central 799 0.151 1.482 0.124 0.113 0.189 Mashonaland East 827 0.178 1.220 0.091 0.146 0.210 Mashonaland West 834 0.178 1.375 0.102 0.142 0.214 Matabeleland North 723 0.202 1.663 0.123 0.152 0.252 Matabeleland South 727 0.227 0.980 0.067 0.197 0.257 Midlands 838 0.174 1.427 0.107 0.137 0.211 Masvingo 846 0.163 1.385 0.108 0.128 0.198 Harare 942 0.167 1.361 0.099 0.134 0.200 Bulawayo 776 0.211 1.274 0.088 0.174 0.248 Zimbabwe 8,202 0.177 1.390 0.033 0.165 0.189 Appendix A • 357 Table A.7 Number of expected HIV tests for men 15-54 and the expected precision by province, Zimbabwe 2015 Men 15-54 Relative standard error and the 95% confidence limits Province Number of tests HIV prevalence Deft RSE Lower limit Upper limit Manicaland 688 0.100 1.232 0.141 0.072 0.128 Mashonaland Central 626 0.124 1.278 0.136 0.090 0.158 Mashonaland East 641 0.129 1.055 0.108 0.101 0.157 Mashonaland West 641 0.120 1.152 0.123 0.090 0.150 Matabeleland North 563 0.167 1.237 0.116 0.128 0.206 Matabeleland South 563 0.191 1.546 0.134 0.140 0.242 Midlands 640 0.138 1.338 0.132 0.102 0.174 Masvingo 656 0.129 1.154 0.117 0.099 0.159 Harare 682 0.097 1.293 0.151 0.068 0.126 Bulawayo 541 0.170 1.394 0.132 0.125 0.215 Zimbabwe 6,241 0.127 1.283 0.043 0.116 0.138 Table A.8 Number of children 0-14 eligible for the HIV testing by province and residence, Zimbabwe 2015 Children 0-14 Province Urban Rural Total Manicaland 447 1,537 1,984 Mashonaland Central 287 1,589 1,876 Mashonaland East 383 1,486 1,869 Mashonaland West 479 1,332 1,811 Matabeleland North 319 1,332 1,651 Matabeleland South 351 1,282 1,633 Midlands 512 1,282 1,794 Masvingo 383 1,537 1,920 Harare 1,023 615 1,638 Bulawayo 1,119 0 1,119 Zimbabwe 5,303 11,992 17,295 A.5 SAMPLE IMPLEMENTATION An examination of the 2015 ZDHS response rates indicates that the survey was successfully implemented. Tables A.9 and A.10 present the interview response rates in the 2015 ZDHS for the women and men, by urban and rural area and province. Tables A.11 and A.12 show HIV testing coverage for women and men by social and demographic characteristics, and Tables A.13 and A.14 show HIV testing coverage by sexual behaviour for women and men. A.6 SAMPLING PROBABILITIES AND SAMPLE WEIGHTS Due to the non-proportional allocation of the sample to the different provinces and the possible differences in response rates, sampling weights are required for any analysis using the 2015 ZDHS data to ensure the actual representation of the survey results at the national and other domain levels. Because the 2015 ZDHS sample is a two-stage stratified cluster sample, sampling weights are calculated based on sampling probabilities separately for each sampling stage and for each cluster. The following notations are used: P1hi: first-stage sampling probability of the ith EA in stratum h from the sampling frame P2hi: second-stage sampling probability within the ith EA (household selection) Let hn be the number of EAs selected in stratum h, Mhi the measure of size (number of residential households) according to the sampling frame in the ith EA, and M hi the total measure of size (total number of residential households) in the stratum h. The probability of selecting the ith EA in stratum h from the sampling frame was calculated as: 358 • Appendix A M M nP hi hih hi  1 Let his be the proportion of households in the selected segment compared to the total number of households in EA i in stratum h if the EA is segmented, otherwise 1his . Let hiL be the number of households listed in the household listing operation in cluster i in stratum h, let him be the number of households selected in the cluster. The second stage’s selection probability for each household in the cluster was calculated as: hi hi hi hi sL m P 2 The overall selection probability of each household in cluster i of stratum h is therefore the production of the selection probabilities: hihihi PPP 21  Therefore the design weight for each household in cluster i of stratum h is the inverse of its overall selection probability: hihi PW /1 A spreadsheet with all the sampling parameters and selection probabilities was prepared to facilitate the calculation of the design weights. Design weights were adjusted for household non-response and for individual non-response to obtain the sampling weights for the women’s and men’s surveys. The differences of the household sampling weights and the individual sampling weights were introduced by individual non-response. The final sampling weights were normalized to give the total number of un- weighted cases equal to the total number of weighted cases at national level, for both household weights and individual weights, respectively. The normalized weights are relative weights which are valid for estimating means, proportions, and ratios, but are not valid for estimating population totals and pooled data. The sampling weights for HIV testing are calculated in a similar way; however, the normalization of the individual sampling weights is different compared with the individual sampling weights. The HIV testing weights are normalized for male and female together at national level to assure that the HIV prevalence calculated for male and female together are valid. Sampling errors have been calculated for selected indicators for the national sample; for the urban and rural areas, separately; and for each of the ten provinces. A pp en di x A • 3 59 Ta bl e A .9 S am pl e im pl em en ta tio n: W om en P er ce nt d is tri bu tio n of h ou se ho ld s an d el ig ib le w om en b y re su lts o f t he h ou se ho ld a nd in di vi du al in te rv ie w s, a nd h ou se ho ld , e lig ib le w om en a nd o ve ra ll w om en r es po ns e ra te s, a cc or di ng to u rb an -r ur al r es id en ce a nd r eg io n (u nw ei gh te d) , Z im ba bw e 20 15 R es id en ce P ro vi nc e To ta l R es ul t U rb an R ur al M an ic al an d M as ho na la nd C en tra l M as ho na la nd E as t M as ho na la nd W es t M at ab el el an d N or th M at ab el el an d S ou th M id la nd s M as vi ng o H ar ar e B ul aw ay o S el ec te d ho us eh ol ds C om pl et ed (C ) 93 .4 94 .5 93 .7 93 .8 94 .4 95 .2 92 .7 98 .3 95 .6 91 .1 92 .0 94 .6 94 .1 H ou se ho ld p re se nt b ut n o co m pe te nt re sp on de nt a t ho m e (H P ) 0. 8 0. 4 0. 9 0. 4 0. 7 0. 4 0. 6 0. 0 0. 3 0. 7 1. 0 1. 0 0. 6 P os tp on ed (P ) 0. 0 0. 0 0. 0 0. 0 0. 0 0. 1 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 R ef us ed (R ) 0. 8 0. 1 0. 6 0. 0 0. 3 0. 1 0. 4 0. 1 0. 1 0. 3 1. 1 0. 7 0. 4 D w el lin g no t f ou nd (D N F) 0. 1 0. 1 0. 0 0. 0 0. 2 0. 3 0. 2 0. 0 0. 3 0. 0 0. 1 0. 0 0. 1 H ou se ho ld a bs en t ( H A ) 1. 6 2. 7 2. 9 2. 5 1. 9 2. 4 3. 3 1. 3 1. 6 3. 7 1. 4 1. 3 2. 2 D w el lin g va ca nt /a dd re ss n ot a dw el lin g (D V ) 3. 0 1. 9 1. 6 2. 9 2. 4 1. 2 2. 5 0. 3 2. 0 3. 9 4. 1 2. 1 2. 3 D w el lin g de st ro ye d (D D ) 0. 0 0. 1 0. 1 0. 0 0. 0 0. 3 0. 1 0. 0 0. 1 0. 0 0. 0 0. 0 0. 1 O th er (O ) 0. 2 0. 1 0. 2 0. 4 0. 1 0. 0 0. 2 0. 0 0. 1 0. 3 0. 3 0. 2 0. 2 To ta l 10 0. 0 10 0. 0 10 0. 0 10 0. 0 10 0. 0 10 0. 0 10 0. 0 10 0. 0 10 0. 0 10 0. 0 10 0. 0 10 0. 0 10 0. 0 N um be r o f s am pl ed ho us eh ol ds 4, 64 6 6, 55 0 1, 23 2 1, 11 9 1, 14 8 1, 14 8 1, 00 6 1, 00 8 1, 14 7 1, 17 5 1, 23 3 98 0 11 ,1 96 H ou se ho ld re sp on se ra te (H R R )1 98 .1 99 .3 98 .4 99 .5 98 .8 99 .1 98 .7 99 .9 99 .4 98 .9 97 .7 98 .2 98 .8 E lig ib le w om en C om pl et ed (E W C ) 95 .1 97 .1 96 .3 96 .4 95 .9 96 .8 96 .0 97 .4 96 .4 97 .1 94 .9 94 .9 96 .2 N ot a t h om e (E W N H ) 2. 6 1. 6 1. 7 2. 3 2. 5 1. 8 2. 0 1. 2 2. 2 1. 5 2. 7 2. 6 2. 1 P os tp on ed (E W P ) 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 2 0. 0 0. 0 R ef us ed (E W R ) 1. 4 0. 2 0. 9 0. 5 1. 1 0. 4 0. 6 0. 2 0. 2 0. 6 1. 3 1. 4 0. 7 P ar tly c om pl et ed (E W P C ) 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 1 0. 0 0. 0 In ca pa ci ta te d (E W I) 0. 5 1. 1 0. 9 0. 8 0. 5 0. 9 1. 0 1. 2 0. 9 0. 7 0. 3 0. 8 0. 8 O th er (E W O ) 0. 4 0. 1 0. 2 0. 0 0. 0 0. 1 0. 3 0. 0 0. 4 0. 0 0. 6 0. 3 0. 2 To ta l 10 0. 0 10 0. 0 10 0. 0 10 0. 0 10 0. 0 10 0. 0 10 0. 0 10 0. 0 10 0. 0 10 0. 0 10 0. 0 10 0. 0 10 0. 0 N um be r o f w om en 4, 75 3 5, 59 8 1, 05 8 1, 03 0 94 9 1, 08 9 88 4 85 1 1, 10 2 1, 07 7 1, 30 2 1, 00 9 10 ,3 51 E lig ib le w om en re sp on se ra te (E W R R )2 95 .1 97 .1 96 .3 96 .4 95 .9 96 .8 96 .0 97 .4 96 .4 97 .1 94 .9 94 .9 96 .2 O ve ra ll w om en re sp on se ra te (O R R )3 93 .4 96 .4 94 .8 96 .0 94 .8 95 .9 94 .8 97 .3 95 .8 96 .0 92 .6 93 .2 95 .1 1 U si ng th e nu m be r o f h ou se ho ld s fa lli ng in to s pe ci fic re sp on se c at eg or ie s, th e ho us eh ol d re sp on se ra te (H R R ) i s ca lc ul at ed a s: 10 0 * C — — — — — — — — — — C + H P + P + R + D N F 2 Th e el ig ib le w om en re sp on se ra te (E W R R ) i s eq ui va le nt to th e pe rc en ta ge o f i nt er vi ew s co m pl et ed (E W C ) 3 Th e ov er al l w om en re sp on se ra te (O W R R ) i s ca lc ul at ed a s: O W R R = H R R * E W R R /1 00 36 0 • A pp en di x A Ta bl e A .1 0 S am pl e im pl em en ta tio n: M en P er ce nt d is tri bu tio n of h ou se ho ld s an d el ig ib le m en b y re su lts o f t he h ou se ho ld a nd in di vi du al in te rv ie w s, a nd h ou se ho ld , e lig ib le m en a nd o ve ra ll m en re sp on se ra te s, a cc or di ng to u rb an -r ur al re si de nc e an d re gi on (u nw ei gh te d) , Zi m ba bw e 20 15 R es id en ce P ro vi nc e To ta l R es ul t U rb an R ur al M an ic al an d M as ho na la nd C en tra l M as ho na la nd E as t M as ho na la nd W es t M at ab el el an d N or th M at ab el el an d S ou th M id la nd s M as vi ng o H ar ar e B ul aw ay o S el ec te d ho us eh ol ds C om pl et ed (C ) 93 .4 94 .5 93 .7 93 .8 94 .4 95 .2 92 .7 98 .3 95 .6 91 .1 92 .0 94 .6 94 .1 H ou se ho ld p re se nt b ut n o co m pe te nt re sp on de nt a t ho m e (H P ) 0. 8 0. 4 0. 9 0. 4 0. 7 0. 4 0. 6 0. 0 0. 3 0. 7 1. 0 1. 0 0. 6 P os tp on ed (P ) 0. 0 0. 0 0. 0 0. 0 0. 0 0. 1 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 R ef us ed (R ) 0. 8 0. 1 0. 6 0. 0 0. 3 0. 1 0. 4 0. 1 0. 1 0. 3 1. 1 0. 7 0. 4 D w el lin g no t f ou nd (D N F) 0. 1 0. 1 0. 0 0. 0 0. 2 0. 3 0. 2 0. 0 0. 3 0. 0 0. 1 0. 0 0. 1 H ou se ho ld a bs en t ( H A ) 1. 6 2. 7 2. 9 2. 5 1. 9 2. 4 3. 3 1. 3 1. 6 3. 7 1. 4 1. 3 2. 2 D w el lin g va ca nt /a dd re ss n ot a dw el lin g (D V ) 3. 0 1. 9 1. 6 2. 9 2. 4 1. 2 2. 5 0. 3 2. 0 3. 9 4. 1 2. 1 2. 3 D w el lin g de st ro ye d (D D ) 0. 0 0. 1 0. 1 0. 0 0. 0 0. 3 0. 1 0. 0 0. 1 0. 0 0. 0 0. 0 0. 1 O th er (O ) 0. 2 0. 1 0. 2 0. 4 0. 1 0. 0 0. 2 0. 0 0. 1 0. 3 0. 3 0. 2 0. 2 To ta l 10 0. 0 10 0. 0 10 0. 0 10 0. 0 10 0. 0 10 0. 0 10 0. 0 10 0. 0 10 0. 0 10 0. 0 10 0. 0 10 0. 0 10 0. 0 N um be r o f s am pl ed ho us eh ol ds 4, 64 6 6, 55 0 1, 23 2 1, 11 9 1, 14 8 1, 14 8 1, 00 6 1, 00 8 1, 14 7 1, 17 5 1, 23 3 98 0 11 ,1 96 H ou se ho ld re sp on se ra te (H R R )1 98 .1 99 .3 98 .4 99 .5 98 .8 99 .1 98 .7 99 .9 99 .4 98 .9 97 .7 98 .2 98 .8 E lig ib le m en C om pl et ed (E M C ) 88 .2 94 .7 92 .3 94 .6 92 .6 92 .8 94 .8 90 .8 91 .8 94 .1 86 .4 90 .4 91 .9 N ot a t h om e (E M N H ) 8. 7 3. 5 5. 2 4. 8 5. 7 6. 0 3. 2 5. 2 5. 3 3. 6 9. 9 7. 1 5. 7 P os tp on ed (E M P ) 0. 1 0. 0 0. 2 0. 0 0. 1 0. 1 0. 0 0. 0 0. 3 0. 0 0. 0 0. 0 0. 1 R ef us ed (E M R ) 2. 1 0. 4 1. 0 0. 1 0. 6 0. 5 0. 9 1. 8 1. 2 0. 7 3. 3 1. 3 1. 2 In ca pa ci ta te d (E M I) 0. 5 1. 2 1. 3 0. 5 0. 9 0. 6 1. 0 2. 2 0. 9 1. 2 0. 3 0. 6 0. 9 O th er (E M O ) 0. 3 0. 1 0. 0 0. 0 0. 0 0. 0 0. 1 0. 0 0. 4 0. 4 0. 2 0. 6 0. 2 To ta l 10 0. 0 10 0. 0 10 0. 0 10 0. 0 10 0. 0 10 0. 0 10 0. 0 10 0. 0 10 0. 0 10 0. 0 10 0. 0 10 0. 0 10 0. 0 N um be r o f m en 3, 91 7 5, 21 5 97 0 1, 04 3 85 3 1, 00 3 78 6 73 1 96 3 83 2 1, 15 1 80 0 9, 13 2 E lig ib le m en re sp on se ra te (E M R R )2 88 .2 94 .7 92 .3 94 .6 92 .6 92 .8 94 .8 90 .8 91 .8 94 .1 86 .4 90 .4 91 .9 O ve ra ll m en re sp on se ra te (O R R )3 86 .6 94 .1 90 .8 94 .2 91 .5 92 .0 93 .6 90 .7 91 .2 93 .1 84 .4 88 .7 90 .9 1 U si ng th e nu m be r o f h ou se ho ld s fa lli ng in to s pe ci fic re sp on se c at eg or ie s, th e ho us eh ol d re sp on se ra te (H R R ) i s ca lc ul at ed a s: 10 0 * C — — — — — — — — — — C + H P + P + R + D N F 2 Th e el ig ib le m en re sp on se ra te (E M R R ) i s eq ui va le nt to th e pe rc en ta ge o f i nt er vi ew s co m pl et ed (E M C ) 3 Th e ov er al l m en re sp on se ra te (O M R R ) i s ca lc ul at ed a s: O M R R = H R R * E M R R /1 00 Appendix A • 361 Table A.11 Coverage of HIV testing by social and demographic characteristics: Women Percent distribution of interviewed women age 15-49 by HIV testing status, according to social and demographic characteristics (unweighted), Zimbabwe 2015 Testing status Total Number of women Characteristic DBS Tested1 Refused to provide blood Absent at the time of blood collection Other/missing2 Marital status Never married 91.4 4.8 1.6 2.2 100.0 2,666 Ever had sexual intercourse 92.7 4.2 1.1 2.0 100.0 841 Never had sexual intercourse 90.8 5.2 1.8 2.2 100.0 1,825 Married/living together 90.7 6.7 1.2 1.5 100.0 6,015 Divorced or separated 91.7 5.1 1.2 2.0 100.0 844 Widowed 90.0 5.1 2.8 2.1 100.0 430 Type of union In polygynous union 79.0 19.0 0.7 1.4 100.0 580 In non-polygynous union 92.0 5.3 1.2 1.5 100.0 5,359 Not currently in union 91.3 4.9 1.6 2.1 100.0 3,940 Don’t know/missing 90.8 6.6 1.3 1.3 100.0 76 Ever had sexual intercourse Yes 91.0 6.2 1.3 1.6 100.0 8,130 No 90.8 5.2 1.8 2.2 100.0 1,825 Currently pregnant Pregnant 90.3 7.0 1.5 1.1 100.0 611 Not pregnant or not sure 91.0 5.9 1.3 1.8 100.0 9,344 Times slept away from home in past 12 months None 92.0 5.0 1.4 1.6 100.0 4,262 1-2 90.4 6.5 1.5 1.6 100.0 2,903 3-4 90.0 7.0 1.1 1.9 100.0 1,042 5+ 89.7 7.0 1.3 2.1 100.0 1,748 Time away in past 12 months Away for more than 1 month 91.1 5.8 1.0 2.1 100.0 1,545 Away for less than 1 month 89.8 7.1 1.5 1.7 100.0 4,148 Not away 92.0 5.0 1.4 1.6 100.0 4,262 Religion Traditional 96.7 3.3 0.0 0.0 100.0 60 Roman Catholic 89.6 6.4 1.8 2.2 100.0 670 Protestant 90.0 6.4 1.4 2.3 100.0 1,618 Pentecostal 91.6 4.6 2.0 1.9 100.0 2,679 Apostolic sect 90.3 7.3 1.0 1.4 100.0 3,829 Other Christian 95.2 3.1 0.5 1.2 100.0 589 Muslim 80.0 16.7 3.3 0.0 100.0 30 None 92.4 4.5 1.3 1.9 100.0 471 Other 88.9 0.0 11.1 0.0 100.0 9 Total 15-49 90.9 6.0 1.4 1.7 100.0 9,955 1 Includes all dried blood spot (DBS) specimens tested at the lab and for which there is a result, i.e. positive, negative, or indeterminate. Indeterminate means that the sample went through the entire algorithm, but the final result was inconclusive. 2 Includes: 1) other results of blood collection (e.g. technical problem in the field), 2) lost specimens, 3) non corresponding bar codes, and 4) other lab results such as blood not tested for technical reason, not enough blood to complete the algorithm, etc. 362 • Appendix A Table A.12 Coverage of HIV testing by social and demographic characteristics: Men Percent distribution of interviewed men 15-54 by HIV testing status, according to social and demographic characteristics (unweighted), Zimbabwe 2015 Testing status Total Number of men Characteristic DBS Tested1 Refused to provide blood Absent at the time of blood collection Other/missing2 Marital status Never married 90.0 6.6 2.1 1.3 100.0 3,619 Ever had sexual intercourse 90.2 6.4 2.1 1.4 100.0 1,777 Never had sexual intercourse 89.8 6.9 2.1 1.2 100.0 1,842 Married/living together 87.1 8.3 3.0 1.6 100.0 4,337 Divorced or separated 88.8 5.1 3.2 2.9 100.0 374 Widowed 84.8 4.5 10.6 0.0 100.0 66 Type of union In polygynous union 74.4 21.9 2.7 0.9 100.0 219 In non-polygynous union 87.7 7.6 3.0 1.6 100.0 4,118 Not currently in union 89.8 6.5 2.3 1.4 100.0 4,059 Ever had sexual intercourse Yes 88.0 7.6 2.9 1.6 100.0 6,554 No 89.8 6.9 2.1 1.2 100.0 1,842 Male circumcision Circumcised 90.8 4.9 2.9 1.4 100.0 1,327 Not circumcised 88.0 7.9 2.6 1.5 100.0 7,057 Don’t know/missing 66.7 25.0 8.3 0.0 100.0 12 Times slept away from home in past 12 months None 89.6 6.7 2.3 1.4 100.0 3,523 1-2 89.2 6.7 2.4 1.7 100.0 1,919 3-4 89.7 6.7 2.4 1.2 100.0 936 5+ 84.9 9.7 3.8 1.6 100.0 2,018 Time away in past 12 months Away for more than 1 month 86.2 8.8 3.1 1.8 100.0 1,246 Away for less than 1 month 88.0 7.7 2.9 1.5 100.0 3,627 Not away 89.6 6.7 2.3 1.4 100.0 3,523 Religion Traditional 90.0 5.9 2.3 1.8 100.0 220 Roman Catholic 87.1 7.7 3.4 1.7 100.0 698 Protestant 88.4 7.7 2.8 1.2 100.0 1,272 Pentecostal 87.9 6.4 4.1 1.5 100.0 1,551 Apostolic sect 86.9 9.8 2.1 1.3 100.0 2,507 Other Christian 90.6 5.0 2.3 2.1 100.0 606 Muslim 88.7 7.5 1.9 1.9 100.0 53 None 90.9 5.3 2.0 1.7 100.0 1,479 Other 80.0 10.0 10.0 0.0 100.0 10 Total 15-54 88.4 7.4 2.7 1.5 100.0 8,396 1 Includes all dried blood spot (DBS) specimens tested at the lab and for which there is a result, i.e. positive, negative, or indeterminate. Indeterminate means that the sample went through the entire algorithm, but the final result was inconclusive. 2 Includes: 1) other results of blood collection (e.g. technical problem in the field), 2) lost specimens, 3) non corresponding bar codes, and 4) other lab results such as blood not tested for technical reason, not enough blood to complete the algorithm, etc. Appendix A • 363 Table A.13 Coverage of HIV testing by sexual behaviour characteristics: Women Percent distribution of interviewed women age 15-49 who ever had sexual intercourse by HIV test status, according to sexual behaviour characteristics (unweighted), Zimbabwe 2015 Testing status Total Number of women Sexual behaviour characteristic DBS Tested1 Refused to provide blood Absent at the time of blood collection Other/ missing2 Age at first sexual intercourse <16 92.5 5.5 0.9 1.1 100.0 1,318 16-17 90.8 6.5 1.0 1.7 100.0 2,312 18-19 92.4 5.1 1.2 1.3 100.0 2,207 20+ 89.0 7.2 1.7 2.1 100.0 2,238 Missing 85.5 7.3 3.6 3.6 100.0 55 Multiple sexual partners and partner concurrency in past 12 months 0 91.0 4.9 1.6 2.5 100.0 893 1 91.0 6.2 1.2 1.5 100.0 7,055 2+ 93.1 4.6 0.8 1.5 100.0 131 Had concurrent partners3 85.7 8.6 2.9 2.9 100.0 35 None of the partners were concurrent 95.8 3.1 0.0 1.0 100.0 96 Missing 76.5 23.5 0.0 0.0 100.0 51 Condom use at last sexual intercourse in past 12 months Used condom 91.5 5.2 1.2 2.1 100.0 1,447 Did not use condom 91.0 6.4 1.2 1.4 100.0 5,739 No sexual intercourse in last 12 months 90.3 5.9 1.5 2.3 100.0 944 Number of lifetime partners 1 90.4 7.1 1.1 1.4 100.0 4,799 2 91.9 4.8 1.2 2.1 100.0 1,868 3-4 92.6 3.7 2.1 1.6 100.0 1,108 5-9 92.6 5.3 1.2 0.8 100.0 244 10+ 88.0 8.0 0.0 4.0 100.0 75 Missing 69.4 25.0 2.8 2.8 100.0 36 Prior HIV testing Ever tested 92.8 4.5 1.2 1.6 100.0 7,394 Received results 92.7 4.5 1.2 1.6 100.0 7,330 Did not receive results 95.3 4.7 0.0 0.0 100.0 64 Never tested 73.1 23.1 2.0 1.8 100.0 736 Total 15-49 91.0 6.2 1.3 1.6 100.0 8,130 1 Includes all dried blood spot (DBS) specimens tested at the lab and for which there is a result, i.e. positive, negative, or indeterminate. Indeterminate means that the sample went through the entire algorithm, but the final result was inconclusive. 2 Includes: 1) other results of blood collection (e.g. technical problem in the field), 2) lost specimens, 3) non corresponding bar codes, and 4) other lab results such as blood not tested for technical reason, not enough blood to complete the algorithm, etc. 3 A respondent is considered to have had concurrent partners if he or she had overlapping sexual partnerships with two or more people during the 12 months before the survey 364 • Appendix A Table A.14 Coverage of HIV testing by sexual behaviour characteristics: Men Percent distribution of interviewed men age 15-54 who ever had sexual intercourse by HIV test status, according to sexual behaviour characteristics (unweighted), Zimbabwe 2015 Testing status Total Number of men Sexual behaviour characteristic DBS Tested1 Refused to provide blood Absent at the time of blood collection Other/ missing Age at first sexual intercourse <16 90.3 7.1 1.5 1.1 100.0 849 16-17 89.9 6.3 2.4 1.5 100.0 1,228 18-19 88.1 7.2 3.2 1.5 100.0 1,525 20+ 86.6 8.3 3.3 1.8 100.0 2,787 Missing 83.6 11.5 3.6 1.2 100.0 165 Multiple sexual partners and partner concurrency in past 12 months 0 90.1 6.3 1.9 1.6 100.0 568 1 88.1 7.3 3.0 1.5 100.0 4,766 2+ 86.5 9.1 2.6 1.7 100.0 1,218 Had concurrent partners2 75.9 20.3 2.5 1.2 100.0 241 None of the partners were concurrent 89.2 6.3 2.7 1.8 100.0 977 Missing 50.0 50.0 0.0 0.0 100.0 2 Condom use at last sexual intercourse in past 12 months Used condom 89.8 5.9 2.7 1.6 100.0 1,880 Did not use condom 86.9 8.5 3.1 1.5 100.0 4,104 No sexual intercourse in last 12 months 90.0 6.5 1.9 1.6 100.0 570 Paid for sexual intercourse in past 12 months Yes 89.5 5.1 3.4 2.0 100.0 295 Used condom 89.3 5.0 3.4 2.3 100.0 261 Did not use condom 91.2 5.9 2.9 0.0 100.0 34 No (No paid sexual intercourse/no sexual intercourse in last 12 months) 87.9 7.7 2.8 1.5 100.0 6,259 Number of lifetime partners 1 86.2 9.5 2.3 2.0 100.0 1,177 2 88.4 7.8 2.5 1.3 100.0 1,020 3-4 89.3 6.9 2.7 1.1 100.0 1,743 5-9 89.0 6.1 3.2 1.6 100.0 1,406 10+ 87.3 7.4 3.4 1.9 100.0 1,042 Missing 78.9 13.3 5.4 2.4 100.0 166 Prior HIV testing Ever tested 89.2 6.2 3.0 1.6 100.0 4,825 Received results 89.0 6.3 3.0 1.6 100.0 4,724 Did not receive results 96.0 1.0 2.0 1.0 100.0 101 Never tested 84.7 11.5 2.4 1.4 100.0 1,729 Total 15-54 88.0 7.6 2.9 1.6 100.0 6,554 1 Includes all dried blood spot (DBS) specimens tested at the lab and for which there is a result, i.e. positive, negative, or indeterminate. Indeterminate means that the sample went through the entire algorithm, but the final result was inconclusive. 2 Includes: 1) other results of blood collection (e.g. technical problem in the field), 2) lost specimens, 3) non corresponding bar codes, and 4) other lab results such as blood not tested for technical reason, not enough blood to complete the algorithm, etc. 3 A respondent is considered to have had concurrent partners if he or she had overlapping sexual partnerships with two or more people during the 12 months before the survey. (Respondents with concurrent partners includes polygynous men who had overlapping sexual partnerships with two or more wives). Appendix B • 365 HIV TESTING METHODOLOGY Appendix B he 2015 Zimbabwe Demographic and Health Survey (2015 ZDHS) included HIV serological testing of the household population to generate national and provincial estimates of HIV prevalence. The HIV prevalence algorithm used for the official ZDHS HIV prevalence estimates provided in Chapter 14 of this report differs from the algorithm included in the initial survey protocol. This Appendix includes a discussion of the following:  The consent procedures and specimen collection and handling  The original testing algorithm as per the survey protocol  The testing algorithm used for the official 2015 ZDHS HIV prevalence estimates  The rationale for the change in testing algorithms  A comparison of results from both algorithms Procedures for HIV testing in the 2015 ZDHS consisted of the collection of blood specimens in the form of dried blood spots (DBS) on a filter paper card via finger prick (or heel prick for children under the age of 12 months) for anonymous centralized laboratory testing. SPECIMEN COLLECTION AND HANDLING Female household members age 0-49 and male household members age 0-54 were eligible for the HIV test. ZDHS biomarker interviewers explained the blood collection procedure, the confidentiality of the data, and the fact that the test results would not be made available to the respondent. Informed consent for HIV testing was sought from parents or guardians of children age 0-6 years. In accordance with human subjects practices in Zimbabwe, for children/youth age 7-17 years parental/guardian consent and youth assent were sought for HIV testing. Minors age 13-17 who have ever been married, or who live in households in which no household members are 18 years of age or above, are considered emancipated and were able to consent to participate in the HIV test without the permission of a parent or guardian. ZDHS biomarker interviewers read informed consent statements aloud to participants and their parents/guardians and provided printed copies of the consent statements. Adults and parents/guardians provided written consent, and unemancipated minors age 7-17 provided written assent. Each household, whether individuals consented to HIV testing or not, was given an informational brochure on HIV/AIDS and a list of fixed sites providing voluntary counselling and testing services in surrounding districts within the province. If a participant consented to HIV testing, five blood spots from the finger or heel prick were collected on a filter paper card to which a barcode label unique to the respondent was affixed. The barcode number was entered into the electronic Biomarker Data Collection Form on the tablet computer, using double entry for confirmation of data entry accuracy. A copy of the same barcode was affixed to the Blood Sample Transmittal Form to track the blood samples from the field to the laboratory. This protocol allows for merging of HIV test results with the sociodemographic data collected in the individual questionnaires after removal of all information that could potentially identify an individual. Blood samples were dried overnight and packaged for storage the following morning. Samples were periodically collected in the field, along with the signed consent and assent forms, and transported to ZIMSTAT in Harare to be logged in and checked; they were then transported to the National Microbiology Reference Laboratory (NMRL) in Harare. T 366 • Appendix B After receipt at NMRL, the laboratory staff logged each blood sample into the CSPro HIV Test Tracking System database, given a laboratory number, and stored at -20˚C until tested. The HIV testing protocol stipulated that blood could be tested only after questionnaire data collection had been completed, data had been verified and cleaned, and all unique identifiers other than the anonymous barcode number had been removed from the data file. LABORATORY TESTING All HIV testing was conducted by NMRL. The testing algorithm for participants age 2 years and older specified in the original survey protocol is as follows. All specimens were first screened on a highly sensitive assay (Vironostika HIV Ag/Ab Combination assay—BioMerieux, Boxtel, Netherlands), and then all samples that tested positive on the screening assay were tested on a highly specific assay (Enzygnost HIV Integral II—Siemens, Marburg, Germany). If the two assays yielded discrepant results, they were repeated in parallel. If they remained discrepant after repeat testing, specimens were tested on a third assay, INNO-LIA™ HIV I/II Score Blot Assay (Fujirebio, Zwignaard, Belgium). The result of the third assay was used to render the final HIV result for the specimen (Figure B.1). Figure B.1 Original HIV testing algorithm, participants age 2 years and older All survey specimens were tested on this algorithm in full, enabling the calculation of an HIV prevalence estimate according to the original survey testing algorithm, for comparison purposes. Recently, concerns have been raised that algorithms which include two enzyme immunoassays (EIAs) as the first two assays in the HIV testing algorithm—as in the original testing algorithm for the 2015 ZDHS—may misclassify some true negative specimens as positive, thus introducing a risk of overestimation in the HIV prevalence estimate. In accordance with new recommendations, released after the 2015 ZDHS survey protocol was finalized (see UNAIDS/WHO, 2015), a decision was taken to add an additional test to the algorithm. To reduce the risk of false-positive results, all specimens that were rendered positive in the original HIV testing algorithm for the survey were tested on a highly specific confirmatory assay, Geenius HIV 1/2 (Bio-Rad, France). The algorithm used to calculate the official 2015 ZDHS HIV prevalence estimate is shown in Figure B.2. Both the original and the revised HIV testing algorithms are identical through the first two assays. However, in the revised algorithm, specimens that were found positive on the first two assays were then tested on Geenius HIV 1/2, and were rendered final positives only if the result of this test was also A1 A1+ A1- A2 A2 A1+A2+ POSITIVE A1+A2- A1-A2+ A1-A2- NEGATIVE A3+ POSITIVE A3 Indeterminate INDETERMINATE NEGATIVE 5% IQC A1 = Assay 1 A2 = Assay 2 A3 = Western blot IQC = internal quality control 95% Repeat A1 & A2 A3- NEGATIVE A1+A2- or A1-A2+ A1-A2-A1+A2+ Appendix B • 367 positive. For the purpose of HIV prevalence calculation, specimens rendered “inconclusive” are included in the denominator of the percentage and not the numerator—i.e., they are treated as negatives. It should be noted that the final testing algorithm is not completely consistent with the latest UNAIDS/WHO guidelines regarding the classification of specimens that have discrepant results on the two EIAs. The latest UNAIDS/WHO HIV testing guidelines recommend that specimens that are positive on the first assay, negative on the second assay, and positive on the third assay should be rendered “inconclusive.” In the case of the 2015 ZDHS, specimens with discrepant results were first tested on Western Blot for the original testing algorithm. In the final testing algorithm, these specimens were tested again on Geenius. If the results were positive for INNO-LIA and Geenius, there was sufficient evidence to render the specimen positive, even if one of the EIAs was negative. There were four such specimens in the survey. Figure B.2 Final HIV testing algorithm, participants age 2 years and older The HIV testing algorithm for children under the age of 2 years remained consistent throughout the course of the 2015 ZDHS. All specimens from children under the age of 2 years were screened on Vironostika HIV Ag/Ab Combination assay (BioMerieux, Boxtel, Netherlands). Specimens found positive on Vironostika were subjected to nucleic acid amplification testing (NAAT) using the Roche Ampliprep/COBAS Taqman HIV-1 Qual Test. Those specimens found to be positive on NAAT were rendered HIV positive. HIV PREVALENCE RESULTS ACCORDING TO THE ORIGINAL AND FINAL TESTING ALGORITHMS As stated above, the official 2015 ZDHS HIV prevalence estimates shown in Chapter 14 are based on the final HIV testing algorithm shown in Figure B.2. In this Appendix, we compare these official results to those derived from the original HIV testing algorithm from the 2015 ZDHS protocol. The HIV prevalence estimates derived from the final algorithm are more refined than the results derived from the original algorithm. The addition of a highly specific confirmatory assay in the final algorithm helps to identify specimens that were false positive in the original algorithm. It is useful to present the findings from the original algorithm for two reasons. First, they are the results as per the testing algorithm in the survey A1 A1+ A1- A2 A2 A1+A2+ A1+A2- A1-A2+ A1-A2- NEGATIVE NEGATIVE 5% IQC A1 = Assay 1 A2 = Assay 2 A3 = Geenius HIV 1/2 IQC = internal quality control 95% Repeat A1 & A2 A1+A2- or A1-A2+ A1-A2-A1+A2+ A3+ POSITIVE A3- NEGATIVE A3 Indeterminate INCONCLUSIVE A3+ POSITIVE A3- INCONCLUSIVE A3 Indeterminate INCONCLUSIVE 368 • Appendix B protocol that was agreed to by all stakeholders, and it is important to note how the results of the two algorithms compare. Second, the original HIV testing algorithm is more similar to the HIV testing algorithm used in the 2010-11 ZDHS, thus the HIV prevalence derived from the original survey algorithm is more comparable to the HIV prevalence estimates from the previous survey for trend analysis. Tables B.1 and B.2 below show the HIV prevalence estimates according to both the final and original HIV testing algorithms for the 2015 ZDHS. Overall, the addition of confirmatory testing in the final algorithm resulted in a decrease in the HIV prevalence rate for women and men age 15-49 of 0.2 percentage points, from 14.0 percent to 13.8 percent. The difference between these two estimates is likely to be false-positive results in the original testing algorithm. Over 98 percent of the original 3,003 positive specimens (unweighted number) were confirmed positive on Geenius—only 1.8 percent of the specimens found positive according to the original algorithm, were found negative or inconclusive following confirmatory testing. As expected, the amount of difference between the HIV prevalence estimates from the two algorithms is similar across age, sex, and background characteristics, such that the patterns in the distribution of HIV are similar across the two algorithms. Table B.1 HIV prevalence according to final and original HIV testing algorithms, by age Among respondents who were tested according to the final and original HIV testing algorithms, percentage who are HIV-positive by sex and testing algorithm, according to age, Zimbabwe 2015 Female Male Total Age Percentage HIV positive according to: Number Percentage HIV positive according to: Number Percentage HIV positive according to: Number Final algorithm Original algorithm Final algorithm Original algorithm Final algorithm Original algorithm 15-19 4.0 4.2 1,917 2.5 2.8 2,018 3.2 3.5 3,935 20-24 10.3 10.4 1,489 3.7 3.8 1,257 7.3 7.4 2,745 25-29 15.5 15.5 1,453 7.5 7.8 1,052 12.1 12.3 2,505 30-34 21.9 22.0 1,408 13.1 13.3 1,049 18.2 18.3 2,457 35-39 28.0 28.3 1,064 18.0 18.5 831 23.6 24.0 1,895 40-44 31.3 31.4 847 27.0 27.2 737 29.3 29.4 1,585 45-49 24.3 24.3 489 23.2 23.2 532 23.7 23.7 1,021 50-54 na na na 28.9 29.1 333 na na 333 Total 15-49 16.7 16.8 8,667 10.5 10.8 7,475 13.8 14.0 16,142 Total 15-54 na na na 11.3 11.6 7,808 na na na Note: The “Final algorithm” columns show the official 2015 ZDHS HIV prevalence estimates. na = Not applicable Appendix B • 369 Table B.2 HIV prevalence according to final and original HIV testing algorithms, by socioeconomic characteristics Among women and men age 15-49 who were tested according to the final and original HIV testing algorithms, percentage who are HIV-positive by sex and testing algorithm, according to socioeconomic characteristics, Zimbabwe 2015 Women Men Total Background characteristic Percentage HIV positive according to: Number Percentage HIV positive according to: Number Percentage HIV positive according to: Number Final algorithm Original algorithm Final algorithm Original algorithm Final algorithm Original algorithm Residence Urban 16.8 17.0 3,334 11.3 11.5 2,698 14.3 14.5 6,031 Rural 16.6 16.7 5,334 10.1 10.4 4,777 13.5 13.7 10,111 Province Manicaland 12.9 12.9 1,102 7.9 7.9 996 10.5 10.5 2,099 Mashonaland Central 13.7 13.9 768 10.0 10.5 748 11.9 12.3 1,517 Mashonaland East 18.0 18.1 829 12.0 12.1 750 15.2 15.3 1,579 Mashonaland West 16.3 16.5 1,010 9.8 10.0 933 13.2 13.4 1,943 Matabeleland North 21.6 21.8 405 12.8 13.4 340 17.6 18.0 745 Matabeleland South 27.3 27.4 365 14.7 15.0 313 21.5 21.7 678 Midlands 17.8 18.0 1,100 11.6 12.1 919 15.0 15.3 2,018 Masvingo 16.2 16.4 1,033 8.4 8.6 784 12.9 13.1 1,818 Harare 16.5 16.6 1,553 10.5 10.7 1,312 13.8 13.9 2,865 Bulawayo 15.1 15.4 502 13.3 13.6 379 14.3 14.6 881 Education No education 16.4 16.4 107 (9.0) (9.0) 36 14.5 14.5 143 Primary 20.5 20.7 2,217 11.7 12.1 1,679 16.7 17.0 3,896 Secondary 15.7 15.8 5,737 10.2 10.4 4,998 13.1 13.3 10,735 More than secondary 11.5 11.8 607 9.9 10.2 762 10.6 10.9 1,368 Wealth quintile Lowest 17.9 17.9 1,472 11.8 12.0 1,135 15.2 15.4 2,606 Second 15.3 15.6 1,467 11.2 11.4 1,320 13.4 13.6 2,787 Middle 17.7 17.8 1,540 9.6 9.9 1,457 13.8 14.0 2,997 Fourth 19.5 19.7 2,046 11.5 11.7 1,753 15.8 16.0 3,798 Highest 13.2 13.4 2,143 9.0 9.2 1,810 11.3 11.5 3,953 Total 15-49 16.7 16.8 8,667 10.6 10.8 7,475 13.8 14.0 16,142 Note: The “Final algorithm” columns show the official 2015 ZDHS HIV prevalence estimates. Trends in HIV prevalence are addressed in Figure B.3. As noted above, the HIV prevalence estimate for the 2015 ZDHS according to the final HIV testing algorithm is 0.2 percentage points lower than the HIV prevalence estimate according to the original HIV testing algorithm. The HIV testing algorithm used in the 2010-11 survey was similar to the original HIV testing algorithm for the 2015 ZDHS. Therefore, it is important to note that when comparing results from the 2010-11 ZDHS with those from the 2015 ZDHS, part of this difference could be due to using two different testing algorithms that are not strictly comparable. As shown in Figure B.3, HIV prevalence decreased from 15.2 percent in the 2010-11 ZDHS to 14.0 percent according to the 2015 ZDHS original algorithm estimate and 13.8 according to the final algorithm. The difference between the two results for the 2015 survey is quite small relative to the change since the 2010-11 survey. Therefore, most of the difference observed between the 2010-11 ZDHS results and the 2015 ZDHS final algorithm results is likely to reflect a change in the population over time, with a small portion of this difference being attributable to the change in the testing algorithm. 370 • Appendix B Figure B.3 Trends in HIV prevalence 19.3 16.1 15.1 14.7 22.6 18.8 18.1 17.8 15.9 13.3 11.9 11.5 16.9 14.3 13.2 12.9 19.6 16.6 15.8 15.5 13.2 11.3 9.8 9.5 18.1 15.2 14.1 13.8 21.1 17.7 16.9 16.7 14.5 12.3 10.9 10.5 6 8 10 12 14 16 18 20 22 24 2005- 06 2010- 11 2015 O 2015 Fin 2005- 06 2010- 11 2015 O 2015 Fin 2005- 06 2010- 11 2015 O 2015 Fin Total 15-49 Women 15-49 Men 15-49 O = HIV prevalence estimate according to original testing algorithm. Fin = HIV prevalence estimate according to the final result using the original testing algorithm and confirmation of all positive smpales on a thris assay. Appendix C • 371 ESTIMATES OF SAMPLING ERRORS Appendix C stimates from a sample survey are affected by two types of errors: non-sampling errors and sampling errors. Non-sampling errors are the results of mistakes made in implementing data collection and data processing, such as failure to locate and interview the correct household, misunderstanding of the questions on the part of either the interviewer or the respondent, and data entry errors. Although numerous efforts were made during the implementation of the 2015 Zimbabwe DHS (ZDHS) to minimize this type of error, non-sampling errors are impossible to avoid and difficult to evaluate statistically. Sampling errors, on the other hand, can be evaluated statistically. The sample of respondents selected in the 2015 ZDHS is only one of many samples that could have been selected from the same population, using the same design and expected size. Each of these samples would yield results that differ somewhat from the results of the actual sample selected. Sampling errors are a measure of the variability between all possible samples. Although the degree of variability is not known exactly, it can be estimated from the survey results. Sampling error is usually measured in terms of the standard error for a particular statistic (mean, percentage, etc.), which is the square root of the variance. The standard error can be used to calculate confidence intervals within which the true value for the population can reasonably be assumed to fall. For example, for any given statistic calculated from a sample survey, the value of that statistic will fall within a range of plus or minus two times the standard error of that statistic in 95 percent of all possible samples of identical size and design. If the sample of respondents had been selected as a simple random sample, it would have been possible to use straightforward formulas for calculating sampling errors. However, the 2015 ZDHS sample is the result of a multi-stage stratified design, and, consequently, it was necessary to use more complex formulae. Sampling errors are computed in either ISSA or SAS, using programs developed by ICF International. These programs use the Taylor linearization method of variance estimation for survey estimates that are means, proportions, or ratios. The Jackknife repeated replication method is used for variance estimation of more complex statistics such as fertility and mortality rates. The Taylor linearization method treats any percentage or average as a ratio estimate, r = y x , where y represents the total sample value for variable y, and x represents the total number of cases in the group or subgroup under consideration. The variance of r is computed using the formula given below, with the standard error being the square root of the variance:     2 2 2 2 1 1 1 var 1 hmH h h hi h ih h f m z SE r = r z x m m               in which hi hi hiz = y rx , and h h hz = y rx where h represents the stratum which varies from 1 to H, hm is the total number of clusters selected in the hth stratum, hiy is the sum of the weighted values of variable y in the ith cluster in the hth stratum, E 372 • Appendix C hix is the sum of the weighted number of cases in the ith cluster in the hth stratum, and f is the overall sampling fraction, which is so small that it is ignored. The Jackknife repeated replication method derives estimates of complex rates from each of several replications of the parent sample, and calculates standard errors for these estimates using simple formulae. Each replication considers all but one cluster in the calculation of the estimates. Pseudo-independent replications are thus created. In the 2015 ZDHS, there were 400 non-empty clusters. Hence, 400 replications were created. The variance of a rate r is calculated as follows:         22 1 1 var 1 k i i SE r = r r r k k      in which    1i ir = kr k r  where r is the estimate computed from the full sample of 400 clusters,  ir is the estimate computed from the reduced sample of 399 clusters (i th cluster excluded), and k is the total number of clusters. In addition to the standard error, the design effect (DEFT) for each estimate is also calculated. The design effect is defined as the ratio between the standard error using the given sample design and the standard error that would result if a simple random sample had been used. A DEFT value of 1.0 indicates that the sample design is as efficient as a simple random sample, while a value