Ethiopia - Demographic and Health Survey - 2017

Publication date: 2017

Ethiopia Demographic and Health Survey 2016 E thiopia 2016 D em ographic and H ealth S urvey FEDERAL DEMOCRATIC REPUBLIC OF ETHIOPIA ETHIOPIA Demographic and Health Survey 2016 Central Statistical Agency Addis Ababa, Ethiopia The DHS Program ICF Rockville, Maryland, USA July 2017 ETHIOPIANS AND AMERICANS IN PARTNERSHIP TO FIGHT HIV/AIDS The 2016 Ethiopia Demographic and Health Survey (2016 EDHS) was implemented by the Central Statistical Agency (CSA) from January 18, 2016, to June 27, 2016. The funding for the 2016 EDHS was provided by the government of Ethiopia, the United States Agency for International Development (USAID), the government of the Netherlands, the Global Fund, Irish Aid, the World Bank, the United Nations Population Fund (UNFPA), the United Nations Children’s Fund (UNICEF), and UN Women. ICF provided technical assistance through The DHS Program, a USAID-funded project providing support and technical assistance in the implementation of population and health surveys in countries worldwide. Additional information about the 2016 EDHS may be obtained from the Central Statistical Agency of Ethiopia, P.O. Box 1143, Addis Ababa, Ethiopia; Telephone +251-111-55-30-11/111-15 78-41; Fax: +251-111-55-03-34; E-mail: csa@ethionet.et. Information about The DHS Program may be obtained from ICF, 530 Gaither Road, Suite 500, Rockville, MD 20850, USA; Telephone: +1-301-407-6500; Fax: +1-301-407-6501; E-mail: info@DHSprogram.com; Internet: www.DHSprogram.com. Cover photo “Colorful Baskets in Addis Market” © 2005 Philip Kromer. Used under Creative Commons CC2.0 Generic license. Recommended citation: Central Statistical Agency (CSA) [Ethiopia] and ICF. 2016. Ethiopia Demographic and Health Survey 2016. Addis Ababa, Ethiopia, and Rockville, Maryland, USA: CSA and ICF. Contents • iii CONTENTS TABLES AND FIGURES . ix FOREWORD . xix ACKNOWLEDGMENTS . xxi ACRONYMS AND ABBREVIATIONS .xxiii READING AND UNDERSTANDING TABLES FROM THE 2016 ETHIOPIA DEMOGRAPHIC AND HEALTH SURVEY (EDHS) . xxv 1 INTRODUCTION AND SURVEY METHODOLOGY . 1 1.1 Survey Objectives . 1 1.2 Sample Design . 2 1.3 Questionnaires . 2 1.4 Anthropometry, Anaemia Testing, and HIV Testing . 3 1.4.1 Height and Weight Measurement . 3 1.4.2 Anaemia Testing . 4 1.4.3 HIV Testing . 4 1.5 Pretest . 5 1.6 Training of Field Staff . 6 1.7 Fieldwork . 6 1.8 Data Processing . 6 1.9 Response Rates . 7 2 HOUSING CHARACTERISTICS AND HOUSEHOLD POPULATION . 9 2.1 Drinking Water Sources and Treatment . 9 2.2 Sanitation . 10 2.3 Exposure to Smoke inside the Home . 11 2.3.1 Other Housing Characteristics . 11 2.3.2 Household Durable Goods . 11 2.4 Household Wealth . 11 2.5 Hand Washing . 12 2.6 Household Population and Composition . 12 2.7 Children’s Living Arrangements and Parental Survival . 13 2.8 Birth Registration . 13 2.9 Education . 14 2.9.1 Educational Attainment . 14 2.9.2 School Attendance . 15 2.9.3 Other Measures of School Attendance . 15 2.10 Injury and Accidents . 17 3 CHARACTERISTICS OF RESPONDENTS . 33 3.1 Basic Background Characteristics of Survey Respondents . 33 3.2 Education and Literacy . 34 3.3 Mass Media Exposure and Internet Usage . 35 3.4 Employment . 36 3.5 Occupation . 37 3.6 Type of Women’s Employment . 38 3.7 Health Insurance Coverage . 38 3.8 Tobacco Use . 38 iv • Contents 3.9 Alcohol Consumption . 39 3.10 Chewing Chat . 39 4 MARRIAGE AND SEXUAL ACTIVITY . 65 4.1 Marital Status . 65 4.2 Polygyny . 66 4.3 Age at First Marriage . 67 4.4 Age at First Sexual Intercourse . 67 4.5 Recent Sexual Activity . 68 5 FERTILITY . 77 5.1 Current Fertility . 77 5.2 Children Ever Born and Living . 79 5.3 Birth Intervals . 79 5.4 Insusceptibility to Pregnancy . 80 5.5 Age at First Birth . 81 5.6 Teenage Childbearing . 81 6 FERTILITY PREFERENCES . 91 6.1 Desire for Another Child . 91 6.2 Ideal Family Size . 92 6.3 Fertility Planning Status . 93 6.4 Wanted Fertility Rates . 94 7 FAMILY PLANNING . 103 7.1 Contraceptive Knowledge and Use . 103 7.2 Source of Modern Contraceptive Methods . 106 7.3 Informed Choice . 106 7.4 Discontinuation of Contraceptives . 107 7.5 Knowledge of the Fertile Period . 107 7.6 Demand for Family Planning . 107 7.6.1 Decision Making about Family Planning . 109 7.6.2 Future Use of Contraception . 109 7.6.3 Exposure to Family Planning Messages in the Media . 109 7.7 Contact of Nonusers with Family Planning Providers . 109 8 INFANT AND CHILD MORTALITY . 123 8.1 Infant and Child Mortality . 124 8.2 Biodemographic Risk Factors . 125 8.3 Perinatal Mortality . 125 8.4 High-risk Fertility Behaviour . 126 9 MATERNAL HEALTH CARE . 133 9.1 Antenatal Care Coverage and Content . 134 9.1.1 Skilled Providers . 134 9.1.2 Timing and Number of ANC Visits . 134 9.2 Components of ANC . 135 9.3 Protection against Neonatal Tetanus . 135 9.4 Delivery Services . 136 9.4.1 Institutional Deliveries . 136 9.4.2 Skilled Assistance during Delivery . 138 9.4.3 Delivery by Caesarean Section . 138 9.5 Postnatal Care . 139 9.5.1 Postnatal Health Check for Mothers . 139 Contents • v 9.5.2 Postnatal Health Check for Newborns . 140 9.6 Obstetric Fistula . 141 9.7 Problems in Accessing Health Care . 141 10 CHILD HEALTH . 161 10.1 Birth Weight . 161 10.2 Vaccination of Children. 162 10.2.1 Uptake of the Newly Introduced Vaccines . 163 10.2.2 Vaccination Card Ownership and Availability . 165 10.2.3 Health Facility Visit . 165 10.3 Symptoms of Acute Respiratory Infection . 165 10.4 Fever . 166 10.5 Diarrhoeal Disease . 167 10.5.1 Prevalence of Diarrhoea . 167 10.5.2 Feeding Practices . 167 10.5.3 Oral Rehydration Therapy and Other Treatments for Diarrhoea . 168 10.5.4 Knowledge of ORS Packets . 169 10.5.5 Treatment of Childhood Illnesses . 169 10.6 Disposal of Children’s Stools . 169 11 NUTRITION OF CHILDREN AND ADULTS . 187 11.1 Nutritional Status of Children . 187 11.1.1 Measurement of Nutritional Status among Young Children . 188 11.1.2 Data Collection . 189 11.1.3 Levels of Child Malnutrition . 189 11.2 Infant and Young Child Feeding Practices . 190 11.2.1 Breastfeeding . 190 11.2.2 Median Duration of Breastfeeding . 193 11.2.3 Complementary Feeding . 193 11.2.4 Minimum Acceptable Diet . 194 11.3 Anaemia Prevalence in Children . 195 11.4 Micronutrient Intake and Supplementation among Children. 197 11.5 Presence of Iodised Salt in Households . 197 11.6 Adults’ Nutritional Status . 198 11.6.1 Nutritional Status of Women . 198 11.6.2 Nutritional Status of Men Age 15-49 Years . 199 11.7 Anaemia Prevalence in Adults. 200 11.7.1 Anaemia Prevalence in Women . 200 11.7.2 Anaemia Prevalence in Men . 200 11.8 Micronutrient Intake among Mothers . 201 12 HIV/AIDS-RELATED KNOWLEDGE, ATTITUDES, AND BEHAVIOUR . 219 12.1 Background Information on HIV and AIDS in Ethiopia . 219 12.2 HIV/AIDS Knowledge, Transmission, and Prevention Methods . 219 12.3 Knowledge about Mother-to-Child Transmission . 220 12.4 Discriminatory Attitudes towards People Living with HIV . 221 12.5 Multiple Sexual Partners . 222 12.6 Paid Sex . 223 12.7 Coverage of HIV Testing Services . 224 12.7.1 Awareness of HIV Testing Services and Experience with HIV Testing . 224 12.7.2 HIV Testing of Pregnant Women . 225 12.8 Male Circumcision . 225 12.9 Self-reporting of Sexually Transmitted Infections . 226 vi • Contents 12.10 HIV/AIDS-Related Knowledge and Behaviour among Young People . 226 12.10.1 Knowledge . 226 12.10.2 First Sex . 227 12.10.3 Premarital Sex . 227 12.10.4 Multiple Sexual Partners . 228 12.10.5 Coverage of HIV Testing Services . 228 12.10.6 Coverage of HIV Testing Services among Children . 228 13 ADULT AND MATERNAL MORTALITY . 249 13.1 Sibling History Data . 249 13.2 Direct Estimates of Adult Mortality . 250 13.3 Direct Estimates of Pregnancy-Related Mortality . 251 13.4 Trends in Pregnancy-Related Mortality . 251 14 WOMEN’S EMPOWERMENT . 255 14.1 Married Women’s and Men’s Employment . 256 14.2 Control over Women’s Earnings . 257 14.3 Control over Men’s Earnings . 257 14.4 Women’s and Men’s Ownership of Assets . 258 14.5 Possession of Title or Deed for a House or Land . 258 14.6 Ownership and Use of Bank Accounts and Mobile Phones . 259 14.7 Decision to Marry . 259 14.8 Schooling after Marriage . 260 14.9 Men’s Participation in Household Chores . 260 14.10 Women’s Participation in Decision Making . 260 14.11 Attitudes toward Wife Beating . 262 14.12 Attitude toward Negotiating Safe Sex . 263 14.13 Ability to Negotiate Sexual Relations . 264 14.14 Women’s Empowerment and Demographic and Health Outcomes . 264 15 VIOLENCE AGAINST WOMEN . 289 15.1 Measurement of Violence . 290 15.2 Women’s Experience of Physical Violence from Anyone . 291 15.2.1 Prevalence of Physical Violence . 291 15.2.2 Perpetrators of Physical Violence . 292 15.3 Experience of Sexual Violence . 292 15.3.1 Prevalence of Sexual Violence . 292 15.3.2 Perpetrators of Sexual Violence . 292 15.4 Experience of Different Forms of Violence . 293 15.5 Marital Control by Husband . 293 15.6 Forms of Spousal Violence . 293 15.6.1 Prevalence of Spousal Violence . 293 15.6.2 Onset of Spousal Violence . 296 15.7 Injuries to Women due to Spousal Violence . 296 15.8 Violence Initiated by Women against Husbands . 296 15.9 Response to Violence . 297 15.9.1 Help-Seeking among Women Who Have Experienced Violence . 297 15.9.2 Sources for Help . 297 16 FEMALE GENITAL MUTILATION/CUTTING . 315 16.1 Knowledge . 316 16.2 Prevalence of and Age at Circumcision among Women . 316 16.2.1 Prevalence and Type of Procedure . 316 Contents • vii 16.2.2 Age at Circumcision . 319 16.3 Prevalence of and Age at Circumcision for Girls Age 0-14 . 319 16.4 Opinions about the Practice . 320 REFERENCES. 329 APPENDIX A SAMPLE DESIGN . 331 A.1 Introduction . 331 A.2 Sampling Frame . 331 A.3 Sample Design and Selection . 333 A.4 Sampling Weights . 337 APPENDIX B ESTIMATES OF SAMPLING ERRORS . 339 APPENDIX C DATA QUALITY TABLES . 355 APPENDIX D PERSONS INVOLVED IN THE 2016 ETHIOPIA DEMOGRAPHIC AND HEALTH SURVEY . 361 APPENDIX E QUESTIONNAIRES . 373 Tables and Figures • ix TABLES AND FIGURES 1 INTRODUCTION AND SURVEY METHODOLOGY . 1 Table 1.1 Results of the household and individual interviews . 8 Figure 1.1 2016 EDHS HIV testing algorithm . 5 2 HOUSING CHARACTERISTICS AND HOUSEHOLD POPULATION . 9 Table 2.1 Household drinking water . 19 Table 2.2 Availability of water . 20 Table 2.3 Household sanitation facilities . 20 Table 2.4 Household characteristics . 21 Table 2.5 Household possessions . 22 Table 2.6 Wealth quintiles . 22 Table 2.7 Hand washing . 23 Table 2.8 Household population by age, sex, and residence . 23 Table 2.9 Household composition . 24 Table 2.10 Children’s living arrangements and orphanhood . 25 Table 2.11 Birth registration of children under age 5 . 26 Table 2.12.1 Educational attainment of the female household population . 27 Table 2.12.2 Educational attainment of the male household population . 28 Table 2.13 School attendance ratios . 29 Table 2.14 Injury or death in an accident among household members . 30 Table 2.15 Injury or death in an accident . 30 Table 2.16 Length of injury . 31 Table 2.17 Type of accident . 31 Figure 2.1 Household drinking water by residence . 10 Figure 2.2 Household toilet facilities by residence . 11 Figure 2.3 Household wealth by residence. 12 Figure 2.4 Population pyramid . 13 Figure 2.5 Birth registration by household wealth . 14 Figure 2.6 Birth registration by region . 14 Figure 2.7 Secondary school attendance by household wealth . 15 Figure 2.8 Age-specific attendance rates for the de facto population age 5 to 24 . 17 3 CHARACTERISTICS OF RESPONDENTS . 33 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 x • Tables and Figures Table 3.7.2 Occupation: Men . 54 Table 3.8 Type of employment: Women . 55 Table 3.9.1 Health insurance coverage: Women . 55 Table 3.9.2 Health insurance coverage: Men . 56 Table 3.10.1 Tobacco smoking: Women . 57 Table 3.10.2 Tobacco smoking: Men . 58 Table 3.11 Average number of cigarettes smoked daily: Men . 59 Table 3.12.1 Alcohol consumption: Women . 60 Table 3.12.2 Alcohol consumption: Men . 61 Table 3.13.1 Chewing chat: Women . 62 Table 3.13.2 Chewing chat: Men . 63 Figure 3.1 Education of survey respondents . 34 Figure 3.2 Secondary education by region . 35 Figure 3.3 Exposure to mass media . 36 Figure 3.4 Employment status by residence . 37 Figure 3.5 Occupation . 37 4 MARRIAGE AND SEXUAL ACTIVITY . 65 Table 4.1 Current marital status . 70 Table 4.2.1 Number of women’s co-wives . 70 Table 4.2.2 Number of men’s wives . 71 Table 4.3 Age at first marriage . 72 Table 4.4 Median age at first marriage according to background characteristics . 73 Table 4.5 Age at first sexual intercourse . 74 Table 4.6 Median age at first sexual intercourse according to background characteristics . 74 Table 4.7.1 Recent sexual activity: Women . 75 Table 4.7.2 Recent sexual activity: Men . 76 Figure 4.1 Marital status . 65 Figure 4.2 Polygyny by region . 66 Figure 4.3 Women’s median age at marriage by education . 67 Figure 4.4 Median age at first sex and first marriage . 68 Figure 4.5 Trends in early sexual intercourse . 68 5 FERTILITY . 77 Table 5.1 Current fertility . 84 Table 5.2 Fertility by background characteristics . 84 Table 5.3.1 Trends in age-specific fertility rates . 85 Table 5.3.2 Trends in age-specific and total fertility rates . 85 Table 5.4 Children ever born and living . 85 Table 5.5 Birth intervals . 86 Table 5.6 Postpartum amenorrhoea, abstinence, and insusceptibility . 87 Table 5.7 Median duration of amenorrhoea, postpartum abstinence, and postpartum insusceptibility . 87 Table 5.8 Menopause . 88 Table 5.9 Age at first birth . 88 Table 5.10 Median age at first birth . 89 Table 5.11 Teenage pregnancy and motherhood . 89 Figure 5.1 Trends in fertility by residence . 78 Figure 5.2 Trends in age-specific fertility . 78 Figure 5.3 Fertility by region . 78 Tables and Figures • xi Figure 5.4 Fertility by education . 78 Figure 5.5 Birth intervals . 79 Figure 5.6 Median age at first birth by residence . 81 Figure 5.7 Teenage pregnancy and motherhood by region . 82 Figure 5.8 Teenage pregnancy and motherhood by household wealth . 82 Figure 5.9 Sexual and reproductive health behaviours before age 15 . 83 6 FERTILITY PREFERENCES . 91 Table 6.1 Fertility preferences by number of living children . 96 Table 6.2.1 Desire to limit childbearing: Women . 97 Table 6.2.2 Desire to limit childbearing: Men . 98 Table 6.3 Ideal number of children by number of living children . 99 Table 6.4 Mean ideal number of children according to background characteristics . 100 Table 6.5 Fertility planning status . 100 Table 6.6 Wanted fertility rates . 101 Figure 6.1 Trends in desire to limit childbearing by number of living children . 92 Figure 6.2 Desire to limit childbearing by number of living children . 92 Figure 6.3 Ideal family size . 93 Figure 6.4 Ideal family size by number of living children . 93 Figure 6.5 Fertility planning status . 94 Figure 6.6 Trends in wanted and actual fertility . 94 7 FAMILY PLANNING . 103 Table 7.1 Knowledge of contraceptive methods . 111 Table 7.2 Knowledge of contraceptive methods according to background characteristics 112 Table 7.3 Current use of contraception according to age . 113 Table 7.4 Current use of contraception according to background characteristics . 114 Table 7.5 Source of modern contraception methods . 114 Table 7.6 Informed choice . 115 Table 7.7 Twelve-month contraceptive discontinuation rates . 115 Table 7.8 Reasons for discontinuation . 116 Table 7.9 Knowledge of fertile period . 116 Table 7.10.1 Need and demand for family planning among currently married women . 117 Table 7.10.2 Need and demand for family planning for all women and for sexually active unmarried women . 118 Table 7.11 Decision making about family planning . 119 Table 7.12 Future use of contraception . 119 Table 7.13 Exposure to family planning messages . 120 Table 7.14 Contact of nonusers with family planning providers . 121 Figure 7.1 Contraceptive use . 104 Figure 7.2 Trends in contraceptive use . 105 Figure 7.3 Use of modern methods by region . 105 Figure 7.4 Use of modern methods by household wealth . 105 Figure 7.5 Source of modern contraceptive methods . 106 Figure 7.6 Contraceptive discontinuation rates . 107 Figure 7.7 Demand for family planning . 108 Figure 7.8 Trends in demand for family planning . 108 Figure 7.9 Unmet need by residence . 108 Figure 7.10 Unmet need by region . 109 xii • Tables and Figures 8 INFANT AND CHILD MORTALITY . 123 Table 8.1 Early childhood mortality rates . 128 Table 8.2 Early childhood mortality rates according to socioeconomic characteristics . 128 Table 8.3 Early childhood mortality rates according to demographic characteristics . 129 Table 8.4 Perinatal mortality . 130 Table 8.5 High-risk fertility behaviour . 131 Figure 8.1 Trends in early childhood mortality rates . 124 Figure 8.2 Under-5 mortality by region . 125 Figure 8.3 Infant mortality by mother’s education . 125 Figure 8.4 Childhood mortality by previous birth interval . 125 Figure 8.5 Perinatal mortality by mother’s education . 126 9 MATERNAL HEALTH CARE . 133 Table 9.1 Antenatal care . 142 Table 9.2 Number of antenatal care visits and timing of first visit . 143 Table 9.3 Components of antenatal care . 144 Table 9.4 Signs of pregnancy complications . 145 Table 9.5 Birth preparedness plan . 146 Table 9.6 Tetanus toxoid injections . 147 Table 9.7 Tetanus vaccination card . 148 Table 9.8 Place of delivery . 149 Table 9.9 Assistance during delivery . 150 Table 9.10 Caesarean section . 151 Table 9.11 Duration of stay in health facility after birth . 152 Table 9.12 Timing of first postnatal check-up for the mother . 152 Table 9.13 Type of provider for the first postnatal check for the mother . 153 Table 9.14 Timing of first postnatal check for the newborn . 154 Table 9.15 Type of provider for the first postnatal check for the newborn . 155 Table 9.16 Content of postnatal care for newborns . 156 Table 9.17 Newborn care . 157 Table 9.18 Care of umbilical cord . 158 Table 9.19 Obstetrical fistula . 159 Table 9.20 Problems in accessing health care . 160 Figure 9.1 Trends in antenatal care coverage . 134 Figure 9.2 Components of antenatal care . 135 Figure 9.3 Trends in place of birth . 137 Figure 9.4 Health facility births by region . 137 Figure 9.5 Health facility births by education . 137 Figure 9.6 Assistance during delivery . 138 Figure 9.7 Skilled assistance at delivery by household wealth . 138 Figure 9.8 Components of information about maternal danger signs after delivery . 140 10 CHILD HEALTH . 161 Table 10.1 Child’s size and weight at birth. 170 Table 10.2 Vaccinations by source of information . 171 Table 10.3 Vaccinations by background characteristics . 172 Table 10.4 Possession and observation of vaccination cards, according to background characteristics . 173 Table 10.5 Observation of vaccination history at health facilities: Children 0-35 months . 174 Table 10.6 Observation of vaccination history at health facilities: Children 12-35 months . 175 Table 10.7 Outcome of health facilities visit . 176 Tables and Figures • xiii Table 10.8 Prevalence and treatment of symptoms of ARI . 177 Table 10.9 Source of advice or treatment for children with symptoms of ARI . 178 Table 10.10 Prevalence and treatment of fever . 179 Table 10.11 Prevalence and treatment of diarrhoea . 180 Table 10.12 Feeding practices during diarrhoea . 181 Table 10.13 Oral rehydration therapy, zinc, and other treatments for diarrhoea . 182 Table 10.14 Source of advice or treatment for children with diarrhoea . 183 Table 10.15 Knowledge of ORS packets (LEMLEM) or pre-packaged liquids . 184 Table 10.16 Disposal of children’s stools . 185 Figure 10.1 Childhood vaccinations . 163 Figure 10.2 Trends in childhood vaccinations . 164 Figure 10.3 Vaccination coverage by region . 164 Figure 10.4 Vaccination coverage by mother’s education . 164 Figure 10.5 Diarrhoea prevalence by age . 166 Figure 10.6 Feeding practices during diarrhoea . 167 Figure 10.7 Treatment of diarrhoea . 167 Figure 10.8 Prevalence and treatment of childhood illness . 168 11 NUTRITION OF CHILDREN AND ADULTS . 187 Table 11.1 Nutritional status of children . 202 Table 11.2 Initial breastfeeding . 204 Table 11.3 Breastfeeding status according to age . 205 Table 11.4 Median duration of breastfeeding . 206 Table 11.5 Foods and liquids consumed by children in the day or night preceding the interview . 207 Table 11.6 Minimum acceptable diet . 208 Table 11.7 Prevalence of anaemia in children . 210 Table 11.8 Micronutrient intake among children . 211 Table 11.9 Presence of iodised salt in household . 212 Table 11.10.1 Nutritional status of women . 213 Table 11.10.2 Nutritional status of men . 214 Table 11.11.1 Prevalence of anaemia in women . 215 Table 11.11.2 Prevalence of anaemia in men . 216 Table 11.12 Micronutrient intake among mothers . 217 Figure 11.1 Trends in nutritional status of children . 189 Figure 11.2 Stunting in children by region . 190 Figure 11.3 Stunting in children by mother’s education . 190 Figure 11.4 Breastfeeding practices by age . 191 Figure 11.5 IYCF indicators on breastfeeding status . 192 Figure 11.6 IYCF indicators on minimum acceptable diet (MAD). 194 Figure 11.7 Trends in childhood anaemia . 195 Figure 11.8 Anaemia in children by region . 196 Figure 11.9 Nutritional status of women and men . 198 Figure 11.10 Trends in anaemia status among women . 199 12 HIV/AIDS-RELATED KNOWLEDGE, ATTITUDES, AND BEHAVIOUR . 219 Table 12.1 Knowledge of HIV prevention methods . 230 Table 12.2 Comprehensive knowledge about HIV . 231 Table 12.3 Knowledge of prevention of mother-to-child transmission of HIV . 232 Table 12.4 Discriminatory attitudes towards people living with HIV . 233 xiv • Tables and Figures Table 12.5.1 Multiple sexual partners and higher-risk sexual intercourse in the past 12 months: Women . 234 Table 12.5.2 Multiple sexual partners and higher-risk sexual intercourse in the past 12 months: Men . 235 Table 12.6 Payment for sexual intercourse and condom use at last paid sexual intercourse . 236 Table 12.7.1 Coverage of prior HIV testing: Women . 237 Table 12.7.2 Coverage of prior HIV testing: Men . 238 Table 12.8 Coverage of prior HIV testing among married women. 239 Table 12.9 Pregnant women counselled and tested for HIV . 240 Table 12.10 Male circumcision . 241 Table 12.11 Self-reported prevalence of sexually-transmitted infections (STIs) and STI symptoms . 242 Table 12.12 Women and men seeking treatment for STIs . 243 Table 12.13 Comprehensive knowledge about HIV among young people . 243 Table 12.14 Age at first sexual intercourse among young people . 244 Table 12.15 Premarital sexual intercourse among young people . 244 Table 12.16.1 Multiple sexual partners and higher-risk sexual intercourse in the past 12 months among young people: Women . 245 Table 12.16.2 Multiple sexual partners and higher-risk sexual behaviour in the past 12 months among young people: Men . 246 Table 12.17 Recent HIV tests among young people . 246 Table 12.18 HIV tests among children . 247 Figure 12.1 Knowledge of HIV prevention methods . 220 Figure 12.2 Knowledge of mother-to-child transmission (MTCT) . 221 Figure 12.3 Trends in knowledge of mother-to-child transmission (MTCT) . 221 Figure 12.4 Discriminatory attitudes* towards people living with HIV by education . 222 Figure 12.5 Sex and condom use with non-regular partners . 223 Figure 12.6 HIV testing . 224 Figure 12.7 Recent HIV testing by region. 224 Figure 12.8 Recent HIV testing by education . 225 Figure 12.9 Male circumcision by age . 226 Figure 12.10 Trends in comprehensive HIV knowledge among youth . 227 13 ADULT AND MATERNAL MORTALITY . 249 Table 13.1 Completeness of information on siblings . 253 Table 13.2 Adult mortality rates . 253 Table 13.3 Adult mortality probabilities . 253 Table 13.4 Pregnancy-related mortality rates . 254 Figure 13.1 Trends in pregnancy-related mortality ratio (PRMR) with confidence intervals . 252 14 WOMEN’S EMPOWERMENT . 255 Table 14.1 Employment and cash earnings of currently married women and men . 267 Table 14.2.1 Control over women’s cash earnings and relative magnitude of women’s cash earnings . 268 Table 14.2.2 Control over men’s cash earnings . 269 Table 14.3 Women’s control over their own earnings and those of their husbands . 270 Table 14.4.1 Ownership of assets (house and land): Women . 270 Table 14.4.2 Ownership of assets (house and land): Men . 271 Table 14.5.1 Possession of title or deed for house: Women . 272 Tables and Figures • xv Table 14.5.2 Possession of title or deed for house: Men . 273 Table 14.6.1 Possession of title or deed for land: Women . 274 Table 14.6.2 Possession of title or deed for land: Men . 275 Table 14.7.1 Ownership and use of bank accounts and mobile phones: Women . 276 Table 14.7.2 Ownership and use of bank accounts and mobile phones: Men . 277 Table 14.8 Person deciding on a woman’s first marriage . 278 Table 14.9 Schooling after marriage . 279 Table 14.10 Men’s participation in household chores . 280 Table 14.11 Participation in decision making . 280 Table 14.12.1 Women’s participation in decision making by background characteristics . 281 Table 14.12.2 Men’s participation in decision making by background characteristics . 282 Table 14.13.1 Attitude toward wife beating: Women . 283 Table 14.13.2 Attitude toward wife beating: Men . 284 Table 14.14 Attitudes toward negotiating safer sexual relations with husband . 285 Table 14.15 Ability to negotiate sexual relations with husband . 286 Table 14.16 Indicators of women’s empowerment . 286 Table 14.17 Current use of contraception by women’s empowerment . 287 Table 14.18 Ideal number of children and unmet need for family planning by women’s empowerment . 287 Table 14.19 Reproductive health care by women’s empowerment . 288 Table 14.20 Early childhood mortality rates by indicators of women’s empowerment . 288 Figure 14.1 Employment by age . 256 Figure 14.2 Control over woman’s earnings . 257 Figure 14.3 Ownership of assets . 259 Figure 14.4 Women’s participation in decision making. 262 Figure 14.5 Attitudes towards wife beating . 263 Figure 14.6 Trend of wife beating justified . 263 15 VIOLENCE AGAINST WOMEN . 289 Table 15.1 Experience of physical violence . 299 Table 15.2 Experience of violence during pregnancy . 300 Table 15.3 Persons committing physical violence . 301 Table 15.4 Experience of sexual violence. 302 Table 15.5 Age at first experience of sexual violence . 303 Table 15.6 Persons committing sexual violence . 303 Table 15.7 Experience of different forms of violence . 303 Table 15.8 Marital control exercised by husbands . 304 Table 15.9 Forms of spousal violence . 305 Table 15.10 Spousal violence by background characteristics . 306 Table 15.11 Spousal violence by husband’s characteristics and empowerment indicators . 307 Table 15.12 Physical or sexual violence in the past 12 months by any husband/partner . 308 Table 15.13 Experience of spousal violence by duration of marriage . 309 Table 15.14 Injuries to women due to spousal violence . 309 Table 15.15 Violence by women against their husband by women’s background characteristics . 310 Table 15.16 Violence by women against their husband by husband’s characteristics and empowerment indicators . 311 Table 15.17 Help seeking to stop violence . 312 Table 15.18 Sources for help to stop the violence . 313 xvi • Tables and Figures Figure 15.1 Women’s experience of violence by marital status . 291 Figure 15.2 Violence during pregnancy by education . 292 Figure 15.3 Types of spousal violence . 294 Figure 15.4 Spousal violence by region . 295 Figure 15.5 Spousal violence by husband’s alcohol consumption . 295 16 FEMALE GENITAL MUTILATION/CUTTING . 315 Table 16.1 Knowledge of female circumcision . 320 Table 16.2 Prevalence of female circumcision . 321 Table 16.3 Age at circumcision . 322 Table 16.4 Prevalence of circumcision and age at circumcision: Girls 0-14 . 323 Table 16.5 Circumcision of girls age 0-14 by mother’s background characteristics . 323 Table 16.6 Infibulation among circumcised girls age 0-14 . 324 Table 16.7 Aspects of circumcision among circumcised girls age 0-14 and women age 15-49 . 325 Table 16.8 Opinions of women and men about whether circumcision is required by religion . 326 Table 16.9 Opinions of women and men about whether the practice of circumcision should continue . 327 Figure 16.1 Type of female circumcision. 317 Figure 16.2 Trends in circumcision . 317 Figure 16.3 Circumcision by age . 317 Figure 16.4 Circumcision by region . 317 Figure 16.5 Age at circumcision . 318 Figure 16.6 Age at circumcision among women and girls . 318 Figure 16.7 Attitudes about FGC by circumcision status . 319 APPENDIX A SAMPLE DESIGN . 331 Table A.1 Distribution of residential households . 332 Table A.2 Enumeration areas and households . 332 Table A.3 Sample allocation of clusters and households . 333 Table A.4 Sample allocation of expected number of completed interviews with women and men . 334 Table A.5 Sample implementation: Women . 335 Table A.6 Sample implementation: Men . 336 APPENDIX B ESTIMATES OF SAMPLING ERRORS . 339 Table B.1 Sampling errors: Total sample, Ethiopia DHS 2016 . 341 Table B.2 Sampling errors: Urban sample, Ethiopia DHS 2016 . 342 Table B.3 Sampling errors: Rural sample, Ethiopia DHS 2016 . 343 Table B.4 Sampling errors: Tigray sample, Ethiopia DHS 2016 . 344 Table B.5 Sampling errors: Affar sample, Ethiopia DHS 2016 . 345 Table B.6 Sampling errors: Amhara sample, Ethiopia DHS 2016 . 346 Table B.7 Sampling errors: Oromiya sample, Ethiopia DHS 2016 . 347 Table B.8 Sampling errors: Somali sample, Ethiopia DHS 2016 . 348 Table B.9 Sampling errors: Benishangul-Gumuz sample, Ethiopia DHS 2016 . 349 Table B.10 Sampling errors: SNNPR sample, Ethiopia DHS 2016 . 350 Table B.11 Sampling errors: Gambela sample, Ethiopia DHS 2016 . 351 Table B.12 Sampling errors: Harari sample, Ethiopia DHS 2016 . 352 Table B.13 Sampling errors: Addis Ababa sample, Ethiopia DHS 2016 . 353 Table B.14 Sampling errors: Dire Dawa sample, Ethiopia DHS 2016 . 354 Tables and Figures • xvii APPENDIX C DATA QUALITY TABLES . 355 Table C.1 Household age distribution . 355 Table C.2.1 Age distribution of eligible and interviewed women . 356 Table C.2.2 Age distribution of eligible and interviewed men . 356 Table C.3 Completeness of reporting . 357 Table C.4 Births by calendar years . 357 Table C.5 Reporting of age at death in days . 358 Table C.6 Reporting of age at death in months . 358 Table C.7 Nutritional status of children based on the NCHS/CDC/WHO International Reference Population . 359 Table C.8 Sibling size and sex ratio of siblings . 360 Foreword • xix FOREWORD he 2016 Ethiopia Demographic and Health Survey (EDHS) is the fourth survey implemented by the Central Statistical Agency (CSA). By virtue of its mandate, the CSA has conducted the survey in collaboration with the Federal Ministry of Health (FMoH) and the Ethiopian Public Health Institute (EPHI) with technical assistance from ICF International, and financial as well as technical support from development partners. All actors in this effort have exerted themselves to get reliable, accurate, and up-to-date data to measure the success of the national development agenda— Growth and Transformation Plan II as well as the Sustainable Development Goals. The survey was conducted from January 18, 2016, to June 27, 2016, based on a nationally representative sample that provides estimates at the national and regional levels and for urban and rural areas. The survey target groups were women age 15-49 and men age 15-59 in randomly selected households across Ethiopia. Detailed information was collected on background characteristics of the respondents, fertility, marriage, fertility preferences, awareness and the use of family planning methods, child feeding practices, nutritional status of women and children, adult and childhood mortality, awareness and attitudes regarding HIV/AIDS, female genital mutilation, domestic violence, and height and weight of women and children age 0-5 from 16,650 households, 15,683 female respondents, and 12,688 male respondents. This report presents comprehensive, detailed, final outcomes of the survey at the national level, for the nine regional states and two city administrations of Ethiopia. Information can be used for various purposes, including program planning and evaluation. The success of the 2016 EDHS was made possible by a number of local government, nongovernmental, and international development partners, and individuals. In this regard, the Agency is grateful for the commitment of the government of Ethiopia, the United States Agency for International Development (USAID), and the government of the Netherlands, the Global Fund, HAPCO, Irish Aid, the World Bank, the United Nations Population Fund (UNFPA), the United Nations Children’s Fund (UNICEF), World Health Organization (WHO), and UN Women. Special thanks go to the Federal Ministry of Health and its allies. We would like to extend our gratitude to the Ethiopian Public Health Institute (EPHI) for providing technical support on dried blood sample taking and testing, height and weight measurement of women and children during the training, and Survey Steering Committee & Technical Working Group Members, who were instrumental in guiding the resource mobilization process, implementation, and technical aspects of the survey. Similarly, we wish to express appreciation to ICF for its technical assistance in all stages of the survey. We greatly appreciate Ms. Yodit Bekele (ICF DHS Country Manager) for the commitment and great expertise with which she managed all the components of this survey. Finally, we would like to acknowledge the 2016 EDHS Project Director Mr. Asalfew Abera (survey director); Mr. Sahelu Tilahun and technical team members; finance, procurement, human resources, and operation units; and others for the management of all technical, administrative, and logistical phases of the survey. We are also thankful to CSA and field staffs, data processing specialists, and, in particular, survey respondents who generously provided data, without which it would have been impossible to produce this report. Biratu Yigezu Director General Central Statistical Agency T Acknowledgments • xxi ACKNOWLEDGMENTS The following persons contributed to the preparation of this report: Mr. Asalefew Abera, CSA Mr. Sahelu Tilahun, CSA Mr. Abate Sidelel, CSA Mrs. Asnakech Habtamu, CSA Mrs. Sehin Merawi, CSA Ms. Asres Abayneh, CSA Mrs. Tiruzer Tenagne, CSA Mr. Mesfin Tefera, CSA Mr. Akalework Bezu, CSA Mr. Endeshaw Feleke, CSA Mr. Dawit Tessentu, CSA Mr. Hailu Bekele, CSA Mr. Kassahun Mengistu, CSA Mr. Hailu Aleme Selassie, CSA Mr. Neway Kifle, CSA Ms. Senait Teame, CSA Dr. Abdurahman Ismeal, MOH Dr. Taddese Alemu, MOH Dr. Awoke Kebede, MOH Mr. Theodros Getachew, EPHI Mrs. Misrak Getnet, EPHI Mr. Sileshi Tadesse, MoWCA Mr. Tsegaye Debebe, MoWIE Mr. Gebeyehu Abelti, USAID Mrs. Gezu Berhanu, UNFPA Mrs. Martha Kibur, UNICEF Ms. Ki Yeon Yoon, UNICEF Mr. Agazi Ameha, UNICEF Mrs. Zemzem Shikur, UNICEF Mrs. Elleni Seyum, WHO Mrs. Luwam Zenebe, UN Women Mrs. Etagegnehu Getachew, UN Women Acronyms and Abbreviations • xxiii ACRONYMS AND ABBREVIATIONS AIDS acquired immunodeficiency syndrome ANC antenatal care ARI acute respiratory infections BCG Bacille Calmette-Guerin (vaccine) CAPI computer-assisted personal interview CHTTS CSPro HIV test tracking system CPR contraceptive prevalence rate CSA Central Statistical Agency CSPro Census Survey Program DBS dried blood spots DPT diphtheria, pertussis, tetanus vaccine EAs enumeration areas EDHS Ethiopia Demographic and Health Survey EPHC Ethiopian Population and Housing Census EPHI Ethiopia Public Health Institute FGC female genital cutting FGM female genital mutilation HepB hepatitis B (vaccine) HEW health extension worker HF health facility Hib haemophilus influenzae type B (vaccine) HIV human immunodeficiency virus IFSS internet file streaming system IUD intrauterine device IYCF infant and young child feeding LAM lactational amenorrhoea method MOFED Ministry of Finance and Economic Development MoH Ministry of Health NRERC National Research Ethics Review Committee ORS oral rehydration salts ORT oral rehydration therapy PBS Promoting Basic Services (PROJECT) PCV pneumococcal conjugate vaccine PMTCT prevention of mother-to-child transmission PNC postnatal care xxiv • Acronyms and Abbreviations RV1 rotavirus vaccine SDM standard days method SNNPR southern nations, nationalities, and people’s region STDs sexually transmitted diseases TFR total fertility rate UNDP United Nations Development Programme UNFPA United Nations Population Fund UNICEF United Nations Children’s Fund UN Women United Nations Entity on Gender Equality and the Empowerment of Women USAID United States Agency for International Development VAW violence against women VCT voluntary counselling and testing WHO World Health Organization Reading and Understanding Tables from the 2016 Ethiopia Demographic and Health Survey (EDHS) • xxv READING AND UNDERSTANDING TABLES FROM THE 2016 ETHIOPIA DEMOGRAPHIC AND HEALTH SURVEY (EDHS) he new format of the 2016 Ethiopia Demographic and Health Survey (EDHS) final report is based on approximately 200 tables of data. They are located for quick reference through links in the text (electronic version) and at the end of each chapter. Additionally, this more reader-friendly version features about 90 figures that clearly highlight trends, subnational patterns, and background characteristics. The text has been simplified to highlight key points in bullets and to clearly identify indicator definitions in boxes. While the text and figures featured in each chapter highlight some of the most important findings from the tables, not every finding can be discussed or displayed graphically. For this reason, EDHS data users should be comfortable reading and interpreting tables. The following pages provide an introduction to the organization of EDHS tables, the presentation of background characteristics, and a brief summary of sampling and understanding denominators. In addition, this section provides some exercises for users as they practice their new skills in interpreting EDHS tables. T xxvi • Reading and Understanding Tables from the 2016 Ethiopia Demographic and Health Survey (EDHS) Example 1: Women’s Exposure to Mass Media A Question Asked of All Survey Respondents Table 3.4.1 Exposure to mass media: Women Percentage of women age 15-49 who are exposed to specific media on a weekly basis, according to background characteristics, Ethiopia DHS 2016 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 6.9 18.1 17.3 1.2 68.9 3,381 20-24 4.3 18.5 18.2 1.6 70.6 2,762 25-29 4.3 17.5 18.9 1.7 70.4 2,957 30-34 2.0 14.8 16.9 1.1 75.0 2,345 35-39 3.1 12.0 13.2 1.3 79.6 1,932 40-44 1.2 10.7 11.4 0.9 82.7 1,290 45-49 1.8 12.5 13.4 1.0 80.1 1,017 Residence Urban 10.4 60.7 32.4 5.3 31.8 3,476 Rural 2.1 3.1 11.9 0.2 85.5 12,207 Region Tigray 4.4 18.9 15.4 1.7 71.6 1,129 Affar 3.0 15.6 13.3 1.3 74.3 128 Amhara 1.7 10.3 8.4 0.3 83.5 3,714 Oromiya 4.2 12.5 20.2 1.2 72.3 5,701 Somali 1.3 7.9 4.1 0.5 89.3 459 Benishangul-Gumuz 3.4 9.3 11.4 0.4 80.4 160 SNNPR 4.4 8.4 13.3 1.1 80.7 3,288 Gambela 3.5 25.6 13.8 1.1 65.9 44 Harari 5.8 41.6 18.1 4.1 54.6 38 Addis Ababa 10.5 81.1 45.3 6.8 14.1 930 Dire Dawa 5.8 51.5 20.0 2.9 44.2 90 Education No education 0.1 3.6 8.8 0.1 89.0 7,498 Primary 4.1 15.2 17.5 0.7 71.5 5,490 Secondary 11.8 44.5 32.7 4.5 41.0 1,817 More than secondary 19.9 65.6 42.1 9.6 22.4 877 Wealth quintile Lowest 0.9 0.7 3.8 0.0 95.5 2,633 Second 1.6 0.7 6.6 0.0 91.8 2,809 Middle 2.0 1.7 10.7 0.2 87.5 2,978 Fourth 3.1 3.7 18.4 0.5 77.9 3,100 Highest 9.5 54.9 33.8 4.5 34.3 4,163 Total 3.9 15.8 16.5 1.3 73.6 15,683 Step 1: Read the title and subtitle. They tell you the topic and the specific population group being described. In this case, the table is about women age 15-49 and their exposure to different types of media. All eligible female respondents age 15-49 were asked these questions. Step 2: Scan the column headings—highlighted in green in Example 1.They describe how the information is categorized. In this table, the first three columns of data show different types of media that women access at least once a week. The fourth column shows women who access all three types of media, while the fifth column is women who do not access any of the three types of media at least once a week. The last column lists the number of women interviewed in the survey. Step 3: Scan the row headings—the first vertical column highlighted in blue in Example 1. These show the different ways the data are divided into categories based on population characteristics. In this case, the table presents women’s exposure to media by age, urban-rural residence, region, educational level, and wealth quintile. Most of the tables in the EDHS report will be divided into these same categories. Step 4: Look at the row at the bottom of the table highlighted in pink. These percentages represent the totals of all women age 15-49 and their access to different types of media. In this case, 3.9%* of women age 15-49 read a newspaper at least once a week, 15.8% watch television weekly, and 16.5% listen to the radio weekly. 1 2 3 4 5 Reading and Understanding Tables from the 2016 Ethiopia Demographic and Health Survey (EDHS) • xxvii Step 5: To find out what percentage of women age 15-49 with more than secondary education access all three media weekly, draw two imaginary lines, as shown on the table. This shows that 9.6% of women age 15-49 with more than secondary education access all three types of media weekly. Step 6: By looking at patterns by background characteristics, we can see how exposure to mass media varies across Ethiopia. Mass media are often used to communicate health messages. Knowing how mass media exposure varies among different groups can help program planners and policy makers determine how to most effectively reach their target populations. *For the purpose of this document data are presented exactly as they appear in the table including decimal places. However, the text in the remainder of this report rounds data to the nearest whole percentage point. Practice: Use the table in Example 1 to answer the following questions: a) What percentage of women in Ethiopia do not access any of the three media at least once a week? b) What age group of women are most likely to read a newspaper weekly? c) Compare women in urban areas and women in rural areas—which group is more likely to watch television weekly? d) What are the lowest and highest percentages (range) of women who do not access any of the three media at least once a week by region? e) Is there a clear pattern in exposure to television on a weekly basis by education level? f) Is there a clear pattern in exposure to radio on a weekly basis by wealth quintile? Answers: a) 73.6% b) Women age 15-19: 6.9% of women in this age group read a newspaper at least once a week. c) Women in urban areas, 60.7% watch television weekly, compared to 3.1% of women in rural areas. d) 14.1% of women in Addis Ababa do not access any of the three media on a weekly basis, compared to 89.3% of women in Somali region. e) Exposure to television on a weekly basis increases with a woman’s level of education; 3.6% of women with no education watch television weekly, compared to 65.6% of women with more than secondary education. f) Exposure to radio on a weekly basis increases as household wealth increases; 3.8% of women in the lowest wealth quintile listen to the radio on a weekly basis, compared to 33.8% of women in the highest wealth quintile. xxviii • Reading and Understanding Tables from the 2016 Ethiopia Demographic and Health Survey (EDHS) Example 2: Prevalence and Treatment of Symptoms of ARI A Question Asked of a Subgroup of Survey Respondents Table 10.8 Prevalence and treatment of symptoms of ARI Among children under age 5, percentage who had symptoms of acute respiratory infection (ARI) in the 2 weeks preceding the survey; and among children with symptoms of ARI in the 2 weeks preceding the survey, percentage for whom advice or treatment was sought, according to background characteristics, Ethiopia DHS 2016 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 Percentage for whom treatment was sought same or next day Number of children Age in months <6 6.0 1,200 (33.5) (3.5) 72 6-11 8.9 1,071 43.1 0.7 95 12-23 9.1 2,004 33.7 3.2 183 24-35 5.9 1,944 27.0 2.3 114 36-47 6.7 2,007 22.5 4.8 135 48-59 4.2 2,191 30.5 3.7 91 Sex Male 6.5 5,342 34.1 2.7 349 Female 6.7 5,075 28.4 3.5 342 Cooking fuel Electricity or gas 3.5 350 * * 12 Kerosene (0.0) 7 * * 0 Charcoal 4.2 475 (39.3) (5.0) 20 Wood/straw3 7.0 8,964 30.9 3.0 631 Animal dung 4.4 614 * * 27 Other fuel * 7 * * 0 Residence Urban 4.1 1,163 59.1 4.8 48 Rural 6.9 9,254 29.2 3.0 643 Region Tigray 7.7 686 33.6 4.7 53 Affar 4.3 105 (44.3) (5.7) 4 Amhara 8.0 1,967 29.1 2.9 157 Oromiya 7.4 4,571 26.4 0.7 339 Somali 2.1 476 (32.2) (2.9) 10 Benishangul-Gumuz 1.8 113 * * 2 SNNPR 5.4 2,169 43.2 8.3 117 Gambela 3.5 25 * * 1 Harari 0.7 24 * * 0 Addis Ababa 2.7 236 * * 6 Dire Dawa 3.9 44 * * 2 Mother's education No education 6.9 6,858 26.7 2.4 476 Primary 6.3 2,807 40.7 3.3 177 Secondary 5.3 493 * * 26 More than secondary 4.4 260 * * 11 Wealth quintile Lowest 5.3 2,499 25.0 3.1 133 Second 7.2 2,386 26.9 4.4 172 Middle 8.1 2,159 28.9 1.2 176 Fourth 7.9 1,860 41.0 3.5 147 Highest 4.1 1,513 40.2 3.6 63 Total 6.6 10,417 31.3 3.1 691 Note: Figures in parentheses are based on 25-49 unweighted cases. An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. 1 Symptoms of ARI include cough accompanied by short, rapid breathing that is chest-related and/or by difficult breathing that is chest- related. 2 Includes advice or treatment from the following sources: public sector, private medical sector, NGO medical sector, shop, drug vendor, and market. Excludes advice or treatment from a traditional practitioner. Excludes pharmacy, shop, market, traditional practitioner, and itinerant drug peddler. 3 Includes grass, shrubs, crop residues Step 1: Read the title and subtitle. In this case, the table is about two separate groups of children: all children under age five (a) and children under age five who had symptoms of acute respiratory infection (ARI) in the two weeks before the survey (b). 1 2 3 4 a b Reading and Understanding Tables from the 2016 Ethiopia Demographic and Health Survey (EDHS) • xxix Step 2: Identify the two panels. First, identify the columns that refer to all children under age five (a), and then isolate the columns that refer only to children under age five who had symptoms of acute respiratory infection (ARI) in the two weeks before the survey (b). Step 3: Look at the first panel. What percentage of children under age five had symptoms of ARI in the two weeks before the survey? It’s 6.6%. Now look at the second panel. How many children under age five are there who had symptoms of ARI in the two weeks before the survey? It’s 691 children or 6.6% of the 10,417 children under age five (with rounding). The second panel is a subset of the first panel. Step 4: Only 6.6% of children under age five had symptoms of ARI in the two weeks before the survey. Once these children are further divided into the background characteristic categories, there may be too few cases for the percentages to be reliable.  What percentage of children under age five in the Somali region with symptoms of ARI in the two weeks before the survey sought advice or treatment from a health facility or provider? It’s 32.2%. This percentage is in parentheses because there are between 25 and 49 children under age five in Somali who had symptoms of ARI in the two weeks before the survey (unweighted). Readers should use this number with caution—it may not be reliable. (For more information on weighted and unweighted numbers, see Example 4.)  What percentage of children under age five in Gambela with symptoms of ARI in the two weeks before the survey sought advice or treatment from a health facility or provider? There is no number in this cell—only an asterisk. This is because fewer than 25 children under age five in Gambela had symptoms of ARI in the two weeks before the survey (unweighted). Results for this group are not reported. The subgroup is too small, and therefore the data are not reliable. Note: When parentheses or asterisks are used in a table, the explanation will be noted under the table. If there are no parentheses or asterisks in a table, you can proceed with confidence that enough cases were included in all categories that the data are reliable. xxx • Reading and Understanding Tables from the 2016 Ethiopia Demographic and Health Survey (EDHS) Example 3: Understanding Sampling Weights in EDHS Tables A sample is a group of people who have been selected for a survey. In the EDHS, the sample is designed to represent the national population age 15-49. In addition to national data, most countries want to collect and report data on smaller geographical or administrative areas. However, doing so requires a minimum sample size per area. For the 2016 EDHS, the survey sample is representative at the national and regional levels, and for urban and rural areas. To generate statistics that are representative of the Ethiopia as a whole and the 11 regions, the number of women surveyed in each region should contribute to the size of the total (national) sample in proportion to size of the region. However, if some regions have small populations, then a sample allocated in proportion to each region’s population may not include sufficient women from each region for analysis. To solve this problem, regions with small populations are oversampled. For example, let’s say that you have enough money to interview 15,683 women and want to produce results that are representative of Ethiopia as a whole and its regions (as in Table 3.1). However, the total population of Ethiopia is not evenly distributed among the regions: some regions, such as Oromiya, are heavily populated while others, such as Harari are not. Thus, Harari must be oversampled. A sampling statistician determines how many women should be interviewed in each region in order to get reliable statistics. The blue column (1) in the table at the right shows the actual number of women interviewed in each region. Within the regions, the number of women interviewed ranges from 906 in Harari to 1,892 in Oromiya. The number of interviews is sufficient to get reliable results in each region. With this distribution of interviews, some regions are overrepresented and some regions are underrepresented. For example, the population in Oromiya is about 36% of the population in Ethiopia, while Harari’s population contributes only 0.2% of the population in Ethiopia. But as the blue column shows, the number of women interviewed in Oromiya accounts for only about 12% of the total sample of women interviewed (1,892/15,683) and the number of women interviewed in Harari accounts for about 6% of women interviewed (906 /15,683). This unweighted distribution of women does not accurately represent the population. In order to get statistics that are representative of Ethiopia, the distribution of the women in the sample needs to be weighted (or mathematically adjusted) such that it resembles the true distribution in the Ethiopia. Women from a small region, like Harari, should only contribute a small amount to the national total. Women from a large region, like Oromiya, should contribute much more. Therefore, DHS statisticians mathematically calculate a “weight” which is used to adjust the number of women from each region so that each region’s contribution to the total is proportional to the actual population of the region. The numbers in the purple column (2) represent the “weighted” values. The weighted values can be smaller or larger than the unweighted values at regional level. The total national sample size of 15,683 women has not changed after weighting, but the distribution of the women in the regions has been changed to represent their contribution to the total population size. Table 3.1 Background characteristics of respondents Percent distribution of women and men age 15-49 by selected background characteristics, Ethiopia DHS 2016 Women Background characteristic Weighted percent Weighted number Unweighted number Region Tigray 7.2 1,129 1,682 Affar 0.8 128 1,128 Amhara 23.7 3,714 1,719 Oromiya 36.4 5,701 1,892 Somali 2.9 459 1,391 Benishangul-Gumuz 1.0 160 1,126 SNNPR 21.0 3,288 1,849 Gambela 0.3 44 1,035 Harari 0.2 38 906 Addis Ababa 5.9 930 1,824 Dire Dawa 0.6 90 1,131 Total 15-49 100.0 15,683 15,683 1 2 3 Reading and Understanding Tables from the 2016 Ethiopia Demographic and Health Survey (EDHS) • xxxi How do statisticians weight each category? They take into account the probability that a woman was selected in the sample. If you were to compare the green column (3) to the actual population distribution of Ethiopia, you would see that women in each region are contributing to the total sample with the same weight that they contribute to the population of the Ethiopia. The weighted number of women in the survey now accurately represents the proportion of women who live in Oromiya and the proportion of women who live in Harari. With sampling and weighting, it is possible to interview enough women to provide reliable statistics at national and regional levels. In general, only the weighted numbers are shown in each of the EDHS tables, so don’t be surprised if these numbers seem low: they may actually represent a larger number of women interviewed. Introduction and Survey Methodology • 1 INTRODUCTION AND SURVEY METHODOLOGY 1 he 2016 Ethiopia Demographic and Health Survey (EDHS) is the fourth Demographic and Health Survey conducted in Ethiopia. It was implemented by the Central Statistical Agency (CSA) at the request of the Federal Ministry of Health (FMoH). Data collection took place from January 18, 2016, to June 27, 2016. ICF provided technical assistance through the DHS Program, which is funded by the United States Agency for International Development (USAID) and offers support and technical assistance for the implementation of population and health surveys in countries worldwide. Financial support for the 2016 EDHS was provided by the government of Ethiopia, USAID, the government of the Netherlands, the Global Fund via the FMoH and the Ministry of Finance and Economic Development (MOFED), the World Bank via MOFED and Promoting Basic Services (PBS), Irish Aid, the United Nations Population Fund (UNFPA), the United Nations Children’s Fund (UNICEF), and UN Women. 1.1 SURVEY OBJECTIVES The primary objective of the 2016 EDHS is to provide up-to-date estimates of key demographic and health indicators. The EDHS provides a comprehensive overview of population, maternal, and child health issues in Ethiopia. More specifically, the 2016 EDHS:  Collected data at the national level that allowed calculation of key demographic indicators, particularly fertility and under-5 and adult mortality rates  Explored the direct and indirect factors that determine levels and trends of fertility and child mortality  Measured levels of contraceptive knowledge and practice  Collected data on key aspects of family health, including immunisation coverage among children, prevalence and treatment of diarrhoea and other diseases among children under age 5, and maternity care indicators such as antenatal visits and assistance at delivery  Obtained data on child feeding practices, including breastfeeding  Collected anthropometric measures to assess the nutritional status of children under age 5, women age 15-49, and men age 15-59  Conducted haemoglobin testing on eligible children age 6-59 months, women age 15-49, and men age 15-59 to provide information on the prevalence of anaemia in these groups  Collected data on knowledge and attitudes of women and men about sexually transmitted diseases and HIV/AIDS and evaluated potential exposure to the risk of HIV infection by exploring high-risk behaviours and condom use  Conducted HIV testing of dried blood spot (DBS) samples collected from women age 15-49 and men age 15-59 to provide information on the prevalence of HIV among adults of reproductive age  Collected data on the prevalence of injuries and accidents among all household members T 2 • Introduction and Survey Methodology  Collected data on knowledge and prevalence of fistula and female genital mutilation or cutting (FGM/C) among women age 15-49 and their daughters age 0-14  Obtained data on women’s experience of emotional, physical, and sexual violence. As the fourth DHS conducted in Ethiopia, following the 2000, 2005, and 2011 EDHS surveys, the 2016 EDHS provides valuable information on trends in key demographic and health indicators over time. The information collected through the 2016 EDHS is intended to assist policymakers and programme managers in evaluating and designing programmes and strategies for improving the health of the country’s population. Additionally, the 2016 EDHS included a health facility component that recorded data on children’s vaccinations, which were then combined with the household data on vaccinations. 1.2 SAMPLE DESIGN The sampling frame used for the 2016 EDHS is the Ethiopia Population and Housing Census (PHC), which was conducted in 2007 by the Ethiopia Central Statistical Agency. The census frame is a complete list of 84,915 enumeration areas (EAs) created for the 2007 PHC. An EA is a geographic area covering on average 181 households. The sampling frame contains information about the EA location, type of residence (urban or rural), and estimated number of residential households. With the exception of EAs in six zones of the Somali region, each EA has accompanying cartographic materials. These materials delineate geographic locations, boundaries, main access, and landmarks in or outside the EA that help identify the EA. In Somali, a cartographic frame was used in three zones where sketch maps delineating the EA geographic boundaries were available for each EA; in the remaining six zones, satellite image maps were used to provide a map for each EA. Administratively, Ethiopia is divided into nine geographical regions and two administrative cities. The sample for the 2016 EDHS was designed to provide estimates of key indicators for the country as a whole, for urban and rural areas separately, and for each of the nine regions and the two administrative cities. The 2016 EDHS sample was stratified and selected in two stages. Each region was stratified into urban and rural areas, yielding 21 sampling strata. Samples of EAs were selected independently in each stratum in two stages. Implicit stratification and proportional allocation were achieved at each of the lower administrative levels by sorting the sampling frame within each sampling stratum before sample selection, according to administrative units in different levels, and by using a probability proportional to size selection at the first stage of sampling. In the first stage, a total of 645 EAs (202 in urban areas and 443 in rural areas) were selected with probability proportional to EA size (based on the 2007 PHC) and with independent selection in each sampling stratum. A household listing operation was carried out in all of the selected EAs from September to December 2015. The resulting lists of households served as a sampling frame for the selection of households in the second stage. Some of the selected EAs were large, consisting of more than 300 households. To minimise the task of household listing, each large EA selected for the 2016 EDHS was segmented. Only one segment was selected for the survey with probability proportional to segment size. Household listing was conducted only in the selected segment; that is, a 2016 EDHS cluster is either an EA or a segment of an EA. In the second stage of selection, a fixed number of 28 households per cluster were selected with an equal probability systematic selection from the newly created household listing. All women age 15-49 and all men age 15-59 who were either permanent residents of the selected households or visitors who stayed in the household the night before the survey were eligible to be interviewed. In half of the selected households, all women age 15-49 were eligible for the FGM/C module, and only one woman per household was selected for the domestic violence module. In all of the selected households, height and Introduction and Survey Methodology • 3 weight measurements were collected from children age 0-59 months, women age 15-49, and men age 15- 59. Anaemia testing was performed on consenting women age 15-49 and men age 15-59 and on children age 6-59 months whose parent/guardian consented to the testing. In addition, DBS samples were collected for HIV testing in the laboratory from women age 15-49 and men age 15-59 who consented to testing. 1.3 QUESTIONNAIRES Five questionnaires were used for the 2016 EDHS: the Household Questionnaire, the Woman’s Questionnaire, the Man’s Questionnaire, the Biomarker Questionnaire, and the Health Facility Questionnaire. These questionnaires, based on the DHS Program’s standard Demographic and Health Survey questionnaires, were adapted to reflect the population and health issues relevant to Ethiopia. Input was solicited from various stakeholders representing government ministries and agencies, nongovernmental organisations, and international donors. After all questionnaires were finalised in English, they were translated into Amarigna, Tigrigna, and Oromiffa. The Household Questionnaire was used to list all members of and visitors to selected households. Basic demographic information was collected on the characteristics of each person listed, including his or her age, sex, marital status, education, and relationship to the head of the household. For children under age 18, parents’ survival status was determined. The data on age and sex of household members obtained in the Household Questionnaire were used to identify women and men who were eligible for individual interviews. The Household Questionnaire also collected information on characteristics of the household’s dwelling unit, such as source of water, type of toilet facilities, and flooring materials, as well as on ownership of various durable goods. The Household Questionnaire included an additional module developed by the DHS Program to estimate the prevalence of injuries/accidents among all household members. The Woman’s Questionnaire was used to collect information from all eligible women age 15-49. These women were asked questions on the following topics:  Background characteristics (including age, education, and media exposure)  Birth history and childhood mortality  Family planning, including knowledge, use, and sources of contraceptive methods  Fertility preferences  Antenatal, delivery, and postnatal care  Breastfeeding and infant feeding practices  Vaccinations and childhood illnesses  Women’s work and husbands’ background characteristics  Knowledge, awareness, and behaviour regarding HIV/AIDS and other sexually transmitted diseases (STDs)  Knowledge, attitudes, and behaviours related to other health issues (e.g., injections, smoking, use of chat)  Adult and maternal mortality  Female genital mutilation or cutting  Fistula  Violence against women The Man’s Questionnaire was administered to all eligible men age 15-59. This questionnaire collected much of the same information elicited from the Woman’s Questionnaire but was shorter because it did not contain a detailed reproductive history, questions on maternal and child health, or questions on domestic violence. The Biomarker Questionnaire was used to record biomarker data collected from respondents by health technicians. 4 • Introduction and Survey Methodology For the first time, the 2016 EDHS also included a Health Facility Questionnaire. This questionnaire was used to record vaccination information for all children without a vaccination card identified through the Woman’s Questionnaire. The 2016 EDHS interviewers used tablet computers to record responses during the interviews. The tablets were equipped with Bluetooth technology to enable remote electronic transfer of files (transfer of assignment sheets from team editors to interviewers and transfer of completed questionnaires from interviewers to editors). The computer-assisted personal interviewing (CAPI) data collection system employed in the 2016 EDHS was developed by the DHS Program using the mobile version of CSPro. The CSPro software was developed jointly by the U.S. Census Bureau, the DHS Program, and Serpro S.A. 1.4 ANTHROPOMETRY, ANAEMIA TESTING, AND HIV TESTING The 2016 EDHS incorporated the following biomarkers: anthropometry, anaemia testing, and HIV testing. These biomarkers were collected in all households. In contrast with the data collection procedures for the household and individual interviews, biomarker data were initially recorded on the paper-based Biomarker Questionnaire and subsequently entered into interviewers’ tablet computers. The survey protocol, including biomarker collection, was reviewed and approved by the Federal Democratic Republic of Ethiopia Ministry of Science and Technology and the Institutional Review Board of ICF International. 1.4.1 Height and Weight Measurement Height and weight measurements were carried out on women age 15-49, men age 15-59, and children under age 5 in all selected households. Weight measurements were obtained using lightweight SECA mother-infant scales with a digital screen designed and manufactured under the guidance of UNICEF. Height measurements were carried out using a Shorr measuring board. Children younger than 24 months were measured for height while lying down, and older children were measured while standing. 1.4.2 Anaemia Testing Blood specimens for anaemia testing were collected from women age 15-49 and men age 15-59 who voluntarily consented to be tested and from all children age 6-59 months for whom consent was obtained from their parents or other adults responsible for them. Blood samples were drawn from a drop of blood taken from a finger prick (or a heel prick in the case of children age 6-11 months) and collected in a microcuvette. Haemoglobin analysis was carried out on-site using a battery-operated portable HemoCue analyser. Results were provided verbally and in writing. Parents or responsible adults of children whose haemoglobin level was below 7 g/dl were instructed to take the child to a health facility for follow-up care. Likewise, nonpregnant women and pregnant women were referred for follow-up care if their haemoglobin levels were below 7 g/dl and 9 g/dl, respectively. All households in which anaemia testing was conducted were given a brochure explaining the causes and prevention of anaemia. 1.4.3 HIV Testing Interviewers collected finger-prick blood specimens from women age 15-49 and men age 15-59 who consented to HIV testing. The protocol for blood specimen collection and analysis was based on the anonymous linked protocol developed for the DHS Program. 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. Interviewers explained the procedure, the confidentiality of the data, and the fact that the test results would not be made available to respondents. If a respondent consented to 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. A duplicate label was attached to the Biomarker Questionnaire. A third copy of the same barcode Introduction and Survey Methodology • 5 was affixed to the Dried Blood Spot Transmittal Sheet to track the blood samples from the field to the laboratory. Respondents were also asked whether they would consent to having the laboratory store their blood sample for future testing of hepatitis B and C, rubella, and measles. If respondents did not consent to additional testing of their blood sample in the future, their refusal was recorded on the Biomarker Questionnaire and the words “no additional testing” were written on the filter paper card. All respondents, irrespective of whether or not they provided consent, were given an informational brochure on HIV and a list of nearby sites providing HIV counselling and testing (HCT) services. Blood samples were dried overnight and packaged for storage the following morning. Samples were periodically collected from the field and transported to the laboratory at the Ethiopian Public Health Institute (EPHI) in Addis Ababa. Upon arrival at EPHI, each blood sample was logged into the CSPro HIV Test Tracking System database, given a laboratory number, and stored at -20°C until tested. The HIV testing protocol (Figure 1.1) stipulated that blood could be tested only after questionnaire data collection had been completed, the data had been verified and cleaned, and all unique identifiers other than the anonymous barcode number had been removed from the data file. Figure 1.1 2016 EDHS HIV testing algorithm The testing algorithm calls for testing all samples with the first assay, the Genscreen ULTRA Ag/Ab (Bio- Rad) enzyme-linked immunoassay (ELISA I). All samples testing positive on the ELISA I are subjected to a second ELISA (ELISA II), the Bioelisa HIV 1+2 Ag/Ab combination (Biokit). Five percent of the samples that test negative on the ELISA I are also subjected to the ELISA II, while the other 95% are recorded as negative. 95% 5% Positive ELISA 1 Genscreen ULTRA Ag/Ab ELISA 2 Bioelisa HIV 1+2 Ag/Ab combination Bioelisa HIV 1+2 Ag/Ab combination Negative Negative Positive Internal Quality Control ELISA 2 Negative Positive Negative Repeat Positive Inno-Lia HIV I/II line immunoassay Indeterminate/Missing Negative ELISA 1 & ELISA 2 POSITIVE ELISA 1 NEGATIVE & ELISA 2 POSITIVE ELISA 1 POSITIVE & ELISA 2 NEGATIVE Positive ELISA 1 & ELISA 2 Inconclusive/ Missing Inconclusive Inconclusive 6 • Introduction and Survey Methodology Concordant negative results on the ELISA I and ELISA II are recorded as negative. If the results of the ELISA I and ELISA II are discordant, the specimen is rendered inconclusive. Concordant positive results on the ELISA I and ELISA II are also subjected to the third confirmatory assay. When both the ELISA I and the ELISA II are positive, the sample is rendered positive if the Inno-Lia is positive and inconclusive if the Inno-Lia is negative or indeterminate. To monitor the quality of HIV testing and assess the validity of test results, two quality control steps were employed. During HIV testing at EPHI, an internal quality control process was established through the use of control materials and retesting of a randomly selected proportion of negative samples. For the purposes of internal quality control, positive and negative serum controls supplied by the manufacturer with the test kits were included on each microtiter plate of samples, and known HIV- negative, low-positive, and high-positive DBS controls obtained from the CDC were tested in parallel with the kit controls on every microtiter plate of samples. After HIV testing has been completed, the test results for the 2016 EDHS will be entered into a spreadsheet with a barcode as the unique identifier. The barcode links the HIV test results with the individual interview data. At the time of this report’s release, HIV testing had not been completed. A separate report focusing on HIV prevalence will be published as soon as all testing has been completed. 1.5 PRETEST The pretest for the 2016 EDHS was conducted from October 1-28, 2015, in Bishoftu at the Asham African Training Centre. It consisted of in-class training, biomarker training, and field practice days. The field practice was conducted in clusters surrounding Bishoftu that were not included in the 2016 EDHS sample. A total of 60 trainees attended the pretest. Some of the trainees had experience with household surveys, having been involved in either previous Ethiopia DHS surveys or other similar surveys. Following the field practice, a debriefing session was held with the pretest field staff, and modifications to the questionnaires were made based on lessons drawn from the exercise. 1.6 TRAINING OF FIELD STAFF CSA recruited and trained 294 people for the main fieldwork to serve as team supervisors, field editors, interviewers, secondary editors, and reserve interviewers. The training took place from December 14, 2015, to January 17, 2016, at the Debre Zeit Management Institute in Bishoftu. The training course consisted of instruction regarding interviewing techniques and field procedures, a detailed review of questionnaire content, instruction on how to administer the paper and electronic questionnaires, mock interviews between participants in the classroom, and practice interviews with real respondents in areas outside the survey sample. In addition, 72 individuals were recruited and trained on how to collect biomarker data, including taking height and weight measurements, testing for anaemia by measuring haemoglobin levels, and preparing dried blood spots for HIV testing in the laboratory. The biomarker training was held from January 2-11, 2016, and consisted of lectures, demonstrations of biomarker measurement or testing procedures, and field practice with children at the training centre. The interviewer training also included presentations given by various specialists and experts from the Federal Ministry of Health covering Ethiopia-specific policies and programmes on HIV/AIDS, child immunisations, family planning, child nutrition, childhood diseases, and violence against women. A four-day field practice was organised, from January 12-15, 2016, to provide trainees with additional hands-on experience before the actual fieldwork. A total of 36 teams were formed for field practice. Each team consisted of a team supervisor, a field editor, three female interviewers, one male interviewer, and two biomarker technicians. Introduction and Survey Methodology • 7 Training participants were evaluated through homework, in-class exercises, quizzes, and observations made during field practice. Ultimately, 132 individuals were selected as interviewers, 66 as biomarker technicians, 33 as field editors, and 33 as team supervisors. The selection of team supervisors and field editors was based on their experience in leading survey teams and their performance during the pretest and the main training. Team supervisors and field editors received additional instructions and practice using the CAPI system to perform supervisory activities. Supervisory activities included assigning households and receiving completed interviews from interviewers, recognising and dealing with error messages, receiving system updates and distributing updates to interviewers, completing biomarker questionnaires and DBS transmittal sheets, dealing with duplicated cases, closing clusters, and transferring interviews to the central office via a secure Internet file streaming system (IFSS). In addition to the CAPI material, team supervisors and field editors received further training on their roles and responsibilities and how to fulfil them. Fifteen individuals were trained for two days on the Health Facility Questionnaire. Among other components, the training consisted of a brief introduction to the 2016 EDHS survey and an overview of their tasks, including detailed training on the vaccination section of the Woman’s Questionnaire. Data from the field practice were used to generate the list of children without vaccination cards, to be used as part of the training. In addition, the team visited health facilities in order to see the various systems that exist in different facilities. 1.7 FIELDWORK Data collection took place over a 5.5-month period, from January 18, 2016, to June 27, 2016. Fieldwork was carried out by 33 field teams, each consisting of one team supervisor, one field editor, three female interviewers, one male interviewer, two biomarker technicians, and one driver. In addition, 28 quality controllers (14 for interviews and 14 for biomarkers) were dispatched during data collection to support and monitor fieldwork. Electronic data files were transferred to the CSA central office in Addis Ababa every few days via the secured IFSS. Staff from CSA, FMoH, and EPHI and specialists from the DHS Program coordinated and supervised fieldwork activities. 1.8 DATA PROCESSING All electronic data files for the 2016 EDHS were transferred via IFSS to the CSA central office in Addis Ababa, where they were stored on a password-protected computer. The data processing operation included secondary editing, which required resolution of computer-identified inconsistencies and coding of open- ended questions; it also required generating a file for the list of children for whom a vaccination card was not seen by the interviewers and whose vaccination records had to be checked at health facilities. The data were processed by two individuals who took part in the main fieldwork training; they were supervised by two senior staff from CSA. Data editing was accomplished using CSPro software. During the duration of fieldwork, tables were generated to check various data quality parameters and specific feedback was given to the teams to improve performance. Secondary editing and data processing were initiated in January 2016 and completed in August 2016. 1.9 RESPONSE RATES Table 1.1 shows response rates for the 2016 EDHS. A total of 18,008 households were selected for the sample, of which 17,067 were occupied. Of the occupied households, 16,650 were successfully interviewed, yielding a response rate of 98%. 8 • Introduction and Survey Methodology Table 1.1 Results of the household and individual interviews Number of households, number of interviews, and response rates, according to residence (unweighted), Ethiopia DHS 2016 Residence Total Result Urban Rural Household interviews Households selected 5,659 12,349 18,008 Households occupied 5,411 11,656 17,067 Households interviewed 5,232 11,418 16,650 Household response rate1 96.7 98.0 97.6 Interviews with women age 15-49 Number of eligible women 5,720 10,863 16,583 Number of eligible women interviewed 5,348 10,335 15,683 Eligible women response rate2 93.5 95.1 94.6 Interviews with men age 15-59 Number of eligible men 4,801 9,994 14,795 Number of eligible men interviewed 3,866 8,822 12,688 Eligible men response rate2 80.5 88.3 85.8 1 Households interviewed/households occupied 2 Respondents interviewed/eligible respondents In the interviewed households, 16,583 eligible women were identified for individual interviews. Interviews were completed with 15,683 women, yielding a response rate of 95%. A total of 14,795 eligible men were identified in the sampled households and 12,688 were successfully interviewed, yielding a response rate of 86%. Although overall there was little variation in response rates according to residence, response rates among men were higher in rural than in urban areas. Housing Characteristics and Household Population • 9 HOUSING CHARACTERISTICS AND HOUSEHOLD POPULATION 2 Key Findings  Drinking water: In Ethiopia, 97% of urban households have access to an improved source of drinking water, as compared with 57% of rural households.  Hand washing: Soap and water, the essential hand washing agents, were observed in 28% of urban households and 7% of rural households. On a regional basis, the availability of soap and water is highest in Addis Ababa (39%) and lowest in Amhara (5%).  Electricity: In Ethiopia, 93% of urban households and 8% of rural households have access to electricity.  Household population and composition: Nearly half of Ethiopians are under age 15 (47%), while 4% are age 65 and older. nformation on the socioeconomic characteristics of the household population in the 2016 EDHS provides a context to interpret demographic and health indicators and can furnish an approximate indication of the representativeness of the survey. In addition, this information sheds light on the living conditions of the population. This chapter presents information on sources of drinking water, sanitation, exposure to smoke inside the home, wealth, hand washing, household population and composition, educational attainment, school attendance, birth registration, children’s living arrangements, and parental survivorship. 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 unknown, households that use bottled water for drinking are classified as using an improved source only if the water they use for cooking and hand washing comes from an improved source. Sample: Households In Ethiopia, 97% of urban households have access to an improved source of drinking water, as compared with 57% of rural households (Table 2.1). Urban and rural households rely on different sources of drinking water. The three most common sources of drinking water in urban households are water piped into the household’s dwelling, yard, or plot (63%); water piped into a public tap/standpipe (13%); and water piped I 10 • Housing Characteristics and Household Population to a neighbour (12%). By contrast, rural households obtain their drinking water mainly from public taps/standpipes (19%), followed by protected springs (14%) and tube wells or boreholes (13%) (Figure 2.1). In urban areas, 77% of households have piped water on their premises, compared with 6% of rural households. Fetching drinking water is an additional chore that could be of great cost to household members, depending on the time spent to obtain it. More than half of rural households (53%) travel 30 minutes or longer round trip to fetch drinking water. In both rural and urban households, adult women are most likely to be responsible for fetching drinking water (17% in urban households and 68% in rural households). In rural areas, female children under age 15 are three times more likely than male children in the same age group to fetch drinking water (13% versus 4%). Clean water is a basic need for human life; however, most household residents in both urban (88%) and rural (92%) areas report that they do not treat their water prior to drinking. Overall, 7% of households in Ethiopia (11% in urban areas and 6% in rural areas) are using an appropriate treatment method. Appropriate treatment methods include boiling, adding bleach/chlorine, straining through a cloth, filtering, solar disinfecting, and letting it stand and settle. Table 2.2 presents information on the percentage of households using piped water or water from a tube well or borehole that reported availability of water in the last 2 weeks. Fifty-one percent of households in Ethiopia reported having water with no interruption of at least 1 day in the last 2 weeks. Urban households were more likely than rural households to report no availability of water for at least 1 day (69% versus 35%). 2.2 SANITATION Improved toilet facilities Include any non-shared toilet of the following types: flush/pour flush toilets to piped sewer systems, septic tanks, and pit latrines; ventilated improved pit (VIP) latrines; pit latrines with slabs; and composting toilets. Sample: Households Overall, 6% of Ethiopian households use improved toilet facilities (16% in urban areas and 4% in rural areas). More than half (56%) of rural households use unimproved toilet facilities. More than one-third (35%) of toilet facilities are shared in urban households, whereas only 2% of rural households share their Figure 2.1 Household drinking water by residence 18 75 3 18 13 19 11 3 13 18 5 21 35 3 43 Total Urban Rural Percent distribution of households by source of drinking water Unimproved source Protected well or spring Tube well or borehole Public tap/ standpipe Piped water into dwelling/yard/plot/ neighbour’s yard Housing Characteristics and Household Population • 11 toilet facilities with other households. One in three households in Ethiopia have no toilet facility (39% in rural areas and 7% in urban areas) (Table 2.3 and Figure 2.2). 2.3 EXPOSURE TO SMOKE INSIDE THE HOME Exposure to smoke inside the home, either from cooking with solid fuels or smoking tobacco, has potentially harmful health effects. Ninety-three percent of households in Ethiopia use some type of solid fuel for cooking, with virtually all of these households using wood (Table 2.4). Exposure to cooking smoke is greater when cooking takes place inside the house rather than in a separate building or outdoors. In Ethiopia, cooking is done in a separate building in 47% of households, a figure that has increased since the 2011 EDHS (36%). In 6% of households, someone smokes inside the house on a daily basis. 2.3.1 Other Housing Characteristics The 2016 EDHS also collected data on access to electricity, flooring materials, and the number of rooms used for sleeping. One in four households in Ethiopia have access to electricity (93% in urban areas and 8% in rural areas). The two most commonly used materials for flooring in Ethiopia are earth or sand (48%) and dung (33%). Flooring materials differ widely in urban and rural areas. Earth or sand, vinyl or asphalt strips, and carpet are most often used in urban households (23% each), whereas households in rural areas primarily use earth or sand (55%) and dung (39%) (Table 2.4). 2.3.2 Household Durable Goods The survey also collected information on household effects, means of transportation, and ownership of agricultural land and farm animals. In general, urban households are more likely than rural households to possess household effects. The most commonly found item in all households is a mobile phone (56%); 88% of urban households and 47% of rural households own a mobile phone. As expected, rural households are more likely than urban households to own agricultural land and farm animals. One in five urban households own agricultural land, as compared with 86% of rural households (Table 2.5). 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 car, in addition to 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 her or his score, and then dividing the distribution into five equal categories, each comprising 20% of the population. Sample: Households Figure 2.2 Household toilet facilities by residence 6 16 4 9 35 2 53 43 56 32 7 39 Total Urban Rural Percent distribution of households by type of toilet facilities No facility/ bush/field Unimproved facility Shared facility Improved facility 12 • Housing Characteristics and Household Population Table 2.6 presents data on wealth quintiles according to urban-rural residence and region. The wealthiest households are concentrated in urban areas (89%). In contrast, approximately half of the rural population (46%) falls in the lowest two wealth quintiles (Figure 2.3). There are regional variations in wealth. The wealthiest households are concentrated in Addis Ababa (100%) and the poorest households in the Affar Region (74%). 2.5 HAND WASHING To obtain hand washing information, interviewers asked to see the place where members of the household most often wash their hands. Interviewers were able to see a place for hand washing in 60% of households (81% in urban areas and 55% in rural areas). Soap and water, the essential hand washing agents, were observed in 28% of urban households and 7% of rural households. Water, soap, and other cleaning agents were absent in 43% of urban households and 68% of rural households (Table 2.7). The availability of soap and water varies across regions, from a low of 5% in Amhara to a high of 39% in Addis Ababa. Soap and water availability increases with increasing wealth. Households in the highest wealth quintile are almost 9 times as likely to have soap and water as those in the lowest wealth quintile (26% versus 3%). 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 acknowledge one adult male or female as the head of the household, who share the same housekeeping arrangements, and who are considered a single unit. De facto population All persons who stayed in the selected households the night before the interview (whether usual residents or visitors). De jure population All persons who are usual residents of the selected households, whether or not they stayed in the household the night before the interview. How data are calculated All tables are based on the de facto population unless otherwise specified. Household composition and population data provide information on the socioeconomic characteristics of the households and respondents surveyed in terms of age, sex, educational status, household facilities, place of residence, and housing characteristics. Figure 2.3 Household wealth by residence 4 23 1 23 2 23 4 23 89 7 Urban Rural Percent distribution of de jure population by wealth quintiles Highest Fourth Middle Second Lowest Note: Values may not add up to 100% due to rounding. Housing Characteristics and Household Population • 13 A total of 75,551 individuals stayed overnight in the 16,650 interviewed households in the 2016 EDHS. About 51% of them (38,523) were female, and 49% (37,028) were male (Table 2.8). Children under age 15 (47%) and individuals age 15-64 (48%) each represent nearly half of the population, while 4% of Ethiopians are age 65 or older. The population pyramid in Figure 2.4 shows the population distribution by 5-year age groups, separately for males and females. The broad base of the pyramid indicates that Ethiopia’s population is young, which is typical of countries with low life expectancies and high fertility rates. The average household size in Ethiopia is 4.6 persons. Urban households are slightly smaller than rural households (3.5 persons versus 4.9 persons). Men head the majority of Ethiopian households (75%), with only 1 in 4 households headed by women (Table 2.9). Trends: The age distribution of the household population has not changed since 2011, when children under age 15 accounted for 47% of the population and individuals age 65 and older accounted for 4%. Average household size remained the same between 2011 and 2016 (4.6 persons in both surveys). The percentage of female-headed households also remained essentially the same during that period (26% in 2011 versus 25% in 2016). 2.7 CHILDREN’S LIVING ARRANGEMENTS AND PARENTAL SURVIVAL Orphan A child with one or both parents who are dead. Sample: Children under age 18 One in 10 children under age 18 are not living with a biological parent and 7% of these children are orphans, with one or both parents dead. The percentage of children who are orphans rises rapidly with age, from 2% among children under age 5 to 6% among children age 5-9 and 17% among children age 15-17. The Gambela Region has the highest percentage of children who are orphans (13%), while Tigray, Amhara, Oromiya, Benishangul-Gumuz, and Harari have the lowest percentages (7% each) (Table 2.10). Trends: The percentage of children under age 18 who do not live with a biological parent remained the same between 2011 and 2016 (11% and 10%, respectively). The percentage of children under age 18 who are orphans declined slightly, from 9% to 7%. 2.8 BIRTH REGISTRATION Registered birth Child has a birth certificate or child does not have a birth certificate, but his/her birth is registered with the civil authorities. Sample: De jure children under age 5 Figure 2.4 Population pyramid 20 15 10 5 0 5 10 15 20 <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 1520 10 5 14 • Housing Characteristics and Household Population Table 2.11 presents information on birth registration of children under age 5. At the time of the survey, 3% of children under age 5 were registered with the civil authorities. Two in three of these children have birth certificates. The percentage of children whose birth is registered is the same among children under age 2 and those between age 2 and 4 (3% each). Boys and girls are equally likely to have their births registered (3% each). However, children in urban areas are much more likely than rural children to have their births registered (12% versus 2%). Birth registration increases with increasing household wealth (from 1% in the lowest wealth quintile to 10% in the highest quintile) (Figure 2.5). Figure 2.6 depicts the proportion of children under age 5 whose births are registered by region. Children in Addis Ababa and Dire Dawa are much more likely to have their birth registered (24% and 19%, respectively) than children in other regions (5% or less). 2.9 EDUCATION Education is one of the most important aspects of social and economic development. Education improves capabilities and is strongly associated with various socioeconomic variables such as lifestyle, income, and fertility for both individuals and societies. 2.9.1 Educational Attainment Median educational attainment Half of the population has completed less than the median number of years of schooling, and half of the population has completed more than the median number of years of schooling. Sample: De facto household population age 6 and older Overall, 51% of females and 65% of males age 6 and over have ever attended school. For the majority of women, primary school is the highest level of schooling attended or completed; 40% of women have some primary education and 2% have completed primary education. Similarly, 50% of men have some primary education, and 3% have completed primary schooling. Only 4% of women and 5% of men have completed secondary school or gone beyond secondary school. Forty-nine percent of females and 35% of males have never attended school (Tables 2.12.1 and 2.12.2). Trends: Educational attainment at the household level has increased since 2000. The percentage of women with no education decreased from 77% in 2000 and 52% in 2011 to 49% in 2016, while the percentage of men with no education declined from 62% in 2000 and 38% in 2011 to 35% in 2016. Figure 2.5 Birth registration by household wealth Figure 2.6 Birth registration by region 1 1 2 2 10 Lowest Second Middle Fourth Highest Percentage of de jure children under age 5 whose births are registered with the civil authorities Poorest Wealthiest 1 1 1 2 2 2 3 3 5 19 24 Somali Benishangul-Gumuz Amhara Affar Tigray Oromiya Gambela SNNPR Harari Dire Dawa Addis Ababa Percentage of de jure children under age 5 whose births are registered with the civil authorities Housing Characteristics and Household Population • 15 Patterns by background characteristics  Urban residents are much more likely than rural residents to be educated. Twenty-four percent of females age 6 and older in urban areas have no education, as compared with 54% of females in rural areas. The corresponding proportions among males are 14% and 39%.  Addis Ababa has the lowest proportions of both females and males with no education (16% and 8%, respectively), while the Somali Region has the highest proportions (66% and 51%, respectively). 2.9.2 School Attendance Net attendance ratio (NAR) Percentage of the school-age population that attends primary or secondary school. Sample: Children age 7-14 for primary school NAR and children age 15-18 for secondary school NAR In Ethiopia, the primary school net attendance ratio (NAR) for the population age 7-14 is 71% (72% for girls and 71% for boys). The secondary school NAR drops drastically to 18% (Table 2.13). Patterns by background characteristics  There is a substantial difference in the primary school NAR between urban and rural areas (83% and 70%, respectively), and this difference increases at the secondary school level (42% in urban areas and 12% in rural areas).  Among regions, Gambela has the highest NAR at the primary school level (88%) and Addis Ababa has the highest NAR at the secondary school level (36%).  The NAR increases with increasing household wealth, especially at the secondary school level. The secondary school NAR rises from 6% in the lowest quintile to 36% in the highest quintile for girls and from 5% in the lowest quintile to 38% in the highest quintile for boys (Figure 2.7). 2.9.3 Other Measures of School Attendance Gross attendance ratios (GAR) The total number of children attending primary school divided by the official primary school-age population and the total number of children attending secondary school divided by the official secondary school-age population. Sample: Children age 7-14 for primary school GAR and children age 15-18 for secondary school GAR Gender parity index (GPI) The ratio of female to male students attending primary school and the ratio of female to male children attending secondary school. The index reflects the magnitude of the gender gap. Sample: Primary and secondary school students Figure 2.7 Secondary school attendance by household wealth 6 6 11 20 36 5 9 12 15 38 Lowest Second Middle Fourth Highest Net attendance ratio for secondary school among children age 15-18 Girls Boys WealthiestPoorest 16 • Housing Characteristics and Household Population The gross attendance ratio (GAR) is 91% (91% for girls and 92% for boys) at the primary school level and 30% (27% for girls and 32% for boys) at the secondary school level. Although the primary school GAR is 91%, there are differences in overage and/or underage participation in urban (103%) and rural areas (90%), as well as in Gambela (121%), Addis Ababa (114%), and Dire Dawa (102%). The figures indicate that a number of children outside the official school-age population for that level are attending primary school, and not all of those who should be attending secondary school are doing so (Table 2.13). A gender parity index (GPI) of 1 indicates parity or equality between male and female school participation ratios. 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. The GPI for the NAR is 1.01 at the primary school level, which indicates that there is relatively little difference in overall primary school attendance by girls and boys. However, the GPI for the NAR is 1.05 at the secondary school level, meaning that a higher proportion of females than males attend secondary school. In contrast, the GPI for the GAR at the secondary school level is less than 1 (0.85), which indicates that males outside of the official school-age population are more likely to attend school than their female counterparts. Patterns by background characteristics  The GPI for the NAR is 0.98 in urban primary schools and 1.01 in rural primary schools. Similarly, the GPI is 0.88 in urban secondary schools and 1.04 in rural secondary schools.  The GPI for the NAR at the primary school level is highest in the Amhara and Tigray Regions (1.08 each) and lowest in Benishangul-Gumuz (0.86). At the secondary school level, the GPI for the NAR is highest in Amhara (1.39) and lowest in Affar (0.27).  The primary school GPI for the NAR is highest in the middle and fourth wealth quintiles (1.04 each) and lowest in the lowest quintile (0.92). The secondary school GPI is highest in the fourth quintile (1.34) and lowest in the second quintile (0.69) (Table 2.13). Age-specific attendance rate (ASAR) Children attending school, irrespective of whether they are attending the appropriate grade for their age. Sample: De facto household population age 5-24 attending school Housing Characteristics and Household Population • 17 Age-specific attendance rates (ASARs) for the population age 5 to 24 are presented in Figure 2.8 by age and sex. The ASAR indicates participation in schooling at any level, from primary to higher levels of education. The trends are generally the same for males and females. Approximately 70% of children attend school by age 7. Between age 8 and age 13, more than 60% of children attend school. The attendance rate declines rapidly from age 16 to age 24, and in this age group ASARs are higher for males than females. 2.10 INJURY AND ACCIDENTS Injury is physical damage that results when a human body, intentionally or unintentionally, is subjected to intolerable levels of energy (Holder et al. 2001). It can be caused by traffic collisions, drowning, poisoning, falls or burns, or violence (e.g., assault, self-inflicted violence, or acts of war). According to WHO, injuries are becoming among the leading causes of global disease burden and represent a serious public health problem threatening future generations. For every death, dozens of hospitalizations, hundreds of emergency department visits, and thousands of doctors’ appointments are expected. A large proportion of people surviving their injuries also incur temporary or permanent disabilities (WHO 2014). In Ethiopia, information on injuries and accidents was collected for the first time in the 2016 EDHS. Table 2.14 shows that 3% of households reported having at least one member who was injured or killed in the 12 months before the survey. Among household members who were involved in an accident in the past 12 months, 89% survived and 10% died as a result of the accident (Table 2.15). With respect to length of injury, 27% of household members who were involved in an accident were unable to do their normal activities for less than 7 days, 31% stopped performing normal activities between 8 and 30 days, and 30% were unable to perform activities between 2 and 6 months (Table 2.16). Accidental falls and road traffic accidents accounted for the highest percentages of accidental injuries and deaths (28% and 23%, respectively). Animal bites, drowning, poisoning, and being kicked by cattle each accounted for less than 2% of injuries or deaths (Table 2.17). Patterns by background characteristics  There are no variations by residence in the percentage of households with at least one member injured or killed in an accident in the past 12 months (4% in urban areas and 3% in rural areas) (Table 2.14).  Among regions, Amhara has the highest percentage of households with at least one member injured or killed in an accident (4%), while Somali has the lowest percentage (1%) (Table 2.14).  Females and males were equally likely to have been injured or killed in a road traffic accident in the past 12 months (23% each). However, urban residents (32%) were more likely than rural residents (20%) to have been injured or killed in a road traffic accident (Table 2.17). Figure 2.8 Age-specific attendance rates for the de facto population age 5 to 24 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 Age in years Female Male Percentage of the de facto household population age 5-24 attending school 18 • Housing Characteristics and Household Population LIST OF TABLES For more 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 Household possessions  Table 2.6 Wealth quintiles  Table 2.7 Hand washing  Table 2.8 Household population by age, sex, and residence  Table 2.9 Household composition  Table 2.10 Children’s living arrangements and orphanhood  Table 2.11 Birth registration of children under age 5  Table 2.12.1 Educational attainment of the female household population  Table 2.12.2 Educational attainment of the male household population  Table 2.13 School attendance ratios  Table 2.14 Injury or death in an accident among household members  Table 2.15 Injury or death in an accident  Table 2.16 Length of injury  Table 2.17 Type of accident 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, person who usually collects drinking water, and treatment of drinking water, according to residence, Ethiopia DHS 2016 Households Population Characteristic Urban Rural Total Urban Rural Total Source of drinking water Improved source 97.3 56.5 64.8 96.9 55.1 61.6 Piped into dwelling/yard/plot 63.0 1.8 14.3 62.1 1.6 10.9 Piped to neighbour 12.3 1.1 3.4 11.1 0.8 2.4 Public tap/standpipe 13.1 18.9 17.7 13.4 18.6 17.8 Tube well or borehole 3.2 13.1 11.1 3.1 12.5 11.1 Protected dug well 1.5 7.0 5.9 2.3 7.1 6.4 Protected spring 3.3 13.9 11.7 4.1 13.8 12.3 Rainwater 0.0 0.7 0.5 0.0 0.7 0.6 Bottled water, improved source for drinking1 0.9 0.0 0.2 0.8 0.0 0.1 Unimproved source 2.7 43.4 35.1 3.1 44.8 38.3 Unprotected dug well 0.2 5.1 4.1 0.2 5.3 4.5 Unprotected spring 1.3 24.7 20.0 1.6 25.5 21.8 Tanker truck/cart with small tank 0.5 0.4 0.4 0.7 0.4 0.5 Surface water 0.7 13.2 10.7 0.6 13.5 11.5 Other source 0.0 0.1 0.1 0.0 0.1 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 76.8 5.6 20.1 74.6 5.0 15.8 Less than 30 minutes 10.2 41.7 35.3 11.0 41.0 36.4 30 minutes or longer 12.6 52.6 44.5 13.8 53.9 47.6 Don’t know/missing 0.4 0.2 0.2 0.6 0.1 0.2 Total 100.0 100.0 100.0 100.0 100.0 100.0 Person who usually collects drinking water Adult woman 16.6 68.2 57.7 17.9 67.8 60.1 Adult man 2.8 8.3 7.2 2.3 7.1 6.4 Female child under age 15 1.9 12.5 10.4 2.8 14.8 12.9 Male child under age 15 0.9 4.1 3.5 1.4 4.6 4.1 Other 1.0 1.3 1.2 1.1 0.7 0.8 Water on premises 76.8 5.6 20.1 74.6 5.0 15.8 Total 100.0 100.0 100.0 100.0 100.0 100.0 Water treatment prior to drinking3 Boiled 2.8 2.0 2.2 3.0 1.9 2.1 Bleach/chlorine added 6.5 2.6 3.4 6.7 2.6 3.2 Strained through cloth 0.7 2.3 2.0 0.7 2.4 2.2 Ceramic, sand, or other filter 1.7 0.9 1.1 2.1 1.0 1.2 Let stand and settle 0.0 0.4 0.4 0.0 0.4 0.4 Other 0.4 0.1 0.2 0.5 0.1 0.2 No treatment 88.4 92.1 91.3 87.5 92.1 91.4 Percentage using an appropriate treatment method4 10.5 5.5 6.5 11.3 5.4 6.3 Number 3,384 13,266 16,650 11,896 64,871 76,767 Note: Total includes a small number of households with solar disinfection as the water treatment method. 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 hand washing. 2 Includes water piped to a neighbour 3 Respondents may report multiple treatment methods, so the sum of treatment may exceed 100%. 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 lacking available water in the last 2 weeks, according to residence, Ethiopia DHS 2016 Households Population Availability of water in last 2 weeks Urban Rural Total Urban Rural Total Not available for at least one day 68.5 34.5 48.2 70.5 34.4 46.3 Available with no interruption of at least one day 30.3 65.1 51.1 28.8 65.2 53.2 Don’t know/missing 1.2 0.4 0.7 0.7 0.4 0.5 Total 100.0 100.0 100.0 100.0 100.0 100.0 Number using piped water or water from a tube well1 3,131 4,633 7,764 10,760 21,757 32,517 1 Includes households reporting piped water or water from a tube well or borehole as their main source of drinking water and households reporting bottled water as their main source of drinking water if their main source of water for cooking and hand washing is piped water or water from a tube well or borehole Table 2.3 Household sanitation facilities Percent distribution of households and de jure population by type of toilet/latrine facility and percent distribution of households and de jure population with a toilet/latrine facility by location of the facility, according to residence, Ethiopia DHS 2016 Type and location of toilet/latrine facility Households Population Urban Rural Total Urban Rural Total Improved 15.9 3.9 6.3 20.1 4.2 6.7 Flush/pour flush to piped sewer system 1.8 0.0 0.4 2.3 0.0 0.4 Flush/pour flush to septic tank 2.8 0.1 0.7 3.4 0.1 0.6 Flush/pour flush to pit latrine 1.4 0.4 0.6 1.8 0.5 0.7 Ventilated improved pit (VIP) latrine 0.4 0.0 0.1 0.6 0.0 0.1 Pit latrine with slab 9.4 2.3 3.8 11.9 2.6 4.1 Composting toilet 0.1 1.0 0.8 0.1 0.9 0.8 Unimproved sanitation 84.1 96.1 93.7 79.9 95.8 93.3 Shared facility1 34.6 1.8 8.5 30.9 1.4 6.0 Flush/pour flush to piped sewer system 0.5 0.0 0.1 0.5 0.0 0.1 Flush/pour flush to septic tank 1.7 0.0 0.3 1.5 0.0 0.2 Flush/pour flush to pit latrine 3.0 0.2 0.7 2.9 0.1 0.6 Ventilated improved pit (VIP) latrine 1.1 0.0 0.2 1.1 0.0 0.2 Pit latrine with slab 27.7 1.4 6.7 24.6 1.1 4.8 Composting toilet 0.5 0.2 0.2 0.4 0.1 0.2 Unimproved facility 42.7 55.6 52.9 42.2 56.6 54.4 Flush/pour flush not to sewer/septic tank/ pit latrine 0.8 0.0 0.2 0.8 0.1 0.2 Pit latrine without slab/open pit 40.5 55.2 52.2 40.1 56.3 53.8 Hanging toilet/hanging latrine 0.6 0.0 0.1 0.5 0.0 0.1 Other 0.8 0.3 0.4 0.8 0.2 0.3 Open defecation (no facility/bush/field) 6.9 38.8 32.3 6.8 37.7 32.9 Total 100.0 100.0 100.0 100.0 100.0 100.0 Number of households/population 3,384 13,266 16,650 11,896 64,871 76,767 Location of toilet facility In own dwelling 5.4 0.8 2.1 6.1 0.8 1.9 In own yard/plot 87.0 82.7 83.9 86.1 83.2 83.8 Elsewhere 7.6 16.4 14.0 7.9 16.0 14.3 Total 100.0 100.0 100.0 100.0 100.0 100.0 Number of households/population with a toilet/latrine facility 3,152 8,124 11,276 11,083 40,403 51,486 1 Facilities that would be considered improved if they were not shared by two or more households Housing Characteristics and Household Population • 21 Table 2.4 Household characteristics Percent distribution of households and de jure population by housing characteristics, percentage using solid fuel for cooking, and percent distribution by frequency of smoking in the home, according to residence, Ethiopia DHS 2016 Households Population Housing characteristic Urban Rural Total Urban Rural Total Electricity Yes 93.3 8.4 25.6 92.2 7.7 20.8 No 6.7 91.6 74.4 7.8 92.3 79.2 Total 100.0 100.0 100.0 100.0 100.0 100.0 Flooring material Earth, sand 22.9 54.7 48.2 23.2 55.5 50.5 Dung 9.1 39.1 33.0 9.2 38.2 33.7 Wood/planks 0.3 0.1 0.2 0.3 0.1 0.2 Palm/bamboo 0.8 1.7 1.5 1.1 1.8 1.7 Parquet or polished wood 1.1 0.1 0.3 1.3 0.1 0.3 Vinyl or asphalt strips 22.7 1.2 5.6 21.3 1.0 4.2 Ceramic tiles 4.1 0.1 0.9 4.9 0.1 0.8 Cement 16.1 1.6 4.5 17.3 1.6 4.1 Carpet 22.9 1.4 5.8 21.4 1.4 4.5 Total 100.0 100.0 100.0 100.0 100.0 100.0 Rooms used for sleeping One 65.2 71.6 70.3 52.5 66.6 64.4 Two 25.0 23.1 23.5 32.4 26.4 27.3 Three or more 9.4 5.2 6.1 14.9 7.0 8.2 Total 100.0 100.0 100.0 100.0 100.0 100.0 Place for cooking In the house 31.2 42.1 39.9 26.4 40.0 37.9 In a separate building 52.4 46.1 47.3 59.8 48.9 50.6 Outdoors 13.6 11.2 11.7 12.8 10.9 11.2 No food cooked in household 2.8 0.5 1.0 0.9 0.1 0.3 Other 0.1 0.2 0.1 0.1 0.1 0.1 Total 100.0 100.0 100.0 100.0 100.0 100.0 Cooking fuel Electricity 23.2 0.3 5.0 24.2 0.3 4.0 LPG/natural gas/biogas 1.3 0.3 0.5 1.1 0.3 0.5 Kerosene 2.1 0.0 0.5 1.3 0.0 0.2 Charcoal 30.2 2.1 7.8 27.8 1.5 5.6 Wood 38.7 85.6 76.1 42.5 86.9 80.0 Straw/shrubs/grass 0.0 0.5 0.4 0.0 0.5 0.4 Agricultural crop 0.3 2.2 1.8 0.4 2.1 1.9 Animal dung 1.3 8.3 6.9 1.7 8.2 7.2 No food cooked in household 2.8 0.5 1.0 0.9 0.1 0.3 Total 100.0 100.0 100.0 100.0 100.0 100.0 Percentage using solid fuel for cooking1 70.6 98.8 93.0 72.3 99.2 95.0 Frequency of smoking in the home Daily 4.4 6.2 5.8 5.2 6.8 6.6 Weekly 4.5 5.8 5.5 4.7 5.9 5.7 Monthly 0.8 0.3 0.4 0.6 0.3 0.4 Less than once a month 1.3 1.3 1.3 1.1 1.3 1.3 Never 89.1 86.4 87.0 88.5 85.7 86.1 Total 100.0 100.0 100.0 100.0 100.0 100.0 Number of households/population 3,384 13,266 16,650 11,896 64,871 76,767 Note: Total includes a small number of households with “other” types of flooring material and a small amount of missing data on number of rooms used for sleeping. LPG = Liquefied petroleum gas 1 Includes charcoal, wood, straw/shrubs/grass, agricultural crops, and animal dung 22 • Housing Characteristics and Household Population Table 2.5 Household possessions Percentage of households possessing various household effects, means of transportation, agricultural land, and livestock/farm animals by residence, Ethiopia DHS 2016 Residence Total Possession Urban Rural Household effects Radio 44.3 24.1 28.2 Television 59.4 2.1 13.8 Mobile phone 88.0 47.2 55.5 Watch 33.1 21.0 23.5 Computer 11.3 0.2 2.4 Non-mobile telephone 15.2 0.6 3.6 Refrigerator 24.4 0.4 5.3 Table 69.9 30.8 38.7 Chair 74.7 43.0 49.4 Bed with cotton/sponge/spring mattress 79.6 26.2 37.0 Electric mitad 26.7 0.4 5.7 Kerosene lamp/pressure lamp 3.9 8.1 7.2 Means of transport Bicycle 7.1 1.0 2.3 Animal-drawn cart 2.5 1.3 1.6 Motorcycle/scooter 2.5 0.8 1.1 Car/truck 3.3 0.2 0.8 Boat with a motor 0.2 0.2 0.2 Bagag 1.6 0.3 0.6 Ownership of agricultural land 20.1 86.1 72.7 Ownership of farm animals1 26.0 87.6 75.1 Number of households 3,384 13,266 16,650 1 Cows, bulls, other cattle, horses, donkeys, camels, goats, sheep, chickens or other poultry, or beehives Table 2.6 Wealth quintiles Percent distribution of the de jure population by wealth quintiles, and the Gini coefficient, according to residence and region, Ethiopia DHS 2016 Wealth quintile Total Number of persons Gini coefficient Residence/region Lowest Second Middle Fourth Highest Residence Urban 4.1 1.4 1.8 3.5 89.2 100.0 11,896 0.13 Rural 22.9 23.4 23.3 23.0 7.3 100.0 64,871 0.12 Region Tigray 29.1 21.0 15.8 10.3 23.9 100.0 5,091 0.44 Affar 74.2 2.2 1.6 2.1 20.0 100.0 622 0.54 Amhara 16.4 21.0 22.7 22.9 17.0 100.0 17,233 0.27 Oromiya 17.7 22.1 21.4 21.8 17.0 100.0 30,160 0.36 Somali 68.5 8.3 5.7 5.1 12.4 100.0 2,653 0.21 Benishangul-Gumuz 29.3 23.4 17.0 17.2 13.1 100.0 787 0.36 SNNPR 18.2 20.8 22.8 23.7 14.4 100.0 16,739 0.11 Gambela 36.3 9.8 8.4 11.3 34.2 100.0 202 0.41 Harari 9.1 15.1 10.9 10.5 54.4 100.0 180 0.39 Addis Ababa 0.0 0.0 0.0 0.1 99.9 100.0 2,714 0.05 Dire Dawa 18.6 11.1 6.2 3.5 60.7 100.0 384 0.35 Total 20.0 20.0 20.0 20.0 20.0 100.0 76,767 0.22 Housing Characteristics and Household Population • 23 Table 2.7 Hand washing Percentage of households in which the place most often used for washing hands was observed by whether the location was fixed or mobile and total percentage of households in which the place for hand washing 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, according to background characteristics, Ethiopia DHS 2016 Percentage of households in which place for washing hands was observed and: Number of households Among households where place for hand washing was observed, percentage with: Number of households in which place for hand washing was observed Background characteristic Place for hand washing was fixed Place for hand washing was mobile Total Soap and water1 Water and cleansing agent other than soap only2 Water only Soap but no water3 Cleansing agent other than soap only2 No water, no soap, no other cleansing agent Total Residence Urban 10.8 70.0 80.9 3,384 27.8 0.1 18.6 10.8 0.0 42.6 100.0 2,736 Rural 1.8 52.7 54.5 13,266 7.4 0.7 18.8 5.1 0.2 67.7 100.0 7,230 Region Tigray 6.0 45.2 51.2 1,186 17.3 0.0 16.6 10.0 0.1 56.0 100.0 607 Affar 1.3 34.4 35.7 140 16.6 0.0 18.4 11.7 0.2 53.0 100.0 50 Amhara 1.7 77.3 79.0 4,239 5.2 0.5 19.2 6.8 0.1 68.2 100.0 3,349 Oromiya 3.3 47.8 51.1 6,062 11.9 0.7 18.5 4.0 0.1 64.8 100.0 3,099 Somali 4.2 33.2 37.4 511 6.8 0.0 30.2 2.2 0.0 60.9 100.0 191 Benishangul- Gumuz 8.5 54.0 62.5 182 18.5 0.5 30.9 2.7 0.5 47.0 100.0 113 SNNPR 1.7 50.7 52.5 3,388 18.5 0.9 18.0 8.4 0.4 53.9 100.0 1,777 Gambela 3.6 57.4 61.0 50 12.6 0.3 14.0 7.2 0.1 65.8 100.0 31 Harari 5.5 26.3 31.8 46 21.0 0.0 34.2 6.7 0.0 38.0 100.0 15 Addis Ababa 21.0 70.7 91.7 751 38.9 0.0 16.6 11.8 0.0 32.6 100.0 689 Dire Dawa 4.1 44.1 48.2 95 13.1 0.6 16.7 5.6 0.1 63.8 100.0 46 Wealth quintile Lowest 1.2 38.4 39.6 3,202 3.2 0.2 18.2 4.8 0.2 73.4 100.0 1,268 Second 1.2 49.8 51.1 3,203 6.3 1.0 18.6 3.2 0.3 70.6 100.0 1,636 Middle 1.8 55.6 57.4 3,121 6.5 0.6 18.3 4.9 0.4 69.3 100.0 1,792 Fourth 2.1 62.3 64.4 3,084 9.6 0.9 20.8 5.4 0.0 63.3 100.0 1,986 Highest 10.0 71.3 81.3 4,040 25.8 0.3 18.0 10.7 0.0 45.0 100.0 3,284 Total 3.6 56.2 59.9 16,650 13.0 0.6 18.8 6.6 0.2 60.8 100.0 9,966 1 Soap includes soap or detergent in bar, liquid, powder, or paste form. This column includes households with soap and water only as well as those that had soap and water and another cleansing agent. 2 Cleansing agents other than soap include locally available materials such as ash, mud, or sand. 3 Includes households with soap only as well as those with soap and another cleansing agent Table 2.8 Household population by age, sex, and residence Percent distribution of the de facto household population by various age groups and percentage of the de facto household population age 10-19, according to sex and residence, Ethiopia DHS 2016 Urban Rural Male Female Total Age Male Female Total Male Female Total <5 11.8 9.5 10.6 16.0 15.0 15.5 15.4 14.1 14.7 5-9 11.9 8.8 10.2 18.5 17.3 17.9 17.5 15.9 16.7 10-14 12.1 12.0 12.0 17.9 15.1 16.5 17.0 14.6 15.8 15-19 11.1 13.5 12.4 8.2 8.6 8.4 8.7 9.4 9.0 20-24 8.2 10.8 9.6 5.7 7.0 6.4 6.1 7.7 6.9 25-29 11.1 12.3 11.8 5.8 7.2 6.5 6.6 8.1 7.3 30-34 8.4 7.8 8.0 5.0 5.9 5.5 5.5 6.2 5.9 35-39 5.9 6.5 6.2 4.5 5.1 4.8 4.7 5.3 5.0 40-44 4.7 3.8 4.2 3.7 3.4 3.6 3.9 3.4 3.7 45-49 3.4 2.8 3.1 2.8 2.6 2.7 2.9 2.6 2.8 50-54 2.5 3.8 3.2 1.8 4.2 3.0 1.9 4.2 3.1 55-59 1.9 2.4 2.2 1.5 2.8 2.2 1.6 2.7 2.2 60-64 2.7 2.2 2.5 3.1 1.9 2.5 3.0 2.0 2.5 65-69 1.7 1.3 1.4 2.0 1.2 1.6 2.0 1.2 1.6 70-74 1.0 1.1 1.1 1.3 1.2 1.3 1.3 1.2 1.2 75-79 0.7 0.6 0.6 0.8 0.5 0.6 0.7 0.5 0.6 80+ 0.9 0.7 0.8 1.3 0.8 1.0 1.2 0.8 1.0 Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 Dependency age groups 0-14 35.8 30.3 32.8 52.4 47.4 49.9 50.0 44.6 47.2 15-64 59.9 66.0 63.2 42.3 48.9 45.6 44.8 51.7 48.3 65+ 4.3 3.7 4.0 5.3 3.7 4.5 5.2 3.7 4.4 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 42.3 38.0 40.0 57.5 52.7 55.1 55.3 50.2 52.7 18+ 57.6 61.9 60.0 42.4 47.3 44.9 44.6 49.7 47.2 Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 Adolescents 10-19 23.1 25.5 24.4 26.1 23.7 24.9 25.7 24.0 24.8 Number of persons 5,337 6,355 11,691 31,691 32,169 63,860 37,028 38,523 75,551 24 • Housing Characteristics and Household Population Table 2.9 Household composition Percent distribution of households by sex of head of household and by household size, mean size of households, and percentage of households with orphans and foster children under age 18, according to residence, Ethiopia DHS 2016 Residence Total Characteristic Urban Rural Household headship Male 61.6 77.9 74.6 Female 38.4 22.1 25.4 Total 100.0 100.0 100.0 Number of usual members 0 0.1 0.1 0.1 1 17.9 4.9 7.5 2 18.8 9.7 11.6 3 18.5 14.7 15.4 4 15.4 17.0 16.7 5 13.1 15.9 15.3 6 7.9 14.4 13.1 7 3.8 11.1 9.6 8 2.1 6.3 5.5 9+ 2.4 6.1 5.3 Total 100.0 100.0 100.0 Mean size of households 3.5 4.9 4.6 Percentage of households with orphans and foster children under age 18 Double orphans 0.9 0.8 0.8 Single orphans1 9.1 9.5 9.4 Foster children2 19.3 17.3 17.7 Foster and/or orphan children 23.7 22.8 23.0 Number of households 3,384 13,266 16,650 Note: Table is based on de jure household members, i.e., usual residents. 1 Includes children with one dead parent and an unknown survival status of the other parent 2 Foster children are those under age 18 living in households with neither their mother nor their father present, and the mother and/or the father are alive. ` Housing Characteristics and Household Population • 25 Table 2.10 Children’s living arrangements and orphanhood Percent distribution of de jure children under age 18 by living arrangements and survival status of parents, percentage of children not living with a biological parent, and percentage of children with one or both parents dead, according to background characteristics, Ethiopia DHS 2016 Living with both parents Living with mother but not with father Living with father but not with mother Not living with either parent Total Percent- age not living with a bio- logical parent Percent- age with one or both parents dead1 Number of children Background characteristic Father alive Father dead Mother alive Mother dead Both alive Only father alive Only mother alive Both dead Missing infor- mation on father/ mother Age 0-4 82.2 11.6 1.3 1.2 0.1 3.1 0.2 0.1 0.1 0.1 100.0 3.5 1.8 11,144 <2 84.6 12.4 0.8 0.8 0.0 1.3 0.0 0.0 0.1 0.0 100.0 1.4 0.9 4,352 2-4 80.7 11.2 1.7 1.4 0.1 4.3 0.3 0.2 0.0 0.1 100.0 4.8 2.3 6,792 5-9 72.9 10.5 3.2 2.6 0.8 8.0 0.8 0.7 0.3 0.2 100.0 9.9 5.9 12,697 10-14 67.3 10.0 6.1 3.2 1.5 9.0 0.8 1.5 0.5 0.1 100.0 11.8 10.4 12,038 15-17 56.6 9.1 8.7 2.9 2.7 14.5 1.7 2.5 1.2 0.1 100.0 19.9 16.8 4,220 Sex Male 72.3 10.7 4.4 2.6 1.0 6.8 0.7 0.9 0.3 0.1 100.0 8.8 7.4 20,676 Female 71.8 10.3 3.8 2.2 1.0 8.5 0.8 1.1 0.4 0.1 100.0 10.8 7.0 19,422 Residence Urban 56.4 16.3 6.0 3.1 0.6 13.2 0.9 2.5 0.7 0.3 100.0 17.3 10.7 4,701 Rural 74.1 9.7 3.9 2.3 1.0 6.9 0.7 0.8 0.3 0.1 100.0 8.7 6.8 35,397 Region Tigray 70.3 15.5 4.2 1.3 0.7 5.5 0.8 1.0 0.3 0.2 100.0 7.7 7.1 2,558 Affar 62.5 20.1 4.9 2.6 0.7 6.6 1.2 1.2 0.2 0.0 100.0 9.2 8.2 340 Amhara 75.0 8.1 3.4 2.9 1.3 7.0 1.0 1.0 0.3 0.1 100.0 9.3 7.0 8,094 Oromiya 74.0 9.3 4.3 2.3 0.8 7.6 0.5 0.8 0.3 0.1 100.0 9.2 6.8 16,755 Somali 62.3 19.6 5.0 2.5 1.5 6.8 1.1 0.9 0.3 0.1 100.0 9.1 8.8 1,657 Benishangul- Gumuz 75.4 10.4 4.0 3.4 1.5 3.7 0.6 0.8 0.2 0.0 100.0 5.3 7.1 422 SNNPR 70.7 10.6 4.2 2.7 1.1 8.3 0.7 1.2 0.4 0.1 100.0 10.6 7.6 9,072 Gambela 50.5 22.1 8.6 4.4 0.7 9.6 0.6 2.1 1.4 0.0 100.0 13.6 13.4 101 Harari 72.2 10.2 4.8 2.2 0.5 8.3 0.5 0.8 0.5 0.0 100.0 10.1 7.1 86 Addis Ababa 51.3 17.9 4.1 2.3 1.0 17.3 1.5 2.6 1.3 0.8 100.0 22.7 10.5 835 Dire Dawa 63.0 12.6 5.0 2.6 0.8 11.8 1.2 1.9 0.7 0.4 100.0 15.6 9.6 176 Wealth quintile Lowest 69.5 12.7 5.2 2.4 1.0 6.6 1.0 1.2 0.3 0.1 100.0 9.1 8.8 8,873 Second 77.2 9.3 3.2 1.8 0.9 6.1 0.6 0.5 0.3 0.1 100.0 7.5 5.5 8,476 Middle 75.5 8.9 3.8 2.7 1.1 6.3 0.6 0.6 0.4 0.0 100.0 8.0 6.5 8,276 Fourth 73.5 8.8 4.3 2.5 1.0 7.8 0.5 1.1 0.4 0.1 100.0 9.7 7.3 7,999 Highest 62.8 13.2 4.0 2.9 0.9 12.7 0.9 1.8 0.5 0.3 100.0 15.9 8.1 6,473 Total <15 73.9 10.7 3.6 2.4 0.8 6.8 0.6 0.8 0.3 0.1 100.0 8.5 6.1 35,878 Total <18 72.1 10.5 4.1 2.4 1.0 7.6 0.7 1.0 0.4 0.1 100.0 9.7 7.2 40,098 Note: Table is based on de jure household 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 26 • Housing Characteristics and Household Population Table 2.11 Birth registration of children under age 5 Percentage of de jure children under age 5 whose births are registered with the civil authorities, according to background characteristics, Ethiopia DHS 2016 Percentage of children whose births are registered and who: Total percentage of children whose births are registered Number of children Background characteristic Had a birth certificate Did not have a birth certificate Age <2 1.6 1.0 2.6 4,352 2-4 1.7 1.1 2.7 6,792 Sex Male 1.8 0.9 2.7 5,711 Female 1.5 1.2 2.6 5,433 Residence Urban 9.2 2.3 11.5 1,219 Rural 0.7 0.9 1.6 9,925 Region Tigray 1.8 0.2 2.0 737 Affar 1.6 0.1 1.6 113 Amhara 0.8 0.5 1.3 2,157 Oromiya 1.1 1.0 2.1 4,816 Somali 0.9 0.1 1.0 500 Benishangul-Gumuz 0.9 0.1 1.0 124 SNNPR 1.6 1.7 3.4 2,364 Gambela 1.6 1.0 2.5 28 Harari 3.9 1.1 5.0 25 Addis Ababa 20.1 4.1 24.2 233 Dire Dawa 12.3 6.3 18.5 48 Wealth quintile Lowest 0.6 0.1 0.8 2,672 Second 0.3 1.2 1.4 2,566 Middle 0.9 1.5 2.4 2,320 Fourth 0.9 0.7 1.6 1,986 Highest 7.4 2.1 9.5 1,600 Total 1.6 1.0 2.7 11,144 Housing Characteristics and Household Population • 27 Table 2.12.1 Educational attainment of the female household population Percent distribution of the de facto female household population age 6 and over by highest level of schooling attended or completed and median years completed, according to background characteristics, Ethiopia DHS 2016 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 54.2 45.8 0.0 0.0 0.0 0.0 0.0 100.0 5,206 0.0 10-14 14.8 84.0 0.3 0.9 0.0 0.0 0.0 100.0 5,621 1.9 15-19 13.6 57.7 5.7 19.7 0.7 2.4 0.1 100.0 3,623 5.0 20-24 27.8 39.8 3.5 17.4 0.7 10.8 0.0 100.0 2,954 4.0 25-29 48.6 29.5 2.6 9.5 1.2 8.6 0.1 100.0 3,113 0.2 30-34 69.6 19.0 1.4 3.7 1.4 4.8 0.0 100.0 2,406 0.0 35-39 70.0 19.6 2.0 3.2 2.3 2.9 0.0 100.0 2,049 0.0 40-44 70.7 19.5 1.6 2.6 2.8 2.7 0.0 100.0 1,327 0.0 45-49 75.2 16.4 2.3 1.7 1.6 2.8 0.0 100.0 1,021 0.0 50-54 87.7 8.4 0.6 0.8 1.0 1.4 0.0 100.0 1,601 0.0 55-59 91.7 6.4 0.2 0.3 0.4 0.8 0.2 100.0 1,058 0.0 60-64 94.1 5.0 0.1 0.1 0.3 0.3 0.0 100.0 767 0.0 65+ 97.2 2.2 0.0 0.2 0.1 0.2 0.1 100.0 1,420 0.0 Residence Urban 24.1 36.9 4.0 16.9 3.9 14.0 0.2 100.0 5,679 4.9 Rural 54.4 40.6 1.2 3.2 0.1 0.6 0.0 100.0 26,501 0.0 Region Tigray 44.2 39.9 2.0 9.8 0.5 3.5 0.0 100.0 2,167 0.4 Affar 61.8 32.1 2.1 2.4 0.1 1.5 0.0 100.0 249 0.0 Amhara 52.3 36.9 0.9 6.4 0.3 3.0 0.1 100.0 7,311 0.0 Oromiya 51.5 40.2 2.0 3.8 0.7 1.8 0.0 100.0 12,200 0.0 Somali 66.3 29.6 0.7 2.0 0.2 1.1 0.0 100.0 1,075 0.0 Benishangul-Gumuz 46.5 44.0 0.9 5.0 0.2 3.3 0.1 100.0 326 0.0 SNNPR 47.0 44.6 1.2 4.8 0.3 2.0 0.0 100.0 7,121 0.0 Gambela 30.7 46.8 2.4 12.4 0.7 6.8 0.1 100.0 84 2.0 Harari 40.2 39.0 3.3 7.7 2.3 7.4 0.0 100.0 81 1.1 Addis Ababa 16.3 37.4 5.2 16.6 6.5 17.7 0.4 100.0 1,392 6.5 Dire Dawa 37.9 41.5 4.0 9.3 2.2 5.2 0.0 100.0 174 1.5 Wealth quintile Lowest 67.0 31.1 0.6 1.1 0.0 0.2 0.0 100.0 6,155 0.0 Second 57.7 39.5 0.8 1.7 0.0 0.3 0.1 100.0 6,161 0.0 Middle 52.7 42.9 1.2 2.7 0.0 0.4 0.0 100.0 6,315 0.0 Fourth 45.3 46.3 1.5 5.6 0.1 1.2 0.0 100.0 6,509 0.0 Highest 25.9 39.6 4.0 15.5 3.3 11.6 0.1 100.0 7,041 4.3 Total 49.1 39.9 1.7 5.6 0.8 3.0 0.0 100.0 32,180 0.0 Note: Total includes 14 weighted cases with missing information on age. 1 Completed 8th grade at the primary level 2 Completed 4th grade at the secondary level 28 • Housing Characteristics and Household Population Table 2.12.2 Educational attainment of the male household population Percent distribution of the de facto male household population age 6 and over by highest level of schooling attended or completed and median years completed, according to background characteristics, Ethiopia DHS 2016 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 52.6 47.4 0.0 0.0 0.0 0.0 0.0 100.0 5,461 0.0 10-14 14.8 83.6 0.6 1.0 0.0 0.0 0.1 100.0 6,313 1.7 15-19 7.9 65.3 6.5 18.4 0.1 1.7 0.1 100.0 3,205 5.1 20-24 14.8 46.7 6.0 22.1 1.0 9.3 0.1 100.0 2,249 5.5 25-29 20.8 36.5 5.9 19.7 1.3 15.5 0.4 100.0 2,434 5.8 30-34 37.2 34.9 3.0 11.4 2.2 10.8 0.5 100.0 2,024 2.5 35-39 40.3 39.1 3.9 6.1 2.1 7.7 0.7 100.0 1,752 2.0 40-44 45.8 35.1 5.1 4.7 3.3 5.9 0.1 100.0 1,435 1.2 45-49 46.6 37.3 2.6 5.1 1.8 6.3 0.3 100.0 1,084 1.1 50-54 47.9 33.1 2.6 4.3 3.2 8.0 1.0 100.0 715 0.5 55-59 62.6 21.8 2.6 4.6 0.4 8.0 0.0 100.0 579 0.0 60-64 73.6 18.8 1.1 2.7 1.1 2.7 0.1 100.0 1,118 0.0 65+ 84.5 11.7 1.1 1.1 0.4 1.2 0.0 100.0 1,920 0.0 Residence Urban 13.6 37.4 4.3 19.1 4.0 21.1 0.4 100.0 4,598 6.8 Rural 39.1 51.7 2.4 5.1 0.3 1.3 0.2 100.0 25,701 0.5 Region Tigray 33.8 50.5 2.3 8.5 0.5 4.1 0.3 100.0 1,884 1.7 Affar 48.2 39.1 3.2 5.4 0.8 3.1 0.2 100.0 220 0.0 Amhara 43.4 43.6 1.6 6.6 0.4 4.1 0.3 100.0 6,852 0.3 Oromiya 34.4 51.7 3.4 6.5 0.7 3.2 0.1 100.0 12,050 0.9 Somali 51.0 37.2 2.9 4.7 0.5 3.4 0.2 100.0 956 0.0 Benishangul-Gumuz 29.6 54.5 1.4 7.8 0.4 6.0 0.3 100.0 300 1.7 SNNPR 31.2 56.2 2.2 7.0 0.4 3.0 0.0 100.0 6,695 1.5 Gambela 20.5 50.5 3.0 10.3 1.5 14.0 0.1 100.0 78 3.9 Harari 24.8 40.9 5.1 12.6 3.4 13.0 0.1 100.0 68 3.8 Addis Ababa 8.2 31.1 4.9 21.0 8.5 25.6 0.8 100.0 1,042 8.4 Dire Dawa 23.1 44.0 5.3 13.4 4.1 10.0 0.3 100.0 154 3.8 Wealth quintile Lowest 51.6 44.5 1.3 2.1 0.0 0.3 0.2 100.0 5,771 0.0 Second 42.6 50.9 2.4 3.3 0.1 0.5 0.1 100.0 5,909 0.1 Middle 38.0 53.4 2.2 5.4 0.2 0.7 0.1 100.0 6,074 0.7 Fourth 31.0 55.2 3.0 8.0 0.3 2.3 0.1 100.0 6,359 1.6 Highest 14.6 43.0 4.5 16.9 3.4 17.3 0.3 100.0 6,185 5.7 Total 35.2 49.5 2.7 7.2 0.8 4.3 0.2 100.0 30,299 1.1 Note: Total includes 11 weighted cases with missing information on age. 1 Completed 8th grade at the primary level 2 Completed 4th grade at the secondary level Housing Characteristics and Household Population • 29 Table 2.13 School attendance ratios Net attendance ratios (NAR) and gross attendance ratios (GAR) for the de facto household population by sex and level of schooling, and the gender parity index (GPI), according to background characteristics, Ethiopia DHS 2016 Net attendance ratio1 Gross attendance ratio2 Background characteristic Male Female Total Gender parity index3 Male Female Total Gender parity index3 PRIMARY SCHOOL Residence Urban 83.9 82.3 83.1 0.98 102.7 102.3 102.5 1.00 Rural 69.5 70.2 69.8 1.01 90.2 89.5 89.9 0.99 Region Tigray 77.1 83.2 79.9 1.08 98.4 100.4 99.3 1.02 Affar 61.1 62.0 61.5 1.02 87.4 88.7 88.0 1.02 Amhara 72.7 78.6 75.6 1.08 95.7 95.5 95.6 1.00 Oromiya 67.4 66.1 66.8 0.98 86.9 83.8 85.5 0.96 Somali 62.1 56.2 59.2 0.90 78.1 75.0 76.6 0.96 Benishangul-Gumuz 83.0 71.0 76.9 0.86 107.3 91.4 99.2 0.85 SNNPR 74.3 73.3 73.8 0.99 94.4 97.1 95.7 1.03 Gambela 87.1 89.1 88.1 1.02 122.8 119.4 121.1 0.97 Harari 76.6 72.5 74.5 0.95 90.1 86.4 88.2 0.96 Addis Ababa 89.4 85.1 87.0 0.95 108.8 118.5 114.2 1.09 Dire Dawa 79.5 71.5 75.6 0.90 108.6 94.4 101.7 0.87 Wealth quintile Lowest 58.8 54.1 56.6 0.92 77.1 68.1 72.9 0.88 Second 66.3 68.2 67.2 1.03 84.2 84.9 84.6 1.01 Middle 73.3 75.9 74.6 1.04 94.2 96.0 95.1 1.02 Fourth 75.9 78.9 77.3 1.04 101.7 103.9 102.8 1.02 Highest 84.0 83.7 83.9 1.00 103.0 105.5 104.2 1.02 Total 71.0 71.6 71.3 1.01 91.5 91.1 91.3 0.99 SECONDARY SCHOOL Residence Urban 44.5 39.3 41.5 0.88 71.3 56.8 62.7 0.80 Rural 11.5 11.9 11.7 1.04 23.4 18.3 20.7 0.78 Region Tigray 20.5 26.1 23.7 1.27 37.0 37.3 37.2 1.01 Affar 27.0 7.2 14.9 0.27 47.4 13.7 26.7 0.29 Amhara 15.3 21.2 18.2 1.39 26.5 33.1 29.7 1.25 Oromiya 15.0 15.5 15.3 1.03 27.9 21.2 24.4 0.76 Somali 26.3 10.1 18.0 0.39 43.4 14.0 28.3 0.32 Benishangul-Gumuz 20.6 16.9 18.6 0.82 34.4 24.0 28.6 0.70 SNNPR 17.6 15.3 16.4 0.87 37.3 27.0 31.9 0.72 Gambela 21.4 24.9 23.1 1.17 43.6 48.9 46.2 1.12 Harari 43.2 27.8 34.7 0.64 65.9 37.8 50.4 0.57 Addis Ababa 46.5 31.7 36.3 0.68 67.4 40.6 49.0 0.60 Dire Dawa 32.5 26.8 29.2 0.82 55.6 36.2 44.2 0.65 Wealth quintile Lowest 5.4 5.7 5.5 1.05 12.2 8.8 10.4 0.72 Second 8.7 6.0 7.2 0.69 21.1 10.1 15.0 0.48 Middle 12.2 10.9 11.6 0.89 25.0 15.0 19.8 0.60 Fourth 15.1 20.2 17.6 1.34 30.8 30.1 30.5 0.98 Highest 38.1 35.9 36.9 0.94 59.8 53.2 56.0 0.89 Total 17.6 18.4 18.1 1.05 32.3 27.4 29.7 0.85 1 The NAR for primary school is the percentage of the primary school-age (7-14 years) population that is attending primary school. The NAR for secondary school is the percentage of the secondary school-age (15-18 years) population that is attending secondary school. By definition, the NAR cannot exceed 100%. 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%. 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. 30 • Housing Characteristics and Household Population Table 2.14 Injury or death in an accident among household members Percentage of households with at least one member injured or killed in an accident in the past 12 months, according to background characteristics, Ethiopia DHS 2016 Background characteristic Percentage of households with at least one member injured or killed in an accident Total number of households Residence Urban 3.6 3,384 Rural 3.1 13,266 Region Tigray 3.0 1,186 Affar 3.1 140 Amhara 4.0 4,239 Oromiya 3.3 6,062 Somali 1.2 511 Benishangul-Gumuz 2.9 182 SNNPR 2.7 3,388 Gambela 2.8 50 Harari 1.7 46 Addis Ababa 2.5 751 Dire Dawa 3.1 95 Wealth quintile Lowest 2.1 3,202 Second 3.3 3,203 Middle 3.8 3,121 Fourth 3.2 3,084 Highest 3.6 4,040 Total 3.2 16,650 Table 2.15 Injury or death in an accident Percent distribution of household members injured or killed in an accident in the past 12 months, according to background characteristics, Ethiopia DHS 2016 Result of accident Total Number of household members injured or killed in an accident Background characteristic Injured and still alive Died because of accident Died of different cause Sex Male 89.1 10.0 0.9 100.0 360 Female 88.4 9.1 2.5 100.0 188 Residence Urban 83.7 13.7 2.5 100.0 123 Rural 90.3 8.6 1.1 100.0 425 Region Tigray 89.2 10.8 0.0 100.0 37 Affar 56.5 41.1 (2.4) 100.0 5 Amhara 89.9 8.3 1.8 100.0 172 Oromiya 89.4 9.2 1.4 100.0 204 Somali 62.3 37.7 (0.0) 100.0 7 Benishangul-Gumuz 100.0 0.0 (0.0) 100.0 5 SNNPR 89.2 9.1 1.7 100.0 92 Gambela 45.9 53.6 0.6 100.0 2 Harari 95.7 4.3 * 100.0 1 Addis Ababa 89.2 10.8 (0.0) 100.0 19 Dire Dawa 94.2 5.8 (0.0) 100.0 3 Wealth quintile Lowest 86.8 13.0 0.2 100.0 68 Second 90.2 9.8 0.0 100.0 112 Middle 89.6 7.9 2.5 100.0 119 Fourth 91.9 6.5 1.6 100.0 99 Highest 86.2 11.8 2.1 100.0 149 Total 88.8 9.7 1.4 100.0 547 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. Housing Characteristics and Household Population • 31 Table 2.16 Length of injury Percentage of household members injured in an accident in the past 12 months by length of time they were unable to carry out normal daily activities, according to background characteristics, Ethiopia DHS 2016 Length of time unable to carry out normal daily activities Total Number of household members injured and alive Background characteristic Less than 7 days Between 8 and 30 days Between 2 and 6 months Longer than 6 months Don’t know Age 0-9 32.1 28.1 25.5 9.8 4.6 100.0 85 10-19 36.3 38.6 18.2 6.9 0.0 100.0 70 20-39 30.0 32.2 30.6 6.7 0.5 100.0 172 40-59 14.6 24.0 43.9 17.5 0.0 100.0 104 60+ 17.4 31.3 24.1 22.7 4.4 100.0 56 Sex Male 28.5 29.2 31.4 10.6 0.2 100.0 320 Female 22.7 33.1 27.4 12.9 3.9 100.0 166 Residence Urban 35.3 32.6 23.1 6.0 2.9 100.0 103 Rural 24.2 30.0 31.9 12.8 1.1 100.0 384 Wealth quintile Lowest 9.9 35.9 41.1 11.7 1.4 100.0 59 Second 28.1 31.1 22.3 18.5 0.0 100.0 101 Middle 29.6 25.5 36.0 8.8 0.0 100.0 106 Fourth 27.0 23.8 33.3 12.3 3.6 100.0 91 Highest 30.1 36.6 23.7 7.2 2.3 100.0 129 Total 26.6 30.5 30.0 11.4 1.5 100.0 486 Table 2.17 Type of accident Percentage of household members injured or killed in an accident in the past 12 months by type of accident, according to background characteristics, Ethiopia DHS 2016 Type of accident Total Number of house- hold members injured or killed Background characteristic Road traffic accident Violence/ assault Fire/ burning Animal bite Accidental fall Drowning Poisoning Kicked by cattle Fall from tree/ building Other Don’t know Sex Male 22.7 19.3 7.1 1.5 25.4 0.6 1.3 0.8 7.9 12.6 0.7 100.0 360 Female 23.2 4.2 12.0 2.6 33.7 3.4 3.2 3.4 1.7 10.4 2.2 100.0 188 Residence Urban 32.0 6.4 4.8 0.5 31.6 3.3 4.7 0.0 1.0 12.4 3.4 100.0 123 Rural 20.3 16.4 9.9 2.3 27.2 1.1 1.1 2.2 7.2 11.8 0.6 100.0 425 Wealth quintile Lowest 20.7 13.4 10.5 7.7 29.1 0.0 0.3 4.1 5.2 9.0 0.0 100.0 68 Second 19.8 7.1 12.8 0.9 34.6 4.0 2.4 0.0 14.9 3.4 0.1 100.0 112 Middle 10.7 28.6 12.2 2.9 19.9 0.0 0.4 5.5 0.5 19.4 0.0 100.0 119 Fourth 29.8 19.6 3.6 0.0 23.0 0.1 0.0 0.1 9.8 11.5 2.5 100.0 99 Highest 31.2 4.7 5.6 0.4 33.1 2.7 4.8 0.0 0.8 13.9 2.8 100.0 149 Total 22.9 14.1 8.7 1.9 28.2 1.6 1.9 1.7 5.8 11.9 1.2 100.0 547 Characteristics of Respondents • 33 CHARACTERISTICS OF RESPONDENTS 3 Key Findings  Education: The percentage of women with no education decreased from 66% in 2005 and 51% in 2011 to 48% in 2016. Among men, the percentage declined from 43% in 2005 to 28% in 2016.  Literacy: Four in 10 (42%) women and 69% of men age 15-49 are literate.  Exposure to mass media: Nearly three in four (74%) women and 62% of men have no access to radio, television, or newspapers on a weekly basis.  Internet usage: Five percent of women and 13% of men have ever used the Internet.  Employment: One in three (33%) women and 88% of men were employed in the 7 days preceding the survey. Half of women and 8% of men had not been employed in the past 12 months.  Health insurance: Health insurance coverage is extremely low; 95% of women and 94% of men are not covered by any type of health insurance.  Tobacco use: Cigarette smoking is rare; less than 1% of women and 4% of men smoke any type of tobacco.  Chewing chat: Twelve percent of women and 27% of men have ever chewed chat. Among chat chewers, two in three chewed for 6 or more days in the last 30 days. his chapter presents information on demographic and socioeconomic characteristics of the survey respondents such as sex, age, religion, ethnic group, education, and wealth status. The survey also collected data on use of mass media and the Internet, health insurance coverage, tobacco smoking, alcohol consumption, and chat chewing. This information is useful in understanding the factors that affect use of reproductive health services, contraceptive use, and other health behaviours. 3.1 BASIC BACKGROUND CHARACTERISTICS OF SURVEY RESPONDENTS Table 3.1 shows the percent distribution of women and men age 15-49 by background characteristics. The majority of women and men are under age 30 (58% of women and 55% of men). In general, for both sexes the percentage of the population in each age group steadily decreases as age increases, reflecting the comparatively young age structure, which is a result of high fertility in past decades. The main religions in Ethiopia are Orthodox Christianity (43% of women and 45% of men) and Muslim (31% each of women and men). Twenty-three percent of women and 22% of men are Protestants. T 34 • Characteristics of Respondents The largest ethnic group is Oromo (34% of women and 36% of men), followed by Amhara (30% each of women and men). While there are more than 80 ethnic groups in Ethiopia, most are small in percentage compared with the above two groups. The proportion of women who are currently married or living together with a partner is higher than that among men (65% versus 56%). Women are less likely than men to have never been married (26% versus 42%) and more likely to be divorced or separated (6% versus 2%). A person’s place of residence, whether rural or urban, determines her or his access to services and information about health and other aspects of life. Eight in 10 respondents live in rural areas (78% of women and 80% of men). Eight in 10 women and 84% of men live in three major regions: Amhara, Oromiya, and the Southern Nations Nationalities and Peoples’ Region (SNNPR). Nearly half of women age 15-49 (48%) have no education, as compared with 28% of men. 3.2 EDUCATION AND LITERACY Literacy Respondents who had attended higher than secondary school were assumed to be literate. All other respondents were given a sentence to read, and they were considered literate if they could read all or part of the sentence. Sample: Women and men age 15-49 Education is an important factor influencing an individual’s attitudes and opportunities. Tables 3.2.1 and 3.2.2 show that men are better educated than women. About half of women (48%) and 28% of men age 15-49 have no formal education. Three percent of women and 5% of men have completed primary school, while 1% of women and men have a secondary education. Six percent of women and 9% of men have more than a secondary education (Figure 3.1). Trends: The percentage of women with no education has decreased over the last decade, from 66% in 2005 and 51% in 2011 to 48% in 2016. The percentage of men with no education has declined as well, from 43% in 2005 to 30% in 2011 and 28% in 2016. Patterns by background characteristics  The percentage of women with no education increases steadily by age group, from 14% among women age 15-19 to 79% among those age 45-49, suggesting an improvement in women’s education over time.  Education in urban areas is better than in rural areas; 57% of rural women have no formal education, as compared with 16% of urban women. The urban-rural difference is more pronounced at the secondary or higher levels of education. For example, only 1% of women in rural areas have more than a secondary education, compared with 21% of urban women. Figure 3.1 Education of survey respondents 48 28 32 44 3 5 10 14 1 1 6 9 Women Men Percent distribution of women and men age 15-49 by highest level of schooling attended or completed More than secondary Completed secondary Some secondary Primary complete Primary incomplete No education Note: Values may not add up to 100% due to rounding. Characteristics of Respondents • 35  Educational attainment varies across regions. The highest proportions of women with no education are in Somali and Affar (75% and 69%, respectively) and the lowest in Addis Ababa (9%) (Figure 3.2).  Educational attainment also varies by wealth quintile. Seventy-four percent of women in the lowest wealth quintile have no education, as compared with 19% of women in the highest quintile. Similarly, less than 1% of women in the lowest wealth quintile have more than a secondary education, compared with 18% of those in the highest quintile.  There are wide variations by place of residence in median number of years of education completed. Urban women have completed a median of 7.7 years of education, while the median among rural women is 0.0. The corresponding figures among men are 9.3 and 2.9 years.  Median number of years of education is highest among women in Addis Ababa (8.1 years) and lowest among women in Affar, Amhara, Oromiya, and Somali (0.0 years).  Men are much more literate than women. Two in three men (69%) men are literate, as compared with 42% of women (Tables 3.3.1 and 3.3.2). 3.3 MASS MEDIA EXPOSURE 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. Exposure to the Internet The Internet is a global communication network that allows almost all computers worldwide to connect and exchange information. Respondents were asked to report the frequency of their use of the Internet. Sample: Women and men age 15-49 Tables 3.4.1 and 3.4.2 show the percentage of women and men who are exposed to different types of media, by background characteristics. The level of exposure to mass media is low in Ethiopia. Among both women and men, radio was the most frequently accessed form of media in the past week (17% and 29%, respectively), followed by television (16% and 21%, respectively). Because of the low literacy rate, print Figure 3.2 Secondary education by region 7 8 8 10 10 10 12 24 26 28 44 4 6 5 7 3 2 6 12 14 16 32 SNNPR Amhara Oromiya Tigray Affar Somali Benishangul-Gumuz Dire Dawa Gambela Harari Addis Ababa Percentage of women and men age 15-49 with secondary education completed or higher Women Men 36 • Characteristics of Respondents media are not popular among either women (4%) or men (9%). The majority of respondents have no access to any of the three media at least once a week (74% of women and 62% of men) (Figure 3.3). The Internet is also a critical tool through which information is accessed. Overall, 4% of women and 12% of men age 15-49 have used the Internet in the past 12 months (Tables 3.5.1 and 3.5.2). Trends: Since 2011, women’s and men’s exposure to mass media has changed. For example, the proportion of women who listen to the radio at least once a week has decreased from 22% to 17%. Among men, the proportion has declined from 38% to 29%. Patterns by background characteristics  Urban women are five times more likely than rural women to read a newspaper at least once a week. The urban-rural gap is more evident in television viewing; 61% of urban women watch television at least once a week, as compared with 3% of rural women.  Among women, exposure to media increases with increasing education. For example, 20% of women with more than a secondary education read a newspaper at least once a week, as compared with 4% of women with a primary education.  Exposure to mass media also increases with wealth. Only 1% of women in the lowest wealth quintile read a newspaper at least once a week, compared with 10% of women in the highest quintile.  Men are slightly more likely than women to use the Internet on a daily basis; 36% of men report that they used the Internet nearly every day in the past month, compared with 34% of women.  Internet usage increases as level of education increases. For example, 5% of men with a primary education and 68% of men with more than a secondary education have ever used the Internet. 3.4 EMPLOYMENT Currently employed Respondents who were employed in the 7 days before the survey; includes persons who did not work in the past 7 days but who are regularly employed and were absent from work for leave, illness, vacation, or any other such reason. Sample: Women and men age 15-49 In the 2016 EDHS, respondents were asked whether they were employed at the time of the survey (that is, had worked in the past 7 days) and, if not, whether they had worked at any time during the 12 months preceding the survey. Tables 3.6.1 and 3.6.2 show that 33% of women and 88% of men are currently employed. An additional 17% of women and 4% of men reported that they had worked in the past 12 months but were not currently employed. Trends: Current employment among women age 15-49 increased from 29% in 2005 to 38% in 2011 but decreased to 33% in 2016. The percentage of men who are currently employed has shown a slight increase since 2005, from 85% to 88%. Figure 3.3 Exposure to mass media 4 16 17 1 74 9 21 29 5 62 Reads newspaper Watches television Listens to radio All three media None of these media Percentage of women and men age 15-49 who are exposed to media on a weekly basis Women Men Characteristics of Respondents • 37 Patterns by background characteristics  Divorced, separated, or widowed women are more likely to be employed than those who are currently married and those who have never been married. Among men, those who are currently married or divorced, separated, or widowed are more likely to be employed than those who have never been married.  There are notable variations in the proportion of currently employed women and men by place of residence. Urban women are more likely than rural women to be employed (52% versus 28%). Conversely, urban men are less likely to be employed than rural men (81% versus 90%) (Figure 3.4).  The percentage of women who are currently employed increases with increasing education, from 29% among women with no education to 70% among women with more than a secondary education.  The percentage of women who are employed also increases with increasing wealth, from 24% among those in the lowest wealth quintile to 49% among those in highest quintile. 3.5 OCCUPATION Occupation Categorized as professional/technical/managerial, clerical, sales and services, skilled manual, unskilled manual, domestic service, agriculture, and other. Sample: Women and men age 15-49 who were currently employed or had worked in the 12 months before the survey Currently employed respondents were asked to state their occupation. Tables 3.7.1 and 3.7.2, respectively, show that 42% of women and 71% of men age 15-49 are engaged in agricultural occupations, while 37% of women and 8% of men are employed in sales and services. Eight percent of women and 7% of men work in skilled manual labour. Only 5% of men and women are working in professional/technical/managerial occupations (Figure 3.5). Trends: There has been a decline since 2005 in the proportion of women working in agricultural occupations, from 52% to 42%. Among men, the proportion has decreased from 84% to 71%. The proportion of women who are employed in sales and services has increased over the past several years, from 31% in 2005 and 33% in 2011 to 37% in 2016. Figure 3.4 Employment status by residence Figure 3.5 Occupation 33 52 28 88 81 90 Total Urban Rural Percentage of women and men age 15-49 who are currently employed Women Men 2 3 5 5 8 37 42 1 3 5 5 7 8 71 Clerical Unskilled manual Other Professional/tech- nical/managerial Skilled manual Sales and services Agriculture Percentage of women and men age 15-49 employed in the 12 months before the survey by occupation Women Men 38 • Characteristics of Respondents Patterns by background characteristics  Urban women are most likely to be employed in sales and services (56%) and in the professional/technical/managerial sector (13%). In contrast, urban men are most likely to be employed in skilled manual labour (25%) and sales and services (22%).  In rural areas, 55% of employed women and 83% of employed men are engaged in agricultural work.  Women with a secondary education or higher tend to be employed in sales and services and in professional, technical, and managerial occupations, whereas women with little or no education tend to be employed in the agricultural sector.  The percentage of women who work in agriculture is highest among those who are currently married, those with five or more children, those living in rural areas, those with no education, and those in the lowest wealth quintile.  Among both men and women, employment in professional/technical/managerial occupations, sales and services, and skilled manual labour generally increases with increasing education and wealth. 3.6 TYPE OF WOMEN’S EMPLOYMENT Table 3.8 presents the percent distribution of women who were employed in the 12 months preceding the survey by type of earnings, type of employer, and continuity of employment, according to sector of employment (agricultural or nonagricultural). Seven in 10 women (70%) engaged in agricultural work are unpaid workers, most likely employed by family members at the peak of the agricultural season. Trends: The proportion of self-employed women in the agricultural sector increased from 22% in 2005 to 46% in 2016. There has been no marked change among women in employment by non-family members since 2005, but the proportion of women working in agricultural sectors who are paid in cash only increased from 3% in 2005 to 8% in 2016. The percentage of women engaged in agricultural activities year-round increased from 6% in 2005 to 13% in 2011 and 23% in 2016. Seasonal agricultural employment decreased from 89% in 2005 and 78% in 2011 to 67% in 2016.  Women employed in the nonagricultural sector (62%) are more likely than women working in the agricultural sector (8%) to be paid in cash only. Overall, 46% of employed women are not paid at all for their work, and 40% are paid in cash only.  Almost half (49%) of employed women are self-employed, 37% work for a family member, and 15% work for someone outside the family.  Women in the agricultural sector are much more likely than women in the nonagricultural sector to work for a family member (51% versus 26%). In contrast, the proportion of women employed by someone outside the family is much higher in the nonagricultural sector than in the agricultural sector (23% versus 3%).  Continuity of employment varies by employment sector. Whereas 67% of women employed in the agricultural sector are seasonal workers, only 15% in the nonagricultural sector work seasonally. The majority of women who are engaged in the nonagricultural sector (69%) work all year. 3.7 HEALTH INSURANCE COVERAGE Since 2011, Ethiopia has implemented the community-based health insurance (CBHI) scheme, aimed at reaching and covering the very large rural agricultural sector and small and informal sectors in urban Characteristics of Respondents • 39 settings. The overall objective of insurance coverage is to promote equitable access to sustainable quality health care, increase financial protection, and enhance social inclusion for the majority of Ethiopian families via the health sector. The CBHI benefit package covers all outpatient and inpatient services at the health centre and hospital levels other than services related to dentures, eyeglasses, and cosmetic procedures (USAID 2015). Tables 3.9.1 and 3.9.2 show that, overall, 95% of women and 94% of men age 15-49 are not covered by any type of health insurance. Less than 1% each of women and men are covered by social security insurance, and less than 1% of women and men have employer-based insurance coverage. Mutual Health Organisation/community-based insurance covers 4% of women and 5% of men. Patterns by background characteristics  Mutual Health Organisation/community-based health insurance coverage varies by place of residence among both women (3% in urban areas and 4% in rural areas) and men (2% in urban areas and 5% in rural areas).  This type of insurance coverage also varies by region. It is highest in Amhara (12% among women and 13% among men) and is nonexistent in Somali and Benishangul-Gumuz. 3.8 TOBACCO USE Table 3.10.1 shows that cigarette smoking and use of any type of tobacco are rare among women (less than 1%). Four percent of men smoke any type of tobacco, among whom almost all smoke cigarettes (Table 3.10.2). Among men who smoke cigarettes daily, one-quarter (25%) smoke 5-9 cigarettes each day; 6% of daily cigarette smokers smoke 25 or more cigarettes each day (Table 3.11). Trends: The percentage of men age 15-49 who do not smoke cigarettes has increased slightly since 2011, from 93% to 95%. The decline in smoking varies by region. For example, the proportion of cigarette smokers in Harari decreased from 27% in 2011 to 12% in 2016, while the proportion in Dire Dawa declined from 24% to 13%. Patterns by background characteristics  Use of tobacco increases with age among men and reaches a peak at age 40-44 (8%).  There are wide regional variations in cigarette smoking, ranging from less than 1% of men in Amhara to 13% in Dire Dawa and 18% in Somali.  The likelihood of men smoking tobacco varies little by education (5% among men with no education and 3% among men with more than a secondary education).  The proportion of men who smoke tobacco decreases with increasing wealth; 7% of men in the lowest wealth quintile smoke tobacco, as compared with 2% of men in the fourth quintile. 3.9 ALCOHOL CONSUMPTION Tables 3.12.1 and 3.12.2 show that 35% of women and about half of men (46%) reported drinking alcohol at some point in their lives. Overall, 8% each of women and men did not drink alcohol in the last 30 days, and 3%-4% did not drink alcohol in the past 12 months. Among respondents who ever drank alcohol, 50% of women and 58% of men drank on 6 or more days in the preceding 30 days. Six percent of women and 9% of men consumed alcoholic drinks almost every day in the last 30 days. Trends: The percentage of women who ever drank alcohol decreased from 45% in 2011 to 35% in 2016. The decline among men was similar (53% in 2011 to 46% in 2016). The proportion of women who 40 • Characteristics of Respondents consumed alcohol on 6 or more days in the last 30 days has increased since 2011, from 48% to 50%. Among men, the proportion has increased from 53% to 58%. Patterns by background characteristics  Among both women and men, consumption of alcohol increases with increasing age.  Alcohol consumption is higher in urban than in rural areas (43% versus 33% among women and 57% versus 43% among men).  By region, the percentage of women who ever drank alcohol ranges from less than 1% in Somali to 76% in Amhara. The proportion among men ranges from 1% in Somali to 91% in Tigray.  Among both men and women, alcohol consumption generally increases with increasing education and wealth. 3.10 CHEWING CHAT Tables 3.13.1 and 3.13.2 show that 12% of women and 27% of men report having ever chewed chat. Among respondents who ever chewed chat, two in three chewed chat for 6 or more days in the last 30 days (65% of women and 64% of men). Trends: The proportion of women and men who ever chewed chat has not changed since 2011 (11% in 2011 and 12% in 2016 among women and 28% in 2011 and 27% in 2016 among men). The percentage of women who chewed chat for 6 days or more in the last 30 days increased from 43% in 2011 to 65% in 2016. Among men, the proportion increased from 56% to 64%. Patterns by background characteristics  Chat consumption generally increases with age and peaks at age 30-34 among both women (15%) and men (34%).  Chat consumption is slightly higher in rural areas than in urban areas (13% versus 9% among women and 27% versus 25% among men).  Chat chewing varies across regions, ranging from 1% among women and 5% among men in Tigray to 32% among women and 74% among men in Harari to.  Chat consumption varies widely by education and wealth status. For example, 16% of women with no education have ever chewed chat, as compared with 4% of women with more than a secondary education. Similarly, 31% of men with no education have ever chewed chat, compared with 23% of men with more than a secondary education. Chat chewing follows the same pattern according to wealth. LIST OF TABLES For more information on the characteristics of respondents, see the following tables:  Table 3.1 Background characteristics of respondents  Table 3.2.1 Educational attainment: Women  Table 3.2.2 Educational attainment: Men  Table 3.3.1 Literacy: Women  Table 3.3.2 Literacy: Men  Table 3.4.1 Exposure to mass media: Women  Table 3.4.2 Exposure to mass media: Men Characteristics of Respondents • 41  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  Table 3.12.1 Alcohol consumption: Women  Table 3.12.2 Alcohol consumption: Men  Table 3.13.1 Chewing chat: Women  Table 3.13.2 Chewing chat: 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, Ethiopia DHS 2016 Women Men Background characteristic Weighted percent Weighted number Unweighted number Weighted percent Weighted number Unweighted number Age 15-19 21.6 3,381 3,498 22.2 2,572 2,533 20-24 17.6 2,762 2,903 16.2 1,883 1,969 25-29 18.9 2,957 2,845 17.0 1,977 2,030 30-34 15.0 2,345 2,241 14.1 1,635 1,585 35-39 12.3 1,932 1,917 11.9 1,386 1,375 40-44 8.2 1,290 1,302 10.4 1,206 1,217 45-49 6.5 1,017 977 8.2 947 869 Religion Orthodox 43.3 6,786 6,413 44.5 5,160 4,956 Catholic 0.8 120 91 0.7 78 94 Protestant 23.4 3,674 2,814 22.1 2,561 1,970 Muslim 31.2 4,893 6,209 31.4 3,649 4,440 Traditional 0.8 123 84 0.3 31 28 Other 0.6 87 72 1.1 128 90 Ethnic group Affar 0.7 107 947 0.5 63 527 Amhara 29.8 4,671 3,688 30.1 3,497 2,824 Guragie 2.8 444 655 2.7 311 481 Hadiya 2.4 372 230 1.9 217 169 Oromo 34.0 5,340 3,611 36.0 4,175 2,740 Sidama 4.0 627 355 4.2 490 304 Somali 2.8 441 1,463 2.6 299 1,042 Tigray 7.7 1,204 1,905 6.7 778 1,317 Welaita 3.1 494 322 2.8 321 222 Other 12.6 1,984 2,507 12.5 1,455 1,952 Marital status Never married 25.7 4,036 4,278 42.1 4,882 5,084 Married 63.9 10,014 9,602 52.1 6,045 5,987 Living together 1.3 209 222 3.4 397 190 Divorced/separated 6.3 994 1,130 2.2 254 283 Widowed 2.7 429 451 0.2 28 34 Residence Urban 22.2 3,476 5,348 19.8 2,303 3,559 Rural 77.8 12,207 10,335 80.2 9,302 8,019 Region Tigray 7.2 1,129 1,682 6.1 708 1,130 Affar 0.8 128 1,128 0.7 82 665 Amhara 23.7 3,714 1,719 25.1 2,914 1,514 Oromiya 36.4 5,701 1,892 38.0 4,409 1,595 Somali 2.9 459 1,391 2.6 301 927 Benishangul-Gumuz 1.0 160 1,126 1.0 118 902 SNNPR 21.0 3,288 1,849 20.4 2,371 1,465 Gambela 0.3 44 1,035 0.3 35 810 Harari 0.2 38 906 0.2 29 620 Addis Ababa 5.9 930 1,824 4.9 573 1,132 Dire Dawa 0.6 90 1,131 0.6 66 818 Education No education 47.8 7,498 7,033 27.6 3,203 2,904 Primary 35.0 5,490 5,213 48.3 5,608 5,036 Secondary 11.6 1,817 2,238 15.4 1,785 2,142 More than secondary 5.6 877 1,199 8.7 1,010 1,496 Wealth quintile Lowest 16.8 2,633 3,894 15.8 1,839 2,650 Second 17.9 2,809 2,046 18.3 2,118 1,641 Middle 19.0 2,978 2,002 19.4 2,246 1,591 Fourth 19.8 3,100 2,042 21.3 2,466 1,736 Highest 26.5 4,163 5,699 25.3 2,935 3,960 Total 15-49 100.0 15,683 15,683 100.0 11,606 11,578 50-59 na na na na 1,082 1,110 Total 15-59 na na na na 12,688 12,688 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, Ethiopia DHS 2016 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 20.0 49.0 5.2 18.7 0.6 6.4 100.0 4.8 6,143 15-19 13.9 57.3 6.3 19.8 0.3 2.6 100.0 5.1 3,381 20-24 27.6 38.9 4.0 17.3 1.1 11.2 100.0 4.1 2,762 25-29 50.5 27.8 2.2 9.8 1.2 8.5 100.0 0.0 2,957 30-34 71.0 17.9 2.1 3.5 1.1 4.5 100.0 0.0 2,345 35-39 70.9 18.9 1.3 3.2 2.3 3.3 100.0 0.0 1,932 40-44 72.9 17.9 1.6 2.4 2.3 2.9 100.0 0.0 1,290 45-49 78.5 13.6 2.2 1.3 1.9 2.5 100.0 0.0 1,017 Residence Urban 16.4 27.4 5.8 24.3 5.0 21.1 100.0 7.7 3,476 Rural 56.8 33.1 2.5 6.4 0.2 1.2 100.0 0.0 12,207 Region Tigray 43.0 29.2 3.0 17.4 1.1 6.3 100.0 2.1 1,129 Affar 68.7 20.4 3.9 3.9 0.2 2.8 100.0 0.0 128 Amhara 54.1 26.3 1.7 11.9 0.6 5.4 100.0 0.0 3,714 Oromiya 51.1 32.7 4.1 7.1 1.1 3.8 100.0 0.0 5,701 Somali 75.3 16.7 1.5 4.1 0.4 2.0 100.0 0.0 459 Benishangul-Gumuz 46.7 36.4 1.1 9.6 0.3 5.9 100.0 0.9 160 SNNPR 43.9 39.9 2.8 9.2 0.5 3.7 100.0 1.6 3,288 Gambela 26.7 34.2 4.5 20.6 1.5 12.5 100.0 5.6 44 Harari 36.1 29.2 5.3 13.7 3.6 12.0 100.0 4.0 38 Addis Ababa 8.6 30.8 6.4 22.7 7.5 24.0 100.0 8.1 930 Dire Dawa 33.3 31.8 6.4 16.1 2.6 9.8 100.0 4.7 90 Wealth quintile Lowest 73.9 22.5 1.1 2.2 0.0 0.3 100.0 0.0 2,633 Second 62.3 31.9 1.7 3.6 0.1 0.4 100.0 0.0 2,809 Middle 54.6 36.3 2.6 5.5 0.1 0.9 100.0 0.0 2,978 Fourth 44.7 38.5 3.5 10.8 0.2 2.3 100.0 1.3 3,100 Highest 19.0 29.3 5.9 23.2 4.4 18.3 100.0 7.2 4,163 Total 47.8 31.8 3.2 10.4 1.2 5.6 100.0 0.6 15,683 1 Completed 8th grade at the primary level 2 Completed 4th 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, Ethiopia DHS 2016 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 12.2 55.4 6.2 20.0 0.4 5.8 100.0 5.2 4,455 15-19 9.9 63.0 6.5 18.5 0.2 1.9 100.0 5.1 2,572 20-24 15.3 44.9 5.8 22.2 0.7 11.1 100.0 5.5 1,883 25-29 22.7 34.9 5.0 19.5 1.5 16.5 100.0 5.4 1,977 30-34 36.7 36.5 2.4 10.7 1.5 12.2 100.0 2.7 1,635 35-39 42.9 39.1 3.6 6.1 1.5 6.8 100.0 1.5 1,386 40-44 45.7 35.3 4.3 4.6 3.2 6.9 100.0 1.3 1,206 45-49 49.3 37.1 2.0 4.5 1.9 5.3 100.0 0.1 947 Residence Urban 7.9 23.0 4.7 27.7 5.0 31.7 100.0 9.3 2,303 Rural 32.5 48.8 4.6 10.7 0.4 3.0 100.0 2.9 9,302 Region Tigray 23.2 45.5 5.3 16.2 1.0 8.8 100.0 4.1 708 Affar 45.5 26.8 6.4 11.3 2.4 7.6 100.0 1.6 82 Amhara 41.2 36.4 2.4 11.9 0.5 7.5 100.0 2.0 2,914 Oromiya 26.7 46.2 6.0 13.2 1.3 6.7 100.0 3.7 4,409 Somali 44.8 25.7 7.0 12.3 1.1 9.1 100.0 2.4 301 Benishangul-Gumuz 21.2 46.7 3.3 16.6 0.4 11.8 100.0 4.7 118 SNNPR 18.0 56.6 4.0 14.4 0.4 6.6 100.0 4.4 2,371 Gambela 10.3 40.7 5.4 18.0 1.7 24.0 100.0 6.5 35 Harari 17.5 28.6 5.5 20.2 4.1 24.1 100.0 7.3 29 Addis Ababa 3.7 19.3 5.4 27.3 8.9 35.5 100.0 9.8 573 Dire Dawa 13.2 32.1 6.4 24.6 4.9 18.8 100.0 7.2 66 Wealth quintile Lowest 48.3 42.9 2.9 5.0 0.1 0.8 100.0 0.1 1,839 Second 37.6 49.4 4.5 7.2 0.2 1.1 100.0 1.9 2,118 Middle 31.5 51.1 4.7 10.9 0.3 1.5 100.0 2.9 2,246 Fourth 23.5 49.6 5.1 16.2 0.5 5.1 100.0 4.3 2,466 Highest 7.8 29.5 5.2 25.5 4.3 27.7 100.0 8.6 2,935 Total 15-49 27.6 43.7 4.6 14.1 1.3 8.7 100.0 3.9 11,606 50-59 58.9 24.7 2.4 4.2 1.5 8.4 100.0 0.0 1,082 Total 15-59 30.3 42.1 4.4 13.2 1.3 8.7 100.0 3.6 12,688 1 Completed 8th grade at the primary level 2 Completed 4th 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, Ethiopia DHS 2016 More than a secondary education No schooling, primary school, or secondary school Total Percentage literate1 Number of women Background characteristic Can read a whole sentence Can read part of a sentence Cannot read at all No card with required language Blind/ visually impaired Age 15-24 2.4 41.1 20.3 34.7 1.5 0.1 100.0 63.8 6,143 15-19 0.6 46.4 22.7 28.3 1.9 0.1 100.0 69.8 3,381 20-24 4.6 34.6 17.3 42.5 1.0 0.0 100.0 56.5 2,762 25-29 3.3 22.1 13.0 60.7 0.8 0.0 100.0 38.5 2,957 30-34 2.6 12.2 8.3 76.5 0.4 0.0 100.0 23.1 2,345 35-39 1.9 11.8 9.8 76.3 0.0 0.2 100.0 23.5 1,932 40-44 1.6 11.5 11.8 74.8 0.3 0.0 100.0 24.9 1,290 45-49 1.7 8.5 11.3 78.5 0.0 0.0 100.0 21.5 1,017 Residence Urban 9.9 54.2 13.8 21.6 0.5 0.0 100.0 77.9 3,476 Rural 0.3 16.8 14.7 67.2 0.9 0.1 100.0 31.8 12,207 Region Tigray 2.7 35.1 13.2 48.9 0.0 0.1 100.0 51.0 1,129 Affar 1.2 13.8 8.8 75.6 0.7 0.0 100.0 23.7 128 Amhara 2.0 31.3 11.6 55.0 0.0 0.1 100.0 44.9 3,714 Oromiya 1.4 21.1 14.8 62.6 0.0 0.1 100.0 37.3 5,701 Somali 1.2 6.2 5.0 79.4 8.1 0.1 100.0 12.4 459 Benishangul-Gumuz 1.6 21.4 15.7 60.9 0.2 0.2 100.0 38.7 160 SNNPR 1.5 14.1 19.7 62.4 2.3 0.0 100.0 35.3 3,288 Gambela 3.2 27.6 19.2 41.2 8.8 0.0 100.0 50.0 44 Harari 4.2 32.4 18.0 44.9 0.3 0.2 100.0 54.6 38 Addis Ababa 13.7 61.3 12.8 11.4 0.7 0.0 100.0 87.8 930 Dire Dawa 3.4 34.9 16.3 44.2 1.2 0.1 100.0 54.5 90 Wealth quintile Lowest 0.1 7.2 8.2 82.9 1.3 0.2 100.0 15.6 2,633 Second 0.1 12.4 13.1 73.4 0.9 0.0 100.0 25.6 2,809 Middle 0.1 16.9 16.3 65.9 0.8 0.0 100.0 33.3 2,978 Fourth 0.9 23.5 19.5 55.5 0.6 0.0 100.0 43.9 3,100 Highest 8.3 51.9 14.6 24.7 0.6 0.0 100.0 74.7 4,163 Total 2.4 25.1 14.5 57.1 0.8 0.1 100.0 42.0 15,683 1 Refers to women who have more than a secondary education 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, Ethiopia DHS 2016 More than a secondary education No schooling, primary school, or secondary school Total Percentage literate1 Number of men Background characteristic Can read a whole sentence Can read part of a sentence Cannot read at all No card with required language Blind/ visually impaired Age 15-24 2.9 59.4 16.3 20.8 0.6 0.0 100.0 78.5 4,455 15-19 0.5 61.9 17.4 19.5 0.7 0.0 100.0 79.8 2,572 20-24 6.1 55.9 14.8 22.6 0.5 0.0 100.0 76.9 1,883 25-29 10.0 46.1 14.6 28.7 0.5 0.1 100.0 70.7 1,977 30-34 8.5 36.5 16.0 38.5 0.5 0.0 100.0 61.0 1,635 35-39 4.7 34.5 18.0 42.6 0.3 0.0 100.0 57.1 1,386 40-44 4.3 40.2 17.8 37.6 0.0 0.0 100.0 62.3 1,206 45-49 3.5 31.2 22.5 42.2 0.2 0.4 100.0 57.2 947 Residence Urban 20.0 65.4 7.2 6.9 0.4 0.2 100.0 92.5 2,303 Rural 1.7 42.0 19.2 36.7 0.4 0.0 100.0 62.9 9,302 Region Tigray 5.1 57.8 17.0 19.7 0.3 0.1 100.0 79.9 708 Affar 3.8 26.4 20.6 48.9 0.3 0.0 100.0 50.8 82 Amhara 4.8 48.1 12.8 34.1 0.0 0.2 100.0 65.7 2,914 Oromiya 4.3 46.6 17.6 31.4 0.1 0.0 100.0 68.5 4,409 Somali 6.7 39.7 10.2 40.5 2.8 0.0 100.0 56.7 301 Benishangul-Gumuz 5.7 44.9 19.1 30.3 0.0 0.0 100.0 69.7 118 SNNPR 3.9 36.7 24.0 34.0 1.4 0.0 100.0 64.6 2,371 Gambela 10.5 54.3 16.7 14.7 3.6 0.1 100.0 81.5 35 Harari 11.0 59.0 10.9 19.0 0.0 0.0 100.0 81.0 29 Addis Ababa 19.8 71.3 4.6 4.2 0.1 0.0 100.0 95.7 573 Dire Dawa 10.4 57.4 14.6 16.8 0.7 0.1 100.0 82.4 66 Wealth quintile Lowest 0.4 28.5 17.1 53.0 1.0 0.0 100.0 46.0 1,839 Second 0.5 34.8 18.8 45.2 0.6 0.1 100.0 54.1 2,118 Middle 0.8 43.8 21.5 33.6 0.3 0.0 100.0 66.1 2,246 Fourth 2.9 52.0 19.1 25.8 0.3 0.0 100.0 73.9 2,466 Highest 17.3 64.1 9.8 8.4 0.2 0.2 100.0 91.2 2,935 Total 15-49 5.3 46.6 16.8 30.8 0.4 0.1 100.0 68.8 11,606 50-59 6.1 25.5 20.8 47.4 0.1 0.2 100.0 52.3 1,082 Total 15-59 5.4 44.8 17.2 32.2 0.4 0.1 100.0 67.4 12,688 1 Refers to men who have more than a secondary education 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, Ethiopia DHS 2016 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 6.9 18.1 17.3 1.2 68.9 3,381 20-24 4.3 18.5 18.2 1.6 70.6 2,762 25-29 4.3 17.5 18.9 1.7 70.4 2,957 30-34 2.0 14.8 16.9 1.1 75.0 2,345 35-39 3.1 12.0 13.2 1.3 79.6 1,932 40-44 1.2 10.7 11.4 0.9 82.7 1,290 45-49 1.8 12.5 13.4 1.0 80.1 1,017 Residence Urban 10.4 60.7 32.4 5.3 31.8 3,476 Rural 2.1 3.1 11.9 0.2 85.5 12,207 Region Tigray 4.4 18.9 15.4 1.7 71.6 1,129 Affar 3.0 15.6 13.3 1.3 74.3 128 Amhara 1.7 10.3 8.4 0.3 83.5 3,714 Oromiya 4.2 12.5 20.2 1.2 72.3 5,701 Somali 1.3 7.9 4.1 0.5 89.3 459 Benishangul-Gumuz 3.4 9.3 11.4 0.4 80.4 160 SNNPR 4.4 8.4 13.3 1.1 80.7 3,288 Gambela 3.5 25.6 13.8 1.1 65.9 44 Harari 5.8 41.6 18.1 4.1 54.6 38 Addis Ababa 10.5 81.1 45.3 6.8 14.1 930 Dire Dawa 5.8 51.5 20.0 2.9 44.2 90 Education No education 0.1 3.6 8.8 0.1 89.0 7,498 Primary 4.1 15.2 17.5 0.7 71.5 5,490 Secondary 11.8 44.5 32.7 4.5 41.0 1,817 More than secondary 19.9 65.6 42.1 9.6 22.4 877 Wealth quintile Lowest 0.9 0.7 3.8 0.0 95.5 2,633 Second 1.6 0.7 6.6 0.0 91.8 2,809 Middle 2.0 1.7 10.7 0.2 87.5 2,978 Fourth 3.1 3.7 18.4 0.5 77.9 3,100 Highest 9.5 54.9 33.8 4.5 34.3 4,163 Total 3.9 15.8 16.5 1.3 73.6 15,683 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, Ethiopia DHS 2016 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 9.2 21.6 26.2 3.4 61.7 2,572 20-24 8.8 22.6 28.4 5.0 61.1 1,883 25-29 10.5 24.7 32.1 5.4 57.9 1,977 30-34 9.1 24.2 31.5 5.1 58.5 1,635 35-39 9.8 18.1 29.1 5.6 63.4 1,386 40-44 10.0 18.4 28.6 5.2 64.0 1,206 45-49 7.3 13.3 23.6 3.8 71.4 947 Residence Urban 22.3 64.0 50.3 15.5 24.9 2,303 Rural 6.1 10.6 23.3 2.1 70.9 9,302 Region Tigray 13.0 32.9 35.0 4.9 46.4 708 Affar 6.4 28.7 19.6 2.6 63.3 82 Amhara 3.2 19.5 24.6 1.4 64.0 2,914 Oromiya 12.0 19.8 32.2 6.3 60.7 4,409 Somali 5.9 14.6 11.7 3.4 77.6 301 Benishangul-Gumuz 7.1 14.6 29.0 1.7 62.0 118 SNNPR 6.2 7.9 18.1 1.4 76.9 2,371 Gambela 14.4 40.5 37.0 6.4 44.2 35 Harari 10.6 33.2 25.2 7.0 59.0 29 Addis Ababa 30.7 80.8 67.1 23.7 10.9 573 Dire Dawa 16.4 47.5 35.3 7.5 35.8 66 Education No education 0.9 6.8 15.3 0.2 80.9 3,203 Primary 6.9 14.7 27.1 2.3 65.0 5,608 Secondary 17.9 42.3 42.1 10.5 41.8 1,785 More than secondary 34.6 66.0 56.1 22.2 18.4 1,010 Wealth quintile Lowest 3.0 5.0 12.3 0.7 83.9 1,839 Second 2.5 6.5 17.2 0.1 79.2 2,118 Middle 5.9 9.9 23.1 1.5 70.9 2,246 Fourth 9.2 13.4 31.8 3.7 61.1 2,466 Highest 21.0 57.2 49.0 13.8 28.9 2,935 Total 15-49 9.4 21.2 28.7 4.7 61.8 11,606 50-59 7.5 18.0 24.0 4.7 67.4 1,082 Total 15-59 9.2 21.0 28.3 4.7 62.2 12,688 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, Ethiopia DHS 2016 Ever used the Internet Used the Internet in the past 12 months Number of women 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 of women Age 15-19 7.1 6.4 3,381 22.8 49.8 22.9 4.5 100.0 217 20-24 8.1 7.2 2,762 36.7 38.1 17.3 7.9 100.0 200 25-29 5.8 5.2 2,957 45.2 31.1 19.8 3.9 100.0 153 30-34 2.9 2.4 2,345 38.7 41.1 15.7 4.5 100.0 56 35-39 2.4 2.0 1,932 31.6 36.5 27.0 4.9 100.0 39 40-44 1.4 1.3 1,290 (33.5) (38.8) (24.4) (3.3) 100.0 17 45-49 1.2 1.1 1,017 * * * * 100.0 11 Residence Urban 18.8 17.5 3,476 35.6 42.5 17.8 4.1 100.0 609 Rural 1.0 0.7 12,207 18.8 30.2 36.6 14.4 100.0 84 Region Tigray 5.5 5.0 1,129 42.7 28.9 19.5 8.9 100.0 56 Affar 2.7 2.7 128 * * * * 100.0 4 Amhara 3.3 2.5 3,714 (18.0) (39.6) (35.7) (6.6) 100.0 91 Oromiya 2.8 2.5 5,701 (14.3) (62.6) (20.5) (2.5) 100.0 144 Somali 2.9 2.7 459 (58.7) (35.4) (5.9) (0.0) 100.0 12 Benishangul-Gumuz 2.7 2.3 160 * * * * 100.0 4 SNNPR 2.5 2.2 3,288 (35.5) (36.1) (23.4) (4.9) 100.0 73 Gambela 6.6 5.3 44 (27.2) (30.6) (34.3) (7.9) 100.0 2 Harari 12.6 11.9 38 42.3 41.3 14.2 2.2 100.0 5 Addis Ababa 32.9 30.8 930 44.8 34.6 14.5 6.1 100.0 287 Dire Dawa 18.7 16.3 90 38.3 42.5 17.0 2.2 100.0 15 Education No education 0.1 0.0 7,498 * * * * 100.0 2 Primary 1.9 1.5 5,490 20.4 31.5 38.3 9.7 100.0 81 Secondary 15.9 13.9 1,817 25.6 49.3 18.5 6.6 100.0 253 More than secondary 42.8 40.7 877 42.2 37.1 17.3 3.4 100.0 357 Wealth quintile Lowest 0.1 0.1 2,633 * * * * 100.0 2 Second 0.4 0.2 2,809 * * * * 100.0 7 Middle 1.1 0.7 2,978 * * * * 100.0 20 Fourth 1.7 1.2 3,100 (16.8) (27.2) (45.6) (10.4) 100.0 39 Highest 16.3 15.0 4,163 35.5 42.0 18.1 4.4 100.0 625 Total 5.0 4.4 15,683 33.6 41.0 20.1 5.3 100.0 693 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. 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, Ethiopia DHS 2016 Ever used the Internet Used the Internet in the past 12 months Number of men Among men 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 of men Age 15-19 14.5 13.5 2,572 32.9 32.0 33.4 1.6 100.0 347 20-24 19.0 17.2 1,883 34.2 30.4 31.9 3.5 100.0 325 25-29 20.0 18.6 1,977 39.5 28.1 30.0 2.4 100.0 368 30-34 12.0 11.0 1,635 42.8 31.6 24.6 1.1 100.0 180 35-39 6.8 6.5 1,386 33.7 34.7 27.2 4.4 100.0 90 40-44 5.4 5.2 1,206 32.0 28.7 33.4 5.8 100.0 63 45-49 4.4 3.6 947 39.6 19.6 34.7 6.1 100.0 34 Residence Urban 46.9 44.9 2,303 41.6 27.7 28.7 1.9 100.0 1,034 Rural 4.8 4.0 9,302 21.8 37.5 36.0 4.7 100.0 373 Region Tigray 13.6 12.6 708 37.0 29.2 29.8 4.1 100.0 89 Affar 17.8 16.4 82 25.3 29.3 39.9 5.5 100.0 13 Amhara 10.1 9.7 2,914 27.1 35.9 32.7 4.3 100.0 283 Oromiya 11.5 10.2 4,409 36.9 32.2 29.2 1.7 100.0 449 Somali 14.9 14.4 301 45.6 18.7 35.7 0.0 100.0 43 Benishangul-Gumuz 10.3 10.0 118 33.6 31.2 33.0 2.3 100.0 12 SNNPR 6.9 5.8 2,371 36.9 22.9 37.7 2.5 100.0 136 Gambela 26.0 24.0 35 28.8 30.9 39.0 1.3 100.0 8 Harari 40.0 38.2 29 35.8 10.9 50.6 2.6 100.0 11 Addis Ababa 60.2 58.5 573 42.0 29.3 26.3 2.5 100.0 336 Dire Dawa 39.8 39.0 66 45.0 19.9 32.4 2.7 100.0 26 Education No education 0.3 0.2 3,203 * * * * 100.0 7 Primary 4.6 4.1 5,608 22.7 30.7 42.8 3.8 100.0 228 Secondary 31.7 29.1 1,785 28.3 34.2 34.2 3.3 100.0 520 More than secondary 68.2 64.6 1,010 47.5 27.0 23.7 1.7 100.0 652 Wealth quintile Lowest 1.9 1.8 1,839 31.7 26.6 38.9 2.8 100.0 33 Second 2.8 2.3 2,118 32.0 37.1 26.2 4.6 100.0 49 Middle 3.9 3.3 2,246 12.1 49.6 31.2 7.0 100.0 74 Fourth 7.8 6.5 2,466 20.2 35.0 39.7 5.0 100.0 159 Highest 39.1 37.2 2,935 40.7 28.1 29.3 1.9 100.0 1,091 Total 15-49 13.1 12.1 11,606 36.4 30.3 30.7 2.7 100.0 1,407 50-59 4.5 4.2 1,082 33.7 26.9 36.6 2.8 100.0 45 Total 15-59 12.4 11.4 12,688 36.3 30.2 30.9 2.7 100.0 1,452 Note: 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, Ethiopia DHS 2016 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 24.3 16.7 59.0 100.0 3,381 20-24 31.0 16.3 52.7 100.0 2,762 25-29 36.8 16.7 46.5 100.0 2,957 30-34 39.9 16.2 43.9 100.0 2,345 35-39 36.8 17.1 46.1 100.0 1,932 40-44 36.7 18.2 45.1 100.0 1,290 45-49 32.8 19.1 48.1 100.0 1,017 Marital status Never married 32.1 14.8 53.0 100.0 4,036 Married or living together 30.9 17.5 51.6 100.0 10,223 Divorced/separated/widowed 53.4 18.2 28.4 100.0 1,423 Number of living children 0 33.5 16.0 50.4 100.0 5,185 1-2 35.9 15.9 48.2 100.0 3,770 3-4 33.6 18.3 48.1 100.0 3,064 5+ 29.9 17.8 52.2 100.0 3,664 Residence Urban 52.0 9.6 38.5 100.0 3,476 Rural 28.0 18.9 53.1 100.0 12,207 Region Tigray 37.4 24.1 38.6 100.0 1,129 Affar 22.7 3.4 73.9 100.0 128 Amhara 27.0 34.5 38.5 100.0 3,714 Oromiya 32.9 12.8 54.3 100.0 5,701 Somali 18.3 5.6 76.1 100.0 459 Benishangul-Gumuz 49.7 17.7 32.6 100.0 160 SNNPR 34.1 6.8 59.0 100.0 3,288 Gambela 41.6 7.1 51.3 100.0 44 Harari 41.1 3.8 55.1 100.0 38 Addis Ababa 57.8 7.5 34.7 100.0 930 Dire Dawa 36.9 5.9 57.1 100.0 90 Education No education 28.7 19.2 52.1 100.0 7,498 Primary 33.1 16.1 50.8 100.0 5,490 Secondary 35.2 13.7 51.2 100.0 1,817 More than secondary 69.5 8.3 22.2 100.0 877 Wealth quintile Lowest 24.4 18.2 57.4 100.0 2,633 Second 26.7 21.2 52.2 100.0 2,809 Middle 27.1 19.0 53.8 100.0 2,978 Fourth 32.0 17.9 50.1 100.0 3,100 Highest 48.7 10.8 40.5 100.0 4,163 Total 33.3 16.9 49.9 100.0 15,683 1 “Currently employed” is defined as having done work in the past 7 days. Includes persons who did not work in the past 7 days but who are regularly employed and were absent from work for leave, illness, vacation, or any other such reason. 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, Ethiopia DHS 2016 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 68.6 6.9 24.6 100.0 2,572 20-24 84.4 6.2 9.5 100.0 1,883 25-29 94.9 2.8 2.3 100.0 1,977 30-34 96.6 2.2 1.2 100.0 1,635 35-39 97.1 2.0 1.0 100.0 1,386 40-44 96.4 1.6 2.0 100.0 1,206 45-49 96.6 2.1 1.3 100.0 947 Marital status Never married 75.9 6.4 17.8 100.0 4,882 Married or living together 97.2 1.9 0.9 100.0 6,441 Divorced/separated/widowed 93.2 5.2 1.5 100.0 282 Number of living children 0 78.7 5.8 15.5 100.0 5,658 1-2 97.4 1.9 0.7 100.0 2,202 3-4 96.7 2.2 1.2 100.0 1,770 5+ 97.1 2.1 0.7 100.0 1,976 Residence Urban 80.5 4.7 14.8 100.0 2,303 Rural 90.0 3.7 6.3 100.0 9,302 Region Tigray 74.9 11.3 13.8 100.0 708 Affar 67.9 4.6 27.5 100.0 82 Amhara 89.3 4.8 5.9 100.0 2,914 Oromiya 92.3 2.9 4.8 100.0 4,409 Somali 68.3 2.2 29.5 100.0 301 Benishangul-Gumuz 89.9 2.5 7.6 100.0 118 SNNPR 88.3 2.3 9.5 100.0 2,371 Gambela 85.2 2.1 12.7 100.0 35 Harari 81.8 1.7 16.4 100.0 29 Addis Ababa 81.3 5.0 13.6 100.0 573 Dire Dawa 76.2 3.6 20.2 100.0 66 Education No education 94.2 3.1 2.8 100.0 3,203 Primary 87.9 3.8 8.3 100.0 5,608 Secondary 78.0 6.2 15.8 100.0 1,785 More than secondary 88.2 2.9 8.9 100.0 1,010 Wealth quintile Lowest 86.0 5.0 9.0 100.0 1,839 Second 92.1 3.9 4.0 100.0 2,118 Middle 90.8 3.2 6.0 100.0 2,246 Fourth 88.7 3.6 7.7 100.0 2,466 Highest 84.1 3.9 12.0 100.0 2,935 Total 15-49 88.2 3.9 8.0 100.0 11,606 50-59 94.9 2.8 2.3 100.0 1,082 Total 15-59 88.7 3.8 7.5 100.0 12,688 1 “Currently employed” is defined as having done work in the past 7 days. Includes persons who did not work in the past 7 days but who are regularly employed and were absent from work for leave, illness, vacation, or any other such reason. Characteristics of Respondents • 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, Ethiopia DHS 2016 Background characteristic Professional/ technical/ managerial Clerical Sales and services Skilled manual Unskilled manual Agriculture Other Total Number of women Age 15-19 1.2 0.3 42.5 4.3 3.4 38.7 9.6 100.0 1,386 20-24 7.2 4.4 36.6 9.9 3.4 35.3 3.3 100.0 1,305 25-29 7.8 2.1 38.8 7.1 2.0 38.0 4.2 100.0 1,580 30-34 4.6 1.2 39.9 8.7 1.9 40.4 3.3 100.0 1,316 35-39 3.9 1.6 32.0 7.9 3.4 46.5 4.6 100.0 1,041 40-44 2.6 1.8 28.7 9.4 2.1 52.3 3.1 100.0 707 45-49 5.2 0.7 29.6 7.3 1.6 53.2 2.4 100.0 528 Marital status Never married 6.2 3.6 43.5 6.3 3.8 27.1 9.5 100.0 1,896 Married or living together 4.7 1.3 32.7 7.8 1.7 48.4 3.3 100.0 4,948 Divorced/separated/widowed 2.8 1.1 44.2 9.7 5.2 34.6 2.5 100.0 1,019 Number of living children 0 6.7 3.6 41.6 6.8 4.1 29.5 7.7 100.0 2,570 1-2 7.6 1.8 39.2 8.1 2.0 37.3 3.9 100.0 1,952 3-4 2.2 0.8 32.6 9.3 2.0 49.7 3.3 100.0 1,591 5+ 1.3 0.2 30.9 6.9 1.8 56.3 2.5 100.0 1,751 Residence Urban 12.9 6.4 56.2 9.9 3.3 5.3 6.0 100.0 2,138 Rural 1.8 0.1 29.6 6.8 2.4 55.0 4.2 100.0 5,726 Region Tigray 5.2 1.5 28.6 10.4 7.8 41.0 5.5 100.0 693 Affar 6.4 0.8 41.7 7.3 11.8 25.2 6.7 100.0 33 Amhara 5.0 0.9 16.7 7.8 3.1 61.8 4.6 100.0 2,283 Oromiya 3.3 1.3 44.0 5.3 1.1 41.1 3.9 100.0 2,604 Somali 10.3 0.7 62.6 6.8 0.8 16.6 2.1 100.0 110 Benishangul-Gumuz 3.3 1.1 10.7 2.7 7.2 71.1 3.9 100.0 108 SNNPR 3.6 1.2 51.0 8.7 1.5 28.1 6.0 100.0 1,347 Gambela 8.9 3.0 44.0 8.5 3.6 22.8 9.1 100.0 21 Harari 12.0 4.4 55.0 8.1 2.8 11.5 6.2 100.0 17 Addis Ababa 11.9 9.1 56.9 12.9 2.9 1.0 5.2 100.0 607 Dire Dawa 6.6 4.1 64.3 4.5 2.8 9.6 8.1 100.0 39 Education No education 0.5 0.0 29.2 7.9 2.4 57.6 2.4 100.0 3,593 Primary 0.7 0.3 45.0 7.4 2.7 37.7 6.1 100.0 2,701 Secondary 5.1 2.5 53.1 10.4 4.8 16.5 7.6 100.0 888 More than secondary 43.6 16.7 23.5 3.8 0.8 4.1 7.6 100.0 682 Wealth quintile Lowest 1.2 0.0 24.4 5.7 4.2 59.7 4.8 100.0 1,121 Second 0.8 0.1 26.7 8.1 2.4 57.4 4.4 100.0 1,344 Middle 0.8 0.2 30.7 6.5 2.5 56.9 2.3 100.0 1,375 Fourth 3.0 0.1 30.5 7.3 1.3 52.3 5.5 100.0 1,548 Highest 12.1 5.6 55.3 9.1 2.9 9.3 5.6 100.0 2,476 Total 4.8 1.8 36.8 7.7 2.6 41.5 4.7 100.0 7,864 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, Ethiopia DHS 2016 Background characteristic Professional/ technical/ managerial Clerical Sales and services Skilled manual Unskilled manual Agriculture Other Total Number of men Age 15-19 0.6 0.2 7.2 4.2 1.9 74.2 11.7 100.0 1,940 20-24 4.4 1.1 9.0 8.8 4.3 66.6 5.9 100.0 1,704 25-29 8.9 1.4 8.5 11.2 2.5 63.0 4.5 100.0 1,931 30-34 8.3 0.7 9.0 8.4 3.4 67.3 2.9 100.0 1,615 35-39 4.7 0.4 6.1 6.3 2.0 77.6 2.9 100.0 1,372 40-44 6.4 0.7 7.1 6.3 1.6 74.5 3.4 100.0 1,182 45-49 3.6 1.2 5.8 4.3 1.3 80.0 3.9 100.0 935 Marital status Never married 5.1 1.0 9.2 8.4 3.0 63.7 9.5 100.0 4,015 Married or living together 5.3 0.7 6.6 6.5 2.2 75.8 2.9 100.0 6,386 Divorced/separated/widowed 6.7 0.2 11.6 9.5 5.5 62.1 4.4 100.0 278 Number of living children 0 5.5 1.1 9.4 8.8 3.2 63.3 8.6 100.0 4,782 1-2 8.4 0.7 9.4 9.9 2.7 66.3 2.6 100.0 2,187 3-4 3.8 0.8 4.9 5.4 1.7 79.9 3.5 100.0 1,749 5+ 2.5 0.1 4.3 2.6 1.6 86.5 2.6 100.0 1,962 Residence Urban 17.8 3.8 22.3 25.0 7.1 16.5 7.5 100.0 1,962 Rural 2.4 0.1 4.4 3.4 1.5 83.1 4.9 100.0 8,717 Region Tigray 5.8 0.9 7.6 11.4 6.9 52.0 15.5 100.0 611 Affar 10.2 0.5 12.5 8.4 12.1 46.9 9.3 100.0 59 Amhara 5.0 1.1 5.2 6.0 2.7 76.8 3.2 100.0 2,744 Oromiya 3.5 0.4 6.3 3.9 1.2 79.0 5.7 100.0 4,196 Somali 13.9 1.2 14.9 9.5 6.5 44.9 9.0 100.0 212 Benishangul-Gumuz 7.8 0.9 9.3 6.4 1.4 69.0 5.1 100.0 109 SNNPR 4.8 0.3 8.7 6.2 2.3 73.7 4.0 100.0 2,147 Gambela 14.9 1.5 17.8 9.4 1.5 44.7 10.2 100.0 30 Harari 15.0 2.3 14.8 15.6 1.6 40.7 10.0 100.0 24 Addis Ababa 17.6 4.2 24.1 39.8 6.1 2.4 5.8 100.0 495 Dire Dawa 9.2 1.3 18.8 25.8 6.3 26.3 12.3 100.0 53 Education No education 0.8 0.0 3.0 3.0 1.8 87.6 3.8 100.0 3,115 Primary 0.8 0.2 7.5 5.8 2.8 77.1 5.9 100.0 5,142 Secondary 4.6 1.0 15.7 16.4 3.7 51.6 7.0 100.0 1,503 More than secondary 46.7 6.7 11.9 15.7 1.9 11.3 5.9 100.0 920 Wealth quintile Lowest 1.5 0.0 2.8 2.9 1.7 84.6 6.6 100.0 1,675 Second 1.1 0.0 3.0 2.4 2.0 87.4 4.1 100.0 2,033 Middle 1.2 0.4 3.3 2.6 1.6 85.6 5.3 100.0 2,112 Fourth 3.9 0.2 5.2 3.8 1.4 80.9 4.6 100.0 2,275 Highest 15.5 2.8 20.5 21.1 5.4 28.1 6.5 100.0 2,583 Total 15-49 5.3 0.8 7.7 7.3 2.6 70.9 5.4 100.0 10,679 50-59 6.4 1.1 5.9 4.0 0.5 79.9 2.0 100.0 1,058 Total 15-59 5.4 0.8 7.6 7.0 2.4 71.7 5.1 100.0 11,737 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), Ethiopia DHS 2016 Employment characteristic Agricultural work Nonagricultural work Total Type of earnings Cash only 7.5 62.4 39.6 Cash and in-kind 7.8 7.0 7.3 In-kind only 14.7 2.3 7.4 Not paid 69.9 28.4 45.6 Total 100.0 100.0 100.0 Type of employer Employed by family member 51.2 26.0 36.5 Employed by non-family member 2.7 23.3 14.8 Self-employed 46.1 50.7 48.8 Total 100.0 100.0 100.0 Continuity of employment All year 23.4 68.7 49.9 Seasonal 66.8 15.4 36.8 Occasional 9.8 15.8 13.3 Total 100.0 100.0 100.0 Number of women employed during the last 12 months 3,263 4,600 7,864 Note: Total includes women with missing information on type of employment who are not shown separately. 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, Ethiopia DHS 2016 Background characteristic Social security Other employer- based insurance Mutual Health Organisation/ community- based insurance None Number of women Age 15-19 0.9 0.1 4.4 94.5 3,381 20-24 0.5 0.7 2.8 95.9 2,762 25-29 0.8 0.4 2.5 96.2 2,957 30-34 0.4 0.5 4.1 95.1 2,345 35-39 0.4 0.5 5.5 93.6 1,932 40-44 1.3 1.0 5.3 92.3 1,290 45-49 2.0 0.3 5.6 92.1 1,017 Residence Urban 1.0 1.8 2.5 94.7 3,476 Rural 0.7 0.1 4.4 94.7 12,207 Region Tigray 1.9 0.9 8.9 88.1 1,129 Affar 0.6 0.0 0.6 98.8 128 Amhara 1.2 0.3 12.3 86.2 3,714 Oromiya 0.4 0.1 0.6 98.8 5,701 Somali 0.0 0.1 0.0 99.9 459 Benishangul-Gumuz 0.1 0.3 0.0 99.7 160 SNNPR 0.9 0.0 0.6 98.4 3,288 Gambela 0.1 0.1 0.1 99.6 44 Harari 0.0 0.0 0.2 99.8 38 Addis Ababa 0.1 4.8 1.3 93.8 930 Dire Dawa 0.0 0.5 0.6 98.7 90 Education No education 0.7 0.1 4.4 94.8 7,498 Primary 0.7 0.2 3.9 95.3 5,490 Secondary 1.1 0.9 4.2 93.7 1,817 More than secondary 1.1 4.7 1.5 92.4 877 Wealth quintile Lowest 0.5 0.0 1.7 97.7 2,633 Second 0.8 0.0 3.4 95.8 2,809 Middle 0.5 0.0 6.0 93.5 2,978 Fourth 1.0 0.3 6.3 92.3 3,100 Highest 1.0 1.5 2.7 94.7 4,163 Total 0.8 0.5 4.0 94.7 15,683 56 • Characteristics of Respondents 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, Ethiopia DHS 2016 Background characteristic Social security Other employer- based insurance Mutual Health Organisation/ community- based insurance Privately purchased commercial insurance None Number of men Age 15-19 0.7 0.0 5.6 0.0 93.7 2,572 20-24 0.3 0.6 4.7 0.0 94.4 1,883 25-29 0.7 1.4 3.0 0.1 94.9 1,977 30-34 0.4 1.2 2.3 0.0 96.0 1,635 35-39 0.7 0.8 3.7 0.0 94.8 1,386 40-44 1.7 1.0 6.5 0.2 90.6 1,206 45-49 1.2 0.7 7.1 0.1 90.9 947 Residence Urban 0.8 3.1 1.5 0.1 94.5 2,303 Rural 0.7 0.2 5.3 0.0 93.8 9,302 Region Tigray 2.6 1.7 7.9 0.1 88.0 708 Affar 0.3 0.3 0.6 0.0 98.8 82 Amhara 1.9 0.6 13.2 0.0 84.3 2,914 Oromiya 0.1 0.1 1.7 0.0 98.2 4,409 Somali 0.0 0.0 0.0 0.0 100.0 301 Benishangul-Gumuz 0.0 0.5 0.0 0.3 99.2 118 SNNPR 0.1 0.2 0.4 0.1 99.3 2,371 Gambela 0.5 1.3 1.1 0.6 96.4 35 Harari 0.0 0.3 0.3 0.1 99.2 29 Addis Ababa 0.7 8.8 0.6 0.2 89.7 573 Dire Dawa 0.4 2.5 0.2 0.1 96.8 66 Education No education 0.9 0.0 7.1 0.0 92.0 3,203 Primary 0.6 0.1 4.3 0.0 95.1 5,608 Secondary 0.9 1.2 2.9 0.0 95.0 1,785 More than secondary 0.9 6.1 1.1 0.2 91.7 1,010 Wealth quintile Lowest 0.3 0.0 2.9 0.0 96.7 1,839 Second 0.9 0.0 3.8 0.0 95.2 2,118 Middle 0.7 0.3 8.2 0.0 90.8 2,246 Fourth 0.9 0.3 5.9 0.1 92.8 2,466 Highest 0.7 2.5 2.2 0.1 94.5 2,935 Total 15-49 0.7 0.8 4.6 0.0 93.9 11,606 50-59 0.7 0.5 9.7 0.1 88.7 1,082 Total 15-59 0.7 0.7 5.0 0.1 93.5 12,688 Note: Total includes men with missing information on other types of health insurance coverage. Characteristics of Respondents • 57 Table 3.10.1 Tobacco smoking: Women Percentage of women age 15-49 who smoke various tobacco products, according to background characteristics, Ethiopia DHS 2016 Percentage who smoke:1 Number of women Background characteristic Cigarettes2 Other type of tobacco3 Any type of tobacco Age 15-19 0.0 0.0 0.0 3,381 20-24 1.0 0.3 1.0 2,762 25-29 0.7 0.4 0.8 2,957 30-34 0.8 0.5 1.1 2,345 35-39 0.6 0.5 0.8 1,932 40-44 0.2 0.5 0.7 1,290 45-49 1.4 0.6 1.6 1,017 Residence Urban 0.4 0.2 0.5 3,476 Rural 0.7 0.4 0.8 12,207 Region Tigray 0.2 0.0 0.2 1,129 Affar 0.9 2.1 2.9 128 Amhara 0.1 0.1 0.1 3,714 Oromiya 1.0 0.3 1.0 5,701 Somali 0.1 0.2 0.3 459 Benishangul-Gumuz 2.4 1.8 3.6 160 SNNPR 0.8 0.6 1.0 3,288 Gambela 2.2 7.5 8.5 44 Harari 1.2 0.8 1.7 38 Addis Ababa 0.4 0.2 0.5 930 Dire Dawa 1.2 1.0 2.0 90 Education No education 0.8 0.5 1.0 7,498 Primary 0.5 0.2 0.5 5,490 Secondary 0.5 0.2 0.6 1,817 More than secondary 0.1 0.0 0.1 877 Wealth quintile Lowest 0.5 0.8 0.8 2,633 Second 0.7 0.5 0.7 2,809 Middle 1.0 0.3 1.1 2,978 Fourth 0.7 0.2 0.8 3,100 Highest 0.3 0.2 0.4 4,163 Total 0.6 0.4 0.8 15,683 1 Includes daily and occasional (less than daily) use 2 Includes any manufactured cigarettes 3 Includes pipes and shisha 58 • Characteristics of Respondents 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, Ethiopia DHS 2016 Percentage who smoke:1 Smoking frequency Total Number of men Background characteristic Cigarettes2 Other type of tobacco3 Any type of tobacco Daily smoker Occasional smoker4 Non-smoker Age 15-19 0.4 0.0 0.4 0.1 0.5 99.4 100.0 2,572 20-24 2.6 0.2 2.6 1.2 2.0 96.8 100.0 1,883 25-29 4.1 0.2 4.1 3.4 1.7 94.8 100.0 1,977 30-34 5.2 0.5 5.3 4.0 3.1 92.9 100.0 1,635 35-39 6.5 0.5 6.7 5.4 3.3 91.4 100.0 1,386 40-44 7.6 0.1 7.7 6.6 3.0 90.5 100.0 1,206 45-49 5.8 0.2 6.0 6.6 1.4 92.0 100.0 947 Residence Urban 3.9 0.4 3.9 3.6 2.1 94.3 100.0 2,303 Rural 4.0 0.2 4.1 3.2 1.9 94.9 100.0 9,302 Region Tigray 1.2 0.6 1.2 0.8 0.4 98.8 100.0 708 Affar 8.2 0.4 8.3 6.1 6.4 87.4 100.0 82 Amhara 0.4 0.0 0.4 0.5 0.6 98.9 100.0 2,914 Oromiya 6.2 0.2 6.2 4.4 3.0 92.6 100.0 4,409 Somali 17.7 0.4 17.8 19.1 1.9 78.9 100.0 301 Benishangul-Gumuz 11.3 1.3 12.0 11.4 1.8 86.9 100.0 118 SNNPR 2.1 0.2 2.2 1.9 1.6 96.5 100.0 2,371 Gambela 10.5 0.2 10.5 9.7 3.0 87.2 100.0 35 Harari 11.6 0.0 11.6 13.6 3.5 82.9 100.0 29 Addis Ababa 5.3 0.6 5.4 4.2 3.5 92.3 100.0 573 Dire Dawa 12.5 0.8 13.0 12.5 4.5 83.1 100.0 66 Education No education 5.2 0.2 5.3 4.8 2.0 93.3 100.0 3,203 Primary 3.8 0.2 3.8 2.8 2.2 95.0 100.0 5,608 Secondary 3.0 0.1 3.1 2.2 2.0 95.7 100.0 1,785 More than secondary 2.7 0.4 2.7 2.5 0.8 96.7 100.0 1,010 Wealth quintile Lowest 6.6 0.4 6.6 4.8 2.8 92.4 100.0 1,839 Second 4.3 0.2 4.4 3.7 2.9 93.4 100.0 2,118 Middle 5.1 0.1 5.1 3.8 2.0 94.2 100.0 2,246 Fourth 1.7 0.1 1.8 1.5 0.7 97.8 100.0 2,466 Highest 3.2 0.3 3.2 2.9 1.9 95.2 100.0 2,935 Total 15-49 4.0 0.2 4.0 3.2 2.0 94.8 100.0 11,606 50-59 6.8 0.1 6.8 6.6 0.8 92.5 100.0 1,082 Total 15-59 4.2 0.2 4.3 3.5 1.9 94.6 100.0 12,688 1 Includes daily and occasional (less than daily) use 2 Includes manufactured cigarettes and hand-rolled cigarettes 3 Includes pipes, cigars, cheroots, cigarillos, and shisha 4 Occasional refers to less than daily use Characteristics of Respondents • 59 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, Ethiopia DHS 2016 Average number of cigarettes smoked per day1 Total Number of men who smoke cigarettes daily1 Background characteristic <5 5-9 10-14 15-24 ≥25 Don’t know/ missing Age 15-19 * * * * * * 100.0 3 20-24 20.9 35.8 4.1 23.8 15.3 0.0 100.0 22 25-29 50.8 18.6 18.7 6.0 5.9 0.0 100.0 61 30-34 33.2 25.5 25.7 5.4 10.2 0.0 100.0 55 35-39 45.1 24.8 14.0 11.3 4.9 0.0 100.0 73 40-44 37.7 27.0 21.1 13.6 0.4 0.1 100.0 69 45-49 31.8 28.2 28.8 1.1 9.7 0.3 100.0 54 Residence Urban 28.2 26.7 25.6 11.0 8.5 0.1 100.0 76 Rural 41.9 25.0 18.7 8.4 5.8 0.1 100.0 261 Region Tigray * * * * * * 100.0 6 Affar 42.3 21.2 15.8 9.4 7.1 4.2 100.0 4 Amhara * * * * * * 100.0 9 Oromiya 42.8 22.7 16.0 7.7 10.8 0.0 100.0 178 Somali 15.0 30.9 37.4 15.2 1.4 0.0 100.0 52 Benishangul-Gumuz 44.1 29.5 12.5 11.2 2.6 0.0 100.0 13 SNNPR * * * * * * 100.0 39 Gambela 36.5 30.9 20.7 8.5 3.4 0.0 100.0 3 Harari 9.2 26.4 17.8 42.7 3.9 0.0 100.0 3 Addis Ababa (31.7) (28.3) (34.5) (5.5) (0.0) (0.0) 100.0 24 Dire Dawa 15.7 23.6 21.8 34.7 3.2 1.0 100.0 7 Education No education 41.4 21.5 21.0 11.5 4.3 0.2 100.0 133 Primary 40.0 29.3 18.9 7.2 4.6 0.0 100.0 140 Secondary 31.4 28.5 25.4 5.4 9.2 0.0 100.0 39 More than secondary 29.5 19.1 16.5 11.0 23.8 0.0 100.0 25 Wealth quintile Lowest 39.2 25.5 24.6 9.3 1.2 0.2 100.0 80 Second 21.8 19.6 30.3 14.8 13.4 0.0 100.0 62 Middle 52.7 21.6 13.1 5.9 6.7 0.1 100.0 82 Fourth (58.6) (37.1) (1.8) (1.5) (1.0) (0.0) 100.0 33 Highest 29.1 28.9 23.3 10.5 8.3 0.0 100.0 80 Total 15-49 38.8 25.4 20.3 9.0 6.4 0.1 100.0 337 50-59 30.1 43.7 12.3 8.6 5.3 0.0 100.0 71 Total 15-59 37.3 28.6 18.9 8.9 6.2 0.1 100.0 408 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 manufactured cigarettes and hand-rolled cigarettes 60 • Characteristics of Respondents Table 3.12.1 Alcohol consumption: Women Percentage of women age 15-49 who ever drank alcohol, and among women who ever drank alcohol, percent distribution by the number of days they drank alcohol in the last 30 days, and percent distribution by the number of times they drank alcohol in the last 12 months, according to background characteristics, Ethiopia DHS 2016 Percent- age of all women who ever drank alcohol Number of women Among women who ever drank alcohol: Number of women who ever drank alcohol Number of days they drank alcohol in the last 30 days: Total Number of times they drank alcohol in the last 12 months: Total Background characteristic None 1-5 6+ Don’t know Almost every day At least once a week Less than once a week Not in the past 12 months Age 15-19 30.4 3,381 9.8 51.8 36.8 1.5 100.0 3.4 28.6 64.7 3.3 100.0 1,029 20-24 34.1 2,762 9.8 44.1 43.3 2.8 100.0 4.5 30.2 62.8 2.4 100.0 942 25-29 34.0 2,957 6.4 41.9 51.0 0.7 100.0 6.7 32.7 57.7 2.9 100.0 1,006 30-34 36.3 2,345 7.6 39.8 51.1 1.4 100.0 5.7 30.3 61.4 2.6 100.0 852 35-39 38.4 1,932 5.6 31.7 60.6 2.1 100.0 7.5 36.3 53.0 3.2 100.0 742 40-44 40.4 1,290 6.6 32.0 59.0 2.4 100.0 7.7 35.2 53.0 4.1 100.0 520 45-49 43.5 1,017 9.6 26.3 59.9 4.1 100.0 8.0 35.1 52.6 4.3 100.0 442 Residence Urban 43.0 3,476 17.6 52.7 28.3 1.4 100.0 3.3 23.4 68.6 4.7 100.0 1,495 Rural 33.1 12,207 4.4 35.7 57.8 2.1 100.0 6.8 35.2 55.4 2.5 100.0 4,039 Region Tigray 71.3 1,129 2.3 52.1 42.2 3.3 100.0 5.1 36.1 57.4 1.4 100.0 805 Affar 5.1 128 (27.5) (58.4) (14.1) (0.0) 100.0 (11.0) (20.7) (56.9) (11.4) 100.0 7 Amhara 75.9 3,714 3.7 32.4 62.0 1.9 100.0 4.1 30.1 64.7 1.0 100.0 2,820 Oromiya 14.4 5,701 5.9 41.9 49.8 2.4 100.0 11.3 39.9 44.1 4.7 100.0 822 Somali 0.3 459 * * * * 100.0 * * * * 100.0 1 Benishangul-Gumuz 31.7 160 3.9 50.5 44.0 1.6 100.0 17.0 44.6 36.5 1.9 100.0 51 SNNPR 12.9 3,288 18.8 40.9 39.9 0.4 100.0 12.4 47.1 28.4 12.0 100.0 424 Gambela 25.8 44 14.7 55.2 29.1 1.1 100.0 9.4 42.9 41.5 6.2 100.0 11 Harari 11.2 38 14.0 23.7 61.1 1.2 100.0 5.7 25.9 66.0 2.4 100.0 4 Addis Ababa 61.6 930 31.3 57.9 10.0 0.7 100.0 1.8 12.6 78.9 6.6 100.0 573 Dire Dawa 17.2 90 19.2 57.7 23.1 0.0 100.0 2.7 19.5 73.0 4.8 100.0 16 Education No education 36.0 7,498 3.7 31.6 62.2 2.5 100.0 7.5 35.4 53.8 3.2 100.0 2,698 Primary 29.7 5,490 9.6 42.9 46.0 1.5 100.0 4.5 32.2 60.4 3.0 100.0 1,628 Secondary 42.7 1,817 13.6 53.3 31.6 1.4 100.0 5.0 27.2 64.8 3.0 100.0 776 More than secondary 49.2 877 18.3 61.0 19.5 1.2 100.0 2.4 19.3 75.4 3.0 100.0 431 Wealth quintile Lowest 30.3 2,633 3.8 41.3 53.4 1.6 100.0 6.7 34.1 57.8 1.4 100.0 797 Second 32.8 2,809 3.9 35.8 58.3 1.9 100.0 7.1 34.5 56.1 2.3 100.0 923 Middle 33.6 2,978 4.7 32.8 60.2 2.3 100.0 6.2 36.4 54.1 3.2 100.0 1,001 Fourth 35.0 3,100 4.6 34.0 58.8 2.5 100.0 5.6 35.2 56.9 2.3 100.0 1,085 Highest 41.5 4,163 16.1 50.4 32.0 1.5 100.0 4.8 25.3 65.2 4.8 100.0 1,728 Total 35.3 15,683 8.0 40.3 49.8 1.9 100.0 5.9 32.1 59.0 3.1 100.0 5,534 Note: Figures in parentheses are based on 25-49 unweighted cases. An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. Characteristics of Respondents • 61 Table 3.12.2 Alcohol consumption: Men Percentage of men age 15-49 who ever drank alcohol, and among men who ever drank alcohol, percent distribution by the number of days they drank alcohol in the last 30 days, and percent distribution by the number of times they drank alcohol in the last 12 months, according to background characteristics, Ethiopia DHS 2016 Percent- age of all men who ever drank alcohol Number of men Among men who ever drank alcohol: Total Number of men who ever drank alcohol Number of days they drank alcohol in the last 30 days: Total Number of times they drank alcohol in the last 12 months: Background characteristic None 1-5 6+ Don’t know Almost every day At least once a week Less than once a week Not in the past 12 months Age 15-19 39.1 2,572 8.8 47.5 43.3 0.5 100.0 4.6 39.8 53.7 1.9 100.0 1,005 20-24 46.4 1,883 7.1 40.4 52.2 0.3 100.0 6.4 51.0 39.0 3.6 100.0 873 25-29 45.9 1,977 9.2 34.6 55.7 0.4 100.0 7.6 48.0 39.7 4.7 100.0 908 30-34 45.4 1,635 7.8 27.5 64.6 0.1 100.0 12.3 48.9 33.9 4.9 100.0 743 35-39 49.2 1,386 5.1 23.9 70.7 0.4 100.0 13.7 54.5 28.7 3.1 100.0 681 40-44 52.5 1,206 6.8 28.3 64.5 0.4 100.0 13.7 51.3 29.8 5.2 100.0 633 45-49 48.4 947 6.8 22.4 70.4 0.4 100.0 9.9 53.2 32.0 4.9 100.0 458 Residence Urban 56.8 2,303 12.6 41.0 45.6 0.8 100.0 11.8 39.7 43.3 5.2 100.0 1,307 Rural 42.9 9,302 5.9 31.5 62.4 0.2 100.0 8.4 51.7 36.5 3.5 100.0 3,994 Region Tigray 90.7 708 4.5 38.7 56.4 0.4 100.0 5.0 62.9 30.8 1.3 100.0 642 Affar 9.9 82 10.7 35.3 54.0 0.0 100.0 17.5 34.5 33.8 14.1 100.0 8 Amhara 83.1 2,914 3.1 27.0 69.8 0.1 100.0 5.0 47.1 47.0 0.8 100.0 2,423 Oromiya 25.5 4,409 7.5 39.8 51.9 0.8 100.0 23.3 49.0 22.6 5.1 100.0 1,125 Somali 1.0 301 * * * * 100.0 * * * * 100.0 3 Benishangul-Gumuz 47.4 118 4.8 44.8 50.0 0.4 100.0 10.6 48.7 38.4 2.3 100.0 56 SNNPR 25.2 2,371 20.3 33.8 45.3 0.5 100.0 7.2 45.0 33.0 14.8 100.0 599 Gambela 51.3 35 11.3 47.0 41.5 0.2 100.0 9.7 57.8 25.3 7.2 100.0 18 Harari 16.0 29 5.9 46.4 47.7 0.0 100.0 5.8 39.6 52.5 2.1 100.0 5 Addis Ababa 71.0 573 19.7 48.2 31.9 0.2 100.0 4.4 41.7 47.5 6.4 100.0 407 Dire Dawa 25.5 66 21.2 42.4 36.1 0.3 100.0 7.8 36.4 47.0 8.9 100.0 17 Education No education 49.2 3,203 2.9 25.0 71.9 0.2 100.0 11.1 53.1 34.4 1.4 100.0 1,576 Primary 41.3 5,608 7.9 34.6 57.1 0.4 100.0 8.6 49.6 36.9 4.9 100.0 2,315 Secondary 46.1 1,785 11.1 42.5 46.3 0.1 100.0 9.0 43.9 43.1 4.1 100.0 823 More than secondary 58.2 1,010 13.8 42.5 42.8 0.9 100.0 6.8 40.6 46.2 6.4 100.0 587 Wealth quintile Lowest 38.3 1,839 3.9 34.4 61.7 0.0 100.0 4.9 53.7 39.4 2.1 100.0 704 Second 40.9 2,118 4.5 35.3 59.8 0.4 100.0 7.2 47.0 42.6 3.1 100.0 866 Middle 43.6 2,246 6.2 26.1 67.4 0.3 100.0 7.6 51.8 36.6 4.0 100.0 980 Fourth 45.7 2,466 7.7 29.6 62.6 0.1 100.0 10.6 51.6 33.6 4.2 100.0 1,126 Highest 55.4 2,935 11.5 40.5 47.4 0.6 100.0 12.1 43.7 39.4 4.8 100.0 1,626 Total 15-49 45.7 11,606 7.6 33.8 58.3 0.3 100.0 9.2 48.8 38.2 3.9 100.0 5,302 50-59 52.9 1,082 8.0 24.6 66.0 1.4 100.0 13.9 50.1 30.7 5.3 100.0 572 Total 15-59 46.3 12,688 7.6 32.9 59.0 0.5 100.0 9.7 48.9 37.4 4.0 100.0 5,874 Note: An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. 62 • Characteristics of Respondents Table 3.13.1 Chewing chat: Women Percentage of women age 15-49 who ever chewed chat, and among women who ever chewed chat, percent distribution by the number of days they chewed chat in the last 30 days, according to background characteristics, Ethiopia DHS 2016 Background characteristic Percentage of all women who ever chewed chat Number of women Among women who ever chewed chat, number of days they chewed chat in the last 30 days Total Number of women who ever chewed chat None 1-5 6+ Don’t know Age 15-19 7.4 3,381 8.6 24.6 65.2 1.7 100.0 250 20-24 10.0 2,762 11.5 23.3 64.9 0.3 100.0 277 25-29 13.5 2,957 9.0 28.8 60.0 2.3 100.0 399 30-34 15.2 2,345 11.6 22.6 65.4 0.4 100.0 357 35-39 14.3 1,932 11.0 18.5 68.2 2.4 100.0 276 40-44 14.9 1,290 10.2 22.4 67.1 0.3 100.0 192 45-49 15.0 1,017 7.6 28.7 63.7 0.0 100.0 153 Residence Urban 9.0 3,476 27.3 31.9 40.0 0.8 100.0 312 Rural 13.0 12,207 6.7 22.6 69.4 1.2 100.0 1,591 Region Tigray 0.6 1,129 * * * * 100.0 7 Affar 8.0 128 18.3 51.3 27.4 3.1 100.0 10 Amhara 7.4 3,714 21.3 56.5 20.0 2.2 100.0 276 Oromiya 23.8 5,701 4.6 14.7 79.9 0.8 100.0 1,356 Somali 2.4 459 (6.4) (22.8) (68.8) (2.0) 100.0 11 Benishangul-Gumuz 3.2 160 (14.7) (56.1) (29.1) (0.0) 100.0 5 SNNPR 3.8 3,288 13.2 47.8 37.7 1.3 100.0 126 Gambela 4.7 44 (30.3) (54.2) (9.4) (6.0) 100.0 2 Harari 32.0 38 4.6 7.7 87.7 0.0 100.0 12 Addis Ababa 7.7 930 64.4 25.7 7.0 2.9 100.0 71 Dire Dawa 28.7 90 10.7 27.7 58.8 2.8 100.0 26 Education No education 15.5 7,498 6.6 19.1 73.6 0.8 100.0 1,159 Primary 11.1 5,490 10.8 32.0 55.1 2.1 100.0 610 Secondary 5.3 1,817 32.6 30.8 36.6 0.0 100.0 95 More than secondary 4.4 877 49.7 34.6 14.1 1.5 100.0 38 Wealth quintile Lowest 13.0 2,633 3.4 17.0 79.5 0.1 100.0 341 Second 17.4 2,809 4.9 16.4 78.2 0.5 100.0 490 Middle 14.5 2,978 6.5 23.4 68.9 1.2 100.0 432 Fourth 9.3 3,100 12.7 32.7 51.1 3.5 100.0 287 Highest 8.5 4,163 26.1 35.6 37.1 1.2 100.0 353 Total 12.1 15,683 10.1 24.1 64.6 1.2 100.0 1,904 Note: Figures in parentheses are based on 25-49 unweighted cases. An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. Characteristics of Respondents • 63 Table 3.13.2 Chewing chat: Men Percentage of men age 15-49 who ever chewed chat, and among men who ever chewed chat, percent distribution by the number of days they chewed chat in the last 30 days, according to background characteristics, Ethiopia DHS 2016 Background characteristic Percentage of all men who ever chewed chat Number of men Among men who ever chewed chat, number of days they chewed chat in the last 30 days Total Number of men who ever chewed chat None 1-5 6+ Don’t know Age 15-19 13.8 2,572 6.8 25.1 67.7 0.4 100.0 355 20-24 23.8 1,883 12.3 26.4 61.4 0.0 100.0 449 25-29 33.6 1,977 13.0 21.1 65.1 0.7 100.0 664 30-34 34.1 1,635 10.3 28.7 61.0 0.0 100.0 558 35-39 31.9 1,386 15.0 21.1 63.7 0.3 100.0 441 40-44 31.4 1,206 16.4 24.5 58.8 0.2 100.0 379 45-49 27.1 947 13.3 17.4 68.8 0.5 100.0 256 Residence Urban 25.4 2,303 27.0 28.8 42.9 1.3 100.0 586 Rural 27.1 9,302 9.0 22.6 68.3 0.1 100.0 2,517 Region Tigray 4.7 708 48.5 21.9 23.7 5.9 100.0 33 Affar 30.9 82 4.7 38.1 55.4 1.7 100.0 25 Amhara 11.6 2,914 23.1 49.8 27.2 0.0 100.0 339 Oromiya 42.2 4,409 6.6 17.7 75.5 0.2 100.0 1,860 Somali 44.8 301 4.7 16.0 79.0 0.2 100.0 135 Benishangul-Gumuz 20.6 118 16.9 58.1 25.0 0.0 100.0 24 SNNPR 18.3 2,371 18.5 28.1 53.5 0.0 100.0 434 Gambela 26.5 35 22.3 38.7 37.2 1.8 100.0 9 Harari 73.5 29 1.3 7.7 91.0 0.0 100.0 21 Addis Ababa 31.2 573 40.2 30.4 27.9 1.5 100.0 179 Dire Dawa 64.4 66 4.9 14.6 80.3 0.2 100.0 43 Education No education 31.3 3,203 6.5 19.2 74.2 0.0 100.0 1,002 Primary 26.7 5,608 10.7 24.9 64.3 0.1 100.0 1,498 Secondary 20.9 1,785 22.3 29.4 47.8 0.5 100.0 373 More than secondary 22.7 1,010 33.5 27.3 36.5 2.6 100.0 229 Wealth quintile Lowest 32.3 1,839 5.9 23.7 70.1 0.2 100.0 595 Second 31.5 2,118 6.6 21.6 71.8 0.0 100.0 668 Middle 27.7 2,246 8.4 23.1 68.5 0.0 100.0 622 Fourth 21.1 2,466 15.4 21.4 63.1 0.0 100.0 519 Highest 23.8 2,935 24.9 28.3 45.6 1.1 100.0 698 Total 15-49 26.7 11,606 12.4 23.8 63.5 0.3 100.0 3,102 50-59 29.2 1,082 18.4 23.4 57.8 0.5 100.0 316 Total 15-59 26.9 12,688 13.0 23.8 62.9 0.3 100.0 3,418 Marriage and Sexual Activity • 65 MARRIAGE AND SEXUAL ACTIVITY 4 Key Findings  Current marital status: Sixty-five percent of women and 56% of men in Ethiopia are currently in a union.  Polygyny: Eleven percent of currently married women report that their husband has multiple wives.  Age at first marriage: Marriage is nearly universal in Ethiopia, although women marry about 6.6 years earlier than men on average. Median age at first marriage is 17.1 years among women and 23.7 years among men age 25- 49.  Sexual initiation: The median age at first sexual intercourse is 0.5 years earlier than the median age at first marriage for women and 2.5 years earlier for men; this indicates that both women and men engage in sex before marriage.  Trends: Age at first marriage has dramatically changed for women and girls. More than 30% of women born in the seventies married before age 15, while for those born in the nineties, this indicator is around 10 percent. 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. 4.1 MARITAL STATUS Currently married Women and men who report being married or living together with a partner as though married at the time of the survey. Sample: Women and men age 15-49 Marriage is nearly universal in Ethiopia. By age 45-49, only 1% of women and 2% of men have never been married. Two in three (65%) women and 56% of men age 15-49 are currently married or living together with a partner (Table 4.1 and Figure 4.1). Overall, women are more likely than men to be separated, divorced, or widowed. Women are less likely than men to be single; one in four women (26%) and 42% of men have never been married. M Figure 4.1 Marital status Percent distribution of women and men age 15-49 Never married 26% Married or living together 65% Divorced/ separated 6% Widowed 3% Women Never married 42% Married or living together 56% Divorced/ separated 2% Widowed 0.2% Men 66 • Marriage and Sexual Activity Trends: Overall, the percentages of women and men who are currently in a union have remained at the same level since the 2000 EDHS. Patterns by background characteristics  There are marked differences in marital status by sex and age. The percentage of women in a union is higher than that among men until age 34. For example, 17% of women age 15-19 are currently married or living together with a partner, as compared with only 1% of men in the same age category. This pattern reverses at age 35 and older.  The percentage of women currently in a union increases up to age 30-34, at which point it starts to decline. Among men, the percentage increases as age increases.  In general, the proportion of women who are divorced or separated increases with age. There are no differentials by age in the proportions of men who are divorced, separated, or widowed. 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 age 15-49 Eleven percent of women age 15-49 reported that their husband or partner has other wives (Table 4.2.1), while 5% of men reported having more than one wife (Table 4.2.2). Trends: The percentage of women who report being in a polygynous union has declined slightly over time, from 14% in 2000 and 12% in 2005 to 11% in both 2011 and 2016. Patterns by background characteristics  Older women are much more likely than younger women to have co-wives. The percentage of women with co-wives ranges from 4% among those age 15-19 to 18% among those age 45-49 (Table 4.2.1).  Women living in rural areas are more likely to report having co-wives (12%) than women living in urban areas (5%).  The Somali region has the highest percentage of women who report being in a polygynous union (29%), while the Amhara region has the lowest percentage (1%) (Figure 4.2).  Women with no education are much more likely to have co-wives (14%) than women who have attended school (7% or less) (Table 4.2.1). Figure 4.2 Polygyny by region 1 2 3 5 6 14 16 19 21 21 29 Amhara Addis Ababa Tigray Harari Dire Dawa Oromiya SNNPR Affar Gambela Benishangul-Gumuz Somali Percentage of currently married women age 15-49 in a polygynous union Marriage and Sexual Activity • 67 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 25-49 and men age 20-49, 25-49, 20-59, and 25-59 In Ethiopia, women tend to marry considerably earlier than men. The median age at first marriage is 17.1 years among women age 25-49 and 23.8 years among men age 25-59. Fifty-eight percent of women and only 9% of men age 25-49 marry before their 18th birthday (Table 4.3). Trends: The median age at first marriage among women age 25-49 has increased slightly since 2011, from 16.5 years to 17.1 years. During the same period, the percentage of women marrying before age 18 has declined from 63% to 58%. Eight percent of women married before their 15th birthday in 2011, as compared with 6% in 2016. Among men age 25-59, median age at first marriage increased slightly from 23.1 years in 2011 to 23.8 years in 2016. When the data is analysed by cohort of women, defined by their age at the moment of the interview, those changes look more dramatic. The result shows that the percentage of women 45-49 married before age 15 is 29%, while this indicator is 14% for women 20-24 and 6% for the youngest women (15-19). Patterns by background characteristics  Women living in urban areas marry later than women living in rural areas. Median age at first marriage is 2.6 years older among urban women than rural women (19.3 years versus 16.7 years) (Table 4.4).  Median age at first marriage varies by region, from 15.7 years among women in Amhara to 23.9 years among women in Addis Ababa.  Median age at first marriage increases with increasing education, from 16.3 years among women with no education to 24.0 years among women with more than a secondary education (Figure 4.3). 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 25-49 and men age 20-49, 25-49, 20-59, and 25-59 In Ethiopia, the median age at first sexual intercourse among women age 25-49 is 16.6 years. One in four (24%) women have first sexual intercourse before age 15 and 62% before age 18. By age 20, 76% of women have had sexual intercourse (Table 4.5). On average, men in Ethiopia initiate sexual intercourse at older ages than women. The median age at first intercourse among men age 25-49 is 21.2 years. Only 2% of men have first sex before age 15, while 17% have initiated sexual intercourse by age 18. By age 20, 36% of men have had sexual intercourse. Figure 4.3 Women’s median age at marriage by education 16.3 17.8 22.4 24.0 No education Primary Secondary More than secondary Median age at first marriage among women age 25-49 68 • Marriage and Sexual Activity Age at first marriage is widely considered a proxy indicator for the age at which women begin to be exposed to the risks inherent in sexual activity. 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. Among women age 25-49 in Ethiopia, the median age at first intercourse is 0.5 years younger than the median age at first marriage (16.6 years versus 17.1 years). This indicates that many women engage in sex before marriage (Figure 4.4). Thus, women in Ethiopia may be exposed to the risk of pregnancy and begin childbearing at an even earlier age than indicated by the median age at first marriage. The median age at first intercourse among men age 25-49 is 21.2 years. By contrast, the median age at first marriage among men age 25-49 is 23.7 years. Thus, on average, men in Ethiopia initiate sexual intercourse 2.5 years before marriage. Trends: The percentages of women age 25-49 and men age 25-59 who have had sexual intercourse by age 18 have declined over time. Among women, the proportion having first sex by age 18 declined from 69% in 2000 to 62% in 2016. The corresponding figures among men are 25% and 17% (Figure 4.5). Median age at first sexual intercourse among women age 25-49 has not changed over the past 5 years (16.6 years in both 2011 and 2016). The corresponding figures among men age 25-59 are 21.1 years and 21.2 years. However, as indicated in the case of age at first marriage, the age- disaggregated data by cohort shows a consistent and remarkable decline (see Table 4.5), similar to the decline observed in age at first marriage. Patterns by background characteristics  Rural women begin having sexual intercourse about 2.2 years earlier than urban women (16.3 years versus 18.5 years) (Table 4.6).  By region, women’s median age at first sexual intercourse is lowest in Amhara (15.5 years) and highest in Addis Ababa (20.4 years).  Median age at first sexual intercourse generally increases with increasing education among both women and men. There is a 6.3-year gap in median age at first sex between women with no education and women with more than a secondary education and a corresponding 1.3-year gap among men. 4.5 RECENT SEXUAL ACTIVITY The survey also collected data on recent sexual activity. Overall, 54% of women and 49% of men age 15- 49 reported having sexual intercourse during the 4 weeks before the survey. Twenty-three percent of Figure 4.4 Median age at first sex and first marriage Figure 4.5 Trends in early sexual intercourse 16.6 17.1 21.2 23.8 Median age at first sex Median age at first marriage Median age in years Women age 25-49 Men age 25-59 69 65 62 62 25 16 18 17 2000 EDHS 2005 EDHS 2011 EDHS 2016 EDHS Percentage who had first sexual intercourse by age 18 Women age 25-49 Men age 25-59 Marriage and Sexual Activity • 69 women and 33% of men have never had sexual intercourse. For more information on recent sexual activity, see Tables 4.7.1 and 4.7.2. 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 according to background characteristics  Table 4.5 Age at first sexual intercourse  Table 4.6 Median age at first sexual intercourse according to background characteristics  Table 4.7.1 Recent sexual activity: Women  Table 4.7.2 Recent sexual activity: Men 70 • 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, Ethiopia DHS 2016 Marital status Total Percentage of respondents currently in a union Number of respondents Age Never married Married Living together Divorced Separated Widowed WOMEN 15-19 78.1 16.8 0.6 2.9 1.6 0.0 100.0 17.4 3,381 20-24 31.1 59.9 2.0 4.7 1.9 0.4 100.0 61.9 2,762 25-29 11.7 79.7 1.6 4.7 1.3 1.2 100.0 81.3 2,957 30-34 4.1 86.0 1.4 5.3 1.4 1.9 100.0 87.4 2,345 35-39 3.2 82.1 1.4 6.4 1.3 5.6 100.0 83.5 1,932 40-44 1.8 81.3 1.1 5.3 1.1 9.2 100.0 82.5 1,290 45-49 1.1 77.1 1.5 7.9 1.6 10.9 100.0 78.5 1,017 Total 15-49 25.7 63.9 1.3 4.9 1.5 2.7 100.0 65.2 15,683 MEN 15-19 98.3 1.0 0.0 0.4 0.3 0.0 100.0 1.0 2,572 20-24 72.3 23.0 2.1 2.3 0.2 0.0 100.0 25.2 1,883 25-29 34.1 58.1 4.0 2.8 0.7 0.3 100.0 62.1 1,977 30-34 11.7 78.9 6.1 2.5 0.6 0.3 100.0 85.0 1,635 35-39 4.7 86.3 6.5 1.7 0.3 0.5 100.0 92.8 1,386 40-44 3.5 89.5 4.7 1.6 0.4 0.3 100.0 94.2 1,206 45-49 2.1 92.1 3.2 2.1 0.0 0.5 100.0 95.3 947 Total 15-49 42.1 52.1 3.4 1.8 0.4 0.2 100.0 55.5 11,606 50-59 1.2 92.6 2.5 1.8 0.4 1.6 100.0 95.1 1,082 Total 15-59 38.6 55.5 3.3 1.8 0.4 0.4 100.0 58.9 12,688 Table 4.2.1 Number of women’s co-wives Percent distribution of currently married women age 15-49 by number of co-wives, and percentage of currently married women with one or more co-wives, according to background characteristics, Ethiopia DHS 2016 Background characteristic Number of co-wives Total Percentage with one or more co- wives1 Number of women 0 1 2+ Don’t know Age 15-19 96.1 3.5 0.0 0.4 100.0 3.5 588 20-24 95.6 3.8 0.2 0.5 100.0 3.9 1,710 25-29 92.1 6.3 1.0 0.6 100.0 7.3 2,402 30-34 86.2 11.9 1.3 0.6 100.0 13.2 2,049 35-39 85.3 12.0 1.7 1.0 100.0 13.8 1,613 40-44 82.2 14.5 2.5 0.7 100.0 17.1 1,064 45-49 81.7 14.1 3.5 0.8 100.0 17.6 798 Residence Urban 93.5 4.6 0.7 1.3 100.0 5.2 1,658 Rural 87.9 10.1 1.5 0.5 100.0 11.6 8,565 Region Tigray 95.0 2.8 0.4 1.7 100.0 3.2 658 Affar 80.2 16.4 2.8 0.5 100.0 19.2 96 Amhara 97.9 0.7 0.2 1.2 100.0 0.9 2,414 Oromiya 86.1 12.1 1.5 0.3 100.0 13.6 3,987 Somali 70.8 24.7 4.5 0.1 100.0 29.2 324 Benishangul-Gumuz 79.1 15.2 5.7 0.0 100.0 20.9 114 SNNPR 84.2 13.7 1.9 0.2 100.0 15.6 2,173 Gambela 78.2 15.0 5.6 1.2 100.0 20.6 29 Harari 95.5 4.2 0.3 0.0 100.0 4.5 25 Addis Ababa 95.9 1.4 0.4 2.4 100.0 1.8 355 Dire Dawa 93.6 4.9 0.8 0.7 100.0 5.7 50 Education No education 85.7 12.0 1.8 0.6 100.0 13.8 6,253 Primary 93.0 5.8 0.8 0.5 100.0 6.6 2,895 Secondary 95.3 2.4 0.1 2.1 100.0 2.5 654 More than secondary 96.7 2.1 0.3 0.9 100.0 2.4 421 Wealth quintile Lowest 84.4 13.5 2.1 0.1 100.0 15.6 1,953 Second 88.4 9.6 1.4 0.6 100.0 11.0 2,074 Middle 88.6 10.1 0.7 0.6 100.0 10.8 2,057 Fourth 88.8 8.4 2.0 0.9 100.0 10.3 1,999 Highest 93.5 4.9 0.6 1.1 100.0 5.5 2,140 Total 88.8 9.2 1.3 0.7 100.0 10.5 10,223 1 Excludes women who responded “don’t know” when asked if their husband has other wives Marriage and Sexual Activity • 71 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, Ethiopia DHS 2016 Background characteristic Number of wives Total Number of men 1 2+ Age 15-19 (100.0) (0.0) 100.0 26 20-24 99.3 0.7 100.0 474 25-29 98.2 1.8 100.0 1,227 30-34 96.6 3.4 100.0 1,389 35-39 94.4 5.6 100.0 1,285 40-44 91.9 8.1 100.0 1,137 45-49 92.0 8.0 100.0 903 Residence Urban 98.4 1.6 100.0 1,011 Rural 94.6 5.4 100.0 5,430 Region Tigray 99.8 0.2 100.0 352 Affar 89.0 11.0 100.0 48 Amhara 99.4 0.6 100.0 1,633 Oromiya 93.7 6.3 100.0 2,558 Somali 88.1 11.9 100.0 174 Benishangul-Gumuz 90.2 9.8 100.0 72 SNNPR 92.3 7.7 100.0 1,323 Gambela 91.8 8.2 100.0 17 Harari 96.1 3.9 100.0 16 Addis Ababa 100.0 0.0 100.0 217 Dire Dawa 98.2 1.8 100.0 32 Education No education 95.1 4.9 100.0 2,558 Primary 93.9 6.1 100.0 2,769 Secondary 98.3 1.7 100.0 625 More than secondary 99.3 0.7 100.0 489 Wealth quintile Lowest 92.8 7.2 100.0 1,161 Second 96.0 4.0 100.0 1,359 Middle 95.0 5.0 100.0 1,310 Fourth 94.2 5.8 100.0 1,255 Highest 97.6 2.4 100.0 1,357 Total 15-49 95.2 4.8 100.0 6,441 50-59 87.0 13.0 100.0 1,029 Total 15-59 94.1 5.9 100.0 7,471 Note: Figures in parentheses are based on 25-49 unweighted cases. 72 • Marriage and Sexual Activity Table 4.3 Age at first marriage Percentage of women and men age 15-49 who were first married by specific exact ages and median age at first marriage, according to current age, Ethiopia DHS 2016 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 5.7 na na na na 78.1 3,381 a 20-24 14.1 40.3 57.8 na na 31.1 2,762 19.0 25-29 20.5 49.3 65.5 75.0 84.8 11.7 2,957 18.1 30-34 27.3 61.3 74.0 82.8 90.9 4.1 2,345 16.9 35-39 26.8 60.2 73.2 81.8 87.6 3.2 1,932 16.8 40-44 31.9 66.0 77.7 84.7 92.0 1.8 1,290 16.2 45-49 29.1 64.0 75.7 83.2 90.8 1.1 1,017 16.5 20-49 23.3 54.2 68.7 na na 11.3 12,302 17.5 25-49 25.9 58.3 71.9 80.5 88.5 5.6 9,540 17.1 MEN 15-19 0.0 na na na na 98.3 2,572 a 20-24 0.2 5.0 13.4 na na 72.3 1,883 a 25-29 0.4 7.9 16.9 29.2 51.6 34.1 1,977 24.7 30-34 0.4 8.2 21.6 36.8 58.7 11.7 1,635 23.7 35-39 0.8 10.1 23.2 40.3 64.1 4.7 1,386 23.1 40-44 0.3 9.7 26.6 43.0 62.4 3.5 1,206 22.9 45-49 0.6 10.9 24.6 39.7 59.3 2.1 947 23.4 20-49 0.4 8.2 20.1 na na 26.1 9,033 a 25-49 0.5 9.1 21.9 36.8 58.5 13.9 7,151 23.7 20-59 0.5 8.3 20.0 na na 23.4 10,116 a 25-59 0.5 9.1 21.6 36.2 57.8 12.2 8,233 23.8 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% of the women or men began living with their spouse or partner for the first time before reaching the beginning of the age group Marriage and Sexual Activity • 73 Table 4.4 Median age at first marriage according to 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 25-59, according to background characteristics, Ethiopia DHS 2016 Background characteristic Women age Men age 25-59 20-49 25-49 Residence Urban a 19.3 a Rural 17.0 16.7 23.1 Region Tigray 17.2 16.6 24.8 Affar 16.4 16.4 a Amhara 16.2 15.7 22.5 Oromiya 17.4 17.2 24.0 Somali 18.1 18.1 24.1 Benishangul-Gumuz 17.1 16.8 22.7 SNNPR 18.2 17.7 23.5 Gambela 17.3 16.9 23.8 Harari 18.5 18.3 a Addis Ababa a 23.9 a Dire Dawa 18.7 18.1 a Education No education 16.4 16.3 22.7 Primary 18.1 17.8 23.2 Secondary a 22.4 a More than secondary a 24.0 a Wealth quintile Lowest 17.1 16.9 23.0 Second 16.6 16.4 23.4 Middle 17.0 16.7 23.3 Fourth 17.5 16.9 22.7 Highest 19.9 18.7 a Total 17.5 17.1 23.8 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% of the women or men began living with their spouse or partner for the first time before reaching the beginning of the age group 74 • Marriage and Sexual Activity Table 4.5 Age at first sexual intercourse Percentage of women and men age 15-49 who had first sexual intercourse by specific exact ages, percentage who never had sexual intercourse, and median age at first sexual intercourse, according to current age, Ethiopia DHS 2016 Percentage who had first sexual intercourse by exact age: Percentage who never had intercourse Number Median age at first intercourse Current age 15 18 20 22 25 WOMEN 15-19 6.3 na na na na 75.4 3,381 a 20-24 13.2 43.1 62.1 na na 26.4 2,762 18.6 25-29 19.8 52.5 67.6 77.9 87.1 8.6 2,957 17.7 30-34 23.9 64.3 78.6 85.4 90.8 2.9 2,345 16.6 35-39 23.5 65.7 77.6 85.7 90.1 1.7 1,932 16.5 40-44 30.1 71.0 82.3 90.4 94.0 0.8 1,290 15.9 45-49 29.4 69.0 82.7 88.5 93.7 0.5 1,017 15.9 20-49 21.6 58.0 72.8 na na 8.9 12,302 17.1 25-49 24.0 62.3 75.9 84.1 90.2 3.9 9,540 16.6 15-24 9.4 na na na na 53.4 6,143 a MEN 15-19 0.8 na na na na 91.9 2,572 a 20-24 1.3 12.0 29.6 na na 51.8 1,883 a 25-29 2.2 16.1 33.9 51.6 73.5 18.9 1,977 21.8 30-34 1.4 17.8 37.3 57.6 76.0 5.4 1,635 21.1 35-39 1.3 15.9 35.7 57.8 77.1 1.2 1,386 21.0 40-44 2.1 18.8 38.0 59.3 77.9 0.8 1,206 20.9 45-49 2.1 16.9 38.9 58.2 75.5 1.1 947 20.8 20-49 1.7 16.0 35.0 na na 16.3 9,033 a 25-49 1.8 17.0 36.4 56.3 75.8 7.0 7,151 21.2 15-24 1.0 na na na na 74.9 4,455 a 20-59 1.6 16.1 34.9 na na 14.6 10,116 a 25-59 1.7 17.0 36.2 56.0 75.6 6.1 8,233 21.2 na = Not applicable due to censoring a = Omitted because less than 50% of the respondents had sexual intercourse for the first time before reaching the beginning of the age group Table 4.6 Median age at first sexual intercourse according to 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 25- 59, according to background characteristics, Ethiopia DHS 2016 Background characteristic Women age Men age 25-59 20-49 25-49 Residence Urban 19.3 18.5 21.5 Rural 16.6 16.3 21.1 Region Tigray 16.6 16.1 22.1 Affar 16.4 16.2 20.3 Amhara 15.8 15.5 20.8 Oromiya 17.0 16.7 20.9 Somali 18.0 17.9 22.7 Benishangul-Gumuz 16.9 16.5 19.0 SNNPR 18.2 17.8 22.1 Gambela 16.6 16.2 19.5 Harari 18.1 17.7 22.5 Addis Ababa a 20.4 21.1 Dire Dawa 18.1 17.7 22.0 Education No education 16.0 16.0 20.9 Primary 17.6 17.1 21.0 Secondary a 20.8 22.0 More than secondary a 22.3 22.2 Wealth quintile Lowest 16.6 16.4 20.9 Second 16.3 16.0 21.7 Middle 16.7 16.4 21.2 Fourth 16.9 16.4 20.9 Highest 18.7 18.0 21.3 Total 17.1 16.6 21.2 a = Omitted because less than 50% of the respondents had sexual intercourse for the first time before reaching the beginning of the age group Marriage and Sexual Activity • 75 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, Ethiopia DHS 2016 Timing of last sexual intercourse Total Number of women Background characteristic Within the past 4 weeks Within 1 year1 One or more years Never had sexual intercourse Age 15-19 15.0 5.8 3.8 75.4 100.0 3,381 20-24 51.2 14.2 8.3 26.4 100.0 2,762 25-29 69.4 13.6 8.4 8.6 100.0 2,957 30-34 69.3 15.7 12.1 2.9 100.0 2,345 35-39 68.6 14.0 15.7 1.7 100.0 1,932 40-44 68.1 11.0 20.1 0.8 100.0 1,290 45-49 59.7 12.4 27.3 0.5 100.0 1,017 Marital status Never married 1.9 3.0 5.1 90.1 100.0 4,036 Married or living together 80.6 14.5 4.8 0.1 100.0 10,223 Divorced/separated/widowed 6.4 20.5 72.6 0.6 100.0 1,423 Marital duration2 0-4 years 78.3 17.9 3.4 0.3 100.0 1,788 5-9 years 82.1 13.3 4.6 0.0 100.0 1,700 10-14 years 80.0 16.0 4.0 0.0 100.0 1,667 15-19 years 83.3 10.2 6.5 0.0 100.0 1,326 20-24 years 83.6 11.8 4.6 0.0 100.0 975 25+ years 77.5 14.7 7.8 0.0 100.0 975 Married more than once 80.1 15.5 4.5 0.0 100.0 1,792 Residence Urban 38.8 12.9 15.4 32.9 100.0 3,476 Rural 57.8 11.8 9.8 20.5 100.0 12,207 Region Tigray 41.8 20.2 15.5 22.4 100.0 1,129 Affar 53.8 17.5 14.2 14.2 100.0 128 Amhara 55.1 13.2 11.9 19.8 100.0 3,714 Oromiya 58.9 10.0 10.5 20.7 100.0 5,701 Somali 48.9 18.0 11.0 22.0 100.0 459 Benishangul-Gumuz 61.0 9.6 9.2 20.2 100.0 160 SNNPR 54.3 9.8 7.5 28.3 100.0 3,288 Gambela 43.2 20.7 20.6 15.4 100.0 44 Harari 45.3 18.2 14.6 21.9 100.0 38 Addis Ababa 30.0 14.4 17.1 38.5 100.0 930 Dire Dawa 44.0 14.0 16.0 26.0 100.0 90 Education No education 68.2 13.7 12.7 5.4 100.0 7,498 Primary 43.7 10.4 9.7 36.3 100.0 5,490 Secondary 29.7 9.3 8.5 52.3 100.0 1,817 More than secondary 40.4 14.3 10.6 34.7 100.0 877 Wealth quintile Lowest 57.9 14.8 12.9 14.4 100.0 2,633 Second 60.3 12.0 10.1 17.7 100.0 2,809 Middle 57.5 12.3 9.2 21.0 100.0 2,978 Fourth 55.2 10.0 8.8 25.9 100.0 3,100 Highest 42.3 11.8 13.5 32.4 100.0 4,163 Total 53.6 12.1 11.0 23.3 100.0 15,683 1 Excludes women who had sexual intercourse within the last 4 weeks 2 Excludes women who are not currently married 76 • 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, Ethiopia DHS 2016 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 Age 15-19 2.4 3.3 2.4 91.9 100.0 2,572 20-24 26.3 13.2 8.7 51.8 100.0 1,883 25-29 56.3 16.6 8.2 18.9 100.0 1,977 30-34 74.7 14.4 5.5 5.4 100.0 1,635 35-39 78.2 14.9 5.7 1.2 100.0 1,386 40-44 79.4 14.8 5.0 0.8 100.0 1,206 45-49 83.8 10.2 4.9 1.1 100.0 947 Marital status Never married 5.0 9.0 7.7 78.3 100.0 4,882 Married or living together 84.5 12.9 2.4 0.1 100.0 6,441 Divorced/separated/widowed 12.9 37.3 47.0 2.7 100.0 282 Marital duration2 0-4 years 84.0 13.2 2.3 0.4 100.0 1,315 5-9 years 81.5 15.4 3.1 0.0 100.0 1,105 10-14 years 83.8 13.8 2.4 0.0 100.0 1,000 15-19 years 83.4 14.9 1.8 0.0 100.0 673 20-24 years 86.5 10.5 3.0 0.0 100.0 530 25+ years 88.3 9.5 2.2 0.0 100.0 258 Married more than once 86.8 11.0 2.0 0.2 100.0 1,559 Residence Urban 41.3 16.6 9.2 32.9 100.0 2,303 Rural 51.3 10.7 4.8 33.1 100.0 9,302 Region Tigray 40.6 16.7 5.5 37.2 100.0 708 Affar 55.9 19.7 6.8 17.7 100.0 82 Amhara 49.8 11.3 6.0 32.8 100.0 2,914 Oromiya 53.4 9.7 4.7 32.2 100.0 4,409 Somali 47.2 10.8 3.8 38.2 100.0 301 Benishangul-Gumuz 56.9 14.0 6.0 23.1 100.0 118 SNNPR 48.6 9.6 5.9 35.9 100.0 2,371 Gambela 43.9 23.8 10.0 22.3 100.0 35 Harari 41.2 20.4 5.9 32.5 100.0 29 Addis Ababa 30.3 32.1 11.1 26.5 100.0 573 Dire Dawa 42.0 17.0 10.3 30.7 100.0 66 Education No education 68.3 12.6 4.6 14.5 100.0 3,203 Primary 44.8 8.9 4.5 41.8 100.0 5,608 Secondary 31.3 14.0 9.2 45.6 100.0 1,785 More than secondary 46.4 22.6 9.5 21.5 100.0 1,010 Wealth quintile Lowest 54.4 10.7 4.0 30.9 100.0 1,839 Second 57.0 10.3 4.2 28.5 100.0 2,118 Middle 50.5 10.0 4.7 34.7 100.0 2,246 Fourth 46.2 10.8 5.9 37.0 100.0 2,466 Highest 42.4 16.1 8.4 33.0 100.0 2,935 Total 15-49 49.4 11.9 5.7 33.1 100.0 11,606 50-59 75.8 16.2 7.8 0.2 100.0 1,082 Total 15-59 51.6 12.3 5.9 30.3 100.0 12,688 1 Excludes men who had sexual intercourse within the last 4 weeks 2 Excludes men who are not currently married Fertility • 77 FERTILITY 5 Key Findings  Total fertility rate: The total fertility rate for the 3 years preceding the survey is 4.6 children per woman (2.3 in urban areas and 5.2 in rural areas).  Patterns of fertility: Fertility levels are much lower among highly educated women and women living in Addis Ababa.  Teenage pregnancy: Among women age 15-19, 10% are already mothers and 2% are pregnant with their first child.  Birth intervals: The median birth interval in Ethiopia is 34.5 months. The interval is longer in urban areas than in rural areas.  Age at first birth: The median age at first birth among women age 25-49 is 19.2 years. he 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) are associated with harmful outcomes for both newborns and their mothers, such as preterm birth, low birth weight, and death. Childbearing at a very young age is linked to an increased risk of complications during pregnancy and childbirth and higher rates of neonatal mortality. This chapter describes the current level of fertility in Ethiopia 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. 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 Ethiopia is 4.6 children per woman. The age-specific fertility rate in the 15- 19 age group is 80 births per 1,000 women. Fertility peaks at age 25-29 (214 births per 1,000 women) and drops thereafter, to 22 births per 1,000 women in the 45-49 age group. Age-specific fertility rates are lower in urban areas than in rural areas among women in all age groups. On average, rural women have 2.9 more children than urban women (5.2 versus 2.3 children) (Table 5.1). T 78 • Fertility Trends: The TFR has declined in Ethiopia over time, from 5.5 children per woman in 2000 to 4.6 children per woman in 2016, a decrease of 0.9 children. The decline is most obvious between the two most recent 5-year periods. The TFR among women in rural areas declined from 6.0 children in 2000 to 5.2 children in 2016. In urban areas, the TFR declined from 3.0 children in 2000 to 2.3 children in 2016 (Table 5.3.1 and Figure 5.1). In all EDHS surveys, age-specific fertility rate are higher in women age 20-34 (Figure 5.2). Figure 5.2 Trends in age-specific fertility Patterns by background characteristics  By region, the TFR is highest in Somali (7.2 children per woman) and lowest in Addis Ababa (1.8 children per woman) (Table 5.2 and Figure 5.3).  The number of children per woman declines with increasing education. Women with no education have 3.8 more children than women with more than a secondary education (5.7 children versus 1.9 children) (Figure 5.4). Figure 5.4 Fertility by education 0 50 100 150 200 250 300 15-19 20-24 25-29 30-34 35-39 40-44 45-49 Age group Births per 1,000 women 2000 EDHS 2011 EDHS 2005 EDHS 2016 EDHS 5.7 4.2 2.2 1.9 No education Primary Secondary More than secondary TFR for the 3 years before the survey Figure 5.1 Trends in fertility by residence Figure 5.3 Fertility by region 5.5 5.4 4.8 4.6 3.0 2.4 2.6 2.3 6.0 6.0 5.5 5.2 2000 EDHS 2005 EDHS 2011 EDHS 2016 EDHS TFR for the 3 years before each survey Rural Total Urban 1.8 3.1 3.5 3.7 4.1 4.4 4.4 4.7 5.4 5.5 7.2 Addis Ababa Dire Dawa Gambela Amhara Harari Benishangul-Gumuz SNNPR Tigray Oromiya Affar Somali TFR for the 3 years before the survey Fertility • 79  Similarly, women in the lowest wealth quintile have 3.8 more children than women in the highest wealth quintile (6.4 children versus 2.6 children). 5.2 CHILDREN EVER BORN AND LIVING The 2016 EDHS also collected information on the number of children ever born to women age 15-49 and those still surviving by the time of the survey. On average, women age 45-49 have given birth to 6.6 children, of whom 5.4 survived to the time of the survey. Of the 7.0 children on average born to currently married women age 45-49, 5.8 survived to the time of the survey. In Ethiopia, 2% of currently married women age 45-49 have never given birth. Since voluntary childlessness is rare, this is often viewed as a measure of primary sterility (Table 5.4). 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 Short birth intervals, particularly those less than 24 months, place newborns and their mothers at increased health risk. The median birth interval in Ethiopia is 34.5 months; thus, half of non-first births occur within 3 years after the first birth (Table 5.5). One in three births (32%) occur within 24-35 months of the previous birth, and one in five births (21%) occur within at least 3 years after the previous birth (Figure 5.5). Trends: There are no substantial differences in the length of the median birth interval over the last 15 years in Ethiopia. Median intervals were 33.6 months in 2000, 33.8 months in 2005, 33.9 months in 2011, and 34.5 months in 2016. Patterns by background characteristics  Births to older women occur after longer intervals than births to younger women. The median birth interval among women age 40-49 is nearly 15 months longer than the interval among women age 15- 19 (39.0 months versus 24.5 months).  The median birth interval is 8 months longer if the child from the preceding birth is living than if the child has died. In contrast, there is no difference in the median birth interval by sex of the child.  Rural women have shorter birth intervals than urban women (34.0 versus 46.8 months).  Across regions, the median birth interval ranges from 25.1 months in Somali to 47.6 months in Addis Ababa.  Median birth intervals increase with increasing education and wealth. For example, birth intervals among women with more than a secondary education are 13.7 months longer than intervals among women with no education (47.7 months versus 34.0 months). Likewise, birth intervals among women in the highest wealth quintile are 10.9 months longer than those among women in the lowest quintile (43.0 versus 32.1 months). Figure 5.5 Birth intervals 7-17 9% 18-23 12% 24-35 32% 36-47 21% 48-59 11% 60+ 14% Percent distribution of non-first births by number of months preceding birth 80 • Fertility 5.4 INSUSCEPTIBILITY TO PREGNANCY Postpartum amenorrhoea The period of time after the birth of a child and before the resumption of menstruation. Postpartum abstinence The period of time after the birth of a child and before the resumption of sexual intercourse. Postpartum insusceptibility The period of time during which a woman is considered not at risk of pregnancy because she is postpartum amenorrhoeic and/or abstaining from sexual intercourse. Sample: Women age 15-49 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 by either postpartum amenorrhoea or abstinence from sexual intercourse. Sample: Women who gave birth in the 3 years before the survey Postpartum amenorrhoea refers to the interval between the birth of a child and the resumption of menstruation. The length and intensity of breastfeeding influence the duration of amenorrhoea, which offers protection from conception. Postpartum abstinence refers to the period between childbirth and the time when a woman resumes sexual activity. Among births in the 3 years preceding the survey, the median duration of postpartum amenorrhoea is 14.6 months, while the median duration of abstinence from sexual intercourse is 2.3 months after giving birth. Overall, women are insusceptible to pregnancy after childbirth for a median duration of 15.5 months (Table 5.6). Trends: In Ethiopia, the median duration of postpartum amenorrhoea has declined steadily since 2000, from 19.0 months to 14.6 months. In contrast, the median duration of postpartum abstinence is nearly identical over the same period (2.4 months in 2000 and 2005 and 2.3 months in 2011 and 2016). Overall, the median duration of insusceptibility declined from 19.6 months in 2000 to 15.5 months in 2016. Patterns by background characteristics  Women living in rural areas have a longer duration of postpartum insusceptibility than urban women (16.2 months and 7.3 months, respectively) because the period of postpartum amenorrhoea is longer among rural than urban women (15.3 months and 5.7 months, respectively). Postpartum abstinence is almost identical among rural and urban women (2.3 months and 2.4 months, respectively) (Table 5.7).  Consistent with duration of postpartum amenorrhoea, duration of postpartum insusceptibility decreases as mother’s education increases.  The duration of postpartum insusceptibility generally decreases with increasing wealth, falling from 17.5 months among women in the lowest quintile to 7.7 months among women in the highest quintile. Fertility • 81 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 Women who have reached menopause are no longer able to become pregnant. In Ethiopia, 16% of women age 30-49 are menopausal. The percentage of menopausal women increases with age, from 6% among those age 30-34 to 49% among those age 48-49 (Table 5.8). 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 age at which childbearing commences is an important determinant of the overall level of fertility as well as the health and well-being of the mother and child. In Ethiopia, the median age at first birth among women age 25-49 is 19.2 years. This means that half of women age 25-49 give birth for the first time before age 20 (Table 5.9). Trends: The median age at first birth seems to have changed little between 2000 and 2016. Among women age 25-49, median age at first birth was 19.0 years in 2000 and 2005, after which it increased slightly to 19.2 years in 2016. However, data by age shows an important decline in the proportion of women having birth before age 15 and 18. Patterns by background characteristics  Urban women age 25-49 begin childbearing 2.7 years later than their peers in rural areas (21.6 versus 18.9 years) (Table 5.10 and Figure 5.6).  By region, median age at first birth ranges from 18.4 years among women in Benishangul- Gumuz to 20.4 years among women in Harari.  Women with a secondary education start childbearing about 6 years later than women with no education (24.5 years versus 18.6 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 Teenage pregnancy is a major health concern because of its association with higher morbidity and mortality for both the mother and the child. Childbearing during adolescence is known to have adverse social consequences, particularly regarding educational attainment, as women who become mothers in their teens are more likely to drop out of school. In Ethiopia, 13% of women age 15-19 have begun childbearing: 10% have given birth, and an additional 2% are pregnant with their first child (Table 5.11). Figure 5.6 Median age at first birth by residence 19.2 21.6 18.9 Total Urban Rural Median age at first birth among women age 25-49 82 • Fertility Trends: The percentage of teenagers who have given birth or are pregnant with their first child has decreased since 2000, from 16% to 13%. Patterns by background characteristics  Teenagers in rural areas are three times more likely to have begun childbearing than their urban peers: 15% of rural teenagers have had a live birth or are pregnant, as compared with 5% of urban teenagers.  By region, teenage childbearing is highest in Affar (23%) and Somali (19%) and lowest in Addis Ababa (3%) and Amhara (8%) (Figure 5.7).  Teenage childbearing decreases with increasing education. The percentage of teenagers who have begun childbearing rises from 3% among those with more than a secondary education to 12% among those with a primary education and 28% among those with no education.  Teenage childbearing is less common in the wealthiest households: 6% of women age 15-19 from the highest wealth quintile have begun childbearing, as compared with 24% of those from the lowest quintile (Figure 5.8). Figure 5.7 Teenage pregnancy and motherhood by region Figure 5.8 Teenage pregnancy and motherhood by household wealth 3 8 11 12 13 14 16 17 17 19 23 Addis Ababa Amhara SNNPR Tigray Dire Dawa Benishangul-Gumuz Gambela Harari Oromiya Somali Affar Percentage of women age 15-19 who have begun childbearing 24 17 15 8 6 Lowest Second Middle Fourth Highest Percentage of women age 15-19 who have begun childbearing Poorest Wealthiest Fertility • 83  Women start having sexual intercourse at an earlier age than men. Figure 5.9 shows that 6% of women age 15-19 had sexual intercourse and married before age 15, compared with less than 1% of men in the same age group. 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  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 5.9 Sexual and reproductive health behaviours before age 15 6 6 11 0 1 Had sexual intercourse before age 15 Married before age 15 Gave birth/ fathered a child before age 15 Percentage of women and men age 15-19 Women Men 84 • 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, Ethiopia DHS 2016 Residence Total Age group Urban Rural 15-19 20 98 80 20-24 113 230 200 25-29 120 243 214 30-34 112 210 190 35-39 77 153 138 40-44 14 80 69 45-49 0 27 22 TFR (15-49) 2.3 5.2 4.6 GFR 81 177 156 CBR 23.9 33.2 31.8 Note: Age-specific fertility rates are per 1,000 women. Rates for the 45-49 age group may be slightly biased due to truncation. Rates are for the period 1-36 months prior to the 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 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, according to background characteristics, Ethiopia DHS 2016 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 2.3 4.6 4.3 Rural 5.2 8.0 6.8 Region Tigray 4.7 5.0 6.1 Affar 5.5 9.5 6.5 Amhara 3.7 5.9 6.2 Oromiya 5.4 8.3 6.7 Somali 7.2 12.9 7.4 Benishangul-Gumuz 4.4 7.3 6.7 SNNPR 4.4 8.0 6.9 Gambela 3.5 5.9 4.9 Harari 4.1 9.2 4.3 Addis Ababa 1.8 2.6 2.6 Dire Dawa 3.1 5.5 5.2 Education No education 5.7 8.1 6.8 Primary 4.2 7.2 5.8 Secondary 2.2 5.2 2.9 More than secondary 1.9 4.5 3.1 Wealth quintile Lowest 6.4 9.8 7.0 Second 5.6 9.4 6.6 Middle 4.9 7.2 6.6 Fourth 4.3 6.4 6.9 Highest 2.6 4.8 4.8 Total 4.6 7.2 6.4 Note: Total fertility rates are for the period 1-36 months prior to the interview. Fertility • 85 Table 5.3.1 Trends in age-specific fertility rates Age-specific fertility rates for 5-year periods preceding the survey, according to mother’s age at the time of the birth, Ethiopia DHS 2016 Number of years preceding survey Mother’s age at birth 0-4 5-9 10-14 15-19 15-19 83 133 180 173 20-24 213 259 283 261 25-29 218 278 295 256 30-34 203 259 271 [252] 35-39 143 196 [233] 40-44 75 [116] 45-49 [22] Note: Age-specific fertility rates are per 1,000 women. Estimates in brackets are truncated. Rates exclude the month of the interview. Table 5.3.2 Trends in age-specific and total fertility rates Age-specific and total fertility rates (TFR) for the 3-year period preceding various surveys, according to mother’s age at the time of the birth, Ethiopia DHS 2016 Mother’s age at birth 2000 EDHS (1997-2000) 2005 EDHS (2002-2005) 2011 EDHS (2008-2011) 2016 EDHS (2013-2016) 15-19 100 104 79 80 20-24 235 228 206 200 25-29 251 241 237 214 30-34 243 231 194 190 35-39 168 160 147 138 40-44 89 84 69 69 45-49 19 34 28 22 TFR 15-49 5.5 5.4 4.8 4.6 Note: Age-specific fertility rates are per 1,000 women. Rates for the 45-49 age group may be slightly biased due to truncation. 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, Ethiopia DHS 2016 Number of children ever born Total Number of women Mean number of children ever born Mean number of living children Age 0 1 2 3 4 5 6 7 8 9 10+ ALL WOMEN 15-19 89.9 8.9 1.1 0.1 0.0 0.0 0.0 0.0 0.0 0.0 0.0 100.0 3,381 0.11 0.11 20-24 44.7 27.4 17.6 7.2 2.5 0.5 0.0 0.0 0.0 0.0 0.0 100.0 2,762 0.97 0.91 25-29 17.3 16.3 19.4 19.0 13.9 8.3 3.0 1.7 0.8 0.1 0.2 100.0 2,957 2.48 2.27 30-34 6.5 6.4 11.0 17.7 16.0 17.3 11.9 8.6 3.3 1.1 0.3 100.0 2,345 4.02 3.66 35-39 4.8 3.7 7.4 8.9 12.4 15.6 14.4 13.9 10.1 5.0 3.8 100.0 1,932 5.22 4.63 40-44 2.8 2.7 4.5 7.7 8.5 11.7 13.1 16.5 13.7 9.9 9.0 100.0 1,290 6.16 5.25 45-49 2.8 2.9 4.1 4.9 8.1 10.3 11.0 13.8 16.1 11.7 14.5 100.0 1,017 6.61 5.42 Total 32.5 11.6 10.2 9.6 8.2 7.8 5.9 5.6 4.1 2.4 2.2 100.0 15,683 2.84 2.51 CURRENTLY MARRIED WOMEN 15-19 52.1 41.9 6.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 100.0 588 0.54 0.52 20-24 18.6 38.2 26.9 11.4 4.0 0.8 0.1 0.0 0.0 0.0 0.0 100.0 1,710 1.47 1.38 25-29 6.1 16.1 22.2 22.3 16.4 10.2 3.3 2.1 1.0 0.1 0.2 100.0 2,402 2.90 2.64 30-34 2.4 5.3 10.0 18.0 17.4 19.0 13.0 9.6 3.8 1.2 0.3 100.0 2,049 4.34 3.95 35-39 1.8 1.8 5.3 8.6 11.9 16.3 16.4 16.2 11.9 5.5 4.3 100.0 1,613 5.69 5.06 40-44 1.3 1.3 3.5 5.8 7.1 11.7 13.5 18.5 15.4 11.2 10.7 100.0 1,064 6.62 5.65 45-49 1.5 1.7 3.1 3.8 7.6 9.5 11.9 12.6 17.7 13.1 17.4 100.0 798 7.03 5.76 Total 8.5 14.2 13.5 13.0 11.2 10.9 8.3 7.9 5.9 3.3 3.3 100.0 10,223 3.96 3.51 86 • Fertility Table 5.5 Birth intervals Percent distribution of non-first births in the 5 years before the survey by number of months since preceding birth, and median number of months since preceding birth, according to background characteristics, Ethiopia DHS 2016 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 22.8 23.6 44.7 8.4 0.5 0.0 100.0 43 24.5 20-29 12.5 13.6 35.1 20.4 9.8 8.5 100.0 3,800 32.2 30-39 7.3 11.0 31.5 20.4 12.3 17.4 100.0 4,150 36.1 40-49 5.2 12.1 25.3 21.6 12.7 23.2 100.0 960 39.0 Sex of preceding birth Male 9.8 12.0 32.2 21.1 10.4 14.5 100.0 4,627 34.4 Female 8.9 12.6 32.7 19.9 12.1 13.8 100.0 4,326 34.5 Survival of preceding birth Living 8.2 12.1 32.5 21.1 11.6 14.6 100.0 8,318 35.0 Dead 24.6 15.5 31.3 12.9 7.1 8.7 100.0 635 27.0 Birth order 2-3 8.4 10.6 30.5 20.8 12.1 17.7 100.0 3,366 36.2 4-6 10.4 12.8 33.3 19.8 10.6 13.1 100.0 3,595 34.0 7+ 9.2 14.3 34.1 21.4 11.0 10.0 100.0 1,992 33.4 Residence Urban 5.5 9.9 21.3 15.7 13.2 34.2 100.0 802 46.8 Rural 9.8 12.5 33.5 21.0 11.1 12.2 100.0 8,151 34.0 Region Tigray 4.2 7.6 29.9 22.0 16.9 19.3 100.0 542 38.9 Affar 14.3 19.9 35.1 16.4 6.6 7.8 100.0 89 27.3 Amhara 4.4 6.2 22.9 23.4 14.6 28.4 100.0 1,681 44.1 Oromiya 11.3 13.7 36.8 19.4 9.7 9.2 100.0 4,007 32.3 Somali 22.4 23.5 32.3 13.4 4.8 3.6 100.0 441 25.1 Benishangul-Gumuz 10.3 14.7 32.5 22.9 9.2 10.4 100.0 100 32.8 SNNPR 8.1 13.4 33.1 21.9 11.7 11.8 100.0 1,885 34.4 Gambela 4.6 9.3 31.4 21.3 15.0 18.6 100.0 20 38.5 Harari 10.5 15.3 32.0 16.4 10.8 15.0 100.0 20 33.0 Addis Ababa 5.6 6.9 22.1 15.9 12.7 36.8 100.0 135 47.6 Dire Dawa 11.0 18.2 28.0 19.3 8.6 14.9 100.0 34 32.4 Education No education 9.7 13.0 32.9 20.2 11.1 13.2 100.0 6,619 34.0 Primary 9.0 10.8 32.8 21.4 11.5 14.5 100.0 1,961 35.1 Secondary 5.1 8.0 22.2 25.0 16.7 23.0 100.0 246 43.2 More than secondary 7.4 7.6 23.4 13.0 6.9 41.7 100.0 127 47.7 Wealth quintile Lowest 11.6 15.6 34.0 21.5 9.9 7.5 100.0 2,250 32.1 Second 10.6 13.7 33.1 20.3 11.3 11.1 100.0 2,091 33.4 Middle 9.4 10.8 33.6 20.9 9.9 15.4 100.0 1,896 34.5 Fourth 8.0 10.4 33.1 19.7 13.1 15.7 100.0 1,607 35.5 Highest 4.6 8.5 24.9 19.5 13.5 29.1 100.0 1,108 43.0 Total 9.4 12.3 32.4 20.5 11.3 14.1 100.0 8,953 34.5 Note: 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. Fertility • 87 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, by number of months since birth, and median and mean durations, Ethiopia DHS 2016 Percentage of births for which the mother is: Number of births Months since birth Amenorrhoeic Abstaining Insusceptible1 <2 89.7 79.2 94.6 392 2-3 85.2 35.9 90.4 393 4-5 76.5 24.4 79.4 434 6-7 69.6 14.6 74.0 396 8-9 69.1 11.0 72.2 369 10-11 56.7 7.5 58.9 337 12-13 60.0 9.8 63.3 428 14-15 51.9 13.7 57.0 398 16-17 37.0 6.3 39.4 332 18-19 35.6 7.7 39.0 355 20-21 29.4 8.0 33.8 290 22-23 25.5 8.3 30.6 283 24-25 11.9 10.8 17.6 396 26-27 8.5 5.4 13.2 358 28-29 10.9 6.4 16.3 300 30-31 12.4 4.2 16.0 340 32-33 12.4 6.2 17.4 337 34-35 10.3 2.9 11.5 298 Total 44.0 15.5 48.1 6,435 Median 14.6 2.3 15.5 na Mean 15.4 5.6 16.8 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 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, Ethiopia DHS 2016 Background characteristic Postpartum amenorrhoea Postpartum abstinence Postpartum insusceptibility1 Mother’s age 15-29 13.2 2.3 14.9 30-49 15.3 2.3 16.2 Residence Urban 5.7 2.4 7.3 Rural 15.3 2.3 16.2 Region Tigray 15.4 2.8 16.2 Affar 11.8 2.6 14.6 Amhara 15.2 (2.0) 15.6 Oromiya 14.6 2.3 15.5 Somali 8.3 2.0 9.4 Benishangul-Gumuz 16.6 (2.2) 17.3 SNNPR 15.5 (2.4) 16.4 Gambela 13.3 8.0 19.5 Harari 8.8 * 11.5 Addis Ababa 4.7 2.5 5.4 Dire Dawa (13.5) * 14.9 Education No education 16.0 2.1 16.8 Primary 12.9 2.5 14.6 Secondary 6.4 (2.2) 7.2 More than secondary (4.9) (4.2) (6.3) Wealth quintile Lowest 15.5 2.2 17.5 Second 15.9 2.0 16.0 Middle 15.8 (2.3) 17.1 Fourth 11.6 (2.2) 12.4 Highest 6.4 2.9 7.7 Total 14.6 2.3 15.5 Note: Medians are based on 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 88 • Fertility Table 5.8 Menopause Percentage of women age 30-49 who are menopausal, according to age, Ethiopia DHS 2016 Age Percentage menopausal1 Number of women 30-34 6.3 2,345 35-39 10.9 1,932 40-41 16.9 729 42-43 21.9 441 44-45 32.0 444 46-47 41.8 364 48-49 49.2 328 Total 15.7 6,584 1 Percentage of all women who are not pregnant and not postpartum amenorrhoeic whose last menstrual period occurred 6 or more months before the survey 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, Ethiopia DHS 2016 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 89.9 3,381 a 20-24 3.2 21.1 38.4 na na 44.7 2,762 a 25-29 5.5 31.6 50.3 65.3 77.1 17.3 2,957 20.0 30-34 6.4 39.6 61.0 75.6 85.7 6.5 2,345 18.9 35-39 8.6 39.5 59.4 73.5 84.9 4.8 1,932 19.1 40-44 8.9 46.1 62.8 76.1 88.8 2.8 1,290 18.4 45-49 8.5 38.2 59.0 74.1 86.0 2.8 1,017 19.1 20-49 6.3 34.1 53.1 na na 16.7 12,302 19.7 25-49 7.1 37.8 57.4 71.9 83.3 8.6 9,540 19.2 na = Not applicable due to censoring a = Omitted because less than 50% of women had a birth before reaching the beginning of the age group Fertility • 89 Table 5.10 Median age at first birth Median age at first birth among women age 20-49 and 25-49, according to background characteristics, Ethiopia DHS 2016 Background characteristic Women age 20-49 25-49 Residence Urban a 21.6 Rural 19.2 18.9 Region Tigray 19.6 19.2 Affar 18.7 18.6 Amhara 19.4 18.8 Oromiya 19.1 18.8 Somali 20.0 20.0 Benishangul-Gumuz 18.9 18.4 SNNPR a 19.5 Gambela 19.4 19.2 Harari a 20.4 Addis Ababa * a Dire Dawa a 20.3 Education No education 18.6 18.6 Primary a 19.7 Secondary a 24.5 More than secondary * a Wealth quintile Lowest 19.1 19.0 Second 19.0 18.8 Middle 19.4 19.0 Fourth 19.3 18.8 Highest a 20.8 Total 19.7 19.2 Note: An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. a = Omitted because less than 50% of women had a birth before reaching the beginning of the age group 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, according to background characteristics, Ethiopia DHS 2016 Background characteristic Percentage of women age 15-19 who: Percentage who have begun childbearing Number of women Have had a live birth Are pregnant with first child Age 15 0.6 1.0 1.6 708 16 3.5 0.9 4.4 701 17 11.2 2.1 13.2 641 18 14.7 4.9 19.6 913 19 25.1 2.6 27.7 417 Residence Urban 2.2 2.7 4.9 805 Rural 12.5 2.3 14.8 2,576 Region Tigray 9.4 2.5 12.0 276 Affar 20.0 3.3 23.4 30 Amhara 7.0 1.3 8.3 767 Oromiya 14.5 2.5 17.0 1,234 Somali 13.1 5.6 18.7 105 Benishangul-Gumuz 11.5 2.1 13.6 34 SNNPR 7.2 3.4 10.7 681 Gambela 14.7 1.5 16.2 9 Harari 15.3 1.6 16.9 8 Addis Ababa 1.9 1.1 3.0 217 Dire Dawa 9.3 3.2 12.5 20 Education No education 24.1 3.8 27.9 469 Primary 9.8 2.3 12.1 2,148 Secondary 2.0 2.1 4.1 678 More than secondary 3.4 0.0 3.4 87 Wealth quintile Lowest 18.8 5.2 24.0 478 Second 15.0 2.3 17.3 558 Middle 13.3 1.6 14.9 638 Fourth 6.4 1.7 8.1 716 Highest 3.6 2.2 5.8 992 Total 10.1 2.4 12.5 3,381 Fertility Preferences • 91 FERTILITY PREFERENCES 6 Key Findings  Desire for another child: Eighteen percent of currently married women age 15-49 want to have another child soon, while 36% 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, 37% of women and 27% of men want to limit childbearing.  Ideal family size: Women prefer 4.5 children on average, while men prefer 4.6 children.  Unwanted births: Of all births in the past 5 years and current pregnancies, 75% were wanted at the time of conception, 17% were mistimed, and 8% were unwanted.  Wanted births: Overall, the difference between the wanted fertility rate and the total fertility rate is one child. This suggests that Ethiopian women are currently having, on average, one child more than they want. nformation on fertility preferences can help family planning programme planners assess the desire for children, the extent of mistimed and unwanted pregnancies, and the demand for contraception to space or limit births. The underlying rationale of most family planning programmes is to give couples the freedom and ability to bear the number of children they want and to achieve the spacing of births they prefer. Data on fertility preferences may suggest the direction that fertility patterns will take in the future. 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 Fifty-six percent of currently married women age 15-49 want to have another child; 18% of these women want to have another child within 2 years, and 36% want to wait at least 2 years. The majority of other women want to limit childbearing: 37% of currently married women want no more children or are sterilised. Overall, 69% of currently married men age 15-49 want to have another child; 22% want the child within 2 years, 44% want to wait at least 2 years, and 3% are undecided with respect to time. Twenty-seven percent of currently married men want no more children or are sterilised (Table 6.1). I 92 • Fertility Preferences Trends: The percentage of currently married women age 15-49 who want no more children (including women who are sterilised) increased from 32% in 2000 to 37% in 2016. With respect to number of living children, the percentage of currently married women with four living children who want no more children increased slightly from 39% in 2000 to 43% in 2016, while the percentage of women with two living children who want no more children rose from 18% in 2000 to 22% in 2016 (Figure 6.1). Patterns by background characteristics  Fifty-seven percent of currently married women with no living children want to have a child soon, as compared with 10% of women with six or more children. The corresponding figures among men are 59% and 22%.  The proportion of currently married women who want no more children increases with number of living children, from 4% among those with no children to 67% among those with six or more children (Figure 6.2).  Women in rural areas are more likely to want to limit childbearing than women in urban areas (38% versus 30%). Similarly, rural men are more likely than urban men to want to limit childbearing (28% versus 20%) (Tables 6.2.1 and 6.2.2).  There are large differences by region in desire to limit childbearing. The proportion of women who want to limit childbearing is highest in SNNPR and Oromiya (40% each) and lowest in Somali and Affar (8% and 12%, respectively). Regional disparities in desire to limit childbearing are similar among men.  The percentage of women who want no more children decreases with increasing education, from 43% among those with no education to 15% among those with more than a secondary education. 6.2 IDEAL FAMILY SIZE 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 Figure 6.1 Trends in desire to limit childbearing by number of living children Figure 6.2 Desire to limit childbearing by number of living children 18 27 22 22 26 31 32 33 39 50 42 43 2000 EDHS 2005 EDHS 2011 EDHS 2016 EDHS Percentage of currently married women age 15-49 who want no more children 2 children 3 children 4 children 4 9 22 33 43 52 67 0 1 2 3 4 5 6+ Number of living children Percentage of currently married women age 15-49 who want no more children Fertility Preferences • 93 On average, Ethiopian men want to have the same number of children as women (4.6 children and 4.5 children, respectively) (Table 6.3). The ideal family size is slightly larger among currently married women and men than among women and men overall (Figure 6.3). Sixty-three percent of women age 15-49 consider four or more children to be ideal, while 27% prefer to have three or fewer children. Trends: Mean ideal number of children among currently married women decreased from 5.8 in 2000 and 5.1 in 2005 to 4.9 in both 2011 and 2016. Patterns by background characteristics  The more children respondents already have, the more children they consider ideal. For example, on average, women who have one child consider 3.9 children to be ideal. In contrast, women who have six or more children consider 6.3 children to be ideal (Table 6.4 and Figure 6.4).  Urban women prefer fewer children than rural women (3.8 versus 4.6).  By region, women’s ideal family size is largest in Somali (10.6 children) and smallest in Addis Ababa (3.6 children).  Mean ideal number of children decreases as women’s level of education increases. Women with no education want 5.2 children, while those with more than a secondary education want 3.6 children.  Mean ideal number of children also decreases with increasing wealth. Women in the lowest wealth quintile prefer 5.5 children, while women in the highest quintile prefer 3.9 children. 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 Figure 6.3 Ideal family size Figure 6.4 Ideal family size by number of living children 4.5 4.94.6 5.5 All Currently married Mean ideal number of children among women and men age 15-49 Women Men 4.0 3.9 4.4 4.7 5.1 5.4 6.3 3.9 4.1 4.7 5.3 6.1 6.2 7.7 0 1 2 3 4 5 6+ Number of living children Mean ideal number of children Women Men 94 • Fertility Preferences In Ethiopia, a large majority of births were wanted at the time of conception (75%), while 17% were mistimed (that is, wanted at a later date). Only 8% of births were not wanted at all (Table 6.5 and Figure 6.5). Trends: The proportion of women age 15-49 who have unwanted births has decreased steadily over time, from 17% in 2000 to 8% in 2016. Similarly, the proportion of mistimed births decreased from 20% in 2000 to 17% in 2016. Patterns by background characteristics  The more children a woman has, the more likely it is that her most recent birth was unwanted. Three percent of first births were unwanted, as compared with 13% of fourth- or higher-order births.  The likelihood of unwanted births increases with mother’s age. Three percent each of births to women less than age 20 and age 20-24 were unwanted, compared with 22% of births to women age 40-44. 6.4 WANTED FERTILITY RATES Unwanted birth Any birth in excess of the number of children a woman reported as her ideal number. Wanted birth Any birth fewer than or equal to the number of children a woman reported as her ideal number. Wanted 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, excluding unwanted births. Sample: Women age 15-49 The wanted fertility rate measures the potential demographic impact of fertility that would have prevailed in the 3 years preceding the survey if all unwanted births were prevented. It is calculated in the same manner as the total fertility rate, except that only wanted births are included. A birth is considered wanted if the number of living children at the time of conception is fewer than the ideal number of children reported by the respondent. The wanted fertility rate in Ethiopia is 3.6 children, as compared with the actual total fertility rate of 4.6 children. In other words, on average, women in Ethiopia have one child more than they wanted (Table 6.6 and Figure 6.6). Figure 6.5 Fertility planning status Figure 6.6 Trends in wanted and actual fertility Wanted then 75% Mistimed 17% Unwanted 8% Percent distribution of births to women age 15-49 in the 5 years before the survey (including current pregnancies) by planning status of births 4.9 4.0 3.8 3.6 1.0 1.4 1.0 1.0 5.9 5.4 4.8 4.6 2000 EDHS 2005 EDHS 2011 EDHS 2016 EDHS Total wanted fertility Difference TFR Wanted and actual number of children per woman Fertility Preferences • 95 Trends: The total wanted fertility rate in Ethiopia declined from 4.9 children in 2000 to 3.6 children in 2016. However, the gap between wanted and actual fertility has remained relatively constant over time (Figure 6.6). Patterns by background characteristics  The gap between wanted and actual fertility is much larger among rural women (1.2 children) than urban women (0.2 children).  The gap between wanted and actual fertility narrows with increasing education and wealth. For example, the gap falls from 1.3 among women with no education to 0.2 among women with a secondary education or higher and from 1.2 among women in the lowest wealth quintile to 0.5 among women in the highest quintile. 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 according to background characteristics  Table 6.5 Fertility planning status  Table 6.6 Wanted fertility rates 96 • Fertility Preferences 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, Ethiopia DHS 2016 Number of living children Total 15-49 Total 15-59 Desire for children 0 1 2 3 4 5 6+ WOMEN1 Have another soon2 57.0 21.5 18.2 16.0 13.0 10.4 9.5 17.5 na Have another later3 28.1 63.1 51.7 41.1 34.7 26.4 10.5 35.7 na Have another, undecided when 6.0 3.8 3.2 4.4 2.3 2.3 2.3 3.2 na Undecided 2.6 2.2 4.4 5.2 5.6 7.2 7.2 5.2 na Want no more 3.8 8.5 21.7 32.3 42.8 51.0 66.5 36.3 na Sterilised4 0.0 0.0 0.1 0.2 0.6 0.9 0.8 0.4 na Declared infecund 2.5 0.8 0.7 0.8 1.0 1.7 3.2 1.6 na Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 na Number 709 1,625 1,531 1,482 1,348 1,201 2,328 10,223 na MEN5 Have another soon2 58.5 27.3 21.6 17.7 17.7 12.1 14.7 21.8 20.8 Have another later3 31.8 61.1 58.3 48.6 40.8 37.8 26.3 44.2 39.3 Have another, undecided when 3.0 4.8 3.3 4.9 1.6 2.6 2.3 3.3 3.2 Undecided 2.2 2.3 1.8 3.4 3.7 4.4 4.5 3.2 3.0 Want no more 3.5 3.9 14.4 24.6 33.9 42.4 50.0 26.3 30.9 Sterilised4 0.0 0.1 0.3 0.0 1.5 0.4 1.1 0.5 1.2 Declared infecund 0.9 0.5 0.4 0.9 0.8 0.2 1.0 0.7 1.6 Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 Number 502 1,052 1,063 966 798 749 1,312 6,441 7,471 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 the respondent’s wife is pregnant (or, for men who have more than one current wife, if any wife is pregnant). Fertility Preferences • 97 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, Ethiopia DHS 2016 Background characteristic Number of living children1 Total 0 1 2 3 4 5 6+ Residence Urban 1.2 9.6 25.7 47.3 51.4 65.7 68.5 29.7 Rural 4.9 8.1 20.7 29.4 42.2 51.0 67.3 38.1 Region Tigray 1.2 3.6 11.5 20.3 23.1 47.1 64.7 27.6 Affar 5.5 3.0 6.3 12.7 16.4 22.2 23.0 12.4 Amhara 3.7 9.7 24.3 33.3 48.4 61.9 72.4 36.9 Oromiya 4.4 10.2 21.9 34.1 50.6 52.4 67.3 40.3 Somali 0.0 1.4 0.5 3.7 3.0 8.7 15.9 7.9 Benishangul-Gumuz 3.5 7.1 20.2 38.5 32.6 55.6 66.6 35.1 SNNPR 4.5 6.0 21.1 32.2 37.9 49.7 76.9 40.0 Gambela 4.2 14.6 27.9 44.5 47.5 50.4 48.2 30.7 Harari 4.3 13.0 21.5 24.9 39.0 (52.6) 64.7 29.9 Addis Ababa 4.4 10.8 33.2 50.6 (47.7) * * 28.0 Dire Dawa 0.9 8.1 26.8 36.8 45.0 (49.8) 69.1 30.8 Education No education 4.6 8.3 23.4 28.8 43.7 51.1 65.7 43.0 Primary 5.3 9.8 21.9 37.9 40.4 51.7 74.8 30.5 Secondary 2.1 8.5 17.2 41.5 43.6 (75.8) * 18.0 More than secondary 0.0 2.2 17.2 54.6 * * * 15.4 Wealth quintile Lowest 1.4 6.6 18.8 31.6 37.4 35.5 53.5 32.5 Second 9.7 10.8 26.4 26.3 43.3 59.8 70.8 40.2 Middle 2.7 7.0 21.7 29.0 36.1 51.5 72.7 37.7 Fourth 7.5 6.5 16.6 32.0 55.0 52.3 73.5 41.7 Highest 1.0 10.1 24.1 43.4 49.3 64.8 67.7 31.7 Total 3.8 8.5 21.8 32.5 43.4 51.9 67.3 36.7 Note: Women who have been sterilised 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. 98 • Fertility Preferences 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, Ethiopia DHS 2016 Background characteristic Number of living children1 Total 0 1 2 3 4 5 6+ Residence Urban 2.0 2.6 18.1 32.6 49.1 43.5 58.1 19.6 Rural 4.3 4.5 13.7 23.3 33.8 42.8 50.7 28.1 Region Tigray (0.0) 0.8 7.3 16.3 35.1 33.6 55.3 22.6 Affar (12.7) 7.6 16.0 14.1 (10.6) (8.0) 7.0 10.3 Amhara 0.7 3.7 21.8 26.5 42.8 48.3 62.5 27.7 Oromiya 7.9 6.1 11.0 30.7 34.8 41.6 48.6 27.9 Somali * 2.8 1.5 3.7 (3.4) 4.4 3.9 3.3 Benishangul-Gumuz (5.4) 1.1 9.4 15.1 30.6 40.1 43.7 23.1 SNNPR * 1.6 15.7 16.6 32.7 45.3 57.8 30.4 Gambela (12.8) 11.3 15.0 20.2 (26.8) (40.6) 34.3 20.6 Harari (4.9) 9.5 13.8 (14.6) (17.1) (23.0) 38.2 16.7 Addis Ababa 6.3 2.0 18.9 23.5 * * * 18.1 Dire Dawa (0.0) 1.4 6.4 18.5 (28.4) (29.3) 26.3 12.6 Education No education 2.1 6.3 14.9 24.3 39.7 40.2 45.6 29.8 Primary 6.5 4.0 14.1 23.7 26.7 46.0 54.0 27.6 Secondary 0.1 2.2 5.8 21.5 68.5 40.5 71.2 16.4 More than secondary 3.1 2.0 28.6 36.7 (31.7) (47.3) (70.7) 19.6 Wealth quintile Lowest 3.5 6.5 14.3 21.5 29.5 36.0 36.9 24.5 Second 0.1 8.3 9.5 20.4 38.9 44.8 47.0 26.0 Middle 10.7 3.8 17.2 18.3 38.1 43.4 53.1 29.7 Fourth 3.8 0.1 17.4 34.5 29.3 43.5 60.5 31.8 Highest 1.6 2.3 15.3 30.0 41.5 49.6 64.1 22.2 Total 15-49 3.6 4.0 14.6 24.6 35.4 42.8 51.1 26.8 50-59 * (35.4) 30.7 56.2 67.1 76.3 68.2 65.6 Total 15-59 4.2 4.5 15.2 26.2 39.1 47.7 56.8 32.1 Note: Men who have been sterilised or who state in response to the question about desire for children that their wife has been sterilised 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 the respondent’s wife is pregnant (or, for men who have more than one current wife, if any wife is pregnant). Fertility Preferences • 99 Table 6.3 Ideal number of children by number of living children Percent distribution of women and men age 15-49 by ideal number of children, and mean ideal number of children for all respondents and for currently married respondents, according to number of living children, Ethiopia DHS 2016 Number of living children Total Ideal number of children 0 1 2 3 4 5 6+ WOMEN1 0 7.7 5.9 5.8 7.8 9.6 10.9 11.4 8.3 1 1.2 1.4 0.3 0.2 0.5 0.1 0.4 0.7 2 21.7 12.0 7.9 3.2 2.7 1.6 1.0 10.2 3 12.1 13.2 6.0 6.2 1.4 2.0 1.0 7.3 4 34.4 40.0 42.3 32.3 23.2 15.5 10.9 29.5 5 7.3 6.2 9.6 12.9 10.0 8.1 5.1 8.0 6+ 10.4 14.3 17.8 27.8 38.0 44.2 50.3 25.3 Non-numeric responses 5.1 7.0 10.3 9.6 14.6 17.5 19.9 10.7 Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 Number of women 4,945 2,012 1,801 1,670 1,462 1,306 2,487 15,683 Mean ideal number of children for:2 All women 3.5 3.9 4.3 4.7 5.0 5.4 6.2 4.5 Number of women 4,691 1,872 1,614 1,510 1,249 1,077 1,992 14,005 Currently married women 4.0 3.9 4.4 4.7 5.1 5.4 6.3 4.9 Number of currently married women 662 1,506 1,365 1,342 1,154 994 1,878 8,901 MEN3 0 6.7 3.5 2.1 3.8 2.3 6.3 8.8 5.6 1 1.1 1.0 0.1 0.0 0.3 0.0 0.2 0.6 2 21.2 13.2 7.4 3.9 2.5 1.6 0.9 12.7 3 18.2 20.9 8.5 7.6 3.4 4.0 1.5 12.8 4 31.6 36.9 41.9 25.9 22.1 13.9 10.2 28.4 5 7.5 6.7 13.2 15.5 8.2 14.7 5.8 9.0 6+ 10.2 15.4 22.0 36.9 53.3 53.5 59.5 25.5 Non-numeric responses 3.6 2.4 4.9 6.4 7.9 6.0 13.1 5.4 Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 Number of men 5,489 1,145 1,098 985 813 752 1,324 11,606 Mean ideal number of children for men 15-49:2 All men 3.5 4.0 4.7 5.3 6.1 6.2 7.7 4.6 Number of men 5,291 1,117 1,045 922 749 706 1,151 10,981 Currently married men 3.9 4.1 4.7 5.3 6.1 6.2 7.7 5.5 Number of currently married men 486 1,032 1,015 904 734 703 1,139 6,014 Mean ideal number of children for men 15-59:2 All men 3.6 4.0 4.7 5.2 6.0 6.2 7.8 4.8 Number of men 5,317 1,137 1,084 974 850 838 1,730 11,930 Currently married men 4.1 4.1 4.7 5.3 6.0 6.2 7.8 5.7 Number of currently married men 506 1,051 1,049 951 833 825 1,703 6,917 1 The number of living children includes the current pregnancy. 2 Means are calculated excluding respondents who gave non-numeric responses. 3 The number of living children includes one additional child if the respondent’s wife is pregnant (or, for men who have more than one current wife, if any wife is pregnant). 100 • Fertility Preferences Table 6.4 Mean ideal number of children according to background characteristics Mean ideal number of children for all women age 15-49 according to background characteristics, Ethiopia DHS 2016 Background characteristic Mean Number of women1 Age 15-19 3.6 3,188 20-24 3.9 2,590 25-29 4.4 2,654 30-34 4.8 2,023 35-39 5.3 1,667 40-44 5.7 1,063 45-49 5.7 820 Residence Urban 3.8 3,278 Rural 4.6 10,728 Region Tigray 4.8 967 Affar 5.6 102 Amhara 4.0 3,278 Oromiya 4.1 5,055 Somali 10.6 350 Benishangul-Gumuz 5.0 145 SNNPR 4.9 3,040 Gambela 4.5 41 Harari 4.2 35 Addis Ababa 3.6 910 Dire Dawa 5.4 82 Education No education 5.2 6,306 Primary 4.0 5,093 Secondary 3.6 1,746 More than secondary 3.6 860 Wealth quintile Lowest 5.5 2,184 Second 4.6 2,462 Middle 4.5 2,671 Fourth 4.3 2,778 Highest 3.9 3,910 Total 4.5 14,005 1 Number of women who gave a numeric response Table 6.5 Fertility planning status Percent distribution of births to women age 15-49 in the 5 years preceding the survey (including current pregnancies), by planning status of the birth, according to birth order and mother’s age at birth, Ethiopia DHS 2016 Birth order and mother’s age at birth Planning status of birth Number of births Wanted then Wanted later Wanted no more Total Birth order 1 82.8 14.6 2.6 100.0 2,299 2 78.1 19.0 2.9 100.0 1,978 3 78.6 17.6 3.8 100.0 1,733 4+ 69.4 17.3 13.3 100.0 6,148 Mother’s age at birth <20 78.8 18.3 2.9 100.0 1,399 20-24 78.8 18.4 2.8 100.0 3,393 25-29 74.1 18.9 7.0 100.0 3,283 30-34 73.1 15.1 11.8 100.0 2,272 35-39 66.7 13.2 20.1 100.0 1,319 40-44 67.1 11.1 21.8 100.0 437 45-49 (68.5) (13.5) (18.0) 100.0 55 Total 74.7 17.1 8.3 100.0 12,158 Note: Figures in parentheses are based on 25-49 unweighted cases. Fertility Preferences • 101 Table 6.6 Wanted fertility rates Total wanted fertility rates and total fertility rates for the 3 years preceding the survey, according to background characteristics, Ethiopia DHS 2016 Background characteristic Total wanted fertility rate Total fertility rate Residence Urban 2.1 2.3 Rural 4.0 5.2 Region Tigray 4.4 4.7 Affar 4.2 5.5 Amhara 3.1 3.7 Oromiya 3.8 5.4 Somali 6.9 7.2 Benishangul-Gumuz 4.0 4.4 SNNPR 3.5 4.4 Gambela 3.1 3.5 Harari 3.3 4.1 Addis Ababa 1.6 1.8 Dire Dawa 2.9 3.1 Education No education 4.4 5.7 Primary 3.3 4.2 Secondary 2.0 2.2 More than secondary 1.7 1.9 Wealth quintile Lowest 5.2 6.4 Second 4.4 5.6 Middle 3.7 4.9 Fourth 3.2 4.3 Highest 2.1 2.6 Total 3.6 4.6 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 • 103 FAMILY PLANNING 7 Key Findings  Modern contraceptive use: Modern contraceptive use by currently married Ethiopian women has steadily increased over the last 15 years, jumping from 6% of women using modern contraceptive method in 2000 to 35% in 2016.  Methods used: By method, the largest growth has been in injectables use, which expanded from use by 3% of women in 2000 to 23% in 2016, followed by growth in implant use, from less than 1% of women using in 2000 to 8% in 2016.  Sources of modern methods: The most popular sources of modern contraception are public sector sources (84%); only 14% get their modern methods from private sector sources.  Contraceptive discontinuation: In the 5 years preceding the survey more than one-third of all contraceptive users (35%) discontinued use within 12 months. The most common reason for stopping a method was the desire to become pregnant (42%), followed by method-related health concerns or side effects (18%).  Unmet need for family planning: Twenty-two percent of currently married women have an unmet need for family planning  Percentage of demand for family planning satisfied: Overall, about 6 in 10 currently married women age 15- 49 have their demand for family planning satisfied. ouples can use contraceptive methods to limit or space the number of children they have. This chapter presents information on the knowledge, use, and sources of contraceptive methods, informed decision-making about use, and rates and reasons for discontinuing use. It also examines the need for family planning and the demand for family planning that is satisfied. In addition, it provides information on whether nonusers are discussing family planning with health providers. The use of contraception helps women avoid unplanned or unwanted pregnancies, and prevent unsafe abortions. Additionally, contraceptive use helps women space the births of their children, which benefits the health of the mother and child. Although information is presented here for both women and men, the focus is mostly on women. In line with Ethiopia’s FP2020 commitments, the Ministry of Health (MoH) developed the health sector transformation plan of 2015, which aimed to increase the contraceptive prevalence rate (CPR) to 55%. This would mean reaching an additional 6.2 million women and adolescent girls with family planning services by 2020 (MOH 2015). C 104 • Family Planning 7.1 CONTRACEPTIVE KNOWLEDGE AND USE Knowledge of contraceptive methods is almost universal in Ethiopia, with 99% of currently married women and men age 15-49 knowing at least one method of contraception. The most well-known methods for currently married women and men are injectables and the pill. Among all women, the standard days method is the least-known modern contraceptive method (11%). On average, women and men each know six contraceptive methods (Table 7.1). Knowledge of contraceptive methods does not vary by most background characteristics except region. All currently married women and men in Addis Ababa know at least one method of contraception, while in Somali only 79% of currently married women and 83% of currently married men know at least one method of contraception (Table 7.2). Contraceptive prevalence rate Percentage of women 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 The contraceptive prevalence rate (CPR) for currently married women age 15-49 in Ethiopia is 36%, with 35% using modern methods and 1% using traditional methods. Fifty-eight percent of sexually active unmarried women use contraceptive methods, with 55% using modern methods and 3% using traditional methods (Table 7.3). Modern methods Modern methods include male and female sterilisation, injectables, intrauterine devices (IUDs), contraceptive pills, implants, female and male condoms, standard days method, lactational amenorrhoea method, and emergency contraception The most commonly used contraceptive method for currently married women in Ethiopia is injectables (23%), followed by implants (8%). For sexually active unmarried women, the most popular methods are injectables (35%), followed by implants (11%), and male condom and emergency contraception (4% each) (Figure 7.1). Figure 7.1 Contraceptive use 36 35 23 8 2 2 0 <1 <1 1 58 55 35 11 1 1 4 0 4 3 Any method Any modern method Injectables Implants Pill IUD Emergency contraception Female sterilisation Male condom Traditional method Percentage of women age 15-49 currently using a contraceptive method Currently married women Sexually active, unmarried women Family Planning • 105 Trends: Modern contraceptive use for currently married women has steadily increased over the last 16 years in Ethiopia from 6% in 2000 to 35% in 2016 (Figure 7.2). The largest increases were in the use of injectables (from 3% in 2000 to 23% in 2016) and implants (from less than 1% in 2000 to 8% in 2016). Patterns by background characteristics  Currently married women with 1-2 living children are more likely to use a modern contraceptive method than women with more than 5 children (42% and 28%, respectively) (Table 7.4).  Current use of modern contraception for married women is higher in urban areas (50%) than in rural areas (32%).  By region, currently married women in Somali have the lowest use of modern contraception (1%), followed by Affar (12%). The highest use of modern contraception among currently married women is observed in Addis Ababa (50%) followed by Amhara (47%) (Figure 7.3).  Modern contraceptive use among currently married women increases with education from 31% for women with no education to 51% for women with secondary education or higher.  Use of modern contraception increases sharply with wealth, ranging from 20% for women in the lowest wealth quintile to 47% for women in the highest wealth quintile (Figure 7.4). Figure 7.2 Trends in contraceptive use Figure 7.3 Use of modern methods by region Figure 7.4 Use of modern methods by household wealth 6 14 27 35 2 1 1 1 2000 EDHS 2005 EDHS 2011 EDHS 2016 EDHS Percentage of currently married women currently using a modern contraceptive method Any traditional method Any modern method 1 12 28 28 29 29 35 35 40 47 50 Somali Affar Oromiya Benishangul-Gumuz Dire Dawa Harari Gambela Tigray SNNPR Amhara Addis Ababa Percentage of currently married women age 15-49 20 31 37 41 47 Lowest Second Middle Fourth Highest Percentage of currently married women age 15-49 Poorest Wealthiest 106 • Family Planning 7.2 SOURCE OF MODERN CONTRACEPTIVE METHODS Source of modern contraceptives The 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 Information on current sources of modern contraceptive methods is important for family planners and program implementers. The most popular source of modern contraception is the public sector (84%), followed by the private medical sector (14%) (Table 7.5 and Figure 7.5).  Injectables: The main source of injectables is the public sector (82%), primarily the government health station/centre. Only 17% of injectables users used the private sector as their source.  Implants, IUDs, and female sterilisation: Almost all users of implants, IUDs, and female sterilisation obtained their method from a public sector source (95%, 93%, and 84%, respectively).  Pill: Fifty-eight percent of pill users obtained their method from a public sector source, mainly a government health station/centre or post. Forty-one percent of pill users got their supply from the private sector, mainly a private clinic or private pharmacy. 7.3 INFORMED CHOICE Informed choice Informed choice indicates that women were informed at the time they started the current episode of method use about the method’s side effects, about what to do if they experience side effects, and about 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 Less than half of current users of modern contraceptive methods (46%) were informed of the potential side effects or problems associated with the method they used; 36% were told what to do if they experienced side effects. Fifty-six percent were informed of other methods that they could use. Overall, 30% of all women currently using modern contraceptives were informed at the time they started the current episode of method use about the method’s side effects, what to do if they experience side effects, and other available methods (Table 7.6). Figure 7.5 Source of modern contraceptive methods Public sector 84% NGO 1% Private medical sectors 14% Other source 1% Percent distribution of current users of modern methods age 15-49 by most recent source of method Family Planning • 107 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, experienced by women who are currently age 15-49 (one woman may contribute more than one episode) Table 7.7 shows that for all women age 15-49 who started an episode of contraceptive use in the 5 years preceding the survey, 35% of the episodes were discontinued within 12 months. In 6% of the episodes, the woman switched to another method. Discontinuation rates are highest for the pill (70%). Thirty-eight percent of users of injectables discontinue use within one year (Figure 7.6). Table 7.8 shows the most common reason for discontinuing a method is the desire to become pregnant (42%), followed by method-related health concerns or side effects (18%), wanting a more effective method (11%), infrequent sex or husband away (8%), and inconvenience of use (6%). 7.5 KNOWLEDGE OF THE FERTILE PERIOD The survey also collected data on women’s knowledge of the fertile period. Table 7.9 shows that only one in four women age 15-49 (24%) correctly know that a woman is most likely to conceive halfway between two periods. As expected, users of the rhythm method are much more likely to know this (66%) than nonusers of the rhythm method (23%). The most common misconception is that the fertile period is right after a woman’s menstrual period has ended (25%). One in five women (20%) don’t know about the fertile period at all. 7.6 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 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) Figure 7.6 Contraceptive discontinuation rates 70 38 13 11 35 Pill Inject- ables IUD Implants Any method Percentage of contraceptive episodes discontinued within 12 months, among women age 15-49 108 • Family Planning Table 7.10.1 shows that 58% of currently married women age 15-49 have a demand for family planning; 35% want to space births, and 24% want to limit births. Thirty-six percent of currently married women are already using a contraceptive method either to space (22%) or to limit births (14%); that is, their family planning need is met. However, 22% of currently married women have an unmet need for family planning: they want to space (13%) or limit (9%) births but are not currently using contraception. Overall, 62% of currently married women age 15-49 have their demand for family planning satisfied (Figure 7.7). Trends: The total demand for family planning among currently married women age 15-49 has increased over time, rising from 45% in 2000, to 51% in 2005, 55% in 2011, and 58% in 2016 (Figure 7.8). Met need for family planning has also increased over the same period, rising from 8% in 2000, to 15% in 2005, to 29% in 2011, and 36% in 2016; most of the need has been met with modern methods. Unmet need for family planning among married women has declined over time, from 37% in 2000 to 22% in 2016. Figure 7.8 Trends in demand for family planning Patterns by background characteristics  Unmet need for family planning for currently married women age 15-49 is higher in rural areas (25%) than in urban areas (11%) (Figure 7.9). 0 10 20 30 40 50 60 70 80 90 100 2000 EDHS 2005 EDHS 2011 EDHS 2016 EDHS Percentage of currently married women age 15-49 Unmet need Met need, traditional methods Met need, modern methods 51 55 58 Total demand 45 Figure 7.7 Demand for family planning Figure 7.9 Unmet need by residence Unmet need for spacing 13% Unmet need for limiting 9% Met need for spacing 22% Met need for limiting 14% No need for family planning 42% Percent distribution of currently married women age 15-49 by need for family planning 22 11 25 Total Urban Rural Percentage of currently married women age 15-49 with unmet need Family Planning • 109  Unmet need for currently married women age 15-49 is lowest in Addis Ababa (11%) and highest in Oromiya region (29%) (Figure 7.10).  Unmet need for family planning generally declines with increasing wealth, from 27-28% of currently married women in the lowest and second wealth quintiles having unmet need to 14% of women in the highest wealth quintile.  The total demand for family planning among sexually active unmarried women exceeds that of currently married women (85% versus 58%), and the percentage of demand satisfied is also higher for sexually active unmarried women than for married women (69% versus 62%). For more information on need and demand for family planning among all women and sexually active unmarried women, see Table 7.10.2. 7.6.1 Decision Making about Family Planning The survey collected information regarding decision making about family planning. Table 7.11 shows that for 73% of currently married women age 15-49 who are using a family planning method, the decision to use it was made jointly with their husband; for 22% of these women the decision was made mainly by themselves, and for 5% the husband mainly made the decision. Among currently married women age 15- 49 who are not using a family planning method, 58% made the decision not to use family planning jointly with their husband, 30% decided themselves, and for 10% the husband decided. 7.6.2 Future Use of Contraception This survey also collected information on nonusers’ intent to use contraception in the future. Table 7.12 shows that 49% of currently married women age 15-49 who are not currently using contraception intend to use family planning at some future time. The same proportion (49%) of currently married women who are not using contraceptive methods do not intend to use family planning in the future and 2% are unsure. 7.6.3 Exposure to Family Planning Messages in the Media Table 7.13 offers information on women’s exposure to family planning messages in the media or from other sources. The most often cited source of information on family planning messages reported by women and men age 15-49 in the past few months is community event or conversation (38% and 37%, respectively). Other main sources include radio (24% for women and 33% for men) and television (18% for women and 23% for men). Printed materials such as newspapers or magazines and pamphlets, posters, or, leaflets are cited as sources of family planning messages by 5-6% of women. Women’s exposure to family planning messages using new technologies, such as mobile phone (3%) and the internet (2%), is limited. Overall, 46% of women and 40% of men age 15-49 have no exposure to family planning messages through any of these seven main mass media means. 7.7 CONTACT OF NONUSERS WITH FAMILY PLANNING PROVIDERS Contact of nonusers 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 Figure 7.10 Unmet need by region 11 13 17 17 18 19 21 21 21 23 29 Addis Ababa Somali Affar Amhara Tigray Dire Dawa SNNPR Benishangul-Gumuz Harari Gambela Oromiya Percentage of currently married women age 15-49 with unmet need 110 • Family Planning In the survey, women age 15-49 who are not using contraception were asked if they had been visited by a health care worker who discussed family planning with them. Table 7.14 shows that 22% of women not using contraception were visited by a fieldworker who discussed family planning. Twelve percent of women went to a health facility in the 12 months before the survey and discussed family planning, while 25% of women visited a health facility but did not discuss family planning during that visit. Overall, almost three-quarters (73%) of women age 15-49 who are not using a contraceptive method said they did not discuss family planning either with a fieldworker or at a health facility in the 12 months before the survey. Patterns by background characteristics  By age, women age 30-34 are most likely (32%) and women age 15-19 (13%) are least likely to have been visited by a fieldworker and discussed family planning in the 12 months before the survey.  Women in Benishangul-Gumuz are the most likely to have been visited by a fieldworker (43%) and discussed family planning, while women in Tigray and Harari are the most likely to have visited a health facility and discussed family planning in the past 12 months (22% for each). The percentage of women in Somali who discussed family planning with a fieldworker (11%) or at a health facility (2%) is the lowest among all regions. LIST OF TABLES For more information on family planning, see the following tables:  Table 7.1 Knowledge of contraceptive methods  Table 7.2 Knowledge of contraceptive methods according to background characteristics  Table 7.3 Current use of contraception according to age  Table 7.4 Current use of contraception according to 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 Knowledge of fertile period  Table 7.10.1 Need and demand for family planning among currently married women  Table 7.10.2 Need and demand for family planning for all women and for sexually active unmarried women  Table 7.11 Decision making about family planning  Table 7.12 Future use of contraception  Table 7.13 Exposure to family planning messages  Table 7.14 Contact of nonusers with family planning providers Family Planning • 111 Table 7.1 Knowledge of contraceptive methods Percentage of all respondents, currently married respondents, and sexually active unmarried respondents age 15-49 who have heard of any contraceptive method, according to specific method, Ethiopia DHS 2016 Women Men Method All women Currently married women Sexually active unmarried women1 All men Currently married men Sexually active unmarried men1 Any method 98.3 98.7 99.8 98.1 99.3 99.9 Any modern method 98.3 98.7 99.8 98.0 99.2 99.9 Female sterilisation 34.2 35.6 38.7 35.4 38.7 46.2 Male sterilisation 11.5 11.3 19.5 22.2 23.5 32.4 Pill 87.2 88.6 90.4 89.3 92.6 95.1 IUD 45.6 45.5 62.8 42.2 41.5 73.9 Injectables 96.2 97.4 99.8 92.5 95.5 94.4 Implants 74.3 75.6 91.1 67.4 71.9 85.8 Male condom 66.2 62.5 88.5 89.7 90.0 98.0 Female condom 21.7 18.4 51.6 38.1 35.1 61.8 Emergency contraception 19.5 16.1 51.7 31.0 30.0 67.8 Standard days method (SDM) 10.6 10.3 20.2 18.7 19.6 34.0 Lactational amenorrhoea method (LAM) 29.3 31.7 37.6 23.8 26.8 30.9 Other modern method 0.4 0.4 1.2 0.1 0.1 0.0 Any traditional method 34.4 32.7 53.4 57.8 60.4 82.6 Rhythm 29.2 27.6 46.9 47.6 49.8 72.6 Withdrawal 18.8 17.7 45.0 37.3 38.7 66.0 Other 0.3 0.3 2.0 0.2 0.2 0.5 Mean number of methods known by respondents 15-49 5.5 5.4 7.5 6.4 6.5 8.6 Number of respondents 15,683 10,223 176 11,606 6,441 286 Mean number of methods known by respondents 15-59 na na na 6.4 6.5 8.6 Number of respondents na na na 12,688 7,471 299 na = Not applicable 1 Had last sexual intercourse within 30 days preceding the survey 112 • Family Planning Table 7.2 Knowledge of contraceptive methods according to 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, according to background characteristics, Ethiopia DHS 2016 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 98.2 97.5 588 (96.7) (96.7) 26 20-24 98.7 98.7 1,710 99.1 99.1 474 25-29 98.9 98.9 2,402 99.3 99.3 1,227 30-34 98.8 98.8 2,049 99.4 99.4 1,389 35-39 98.9 98.9 1,613 99.3 99.1 1,285 40-44 98.3 98.3 1,064 99.2 99.2 1,137 45-49 98.6 98.5 798 99.2 99.2 903 Residence Urban 99.7 99.7 1,658 99.8 99.8 1,011 Rural 98.5 98.5 8,565 99.2 99.1 5,430 Region Tigray 99.6 99.6 658 100.0 100.0 352 Affar 89.6 89.2 96 99.2 99.2 48 Amhara 99.9 99.9 2,414 100.0 100.0 1,633 Oromiya 99.3 99.2 3,987 99.7 99.7 2,558 Somali 79.0 78.6 324 82.8 82.4 174 Benishangul-Gumuz 97.6 97.6 114 98.7 98.1 72 SNNPR 99.2 99.2 2,173 99.4 99.3 1,323 Gambela 97.1 97.1 29 99.3 99.3 17 Harari 97.2 97.2 25 98.6 98.6 16 Addis Ababa 100.0 100.0 355 100.0 100.0 217 Dire Dawa 99.8 99.8 50 99.3 99.3 32 Education No education 98.1 98.0 6,253 98.4 98.4 2,558 Primary 99.7 99.6 2,895 99.7 99.7 2,769 Secondary 99.6 99.6 654 100.0 100.0 625 More than secondary 100.0 100.0 421 100.0 99.9 489 Wealth quintile Lowest 95.4 95.2 1,953 97.3 97.2 1,161 Second 99.4 99.3 2,074 99.3 99.1 1,359 Middle 98.9 98.9 2,057 99.7 99.7 1,310 Fourth 99.9 99.9 1,999 100.0 100.0 1,255 Highest 99.9 99.9 2,140 99.9 99.9 1,357 Total 15-49 98.7 98.7 10,223 99.3 99.2 6,441 50-59 na na na 98.6 98.6 1,029 Total 15-59 na na na 99.2 99.1 7,471 Note: Figures in parentheses are based on 25-49 unweighted cases. na = Not applicable 1 Female sterilisation, male sterilisation, pill, IUD, injectables, implants, male condom, female condom, emergency contraception, standard days method (SDM), lactational amenorrhoea method (LAM), and other modern methods Family Planning • 113 Table 7.3 Current use of contraception according to age Percent distribution of all women, currently married women, and sexually active unmarried women age 15-49 by contraceptive method currently used, according to age, Ethiopia DHS 2016 Any method Any modern method Modern method Any tradi- tional method Traditional method Not currently using Total Number of women Age Female sterili- sation Pill IUD Inject- ables Implants Other1 Rhythm With- drawal ALL WOMEN 15-19 7.5 7.4 0.0 0.3 0.2 5.3 1.5 0.1 0.1 0.1 0.0 92.5 100.0 3,381 20-24 26.4 26.0 0.0 1.7 0.7 17.5 5.9 0.3 0.3 0.3 0.1 73.6 100.0 2,762 25-29 35.7 34.9 0.0 2.2 2.2 21.2 8.9 0.5 0.7 0.6 0.1 64.3 100.0 2,957 30-34 35.0 34.6 0.3 1.4 2.9 21.3 8.2 0.5 0.5 0.3 0.1 65.0 100.0 2,345 35-39 30.1 29.1 0.7 1.3 2.2 17.4 7.3 0.3 1.0 0.9 0.1 69.9 100.0 1,932 40-44 28.2 27.7 1.0 1.4 1.0 18.7 5.3 0.2 0.5 0.2 0.3 71.8 100.0 1,290 45-49 16.8 16.4 1.1 0.7 1.1 10.6 2.5 0.2 0.5 0.5 0.0 83.2 100.0 1,017 Total 25.3 24.9 0.3 1.3 1.4 15.8 5.7 0.3 0.5 0.4 0.1 74.7 100.0 15,683 CURRENTLY MARRIED WOMEN 15-19 31.9 31.8 0.0 2.0 0.9 24.0 4.9 0.0 0.1 0.1 0.0 68.1 100.0 588 20-24 38.8 38.5 0.0 2.2 1.2 26.2 8.7 0.1 0.3 0.3 0.0 61.2 100.0 1,710 25-29 41.0 40.2 0.0 2.6 2.6 24.9 9.8 0.3 0.8 0.7 0.2 59.0 100.0 2,402 30-34 37.3 36.9 0.2 1.3 3.1 23.3 8.4 0.5 0.5 0.3 0.1 62.7 100.0 2,049 35-39 34.7 33.5 0.8 1.5 2.3 20.2 8.4 0.3 1.2 1.1 0.1 65.3 100.0 1,613 40-44 33.4 32.7 1.2 1.7 1.2 22.2 6.1 0.3 0.6 0.3 0.4 66.6 100.0 1,064 45-49 19.3 18.7 1.5 0.9 0.9 12.6 2.6 0.3 0.5 0.5 0.0 80.7 100.0 798 Total 35.9 35.3 0.4 1.8 2.0 22.8 7.9 0.3 0.6 0.5 0.1 64.1 100.0 10,223 SEXUALLY ACTIVE UNMARRIED WOMEN2 15-19 (59.0) (57.5) (0.0) (0.1) (0.0) (33.6) (14.0) (9.8) (1.4) (1.4) (0.0) (41.0) 100.0 50 20-24 56.3 47.0 0.0 2.4 0.3 31.1 2.1 11.1 9.3 2.6 6.7 43.7 100.0 35 25+ 58.4 56.7 0.0 0.5 1.6 37.4 12.0 5.2 1.7 1.7 0.0 41.6 100.0 92 Total 58.1 55.0 0.0 0.7 0.9 35.1 10.6 7.7 3.1 1.8 1.3 41.9 100.0 176 Note: If more than one method is used, only the most effective method is considered in this tabulation. Figures in parentheses are based on 25-49 unweighted cases. na = Not applicable SDM = Standard days method LAM = Lactational amenorrhoea 1 Other includes male condom, emergency contraception, standard days method (SDM), and lactational amenorrhoea method (LAM). 2 Women who have had sexual intercourse within 30 days preceding the survey 114 • Family Planning Table 7.4 Current use of contraception according to background characteristics Percent distribution of currently married women age 15-49 by contraceptive method currently used, according to background characteristics, Ethiopia DHS 2016 Any method Any modern method Modern method Any tradi- tional method Traditional method Not currently using Total Number of women Background characteristic Female sterili- sation Pill IUD Inject- ables Implants Other1 Rhythm With- drawal Number of living children 0 30.1 29.4 0.0 2.8 1.1 20.5 4.7 0.3 0.6 0.6 0.0 69.9 100.0 925 1-2 43.2 42.2 0.1 2.9 2.7 25.8 10.5 0.2 1.1 1.0 0.1 56.8 100.0 3,137 3-4 38.9 38.4 0.4 2.0 2.1 24.7 8.8 0.4 0.5 0.3 0.2 61.1 100.0 2,761 5+ 28.3 27.9 0.9 0.5 1.6 19.0 5.6 0.3 0.4 0.3 0.1 71.7 100.0 3,401 Residence Urban 52.0 49.8 0.4 6.5 4.6 26.4 11.0 0.8 2.2 1.9 0.3 48.0 100.0 1,658 Rural 32.8 32.4 0.4 0.9 1.5 22.1 7.3 0.2 0.3 0.2 0.1 67.2 100.0 8,565 Region Tigray 36.3 35.2 0.2 3.6 1.0 19.3 10.7 0.3 1.1 1.0 0.1 63.7 100.0 658 Affar 11.6 11.6 0.0 0.4 0.2 9.5 1.4 0.1 0.0 0.0 0.0 88.4 100.0 96 Amhara 47.3 46.9 0.5 2.0 3.0 29.3 12.1 0 0.4 0.3 0.1 52.7 100.0 2,414 Oromiya 28.6 28.1 0.2 1.2 1.7 19.6 5.1 0.3 0.5 0.4 0.1 71.4 100.0 3,987 Somali 1.5 1.4 0.0 0.4 0.1 0.6 0.1 0.1 0.2 0.0 0.2 98.5 100.0 324 Benishangul-Gumuz 28.5 28.4 0.2 1.0 1.5 19.5 6.3 0 0.2 0.2 0.0 71.5 100.0 114 SNNPR 39.9 39.6 0.9 1.6 1.3 27.7 8.0 0.3 0.3 0.2 0.1 60.1 100.0 2,173 Gambela 34.9 34.9 0.0 2.9 0.5 28.9 1.9 0.8 0.0 0.0 0.0 65.1 100.0 29 Harari 29.5 29.3 0.0 5.0 2.5 12.6 7.5 1.7 0.2 0.2 0.0 70.5 100.0 25 Addis Ababa 55.9 50.1 0.5 7.8 8.5 17.4 14.1 1.8 5.9 4.8 1.0 44.1 100.0 355 Dire Dawa 30.3 29.1 0.0 3.4 1.2 11.0 12.0 1.6 1.2 1.2 0.0 69.7 100.0 50 Education No education 31.2 30.9 0.5 0.9 1.8 19.9 7.7 0.1 0.3 0.2 0.1 68.8 100.0 6,253 Primary 39.6 39.0 0.4 1.9 1.9 27.3 7.2 0.3 0.6 0.5 0.0 60.4 100.0 2,895 Secondary 52.4 50.6 0.0 5.0 3.2 32.9 8.9 0.5 1.8 1.6 0.2 47.6 100.0 654 More than secondary 55.0 50.7 0.7 10.2 4.8 18.8 14.3 2 4.3 3.9 0.4 45.0 100.0 421 Wealth quintile Lowest 19.6 19.5 0.0 1.0 0.3 13.0 5.0 0.2 0.1 0.1 0.0 80.4 100.0 1,953 Second 31.1 31.0 0.2 1.3 1.1 20.6 7.7 0.1 0.1 0.1 0.0 68.9 100.0 2,074 Middle 37.2 36.7 0.4 0.9 1.9 24.6 8.7 0.2 0.4 0.4 0.0 62.8 100.0 2,057 Fourth 40.9 40.6 1.0 0.6 2.4 28.5 7.9 0.2 0.4 0.1 0.2 59.1 100.0 1,999 Highest 49.4 47.4 0.6 5.1 4.4 26.6 9.9 0.9 2.0 1.7 0.3 50.6 100.0 2,140 Total 35.9 35.3 0.4 1.8 2.0 22.8 7.9 0.3 0.6 0.5 0.1 64.1 100.0 10,223 Note: If more than one method is used, only the most effective method is considered in this tabulation. 1 Other include male condom, emergency contraception, standard days method (SDM), and lactational amenorrhoea method (LAM). 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, Ethiopia DHS 2016 Source Female sterilisation Pill IUD Injectables Implants Total Public sector (84.3) 58.0 92.7 81.7 94.8 83.8 Government hospital (75.0) 3.8 8.8 2.0 3.5 3.7 Government health station/ centre (9.3) 27.1 65.4 50.2 64.5 52.5 Government health post (0.0) 21.6 18.2 29.0 26.7 26.9 Public pharmacy (0.0) 5.5 0.2 0.2 0.1 0.5 Other (0.0) 0.0 0.0 0.3 0.0 0.2 NGO (5.5) 0.7 2.9 0.9 2.0 1.3 Health facility (5.5) 0.7 2.9 0.9 1.6 1.2 Other (0.0) 0.0 0.0 0.0 0.4 0.1 Private sector (10.2) 41.2 4.2 16.9 3.2 14.4 Private hospital (7.0) 0.6 1.5 0.5 0.2 0.5 Private clinic (3.2) 22.2 2.4 14.8 2.9 11.5 Private pharmacy (0.0) 18.4 0.2 1.6 0.1 2.3 Other (0.0) 0.0 0.0 0.1 0.0 0.1 Other source (0.0) 0.0 0.3 0.5 0.0 0.1 Friend/relative (0.0) 0.0 0.0 0.1 0.0 0.1 Other (0.0) 0.0 0.3 0.4 0.0 0.4 Total 100.0 100.0 100.0 100.0 100.0 100.0 Number of women 45 205 226 2,474 901 3,884 Note: Total includes other modern methods (male condoms, female condoms, emergency contraception, and standard days method) but excludes lactational amenorrhoea method (LAM). Figures in parentheses are based on 25-49 unweighted cases. Family Planning • 115 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, and percentage who were informed of all three, according to method and initial source, Ethiopia DHS 2016 Among women who started last episode of modern contraceptive method within the 5 years preceding the survey: Number of women Method/source Percentage who were informed about side effects or problems of method used Percentage who were informed about what to do if experienced side effects Percentage who were informed by a health or family planning worker of other methods that could be used Percentage who were informed of all three (Method Information Index) Method Female sterilisation * * * * 20 Pill 46.0 32.4 54.8 25.4 187 IUD 60.0 51.9 65.1 46.9 199 Injectables 40.4 30.7 53.9 26.9 2,218 Implants 55.6 44.8 58.1 36.2 829 Initial source of method1 Public sector 46.3 36.5 57.1 31.6 2,995 Government hospital 62.0 47.0 70.5 43.5 100 Government health station/ centre 46.3 36.2 56.9 31.3 1,908 Government health post 45.4 36.6 57.1 31.2 967 Public pharmacy * * * * 17 Other * * * * 3 NGO 67.4 59.6 45.9 37.2 43 Health facility 67.4 60.4 45.5 37.7 43 Other * * * * 1 Private sector 39.4 26.8 45.2 21.1 393 Private hospital * * * * 19 Private clinic 40.5 28.3 43.6 21.4 318 Private pharmacy 30.1 11.9 51.9 11.0 55 Other source * * * * 3 Friend/relative * * * * 3 Other * * * * 19 Total 45.5 35.5 55.6 30.2 3,453 Note: Table includes users of only the methods listed individually. An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. 1 Source at start of current episode of use Table 7.7 Twelve-month contraceptive discontinuation rates Among episodes of contraceptive use experienced within the 5 years preceding the survey, percentage of episodes discontinued within 12 months, according to reason for discontinuation and specific method, Ethiopia DHS 2016 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 4.4 12.1 8.7 13.8 17.7 9.3 4.1 70.1 24.2 536 IUD 0.0 2.0 0.0 7.0 0.1 2.2 2.1 13.3 3.4 248 Injectables 0.4 13.1 4.9 8.1 3.4 5.2 3.1 38.3 4.4 4,365 Implants 0.3 3.9 0.3 2.5 0.9 2.0 1.0 10.9 2.4 1,136 Rhythm/withdrawal 3.3 9.9 1.3 0.0 7.5 2.1 0.0 24.0 5.0 122 Other1 0.1 5.3 25.7 5.2 9.3 2.7 4.9 53.4 10.0 151 All methods 0.8 10.8 4.7 7.4 4.2 4.8 2.8 35.3 5.8 6,559 Note: Figures are based on life table calculations using information on episodes of use that began 3-62 months preceding the survey. 1 Includes lactational amenorrhoea method (LAM), female sterilisation, male condom, female condom, emergency contraception, standard days method (SDM) 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 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 2 months of discontinuation. 6 All episodes of use that occur within the 5 years preceding the survey are included. Episodes of use include episodes that were discontinued during the period of observation and episodes of use that were not discontinued during the period of observation. 116 • Family Planning Table 7.8 Reasons for discontinuation Percent distribution of discontinuations of contraceptive methods in the 5 years preceding the survey by main reason stated for discontinuation, according to specific method, Ethiopia DHS 2016 Reason Pill IUD Injectables Implants Male condom Emergency contra- ception Rhythm Withdrawal Other All methods Became pregnant while using 7.0 0.5 1.6 0.8 1.4 5.4 7.4 (10.2) (0.0) 2.2 Wanted to become pregnant 25.5 36.0 44.6 42.1 25.4 9.8 60.6 (52.6) (20.7) 41.8 Husband disapproved 0.3 4.3 1.1 0.5 1.5 0.0 0.0 (0.0) (0.0) 1.0 Wanted a more effective method 21.7 5.4 9.8 10.8 10.9 6.6 18.4 (6.8) (25.4) 11.2 Health concerns/side effects 18.6 25.3 16.9 24.1 0.8 3.3 0.0 (0.0) (24.2) 17.5 Lack of access/too far 3.4 2.5 4.4 0.8 0.0 0.0 0.0 (3.2) (0.0) 3.7 Inconvenient to use 7.1 18.5 6.1 6.0 1.3 6.7 5.3 (16.7) (0.1) 6.4 Up to God/fatalistic 2.0 0.0 1.4 1.9 1.8 0.0 0.0 (0.0) (1.5) 1.5 Difficult to get pregnant/ menopausal 0.3 0.7 0.7 0.5 0.0 0.0 2.5 (0.0) (7.0) 0.7 Infrequent sex/husband away 11.2 4.1 6.3 6.5 38.9 65.8 4.5 (7.6) (2.7) 7.6 Marital dissolution/ separation 0.8 0.0 3.1 0.3 4.0 2.3 1.2 (2.9) (0.0) 2.5 Other 2.1 2.8 4.0 5.3 13.0 0.0 0.0 (0.0) (6.6) 3.9 Don’t know 0.0 0.0 0.0 0.4 1.1 0.0 0.0 (0.0) (11.8) 0.1 Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 Number of discontinuations 478 85 3,359 520 48 37 58 14 31 4,644 Note: Total includes users of female condom and standard days method (SDM). Figures in parentheses are based on 25-49 unweighted cases. Table 7.9 Knowledge of fertile period Percent distribution of women age 15-49 by knowledge of the fertile period during the ovulatory cycle, according to current use of the rhythm method, Ethiopia DHS 2016 Perceived fertile period Users of rhythm method Nonusers of SDM All women Just before her menstrual period begins 5.9 7.6 7.6 During her menstrual period 2.4 4.1 4.1 Right after her menstrual period has ended 23.5 24.9 24.9 Halfway between two menstrual periods 66.1 23.4 23.6 No specific time 1.7 20.1 20.1 Don’t know 0.4 19.8 19.7 Total 100.0 100.0 100.0 Number of women 61 15,622 15,683 SDM = Standard days method Family Planning • 117 Table 7.10.1 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 family planning that is satisfied, by background characteristics, Ethiopia DHS 2016 Unmet need for family planning Met need for family planning (currently using) Total demand for family planning1 Percent- age of demand satisfied2 Percent- age 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 Age 15-19 18.7 1.9 20.5 29.3 2.7 31.9 48.0 4.5 52.5 60.9 60.7 588 20-24 15.8 2.7 18.5 34.2 4.5 38.8 50.0 7.2 57.3 67.7 67.1 1,710 25-29 16.6 4.5 21.1 30.5 10.5 41.0 47.1 15.0 62.1 66.0 64.7 2,402 30-34 14.8 10.0 24.9 20.9 16.5 37.3 35.7 26.5 62.2 60.0 59.2 2,049 35-39 10.2 16.6 26.8 12.3 22.4 34.7 22.5 39.0 61.5 56.4 54.5 1,613 40-44 5.2 18.8 24.1 6.7 26.7 33.4 11.9 45.5 57.5 58.1 57.0 1,064 45-49 3.1 14.4 17.5 2.0 17.3 19.3 5.1 31.7 36.8 52.4 51.0 798 Residence Urban 5.7 5.7 11.3 36.9 15.1 52.0 42.5 20.8 63.3 82.1 78.6 1,658 Rural 14.4 10.0 24.5 18.6 14.2 32.8 33.0 24.2 57.2 57.3 56.7 8,565 Region Tigray 11.8 6.2 18.0 25.3 11.0 36.3 37.1 17.1 54.3 66.9 64.8 658 Affar 12.9 4.3 17.2 9.7 1.9 11.6 22.6 6.3 28.9 40.3 40.3 96 Amhara 8.5 9.0 17.4 29.9 17.4 47.3 38.3 26.4 64.8 73.1 72.4 2,414 Oromiya 17.1 11.8 28.9 15.7 12.9 28.6 32.8 24.7 57.5 49.8 48.9 3,987 Somali 9.4 3.2 12.6 1.4 0.1 1.5 10.8 3.3 14.1 10.8 9.6 324 Benishangul-Gumuz 11.5 9.6 21.1 17.9 10.6 28.5 29.5 20.2 49.6 57.5 57.2 114 SNNPR 12.7 8.1 20.8 22.6 17.2 39.9 35.4 25.4 60.7 65.7 65.3 2,173 Gambela 13.1 9.9 23.0 22.6 12.3 34.9 35.7 22.2 57.9 60.3 60.3 29 Harari 12.3 9.0 21.3 19.8 9.6 29.5 32.1 18.6 50.7 58.1 57.7 25 Addis Ababa 6.0 4.5 10.5 39.4 16.5 55.9 45.4 21.0 66.4 84.2 75.4 355 Dire Dawa 10.1 9.3 19.4 21.0 9.3 30.3 31.1 18.6 49.8 61.0 58.6 50 Education No education 13.3 11.1 24.5 15.1 16.0 31.2 28.5 27.2 55.6 56.0 55.5 6,253 Primary 14.1 7.4 21.5 26.5 13.1 39.6 40.6 20.5 61.1 64.8 63.9 2,895 Secondary 9.7 3.4 13.1 44.1 8.3 52.4 53.8 11.7 65.5 80.0 77.3 654 More than secondary 5.5 5.3 10.8 47.9 7.1 55.0 53.4 12.4 65.8 83.6 77.1 421 Wealth quintile Lowest 16.6 9.9 26.5 11.3 8.3 19.6 27.9 18.2 46.1 42.5 42.2 1,953 Second 15.7 11.8 27.5 18.2 12.9 31.1 33.9 24.7 58.6 53.1 52.9 2,074 Middle 14.3 9.5 23.8 21.1 16.0 37.2 35.4 25.6 60.9 61.0 60.3 2,057 Fourth 11.7 8.9 20.7 22.5 18.5 40.9 34.2 27.4 61.6 66.4 65.8 1,999 Highest 7.1 6.6 13.6 33.7 15.8 49.4 40.7 22.3 63.1 78.4 75.2 2,140 Total 13.0 9.3 22.3 21.5 14.3 35.9 34.5 23.7 58.2 61.6 60.6 10,223 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, IUD, injectables, implants, male condom, female condom, emergency contraception, standard days method (SDM), and lactational amenorrhoea method (LAM), and other modern methods. 118 • Family Planning Table 7.10.2 Need and demand for family planning for all women and for sexually active unmarried women Percentage of all women and sexually active unmarried 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 demand for family planning that is satisfied, according to background characteristics, Ethiopia DHS 2016 Unmet need for family planning Met need for family planning (currently using) Total demand for family planning1 Percent-age of demand satisfied2 Percent- age 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 4.2 0.6 4.7 6.9 0.6 7.5 11.1 1.2 12.2 61.4 60.7 3,381 20-24 10.4 1.9 12.3 23.1 3.2 26.4 33.5 5.1 38.7 68.3 67.4 2,762 25-29 14.1 3.8 17.8 26.4 9.3 35.7 40.4 13.0 53.5 66.7 65.3 2,957 30-34 13.1 9.0 22.1 19.1 16.0 35.0 32.1 25.0 57.1 61.4 60.5 2,345 35-39 8.6 14.4 22.9 10.8 19.3 30.1 19.4 33.6 53.0 56.7 54.9 1,932 40-44 4.3 15.7 20.0 5.8 22.4 28.2 10.2 38.1 48.2 58.5 57.4 1,290 45-49 2.4 11.3 13.8 1.7 15.2 16.8 4.1 26.5 30.6 55.0 53.5 1,017 Residence Urban 3.4 2.9 6.3 20.3 8.2 28.5 23.7 11.1 34.8 81.9 78.2 3,476 Rural 10.5 7.3 17.7 13.9 10.6 24.5 24.3 17.8 42.2 58.0 57.4 12,207 Region Tigray 7.3 3.7 11.0 17.5 7.7 25.2 24.8 11.4 36.2 69.7 67.7 1,129 Affar 9.9 3.2 13.1 8.3 1.6 10.0 18.2 4.9 23.0 43.2 43.2 128 Amhara 5.9 6.0 11.9 21.8 12.3 34.1 27.7 18.3 46.0 74.1 73.3 3,714 Oromiya 12.5 8.6 21.1 11.6 9.7 21.3 24.1 18.3 42.4 50.2 49.3 5,701 Somali 6.7 2.2 9.0 1.0 0.1 1.1 7.7 2.3 10.0 10.7 9.5 459 Benishangul-Gumuz 8.6 6.9 15.5 13.4 8.5 22.0 22.0 15.5 37.5 58.6 58.3 160 SNNPR 8.6 5.5 14.0 15.1 11.6 26.7 23.6 17.1 40.7 65.6 65.1 3,288 Gambela 9.5 7.0 16.5 17.2 9.3 26.5 26.7 16.3 43.0 61.7 61.7 44 Harari 8.2 5.8 14.0 13.6 6.7 20.3 21.8 12.4 34.2 59.2 58.8 38 Addis Ababa 3.2 1.7 4.9 19.0 7.0 26.0 22.1 8.7 30.9 84.2 75.1 930 Dire Dawa 6.4 5.3 11.7 13.7 5.9 19.6 20.0 11.2 31.3 62.6 60.1 90 Education No education 11.4 9.5 20.8 13.3 14.2 27.6 24.7 23.7 48.4 57.0 56.5 7,498 Primary 8.0 4.2 12.3 15.4 7.5 22.9 23.5 11.7 35.2 65.1 64.1 5,490 Secondary 4.2 1.3 5.5 17.5 3.3 20.8 21.7 4.6 26.3 79.0 75.8 1,817 More than secondary 3.0 2.5 5.5 27.0 4.0 31.0 29.9 6.6 36.5 84.9 77.8 877 Wealth quintile Lowest 13.0 7.8 20.8 9.1 7.0 16.1 22.1 14.7 36.8 43.7 43.4 2,633 Second 11.8 9.0 20.9 13.9 10.2 24.1 25.8 19.2 45.0 53.6 53.4 2,809 Middle 10.4 6.7 17.2 15.7 11.6 27.4 26.2 18.4 44.5 61.5 60.7 2,978 Fourth 7.6 5.9 13.5 15.7 12.7 28.3 23.3 18.6 41.8 67.8 67.2 3,100 Highest 4.2 3.5 7.7 19.6 8.8 28.4 23.8 12.3 36.1 78.5 75.1 4,163 Total 8.9 6.3 15.2 15.3 10.0 25.3 24.2 16.3 40.5 62.5 61.3 15,683 SEXUALLY ACTIVE UNMARRIED WOMEN4 Total 25.8 0.6 26.4 44.6 13.5 58.1 70.4 14.1 84.5 68.8 65.1 176 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, IUD, injectables, implants, male condom, female condom, emergency contraception, standard days method (SDM), lactational amenorrhoea method (LAM), and other modern methods. 4 Women who have had sexual intercourse within 30 days preceding the survey Family Planning • 119 Table 7.11 Decision making about family planning Among currently married women age 15-49 who are current users of family planning, percent distribution by who makes the decision to use family planning; among currently married women who are not currently using family planning, percent distribution by who makes the decision not to use family planning, according to background characteristics, Ethiopia DHS 2016 Among currently married women who are current users of family planning Among currently married women who are not currently using family planning Background characteristic Mainly wife Wife and husband jointly Mainly husband Other Total Number Mainly wife Wife and husband jointly Mainly husband Other Total Number Age 15-19 22.8 74.2 3.0 0.0 100.0 188 19.9 70.7 7.8 1.6 100.0 313 20-24 18.1 76.7 5.1 0.0 100.0 663 23.2 62.3 12.8 1.7 100.0 762 25-29 17.3 75.9 6.8 0.0 100.0 985 27.1 60.9 10.9 1.0 100.0 1,090 30-34 22.8 70.6 6.6 0.0 100.0 765 29.5 57.2 11.2 2.2 100.0 1,064 35-39 27.4 67.7 4.9 0.1 100.0 559 32.8 55.9 10.4 0.9 100.0 928 40-44 30.2 67.9 1.9 0.0 100.0 355 36.5 51.9 9.1 2.5 100.0 666 45-49 16.1 75.4 4.7 3.8 100.0 154 38.7 50.4 8.1 2.8 100.0 636 Number of living children 0 25.2 71.4 3.4 0.0 100.0 278 26.6 62.6 8.0 2.8 100.0 430 1-2 19.5 77.1 3.4 0.0 100.0 1,357 25.9 62.5 10.5 1.1 100.0 1,389 3-4 21.8 70.6 7.5 0.0 100.0 1,073 32.5 55.8 10.5 1.2 100.0 1,415 5+ 23.2 69.7 6.5 0.6 100.0 961 31.8 55.1 10.9 2.3 100.0 2,223 Residence Urban 22.9 73.9 3.1 0.1 100.0 862 33.1 60.7 5.0 1.3 100.0 643 Rural 21.2 72.5 6.1 0.2 100.0 2,806 29.7 57.4 11.2 1.8 100.0 4,815 Region Tigray 28.6 68.2 3.2 0.0 100.0 239 36.4 57.8 5.0 0.8 100.0 365 Affar 22.6 75.9 1.5 0.0 100.0 11 31.6 56.3 7.7 4.4 100.0 72 Amhara 23.1 75.8 1.1 0.0 100.0 1,142 39.4 56.6 2.8 1.3 100.0 1,065 Oromiya 17.1 72.8 10.1 0.0 100.0 1,141 24.9 60.0 14.1 1.1 100.0 2,390 Somali * * * * * 5 21.5 62.6 8.4 7.5 100.0 261 Benishangul-Gumuz 14.4 75.9 9.8 0.0 100.0 32 22.3 55.1 21.2 1.4 100.0 70 SNNPR 22.6 70.7 6.1 0.6 100.0 867 32.2 52.8 12.6 2.4 100.0 1,042 Gambela 23.8 71.9 4.3 0.0 100.0 10 39.3 44.3 10.4 6.1 100.0 17 Harari 43.7 50.6 5.7 0.0 100.0 7 50.3 36.1 13.0 0.6 100.0 14 Addis Ababa 25.0 72.2 2.4 0.5 100.0 198 31.0 62.4 4.0 2.5 100.0 132 Dire Dawa 37.4 58.5 4.2 0.0 100.0 15 33.3 56.9 9.6 0.3 100.0 30 Education No education 24.2 69.1 6.5 0.2 100.0 1,948 30.2 56.2 11.5 2.1 100.0 3,718 Primary 19.2 75.0 5.6 0.2 100.0 1,146 30.5 59.5 8.8 1.1 100.0 1,370 Secondary 18.1 80.3 1.5 0.1 100.0 343 26.5 65.6 7.1 0.8 100.0 220 More than secondary 17.0 82.1 0.9 0.0 100.0 231 27.7 67.3 4.9 0.1 100.0 150 Wealth quintile Lowest 27.1 65.8 7.2 0.0 100.0 382 29.6 55.9 12.1 2.4 100.0 1,325 Second 26.0 66.9 6.8 0.2 100.0 645 28.3 57.3 12.9 1.4 100.0 1,169 Middle 20.7 72.5 6.8 0.0 100.0 765 30.3 57.7 10.7 1.3 100.0 1,089 Fourth 16.2 78.8 4.6 0.4 100.0 818 30.4 58.3 9.4 1.9 100.0 987 Highest 21.8 74.6 3.5 0.1 100.0 1,058 32.4 60.6 5.5 1.5 100.0 888 Total 15-49 21.6 72.8 5.4 0.2 100.0 3,669 30.1 57.8 10.4 1.7 100.0 5,458 Note: Table excludes women who are currently pregnant. An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. Table 7.12 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, Ethiopia DHS 2016 Number of living children1 Total Intention to use in the future 0 1 2 3 4+ Intends to use 55.0 64.3 56.2 53.6 40.2 48.6 Unsure 4.6 2.0 2.8 2.0 2.1 2.3 Does not intend to use 40.4 33.7 41.0 44.4 57.7 49.1 Total 100.0 100.0 100.0 100.0 100.0 100.0 Number of women 430 940 860 916 3,409 6,555 1 Includes current pregnancy 12 0 • F am ily P la nn in g Ta bl e 7. 13 E xp o su re t o fa m ily p la nn in g m es sa ge s P er ce nt ag e of w om en a nd m en a ge 1 5- 49 w ho h ea rd o r s aw a fa m ily p la nn in g m es sa ge o n ra di o; o n te le vi si on ; i n a ne w sp ap er o r m ag az in e; in a p am ph le t, po st er , o r l ea fle t; at a c om m un ity e ve nt o r i n co nv er sa tio n; o n a m ob ile ph on e; o r o n th e In te rn et in th e pa st fe w m on th s, a cc or di ng to b ac kg ro un d ch ar ac te ris tic s, E th io pi a D H S 2 01 6 W om en M en B ac kg ro un d ch ar ac te ris tic R ad io T el ev is io n N ew s- pa pe r/ m ag az in e P am ph le t/ po st er s/ le af le ts C om - m un ity ev en t/ co nv er - sa tio n M ob ile ph on e In te rn et N on e of th es e se ve n m ed ia so ur ce s N um be r of w om en R ad io T el e- vi si on N ew s- pa pe r/ m ag az in e P am ph le t/ po st er s/ le af le ts C om - m un ity ev en t/ co nv er - sa tio n M ob ile ph on e In te rn et N on e of th es e se ve n m ed ia so ur ce s N um be r of m en A ge 15 -1 9 24 .0 19 .6 6. 6 8. 3 26 .8 3. 2 2. 0 50 .9 3, 38 1 23 .4 17 .1 8. 7 12 .5 17 .8 2. 7 3. 0 56 .2 2, 57 2 20 -2 4 27 .2 20 .9 7. 7 8. 3 35 .6 3. 8 3. 2 46 .5 2, 76 2 35 .5 23 .6 13 .5 18 .6 31 .0 4. 4 5. 7 41 .9 1, 88 3 25 -2 9 27 .3 19 .7 5. 1 6. 8 39 .8 2. 4 1. 9 41 .9 2, 95 7 38 .4 27 .9 14 .6 20 .1 42 .4 6. 3 6. 1 34 .0 1, 97 7 30 -3 4 24 .3 18 .2 2. 6 4. 1 41 .7 2. 0 1. 1 44 .5 2, 34 5 36 .2 25 .2 12 .7 17 .7 46 .5 5. 2 4. 6 32 .9 1, 63 5 35 -3 9 20 .0 14 .5 3. 9 4. 2 44 .9 2. 8 1. 2 43 .7 1, 93 2 39 .3 22 .8 10 .8 12 .6 47 .2 2. 6 3. 0 32 .9 1, 38 6 40 -4 4 17 .9 12 .2 3. 1 4. 1 47 .2 1. 6 0. 4 43 .7 1, 29 0 31 .9 22 .8 9. 6 15 .4 49 .6 2. 2 1. 7 33 .2 1, 20 6 45 -4 9 21 .2 15 .1 2. 9 4. 8 43 .4 1. 0 0. 1 46 .3 1, 01 7 33 .4 17 .9 8. 3 11 .0 44 .1 2. 4 1. 4 36 .2 94 7 R es id en ce U rb an 46 .4 63 .3 14 .4 17 .7 39 .0 6. 6 6. 4 20 .3 3, 47 6 50 .1 58 .3 21 .6 34 .8 29 .6 8. 6 14 .0 23 .8 2, 30 3 R ur al 17 .7 5. 2 2. 4 3. 1 37 .7 1. 5 0. 4 52 .9 12 ,2 07 29 .2 13 .6 8. 8 11 .0 39 .0 2. 7 1. 4 44 .0 9, 30 2 R eg io n T ig ra y 28 .8 23 .4 7. 2 10 .0 58 .3 1. 4 2. 8 29 .4 1, 12 9 27 .4 28 .4 13 .9 18 .2 51 .5 2. 9 3. 7 30 .3 70 8 A ffa r 13 .8 19 .6 2. 5 3. 8 25 .2 1. 0 0. 6 57 .5 12 8 38 .5 37 .7 5. 9 5. 1 10 .5 1. 8 1. 9 49 .9 82 A m ha ra 19 .8 15 .2 4. 5 6. 9 50 .8 1. 6 0. 9 38 .7 3, 71 4 27 .2 22 .7 7. 5 14 .9 41 .6 2. 0 1. 8 37 .5 2, 91 4 O ro m iy a 25 .7 14 .9 4. 7 3. 9 30 .4 4. 3 1. 6 51 .9 5, 70 1 38 .0 19 .9 12 .1 12 .6 37 .0 5. 4 4. 5 40 .4 4, 40 9 S om al i 4. 8 6. 6 1. 4 1. 8 17 .0 0. 9 0. 7 77 .4 45 9 7. 4 5. 8 2. 4 2. 7 8. 3 0. 7 1. 7 83 .9 30 1 B en is ha ng ul -G um uz 26 .0 13 .1 5. 5 6. 2 31 .1 1. 8 1. 0 49 .5 16 0 28 .7 14 .4 4. 5 9. 0 26 .2 1. 9 2. 9 47 .5 11 8 S N N P R 18 .5 9. 0 3. 6 4. 1 36 .3 1. 4 1. 1 52 .0 3, 28 8 30 .4 15 .2 12 .3 15 .7 37 .2 3. 3 2. 0 45 .1 2, 37 1 G am be la 16 .4 24 .4 3. 2 5. 2 34 .1 2. 1 1. 5 48 .7 44 28 .7 32 .1 9. 2 17 .3 16 .5 2. 3 5. 9 50 .1 35 H ar ar i 41 .4 58 .2 16 .7 15 .5 30 .5 4. 4 4. 1 30 .6 38 41 .9 40 .1 14 .1 13 .1 15 .4 6. 0 10 .5 40 .1 29 A dd is A ba ba 54 .4 76 .9 12 .4 23 .5 30 .1 3. 7 7. 4 16 .8 93 0 60 .8 68 .6 24 .1 49 .3 22 .7 6. 7 18 .9 14 .6 57 3 D ire D aw a 31 .2 46 .5 11 .7 11 .6 23 .7 3. 6 4. 5 39 .7 90 36 .8 42 .8 22 .1 23 .0 25 .9 5. 4 10 .0 33 .7 66 E du ca ti o n N o ed uc at io n 13 .7 5. 0 0. 3 0. 6 40 .0 0. 8 0. 2 53 .3 7, 49 8 21 .1 9. 6 0. 9 2. 6 43 .0 0. 9 0. 4 46 .1 3, 20 3 P rim ar y 25 .2 16 .5 4. 3 5. 1 33 .8 2. 1 0. 7 47 .8 5, 49 0 31 .0 16 .6 9. 2 12 .2 33 .9 2. 4 1. 2 44 .5 5, 60 8 S ec on da ry 46 .4 49 .0 16 .5 20 .6 39 .8 7. 4 4. 7 23 .8 1, 81 7 47 .5 40 .0 22 .3 31 .1 33 .5 7. 7 8. 2 29 .9 1, 78 5 M or e th an s ec on da ry 59 .6 76 .5 26 .7 33 .3 43 .5 11 .6 15 .1 12 .8 87 7 59 .9 65 .2 37 .3 49 .7 43 .2 14 .5 22 .2 13 .8 1, 01 0 W ea lt h q ui nt ile Lo w es t 8. 2 1. 5 0. 7 1. 0 32 .9 0. 7 0. 1 62 .8 2, 63 3 16 .4 8. 3 4. 1 5. 4 34 .5 1. 2 0. 6 55 .1 1, 83 9 S ec on d 12 .6 2. 6 1. 7 1. 9 38 .0 2. 0 0. 5 54 .9 2, 80 9 22 .6 8. 7 5. 8 6. 0 38 .6 1. 8 0. 7 47 .9 2, 11 8 M id dl e 15 .1 2. 8 2. 0 2. 3 38 .9 1. 1 0. 1 54 .4 2, 97 8 28 .5 12 .1 7. 7 10 .7 39 .2 1. 8 0. 8 44 .8 2, 24 6 Fo ur th 26 .5 7. 0 3. 8 4. 4 40 .2 1. 5 0. 4 46 .9 3, 10 0 36 .8 16 .1 12 .7 15 .9 41 .8 4. 4 2. 1 37 .7 2, 46 6 H ig he st 46 .5 58 .3 13 .2 16 .9 39 .0 6. 3 5. 6 21 .6 4, 16 3 52 .4 54 .6 21 .5 32 .8 32 .3 8. 1 12 .2 23 .2 2, 93 5 T ot al 1 5- 49 24 .1 18 .1 5. 0 6. 3 38 .0 2. 6 1. 7 45 .7 15 ,6 83 33 .3 22 .5 11 .4 15 .7 37 .1 3. 8 3. 9 40 .0 11 ,6 06 50 -5 9 na na na na na na na na na 33 .5 23 .0 12 .9 14 .4 53 .5 4. 4 2. 6 32 .1 1, 08 2 T ot al 1 5- 59 na na na na na na na na na 33 .3 22 .5 11 .5 15 .6 38 .5 3. 9 3. 8 39 .3 12 ,6 88 na = N ot a pp lic ab le Family Planning • 121 Table 7.14 Contact of nonusers 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, Ethiopia DHS 2016 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 12.9 3.9 18.1 84.6 3,127 20-24 21.5 13.1 26.6 71.5 2,033 25-29 21.5 14.2 29.6 71.3 1,903 30-34 32.3 20.2 30.0 59.1 1,524 35-39 25.7 14.8 26.2 67.9 1,351 40-44 24.3 10.2 25.6 70.5 926 45-49 26.1 12.1 26.9 67.5 846 Residence Urban 20.0 12.8 33.4 73.0 2,487 Rural 22.1 11.3 22.9 72.5 9,222 Region Tigray 34.5 21.8 29.3 58.9 844 Affar 15.4 6.9 35.5 80.5 115 Amhara 22.3 12.7 28.2 70.2 2,448 Oromiya 22.5 11.8 23.6 71.0 4,488 Somali 11.1 2.1 17.6 87.6 455 Benishangul-Gumuz 42.9 12.1 28.7 53.5 125 SNNPR 18.4 8.6 19.2 78.7 2,410 Gambela 15.2 10.1 39.4 77.4 32 Harari 29.2 21.6 14.7 65.9 31 Addis Ababa 13.7 10.6 42.0 79.0 688 Dire Dawa 21.8 16.3 29.3 69.3 73 Education No education 23.9 12.7 24.8 69.9 5,431 Primary 19.4 9.6 23.7 76.0 4,233 Secondary 21.4 11.7 25.7 73.2 1,439 More than secondary 18.3 16.3 37.8 71.4 606 Wealth quintile Lowest 18.6 8.5 21.4 76.8 2,209 Second 21.7 11.2 24.3 73.0 2,133 Middle 23.3 11.4 23.9 71.7 2,163 Fourth 24.3 12.9 22.3 70.0 2,221 Highest 20.8 13.5 31.6 71.8 2,983 Total 21.7 11.6 25.2 72.6 11,709 Infant and Child Mortality • 123 INFANT AND CHILD MORTALITY 8 Key Findings  Current levels: For the 5-year period preceding the survey, the under-5 mortality rate is 67 deaths per 1,000 live births, and the infant mortality rate is 48 deaths per 1,000 live births. This means that 1 in 15 children in Ethiopia dies before reaching age 5, and 7 in 10 of the deaths occur during infancy.  Trends: Childhood mortality has declined substantially since 2000. However, the change in neonatal mortality is not as significant as the change in post-neonatal and child mortality.  Regional differences: Regions show large variations in childhood mortality. Under-5 mortality ranges from a low of 39 deaths per 1,000 live births in Addis Ababa to a high of 125 deaths per 1,000 live births in Affar.  High-risk fertility behaviour: Seventy-seven percent of currently married women have the potential for a high-risk birth. Sixty-two percent of births have high mortality risks that are avoidable; 38% fall into a single high-risk category and 24% are in a multiple high-risk category. Only 24% of births are not in any high-risk category. nformation on infant and child mortality is relevant to a demographic assessment of the population, and is an important indicator of a country’s socioeconomic development and quality of life. It can also help to estimate how many children may be at higher risk of death and support the development of strategies to reduce this risk, such as promoting birth spacing. This chapter presents information on levels, trends, and differentials in perinatal, neonatal, postneonatal, infant, child, and under-5 mortality rates. It also examines biodemographic factors and fertility behaviours that increase mortality risks for infants and children. The information is collected during a retrospective birth history, in which female respondents list all of the children they have ever borne, along with each child’s date of birth, survivorship status, and current age or age at death for deceased children. The quality of mortality estimates calculated from birth histories depends on 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.  Displacement of birth dates, which may distort mortality trends. An interviewer might knowingly record a birth as occurring in a different year than the one in which it occurred. This may happen if an interviewer is trying to cut down on his or her overall work load, because live births occurring during the 5 years before the interview are the subject of a lengthy set of additional questions. I 124 • Infant and Child Mortality  Inaccurate 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.  Misplaced reliance on mothers’ reports (birth histories) to measure childhood mortality. Any method that relies on retrospective information based on the mothers’ reports 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. Selected indicators of the quality of the mortality data in this chapter are presented in Appendix C, Tables C.4-C.6. 8.1 INFANT AND CHILD MORTALITY Neonatal mortality: The probability of dying within the first month of life Post neonatal mortality: The probability of dying between one month and the first birthday (computed as the difference between infant and neonatal mortality) Infant mortality: The probability of dying between birth and the first birthday Child mortality: The probability of dying between the first and the fifth birthday Under-5 mortality: The probability of dying between birth and the fifth birthday The 2016 EDHS results show that the neonatal, infant, and under-5 mortality rates for the 5 years before the survey are 29, 48, and 67 deaths per 1,000 live births, respectively. In other words, in Ethiopia 1 in every 35 children dies within the first month, 1 in every 21 children dies before celebrating the first birthday, and 1 of every 15 children dies before reaching the fifth birthday (Table 8.1). Trends: Under-5 mortality declined from 166 deaths per 1,000 live births in 2000 to 67 deaths per 1,000 live births in 2016 (Figure 8.1). This represents a 60% decrease in under-5 mortality over a period of 16 years. Infant mortality also declined from 97 deaths per 1,000 live births in 2000 to 48 deaths per 1,000 live births in 2016, which is about a 50% reduction in the last 16 years. Neonatal mortality declined from 49 deaths per 1,000 live births in 2000 to 29 deaths per 1,000 births in 2016, a reduction of 41% over the past 16 years. Patterns by background characteristics  It is important to note that 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). Figure 8.1 Trends in early childhood mortality rates 166 123 88 6797 77 59 4849 39 37 29 2000 EDHS 2005 EDHS 2011 EDHS 2016 EDHS 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 • 125  Under-5 mortality is higher in rural areas than in urban areas (83 versus 66 deaths per 1,000 live births).  By region, the under-5 mortality rate is highest in Affar (125 deaths per 1,000 live births) and lowest in Addis Ababa (39 deaths per 1,000 live births) (Figure 8.2).  The infant mortality rate declines with increases in the mother’s education, falling from 64 deaths per 1,000 live births among children whose mothers have no education to 35 deaths per 1,000 live births among children whose mothers have more than secondary education (Figure 8.3). 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 on the circumstances of the birth. Table 8.3 illustrates the relationship between these risk factors and neonatal, postneonatal, infant, and under-5 mortality.  Boys are more likely to die in childhood than girls. The gender gap is most pronounced in the neonatal period (within 1 month after birth), when male children are nearly twice as likely as female children to die (49 deaths compared with 26 deaths, per 1,000 live births, respectively).  Shorter intervals between births are associated with higher mortality. The under-5 mortality rate for children born less than 2 years after the preceding birth is more than twice as high as that of children born 4 or more years after their preceding sibling (114 deaths per 1,000 live births compared with 55 deaths per 1,000 live births). Similarly, the infant mortality rate is 92 deaths per 1,000 live births for a birth interval less than2 years and 44 deaths per 1,000 live births for children born 4 or more years after the preceding birth (Figure 8.4).  Children reported to be small or very small at birth are more likely to die than children reported to be average or larger at birth. For example, infant mortality for children who were reported to be small or very small at birth is 56 deaths per 1,000 live births compared with 43 deaths per 1,000 live births for children who were reported to be average or larger at birth. Figure 8.2 Under-5 mortality by region Figure 8.3 Infant mortality by mother’s education Figure 8.4 Childhood mortality by previous birth interval 39 59 72 79 85 88 88 93 94 98 125 Addis Ababa Tigray Harari Oromiya Amhara SNNPR Gambela Dire Dawa Somali Benishangul-Gumuz Affar Deaths per 1,000 live births for the 10-year period before the survey 64 57 43 35 No education Primary Secondary More than secondary Deaths per 1,000 live births for the 10-year period before the survey 92 114 52 78 30 4444 55 Infant mortality Under-5 mortality Previous birth interval: Deaths per 1,000 live births for the 10-year period before the survey <2 years 2 years 3 years 4+ years 126 • Infant and Child Mortality 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 5 years before the survey. The causes of stillbirths and early neonatal deaths are closely linked, and it can be difficult to determine whether a death is attributable to one cause or the other. The perinatal mortality rate encompasses both stillbirths and early neonatal deaths, and offers a better measure of the level of mortality and quality of service at delivery. During the 5 years before the survey, the perinatal mortality rate is 33 deaths per 1,000 pregnancies (Table 8.4). Patterns by background characteristics  Perinatal mortality increases with mother’s age at birth, from 28 deaths per 1,000 pregnancies for women age 20-29 to 63 deaths per 1,000 pregnancies for women age 40-49. This shows that perinatal mortality among children born to women age 40-49 is more than twice as high as for women age 20- 29.  The perinatal mortality rate is relatively high for first pregnancies (33 deaths per 1,000 pregnancies) and among women with a pregnancy interval of less than 15 months (45 deaths per 1,000 pregnancies).  The perinatal mortality rate is higher in urban than in rural areas (42 versus 32 deaths per 1,000 pregnancies, respectively).  The perinatal mortality rate is highest in Somali (50 deaths per 1,000 pregnancies) and lowest in Affar and SNNPR (26 deaths per 1,000 pregnancies for each region).  The perinatal mortality rate is highest among pregnancies to women with more than secondary education (52 deaths per 1,000 pregnancies) compared with pregnancies to women with no education (Figure 8.5). 8.4 HIGH-RISK FERTILITY BEHAVIOUR Findings from scientific studies have confirmed a strong relationship between a child’s chance of dying and specific fertility behaviours, meaning that the survival of infants and children depends in part on the demographic and biological characteristics of their mothers. The probability of children dying in infancy is much greater among children born to mothers who are too young (under age 18) or too old (over age 34), children born after a short birth interval (less than 24 months after the preceding birth), and children born to mothers of high parity (more than three children). The risk is elevated when a child is born to a mother who has a combination of these risk characteristics. Figure 8.5 Perinatal mortality by mother’s education 33 32 30 52 No education Primary Secondary More than secondary Deaths per 1,000 pregancies of 7 or more months’ duration in the 5-year period before the survey Infant and Child Mortality • 127 Table 8.5 presents the percentage distribution of children born in the 5 years preceding the survey that fall into different risk categories: either not in any high risk category, in an unavoidable risk category, in a single high risk category, or in a multiple high-risk category.  In the 5 years before the survey, three-fifths of births in Ethiopia (62%) are at an elevated risk of dying from avoidable risks; 38% of births are in a single high-risk category, and 24% of births are in a multiple high-risk category). Twenty-four percent of births are not in any high risk category, while 15% of births are in the unavoidable risk category.  In general, risk ratios are higher for children in a multiple high-risk category than in a single high-risk category. The most vulnerable births are those to two groups of women: women age 34 or older, birth interval less than 24 months after the previous birth, and with birth order higher than three (2.58); women of age less than 18, and with birth interval less than 24 months (2.33).  Overall, 77% of currently married women have the potential for having a high-risk birth, with 31% falling into a single high-risk category and 45% falling into a multiple high-risk category. LIST OF TABLES For more information on infant and child mortality, see the following tables:  Table 8.1 Early childhood mortality rates  Table 8.2 Early childhood mortality rates according to socioeconomic characteristics  Table 8.3 Early childhood mortality rates according to demographic characteristics  Table 8.4 Perinatal mortality  Table 8.5 High-risk fertility behaviour 128 • Infant and Child Mortality Table 8.1 Early childhood mortality rates Neonatal, postneonatal, infant, child, and under-5 mortality rates for 5-year periods preceding the survey, Ethiopia DHS 2016 Years preceding the survey Neonatal mortality (NN) Post- neonatal mortality (PNN)1 Infant mortality (1q0) Child mortality (4q1) Under-5 mortality (5q0) 0-4 29 19 48 20 67 5-9 46 27 73 24 95 10-14 47 30 78 42 116 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, Ethiopia DHS 2016 Background characteristic Neonatal mortality (NN) Post- neonatal mortality (PNN)1 Infant mortality (1q0) Child mortality (4q1) Under-5 mortality (5q0) Residence Urban 41 13 54 13 66 Rural 38 24 62 23 83 Region Tigray 34 8 43 17 59 Affar 38 42 81 48 125 Amhara 47 20 67 19 85 Oromiya 37 23 60 20 79 Somali 41 26 67 29 94 Benishangul-Gumuz 35 26 62 38 98 SNNPR 35 30 65 25 88 Gambela 36 21 56 33 88 Harari 34 23 57 16 72 Addis Ababa 18 10 28 11 39 Dire Dawa 36 31 67 28 93 Mother’s education No education 39 25 64 23 86 Primary 35 21 57 19 74 Secondary 31 12 43 11 54 More than secondary 34 0 35 (8) (42) Wealth quintile Lowest 36 25 62 30 90 Second 34 21 55 23 76 Middle 35 25 60 22 80 Fourth 47 28 75 18 91 Highest 40 14 54 13 67 Notes: Figures in parentheses are based on 250-499 unweighted persons-years of exposure to the risk of death. 1 Computed as the difference between the infant and neonatal mortality rates Infant and Child Mortality • 129 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, Ethiopia DHS 2016 Demographic characteristic Neonatal mortality (NN) Post- neonatal mortality (PNN)1 Infant mortality (1q0) Child mortality (4q1) Under-5 mortality (5q0) Child’s sex Male 49 26 74 22 94 Female 26 20 47 22 68 Mother’s age at birth <20 47 27 74 21 93 20-29 32 24 55 20 74 30-39 44 19 63 27 88 40-49 56 (26) (82) * * Birth order 1 48 25 73 24 95 2-3 32 22 53 23 75 4-6 33 22 55 17 71 7+ 49 26 75 27 100 Previous birth interval2 <2 years 54 38 92 24 114 2 years 29 23 52 28 78 3 years 20 10 30 14 44 4+ years 33 11 44 11 55 Birth size3 Small/very small 31 25 56 na na Average or larger 27 16 43 na na Note: Figures in parentheses are based on 250-499 unweighted person-years 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 5-year period preceding the survey 130 • Infant and Child Mortality Table 8.4 Perinatal mortality Number of stillbirths and early neonatal deaths, and the perinatal mortality rate for the 5-year period preceding the survey, according to background characteristics, Ethiopia DHS 2016 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 22 23 34 1,317 20-29 56 114 28 6,055 30-39 35 87 38 3,243 40-49 17 12 63 455 Previous pregnancy interval in months4 First pregnancy 29 37 33 2,019 <15 20 52 45 1,624 15-26 19 53 29 2,507 27-38 16 28 23 1,920 39+ 45 66 37 3,000 Residence Urban 10 41 42 1,215 Rural 120 195 32 9,855 Region Tigray 10 15 36 720 Affar 1 2 26 115 Amhara 50 43 44 2,105 Oromiya 39 106 30 4,856 Somali 7 19 50 513 Benishangul-Gumuz 1 3 29 122 SNNPR 20 41 26 2,298 Gambela 0 1 28 27 Harari 0 1 40 26 Addis Ababa 2 5 28 243 Dire Dawa 0 1 27 47 Mother’s education No education 84 156 33 7,305 Primary 40 56 32 2,977 Secondary 3 13 30 516 More than secondary 3 11 52 272 Wealth quintile Lowest 31 41 27 2,654 Second 28 43 28 2,516 Middle 27 53 35 2,290 Fourth 27 52 39 2,018 Highest 16 47 40 1,592 Total 130 236 33 11,071 1 Stillbirths are foetal deaths in pregnancies lasting 7 or more months. 2 Early neonatal deaths are deaths at age 0-6 days among children born alive. 3 The sum of the number of stillbirths and early neonatal deaths divided by the number of pregnancies of 7 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 • 131 Table 8.5 High-risk fertility behaviour Percent distribution of children born in the 5 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, Ethiopia DHS 2016 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 23.7 1.00 16.3a Unavoidable risk category First order births between ages 18 and 34 years 14.6 1.03 7.2 In any avoidable high-risk category 61.7 1.15 76.5 Single high-risk category Mother’s age <18 4.4 1.30 0.8 Mother’s age >34 0.8 1.15 2.6 Birth interval <24 months 5.4 1.31 9.3 Birth order >3 27.1 0.81 18.7 Subtotal 37.8 0.95 31.4 Multiple high-risk category Age <18 and birth interval <24 months2 0.4 2.33 0.3 Age >34 and birth interval <24 months 0.0 * 0.2 Age >34 and birth order >3 11.7 0.84 27.6 Age >34 and birth interval <24 months and birth order >3 2.3 2.58 5.2 Birth interval <24 months and birth order >3 9.5 1.97 11.8 Subtotal 23.9 1.48 45.1 Total 100.0 na 100.0 Subtotals by individual avoidable high-risk category Mother’s age <18 4.8 3.60 1.1 Mother’s age >34 14.8 14.44 35.5 Birth interval <24 months 19.8 16.94 42.5 Birth order >3 50.7 6.20 63.3 Number of births/women 11,023 na 10,223 Note: Risk ratio is the ratio of the proportion dead among births in a specific high-risk category to the proportion dead among births not in any high-risk category. An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. na = Not applicable 1 Women are assigned to risk categories according to the status they would have at the birth of a child if they were to conceive at the time of the survey: current age less than 17 years and 3 months or older than 34 years and 2 months, latest birth less than 15 months ago, or latest birth being of order 3 or higher. 2 Includes the category age <18 and birth order >3 a Includes sterilised women Maternal Health Care • 133 MATERNAL HEALTH CARE 9 Key Findings  Antenatal care: The proportion of women age 15-49 in Ethiopia who received antenatal care (ANC) from a skilled provider has increased from 27% in 2000 to 34% in 2011, and 62% in 2016. Thirty-two percent of women had at least four ANC visits during their last pregnancy.  Components of antenatal care: Pregnant women are more likely to have their blood pressure measured (75%) and blood sample taken (73%), than to have their urine sample taken or to have received nutritional counselling (66% for both).  Protection against neonatal tetanus: Nearly 49% of women had their last birth protected against neonatal tetanus.  Delivery: Institutional deliveries have increased from 5% in 2000 to 10% in 2011, and 26% in 2016. During the same period, home deliveries decreased from 95% in 2000 to 90% in 2011, and 73% in 2016.  Postnatal care: Seventeen percent of women and 13% of newborns received a postnatal check within the first 2 days of birth.  Problems in accessing health care: The proportion of women age 15-49 who report having at least one of the specified problems in accessing health care decreased from 96% in 2005, to 94% in 2011, and 70% in 2016. ealth care services during pregnancy and after delivery are important for the survival and wellbeing of both the mother and the infant. Skilled care during pregnancy, childbirth, and the postpartum period are important interventions in reducing maternal and neonatal morbidity and mortality. As highlighted in the 2015-16 Health Sector Transformation Plan (HSTP), maternal and newborn health are priorities for the Government of Ethiopia (MOH, 2015). The HSTP key components are delivery at a health facility, with skilled medical attention and hygienic conditions; reduction in complications and infections during labour and delivery; timely postnatal care that treats complications from delivery; and education of the mother on care for herself and her infant. The goal of the reproductive health program is to reduc the maternal mortality ratio to 199 maternal deaths per 100,000 live births and the neonatal mortality rate to 10 per 1,000 live births by 2020. This chapter presents information on antenatal care (ANC) and its main components: the number and timing of ANC visits, protection at birth from tetanus, blood pressure measurement, blood and urine sampling, nutritional counselling, iron folate supplementation, and information of the danger signs of pregnancy complications. The chapter also presents information on childbirth and postnatal care such as place of delivery, assistance during delivery, caesarean delivery, postnatal health checks for mothers and H 134 • Maternal Health Care newborns, and awareness and self-reports of obstetric fistula. The chapter concludes with an examination of key barriers women may face when seeking care during pregnancy, delivery, and the postnatal period. 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, such as doctors and nurses/midwives, health officers, and health extension workers. Sample: Women age 15-49 who had a live birth in the 5 years before the survey The 2016 EDHS shows that 62% of women who had a live birth in the 5 years before the survey received ANC from a skilled provider at least once for their last birth (Table 9.1). Trends: The proportion of women age 15-49 who received any ANC from a skilled provider has increased from 27% in 2000, to 28% in 2005, 34% in 2011, and 62% in 2016 (Figure 9.1). Patterns by background characteristics  Higher order births are less likely to receive ANC than lower order births. Fifty percent of women giving birth to their sixth or higher order child received ANC from a skilled provider, compared with 78% of women giving birth to their first child.  Use of a skilled provider for ANC services varies by residence: urban women are more likely than rural women to receive any ANC from a skilled provider (90% and 58%, respectively).  Among regions, ANC coverage from a skilled provider is highest in Addis Ababa (97%) and lowest in Somali (44%).  Use of a skilled provider for ANC services increases with mother’s level of education. Fifty-three percent of women with no education obtained ANC services from a skilled provider, compared with 98% of women with more than secondary education.  Women in the highest wealth quintile (85%) are more likely than those in the lowest quintile (48%) to receive ANC from a skilled provider. 9.1.2 Timing and Number of ANC Visits As recommended by the WHO, 32% of women had at least four ANC visits during their last pregnancy, while 37% of women in Ethiopia had no ANC visits (Table 9.2). Rural women are more likely to have had no ANC visits than urban women (41% and 10%, respectively). Only 20% of women had their first ANC during the first trimester, 26% during their fourth to fifth month of pregnancy, and 14% during their sixth to seventh month of pregnancy. Two percent of women did not receive any ANC until the eight month of pregnancy or later. Figure 9.1 Trends in antenatal care coverage 27 28 34 62 10 12 19 32 6 6 11 20 2000 EDHS 2005 EDHS 2011 EDHS 2016 EHDS Percentage of women age 15-49 who had a live birth in the 5 years before the survey (for the most recent birth) Received any ANC from skilled provider Had 4+ ANC visits Had ANC in first trimester * Skilled provider for EDHS 2000, 2005, and 2011 includes doctor, nurse, and midwife. Skilled provider for EDHS 2016 includes doctor, nurse, midwife, health officer, and health extension worker. Maternal Health Care • 135 Forty-four percent of women in urban areas receive ANC within their first trimester of pregnancy, compared with 17% of those in rural areas. Trends: The proportion of women who received the recommended four or more ANC visits increased from 2000 (10%) to 2016 (32%). During this same time period, the proportion of women who received ANC in the first trimester has increased more than three times, from 6% in 2000 to 20% in 2016 (Figure 9.1). 9.2 COMPONENTS OF ANC Standard guidelines for ANC in Ethiopia emphasise that every pregnant mother should receive ANC from a skilled provider that includes a thorough physical examination, blood tests for infection screening and anaemia, a urine test, tetanus toxoid injections, iron and folate supplements, and deworming medications. Forty-two percent of women age 15-49 said that they took iron supplements, and 6% took drugs for intestinal parasites during the pregnancy of their last live birth in the 4 years before the survey (Table 9.3). Among women who received ANC, about 4 in 5 women (75%) had their blood pressure measured, 73% had a blood sample taken, and 66% had a urine sample taken as a part of an ANC visit. Two-thirds of the women (66%) received nutritional counselling during their ANC visits (Figure 9.2). Trends: Between 2000 and 2016, there has been an increase in three components of ANC visits. The proportion of pregnant women who had a urine sample collected increased 21% in 2000 to 66% in 2016, and blood samples from 25% in 2000 to 73% in 2016. The proportions of women who had their blood pressure measured increased from 69% to 75% between 2000 and 2016. Patterns by background characteristics  Women living in urban areas are more likely than women living in rural areas to take iron tablets (61% versus 39%).  Sixty nine percent of women with more than secondary education took iron tablets during their pregnancy, compared with 36% of women with no education. The survey also collected data on other components of ANC, such as whether the mother was informed of pregnancy complications or dangers signs, and the need for a birth preparedness plan. Among the women who had a live birth in the 5 years before the survey, 45% of women were informed of the signs of pregnancy complications or danger signs of pregnancy during ANC visits. Among women who were informed of danger signs and pregnancy complications during ANC visits, 50% were informed about vaginal bleeding; 49% about severe headache; 36% about fever; 29% about abdominal pain, 28% about vaginal gush of fluid; 18% about blurred vision; and 8% about convulsions (Table 9.4). Among women who received ANC for their most recent live birth in the past 5 years, 56% were informed about a birth preparedness plan. Eighty seven percent of women were informed about place of birth, 39% about supplies needed for giving birth, 20% about emergency transportation, 19% about an emergency fund or money, 5% about support during and after birth, and 3% about potential blood donors (Table 9.5). Figure 9.2 Components of antenatal care 75 73 66 66 Blood pressure measured Blood sample taken Urine sample taken Nutritional counselling Among women who received ANC for their most recent birth, the percentage with selected services 136 • Maternal Health Care 9.3 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 Neonatal tetanus, a major cause of early infant death in many developing countries, is often due to failure to observe hygienic procedures during delivery. Table 9.6 shows that 49% of women’s last births were protected against neonatal tetanus. Patterns by background characteristics  First births are more likely to be protected against neonatal tetanus than sixth and higher order births (57% versus 43%)  Women in urban areas are more likely to have their births protected again neonatal tetanus (72%) than women in rural areas (46%).  Among regions, births protected again neonatal tetanus are highest in Addis Ababa (82%) and lowest in Affar (30%).  The percentage of women whose last birth was protected from tetanus increases with education, from 41% among women with no education to 83% among those with more than secondary education. Tetanus Vaccination Card The 2016 EDHS also collected information on tetanus vaccination cards. The proportion of women who ever had a tetanus vaccination card was 85% (data not shown separately). All women were not able to produce their tetanus vaccination card at the time of the interview. Only 11% of women who had a TT injection had their cards seen by the interviewers, while 74% of the women were not able to show the card during the interview (Table 9.7). 9.4 DELIVERY SERVICES 9.4.1 Institutional Deliveries Institutional deliveries Deliveries that occur in a health facility. Sample: All live births in the 5 years before the survey Increasing institutional deliveries is important for reducing maternal and neonatal mortality. However, access to health facilities in rural areas is more difficult than in urban areas because of distance, inaccessibility, and the lack of appropriate facilities. Although institutional delivery has been promoted in Ethiopia, home delivery is still common, primarily in hard-to-reach areas. Twenty-six percent of live births in the 5 years before the survey were delivered in a health facility (Table 9.8). Maternal Health Care • 137 Trends: Institutional deliveries have increased from 5% in 2000, 10% in 2011, and 26% in the 2016 EDHS. During the same period, a sharp decline in home deliveries was observed, from 95% in 2000 to 73% in 2016 (Figure 9.3). Institutional deliveries for women living in rural areas has substantially increased in the last 16 years, from 2% in 2000 to 20% in the 2016 EDHS. Facility delivery among urban women has also increased from 32% in 2000 to 79% in 2016. Patterns by background characteristics  Sixth and higher-order births are much more likely to be home deliveries; 84% of sixth or higher order births occurred at home compared with 50% of first births.  Antenatal care increases the likelihood of an institutional delivery. Fifty-six percent of births to mothers who attended more than four ANC visits were delivered in a health facility compared to 8% of births to mothers with no ANC visits.  Institutional delivery is lowest in Affar (15%) followed by Somali (18%) (Figure 9.4).  Ninety-two percent of births to mothers with more than a secondary education were delivered in a health facility compared with 16% of births to mothers with no education (Figure 9.5). Figure 9.3 Trends in place of birth Figure 9.4 Health facility births by region Figure 9.5 Health facility births by education 5 5 10 26 95 94 90 73 2000 EDHS 2005 EDHS 2011 EDHS 2016 EDHS Percentage of live births in the 5 years before the survey Delivered in health facility Delivered at home 15 18 19 26 26 27 45 50 56 57 97 Affar Somali Oromiya Benishangul-Gumuz SNNPR Amhara Gambela Harari Dire Dawa Tigray Addis Ababa Percentage of live births in the 5 years before the survey that were delivered in a health facility 16 37 77 92 No education Primary Secondary More than secondary Percentage of live births in the 5 years before the survey that were delivered in a health facility 138 • Maternal Health Care 9.4.2 Skilled Assistance during Delivery Skilled assistance during delivery Births delivered with the assistance of doctors, nurse/midwives, health officers, and health extension workers. Sample: All live births in the 5 years before the survey In the 5 years before the survey, 28% of births were delivered by a skilled provider (Table 9.9). The majority of births are attended by traditional birth attendant (42%), nurses or midwives (20%) followed by doctors (6%), health extension workers (2%), and health officers (0.4%) (Figure 9.6). Trends: Skilled assistance during deliveries in Ethiopia has been increasing during the last 16 years. The proportion of births in health facilities assisted by a skilled provider increased from 6% in 2000 to 28% in 2016. Patterns by background characteristics  Fifty-eight percent of births to mothers who attended four or more ANC visits were delivered by a skilled attendant compared to 10% of births to mothers with no ANC visits.  Births to urban women (80%) are more likely to have skilled attendance compared with women in rural areas (21%).  There are large differences by regions in the proportion of births assisted by skilled providers; these range from 97% in Addis Ababa to only 16% in Affar.  Births in the highest wealth quintile are almost six times more likely than those in lowest quintile to be assisted by skilled providers (70% versus 11%) (Figure 9.7). 9.4.3 Delivery by Caesarean Section Access to caesarean sections can reduce maternal and neonatal mortality and complications such as obstetric fistula. However, use of caesarean section without medical need can put women at risk of short-term and long-term health problems. The WHO advises that caesarean sections be done when medically necessary, but does not recommend a specific rate for countries to achieve at the population level. The 2016 EDHS found that 2% of live births in the 5 years before the survey were delivered by caesarean section (C-section). One percent of the C-sections were decided after the onset of labour pains, compared to the less than 1% that were decided before onset of labour pains (Table 9.10). Trends: Since 2000, the rates of C-sections have not changed. One percent of births occurred with C- section in 2000 compared with 2% in 2011 and in 2016. Figure 9.6 Assistance during delivery Figure 9.7 Skilled assistance at delivery by household wealth Traditional birth attendant 42% No one 15% Relative/ friend 14% Nurse/ Midwife 20% Doctor 6% Health extension worker 2% Health officer 0.4% Other 1% Percent distribution of births in the 5 years before the survey 11 21 24 29 70 Lowest Second Middle Fourth Highest Percentage of live births in the 5 years before the survey assisted by a skilled provider* WealthiestPoorest * Skilled provider for EDHS 2000, 2005, and 2011 includes doctor, nurse, and midwife. Skilled provider for EDHS 2016 includes doctor, nurse, midwife, health officer, and health extension worker. Maternal Health Care • 139 Patterns by background characteristics  Caesarean section rates are higher among first births (4.3%) than for those of higher orders.  The caesarean section rate in urban areas is more than 10 times (11%) that in rural areas (1%).  More educated women are more likely to undergo caesarean deliveries. The caesarean rate for deliveries for women with more than secondary education is 21%, compared with women with secondary education (6%), primary education (3%), and no education (1%). Among women who had their most recent live birth in a health facility, 79% of those who gave birth by C- section spent three or more days at the facility after delivery compared with 5% of those who had a vaginal birth (Table 9.11). 9.5 POSTNATAL CARE 9.5.1 Postnatal Health Check for Mothers A large proportion of maternal and neonatal deaths occurs during the first 24 hours after delivery. For both the mother and infant, prompt postnatal care is important for treating complications that arise from delivery and providing the mother with important information on caring for herself and her baby. The 2016 EDHS found that among women age 15-49 giving birth in the 2 years before the survey, 17% had a postnatal check during the first 2 days after birth. Four in five women (81%) did not receive a postnatal check (Table 9.12). Patterns by background characteristics  Women who delivered in a health facility were much more likely to receive a postnatal health check within 2 days of delivery than those who delivered elsewhere (42% versus 2%).  Forty-five percent of urban women received a postnatal check-up within 2 days compared to 13% of rural women.  The proportion of women who received postnatal check-ups in the 2 days after delivery varies widely by region, from a low of 9% in Oromiya to a high of 55% in Addis Ababa. Type of Provider The skills of the provider determine the provider’s ability to diagnose problems and recommend appropriate treatment or referral. Fifteen percent of women received a postnatal check from a doctor, nurse, or midwife. Only 1% of women received a check from a health officer, and another 1% from a health extension worker (HEW) (Table 9.13). 140 • Maternal Health Care Among women who had a postnatal check during the first 2 days after birth, 25% were informed about danger signs of maternal health after delivery (table not shown). Eighty percent were informed about heavy vaginal bleeding, 57% about fever, 30% about smelly vaginal bleeding, and 9% about depression (Figure 9.8). 9.5.2 Postnatal Health Check for Newborns The first 48 hours of life is a critical phase in the lives of newborn babies and a period in which many neonatal deaths occur. Lack of postnatal health checks during this period can delay the identification of newborn complications and the initiation of appropriate care and treatment. Table 9.14 shows that only 13% of newborns had a postnatal check within the first 2 days after birth, while 86% received no postnatal check-up. Patterns by background characteristics  Newborns born to urban women are more likely than those born to rural women to receive a check-up within the first 2 days after birth (37% and 10%).  The percentage of newborn check-ups within the first 2 days increases with education and wealth quintile: 7% of babies born to women with no education received a postnatal check-up, compared with 52% of babies born to women with more than secondary education. Type of Provider Content Twelve percent of newborns received a postnatal check-up within 2 days after birth from either a doctor, nurse, or midwife, while less than 1% received a check-up from a health officer, 1% from a HEW, and less than 1% from traditional birth attendant (Table 9.15). Patterns by background characteristics  Newborns delivered in a health facility were much more likely to receive a postnatal health check from a skilled provider within 2 days of birth than those delivered elsewhere (34% versus 1%).  Newborns born to women who reside in urban areas (37%) are more likely to receive a postnatal check from a skilled provider within the first 2 days after birth compared with newborns born to women from rural areas (10%).  Fifty-two percent of babies born to mothers with more than secondary education received postnatal check from a skilled provider within 2 days compared with 7% of babies born to mothers with no education. Other Components of Newborn Postnatal Care The survey also collected data on other components of postnatal care such as whether selected functions were performed within 2 days after birth, and whether the mother was informed of dangers signs in newborns. Among last births in the 2 years before the survey, 27% of newborns had at least two signal functions performed within 2 days after birth (Table 9.16). Among recent live births in the 2 years before the survey, one in three women (34%) were informed about danger signs in newborns (table not shown). Figure 9.8 Components of information about maternal danger signs after delivery 5 9 30 57 80 Other Depression Smelly vaginal bleeding Fever Heavy vaginal bleeding Among most recent live birth in the 2 years preceding the survey, the percentage of women who were informed about selected maternal danger signs after delivery Maternal Health Care • 141 Additional data on important newborn care practice such as Vitamin K injection and tetracycline (TTC) eye ointment were also collected. Among most recent live births in the 2 years before the survey delivered in a health facility, 41% of newborn received a Vitamin K injection, and 34% of newborns had TTC ointment applied to their eyes. For detailed information on Vitamin K injection and TTC eye ointment application, see Table 9.17. One important newborn care practice is care of the umbilical cord. Table 9.18 shows that 15% of babies had some material placed on their umbilical stump. Among births who had something applied on stump, the materials applied included any type of oil (68%), ointment (19%), unknown material (11%), ash (2%), and dung (1%). For detailed information on care of the umbilical cord, see Table 9.18. 9.6 OBSTETRIC FISTULA Obstetric fistula is a hole between the vagina and rectum or bladder that causes urinary or faecal incontinence. Fistula typically results from problems during labour, surgical error, or trauma. In Ethiopia, only 4 in 10 women age 15-49 (39%) have heard of obstetric fistula. Less than one percent of women report that they have experienced obstetric fistula (Table 9.19). 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 Many factors can prevent women from obtaining medical advice or treatment for themselves when they are sick. Information on such factors is particularly important in understanding and addressing the barriers that women face in seeking care during pregnancy and delivery. In Ethiopia, more than 2 in 3 women (70%) report having at least one of the specified problems in accessing health care. Among these problems, getting money for advice or treatment was the leading issue (55%), followed by the distance to a health facility (50%), not wanting to go alone (42%), and getting permission to go for treatment (32%) (Table 9.20). LIST OF TABLES For more 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 Signs of pregnancy complications  Table 9.5 Birth preparedness plan  Table 9.6 Tetanus toxoid injections  Table 9.7 Tetanus vaccination card  Table 9.8 Place of delivery  Table 9.9 Assistance during delivery  Table 9.10 Caesarean section  Table 9.11 Duration of stay in health facility after birth  Table 9.12 Timing of first postnatal check-up for the mother 142 • Maternal Health Care  Table 9.13 Type of provider for the first postnatal check for the mother  Table 9.14 Timing of first postnatal check for the newborn  Table 9.15 Type of provider for the first postnatal check for the newborn  Table 9.16 Content of postnatal care for newborns  Table 9.17 Newborn care  Table 9.18 Care of umbilical cord  Table 9.19 Obstetrical fistula  Table 9.20 Problems in accessing health care Table 9.1 Antenatal care Percent distribution of women age 15-49 who had a live birth in the 5 years before the survey by antenatal care (ANC) provider during pregnancy for the most recent birth and percentage receiving antenatal care from a skilled provider for the most recent birth, according to background characteristics, Ethiopia DHS 2016 Antenatal care provider No ANC Total Percentage receiving antenatal care from a skilled provider1 Number of women Background characteristic Doctor Nurse/ midwife Health officer Health extension worker Traditional birth attendant Other Mother’s age at birth <20 4.3 47.0 0.5 14.9 0.4 0.0 32.8 100.0 66.8 835 20-34 6.2 42.8 1.8 13.3 0.3 0.2 35.4 100.0 64.0 5,428 35-49 4.8 35.7 0.4 11.9 0.1 0.2 47.0 100.0 52.8 1,326 Birth order 1 10.1 54.9 1.4 11.4 0.4 0.2 21.6 100.0 77.8 1,445 2-3 7.2 44.3 1.8 13.6 0.2 0.2 32.7 100.0 66.9 2,288 4-5 3.9 39.7 1.4 13.2 0.4 0.2 41.2 100.0 58.2 1,751 6+ 2.6 32.6 1.0 14.2 0.2 0.1 49.3 100.0 50.4 2,105 Residence Urban 24.2 64.0 1.1 0.8 0.2 0.0 9.7 100.0 90.1 969 Rural 3.0 38.8 1.4 15.1 0.3 0.2 41.2 100.0 58.3 6,621 Region Tigray 10.6 71.4 1.3 6.7 0.0 0.4 9.6 100.0 90.0 537 Affar 12.0 38.8 0.0 0.5 0.0 0.3 48.4 100.0 51.3 71 Amhara 6.9 48.4 0.7 11.1 0.1 0.4 32.4 100.0 67.1 1,632 Oromiya 3.1 32.4 1.4 13.8 0.5 0.1 48.6 100.0 50.7 3,129 Somali 7.2 33.1 0.9 2.5 0.4 0.0 56.0 100.0 43.6 269 Benishangul-Gumuz 3.8 44.5 2.6 17.9 0.3 0.2 30.8 100.0 68.7 81 SNNPR 2.1 44.5 2.0 20.7 0.1 0.2 30.4 100.0 69.3 1,601 Gambela 14.1 54.2 0.9 3.1 0.4 0.0 27.3 100.0 72.3 21 Harari 18.4 53.0 0.0 4.5 0.4 0.0 23.7 100.0 75.9 17 Addis Ababa 46.1 49.0 1.3 0.3 0.0 0.0 3.2 100.0 96.8 198 Dire Dawa 21.7 58.9 2.3 4.5 0.0 0.0 12.6 100.0 87.4 33 Education No education 2.8 35.5 1.2 13.8 0.3 0.2 46.1 100.0 53.3 4,791 Primary 6.7 49.9 1.7 14.7 0.2 0.2 26.6 100.0 73.0 2,150 Secondary 17.3 67.6 2.5 4.9 0.1 0.0 7.6 100.0 92.3 420 More than secondary 37.8 57.3 0.4 2.6 0.8 0.0 1.1 100.0 98.0 230 Wealth quintile Lowest 2.1 30.0 0.4 15.0 0.5 0.1 51.9 100.0 47.5 1,651 Second 3.5 38.1 1.3 12.9 0.4 0.4 43.4 100.0 55.8 1,654 Middle 2.0 42.0 1.7 16.8 0.0 0.1 37.3 100.0 62.6 1,588 Fourth 4.8 45.4 2.7 14.2 0.3 0.4 32.2 100.0 67.1 1,427 Highest 19.2 58.9 1.0 5.7 0.2 0.1 15.0 100.0 84.8 1,269 Total 5.7 42.0 1.4 13.2 0.3 0.2 37.1 100.0 62.4 7,590 Note: If more than one source of ANC was mentioned, only the provider with the highest qualifications is considered in this tabulation. 1 Skilled provider includes doctor, nurse, midwife, health officer, and health extension worker (HEW). Maternal Health Care • 143 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 before 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, Ethiopia DHS 2016 Number of ANC visits and timing of first visit Residence Total Urban Rural Number of ANC visits None 9.7 41.2 37.1 1 3.2 4.6 4.4 2-3 23.9 26.8 26.4 4+ 62.7 27.3 31.8 Don’t know/missing 0.6 0.1 0.2 Total 100.0 100.0 100.0 Number of months pregnant at time of first ANC visit No antenatal care 9.7 41.2 37.1 <4 44.1 17.0 20.4 4-5 35.1 24.6 26.0 6-7 9.9 14.2 13.6 8+ 1.1 2.6 2.4 Don’t know/missing 0.1 0.5 0.4 Total 100.0 100.0 100.0 Number of women 969 6,621 7,590 Median months pregnant at first visit (for those with ANC) 4.0 4.9 4.7 Number of women with ANC 875 3,896 4,771 144 • Maternal Health Care Table 9.3 Components of antenatal care Among women age 15-49 with a live birth in the 5 years before the survey, percentage who took iron tablets 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 before the survey, percentage receiving specific antenatal services, according to background characteristics, Ethiopia DHS 2016 Among women with a live birth in the past 5 years, percentage who during the pregnancy for their most recent live birth: Number of women with a live birth in the past 5 years 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 Took intestinal parasite drugs Blood pressure measured Urine sample taken Blood sample taken Nutritional Counselling Mother’s age at birth <20 43.6 5.8 835 68.1 67.5 67.9 59.3 561 20-34 43.5 6.1 5,428 75.8 66.4 73.6 67.0 3,508 35-49 35.3 4.0 1,326 78.7 63.5 71.1 68.2 702 Birth order 1 53.1 6.2 1,445 77.6 77.7 79.4 67.0 1,134 2-3 45.4 6.7 2,288 77.9 68.2 76.7 67.9 1,541 4-5 38.9 5.5 1,751 70.3 60.5 67.3 65.4 1,030 6+ 33.4 4.4 2,105 73.7 56.2 64.3 64.0 1,067 Residence Urban 60.6 7.7 969 91.3 91.8 94.5 75.4 875 Rural 39.3 5.4 6,621 71.7 60.3 67.6 64.2 3,896 Region Tigray 77.2 8.7 537 89.6 82.3 90.7 82.9 486 Affar 43.4 4.5 71 73.5 71.7 76.2 53.7 37 Amhara 53.4 6.7 1,632 77.3 69.0 80.2 73.5 1,104 Oromiya 29.9 5.3 3,129 69.6 60.5 62.4 58.7 1,607 Somali 27.7 1.4 269 82.0 73.0 74.6 48.0 118 Benishangul-Gumuz 47.9 9.0 81 65.4 63.3 72.9 61.7 56 SNNPR 41.3 5.0 1,601 70.8 56.7 66.0 62.3 1,115 Gambela 41.6 4.7 21 75.9 78.5 82.8 56.9 15 Harari 50.8 3.8 17 90.0 85.9 87.8 74.9 13 Addis Ababa 63.7 5.4 198 97.3 99.3 98.7 83.1 192 Dire Dawa 59.9 11.8 33 88.3 91.3 91.8 72.7 29 Education No education 36.2 4.8 4,791 69.8 57.4 65.4 63.6 2,580 Primary 47.9 7.1 2,150 77.4 71.6 76.9 65.8 1,577 Secondary 64.7 8.2 420 91.0 85.5 88.5 76.8 388 More than secondary 68.9 6.5 230 96.0 93.2 96.5 81.8 227 Wealth quintile Lowest 31.4 3.9 1,651 68.5 53.3 60.0 53.7 794 Second 41.3 4.5 1,654 68.1 59.6 68.4 62.3 935 Middle 39.2 6.3 1,588 71.6 59.1 66.9 65.3 996 Fourth 45.4 7.0 1,427 74.7 67.6 71.5 69.3 967 Highest 56.6 7.3 1,269 90.3 86.3 91.5 77.1 1,079 Total 42.1 5.7 7,590 75.3 66.1 72.5 66.3 4,771 Maternal Health Care • 145 Table 9.4 Signs of pregnancy complications Among women who received antenatal care for their most recent live birth in the past 5 years, percentages who were informed of signs of pregnancy complications or danger signs at an antenatal care visit, and among women who were informed of signs of pregnancy complications or danger signs, percentage who were informed of specific pregnancy complications, according to background characteristics, Ethiopia DHS 2016 Percentage who were informed of pregnancy compli- cations or danger signs of pregnancy Number of women with a live birth in the past 5 years with ANC for their most recent birth Among women who received antenatal care for their most recent live birth in the past 5 years, percentage who were informed of specific pregnancy complications Number of women were informed of specific pregnancy compli- cations at an ante- natal care visit for their most recent birth Background characteristic Vaginal bleeding Vaginal gush of fluid Severe headache Blurred vision Fever Abdominal pain Convulsion Other Mother’s age at birth <20 37.7 561 48.0 27.7 50.6 19.2 43.2 27.8 9.9 2.8 212 20-34 45.9 3,508 48.9 26.4 50.2 18.3 36.5 29.1 8.2 1.6 1,611 35-49 45.9 702 56.1 32.8 43.8 17.3 30.0 29.4 8.3 0.0 323 Birth order 1 45.4 1,134 51.4 30.8 53.0 19.9 39.2 29.0 9.2 2.2 515 2-3 46.4 1,541 47.8 22.5 49.3 18.0 41.7 31.4 9.2 2.3 714 4-5 43.8 1,030 49.4 27.7 47.5 15.7 28.6 25.7 6.8 0.8 451 6+ 43.6 1,067 52.1 31.2 46.8 19.2 31.6 28.6 7.7 0.0 465 Residence Urban 60.2 875 55.7 26.6 54.2 21.1 39.0 28.9 9.9 2.8 527 Rural 41.5 3,896 48.0 27.8 47.7 17.3 35.2 29.1 7.9 1.0 1,619 Region Tigray 54.1 486 51.6 20.8 47.1 23.0 30.6 25.7 13.7 0.3 263 Affar 33.5 37 34.9 13.9 51.2 10.2 36.8 24.8 4.8 1.0 12 Amhara 47.1 1,104 59.6 25.4 48.1 10.0 34.3 17.8 4.1 3.1 520 Oromiya 35.0 1,607 37.7 33.0 47.7 17.6 39.9 29.5 8.1 0.0 562 Somali 30.7 118 42.2 21.0 60.5 23.3 33.8 33.5 20.7 0.0 36 Benishangul-Gumuz 50.6 56 49.3 13.0 54.9 21.9 35.9 33.7 12.7 0.0 28 SNNPR 49.9 1,115 49.3 27.5 46.8 22.1 34.5 38.3 9.2 2.4 556 Gambela 38.1 15 49.7 31.7 58.1 32.2 36.9 26.8 14.2 0.6 6 Harari 52.9 13 33.1 26.6 56.2 21.1 30.2 26.5 1.8 1.1 7 Addis Ababa 74.9 192 66.9 32.3 67.1 25.2 45.4 36.8 8.9 0.7 144 Dire Dawa 34.3 29 36.9 10.9 65.6 7.1 40.4 23.1 3.0 0.0 10 Education No education 40.0 2,580 49.5 26.9 45.6 17.0 33.4 26.9 5.4 0.7 1,032 Primary 45.6 1,577 48.2 27.0 53.2 16.9 38.9 30.2 8.9 1.3 719 Secondary 63.1 388 53.3 31.5 47.2 19.2 37.7 35.1 17.1 3.6 245 More than secondary 66.3 227 55.1 27.4 59.0 31.5 39.8 28.1 12.2 3.5 150 Wealth quintile Lowest 33.1 794 51.7 29.4 45.3 18.3 34.7 22.6 6.0 0.3 263 Second 38.5 935 41.7 25.3 45.1 19.1 38.2 28.3 7.9 1.4 360 Middle 40.1 996 50.8 25.2 51.3 16.1 33.9 26.3 7.3 1.7 400 Fourth 45.7 967 49.6 28.6 47.2 18.3 32.7 34.7 9.5 0.9 442 Highest 63.1 1,079 53.2 28.5 53.1 18.9 39.3 29.8 9.4 2.2 680 Total 45.0 4,771 49.9 27.5 49.3 18.2 36.2 29.0 8.4 1.5 2,145 146 • Maternal Health Care Table 9.5 Birth preparedness plan Among women who received antenatal care for their most recent live birth in the past 5 years, percentages who were informed about a birth preparedness plan at an antenatal care visit, and among women who were informed about a birth preparedness plan at an antenatal care visit, percentage who were informed of specific preparation plans, according to background characteristics, Ethiopia DHS 2016 Percentage who were informed about a birth prepared- ness plan Number of women with a live birth in the past 5 years with ANC for their most recent birth Among women who received antenatal care for their most recent live birth in the past 5 years, percentage who were informed of: Number of women informed about birth prepared- ness plan at an antenatal care visit for their most recent birth Background characteristic Place of birth Supplies needed for birth Emergency transpor- tation Money/ emergency fund People to support during/ after birth Potential blood donors Other Mother’s age at birth <20 50.5 561 87.4 40.6 16.6 18.9 3.8 1.5 0.0 283 20-34 55.9 3,508 86.8 40.0 19.8 19.0 5.3 2.7 0.2 1,962 35-49 60.7 702 87.6 35.3 21.4 18.1 5.5 2.7 0.4 426 Birth order 1 57.7 1,134 86.1 44.6 22.4 18.0 5.1 2.6 0.4 654 2-3 56.4 1,541 87.8 38.2 19.5 20.5 5.8 3.0 0.2 869 4-5 53.0 1,030 85.2 36.7 16.7 15.6 3.5 1.8 0.0 546 6+ 56.5 1,067 88.3 37.5 19.9 20.5 5.8 2.6 0.3 603 Residence Urban 59.1 875 82.5 51.2 29.5 24.2 8.4 5.8 0.5 517 Rural 55.3 3,896 88.1 36.5 17.4 17.6 4.4 1.8 0.2 2,155 Region Tigray 77.2 486 89.8 40.1 27.5 10.8 4.3 1.9 0.0 375 Affar 21.9 37 78.8 37.7 11.8 7.8 4.5 0.0 0.0 8 Amhara 65.8 1,104 95.3 19.5 9.9 4.4 2.3 1.3 0.0 727 Oromiya 46.3 1,607 78.9 48.9 24.9 26.9 3.9 3.0 0.4 744 Somali 32.8 118 92.9 28.5 12.7 15.7 9.4 1.3 0.0 39 Benishangul-Gumuz 48.9 56 90.1 21.4 17.8 17.1 12.1 0.0 0.0 27 SNNPR 54.2 1,115 89.3 46.1 17.3 26.7 7.8 3.6 0.6 604 Gambela 42.9 15 91.7 48.9 29.4 17.8 2.7 2.9 0.0 6 Harari 60.8 13 78.8 16.1 27.5 17.5 9.8 5.3 0.0 8 Addis Ababa 62.9 192 64.5 72.5 36.8 43.3 17.6 5.8 0.0 121 Dire Dawa 45.6 29 87.9 32.6 13.9 27.2 0.9 2.4 0.0 13 Education No education 54.1 2,580 88.6 33.0 15.8 16.6 4.1 2.1 0.1 1,395 Primary 55.9 1,577 86.4 41.6 19.6 20.4 5.6 1.5 0.0 882 Secondary 62.5 388 81.9 58.5 32.6 17.4 7.0 2.7 2.0 242 More than secondary 67.5 227 84.4 53.8 35.4 32.6 9.4 12.1 0.0 153 Wealth quintile Lowest 49.0 794 87.9 36.7 19.4 14.8 2.2 0.0 0.0 389 Second 49.9 935 90.8 34.0 13.6 13.0 4.2 2.7 0.4 467 Middle 56.7 996 86.7 35.9 15.7 21.2 4.2 1.8 0.3 565 Fourth 58.8 967 89.8 34.9 18.4 16.8 5.8 2.2 0.0 568 Highest 63.3 1,079 81.8 51.0 28.5 25.0 7.8 4.9 0.4 683 Total 56.0 4,771 87.0 39.3 19.7 18.9 5.2 2.6 0.2 2,672 Maternal Health Care • 147 Table 9.6 Tetanus toxoid injections Among mothers age 15-49 with a live birth in the 5 years before the survey, percentage receiving two or more tetanus toxoid (TT) injections during the pregnancy for the most recent live birth and percentage whose most recent live birth was protected against neonatal tetanus, according to background characteristics, Ethiopia DHS 2016 Background characteristic Percentage receiving two or more injections during the pregnancy for the most recent live birth Percentage whose most recent live birth was protected against neonatal tetanus1 Number of mothers Mother’s age at birth <20 40.5 47.3 835 20-34 43.2 51.2 5,428 35-49 32.5 40.9 1,326 Birth order 1 48.4 56.9 1,445 2-3 42.8 52.0 2,288 4-5 38.3 45.9 1,751 6+ 36.4 42.9 2,105 Residence Urban 56.9 72.4 969 Rural 38.7 45.6 6,621 Region Tigray 41.2 62.0 537 Affar 28.1 30.2 71 Amhara 35.7 44.8 1,632 Oromiya 41.4 46.7 3,129 Somali 32.2 38.4 269 Benishangul-Gumuz 44.4 53.4 81 SNNPR 44.3 50.9 1,601 Gambela 49.2 55.4 21 Harari 63.9 70.1 17 Addis Ababa 61.7 81.5 198 Dire Dawa 63.3 71.5 33 Education No education 34.9 41.3 4,791 Primary 49.1 57.4 2,150 Secondary 59.5 76.0 420 More than secondary 61.6 82.5 230 Wealth quintile Lowest 30.6 35.8 1,651 Second 37.3 43.8 1,654 Middle 38.8 46.6 1,588 Fourth 47.2 54.5 1,427 Highest 55.7 69.8 1,269 Total 41.1 49.0 7,590 1 Includes mothers with two injections during the pregnancy for her most recent live birth, or two or more injections (the last within 3 years of the most recent live birth), or three or more injections (the last within 5 years of the most recent live birth), or four or more injections (the last within 10 years of the most recent live birth), or five or more injections at any time prior to the most recent live birth. 148 • Maternal Health Care Table 9.7 Tetanus vaccination card Among women age 15-49 with a live birth in the 5 years before the survey who received tetanus toxoid (TT) injection, percentage who received a tetanus vaccination card during the pregnancy for the most recent live birth, according to background characteristics, Ethiopia DHS 2016 Percentage with TT vaccination card Total Number of mothers who had TT injection Background characteristic TT card seen TT card not seen Never had a TT card Mother’s age at birth <20 11.9 75.7 12.4 100.0 454 20-34 10.8 74.0 15.2 100.0 3,071 35-49 12.5 74.6 12.9 100.0 562 Birth order 1 13.6 73.0 13.4 100.0 909 2-3 12.3 74.0 13.7 100.0 1,354 4-5 8.9 74.2 16.9 100.0 863 6+ 9.2 75.8 15.0 100.0 961 Residence Urban 16.9 73.1 9.9 100.0 723 Rural 9.9 74.5 15.6 100.0 3,365 Region Tigray 7.1 71.7 21.2 100.0 319 Affar 16.3 61.6 22.2 100.0 27 Amhara 6.8 76.0 17.2 100.0 863 Oromiya 13.6 71.0 15.4 100.0 1,607 Somali 7.9 56.1 36.0 100.0 116 Benishangul-Gumuz 9.5 77.0 13.4 100.0 43 SNNPR 8.7 83.8 7.5 100.0 907 Gambela 4.7 85.3 10.1 100.0 13 Harari 1.4 92.7 5.9 100.0 13 Addis Ababa 36.0 58.6 5.4 100.0 154 Dire Dawa 14.1 82.5 3.4 100.0 26 Education No education 9.9 74.3 15.9 100.0 2,242 Primary 10.1 75.2 14.7 100.0 1,350 Secondary 18.3 71.5 10.3 100.0 316 More than secondary 22.6 71.8 5.7 100.0 179 Wealth quintile Lowest 5.5 76.9 17.6 100.0 690 Second 10.6 74.3 15.2 100.0 817 Middle 8.0 75.4 16.6 100.0 828 Fourth 13.2 72.2 14.6 100.0 851 Highest 16.9 73.2 9.9 100.0 902 Total 11.1 74.3 14.6 100.0 4,087 Maternal Health Care • 149 Table 9.8 Place of delivery Percent distribution of live births in the 5 years before the survey by place of delivery and percentage delivered in a health facility, according to background characteristics, Ethiopia DHS 2016 Health facility Home Other Total Percentage delivered in a health facility Number of births Background characteristic Public sector Private sector NGO Mother’s age at birth <20 30.1 1.0 0.3 66.8 1.7 100.0 31.4 1,301 20-34 24.9 1.2 0.3 72.4 1.2 100.0 26.4 8,090 35-49 20.0 0.9 0.3 77.8 1.0 100.0 21.2 1,632 Birth order 1 44.9 2.5 0.9 50.4 1.3 100.0 48.3 2,070 2-3 27.5 1.3 0.2 69.4 1.5 100.0 29.1 3,366 4-5 17.5 0.6 0.1 80.9 0.9 100.0 18.2 2,609 6+ 14.2 0.5 0.1 84.2 1.1 100.0 14.7 2,978 Antenatal care visits1 None 8.0 0.4 0.0 90.7 0.9 100.0 8.4 2,818 1-3 33.4 0.5 0.4 64.1 1.6 100.0 34.3 2,342 4+ 52.7 3.0 0.6 41.6 2.0 100.0 56.3 2,415 Residence Urban 71.0 6.8 1.4 20.6 0.2 100.0 79.2 1,216 Rural 19.1 0.4 0.1 79.0 1.3 100.0 19.7 9,807 Region Tigray 56.5 0.3 0.1 41.0 2.0 100.0 56.9 716 Affar 12.9 1.1 0.7 85.1 0.2 100.0 14.7 114 Amhara 26.4 0.5 0.2 71.4 1.5 100.0 27.1 2,072 Oromiya 17.8 0.8 0.2 80.5 0.8 100.0 18.8 4,851 Somali 16.1 1.2 0.6 82.0 0.1 100.0 17.9 508 Benishangul-Gumuz 25.4 0.0 0.3 73.3 1.1 100.0 25.7 122 SNNPR 25.0 0.3 0.2 72.5 2.0 100.0 25.5 2,296 Gambela 38.1 1.8 5.0 53.6 1.4 100.0 45.0 27 Harari 41.7 6.9 1.7 49.4 0.3 100.0 50.2 26 Addis Ababa 71.4 22.2 3.0 3.0 0.4 100.0 96.6 244 Dire Dawa 49.8 6.4 0.0 42.1 1.7 100.0 56.2 47 Mother’s education No education 15.5 0.4 0.1 83.0 1.1 100.0 15.9 7,284 Primary 34.9 1.3 0.5 61.7 1.6 100.0 36.8 2,951 Secondary 71.8 4.3 1.3 21.9 0.7 100.0 77.4 514 More than secondary 75.6 13.8 2.0 8.5 0.0 100.0 91.5 274 Wealth quintile Lowest 10.5 0.1 0.1 88.1 1.3 100.0 10.6 2,636 Second 18.6 0.0 0.0 80.2 1.2 100.0 18.6 2,520 Middle 21.7 0.5 0.1 76.1 1.6 100.0 22.2 2,280 Fourth 26.4 0.8 0.1 71.2 1.5 100.0 27.3 1,999 Highest 60.9 6.1 1.6 31.2 0.1 100.0 68.6 1,588 Total 24.8 1.1 0.3 72.6 1.2 100.0 26.2 11,023 Note: Total includes 15 weighted cases with information missing on antenatal care visits. 1 Includes only the most recent birth in the 5 years before the survey. 150 • Maternal Health Care Table 9.9 Assistance during delivery Percent distribution of live births in the 5 years before the survey by person providing assistance during delivery, percentage of birth assisted by a skilled provider, according to background characteristics, Ethiopia DHS 2016 Person providing assistance during delivery Percentage delivered by a skilled provider1 Number of births Background characteristic Doctor Nurse/ midwife Health officer Health extension worker (HEW) Traditional birth attendant Relative/ friends/ neighbors Other No one Total Mother’s age at birth <20 4.8 25.3 0.3 2.4 40.3 14.3 1.1 11.3 100.0 32.8 1,301 20-34 5.8 19.7 0.5 1.8 42.1 14.3 0.9 14.9 100.0 27.8 8,090 35-49 4.6 17.0 0.2 1.3 45.6 12.3 0.9 18.0 100.0 23.1 1,632 Birth order 1 11.8 35.2 0.6 2.1 30.8 12.6 1.0 5.8 100.0 49.8 2,070 2-3 6.9 22.2 0.4 1.5 40.9 13.8 0.4 13.9 100.0 31.0 3,366 4-5 2.3 14.7 0.8 1.3 46.4 15.2 1.0 18.3 100.0 19.0 2,609 6+ 2.2 11.6 0.0 2.4 48.6 14.3 1.4 19.6 100.0 16.2 2,978 Antenatal care visits2 None 1.4 7.2 0.2 0.9 53.9 13.3 1.4 21.7 100.0 9.7 2,818 1-3 5.4 26.8 0.4 3.1 37.5 14.4 1.1 11.3 100.0 35.7 2,342 4+ 13.7 40.8 1.1 2.6 23.0 11.3 0.4 7.0 100.0 58.2 2,415 Place of delivery Health facility 19.6 73.0 1.5 4.7 0.5 0.2 0.3 0.2 100.0 98.9 2,892 Public facility 17.0 75.5 1.6 5.0 0.4 0.2 0.2 0.2 100.0 99.1 2,734 Private facility 64.9 29.8 0.0 0.0 2.5 0.0 2.8 0.0 100.0 94.7 126 NGO 67.9 31.4 0.0 0.0 0.2 0.0 0.5 0.0 100.0 99.3 31 Elsewhere 0.4 1.1 0.0 0.8 57.3 19.0 1.2 20.2 100.0 2.4 8,131 Residence Urban 30.0 48.7 0.7 0.6 12.1 3.8 0.0 4.0 100.0 80.1 1,216 Rural 2.4 16.4 0.4 2.0 46.1 15.3 1.0 16.3 100.0 21.2 9,807 Region Tigray 8.5 49.6 0.1 1.0 23.2 13.1 0.6 3.8 100.0 59.3 716 Affar 5.8 10.3 0.2 0.0 83.5 0.1 0.0 0.0 100.0 16.4 114 Amhara 6.7 19.6 0.2 1.2 55.8 11.7 0.4 4.4 100.0 27.7 2,072 Oromiya 2.4 15.6 0.3 1.3 45.1 14.1 1.4 19.8 100.0 19.7 4,851 Somali 5.0 14.4 0.1 0.5 75.0 2.8 0.1 2.2 100.0 20.0 508 Benishangul-Gumuz 4.1 19.7 0.3 4.5 41.8 6.7 0.1 22.7 100.0 28.6 122 SNNPR 3.6 20.0 1.0 4.0 25.9 21.9 1.0 22.6 100.0 28.6 2,296 Gambela 11.4 34.6 0.1 0.7 30.4 10.1 0.3 12.4 100.0 46.9 27 Harari 17.3 33.2 0.6 0.2 45.5 0.5 0.0 2.8 100.0 51.2 26 Addis Ababa 61.1 35.1 0.0 0.6 2.3 0.5 0.0 0.4 100.0 96.8 244 Dire Dawa 23.0 33.3 0.2 0.1 32.8 0.2 0.0 10.4 100.0 56.7 47 Mother’s education No education 2.1 13.2 0.3 1.6 49.1 14.5 1.1 18.1 100.0 17.2 7,284 Primary 7.4 28.1 0.7 2.4 34.2 15.7 0.7 10.7 100.0 38.6 2,951 Secondary 23.1 51.7 1.1 2.5 14.8 3.9 0.2 2.7 100.0 78.4 514 More than secondary 39.5 52.7 0.9 0.1 2.7 3.5 0.6 0.1 100.0 93.2 274 Wealth quintile Lowest 1.1 9.1 0.0 0.8 57.5 15.5 1.6 14.3 100.0 11.0 2,636 Second 2.2 16.8 0.0 1.8 47.0 12.1 0.6 19.5 100.0 20.8 2,520 Middle 2.7 17.4 1.0 3.1 42.8 15.2 0.7 17.1 100.0 24.2 2,280 Fourth 4.1 22.3 0.5 1.6 36.2 19.1 1.3 14.9 100.0 28.5 1,999 Highest 23.6 44.0 0.8 1.9 17.2 6.6 0.3 5.7 100.0 70.3 1,588 Total 5.5 20.0 0.4 1.8 42.4 14.0 0.9 15.0 100.0 27.7 11,023 Note: If the respondent mentioned more than one person attending during delivery, only the most qualified person is considered in this tabulation. Total includes 15 weighted cases with information missing on antenatal care visits. 1 Skilled provider includes doctor, nurse, midwife, health officer, and health extension worker (HEW). 2 Includes only the most recent birth in the 5 years before the survey. Maternal Health Care • 151 Table 9.10 Caesarean section Percentage of live births in the 5 years before the survey delivered by caesarian section (C- section), percentage delivered by C-section that was planned before the onset of labor pains, and percentage delivered by C-section that was decided after the onset of labor pains, according to background characteristics, Ethiopia DHS 2016 Background characteristic Percentage delivered by C-section Timing of decision to conduct C-section Number of births Decided before onset of labor pains Decided after onset of labor pains Mother’s age at birth <20 1.1 0.3 0.8 1,301 20-34 2.1 0.8 1.3 8,090 35-49 1.9 0.9 1.0 1,632 Birth order 1 4.3 1.5 2.8 2,070 2-3 2.9 1.2 1.7 3,366 4-5 0.6 0.3 0.3 2,609 6+ 0.4 0.1 0.4 2,978 Antenatal care visits1 None 0.5 0.2 0.3 2,818 1-3 1.3 0.2 1.1 2,342 4+ 5.7 2.3 3.4 2,415 Place of delivery Health facility 7.4 2.7 4.6 2,892 Public facility 6.5 2.2 4.4 2,734 Private facility 23.0 14.6 8.4 126 NGO 16.2 3.8 12.4 31 Residence Urban 10.6 5.5 5.1 1,216 Rural 0.9 0.1 0.7 9,807 Region Tigray 2.0 0.5 1.5 716 Affar 0.7 0.1 0.6 114 Amhara 2.3 1.0 1.2 2,072 Oromiya 0.9 0.3 0.6 4,851 Somali 0.4 0.2 0.3 508 Benishangul-Gumuz 1.0 0.2 0.7 122 SNNPR 1.9 0.1 1.9 2,296 Gambela 1.3 0.4 1.0 27 Harari 9.0 5.0 4.0 26 Addis Ababa 21.4 13.5 7.9 244 Dire Dawa 5.3 1.9 3.3 47 Mother’s education No education 0.7 0.2 0.5 7,284 Primary 2.5 0.9 1.7 2,951 Secondary 6.3 2.8 3.5 514 More than secondary 20.8 10.0 10.8 274 Wealth quintile Lowest 0.6 0.3 0.3 2,636 Second 1.0 0.1 0.9 2,520 Middle 1.0 0.2 0.8 2,280 Fourth 1.0 0.0 1.0 1,999 Highest 8.1 3.9 4.2 1,588 Total 1.9 0.7 1.2 11,023 Note: The question on C-section is asked only of women who delivered in a health facility. In this table, it is assumed that women who did not give birth in health facility did not receive a C-section. Total includes 15 weighted cases with information missing on antenatal care visits. 1 Includes only the most recent birth in the 5 years before the survey. 152 • Maternal Health Care Table 9.11 Duration of stay in health facility after birth Among women with a birth in the 5 years before the survey who delivered their most recent live birth in a health facility, percent distribution by duration of stay in the health facility following their most recent live birth, according to type of delivery, Ethiopia DHS 2016 Type of delivery <6 hours 6-11 hours 12-23 hours 1-2 days 3+ days Don’t know Total Number of women Vaginal birth 26.7 26.3 15.6 26.7 4.6 0.1 100.0 2,225 Caesarean section 4.8 2.3 3.8 10.1 79.0 0.0 100.0 183 Table 9.12 Timing of first postnatal check-up for the mother Among women age 15-49 giving birth in the 2 years before the survey, percent distribution of the mother’s first postnatal check for the most recent live birth by time after delivery, and percentage of women with a live birth in the 2 years before the survey who received a postnatal check during the first 2 days after giving birth, according to background characteristics, Ethiopia DHS 2016 Time after delivery of mother’s first postnatal check1 No postnatal check-up2 Total Percentage of women with a postnatal check during 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 10.6 1.8 0.5 1.2 0.4 0.3 85.2 100.0 13.0 508 20-34 13.6 3.4 0.8 0.8 1.9 0.2 79.3 100.0 17.8 3,126 35-49 9.4 2.8 0.8 0.3 1.2 0.4 85.1 100.0 13.1 674 Birth order 1 15.6 4.4 0.6 1.9 1.6 0.2 75.6 100.0 20.6 885 2-3 15.3 4.0 0.5 0.6 2.6 0.2 76.8 100.0 19.8 1,320 4-5 11.4 2.4 1.9 0.7 0.7 0.0 82.9 100.0 15.6 939 6+ 8.2 1.9 0.3 0.1 1.2 0.4 87.9 100.0 10.4 1,165 Place of delivery Health facility 32.9 7.8 1.5 1.5 1.6 0.4 54.3 100.0 42.2 1,560 Public facility 32.8 7.8 1.6 1.4 1.6 0.5 54.3 100.0 42.2 1,497 Private facility 37.2 7.4 0.0 4.5 2.0 0.0 48.9 100.0 44.6 48 NGO (27.5) (4.1) (0.3) (0.0) (0.0) (0.0) (68.2) (100.0) (31.8) 15 Elsewhere 1.1 0.5 0.3 0.3 1.6 0.1 96.1 100.0 1.9 2,748 Residence Urban 33.1 11.2 0.9 2.6 1.3 0.3 50.6 100.0 45.2 520 Rural 9.8 2.1 0.7 0.5 1.6 0.2 85.1 100.0 12.6 3,788 Region Tigray 33.4 9.0 3.0 1.0 2.2 0.9 50.5 100.0 45.4 314 Affar 10.2 1.1 0.2 0.9 0.9 0.0 86.6 100.0 11.6 43 Amhara 14.5 2.9 0.9 2.2 2.0 0.5 76.9 100.0 18.4 789 Oromiya 6.7 1.6 0.7 0.0 1.3 0.0 89.7 100.0 9.0 1,915 Somali 10.3 1.1 0.5 0.3 0.3 0.1 87.4 100.0 11.9 178 Benishangul-Gumuz 9.9 3.1 1.5 1.0 0.3 0.5 83.7 100.0 14.5 45 SNNPR 13.5 3.4 0.0 0.6 1.8 0.1 80.6 100.0 16.9 876 Gambela 12.3 2.9 1.7 0.5 0.0 0.5 82.2 100.0 16.9 10 Harari 29.3 7.6 0.5 0.0 1.2 0.4 60.9 100.0 37.4 10 Addis Ababa 37.5 17.4 0.5 3.7 4.5 1.1 35.3 100.0 55.4 110 Dire Dawa 20.8 6.6 0.4 2.4 0.4 0.0 69.5 100.0 27.8 18 Education No education 8.2 1.6 0.7 0.6 1.5 0.2 87.2 100.0 10.6 2,606 Primary 15.7 4.2 0.8 0.5 1.7 0.3 76.8 100.0 20.7 1,319 Secondary 27.9 8.0 1.2 1.1 2.1 0.0 59.6 100.0 37.1 262 More than secondary 39.2 14.7 0.6 6.7 2.0 1.0 35.9 100.0 54.4 121 Wealth quintile Lowest 5.4 1.5 0.4 0.1 0.9 0.1 91.7 100.0 7.3 1,011 Second 9.5 1.2 0.2 0.7 1.7 0.2 86.6 100.0 10.8 943 Middle 10.0 2.7 1.7 0.4 1.7 0.2 83.4 100.0 14.3 890 Fourth 11.3 2.9 1.1 0.9 2.4 0.5 80.9 100.0 15.3 796 Highest 32.9 9.4 0.7 2.1 1.5 0.2 53.3 100.0 43.0 667 Total 12.6 3.2 0.8 0.7 1.6 0.2 80.9 100.0 16.5 4,308 Note: Figures in parentheses are based on 25-49 unweighted cases. 1 Includes women who received a check-up from a doctor, nurse, midwife, health officer, health extension worker (HEW), or traditional birth attendant. 2 Includes women who received a check-up after 41 days. Maternal Health Care • 153 Table 9.13 Type of provider for the first postnatal check for the mother Among women age 15-49 giving birth in the 2 years before the survey, percent distribution by type of provider for the mother’s first postnatal health check during the 2 days after the last live birth, according to background characteristics, Ethiopia DHS 2016 Type of health provider for mother’s first postnatal check-up No postnatal check during the first 2 days after the birth Total Number of women Background characteristic Doctor/nurse/ midwife Health officer Health extension worker Mother’s age at birth <20 12.2 0.5 0.3 87.0 100.0 508 20-34 16.4 0.6 0.9 82.2 100.0 3,126 35-49 13.1 0.0 0.0 86.9 100.0 674 Birth order 1 19.6 0.8 0.2 79.4 100.0 885 2-3 18.6 0.5 0.7 80.2 100.0 1,320 4-5 14.2 0.6 0.8 84.4 100.0 939 6+ 9.5 0.0 0.9 89.6 100.0 1,165 Place of delivery Health facility 40.2 1.2 0.9 57.8 100.0 1,560 Public facility 40.1 1.2 0.9 57.8 100.0 1,497 Private facility 44.6 0.0 0.0 55.4 100.0 48 NGO (31.8) (0.0) (0.0) (68.2) (100.0) 15 Elsewhere 1.3 0.1 0.5 98.1 100.0 2,748 Residence Urban 43.8 1.4 0.0 54.8 100.0 520 Rural 11.5 0.3 0.8 87.4 100.0 3,788 Region Tigray 43.6 0.7 1.1 54.6 100.0 314 Affar 11.2 0.0 0.4 88.4 100.0 43 Amhara 17.9 0.0 0.4 81.6 100.0 789 Oromiya 7.8 0.7 0.4 91.0 100.0 1,915 Somali 11.7 0.2 0.0 88.1 100.0 178 Benishangul-Gumuz 13.1 0.0 1.4 85.5 100.0 45 SNNPR 15.0 0.4 1.5 83.1 100.0 876 Gambela 16.3 0.6 0.0 83.1 100.0 10 Harari 37.0 0.0 0.4 62.6 100.0 10 Addis Ababa 55.4 0.0 0.0 44.6 100.0 110 Dire Dawa 27.2 0.6 0.0 72.2 100.0 18 Education No education 9.5 0.4 0.6 89.4 100.0 2,606 Primary 19.8 0.3 0.6 79.3 100.0 1,319 Secondary 35.6 0.0 1.5 62.9 100.0 262 More than secondary 49.7 4.8 0.0 45.6 100.0 121 Wealth quintile Lowest 6.8 0.2 0.2 92.7 100.0 1,011 Second 9.9 0.5 0.4 89.2 100.0 943 Middle 12.7 0.3 1.4 85.7 100.0 890 Fourth 13.6 0.4 1.3 84.7 100.0 796 Highest 41.9 1.1 0.0 57.0 100.0 667 Total 15.4 0.5 0.7 83.5 100.0 4,308 Note: Figures in parentheses are based on 25-49 unweighted cases. 154 • Maternal Health Care Table 9.14 Timing of first postnatal check for the newborn Percent distribution of most recent live births in the 2 years before the survey by time after birth of first postnatal check, and percentage of births with a postnatal check during the first 2 days after birth, according to background characteristics, Ethiopia DHS 2016 Time after delivery of newborn’s first postnatal check1 No postnatal check-up2 Total Percentage of births with a postnatal check during 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 Mother’s age at birth <20 1.9 7.8 1.6 0.4 1.3 0.0 86.9 100.0 11.8 508 20-34 3.1 7.5 2.3 1.2 0.5 0.3 85.2 100.0 14.0 3,126 35-49 1.2 5.4 2.3 0.8 0.5 0.1 89.7 100.0 9.7 674 Birth order 1 3.5 11.5 3.1 0.9 1.8 0.4 78.8 100.0 19.0 885 2-3 3.6 7.8 2.0 1.5 0.1 0.4 84.6 100.0 14.9 1,320 4-5 2.8 6.1 1.7 1.2 0.6 0.0 87.6 100.0 11.8 939 6+ 0.9 4.1 2.3 0.4 0.2 0.1 92.1 100.0 7.6 1,165 Place of delivery Health facility 6.9 19.1 5.8 2.3 1.2 0.7 63.9 100.0 34.2 1,560 Public facility 6.8 19.3 5.6 2.3 1.2 0.7 64.1 100.0 34.1 1,497 Private facility 8.3 18.4 8.0 2.1 3.1 1.0 59.1 100.0 36.8 48 NGO (6.6) (4.2) (20.7) (3.2) (0.0) (0.0) (65.3) (100.0) (34.7) 15 Elsewhere 0.3 0.4 0.2 0.3 0.2 0.0 98.6 100.0 1.1 2,748 Residence Urban 9.4 18.5 6.8 2.7 2.2 0.6 59.8 100.0 37.4 520 Rural 1.7 5.6 1.6 0.8 0.4 0.2 89.7 100.0 9.8 3,788 Region Tigray 5.5 19.2 3.6 2.9 1.6 0.2 67.0 100.0 31.2 314 Affar 2.3 2.8 1.2 0.3 0.2 1.2 92.1 100.0 6.5 43 Amhara 2.9 6.7 0.9 0.9 1.3 0.3 87.0 100.0 11.4 789 Oromiya 1.8 3.6 2.2 0.9 0.0 0.2 91.4 100.0 8.4 1,915 Somali 1.0 7.7 2.1 0.8 1.6 0.6 86.2 100.0 11.6 178 Benishangul-Gumuz 3.4 6.8 2.3 2.3 2.4 0.0 82.9 100.0 14.7 45 SNNPR 2.3 9.3 2.0 0.6 0.0 0.1 85.7 100.0 14.2 876 Gambela 1.4 11.2 2.2 3.7 1.4 0.4 79.7 100.0 18.4 10 Harari 5.5 25.8 3.6 0.0 0.2 0.4 64.5 100.0 34.8 10 Addis Ababa 14.0 19.8 10.1 2.2 5.2 1.8 46.9 100.0 46.1 110 Dire Dawa 3.9 17.9 4.8 0.4 0.6 0.0 72.3 100.0 27.1 18 Mother’s education No education 0.9 4.3 1.1 0.9 0.5 0.2 92.0 100.0 7.3 2,606 Primary 4.1 9.2 2.3 1.2 0.4 0.2 82.5 100.0 16.9 1,319 Secondary 6.7 20.6 5.6 1.0 0.9 0.2 65.1 100.0 33.9 262 More than secondary 15.2 18.1 16.9 1.8 4.7 1.3 42.0 100.0 51.9 121 Wealth quintile Lowest 0.3 2.3 0.9 0.6 0.5 0.0 95.4 100.0 4.1 1,011 Second 1.4 4.8 0.7 0.5 0.3 0.3 91.9 100.0 7.5 943 Middle 2.2 4.5 1.9 1.2 0.5 0.5 89.2 100.0 9.7 890 Fourth 2.8 9.5 1.6 0.9 0.2 0.0 84.9 100.0 14.8 796 Highest 8.5 18.8 7.6 2.3 1.7 0.4 60.8 100.0 37.1 667 Total 2.7 7.2 2.2 1.0 0.6 0.2 86.1 100.0 13.1 4,308 Note: Figures in parentheses are based on 25-49 unweighted cases. 1 Includes newborns who received a check-up from a doctor, nurse, midwife, health officer, health extension worker (HEW), or traditional birth attendant. 2 Includes newborns who received a check-up after the first week of life. Maternal Health Care • 155 Table 9.15 Type of provider for the first postnatal check for the newborn Percent distribution of most recent live births in the 2 years before the survey by type of provider for the newborn’s first postnatal health check during the 2 days after the birth, according to background characteristics, Ethiopia DHS 2016 Type of health provider for newborn’s first postnatal check-up No postnatal check-up in the first 2 days after birth Total Number of births Background characteristic Doctor/ nurse/ midwife Health officer Health extension worker Traditional birth attendant Mother’s age at birth <20 11.1 0.0 0.0 0.7 88.2 100.0 508 20-34 12.4 0.5 1.1 0.0 86.0 100.0 3,126 35-49 9.0 0.2 0.4 0.0 90.3 100.0 674 Birth order 1 18.5 0.0 0.1 0.4 81.0 100.0 885 2-3 12.9 0.9 1.1 0.0 85.1 100.0 1,320 4-5 10.4 0.5 0.8 0.0 88.2 100.0 939 6+ 6.3 0.1 1.2 0.0 92.4 100.0 1,165 Place of delivery Health facility 31.6 1.1 1.5 0.0 65.8 100.0 1,560 Public facility 31.4 1.1 1.5 0.0 65.9 100.0 1,497 Private facility 36.8 0.0 0.0 0.0 63.2 100.0 48 NGO (34.7) (0.0) (0.0) (0.0) (65.3) (100.0) 15 Elsewhere 0.4 0.1 0.5 0.1 98.9 100.0 2,748 Residence Urban 36.1 1.3 0.0 0.0 62.6 100.0 520 Rural 8.4 0.3 1.0 0.1 90.2 100.0 3,788 Region Tigray 30.4 0.0 0.8 0.0 68.8 100.0 314 Affar 6.5 0.0 0.0 0.0 93.5 100.0 43 Amhara 10.2 0.2 1.0 0.0 88.6 100.0 789 Oromiya 7.1 0.5 0.7 0.2 91.6 100.0 1,915 Somali 11.3 0.2 0.0 0.1 88.4 100.0 178 Benishangul-Gumuz 12.7 0.0 2.0 0.0 85.3 100.0 45 SNNPR 12.0 0.7 1.4 0.0 85.8 100.0 876 Gambela 17.9 0.6 0.0 0.0 81.6 100.0 10 Harari 33.4 0.6 0.0 0.9 65.2 100.0 10 Addis Ababa 45.6 0.5 0.0 0.0 53.9 100.0 110 Dire Dawa 25.6 1.4 0.0 0.0 72.9 100.0 18 Mother’s education No education 6.2 0.2 0.9 0.0 92.7 100.0 2,606 Primary 15.3 0.5 0.8 0.3 83.1 100.0 1,319 Secondary 32.7 0.2 1.0 0.0 66.1 100.0 262 More than secondary 46.6 4.8 0.5 0.0 48.1 100.0 121 Wealth quintile Lowest 3.6 0.0 0.4 0.0 95.9 100.0 1,011 Second 6.8 0.0 0.7 0.0 92.5 100.0 943 Middle 7.1 0.5 1.7 0.4 90.3 100.0 890 Fourth 13.1 0.8 0.9 0.0 85.2 100.0 796 Highest 35.6 1.0 0.5 0.0 62.9 100.0 667 Total 11.7 0.4 0.9 0.1 86.9 100.0 4,308 Note: Figures in parentheses are based on 25-49 unweighted cases. 156 • Maternal Health Care Table 9.16 Content of postnatal care for newborns Among most recent live births in the 2 years before the survey, percentage for whom selected functions were performed during the first 2 days after the birth, and percentage with at least two signal functions performed during the first 2 days after the birth, according to background characteristics, Ethiopia DHS 2016 Among most recent live births in the 2 years before the survey, percentage for whom the selected function was performed during the first 2 days after the birth: Percentage with at least two signal functions performed during the first 2 days after birth Number of births Background characteristic Cord examined Temperature measured Counselling on danger signs Counselling on breastfeeding Observation of breastfeeding Weighed1 Mother’s age at birth <20 8.7 13.1 9.1 25.5 27.0 15.8 26.6 508 20-34 10.9 14.3 12.4 25.6 29.9 19.2 27.7 3,126 35-49 8.1 11.4 9.8 25.9 25.9 12.7 25.9 674 Birth order 1 13.5 20.1 14.4 36.1 40.1 31.2 40.2 885 2-3 11.4 16.6 14.5 27.9 32.1 21.0 30.1 1,320 4-5 10.3 11.4 10.4 23.8 25.5 12.5 23.6 939 6+ 6.1 7.4 7.0 16.8 19.6 8.1 17.2 1,165 Place of delivery Health facility 24.5 33.7 25.8 55.5 60.4 46.9 62.2 1,560 Public facility 24.3 32.9 25.7 55.3 60.2 46.1 61.8 1,497 Private facility 34.0 59.1 30.2 61.6 65.9 73.8 73.4 48 NGO (18.9) (29.9) (20.7) (56.1) (63.9) (46.1) (62.7) 15 Elsewhere 2.0 2.4 3.5 8.7 11.1 1.2 7.5 2,748 Residence Urban 25.6 41.1 30.0 60.6 65.0 65.1 71.8 520 Rural 8.1 9.9 9.0 20.9 24.0 11.3 21.2 3,788 Region Tigray 31.1 34.9 31.8 55.2 64.4 36.7 63.4 314 Affar 3.3 3.9 5.4 14.7 23.4 8.8 17.0 43 Amhara 8.2 16.4 12.0 34.2 35.1 12.6 31.4 789 Oromiya 7.7 9.0 6.1 14.8 18.7 12.5 16.9 1,915 Somali 5.3 6.6 2.4 13.1 15.4 13.3 14.1 178 Benishangul-Gumuz 6.3 11.4 10.3 28.2 41.5 24.2 32.6 45 SNNPR 7.9 10.4 14.2 28.2 29.6 17.7 28.6 876 Gambela 6.2 9.6 6.1 19.6 22.6 35.1 23.9 10 Harari 19.9 16.3 13.4 31.7 55.4 40.4 40.4 10 Addis Ababa 35.7 57.4 43.4 71.8 72.5 91.5 85.6 110 Dire Dawa 20.5 19.1 13.8 34.8 32.7 49.0 41.0 18 Mother’s education No education 6.6 7.9 8.0 19.1 21.4 8.5 18.9 2,606 Primary 12.6 17.6 14.3 28.9 33.4 23.1 31.2 1,319 Secondary 25.4 32.5 26.6 54.6 59.3 51.1 64.7 262 More than secondary 27.4 54.9 25.1 68.8 77.0 87.1 84.9 121 Wealth quintile Lowest 3.2 5.5 5.4 13.0 16.8 5.7 12.1 1,011 Second 6.9 7.3 6.2 18.0 20.8 8.8 18.9 943 Middle 9.9 10.9 9.4 25.9 27.4 13.2 25.6 890 Fourth 11.2 15.6 15.2 27.6 30.2 16.8 29.3 796 Highest 24.6 36.8 27.0 53.1 59.5 56.0 62.0 667 Total 10.2 13.7 11.6 25.7 29.0 17.8 27.3 4,308 Note: Figures in parentheses are based on 25-49 unweighted cases. 1 Includes newborns who were weighed “at birth.” May exclude some newborns who were weighed during the 2 days after birth. Maternal Health Care • 157 Table 9.17 Newborn care Among most recent live births in the 2 years before the survey delivered in a health facility, percentage of births given Vitamin K injection and percentage of births with TTC eye ointment applied, according to background characteristics, Ethiopia DHS 2016 Background characteristic Percentage given Vitamin K injection Percentage having TTC eye ointment applied Number of live births delivered in a health facility in the 2 years before the survey Mother’s age at birth <20 36.3 32.2 198 20-34 42.3 34.8 1,170 35-49 36.1 32.7 192 Birth order 1 40.4 32.1 521 2-3 45.8 33.4 518 4-5 36.5 41.6 277 6+ 35.5 32.2 244 Residence Urban 47.4 37.7 467 Rural 37.9 32.8 1,093 Region Tigray 59.9 57.2 226 Affar 33.7 32.2 9 Amhara 31.6 24.0 295 Oromiya 38.3 28.1 515 Somali 40.3 53.2 39 Benishangul-Gumuz 41.9 53.2 15 SNNPR 37.8 32.7 330 Gambela 24.3 31.1 5 Harari 39.3 53.3 6 Addis Ababa 46.1 37.9 107 Dire Dawa 60.0 37.1 12 Mother’s education No education 37.6 33.7 617 Primary 39.9 33.7 613 Secondary 43.8 33.1 215 More than secondary 56.5 42.3 115 Wealth quintile Lowest 27.6 29.7 150 Second 36.5 30.0 262 Middle 34.4 32.9 285 Fourth 41.4 37.4 324 Highest 49.4 36.4 539 Total 40.7 34.2 1,560 Note: Total includes 4 weighted cases with information missing on antenatal care visits. 158 • Maternal Health Care Table 9.18 Care of umbilical cord Among most recent live births in the 2 years before the survey, percentage who had something applied on stump after umbilical cord was cut, and description of what was applied on stump, according to background characteristics, Ethiopia DHS 2016 Background characteristic Percentage of birth with something applied on stump after umbilical cord was cut Number of recent live births in the 2 years before the survey Description of what was applied on stump Number of births who had something applied on stump Any type of oil Dung Ash Ointment Other Mother’s age at birth <20 19.1 508 76.6 0.0 0.8 16.0 6.6 97 20-34 15.3 3,126 65.9 1.3 2.4 19.3 12.2 478 35-49 11.0 674 68.3 1.4 0.5 20.2 12.5 74 Birth order 1 20.9 885 64.1 2.1 0.5 22.4 12.3 185 2-3 16.8 1,320 70.0 0.3 1.2 18.3 11.4 222 4-5 14.1 939 65.2 0.3 1.4 20.2 13.2 132 6+ 9.5 1,165 72.6 2.1 6.6 12.7 7.5 110 Residence Urban 20.2 520 46.6 0.1 0.7 33.7 22.6 105 Rural 14.4 3,788 71.8 1.3 2.2 16.0 9.2 545 Region Tigray 39.3 314 61.5 2.5 0.0 21.2 16.3 124 Affar 6.8 43 * * * * * 3 Amhara 9.0 789 (34.4) (0.0) (0.0) (11.9) (53.7) 71 Oromiya 13.2 1,915 81.4 0.0 2.0 16.7 0.0 254 Somali 18.0 178 58.5 0.6 18.8 13.0 12.2 32 Benishangul-Gumuz 6.2 45 * * * * * 3 SNNPR 16.2 876 68.7 2.8 0.0 24.2 5.1 142 Gambela 8.3 10 * * * * * 1 Harari 26.7 10 54.5 1.5 29.5 8.0 12.5 3 Addis Ababa 14.6 110 (66.3) (0.0) (0.0) (30.1) (20.7) 16 Dire Dawa 15.2 18 (88.2) (0.0) (0.0) (9.5) (2.4) 3 Mother’s education No education 10.9 2,606 68.6 1.0 4.2 15.5 11.1 284 Primary 20.7 1,319 69.2 1.6 0.2 18.5 11.5 273 Secondary 23.8 262 69.9 0.1 0.2 25.4 8.1 62 More than secondary 24.3 121 (42.9) (0.0) (0.4) (41.1) (19.3) 30 Wealth quintile Lowest 14.6 1,011 68.1 1.9 7.6 11.9 10.8 147 Second 12.7 943 78.7 0.4 0.3 16.1 4.7 120 Middle 14.0 890 75.0 1.3 0.5 17.3 6.3 125 Fourth 16.2 796 62.6 1.7 0.2 21.0 15.4 129 Highest 19.2 667 55.4 0.1 0.2 29.0 19.1 128 Total 15.1 4,308 67.8 1.1 2.0 18.9 11.4 650 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. Maternal Health Care • 159 Table 9.19 Obstetrical fistula Percentage of women age 15-49 who have heard of obstetrical fistula, and percentage of women who have experienced obstetric fistula, by background characteristics, Ethiopia DHS 2016 Background characteristic Percentage of women who have heard of obstetrical fistula Percentage of women who have experienced obstetrical fistula Number of women Age 15-19 36.8 0.2 3,381 20-24 41.6 0.3 2,762 25-29 38.5 0.6 2,957 30-34 36.6 0.6 2,345 35-39 35.9 0.4 1,932 40-44 43.4 0.7 1,290 45-49 41.1 0.6 1,017 Residence Urban 66.6 0.3 3,476 Rural 30.7 0.5 12,207 Region Tigray 65.8 1.1 1,129 Affar 35.5 0.5 128 Amhara 45.0 0.7 3,714 Oromiya 28.6 0.2 5,701 Somali 31.0 0.3 459 Benishangul-Gumuz 40.2 0.5 160 SNNPR 28.0 0.3 3,288 Gambela 40.0 0.4 44 Harari 62.5 0.0 38 Addis Ababa 81.5 0.4 930 Dire Dawa 45.1 0.2 90 Education No education 27.9 0.5 7,498 Primary 37.0 0.4 5,490 Secondary 65.2 0.1 1,817 More than secondary 84.9 0.1 877 Wealth quintile Lowest 26.4 0.5 2,633 Second 26.1 0.3 2,809 Middle 29.2 0.5 2,978 Fourth 35.9 0.5 3,100 Highest 63.6 0.4 4,163 Total 15-49 38.6 0.4 15,683 160 • Maternal Health Care Table 9.20 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, Ethiopia DHS 2016 Problems in accessing health care Background characteristic Getting permission to go for treatment Getting money for treatment Distance to health facility Not wanting to go alone At least one problem accessing health care Number of women Age 15-19 32.9 50.5 46.7 44.3 67.8 3,381 20-34 31.8 54.2 50.4 41.0 69.2 8,064 35-49 32.1 59.3 53.1 42.0 73.2 4,238 Number of living children 0 28.0 46.7 41.4 39.5 63.7 5,185 1-2 29.3 53.2 47.0 39.8 66.8 3,770 3-4 34.5 59.7 55.9 43.1 73.9 3,064 5+ 38.8 63.6 61.7 46.9 78.9 3,664 Marital status Never married 28.1 47.7 41.2 39.5 64.2 4,036 Married or living together 34.3 56.3 54.6 43.6 71.9 10,223 Divorced/separated/widowed 27.6 63.9 45.2 37.5 73.0 1,423 Employed last 12 months Not employed 36.2 59.1 55.5 45.9 73.7 7,819 Employed for cash 25.8 50.3 37.2 30.7 61.5 3,693 Employed not for cash 30.1 50.5 52.2 44.6 70.6 4,171 Residence Urban 15.1 34.7 17.0 21.4 45.6 3,476 Rural 37.0 60.5 59.8 47.9 76.9 12,207 Region Tigray 15.3 46.1 37.4 24.6 60.7 1,129 Affar 28.2 51.7 54.3 41.8 66.6 128 Amhara 15.4 35.3 33.7 34.6 55.7 3,714 Oromiya 58.3 70.1 68.9 57.0 82.9 5,701 Somali 25.7 63.0 47.3 32.2 72.6 459 Benishangul-Gumuz 36.5 62.4 57.4 43.8 76.8 160 SNNPR 18.4 59.1 52.7 39.5 75.4 3,288 Gambela 24.3 44.3 41.0 33.7 61.2 44 Harari 16.3 28.2 18.1 13.8 30.8 38 Addis Ababa 8.7 29.2 10.8 14.5 40.0 930 Dire Dawa 58.7 64.5 57.4 55.2 71.4 90 Education No education 37.6 62.9 59.2 47.1 78.0 7,498 Primary 31.9 55.7 50.3 43.2 71.1 5,490 Secondary 18.2 33.2 27.8 27.8 48.1 1,817 More than secondary 15.9 23.8 20.6 20.4 39.8 877 Wealth quintile Lowest 40.0 70.9 67.7 54.5 85.3 2,633 Second 42.1 67.0 66.8 52.7 82.9 2,809 Middle 35.2 61.0 59.4 47.6 77.3 2,978 Fourth 33.8 50.2 49.8 41.2 68.2 3,100 Highest 17.0 35.2 22.1 23.4 47.7 4,163 Total 32.1 54.8 50.3 42.0 70.0 15,683 Child Health • 161 CHILD HEALTH 10 Key Findings  Child size and birth weight: Information on birth weight was obtained for only 14% of births. Thirteen percent of babies weighed less than 2.5 kg at birth.  Vaccinations: Close to two in every five children age 12- 23 months (39%) received all basic vaccinations at some time, and 22% were vaccinated by the appropriate age. The percentage of children age 12-23 months who are fully vaccinated increased by 15%, from 24% in 2011 to 39% in 2016.  Symptoms of acute respiratory infection (ARI): Seven percent of children under age 5 had symptoms of ARI in the 2 weeks before the survey. Three out of 10 of these children sought treatment.  Fever: Fourteen percent of children under age 5 were reported to have fever in the 2 weeks before the survey. Treatment from a health facility or provider was sought only for 35% of children with fever.  Diarrhoea: Twelve percent of children under age 5 had diarrhoea in 2 weeks before the survey. More than four out of 10 children under age 5 (44%) who had diarrhoea sought treatment. Among children under age 5 with diarrhoea, 46% received some form of ORT, while 39% received ORT or increased liquids. nformation on child health and survival can help policymakers and programme managers assess the efficacy of current strategies, formulate appropriate interventions to prevent deaths from childhood illnesses, and improve the health of children in the country. This chapter presents information on birth weight and vaccination status for young children. The chapter also looks at the prevalence of and treatment practices for three common childhood illnesses: symptoms of acute respiratory infection (ARI), fever, and diarrhoea. Because appropriate sanitary practices can help prevent and reduce the severity of diarrheal disease, information is also provided on the disposal of children’s faecal matter. 10.1 BIRTH WEIGHT Low birth weight is closely associated with foetal and neonatal morbidity, inhibited growth and cognitive development, and chronic diseases in life (Negrato et al. 2013). Birth weight is a good summary measure of multifaceted public health problems that include long-term maternal malnutrition, ill health, and poor health care during pregnancy. In this survey, information on birth weight was collected by either a written record or the mother’s report. The mother’s assessment of the child’s weight was necessary because information on birth weight was rarely available. Children are considered to have a low birth weight if they weigh less than 2.5 I 162 • Child Health kilogrammes (kg) at birth. The mother’s estimate of weight is subjective and interpretation of the finding should be viewed with caution. Low birth weight Percentage of births with a reported birth weight <2.5 kilogrammes 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 Information on birth weight was obtained from only 14% of births (Table 10.1). Among these, 13% weighed less than 2.5 kg at birth. Table 10.1 also includes information on mothers’ subjective estimates of their infant’s size in the 5 years before the survey. This estimate was obtained because birth weight is unknown for most (86%) newborns in Ethiopia. According to mother’s report, 16% of births are very small, 10% are smaller than average, and 73% are average or larger. Patterns by background characteristics  Births to mothers with no education are more likely to have low birth weight (18%) compared with births to women with primary and secondary education (11% and 8%, respectively). Data on low birth weight by mother’s education should be carefully interpreted because the data were available for 84% of births to mothers with secondary education compared with only 6% of births to mothers with no education. Trends: The percentage of mothers who reported information on birth weight in the 5 years before the survey has increased from 3% in 2005 to 5% in 2011, and 14% in 2016. The proportion of births weighing less than 2.5 kg at birth in the past three DHS surveys was 14% in 2005, 11% in 2011, and 13% in 2016. 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, health facility visit, 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-HepB-Hib, which protects against diphtheria, pertussis (whooping cough), and tetanus  three doses of polio vaccine  one dose of measles vaccine Sample: Living children age 12-23 months Child Health • 163 The Expanded Programme for Immunisation (EPI) in Ethiopia, launched in 1980, has been one of the core priorities in the past Health Sector Development Programmes (HSDPs) and the current Health Sector Transformation Plan (HSTP) (MOH 2015). The country has mobilised women development armies or volunteers, health extension workers, and health facilities to deliver its immunisation services. Improved district planning and management were initiated in 2011 with a goal of reaching every district. Stationary, outreach, and mobile are the three important service delivery platforms for vaccination services. In addition, several campaigns provided polio, measles and other antigens to children. Information on vaccination coverage was obtained in three ways in the 2016 EDHS: written vaccination records (including the infant immunisation card and other health cards), mothers’ verbal reports, and health facility records. In the 2016 EDHS, for each child born in the 3 years before the survey, mothers were asked to provide information about the vaccinations her child has received. Unlike the previous EDHS surveys, in the 2016 EDHS, a separate team visited the health facility to collect complementary vaccination records if the mother was not able to present the infant immunisation card and the child had visited a health facility. Consent was obtained from mothers prior to contacting the facilities and verifying child vaccination records. The purpose of obtaining information at the health facility was to complement the information collected by mother’s recall. In Ethiopia, four in ten children age 12-23 months (39%) received all basic vaccinations at some time, and 22% received these vaccinations before their first birthday (Table 10.2 and Figure 10.1). In Ethiopia, the vaccination coverage among children age 12-23 months is highest for the first dose of polio vaccine (81%) followed by first dose of DPT-HepB-Hib vaccine (73%). More than half (53%) of children in Ethiopia have received three doses of DPT-HepB-Hib vaccine and 54% received the measles vaccination. There is a 20 percentage-point dropout rate at the national level from the first to the third dose of DPT-HepB-Hib vaccine and a 25 percentage-point dropout rate from the first to the third dose of polio vaccine. 10.2.1 Uptake of the Newly Introduced Vaccines The government of Ethiopia introduced the pneumococcal conjugate vaccine (PCV) and monovalent human rotavirus vaccine (RV) into the national infant immunisation programme in November 2011 and October 2012, respectively. The PCV protects against streptococcus pneumoniae bacteria, which cause severe pneumonia, meningitis, and other illnesses. Rotavirus is a virus that causes gastroenteritis, an inflammation of the stomach and intestines. If left untreated, rotavirus can lead to severe dehydration and death. Among children age 12-23 months, 49% received the third dose of PCV and 56% received the second dose of RV. Figure 10.1 Childhood vaccinations 69 73 65 53 81 72 56 54 39 16 BCG 1 2 3 1 2 3 Measles All basic None Percentage of children age 12-23 months vaccinated at any time before the survey PolioDPT/Pentavalent 164 • Child Health Trends: The EDHS surveys have shown a steady progress in EPI coverage. The percentage of children age 12-23 months who received all basic vaccinations increased from 14% in 2000, to 20% in 2005, 24% in 2011, and 39% in 2016. However, the proportion of children age 12-23 months with no vaccination decreased from 24% in 2005 to 16% in 2016 (Figure 10.2). Patterns by background characteristics  Among children age 12-23, vaccination coverage declines as the birth order of children increases, from 47% for first order births to 29% for sixth or higher order births (Table 10.3).  Children age 12-23 months in rural areas are more likely to receive all basic vaccinations than children in urban areas (65% versus 35%).  At the regional level, coverage of all basic vaccinations is highest in Addis Ababa (89%), Dire Dawa (76%), and Tigray (67%) and lowest in Affar (15%), Somali (22%) and Oromiya (25%) (Figure 10.3).  Children are more likely to receive all basic vaccinations if their mothers have more than secondary education (72%) or secondary education (70%), than if their mothers have only a primary education (46%) or no education (31%) (Figure 10.4).  Children in the highest household wealth quintile are more likely to receive all basic vaccinations than children in the lowest quintile (63% versus 22%). 10.2.2 Vaccination Card Ownership and Availability Vaccination cards are critical tools in ensuring that children receive all recommended vaccinations according to schedule. The 2016 EDHS found that 46% of children age 12-23 months and 35% of children age 24 -35 months were reported to have a vaccination card. However, interviewers were able to see a vaccination card, booklet, or other home-based record for only 34% of children age 12-23 months and 17% of children age 24-35 months (Table 10.4). 10.2.3 Health Facility Visit Tables 10.5, 10.6, and 10.7 present results from the health facilities visit. Table 10.5 presents information on children age 0-35 months, while Tables 10.6 and 10.7 present information on children age 12-35 Figure 10.2 Trends in childhood vaccinations Figure 10.3 Vaccination coverage by region Figure 10.4 Vaccination coverage by mother’s education 14 20 24 39 17 24 15 16 2000 EDHS 2005 EDHS 2011 EDHS 2016 EDHS Percentage of children age 12-23 months who received all basic vaccinations at any time before the survey No vaccinations All basic vaccinations 15 22 25 41 42 46 47 57 67 76 89 Affar Somali Oromiya Gambela Harari Amhara SNNPR Benishangul-Gumuz Tigray Dire Dawa Addis Ababa Percentage of children age 12-23 months who received all basic vaccinations at any time before the survey 31 46 70 72 No education Primary Secondary More than secondary Percentage of children age 12-23 months who received all basic vaccinations at any time before the survey Child Health • 165 months. Table 10.6 shows that 74% of children age 12-35 months did not have a vaccination card that was seen during home visit. Among these children, 51% had received at least one vaccination at a health facility. For 46% of the children, interviewers were able to obtain the mother’s consent to search for the health record at a health facility. Vaccination history was searched at a health facility for 45% of children, and information on vaccination history was found for 32% of children. Table 10.7 shows that among the children with a vaccination history searched at health facility, vaccination history was found and seen by interviewers for 71% of children; for 16% of children, vaccination records were not located at the health facilities by the interviewer, and for 13% of children, while other vaccination records were located at health facilities, records for the specific children identified without vaccination records during home interview were not found by the health facility teams. For detailed information on health facility, see Tables 10.5 and 10.6. 10.3 SYMPTOMS OF ACUTE RESPIRATORY INFECTION In Ethiopia, 88 in 1,000 children under age 5 die before their fifth birthday (CSA 2012). Acute respiratory infection (ARI), and particularly pneumonia, is one of leading causes of morbidity and mortality that accounts for 18% of deaths (WHO and UNICEF 2013). Improving early care is a key strategy for early diagnosis and treatment. Ethiopia has made investments to reduce the morbidly and mortality of ARI. Integrated management of common childhood illness and community case management are among the programme initiatives scaled up nationally to address ARI (Miller et al. 2013). Treatment of acute respiratory infection (ARI) symptoms Children with ARI symptoms for whom advice or treatment was sought. The ARI symptoms 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 Seven percent of children under age 5 had symptoms of ARI in the 2 weeks before the survey. Treatment was sought for three out of 10 children and only 3% of these children received treatment on the same or next day (Table 10.8). Government health centres are the most commonly preferred sources for care of ARI (64%) (Table 10.9). 10.4 FEVER Fever is an abnormally high body temperature, which is usually accompanied by shivering, headache, and restlessness. Fever indicates the presence of various illnesses such as malaria, pneumonia, an ear problem, the common cold, influenza, and other infections. Treatment of fever Children with fever for whom advice or treatment was sought. Sample: Children under age 5 with fever in the 2 weeks before the survey Fourteen percent of children under 5 were reported to have fever in the 2 weeks before the survey. Treatment was sought only for one-third (35%) of febrile children, while for less than one in ten children (8%) treatment was sought within the same or next day of onset of illness. Twenty-seven percent of children with fever were given antibiotics for the illness (Table 10.10). 166 • Child Health Patterns by background characteristics  Fever is more prevalent among children age 6-35 months than those age less than 6 months.  The percentage of children with fever who were taken to a health facility or provider for advice or treatment is higher in urban than in rural areas (59% versus 32%).  Care-seeking for children with fever increases with the mother’s level of education and the wealth quintile. The likelihood that a child received an antibiotic also increases with the mother’s education and wealth quintile. 10.5 DIARRHOEAL DISEASE 10.5.1 Prevalence of Diarrhoea Diarrhoea is one of the major contributors to deaths for under age 5 children in Ethiopia. Based on the WHO/CHERG estimates, diarrhoea contributes to more than one in every ten (13%) child deaths in Ethiopia (WHO 2014). Mothers reported that 12% of children under age 5 had a diarrhoeal episode in the 2 weeks before the survey (Table 10.11). Among children under age 5 who had diarrhoea in the 2 weeks before the survey, advice or treatment was sought for 44%. Trend: The percentage of children under age 5 who had diarrhoea in the 2 weeks before the survey period decreased from 24% in 2000, to 18% in 2005, 13% in 2011, and 12% in 2016. Patterns by background characteristics  The prevalence of diarrhoea increases after age 6 months, from 8% among children under age 6 months to 23% among those 6-11 months, when complimentary foods and other liquids are introduced. Prevalence remains high (18%) at age 12-23 months, which is the time when children begin walking and are at increased risk of contamination from the environment (Figure 10.5).  The prevalence of diarrhoea is slightly higher for children in households with unimproved sanitation than for children in households with improved sanitation  The prevalence of diarrhoea is lower among children whose mothers have more than a secondary education than among children whose mothers have a secondary or less education (7% versus 11% or higher). 10.5.2 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 Figure 10.5 Diarrhoea prevalence by age 8 23 18 13 9 5 12 <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 before the survey Age in months Child Health • 167 To reduce dehydration and minimise the effects of diarrhoea on nutritional status, mothers are encouraged to continue normal feeding of children with diarrhoea and to increase the amount of fluids. Mothers in the 2016 EDHS reported that 15% of children under age 5 with diarrhoea in the 2 weeks before the survey were given more liquids than usual, 21% were given the usual amount of liquids, and 33% received somewhat less amount of liquids than usual (Table 10.12). With food intake during a diarrhoea episode in the past 2 weeks, 7% were fed more food, 18% were fed the usual amount, and 60% were given less food (35% were fed somewhat less and 25% were fed much less than usual) (Figure 10.6). For additional information on feeding practices during diarrhoea, see Table 10.12. 10.5.3 Oral Rehydration Therapy and Other Treatments for Diarrhoea Deaths from diarrhoea can easily be averted with early and proper treatment. Oral rehydration therapy (ORT) is most commonly used and most simple therapy for treating diarrhoea. Depending on the severity, treatment may involve administration of antibiotics, oral rehydration therapy, as well as anti-motility and intravenous solutions. Zinc supplementation helps to reduce the severity, frequency, and duration of the diarrhoea episode. Oral rehydration therapy Children with diarrhoea are given increased fluids, or a fluid made from a special packet of oral rehydration salts (ORS), or government episode- recommended homemade fluids (RHF). Sample: Children under age 5 with diarrhoea in the 2 weeks before the survey Close to half (46%) of children under age 5 with diarrhoea in the 2 weeks before the survey received some form of ORT, either ORS packets (30%), recommended home fluids (19%), or increased fluids. One in three children (33%) under age 5 with diarrhoea received zinc and 17% received a combination of ORS and zinc. Antibiotics were given to 9% of children with diarrhoea. Close to two in five (38%) of children with diarrhoea did not receive any treatment (Table 10.13 and Figure 10.7). Trends: The percentage of under age 5 children with diarrhoea who received treatment has increased from 13% in 2000, 22% in 2005, 32% in 2011, and 44% in 2016. The percentage of children who received no treatment has decreased from 42% in 2011 to 38% in 2016. Figure 10.6 Feeding practices during diarrhoea Figure 10.7 Treatment of diarrhoea 7 15 18 21 35 33 33 23 7 8 Food 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) 38 9 9 15 17 33 38 19 30 44 No treatment Home remedy/other Antibiotics Increased fluids ORS and zinc Zinc ORS or RHF Recommended home fluids Fluid from ORS packet Sought advice or treatment Percentage of children under age 5 with diarrhoea in the 2 weeks before the survey 168 • Child Health Patterns by background characteristics  Children with access to improved drinking water and improved toilet facilities, as well as urban dwellers, those whose mother is more educated, and those who live in wealthier households are more likely to seek advice for treatment from a health provider or facility than other children.  Three in four (76%) of children under age 2 with diarrhoea for whom advice or treatment was sought were taken to a public health facility for treatment (Table 10.14). 10.5.4 Knowledge of ORS Packets Oral rehydration solutions (ORS), which can be given at home and are available over the counter, prevents dehydration through the replenishment of water and the replacement of electrolytes in the body. In the Ethiopian context, an ORS packet is referred as LEMLEM. Two in three (66%) women age 15-49 in Ethiopia know about ORS packets (LEMLEM) or pre-packaged liquids for the treatment of diarrhoea (Table 10.15). Knowledge of ORS packets is highest among women in urban areas (90%), those with more than secondary education (96%), and those in the wealthiest households (86%). 10.5.5 Treatment of Childhood Illnesses During the 2 weeks before the survey, ARI symptoms, fever, and diarrhoea were found in 7%, 14%, and 12% of children under age 5, respectively. Advice from a health facility or treatment was sought for 31% of children with ARI, 35% of children with fever, and 44% of children with diarrhoea (Figure 10.8). 10.6 DISPOSAL OF CHILDREN’S STOOLS Globally, close to nine in ten of the diarrhoeal disease burden has been estimated to be linked to poor water, sanitation, and hygiene provision. Proper disposal of children’s faeces is important in preventing the spread of diseases. If faeces is left uncontained, diseases may spread by direct contact or animal contact (WHO/UNICEF 2013). 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 Forty percent of children under age 2 had their last stool disposed of safely, either by using a toilet or latrine or having the stool rinsed or put in a toilet or latrine. In contrast, 44% had their stool disposed unsafely, either left in the open (26%) or thrown into garbage (18%) (Table 10.16). Patterns by background characteristics  Safe disposal of children’s stools increases with increasing mother’s education, and the wealth quintile.  Children’s stools are less likely to be disposed of safely in households that use open defecation (14%), as compared with improved sanitation (50%). Figure 10.8 Prevalence and treatment of childhood illness 7 14 12 31 35 44 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 for whom advice or treatment was sought Child Health • 169  Children’s stools are more likely to be disposed safely in urban households (61%) than in rural households (37%).  The percentage of children whose last stool was disposed of safely ranges from 29% in Somali to 62% in SNNPR. LIST OF TABLES For more 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 Observation of vaccination history at health facilities: Children 0-35 months  Table 10.6 Observation of vaccination history at health facilities: Children 12-35 months  Table 10.7 Outcome of health facilities visit  Table 10.8 Prevalence and treatment of symptoms of ARI  Table 10.9 Source of advice or treatment for children with symptoms of ARI  Table 10.10 Prevalence and treatment of fever  Table 10.11 Prevalence and treatment of diarrhoea  Table 10.12 Feeding practices during diarrhoea  Table 10.13 Oral rehydration therapy, zinc, and other treatments for diarrhoea  Table 10.14 Source of advice or treatment for children with diarrhoea  Table 10.15 Knowledge of ORS packets (LEMLEM) or pre-packaged liquids  Table 10.16 Disposal of children’s stools 170 • Child Health Table 10.1 Child’s size and weight at birth Percent distribution of live births in the 5 years before the survey by mother’s estimate of baby’s size at birth, percentage of live births in the 5 years before the survey that have a reported birth weight, and among live births in the 5 years before the survey with a reported birth weight, percentage less than 2.5 kg, according to background characteristics, Ethiopia DHS 2016 Percent distribution of births by size of baby at birth Percentage of births that have a reported birth weight1 Number of births Among births with a reported birth weight1 Background characteristic Very small Smaller than average Average or larger Don’t know Total Percentage less than 2.5 kg Number of births Mother’s age at birth <20 16.3 14.5 68.5 0.7 100.0 14.1 1,301 16.9 183 20-34 15.6 9.5 74.0 0.9 100.0 14.5 8,090 12.9 1,171 35-49 17.5 9.1 72.9 0.5 100.0 9.0 1,632 10.8 147 Birth order 1 15.4 11.0 72.3 1.3 100.0 27.1 2,070 11.6 561 2-3 15.2 10.3 73.9 0.6 100.0 15.8 3,366 13.6 533 4-5 17.7 8.8 72.8 0.7 100.0 8.6 2,609 20.6 224 6+ 15.7 10.2 73.3 0.9 100.0 6.1 2,978 7.8 183 Mother’s smoking status Smokes cigarettes/tobacco 3.6 9.5 86.4 0.5 100.0 7.0 85 * 6 Does not smoke 16.1 10.0 73.1 0.8 100.0 13.7 10,938 13.2 1,496 Residence Urban 12.8 7.3 78.8 1.1 100.0 60.1 1,216 10.9 730 Rural 16.4 10.4 72.5 0.8 100.0 7.9 9,807 15.4 772 Region Tigray 13.9 10.5 74.0 1.7 100.0 29.3 716 7.6 210 Affar 39.1 13.4 47.2 0.4 100.0 5.7 114 (26.2) 7 Amhara 21.8 11.8 66.2 0.3 100.0 9.9 2,072 22.2 205 Oromiya 14.8 10.5 73.8 0.9 100.0 8.8 4,851 13.1 428 Somali 16.6 7.7 75.1 0.6 100.0 10.2 508 11.1 52 Benishangul-Gumuz 7.7 9.6 79.1 3.6 100.0 21.2 122 9.9 26 SNNPR 13.4 8.1 77.6 0.9 100.0 13.9 2,296 13.1 319 Gambela 12.6 8.0 77.8 1.6 100.0 32.1 27 11.9 9 Harari 20.3 3.8 75.2 0.7 100.0 36.9 26 4.4 10 Addis Ababa 10.7 7.4 81.1 0.9 100.0 89.2 244 11.5 218 Dire Dawa 20.5 8.0 69.2 2.3 100.0 43.6 47 9.2 20 Mother’s education No education 17.4 11.0 70.8 0.8 100.0 5.9 7,284 18.3 433 Primary 13.5 8.2 77.4 0.9 100.0 19.4 2,951 11.0 571 Secondary 11.9 7.7 79.7 0.6 100.0 52.1 514 7.7 268 More than secondary 12.4 8.5 78.8 0.3 100.0 83.7 274 15.4 230 Wealth quintile Lowest 18.2 12.6 68.3 0.9 100.0 3.9 2,636 11.3 104 Second 17.3 10.2 71.3 1.1 100.0 6.1 2,520 18.7 155 Middle 16.0 10.2 73.2 0.6 100.0 9.2 2,280 17.3 209 Fourth 13.4 8.8 77.3 0.5 100.0 12.1 1,999 15.7 242 Highest 13.3 6.7 78.9 1.1 100.0 49.9 1,588 10.5 792 Total 16.0 10.0 73.2 0.8 100.0 13.6 11,023 13.2 1,502 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 Based on either a written record or the mother’s recall. Child Health • 171 Table 10.2 Vaccinations by source of information Percentage of children age 12-23 months and children age 24-35 months who received specific vaccines at any time before the survey, by source of information (vaccination card, health facility, or mother’s report), and percentage who received specific vaccines by the appropriate age, Ethiopia DHS 2016 Children age 12-23 months Children age 24-35 months Vaccinated at any time before the survey according to: Vaccinated by appro- priate age2,3 Vaccinated at any time before the survey according to: Vaccinated by appro- priate age2,3 Vaccine Vaccination card1 Health facility Mother’s report Any source Vaccination card1 Health facility Mother’s report Any source BCG 29.4 22.0 17.7 69.2 67.9 16.4 24.0 27.6 67.9 62.9 DPT-HepB-Hib 1 33.7 23.1 16.4 73.2 56.7 17.1 24.1 26.0 67.1 44.8 2 30.7 22.4 12.0 65.1 45.2 15.4 22.8 18.5 56.7 34.2 3 26.4 21.3 5.5 53.2 32.2 14.9 21.2 8.8 44.9 23.5 Polio 1 33.5 23.3 23.8 80.6 79.1 17.0 24.1 36.4 77.6 73.0 2 30.5 22.8 18.5 71.7 69.9 15.4 22.9 31.3 69.6 64.9 3 25.9 22.2 8.3 56.4 54.4 14.0 21.8 15.8 51.6 46.7 Pneumococcal (PCV) 1 31.2 22.8 13.0 67.0 65.8 15.2 22.5 21.3 58.9 56.2 2 28.1 21.5 10.8 60.5 59.2 14.0 21.1 15.3 50.4 47.5 3 24.0 19.9 5.3 49.1 47.6 13.2 17.8 7.7 38.8 35.3 Rotavirus (RV) 1 30.2 21.3 12.5 64.0 62.5 11.1 17.8 21.6 50.4 46.9 2 26.7 19.6 9.7 56.0 54.1 10.0 16.3 17.8 44.1 40.1 Measles 21.5 20.5 12.4 54.3 47.4 12.5 22.2 20.0 54.6 41.8 All basic vaccinations4 18.6 18.4 1.5 38.5 22.3 11.5 19.8 3.5 34.8 16.5 All age appropriate vaccinations5 16.8 15.5 1.0 33.3 19.4 6.8 12.8 2.5 22.1 12.0 No vaccinations 0.1 0.0 15.7 15.9 na 0.0 0.0 18.7 18.8 na Number of children 684 468 852 2,004 2,004 335 477 1,132 1,944 1,944 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 BCG, three doses of DPT-HepB-Hib, three doses of oral polio vaccine (excluding polio vaccine given at birth), and one dose of measles. 5 BCG, three doses of DPT-HepB-Hib, three doses of oral polio vaccine (excluding polio vaccine given at birth), three doses of pneumococcal vaccine, two doses of rotavirus vaccine, and one dose of measles. 172 • Child Health Table 10.3 Vaccinations by background characteristics Percentage of children age 12-23 months and children age 24-35 months who received specific vaccines at any time before the survey (according to a vaccination card, health facility, or the mother’s report), percentage with all basic vaccinations, and percentage with all age appropriate vaccinations, according to background characteristics, Ethiopia DHS 2016 Background characteristic BCG DPT-HepB-Hib Polio1 Pneumococcal (PCV) Rotavirus (RV) Measles All basic vaccina- tions2 All age appropriate vaccina- tions3 No vaccina- tions Number of children 1 2 3 1 2 3 1 2 3 1 2 Sex Male 68.9 73.5 63.3 52.9 79.5 71.2 56.5 64.1 58.8 48.6 62.4 54.5 52.7 36.5 31.6 16.0 926 Female 69.4 73.0 66.6 53.3 81.5 72.2 56.3 69.5 62.0 49.6 65.4 57.2 55.8 40.3 34.7 15.7 1,078 Birth order 1 71.7 73.7 69.5 59.6 81.1 73.0 60.6 71.9 66.7 55.3 68.7 64.9 59.4 47.1 43.1 13.4 374 2-3 73.5 78.2 71.1 58.3 85.2 76.3 61.7 72.8 66.5 52.8 66.9 58.5 57.3 42.5 36.6 12.8 611 4-5 68.2 76.9 66.0 54.0 83.7 72.7 56.4 67.8 58.4 48.2 66.5 53.4 56.1 37.7 30.2 12.00 453 6+ 63.5 64.6 54.8 42.7 72.7 65.3 47.9 56.9 51.7 41.7 55.9 49.4 46.3 29.3 25.7 23.9 566 Residence Urban 88.8 91.1 87.8 79.5 92.7 87.1 79.5 81.4 78.6 72.9 82.1 79.1 76.0 64.6 60.9 3.8 232 Rural 66.6 70.9 62.1 49.7 79.0 69.7 53.4 65.1 58.1 46.0 61.7 52.9 51.5 35.1 29.7 17.4 1,772 Region Tigray 88.1 92.3 90.1 81.4 92.3 86.9 79.3 90.6 87.9 77.7 84.0 79.8 80.1 67.3 62.1 4.7 152 Affar 43.5 47.1 26.8 20.1 68.5 53.5 36.4 38.3 24.3 17.5 32.5 23.3 30.1 15.2 12.4 28.2 20 Amhara 75.2 80.8 75.2 63.8 87.0 81.1 66.1 75.9 68.9 60.5 68.2 59.1 61.9 45.8 39.9 8.3 364 Oromiya 59.7 64.8 53.5 39.9 74.3 61.6 43.4 58.8 51.5 38.3 58.2 50.2 43.2 24.7 24.3 21.4 881 Somali 55.9 61.6 47.6 36.3 77.4 64.7 43.8 55.1 42.8 34.9 53.6 41.3 48.1 21.8 19.9 19.6 76 Benishangul-Gumuz 76.8 81.9 81.4 76.2 85.6 79.1 70.5 77.8 77.8 71.0 78.8 76.6 70.8 57.4 51.6 13.4 21 SNNPR 76.2 76.7 70.9 59.0 82.2 77.4 63.6 66.9 61.6 48.6 63.7 54.7 57.6 46.9 31.7 15.9 419 Gambela 69.9 73.1 67.3 54.8 78.9 73.8 57.6 65.4 60.2 46.1 65.8 60.5 62.1 41.1 36.5 16.3 5 Harari 77.0 78.8 66.8 58.7 96.4 88.8 79.3 80.5 67.6 58.6 71.7 61.3 53.6 42.2 40.4 2.8 5 Addis Ababa 94.6 97.5 96.8 95.7 96.8 96.8 96.8 93.9 93.2 91.4 93.5 91.7 93.1 89.2 81.6 1.5 52 Dire Dawa 96.8 98.2 92.8 84.9 98.2 92.8 82.1 89.9 85.1 75.3 92.3 85.3 86.9 75.9 65.5 1.5 9 Mother’s education No education 64.3 68.4 58.4 45.3 77.5 67.2 49.5 61.6 53.8 42.4 58.0 49.6 49.0 30.7 26.1 18.9 1,257 Primary 74.3 79.6 73.6 62.3 84.4 77.5 65.0 74.1 69.1 57.1 72.2 62.7 58.7 46.1 39.4 12.1 577 Secondary 84.1 86.6 84.3 80.3 90.7 88.4 78.2 81.3 80.7 70.0 79.5 79.1 78.3 69.6 61.1 6.5 103 More than secondary 93.6 87.7 87.5 79.0 88.5 81.8 78.6 85.2 80.4 74.3 82.1 81.5 79.6 71.8 71.5 5.3 68 Wealth quintile Lowest 57.7 62.3 53.0 36.4 72.4 61.4 43.4 57.4 49.7 36.0 53.2 43.6 43.2 22.2 19.2 24.7 504 Second 65.2 71.8 60.6 50.4 78.7 69.2 53.8 64.0 55.7 48.9 58.2 50.7 49.9 38.1 31.0 17.2 396 Middle 69.4 70.2 61.1 51.4 81.3 71.8 56.0 64.6 58.4 44.2 63.3 53.0 54.4 36.7 29.9 13.3 450 Fourth 77.4 83.2 77.0 63.2 86.6 79.0 62.4 77.9 71.0 56.0 72.8 64.6 58.6 44.6 39.7 11.3 366 Highest 83.9 86.4 83.2 76.3 88.4 84.1 75.8 77.9 76.0 71.3 81.1 78.6 74.3 63.0 58.3 8.4 288 Total 69.2 73.2 65.1 53.2 80.6 71.7 56.4 67.0 60.5 49.1 64.0 56.0 54.3 38.5 33.3 15.9 2,004 Note: Children are considered to have received the vaccine if it was either written on the child’s vaccination card, child’s information found in the health facility, or reported by the mother. 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. BCG = Bacille Calmette-Guérin. DPT = Diphtheria-pertussis-tetanus. HepB = Hepatitis B. Hib = Haemophilus influenzae type b. 1 Polio 0 is the polio vaccination given at birth. 2 BCG, three doses of [DPT-HepB-Hib], three doses of oral polio vaccine (excluding polio vaccine given at birth), and one dose of measles. 3 BCG, hepatitis B (birth dose), three doses of DPT-HepB-Hib], three doses of oral polio vaccine (excluding polio vaccine given at birth), three doses of pneumococcal vaccine, two doses of rotavirus vaccine, and one dose of measles. Child Health • 173 Table 10.4 Possession and observation of vaccination cards, according to background characteristics Percentage of children age 12-23 months and children age 24-35 months who ever had a vaccination card, and percentage with a vaccination card seen, according to background characteristics, Ethiopia DHS 2016 Children age 12-23 months Children age 24-35 months Background characteristic Percentage who ever had a vaccination card1 Percentage with a vaccination card seen1 Number of children Percentage who ever had a vaccination card1 Percentage with a vaccination card seen1 Number of children Sex Male 45.7 30.9 926 35.1 17.7 1,048 Female 45.3 36.9 1,078 34.5 16.7 895 Birth order 1 48.4 35.0 374 45.7 28.2 392 2-3 51.2 42.1 611 40.6 19.9 587 4-5 47.4 35.6 453 28.1 13.3 459 6+ 35.9 23.7 566 25.9 9.2 506 Residence Urban 77.2 67.3 232 71.5 57.4 201 Rural 41.3 29.8 1,772 30.6 12.6 1,742 Region Tigray 65.4 58.3 152 53.9 45.4 128 Affar 24.2 16.7 20 18.8 12.0 22 Amhara 50.3 44.5 364 36.7 18.4 354 Oromiya 39.7 25.9 881 29.6 9.2 858 Somali 35.6 21.0 76 22.3 8.5 100 Benishangul-Gumuz 51.5 41.4 21 40.8 23.4 22 SNNPR 42.3 28.8 419 34.7 18.1 400 Gambela 55.8 41.4 5 55.7 24.3 4 Harari 56.0 44.9 5 44.9 28.8 5 Addis Ababa 93.3 90.3 52 91.9 86.9 43 Dire Dawa 60.9 53.7 9 66.3 48.7 8 Mother’s education No education 40.4 28.8 1,257 28.0 11.2 1,275 Primary 49.7 38.8 577 42.1 21.0 535 Secondary 64.3 57.0 103 60.3 45.3 80 More than secondary 75.3 59.1 68 86.4 83.0 53 Wealth quintile Lowest 30.1 17.3 504 24.2 8.2 501 Second 40.2 32.8 396 33.9 9.8 477 Middle 47.7 28.8 450 29.2 13.8 371 Fourth 50.0 44.8 366 32.1 15.0 315 Highest 70.5 60.3 288 66.2 53.2 280 Total 45.5 34.1 2,004 34.8 17.2 1,944 1 Vaccination card, booklet, or other home-based record. 174 • Child Health Table 10.5 Observation of vaccination history at health facilities: Children 0-35 months Percentage of children age 0-35 months who did not have a vaccination card seen during home visit; and among children age 0-35 months without vaccination card seen during home visit; percentage of children who received at least one vaccination at a health facility; percentage of children with mother’s consent for visiting health facilities, percentage of children with vaccination history searched at health facilities, and percentage of children with vaccination history found and seen by interviewer at health facilities, according to background characteristics, Ethiopia DHS 2016 Percentage of children who did not have vaccination card during home visit Number of children Among children age 0-35 months who did not have vaccination card during home visit Background characteristic Percentage of children who received at least one vaccination at a health facility Percentage of children with mother’s consent for visiting health facilities Percentage of children with vaccination history searched at health facilities Percentage of children with vaccination history found and seen by interviewer Number of children Age in months <6 69.5 1,200 27.3 23.2 22.2 16.9 834 6-11 58.2 1,071 45.1 37.0 36.8 31.6 624 12-23 65.9 2,004 52.3 47.1 46.1 35.4 1,320 24-35 82.8 1,944 50.3 45.0 44.6 29.6 1,608 Sex Male 72.2 3,076 47.6 41.1 40.2 29.6 2,221 Female 68.9 3,143 44.0 39.6 39.1 28.8 2,166 Birth order 1 63.6 1,283 48.9 44.5 43.7 32.0 816 2-3 64.6 1,889 50.5 45.1 44.3 33.0 1,220 4-5 72.9 1,387 41.6 38.0 37.6 27.1 1,012 6+ 80.6 1,659 42.8 35.3 34.5 25.7 1,338 Residence Urban 33.0 719 57.4 51.5 50.3 39.5 237 Rural 75.4 5,500 45.2 39.7 39.0 28.7 4,149 Region Tigray 43.9 439 78.8 78.5 78.5 61.1 193 Affar 83.0 63 12.6 8.9 8.5 5.9 52 Amhara 64.8 1,139 58.5 53.6 53.3 40.0 738 Oromiya 79.7 2,760 33.4 26.4 26.1 18.2 2,201 Somali 79.4 281 23.0 21.0 14.0 12.2 223 Benishangul-Gumuz 62.4 66 73.7 69.9 68.7 49.8 42 SNNPR 70.6 1,261 63.9 59.7 59.2 44.5 890 Gambela 59.7 15 56.6 51.2 41.2 21.0 9 Harari 56.4 15 35.6 32.6 31.7 22.5 8 Addis Ababa 11.5 153 (75.8) (71.7) (71.7) (51.9) 18 Dire Dawa 46.3 26 91.8 88.2 82.7 63.7 12 Mother’s education No education 77.4 3,854 40.8 35.6 34.7 25.5 2,983 Primary 65.3 1,849 55.8 49.6 49.4 36.3 1,207 Secondary 42.7 341 56.5 54.7 54.0 40.2 146 More than secondary 28.8 175 69.4 61.2 59.3 50.8 50 Wealth quintile Lowest 83.4 1,504 37.2 33.5 32.4 23.3 1,255 Second 78.3 1,401 46.7 40.4 39.9 28.9 1,097 Middle 74.2 1,278 46.6 39.1 38.4 28.6 949 Fourth 65.0 1,098 51.8 48.3 48.0 35.3 714 Highest 39.6 938 58.6 51.3 50.5 40.3 371 Total 70.5 6,219 45.8 40.4 39.6 29.2 4,386 Note: Figures in parentheses are based on 25-49 unweighted cases. Child Health • 175 Table 10.6 Observation of vaccination history at health facilities: Children 12-35 months Percentage of children age 12-35 months who did not have a vaccination card seen during home visit; and among children age 12-35 months without vaccination card seen during home visit, percentage of children who received at least one vaccination at a health facility; percentage of children with mother’s consent for visiting health facilities, percentage of children with vaccination history searched at health facilities, and percentage of children with vaccination history found and seen by interviewer at health facilities, according to background characteristics, Ethiopia DHS 2016 Percentage of children who did not have vaccination card during home visit1 Number of children Among children age 12-35 months who did not have vaccination card during home visit: Background characteristic Percentage of children who received at least one vaccination at a health facility Percentage of children with mother’s consent for visiting health facilities Percentage of children with vaccination history searched at health facilities Percentage of children with vaccination history found and seen by interviewer Number of children Age in months 12-23 65.9 2,004 52.3 47.1 46.1 35.4 1,320 24-35 82.8 1,944 50.3 45.0 44.6 29.6 1,608 Sex Male 76.1 1,975 53.4 46.9 45.9 32.7 1,503 Female 72.2 1,973 49.0 45.0 44.5 31.8 1,425 Birth order 1 68.5 766 60.2 54.7 53.5 39.0 525 2-3 68.7 1,197 55.4 50.7 49.8 35.0 823 4-5 75.6 912 46.5 41.9 41.3 28.9 689 6+ 83.1 1,072 45.8 39.6 39.2 28.3 891 Residence Urban 37.3 433 62.0 55.3 53.6 40.1 162 Rural 78.7 3,514 50.6 45.4 44.7 31.8 2,767 Region Tigray 47.6 279 87.5 87.5 87.5 70.3 133 Affar 85.7 42 13.8 9.8 9.3 6.7 36 Amhara 68.4 718 62.8 57.4 57.0 39.3 491 Oromiya 82.3 1,739 38.2 31.0 30.8 21.3 1,431 Somali 86.1 176 26.6 25.4 17.0 15.2 151 Benishangul-Gumuz 67.8 43 78.4 75.5 73.8 49.7 29 SNNPR 76.4 818 70.2 66.9 66.6 47.7 625 Gambela 66.5 10 60.1 56.2 46.6 22.6 6 Harari 62.8 10 40.7 37.9 36.8 25.8 6 Addis Ababa 11.2 95 * * * * 11 Dire Dawa 48.7 18 91.4 87.3 83.2 66.3 9 Mother’s education No education 80.1 2,532 45.2 39.8 38.8 27.3 2,028 Primary 69.7 1,112 64.0 58.9 58.8 42.6 775 Secondary 48.1 183 68.7 68.1 67.5 47.6 88 More than secondary 30.4 121 72.8 61.5 59.4 50.5 37 Wealth quintile Lowest 87.2 1,006 42.6 38.7 37.4 26.5 877 Second 79.8 873 52.0 45.6 45.4 30.6 696 Middle 78.0 820 50.3 43.5 42.9 31.2 640 Fourth 68.9 681 59.8 56.7 56.2 40.4 470 Highest 43.2 568 66.0 58.8 57.7 44.7 245 Total 74.2 3,947 51.2 46.0 45.2 32.3 2,928 Note: An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. 176 • Child Health Table 10.7 Outcome of health facilities visit Among children age 12-35 months with no vaccination card seen during home visit and whose information was searched at health facilities, percentage with vaccination history found and seen by interviewer, percentage of children with other vaccination records located at health facilities, but record for specific children not found, and percentage with no vaccination records located at health facilities, according to background characteristics, Ethiopia DHS 2016 Among children age 12-35 months with vaccination history search at health facilities: Background characteristic Percentage of children with vaccination history found and seen by interviewer Percentage of children with other vaccination records located at health facilities, but record for specific children not found Percentage with no vaccination records located at health facilities Other Number of children with history searched at health facilities Age in months 12-23 76.9 10.9 11.2 1.0 608 24-35 66.5 14.1 19.3 0.1 717 Sex Male 71.3 12.1 15.7 0.9 690 Female 71.3 13.2 15.5 0.0 634 Birth order 1 73.0 8.0 18.4 0.7 281 2-3 70.3 13.4 15.3 1.1 410 4-5 69.8 14.9 15.3 0.0 285 6+ 72.4 13.6 14.0 0.0 349 Residence Urban 74.8 6.9 17.7 0.5 87 Rural 71.1 13.0 15.4 0.5 1,238 Region Tigray 80.3 1.2 18.5 0.0 116 Affar (72.1) (0.0) (25.5) (2.4) 3 Amhara 69.0 5.0 25.3 0.7 280 Oromiya 69.1 15.9 14.2 0.9 441 Somali 89.1 6.4 3.7 0.8 26 Benishangul-Gumuz 67.4 27.7 3.7 1.3 21 SNNPR 71.6 17.0 11.4 0.0 417 Gambela 48.6 36.2 14.3 0.9 3 Harari 70.0 22.1 7.8 0.0 2 Addis Ababa * * * * 8 Dire Dawa 79.6 18.5 0.0 1.8 7 Mother’s education No education 70.3 14.6 14.5 0.5 788 Primary 72.5 9.7 17.3 0.5 456 Secondary 70.6 11.5 17.8 0.2 59 More than secondary (84.9) (3.4) (11.7) (0.0) 22 Wealth quintile Lowest 70.9 12.7 16.3 0.0 328 Second 67.3 11.7 20.4 0.6 316 Middle 72.7 14.0 11.9 1.4 275 Fourth 71.9 14.7 13.4 0.1 264 Highest 77.5 8.0 14.3 0.2 142 Total 71.3 12.6 15.6 0.5 1,325 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. Child Health • 177 Table 10.8 Prevalence and treatment of symptoms of ARI Among children under age 5, percentage who had symptoms of acute respiratory infection (ARI) in the 2 weeks before the survey; and among children with symptoms of ARI in the 2 weeks before the survey, percentage for whom advice or treatment was sought, according to background characteristics, Ethiopia DHS 2016 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 Percentage for whom treatment was sought same or next day Number of children Age in months <6 6.0 1,200 (33.5) (3.5) 72 6-11 8.9 1,071 43.1 0.7 95 12-23 9.1 2,004 33.7 3.2 183 24-35 5.9 1,944 27.0 2.3 114 36-47 6.7 2,007 22.5 4.8 135 48-59 4.2 2,191 30.5 3.7 91 Sex Male 6.5 5,342 34.1 2.7 349 Female 6.7 5,075 28.4 3.5 342 Cooking fuel Electricity or gas 3.5 350 * * 12 Kerosene (0.0) 7 * * 0 Charcoal 4.2 475 (39.3) (5.0) 20 Wood/straw3 7.0 8,964 30.9 3.0 631 Animal dung 4.4 614 * * 27 Other fuel * 7 * * 0 Residence Urban 4.1 1,163 59.1 4.8 48 Rural 6.9 9,254 29.2 3.0 643 Region Tigray 7.7 686 33.6 4.7 53 Affar 4.3 105 (44.3) (5.7) 4 Amhara 8.0 1,967 29.1 2.9 157 Oromiya 7.4 4,571 26.4 0.7 339 Somali 2.1 476 (32.2) (2.9) 10 Benishangul-Gumuz 1.8 113 * * 2 SNNPR 5.4 2,169 43.2 8.3 117 Gambela 3.5 25 * * 1 Harari 0.7 24 * * 0 Addis Ababa 2.7 236 * * 6 Dire Dawa 3.9 44 * * 2 Mother’s education No education 6.9 6,858 26.7 2.4 476 Primary 6.3 2,807 40.7 3.3 177 Secondary 5.3 493 * * 26 More than secondary 4.4 260 * * 11 Wealth quintile Lowest 5.3 2,499 25.0 3.1 133 Second 7.2 2,386 26.9 4.4 172 Middle 8.1 2,159 28.9 1.2 176 Fourth 7.9 1,860 41.0 3.5 147 Highest 4.1 1,513 40.2 3.6 63 Total 6.6 10,417 31.3 3.1 691 Note: Figures in parentheses are based on 25-49 unweighted cases. An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. 1 Symptoms of ARI include cough accompanied by short, rapid breathing that is chest-related and/or by difficult breathing that is chest-related. 2 Includes advice or treatment from the following sources: Public sector, private medical sector, NGO medical sector, shop, drug vendor, and market. Excludes advice or treatment from a traditional practitioner. 3 Includes grass, shrubs, and crop residues. 178 • Child Health Table 10.9 Source of advice or treatment for children with symptoms of ARI Percentage of children under age 5 with symptoms of ARI in the 2 weeks before the survey for whom advice or treatment was sought from specific sources; and among children under age 5 with symptoms of ARI in the 2 weeks before the survey for whom advice or treatment was sought, and the percentage for whom advice or treatment was sought from specific sources, Ethiopia DHS 2016 Percentage for whom advice or treatment was sought from each source: Source Among children with symptoms of ARI1 Among children with symptoms of ARI for whom advice or treatment was sought1 Any public sector source 24.6 76.0 Government hospital 1.2 3.7 Government health centre 20.7 64.0 Other public sector 2.7 8.4 NGO sector 0.4 1.1 Health facility 0.4 1.1 Any private sector source 5.0 15.5 Private hospital 0.1 0.2 Private clinic 4.8 14.8 Other private medical sector 0.2 0.6 Any other source 2.6 8.0 Shop 1.8 5.6 Traditional practitioner 0.8 2.3 Number of children 691 224 1 Symptoms of ARI include short, rapid breathing which was chest- related and/or by difficult breathing which was chest-related. Child Health • 179 Table 10.10 Prevalence and treatment of fever Among children under age 5, the percentage who had a fever in the 2 weeks before the survey and among children with fever in the 2 weeks before the survey, percentage for whom advice or treatment was sought, and percentage who received antibiotics as treatment, according to background characteristics, Ethiopia DHS 2016 Among children under age 5: Among children under age 5 with fever: Background characteristic Percentage with fever Number of children Percentage for whom advice or treatment was sought 1 Percentage for whom treatment was sought same or next day Percentage who took antibiotic drugs Number of children with fever Age in months <6 11.8 1,200 30.0 8.4 19.0 141 6-11 20.5 1,071 40.8 4.2 27.8 220 12-23 19.7 2,004 36.4 6.9 29.6 395 24-35 14.8 1,944 36.0 10.7 35.2 287 36-47 11.6 2,007 35.2 10.2 22.8 232 48-59 10.0 2,191 30.5 8.7 20.4 219 Sex Male 14.4 5,342 35.9 8.0 25.9 768 Female 14.3 5,075 34.7 8.3 28.1 727 Residence Urban 16.5 1,163 59.3 20.4 48.6 192 Rural 14.1 9,254 31.8 6.4 23.8 1,303 Region Tigray 23.8 686 34.1 7.9 20.2 163 Affar 16.8 105 41.3 9.0 28.3 18 Amhara 12.6 1,967 31.4 10.7 31.4 248 Oromiya 13.9 4,571 35.0 6.1 23.8 635 Somali 8.5 476 26.8 2.6 20.5 40 Benishangul-Gumuz 7.3 113 41.6 10.7 37.6 8 SNNPR 15.4 2,169 36.7 9.8 31.9 335 Gambela 15.1 25 45.0 15.5 23.6 4 Harari 9.6 24 53.8 15.5 27.0 2 Addis Ababa 14.9 236 62.5 16.6 42.4 35 Dire Dawa 13.2 44 51.2 12.5 41.2 6 Mother’s education No education 13.1 6,858 29.5 5.6 22.7 898 Primary 17.1 2,807 43.5 11.1 32.3 481 Secondary 15.9 493 39.9 15.9 32.7 78 More than secondary 14.3 260 (59.0) (16.1) (49.5) 37 Wealth quintile Lowest 12.5 2,499 23.8 5.7 15.3 313 Second 13.3 2,386 30.4 5.7 26.6 317 Middle 14.2 2,159 33.0 6.5 26.9 306 Fourth 17.3 1,860 42.3 10.0 27.4 322 Highest 15.7 1,513 50.5 14.4 42.6 237 Total 14.3 10,417 35.3 8.2 27.0 1,495 Note: Figures in parentheses are based on 25-49 unweighted cases. 1 Includes advice or treatment from the following sources: Public sector, private medical sector, NGO medical sector, shop, drug vendor, market. Excludes advice or treatment from a traditional practitioner. 180 • Child Health Table 10.11 Prevalence and treatment of diarrhoea Percentage of children under age 5 who had diarrhoea in the 2 weeks before the survey; among children with diarrhoea in the 2 weeks before the survey, percentage for whom advice or treatment was sought, according to background characteristics, Ethiopia DHS 2016 Percentage with diarrhoea Number of children Among children under age 5 with diarrhoea: Background characteristic Percentage for whom advice or treatment was sought1 Number of children with diarrhoea Age in months <6 7.6 1,200 (31.4) 92 6-11 22.5 1,071 52.4 241 12-23 17.8 2,004 52.7 357 24-35 12.9 1,944 37.4 250 36-47 9.1 2,007 40.6 183 48-59 4.8 2,191 (32.1) 105 Sex Male 12.1 5,342 40.9 649 Female 11.4 5,075 48.3 578 Source of drinking water2 Improved 12.1 5,863 48.4 709 Not improved 11.4 4,554 38.8 519 Toilet facility3 Improved sanitation 7.0 577 (56.9) 40 Unimproved sanitation 12.1 9,841 43.9 1,187 Shared facility4 13.1 486 48.0 64 Unimproved facility 12.3 5,527 43.2 680 Open defecation 11.6 3,827 44.5 444 Residence Urban 10.8 1,163 60.3 126 Rural 11.9 9,254 42.5 1,101 Region Tigray 13.0 686 50.7 89 Affar 11.5 105 53.0 12 Amhara 13.7 1,967 (40.0) 270 Oromiya 10.7 4,571 41.9 487 Somali 6.0 476 (44.7) 29 Benishangul-Gumuz 9.0 113 (61.3) 10 SNNPR 13.9 2,169 47.8 301 Gambela 14.5 25 58.7 4 Harari 10.8 24 (54.5) 3 Addis Ababa 7.4 236 * 18 Dire Dawa 12.1 44 (68.2) 5 Mother’s education No education 11.2 6,858 37.5 767 Primary 13.2 2,807 56.7 370 Secondary 14.7 493 (46.1) 72 More than secondary 7.3 260 (73.9) 19 Wealth quintile Lowest 10.2 2,499 40.1 254 Second 11.9 2,386 39.6 284 Middle 12.4 2,159 43.5 267 Fourth 13.6 1,860 44.0 253 Highest 11.2 1,513 60.6 169 Total 11.8 10,417 44.4 1,227 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 advice or treatment from the following sources: Public sector, private medical sector, NGO medical sector, shop, drug vendor, market. Excludes advice or treatment from a traditional practitioner. 2 See Table 2.1 for definition of categories. 3 See Table 2.2 for definition of categories. 4 Facilities that would be considered improved if they were not shared by two or more households. Child Health • 181 Table 10.12 Feeding practices during diarrhoea Percent distribution of children under age 5 who had diarrhoea in the 2 weeks before the survey by amount of liquids and food offered compared with normal practice, according to background characteristics, Ethiopia DHS 2016 Amount of liquids given Amount of food given Number of children with diarrhoea Background characteristic More Same as usual Somewhat less Much less None Don’t know/ missing Total More Same as usual Somewhat less Much less None Never gave food Don’t know/ missing Total Age in months <6 12.2 28.0 21.7 14.8 23.3 0.0 100.0 8.0 15.3 19.0 8.1 0.0 47.4 2.1 100.0 92 6-11 11.8 23.5 38.3 18.7 6.5 1.2 100.0 7.7 19.8 36.9 15.9 9.6 10.1 0.0 100.0 241 12-23 12.9 26.4 30.0 24.2 6.5 0.0 100.0 4.0 17.8 35.8 27.1 11.4 3.9 0.0 100.0 357 24-35 13.7 16.0 33.8 32.0 4.4 0.1 100.0 7.1 15.8 39.0 32.1 4.3 1.6 0.0 100.0 250 36-47 20.8 13.1 33.1 20.6 9.9 2.5 100.0 13.3 16.5 32.9 26.5 6.9 0.4 3.6 100.0 183 48-59 20.3 16.3 35.2 23.1 4.9 0.1 100.0 6.5 19.5 39.1 31.0 3.8 0.1 0.1 100.0 105 Sex Male 12.9 21.6 34.1 24.3 7.0 0.0 100.0 6.5 18.6 35.6 25.5 5.9 7.3 0.6 100.0 649 Female 16.5 20.3 31.2 22.3 8.4 1.3 100.0 8.1 16.4 34.8 23.9 9.1 6.8 0.9 100.0 578 Breastfeeding status Breastfeeding 13.5 24.0 32.3 21.1 8.8 0.4 100.0 7.8 18.1 34.5 20.5 7.8 10.9 0.3 100.0 784 Not breastfeeding 16.5 15.7 33.5 27.5 5.8 1.1 100.0 6.2 16.5 36.5 32.3 6.8 0.2 1.5 100.0 443 Residence Urban 17.1 32.9 23.0 20.7 6.2 0.0 100.0 8.8 24.2 27.2 27.4 10.3 2.0 0.2 100.0 126 Rural 14.3 19.6 33.8 23.7 7.8 0.7 100.0 7.1 16.8 36.2 24.5 7.1 7.6 0.8 100.0 1,101 Region Tigray 14.5 32.0 32.8 19.5 1.3 0.0 100.0 5.7 26.6 23.3 27.1 8.2 9.1 0.0 100.0 89 Affar 1.4 20.8 28.1 36.9 12.3 0.5 100.0 0.0 15.0 28.6 38.8 10.2 4.8 2.7 100.0 12 Amhara 25.7 32.2 20.5 12.6 9.0 0.0 100.0 9.2 23.2 27.2 13.3 16.5 10.4 0.0 100.0 270 Oromiya 12.6 12.1 34.9 28.8 10.3 1.2 100.0 8.8 12.3 33.4 31.0 6.8 6.3 1.3 100.0 487 Somali 6.7 19.8 41.5 26.3 5.7 0.0 100.0 2.3 14.1 34.8 39.5 3.2 6.2 0.0 100.0 29 Benishangul-Gumuz 25.2 22.1 32.9 14.4 2.9 2.5 100.0 19.6 33.0 32.9 9.0 2.0 2.6 1.0 100.0 10 SNNPR 7.5 21.2 40.5 25.5 4.7 0.5 100.0 3.7 17.7 49.1 23.0 1.0 5.1 0.6 100.0 301 Gambela 21.1 31.3 23.8 14.2 9.6 0.0 100.0 5.9 23.7 31.2 27.5 4.3 7.5 0.0 100.0 4 Harari 0.0 13.6 50.5 36.0 0.0 0.0 100.0 4.4 26.5 45.4 20.7 0.0 3.0 0.0 100.0 3 Addis Ababa (35.4) (38.8) (15.1) (8.0) (2.6) (0.0) 100.0 (9.1) (28.1) (40.0) (13.3) (2.6) (6.8) (0.0) 100.0 18 Dire Dawa 21.7 6.5 25.5 46.4 0.0 0.0 100.0 6.1 3.4 34.1 50.6 2.7 3.1 0.0 100.0 5 Mother’s education No education 15.1 18.4 33.7 23.8 7.9 1.0 100.0 7.5 17.8 34.8 24.5 6.9 7.3 1.1 100.0 767 Primary 13.9 22.0 29.7 26.0 8.4 0.0 100.0 6.5 16.7 37.1 27.2 6.7 5.7 0.0 100.0 370 Secondary 12.3 32.9 43.7 8.4 2.8 0.0 100.0 9.5 12.3 35.4 17.0 13.1 12.6 0.0 100.0 72 More than secondary (17.7) (58.9) (8.0) (13.0) (2.4) (0.0) 100.0 (3.2) (42.0) (17.4) (17.7) (18.9) (0.9) (0.0) 100.0 19 Wealth quintile Lowest 16.9 16.8 29.8 25.0 9.7 1.8 100.0 10.2 19.5 27.2 25.7 9.9 6.1 1.4 100.0 254 Second 13.1 23.8 38.2 20.4 4.6 0.0 100.0 5.9 20.4 43.9 18.8 3.0 8.1 0.0 100.0 284 Middle 12.9 19.1 36.0 19.8 12.1 0.0 100.0 5.3 18.2 37.3 21.4 9.3 8.5 0.1 100.0 267 Fourth 13.3 19.8 31.1 27.5 7.0 1.2 100.0 8.3 10.7 34.7 30.2 6.1 8.1 1.9 100.0 253 Highest 18.2 27.2 25.1 25.4 4.0 0.0 100.0 6.6 19.2 30.4 30.5 10.4 2.8 0.0 100.0 169 Total 14.6 21.0 32.7 23.4 7.7 0.6 100.0 7.2 17.6 35.3 24.8 7.4 7.1 0.7 100.0 1,227 Note: It is recommended that children should be given more liquids to drink during diarrhoea and food should not be reduced. Figures in parentheses are based on 25-49 unweighted cases. 182 • Child Health Table 10.13 Oral rehydration therapy, zinc, and other treatments for diarrhoea Among children under age 5 who had diarrhoea in the 2 weeks before the survey, percentage given fluid from an ORS packet or pre-packaged ORS fluid, recommended homemade fluids (RHF), ORS or RHF, zinc, ORS and zinc, ORS or increased fluids, oral rehydration therapy (ORT), continued feeding and ORT, and other treatments; and percentage given no treatment, according to background characteristics, Ethiopia DHS 2016 Percentage of children with diarrhoea who were given: Percentage given no treatment Number of children with diarrhoea Background characteristic Fluid from ORS packet (LEMLEM) or pre- packaged ORS fluid Recom- mended home fluids (RHF) Either ORS or RHF Zinc ORS and zinc ORS or increased fluids ORT (ORS, RHF, or increased fluids) Continued feeding and ORT1 Other treatments Anti-biotic drugs Anti-motility drugs Intravenous solution Home remedy/ other Age in months <6 5.8 5.8 6.2 23.4 5.5 18.0 18.3 15.4 4.4 1.4 0.0 6.3 60.2 92 6-11 31.7 23.2 43.2 34.0 19.3 37.5 47.6 30.1 11.6 2.9 0.7 14.4 35.9 241 12-23 36.6 23.2 46.2 41.6 22.2 44.4 52.8 29.7 10.6 2.7 0.0 9.5 29.6 357 24-35 26.1 16.3 33.5 31.5 16.7 36.2 42.8 26.0 10.4 0.9 0.0 8.8 41.5 250 36-47 31.4 14.4 38.3 29.1 13.1 42.1 48.9 31.0 5.3 0.0 0.0 7.0 39.3 183 48-59 26.2 15.0 36.6 23.6 7.6 42.9 50.8 35.5 8.7 2.4 0.0 4.0 37.2 105 Sex Male 30.2 19.4 38.0 30.9 17.3 38.7 45.9 29.9 9.7 2.6 0.0 8.3 38.1 649 Female 28.8 17.5 38.1 35.9 15.9 39.1 47.1 27.2 8.9 1.0 0.3 10.3 37.1 578 Residence Urban 40.5 25.0 52.9 50.8 24.2 49.7 58.7 35.6 12.3 4.0 0.0 11.5 22.8 126 Rural 28.3 17.7 36.3 31.3 15.8 37.7 45.0 27.9 9.0 1.6 0.2 9.0 39.3 1,101 Region Tigray 43.0 24.4 47.8 37.6 30.3 49.8 54.6 25.5 10.7 2.1 0.0 9.7 40.8 89 Affar 32.9 20.5 38.2 41.4 20.1 34.3 39.7 20.5 4.9 4.8 0.0 16.7 33.0 12 Amhara 28.4 13.5 35.5 28.0 15.4 44.6 48.1 26.8 8.6 2.5 0.0 14.1 41.6 270 Oromiya 22.5 17.5 32.0 33.7 11.3 31.9 41.4 26.8 7.8 0.5 0.0 5.8 37.8 487 Somali 44.2 23.3 51.2 33.4 26.1 46.2 53.2 26.1 17.4 1.3 0.0 14.2 37.1 29 Benishangul-Gumuz 55.3 16.8 58.0 47.9 35.3 64.7 65.2 58.8 7.9 0.0 0.0 8.8 23.7 10 SNNPR 33.3 20.5 42.8 34.6 19.8 38.7 47.7 32.2 11.3 3.2 0.6 9.3 35.1 301 Gambela 39.7 15.4 42.4 38.0 21.6 48.6 51.3 25.9 19.5 0.2 0.0 10.8 27.5 4 Harari 39.1 44.6 56.1 58.2 29.2 39.1 56.1 37.2 34.7 6.0 0.0 11.8 19.3 3 Addis Ababa (55.8) (39.1) (68.0) (35.0) (23.0) (65.3) (72.0) (55.1) (9.4) (5.4) (0.0) (15.3) (22.7) 18 Dire Dawa 51.1 35.0 60.9 53.3 36.3 56.5 65.2 29.8 5.1 3.5 0.0 8.1 17.9 5 Mother’s education No education 27.9 13.8 33.5 26.1 13.5 37.8 42.8 27.6 8.1 1.9 0.2 9.1 41.6 767 Primary 31.6 27.8 47.1 47.1 21.4 41.2 54.8 31.9 10.8 1.3 0.0 7.8 28.8 370 Secondary 31.7 20.5 35.3 33.8 19.7 36.2 39.8 21.1 10.9 0.0 0.0 13.3 46.1 72 More than secondary (48.0) (18.6) (53.8) (50.2) (37.7) (50.6) (53.8) (37.6) (22.9) (16.5) (0.0) (26.1) (20.1) 19 Wealth quintile Lowest 26.7 17.8 33.5 29.2 15.7 38.3 44.2 23.8 8.8 1.9 0.0 6.6 41.9 254 Second 27.7 15.9 36.3 27.1 11.2 35.9 44.5 34.2 8.2 2.7 0.0 8.0 36.5 284 Middle 32.4 16.9 39.9 30.5 18.1 39.5 46.9 28.5 8.8 1.7 0.0 9.2 41.5 267 Fourth 23.4 18.6 33.2 36.7 14.5 34.5 42.5 25.5 10.2 0.0 0.7 10.3 37.0 253 Highest 41.4 26.2 52.0 49.2 28.1 50.7 58.0 31.4 11.6 3.4 0.0 13.7 27.9 169 Total 29.5 18.5 38.0 33.3 16.6 38.9 46.4 28.7 9.3 1.8 0.1 9.2 37.6 1,227 Note: Figures in parentheses are based on 25-49 unweighted cases. ORS = Oral rehydration salts. 1 Continued feeding includes children who were given more, same as usual, or somewhat less food during the diarrhoea episode. Child Health • 183 Table 10.14 Source of advice or treatment for children with diarrhoea Percentage of children under age 5 with diarrhoea in the 2 weeks before the survey for whom advice or treatment was sought from specific sources; among children under age 5 with diarrhoea in the 2 weeks before the survey for whom advice or treatment was sought, percentage for whom advice or treatment was sought from specific sources; and among children with diarrhoea who received ORS, percentage for whom advice or treatment was sought from specific sources, Ethiopia DHS 2016 Percentage for whom advice or treatment was sought from each source: Source Among children with diarrhoea Among children with diarrhoea for whom advice or treatment was sought Among children with diarrhoea who received ORS1 Any public sector source 33.9 75.7 63.3 Government hospital 2.2 4.8 4.7 Government health centre 24.8 55.4 47.3 Other public sector 7.2 16.0 11.9 NGO sector 0.2 0.3 0.5 Health facility 0.2 0.3 0.5 Any private sector source 9.0 20.0 14.3 Private hospital 1.1 2.4 1.5 Private clinic 7.7 17.2 12.4 Any other source 2.2 4.9 1.1 Shop 1.7 3.7 1.1 Market 0.1 0.3 0.0 Other 0.4 0.9 0.0 Number of children 1,227 549 362 ORS = Oral rehydration salts 1 Fluid from ORS packet or pre-packaged ORS fluid. 184 • Child Health Table 10.15 Knowledge of ORS packets (LEMLEM) or pre- packaged liquids Percentage of women age 15-49 with a live birth in the 5 years before the survey who know about ORS packets or ORS pre- packaged liquids for treatment of diarrhoea, according to background characteristics, Ethiopia DHS 2016 Background characteristic Percentage of women who know about ORS packets called LEMLEM or ORS pre- packaged liquids Number of women Age 15-19 56.0 339 20-24 67.1 1,465 25-34 67.8 3,826 35-49 62.8 1,959 Residence Urban 89.7 969 Rural 62.3 6,621 Region Tigray 89.7 537 Affar 84.8 71 Amhara 63.0 1,632 Oromiya 59.6 3,129 Somali 85.1 269 Benishangul-Gumuz 84.3 81 SNNPR 63.6 1,601 Gambela 78.6 21 Harari 93.3 17 Addis Ababa 94.5 198 Dire Dawa 83.9 33 Education No education 60.3 4,791 Primary 70.5 2,150 Secondary 88.6 420 More than secondary 96.4 230 Wealth quintile Lowest 60.5 1,651 Second 58.5 1,654 Middle 61.7 1,588 Fourth 66.8 1,427 Highest 86.4 1,269 Total 65.8 7,590 ORS = Oral rehydration salts. Child Health • 185 Table 10.16 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, Ethiopia DHS 2016 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 0.1 31.7 5.1 4.7 8.6 24.0 25.8 100.0 36.9 388 2-3 0.4 26.4 4.0 2.6 15.4 22.5 28.7 100.0 30.8 379 4-5 0.0 31.3 2.4 3.6 13.9 22.2 26.6 100.0 33.7 418 6-8 0.6 35.8 1.0 2.9 19.9 28.5 11.3 100.0 37.5 561 9-11 0.1 46.8 2.4 3.7 21.2 18.8 7.0 100.0 49.3 499 12-17 0.8 37.2 2.9 3.5 21.2 29.4 5.1 100.0 40.9 1,085 18-23 1.9 37.6 2.9 4.8 19.7 26.1 6.9 100.0 42.5 816 6-23 1.0 38.7 2.4 3.8 20.6 26.5 7.1 100.0 42.1 2,960 Toilet facility2 Improved sanitation 1.6 47.6 0.3 2.6 20.1 17.4 10.3 100.0 49.5 217 Unimproved sanitation 0.7 35.5 3.0 3.8 18.2 25.9 12.9 100.0 39.2 3,928 Shared facility3 1.1 53.6 2.0 2.4 27.7 6.3 6.9 100.0 56.7 214 Unimproved facility 1.0 50.2 3.1 4.5 13.2 16.9 11.1 100.0 54.3 2,217 Open defecation 0.2 11.2 2.9 2.9 24.3 42.0 16.5 100.0 14.3 1,497 Residence Urban 1.5 58.1 1.6 3.7 23.8 4.0 7.3 100.0 61.2 498 Rural 0.6 33.2 3.0 3.7 17.6 28.4 13.5 100.0 36.8 3,647 Region Tigray 1.7 27.4 5.7 4.2 26.9 21.7 12.5 100.0 34.7 304 Affar 0.6 23.9 5.9 8.9 22.3 19.9 18.4 100.0 30.4 40 Amhara 0.9 33.5 4.3 2.4 20.7 16.8 21.4 100.0 38.7 761 Oromiya 0.4 28.4 2.5 4.0 16.1 38.9 9.8 100.0 31.3 1,848 Somali 0.5 24.0 4.9 2.9 42.1 20.6 5.0 100.0 29.4 170 Benishangul-Gumuz 0.6 48.5 4.7 1.9 22.7 12.9 8.7 100.0 53.8 44 SNNPR 0.9 59.9 0.9 3.9 9.4 10.4 14.6 100.0 61.7 836 Gambela 0.7 32.7 3.7 1.7 24.3 20.7 16.2 100.0 37.1 10 Harari 1.6 40.0 2.1 12.7 14.6 22.2 6.7 100.0 43.7 10 Addis Ababa 1.5 45.9 0.0 4.9 44.3 0.0 3.4 100.0 47.4 105 Dire Dawa 2.1 53.4 1.0 11.1 14.1 17.5 0.8 100.0 56.5 17 Mother’s education No education 0.3 31.8 3.2 3.9 18.2 29.4 13.2 100.0 35.3 2,500 Primary 1.4 40.4 2.3 3.4 17.2 22.5 12.7 100.0 44.1 1,279 Secondary 0.7 46.4 2.5 4.1 21.0 11.6 13.6 100.0 49.7 254 More than secondary 3.7 62.6 0.0 2.2 27.3 2.3 1.8 100.0 66.3 112 Wealth quintile Lowest 0.0 18.3 2.6 3.5 22.0 39.8 13.8 100.0 20.9 975 Second 1.3 28.5 4.2 2.4 17.1 33.0 13.6 100.0 33.9 905 Middle 0.6 39.3 3.2 3.9 17.2 22.1 13.7 100.0 43.0 867 Fourth 0.7 45.1 2.3 5.3 15.0 18.3 13.4 100.0 48.1 755 Highest 1.3 59.4 1.4 4.1 19.8 6.0 8.0 100.0 62.2 642 Total 0.7 36.2 2.8 3.7 18.3 25.5 12.8 100.0 39.7 4,145 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/rinsed into a toilet or latrine, or if it was buried. 2 See Table 2.3 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 • 187 NUTRITION OF CHILDREN AND ADULTS 11 Key Findings  Nutritional status of children: Thirty-eight percent of children under age 5 are stunted (short for their age); 10% are wasted (thin for their height); 24% are underweight (thin for their age), and 1% are overweight (heavy for their height).  Breastfeeding: Almost all children (97%) are breastfed at some point. However, only 58% of infants under age 6 months are exclusively breastfed.  Minimum acceptable diet: The feeding practices of only 7% of children age 6-23 months meet the minimum acceptable dietary standards. Only 14% of children had an adequately diverse diet.  Anaemia: More than half of children age 6-59 months (57%) and 24% of women age 15-49 are anaemic.  Salt iodisation: Eighty-nine percent of households use iodised salt for cooking.  Maternal nutrition: Twenty-two percent of women age 15-49 are thin (with BMI less than 18.5), while 8% are overweight or obese. n an effort to accelerate the reduction of undernutrition, the Government of Ethiopia developed the National Nutrition Strategy (FDRE 2008) and the National Nutrition Programmes (NNP). The second phase of NNP (NNP II), which covers the period from 2016 to 2020, addresses the multi-sectoral and multi-dimensional nature of nutrition, and guides policies, strategies, programmes, and partnerships that deliver evidence-based, cost-effective nutrition interventions (FDRE 2016c). Several additional initiatives embody the government’s commitment for improved nutrition. The Seqota Declaration (2015-2030) aims to eliminate all forms of malnutrition among children under age 2 by 2030 (FDRE 2015b). Nutrition is fully integrated in the Health Sector Transformation Plan (HSTP) (FDRE 2015a). In a broader context, nutrition indicators are included in the Growth and Transformation Plan (GTP), an economic development plan of the Government of Ethiopia (FDRE 2016a). This chapter focuses on the nutritional status of children and adults, and provides indicators that can be used in planning and monitoring national efforts to improve nutrition. The chapter describes the nutritional status of children under age 5, and infant and young child feeding practices, which include breastfeeding and feeding with solid/semisolid foods. The chapter also describes the diversity of foods and the frequency of feeding as well as micronutrient status, supplementation, and fortification. Relevant aspects of the nutritional status of women and men age 15-49 and 15-59 are also addressed. 11.1 NUTRITIONAL STATUS OF CHILDREN The anthropometric data on the height and weight collected in the 2016 EDHS permit the measurement and evaluation of the nutritional status of infants and young children using nutritional indices. This evaluation allows for the identification of subgroups of the child population that are at increased risk of faltered growth, impaired mental development, and death. I 188 • Nutrition of Children and Adults 11.1.1 Measurement of Nutritional Status among Young Children The 2016 EDHS collected data on the nutritional status of children by measuring the weight and height of children under age 5 in all sampled households, regardless of whether their mothers were interviewed in the survey. Weight was measured with an electronic mother-infant scale (SECA 878 flat) designed for mobile use. Height was measured with a measuring board (Shorr Board®). Children younger than age 24 months were measured lying down on the board (recumbent length), while standing height was measured for the older children. 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 index provides different information about growth and body composition for assessing nutritional status. As indicated below, stunting (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 (low weight-for-height) is a measure of acute undernutrition that 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. Thus, weight- for-age, which includes both acute (wasting) and chronic (stunting) undernutrition, is an indicator of overall undernutrition. Stunting (assessed via 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 that accounts for 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 children Children whose weight-for-height Z-score is more than two standard deviations (+2 SD) above the median of the reference population are considered overweight. Sample: Children under age 5 Nutrition of Children and Adults • 189 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 cut-off 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 A total of 10,752 children under age 5 were eligible for height and weight measurements. For some eligible children, however, complete or valid data were not obtained due to misclassifications or errors. In this report, height-for-age data are analysed based on 88% of eligible children with complete and credible measurement, weight-for-height on 89% of eligible children, and weight-for-age data on 90% of eligible children. 11.1.3 Levels of Child Malnutrition Table 11.1 shows that 38% of children under age 5 are stunted or too short for their age, and 18% severely stunted. Ten percent are wasted or too thin for their height, including 3% who are severely wasted. Twenty-four percent of children under age 5 are underweight or too thin for their age, with 7% severely underweight. The prevalence of overweight children remained low at 1%. Trends: Figure 11.1 shows the trend in the reduction of child undernutrition between 2000 and 2016. The prevalence of stunting has decreased considerably from 58% in 2000 to 38% in 2016, an average decline of more than 1 percentage point per year. On the other hand, the prevalence of wasting changed little over the same time period, with a wasting rate of 10% at the time of the EDHS 2016, which was the same level as in 2011. The prevalence of underweight has consistently decreased from 41% to 24% over the 16-year period. Patterns by background characteristics  Stunting for children under age 5 sharply increases between age 6 and 23 months, and peaks at age 24- 35 months; this represents the impact of undernutrition in the first 1,000 days of life.  Child malnutrition is associated with childbirth size and maternal malnutrition. Children who are smaller at birth are more likely to be stunted, wasted, or underweight than children who are normal or larger at birth. Likewise, children whose mothers are thin (with BMI less than 18.5) are more likely to be stunted, wasted, or underweight than children whose mothers have a normal BMI, or those children whose mothers are overweight or obese. Figure 11.1 Trends in nutritional status of children 58 51 44 38 12 12 10 10 41 33 29 24 2000 EDHS 2005 EDHS 2011 EDHS 2016 EDHS Percentage of children under age 5 who are malnourished Stunted Underweight Wasted 190 • Nutrition of Children and Adults  Stunting, underweight, and wasting prevalence is higher among children in rural areas than those in urban areas.  Amhara, Benishangul-Gumuz, Affar, and Dire Dawa are most highly affected by child stunting (41-46%) (Figure 11.2), whereas wasting imposes the heaviest burden in Somali, Affar, and Gambela, with rates of 23%, 18%, and 14%, respectively.  The proportions of children who are stunted and underweight decline with increasing mother’s education (Figure 11.3) and increasing household wealth. 11.2 INFANT AND YOUNG CHILD FEEDING PRACTICES Appropriate infant and young child feeding (IYCF) practices include exclusive breastfeeding in the first 6 months of life, continued breastfeeding through age 2, introduction of solid and semisolid foods at age 6 months, and gradual increases in the amount of food given and frequency of feeding as the child grows older. It is also important for young children to receive a diverse diet, which includes eating foods from different food groups that satisfy children’s growing micronutrient needs (WHO 2008). 11.2.1 Breastfeeding Initiation of Breastfeeding Early initiation of breastfeeding is important for both the mother and the child. The first breast milk contains colostrum, which is highly nutritious and has antibodies that protect the newborn from diseases. Early initiation of breastfeeding also encourages bonding between the mother and her newborn, and facilitates the production of regular breast milk. 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 initiated or regularly given in the first days) be discouraged. Early initiation of breastfeeding Initiation of breastfeeding within 1 hour of birth. Sample: Last born children who were born in the 2 years before the survey In 2016, the Ministry of Health (MoH) established the National Nutrition Programme II (NNP II) and the National Guideline on Adolescent, Maternal, Infant, and Young Child Nutrition (AMIYCN) (FDRE 2106b) to promote optimal feeding and care practices that follow international recommendations. Mothers are encouraged to breastfeed exclusively until the child is age 6 months without adding any water, other fluids or foods, and to continue breastfeeding until the child turns age 2. Figure 11.2 Stunting in children by region Figure 11.3 Stunting in children by mother’s education 15 24 27 32 37 39 39 40 41 43 46 Addis Ababa Gambela Somali Harari Oromiya SNNPR Tigray Dire Dawa Affar Benishangul-Gumuz Amhara Percentage of children under age 5 who are stunted 42 35 22 17 No education Primary Secondary More than secondary Percentage of children under age 5 who are stunted Nutrition of Children and Adults • 191 Table 11.2 shows that 97% of last-born children born in the 2 years before the survey were breastfed at some point. A little less than three-quarter (73%) were breastfed within 1 hour of birth, and nearly all infants (92%) were breastfed within 1 day of birth. Eight percent of children received prelacteal feeding. Trends: Seventy-three percent of children began breastfeeding within 1 hour of birth, and 92% within 1 day of birth, which are 22 and 12 percentage points higher than in 2011, respectively. The practice of prelacteal feeding, likewise, decreased from 29% in 2005 to 27% in 2011, and dropped further to 8% in 2016. Patterns by background characteristics  Only 61% of infants whose mothers have more than secondary education started breastfeeding within 1 hour of birth, compared with 73-74% infants whose mothers had lower education levels.  Infants in urban areas were more likely to receive prelacteal feeding than those in rural areas (12% and 7%, respectively).  Affar Region has the lowest level of early initiation of breastfeeding (42%) and the highest level of prelacteal feeding (41%).  Children born to mothers with more than secondary education were more likely to receive a prelacteal feeding (17%), compared with children of mothers with secondary education or lower (7-8%). Exclusive Breastfeeding Breast milk contains all the nutrients needed by children in the first 6 months of life and is an uncontaminated nutritional source. It is recommended that children be exclusively breastfed during the first 6 months of their life; this means that they should be given nothing but breast milk. Complementing breast milk before age 6 months is unnecessary and is discouraged because of the likelihood of contamination and the resulting high risk of diarrheal diseases. Early initiation of complementary feeding also reduces breast milk output because the production and release of breast milk is stimulated by the frequency and intensity of suckling. Overall, 58% of children under age 6 months are exclusively breastfed, and the percentage of exclusive breastfeeding declines with age from 74% in 0-1 months to 36% in 4-5 months (Table 11.3 and Figure 11.4). Contrary to the recommendation that children under the age of 6 months be exclusively breastfed, many infants are also fed with other liquids such as water (17%), non-milk liquids (5%), and other milks (5%) before reaching age 6 months (0-5 months). Moreover, 11% of infants begin complementary foods before 6 months of age, with more than one-fifth of children (21%) consuming complementary foods by age 4-5 months. Figure 11.4 Breastfeeding practices by age 0 20 40 60 80 100 <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 Percentage of children under age 2 Breastfeeding and receiving complementary foods Not breastfeeding Exclusive breastfeeding 192 • Nutrition of Children and Adults Among children under age 24 months, 67% are receiving age- appropriate breastfeeding. Sixty percent of children are introduced to solid, semi-solid, or soft foods at 6-8 months, which is an improvement since 2011 (49%). Continued breastfeeding is relatively long at 92% at age 1, while 76% continue breastfeeding until their second birthdays. Fourteen percent of children under age 2 are being fed by bottles with nipples (Figure 11.5). Trends: Exclusive breastfeeding among children under age 6 months has consistently increased from 49% in 2005 to 52% in 2011 and 58% in 2016. 11.2.2 Median Duration of Breastfeeding In Ethiopia, the median duration of breastfeeding is 23.9 months for children less than age 36 months. The median duration of exclusive breastfeeding, the time by which half of children have stopped exclusive breastfeeding, is 3.1 months. 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 5.5 months (Table 11.4). Patterns by background characteristics  On average, female children have a longer median duration (6.0 months) of predominant breastfeeding than male children (5.1 months).  The median duration of any breastfeeding is highest in Amhara (31.2 months) and Benishangul- Gumuz (28.4 months) and lowest in the Somali and Harari Regions (14.3 and 18.4 months, respectively).  In general, the median duration for any breastfeeding increases with the household wealth, from 22.4 months in the lowest quintile to 24.7 months in the highest quintile. 11.2.3 Complementary Feeding After the first 6 months, breast milk is no longer adequate to meet the nutritional needs of the infant, and complementary foods should be added to the child’s diet. The transition from exclusive breastfeeding to family foods is referred to as complementary feeding. This is the most critical period for children, because children are most vulnerable to malnutrition during this transition. Complementary feeding should be timely, which means that all infants should start receiving foods in addition to breast milk at age 6 months. Appropriate complementary feeding should include feeding children a variety of foods to ensure that nutritional requirements 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 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). Figure 11.5 IYCF indicators on breastfeeding status 14 67 60 76 92 79 36 58 Bottle feeding (0-23 months) Age-appropriate breastfeeding** (0-23 months) Introduction of solid, semisolid or soft foods (6-8 months) Continued breastfeeding at 2 years Continued breastfeeding at 1 year Predominant breastfeeding* (0-5 months) Exclusive breastfeeding at age 4-5 months Exclusive breastfeeding under age 6 months * Predominant breastfeeding includes exclusive breastfeeding, breastfeeding plus 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 breast milk and complementary foods Nutrition of Children and Adults • 193 In the 2016 EDHS, women who had at least one child living with them who was born in 2014 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 2014 or a later year were asked questions about the youngest child living with them. Table 11.5 indicates the types of foods and liquids children under 2 years of age living with the mother consumed during the day and night before the interview, by their age and breastfeeding status. Overall, the food items most commonly given to children were food made from grains, followed by fruits and vegetables rich in vitamin A, cheese, yogurt, or other milk products. Patterns by background characteristics  Except for infant formula and foods made from roots and tubers, the consumption of all types of foods is higher among non-breastfed children than among breastfed children of the same age group (age 6-23 months).  Fifty-six percent of breastfed children age 6-23 months and 63% of non-breastfed children age 6-23 months consumed food made from grains in the 24 hours before the survey.  Twenty-eight percent of breastfed children age 6-23 months and 32% of non-breastfed children age 6- 23 months received fruits and vegetables rich in vitamin A.  Children age 6-23 months are much less likely to consume meat, fish, and poultry than other food groups (8% for breastfeeding children and 14% for non-breastfeeding children). 11.2.4 Minimum Acceptable Diet The minimum acceptable diet (MAD) is a combination of the minimum dietary diversity (MDD) and minimum meal frequency (MMF). 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 is different for breastfed and non-breastfed children. The definition of the composite indicator of a MAD for all children age 6-23 months is shown below. Dietary diversity is a proxy for adequate micronutrient density of foods. Minimum dietary diversity assesses food intake among children age 6-23 months from at least four food groups. The cut-off of four food groups is associated with better-quality diets for both breastfed and non-breastfed children. Consumption of food from at least four food groups means that the child has a high likelihood of consuming at least one animal source of food and at least one fruit or vegetable in addition to a staple food (grains, roots, or tubers) (WHO 2008). The four food groups should come from a list of seven 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, a proxy for a child’s energy requirements, examines the number of times children received foods other than breastmilk. The minimum number is specific to the age and breastfeeding status of the child. 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. Non-breastfed 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. 194 • Nutrition of Children and Adults 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 Non-breastfed 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 Non-breastfed children age 6-23 months According to the EDHS results, the feeding practices of only 7% of children in Ethiopia age 6-23 months meet the minimum standards with respect to all three IYCF practices (breastfeeding status, number of food groups, and times they were fed during the day or night before the survey) (Table 11.6). Fourteen percent of children had an adequately diverse diet in which they had been given foods from the appropriate number of food groups, and 45% had been fed the minimum number of times appropriate for their age (Figure 11.6). Trends: The percentage of children fed according to the minimum acceptable diet standards shows only a small increase from 4% in 2011 to 7% in 2016. Patterns by background characteristics  The proportion fed according to the minimum acceptable dietary standards is somewhat lower among non-breastfed children (4%) than among breastfed children (8%). This is because only 40% of non- breastfed children are fed with milk or milk products as recommended.  Children in urban areas (19%) are more likely to fed according to the minimum acceptable dietary standards than those in rural areas (6%).  A significant regional variation exists in the proportion of children who receive the minimum acceptable diet, with the highest level of 27% in Addis Ababa and the lowest levels (2-3%) in Affar, Somali, and Amhara.  The likelihood that a child is receiving the minimum acceptable diet generally improves with the mother’s education level and household wealth. However, the proportions of children fed according to the minimum acceptable dietary standards are quite low even among children whose mothers have secondary education (15%) and children in the highest wealth quintile (16%). Figure 11.6 IYCF indicators on minimum acceptable diet (MAD) 13 45 8 20 49 4 14 45 7 Minimum dietary diversity (IYCF Indicator 5) Minimum meal frequency (IYCF Indicator 6) Minimum acceptable diet (IYCF Indicator 7) Percentage of children age 6-23 months Breastfed Nonbreastfed All children 6-23 months Nutrition of Children and Adults • 195 11.3 ANAEMIA PREVALENCE IN CHILDREN Anaemia in children Anaemia status Haemoglobin level in grams/decilitre* Anaemic <11.0 Mildly anaemic 10.0-10.9 Moderately anaemic 7.0-9.9 Severely anaemic <7.0 Not anaemic 11.0 or higher *Haemoglobin levels are adjusted for altitude in enumeration areas that are above 1,000 metres Sample: Children 6-59 months 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 for children because it can impair cognitive development, stunt growth, and increase morbidity from infectious diseases. In the EDHS, haemoglobin testing was performed for children age 6-59 months, using the methodology described in Chapter 1. The testing was successfully completed for 88% of eligible children. The prevalence of anaemia in children is presented in Table 11.7. In Ethiopia, 57% of children age 6-59 months suffered from some degree of anaemia (haemoglobin levels below 11 g/dl). Twenty-five percent of children are classified with mild anaemia, 29% with moderate anaemia, and 3% with severe anaemia. Trends: Between 2005 and 2016, the prevalence of anaemia among Ethiopian children declined from 54% to 44% from 2005 to 2011, but increased to 57% in 2016 (Figure 11.7). Patterns by background characteristics  The prevalence of anaemia decreases with the child’s age, ranging from a high of 78% among children age 6-8 months to a low of 40% among children age 48-59 months.  Children in rural areas (58%) are more likely to be anaemic than those in urban areas (49%). Figure 11.7 Trends in childhood anaemia 21 21 25 28 20 29 4 3 353 44 57 2005 EDHS 2011 EDHS 2016 EDHS Percentage of children age 6-59 months Moderate Mild Severe 196 • Nutrition of Children and Adults  The Somali Region has the highest level of childhood anaemia (83%), followed by Affar (75%) and Dire Dawa (72%); the Amhara Region has the lowest anaemia prevalence among children (42%) (Figure 11.8).  The prevalence of anaemia generally decreases with increasing mother’s education and household wealth. 11.4 MICRONUTRIENT INTAKE AND SUPPLEMENTATION AMONG 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. 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. In addition to questions on food consumption, the 2016 EDHS included questions to ascertain whether young children had received vitamin A supplements or deworming medication in the 6 months before the survey. Consumption of foods rich in vitamin A or iron remains low among young children in Ethiopia. Thirty- eight percent of children age 6-23 months consumed foods rich in vitamin A, and 22% consumed iron-rich foods during the 24 hours before the interview. Among children age 6-59 months, 9% were given iron supplements in the 7 days before the survey, 45% were given vitamin A supplements in the 6 months before the survey, and 13% were given deworming medication during the same period (Table 11.8). Although the deworming prevention programme guided by the Ministry of Health targets only children age 24-59 months, 8-10% of children age 6-23 months were reported to have received deworming medication. This indicates that these children may have received a deworming tablet as a treatment instead of prophylaxis. Thus, the results related to deworming medication should be interpreted with caution. Patterns by background characteristics  Intake of both vitamin A rich and iron rich foods increases with increasing age.  Among children age 6-23 months, considerable regional variation exists for vitamin A rich foods consumption in the 24 hours before the survey, ranging from 11% in Affar to 69% in Addis Ababa.  Children in urban areas (59%) are more likely to receive a vitamin A supplement in the 6 months before the survey than those in rural areas (43%).  Consumption of vitamin A and iron rich foods tends to increase with household wealth and maternal education. Figure 11.8 Anaemia in children by region 42 43 49 50 54 56 66 68 72 75 83 Amhara Benishangul-Gumuz Addis Ababa SNNPR Tigray Gambela Oromiya Harari Dire Dawa Affar Somali Percentage of children under age 5 who are anaemic Nutrition of Children and Adults • 197 11.5 PRESENCE OF IODISED SALT IN HOUSEHOLDS Iodine is an essential micronutrient, and iodised salt prevents goitre or other thyroid-related health problems among children and adults. In compliance with food and drug regulations, household salt should be fortified with iodine to at least 15 parts per million (ppm). The 2016 EDHS tested the presence of potassium iodate in household salt. Overall, salt was tested in 96% of households (Table 11.9). Among households in which salt was tested, 89% had iodised salt. Household salt was tested for the presence or absence of iodine only, and the iodine content in the salt was not measured. Trends: The coverage of iodised salt has greatly improved over the last 5 years from 15% (2011) to 89% (2016). Patterns by background characteristics  The use of iodised salt is relatively widespread in Ethiopia, and there are no large differences by residence, or household wealth.  The coverage of iodised salt is relatively homogenous across regions, except in Somali and Affar, where the levels were lowest at 63% and 74%, respectively. 11.6 ADULTS’ NUTRITIONAL STATUS 11.6.1 Nutritional Status of Women Chronic energy deficiency is caused by eating too little or having an unbalanced diet that lacks adequate nutrients. Women of reproductive age are especially vulnerable to chronic energy deficiency and malnutrition due to low dietary intake, inequitable distribution of food within the household, improper food storage and preparation, dietary taboos, infectious diseases, and inadequate care practices. It is well known that chronic energy deficiency leads to low productivity among adults and is related to heightened morbidity and mortality. In addition, chronic undernutrition among women is a major risk factor for adverse birth outcomes. The 2016 EDHS collected anthropometric data on height and weight for women age 15-49. These data were used to calculate several measures of nutritional status such as maternal height and body mass index (BMI). Body mass index (BMI) BMI is calculated by dividing weight in kilograms by height in metres squared (kg/m2). Status BMI Too thin for their height Less than 18.5 Normal Between 18.5 and 24.9 Overweight Between 25.0 and 29.9 Obese 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 15-49 198 • Nutrition of Children and Adults Two percent of women age 15-49 are of short stature (below 145cm). The women’s mean BMI is 20.7. Seventy percent of women have a normal BMI (between 18.5 and 24.9), 22% are thin, and 8% are overweight or obese (Table 11.10.1 and Figure 11.9). Trends: Undernutrition among women age 15-49, as measured by BMI less than 18.5, has declined over the last 16 years. The percentage of thin women dropped from 30% in 2000 to 22% in 2016. In contrast, the proportion of women who are overweight or obese, which is indicative of overnutrition, has increased during the same period. The proportion of women who are overweight or obese has increased from 3% in 2000 to 8% in 2016. Patterns by background characteristics  Adolescent girls age 15-19 (29%) are most likely to be thin (BMI below 18.5).  Rural areas have a higher percentage of thin women (25%) than urban areas (15%). Conversely, the percentage of overweight or obese women is higher in urban areas (21%) than in rural areas (4%).  Overweight/obesity increases with education and wealth. For example, women with more than secondary education are more than four times as likely to be overweight or obese than those with no education (22% and 5%, respectively). 11.6.2 Nutritional Status of Men Age 15-49 Years Anthropometric data were also collected on the height and weight for men age 15-49 interviewed in the survey. These data were used to calculate the BMI by using the same formula used for women. The mean BMI for men age 15-49 is 19.6. Sixty-four percent of men have a normal BMI (between 18.5 and 24.9), 33% are thin (BMI below 18.5), and 3% overweight or obese (BMI over 24.9) (Table 11.10.2 and Figure 11.9). Patterns by background characteristics  Adolescent boys (age 15-19) are most likely to be thin (59%). The rate decreases rapidly thereafter, reaching 23% for men age 40-49.  Chronic energy deficiency among men, as measured by BMI less than 18.5, is more prevalent in rural areas (34%) than in urban areas (26%); conversely, urban residents have a higher proportion of overweight or obese men (12%) than rural residents (1%).  The percentage of overweight or obese men tends to increase with education and wealth and is much more common among men in the highest wealth quintile (10 percent) than among men in lower quintiles (1% or less). Figure 11.9 Nutritional status of women and men 22 33 70 64 8 3 Women Men Percent distribution of women and men age 15-49 Overweight and obese Normal weight Thin Nutrition of Children and Adults • 199 11.7 ANAEMIA PREVALENCE IN ADULTS Haemoglobin levels below which women and men are considered anaemic Respondents Haemoglobin level in grams/ decilitre* Non-pregnant women age 15-49 Less than 11.0 Pregnant women age 15-49 Less than 12.0 Men age 15-49 Less than 13.0 *Haemoglobin levels are adjusted for cigarette smoking, and for altitude in enumeration areas that are above 1,000 metres Anaemia among women and men age 15-49 was measured with similar procedures used for children age 6- 59 months, except that capillary blood was collected exclusively from a finger prick. 11.7.1 Anaemia Prevalence in Women Table 11.11.1 shows that 24% percent of women in Ethiopia are anaemic. Eighteen percent of women are classified as mildly anaemic, 5% moderately anaemic, and 1% severely anaemic. Trends: In Ethiopia, anaemia prevalence among women age 15-49 declined from 27% in 2005 to 17% in 2011 but then increased to 24% in 2016; these data suggest that anaemia is a moderate public health problem (Figure 11.10). Increases were observed from 2011 to 2016 in all anaemia categories. Patterns by background characteristics  Anaemia is more prevalent among women who have had six or more births and among women who are using IUDs.  Anaemia varies by maternity status. Women who are pregnant or breastfeeding are more likely to be anaemic (29% for both groups) than those who are neither pregnant nor breastfeeding (21%).  Women living in rural areas are more likely to be anaemic (25%) than those living in urban areas (17%).  Women in the Somali and Affar Regions are most highly affected by anaemia, with rates of 60% and 45%, respectively.  The prevalence of anaemia decreases with increasing women’s education and household wealth. 11.7.2 Anaemia Prevalence in Men Fifteen percent of men age 15-49 are anaemic (Table 11.11.2). In many aspects, the patterns of anaemia prevalence among men are similar to those among women. Figure 11.10 Trends in anaemia status among women 17 13 18 8 3 5 1 1 1 27 17 24 2005 EDHS 2011 EDHS 2016 EDHS Percentage of women age 15-49 who are anaemic Moderate Mild Severe 200 • Nutrition of Children and Adults Patterns by background characteristics  Men living in rural areas are more likely to be anaemic (16%) than those living in urban areas (7%).  Similar to women, men from the Somali and Affar Regions are more affected by anaemia, with prevalence of 21 and 24 %, respectively.  The prevalence of anaemia decreases with increasing men’s education level and household wealth. 11.8 MICRONUTRIENT INTAKE AMONG MOTHERS During pregnancy, women are at a higher risk of anaemia due to an increase in blood volume. Severe anaemia can put both the mother and the baby in danger through increased risk of blood loss during labour, preterm delivery, low birth weight, and perinatal mortality. To prevent anaemia, pregnant women are advised to take iron folate supplements, eat iron-rich foods, and prevent intestinal worms. According to the findings from the 2016 EDHS, more than half of the women with a child born in the last 5 years (58%) did not take any iron tablets during their most recent pregnancy. Only 5% percent of women took iron tablets for 90 days or more during their most recent pregnancy, while only 6% of women took deworming medication (Table 11.12). Trends: The percentage of women taking iron supplementation for 90 days or more has improved from less than 1% in 2011 to 5% in 2016, but remains at a substandard level. The number of women who do not take any iron supplementation has decreased from 83% in 2011 to 58% in the current survey. Deworming during pregnancy did not show improvement during the last 5 years. Patterns by background characteristics  Women in urban areas were more likely than those in rural areas to have taken iron supplements during pregnancy for at least 90 days (10% versus 4%), and to have taken deworming tablets during pregnancy (8% versus 5%)  Women in Addis Ababa have the highest proportion of taking iron supplements for 90 days or more (18%), followed by the Tigray Region (16%). Conversely, women living in the Oromiya and Somali Regions have the lowest percentage (3% and 2%, respectively).  The proportion of women taking iron tablets for 90 days or more increases with increasing education level and household wealth. For instance, 17% of women with more than secondary education took iron tablets for 90 days or more, compared with 4% of women with no education.  The proportion of women taking both iron tablets (for 90 days or more) and deworming medication during pregnancy increases with household wealth. 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 before the interview  Table 11.6 Minimum acceptable diet  Table 11.7 Prevalence of anaemia in children  Table 11.8 Micronutrient intake among children Nutrition of Children and Adults • 201  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 20 2 • N ut rit io n of C hi ld re n an d A du lts Ta bl e 11 .1 N u tr iti o 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 a ge 5 c la ss ifi ed a s m al no ur is he d ac co rd in g to th re e an th ro po m et ric in di ce s of n ut rit io na l s ta tu s: h ei gh t- fo r- ag e, w ei gh t- fo r- he ig ht , a nd w ei gh t- fo r- ag e, a cc or di ng to b ac kg ro un d ch ar ac te ris tic s, E th io pi a 20 16 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 of 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 of 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 of ch ild re n A ge in m o nt hs <6 6. 6 16 .2 -0 .3 1, 10 8 5. 8 15 .4 9. 6 -0 .3 1, 07 7 5. 1 12 .3 2. 7 -0 .4 1, 15 8 6- 8 5. 3 15 .3 -0 .3 57 0 4. 9 15 .4 3. 9 -0 .6 57 2 3. 6 12 .7 1. 2 -0 .8 57 4 9- 11 8. 1 19 .4 -0 .7 50 0 3. 7 11 .0 3. 6 -0 .5 49 9 5. 0 17 .8 2. 0 -0 .8 51 1 12 -1 7 15 .0 34 .9 -1 .4 1, 12 8 3. 0 14 .7 3. 0 -0 .6 1, 14 2 7. 6 22 .6 0. 9 -1 .1 1, 15 2 18 -2 3 17 .6 47 .2 -1 .7 89 2 2. 3 10 .6 2. 7 -0 .5 89 6 9. 1 25 .3 0. 7 -1 .2 90 2 24 -3 5 21 .9 47 .8 -1 .8 1, 94 1 3. 0 8. 9 0. 9 -0 .4 1, 95 1 7. 9 25 .9 0. 6 -1 .3 1, 96 7 36 -4 7 22 .8 46 .4 -1 .8 2, 01 2 1. 8 6. 8 2. 3 -0 .3 2, 02 3 7. 6 25 .6 0. 7 -1 .3 2, 04 0 48 -5 9 21 .1 42 .2 -1 .7 2, 22 4 1. 9 6. 7 1. 2 -0 .5 2, 25 3 6. 7 29 .4 0. 3 -1 .4 2, 24 8 S ex M al e 19 .3 41 .3 -1 .5 5, 30 5 2. 9 10 .2 2. 9 -0 .5 5, 35 8 7. 6 25 .2 1. 0 -1 .2 5, 42 4 Fe m al e 15 .8 35 .3 -1 .3 5, 07 1 2. 9 9. 6 2. 7 -0 .4 5, 05 4 6. 2 21 .9 0. 9 -1 .1 5, 12 8 B ir th in te rv al in m on th s3 Fi rs t b irt h4 16 .5 36 .3 -1 .4 1, 77 0 2. 1 8. 8 3. 7 -0 .4 1, 76 8 5. 5 20 .9 0. 8 -1 .1 1, 80 2 <2 4 23 .0 45 .3 -1 .6 1, 51 1 3. 1 10 .5 2. 3 -0 .5 1, 51 4 8. 8 29 .2 0. 9 -1 .3 1, 53 7 24 -4 7 18 .3 38 .7 -1 .4 4, 26 6 3. 8 11 .2 2. 7 -0 .5 4, 29 4 7. 7 24 .9 0. 8 -1 .2 4, 33 7 48 + 12 .8 35 .4 -1 .4 2, 13 9 2. 1 8. 6 2. 6 -0 .4 2, 12 8 6. 1 20 .3 0. 9 -1 .1 2, 17 6 S iz e at b ir th 3 V er y sm al l 22 .5 45 .8 -1 .7 1, 53 6 3. 6 13 .2 1. 7 -0 .7 1, 52 9 12 .5 33 .6 0. 6 -1 .5 1, 56 1 S m al l 20 .6 43 .3 -1 .6 98 1 3. 9 12 .2 3. 0 -0 .7 97 8 9. 2 30 .7 0. 2 -1 .4 99 9 A ve ra ge o r la rg er 16 .0 36 .4 -1 .4 7, 10 6 2. 8 9. 2 3. 1 -0 .4 7, 13 4 5. 6 20 .8 1. 0 -1 .1 7, 22 9 M is si ng 18 .6 31 .5 -1 .4 63 0. 2 7. 9 0. 0 -0 .7 64 9. 6 20 .5 0. 0 -1 .4 63 M ot h er ’s in te rv ie w st at u s In te rv ie w ed 17 .5 38 .6 -1 .4 9, 68 6 3. 0 10 .1 2. 8 -0 .5 9, 70 4 7. 1 23 .8 0. 8 -1 .2 9, 85 2 N ot in te rv ie w ed b ut in h ou se ho ld 21 .3 33 .6 -1 .2 23 0 1. 3 8. 0 2. 9 -0 .3 22 5 5. 9 21 .9 4. 5 -0 .9 23 3 N ot in te rv ie w ed an d no t i n th e ho us eh ol d5 17 .8 36 .5 -1 .4 46 0 1. 6 7. 4 2. 8 -0 .2 48 3 4. 2 19 .4 1. 1 -1 .0 46 7 M ot h er ’s n ut ri ti o na l st at u s6 T hi n (B M I< 18 .5 ) 19 .3 41 .9 -1 .5 1, 74 1 4. 3 13 .1 1. 8 -0 .8 1, 73 3 9. 4 30 .5 0. 4 -1 .4 1, 74 8 N or m al ( B M I 1 8. 5- 24 .9 ) 17 .4 39 .1 -1 .5 5, 93 9 2. 4 9. 5 2. 4 -0 .4 5, 96 7 6. 4 23 .1 0. 7 -1 .2 6, 04 3 O ve rw ei gh t/o be se (B M I≥ 25 ) 9. 0 20 .3 -0 .7 46 9 1. 4 3. 9 3. 3 -0 .0 47 0 1. 7 9. 0 2. 6 -0 .4 47 4 (C on tin ue d… ) N ut rit io n of C hi ld re n an d A du lts • 2 03 T ab le 1 1. 1— C on tin ue 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 of 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 of 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 of ch ild re n R es id en ce U rb an 10 .6 25 .4 -1 .0 1, 13 1 2. 1 8. 7 3. 1 -0 .2 1, 13 0 4. 3 13 .4 2. 1 -0 .7 1, 14 0 R ur al 18 .4 39 .9 -1 .5 9, 24 5 3. 0 10 .1 2. 8 -0 .5 9, 28 3 7. 3 24 .8 0. 8 -1 .2 9, 41 2 R eg io n T ig ra y 13 .4 39 .3 -1 .5 69 1 3. 4 11 .1 1. 3 -0 .6 69 0 5. 2 23 .0 0. 3 -1 .3 69 9 A ffa r 22 .3 41 .1 -1 .6 98 5. 3 17 .7 0. 5 -1 .0 10 1 14 .4 36 .2 0. 5 -1 .6 10 0 A m ha ra 19 .6 46 .3 -1 .8 2, 08 7 2. 2 9. 8 1. 3 -0 .6 2, 07 9 8. 3 28 .4 0. 3 -1 .4 2, 10 7 O ro m iy a 17 .1 36 .5 -1 .3 4, 49 1 3. 5 10 .6 3. 8 -0 .4 4, 51 0 6. 6 22 .5 0. 9 -1 .1 4, 57 3 S om al i 12 .8 27 .4 -0 .9 41 7 6. 1 22 .7 1. 5 -1 .1 43 1 10 .1 28 .7 1. 4 -1 .3 42 7 B en is ha ng ul - G um uz 21 .7 42 .7 -1 .7 10 6 3. 1 11 .5 1. 5 -0 .6 10 6 11 .9 34 .3 0. 7 -1 .4 10 8 S N N P R 20 .2 38 .6 -1 .5 2, 18 8 1. 7 6. 0 2. 7 -0 .2 2, 19 5 6. 4 21 .1 1. 6 -1 .0 2, 23 4 G am be la 7. 4 23 .5 -0 .9 23 3. 4 14 .1 1. 6 -0 .7 23 6. 4 19 .4 0. 3 -1 .1 23 H ar ar i 12 .6 32 .0 -1 .1 20 3. 0 10 .7 2. 2 -0 .5 20 5. 8 20 .0 0. 7 -1 .0 20 A dd is A ba ba 3. 1 14 .6 -0 .6 21 6 0. 4 3. 5 7. 0 0. 1 21 6 0. 3 5. 0 2. 9 -0 .2 21 8 D ire D aw a 16 .9 40 .2 -1 .3 40 4. 2 9. 7 1. 5 -0 .7 41 7. 9 26 .2 0. 8 -1 .3 42 M ot h er ’s ed uc at io n7 N o ed uc at io n 20 .0 41 .8 -1 .5 6, 53 3 3. 5 10 .7 2. 6 -0 .5 6, 55 5 8. 6 27 .5 0. 7 -1 .3 6, 64 2 P rim ar y 14 .7 35 .1 -1 .3 2, 68 7 2. 0 9. 1 3. 3 -0 .4 2, 68 6 4. 4 18 .0 1. 0 -1 .0 2, 74 2 S ec on da ry 5. 9 21 .9 -0 .7 47 1 1. 4 7. 3 3. 3 -0 .2 46 3 2. 4 11 .3 2. 9 -0 .5 47 4 M or e th an se co nd ar y 5. 3 17 .3 -0 .8 22 6 3. 7 7. 3 1. 8 -0 .2 22 5 4. 6 10 .6 0. 6 -0 .6 22 7 W ea lt h q ui nt ile Lo w es t 22 .6 44 .6 -1 .7 2, 39 1 4. 1 13 .7 3. 4 -0 .6 2, 42 4 10 .5 30 .7 0. 6 -1 .4 2, 46 0 S ec on d 20 .4 42 .8 -1 .6 2, 41 5 2. 7 9. 4 2. 2 -0 .5 2, 43 6 8. 3 27 .0 0. 9 -1 .3 2, 45 6 M id dl e 16 .4 37 .9 -1 .4 2, 16 1 2. 9 10 .5 2. 1 -0 .5 2, 15 6 6. 2 23 .0 0. 7 -1 .2 2, 17 8 Fo ur th 15 .3 35 .4 -1 .4 1, 92 7 2. 0 7. 2 3. 4 -0 .3 1, 92 0 4. 1 18 .0 0. 8 -1 .0 1, 95 3 H ig he st 9. 6 25 .6 -1 .0 1, 48 1 2. 4 7. 3 3. 0 -0 .2 1, 47 6 3. 7 14 .4 2. 0 -0 .7 1, 50 6 T ot al 17 .6 38 .4 -1 .4 10 ,3 76 2. 9 9. 9 2. 8 -0 .5 10 ,4 12 7. 0 23 .6 0. 9 -1 .2 10 ,5 52 N ot e: E ac h of th e 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 ) f ro m th e m ed ia n of th e W H O C hi ld G ro w th S ta nd ar ds . 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 ag e 2; s ta nd in g he ig ht is m ea su re d fo r al l o th er 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- bo rn tw in s an d ot he r m ul tip le b irt hs a re c ou nt ed a s fir st 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 ga ve b irt h 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 fr om 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 204 • Nutrition of Children and Adults Table 11.2 Initial breastfeeding Among last-born children who were born in the 2 years before the survey, percentage who were ever breastfed and percentages who started breastfeeding within 1 hour and within 1 day of birth; and among last-born children born in the 2 years before the survey who were ever breastfed, percentage who received a prelacteal feed, according to background characteristics, Ethiopia 2016 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 96.1 71.3 90.3 2,091 8.9 2,010 Female 97.4 75.2 93.3 2,216 6.9 2,159 Assistance at delivery Health professional3 96.9 73.2 91.4 1,603 7.3 1,554 Traditional birth attendant 95.9 73.1 90.2 1,476 9.4 1,416 Other 99.1 72.5 96.6 588 5.6 583 No one 96.3 74.9 92.4 640 8.0 616 Place of delivery Health facility 97.0 73.7 91.3 1,560 7.2 1,513 At home 96.6 73.5 92.1 2,664 8.3 2,574 Other 97.9 59.9 95.3 84 5.2 82 Residence Urban 95.2 72.6 87.0 520 12.3 495 Rural 97.0 73.4 92.5 3,788 7.3 3,674 Region Tigray 97.7 63.0 93.1 314 6.0 307 Affar 95.9 42.0 81.5 43 40.7 41 Amhara 97.5 66.0 85.9 789 7.9 769 Oromiya 96.1 76.7 94.8 1,915 4.1 1,841 Somali 95.6 78.2 85.9 178 38.8 170 Benishangul-Gumuz 98.0 71.7 87.8 45 3.1 44 SNNPR 97.3 77.1 93.1 876 7.2 852 Gambela 95.0 67.1 82.9 10 10.2 10 Harari 98.3 89.4 95.8 10 27.0 10 Addis Ababa 97.6 67.5 86.3 110 20.9 107 Dire Dawa 96.2 90.5 93.9 18 9.5 18 Mother’s education No education 96.5 73.4 92.1 2,606 8.2 2,515 Primary 97.4 74.1 92.8 1,319 6.6 1,284 Secondary 97.0 73.7 91.8 262 6.8 254 More than secondary 95.6 61.3 78.0 121 17.3 116 Wealth quintile Lowest 96.2 73.9 89.2 1,011 11.5 972 Second 98.3 75.6 95.7 943 5.4 927 Middle 96.7 73.4 93.2 890 6.1 861 Fourth 96.2 69.0 90.9 796 7.0 766 Highest 96.3 74.4 89.9 667 9.6 643 Total 96.8 73.3 91.9 4,308 7.9 4,169 Note: Table is based on last-born children born in the 2 years before the survey regardless of whether the children are living or dead at the time of interview. 1 Includes children who started breastfeeding within 1 hour of birth. 2 Children given something other than breast milk during the first 3 days of life. 3 Doctor, nurse/midwife, health officer, or health extension worker. Nutrition of Children and Adults • 205 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 percentage currently breastfeeding; and percentage of all children under age 2 using a bottle with a nipple, according to age in months, Ethiopia 2016 Not breast- feeding Breastfeeding status Total Percentage currently breast- feeding Number of youngest children under age 2 living with the mother Percentage using a bottle with a nipple Number of all children under age 2 Age in months 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 6.1 74.1 12.6 2.6 1.5 3.1 100.0 93.9 388 3.7 391 2-3 5.5 64.0 14.1 2.9 4.8 8.7 100.0 94.5 379 9.3 389 4-5 4.1 36.0 24.2 7.9 7.0 20.8 100.0 95.9 418 14.1 420 6-8 4.9 12.0 16.0 5.8 5.0 56.3 100.0 95.1 561 18.5 568 9-11 7.2 4.5 6.7 2.2 2.7 76.6 100.0 92.8 499 19.5 503 12-17 8.6 2.5 7.3 1.7 1.2 78.6 100.0 91.4 1,085 13.4 1,124 18-23 24.0 0.7 5.2 0.6 1.3 68.2 100.0 76.0 816 12.9 880 0-3 5.8 69.2 13.3 2.7 3.1 5.9 100.0 94.2 767 6.5 780 0-5 5.2 57.5 17.2 4.6 4.5 11.1 100.0 94.8 1,185 9.2 1,200 6-9 5.0 10.5 14.2 4.4 4.4 61.4 100.0 95.0 736 19.4 745 12-15 8.2 2.8 7.0 2.0 1.1 79.0 100.0 91.8 777 11.8 800 12-23 15.2 1.7 6.4 1.2 1.3 74.2 100.0 84.8 1,900 13.2 2,004 20-23 24.5 0.5 4.4 0.4 0.8 69.3 100.0 75.5 501 10.4 550 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 breastfed, 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%. 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 although they may also receive plain water. Any children who are given 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. 206 • 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 before the survey, according to background characteristics, Ethiopia 2016 Median duration (months) of breastfeeding among children born in the past three years1 Background characteristic Any breast- feeding Exclusive breastfeeding Predominant breastfeeding2 Sex Male 23.4 2.9 5.1 Female 24.4 3.3 6.0 Residence Urban 25.0 2.9 5.0 Rural 23.8 3.1 5.6 Region Tigray 24.6 3.8 6.4 Affar 19.8 2.7 4.9 Amhara 31.2 4.1 6.8 Oromiya 22.7 2.8 4.5 Somali 14.3 a 3.8 Benishangul-Gumuz 28.4 4.6 7.9 SNNPR 26.8 3.0 6.7 Gambela 25.6 2.9 6.8 Harari 18.4 * 5.5 Addis Ababa 24.2 2.9 4.2 Dire Dawa 24.6 3.2 4.3 Mother’s education No education 23.9 3.1 5.6 Primary 24.0 3.1 5.7 Secondary 23.0 3.0 4.4 More than secondary (24.8) * * Wealth quintile Lowest 22.4 3.0 6.2 Second 24.2 3.6 5.4 Middle 26.0 2.8 4.6 Fourth 23.6 (2.3) 4.8 Highest 24.7 3.7 5.6 Total 23.9 3.1 5.5 Mean for all children 24.5 4.5 7.3 Note: Median and mean durations are based on breastfeeding status of the child at the time of the survey (current status). Includes living and deceased 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 For last-born children under age 24 months who live with the mother and are breastfeeding, information to determine exclusive and predominant breastfeeding comes from a 24-hour dietary recall. Tabulations assume that last- born children age 24 months or older who live with the mother and are breastfeeding are neither exclusively nor predominantly breastfed. It is assumed that last-born children not currently living with the mother and all non-last-born children 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 07 Ta bl e 11 .5 F oo d s an d li qu id s co ns u m ed b y ch ild re n in t he d ay o r ni g ht p re ce di ng t h 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 ag e 2 w ho a re li vi ng w ith th e m ot he r by ty pe o f f oo ds c on su m ed in th e da y or n ig ht b ef or e 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 , E th io pi a 20 16 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 of ch ild re n un de r ag e 2 A ge in m on th s In fa nt fo rm ul a O th er m ilk 1 O th er li qu id s2 F or tif ie 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 r oo ts 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 tr y E gg s C he es e, yo gu rt, o th er m ilk p ro du ct B R E A S T FE E D IN G C H IL D R E N 0- 1 0. 1 2. 4 3. 2 0. 0 2. 2 0. 0 0. 0 0. 0 1. 0 0. 0 0. 2 2. 0 3. 3 36 5 2- 3 1. 0 4. 9 6. 9 1. 1 2. 5 1. 6 0. 8 1. 4 0. 8 0. 0 1. 0 3. 8 9. 2 35 8 4- 5 1. 7 9. 8 14 .5 0. 6 7. 5 5. 0 1. 6 3. 7 1. 4 0. 0 4. 1 13 .4 21 .7 40 1 6- 8 1. 6 16 .5 31 .8 5. 3 33 .3 13 .6 4. 2 12 .1 10 .2 2. 5 9. 8 22 .4 59 .2 53 3 9- 11 1. 5 16 .2 27 .4 5. 0 55 .1 24 .1 10 .9 17 .7 27 .4 5. 8 17 .7 27 .2 82 .5 46 3 12 -1 7 2. 1 15 .5 34 .7 3. 1 62 .2 33 .1 11 .1 27 .2 21 .7 11 .0 18 .2 24 .8 86 .0 99 1 18 -2 3 0. 9 14 .5 33 .0 1. 4 66 .8 33 .8 13 .1 31 .1 25 .5 9. 7 20 .9 26 .5 89 .8 62 0 6- 23 1. 6 15 .6 32 .4 3. 4 56 .1 27 .7 10 .1 23 .4 21 .3 8. 0 17 .0 25 .1 80 .8 2, 60 7 T ot al 1. 4 12 .6 25 .2 2. 6 40 .5 20 .0 7. 3 16 .9 15 .2 5. 6 12 .5 19 .6 60 .0 3, 73 0 N O N B R E A S T FE E D IN G C H IL D R E N 0- 1 * * * * * * * * * * * * * 24 2- 3 * * * * * * * * * * * * * 21 4- 5 * * * * * * * * * * * * * 17 6- 8 * * * * * * * * * * * * * 28 9- 11 (4 .3 ) (2 2. 9) (5 5. 9) (6 .0 ) (7 0. 4) (5 6. 5) (1 8. 8) (2 5. 8) (1 8. 3) (1 1. 6) (4 4. 0) (5 6. 3) (9 0. 7) 36 12 -1 7 1. 9 29 .6 43 .5 8. 0 53 .9 25 .8 7. 1 21 .5 25 .7 16 .0 20 .6 40 .7 75 .9 94 18 -2 3 1. 0 29 .2 33 .7 2. 5 70 .1 32 .4 11 .1 25 .5 23 .2 13 .5 15 .4 36 .2 90 .4 19 6 6- 23 1. 5 27 .0 39 .6 4. 1 62 .5 32 .4 11 .5 23 .1 22 .3 13 .5 18 .5 40 .5 85 .4 35 3 T ot al 1. 4 23 .6 34 .5 3. 5 55 .2 27 .6 9. 9 19 .7 19 .0 11 .5 16 .1 35 .5 75 .0 41 5 N ot e: B re as tfe ed in g st at us a nd fo od c on su m ed r ef er to a “ 24 -h ou r” p er io d (y es te rd ay a nd la st n ig ht ). 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 25 u nw ei gh te d ca se s an d ha s be en s up pr es se d. 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 ot he r 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 , c ar ro ts , s qu as h, o r y el lo w o r o ra ng e sw ee t p ot at oe s, a nd a ny d ar k gr ee n, le af y ve ge ta bl es li ke k al e, s pi na ch , o r a m ar an th le av es , r ip e m an go es , r ip e pa pa ya s, a nd o th er lo ca lly g ro w n fr ui ts a nd v eg et ab le s ric h in v ita m in A . 20 8 • N ut rit io n of C hi ld re n an d A du lts Ta bl e 11 .6 M in im um a cc ep ta bl e di et 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 a m in im um a cc ep ta bl e di et 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 b ef or e th e su rv ey , ac co rd in g to b ac kg ro un d ch ar ac te ris tic s, E th io pi a 20 16 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: A m on g no n- br ea st fe d ch ild re n ag e 6- 23 m on th s, p er ce nt ag e fe d: A m on g al l c hi ld re n ag e 6- 23 m on th s, p er ce nt ag e fe d: B ac kg ro un d ch ar ac te ris tic M in im um di et ar y di ve rs ity 1 M in im um m ea l fre qu en cy 2 M in im um ac ce pt ab le di et 3 N um be r of br ea st fe d ch ild re n 6- 23 m on th s M ilk o r m ilk pr od uc ts 4 M in im um di et ar y di ve rs ity 1 M in im um m ea l fre qu en cy 5 M in im um ac ce pt ab le di et 6 N um be r of no n- br ea st fe d ch ild re n 6- 23 m on th s B re as tm ilk , m ilk , o r m ilk pr od uc ts 7 M in im um di et ar y di ve rs ity 1 M in im um m ea l fre qu en cy 8 M in im um ac ce pt ab le di et 9 N um be r of a ll ch ild re n 6- 23 m on th s A ge in m o nt hs 6- 8 5. 0 44 .0 3. 9 53 3 * * * * 28 97 .0 5. 3 43 .9 3. 7 56 1 9- 11 13 .3 36 .9 7. 9 46 3 (5 7. 7) (4 2. 0) (6 2. 5) (1 9. 2) 36 97 .0 15 .3 38 .7 8. 7 49 9 12 -1 7 17 .5 43 .9 8. 8 99 1 42 .6 19 .4 40 .6 3. 7 94 95 .0 17 .7 43 .6 8. 3 1, 08 5 18 -2 3 12 .6 52 .2 9. 2 62 0 35 .2 17 .0 51 .3 2. 3 19 6 84 .4 13 .7 52 .0 7. 5 81 6 S ex M al e 13 .9 43 .2 8. 1 1, 22 6 38 .3 14 .4 43 .2 4. 8 16 5 92 .7 14 .0 43 .2 7. 7 1, 39 0 Fe m al e 12 .2 45 .9 7. 3 1, 38 1 41 .0 24 .4 53 .7 3. 7 18 9 92 .9 13 .7 46 .9 6. 9 1, 57 0 R es id en ce U rb an 30 .1 59 .7 19 .6 31 9 56 .3 33 .3 55 .6 10 .1 42 94 .9 30 .5 59 .3 18 .5 36 1 R ur al 10 .7 42 .5 6. 1 2, 28 7 37 .5 18 .0 47 .9 3. 4 31 1 92 .5 11 .5 43 .2 5. 7 2, 59 9 R eg io n T ig ra y 13 .0 49 .4 5. 7 20 9 * * * * 14 95 .2 13 .7 50 .6 5. 4 22 3 A ffa r 2. 5 35 .4 1. 9 23 (4 3. 9) (2 .8 ) (4 9. 0) (0 .0 ) 6 87 .6 2. 6 38 .4 1. 5 29 A m ha ra 3. 1 56 .3 3. 1 51 6 * * * * 29 95 .4 3. 2 55 .7 2. 9 54 5 O ro m iy a 16 .9 39 .6 9. 6 1, 12 4 39 .1 23 .2 46 .8 4. 4 17 4 91 .8 17 .8 40 .6 8. 9 1, 29 8 S om al i 3. 8 31 .6 3. 1 77 74 .8 6. 8 64 .1 0. 9 38 91 .7 4. 8 42 .4 2. 4 11 6 B en is ha ng ul -G um uz 20 .4 46 .7 16 .7 29 * * * * 2 92 .9 20 .6 45 .3 15 .4 31 S N N P R 12 .5 41 .9 6. 8 54 3 (3 0. 2) (1 6. 6) (3 7. 5) (6 .2 ) 69 92 .1 13 .0 41 .4 6. 7 61 3 G am be la 14 .7 45 .2 12 .1 6 * * * * 1 94 .4 14 .2 44 .4 10 .8 7 H ar ar i 18 .8 53 .2 10 .7 6 (4 7. 6) (1 5. 6) (6 6. 4) (7 .0 ) 1 89 .3 18 .1 55 .9 9. 9 7 A dd is A ba ba 40 .7 65 .3 30 .3 63 (7 2. 1) (5 4. 6) (7 6. 2) (1 3. 9) 15 94 .5 43 .4 67 .4 27 .1 78 D ire D aw a 14 .0 37 .5 5. 6 11 (3 5. 6) (3 7. 5) (4 1. 6) (1 3. 1) 2 88 .4 18 .2 38 .2 6. 9 13 M ot h er ’s e d uc at io n N o ed uc at io n 10 .0 42 .1 5. 7 1, 57 8 39 .1 16 .4 49 .1 3. 5 22 4 92 .4 10 .8 43 .0 5. 4 1, 80 2 P rim ar y 13 .8 45 .4 7. 7 81 6 32 .9 21 .7 41 .5 3. 5 96 93 .0 14 .6 45 .0 7. 2 91 1 S ec on da ry 22 .5 59 .0 16 .2 14 1 (4 3. 7) (3 2. 9) (7 0. 9) (2 .8 ) 20 93 .1 23 .8 60 .5 14 .5 16 1 M or e th an s ec on da ry 51 .2 62 .8 35 .3 72 (9 2. 1) (4 1. 4) (6 2. 4) (2 2. 2) 14 98 .7 49 .6 62 .8 33 .2 86 (C on tin ue d… ) N ut rit io n of C hi ld re n an d A du lts • 2 09 T ab le 1 1. 6— C on tin ue d A m on g br ea st fe d ch ild re n ag e 6- 23 m on th s, p er ce nt ag e fe d: A m on g no n- br ea st fe d ch ild re n ag e 6- 23 m on th s, p er ce nt ag e fe d: A m on g al l c hi ld re n ag e 6- 23 m on th s, p er ce nt ag e fe d: B ac kg ro un d ch ar ac te ris tic M in im um di et ar y di ve rs ity 1 M in im um m ea l fre qu en cy 2 M in im um ac ce pt ab le di et 3 N um be r of br ea st fe d ch ild re n 6- 23 m on th s M ilk o r m ilk pr od uc ts 4 M in im um di et ar y di ve rs ity 1 M in im um m ea l fre qu en cy 5 M in im um ac ce pt ab le di et 6 N um be r of no n- br ea st fe d ch ild re n 6- 23 m on th s B re as tm ilk , m ilk , o r m ilk pr od uc ts 7 M in im um di et ar y di ve rs ity 1 M in im um m ea l fre qu en cy 8 M in im um ac ce pt ab le di et 9 N um be r of a ll ch ild re n 6- 23 m on th s W ea lt h q ui nt ile Lo w es t 6. 7 37 .6 2. 9 59 0 43 .7 12 .6 43 .8 2. 6 95 92 .2 7. 5 38 .5 2. 8 68 4 S ec on d 11 .5 42 .8 7. 6 55 0 18 .8 11 .0 31 .6 0. 1 78 89 .9 11 .4 41 .4 6. 7 62 8 M id dl e 11 .9 47 .1 8. 4 59 1 (4 5. 3) (1 5. 2) (6 4. 3) (4 .0 ) 58 95 .1 12 .2 48 .7 8. 0 65 0 Fo ur th 12 .0 43 .7 5. 1 47 3 (4 0. 6) (3 4. 2) (5 4. 2) (6 .5 ) 66 92 .7 14 .7 45 .0 5. 2 53 9 H ig he st 27 .4 54 .8 17 .0 40 3 55 .7 32 .1 59 .0 10 .2 55 94 .6 28 .0 55 .3 16 .2 45 8 T ot al 13 .0 44 .6 7. 7 2, 60 7 39 .8 19 .8 48 .8 4. 2 35 3 92 .8 13 .8 45 .1 7. 3 2, 96 0 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 C hi ld re n re ce iv e fo od s fr om fo ur o r m or e of th e fo llo w in g 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 ot he r m ilk p ro du ct s; b . f oo ds m ad e fr om g ra in s, r oo ts , a nd tu be rs , i nc lu di ng p or rid ge a nd fo rt ifi ed 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 fr ui ts a nd v eg et ab le s; e . e gg s; f. m ea t, po ul tr y, fi sh , a nd s he llf is h (a nd o rg an m ea ts ); g . l eg um 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 r ec ei vi ng s ol id 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 ch ild re n 9- 23 m on th s. 3 B re as tfe 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 a m in im um a cc ep ta bl e di et if th ey a re fe d th e m in im um d ie ta ry d iv er si ty a s de sc rib ed in fo ot no te 1 a nd th e m in im um m ea l f re qu en cy a s de fin ed in fo ot no te 2 . 4 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 5 Fo r n on -b re as tfe 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 r ec ei vi ng s ol id 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 . 6 N on -b re as tfe 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 a m in im um a cc ep ta bl e di et 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, r ec ei ve th e m in im um m ea l f re qu en cy a s de fin ed in fo ot no te 5 , a nd re ce iv e so lid or s em i-s ol id fo od s fr om 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 . 7 B re as tfe ed in g, o r no t 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. 8 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 ag e an d br ea st fe ed in g st at us a s de sc rib ed in fo ot no te s 2 an d 5. 9 C hi ld re n ag e 6- 23 m on th s ar e co ns id er ed to b e fe d a m in im um a cc ep ta bl e di et if th ey r ec ei ve b re as t m ilk , o th er m ilk , o r m ilk p ro du ct s as d es cr ib ed in fo ot no te 7 , a re fe d th e m in im um d ie ta ry d iv er si ty a s de sc rib ed in fo ot no te 1 , a nd a re fe d th e m in im um m ea l f re qu en cy a s de sc rib ed in fo ot no te s 2 an d 5. 210 • Nutrition of Children and Adults Table 11.7 Prevalence of anaemia in children Percentage of children age 6-59 months classified as having anaemia, by background characteristics, Ethiopia 2016 Anaemia status by haemoglobin level 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) Number of children age 6-59 months Age in months 6-8 78.0 30.6 44.8 2.6 549 9-11 76.3 26.8 44.4 5.1 494 12-17 72.1 27.3 39.8 5.0 1,130 18-23 65.5 25.2 37.9 2.3 891 24-35 59.0 24.5 29.6 5.0 1,948 36-47 51.0 23.8 25.2 2.0 2,019 48-59 40.0 23.4 15.1 1.6 2,235 Sex Male 57.3 24.4 29.6 3.3 4,811 Female 56.6 25.6 28.1 3.0 4,455 Mother’s interview status Interviewed 57.5 25.1 29.3 3.1 8,569 Not interviewed but in household 47.7 25.7 20.0 2.0 219 Not interviewed and not in the household1 51.3 22.4 24.7 4.3 479 Residence Urban 49.3 24.3 23.5 1.5 937 Rural 57.8 25.1 29.5 3.3 8,330 Region Tigray 53.6 26.2 25.9 1.5 612 Affar 74.8 27.5 43.3 4.0 91 Amhara 42.2 22.6 17.3 2.3 1,861 Oromiya 65.5 26.8 34.9 3.8 4,008 Somali 82.9 17.7 52.4 12.8 371 Benishangul-Gumuz 42.5 23.8 18.1 0.7 96 SNNPR 50.0 24.9 23.7 1.4 1,992 Gambela 56.2 24.2 31.3 0.7 21 Harari 67.9 24.0 38.3 5.6 16 Addis Ababa 49.2 20.4 27.0 1.8 165 Dire Dawa 71.5 23.7 38.6 9.3 35 Mother’s education2 No education 58.2 24.5 30.2 3.5 5,914 Primary 56.8 27.2 27.4 2.2 2,343 Secondary 48.8 23.2 23.7 1.9 353 More than secondary 49.9 23.3 26.0 0.6 177 Wealth quintile Lowest 67.8 24.1 37.3 6.4 2,164 Second 57.6 27.2 27.2 3.2 2,166 Middle 52.6 24.7 26.2 1.7 1,963 Fourth 54.0 23.8 28.2 2.1 1,723 Highest 47.9 24.6 22.4 0.9 1,250 Total 56.9 25.0 28.9 3.1 9,267 Note: 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). 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. Nutrition of Children and Adults • 211 Table 11.8 Micronutrient intake among children Among youngest children age 6-23 months who are living with their mother, percentages who consumed vitamin A-rich and iron-rich foods in the 24 hours before the survey; among all children age 6-23 months, among all children age 6-59 months, percentages who were given vitamin A supplements in the 6 months before the survey, who were given iron supplements in the 7 days before the survey, and who were given deworming medication in the 6 months before the survey; and among all children age 6-59 months who live in households in which salt was tested for iodine, percentage who live in households with iodised salt, according to background characteristics, Ethiopia 2016 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 tested for iodised salt Background characteristic Percentage who consumed foods rich in vitamin A in last 24 hours1 Percentage who consumed foods rich in iron in last 24 hours2 Number of children Percentage given iron supple- ments in past 7 days3 Percentage given vitamin A supple- ments in past 6 months4 Percentage given deworming medication in past 6 months3,5 Number of children Percentage living in house- holds with iodised salt6 Number of children Age in months 6-8 21.4 11.5 561 6.7 33.1 8.5 568 87.8 556 9-11 39.6 22.4 499 6.3 45.8 7.8 503 88.5 486 12-17 42.7 25.0 1,085 9.7 50.6 10.1 1,124 88.0 1,108 18-23 43.8 24.6 816 7.0 46.3 8.6 880 87.8 866 24-35 na na na 9.0 44.9 14.7 1,944 88.6 1,884 36-47 na na na 10.2 44.6 13.9 2,007 87.2 1,953 48-59 na na na 10.6 43.7 15.1 2,191 87.7 2,140 Sex Male 38.8 22.5 1,390 9.7 44.9 13.6 4,759 88.2 4,647 Female 38.1 21.4 1,570 8.8 44.4 11.8 4,458 87.4 4,346 Breastfeeding status Breastfeeding 37.6 21.4 2,607 8.4 46.9 10.5 3,726 88.6 3,641 Not breastfeeding 44.4 25.9 353 9.8 43.2 14.3 5,492 87.3 5,352 Mother’s age at birth 15-19 53.2 34.9 158 6.2 41.3 9.6 246 89.3 239 20-29 38.7 21.4 1,539 9.6 44.5 12.8 4,500 87.0 4,396 30-39 36.2 20.6 1,054 8.7 44.4 12.9 3,618 88.3 3,522 40-49 36.2 21.9 209 10.3 48.0 12.5 853 90.1 837 Residence Urban 59.6 39.1 361 10.3 59.3 18.9 1,021 90.7 1,007 Rural 35.5 19.5 2,599 9.1 42.9 12.0 8,196 87.5 7,986 Region Tigray 38.2 31.9 223 16.4 73.8 26.5 604 88.9 581 Affar 11.3 8.1 29 3.1 35.0 3.4 94 78.6 91 Amhara 19.2 10.1 545 5.5 47.8 10.7 1,746 92.2 1,694 Oromiya 42.4 27.3 1,298 10.4 37.6 13.3 4,015 90.6 3,939 Somali 15.7 9.0 116 3.4 36.1 3.9 421 63.0 394 Benishangul-Gumuz 47.2 22.1 31 7.9 63.7 23.7 100 96.7 98 SNNPR 48.2 17.4 613 10.3 47.1 10.2 1,944 83.3 1,908 Gambela 47.9 31.3 7 7.2 56.8 19.7 23 88.6 21 Harari 52.3 40.8 7 2.2 39.6 8.0 21 84.0 21 Addis Ababa 69.0 42.2 78 2.0 53.9 17.0 209 87.6 209 Dire Dawa 40.3 26.1 13 15.4 71.2 19.9 40 80.3 37 Mother’s education No education 32.3 17.7 1,802 8.2 41.3 10.3 6,153 87.5 5,988 Primary 43.6 23.9 911 10.8 48.4 16.0 2,434 88.0 2,384 Secondary 57.7 39.0 161 14.3 61.5 19.9 399 88.8 392 More than secondary 76.3 55.1 86 10.5 67.3 31.0 231 93.9 228 Wealth quintile Lowest 29.0 15.8 684 6.9 40.9 9.3 2,207 85.1 2,132 Second 32.2 17.2 628 8.3 41.3 11.8 2,107 88.1 2,030 Middle 41.2 22.9 650 10.7 42.4 11.5 1,939 87.2 1,907 Fourth 39.4 19.3 539 11.6 46.3 15.7 1,643 89.0 1,621 Highest 56.0 38.9 458 9.5 57.8 18.1 1,323 91.6 1,303 Total 38.4 21.9 2,960 9.2 44.7 12.7 9,218 87.9 8,993 na = Not applicable. 1 Includes meat (and organ meat), fish, poultry, eggs, pumpkin, carrots, squash, or yellow or orange sweet potatoes, and any dark green, leafy vegetables like kale, spinach, or amaranth leaves, ripe mangoes, ripe papayas, 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 Based on both mother’s recall, health facility information (where available), and the vaccination card (where available). 5 Deworming for intestinal parasites is commonly done for helminthes and schistosomiasis. 6 Excludes children in households in which salt was not tested. 212 • Nutrition of Children and Adults Table 11.9 Presence of iodised salt in household Among all households, percentage with salt tested for iodine content, percentage with salt in the household but the salt was not tested, and percentage with no salt in the household; and among households with salt tested, percentage with iodised salt, according to background characteristics, Ethiopia 2016 Among all households, percentage Among households in which salt was tested: Background characteristic With salt tested With salt, but salt not tested1 With no salt in the household Number of households Percentage with iodised salt Number of households Residence Urban 93.7 0.3 6.0 3,384 91.9 3,172 Rural 96.2 0.2 3.6 13,266 88.6 12,767 Region Tigray 95.3 0.2 4.4 1,186 87.7 1,130 Affar 94.4 0.0 5.6 140 74.1 132 Amhara 96.0 0.1 3.9 4,239 91.6 4,069 Oromiya 96.2 0.0 3.8 6,062 91.9 5,829 Somali 91.0 0.3 8.7 511 62.5 465 Benishangul-Gumuz 94.9 0.1 5.0 182 94.2 172 SNNPR 96.3 0.6 3.1 3,388 86.3 3,263 Gambela 85.1 0.2 14.7 50 86.4 43 Harari 93.9 0.1 6.0 46 87.2 43 Addis Ababa 94.3 0.4 5.4 751 90.7 708 Dire Dawa 87.3 0.2 12.4 95 83.5 83 Wealth quintile Lowest 94.1 0.1 5.7 3,202 85.8 3,015 Second 96.0 0.3 3.7 3,203 90.1 3,075 Middle 97.4 0.1 2.5 3,121 89.4 3,041 Fourth 97.2 0.2 2.6 3,084 89.3 2,998 Highest 94.3 0.2 5.5 4,040 91.2 3,811 Total 95.7 0.2 4.1 16,650 89.3 15,939 1 Includes households in which salt could not be tested for technical or logistical reasons, including availability of test kits. Nutrition of Children and Adults • 213 Table 11.10.1 Nutritional status of women Among women age 15-49, percentage with height under 145 cm, mean body mass index (BMI), and percentage with specific BMI levels, according to background characteristics, Ethiopia 2016 Height Body Mass Index1 Percent- age below 145 cm Number of women Mean Body Mass Index (BMI) Normal Thin Overweight/obese Number of women Background characteristic 18.5-24.9 (Total normal) <18.5 (Total thin) 17.0-18.4 (Mildly thin) <17 (Moder- ately and severely thin) ≥25.0 (Total over- weight or obese) 25.0-29.9 (Over- weight) ≥30.0 (Obese) Age 15-19 2.9 3,220 20.0 67.6 29.0 18.5 10.6 3.4 3.2 0.2 3,087 20-29 1.6 5,543 20.7 74.1 19.4 14.1 5.3 6.5 5.6 0.9 4,715 30-39 3.0 4,113 21.1 69.1 20.3 14.9 5.4 10.6 8.1 2.5 3,668 40-49 2.3 2,237 20.9 66.0 23.4 16.8 6.6 10.6 7.4 3.2 2,173 Residence Urban 1.5 3,282 22.4 63.8 14.8 10.8 4.0 21.4 15.8 5.6 3,100 Rural 2.6 11,832 20.2 71.8 24.7 17.2 7.5 3.5 3.1 0.3 10,544 Region Tigray 2.8 1,091 19.8 60.4 34.0 21.4 12.5 5.6 4.9 0.7 1,005 Affar 1.7 122 19.8 52.7 39.1 19.0 20.1 8.3 6.5 1.7 107 Amhara 2.9 3,666 20.2 73.7 22.9 15.9 7.0 3.4 3.2 0.3 3,385 Oromiya 1.9 5,465 20.6 67.9 24.7 18.1 6.7 7.4 5.6 1.7 4,826 Somali 0.2 434 20.9 53.7 31.2 17.6 13.6 15.1 10.9 4.2 358 Benishangul-Gumuz 1.6 147 20.6 73.1 20.1 14.7 5.4 6.9 6.4 0.5 132 SNNPR 2.8 3,157 20.9 79.5 14.9 11.1 3.8 5.6 4.7 0.8 2,847 Gambela 1.9 42 20.3 59.7 31.8 19.1 12.7 8.5 6.2 2.3 39 Harari 2.2 34 21.7 59.2 21.0 14.7 6.3 19.8 15.7 4.1 30 Addis Ababa 2.3 873 23.1 57.2 13.4 8.8 4.6 29.4 21.7 7.7 840 Dire Dawa 1.9 81 22.0 56.3 22.1 14.7 7.4 21.6 15.8 5.8 75 Education No education 2.8 7,272 20.3 72.1 23.3 16.7 6.6 4.6 4.0 0.6 6,456 Primary 2.3 5,293 20.6 68.9 23.8 15.9 7.9 7.3 5.7 1.6 4,809 Secondary 1.3 1,723 21.4 70.4 16.4 12.3 4.2 13.2 10.2 3.0 1,600 More than secondary 0.5 825 22.2 58.5 19.4 13.6 5.8 22.1 16.0 6.1 779 Wealth quintile Lowest 3.8 2,536 19.9 69.3 28.1 18.6 9.5 2.5 2.3 0.2 2,207 Second 2.9 2,732 20.2 73.7 23.6 16.8 6.8 2.7 2.4 0.3 2,356 Middle 2.4 2,904 20.0 72.6 24.9 18.2 6.8 2.5 2.5 0.0 2,627 Fourth 2.0 3,001 20.3 72.3 23.4 15.8 7.6 4.3 3.8 0.6 2,756 Highest 1.3 3,940 22.1 64.5 15.9 11.4 4.5 19.6 14.7 4.9 3,698 Total 2.4 15,114 20.7 70.0 22.4 15.7 6.7 7.6 6.0 1.5 13,644 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 previous 2 months. 214 • Nutrition of Children and Adults 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, Ethiopia 2016 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 (Moder- ately and severely thin) ≥25.0 (Total over- weight or obese) 25.0-29.9 (Over- weight) ≥30.0 (Obese) Age 15-19 18.2 40.3 59.0 30.2 28.8 0.6 0.6 0.0 2,425 20-29 19.7 69.9 28.0 22.2 5.8 2.1 1.8 0.3 3,604 30-39 20.2 71.8 23.5 18.2 5.3 4.7 4.0 0.7 2,857 40-49 20.3 71.2 23.1 17.0 6.1 5.6 5.2 0.5 2,056 Residence Urban 20.8 61.8 25.8 16.9 8.9 12.4 10.6 1.7 2,082 Rural 19.3 64.6 34.4 23.1 11.3 0.9 0.9 0.0 8,860 Region Tigray 19.0 53.1 44.3 26.8 17.6 2.6 2.2 0.4 680 Affar 19.2 45.1 50.2 30.6 19.7 4.7 4.0 0.7 76 Amhara 19.3 64.9 33.7 21.8 11.9 1.4 1.4 0.0 2,833 Oromiya 19.6 64.1 33.0 23.1 9.9 2.9 2.5 0.4 4,098 Somali 18.6 42.3 54.6 22.1 32.5 3.1 2.8 0.3 260 Benishangul-Gumuz 19.7 66.3 30.9 24.1 6.7 2.8 2.7 0.2 103 SNNPR 19.7 69.8 28.3 20.6 7.7 1.9 1.8 0.1 2,273 Gambela 19.7 61.8 34.0 22.7 11.2 4.2 4.1 0.2 33 Harari 20.4 61.1 29.9 20.8 9.1 9.0 8.1 0.9 23 Addis Ababa 21.8 62.8 17.6 11.4 6.2 19.6 16.7 2.9 507 Dire Dawa 20.4 63.3 27.8 18.5 9.4 8.8 7.3 1.5 56 Education No education 19.4 68.3 30.4 21.5 8.9 1.3 1.2 0.1 3,032 Primary 19.3 61.5 36.9 23.6 13.3 1.6 1.5 0.2 5,346 Secondary 19.9 63.8 30.7 20.4 10.3 5.6 4.6 0.9 1,646 More than secondary 21.2 66.1 20.4 16.5 3.9 13.5 12.1 1.4 918 Wealth quintile Lowest 19.1 60.7 38.4 24.5 13.9 0.9 0.8 0.1 1,740 Second 19.2 63.7 35.3 23.8 11.5 1.0 0.9 0.1 2,032 Middle 19.3 66.5 32.7 22.3 10.5 0.7 0.7 0.0 2,147 Fourth 19.3 65.9 33.5 23.0 10.5 0.6 0.6 0.0 2,339 Highest 20.7 63.1 26.7 17.7 8.9 10.3 8.9 1.3 2,684 Total 15-49 19.6 64.1 32.8 21.9 10.8 3.1 2.8 0.4 10,942 50-59 20.4 66.1 26.8 20.7 6.1 7.1 6.2 0.8 1,044 Total 15-59 19.7 64.3 32.3 21.8 10.4 3.5 3.1 0.4 11,985 Note: The body mass index (BMI) is expressed as the ratio of weight in kilograms to the square of height in meters (kg/m2). Nutrition of Children and Adults • 215 Table 11.11.1 Prevalence of anaemia in women Percentage of women age 15-49 with anaemia, by background characteristics, Ethiopia 2016 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 19.9 15.6 3.9 0.4 3,165 20-29 24.2 17.3 5.8 1.0 5,467 30-39 25.5 19.2 5.3 1.0 4,078 40-49 24.3 19.9 4.2 0.2 2,213 Number of children ever born 0 18.2 14.1 3.7 0.3 4,745 1 22.7 17.0 4.5 1.3 1,744 2-3 23.4 16.7 6.1 0.6 2,971 4-5 28.4 21.6 5.6 1.1 2,423 6+ 29.1 22.2 6.0 1.0 3,040 Maternity status Pregnant 29.1 16.5 10.4 2.2 1,088 Breastfeeding 28.6 21.9 5.7 1.0 4,554 Neither 20.6 16.0 4.1 0.5 9,281 Using IUD Yes 29.1 25.8 3.3 0.0 221 No 23.6 17.7 5.1 0.8 14,702 Smoking status Smokes cigarettes/tobacco 23.3 17.3 5.7 0.2 81 Does not smoke 23.6 17.8 5.0 0.8 14,842 Residence Urban 17.0 13.9 2.9 0.2 3,169 Rural 25.4 18.9 5.6 0.9 11,754 Region Tigray 19.7 15.9 3.5 0.3 1,073 Affar 44.7 28.8 13.9 2.0 119 Amhara 17.2 14.6 2.4 0.1 3,645 Oromiya 27.3 20.2 5.9 1.2 5,422 Somali 59.5 30.0 24.8 4.8 417 Benishangul-Gumuz 19.2 15.8 3.2 0.2 146 SNNPR 22.5 17.4 4.6 0.5 3,124 Gambela 26.1 20.6 5.2 0.3 42 Harari 27.7 18.9 7.5 1.2 32 Addis Ababa 16.0 12.7 3.2 0.1 825 Dire Dawa 30.1 21.0 7.9 1.3 77 Education No education 27.8 20.3 6.3 1.2 7,215 Primary 21.7 16.8 4.4 0.4 5,244 Secondary 17.8 14.3 2.9 0.5 1,676 More than secondary 11.5 9.2 2.4 0.0 789 Wealth quintile Lowest 34.3 23.0 9.1 2.2 2,519 Second 25.3 18.7 5.7 0.9 2,717 Middle 23.7 18.6 4.8 0.3 2,891 Fourth 21.0 16.6 3.8 0.6 2,979 Highest 17.4 14.2 3.0 0.2 3,816 Total 23.6 17.8 5.0 0.8 14,923 Note: Prevalence is adjusted for altitude and smoking status if known using formulas in CDC 1998. 216 • Nutrition of Children and Adults Table 11.11.2 Prevalence of anaemia in men Percentage of men age 15-49 with anaemia, according to background characteristics, Ethiopia 2016 Anaemia status by haemoglobin level Background characteristic Any anaemia <13.0 g/dl Number of men Age 15-19 18.2 2,375 20-29 12.4 3,539 30-39 12.2 2,800 40-49 17.4 2,016 Residence Urban 7.2 1,963 Rural 16.2 8,767 Region Tigray 16.9 671 Affar 23.7 76 Amhara 13.5 2,808 Oromiya 15.8 4,020 Somali 21.3 249 Benishangul-Gumuz 11.1 102 SNNPR 14.1 2,221 Gambela 10.0 32 Harari 14.0 22 Addis Ababa 4.8 475 Dire Dawa 16.3 54 Education No education 17.9 3,006 Primary 16.0 5,267 Secondary 9.1 1,598 More than secondary 4.4 859 Wealth quintile Lowest 22.4 1,716 Second 17.4 2,015 Middle 15.2 2,123 Fourth 13.0 2,318 Highest 7.9 2,557 Total 15-49 14.5 10,730 50-59 19.3 1,038 Total 15-59 15.0 11,768 Note: Prevalence is adjusted for altitude and smoking status, if known, using formulas in CDC 1998. Nutrition of Children and Adults • 217 Table 11.12 Micronutrient intake among mothers Among women age 15-49 with a child born in the 5 years before the survey, percent distribution by number of days they took iron tablets or syrup during the pregnancy of the last child, and percentage who took deworming medication during the pregnancy of the last child; and among women age 15-49 with a child born in the 5 years before the survey and who live in households that were tested for iodised salt, percentage who live in households with iodised salt, according to background characteristics, Ethiopia 2016 Background characteristic Among women with a child born in the past 5 years: Among women with a child born in the past 5 years who live in households in which salt was tested: Number of days women took iron tablets during pregnancy of last birth Percentage of women who took deworming medication during preg- nancy of last birth Number of women None <60 60-89 90+ Don’t know/ missing Total Percentage living in households with iodised salt1 Number of women Age 15-19 56.6 31.2 6.6 4.6 1.1 100.0 5.5 339 88.4 329 20-29 53.5 33.2 6.3 5.8 1.2 100.0 6.2 3,630 87.9 3,544 30-39 60.9 27.5 5.1 4.6 1.9 100.0 5.8 2,867 88.7 2,788 40-49 66.4 23.4 5.0 3.6 1.5 100.0 3.1 753 90.4 738 Residence Urban 39.2 39.3 8.5 10.3 2.7 100.0 7.7 969 90.8 956 Rural 60.4 28.6 5.3 4.3 1.3 100.0 5.4 6,621 88.1 6,443 Region Tigray 22.2 43.8 14.2 16.1 3.7 100.0 8.7 537 88.9 517 Affar 56.6 33.3 3.9 5.1 1.1 100.0 4.5 71 76.0 69 Amhara 46.4 38.5 7.9 5.2 2.0 100.0 6.7 1,632 91.5 1,581 Oromiya 69.9 22.6 3.5 2.8 1.3 100.0 5.3 3,129 91.0 3,069 Somali 72.1 22.7 2.3 2.3 0.7 100.0 1.4 269 63.9 252 Benishangul-Gumuz 51.5 29.6 7.6 10.6 0.7 100.0 9.0 81 96.1 79 SNNPR 58.7 32.3 4.2 4.2 0.5 100.0 5.0 1,601 84.7 1,567 Gambela 58.4 33.2 2.1 3.1 3.2 100.0 4.7 21 87.5 19 Harari 49.0 30.9 11.7 7.0 1.3 100.0 3.8 17 85.3 17 Addis Ababa 35.6 29.0 14.7 18.0 2.6 100.0 5.4 198 88.5 198 Dire Dawa 39.5 31.7 16.9 7.5 4.4 100.0 11.8 33 82.3 32 Education No education 63.6 26.9 4.5 3.5 1.5 100.0 4.8 4,791 88.3 4,657 Primary 51.9 32.6 7.5 6.5 1.5 100.0 7.1 2,150 88.5 2,103 Secondary 35.2 44.1 9.6 9.4 1.7 100.0 8.2 420 86.9 414 More than secondary 31.1 44.2 7.7 16.5 0.4 100.0 6.5 230 94.3 226 Wealth quintile Lowest 68.4 22.3 4.0 4.3 1.0 100.0 3.9 1,651 86.4 1,590 Second 58.3 30.9 5.0 3.7 2.2 100.0 4.5 1,654 88.9 1,595 Middle 60.6 29.0 5.9 3.4 1.1 100.0 6.3 1,588 87.6 1,557 Fourth 54.4 32.3 7.1 5.2 1.0 100.0 7.0 1,427 88.8 1,405 Highest 43.3 37.5 7.2 9.8 2.2 100.0 7.3 1,269 91.4 1,253 Total 57.7 30.0 5.7 5.1 1.5 100.0 5.7 7,590 88.5 7,399 1 Excludes women in households where salt was not tested. HIV/AIDS-related Knowledge, Attitudes, and Behaviour • 219 HIV/AIDS-RELATED KNOWLEDGE, ATTITUDES, AND BEHAVIOUR 12 Key Findings  Knowledge about HIV transmission and prevention: Twenty percent of women age 15-49 and 38% of men age 15-49 have comprehensive knowledge about the modes of HIV transmission and prevention.  Knowledge of mother-to-child transmission of HIV: Fifty-seven percent of women and 55% of men know that HIV can be transmitted during pregnancy, labour/delivery, or breastfeeding.  Discriminatory attitudes: Forty-eight percent of women and 35% of men thought that children living with HIV should not be able to attend school with children who are HIV negative; 55% of women and 47% of men would not buy fresh vegetables from a shopkeeper with HIV.  Sexual partners: Less than 1% of women and 3% of men reported having two or more sexual partners in the past 12 months.  Condom use: Only 20% of women and 51% of men who had a non-cohabiting partner in the past 12 months reported using a condom during last sexual intercourse with such a partner.  Coverage of HIV testing: Sixty-nine percent of women and 84% of men know where to obtain an HIV test, and 40% women and 43% men have ever been tested for HIV and received the test results. In the 12 months before the survey, 20% of women and 19% of men had been tested for HIV and received the most recent test results.  Male circumcision: Overall, 91% of men 15-49 are circumcised. 12.1 BACKGROUND INFORMATION ON HIV AND AIDS IN ETHIOPIA In response to the HIV epidemic, the Ethiopian government, in collaboration with its key development partners, has been at the forefront of developing and implementing national strategies that adhere to global directions and combine innovations with best practices within the country. Ethiopia developed a five-year national HIV and AIDS strategic plan (2015-2020) based on the investment framework strategy of UNAIDS in 2014 (FHAPCO 2014). This chapter provides key HIV and AIDS-related findings from the 2016 EDHS survey. The chapter is organized in two main sections; the first focuses on the adult population age 15-59. The data in this section are national and include background characteristics of the respondents such as HIV/AIDS knowledge, attitude and behaviour, which includes knowledge of HIV prevention methods, stigma and discrimination, number of sexual partners, condom use, self-reported HIV testing, prevention of mother-to-child 220 • HIV/AIDS-related Knowledge, Attitudes, and Behaviour transmission (PMTCT), and voluntary medical male circumcision in Ethiopia. The second section presents selected indicators for individuals age 15-24. 12.2 HIV/AIDS KNOWLEDGE, TRANSMISSION, AND PREVENTION METHODS Forty-nine percent of women and 69% of men know that consistent condom use and having sex with only one uninfected partner can reduce the risk of HIV infection; 58% of women and 77% of men know that using condom during sexual intercourse can reduce the risk of HIV. In addition, 69% of women and 81% of men identified limiting sexual intercourse to one uninfected partner with no other partners can reduce the risk of HIV (Table 12.1). Trends: The percentage of respondents who know that using condoms consistently and limiting sexual intercourse to one uninfected partner with no other partners can reduce the risk of HIV has increased from 32% in 2000 to 49% in 2016 among women and from 58% to 69% among men (Figure 12.1). Patterns by background characteristics  Among women, knowledge of HIV/AIDS prevention decreases with age; 52% of women age 15-24 know that using condoms and limiting sexual intercourse to one uninfected partner can reduce the risk of HIV, compared with 43% of women age 40-49.  Knowledge of the two methods of HIV prevention is higher among urban women and men than rural women and men.  There are notable differences in knowledge of HIV/AIDS prevention methods by region, ranging from 66% among women and 84% of men in Tigray compared with 10% of women and 38% of men in Somali.  For women and men, knowledge of prevention methods increases with education and wealth quintile. 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 15-24 and 15-49 Table 12.2 shows that 20% of women age 15-49 and 38% of men age 15-49 have comprehensive knowledge of HIV. Thirty percent of women and 49% of men know that a healthy looking person can have HIV and reject that HIV can be transmitted by mosquito bites and that a person can become infected by sharing food with a person who has HIV. Trends: The percentage of women and men with comprehensive knowledge about HIV/AIDS has only increased a few percentage points between 2011 and 2016, moving from 19% to 20% among women and 32% to 38% among men. Figure 12.1 Knowledge of HIV prevention methods 32 35 43 49 58 57 64 69 2000 EDHS 2005 EDHS 2011 EDHS 2016 EDHS Percentage of women and men age 15-49 who have knowledge of HIV prevention methods* Women Men * Percentage who, in response to prompted question, 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. HIV/AIDS-related Knowledge, Attitudes, and Behaviour • 221 12.3 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 by using 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 certain drugs during pregnancy. More than half (57%) of women age 15-49 know that HIV can be transmitted by all the three modes of transmission; during pregnancy (65%), labour and delivery (70%), and breastfeeding (74%). Similarly, 55% of men age 15-49 identified all three modes of HIV mother-to- child transmissions; 66% know that HIV can be transmitted during pregnancy, 75% during delivery, and 73% during breastfeeding (Table 12.3 and Figure 12.2). More men (61%) know that the risk of MTCT can be reduced by mother taking special medications compared with women (51%). Knowledge of medications that can be taken to reduce the risk of MTCT is highest among women age 20-24 (56%) and among men age 25-29 (66%), and lowest among women and men age 40-49 (45% and 58%, respectively). Trends: The percentage of women who know that MTCT of HIV can be reduced by taking special medications has increased in both women and men age 15-49 since 2005. The proportion of women who reported that MTCT of HIV can be reduced by mother taking special drugs has increased five times, from 10% in 2005 to 51% in 2016. A similar trend is observed for men, from 29% in 2005 to 61% in 2016 (Figure 12.3). 12.4 DISCRIMINATORY ATTITUDES TOWARDS PEOPLE LIVING WITH HIV Widespread stigma and discrimination in a population can adversely affect people’s willingness to be tested as well as their initiation of and adherence to antiretroviral therapy (ART). Thus, reduction of stigma and discrimination in a population are important indicators of the success of programs that target HIV/AIDS prevention and control. Figure 12.2 Knowledge of mother-to-child transmission (MTCT) Figure 12.3 Trends in knowledge of mother-to-child transmission (MTCT) 65 70 74 57 66 75 73 55 During pregnancy During delivery By breastfeeding Know that the risk of MTCT can be reduced by mother taking special drugs Percentage of women and men age 15-49 Women Men Know that HIV can be transmitted from mother to child: 10 44 51 29 53 61 2005 EDHS 2011 EDHS 2016 EDHS Percentage of women and men age 15-49 who know that the risk of MTCT can be reduced by mother taking special drugs Women Men 222 • HIV/AIDS-related Knowledge, Attitudes, and Behaviour Discriminatory attitudes towards people living with HIV Women and men are asked two questions to assess discriminatory attitudes towards people living with HIV. Respondents with discriminatory attitudes towards people living with HIV are those who say that they would not buy fresh vegetables from a shopkeeper or vendor if they knew that person had HIV, or who say that children living with HIV should not be allowed to attend school with children who do not have HIV. Sample: Women and men age 15-49 The 2016 EDHS found that discriminatory attitudes are higher in women than in men. For instance, 48% of women and 35% of men thought that children living with HIV should not be able to attend school with children who are HIV negative, while 55% of women and 47% of men would not buy fresh vegetables from a shopkeeper who has HIV (Table 12.4). Patterns by background characteristics  Considerable differences in discriminatory attitudes are observed between urban and rural areas; 28% of women and 27% of men in urban areas have discriminatory attitudes, compared with 73% for women and 60% for men in rural areas.  Discriminatory attitudes are higher in the Somali Region (78% for women and 73% for men), and lower in Addis Ababa (18% for women and 17% for men).  Discriminatory attitudes decrease with education level; 80% of women and 67% of men with no education have discriminatory attitudes, compared with 12% of women and 20% of men with more than secondary education (Figure 12.4).  Discriminatory attitudes decrease with wealth quintile. Among women, the percentage with discriminatory attitudes toward people living with HIV decreases from 81% among those in the lowest wealth quintile to 33% in the highest wealth quintile. Among men, the percentage decreases from 67% among those in the lowest wealth quintile to 33% in the highest wealth quintile. 12.5 MULTIPLE SEXUAL PARTNERS Given that most HIV infections in Ethiopia are acquired through heterosexual intercourse, information on the number of sexual partners and use of safe sex practices is important in designing and monitoring programmes that control the spread of HIV. Table 12.5.1 shows that less than 1% of women age 15-49 reported having two or more sexual partners in the 12 months before the survey, and 2% had sexual intercourse in the past 12 months with a person who was neither their husband nor lived with them. Among women with a non-marital, non-cohabiting partner, 20% reported using a condom during last sexual intercourse with such a partner Figure 12.4 Discriminatory attitudes* towards people living with HIV by education 80 62 27 12 67 58 34 20 No education Primary Secondary More than secondary Percentage with discriminatory attitudes* towards people living with HIV by education Women Men * 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 • 223 Among men age 15-49, 3% reported having two or more sexual partners in the 12 months before the survey, and 7% of men had sexual intercourse in the past 12 months with a person who was neither their wife nor lived with them (Table 12.5.2). Fifty-one percent of men who had intercourse in the past 12 months with a non-marital, non-cohabiting partner reported using a condom during the last sexual intercourse with such a partner (Figure 12.5). The mean number of lifetime sexual partners is 1.6 among women and 2.9 among men. Patterns by background characteristics  Men who are married are more likely to have more than one partner in the past 12 months than those who were never married (4% compared to 2%).  Men in urban areas are more likely to have had intercourse in the past 12 months with a person who was neither their wife nor lived with them than men in rural areas (16% compared to 5%).  The percentage of men who had sex with non-marital, non-cohabiting partners is highest in Addis Ababa (26%) and lowest in Somali (1%).  Using a condom during last sexual intercourse with a non-marital, non-cohabiting partner was higher among men with higher education levels, 58% among men with more than secondary education compared to 26% among men with no education.  The highest mean number of lifetime sexual partners is reported by men in Addis Ababa (5.2). 12.6 PAID SEX The act of paying for sex introduces an uneven negotiating ground for safer sexual intercourse. Transactional sex is the exchange of money, favours, or gifts for sexual intercourse. This type of sexual intercourse is associated with a greater risk of contracting HIV and other STIs because of compromised power relations and the likelihood of having multiple partners. Three percent of men have ever paid for sex. The percentage of men who have ever paid for sex increases with increasing age. The highest (5%) is found among men age 50-59 compared with the lowest (less than 1%) among men age 15-19. Payment for sex in the past 12 months is less than 1% among men 15-49. Eight in ten men (81%) who paid for sex in the past 12 months reported using condoms during the last paid sexual intercourse (Table 12.6). Trends: The percentage of men who reported paying for sex in the 12 months before the survey remained the same in 2011 and 2016 (1% for each). However, condom use during the last paid sex increased from 30% in 2011 to 81% in 2016. Figure 12.5 Sex and condom use with non-regular partners 2 20 7 51 Had sex in the past 12 months with non-regular partner Among those who had sex with a non-regular partner, percentage who used a condom during last sex with a non-regular partner Percentage of women and men age 15-49 Women Men 224 • HIV/AIDS-related Knowledge, Attitudes, and Behaviour 12.7 COVERAGE OF HIV TESTING SERVICES Knowledge of HIV status helps HIV-negative individuals make specific decisions to reduce risk and increase safer sex practices so that 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. 12.7.1 Awareness of HIV Testing Services and Experience with HIV Testing The majority of respondents (69% of women and 84% of men) know where to obtain an HIV test, while 40% of women and 43% of men have ever been tested and received the test results. Overall, 20% of women and 19% men had been tested for HIV in the 12 months before the survey and received the last test results (Tables 12.7.1 and 12.7.2, and Figure 12.6). Trends: The proportion of women and men who were tested for HIV in the 12 months before the survey and received the test results increased from 2% for women and men in 2005 to 20% for women and 21% for men in 2011. However, the HIV testing coverage remains unchanged between 2011 and 2016. Patterns by background characteristics  The proportion of respondents who have never been tested for HIV is highest among women and men age 15-19 (75% and 80%, respectively) compared with 46% of women and 41% of men age 25-59.  Among women, knowledge of where to obtain HIV test services is much higher among urban residents (92%) than among rural residents (63%).  The proportion of women and men who have been tested for HIV in the past 12 months is twice as high in urban areas (36% for women and 33% for men) as in rural areas (15% each for women and men).  HIV testing coverage in the 12 months before the survey is highest in Dire Dawa (39% for women and 36% for men) and lowest in Somali (9% for women and 8% for men) (Figure 12.7). Figure 12.6 HIV testing Figure 12.7 Recent HIV testing by region 40 20 43 19 Ever tested for HIV and received the result Tested in 12 months before the survey and received the result Percentage of women and men age 15-49 Women Men 39 35 34 32 29 24 24 21 18 15 9 36 40 37 25 14 23 29 23 15 15 8 Dire Dawa Addis Ababa Gambela Tigray Harari Benishangul-Gumuz Affar Amhara SNNPR Oromiya Somali Percentage of women and men who were tested for HIV in the year before the survey and received results Women Men HIV/AIDS-related Knowledge, Attitudes, and Behaviour • 225  HIV testing coverage in the last 12 months tends to increase with rising level of education, from 14% of women with no education to 44% among women with more than secondary education. Among men, the HIV testing varies from 13% among those with no education to 39% among those with more than secondary education level (Figure 12.8). Table 12.8 presents information on self-reported HIV testing among currently married women age 15- 49, before getting married or living with a partner. Women living in urban areas, highly educated women, and women from the highest wealth quintile are more likely to report being tested for HIV prior to getting married or living with a partner than most other women. For detailed information on self-reported HIV testing among currently married women before getting married or living with a partner, see Table 12.8. 12.7.2 HIV Testing of Pregnant Women Table 12.9 presents information on self-reported HIV testing during pregnancy and delivery among all women age 15-49 who gave birth in the 2 years before the survey. One in five women (23%) received counselling on HIV during an ANC visit. One in three women (34%) had an HIV test during an ANC visit or labour and received the test results. Twenty-two percent of women were tested for HIV during an ANC visit and received the test results and post-test counselling, 11% were tested and received the results but no post-test counselling, and 3% were tested but did not receive the test results. Overall, 19% of women received counselling on HIV, an HIV test during an antenatal care (ANC) visit, and the test results. Patterns by background characteristics  Women in urban areas are more likely to receive HIV counselling than rural women, 59% and 18%, respectively.  More than half (56%) of women in urban areas received counselling on HIV, an HIV test during an ANC visit, and the test results compared to 14% women in rural areas.  The proportion of women who had HIV testing during an ANC visit or during labour and who received the result increases with education level, from 24% for women with no education to 88% for women with more than secondary education. 12.8 MALE CIRCUMCISION Table 12.10 shows that 91% of men age 15-49 have been circumcised; 17% by a health professional, and 71% by traditional practitioners or family friends. Trends: The percentage of men who are circumcised remained essentially the same in 2005 (93%), 2011 (92%), and 2016 (91%). Figure 12.8 Recent HIV testing by education 14 20 30 44 13 15 31 39 No education Primary Secondary More than secondary Percentage of women and men who were tested for HIV in the year before the survey and received results Women Men 226 • HIV/AIDS-related Knowledge, Attitudes, and Behaviour Patterns by background characteristics  The proportion of men who are circumcised increases by age, ranging from 86% among men age 15-19 to 94% among men age 40-49 (Figure 12.9).  Younger men are more likely to have been circumcised by a health professional than their older counterparts, with 21% among men age 15-24, compared to 8% among those age 40-49. In contrast, older men are more likely than younger men to have been circumcised by traditional practitioners, family, or friends, with 83% among men age 45-49, compared to 61% among those age 15-19.  The proportion of men who have been circumcised by a health care professional is higher in urban areas than in rural areas (20% versus 16%).  Male circumcision is almost universal or above 90% in all regions except in SNNPR (85%) and Gambela (72%). 12.9 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 Overall, 4% of women and men age 15-49 reported having an STI and/or symptoms of an STI in the past 12 months (Table 12.11). Among men, the percentage was 6% in Oromiya, and 5% in Harari compared to less than 1% in the Tigray and Benishangul-Gumuz. Fewer than one in three women and men (32% for each) who had an STI or STI symptoms sought advice or treatment from a clinic, hospital, private doctor, or other health professional. One percent of women and 3% of men sought advice or treatment from a shop or pharmacy. However, 67% of women and 66% men did not seek any advice or treatment (Table 12.12). 12.10 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 young people are engaged in behaviours that may place them at risk of contracting HIV. 12.10.1 Knowledge Knowledge of HIV transmission is crucial to enabling people 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 engage in other risky behaviours. Figure 12.9 Male circumcision by age 21 21 18 15 8 4 3 4 3 3 61 66 70 76 83 86 90 92 94 94 15-19 20-24 25-29 30-39 40-49 Percentage of men who report having been circumcised Traditional practitioner/ family friend Other/ don’t know Health worker/ professional HIV/AIDS-related Knowledge, Attitudes, and Behaviour • 227 In Ethiopia, 24% of women age 15-24 and 39% of men age 15-24 have comprehensive knowledge of HIV, which includes 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 transmission or prevention of HIV (Table 12.13). Trends: The percentage of young women with comprehensive knowledge about HIV has increased slightly from 2005 to 2016, 21% to 24% among young women, and from 33% to 39% among young men (Figure 12.10). Patterns by background characteristics  Comprehensive knowledge about HIV is lowest among women and men age 15-17; 23% of women and 34% of men age 15-17 have comprehensive knowledge compared with 26% of women and 43% of men age 18-19.  Urban youth (42% of women and 48% of men) are more likely than rural youth (19% of women and 37% of men) to have comprehensive knowledge on HIV and AIDS.  Comprehensive HIV knowledge increases with increasing education among women and men age 15-24. Eight percent of women and 27% of men with no education have comprehensive knowledge about HIV compared with 51% of women and 58% of men with more than secondary school. 12.10.2 First Sex Young people who initiate sex at an early age are typically at higher risk of becoming pregnant or contracting an STI than young people who initiate sex at a later age. Consistent condom use can reduce such risks. Table 12.14 provides information on the percentage of young women and men who have had sexual intercourse before age 15 and before age 18. Overall, a higher percentage of young women reported having sex before the age of 15 (9%) compared with young men (1%). An even higher percentage of women reported having sex before age18 (40%) compared with men (12%). Patterns by background characteristics  Young women in rural areas are more likely to have had sex before age 15 than their urban counterparts, with 3% in urban compared with 11% in rural areas.  Among women age 15-24, the percentage who had sexual intercourse before age 15 declines with increasing level of education, from 22% among women with no education to 1% among those with more than secondary education.  Among women and men age 18-24, the percentage who had sexual intercourse before age 18 decreases with increasing level of education. Sixty-six percent of women age 18-24 with no education had sexual intercourse before age 18 compared with 8% of women with more than secondary education. Similar trends can be noted with the percentage of men who have had their first sexual intercourse before age 18. Figure 12.10 Trends in comprehensive HIV knowledge among youth 21 24 24 33 34 39 2005 EDHS 2011 EDHS 2016 EDHS Percentage of young women and men age 15-24 who know how to prevent HIV transmission and reject local myths Women 15-24 Men 15-24 228 • HIV/AIDS-related Knowledge, Attitudes, and Behaviour Trends: Overall, the percentage of young people age 15-24 who have had sex before age 15 has decreased from 16% in 2005, 11% in 2011, and 9% in 2016 for women. The corresponding proportions for men are 2%, 1%, and 1%, respectively. The percentage of young people age 18-24 who have had sex before age 18 has increased from 35% in 2005 to 40% in 2016 among women and from 9% to 12% among men. 12.10.3 Premarital Sex Table 12.15 shows that 93% of never-married women and 86% of never-married men age 15-24 have never had sexual intercourse. The percentage of never-married women and men who have never had sexual intercourse decreases sharply with age; from 97% of never-married women and men age 15-17 to 85% among never-married women and 61% among never-married men age 23-24. Among never-married women age 15-24, the percentage of those who have never had sexual intercourse is higher in rural areas than in urban areas (95% versus 89%). The same trend is observed among never- married men; the percentage of those who have never had sexual intercourse is higher in rural areas than in rural areas (88% versus 77%). 12.10.4 Multiple Sexual Partners Young men age 15-24 are more likely than their female counterparts to have had more than one partner in the previous 12 months; 2% of men have had more than one partner in the last 12 months, compared with less than 1% of women (Tables 12.16.1 and 12.16.2). Young men are also more likely than young women to have had intercourse with a non-marital, non-cohabiting partner in the last 12 months (9% of men versus 3% of women). Condom use at last sex with a non-marital, non-cohabiting partner is 24% among young women and 55% among young men. Condom use at last sex with a non-marital, non-cohabiting partner is higher in urban areas than in rural areas; 31% of women and 64% of men in urban areas have had sex with a non-marital partner, non-cohabiting partner in the last 12 months and used a condom during last sexual intercourse with such a partner, compared with 12% of women and 50% of men in rural areas. 12.10.5 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 because there are often barriers to young people obtaining services. Table 12.17 provides information on sexually active youth age 15-24 who have been tested for HIV and received the results of the last test. Overall, among young people age 15-24 who have had sexual intercourse in the previous 12 months, 27% of young women and 29% of young men were tested for HIV and had received the results of their last test. Patterns by background characteristics  The proportion of young people tested for HIV in the previous 12 months increases with age, 22% among women 15-17 compared to 30% among women age 23-24, and 21% among men age 15-17 compared to 31% among men age 23-24.  Those who have never-married are more likely to have been tested for HIV in the past 12 months and to have received the results of the last test; 43% among never-married women compared with 26% among ever-married women, and 37% among never-married men compared with 22% among ever- married men. 12.10.6 Coverage of HIV Testing Services among Children One additional question to assess HIV coverage among children was included in the 2016 EDHS. Women who had children less than 15 years old were asked if any of their children were tested for HIV. According to the mothers, only 6% of children below age 15 have been tested for HIV (Table 12.18). HIV/AIDS-related Knowledge, Attitudes, and Behaviour • 229  Twenty-two percent of children living in urban areas had been tested for HIV, compared with 5% of children living in rural areas.  Children in the Somali Region (2%) are least likely to be tested for HIV compared with 23% of children living in Addis Ababa.  Children whose mothers have more education and those from the higher wealth quintile are more likely to have been tested for HIV than those whose mothers have less education and those from the lower wealth quintiles. LIST OF TABLES For more information on HIV/AIDS-related knowledge, attitudes, and behaviour, see the following tables:  Table 12.1 Knowledge of HIV prevention methods  Table 12.2 Comprehensive knowledge about HIV  Table 12.3 Knowledge of prevention of mother-to-child transmission of HIV  Table 12.4 Discriminatory attitudes towards people living with HIV  Table 12.5.1 Multiple sexual partners and higher-risk sexual intercourse in the past 12 months: Women  Table 12.5.2 Multiple sexual partners and higher-risk sexual intercourse in the past 12 months: Men  Table 12.6 Payment for sexual intercourse and condom use at last paid sexual intercourse  Table 12.7.1 Coverage of prior HIV testing: Women  Table 12.7.2 Coverage of prior HIV testing: Men  Table 12.8 Coverage of prior HIV testing among married women  Table 12.9 Pregnant women counselled and tested for HIV  Table 12.10 Male circumcision  Table 12.11 Self-reported prevalence of sexually-transmitted infections (STIs) and STI symptoms  Table 12.12 Women and men seeking treatment for STIs  Table 12.13 Comprehensive knowledge about HIV among young people  Table 12.14 Age at first sexual intercourse among young people  Table 12.15 Premarital sexual intercourse among young people  Table 12.16.1 Multiple sexual partners and higher-risk sexual intercourse in the past 12 months among young people: Women  Table 12.16.2 Multiple sexual partners and higher-risk sexual behaviour in the past 12 months among young people: Men  Table 12.17 Recent HIV tests among young people  Table 12.18 HIV tests among children 230 • HIV/AIDS-related Knowledge, Attitudes, and Behaviour Table 12.1 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 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, Ethiopia DHS 2016 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 61.7 70.3 52.0 6,143 76.5 78.6 67.2 4,455 15-19 61.2 68.6 50.6 3,381 74.2 77.0 65.9 2,572 20-24 62.3 72.4 53.8 2,762 79.6 80.8 69.0 1,883 25-29 58.5 69.5 49.1 2,957 80.0 82.2 71.4 1,977 30-39 55.6 68.8 46.9 4,277 78.2 83.3 70.1 3,020 40-49 50.0 65.4 42.6 2,306 74.3 80.0 66.6 2,154 Residence Urban 78.8 81.1 68.8 3,476 83.4 83.8 73.5 2,303 Rural 51.7 65.5 43.0 12,207 75.6 79.9 67.3 9,302 Region Tigray 75.0 81.9 66.0 1,129 89.8 90.2 84.2 708 Affar 36.4 61.6 30.6 128 81.0 81.5 71.6 82 Amhara 61.2 72.5 52.1 3,714 83.2 85.5 76.1 2,914 Oromiya 52.8 68.4 45.9 5,701 75.3 78.6 65.7 4,409 Somali 13.4 25.6 10.3 459 42.5 57.9 38.1 301 Benishangul-Gumuz 44.2 49.7 32.8 160 77.8 79.0 67.8 118 SNNPR 56.3 65.5 43.8 3,288 70.3 78.7 62.1 2,371 Gambela 55.9 60.5 43.9 44 78.3 80.8 69.2 35 Harari 52.8 72.0 47.3 38 67.4 81.8 62.0 29 Addis Ababa 84.6 82.3 73.4 930 91.2 81.6 76.5 573 Dire Dawa 61.5 60.2 45.5 90 75.3 80.5 64.8 66 Education No education 44.6 61.4 37.0 7,498 71.5 77.2 64.2 3,203 Primary 62.8 71.6 51.9 5,490 76.1 79.4 66.8 5,608 Secondary 81.0 83.2 71.7 1,817 84.4 87.4 75.9 1,785 More than secondary 89.4 88.4 81.1 877 87.7 87.4 79.3 1,010 Wealth quintile Lowest 40.6 57.4 33.8 2,633 71.1 74.9 62.8 1,839 Second 49.7 65.9 42.5 2,809 74.3 80.0 66.7 2,118 Middle 52.8 66.5 43.2 2,978 75.7 79.8 67.0 2,246 Fourth 57.7 69.2 46.9 3,100 78.0 81.1 69.0 2,466 Highest 77.5 80.0 67.6 4,163 83.2 85.2 74.3 2,935 Total 15-49 57.7 69.0 48.7 15,683 77.1 80.7 68.6 11,606 50-59 na na na na 73.0 81.9 67.2 1,082 Total 15-59 Na na na na 76.8 80.8 68.4 12,688 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 • 231 Table 12.2 Comprehensive knowledge about HIV Percentage of women and 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 percentage with a comprehensive knowledge about HIV, according to background characteristics, Ethiopia DHS 2016 Percentage of respondents 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 compre- hensive knowledge about HIV2 Number of respondents 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 WOMEN Age 15-24 60.7 56.2 77.7 77.0 35.6 24.3 6,143 15-19 61.0 57.1 76.4 75.5 35.5 24.0 3,381 20-24 60.3 55.0 79.3 78.7 35.6 24.6 2,762 25-29 61.5 47.7 72.4 74.6 29.8 19.4 2,957 30-39 60.3 43.1 72.5 70.4 27.4 18.0 4,277 40-49 57.2 39.0 69.3 67.5 22.2 14.1 2,306 Residence Urban 75.8 67.4 91.4 92.7 51.8 39.4 3,476 Rural 55.8 43.1 69.1 67.8 24.2 14.7 12,207 Region Tigray 77.5 43.7 85.0 79.3 31.8 24.9 1,129 Affar 57.9 36.1 64.8 58.4 22.8 12.2 128 Amhara 65.0 47.7 80.1 82.1 32.3 22.0 3,714 Oromiya 55.0 43.6 59.8 63.3 24.3 17.3 5,701 Somali 26.6 22.4 38.3 31.9 8.4 3.5 459 Benishangul-Gumuz 55.0 59.7 81.2 80.3 35.5 14.0 160 SNNPR 56.9 57.0 86.9 78.2 33.4 17.5 3,288 Gambela 62.0 61.0 82.2 78.8 40.3 22.8 44 Harari 45.5 58.7 84.7 82.2 28.3 20.1 38 Addis Ababa 82.4 67.6 95.7 96.0 55.9 44.1 930 Dire Dawa 54.7 61.6 68.8 78.2 32.5 22.0 90 Total 15-49 60.2 48.5 74.0 73.4 30.3 20.2 15,683 MEN Age 15-24 75.1 65.4 84.4 86.1 50.0 39.1 4,455 15-19 72.1 63.8 82.4 84.5 47.9 37.6 2,572 20-24 79.3 67.7 87.2 88.2 52.9 41.1 1,883 25-29 78.1 68.2 86.8 87.6 52.3 41.5 1,977 30-39 76.6 63.3 87.0 86.4 47.4 37.9 3,020 40-49 76.8 58.3 86.5 86.6 44.8 34.3 2,154 Residence Urban 83.3 74.8 91.9 94.0 61.8 48.6 2,303 Rural 74.6 61.3 84.4 84.7 45.5 35.7 9,302 Region Tigray 89.6 57.2 91.7 91.5 50.4 43.5 708 Affar 78.6 54.6 78.7 82.8 39.7 32.3 82 Amhara 81.5 64.3 91.6 88.9 51.8 44.0 2,914 Oromiya 74.2 63.2 77.8 83.6 46.3 35.3 4,409 Somali 53.2 33.1 52.7 55.4 19.9 12.1 301 Benishangul-Gumuz 64.8 52.6 82.5 86.6 37.8 30.9 118 SNNPR 69.9 69.1 94.2 88.9 49.2 35.8 2,371 Gambela 69.4 75.1 91.4 87.1 52.4 41.8 35 Harari 65.8 73.6 75.3 85.1 46.6 34.8 29 Addis Ababa 91.0 73.8 97.2 97.2 65.9 51.5 573 Dire Dawa 81.3 74.2 82.1 90.9 60.9 44.0 66 Total 15-49 76.3 64.0 85.9 86.5 48.7 38.3 11,606 50-59 77.0 57.3 83.7 81.9 40.9 32.1 1,082 Total 15-59 76.4 63.4 85.7 86.1 48.1 37.8 12,688 1 Two most common local misconceptions: HIV can be transmitted by mosquito bites and a person can become infected 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 transmission or prevention of HIV. 232 • HIV/AIDS-related Knowledge, Attitudes, and Behaviour Table 12.3 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 during pregnancy, during delivery, by breastfeeding, and by all three means, and percentage who know that the risk of mother to child transmission (MTCT) of HIV can be reduced by mother taking special drugs, according to background characteristics, Ethiopia DHS 2016 Percentage who know that HIV can be transmitted from mother to child: Percentage who know that the risk of MTCT can be reduced by mother taking special drugs Number of respondents Background characteristic During pregnancy During delivery By breast- feeding By all three means WOMEN Age 15-24 66.0 71.2 75.2 56.6 54.0 6,143 15-19 64.7 70.3 73.9 55.6 52.7 3,381 20-24 67.6 72.4 76.9 57.8 55.7 2,762 25-29 65.5 69.5 75.2 57.3 52.4 2,957 30-39 64.0 70.3 73.5 57.3 49.9 4,277 40-49 64.2 67.7 70.5 57.2 44.6 2,306 Residence Urban 76.6 83.5 84.2 67.5 78.0 3,476 Rural 61.8 66.4 71.2 54.0 43.6 12,207 Region Tigray 72.8 79.5 81.6 63.4 69.5 1,129 Affar 69.2 74.3 74.5 65.4 42.4 128 Amhara 72.8 77.6 83.0 65.0 55.5 3,714 Oromiya 60.4 64.1 68.0 51.7 46.3 5,701 Somali 31.7 35.9 36.7 29.5 14.4 459 Benishangul-Gumuz 53.4 60.9 67.4 47.1 46.8 160 SNNPR 62.4 69.0 73.8 54.6 44.3 3,288 Gambela 59.9 69.5 76.0 53.6 63.6 44 Harari 68.1 73.9 78.8 65.2 56.4 38 Addis Ababa 81.4 88.6 87.2 72.6 84.6 930 Dire Dawa 58.9 62.2 72.0 51.2 65.3 90 Total 15-49 65.1 70.1 74.1 57.0 51.2 15,683 MEN Age 15-24 64.0 74.0 72.6 53.3 59.3 4,455 15-19 63.3 70.9 71.1 53.1 56.5 2,572 20-24 64.9 78.3 74.6 53.7 63.2 1,883 25-29 67.0 76.9 73.0 54.6 65.7 1,977 30-39 67.5 76.5 73.6 56.5 61.4 3,020 40-49 66.0 72.8 70.5 56.1 57.7 2,154 Residence Urban 73.0 83.7 76.1 59.3 79.5 2,303 Rural 64.0 72.8 71.6 53.8 56.0 9,302 Region Tigray 64.7 80.0 82.5 51.7 77.9 708 Affar 69.7 76.7 70.7 59.3 50.9 82 Amhara 66.2 79.6 76.2 55.0 62.2 2,914 Oromia 66.4 70.9 71.0 55.7 61.9 4,409 Somali 53.1 57.9 57.6 48.2 16.7 301 Benishangul-Gumuz 52.5 67.9 70.2 41.7 59.4 118 SNNPR 63.2 75.1 69.1 54.1 51.0 2,371 Gambela 63.8 74.5 75.8 52.8 69.8 35 Harari 60.5 62.8 62.9 44.7 63.8 29 Addis Ababa 80.0 86.4 76.5 62.2 84.5 573 Dire Dawa 66.0 74.3 72.4 50.6 74.1 66 Total 15-49 65.8 74.9 72.5 54.9 60.6 11,606 50-59 67.8 75.8 74.5 57.3 57.4 1,082 Total 15-59 66.0 75.0 72.7 55.1 60.4 12,688 HIV/AIDS-related Knowledge, Attitudes, and Behaviour • 233 Table 12.4 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, Ethiopia DHS 2016 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 has 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 has HIV Percentage with discriminatory attitudes towards people living with HIV1 Number of men who have heard of HIV or AIDS Age 15-24 40.4 48.6 56.3 5,750 30.5 43.3 49.8 4,294 15-19 39.6 47.0 55.1 3,123 31.2 44.3 51.1 2,441 20-24 41.4 50.6 57.7 2,628 29.6 42.0 48.1 1,853 25-29 48.8 53.7 61.4 2,763 32.1 44.2 50.1 1,937 30-39 54.4 59.8 68.3 3,962 39.4 49.7 56.0 2,978 40-49 54.9 62.7 71.2 2,124 39.3 52.3 58.8 2,119 Marital status Never married 33.0 39.6 46.6 3,820 28.1 39.8 46.1 4,691 Ever had sex 23.8 23.5 30.4 388 21.1 30.8 37.4 1,053 Never had sex 34.1 41.4 48.4 3,431 30.1 42.5 48.7 3,638 Married/Living together 54.8 61.3 70.0 9,465 39.9 52.2 58.6 6,362 Divorced/separated/widowed 41.7 50.5 57.0 1,314 29.0 40.7 47.2 275 Residence Urban 19.5 21.1 28.2 3,437 18.3 20.0 27.4 2,271 Rural 56.6 65.0 73.3 11,162 38.9 53.5 59.6 9,057 Region Tigray 42.1 50.5 57.9 1,113 29.0 40.1 48.4 703 Affar 46.4 46.8 59.5 118 32.5 30.5 46.3 79 Amhara 37.5 51.2 57.2 3,584 24.5 41.0 46.3 2,880 Oromiya 58.6 59.2 69.9 5,087 43.9 51.5 57.3 4,279 Somali 67.6 71.6 77.5 313 59.5 67.7 73.4 262 Benishangul-Gumuz 35.2 47.0 54.0 145 27.7 51.7 55.3 111 SNNPR 54.7 65.4 72.3 3,153 35.9 56.1 63.3 2,316 Gambela 26.2 32.9 39.6 40 27.2 33.3 44.9 33 Harari 33.4 33.9 40.2 37 31.3 33.9 39.5 28 Addis Ababa 12.0 12.2 18.2 925 13.0 7.1 16.7 572 Dire Dawa 25.8 30.1 36.9 83 18.4 23.5 29.1 65 Education No education 63.7 70.8 79.5 6,633 46.1 61.2 67.0 3,071 Primary 45.3 53.8 62.1 5,285 37.2 51.2 57.8 5,475 Secondary 16.7 20.6 27.1 1,805 20.6 27.1 33.6 1,779 More than secondary 8.6 7.4 12.4 876 12.2 14.1 19.8 1,003 Wealth quintile Lowest 67.5 71.9 81.2 2,236 46.5 61.8 67.2 1,756 Second 62.0 70.7 78.6 2,519 42.7 59.6 65.1 2,061 Middle 57.8 65.6 74.2 2,761 38.3 51.1 57.6 2,186 Fourth 46.9 57.2 65.2 2,968 32.9 46.8 53.4 2,425 Highest 22.6 26.3 33.3 4,114 20.8 25.4 32.6 2,901 Total 15-49 47.9 54.7 62.7 14,599 34.7 46.8 53.1 11,328 50-59 na na na 0 40.3 54.4 60.1 1,068 Total 15-59 na na na 0 35.2 47.5 53.7 12,396 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. 234 • HIV/AIDS-related Knowledge, Attitudes, and Behaviour Table 12.5.1 Multiple sexual partners and higher-risk sexual intercourse in the past 12 months: Women Among all women age 15-49, percentage who had sexual intercourse with more than one sexual partner in the past 12 months, and percentage who had intercourse in the past 12 months with a person who was neither their husband nor lived with them; among women age 15-49 who had sexual intercourse in the past 12 months with a person who was neither their husband nor lived with them, percentage who used a condom during last sexual intercourse with such a partner; and among women who ever had sexual intercourse, mean number of sexual partners during their lifetime, according to background characteristics, Ethiopia DHS 2016 All women Women who had intercourse in the past 12 months with a person who was neither their husband nor lived with them Women who ever had sexual intercourse1 Background characteristic Percentage who had 2+ partners in the past 12 months Percentage who had intercourse in the past 12 months with a person who was neither their husband nor lived with them Number of women Percentage who reported using a condom during last sexual intercourse with such a partner Number of women Mean number of sexual partners in lifetime Number of women Age 15-24 0.3 2.8 6,143 21.8 175 1.3 2,862 15-19 0.3 2.1 3,381 26.0 71 1.1 832 20-24 0.3 3.7 2,762 19.0 103 1.4 2,030 25-29 0.5 3.2 2,957 18.4 95 1.5 2,699 30-39 0.2 1.8 4,277 21.3 78 1.7 4,168 40-49 0.5 1.2 2,306 (15.4) 29 2.1 2,291 Marital status Never married 0.2 4.8 4,036 20.9 194 1.7 401 Married or living together 0.2 0.7 10,223 5.6 72 1.6 10,206 Divorced/separated/widowed 1.4 7.8 1,423 29.0 111 2.1 1,413 Residence Urban 0.5 6.3 3,476 30.5 217 1.8 2,323 Rural 0.2 1.3 12,207 6.6 160 1.6 9,697 Region Tigray 0.5 4.4 1,129 23.9 50 1.7 874 Affar 0.2 1.5 128 * 2 1.6 110 Amhara 0.4 2.6 3,714 (12.0) 95 1.8 2,976 Oromiya 0.3 1.9 5,701 (7.0) 106 1.7 4,517 Somali 0.1 0.1 459 * 0 1.1 358 Benishangul-Gumuz 0.2 1.1 160 * 2 1.8 128 SNNPR 0.2 1.0 3,288 * 32 1.2 2,352 Gambela 0.7 7.0 44 30.8 3 2.3 37 Harari 0.2 1.6 38 * 1 1.4 30 Addis Ababa 0.5 8.8 930 41.8 82 1.9 572 Dire Dawa 0.3 4.4 90 27.2 4 1.7 67 Education No education 0.3 1.2 7,498 8.2 88 1.7 7,090 Primary 0.3 2.3 5,490 18.5 124 1.6 3,493 Secondary 0.1 4.7 1,817 32.5 85 1.3 866 More than secondary 0.6 9.2 877 23.5 81 1.3 570 Wealth quintile Lowest 0.1 1.3 2,633 (2.4) 34 1.5 2,254 Second 0.2 0.9 2,809 * 26 1.4 2,311 Middle 0.3 1.3 2,978 (0.3) 37 1.8 2,354 Fourth 0.5 1.9 3,100 (11.0) 60 1.8 2,295 Highest 0.4 5.3 4,163 30.4 219 1.7 2,807 Total 15-49 0.3 2.4 15,683 20.4 377 1.6 12,020 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 Means are calculated excluding respondents who gave non-numeric responses. HIV/AIDS-related Knowledge, Attitudes, and Behaviour • 235 Table 12.5.2 Multiple sexual partners and higher-risk sexual intercourse in the past 12 months: Men Among all men age 15-49, percentage who had sexual intercourse with more than one sexual partner in the past 12 months, and percentage who had intercourse in the past 12 months with a person who was neither their wife nor lived with them; among those having more than one partner in the past 12 months, percentage reporting that a condom was used during last intercourse; among men age 15-49 who had sexual intercourse in the past 12 months with a person who was neither their wife nor lived with them, percentage who used a condom during last sexual intercourse with such a partner; and among men who ever had sexual intercourse, mean number of sexual partners during their lifetime, according to background characteristics, Ethiopia DHS 2016 All men Men who had 2+ partners in the past 12 months Men who had intercourse in the past 12 months with a person who was neither their wife nor lived with them Men who ever had sexual intercourse1 Background characteristic Percentage who had 2+ partners in the past 12 months Percentage who had intercourse in the past 12 months with a person who was neither their wife nor lived with them Number of men Percentage who reported using a condom during last sexual inter- course Number of men Percentage who reported using a condom during last sexual intercourse with such a partner Number of men Mean number of sexual partners in lifetime Number of men Age 15-24 1.8 9.0 4,455 45.5 78 50.5 402 2.2 1,064 15-19 0.8 4.5 2,572 (56.9) 20 51.7 115 2.4 204 20-24 3.1 15.2 1,883 41.5 58 50.0 287 2.1 860 25-29 3.1 11.2 1,977 41.4 60 54.5 221 2.9 1,500 30-39 4.0 4.5 3,020 8.3 120 52.9 136 2.8 2,787 40-49 6.2 1.8 2,154 3.9 133 29.3 38 3.3 2,055 Marital status Never married 2.2 13.8 4,882 60.6 108 53.9 672 3.7 1,009 Married or living together 4.3 1.0 6,441 1.6 274 37.8 63 2.7 6,130 Divorced/separated/ widowed 3.3 22.5 282 * 9 33.2 63 3.9 266 Type of union In polygynous union 65.4 0.2 309 0.0 202 * 1 3.4 286 In non-polygynous union 1.2 1.0 6,132 6.1 72 38.0 62 2.7 5,844 Not currently in union 2.3 14.2 5,164 60.7 118 52.1 735 3.7 1,276 Residence Urban 3.6 15.6 2,303 64.0 83 61.5 359 4.3 1,481 Rural 3.3 4.7 9,302 7.3 308 42.4 439 2.5 5,925 Region Tigray 2.6 8.5 708 (42.5) 18 59.4 60 3.3 440 Affar 5.9 17.3 82 (16.5) 5 42.2 14 3.3 67 Amhara 1.6 5.2 2,914 * 47 48.3 152 2.8 1,956 Oromiya 4.2 7.0 4,409 11.5 184 39.3 310 2.9 2,657 Somali 4.7 0.8 301 1.6 14 * 2 1.6 184 Benishangul-Gumuz 5.6 11.4 118 18.0 7 58.3 13 3.3 91 SNNPR 3.7 3.4 2,371 8.8 87 52.6 80 2.4 1,514 Gambela 5.5 20.4 35 (32.4) 2 58.5 7 3.5 27 Harari 2.2 6.7 29 * 1 (72.8) 2 1.8 19 Addis Ababa 4.7 26.1 573 71.0 27 72.4 150 5.2 405 Dire Dawa 2.5 11.0 66 * 2 74.3 7 3.1 46 Education No education 3.4 1.9 3,203 1.7 108 26.1 59 2.6 2,632 Primary 3.3 5.4 5,608 15.6 185 46.8 304 2.5 3,103 Secondary 2.9 12.2 1,785 46.4 52 56.2 218 3.6 898 More than secondary 4.6 21.4 1,010 45.0 47 58.4 217 4.4 773 Wealth quintile Lowest 4.5 2.8 1,839 8.7 83 30.7 52 2.6 1,232 Second 2.3 3.3 2,118 (9.9) 48 48.4 69 2.1 1,446 Middle 3.0 4.1 2,246 2.2 67 44.5 91 2.5 1,420 Fourth 3.5 6.9 2,466 9.8 85 43.0 171 2.6 1,457 Highest 3.7 14.1 2,935 50.2 108 58.6 415 4.2 1,850 Total 15-49 3.4 6.9 11,606 19.4 392 51.0 798 2.9 7,405 50-59 5.8 1.0 1,082 0.7 63 * 11 4.4 1,029 Total 15-59 3.6 6.4 12,688 16.8 454 50.5 809 3.1 8,435 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 Means are calculated excluding respondents who gave non-numeric responses. 236 • HIV/AIDS-related Knowledge, Attitudes, and Behaviour Table 12.6 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, percentage reporting that a condom was used the last time they paid for sexual intercourse, according to age, Ethiopia DHS 2016 Among all men: Among men who paid for sex in the past 12 months: Age 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 15-24 1.0 0.7 4,455 (94.4) 30 15-19 0.5 0.5 2,572 * 13 20-24 1.7 0.9 1,883 (90.3) 17 25-29 2.9 1.0 1,977 (73.5) 20 30-39 3.2 1.0 3,020 (72.9) 29 40-49 4.3 0.5 2,154 * 11 Total 15-49 2.5 0.8 11,606 81.0 90 50-59 4.8 0.3 1,082 * 3 Total 15-59 2.7 0.7 12,688 79.0 93 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 • 237 Table 12.7.1 Coverage of prior HIV testing: Women Percentage of women age 15-49 who know where to obtain an HIV test, percent distribution of women by testing status and by whether they received the results of the last test, percentage of women ever tested, and percentage of women who were tested in the past 12 months and received the results of the last test, according to background characteristics, Ethiopia DHS 2016 Percentage who know where to obtain 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 68.3 34.1 3.6 62.3 100.0 37.7 18.0 6,143 15-19 61.7 22.4 2.9 74.8 100.0 25.2 12.4 3,381 20-24 76.5 48.4 4.5 47.1 100.0 52.9 24.9 2,762 25-29 73.2 49.1 5.0 45.9 100.0 54.1 24.4 2,957 30-39 69.3 43.3 4.6 52.1 100.0 47.9 20.3 4,277 40-49 67.2 38.5 3.5 58.0 100.0 42.0 16.7 2,306 Marital status Never married 68.9 27.9 2.9 69.1 100.0 30.9 14.3 4,036 Ever had sex 87.3 66.3 1.9 31.8 100.0 68.2 38.0 401 Never had sex 66.9 23.7 3.1 73.3 100.0 26.7 11.7 3,636 Married/living together 69.0 43.4 4.7 51.8 100.0 48.2 21.3 10,223 Divorced/separated/widowed 73.1 50.3 3.2 46.5 100.0 53.5 22.8 1,423 Residence Urban 91.6 67.8 2.6 29.6 100.0 70.4 36.1 3,476 Rural 63.0 32.2 4.6 63.3 100.0 36.7 15.0 12,207 Region Tigray 89.0 61.6 4.5 33.8 100.0 66.2 32.1 1,129 Affar 62.3 37.5 3.1 59.5 100.0 40.5 23.5 128 Amhara 77.2 49.1 4.0 46.8 100.0 53.2 20.8 3,714 Oromiya 55.4 28.4 4.0 67.6 100.0 32.4 15.4 5,701 Somali 43.4 12.8 1.1 86.1 100.0 13.9 8.5 459 Benishangul-Gumuz 73.5 43.6 2.9 53.4 100.0 46.6 23.5 160 SNNPR 73.8 36.5 5.7 57.8 100.0 42.2 17.6 3,288 Gambela 80.2 58.2 2.6 39.3 100.0 60.7 33.5 44 Harari 81.3 53.6 4.5 41.9 100.0 58.1 29.3 38 Addis Ababa 95.1 71.6 1.5 26.8 100.0 73.2 34.8 930 Dire Dawa 80.8 60.9 2.6 36.5 100.0 63.5 39.0 90 Education No education 59.0 31.4 4.3 64.3 100.0 35.7 13.6 7,498 Primary 71.9 39.8 4.2 56.0 100.0 44.0 20.4 5,490 Secondary 91.1 57.6 4.0 38.4 100.0 61.6 30.3 1,817 More than secondary 96.7 79.3 2.6 18.1 100.0 81.9 44.2 877 Wealth quintile Lowest 50.7 21.2 3.2 75.6 100.0 24.4 8.5 2,633 Second 59.6 28.4 4.9 66.7 100.0 33.3 12.0 2,809 Middle 63.8 33.2 3.8 63.0 100.0 37.0 14.6 2,978 Fourth 72.8 41.0 5.9 53.1 100.0 46.9 21.0 3,100 Highest 89.1 64.1 3.1 32.8 100.0 67.2 34.4 4,163 Total 15-49 69.3 40.1 4.1 55.8 100.0 44.2 19.7 15,683 1 Includes ‘don’t know/missing’. 238 • HIV/AIDS-related Knowledge, Attitudes, and Behaviour Table 12.7.2 Coverage of prior HIV testing: Men Percentage of men age 15-49 who know where to get an HIV test, percent distribution of men 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, Ethiopia DHS 2016 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 79.2 28.9 2.0 69.1 100.0 30.9 14.7 4,455 15-19 73.7 18.2 1.6 80.2 100.0 19.8 8.9 2,572 20-24 86.6 43.7 2.5 53.8 100.0 46.2 22.8 1,883 25-29 88.4 56.1 2.9 41.0 100.0 59.0 27.6 1,977 30-39 85.9 50.8 3.1 46.1 100.0 53.9 20.4 3,020 40-49 87.9 48.4 3.2 48.4 100.0 51.6 17.7 2,154 Marital status Never married 80.6 32.6 1.7 65.8 100.0 34.2 16.6 4,882 Ever had sex 95.2 61.6 1.4 37.0 100.0 63.0 36.1 1,061 Never had sex 76.6 24.5 1.7 73.7 100.0 26.3 11.2 3,821 Married/Living together 86.5 49.9 3.4 46.7 100.0 53.3 20.3 6,441 Divorced/separated/widowed 90.5 60.4 4.2 35.4 100.0 64.6 29.6 282 Residence Urban 94.6 64.8 2.2 33.0 100.0 67.0 33.2 2,303 Rural 81.5 37.4 2.8 59.8 100.0 40.2 15.4 9,302 Region Tigray 89.6 55.8 2.5 41.6 100.0 58.4 24.6 708 Affar 90.9 49.9 1.4 48.7 100.0 51.3 29.1 82 Amhara 91.0 52.7 1.6 45.7 100.0 54.3 23.4 2,914 Oromiya 76.9 33.0 3.0 63.9 100.0 36.1 14.8 4,409 Somali 68.8 14.7 0.3 85.0 100.0 15.0 7.6 301 Benishangul-Gumuz 70.6 47.2 2.2 50.6 100.0 49.4 23.4 118 SNNPR 86.2 40.9 3.9 55.2 100.0 44.8 14.7 2,371 Gambela 86.4 61.9 2.5 35.7 100.0 64.3 36.6 35 Harari 77.8 31.3 3.4 65.3 100.0 34.7 13.7 29 Addis Ababa 98.3 71.1 1.9 27.0 100.0 73.0 40.4 573 Dire Dawa 92.2 60.3 2.5 37.2 100.0 62.8 35.8 66 Education No education 77.2 34.1 3.0 62.8 100.0 37.2 12.5 3,203 Primary 82.1 36.1 2.6 61.3 100.0 38.7 15.2 5,608 Secondary 95.2 60.9 2.3 36.8 100.0 63.2 30.9 1,785 More than secondary 97.6 76.3 2.6 21.1 100.0 78.9 39.4 1,010 Wealth quintile Lowest 74.2 24.8 2.8 72.4 100.0 27.6 7.7 1,839 Second 78.6 33.4 3.0 63.6 100.0 36.4 11.1 2,118 Middle 80.9 37.7 2.0 60.3 100.0 39.7 15.5 2,246 Fourth 87.3 45.3 3.3 51.4 100.0 48.6 21.1 2,466 Highest 94.1 62.9 2.3 34.8 100.0 65.2 32.5 2,935 Total 15-49 84.1 42.9 2.7 54.5 100.0 45.5 19.0 11,606 50-59 84.9 44.9 2.5 52.7 100.0 47.3 14.5 1,082 Total 15-59 84.2 43.0 2.7 54.3 100.0 45.7 18.6 12,688 1 Includes ‘don’t know/missing’. HIV/AIDS-related Knowledge, Attitudes, and Behaviour • 239 Table 12.8 Coverage of prior HIV testing among married women Percentage of currently married women age 15-49 ever tested before getting married or living with a partner, according to background characteristics, Ethiopia DHS 2016 Background characteristic Percentage ever tested Number of currently married women Residence Urban 56.9 1,658 Rural 18.2 8,565 Region Tigray 37.4 658 Affar 24.9 96 Amhara 33.7 2,414 Oromiya 16.9 3,987 Somali 2.9 324 Benishangul-Gumuz 19.6 114 SNNPR 20.1 2,173 Gambela 35.2 29 Harari 31.4 25 Addis Ababa 67.9 355 Dire Dawa 32.6 50 Education No education 13.6 6,253 Primary 32.7 2,895 Secondary 61.5 654 More than secondary 71.5 421 Wealth quintile Lowest 12.0 1,953 Second 15.1 2,074 Middle 18.6 2,057 Fourth 24.4 1,999 Highest 50.6 2,140 Total 24.5 10,223 240 • HIV/AIDS-related Knowledge, Attitudes, and Behaviour Table 12.9 Pregnant women counselled and tested for HIV Among all women age 15-49 who gave birth in the 2 years before the survey, percentage who received HIV pretest counselling, percentage who received an HIV test during antenatal care for their most recent birth by whether they received their results and post-test counselling, and percentage who received an HIV test during an ANC visit or labour for their most recent birth by whether they received their test results, according to background characteristics, Ethiopia DHS 2016 Percentage who received counselling on HIV during antenatal care1 Percentage who were tested for HIV during antenatal care and who: Percentage who received counselling on HIV and an HIV test during ANC, and the results Percentage who had an HIV test during ANC or labour and who:2 Number of women who gave birth in the past two years3 Background characteristic Received results and received post-test counselling Received results and did not receive post- test counselling Did not receive results Received results Did not receive results Age 15-24 22.5 22.9 10.8 3.2 17.5 36.0 3.5 1,260 15-19 21.0 20.0 10.3 1.0 16.7 32.5 1.7 281 20-24 23.0 23.8 11.0 3.8 17.7 36.9 4.0 979 25-29 25.5 23.1 10.9 3.6 21.4 36.1 3.9 1,264 30-39 23.1 21.5 9.6 3.0 19.5 32.5 3.2 1,512 40-49 17.9 12.8 12.3 2.8 14.0 28.9 1.7 271 Marital status Never married (15.9) (19.2) (27.9) (0.0) (15.9) (57.1) (8.2) 31 Married or living together 23.5 21.9 10.6 3.3 19.2 34.3 3.4 4,102 Divorced/separated/ widowed 19.9 22.5 5.0 3.3 18.7 31.2 3.3 175 Residence Urban 58.8 56.6 19.7 3.6 55.5 78.9 3.1 520 Rural 18.4 17.1 9.2 3.2 14.1 28.2 3.4 3,788 Region Tigray 46.6 49.6 20.1 3.4 44.0 71.1 3.6 314 Affar 14.0 16.9 9.9 3.2 11.4 28.2 3.2 43 Amhara 32.5 31.5 17.8 6.3 28.9 51.3 5.4 789 Oromiya 13.7 11.6 6.5 1.4 9.9 20.1 2.0 1,915 Somali 5.7 5.8 7.4 1.1 4.7 14.2 0.9 178 Benishangul-Gumuz 23.7 21.2 8.3 2.0 18.5 31.1 2.3 45 SNNPR 24.4 21.6 8.7 5.1 17.2 32.9 5.3 876 Gambela 22.4 31.9 22.0 1.2 21.5 55.3 1.2 10 Harari 27.5 41.3 4.6 2.0 25.9 47.6 2.9 10 Addis Ababa 78.3 76.9 18.1 1.9 76.4 95.8 1.9 110 Dire Dawa 40.5 41.5 17.1 2.8 36.4 60.2 2.6 18 Education No education 15.1 13.4 8.4 2.6 11.7 23.5 2.5 2,606 Primary 30.0 29.4 11.6 3.2 24.8 43.3 4.3 1,319 Secondary 51.5 49.5 19.7 8.8 45.0 72.0 7.2 262 More than secondary 65.7 62.1 24.5 5.4 60.3 88.4 3.9 121 Wealth quintile Lowest 9.4 8.3 6.0 2.2 7.2 15.2 2.2 1,011 Second 15.1 13.7 9.5 2.5 11.2 24.8 2.9 943 Middle 19.1 17.5 9.9 3.3 14.1 31.0 3.9 890 Fourth 27.9 28.1 11.8 4.6 21.6 42.1 4.5 796 Highest 56.2 52.2 17.8 4.1 52.2 71.8 4.0 667 Total 15-49 23.3 21.9 10.5 3.2 19.1 34.3 3.4 4,308 Note: Figures in parentheses are based on 25-49 unweighted cases. 1 In this context, “pretest counselling” means that someone talked with the respondent about all three of the following topics: 1) babies getting HIV from their mother, 2) preventing the virus, and 3) getting tested for HIV. 2 Women are asked whether they received an HIV test during labour only if they gave birth in a health facility. 3 Denominator for percentages includes women who did not receive antenatal care for their last birth in the past 2 years. HIV/AIDS-related Knowledge, Attitudes, and Behaviour • 241 Table 12.10 Male circumcision Percent distribution of men age 15-49 by circumcision status and provider of circumcision, and percentage of men circumcised, according to background characteristics, Ethiopia DHS 2016 Circumcised by: Not circumcised Don’t know/ missing circumcision status Total Percentage of men circumcised1 Number of men Background characteristic Health worker/ professional Traditional practitioner/ family friend Other/don’t know Age 15-24 21.0 63.3 3.5 11.7 0.4 100.0 87.9 4,455 15-19 21.4 61.1 3.8 13.2 0.5 100.0 86.3 2,572 20-24 20.5 66.4 3.2 9.6 0.2 100.0 90.1 1,883 25-29 18.3 69.7 3.5 8.2 0.3 100.0 91.5 1,977 30-39 14.8 76.2 2.9 6.0 0.1 100.0 93.9 3,020 40-49 8.4 82.6 3.4 5.4 0.2 100.0 94.4 2,154 Residence Urban 20.0 69.5 6.7 3.5 0.2 100.0 96.3 2,303 Rural 15.7 71.8 2.5 9.7 0.3 100.0 90.0 9,302 Region Tigray 2.9 83.4 11.0 2.6 0.1 100.0 97.3 708 Affar 12.7 84.9 1.3 0.9 0.2 100.0 98.9 82 Amhara 5.3 84.3 3.6 6.2 0.6 100.0 93.2 2,914 Oromiya 14.3 74.7 1.9 8.9 0.1 100.0 90.9 4,409 Somali 7.1 91.5 0.8 0.6 0.0 100.0 99.4 301 Benishangul-Gumuz 2.8 75.5 17.3 4.1 0.2 100.0 95.6 118 SNNPR 37.6 46.3 0.7 15.3 0.1 100.0 84.6 2,371 Gambela 14.9 54.2 2.8 27.9 0.1 100.0 72.0 35 Harari 13.3 68.9 16.6 0.7 0.4 100.0 98.9 29 Addis Ababa 30.4 55.5 12.0 1.3 0.8 100.0 97.9 573 Dire Dawa 14.9 78.3 6.3 0.5 0.1 100.0 99.4 66 Religion Orthodox 10.5 78.8 5.7 4.7 0.4 100.0 94.9 5,160 Catholic 16.5 63.4 0.1 20.0 0.0 100.0 80.0 78 Protestant 32.2 47.8 0.7 19.0 0.2 100.0 80.7 2,561 Muslim 14.3 78.9 2.0 4.8 0.1 100.0 95.2 3,649 Traditional (4.4) (16.7) (0.2) (78.6) (0.0) 100.0 21.4 31 Other 21.5 46.3 0.0 32.2 0.0 100.0 67.8 128 Ethnic group Affar 10.0 87.6 1.4 0.7 0.2 100.0 99.1 63 Amhara 7.2 82.1 4.5 5.7 0.5 100.0 93.8 3,497 Guragie 16.6 72.9 9.2 1.3 0.0 100.0 98.6 311 Hadiya 23.4 72.1 1.2 2.5 0.8 100.0 96.7 217 Oromo 15.1 75.2 2.2 7.3 0.2 100.0 92.5 4,175 Sidama 54.1 24.5 0.4 21.1 0.0 100.0 78.9 490 Somalie 6.5 92.1 0.7 0.7 0.0 100.0 99.3 299 Tigray 4.9 81.6 10.8 2.3 0.3 100.0 97.4 778 Welaita 75.5 21.7 0.0 2.9 0.0 100.0 97.1 321 Others 25.4 50.2 1.4 23.0 0.0 100.0 77.0 1,455 Total 15-49 16.6 71.4 3.3 8.5 0.3 100.0 91.3 11,606 50-59 7.3 85.4 2.4 4.7 0.2 100.0 95.1 1,082 Total 15-59 15.8 72.6 3.3 8.1 0.3 100.0 91.6 12,688 Note: Figures in parentheses are based on 25-49 unweighted cases. 1 Includes all men who report they are circumcised, regardless of provider. 242 • HIV/AIDS-related Knowledge, Attitudes, and Behaviour Table 12.11 Self-reported prevalence of sexually-transmitted infections (STIs) and STI symptoms Among women and men age 15-49 who ever had sexual intercourse, percentage reporting having an STI and/or symptoms of an STI in the past 12 months, according to background characteristics, Ethiopia DHS 2016 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 or ulcer STI/ genital discharge/ sore or ulcer Number of women who ever had sexual inter- course STI Bad smelling/ abnormal discharge from penis Genital sore or ulcer STI/ abnormal discharge from penis/ sore or ulcer Number of men who ever had sexual inter- course Age 15-24 0.3 2.2 1.8 3.4 2,865 1.0 2.2 1.8 3.1 1,117 15-19 0.3 1.9 1.3 2.5 832 0.1 2.2 1.4 3.6 209 20-24 0.3 2.3 1.9 3.7 2,033 1.3 2.2 1.9 3.0 907 25-29 0.3 2.4 2.0 3.9 2,702 2.2 1.4 0.8 3.2 1,602 30-39 0.2 2.4 2.1 3.8 4,175 2.4 2.4 1.9 3.9 2,916 40-49 0.4 3.5 2.4 4.9 2,291 2.7 2.4 1.6 3.7 2,134 Marital status Never married 0.4 3.3 4.4 6.4 401 2.1 2.3 1.9 3.2 1,061 Married or living together 0.3 2.5 1.9 3.8 10,217 2.4 2.2 1.5 3.7 6,433 Divorced/separated/ widowed 0.4 2.5 2.2 4.3 1,415 0.2 2.1 1.5 2.3 274 Male circumcision Circumcised1 na na na na na 2.3 2.3 1.7 3.8 7,221 Not circumcised na na na na na 1.0 0.4 0.0 1.4 534 Residence Urban 0.5 3.4 2.5 5.4 2,332 1.7 1.8 1.1 3.0 1,545 Rural 0.3 2.3 1.9 3.6 9,701 2.4 2.3 1.7 3.7 6,224 Region Tigray 1.2 2.4 1.9 4.4 876 0.4 0.4 0.5 0.9 445 Affar 0.3 1.1 1.3 2.4 110 0.6 1.9 0.7 2.5 67 Amhara 0.1 3.6 2.2 4.9 2,978 0.9 2.6 1.1 3.3 1,957 Oromiya 0.1 2.1 2.2 3.6 4,521 4.8 3.1 2.8 5.7 2,989 Somali 1.8 3.8 3.5 4.7 358 1.9 2.7 0.9 3.0 186 Benishangul-Gumuz 0.3 1.3 0.9 1.5 128 0.2 0.5 0.6 0.9 91 SNNPR 0.2 2.1 1.6 3.1 2,356 0.2 1.0 0.5 1.5 1,519 Gambela 0.8 2.6 1.6 3.7 37 1.2 1.5 1.1 2.8 27 Harari 0.9 1.5 0.5 1.8 30 4.0 4.2 3.6 5.4 19 Addis Ababa 1.0 3.0 2.0 4.4 572 0.8 0.7 0.3 1.3 422 Dire Dawa 1.2 2.1 2.3 3.7 67 1.3 1.6 0.7 2.2 46 Education No education 0.2 2.2 1.8 3.3 7,095 2.5 2.9 2.2 3.8 2,737 Primary 0.5 2.8 2.1 4.3 3,500 2.2 1.7 1.4 3.5 3,266 Secondary 0.4 2.4 2.5 4.1 866 1.8 2.1 0.6 3.7 971 More than secondary 0.7 5.8 3.9 9.3 573 2.1 2.0 1.3 3.1 793 Wealth quintile Lowest 0.4 2.3 2.3 3.5 2,254 2.1 2.2 1.9 3.1 1,270 Second 0.1 2.2 1.9 3.6 2,313 2.7 2.2 1.5 3.9 1,514 Middle 0.1 2.2 1.5 3.1 2,354 2.1 2.7 2.0 3.7 1,466 Fourth 0.4 2.3 1.9 3.6 2,297 2.5 2.2 1.6 4.1 1,553 Highest 0.4 3.6 2.5 5.6 2,815 1.8 1.8 1.1 3.2 1,965 Total 15-49 0.3 2.6 2.0 3.9 12,033 2.2 2.2 1.6 3.6 7,768 50-59 na na na na na 2.3 1.1 1.5 2.5 1,080 Total 15-59 na Na na na na 2.2 2.1 1.5 3.5 8,849 na = Not applicable Notes: Total includes 13 cases with missing information on male circumcision. 1 Includes all men who report they are circumcised, regardless of provider. HIV/AIDS-related Knowledge, Attitudes, and Behaviour • 243 Table 12.12 Women and men seeking treatment for STIs Percentage of women and men age 15-49 reporting an STI or symptoms of an STI in the past 12 months who sought advice or treatment, Ethiopia DHS 2016 Source of advice or treatment Percentage of women Percentage of men Clinic/hospital/private doctor/other health professional 31.8 31.7 Advice or medicine from shop/pharmacy 0.9 2.6 Advice or treatment from any other source 0.5 0.0 No advice or treatment 66.7 65.7 Number with STI or symptoms of STI 474 279 Table 12.13 Comprehensive knowledge about HIV among young people Percentage of young women and young men age 15-24 with comprehensive knowledge about HIV, according to background characteristics, Ethiopia DHS 2016 Women age 15-24 Men age 15-24 Background characteristic Percentage with compre- hensive knowledge of HIV1 Number of women Percentage with compre- hensive knowledge of HIV1 Number of men Age 15-19 24.0 3,381 37.6 2,572 15-17 22.9 2,050 34.3 1,589 18-19 25.8 1,331 43.0 983 20-24 24.6 2,762 41.1 1,883 20-22 25.0 1,808 40.1 1,216 23-24 23.8 954 42.9 667 Marital status Never married 28.3 3,500 39.2 3,889 Ever had sex 32.6 230 44.9 564 Never had sex 28.0 3,269 38.2 3,325 Ever married 19.0 2,643 38.2 566 Residence Urban 41.7 1,467 47.7 867 Rural 18.8 4,675 37.0 3,588 Education No education 8.4 1,230 27.2 543 Primary 21.4 3,333 37.3 2,744 Secondary 40.1 1,184 46.1 910 More than secondary 51.1 396 58.1 258 Total 15-24 24.3 6,143 39.1 4,455 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 transmission or prevention of HIV. The components of comprehensive knowledge are presented in Tables 12.1, and 12.2. 244 • HIV/AIDS-related Knowledge, Attitudes, and Behaviour Table 12.14 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, Ethiopia DHS 2016 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 6.3 3,381 na na 0.8 2,572 na na 15-17 5.5 2,050 na na 0.6 1,589 na na 18-19 7.4 1,331 34.5 1,331 1.3 983 11.1 983 20-24 13.2 2,762 43.1 2,762 1.3 1,883 12.0 1,883 20-22 13.5 1,808 43.8 1,808 1.5 1,216 11.7 1,216 23-24 12.7 954 41.7 954 1.0 667 12.5 667 Residence Urban 3.0 1,467 21.7 1,004 0.4 867 11.9 582 Rural 11.4 4,675 46.4 3,089 1.2 3,588 11.6 2,285 Education No education 22.1 1,230 66.4 974 0.6 543 12.7 383 Primary 8.2 3,333 42.6 1,926 1.1 2,744 12.3 1,555 Secondary 2.3 1,184 18.7 822 1.3 910 10.5 686 More than secondary 1.0 396 7.5 370 0.4 258 9.4 243 Total 9.4 6,143 40.3 4,092 1.0 4,455 11.7 2,866 na = Not available. Table 12.15 Premarital sexual intercourse among young people Among never-married women and men age 15-24, percentage who have never had sexual intercourse, according to background characteristics, Ethiopia DHS 2016 Women age 15-24 Men age 15-24 Background characteristic Percentage who have never had sexual intercourse Number of never married women Percentage who have never had sexual intercourse Number of never married men Age 15-19 96.2 2,642 93.2 2,527 15-17 97.3 1,817 96.5 1,581 18-19 93.6 825 87.7 946 20-24 84.9 858 71.1 1,362 20-22 84.9 602 74.9 978 23-24 84.8 256 61.4 383 Residence Urban 89.1 1,087 76.5 820 Rural 95.4 2,413 87.9 3,069 Education No education 95.2 341 89.0 408 Primary 94.6 1,990 89.4 2,418 Secondary 93.5 879 80.5 828 More than secondary 82.9 289 56.5 234 Total 15-24 93.4 3,500 85.5 3,889 HIV/AIDS-related Knowledge, Attitudes, and Behaviour • 245 Table 12.16.1 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, and percentage who had intercourse in the past 12 months with a person who was neither their husband nor lived with them; and among young women age 15-24 who had sexual intercourse in the past 12 months with a non-marital, non-cohabiting partner, percentage who used a condom during last sexual intercourse with such a partner, Ethiopia DHS 2016 Women age 15-24 Women age 15-24 who had intercourse in the past 12 months with a person who was neither their husband nor lived with them Background characteristic Percentage who had 2+ partners in the past 12 months Percentage who had intercourse in the past 12 months with a person who was neither their husband nor lived with them Number of women Percentage who reported using a condom during last sexual intercourse with such a partner Number of women Age 15-19 0.3 2.1 3,381 30.3 71 15-17 0.2 1.6 2,050 (16.9) 32 18-19 0.4 3.0 1,331 41.2 39 20-24 0.3 3.7 2,762 19.4 103 20-22 0.2 3.8 1,808 18.1 68 23-24 0.4 3.7 954 21.9 35 Marital status Never married 0.2 3.6 3,500 21.8 127 Ever married 0.3 1.8 2,643 29.3 47 Residence Urban 0.6 7.5 1,467 30.7 110 Rural 0.2 1.4 4,675 12.1 64 Education No education 0.4 1.0 1,230 * 12 Primary 0.3 2.2 3,333 16.4 72 Secondary 0.2 4.2 1,184 29.2 49 More than secondary 0.2 10.3 396 26.7 41 Total 15-24 0.3 2.8 6,143 23.8 175 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. 246 • HIV/AIDS-related Knowledge, Attitudes, and Behaviour Table 12.16.2 Multiple sexual partners and higher-risk sexual behaviour 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, and percentage who had intercourse in the past 12 months with a person who was neither their wife nor lived with them; among those having more than one partner in the past 12 months, percentage reporting that a condom was used during last intercourse; and among young men age 15-24 who had sexual intercourse in the past 12 months with a non-marital, non-cohabiting partner, percentage who used a condom during last sexual intercourse with such a partner, Ethiopia DHS 2016 Men age 15-24 Men age 15-24 who had 2+ partners in the past 12 months Men age 15-24 who had intercourse in the past 12 months with a person who was neither their wife nor lived with them Background characteristic Percentage who had 2+ partners in the past 12 months Percentage who had intercourse in the past 12 months with a person who was neither their wife nor lived with them Number of men Percentage who reported using a condom at last intercourse Number of men Percentage who reported using a condom during last sexual intercourse with such a partner Number of men Age 15-19 0.8 4.5 2,572 (56.9) 20 57.0 115 15-17 0.1 2.2 1,589 * 1 45.8 35 18-19 2.0 8.1 983 (57.7) 19 62.0 80 20-24 3.1 15.2 1,883 41.5 58 53.5 287 20-22 2.6 14.5 1,216 (52.5) 31 48.4 177 23-24 4.1 16.6 667 (29.0) 27 61.5 110 Marital status Never married 1.5 9.7 3,889 54.9 58 54.9 376 Ever married 3.6 4.7 566 * 21 (48.0) 26 Residence Urban 3.0 15.9 867 65.0 26 64.0 137 Rural 1.5 7.4 3,588 36.0 53 49.6 265 Education No education 1.4 5.3 543 * 8 (25.5) 29 Primary 1.2 6.7 2,744 (54.4) 32 52.7 185 Secondary 2.3 11.8 910 (59.4) 21 53.5 107 More than secondary 6.8 31.5 258 * 18 70.2 81 Total 15-24 1.8 9.0 4,455 45.5 78 54.5 402 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. Table 12.17 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 background characteristics, Ethiopia DHS 2016 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 Number of women Percentage who have been tested for HIV in the past 12 months Number of men Age 15-19 25.3 703 18.0 148 15-17 22.1 233 20.7 38 18-19 26.9 470 17.1 110 20-24 27.7 1,804 30.7 743 20-22 26.6 1,142 30.5 383 23-24 29.6 662 30.8 360 Marital status Never married 42.9 129 37.1 377 Ever married 26.2 2,378 22.3 514 Total 27.0 2,507 28.6 891 HIV/AIDS-related Knowledge, Attitudes, and Behaviour • 247 Table 12.18 HIV tests among children Among children less than 15 years old, percentage who were tested for HIV, according to background characteristics, Ethiopia DHS 2016 Background characteristic Percentage ever tested for HIV Number of children Residence Urban 21.6 2,933 Rural 4.6 27,366 Region Tigray 14.6 1,728 Affar 5.8 271 Amhara 6.6 5,945 Oromiya 5.3 13,020 Somali 2.2 1,288 Benishangul-Gumuz 4.2 336 SNNPR 5.1 6,974 Gambela 11.3 64 Harari 9.9 63 Addis Ababa 22.5 491 Dire Dawa 10.5 119 Mother’s education No education 4.4 22,412 Primary 9.3 6,586 Secondary 18.3 854 More than secondary 28.6 447 Wealth quintile Lowest 2.8 6,826 Second 3.9 6,673 Middle 4.4 6,427 Fourth 6.6 6,048 Highest 17.3 4,325 Total 6.2 30,299 Adult and Maternal Mortality • 249 ADULT AND MATERNAL MORTALITY 13 Key Findings  Adult mortality: Women and men who have reached age 15 have a probability of dying before age 50 of 10% and 12%, respectively.  Pregnancy-related mortality: The pregnancy related mortality ratio was 412 maternal deaths per 100,000 live births for the 7 years before the survey. The decline from the estimate of 871 for the 7 years before the 2000 EDHS or the estimate of 676 for the 7 years before the 2011 EDHS is statistically significant.  Lifetime risk of pregnancy-related death: The lifetime risk of pregnancy-related death (a death related to pregnancy or childbirth) is 21 in 1,000 women in Ethiopia. dult and maternal mortality indicators can be used to assess the health status of a population, especially in developing countries such as Ethiopia. Estimation of these mortality rates requires complete and accurate data on adult and pregnancy-related deaths. In the 2016 EDHS, data were collected on the survivorship of the female respondents’ siblings (sisters or brothers) to obtain an estimate of adult mortality. Questions to determine if deaths among female siblings were pregnancy-related enable the estimation of pregnancy-related mortality, a key indicator of maternal health and well-being, as well as the quality of maternal care. The International Classification of Diseases (ICD-10) defines both maternal and pregnancy-related mortality. The 2016 EDHS results reflect pregnancy-related mortality, which accounts for deaths of women while pregnant, during delivery, or within 42 days of the termination of pregnancy, irrespective of the cause of death (WHO 2011). Thus, the adult and maternal mortality module used in the DHS surveys measures only the timing and not the cause of deaths. The data collected with the 2016 EDHS questionnaire are based on information about deaths during the 2 months after a birth rather than the recommended 42 days following a birth. This chapter presents information on the levels and trends of adult mortality and pregnancy-related mortality in Ethiopia. The chapter includes results estimated from sibling history data collected in the sibling survival module (commonly referred to as the maternal mortality module) that is included in 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, or between the 15th and 50th birthdays. 13.1 SIBLING HISTORY DATA To obtain a sibling history, each respondent was first asked to provide the total number of her mother’s live births. The respondent was then asked to provide a list of all children born to her mother, starting with the first born, and the survival status of each sibling. The current age was collected for each surviving A 250 • Adult and Maternal Mortality sibling. The age at death and number of years since the person’s death were recorded for each deceased sibling. When a respondent could not provide precise information on age at death or years since death, the interviewers were instructed to accept an approximate but quantitative answer. For sisters who died at age 12 or above, three questions were used to determine whether the death was maternity-related: “Was [NAME OF SISTER] pregnant when she died?” and, if not, “Did she die during childbirth?” and, if not, “Did she die within 2 months after the end of a pregnancy or childbirth?” Estimation of adult and pregnancy-related mortality by either direct or indirect means requires reasonably accurate reporting of the respondent’s number of sisters and brothers, the number who have died, and for pregnancy-related mortality, the number of sisters who died of pregnancy related causes. Table 13.1 shows the number of siblings reported by the respondents and the completeness of data on current age, age at death, and years since death. Overall, 84,335 siblings were recorded in the adult mortality section of the 2016 EDHS. Survival status was not reported for only 84 (0.1%) siblings. Among surviving siblings, current age was not reported for 1,387 siblings (2%); for 5% of dead siblings, age at the death and years since death were not reported. Instead of excluding siblings with missing data from further analysis, information on the birth order of siblings in conjunction with other information was used to impute the missing data.1 13.2 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: the number of deaths to respondent’s siblings in each age group is divided by the number of person- years of exposure to the risk of dying in that age group during the 7 years before the survey. The number of deaths by age group is the number of siblings (brothers or sisters) reported as having died within the 7 years before the survey by age at death. 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 7 years before the survey, by sex and 5-year age groups One way to assess the quality of the data used to estimate pregnancy-related mortality is to evaluate the plausibility and stability of overall adult mortality. If estimated rates of overall adult mortality are implausible, rates based on a subset of deaths (pregnancy-related deaths in particular) may have questionable plausibility. The reported ages at death and years since death of the respondents’ brothers and sisters are used to make direct estimates of adult mortality. Age and sex-specific death rates are presented in this report because of the differentials in exposure to the risk of dying. 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 mid-2009 to mid-2016). Nevertheless, age-specific mortality rates obtained in this manner are subject to 1 The imputation procedure was based on the assumption that the reported birth ordering of siblings in the history was correct. The first step was to calculate birth dates for each living sibling with a reported age and each dead sibling with complete information on age at death and years since death. For a sibling missing these data, a birth date was imputed within the range defined by the birth dates of the bracketing siblings. In the case of living siblings, an age was then calculated from the imputed birth date. For dead siblings, if either age at death or years since death were reported, the information was combined with the birth date to produce the missing information. If both pieces of information were missing, the distribution of the ages at death for siblings (for whom years since death were not reported but age at death was reported ) was used as a basis for imputing age at death. Adult and Maternal Mortality • 251 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. Table 13.2 shows direct estimates of age-specific mortality rates among women and men age 15-49 for the 7-year period before the survey. Overall, the level of adult mortality among men is higher (3.54 deaths per 1,000 populations) than among women (2.74 deaths per 1,000 population). Rates by age groups show some inconsistencies, probably due to the quality of declaration of age at death of siblings. Trends: Table 13.3 shows the probability of dying between exact ages of 15 and 50, 35q15, which is the probability of a woman or man who has just reached age 15 dying before age 50, if age-specific death rates in the 7 years before the survey are held constant. The 2016 EDHS data show that women have lower probabilities of dying than men: 100 of 1,000 women age 15 and 124 of 1,000 men age 15 would be expected to die before age 50. Since 2000, the probability of dying between the exact ages of 15 and 50 has declined by more than half for both women and men. For women, the probability declined from 221 per 1,000 women in the 7 years before 2000, to 100 per 1,000 women in the 7 years before 2016. The corresponding rate for men decreased from 275 per 1,000 men in the 7 years before 2000 to 124 per 1000 men in the 7 years before 2016. 13.3 DIRECT ESTIMATES OF PREGNANCY-RELATED MORTALITY Pregnancy-related mortality rate The number of pregnancy-related deaths per 1,000 women age 15-49. Pregnancy-related mortality rates by 5-year age groups are calculated by dividing the number of pregnancy-related 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 before the survey. The number of deaths is the number of sisters reported as having died in the 7 years before the survey either during pregnancy or delivery, or in the 2 months after the delivery, 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 7 years before the survey, by 5 year age groups Pregnancy-related mortality ratio The number of pregnancy-related deaths per 100,000 live births. The pregnancy-related mortality ratio is calculated by dividing the age-standardised pregnancy-related mortality rate for women age 15-49 in the 7 years before the survey by the general fertility rate (GFR) for the same time period. Pregnancy-related deaths are a subset of all female deaths, that are defined as any deaths that occurred during pregnancy or childbirth, or within 42 days after the birth or termination of a pregnancy. Estimates of pregnancy-related mortality are 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). Age-specific estimates of pregnancy-related mortality from reported survivorship of sisters are shown in Table 13.4 for the 7-year period before the 2016 survey. Table 13.4 shows that the pregnancy-related mortality rate among women age 15-49 is 0.66 deaths per 1,000 woman-years of exposure. By 5-year age groups, the pregnancy-related mortality rate is highest among women in the 30-34 age group (1.10), followed by women in the 40-44 age group (0.78). The 252 • Adult and Maternal Mortality overall percentage of female deaths due to pregnancy-related causes is 25%; this percentage varies by age and ranges from 14% among women age 45-49 to 30% among women age 30-34. However, this age- specific pattern should be interpreted with caution because of the very small number of pregnancy-related deaths (118) among women of all reproductive ages. The estimated pregnancy-related mortality ratio (PRM) is 412 deaths per 100,000 live births during the 7- year period before the survey (with a 95% confidence interval of 273 to 551). Thus, for every 1,000 live births in Ethiopia during the 7 years before the 2016 EDHS, approximately four women died during pregnancy, childbirth, or within 2 months after childbirth. The lifetime risk of pregnancy-related death (0.021) indicates that of 1,000 women of exact age 15, about 21 (one per 48 woman) would die before age 50 during pregnancy, childbirth, or within 2 months of childbirth. 13.4 TRENDS IN PREGNANCY-RELATED MORTALITY In accordance with the WHO definition2, a pregnancy-related death is defined as the death of a woman while pregnant or during delivery, or in the 42 days after the delivery or within 42 days of termination of pregnancy, if the death is not due to an accident or violence. However, the term maternal mortality used in previous EDHS surveys corresponds to pregnancy-related mortality. The WHO defines a pregnancy- related death as the death of a woman while pregnant or within 42 days of termination of pregnancy, irrespective of the cause of death (http://www.who.int/healthinfo/statistics/indmaternalmortality/en/). In compliance with this definition, the sibling survival module used in DHS surveys measures only the timing of death and not the cause of death. Thus, the data collected in previous EDHS surveys refer to deaths within 2 months after a birth rather than 42 days after a birth, and current estimates are comparable to estimates from previous EDHS surveys. Figure 13.1 presents estimates of the pregnancy-related mortality ratio (PRMR) with confidence intervals for current and previous EDHS surveys. Estimates from EDHS surveys indicate a substantial decline in the pregnancy-related mortality ratio in Ethiopia since 2000, from 871 deaths per 100,000 live births in the 7 years before the 2000 EDHS survey to 673 deaths per 100,000 live births in the 7 years before the 2005 EDHS survey, 676 deaths per 100,000 live births in the 7 years before the 2011 EDHS survey, and 412 deaths per 100,000 live births in the 7 years before the 2016 EDHS survey. The decline, both between 2000 and 2016 and between 2011 and 2016, is statistically significant. LIST OF TABLES For more information on adult and maternal mortality, see the following tables:  Table 13.1 Completeness of information on siblings  Table 13.2 Adult mortality rates  Table 13.3 Adult mortality probabilities  Table 13.4 Pregnancy-related mortality rates 2 http://www.who.int/healthinfo/statistics/indmaternalmortality/en/ Figure 13.1 Trends in pregnancy-related mortality ratio (PRMR) with confidence intervals 1,039 799 810 551 703 548 541 273 871 673 676 412 - 200 400 600 800 1,000 1,200 2000 EDHS (1993-2000) 2005 EDHS (1998-2005) 2011 EDHS (2004-2011) 2016 EDHS (2009-2016) Pregnancy-related deaths per 100,000 live births Adult and Maternal Mortality • 253 Table 13.1 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), Ethiopia DHS 2016 Sisters Brothers All siblings Number Percent Number Percent Number Percent All siblings 39,880 100.0 44,455 100.0 84,335 100.0 Living 33,272 83.4 35,913 80.8 69,185 82.0 Dead 6,583 16.5 8,483 19.1 15,066 17.9 Survival status unknown 25 0.1 59 0.1 84 0.1 Living siblings 33,272 100.0 35,913 100.0 69,185 100.0 Age reported 32,614 98.0 35,184 98.0 67,798 98.0 Age missing 658 2.0 729 2.0 1,387 2.0 Dead siblings 6,583 100.0 8,483 100.0 15,066 100.0 AD and YSD reported 5,845 88.8 7,494 88.3 13,339 88.5 Missing only AD 85 1.3 67 0.8 152 1.0 Missing only YSD 336 5.1 454 5.4 790 5.2 Missing AD and YSD 317 4.8 468 5.5 785 5.2 Table 13.2 Adult mortality rates Direct estimates of female and male mortality rates for the 7-years before the survey, by five-year age groups, Ethiopia DHS 2016 Age Deaths Exposure years Mortality rates1 FEMALE 15-19 77 34,543 2.22 20-24 87 38,862 2.23 25-29 82 35,159 2.32 30-34 107 28,985 3.68 35-39 45 20,199 2.20 40-44 46 12,023 3.85 45-49 31 6,714 4.57 Total 15-49 473 176,485 2.74a MALE 15-19 105 36,865 2.86 20-24 130 40,612 3.19 25-29 110 37,683 2.93 30-34 127 32,069 3.97 35-39 93 22,708 4.11 40-44 80 13,757 5.84 45-49 29 8,047 3.60 Total 15-49 675 191,739 3.54a 1 Expressed per 1,000 population. a Age-adjusted rate. Table 13.3 Adult mortality probabilities The probability of dying between the ages of 15 and 50 for women and men for the 7-years before the survey, Ethiopia DHS 2016 Survey Female 35q151 Male 35q151 2016 EDHS (time period: 2009-2016) 100 (CI: 84-116) 124 (CI: 107-142) 2011 EDHS (time period: 2004-2011) 157 (CI: 137-178) 181 (CI: 162-201) 2005 EDHS (time period: 1998-2005) 217 (CI: 195-239) 207 (CI: 184-229) 2000 EDHS (time period: 1993-2000) 221 (CI: 200-243) 275 (CI: 250-301) CI = Confidence interval. 1 The probability of dying between exact ages 15 and 50, expressed per 1,000 person at age 15. 254 • Adult and Maternal Mortality Table 13.4 Pregnancy-related mortality rates Direct estimates of pregnancy-related mortality rates for the 7 years before the survey, by 5-year age groups, Ethiopia DHS 2016 Age Percentage of female deaths that are pregnancy- related Number of pregnancy- related deaths Exposure years Pregnancy- related mortality rate1 15-19 17.4 13 34,543 0.39 20-24 28.7 25 38,862 0.64 25-29 29.3 24 35,159 0.68 30-34 30.0 32 28,985 1.10 35-39 24.4 11 20,199 0.54 40-44 20.3 9 12,023 0.78 45-49 13.7 4 6,714 0.62 15-49 25.1 118 176,485 0.66a General fertility rate (GFR)2 160a Pregnancy-related mortality ratio (PRM)3 412 (CI: 273-551) Lifetime risk of maternal death4 0.021 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 pregnancy-related 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 before the survey. a Age-adjusted rate. Women’s Empowerment • 255 WOMEN’S EMPOWERMENT 14 Key Findings  Employment and earnings: Forty-eight percent of currently married women age 15-49 were employed in the 12 months before the survey, compared with 99% of currently married men age 15-49. More than half of the men (53%) and just under half of the women (49%) were not paid for their work. The percentage of women who were not paid for their work was highest in the 15-19 age group (66%). Sixty-two percent of the currently married women with cash earnings report that decisions about how their earnings are used are usually made jointly with their husbands. Thirty percent of women make most of these decisions independently.  Ownership of a home and land: Half of all women own a house, either alone or jointly with someone, while just over one-third of women who own a house report that there is a title or deed for the house which includes their name. Similarly, 40 percent of women own land but only one in two of the women who own land say there is a title or deed in their name for the land.  Decision to marry: The majority (61%) of ever-married women say their parents made the decision that they would get married the first time. Only 35% say they made the decision to marry by themselves.  Schooling after marriage: Twenty-five percent of women were attending school at the time they first married, and the majority (75%) of these women stopped going to school after they married.  Participation in decision making: Seventy-one percent of currently married women participate in three specified household decisions (own health care, household purchases, and visits to their family), while 10% are not involved in any of these decisions.  Reproductive health: Use of contraception and access to antenatal care, delivery assistance, and postnatal care increase with women’s empowerment. his chapter explores women’s empowerment in terms of employment, earnings, control over earnings, and magnitude of earnings relative to those of their partners. The chapter presents information about ever-married women’s involvement in the decision to marry, their participation in schooling after marriage, and men’s participation in household chores. The chapter also employs responses to questions on women’s participation in household decision making and attitudes towards wife beating to define two separate indices of women’s empowerment. These indices are used to explore how selected demographic and health indicators vary by women’s empowerment. T 256 • Women’s Empowerment The Government of Ethiopia is strongly committed to promoting gender equality and women’s empowerment, and has adopted a number of institutional and policy measures that support these goals. The 1997 Ethiopian Constitution, the 1993 Ethiopian National Policy on Women, the 2005 Family Law, and the Growth and Transformation Plan (GTP) I and II are among the milestones that further gender equality and empowerment. To strengthen accountability, the government also recently issued proclamation No. 916/2015 that requires all government institutions to address women’s issues in policies, laws, and development programs and projects (FDRE 2015). 14.1 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 Forty-eight percent of currently married women age 15-49 were employed in the 12 months before the survey, compared with 99% of currently married men in the same age group (Table 14.1). Women are more likely than men to be paid in cash only for their work (35% and 23%, respectively) but slightly less likely to receive cash and in-kind payments (7% and 10%, respectively). More than half of married men (53%) and just under half of married women (49%) do not receive any payment for the work they do. Trends: Among married women, the percentage currently employed was 32% in the 2005 EDHS. This increased moderately to 57% in the 2011 EDHS, and then declined slightly to 48% in the 2016 EDHS. The percentage of employed married women who receive cash earnings increased from 27% 2005 to 36% in 2011, and then remained essentially stable at 35% in 2016. The percentage of married women not paid for their work declined from 60% to 30% between 2005 and 2011 and then increased to 49% in 2016. Patterns by background characteristics  Among married women, the percentage currently employed rises with age, from 40% in the 15-19 age group to a peak of 53% in the 30- 34 age group. Among married men, there is virtually no variation in the employment rate with age (Figure 14.1).  The percentage of married women who are not paid for their employment is highest in the 15-19 and 45-49 age groups (66% and 56%, respectively). Figure 14.1 Employment by age 40 42 50 53 50 50 47 98 99 100 99 99 99 99 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 12 months before the survey Currently married men Currently married women Women’s Empowerment • 257 14.2 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 Women gain direct access to economic resources when they are employed for cash. However, this access is meaningless unless women also control how their earnings are used. To measure women’s autonomy, currently married women age 15-49 who were paid in cash for employment in the 12 months before the survey were asked who makes decisions about the utilization of their earnings. The majority of women earning cash report that decisions about how their cash earnings are used are made either jointly with their husbands (62%) or by themselves (30%). Only 8% say the decisions are made primarily by their husbands (Table 14.2.1 and Figure 14.2). While most women earn less than their husbands (58%), 21% are paid about the same as their husbands, while 16% earn more than their husbands. The magnitude of women’s earnings relative to that of their husbands makes a difference in the control of decisions about how their earnings are used. Forty- five percent of women who earn more than their husbands say they make the decisions about how their earnings are used, compared to 11% of women who earn the same as their husbands (Table 14.3). Patterns by background characteristics  The likelihood that married women with cash earnings decide for themselves about how those earnings are used increases with age, peaking at 40% among women age 45-49 (Table 14.2.1).  The large majority of women in both urban and rural either decide for themselves (29% and 30%, respectively) or jointly with their husbands (67% and 59%) about how the woman’s earnings will be used. Only 11% of rural women and 4% of urban women say their husbands mainly make these decisions.  The percentage of women whose husbands make most decisions about the use of their cash earnings is highest in Benishangul-Gumuz (17%) and lowest in Addis Ababa (2%).  Eleven percent of women with no education report that their husbands decide on how their cash earnings are used, compared with 3% of women with more than secondary education. 14.3 CONTROL OVER MEN’S EARNINGS Married men with cash earnings and married women whose husbands have cash earnings were asked about who makes decisions about how the man’s earnings are used. The majority of both men and women report that decisions about the use of the man’s earnings are made jointly (81% and 70%, respectively) (Table 14.2.2). However, women are somewhat more likely than men to say that their husband decides how his Figure 14.2 Control over woman’s earnings Mainly wife 30% Wife and husband jointly 62% Mainly husband 8% Percent distribution of currently married women with cash earnings in the 12 months before the survey 258 • Women’s Empowerment earnings are used (23% and 16%, respectively). Relatively few men or women report that the wife decides on how the husband’s cash earnings will be used (3% and 7%, respectively). Patterns by background characteristics  Married men are most likely to say that they make decisions about how their earnings are used in Somali (44%) and Benishangul-Gumuz (34%). Among women, the highest percentages saying their husbands make these decisions are highest in Affar (39%) and Somali (33%) Regions (Table 14.2.2).  Among both men and women, the percentage saying that the husband makes the decisions about how his earning will be used decreases with wealth quintile. 14.4 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 Sixteen percent of women age 15-49 own a house alone, and 35% own a house jointly with someone. Overall, the house ownership rate among men is similar to women (51% and 50%, respectively), although men are more likely than women to own a house alone (35%), and are less likely to share ownership (17%). With land, the ownership rate is also higher among men than women (48% and 40%, respectively), with men less likely than women to own land jointly with someone (15% and 25%, respectively) (Tables 14.4.1 and 14.4.2). Patterns by background characteristics  Ownership of both housing and land increases with age among women. Similar patterns are observed among men.  Ownership rates are higher in rural than urban areas. About 1 in 5 urban women (27%) own a house, compared to 56% of rural women.  The rates of both housing and land ownership are much lower in Addis Ababa than in other regions. More than 8 in 10 women and men in Addis Ababa do not own a house and more than 9 in 10 do not own land.  The percentages of men and women who do not own a house or land generally increase with increasing education. For example, among women with more than secondary education, 76% do not own a house and 91% do not own land, compared with 32% and 42% of women with no education, respectively. 14.5 POSSESSION OF TITLE OR DEED FOR A HOUSE OR LAND Possession of title or deed for house or land A title or deed is available for the house or land and the respondent’s name is on the title or deed. Sample: Women and men age 15-49 who own a house or land A title or deed that includes the owner’s name is important in establishing legal rights to property. The 2016 EDHS sought information from currently married women and men who own a house or land about whether or not they possess a title or deed for their property, and whether or not their name appears on the title or deed. More than half of women (51%) and nearly two-thirds of men (66%) who own a house do not Women’s Empowerment • 259 have a title or deed for their house (Tables 14.5.1 and 14.5.2). Although possession of a title or deed is somewhat more common for land than for housing, large proportions of both women and men who own land do not have a title or deed (40% and 48%, respectively) (Tables 14.6.1 and 14.6.2). The majority of women and men who have a title or deed for their property say that their name is on the document. However, the percentage of respondents who report their name is not on a title or deed is somewhat higher among women than men in the case of housing (8% and 2%, respectively) and land (7% and 2%, respectively). Patterns by background characteristics  Possession of a title and deed for their house and land generally increases with age among both women and men. For example, 71% of women age 15-19 who own a house do not have a title for the house, as compared to 46% of women age 45-49.  Urban residents are generally more likely to have a title or deed for the house they own than rural residents. However, rural women are slightly more likely than urban women to have a title or deed for the land they own.  Women in the Affar and Somali Regions are more likely not to have a title and deed for their house (86% and 74%, respectively) or land (79% and 83%, respectively) than women in other regions. Similar patterns are observed for men.  Among women and men, the percentage that possesses a title or deed increases with wealth quintile for both housing and land. 14.6 OWNERSHIP AND USE OF BANK ACCOUNTS AND MOBILE PHONES Ownership of a bank account and a mobile phone are reflections of autonomy and financial independence. Women and men interviewed in the 2016 EDHS were asked if they used an account in bank or other financial institution and if they owned a mobile phone. Those who owned phones were also asked if they used the phone for financial transactions. Wider disparities are observed between women and men in the use of bank accounts and especially in the ownership of mobile phones than with respect to ownership of housing or land (Figure 14.3). Fifteen percent of women age 15-49 use an account in a bank or other financial institution, compared with 25% of men. Twenty-seven percent of women and 55% of men owned mobile phones at the time of the survey. Among those with mobile phones, only 5% of women and 9% of men use their phone for financial transactions (Tables 14.7.1 and 14.7.2). Patterns by background characteristics  Large differences in the use of financial accounts and ownership of mobile phones are observed between urban and rural residents. For example, 44% of urban women use a bank account, compared with only 7% of rural women, while 71% of urban women own a mobile phone, compared with 15% of rural women. Figure 14.3 Ownership of assets 50 40 15 27 51 48 25 55 Own house (alone or jointly) Own land (alone or jointly) Use bank account Own mobile phone Percentage of women and men age 15-49 by ownership of specific items Women Men 260 • Women’s Empowerment  More educated women and men are likely to use a bank account or own a mobile phone. For example, virtually all women and men with more than secondary education (98 percent each) own a mobile phone, compared with 9% of women and 32% of men with no education.  Use of a bank account and ownership of a mobile phone increase with wealth quintile. Among women, the percentage using a bank account ranges from 3% in the lowest wealth quintile to 40% in the highest wealth quintile. Only 7 percent of women in the lowest wealth quintile own a mobile phone, compared with 67% in the highest wealth quintile. Similar patterns are observed for men. 14.7 DECISION TO MARRY A critical aspect of women’s autonomy is control over the decision to marry. Ever-married respondents age 15-49 were asked about the person who made the decision when they married the first time. This information is especially useful in designing effective programmes for addressing the problem of child marriage in Ethiopia. More than one-third of ever-married women age 15-49 (35%) reported that they made the decision to marry, while 61% say that their parents made the decision and 3% report the decision was made by other family members or relatives (Table 14.8). Patterns by background characteristics  Younger women are more likely than older women to make the decision to marry. Nevertheless, only 41% of ever-married women age 15-19 and 47% of women age 20-24 made their own decision to marry.  As expected, parents play a greater role in marriage decisions in rural areas than urban areas. Sixty-six percent of ever-married women in rural areas say their parents made the decision when they married, compared to 39% of urban women.  Parents made the decisions about marriage most often in Amhara (83%), Affar (82%), and Tigray (80%), while they were least likely to be involved in the Harari Region (24%) and Addis Ababa (21%).  The percentage of women who made their own decision to marry increases with education level, from only 25% of women with no education to 83% of women with more than secondary education. 14.8 SCHOOLING AFTER MARRIAGE The ability to continue schooling after marriage is another aspect of women’s empowerment. To obtain information on schooling after marriage, ever-married women age 15-49 were asked if they were going to school at the time they married, and women who were attending school were asked if they continued to attend school after they married. In addition, women who stopped attending school after marriage were asked about the reasons for not continuing their schooling. Twenty-five percent of women were attending school before they married. The majority of these women (75%) stopped attending school after they married. Sixty-two percent of women said that they were too busy with family to continue going to school. However, more than 1 in 5 women (23%) said they stopped going to school because their husbands did not want them to go to school (Table 14.9). Patterns by background characteristics  Rural women (86%) were more likely to have stopped attending school after marriage than urban women (54%). Women’s Empowerment • 261  Women in Oromiya (84%) and SNNPR (82%) were more likely to have dropped out of school after marriage than women in other regions.  Eighty-seven percent of women with primary education stopped attending school after marriage compared with only 28% of women with more than secondary education.  Women in the highest wealth quintile are less likely (59%) to have stopped attending school after marriage than women in the lowest wealth quintile (86%). 14.9 MEN’S PARTICIPATION IN HOUSEHOLD CHORES Currently married women were asked whether their husbands participated in household chores and, if so, the frequency with which the husbands helped with such chores. Only slightly more than one-third (37%) of husbands provide any help with household chores. Most of these husbands do not help out on a regular basis; 63% rarely participate in household chores, and only 18% assist with chores almost every day (Table 14.10). Patterns by background characteristics  In general, the likelihood that a husband assists with household chores declines with age and the number of living children.  Half of urban women say their husbands participate in household chores compared with 34% of rural women.  Husbands in the Somali Region (12%) are least likely and those in Addis Ababa (60%) are most likely to participate in household chores.  The more educated and the wealthier the woman, the more likely it is that her husband participates in the household chores. 14.10 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 Participation in household decision making is an essential aspect of women’s empowerment. In the 2016 EDHS, currently married women were asked about their participation in decisions about the woman’s own health care, major household purchases, and visits to their family or relatives. The majority of women reported that they are involved either alone (11-18%) or jointly (66-68%) in these decisions. However, 21% of women said their husbands usually makes decisions about major household purchases, 18% said the husband decides about the woman’s health care, and 16% said the husband is primarily responsible for making decisions about visits to her family or relatives (Table 14.11). 262 • Women’s Empowerment The 2016 EDHS results also show that the majority of currently married men report that key household decisions are made jointly with their wives. For example, when men were asked about who makes most decisions about the man’s own health care, 70% reported that the decisions are made jointly with their wives. Similarly, more than three-fourths of men (77%) said that decisions about major household purchases are typically made jointly with their wives (Table 14.11). Overall, 71 percent of women participate in all decisions and only 10% are not involved in any of the three decisions (Table 14.12.1 and Figure 14.4). Patterns by background characteristics  Employed women, whether they earn cash or not, are slightly more likely to participate in all three decisions (75% each) than women who are not employed (67%).  Urban (81%) women are more likely to participate in all three decisions than rural women (69%).  More than 80% of women in Harari (88%) and Addis Ababa (82%) participate in all three decisions, compared to the national level of 71%.  Women’s participation in decision making increases with increasing education level and wealth quintile. Eighty-seven percent of women with more than secondary education participate in all three decisions, compared with 68% of women with no education. Similarly, 80% of women in the highest wealth quintile participate in all three decisions compared with 65% in the lowest wealth quintile. 14.11 ATTITUDES TOWARD 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 Figure 14.4 Women’s participation in decision making 81 78 84 71 10 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 specific decisions Women’s Empowerment • 263 Freedom from domestic abuse is basic to women’s empowerment. To gain insight into the extent to which domestic abuse is accepted, the 2016 EDHS collected information on women’s and men’s attitudes toward wife beating in five separate circumstances. Overall, 63% of Ethiopian women age 15-49 believe that a husband is justified in beating his wife in at least one of the five specified circumstances, compared with 28% of men (Table 14.13.1, Table 14.13.2 and Figure 14.5). Trends: The percentage of men justifying wife beating in at least one of the five specified circumstances has decreased significantly over time, from 76% in the 2000 EDHS to 28% in 2016 EDHS. The percentage of women who agree that wife beating is justified in at least one of the five specified circumstances has also declined but at a much slower rate than among men, dropping from 85% in 2000 EDHS to 63% in 2016 (Figure 14.6). Patterns by background characteristics  Tolerance of wife beating is less common among women employed for cash than among other women; 55% of women who are employed for cash agree that wife beating is justified in at least one of the five specified circumstances, compared with 71% of women employed but not earning cash and 63% of women who are not employed.  Wife beating is more acceptable in rural areas than urban areas; 70% of women and 31% of men in rural areas agree that wife beating is justified in at least one of the five specified circumstances, compared with 39% of women and 15% of men in urban areas.  Acceptance of wife beating by women varies widely across Ethiopia’s regions. Just over two-thirds of women in Affar and Oromiya (69% each) agree that wife beating is justified in at least one of the five specified circumstances, compared with 23% of women in Addis Ababa.  Acceptance of wife beating decreases with increasing education level and wealth quintile. For example, 72% of women with no education agree that wife beating is justified in at least one of the five specified circumstances, compared with 26% of women with more than secondary education. Similarly, 71% of women in the lowest wealth quintile agree that wife beating is justified in at least one of the five specified circumstances, as compared with 43% of women in the highest wealth quintile. 14.12 ATTITUDE TOWARD NEGOTIATING SAFE SEX The ability of women to negotiate safe sex practices is another aspect of women’s empowerment. To assess attitudes about negotiating safe sex practices with husbands, women and men were asked whether Figure 14.5 Attitudes towards wife beating Figure 14.6 Trend of wife beating justified 40 42 43 48 35 63 12 16 17 19 13 28 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 85 81 68 63 76 51 45 28 2000 EDHS 2005 EDHS 2011 EDHS 2016 EDHS Trend of percentage of women and men who believe that a husband is jusfied in beating his wife in at lease one of the five specified circumstances Men Women 264 • Women’s Empowerment they thought that a wife is justified in refusing to have sexual intercourse with her husband if she knows he has sex with other women or in asking that her husband use a condom if she knows he has an STI. Seventy-three percent of women age 15-49 believe that a woman is justified in refusing to have sexual intercourse with her husband if she knows he has sex with other women, compared with 82% of men. Similarly, 61% of women believe that a woman is justified in asking that a husband use a condom if she knows that he has an STI, compared with 80% of men (Table 14.14). Patterns by background characteristics  Rural women (70%) are less likely to believe that a woman is justified in refusing to have sexual intercourse with her husband if she knows he has sex with other women than urban women (86%). Similarly, 82% of urban women but only 55% of rural women believe that a woman is justified in in asking her husband to use a condom if he has an STI.  Women are most likely to believe that a woman is justified in refusing to have sexual intercourse with her husband if she knows he has sex with other women in Addis Ababa (92%), followed by Amhara (86%), Tigray (84%), and SNNPR (77%), while they are least likely to accept this justification in the Somali Region (38%). The percentage of women who believe that a woman is justified in asking that her husband to use a condom if she knows that he has an STI is also lowest in the Somali Region (18%) and highest in Addis Ababa (90%).  The more educated the woman is, the more likely she is to accept negotiating safer sexual relations with a husband. Ninety-one percent of women with more than secondary education believe that a woman is justified in refusing to have sexual intercourse with her husband if she knows he has sex with other women, compared with 67% of women with no education. Likewise, 90% of women with more than secondary education, but only 47% of women with no education believe that a woman is justified in asking that a husband with an STI to use a condom. Similar patterns are observed by wealth status. 14.13 ABILITY TO NEGOTIATE SEXUAL RELATIONS The 2016 EDHS investigated whether women felt empowered to negotiate sexual relations with their husbands. To assess the ability of a woman to negotiate sexual relations with her husband, currently married women age 15-49 were asked if they can say no to their husband if they do not want to have sexual intercourse and if they can ask their husband to use a condom. Forty-five percent of married women say that they can say no to their husbands if they do not want to have sexual intercourse, but only 30% said that they can ask their husband to use a condom (Table 14.15). Patterns by background characteristics  Rural women are less likely to be able to say no to their husbands if they don’t want to have sexual intercourse than urban women (42% and 64%, respectively). Only 24% of rural women can ask their husbands to use a condom, compared with 61% of urban women.  Women in the Somali Region are least likely to say that they can negotiate sexual relations with their husbands. For example, only 28% of women in the Somali Region say that they can say no to their husbands if they do not want to have sexual intercourse, compared with 70% of women in Tigray and 68% in Addis Ababa.  Seventy-seven percent of women with more than secondary education, but only 40% of women with no education, can say no to their husbands if they do not want to have sexual intercourse. Similarly, 83% of women with more than secondary education can ask their husbands to use a condom, compared with 20% of women with no education. Wealth is similarly associated with a greater ability to negotiate sexual relations. Women’s Empowerment • 265 14.14 WOMEN’S EMPOWERMENT AND DEMOGRAPHIC AND HEALTH OUTCOMES Women’s empowerment indices Two sets of empowerment indicators, women’s participation in making household decisions and women’s attitudes towards wife beating, can be summarized with two indices. The first index shows the number of decisions in which women participate either alone or jointly with their husband or partner. This index ranges from 0 to 3 and reflects the degree of decision-making control that women are able to exercise in areas that affect their lives and the level of women’s empowerment in a society. The second index, which ranges from 0 to 5, is the number of reasons for which a woman thinks that a husband is justified in beating his wife. A lower score on this indicator reflects a higher status of women in the household and society. Sample: Women age 15-49 Two indices based the information collected in the EDHS on women’s participation in household decision- making and women’s attitudes toward wife beating can be used to examine the relationship between women’s empowerment and selected demographic and health indicators. As expected, the two indices are positively associated. The percentage of women who disagree with all the reasons that justify wife beating rises with the number of household decisions in which women participate, from 25% among women who do not participate in any of the household decisions to 36% of women who participate in all three decisions. The percentage of women participating in all the household decisions decreases with the number of reasons women accept as justifying wife beating, from 75% among women who do not agree that wife beating is justified for any reason to 66% among women who accept that wife beating is justified in all five specified reasons (Table 14.16). In exploring the relationship between the empowerment indices and demographic and health outcomes, both decision making and wife beating indices are positively associated with measures of women’s ability and desire to control her fertility. For example, the more women are empowered in the number of decisions in which they participate, the more likely they are to use a contraceptive method. Similarly, women who do not justify wife beating have higher use of contraception methods (Table 14.17). The empowerment indices are positively associated with several additional measures that reflect women’s fertility desires. For example, the mean ideal family size among currently married women declines with the number of household decisions in which women participate, from 5.8 children among women who do not participate in any household decisions to 4.7 children among women involved in all three decisions. The greater the number of household decisions in which women participate, the lower the level of unmet need for family planning. Overall, 31% of currently married women who are not participating in any of the household decisions have an unmet need for family planning, compared with 21% of women who participate in three decisions (Table 14.18). Empowered women are more likely to seek and use health services to meet their reproductive health goals, including safe motherhood. Women who did not participate in any household decisions were much less likely to receive antenatal care (44%) and delivery care (24%) from a skilled provider and to have a postnatal check-up (8%), compared with women participating in all three decisions (65%, 34%, and 15% respectively) (Table 14.19). The percentages of women who reported receiving antenatal and delivery care from a skilled provider and having a postnatal check-up decrease as the number of reasons that justify wife beating increases. The 2016 EDHS results also provide evidence that women’s empowerment has a positive effect on children’s survival. Under-five mortality declines from 86 per 1,000 live births in the 10 years before the 266 • Women’s Empowerment survey among women who do not participate any of the three household decisions to 79 deaths per 1,000 births among women who participate in all decisions (Table 14.20). LIST OF TABLES For more information on women’s empowerment and demographic and health outcomes, see the following tables:  Table 14.1 Employment and cash earnings of currently married women and men  Table 14.2.1 Control over women’s cash earnings and relative magnitude of women’s cash earnings  Table 14.2.2 Control over men’s cash earnings  Table 14.3 Women’s control over their own earnings and those of their husbands  Table 14.4.1 Ownership of assets (house and land): Women  Table 14.4.2 Ownership of assets (house and land): Men  Table 14.5.1 Possession of title or deed for house: Women  Table 14.5.2 Possession of title or deed for house: Men  Table 14.6.1 Possession of title or deed for land: Women  Table 14.6.2 Possession of title or deed for land: Men  Table 14.7.1 Ownership and use of bank accounts and mobile phones: Women  Table 14.7.2 Ownership and use of bank accounts and mobile phones: Men  Table 14.8 Person deciding on a woman’s first marriage  Table 14.9 Schooling after marriage  Table 14.10 Men’s participation in household chores  Table 14.11 Participation in decision making  Table 14.12.1 Women’s participation in decision making by background characteristics  Table 14.12.2 Men’s participation in decision making by background characteristics  Table 14.13.1 Attitude toward wife beating: Women  Table 14.13.2 Attitude toward wife beating: Men  Table 14.14 Attitudes toward negotiating safer sexual relations with husband  Table 14.15 Ability to negotiate sexual relations with husband  Table 14.16 Indicators of women’s empowerment  Table 14.17 Current use of contraception by women’s empowerment  Table 14.18 Ideal number of children and unmet need for family planning by women’s empowerment  Table 14.19 Reproductive health care by women’s empowerment  Table 14.20 Early childhood mortality rates by indicators of women’s empowerment Women’s Empowerment • 267 Table 14.1 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 percent distribution of currently married women and men employed in the past 12 months by type of earnings, according to age, Ethiopia DHS 2016 Among currently married respondents: Percent distribution of currently married respondents employed in the past 12 months, by type of earnings Total Number Age Percentage employed in past 12 months Number Cash only Cash and in-kind In-kind only Not paid Missing/ don’t know WOMEN 15-19 40.1 588 21.2 3.4 9.2 66.2 0.0 100.0 236 20-24 41.7 1,710 39.0 5.1 7.1 48.8 0.0 100.0 713 25-29 50.3 2,402 34.0 10.2 10.3 45.5 0.0 100.0 1,208 30-34 52.9 2,049 39.0 5.6 8.2 47.2 0.0 100.0 1,083 35-39 49.8 1,613 32.2 8.9 10.7 48.1 0.0 100.0 804 40-44 49.7 1,064 33.7 8.9 7.0 50.4 0.0 100.0 528 45-49 47.2 798 29.1 4.7 10.2 56.0 0.0 100.0 377 Total 15-49 48.4 10,223 34.5 7.4 9.0 49.1 0.0 100.0 4,948 MEN 15-19 (97.9) 26 (3.5) (8.6) (52.5) (35.5) (0.0) 100.0 26 20-24 99.3 474 20.5 11.8 14.9 52.8 0.0 100.0 471 25-29 99.6 1,227 29.1 8.1 13.1 49.7 0.0 100.0 1,222 30-34 99.0 1,389 26.2 10.3 13.4 50.1 0.0 100.0 1,376 35-39 99.2 1,285 20.3 10.6 14.3 54.8 0.0 100.0 1,275 40-44 98.7 1,137 22.4 8.0 14.5 55.1 0.0 100.0 1,122 45-49 99.1 903 16.9 10.9 15.4 56.8 0.0 100.0 895 Total 15-49 99.1 6,441 23.1 9.7 14.3 52.9 0.0 100.0 6,386 50-59 97.9 1,029 19.8 7.4 12.2 60.6 0.0 100.0 1,008 Total 15-59 99.0 7,471 22.6 9.4 14.0 54.0 0.0 100.0 7,394 Note: Figures in parentheses are based on 25-49 unweighted cases. 268 • Women’s Empowerment Table 14.2.1 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 before 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, Ethiopia DHS 2016 Person who decides how 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 jointly Mainly husband Other More Less About the same Husband has no earnings Don’t know/ missing Age 15-19 28.4 56.2 15.4 0.0 100.0 6.3 72.5 16.8 0.6 3.9 100.0 58 20-24 25.6 67.9 6.3 0.2 100.0 8.2 63.3 21.8 4.5 2.3 100.0 315 25-29 25.5 63.9 10.6 0.0 100.0 14.6 57.7 23.1 0.6 3.9 100.0 534 30-34 31.0 64.1 4.9 0.0 100.0 18.5 56.7 21.2 1.7 1.8 100.0 482 35-39 32.0 64.2 3.8 0.0 100.0 16.6 58.1 19.4 5.6 0.3 100.0 331 40-44 34.4 51.4 14.2 0.0 100.0 22.8 49.0 20.4 6.9 1.0 100.0 225 45-49 40.1 48.8 11.0 0.1 100.0 18.2 57.9 14.4 6.6 2.9 100.0 127 Number of living children 0 30.9 63.9 5.0 0.3 100.0 15.2 63.8 17.5 0.1 3.3 100.0 263 1-2 26.5 65.6 7.9 0.0 100.0 12.2 60.3 23.6 2.5 1.4 100.0 729 3-4 31.5 60.2 8.2 0.0 100.0 16.4 57.8 20.4 2.6 2.7 100.0 495 5+ 31.9 58.5 9.6 0.0 100.0 19.8 52.3 19.4 6.3 2.3 100.0 585 Residence Urban 29.3 66.9 3.7 0.1 100.0 15.9 61.5 19.3 1.6 1.7 100.0 781 Rural 30.0 59.2 10.7 0.0 100.0 15.7 55.7 21.8 4.3 2.6 100.0 1,291 Region Tigray 29.0 64.0 7.1 0.0 100.0 7.1 58.0 29.1 3.2 2.6 100.0 180 Affar 27.9 61.8 10.1 0.2 100.0 10.6 56.9 19.0 7.4 6.2 100.0 14 Amhara 27.0 69.5 3.4 0.0 100.0 16.8 58.5 23.2 1.5 0.0 100.0 318 Oromiya 22.0 68.0 10.1 0.0 100.0 13.8 46.4 29.0 6.9 4.0 100.0 679 Somali 55.7 33.7 10.6 0.0 100.0 43.8 38.6 8.2 6.0 3.5 100.0 45 Benishangul-Gumuz 8.5 73.4 17.1 1.0 100.0 9.0 34.6 47.6 2.4 6.3 100.0 14 SNNPR 35.3 54.4 10.3 0.0 100.0 18.6 68.4 11.2 0.5 1.3 100.0 602 Gambela 44.5 49.4 6.1 0.0 100.0 13.4 56.0 20.9 4.0 5.7 100.0 9 Harari 28.5 62.9 8.6 0.0 100.0 19.2 56.4 22.6 0.0 1.8 100.0 9 Addis Ababa 40.0 58.1 1.6 0.4 100.0 13.4 71.4 12.4 1.7 1.0 100.0 187 Dire Dawa 35.0 58.1 6.9 0.0 100.0 29.5 53.7 9.6 3.7 3.5 100.0 15 Education No education 31.8 56.8 11.4 0.0 100.0 16.5 55.5 20.1 4.8 3.1 100.0 910 Primary 28.4 62.9 8.7 0.0 100.0 16.5 60.7 18.7 2.8 1.3 100.0 620 Secondary 28.8 70.1 1.1 0.0 100.0 8.3 61.5 25.0 0.7 4.4 100.0 208 More than secondary 27.4 69.9 2.5 0.2 100.0 16.9 56.8 24.4 1.7 0.2 100.0 334 Wealth quintile Lowest 27.9 60.1 12.0 0.0 100.0 13.9 49.4 25.6 8.5 2.6 100.0 232 Second 32.7 50.0 17.3 0.0 100.0 22.8 54.3 15.2 4.9 2.7 100.0 305 Middle 31.3 57.3 11.3 0.0 100.0 20.0 50.6 25.8 2.3 1.4 100.0 288 Fourth 31.6 64.2 4.2 0.0 100.0 11.2 62.4 20.0 3.3 3.2 100.0 343 Highest 28.0 67.5 4.4 0.1 100.0 14.2 61.9 20.3 1.7 1.9 100.0 904 Total 29.8 62.1 8.1 0.0 100.0 15.8 57.9 20.9 3.3 2.2 100.0 2,072 Women’s Empowerment • 269 Table 14.2.2 Control over men’s cash earnings Percent distribution 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, Ethiopia DHS 2016 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: Total Number of women Background characteristic Mainly wife Husband and wife jointly Mainly husband Mainly wife Husband and wife jointly Mainly husband Other Age 15-19 * * * 100.0 3 6.3 63.2 27.4 3.0 100.0 573 20-24 1.1 78.4 20.5 100.0 152 5.2 71.3 23.1 0.4 100.0 1,680 25-29 3.8 78.0 18.1 100.0 455 6.2 73.7 20.0 0.1 100.0 2,378 30-34 2.4 81.3 16.3 100.0 502 7.4 71.3 21.2 0.1 100.0 2,020 35-39 3.5 83.2 13.2 100.0 394 7.2 67.7 25.0 0.1 100.0 1,584 40-44 2.3 80.7 17.0 100.0 341 9.7 66.8 23.4 0.0 100.0 1,020 45-49 3.9 84.4 11.7 100.0 249 10.4 64.4 24.9 0.3 100.0 781 Number of living children 0 5.9 71.3 22.8 100.0 282 6.2 69.2 22.4 2.2 100.0 907 1-2 2.5 81.2 16.4 100.0 839 7.0 71.5 21.2 0.3 100.0 3,092 3-4 3.3 83.4 13.2 100.0 507 8.0 70.4 21.5 0.0 100.0 2,718 5+ 1.9 83.9 14.2 100.0 467 6.7 68.0 25.2 0.1 100.0 3,319 Residence Urban 5.3 77.5 17.2 100.0 748 12.3 73.1 14.3 0.2 100.0 1,632 Rural 1.7 83.0 15.3 100.0 1,348 6.1 69.2 24.3 0.4 100.0 8,403 Region Tigray 1.4 82.8 15.9 100.0 150 6.0 63.8 30.0 0.3 100.0 648 Affar 13.4 64.3 22.3 100.0 29 13.7 46.7 39.0 0.5 100.0 93 Amhara 1.6 85.2 13.3 100.0 287 4.2 80.4 15.0 0.3 100.0 2,346 Oromiya 2.1 87.1 10.8 100.0 736 6.1 71.4 22.2 0.3 100.0 3,898 Somali 10.3 46.2 43.5 100.0 86 17.2 49.8 33.0 0.0 100.0 319 Benishangul-Gumuz 5.5 60.2 34.3 100.0 17 11.5 64.8 23.5 0.1 100.0 113 SNNPR 1.4 82.0 16.6 100.0 560 8.5 62.0 29.1 0.5 100.0 2,167 Gambela 5.4 63.9 30.8 100.0 9 17.5 52.0 29.4 1.0 100.0 29 Harari 17.2 59.8 23.0 100.0 9 12.9 76.7 10.2 0.2 100.0 25 Addis Ababa 7.1 69.9 23.0 100.0 191 15.8 69.5 14.3 0.4 100.0 350 Dire Dawa 17.0 71.7 11.3 100.0 22 19.7 68.5 11.4 0.4 100.0 50 Education No education 1.6 87.1 11.3 100.0 543 6.4 68.4 25.1 0.1 100.0 6,124 Primary 2.4 78.7 18.9 100.0 819 7.8 69.1 22.2 0.8 100.0 2,855 Secondary 2.6 82.2 15.2 100.0 306 9.2 79.0 11.4 0.4 100.0 642 More than secondary 6.1 77.0 16.9 100.0 428 9.8 81.8 8.5 0.0 100.0 415 Wealth quintile Lowest 3.5 71.0 25.5 100.0 255 7.5 63.6 28.7 0.3 100.0 1,903 Second 2.0 83.7 14.4 100.0 296 6.1 66.8 26.7 0.4 100.0 2,033 Middle 1.9 84.9 13.2 100.0 307 6.5 69.7 23.7 0.2 100.0 2,028 Fourth 0.9 87.5 11.6 100.0 333 4.8 75.1 19.6 0.5 100.0 1,962 Highest 4.3 79.3 16.4 100.0 905 10.5 73.7 15.4 0.3 100.0 2,110 Total 15-49 3.0 81.0 16.0 100.0 2,096 7.1 69.8 22.7 0.3 100.0 10,036 50-59 5.1 82.3 12.6 100.0 274 na na na na na na Total 15-59 3.2 81.2 15.6 100.0 2,370 na na na na na na na = Not applicable. Note: An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. 270 • Women’s Empowerment Table 14.3 Women’s control over their own earnings and 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, Ethiopia DHS 2016 Person who decides how the wife’s cash earnings are used: Total Number Person who decides how husband’s cash earnings are used: Total Number 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 husband 44.8 51.3 3.9 0.0 100.0 326 28.2 56.0 15.7 0.1 100.0 326 Less than husband 30.4 59.4 10.1 0.1 100.0 1,199 7.1 69.1 23.7 0.1 100.0 1,199 Same as husband 10.9 83.2 5.9 0.0 100.0 432 2.6 85.0 12.2 0.2 100.0 432 Husband has no cash earnings or did not work 51.6 46.3 2.0 0.0 100.0 68 na na na na na na Woman worked but has no cash earnings na na na na na 0 6.7 73.4 19.4 0.4 100.0 2,826 Woman did not work na na na na na 0 6.1 67.9 25.6 0.3 100.0 5,206 Don’t know/missing 51.5 34.0 14.1 0.4 100.0 46 34.0 47.5 17.4 1.2 100.0 46 Total1 29.8 62.1 8.1 0.0 100.0 2,072 7.1 69.8 22.7 0.3 100.0 10,036 na = Not applicable. 1 Includes cases where a woman does not know whether she earned more or less than her husband. Table 14.4.1 Ownership of assets (house and land): Women Percent distribution of women age 15-49 by ownership of house and land, according to background characteristics, Ethiopia DHS 2016 Percentage who own a house: Do not own a house Total Percentage who own land: Do not own land Total Number of women Background characteristic Alone Jointly Alone and jointly Alone Jointly Alone and jointly Age 15-19 2.1 11.1 0.9 86.0 100.0 3.4 8.3 0.4 87.9 100.0 3,381 20-24 10.5 26.9 0.8 61.8 100.0 10.8 17.9 0.5 70.8 100.0 2,762 25-29 16.4 38.1 1.0 44.5 100.0 17.2 25.0 1.0 56.8 100.0 2,957 30-34 19.9 43.0 1.3 35.8 100.0 18.2 31.9 1.4 48.5 100.0 2,345 35-39 20.9 48.6 0.9 29.6 100.0 20.6 35.0 1.2 43.2 100.0 1,932 40-44 24.1 50.0 1.2 24.7 100.0 26.2 39.5 0.3 34.1 100.0 1,290 45-49 27.3 46.8 1.8 24.1 100.0 29.0 36.3 1.0 33.8 100.0 1,017 Residence Urban 7.7 17.9 1.2 73.3 100.0 4.8 7.9 0.3 87.0 100.0 3,476 Rural 16.7 38.4 1.0 43.9 100.0 18.1 29.0 0.9 51.9 100.0 12,207 Region Tigray 8.9 35.0 1.0 55.2 100.0 17.4 19.2 1.0 62.5 100.0 1,129 Affar 23.7 25.5 2.3 48.5 100.0 10.9 9.7 0.9 78.6 100.0 128 Amhara 8.1 53.7 0.8 37.4 100.0 14.2 36.1 0.7 49.0 100.0 3,714 Oromiya 19.0 26.5 0.8 53.7 100.0 17.6 18.8 0.8 62.9 100.0 5,701 Somali 11.6 44.0 1.9 42.5 100.0 5.4 25.1 0.9 68.6 100.0 459 Benishangul-Gumuz 31.5 28.4 1.3 38.8 100.0 27.5 23.9 0.9 47.7 100.0 160 SNNPR 18.9 30.2 1.7 49.2 100.0 16.6 29.5 1.1 52.9 100.0 3,288 Gambela 17.3 26.5 1.3 54.9 100.0 13.1 20.1 0.3 66.5 100.0 44 Harari 8.8 26.0 0.7 64.5 100.0 5.5 20.3 0.7 73.5 100.0 38 Addis Ababa 5.1 10.0 0.7 84.2 100.0 1.4 2.5 0.1 96.0 100.0 930 Dire Dawa 5.0 22.9 0.8 71.3 100.0 3.3 14.9 0.1 81.7 100.0 90 Education No education 20.8 46.5 1.2 31.6 100.0 22.0 35.1 1.0 41.9 100.0 7,498 Primary 10.4 25.8 0.9 62.9 100.0 11.3 17.9 0.8 70.1 100.0 5,490 Secondary 5.7 15.4 1.0 78.0 100.0 5.0 7.9 0.5 86.6 100.0 1,817 More than secondary 8.3 14.8 0.8 76.1 100.0 2.0 6.5 0.1 91.4 100.0 877 Wealth quintile Lowest 19.3 40.3 1.3 39.1 100.0 19.8 29.6 0.9 49.8 100.0 2,633 Second 17.2 41.7 1.1 40.0 100.0 18.3 31.1 1.1 49.4 100.0 2,809 Middle 15.1 40.1 0.7 44.1 100.0 17.3 31.2 0.7 50.8 100.0 2,978 Fourth 16.5 33.6 0.7 49.2 100.0 18.0 25.8 1.0 55.2 100.0 3,100 Highest 8.4 20.3 1.3 70.0 100.0 6.5 10.4 0.4 82.6 100.0 4,163 Total 14.7 33.9 1.0 50.4 100.0 15.2 24.3 0.8 59.7 100.0 15,683 Women’s Empowerment • 271 Table 14.4.2 Ownership of assets (house and land): Men Percent distribution of men age 15-49 by ownership of house and land, according to background characteristics, Ethiopia DHS 2016 Percentage who own a house: Percent- age who do not own a house Total Percentage who own land: Percent- age who do not own land Total Number of men Background characteristic Alone Jointly Alone and jointly Alone Jointly Alone and jointly Age 15-19 2.3 2.9 0.3 94.5 100.0 5.6 2.9 0.1 91.3 100.0 2,572 20-24 18.0 5.7 0.4 75.8 100.0 20.6 7.1 0.2 72.2 100.0 1,883 25-29 34.5 15.0 1.3 49.2 100.0 31.7 13.3 1.1 53.9 100.0 1,977 30-34 51.1 20.7 1.8 26.4 100.0 47.3 16.5 1.5 34.7 100.0 1,635 35-39 56.5 26.8 1.8 14.9 100.0 51.2 21.9 1.8 25.1 100.0 1,386 40-44 56.3 29.0 2.5 12.2 100.0 54.9 23.8 1.2 20.2 100.0 1,206 45-49 59.7 32.4 2.1 5.9 100.0 55.4 31.0 1.5 12.1 100.0 947 Residence Urban 16.5 9.7 0.7 73.1 100.0 9.9 6.3 0.2 83.5 100.0 2,303 Rural 38.3 17.4 1.4 42.9 100.0 38.7 15.9 1.1 44.3 100.0 9,302 Region Tigray 25.5 12.7 0.0 61.8 100.0 27.2 6.1 0.2 66.6 100.0 708 Affar 46.3 2.1 0.3 51.4 100.0 24.9 2.2 0.1 72.8 100.0 82 Amhara 20.7 30.8 0.5 48.0 100.0 21.6 23.6 0.3 54.5 100.0 2,914 Oromiya 44.7 9.0 0.9 45.4 100.0 43.8 9.8 0.6 45.8 100.0 4,409 Somali 42.2 8.2 0.6 49.0 100.0 24.0 7.0 0.7 68.4 100.0 301 Benishangul-Gumuz 53.0 9.9 0.1 37.0 100.0 46.0 8.0 0.0 46.0 100.0 118 SNNPR 37.1 15.1 3.6 44.2 100.0 37.4 16.9 2.8 42.8 100.0 2,371 Gambela 31.8 10.4 0.3 57.5 100.0 29.0 7.9 0.5 62.6 100.0 35 Harari 21.7 21.5 0.6 56.2 100.0 21.6 9.9 0.7 67.8 100.0 29 Addis Ababa 7.6 9.0 1.0 82.4 100.0 2.5 2.6 0.0 94.8 100.0 573 Dire Dawa 28.4 9.4 0.0 62.2 100.0 15.6 8.9 0.1 75.3 100.0 66 Education No education 48.0 26.4 2.1 23.5 100.0 48.4 22.0 1.2 28.4 100.0 3,203 Primary 33.4 13.4 1.2 52.0 100.0 33.2 12.8 0.9 53.1 100.0 5,608 Secondary 18.4 8.5 0.5 72.6 100.0 16.9 7.9 0.7 74.4 100.0 1,785 More than secondary 20.1 9.3 0.6 70.0 100.0 11.6 5.7 0.1 82.5 100.0 1,010 Wealth quintile Lowest 43.0 17.9 1.3 37.9 100.0 39.9 15.1 0.8 44.2 100.0 1,839 Second 43.3 17.6 1.6 37.5 100.0 43.6 16.1 1.2 39.1 100.0 2,118 Middle 37.6 18.4 1.7 42.2 100.0 39.6 17.2 1.2 42.0 100.0 2,246 Fourth 32.4 16.0 1.1 50.5 100.0 34.1 15.0 1.0 49.9 100.0 2,466 Highest 20.1 11.4 0.7 67.7 100.0 15.0 8.5 0.5 76.1 100.0 2,935 Total 15-49 34.0 15.9 1.3 48.9 100.0 33.0 14.0 0.9 52.1 100.0 11,606 50-59 59.7 32.0 2.0 6.3 100.0 57.2 24.6 1.4 16.9 100.0 1,082 Total 15-59 36.2 17.3 1.3 45.2 100.0 35.1 14.9 0.9 49.1 100.0 12,688 272 • Women’s Empowerment Table 14.5.1 Possession of title or deed for house: Women Among women age 15-49 who own a house, percent distribution by whether the house owned has a title or deed and whether or not the woman’s name appears on the title or deed, according to background characteristics, Ethiopia DHS 2016 House has a title or deed and: Does not have a title deed Don’t know/ missing Total Number of women who own a house1 Background characteristic Woman’s name is on title/deed Woman’s name is not on title/deed Age 15-19 17.6 6.8 70.6 5.0 100.0 475 20-24 29.2 12.1 53.5 5.2 100.0 1,054 25-29 34.4 7.3 54.5 3.9 100.0 1,640 30-34 41.1 9.3 45.2 4.4 100.0 1,505 35-39 41.1 8.0 48.1 2.8 100.0 1,361 40-44 44.4 7.4 45.8 2.4 100.0 971 45-49 44.7 6.3 46.3 2.7 100.0 771 Residence Urban 51.8 9.9 36.2 2.1 100.0 929 Rural 35.4 8.1 52.5 3.9 100.0 6,849 Region Tigray 30.0 23.3 43.1 3.6 100.0 506 Affar 10.9 2.1 85.8 1.2 100.0 66 Amhara 35.6 4.0 57.3 3.1 100.0 2,326 Oromiya 43.4 9.7 41.3 5.6 100.0 2,641 Somali 19.9 4.1 73.5 2.5 100.0 264 Benishangul-Gumuz 24.2 5.4 67.1 3.3 100.0 98 SNNPR 35.6 9.3 53.0 2.1 100.0 1,670 Gambela 36.1 5.2 55.2 3.5 100.0 20 Harari 25.7 8.3 61.6 4.4 100.0 14 Addis Ababa 57.3 3.3 35.9 3.5 100.0 147 Dire Dawa 42.2 3.5 50.1 4.3 100.0 26 Education No education 37.3 7.4 51.4 3.8 100.0 5,129 Primary 33.9 11.0 51.1 4.0 100.0 2,038 Secondary 49.0 7.7 42.3 1.0 100.0 400 More than secondary 51.5 6.3 38.2 3.9 100.0 210 Wealth quintile Lowest 30.5 8.7 57.5 3.4 100.0 1,603 Second 34.5 7.8 53.4 4.3 100.0 1,686 Middle 37.1 6.7 53.1 3.1 100.0 1,665 Fourth 39.6 8.4 47.9 4.1 100.0 1,575 Highest 47.9 10.8 37.7 3.5 100.0 1,248 Total 37.4 8.3 50.5 3.7 100.0 7,777 1 Includes alone, joint, or alone and joint ownership. Women’s Empowerment • 273 Table 14.5.2 Possession of title or deed for house: Men Among men age 15-49 who own a house, percent distribution by whether the house owned has a title or deed and whether or not the man’s name appears on the title or deed, according to background characteristics, Ethiopia DHS 2016 House has a title or deed and: Does not have a title deed Don’t know/ missing Total Number of men who own a house1 Background characteristic Man’s name is on title/deed Man’s name is not on title/deed Age 15-19 9.2 2.2 87.4 1.3 100.0 141 20-24 21.1 1.9 77.0 0.0 100.0 455 25-29 25.4 2.2 72.4 0.0 100.0 1,004 30-34 30.9 1.7 67.3 0.0 100.0 1,204 35-39 35.5 0.6 63.9 0.0 100.0 1,179 40-44 37.1 1.5 61.4 0.0 100.0 1,059 45-49 39.7 1.5 58.8 0.0 100.0 892 Residence Urban 54.9 4.1 40.9 0.0 100.0 619 Rural 29.4 1.2 69.3 0.0 100.0 5,316 Region Tigray 45.5 5.1 49.4 0.0 100.0 271 Affar 10.4 0.1 89.4 0.1 100.0 40 Amhara 28.7 1.1 70.2 0.0 100.0 1,514 Oromiya 34.0 1.1 64.9 0.0 100.0 2,407 Somali 11.6 3.4 84.9 0.1 100.0 153 Benishangul-Gumuz 14.2 2.1 83.6 0.2 100.0 74 SNNPR 31.9 1.4 66.5 0.1 100.0 1,322 Gambela 37.2 1.9 60.9 0.0 100.0 15 Harari 41.6 2.6 55.8 0.0 100.0 13 Addis Ababa 53.7 6.6 39.7 0.0 100.0 101 Dire Dawa 22.6 5.2 71.8 0.3 100.0 25 Education No education 29.2 1.4 69.4 0.0 100.0 2,452 Primary 31.0 1.2 67.7 0.1 100.0 2,691 Secondary 38.6 1.8 59.6 0.0 100.0 489 More than secondary 54.2 5.2 40.6 0.0 100.0 303 Wealth quintile Lowest 22.2 1.3 76.4 0.0 100.0 1,143 Second 27.4 1.7 70.9 0.0 100.0 1,324 Middle 29.1 0.4 70.5 0.0 100.0 1,297 Fourth 35.2 1.2 63.6 0.0 100.0 1,221 Highest 50.4 3.6 45.8 0.2 100.0 949 Total 15-49 32.0 1.5 66.4 0.0 100.0 5,935 50-59 43.5 1.0 55.5 0.0 100.0 1,015 Total 15-59 33.7 1.5 64.8 0.0 100.0 6,950 1 Includes alone, joint, or alone and joint ownership. 274 • Women’s Empowerment Table 14.6.1 Possession of title or deed for land: Women Among women age 15-49 who own land, percent distribution by whether the land owned has a title or deed and whether or not the woman’s name appears on the title or deed, according to background characteristics, Ethiopia DHS 2016 Land has a title or deed and: Does not have a title deed Don’t know/ missing Total Number of women who own land1 Background characteristic Woman’s name is on title/deed Woman’s name is not on title/deed Age 15-19 21.6 7.1 68.4 2.8 100.0 408 20-24 36.2 7.5 52.9 3.4 100.0 807 25-29 41.7 9.4 43.9 5.0 100.0 1,277 30-34 50.2 8.5 36.9 4.4 100.0 1,207 35-39 58.0 5.7 33.9 2.4 100.0 1,098 40-44 60.0 5.1 31.9 3.0 100.0 850 45-49 67.0 5.6 25.0 2.4 100.0 673 Residence Urban 50.1 5.9 43.1 0.9 100.0 453 Rural 49.3 7.3 39.7 3.8 100.0 5,867 Region Tigray 57.4 16.4 23.2 3.0 100.0 424 Affar 15.4 3.7 79.0 2.0 100.0 27 Amhara 62.7 4.8 30.4 2.1 100.0 1,895 Oromiya 47.6 7.6 38.5 6.3 100.0 2,117 Somali 10.9 3.3 83.2 2.6 100.0 144 Benishangul-Gumuz 24.7 4.7 67.3 3.3 100.0 84 SNNPR 39.3 7.8 51.0 1.9 100.0 1,549 Gambela 32.3 5.1 59.4 3.2 100.0 15 Harari 24.9 11.0 54.8 9.3 100.0 10 Addis Ababa 44.0 0.0 53.2 2.7 100.0 38 Dire Dawa 22.5 7.4 66.7 3.4 100.0 17 Education No education 51.8 7.0 37.2 4.0 100.0 4,357 Primary 43.2 8.3 45.7 2.8 100.0 1,644 Secondary 47.4 5.0 46.8 0.7 100.0 244 More than secondary 46.4 3.8 46.4 3.4 100.0 75 Wealth quintile Lowest 44.6 7.8 43.3 4.3 100.0 1,323 Second 47.0 6.5 42.4 4.2 100.0 1,421 Middle 52.1 5.3 39.7 2.9 100.0 1,464 Fourth 52.5 8.7 35.1 3.6 100.0 1,389 Highest 50.9 8.4 38.7 2.0 100.0 723 Total 49.3 7.2 39.9 3.5 100.0 6,320 1 Includes alone, joint, or alone and joint ownership. Women’s Empowerment • 275 Table 14.6.2 Possession of title or deed for land: Men Among men age 15-49 who own land, percent distribution by whether the land owned has a title or deed and whether or not the man’s name appears on the title or deed, according to background characteristics, Ethiopia DHS 2016 Land has a title or deed and: Does not have a title deed Don’t know/ missing Total Number of men who own land1 Background characteristic Man’s name is on title/deed Man’s name is not on title/deed Age 15-19 15.3 1.2 83.5 0.0 100.0 223 20-24 28.6 4.2 67.2 0.0 100.0 524 25-29 38.7 2.1 59.2 0.1 100.0 911 30-34 45.9 1.9 52.1 0.2 100.0 1,067 35-39 52.6 2.4 45.0 0.0 100.0 1,037 40-44 63.2 1.3 35.5 0.0 100.0 962 45-49 69.1 0.8 29.7 0.4 100.0 833 Residence Urban 51.7 3.0 44.3 1.0 100.0 379 Rural 49.4 1.8 48.7 0.0 100.0 5,179 Region Tigray 66.0 7.6 26.4 0.0 100.0 237 Affar 15.1 3.0 80.0 1.9 100.0 22 Amhara 53.1 0.7 45.9 0.3 100.0 1,326 Oromiya 50.2 2.5 47.3 0.0 100.0 2,391 Somali 8.4 1.1 90.2 0.2 100.0 95 Benishangul-Gumuz 15.4 0.9 83.4 0.2 100.0 64 SNNPR 48.0 1.2 50.7 0.1 100.0 1,355 Gambela 32.0 1.4 66.7 0.0 100.0 13 Harari 49.9 5.0 44.4 0.7 100.0 9 Addis Ababa 38.9 3.4 56.2 1.5 100.0 30 Dire Dawa 12.0 1.4 86.6 0.0 100.0 16 Education No education 51.2 1.7 46.9 0.3 100.0 2,294 Primary 48.7 1.9 49.4 0.0 100.0 2,631 Secondary 46.3 2.3 51.4 0.0 100.0 456 More than secondary 50.3 4.1 45.3 0.3 100.0 176 Wealth quintile Lowest 42.4 1.7 55.8 0.1 100.0 1,027 Second 47.1 1.9 50.9 0.1 100.0 1,289 Middle 52.9 2.2 44.9 0.0 100.0 1,303 Fourth 50.7 1.4 47.9 0.0 100.0 1,236 Highest 56.4 2.8 40.3 0.6 100.0 703 Total 15-49 49.6 1.9 48.4 0.1 100.0 5,558 50-59 73.9 0.6 25.4 0.0 100.0 900 Total 15-59 53.0 1.7 45.2 0.1 100.0 6,458 1 Includes alone, joint, or alone and joint ownership. 276 • Women’s Empowerment Table 14.7.1 Ownership and use of bank accounts and mobile phones: Women Percentage of women age 15-49 who use an account in a bank or other financial institution and percentage who own a mobile phone; among women who own a mobile phone, percentage who use the phone for financial transactions, according to background characteristics, Ethiopia DHS 2016 Background characteristic Use a bank account Own a mobile phone Number of women Use mobile phone for financial transactions Number of women who own a mobile phone Age 15-19 7.8 29.3 3,381 2.6 992 20-24 16.3 37.2 2,762 6.8 1,027 25-29 18.7 32.5 2,957 5.4 961 30-34 15.9 23.7 2,345 3.3 557 35-39 17.6 18.4 1,932 9.6 355 40-44 15.7 17.3 1,290 4.4 223 45-49 17.9 16.5 1,017 4.9 167 Residence Urban 43.5 71.3 3,476 6.6 2,477 Rural 7.0 14.8 12,207 3.1 1,806 Region Tigray 22.7 31.4 1,129 8.5 355 Affar 7.4 31.3 128 1.6 40 Amhara 20.9 21.2 3,714 6.3 788 Oromiya 8.4 23.3 5,701 4.2 1,329 Somali 4.5 35.0 459 1.3 161 Benishangul-Gumuz 9.2 25.1 160 4.4 40 SNNPR 8.0 20.4 3,288 4.0 669 Gambela 18.3 46.1 44 4.2 20 Harari 26.0 55.2 38 4.9 21 Addis Ababa 53.6 87.0 930 5.9 809 Dire Dawa 29.1 55.8 90 4.8 50 Education No education 7.1 8.6 7,498 2.1 647 Primary 11.4 27.8 5,490 3.3 1,529 Secondary 32.3 68.9 1,817 4.9 1,251 More than secondary 70.3 97.6 877 11.0 856 Wealth quintile Lowest 2.8 7.2 2,633 2.4 189 Second 3.9 8.8 2,809 0.2 247 Middle 6.3 13.1 2,978 3.7 391 Fourth 10.9 21.7 3,100 3.9 673 Highest 39.8 66.9 4,163 6.2 2,784 Total 15.1 27.3 15,683 5.1 4,283 Women’s Empowerment • 277 Table 14.7.2 Ownership and use of bank accounts and mobile phones: Men Percentage of men age 15-49 who use an account in a bank or other financial institution and percentage who own a mobile phone; among men who own a mobile phone, percentage who use the phone for financial transactions, according to background characteristics, Ethiopia DHS 2016 Background characteristic Use a bank account Own a mobile phone Number of men Use mobile phone for financial transactions Number of men who own a mobile phone Age 15-19 9.7 42.2 2,572 5.2 1,086 20-24 23.3 65.2 1,883 9.9 1,228 25-29 32.3 66.0 1,977 10.2 1,304 30-34 32.3 60.5 1,635 8.3 988 35-39 27.5 54.8 1,386 9.1 760 40-44 32.3 48.6 1,206 9.7 587 45-49 31.1 42.5 947 10.6 403 Residence Urban 62.7 87.0 2,303 12.2 2,004 Rural 15.9 46.8 9,302 7.3 4,352 Region Tigray 35.5 62.3 708 5.1 441 Affar 18.4 66.0 82 6.4 54 Amhara 33.6 48.4 2,914 2.2 1,412 Oromiya 17.0 53.5 4,409 14.2 2,358 Somali 8.1 70.6 301 2.6 212 Benishangul-Gumuz 21.9 55.9 118 2.5 66 SNNPR 18.7 49.5 2,371 8.4 1,174 Gambela 37.4 73.1 35 3.2 25 Harari 32.5 77.3 29 9.3 22 Addis Ababa 66.6 94.4 573 10.5 541 Dire Dawa 43.8 75.6 66 9.7 50 Education No education 14.2 31.9 3,203 3.4 1,020 Primary 17.9 51.8 5,608 6.4 2,905 Secondary 36.5 80.9 1,785 9.6 1,443 More than secondary 80.1 97.7 1,010 20.4 987 Wealth quintile Lowest 6.7 31.4 1,839 3.1 578 Second 9.6 37.3 2,118 5.0 789 Middle 14.5 46.1 2,246 5.2 1,035 Fourth 22.8 57.6 2,466 8.1 1,421 Highest 58.1 86.3 2,935 13.2 2,533 Total 15-49 25.2 54.8 11,606 8.8 6,356 50-59 32.8 41.8 1,082 5.3 453 Total 15-59 25.8 53.7 12,688 8.6 6,808 278 • Women’s Empowerment Table 14.8 Person deciding on a woman’s first marriage Percent distribution of ever-married women age 15-49 by the person making the decision on a woman’s first marriage, according to background characteristics, Ethiopia DHS 2016 Person making decision on a woman’s first marriage Total Number of ever-married women Background characteristic Myself Parents Other family/ relative Other Age 15-19 41.2 55.8 1.6 1.5 100.0 739 20-24 46.7 49.0 3.3 1.0 100.0 1,904 25-29 42.9 54.0 2.1 1.0 100.0 2,612 30-34 32.5 63.0 2.7 1.8 100.0 2,249 35-39 27.2 66.8 3.9 2.2 100.0 1,870 40-44 26.2 69.7 2.7 1.4 100.0 1,266 45-49 20.8 76.2 1.6 1.4 100.0 1,006 Number of living children 0 49.0 47.6 2.7 0.7 100.0 1,240 1-2 46.7 49.6 2.3 1.5 100.0 3,690 3-4 30.8 64.6 2.9 1.7 100.0 3,056 5+ 22.4 73.1 2.8 1.6 100.0 3,661 Residence Urban 58.2 38.5 1.5 1.7 100.0 2,102 Rural 30.1 65.6 2.9 1.4 100.0 9,544 Region Tigray 19.1 80.2 0.6 0.2 100.0 847 Affar 16.8 81.5 1.1 0.6 100.0 108 Amhara 15.1 83.3 1.3 0.3 100.0 2,888 Oromiya 34.6 61.2 2.3 1.8 100.0 4,433 Somali 67.9 31.8 0.2 0.1 100.0 358 Benishangul-Gumuz 25.9 73.3 0.3 0.5 100.0 125 SNNPR 53.8 36.3 6.7 3.2 100.0 2,310 Gambela 58.2 40.3 0.7 0.8 100.0 34 Harari 75.8 23.7 0.1 0.5 100.0 29 Addis Ababa 76.9 20.9 1.2 1.0 100.0 451 Dire Dawa 62.9 36.2 0.3 0.7 100.0 63 Education No education 25.0 71.0 2.8 1.2 100.0 7,059 Primary 42.9 51.8 2.8 2.4 100.0 3,351 Secondary 64.9 33.0 1.6 0.5 100.0 764 More than secondary 83.4 15.3 0.7 0.7 100.0 473 Wealth quintile Lowest 28.9 68.0 2.4 0.7 100.0 2,219 Second 28.4 67.5 2.9 1.2 100.0 2,284 Middle 28.5 66.3 4.0 1.3 100.0 2,324 Fourth 30.7 64.4 2.4 2.4 100.0 2,242 Highest 56.5 40.2 1.7 1.7 100.0 2,576 Total 35.2 60.7 2.7 1.5 100.0 11,647 Women’s Empowerment • 279 Table 14.9 Schooling after marriage Percentage of ever-married women age 15-49 who were attending school before marriage; among women who attended school before marriage, percentage who continued to attend school after marriage; among ever married women who stopped school after marriage, reasons for discontinuing school, according to background characteristics, Ethiopia DHS 2016 Percentage attending school before marriage Number of ever- married women Among women who attended school before marriage: Among women who stopped attending school after marriage, reasons for discontinuing school: Background characteristic Percentage who stopped attending school after marriage Number who attended school before marriage Graduated from school Too busy with family life Husband refused Other Total Number of women who stopped going to school after marriage Age 15-19 46.5 739 72.3 344 4.9 47.2 29.7 18.2 100.0 249 20-24 41.4 1,904 79.3 788 5.9 59.0 23.0 12.2 100.0 625 25-29 28.1 2,612 74.0 733 7.0 65.7 21.0 6.3 100.0 543 30-34 18.8 2,249 73.1 422 4.4 67.2 19.9 8.4 100.0 308 35-39 16.1 1,870 76.4 302 1.8 67.8 20.6 9.9 100.0 231 40-44 16.9 1,266 78.1 214 1.6 65.1 27.2 6.1 100.0 167 45-49 13.4 1,006 67.9 135 2.4 61.9 20.8 15.0 100.0 92 Number of living children 0 43.1 1,240 65.4 534 11.6 35.5 29.9 23.0 100.0 349 1-2 37.6 3,690 74.3 1,389 5.0 65.2 20.1 9.7 100.0 1,032 3-4 19.0 3,056 81.3 581 3.1 70.7 21.0 5.3 100.0 472 5+ 11.9 3,661 83.0 435 0.7 66.8 26.0 6.5 100.0 361 Residence Urban 47.0 2,102 54.1 988 13.7 63.0 12.2 11.1 100.0 534 Rural 20.4 9,544 86.1 1,951 2.2 61.6 26.2 10.0 100.0 1,680 Region Tigray 27.4 847 66.0 232 12.7 46.8 24.9 15.7 100.0 153 Affar 14.8 108 50.0 16 3.3 48.9 32.2 15.6 100.0 8 Amhara 18.7 2,888 63.6 539 5.9 41.2 36.3 16.6 100.0 343 Oromiya 24.7 4,433 83.5 1,096 3.5 71.4 18.9 6.1 100.0 915 Somali 11.3 358 53.4 40 5.2 56.5 15.6 22.7 100.0 22 Benishangul-Gumuz 31.0 125 75.0 39 3.3 57.2 31.7 7.9 100.0 29 SNNPR 31.2 2,310 81.9 720 3.3 62.6 23.5 10.6 100.0 590 Gambela 50.5 34 48.0 17 8.1 69.0 17.0 5.9 100.0 8 Harari 33.1 29 68.5 10 4.9 86.9 4.5 3.8 100.0 7 Addis Ababa 45.5 451 59.8 205 11.4 63.6 10.3 14.7 100.0 123 Dire Dawa 38.7 63 69.4 24 4.9 78.8 7.6 8.7 100.0 17 Education No education 1.0 7,059 82.2 72 0.0 74.2 14.1 11.7 100.0 59 Primary 60.3 3,351 87.3 2,020 0.6 63.5 25.8 10.1 100.0 1,764 Secondary 70.0 764 56.6 535 17.6 56.4 12.9 13.1 100.0 303 More than secondary 65.9 473 28.4 311 51.7 40.4 3.2 4.7 100.0 89 Wealth quintile Lowest 10.6 2,219 86.3 235 1.0 64.6 22.1 12.2 100.0 203 Second 17.2 2,284 93.0 393 2.2 59.0 27.3 11.5 100.0 365 Middle 21.5 2,324 87.5 501 2.1 62.8 25.7 9.4 100.0 438 Fourth 27.9 2,242 81.7 627 2.3 56.7 31.0 9.9 100.0 512 Highest 46.0 2,576 58.8 1,184 11.2 66.0 12.8 10.0 100.0 696 Total 25.2 11,647 75.4 2,939 4.9 61.9 22.8 10.3 100.0 2,215 280 • Women’s Empowerment Table 14.10 Men’s participation in household chores Percentage of currently married women age 15-49 who reported that their husbands help with the household chores; among women whose husbands help with household chores, percent distribution by average frequency of husbands help, according to background characteristics, Ethiopia DHS 2016 Percentage of women whose husband participates in household chores Number of currently married women Among women whose husbands participate in household chores, percent distribution by average frequency of husbands help: Background characteristic Almost every day At least once a week Rarely Total Number of women whose husbands help with household chores Age 15-19 33.7 588 19.2 20.4 60.3 100.0 198 20-24 44.4 1,710 20.6 19.5 59.9 100.0 758 25-29 42.9 2,402 16.5 17.5 66.0 100.0 1,031 30-34 36.8 2,049 13.1 20.1 66.9 100.0 754 35-39 32.7 1,613 19.8 19.9 60.4 100.0 527 40-44 28.1 1,064 18.1 23.5 58.4 100.0 299 45-49 22.4 798 18.8 19.6 61.6 100.0 179 Number of living children 0 41.0 925 23.2 15.2 61.6 100.0 379 1-2 45.5 3,137 18.6 19.6 61.8 100.0 1,427 3-4 37.4 2,761 15.2 21.0 63.8 100.0 1,032 5+ 26.7 3,401 15.8 19.4 64.7 100.0 908 Residence Urban 49.9 1,658 23.4 18.5 58.1 100.0 828 Rural 34.1 8,565 15.8 19.8 64.5 100.0 2,920 Region Tigray 44.0 658 17.1 21.4 61.5 100.0 290 Affar 27.3 96 34.5 24.2 41.3 100.0 26 Amhara 44.2 2,414 16.7 19.0 64.2 100.0 1,066 Oromiya 31.1 3,987 14.3 19.2 66.5 100.0 1,242 Somali 11.8 324 17.5 12.6 69.9 100.0 38 Benishangul-Gumuz 40.0 114 8.5 13.8 77.7 100.0 46 SNNPR 36.6 2,173 19.2 19.8 61.0 100.0 794 Gambela 32.5 29 17.8 9.7 72.6 100.0 10 Harari 23.9 25 22.0 39.4 38.6 100.0 6 Addis Ababa 60.3 355 33.7 21.0 45.4 100.0 214 Dire Dawa 32.1 50 14.0 27.4 58.6 100.0 16 Education No education 30.4 6,253 17.1 21.0 61.9 100.0 1,902 Primary 41.6 2,895 15.3 16.9 67.8 100.0 1,204 Secondary 54.9 654 20.5 22.1 57.3 100.0 359 More than secondary 67.1 421 25.4 17.0 57.7 100.0 282 Wealth quintile Lowest 29.4 1,953 16.9 18.2 64.9 100.0 574 Second 32.5 2,074 17.2 18.6 64.2 100.0 674 Middle 32.1 2,057 13.3 25.0 61.8 100.0 660 Fourth 40.8 1,999 14.8 18.6 66.6 100.0 815 Highest 47.9 2,140 22.8 18.0 59.2 100.0 1,024 Total 36.7 10,223 17.5 19.5 63.0 100.0 3,747 Table 14.11 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, Ethiopia DHS 2016 Decision Mainly wife Wife and husband jointly Mainly husband Someone else Other Total Number of women WOMEN Own health care 15.4 66.0 18.2 0.3 0.1 100.0 10,223 Major household purchases 10.6 67.6 21.4 0.4 0.1 100.0 10,223 Visits to her family or relatives 18.0 65.8 16.0 0.2 0.1 100.0 10,223 MEN Man’s own health care 2.8 69.6 27.3 0.3 0.0 100.0 6,441 Major household purchases 4.3 76.9 18.2 0.5 0.1 100.0 6,441 Women’s Empowerment • 281 Table 14.12.1 Women’s participation in decision making by background characteristics Percentage of currently married women age 15-49 who usually make specific decisions either alone or jointly with their husband, according to background characteristics, Ethiopia DHS 2016 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 78.7 73.3 81.3 68.1 12.8 588 20-24 80.5 76.8 82.7 68.9 11.1 1,710 25-29 82.3 81.2 85.5 71.7 8.0 2,402 30-34 84.3 79.0 85.4 72.6 8.6 2,049 35-39 78.9 76.6 83.1 69.1 12.6 1,613 40-44 82.0 77.2 82.0 70.7 11.5 1,064 45-49 79.5 78.3 82.4 69.9 11.9 798 Employment (last 12 months) Not employed 78.3 73.5 81.0 66.6 13.2 5,275 Employed for cash 86.4 83.5 86.3 74.8 6.9 2,072 Employed not for cash 83.6 83.1 87.1 74.8 7.4 2,876 Number of living children 0 81.4 78.8 85.5 70.5 8.8 925 1-2 83.1 80.7 85.0 72.9 9.0 3,137 3-4 83.1 79.5 84.4 72.3 9.7 2,761 5+ 78.6 74.7 81.6 67.0 12.5 3,401 Residence Urban 91.0 88.1 91.7 80.9 3.2 1,658 Rural 79.6 76.3 82.2 68.6 11.7 8,565 Region Tigray 84.2 79.1 81.5 70.3 9.9 658 Affar 71.2 70.2 74.5 61.5 17.8 96 Amhara 87.0 86.7 90.3 78.3 4.4 2,414 Oromiya 79.8 76.7 83.8 70.9 12.3 3,987 Somali 75.9 69.3 80.5 62.3 13.8 324 Benishangul-Gumuz 79.7 73.5 83.5 67.3 12.5 114 SNNPR 76.7 71.1 76.2 61.1 14.0 2,173 Gambela 79.4 74.7 80.5 64.5 10.6 29 Harari 91.6 89.6 91.5 87.9 6.5 25 Addis Ababa 92.8 89.6 93.5 82.3 1.9 355 Dire Dawa 84.4 83.2 88.7 71.2 4.0 50 Education No education 79.2 75.8 82.4 68.2 12.0 6,253 Primary 82.4 78.6 82.9 70.8 9.8 2,895 Secondary 91.5 88.5 92.0 81.5 2.9 654 More than secondary 92.2 94.9 96.9 87.4 0.6 421 Wealth quintile Lowest 76.3 72.3 79.4 64.8 15.1 1,953 Second 77.5 75.3 80.1 67.2 13.0 2,074 Middle 81.0 75.2 81.0 67.3 11.7 2,057 Fourth 81.7 80.8 86.8 72.6 8.1 1,999 Highest 90.1 86.9 91.2 80.2 4.2 2,140 Total 81.4 78.2 83.8 70.6 10.3 10,223 282 • Women’s Empowerment Table 14.12.2 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, Ethiopia DHS 2016 Specific decisions Both decisions Neither of the two decisions Number of men Background characteristic Man’s own health care Making major household purchases Age 15-19 (95.3) (96.7) (94.7) (2.8) 26 20-24 95.2 93.5 91.8 3.0 474 25-29 95.8 94.0 92.2 2.4 1,227 30-34 97.5 95.8 95.1 1.9 1,389 35-39 96.7 94.6 93.7 2.4 1,285 40-44 98.2 96.6 95.7 0.9 1,137 45-49 97.3 95.0 94.7 2.3 903 Employment (last 12 months) Not employed 82.3 74.1 72.9 16.4 55 Employed for cash 97.2 94.3 93.5 2.1 2,096 Employed not for cash 97.0 95.8 94.6 1.8 4,291 Number of living children 0 93.3 90.7 89.2 5.1 671 1-2 97.1 95.9 94.3 1.3 2,074 3-4 97.4 95.3 94.5 1.9 1,736 5+ 97.5 95.6 95.1 2.0 1,961 Residence Urban 96.9 91.3 90.2 2.1 1,011 Rural 96.9 95.8 94.8 2.0 5,430 Region Tigray 95.0 96.9 92.9 1.0 352 Affar 91.7 86.2 85.4 7.5 48 Amhara 98.4 97.2 96.3 0.8 1,633 Oromiya 96.5 94.7 93.8 2.6 2,558 Somali 94.0 81.7 81.4 5.7 174 Benishangul-Gumuz 96.2 96.4 93.7 1.1 72 SNNPR 98.0 97.4 96.9 1.5 1,323 Gambela 96.7 95.3 92.9 0.9 17 Harari 85.0 77.5 76.4 13.9 16 Addis Ababa 96.9 86.4 84.5 1.3 217 Dire Dawa 69.0 58.1 55.9 28.7 32 Education No education 96.5 95.7 94.6 2.4 2,558 Primary 97.3 95.3 94.4 1.7 2,769 Secondary 97.7 94.2 93.4 1.6 625 More than secondary 95.9 92.0 90.6 2.7 489 Wealth quintile Lowest 96.0 94.3 93.1 2.8 1,161 Second 96.6 95.1 94.3 2.7 1,359 Middle 97.0 96.4 95.6 2.1 1,310 Fourth 97.8 96.8 95.8 1.1 1,255 Highest 97.1 92.9 91.6 1.6 1,357 Total 15-49 96.9 95.1 94.1 2.1 6,441 50-59 96.4 94.3 93.1 2.3 1,029 Total 15-59 96.9 95.0 93.9 2.1 7,471 Note: Figures in parentheses are based on 25-49 unweighted cases. Women’s Empowerment • 283 Table 14.13.1 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, Ethiopia DHS 2016 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 35.5 38.7 39.2 44.5 27.4 60.3 3,381 20-24 37.6 38.4 39.0 45.6 31.2 60.3 2,762 25-29 38.6 41.5 43.5 47.2 36.4 62.1 2,957 30-34 43.2 46.2 49.2 50.6 38.8 66.1 2,345 35-39 44.0 47.1 46.3 50.8 40.0 66.2 1,932 40-44 43.2 46.9 50.0 49.6 38.5 66.5 1,290 45-49 42.9 41.0 40.7 46.8 39.4 64.1 1,017 Employment (last 12 months) Not employed 40.0 42.4 45.2 47.7 35.4 62.5 7,819 Employed for cash 30.2 33.8 36.0 40.7 25.7 54.6 3,693 Employed not for cash 47.9 49.0 46.5 53.1 41.4 71.3 4,171 Number of living children 0 31.7 34.4 35.7 41.6 25.4 56.0 5,185 1-2 39.1 41.6 42.0 47.2 33.7 62.3 3,770 3-4 45.5 48.7 48.4 50.9 41.6 67.7 3,064 5+ 47.2 48.2 51.3 53.2 43.2 69.7 3,664 Marital status Never married 30.5 32.3 34.4 39.8 23.6 53.7 4,036 Married or living together 43.8 46.4 47.5 50.8 39.4 66.6 10,223 Divorced/separated/widowed 37.1 39.7 38.7 45.4 32.7 63.6 1,423 Residence Urban 16.3 21.1 23.6 29.0 15.4 39.2 3,476 Rural 46.4 48.1 49.0 52.7 40.2 69.8 12,207 Region Tigray 39.0 45.5 38.5 53.5 33.4 65.0 1,129 Affar 46.0 48.5 51.6 52.7 50.4 68.5 128 Amhara 35.8 41.5 38.0 47.0 31.2 64.7 3,714 Oromiya 45.9 47.4 53.0 51.0 39.3 68.6 5,701 Somali 19.8 30.6 29.9 27.6 29.8 42.8 459 Benishangul-Gumuz 31.5 35.5 36.7 43.6 34.4 55.2 160 SNNPR 47.6 44.7 46.2 52.3 40.5 65.7 3,288 Gambela 33.0 36.3 38.6 42.0 26.8 60.2 44 Harari 21.9 26.7 32.0 29.7 24.3 39.2 38 Addis Ababa 4.2 8.5 10.1 16.2 4.2 22.9 930 Dire Dawa 23.2 22.3 26.4 28.2 24.9 46.7 90 Education No education 49.3 50.9 52.2 54.5 44.0 71.9 7,498 Primary 39.4 42.3 42.3 47.7 32.9 63.7 5,490 Secondary 17.7 21.4 25.2 31.2 16.1 41.9 1,817 More than secondary 6.4 9.6 11.7 19.6 5.6 26.1 877 Wealth quintile Lowest 50.3 52.5 51.2 53.5 45.2 70.9 2,633 Second 50.5 53.4 54.6 57.9 44.8 75.7 2,809 Middle 46.9 48.0 48.9 53.6 41.4 70.0 2,978 Fourth 41.4 41.6 42.8 47.8 32.9 64.7 3,100 Highest 19.5 24.3 27.1 31.9 17.9 43.2 4,163 Total 39.8 42.2 43.3 47.5 34.7 63.0 15,683 284 • Women’s Empowerment Table 14.13.2 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, Ethiopia DHS 2016 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 14.4 19.8 17.8 23.4 15.2 32.8 2,572 20-24 11.3 15.5 15.8 19.6 12.6 29.4 1,883 25-29 10.5 13.6 16.0 16.6 12.1 24.1 1,977 30-34 10.0 12.8 13.3 15.1 10.5 22.6 1,635 35-39 11.8 15.4 17.8 17.3 11.4 27.2 1,386 40-44 11.4 16.0 17.1 20.5 11.8 26.5 1,206 45-49 10.2 18.2 21.5 19.6 12.9 28.7 947 Employment (last 12 months) Not employed 6.7 11.7 11.5 14.9 9.0 20.9 926 Employed for cash 7.7 9.3 10.6 11.6 8.0 17.5 3,530 Employed not for cash 14.3 19.9 20.5 23.4 15.3 33.6 7,149 Number of living children 0 11.7 16.6 16.0 20.4 13.0 29.0 5,658 1-2 11.9 14.5 16.8 17.8 12.1 25.7 2,202 3-4 11.2 15.0 16.5 17.3 11.8 26.4 1,770 5+ 11.8 16.9 19.3 18.7 12.7 27.3 1,976 Marital status Never married 11.4 16.3 15.7 20.2 12.7 28.2 4,882 Married or living together 11.5 15.5 17.3 18.0 12.1 26.7 6,441 Divorced/separated/widowed 19.8 22.9 22.6 26.6 21.0 40.9 282 Residence Urban 3.8 6.3 7.2 10.6 5.9 15.1 2,303 Rural 13.6 18.4 19.2 21.2 14.3 30.8 9,302 Region Tigray 12.1 18.7 20.8 24.2 13.6 31.4 708 Affar 5.6 9.5 8.1 9.3 9.2 16.4 82 Amhara 18.7 25.3 25.1 33.7 19.5 45.9 2,914 Oromiya 11.1 15.8 17.2 16.5 11.7 25.9 4,409 Somali 3.8 8.8 8.6 8.7 8.8 13.9 301 Benishangul-Gumuz 10.1 12.5 16.5 17.5 10.0 27.5 118 SNNPR 7.8 9.1 9.7 10.4 9.0 14.9 2,371 Gambela 14.2 18.5 18.0 22.7 15.2 36.4 35 Harari 12.3 14.5 12.2 14.8 13.2 22.3 29 Addis Ababa 1.0 2.2 2.3 3.7 2.0 6.9 573 Dire Dawa 5.2 9.0 8.3 5.9 5.1 15.0 66 Education No education 16.7 21.5 22.4 25.9 17.4 36.0 3,203 Primary 12.3 17.4 17.7 19.3 13.3 29.0 5,608 Secondary 5.3 7.9 10.2 13.0 6.4 18.0 1,785 More than secondary 3.2 5.5 5.6 7.5 4.3 11.2 1,010 Wealth quintile Lowest 15.3 19.4 20.2 21.6 16.0 31.8 1,839 Second 15.1 20.0 20.3 23.7 16.5 32.2 2,118 Middle 13.0 18.9 20.2 22.3 13.6 31.2 2,246 Fourth 13.3 17.0 17.4 19.5 13.6 30.4 2,466 Highest 4.4 8.0 8.9 11.6 6.0 16.9 2,935 Total 15-49 11.7 16.0 16.8 19.1 12.6 27.7 11,606 50-59 11.5 14.7 18.2 18.3 12.8 26.5 1,082 Total 15-59 11.6 15.9 16.9 19.1 12.6 27.6 12,688 Women’s Empowerment • 285 Table 14.14 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, Ethiopia DHS 2016 Women Men Woman is justified in: Number of women Woman is justified in: Number of men Background characteristic Refusing to have sexual intercourse with her husband if she knows he has sex with other women Asking that they use a condom if she knows that her husband has an STI Refusing to have sexual intercourse with her husband if she knows he has sex with other women Asking that they use a condom if she knows that her husband has an STI Age 15-24 73.7 65.2 6,143 80.4 79.0 4,455 15-19 71.9 65.6 3,381 78.5 77.6 2,572 20-24 76.0 64.6 2,762 83.0 81.0 1,883 25-29 74.5 60.8 2,957 82.8 81.0 1,977 30-39 71.8 57.5 4,277 81.8 78.8 3,020 40-49 72.0 54.3 2,306 84.3 80.4 2,154 Marital status Never married 75.5 71.4 4,036 79.5 78.5 4,882 Ever had sex 80.6 80.5 401 85.4 84.9 1,061 Never had sex 75.0 70.4 3,636 77.8 76.7 3,821 Married/living together 71.2 55.6 10,223 83.5 80.2 6,441 Divorced/separated/widowed 79.9 66.0 1,423 86.3 84.3 282 Residence Urban 85.6 82.3 3,476 87.9 86.4 2,303 Rural 69.5 54.5 12,207 80.4 77.9 9,302 Region Tigray 83.7 76.0 1,129 90.6 93.6 708 Affar 65.2 37.8 128 82.0 76.0 82 Amhara 86.1 69.1 3,714 91.9 87.3 2,914 Oromiya 60.9 47.9 5,701 77.0 76.0 4,409 Somali 38.0 17.7 459 64.2 45.7 301 Benishangul-Gumuz 55.6 48.0 160 79.3 71.2 118 SNNPR 76.9 67.3 3,288 76.9 74.7 2,371 Gambela 75.1 66.9 44 84.2 78.8 35 Harari 56.1 43.2 38 75.5 68.9 29 Addis Ababa 91.8 90.2 930 87.5 90.5 573 Dire Dawa 67.2 58.1 90 88.9 81.3 66 Education No education 66.6 47.3 7,498 76.8 73.7 3,203 Primary 74.6 66.8 5,490 81.7 79.1 5,608 Secondary 86.8 83.1 1,817 87.9 86.3 1,785 More than secondary 91.0 89.6 877 88.4 88.8 1,010 Wealth quintile Lowest 62.6 44.6 2,633 77.5 73.2 1,839 Second 67.3 51.5 2,809 79.2 76.6 2,118 Middle 71.0 54.1 2,978 81.6 79.7 2,246 Fourth 74.4 62.2 3,100 82.0 80.0 2,466 Highest 84.2 80.5 4,163 86.7 85.2 2,935 Total 15-49 73.1 60.7 15,683 81.9 79.6 11,606 50-59 na na na 81.6 77.6 1,082 Total 15-59 na na na 81.9 79.4 12,688 na = Not applicable. 286 • Women’s Empowerment Table 14.15 Ability to negotiate sexual relations with husband Percentage of currently married women age 15-49 who can say no to their husband if they do not want to have sexual intercourse, and percentage who can ask their husband to use a condom, according to background characteristics, Ethiopia DHS 2016 Background characteristic Percentage who can say no to their husband if they do not want to have sexual intercourse Percentage who can ask their husband to use a condom Number of women Age 15-24 49.6 34.5 2,298 15-19 48.3 35.6 588 20-24 50.0 34.2 1,710 25-29 45.8 33.5 2,402 30-39 43.4 27.7 3,661 40-49 43.8 24.9 1,862 Residence Urban 63.8 61.3 1,658 Rural 41.9 24.1 8,565 Region Tigray 69.7 43.0 658 Affar 44.9 19.7 96 Amhara 64.9 33.4 2,414 Oromiya 34.1 25.6 3,987 Somali 28.3 7.2 324 Benishangul-Gumuz 41.4 29.6 114 SNNPR 36.2 28.1 2,173 Gambela 50.4 35.8 29 Harari 49.1 34.1 25 Addis Ababa 67.8 67.9 355 Dire Dawa 46.3 41.2 50 Education No education 39.8 20.0 6,253 Primary 48.0 36.8 2,895 Secondary 67.5 62.4 654 More than secondary 77.2 83.0 421 Wealth quintile Lowest 36.4 16.8 1,953 Second 39.6 23.8 2,074 Middle 42.4 22.0 2,057 Fourth 48.0 31.0 1,999 Highest 59.8 55.3 2,140 Total 45.4 30.1 10,223 Table 14.16 Indicators of women’s empowerment Percentage of currently married women age 15-49 who participate in all decision making and percentage who disagree with all reasons that justify wife-beating, according to value on each of indicator of women’s empowerment, Ethiopia DHS 2016 Empowerment indicator Percentage who participate in all decision making Percentage who disagree with all the reasons that justify wife- beating Number of women Number of decisions in which women participate1 0 na 25.1 1,055 1-2 na 30.0 1,956 3 na 35.6 7,213 Number of reasons for which wife-beating is justified2 0 75.1 na 3,419 1-2 71.8 na 2,078 3-4 67.3 na 2,345 5 66.1 na 2,381 na = Not applicable. 1 See Table 14.12.1 for the list of decisions. 2 See Table 14.13.1 for the list of reasons. Women’s Empowerment • 287 Table 14.17 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, Ethiopia DHS 2016 Any method Any modern method1 Modern methods Any traditional method Not currently using Total Number of women Empowerment indicator Female sterilization Temporary modern female methods2 Male condom Number of decisions in which women participate3 0 26.5 26.5 0.4 26.1 0.0 0.0 73.5 100.0 1,055 1-2 35.5 34.8 0.3 34.5 0.0 0.7 64.5 100.0 1,956 3 37.4 36.7 0.5 36.1 0.1 0.7 62.6 100.0 7,213 Number of reasons for which wife-beating is justified4 0 40.0 39.0 0.3 38.5 0.1 1.1 60.0 100.0 3,419 1-2 37.1 36.5 0.5 35.9 0.0 0.6 62.9 100.0 2,078 3-4 35.6 35.3 0.4 34.9 0.0 0.3 64.4 100.0 2,345 5 29.2 28.8 0.5 28.3 0.0 0.4 70.8 100.0 2,381 Total 35.9 35.3 0.4 34.8 0.1 0.6 64.1 100.0 10,223 Note: If more than one method is used, only the most effective method is considered in this tabulation. 1 Female sterilization, male sterilization, pill, IUD, injectables, implants, male condom, female condom, emergency contraception, standard days method (SDM), lactational amenorrhea method (LAM), and other modern methods. 2 Pill, IUD, injectables, implants, female condom, emergency contraception, standard days method (SDM), lactational amenorrhea method (LAM), and other modern methods. 3 See Table 14.12.1 for the list of decisions. 4 See Table 14.13.1 for the list of reasons. Table 14.18 Ideal number of children and unmet need for family planning by women’s empowerment Mean ideal number of children for women age 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, Ethiopia DHS 2016 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 5.8 943 17.5 13.2 30.7 1,055 1-2 5.3 1,694 14.6 8.2 22.8 1,956 3 4.7 6,263 11.9 9.1 21.0 7,213 Number of reasons for which wife-beating is justified4 0 4.3 5,370 12.6 8.1 20.7 3,419 1-2 4.2 3,018 13.2 10.8 24.1 2,078 3-4 4.6 2,898 11.8 9.1 20.9 2,345 5 4.8 2,720 14.5 10.0 24.5 2,381 Total 4.5 14,005 13.0 9.3 22.3 10,223 1 Mean excludes respondents who gave non-numeric responses. 2 Figures for unmet need correspond to the revised definition described in Bradley et al. 2012. 3 Restricted to currently married women. See Table 14.12.1 for the list of decisions. 4 See Table 14.13.1 for the list of reasons. 288 • Women’s Empowerment Table 14.19 Reproductive health care by women’s empowerment Percentage of women age 15-49 with a live birth in the 5 years before 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, Ethiopia DHS 2016 Empowerment indicator Percentage receiving antenatal care from a skilled provider1 Percentage receiving delivery care from a skilled provider1 Percentage of women with a postnatal check- up in the first two days after birth2 Number of women with a child born in the last five years Number of decisions in which women participate3 0 44.2 24.0 8.4 789 1-2 62.9 32.7 16.3 1,405 3 65.4 34.4 15.3 4,914 Number of reasons for which wife-beating is justified4 0 67.7 43.2 18.6 2,482 1-2 62.0 32.1 16.3 1,561 3-4 62.3 29.5 13.2 1,720 5 55.6 24.2 10.4 1,828 Total 62.4 33.3 14.9 7,590 1 “Skilled provider” includes doctor, nurse, midwife, health officer, and health extension worker. 2 Includes women who received a postnatal check-up from a doctor, nurse, midwife, health officer, and health extension worker or traditional birth attendant (TBA) in the first 2 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 14.12.1 for the list of decisions. 4 See Table 14.13.1 for the list of reasons. Table 14.20 Early childhood mortality rates by indicators of women’s empowerment Infant, child, and under-5 mortality rates for the 10-year period before the survey, according to indicators of women’s empowerment, Ethiopia DHS 2016 Empowerment indicator Infant mortality (1q0) Child mortality (4q1) Under-5 mortality (5q0) Number of decisions in which women participate1 0 61 26 86 1-2 67 19 84 3 59 21 79 Number of reasons for which wife-beating is justified2 0 63 21 83 1-2 69 27 94 3-4 57 19 74 5 56 21 77 1 Restricted to currently married women. See Table 14.12.1 for the list of decisions. 2 See Table 14.13.1 for the list of reasons. Violence Against Women • 289 VIOLENCE AGAINST WOMEN 15 Key Findings  Experience of violence: Among women age 15-49, 23% have experienced physical violence and 10% have experienced sexual violence. Four percent of women have experienced physical violence during a pregnancy.  Marital control: Sixteen percent of ever-married women have experienced at least three types of marital control behaviours by their husbands or partners. Forty-three percent have never experienced marital control behaviours by their husbands or partners.  Spousal violence: Thirty-four percent of ever-married women age 15-49 have experienced spousal physical, sexual, or emotional violence. Physical and emotional violence were experienced by 24% each, and sexual violence by10%.  Injuries due to spousal violence: Twenty-two percent of ever-married women who experienced spousal, physical, or sexual violence reported injuries, including 19% who reported cuts, bruises, or aches and 10% who reported deep wounds and other serious injuries.  Help seeking: About one-quarter of women who have experienced physical or sexual violence has sought help. ender-based violence against women, often referred to as violence against women and girls, has been acknowledged worldwide as a violation of basic human rights. Growing research has highlighted the health burdens, intergenerational effects, and demographic consequences of such violence (United Nations 2006). In Ethiopia, violence against women and girls continues to be a major challenge and a threat to women’s empowerment. Women and girls face physical, emotional, and sexual abuses that undermine their health and ability to earn a living; disrupt their social systems and relationships; and rob them of their childhood and education. Ethiopia has put in place appropriate and effective legal and policy provisions to promote the rights of women and girls. These rights are enshrined in the Constitution. Ethiopia has also ratified many of the international and continental agreements that promote and protect women’s rights, including the Convention on the Elimination of Discrimination against Women (CEDAW), and the Protocol to the African Charter on the Rights of Women in Africa. In addition, Ethiopia has established specific legal measures and actions to address violence, including the Revised Family Law in 2000 and the Revised Criminal Code in 2005 (UN Women 2016). The government has also put in place the requisite institutional mechanisms at federal and regional levels, including the establishment of (1) The Ministry of Women, Children and Youth Affairs Offices MOWCYA, (2) Child and Women Protection Units within the various police units, and (3) a Special Bench for violence against women cases within the federal criminal court. G 290 • Violence Against Women Ethiopia’s second Growth and Transformational Plan (GTP II 2015) has for the first time included ending violence against women as a priority. In the next 5 years, during the GTP II, Ethiopia will establish hotlines for women and children experiencing violence, set up 11 new one-stop centres and rehabilitation centres, and also strengthen existing ones. The new national Women’s Development and Change Strategy and the revised package on how to realize the strategy has put in place a clear direction on protection, prevention, and provision of services for women survivors of violence. Furthermore, the MOWCYA is committed to ending violence against women by including indicators on violence reduction in its 5-year sectoral plan (2016-2020). Taking into account these initiatives, the 2016 EDHS was tasked with providing up-to-date, reliable, and concrete data on violence against women. This data should allow targeting in a specific, measurable way and enable informed intervention programs. Accordingly, the 2016 EDHS implemented a module of questions on domestic violence, the most common form of violence against women. In accord with the World Health Organization’s guidelines on the ethical collection of information on domestic violence, only one eligible woman per household was randomly selected for interviewing, and the module was not implemented if privacy could not be obtained (WHO 2001). In total, 5,860 women were asked questions about violence against women. Three percent of women eligible for the domestic violence module could not be successfully interviewed, mainly due to lack of privacy. 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. 15.1 MEASUREMENT OF VIOLENCE In the 2016 EDHS, information was obtained from women who had never married on their experience of violence and from ever-married women on their experience of violence committed by their current and former husbands/partners and by others. Specifically, violence committed by the current husband/partner for currently married women and by the most recent husband/partner for formerly married women was measured by asking all ever-married women if their husband/partner ever did the following:  Emotional spousal violence: say or do something to humiliate you in front of others; threaten to hurt or harm you or someone close to you; insult you or make you feel bad about yourself  Physical spousal violence: push you, shake you, or throw something at you; slap you; twist your arm or pull your hair; punch you with his/her fist or with something that could hurt you; kick you, drag you, or beat you up; try to choke you or burn you on purpose; or threaten or attack you with a knife, gun, or any other weapon  Sexual spousal violence: physically force you to have sexual intercourse with him even when you did not want to; physically force you to perform any other sexual acts you did not want to; force you with threats or in any other way to perform sexual acts you did not want to In addition, information was obtained from all women (married and unmarried) about physical violence committed by anyone (other than a current or most recent husband/partner) since they were age 15 by asking if anyone had hit, slapped, kicked, or done something else to hurt them physically. All women were asked about experience of sexual violence committed by anyone (other than a current or most recent husband/partner) by asking if at any time in their life, as a child or as an adult, they were forced in any way to have sexual intercourse or to perform any other sexual acts when they did not want to do so. All women reporting any experience of physical or sexual violence were asked whether and from whom they had sought help. Violence Against Women • 291 15.2 WOMEN’S EXPERIENCE OF PHYSICAL VIOLENCE FROM ANYONE 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 before the survey. Sample: Women age 15-49 15.2.1 Prevalence of Physical Violence Twenty-three percent of women age 15-49 have experienced physical violence since age 15, and 15% have experienced physical violence in the past 12 months (Table 15.1). Women who had ever been pregnant were asked whether they had experienced physical violence during any pregnancy. Overall, 4% of women responded affirmatively (Table 15.2). Patterns by background characteristics  The youngest women (age 15-19), women with no children, and never married women (Figure 15.1) are less likely to have experienced violence since age 15 than most other women (Table 15.1).  There is only a small variation in women’s experience of physical violence by urban-rural residence. Rural women are only somewhat more likely (24%) than urban women (21%) to have experienced physical violence since age 15. This is also true for the recent experience of physical violence: 16% of rural women reported experiencing physical violence in the past 12 months, compared with 11% of urban women.  By region, the proportion of women who have experienced physical violence since age 15 ranges from 6% in Somali to 28% in Oromiya.  The experience of physical violence was more likely among employed women, whether employed for cash or not, than among women who were not employed (25% vs. 22%).  Women’s experience of physical violence since age 15 declines sharply with increasing level of education, from 28% for women with no education, to 13% for women with more than secondary education. Figure 15.1 Women’s experience of violence by marital status 7 2 27 12 39 18 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 292 • Violence Against Women  Women with no education are four times as likely to have experienced violence during pregnancy as women with more than secondary education (Figure 15.2). 15.2.2 Perpetrators of Physical Violence  Among all ever-married women age 15-49 who have experienced physical violence since age 15, 68% report their current husbands/partners as perpetrators of physical violence, and 25% report former husbands/partners as perpetrators (Table 15.3).  Never-married women who have ever experienced physical violence since age 15 reported most common perpetrators to be a sister or brother (27%), other relative (14%), father/step- father (13%), and teacher (11%). Eight percent of women reported former boyfriends as perpetrators. 15.3 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 before the survey Sample: Women age 15-49 15.3.1 Prevalence of Sexual Violence Ten percent of women age 15-49 reported that they have experienced sexual violence at some point in their lives, and 7% reported that they had experienced sexual violence in the past 12 months (Table 15.4). Five percent of women had experienced sexual violence by age 18, including 2% who had experienced sexual violence by age 15 (Table 15.5). Patterns by background characteristics  Women’s experience of sexual violence has a linear relationship with age. The percentage of women who have experienced sexual violence increases from 4% for women age 15-19 to 14% for women age 40-49 (Table 15.4).  Urban women (7%) are less likely than rural women (11%) to experience sexual violence.  The proportion of women who have ever experienced sexual violence ranges from less than 1% in Somali to 11%-13% in Amhara, Tigray, and Oromiya. In the past 12 months, about 1 in 10 women (9%) in Oromiya has experienced sexual violence.  Experience of sexual violence is more common among divorced/separated/widowed women (18%) and women who are currently married or living with someone (12%). Two percent of never-married women reported experiencing sexual violence. Women who have more than five children are more likely to have experienced sexual violence in the past 12 months than women with fewer than five children (11% vs. 2% to 8%).  Women with more than secondary education (5%) are half as likely to have ever experienced sexual violence as women with no education (13%). Figure 15.2 Violence during pregnancy by education 4 3 3 1 4 No education Primary Secondary More than secondary Total Percentage among women age 15-49 who have ever been pregnant Violence Against Women • 293 15.3.2 Perpetrators of Sexual Violence The 2016 EDHS report shows that sexual violence is often committed by individuals with whom women have an intimate relationship. Among ever-married women age 15-49 who had ever experienced sexual violence, 69% reported their current husband/partner and 30% reported former husbands/partners as perpetrators. However, non-trivial percentages of all women who have experienced sexual violence also reported current/former boyfriends and other relatives (2% for each) as perpetrators (Table 15.6). 15.4 EXPERIENCE OF DIFFERENT FORMS OF VIOLENCE Women may experience a combination of different forms of violence. Sixteen percent of women experienced physical violence only, 3% experienced sexual violence only, and 7% experienced both physical and sexual violence. Overall, 26% of women age 15-49 have experienced either physical or sexual violence, or both (Table 15.7). 15.5 MARITAL CONTROL BY HUSBAND 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 controlling behaviours: 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 to closely control and monitor their wives’ behaviour are important warning signs and correlates of violence in a relationship. Because the concentration of behaviours is more significant than the display of any single behaviour, the proportion of women whose husbands/partners display at least three of the specified behaviours is also discussed. Thirty-nine percent of ever-married women reported that their husbands/partners are jealous or angry if they talk with other men, 33% reported that their husbands/partners insist on knowing where they are at all times, 16% reported that their husbands/partners try to limit their contact with their families, 15% reported that their husbands/partners do not permit them to meet their female friends, and 13% reported that their husbands/partners frequently accuse them of being unfaithful. Overall, 16% of ever-married women reported that their husbands/partners display three or more of the specified behaviours, and 43% say that they display none of them (Table 15.8). Patterns by background characteristics  Formerly married women (divorced, separated, or widowed) are more likely (25%) to report that their husbands/partners displayed at least three of the specified behaviours than currently married women (15%).  The display of three or more types of marital control behaviour by women’s husbands/partners varies greatly by region: from 22% in Oromiya to 6% in Somali and Benishangul-Gumuz.  Women with more than secondary education are less likely to have husbands/partners that display three or more forms of marital control behaviours (8%) than women with no education (17%).  Women’s reports of controlling behaviours by their husbands/partners vary greatly by whether they report being afraid of their husband/partner or not. While 9% of women who say that they are never afraid of their husband/partner reported at least three controlling behaviours by their 294 • Violence Against Women husbands/partners, this percentage rose to 27% among women who were afraid of their husband/partner most of the time. 15.6 FORMS OF 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 15.6.1 Prevalence of Spousal Violence Thirty-four percent of ever-married women age 15-49 have ever experienced physical, sexual, or emotional violence by their current husband/partner if currently married or most recent husband/partner if formerly married. Twenty-seven percent of ever-married women experienced physical, sexual, or emotional violence in the past 12 months either sometimes (20%) or often (7%) (Table 15.9). Twenty-four percent of ever- married women have experienced spousal physical violence, with 17% experiencing this type of violence in the past 12 months. Of the acts of physical violence committed by current or most recent husbands/partners, the most common type is slapping (19%). Twelve percent of women reported being pushed, shaken, or having something thrown at them, 10% reported being kicked, dragged, or beaten up, 8% reported being punched with the fist or with something that could hurt them, and 6% reported having their arms twisted or their hair pulled. Two percent each of women reported that their husband/partner tried to choke or burn them on purpose and that their husband/partner had threatened or attacked them with a knife, gun, or other weapon (Figure 15.3). Ten percent of ever-married women have experienced one or more acts of spousal sexual violence, with 8% experiencing this type of violence in the past 12 months. The most frequently reported act of sexual violence, reported by 8% of ever-married women, was that their husband/partner used physical force to have sexual intercourse with them when they did not want to. Four percent reported that their husband/partner physically forced them to perform other sexual acts they did not want to do, and 3% reported that their husband/partner forced them with threats or in other ways to perform sexual acts they did not want to do. Figure 15.3 Types of spousal violence 12 10 8 8 6 4 3 2 2 9 6 5 6 4 4 2 1 2 Pushed her, shook her, or threw something at her Kicked her, dragged her, or beat her up Punched her with his fist or with something that could hurt her Physically forced her to have sexual intercourse with him when she did not want to Twisted her arm or pulled her hair Physically forced her to perform any other sexual acts she did not want to Forced her with threats or in any other way to perform sexual acts she did not want to Tried to choke her or burn her on purpose Threatened her or attacked her with a knife, gun, or other weapon Percentage of ever-married women age 15-49 who have ever experienced specfic acts of violence by their husband/partner Ever Last 12 months Violence Against Women • 295 Women reporting emotional violence were most likely to report that their husband/partner insulted them and made them feel bad about themselves (19%), followed by their husband/partner saying or doing something to humiliate them in front of others (14%), and threatening to hurt or harm them or someone close to them (8%). Women who were married more than once were also asked about spousal violence committed by any other husband/partner. Twenty-eight percent of women have ever experienced physical or sexual violence committed by any husband/partner: 25% have experienced physical violence, and 11% have experienced sexual violence. During the 12 months preceding the survey, 20% of ever-married women experienced physical or sexual violence bya husband/partner, either current or previous (Table 15.9). Patterns by background characteristics  By region, spousal violence (physical, sexual or emotional) is most prevalent in Oromiya (38%) and Harari (37%), and least prevalent in Somali (9%) (Table 15.10 and Figure 15.4).  All forms of spousal violence are higher among divorced/separated/widowed women than among currently married women.  Women’s education is inversely correlated with spousal violence. Women with no education are more likely to have experienced physical, sexual, or emotional violence (36%) than women with more than secondary education (17%).  Spousal violence does not vary consistently with wealth status; however, women in the highest wealth quintile are much less likely than women in the other wealth quintiles to experience spousal violence. Patterns by husband’s characteristics and empowerment indicators  Husbands/partners who have more than a secondary education are less likely (18%) to commit emotional, physical, or sexual spousal violence than husbands/partners with no education (36%) or with primary (34%) education (Table 15.11).  Experience of spousal violence varies greatly with the level of husbands’/partners’ alcohol consumption. Eighty-one percent of women whose husbands/partners are often drunk have experienced spousal violence, compared with 28% of women whose husbands/partners do not drink alcohol (Figure 15.5).  Women in couples where the wife is better educated than the husband/partner (38%), and in which both husband/partner and wife have no education (34%) are more than twice as likely to have experienced spousal violence as women in couples where both have equal education (15%). Figure 15.4 Spousal violence by region Figure 15.5 Spousal violence by husband’s alcohol consumption 9 20 26 29 29 32 33 34 35 37 38 Somali Affar Addis Ababa Dire Dawa SNNPR Benishangul-Gumuz Tigray Gambela Amhara Harari Oromiya Percentage of ever-married women age 15-49 who have ever experienced physical, sexual, or emotional violence committed by their husband/partner 28 32 45 81 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 296 • Violence Against Women  The likelihood of experiencing spousal violence increases sharply with the number of marital control behaviours displayed by husbands/partners; 88% of women whose husbands/partners display all five marital control behaviours have ever experienced spousal violence, compared with 17% of women whose husbands/partners do not display any marital control behaviours.  Women who participate in three or more household decisions and who do not agree with any reason for wife beating have a lower prevalence of spousal violence than women who participate in no household decisions and women who agree with most reasons for wife beating (a difference of about 6 percentage points for each).  Women who reported that their fathers beat their mothers are more likely (49%) to have themselves experienced spousal violence than women who reported that their fathers did not beat their mothers (28%).  Women’s fear of their husbands/partners and spousal violence are correlated. Women who say that they are afraid of their husbands/partners most of the time are most likely to have ever experienced any form of spousal violence (57%), followed by women who are only sometimes afraid of their husbands/partners (35%). Nonetheless, it is notable that 19% of even the women who say that they are never afraid of their husband/partner have experienced spousal violence. 15.6.2 Onset of Spousal Violence Table 15.13 shows when spousal violence first occurred in relation to the start of their marriage among women who were married only once. Among currently married women age 15-49 who have been married only once, 9% first experienced spousal violence within the first 2 years of marriage, and 18% had experienced it by 5 years of marriage. 15.7 INJURIES TO WOMEN 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; 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) Among ever-married women who have experienced any spousal physical or sexual violence, 22% have sustained some kind of physical injury (Table 15.14). Cuts, bruises, or aches are the most common types of injuries (19%) reported by women who have experienced spousal physical or sexual violence. However, a significant proportion of women who have experienced spousal violence also reported having serious injuries such as deep wounds, broken bones, and broken teeth (10%), as well as eye injuries, sprains, dislocations, or burns (7%). 15.8 VIOLENCE INITIATED BY WOMEN AGAINST HUSBANDS Initiation of physical violence by wives Percentage of women who have ever hit, slapped, kicked, or done anything else to physically hurt their current (if currently married) or most recent (if formerly married) husband/partner at times when he was not already beating or physically hurting her. Sample: Ever-married women age 15-49 Violence Against Women • 297 Four percent of ever-married women reported initiating physical violence against their husbands/partners when he was not already beating or physically hurting them. Three percent reported that they initiated violence within the past 12 months. Women who have experienced spousal violence are much more likely than women who have not experienced spousal violence to have ever initiated violence against their husbands/partners. Thirteen percent of women who have ever experienced spousal violence also perpetrated such violence compared with less than 1% for women who have never experienced spousal violence (Table 15.15). Patterns by background characteristics  Women whose husbands/partners get drunk often are more likely to initiate physical violence (12%) than women whose husbands/partners do not drink (3%) (Table 15.16).  The percentage of women who have initiated violence against their husband/partner increases sharply with the number of controlling behaviours that their husbands/partners display, from 2% among women whose husbands/partners do not display any of the specified controlling behaviours to 7% among women whose husbands/partners display all five specified behaviours. 15.9 RESPONSE TO VIOLENCE 15.9.1 Help-Seeking among Women Who Have Experienced Violence Overall, only 23% of women age 15-49 who have ever experienced any type of physical or sexual violence by anyone have sought help. Notably, 66% have never sought help nor told anyone about the violence. Women who have experienced both physical and sexual violence are more likely to have sought help (27%) than women who have experienced only sexual violence (7%) or only physical violence (23%) (Table 15.17). Patterns by background characteristics  Help seeking by women who have ever experienced physical or sexual violence is less common among rural women (19%) than urban women (36%).  Women in Addis Ababa (41%), followed by women in SNNPR and Tigray (24% each) are more likely to seek help than other women, and women in Benishangul-Gumuz are least likely to do so (9%).  Women employed for cash are more likely to seek help (29%) than women who are not employed (19%).  Help seeking is higher among never married women (34%), those belonging to the highest wealth quintile (33%), and those who have secondary or more than secondary education (30%-34%). 15.9.2 Sources for Help Among women who have experienced physical or sexual violence and sought help, the most common source for help was neighbours (34%). Other common sources were the woman’s own family (31%), and her husband’s/partner’s family (14%). Only 8% of women seek help from the police. It is not common for women who have experienced physical and sexual violence to seek help from service providers such as lawyers, doctors/medical personnel, and social work organizations: only 2%-3% have ever sought help from each of these sources (Table 15.18). 298 • Violence Against Women LIST OF TABLES For more information on violence against women, see the following tables:  Table 15.1 Experience of physical violence  Table 15.2 Experience of violence during pregnancy  Table 15.3 Persons committing physical violence  Table 15.4 Experience of sexual violence  Table 15.5 Age at first experience of sexual violence  Table 15.6 Persons committing sexual violence  Table 15.7 Experience of different forms of violence  Table 15.8 Marital control exercised by husbands  Table 15.9 Forms of spousal violence  Table 15.10 Spousal violence by background characteristics  Table 15.11 Spousal violence by husband’s characteristics and empowerment indicators  Table 15.12 Physical or sexual violence in the past 12 months by any husband/partner  Table 15.13 Experience of spousal violence by duration of marriage  Table 15.14 Injuries to women due to spousal violence  Table 15.15 Violence by women against their husband by women’s background characteristics  Table 15.16 Violence by women against their husband by husband’s characteristics and empowerment indicators  Table 15.17 Help seeking to stop violence  Table 15.18 Sources for help to stop the violence Violence Against Women • 299 Table 15.1 Experience of physical violence Percentage of women age 15-49 who have experienced physical violence since age 15 and percentage who have experienced physical violence during the 12 months preceding the survey, according to background characteristics, Ethiopia DHS 2016 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 12.6 0.6 8.4 9.0 1,200 20-24 21.6 1.9 13.7 15.7 969 25-29 24.8 3.7 13.5 17.2 1,088 30-39 28.5 4.9 11.4 16.3 1,702 40-49 27.7 4.8 11.0 15.9 900 Religion Orthodox 24.9 2.7 11.1 13.9 2,588 Catholic (15.2) (0.1) (11.4) (11.4) 41 Protestant 20.9 3.3 9.7 13.0 1,401 Muslim 22.4 3.8 13.3 17.1 1,742 Traditional (30.7) (3.5) (11.4) (15.0) 48 Other (41.3) (20.0) (17.5) (37.5) 39 Ethnic group Affar 12.5 1.0 3.5 4.5 40 Amhara 24.5 2.6 10.8 13.4 1,792 Guragie 21.4 0.1 10.1 10.2 151 Hadiya 21.7 1.0 14.6 15.6 135 Oromo 26.7 5.4 14.1 19.4 1,967 Sidama 28.0 4.9 12.8 17.8 244 Somali 5.6 0.5 3.8 4.2 161 Tigray 23.8 1.6 8.0 9.7 422 Welaita 14.5 3.0 8.4 12.2 175 Others 16.9 1.8 10.5 12.3 773 Residence Urban 20.9 2.5 8.1 10.6 1,266 Rural 23.9 3.5 12.4 16.0 4,594 Region Tigray 25.0 2.4 8.3 10.8 405 Affar 15.5 1.0 5.0 6.0 50 Amhara 24.2 2.8 10.6 13.4 1,393 Oromiya 27.7 5.3 14.9 20.2 2,152 Somali 5.9 0.7 3.9 4.6 170 Benishangul-Gumuz 17.7 1.3 11.0 12.5 55 SNNPR 17.0 1.8 9.5 11.4 1,243 Gambela 25.3 4.6 14.3 18.9 15 Harari 24.5 5.0 15.0 19.9 13 Addis Ababa 23.4 0.7 9.4 10.2 330 Dire Dawa 20.3 1.8 9.3 11.0 35 Marital status Never married 7.2 0.3 3.2 3.4 1,391 Married or living together 26.7 4.1 14.0 18.1 3,897 Divorced/separated/widowed 39.0 5.3 14.8 20.1 573 Number of living children 0 11.8 0.5 6.8 7.3 1,814 1-2 31.2 3.1 16.1 19.3 1,401 3-4 26.7 5.2 11.5 16.7 1,235 5+ 27.2 5.4 12.9 18.3 1,410 Employment Employed for cash 24.7 3.7 10.1 13.7 1,448 Employed not for cash 24.7 2.7 12.0 14.8 1,572 Not employed 21.8 3.4 11.9 15.4 2,840 Education No education 28.1 4.8 12.9 17.7 2,864 Primary 20.6 2.3 12.0 14.4 1,972 Secondary 16.2 1.5 7.5 8.9 660 More than secondary 13.0 0.2 4.8 4.9 363 Wealth quintile Lowest 24.5 3.8 13.4 17.3 987 Second 23.4 3.8 13.0 16.8 1,051 Middle 26.4 4.1 13.1 17.3 1,146 Fourth 23.1 3.2 10.9 14.1 1,146 Highest 20.3 2.0 8.4 10.5 1,530 Total 15-49 23.3 3.3 11.5 14.8 5,860 Note: Figures in parentheses are based on 25-49 unweighted cases. 1 Includes violence in the past 12 months. For women who were married before age 15 and reported physical violence only by their husband/partner, the violence could have occurred before age 15. 2 Includes women who report physical violence in the past 12 months but for whom frequency is not known. 300 • Violence Against Women Table 15.2 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, Ethiopia DHS 2016 Background characteristic Percentage who experienced violence during pregnancy Number of women who have ever been pregnant Age 15-19 1.1 165 20-24 2.0 580 25-29 2.6 942 30-39 4.1 1,636 40-49 5.8 884 Religion Orthodox 4.9 1,726 Catholic * 31 Protestant 3.0 996 Muslim 2.8 1,380 Traditional (0.0) 38 Other (9.8) 37 Ethnic group Affar 1.1 33 Amhara 3.7 1,213 Guragie 3.5 89 Hadiya 0.0 88 Oromo 5.1 1,507 Sidama 3.7 193 Somali 0.2 116 Tigray 5.4 299 Welaita 2.9 102 Others 1.2 567 Residence Urban 3.7 738 Rural 3.7 3,470 Region Tigray 5.5 294 Affar 1.8 38 Amhara 3.5 974 Oromiya 5.0 1,669 Somali 0.5 123 Benishangul-Gumuz 1.5 42 SNNPR 1.7 887 Gambela 3.1 12 Harari 2.9 9 Addis Ababa 4.6 140 Dire Dawa 0.7 20 Marital status Never married 2.8 40 Married or living together 3.1 3,684 Divorced/separated/widowed 8.7 484 Number of living children 0 0.8 161 1-2 3.4 1,401 3-4 3.4 1,235 5+ 4.8 1,410 Education No education 4.2 2,660 Primary 3.2 1,099 Secondary 3.3 281 More than secondary 0.8 167 Wealth quintile Lowest 3.0 813 Second 3.7 805 Middle 3.9 888 Fourth 3.5 793 Highest 4.5 909 Total 15-49 3.7 4,207 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. Violence Against Women • 301 Table 15.3 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, Ethiopia DHS 2016 Marital status Total Person Ever- married Never married Current husband/partner 68.2 na 63.1 Former husband/partner 25.2 na 23.3 Current boyfriend 2.5 0.0 2.3 Former boyfriend 4.1 8.1 4.4 Father/step-father 1.8 13.0 2.6 Mother/step-mother 2.5 3.9 2.6 Sister/brother 4.0 26.5 5.7 Daughter/son 0.6 1.3 0.6 Other relative 3.7 14.1 4.4 Mother-in-law 0.0 na 0.0 Father-in-law 0.2 na 0.1 Other in-law 0.4 na 0.4 Teacher 0.6 10.9 1.3 Employer/someone at work 1.0 5.0 1.3 Other 4.3 25.7 5.9 Number women who have experienced physical violence since age 15 1,264 101 1,364 Note: Women can report more than one person who committed the violence. na = Not applicable 302 • Violence Against Women Table 15.4 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, Ethiopia DHS 2016 Background characteristic Percentage who have experienced sexual violence: Number of women Ever1 Past 12 months Age 15-19 3.5 2.4 1,200 20-24 7.9 5.3 969 25-29 12.4 8.4 1,088 30-39 12.5 7.8 1,702 40-49 13.6 8.4 900 Religion Orthodox 10.7 6.3 2,588 Catholic (5.3) (3.9) 41 Protestant 9.0 5.2 1,401 Muslim 10.1 7.9 1,742 Traditional (10.9) (10.9) 48 Other (7.0) (0.0) 39 Ethnic group Affar 3.3 1.0 40 Amhara 10.3 5.9 1,792 Guragie 5.2 0.9 151 Hadiya 9.2 5.9 135 Oromo 12.9 9.3 1,967 Sidama 4.5 3.3 244 Somali 0.2 0.2 161 Tigray 11.0 5.6 422 Welaita 6.1 2.4 175 Others 7.8 5.9 773 Residence Urban 7.3 2.0 1,266 Rural 10.8 7.7 4,594 Region Tigray 12.0 6.2 405 Affar 4.5 1.4 50 Amhara 10.5 6.9 1,393 Oromiya 13.2 9.4 2,152 Somali 0.3 0.3 170 Benishangul-Gumuz 6.8 4.6 55 SNNPR 6.1 3.7 1,243 Gambela 10.4 7.3 15 Harari 4.2 2.6 13 Addis Ababa 7.7 1.4 330 Dire Dawa 7.0 3.5 35 Marital status Never married 2.0 0.4 1,391 Married or living together 11.8 8.7 3,897 Divorced/separated/widowed 17.8 6.4 573 Employment Employed for cash 12.2 5.3 1,448 Employed not for cash 10.2 6.5 1,572 Not employed 8.9 7.1 2,840 Number of living children 0 3.9 2.1 1,814 1-2 14.0 7.2 1,401 3-4 11.1 7.6 1,235 5+ 13.2 10.5 1,410 Education No education 13.2 9.4 2,864 Primary 8.3 4.8 1,972 Secondary 4.8 1.8 660 More than secondary 4.7 1.2 363 Wealth quintile Lowest 12.1 9.5 987 Second 12.3 9.4 1,051 Middle 12.6 8.3 1,146 Fourth 8.6 5.7 1,146 Highest 6.4 1.8 1,530 Total 15-49 10.1 6.5 5,860 Note: Figures in parentheses are based on 25-49 unweighted cases. 1 Includes violence in the past 12 months Violence Against Women • 303 Table 15.5 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, Ethiopia DHS 2016 Background characteristic Percentage who first experienced sexual violence by exact age Percentage who have not experienced sexual violence Number of women 10 12 15 18 22 Current age 15-19 0.7 0.9 1.3 na na 96.5 1,200 20-24 0.2 0.2 1.1 4.6 na 92.1 969 25-29 1.0 1.1 2.2 5.3 8.3 87.6 1,088 30-39 0.4 0.7 1.7 4.9 7.1 87.5 1,702 40-49 0.2 0.2 1.3 4.8 8.3 86.4 900 Marital status Never married 0.5 0.5 0.5 1.1 1.5 98.0 1,391 Ever married 0.5 0.7 1.9 5.7 8.4 87.4 4,469 Total 0.5 0.6 1.6 4.6 6.8 89.9 5,860 na = Not applicable Table 15.6 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, Ethiopia DHS 2016 Marital status Total Person Ever- married1 Never married Current husband/partner 69.3 na 66.0 Former husband/partner 29.8 na 28.4 Current/former boyfriend 2.2 (7.5) 2.5 Father/step father 0.7 (0.2) 0.7 Brother/step brother 0.0 (0.0) 0.0 Other relative 1.3 (22.0) 2.3 Own friend/acquaintance 0.0 (9.3) 0.5 Family friend 0.7 (3.0) 0.8 Teacher 0.0 (0.0) 0.0 Employer/someone at work 0.6 (14.5) 1.3 Police/soldier 1.1 (0.0) 1.0 Priest/religious leader 0.0 (0.0) 0.0 Stranger 1.2 (17.6) 1.9 Other 2.4 (25.9) 3.5 Missing 0.0 (0.0) 0.0 Number women who have experienced sexual violence 562 28 589 1 Women can report more than one person who committed the violence. Figures in parentheses are based on 25-49 unweighted cases. na = Not applicable Table 15.7 Experience of different forms of violence Percentage of women age 15-49 who have ever experienced different forms of violence by current age, country, Ethiopia DHS 2016 Age Physical violence only Sexual violence only Physical and sexual violence Physical or sexual violence Number of women 15-19 10.5 1.4 2.2 14.0 1,200 15-17 10.2 0.2 2.0 12.3 743 18-19 10.9 3.3 2.5 16.7 457 20-24 16.6 2.8 5.0 24.5 969 25-29 16.3 3.9 8.5 28.7 1,088 30-39 18.9 3.0 9.6 31.4 1,702 40-49 18.4 4.3 9.3 31.9 900 Total 16.2 3.0 7.1 26.3 5,860 304 • Violence Against Women Table 15.8 Marital control exercised by husbands Percentage of ever-married women age 15-49 whose husbands/partners have ever demonstrated specific types of controlling behaviours, according to background characteristics, Ethiopia DHS 2016 Percentage of women whose husband/partner: Background characteristic 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 Insists on knowing where she is at all times Displays 3 or more of the specific behaviours Displays none of the specific behaviours Number of ever-married women Age 15-19 48.1 12.8 16.8 14.0 39.1 19.0 37.3 289 20-24 39.8 8.8 16.3 15.3 35.5 15.1 42.3 669 25-29 38.2 10.8 12.3 14.2 35.2 13.6 42.0 982 30-39 37.5 12.9 15.1 17.6 30.8 15.7 44.2 1,642 40-49 36.5 16.8 16.1 16.4 32.9 20.7 45.8 887 Religion Orthodox 41.8 10.8 16.3 17.8 31.5 17.1 41.2 1,900 Catholic * * * * * * * 33 Protestant 35.6 15.0 14.6 15.3 32.0 14.9 43.3 1,014 Muslim 35.5 12.8 13.2 13.7 36.3 15.6 45.7 1,448 Traditional (37.9) (1.0) (1.7) (11.9) (33.0) (11.7) (50.9) 38 Other (75.1) (41.2) (42.5) (41.8) (70.0) (53.0) (21.3) 37 Ethnic group Affar 40.0 5.5 11.2 11.6 18.8 8.6 50.7 37 Amhara 44.0 7.2 12.1 16.8 27.7 13.6 41.0 1,344 Guragie 44.7 12.1 20.8 24.2 38.7 20.2 29.9 90 Hadiya 41.2 10.1 15.1 24.3 45.2 16.6 24.7 90 Oromo 37.6 19.5 17.2 15.3 44.1 21.3 41.7 1,582 Sidama 41.5 18.4 15.1 18.2 25.9 18.0 48.6 196 Somali 19.2 2.0 7.6 6.0 10.6 5.5 73.1 124 Tigray 29.6 8.9 15.6 15.1 36.4 14.2 46.9 319 Welaita 35.6 14.6 21.0 19.9 28.7 14.8 34.7 101 Others 35.0 9.2 14.8 15.3 22.4 12.4 48.8 587 Residence Urban 37.4 11.7 15.9 18.3 27.7 16.5 45.2 809 Rural 38.7 12.8 14.7 15.5 34.7 16.3 42.9 3,660 Region Tigray 29.3 9.1 17.1 15.5 37.7 15.8 46.6 316 Affar 38.0 6.4 12.6 13.4 19.1 9.4 49.9 43 Amhara 45.7 6.7 10.5 16.0 25.0 12.7 42.8 1,085 Oromiya 37.3 19.6 17.3 15.8 46.8 21.5 39.4 1,746 Somali 20.3 2.3 7.6 6.4 11.0 5.6 71.4 132 Benishangul-Gumuz 16.2 5.6 17.4 12.8 14.1 5.5 59.4 44 SNNPR 40.4 10.1 15.4 17.9 23.0 13.8 43.8 913 Gambela 39.9 14.7 20.3 27.3 31.9 18.0 36.3 13 Harari 44.7 18.1 21.9 23.4 29.9 18.8 35.8 10 Addis Ababa 31.9 9.0 18.7 19.2 22.7 15.2 50.2 146 Dire Dawa 22.7 12.0 12.7 9.2 23.2 11.5 59.6 23 Marital status Married or living together 37.9 11.5 14.2 15.1 33.3 15.1 43.5 3,897 Divorced/separated/widowed 42.6 19.9 20.1 22.4 34.3 24.8 42.0 573 Number of living children 0 41.9 11.0 16.8 15.6 34.4 17.8 41.8 454 1-2 40.2 11.1 16.5 16.6 34.2 15.9 39.6 1,376 3-4 37.6 10.9 12.9 16.8 30.7 14.6 45.3 1,232 5+ 36.4 16.1 14.7 15.0 34.7 17.9 45.6 1,408 Employment Employed for cash 41.4 15.0 16.8 17.4 33.2 16.5 39.1 1,076 Employed not for cash 34.1 9.5 13.7 16.3 30.9 15.1 48.2 1,262 Not employed 39.6 13.2 14.7 15.2 35.0 17.0 42.6 2,131 Education No education 36.7 13.8 15.4 17.1 33.7 17.3 44.5 2,725 Primary 42.5 11.7 15.1 14.5 35.7 16.5 40.6 1,236 Secondary 36.2 7.8 12.9 16.9 27.9 12.3 47.1 312 More than secondary 41.1 9.1 11.7 9.7 23.4 8.2 37.4 196 Wealth quintile Lowest 36.2 12.5 11.9 14.5 31.8 14.2 47.1 842 Second 37.1 12.6 13.9 15.3 31.4 16.6 47.2 857 Middle 37.8 12.9 14.7 17.3 35.1 17.3 42.1 933 Fourth 42.1 11.3 16.7 16.7 39.0 16.3 35.9 848 Highest 39.1 13.5 17.2 16.3 30.1 17.1 44.2 990 Woman afraid of husband/ partner Most of the time afraid 44.9 21.4 22.9 27.0 47.5 26.5 33.0 950 Sometimes afraid 36.2 14.6 15.0 14.5 36.6 18.4 44.3 1,825 Never afraid 37.3 5.5 10.4 11.6 22.1 8.5 48.0 1,694 Total 38.5 12.6 15.0 16.0 33.4 16.4 43.3 4,469 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. 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. Violence Against Women • 305 Table 15.9 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 current or most recent husbands/partners, Ethiopia DHS 2016 Ever experienced Experienced in the past 12 months In the past 12 months Type of violence experienced Often Sometimes SPOUSAL VIOLENCE COMMITTED BY CURRENT OR MOST RECENT HUSBAND/PARTNER1 Physical violence Any physical violence 23.5 16.9 3.7 13.2 Pushed her, shook her, or threw something at her 12.4 8.7 1.6 7.1 Slapped her 18.8 12.7 2.3 10.5 Twisted her arm or pulled her hair 5.6 4.0 1.0 3.1 Punched her with his fist or with something that could hurt her 8.1 4.7 1.1 3.6 Kicked her, dragged her, or beat her up 9.7 6.4 1.3 5.1 Tried to choke her or burn her on purpose 2.1 1.4 0.5 0.9 Threatened her or attacked her with a knife, gun, or other weapon 2.2 1.5 0.6 0.9 Sexual violence Any sexual violence 10.1 8.3 1.7 6.6 Physically forced her to have sexual intercourse with him when she did not want to 8.4 6.4 1.3 5.0 Physically forced her to perform any other sexual acts she did not want to 4.4 3.7 0.6 3.1 Forced her with threats or in any other way to perform sexual acts she did not want to 3.0 2.3 0.3 1.9 Emotional violence Any emotional violence 24.0 20.2 4.7 15.5 Said or did something to humiliate her in front of others 13.7 11.2 3.1 8.0 Threatened to hurt or harm her or someone she cared about 7.9 6.4 1.6 4.8 Insulted her or made her feel bad about herself 19.4 16.5 3.1 13.4 Any form of physical and/or sexual violence 26.3 19.7 4.5 15.3 Any form of emotional and/or physical and/or sexual violence 33.8 27.0 7.4 19.6 SPOUSAL VIOLENCE COMMITTED BY ANY HUSBAND/PARTNER Physical violence 24.9 16.9 na na Sexual violence 11.1 8.3 na na Physical and/or sexual violence 28.0 19.8 na na Number of ever-married women 4,469 4,469 4,469 4,469 na = Not available 1 Includes current husband/partner for currently married women and most recent husband/partner for divorced, separated, or widowed women 306 • Violence Against Women Table 15.10 Spousal violence by background characteristics Percentage of ever-married women age 15-49 who have ever experienced emotional, physical, or sexual violence committed by their current or most recent husband/partner, according to background characteristics, Ethiopia DHS 2016 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 21.6 27.1 10.0 7.5 7.2 29.6 33.4 289 20-24 22.6 23.1 8.3 5.1 3.9 26.3 32.3 669 25-29 19.6 23.1 10.9 7.8 5.5 26.2 31.5 982 30-39 24.7 23.5 9.7 7.5 6.0 25.7 34.2 1,642 40-49 29.3 23.1 11.4 8.1 7.7 26.3 36.8 887 Religion Orthodox 25.6 23.8 10.5 7.0 5.6 27.2 35.3 1,900 Catholic * * * * * * * 33 Protestant 24.7 22.3 8.9 6.3 5.9 24.8 33.1 1,014 Muslim 20.7 23.3 10.7 8.8 6.8 25.2 31.3 1,448 Traditional (25.1) (38.2) (13.6) (2.8) (2.8) (49.0) (59.5) 38 Other (54.9) (40.4) (0.0) (0.0) (0.0) (40.4) (54.9) 37 Ethnic group Affar 12.6 9.7 3.4 3.1 2.2 10.1 18.1 37 Amhara 24.6 23.2 9.5 6.7 5.2 26.0 34.8 1,344 Guragie 29.5 20.8 3.6 1.9 0.5 22.5 32.9 90 Hadiya 31.0 23.4 12.2 12.2 11.9 23.4 36.1 90 Oromo 24.0 28.8 13.3 10.6 8.6 31.5 36.6 1,582 Sidama 32.0 28.9 5.6 5.1 5.1 29.3 39.5 196 Somali 6.7 6.2 0.2 0.2 0.2 6.2 8.9 124 Tigray 25.7 17.3 10.8 5.0 4.8 23.2 31.9 319 Welaita 22.8 16.9 8.6 6.0 3.1 19.5 32.6 101 Others 21.5 17.7 7.5 4.2 3.7 21.0 29.2 587 Residence Urban 21.3 18.2 6.0 4.6 3.8 19.6 27.6 809 Rural 24.6 24.7 11.0 7.9 6.5 27.8 35.2 3,660 Region Tigray 26.7 18.7 11.7 5.7 5.1 24.7 33.4 316 Affar 13.4 11.7 3.0 2.4 1.9 12.3 19.8 43 Amhara 25.8 22.0 10.3 6.8 5.0 25.6 35.1 1,085 Oromiya 25.4 30.1 13.3 10.8 8.9 32.6 38.4 1,746 Somali 7.1 6.8 0.4 0.4 0.2 6.8 9.4 132 Benishangul-Gumuz 25.6 20.2 6.9 4.0 3.1 23.0 31.8 44 SNNPR 21.8 18.1 6.2 4.0 3.5 20.2 29.3 913 Gambela 23.6 24.9 8.2 5.5 4.1 27.6 34.4 13 Harari 31.2 28.4 4.5 4.5 4.2 28.4 37.3 10 Addis Ababa 18.9 20.2 4.2 4.0 4.0 20.4 25.8 146 Dire Dawa 19.2 19.9 6.7 2.3 2.0 24.2 28.9 23 Marital status Married or living together 22.7 21.9 9.5 6.6 5.2 24.8 32.3 3,897 Divorced/separated/ widowed 32.5 34.5 13.9 12.3 11.2 36.1 43.9 573 Number of living children 0 22.4 23.3 9.0 6.4 5.9 25.9 31.4 454 1-2 22.0 25.0 9.9 7.2 5.2 27.8 33.7 1,376 3-4 21.4 22.5 9.5 7.4 5.4 24.6 31.4 1,232 5+ 28.7 23.0 11.1 7.8 7.3 26.4 36.8 1,408 Employment Employed for cash 24.1 23.3 10.3 8.0 6.9 25.6 33.2 1,076 Employed not for cash 25.7 23.9 9.8 6.4 5.1 27.3 36.2 1,262 Not employed 22.9 23.4 10.2 7.5 6.0 26.1 32.6 2,131 Education No education 25.9 24.6 11.6 8.3 7.1 27.9 35.5 2,725 Primary 24.2 24.6 9.0 7.1 5.4 26.5 34.4 1,236 Secondary 16.7 18.2 5.5 4.3 2.1 19.4 27.0 312 More than secondary 7.8 10.0 3.9 0.1 0.0 13.9 17.2 196 Wealth quintile Lowest 24.0 24.2 12.3 8.7 6.2 27.7 35.8 842 Second 25.9 23.9 13.1 8.9 7.5 28.0 35.2 857 Middle 26.5 26.1 12.0 8.8 7.0 29.3 37.6 933 Fourth 25.3 26.4 9.4 7.3 6.9 28.5 35.5 848 Highest 18.8 17.7 4.5 3.4 2.6 18.8 25.7 990 Total 15-49 24.0 23.5 10.1 7.3 6.0 26.3 33.8 4,469 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. 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. Violence Against Women • 307 Table 15.11 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 current or most recent husband/partner, according to the husband’s characteristics and women’s empowerment indicators, Ethiopia DHS 2016 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 25.2 24.4 10.8 8.0 6.2 27.1 35.9 1,807 Primary 23.5 23.1 10.0 6.7 5.4 26.4 33.5 1,397 Secondary 16.7 15.3 6.1 3.6 2.8 17.9 21.6 361 More than secondary 11.1 9.2 3.8 1.2 1.2 11.8 17.9 299 Husband’s/partner’s alcohol consumption Does not drink alcohol 19.5 19.1 7.8 5.5 4.4 21.4 28.2 3,058 Drinks alcohol but is never drunk 19.5 21.4 11.6 6.8 4.3 26.2 32.1 446 Is sometimes drunk 32.9 30.2 13.8 10.3 8.9 33.7 44.7 769 Is often drunk 67.9 71.1 27.7 25.6 23.2 73.2 81.4 197 Spousal education difference1 Husband has more education 21.5 20.9 9.4 5.9 4.7 24.3 30.5 1,506 Wife has more education 24.6 26.6 10.4 8.5 4.7 28.5 37.7 600 Both have equal education 10.1 9.6 2.5 2.3 2.1 9.9 15.0 216 Neither has any education 24.8 22.8 10.3 7.1 6.3 25.9 34.3 1,541 DK/missing 32.2 33.9 13.8 12.0 10.9 35.7 43.3 607 Spousal age difference1 Wife older 19.3 21.9 2.6 2.6 2.6 21.9 29.9 121 Wife is same age 35.0 32.5 9.2 5.2 5.2 36.4 42.6 83 Wife’s 1-4 years younger 20.2 21.6 8.3 5.7 3.6 24.2 30.9 1,108 Wife’s 5-9 years younger 20.9 22.6 8.6 6.1 4.2 25.1 32.1 1,515 Wife’s 10+ years younger 27.3 20.4 12.9 8.7 8.5 24.6 33.5 1,070 Number of marital control behaviours displayed by husband/partner2 0 9.6 10.3 4.2 2.2 1.7 12.2 16.7 1,935 1-2 24.9 25.8 11.2 8.0 5.9 29.1 37.2 1,803 3-4 52.0 46.7 21.3 16.2 14.1 51.8 65.6 566 5 85.8 73.3 29.4 29.4 29.3 73.4 87.6 165 Number of decisions in which women participate3 0 31.2 26.9 11.0 8.4 8.0 29.6 36.4 378 1-2 26.8 24.1 11.1 7.0 5.3 28.2 37.6 825 3 20.3 20.5 8.8 6.2 4.8 23.1 30.1 2,694 Number of reasons for which wife-beating is justified4 0 23.7 22.1 6.3 5.0 4.5 23.4 30.2 1,489 1-2 23.1 21.8 9.3 6.1 4.8 25.0 33.2 903 3-4 24.6 24.8 14.5 9.8 7.8 29.5 38.0 1,001 5 24.5 25.8 11.9 9.3 7.4 28.4 35.2 1,076 Woman’s father beat her mother Yes 34.9 36.2 13.4 10.2 8.3 39.3 48.5 1,226 No 19.4 18.3 8.3 5.9 4.8 20.7 27.6 2,982 DK/Missing 25.3 23.7 14.8 9.9 8.9 28.7 35.3 261 Woman afraid of husband/partner Most of the time afraid 42.4 45.5 21.5 16.9 14.3 50.0 57.3 950 Sometimes afraid 25.1 23.4 9.3 6.9 5.3 25.8 35.3 1,825 Never afraid 12.4 11.3 4.5 2.4 2.0 13.5 18.9 1,694 Total 15-49 24.0 23.5 10.1 7.3 6.0 26.3 33.8 4,469 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. Total includes 32 ever-married women with missing information on husband’s/partner’s education. 1 Includes only currently married women. 2 According to the wife’s report. See 15.8 for list of behaviours. 3 According to the wife’s report. Includes only currently married women. See Table 14.12.1 for list of decisions. 4 According to the wife’s report. See Table 14.13.1 for list of reasons. 308 • Violence Against Women Table 15.12 Physical or sexual violence in the past 12 months by any husband/partner 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, Ethiopia DHS 2016 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 24.3 289 20-24 23.1 669 25-29 20.3 982 30-39 18.2 1,642 40-49 18.2 887 Religion Orthodox 19.2 1,900 Catholic * 33 Protestant 18.0 1,014 Muslim 21.2 1,448 Traditional (29.4) 38 Other (40.3) 37 Ethnic group Affar 4.5 37 Amhara 18.4 1,344 Guragie 14.5 90 Hadiya 15.4 90 Oromo 24.6 1,582 Sidama 21.8 196 Somali 5.2 124 Tigray 12.8 319 Welaita 19.6 101 Others 18.8 587 Residence Urban 11.9 809 Rural 21.5 3,660 Region Tigray 14.4 316 Affar 6.6 43 Amhara 18.9 1,085 Oromiya 25.3 1,746 Somali 5.8 132 Benishangul-Gumuz 18.3 44 SNNPR 16.0 913 Gambela 22.9 13 Harari 24.3 10 Addis Ababa 12.7 146 Dire Dawa 14.5 23 Marital status Married or living together 20.0 3,897 Divorced/separated/widowed 18.4 573 Number of living children 0 19.5 454 1-2 20.1 1,376 3-4 18.7 1,232 5+ 20.5 1,408 Employment Employed for cash 17.0 1,076 Employed not for cash 20.6 1,262 Not employed 20.7 2,131 Education No education 21.0 2,725 Primary 20.7 1,236 Secondary 12.3 312 More than secondary 9.8 196 Wealth quintile Lowest 23.0 842 Second 22.6 857 Middle 23.3 933 Fourth 19.9 848 Highest 11.3 990 Woman afraid of husband/partner Most of the time afraid 37.7 950 Sometimes afraid 19.6 1,825 Never afraid 10.0 1,694 Total 15-49 19.8 4,469 Note: 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. Violence Against Women • 309 Table 15.13 Experience of spousal violence by duration of marriage Among currently married women age 15-49 who have been married only once, percentage who first experienced physical or sexual violence committed by their current husband/partner by specific exact years since marriage according to marital duration, Ethiopia DHS 2016 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 Duration of marriage Before marriage 2 years 5 years 10 years Years since marriage <2 0.0 na na na 80.1 217 2-4 2.7 16.9 na na 76.8 451 5-9 0.2 9.8 20.3 na 75.5 597 10+ 0.5 7.5 15.6 19.4 75.3 1,976 Total 0.7 9.4 17.5 20.8 75.9 3,241 na = Not applicable Table 15.14 Injuries to women due to spousal violence Among ever-married women age 15-49 who have experienced violence committed by their current or most recent husband/partner, the percentage who have been injured as a result of the violence, by types of injuries, according to the type of violence, Ethiopia DHS 2016 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 ever-married women who have ever experienced physical or sexual violence Physical violence1 Ever2 20.4 7.8 10.7 23.9 1,051 In the past 12 months 20.7 7.7 10.7 24.1 755 Sexual violence Ever2 22.4 9.5 13.0 27.9 451 In the past 12 months 20.2 6.8 10.8 24.6 370 Physical or sexual violence1 Ever2 18.7 7.1 9.6 21.8 1,175 In the past 12 months 18.7 6.8 9.2 21.6 883 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 310 • Violence Against Women Table 15.15 Violence by women against their husband by women’s background characteristics Percentage of ever-married women 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, Ethiopia DHS 2016 Percentage who 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 13.4 11.7 1,051 In the past 12 months 15.9 14.9 755 Never 0.7 0.5 3,418 Age 15-19 5.1 5.1 289 20-24 3.9 3.5 669 25-29 2.7 2.7 982 30-39 3.9 3.2 1,642 40-49 3.6 2.6 887 Religion Orthodox 2.8 2.2 1,900 Catholic * * 33 Protestant 2.3 1.6 1,014 Muslim 6.0 5.6 1,448 Traditional (0.3) (0.3) 38 Other (0.0) (0.0) 37 Ethnic group Affar 1.0 0.9 37 Amhara 2.7 2.0 1,344 Guragie 2.8 1.4 90 Hadiya 8.7 8.7 90 Oromo 6.0 5.6 1,582 Sidama 2.1 0.0 196 Somali 0.8 0.6 124 Tigray 1.9 1.1 319 Welaita 3.1 3.1 101 Others 1.4 1.4 587 Residence Urban 3.9 2.7 809 Rural 3.6 3.2 3,660 Region Tigray 1.9 1.1 316 Affar 1.5 1.1 43 Amhara 2.2 1.5 1,085 Oromiya 6.2 5.9 1,746 Somali 1.0 0.9 132 Benishangul-Gumuz 1.7 0.8 44 SNNPR 1.6 1.0 913 Gambela 1.7 1.4 13 Harari 1.5 1.5 10 Addis Ababa 5.7 4.1 146 Dire Dawa 2.6 0.9 23 Marital status Married or living together 3.7 3.2 3,897 Divorced/separated/widowed 3.5 2.4 573 Employment Employed for cash 3.9 3.1 1,076 Employed not for cash 4.0 3.3 1,262 Not employed 3.3 3.1 2,131 Number of living children 0 4.7 4.1 454 1-2 4.0 3.7 1,376 3-4 3.0 2.3 1,232 5+ 3.7 3.0 1,408 Wealth quintile Lowest 3.4 3.0 842 Second 5.3 5.1 857 Middle 3.0 2.5 933 Fourth 3.2 2.6 848 Highest 3.5 2.6 990 Total 3.7 3.1 4,469 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. 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 Violence Against Women • 311 Table 15.16 Violence by women against their husband by husband’s characteristics and empowerment indicators Percentage of ever-married women 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 their husband’s characteristics and women’s empowerment indicators, Ethiopia DHS 2016 Percentage who 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 4.2 3.7 1,807 Primary 3.5 2.9 1,397 Secondary 3.1 2.8 361 More than secondary 2.9 2.8 299 Husband’s/partner’s alcohol consumption Does not drink alcohol 3.2 2.9 3,058 Drinks alcohol but is never drunk 2.5 1.1 446 Is sometimes drunk 4.4 3.2 769 Is often drunk 11.5 11.5 197 Spousal education difference2 Husband has more education 3.5 2.9 1,506 Wife has more education 5.7 5.0 600 Both have equal education 1.7 1.7 216 Neither has any education 3.5 3.2 1,541 DK/missing 3.3 2.2 607 Spousal age difference2 Wife older 2.8 1.7 121 Wife is same age 12.3 12.3 83 Wife’s 1-4 years younger 2.8 2.7 1,108 Wife’s 5-9 years younger 3.6 3.2 1,515 Wife’s 10+ years younger 4.2 3.3 1,070 Number of marital control behaviours displayed by husband/partner3 0 2.2 1.9 1,935 1-2 3.9 3.5 1,803 3-4 7.3 6.0 566 5 6.6 3.2 165 Number of decisions in which women participate4 0 2.3 2.3 378 1-2 3.3 2.3 825 3 4.0 3.7 2,694 Number of reasons for which wife-beating is justified5 0 2.5 2.0 1,489 1-2 4.0 3.3 903 3-4 6.0 5.4 1,001 5 2.8 2.5 1,076 Woman’s father beat her mother Yes 5.0 4.4 1,226 No 2.9 2.5 2,982 DK/Missing 6.0 3.9 261 Woman afraid of husband/ partner Most of the time afraid 7.6 7.2 950 Sometimes afraid 3.8 3.1 1,825 Never afraid 1.4 0.9 1,694 Total 3.7 3.1 4,469 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. Total includes 32 ever-married women with missing information on husband’s/partner’s education. 1 Includes in the past 12 months 2 Includes only currently married women 3 According to the wife’s report. See Table 15.8 for list of behaviours. 4 According to the wife’s report. Includes only currently married women. See Table 14.12.1 for list of decisions. 5 According to the wife’s report. See Table 14.13.1 for list of reasons. 312 • Violence Against Women Table 15.17 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, Ethiopia DHS 2016 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 23.4 10.7 66.0 100.0 951 Sexual only 7.0 13.9 79.1 100.0 176 Physical and sexual 27.0 11.6 61.5 100.0 414 Age 15-19 24.6 15.4 60.0 100.0 168 20-24 11.4 11.5 77.1 100.0 237 25-29 16.7 13.9 69.4 100.0 312 30-39 30.4 9.7 59.9 100.0 535 40-49 21.8 8.7 69.5 100.0 287 Religion Orthodox 24.5 13.8 61.6 100.0 740 Catholic * * * 100.0 6 Protestant 23.2 7.9 68.9 100.0 333 Muslim 19.6 9.8 70.6 100.0 425 Traditional * * * 100.0 19 Other * * * 100.0 18 Ethnic group Affar (12.0) (4.8) (83.3) 100.0 5 Amhara 21.6 14.5 63.9 100.0 501 Guragie 34.2 10.5 55.4 100.0 37 Hadiya * * * 100.0 29 Oromo 22.9 10.4 66.8 100.0 587 Sidama (25.3) (6.2) (68.4) 100.0 69 Somali (25.0) (6.7) (68.3) 100.0 9 Tigray 26.4 14.1 59.4 100.0 116 Welaita * * * 100.0 30 Others 15.9 9.3 74.8 100.0 156 Residence Urban 35.8 18.1 46.2 100.0 295 Rural 19.3 9.7 71.0 100.0 1,245 Region Tigray 24.1 13.8 62.0 100.0 117 Affar 9.6 7.9 82.4 100.0 9 Amhara 21.4 14.2 64.4 100.0 388 Oromiya 20.1 9.8 70.1 100.0 662 Somali (27.5) (6.1) (66.4) 100.0 10 Benishangul-Gumuz 8.5 20.3 71.2 100.0 12 SNNPR 24.2 5.8 70.0 100.0 240 Gambela 10.8 25.5 63.6 100.0 5 Harari 15.5 15.6 68.9 100.0 3 Addis Ababa 41.1 20.0 38.8 100.0 88 Dire Dawa 21.8 13.1 65.1 100.0 9 Marital status Never married 33.9 24.6 41.5 100.0 120 Married or living together 20.2 10.1 69.7 100.0 1,180 Divorced/separated/widowed 27.8 10.3 61.9 100.0 240 Number of living children 0 23.4 15.0 61.7 100.0 245 1-2 21.1 13.0 65.9 100.0 499 3-4 23.2 9.0 67.8 100.0 356 5+ 22.9 9.1 68.0 100.0 439 Employment Employed for cash 29.2 13.9 56.9 100.0 409 Employed not for cash 21.4 9.2 69.3 100.0 446 Not employed 19.1 11.0 69.9 100.0 686 Education No education 22.0 9.4 68.6 100.0 901 Primary 19.3 11.7 69.0 100.0 460 Secondary 34.2 20.2 45.7 100.0 120 More than secondary 29.8 19.2 51.0 100.0 60 Wealth quintile Lowest 17.6 7.5 74.9 100.0 273 Second 19.2 11.0 69.8 100.0 283 Middle 18.2 7.2 74.7 100.0 348 Fourth 22.7 13.0 64.2 100.0 288 Highest 33.0 17.1 49.9 100.0 347 Total 22.5 11.3 66.3 100.0 1,540 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. Violence Against Women • 313 Table 15.18 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, Ethiopia DHS 2016 Type of violence experienced Physical or sexual Source Physical only Sexual only Physical and sexual Own family 30.3 * 31.3 30.6 Husband/partner’s family 6.8 * 26.6 13.5 Husband/partner 0.2 * 0.0 0.1 Friend 7.8 * 15.5 10.2 Neighbour 41.5 * 22.3 34.4 Religious leader 3.2 * 10.8 5.5 Doctor/medical personnel 1.0 * 2.6 1.5 Police 9.8 * 4.1 8.1 Lawyer 1.1 * 5.1 2.8 Social work organization 2.4 * 1.0 1.8 Other 3.3 * 2.4 3.0 Number of women who have sought help 222 12 112 346 Note: Women can report more than one source from which they sought help. An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. Female Genital Mutilation/Cutting • 315 FEMALE GENITAL MUTILATION/CUTTING 16 Key Findings  Prevalence among women: Sixty-five percent of women age 15-49 are circumcised. The prevalence of female circumcision is highest in Somali (99%) and lowest in Tigray (23%).  Types of procedures: Seventy-three percent of circumcised women reported that some flesh was removed, and 7% reported being infibulated.  Age at circumcision: Forty-nine percent of circumcised women age 15-49 were circumcised before age 5, and 24% were circumcised at age 10 or older.  Prevalence among girls: According to their mothers, 16% of girls age 0-14 are circumcised. Girls are five times more likely to be circumcised if their mothers is circumcised, compared with girls of uncircumcised women.  Opinions of the practice: Among women who have heard of female circumcision, 24% believe that the practice is required by their religion, and 18% believe that the practice should be continued. his chapter explores female genital mutilation or cutting (FGM/C), also known as female circumcision. FGM/C involves removing some of the clitoris or the labia for nontherapeutic reasons, usually as part of a rite of passage into adolescence. The practice is widely acknowledged as a violation of human rights, and serious medical complications can result. The government of Ethiopia is committed to eliminating the practice of FGM/C by strategic and programmatic measures. These include putting in place a national Harmful Traditional Practices (HTPs) strategy founded on the three-pillar approach: prevention, provision, and protection. This targeted approach guides the national effort and helps to galvanize the support of stakeholders to end the practice as well as mitigate the impact of FGM/C. Additionally, Ethiopia has criminalized the practice and now penalizes practitioners in the national Criminal Code, revised in 2005. To this end, a mix of prevention, protection, and provisional interventions are under implementation at different levels by government and nongovernmental actors. Moreover, the government of Ethiopia refreshed its commitment to end FGM/C and child marriage by 2025 at the London Global Girls’ Summit held in July 2014. The commitment, which employs an integrated and comprehensive strategy, puts girls at the centre and targets girls themselves, families and communities, service providers, and policy makers. As part of the commitment, the following key areas have been identified: improving availability of data; strengthening coordination; putting in place accountability to enhance enforcement of the existing law; and increasing the budget for the effort to end the practice altogether or decrease it by 10%. T 316 • Female Genital Mutilation/Cutting Accordingly, the National Alliance to end child marriage and FGM/C strengthened the effort at a higher level. Since 2015, the national girls’ summit has tracked progress and kept the national momentum going. A roadmap development initiative, which includes a national and sub-national plan with a monitoring and evaluation framework, is underway. With the existence of a legal and policy framework, and with a high level of political support to end FGM/C, the practice has declined, particularly among younger people, but still continues. In addition, the community-based and faith-based organizations play a key role in mobilizing communities against HTPs, including FGM/C. 16.1 KNOWLEDGE Knowledge Female and male respondents were asked if they had ever heard of female genital mutilation/cutting. Sample: Women age 15-49 and men age 15-59 Overall, 93% of women age 15-49 and 94% of men age 15-49 have heard about FGM/C (Table 16.1). Trends: Awareness of FGM/C among women age 15-49 has remained about the same over the past decade (92% in 2005 to 93% in 2016). Patterns by background characteristics  Ninety-seven percent of women residing in urban areas have heard about FGM/C, compared with 91% of women in rural areas.  Knowledge of FGM/C is higher in Affar (100%), Somali (100%), Harari (99%), Addis Ababa (99%), and Dire Dawa (97%), and lower in Gambela (71%).  Women’s knowledge of FGM/C increases steadily with increasing education, from 90% among women with no education to 100% among those with more than secondary education. 16.2 PREVALENCE OF AND AGE AT CIRCUMCISION AMONG WOMEN To assess FGM/C prevalence, women age 15-49 were asked if they had ever been circumcised. Circumcised women were further asked about the type of circumcision, their age at the time they were circumcised, and the person who performed the circumcision. 16.2.1 Prevalence and Type of Procedure Prevalence of FGM/C Female respondents were asked whether they had ever been circumcised. Sample: Women age 15-49 Type of and age at circumcision Women who were circumcised were asked about  Type of circumcision (cut, no flesh removed; cut, flesh removed; sewn closed [infibulation])  Age at circumcision Sample: Women age 15-49 who reported having been circumcised Female Genital Mutilation/Cutting • 317 Two in three women age 15-49 (65%) in Ethiopia are circumcised (Table 16.2). The most common type of circumcision involved cutting and removal of flesh, with 73% of circumcised women reporting this type of circumcision. Seven percent of circumcised women reported that their genital area had been sewn closed (infibulated) (Figure 16.1). Infibulation is the type of FGM/C that is of greatest concern because of the possible harm to health (Yoder 2013). Trends: The prevalence of FGM/C in Ethiopia has decreased over the past 16 years, dropping from 80% in the 2000 EDHS, to 74% in the 2005 EDHS, and to 65% in the 2016 EDHS (Figure 16.2). The decline is particularly notable among younger women: FGM/C prevalence among women age 15-19 decreased by 24% between 2005 and 2016. The notable decline observed among younger women may be in part a reporting issue. FGM/C was criminalized in 2005, which may lead to under reporting of the practice to avoid legal consequences. Patterns by background characteristics  The prevalence of FGM/C increases with age, from 47% among women age 15-19 to 75%- 76% among women age 30-49 (Figure 16.3).  Women in rural areas are more likely to be circumcised than women in urban areas (68% and 54%, respectively).  FGM/C is highest in Somali at 99%, followed by Affar (91%). Tigray has the lowest prevalence (24%), followed by Gambela (33%) (Figure 16.4).  Infibulation is more common in Somali and Affar (73% and 64%, respectively), and lowest in Addis Ababa and Oromiya (1% and 2%, respectively). Figure 16.1 Type of female circumcision Figure 16.2 Trends in circumcision Figure 16.3 Circumcision by age Figure 16.4 Circumcision by region Cut, flesh removed 73% Cut, no flesh removed 3% Sewn closed 7% Don’t know/ missing 18% Percentage among circumcised women age 15-49 80 74 65 2000 EDHS 2005 EDHS 2016 EDHS Percentage of women age 15-49 who are circumcised 47 59 68 76 75 15-19 20-24 25-29 30-34 35-49 Percentage of women age 15-49 who are circumcised 24 33 54 62 62 63 75 76 82 91 99 Tigray Gambela Addis Ababa Amhara SNNPR Benishangul-Gumuz Dire Dawa Oromiya Harari Affar Somali Percentage of women age 15-49 who are circumcised 318 • Female Genital Mutilation/Cutting 16.2.2 Age at Circumcision In Ethiopia, FGM/C is performed throughout childhood. Thus, nearly half of women (49%) reported that they were circumcised when they were younger than age 5, 22% between ages 5-9, 18% between ages 10-14, and 6% at age 15 or older (Table 16.3 and Figure 16.5). Patterns by background characteristics  Among circumcised women, those in urban areas are more likely to be circumcised before age 5 than rural women (59% versus 46%, respectively).  The percentage of women who were circumcised before age 5 is highest in Tigray (93%), followed by Amhara (92%), and lowest in Somali and Harari (13%). 16.3 PREVALENCE OF AND AGE AT CIRCUMCISION FOR GIRLS AGE 0-14 Information on the circumcision status of women age 15-49 reflects the outcomes of circumcision practices over a nearly 50-year period before the survey. To obtain insights into the extent to which young girls are continuing to be circumcised, women who had daughters were asked in the 2016 EDHS if any of their daughters born in 1992 or later had been circumcised. Prevalence of FGM/C among girls age 0-14 Women were asked about the circumcision status of their living daughters age 0-14. Sample: Girls age 0-14 According to mothers’ reports, the prevalence of FGM/C among girls age 0-14 is 16% (Table 16.4). The low prevalence rate among young girls should be interpreted with caution since it represents the current rather than the final FGM/C status for this age group. As mentioned above, 21% of women age 15-19 were circumcised between age 10-14, so it is still possible that a number of girls age 0-14 may yet be circumcised. To control for the incomplete exposure to the risk of circumcision among young girls, Figure 16.6 shows retrospective information for women on age at circumcision and current status information on girls to provide comparable information on the cumulative percentage of women and girls circumcised by exact year of age. According to these data, the prevalence of circumcision is lower among girls age 0-14 than among women age 15-49—57% of women age 15-49 were circumcised by age 14; by contrast, 38% of girls currently age 14 have been circumcised. This trend should be interpreted with caution as some women also may have been reluctant to report that their daughters were circumcised because the practice is outlawed. Figure 16.5 Age at circumcision Figure 16.6 Age at circumcision among women and girls <5 years 49% 5-9 years 22% 10-14 years 18% 15+ years 6% Don’t know/ missing 6% Percent distribution of women who are circumcised 0 10 20 30 40 50 60 70 <1 1 2 3 4 5 6 7 8 9 10 11 12 13 14 Age in years Percentage of women age 15-49 and girls age 0-14 who are circumcised Women 15-49 Girls 0-14 Female Genital Mutilation/Cutting • 319 Additionally, the decline among girls may also be partly explained by increased government commitment to end FGM/C and a mix of prevention, protection, and provisional interventions by government and non- government actors. For additional information on FGM/C among girls, see tables 16.5-6.7. 16.4 OPINIONS ABOUT THE PRACTICE Women age 15-49 and men age 15-59 who heard about female genital mutilation and cutting were asked their opinion on whether or not their religion requires female circumcision and whether the practice should be continued. More than 7 in 10 women (72%) and 77% of men believe that FGM/C is not required by their religion (Table 16.8). Seventy-nine percent of women and 87% of men believe that the practice should not be continued (Table 16.9). Trends: Overall, the percentage of women who believe that female circumcision should be continued has decreased from 31% in the 2005 EDHS to 18% in the 2016 EDHS. Patterns by background characteristics  Women who are circumcised are more likely to believe that FGM/C is required by their religion (30%) than uncircumcised women (9%). The same pattern is observed with regard to women’s opinion about continuation of the practice; 23% of circumcised women think FGM/C should be continued, compared with 5% of uncircumcised women (Figure 16.7).  By religion, Muslim women are more likely to believe that FGM/C is required by their religion and that FGM/C should continue (41% and 28%, respectively).  Women in rural areas are more than twice as likely to believe that FGM/C is required by their religion (28%) compared to women in urban areas (10%). The same pattern is observed with regard to women’s opinion about continuation of the practice; 21% of rural women think FGM/C should be continued compared with 7% of urban women.  The percentages of women who believe that FGM/C is required by their religion and who want to the practice to continue are highest among those with no education (31% and 25%, respectively) and those in the lowest wealth quintile (39% and 34%, respectively). LIST OF TABLES For more information on FGM/C, see the following tables:  Table 16.1 Knowledge of female circumcision  Table 16.2 Prevalence of female circumcision  Table 16.3 Age at circumcision  Table 16.4 Prevalence of circumcision and age at circumcision: Girls 0-14  Table 16.5 Circumcision of girls age 0-14 by mother’s background characteristics  Table 16.6 Infibulation among circumcised girls age 0-14  Table 16.7 Aspects of circumcision among circumcised girls age 0-14 and women age 15-49  Table 16.8 Opinions of women and men about whether circumcision is required by religion  Table 16.9 Opinions of women and men about whether the practice of circumcision should continue Figure 16.7 Attitudes about FGC by circumcision status 30 23 9 5 Believe circumcision is required by religion Believe circumcision should continue Percentage of women age 15-49 Circumcised Not circumcised 320 • Female Genital Mutilation/Cutting Table 16.1 Knowledge of female circumcision Percentage of women age 15-49 and men age 15-59 who have heard of female circumcision, according to background characteristics, Ethiopia DHS 2016 Women Men Background characteristic Have heard of female circumcision Number of women Have heard of female circumcision Number of men Age 15-19 91.1 1,670 87.9 2,572 20-24 92.5 1,290 93.7 1,883 25-29 92.0 1,474 95.4 1,977 30-34 93.0 2,218 95.6 3,020 35-49 95.1 1,170 96.3 2,154 Religion Orthodox 92.2 3,424 92.2 5,160 Catholic (79.0) 66 85.0 78 Protestant 89.9 1,862 93.1 2,561 Muslim 96.8 2,362 96.8 3,649 Traditional (88.5) 62 (65.7) 31 Other (47.7) 46 90.3 128 Ethnic group Affar 100.0 55 99.5 63 Amhara 94.7 2,328 93.8 3,497 Guragie 98.1 205 97.6 311 Hadiya 98.7 184 97.5 217 Oromo 95.9 2,693 97.2 4,175 Sidama 99.4 321 97.6 490 Somali 99.9 220 99.1 299 Tigray 86.7 565 84.7 778 Welaita 97.4 234 94.5 321 Others 75.3 1,018 84.0 1,455 Residence Urban 97.1 1,714 98.0 2,303 Rural 91.4 6,108 92.6 9,302 Region Tigray 85.6 540 83.1 708 Affar 100.0 67 98.8 82 Amhara 93.2 1,826 92.6 2,914 Oromiya 95.4 2,881 97.7 4,409 Somali 99.9 229 99.2 301 Benishangul-Gumuz 91.1 75 87.9 118 SNNPR 86.7 1,653 88.8 2,371 Gambela 71.3 22 78.5 35 Harari 99.2 18 99.5 29 Addis Ababa 98.9 466 99.4 573 Dire Dawa 97.3 47 97.8 66 Education No education 89.9 3,787 90.9 3,203 Primary 93.5 2,679 92.8 5,608 Secondary 98.0 907 98.1 1,785 More than secondary 99.8 449 99.6 1,010 Wealth quintile Lowest 86.3 1,306 90.3 1,839 Second 90.5 1,419 92.9 2,118 Middle 92.6 1,521 92.4 2,246 Fourth 94.5 1,529 93.6 2,466 Highest 96.9 2,048 97.5 2,935 Total 15-49 92.7 7,822 93.7 11,606 50-59 na na 96.4 1,082 Total 15-59 na na 93.9 12,688 Note: Figures in parentheses are based on 25-49 unweighted cases. na = Not applicable Female Genital Mutilation/Cutting • 321 Table 16.2 Prevalence of female circumcision Percentage of women age 15-49 circumcised, and percent distribution of circumcised women by type of circumcision, according to background characteristics, Ethiopia DHS 2016 Percentage of women circumcised Number of women Type of circumcision Total Number of circumcised women Background characteristic Cut, no flesh removed Cut, flesh removed Sewn closed Don’t know/ missing Age 15-19 47.1 1,670 2.8 65.1 7.4 24.7 100.0 786 20-24 58.6 1,290 2.8 73.3 6.8 17.1 100.0 756 25-29 67.6 1,474 2.2 75.1 5.7 17.1 100.0 996 30-34 75.8 2,218 2.4 76.0 5.7 15.9 100.0 1,682 35-49 75.3 1,170 2.9 71.5 8.1 17.4 100.0 881 Religion Orthodox 54.2 3,424 3.4 62.9 2.3 31.5 100.0 1,856 Catholic (58.2) 66 * * * * 100.0 39 Protestant 65.8 1,862 2.1 90.0 2.5 5.4 100.0 1,226 Muslim 82.2 2,362 2.2 71.5 13.4 13.0 100.0 1,942 Ethnic group Affar 98.4 55 3.1 16.3 71.0 9.6 100.0 54 Amhara 60.5 2,328 3.0 58.5 2.7 35.8 100.0 1,409 Guragie 78.3 205 6.9 75.6 2.7 14.9 100.0 160 Hadiya 92.3 184 1.2 80.3 12.6 6.0 100.0 170 Oromo 77.1 2,693 1.8 82.8 1.9 13.5 100.0 2,076 Sidama 87.6 321 1.3 95.0 2.1 1.6 100.0 281 Somali 98.5 220 1.5 22.4 75.6 0.5 100.0 217 Tigray 23.0 565 8.9 46.0 5.3 39.9 100.0 130 Welaita 92.3 234 5.9 93.5 0.0 0.6 100.0 216 Others 38.1 1,018 1.3 86.0 4.1 8.6 100.0 388 Residence Urban 53.9 1,714 4.5 64.3 8.4 22.8 100.0 924 Rural 68.4 6,108 2.1 74.9 6.1 16.9 100.0 4,177 Region Tigray 24.2 540 9.9 43.3 7.1 39.7 100.0 131 Affar 91.2 67 7.2 24.1 63.6 5.0 100.0 61 Amhara 61.7 1,826 1.8 55.1 2.8 40.2 100.0 1,127 Oromiya 75.6 2,881 2.0 83.8 1.6 12.6 100.0 2,178 Somali 98.5 229 1.7 24.7 73.1 0.5 100.0 225 Benishangul-Gumuz 62.9 75 5.9 66.2 3.2 24.7 100.0 47 SNNPR 62.0 1,653 2.8 88.7 4.3 4.1 100.0 1,024 Gambela 33.0 22 6.6 43.7 4.8 44.9 100.0 7 Harari 81.7 18 0.6 92.2 4.5 2.7 100.0 15 Addis Ababa 54.0 466 5.1 65.4 1.4 28.0 100.0 251 Dire Dawa 75.3 47 3.3 78.1 10.1 8.5 100.0 35 Total 65.2 7,822 2.6 73.0 6.5 17.9 100.0 5,101 Note: Total includes 34 weighted cases of traditional religion, and 5 weighted cases with information missing on religion. 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. 322 • Female Genital Mutilation/Cutting Table 16.3 Age at circumcision Percent distribution of circumcised women age 15-49 by age at circumcision, according to background characteristics, Ethiopia DHS 2016 Background characteristic Age at circumcision Total Number of circumcised women <51 5-9 10-14 15+ Don’t know/ Missing Age 15-19 51.6 22.5 19.3 1.9 4.7 100.0 786 20-24 44.0 22.1 17.8 10.7 5.4 100.0 756 25-29 44.7 24.1 20.0 5.9 5.4 100.0 996 30-34 48.5 21.2 17.1 6.3 6.9 100.0 1,682 35-49 54.4 19.1 16.5 4.6 5.4 100.0 881 Religion Orthodox 75.1 11.3 6.5 1.0 6.0 100.0 1,856 Catholic 43.5 21.6 5.7 5.4 23.8 100.0 39 Protestant 30.4 28.4 27.3 9.7 4.2 100.0 1,226 Muslim 35.1 27.6 23.7 7.8 5.9 100.0 1,942 Traditional 33.8 6.8 1.0 29.2 29.2 100.0 34 Other 2.8 82.6 12.1 0.0 2.4 100.0 5 Ethnic group Affar 91.5 3.5 2.6 0.2 2.2 100.0 54 Amhara 85.9 5.5 2.4 0.4 5.8 100.0 1,409 Guragie 49.1 29.3 17.3 1.1 3.2 100.0 160 Hadiya 25.6 35.9 25.1 6.7 6.6 100.0 170 Oromo 32.4 27.8 23.3 8.6 7.9 100.0 2,076 Sidama 29.1 14.5 32.9 23.5 0.0 100.0 281 Somali 11.4 61.8 24.5 0.4 1.8 100.0 217 Tigray 92.1 1.9 0.1 0.5 5.5 100.0 130 Welaita 23.6 34.9 35.4 3.7 2.5 100.0 216 Others 37.7 23.9 27.1 7.0 4.2 100.0 388 Residence Urban 59.2 20.2 10.8 2.2 7.6 100.0 924 Rural 46.2 22.1 19.6 6.7 5.4 100.0 4,177 Region Tigray 93.0 1.1 0.0 0.5 5.4 100.0 131 Affar 89.5 4.6 3.2 0.2 2.5 100.0 61 Amhara 92.0 3.6 0.9 0.6 3.0 100.0 1,127 Oromiya 31.8 27.4 23.4 8.5 9.0 100.0 2,178 Somali 12.8 61.3 23.8 0.4 1.7 100.0 225 Benishangul-Gumuz 76.5 10.4 5.6 3.0 4.5 100.0 47 SNNPR 30.6 25.9 30.6 10.2 2.7 100.0 1,024 Gambela 63.4 17.6 6.8 2.3 9.9 100.0 7 Harari 13.0 51.4 28.0 1.1 6.6 100.0 15 Addis Ababa 69.3 16.8 5.4 0.4 8.2 100.0 251 Dire Dawa 39.5 22.5 28.8 4.0 5.2 100.0 35 Total 48.6 21.7 18.0 5.9 5.8 100.0 5,101 1 Includes women who reported they were circumcised during infancy but did not provide a specific age. Female Genital Mutilation/Cutting • 323 Table 16.4 Prevalence of circumcision and age at circumcision: Girls 0-14 Percent distribution of girls age 0-14 by age at circumcision, and percentage of girls circumcised according to current age, Ethiopia DHS 2016 Age at circumcision Total Number of girls Percentage circumcised Background characteristic <1 1-4 5-9 10-14 Don’t know/ Missing Percentage not circumcised Current age of girls 0-4 5.1 1.5 na na 0.1 93.1 100.0 2,604 6.9 5-9 7.2 3.6 2.7 na 0.3 85.8 100.0 2,590 14.2 10-14 9.8 5.3 9.4 3.1 0.7 71.6 100.0 2,112 28.4 Total 0-14 7.2 3.4 3.7 1.0 0.3 84.3 100.0 7,306 15.7 Note: The circumcision status of girls is reported by their mothers. na = Not applicable due to censoring Table 16.5 Circumcision of girls age 0-14 by mother’s background characteristics Percentage of girls age 0-14 who are circumcised, according to age and mother’s background characteristics, Ethiopia DHS 2016 Background characteristic Current age of girls Total 0-14 0-4 5-9 10-14 Religion Orthodox 12.6 22.7 34.3 22.9 Catholic * * * (17.6) Protestant 2.8 9.4 20.8 10.8 Muslim 4.8 10.3 28.8 12.8 Ethnic group Affar 71.3 82.4 92.2 80.1 Amhara 16.6 28.8 39.0 28.2 Guragie 0.2 5.5 (38.5) 11.5 Hadiya (0.0) (7.6) (45.7) 16.5 Oromo 2.4 8.5 19.8 9.1 Sidama (0.0) 4.6 23.6 10.7 Somali 2.4 18.4 68.1 24.9 Tigray 6.2 14.8 13.4 11.1 Welaita (13.9) (21.1) (58.6) 29.1 Others 5.2 5.4 14.3 7.8 Residence Urban 0.9 7.8 11.9 6.6 Rural 7.6 14.8 30.5 16.7 Region Tigray 6.3 15.2 13.7 11.3 Affar 73.3 75.9 86.4 77.8 Amhara 22.5 34.8 47.7 34.8 Oromiya 1.9 6.8 16.9 7.6 Somali 2.9 19.4 69.8 25.7 Benishangul-Gumuz 11.9 21.1 26.5 19.1 SNNPR 2.1 7.3 26.6 11.6 Gambela 1.9 0.4 9.6 3.4 Harari 0.0 2.9 23.5 6.7 Addis Ababa 0.2 1.6 4.6 1.8 Dire Dawa 1.3 7.2 23.3 9.6 Mother’s education No education 8.0 15.1 29.1 17.2 Primary 6.2 13.4 28.6 13.9 Secondary 0.3 2.2 12.0 2.7 More than secondary 0.0 (0.0) (1.3) 0.3 Mother’s circumcision status Circumcised 9.0 17.8 36.2 20.2 Not circumcised 2.6 5.0 5.0 4.1 Wealth quintile Lowest 6.3 16.0 32.0 16.1 Second 5.7 14.1 30.3 15.7 Middle 10.2 12.3 27.6 16.0 Fourth 9.0 15.4 32.5 18.6 Highest 2.5 11.9 17.1 10.2 Total 6.9 14.2 28.4 15.7 Note: The circumcision status of girls is reported by their mothers. 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. 324 • Female Genital Mutilation/Cutting Table 16.6 Infibulation among circumcised girls age 0-14 Percent distribution of girls age 0-14 who are circumcised by whether or not they are infibulated, according to mother’s background characteristics, Ethiopia DHS 2016 Infibulation status Total Number Background characteristic Sewn closed Not sewn closed Don’t know/ missing Religion Orthodox 3.1 95.8 1.1 100.0 596 Catholic * * * 100.0 11 Protestant 2.7 97.3 0.0 100.0 192 Muslim 22.2 77.5 0.3 100.0 348 Ethnic group Affar 69.9 29.1 1.0 100.0 45 Amhara 3.7 95.8 0.4 100.0 491 Guragie * * * 100.0 13 Hadiya * * * 100.0 35 Oromo 5.7 92.6 1.7 100.0 259 Sidama * * * 100.0 34 Somali 34.7 65.3 0.0 100.0 76 Tigray 1.3 98.7 0.0 100.0 48 Welaita (0.0) (100.0) (0.0) 100.0 62 Others 6.5 92.9 0.5 100.0 84 Residence Urban 24.2 75.3 0.5 100.0 50 Rural 8.6 90.8 0.6 100.0 1,097 Region Tigray 1.3 98.7 0.0 100.0 49 Affar 68.2 30.8 1.0 100.0 47 Amhara 3.4 96.1 0.4 100.0 520 Oromiya 7.0 91.9 1.1 100.0 234 Somali 32.6 67.4 0.0 100.0 81 Benishangul-Gumuz 10.2 86.8 3.1 100.0 14 SNNPR 5.5 93.6 0.9 100.0 194 Gambela * * * 100.0 1 Harari (3.6) (96.4) (0.0) 100.0 1 Addis Ababa * * * 100.0 2 Dire Dawa (16.7) (83.3) (0.0) 100.0 3 Mother’s education No education 9.9 89.3 0.8 100.0 912 Primary 6.3 93.7 0.0 100.0 228 Secondary * * * 100.0 7 Mother’s circumcision status Infibulated 55.4 44.4 0.2 100.0 133 Circumcised, not infibulated 2.9 96.3 0.7 100.0 961 Not circumcised (8.2) (91.8) (0.0) 100.0 53 Wealth quintile Lowest 24.2 75.7 0.1 100.0 258 Second 2.5 96.7 0.7 100.0 245 Middle 7.0 91.8 1.1 100.0 246 Fourth 3.3 95.8 0.8 100.0 291 Highest 9.8 90.1 0.1 100.0 107 Total 9.3 90.1 0.6 100.0 1,147 Note: The circumcision status of girls is reported by their mothers. 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. Female Genital Mutilation/Cutting • 325 Table 16.7 Aspects of circumcision among circumcised girls age 0-14 and women age 15-49 Percent distribution of circumcised girls age 0-14 by current age and women age 15-49, according to person performing the circumcision and type of circumcision, Ethiopia DHS 2016 Background characteristic Age of girls Girls age 0-14 Women age 15-49 0-4 5-9 10-14 Person who performed the circumcision Traditional agent 99.1 98.4 96.6 97.6 90.1 Traditional circumciser 95.6 96.8 94.4 95.3 87.3 Traditional birth attendant 3.5 1.6 2.2 2.2 2.6 Other traditional agent 0.0 0.0 0.0 0.0 0.2 Medical professional 0.9 1.6 2.4 1.9 1.0 Doctor 0.0 0.0 0.0 0.0 0.1 Nurse/midwife 0.9 1.6 2.1 1.8 0.6 Other health professional 0.0 0.0 0.3 0.2 0.4 Don’t know/missing 0.0 0.0 0.9 0.5 8.9 Total 100.0 100.0 100.0 100.0 100.0 Type of circumcision Sewn closed 7.6 11.4 8.5 9.3 6.5 Not sewn closed 92.3 88.0 90.8 90.1 86.8 Don’t know/missing 0.1 0.7 0.8 0.6 6.6 Total 100.0 100.0 100.0 100.0 100.0 Number 180 367 599 1,147 5,101 Note: The circumcision status of girls is reported by their mothers. 326 • Female Genital Mutilation/Cutting Table 16.8 Opinions of women and men about whether circumcision is required by religion Percent distribution of women age 15-49 and men age 15-59 who have heard of female circumcision by opinion on whether their religion requires female circumcision, according to background characteristics, Ethiopia DHS 2016 Women Men Background characteristic Required Not required No religion Don’t know Total Number of women who have heard of female circum- cision Required Not required No religion Don’t know Total Number of men who have heard of female circum- cision Female circumcision status Circumcised 29.6 66.9 0.3 3.2 100.0 5,101 na na na na na na Not circumcised 9.3 84.5 0.5 5.7 100.0 2,147 na na na na na na Age 15-19 19.0 78.5 0.1 2.4 100.0 1,523 16.0 76.3 0.3 7.5 100.0 2,261 20-24 20.1 75.7 0.3 3.9 100.0 1,194 13.7 78.4 0.2 7.7 100.0 1,764 25-29 23.1 72.8 0.6 3.6 100.0 1,356 17.1 78.4 0.2 4.3 100.0 1,887 30-34 25.5 69.2 0.7 4.5 100.0 1,124 14.9 79.5 0.3 5.3 100.0 1,566 35-39 25.9 70.4 0.1 3.6 100.0 939 18.3 77.5 0.3 4.0 100.0 1,322 40-44 27.2 65.9 0.4 6.5 100.0 610 19.7 74.8 0.4 5.2 100.0 1,160 45-49 34.0 59.2 0.6 6.2 100.0 502 21.4 74.4 0.0 4.1 100.0 913 Religion Orthodox 17.0 76.1 0.6 6.3 100.0 3,157 16.9 76.8 0.2 6.1 100.0 4,755 Catholic (19.6) (76.5) (0.0) (3.8) 100.0 52 5.4 90.6 0.0 4.0 100.0 66 Protestant 12.6 85.3 0.0 2.2 100.0 1,674 4.6 91.9 0.1 3.5 100.0 2,383 Muslim 40.9 56.9 0.1 2.1 100.0 2,288 24.9 68.3 0.0 6.7 100.0 3,533 Traditional * * * * 100.0 55 * * * * 100.0 20 Other * * * * 100.0 22 22.8 61.3 11.5 4.4 100.0 115 Ethnic group Affar 74.6 23.1 0.0 2.3 100.0 55 51.1 46.3 0.6 2.0 100.0 63 Amhara 19.7 73.7 0.7 5.9 100.0 2,204 21.2 72.2 0.1 6.5 100.0 3,278 Guragie 23.2 73.8 0.9 2.1 100.0 201 12.2 83.5 0.0 4.3 100.0 304 Hadiya 24.0 74.8 0.0 1.1 100.0 182 7.9 86.1 0.0 6.0 100.0 212 Oromo 28.0 69.7 0.1 2.2 100.0 2,584 16.2 77.9 0.1 5.7 100.0 4,058 Sidama 23.2 74.6 0.0 2.2 100.0 319 6.6 90.2 0.5 2.7 100.0 478 Somali 56.1 42.5 0.1 1.3 100.0 220 40.8 50.2 0.2 8.9 100.0 296 Tigray 18.0 71.5 0.4 10.1 100.0 490 17.6 73.7 0.2 8.5 100.0 659 Welaita 19.3 80.5 0.0 0.2 100.0 228 4.5 93.1 0.1 2.3 100.0 303 Others 11.9 83.2 0.6 4.3 100.0 767 8.3 87.0 0.9 3.7 100.0 1,222 Residence Urban 10.3 86.2 0.6 2.9 100.0 1,665 11.5 81.6 0.1 6.8 100.0 2,257 Rural 27.6 67.9 0.3 4.2 100.0 5,583 18.2 76.2 0.3 5.4 100.0 8,616 Region Tigray 20.1 68.8 0.5 10.7 100.0 462 18.3 72.5 0.2 9.0 100.0 589 Affar 61.7 35.4 0.0 2.9 100.0 67 40.4 56.4 1.4 1.9 100.0 81 Amhara 22.0 70.8 0.6 6.6 100.0 1,702 24.3 68.7 0.0 7.0 100.0 2,699 Oromiya 27.2 70.0 0.2 2.6 100.0 2,748 15.2 78.9 0.2 5.7 100.0 4,307 Somali 57.0 41.5 0.1 1.4 100.0 228 41.7 49.4 0.1 8.8 100.0 298 Benishangul-Gumuz 14.9 82.3 1.2 1.6 100.0 68 23.2 71.2 0.2 5.5 100.0 104 SNNPR 18.1 79.5 0.4 2.0 100.0 1,433 6.8 90.0 0.7 2.5 100.0 2,106 Gambela 14.7 82.9 0.4 2.1 100.0 16 7.1 88.0 0.7 4.3 100.0 27 Harari 31.1 66.0 0.1 2.8 100.0 18 36.2 60.1 0.0 3.6 100.0 28 Addis Ababa 6.2 89.6 0.5 3.7 100.0 461 8.3 85.0 0.0 6.7 100.0 570 Dire Dawa 36.4 61.6 0.0 2.0 100.0 45 31.2 58.6 0.3 9.9 100.0 65 Education No education 31.2 63.3 0.5 5.1 100.0 3,406 24.0 69.0 0.2 6.8 100.0 2,911 Primary 21.9 74.4 0.4 3.3 100.0 2,505 15.7 78.7 0.2 5.4 100.0 5,205 Secondary 8.2 89.3 0.1 2.4 100.0 889 12.7 81.9 0.5 4.9 100.0 1,751 More than secondary 6.1 91.6 0.2 2.1 100.0 448 8.7 85.7 0.2 5.4 100.0 1,006 Wealth quintile Lowest 39.3 55.4 0.4 4.9 100.0 1,127 23.2 69.0 0.3 7.4 100.0 1,660 Second 28.3 67.5 0.2 4.0 100.0 1,284 21.1 73.1 0.1 5.7 100.0 1,968 Middle 24.8 71.3 0.0 3.9 100.0 1,408 17.6 77.5 0.1 4.7 100.0 2,076 Fourth 22.4 72.1 0.7 4.8 100.0 1,445 14.6 80.4 0.4 4.7 100.0 2,308 Highest 11.7 85.1 0.5 2.8 100.0 1,984 11.2 82.4 0.2 6.1 100.0 2,861 Total 15-49 23.6 72.1 0.4 3.9 100.0 7,248 16.8 77.3 0.2 5.7 100.0 10,873 50-59 na na na na na na 21.5 75.3 0.4 2.7 100.0 1,044 Total 15-59 na na na na na na 17.2 77.1 0.3 5.4 100.0 11,917 Note: Figures in parentheses are based on 25-49 unweighted cases. An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. na = Not applicable Female Genital Mutilation/Cutting • 327 Table 16.9 Opinions of women and men about whether the practice of circumcision should continue Percent distribution of women age 15-49 and men age 15-59 who have heard of female circumcision by their opinion on whether the practice of circumcision should be continued, according to background characteristics, Ethiopia DHS 2016 Women Men Background characteristic Continued Not continued Don’t know/ depends Total Number of women who have heard of female circum- cision Continued Not continued Don’t know/ depends Total Number of men who have heard of female circum- cision Female circumcision status Circumcised 22.9 74.2 2.9 100.0 5,101 na na na na na Not circumcised 4.6 91.5 4.0 100.0 2,147 na na na na na Age 15-19 13.6 85.1 1.3 100.0 1,523 10.4 86.8 2.8 100.0 2,261 20-24 14.8 83.1 2.1 100.0 1,194 9.8 86.7 3.5 100.0 1,764 25-29 19.1 76.9 4.0 100.0 1,356 11.2 87.3 1.5 100.0 1,887 30-34 18.9 77.0 4.1 100.0 1,124 10.8 87.3 1.9 100.0 1,566 35-39 21.4 75.0 3.5 100.0 939 12.1 85.6 2.3 100.0 1,322 40-44 16.5 80.3 3.3 100.0 610 9.8 88.4 1.8 100.0 1,160 45-49 21.7 71.2 7.1 100.0 502 15.5 82.8 1.8 100.0 913 Religion Orthodox 12.4 83.0 4.6 100.0 3,157 12.0 85.7 2.4 100.0 4,755 Catholic (21.2) (75.0) (3.8) 100.0 52 0.3 97.1 2.6 100.0 66 Protestant 13.0 85.3 1.6 100.0 1,674 4.7 93.7 1.6 100.0 2,383 Muslim 27.5 69.9 2.6 100.0 2,288 14.5 82.9 2.6 100.0 3,533 Traditional * * * 100.0 55 * * * 100.0 20 Other * * * 100.0 22 8.2 87.7 4.1 100.0 115 Ethnic group Affar 68.3 30.5 1.2 100.0 55 43.3 54.9 1.7 100.0 63 Amhara 14.8 80.1 5.1 100.0 2,204 15.8 81.7 2.5 100.0 3,278 Guragie 14.6 84.2 1.2 100.0 201 5.0 93.9 1.2 100.0 304 Hadiya 13.5 85.3 1.2 100.0 182 6.6 91.7 1.7 100.0 212 Oromo 19.4 78.1 2.4 100.0 2,584 8.3 89.6 2.1 100.0 4,058 Sidama 27.8 72.2 0.0 100.0 319 7.2 90.6 2.2 100.0 478 Somali 51.4 48.1 0.5 100.0 220 33.4 65.8 0.8 100.0 296 Tigray 7.3 89.3 3.4 100.0 490 12.3 83.0 4.8 100.0 659 Welaita 21.7 77.6 0.7 100.0 228 2.5 96.4 1.0 100.0 303 Others 7.6 87.8 4.5 100.0 767 5.7 92.2 2.1 100.0 1,222 Residence Urban 7.3 91.4 1.3 100.0 1,665 6.0 92.8 1.1 100.0 2,257 Rural 20.5 75.7 3.8 100.0 5,583 12.4 85.0 2.6 100.0 8,616 Region Tigray 7.9 88.5 3.5 100.0 462 13.0 81.7 5.3 100.0 589 Affar 54.8 44.0 1.2 100.0 67 36.0 62.3 1.7 100.0 81 Amhara 16.7 77.4 5.9 100.0 1,702 18.8 78.1 3.1 100.0 2,699 Oromiya 19.2 77.7 3.1 100.0 2,748 7.7 90.1 2.2 100.0 4,307 Somali 52.2 47.3 0.5 100.0 228 34.2 65.1 0.7 100.0 298 Benishangul-Gumuz 9.7 89.2 1.0 100.0 68 12.1 86.7 1.2 100.0 104 SNNPR 15.6 82.8 1.6 100.0 1,433 5.0 93.7 1.3 100.0 2,106 Gambela 7.6 89.8 2.6 100.0 16 5.5 92.1 2.4 100.0 27 Harari 15.9 81.3 2.8 100.0 18 22.0 75.0 3.0 100.0 28 Addis Ababa 3.7 95.4 0.8 100.0 461 3.1 96.0 0.9 100.0 570 Dire Dawa 24.2 72.5 3.3 100.0 45 17.6 78.6 3.8 100.0 65 Education No education 24.9 69.6 5.5 100.0 3,406 18.8 77.9 3.3 100.0 2,911 Primary 14.6 83.7 1.7 100.0 2,505 10.3 87.2 2.5 100.0 5,205 Secondary 5.3 94.3 0.4 100.0 889 4.9 94.4 0.6 100.0 1,751 More than secondary 1.2 98.5 0.3 100.0 448 3.3 95.6 1.1 100.0 1,006 Wealth quintile Lowest 33.6 62.2 4.2 100.0 1,127 18.8 77.9 3.3 100.0 1,660 Second 21.7 73.7 4.6 100.0 1,284 14.2 83.4 2.4 100.0 1,968 Middle 17.8 79.2 3.0 100.0 1,408 12.8 84.4 2.8 100.0 2,076 Fourth 14.4 82.1 3.5 100.0 1,445 8.6 89.3 2.2 100.0 2,308 Highest 7.5 90.7 1.8 100.0 1,984 5.2 93.4 1.4 100.0 2,861 Total 15-49 17.5 79.3 3.2 100.0 7,248 11.1 86.7 2.3 100.0 10,873 50-59 na na na na na 14.1 83.3 2.6 100.0 1,044 Total 15-59 na na na na na 11.3 86.4 2.3 100.0 11,917 Note: Figures in parentheses are based on 25-49 unweighted cases. An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. na = Not applicable References • 329 REFERENCES Central Statistical Agency [Ethiopia] and ORC Macro. 2001. Ethiopia Demographic and Health Survey 2000. Addis Ababa, Ethiopia, and Calverton, Maryland, USA: Central Statistical Agency and ORC Macro. Central Statistical Agency [Ethiopia] and ORC Macro. 2006. Ethiopia Demographic and Health Survey 2005. Addis Ababa, Ethiopia, and Calverton, Maryland, USA: Central Statistical Agency and ORC Macro. Central Statistical Agency [Ethiopia] and ICF International. 2012. Ethiopia Demographic and Health Survey 2011. Addis Ababa, Ethiopia and Calverton, Maryland, USA: Central Statistical Agency and ICF International. Ethiopian Public Health Institute (EPHI). 2017. HIV and AIDS Estimation and Projection for Ethiopia Based on SPECTRUM Modeling. Addis Ababa, Ethiopia: EPHI. Federal Democratic Republic of Ethiopia (FDRE). 2008. 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Federal Ministry of Health (FMOH) [Ethiopia]. 2015. Health Sector Transformation Plan, 2015/16 – 2019/20. Addis Ababa, Ethiopia: FMOH. Graham, W., W. Brass, and R. W. Snow. 1989. “Indirect Estimation of Maternal Mortality: The Sisterhood Method.” Studies in Family Planning 20(3): 125-135. doi:10.2307/1966567. HFG. 2015. Ethiopia’s Community-based Health Insurance: A Step on the Road to Universal Health Coverage. http://pdf.usaid.gov/pdf_docs/PA00KDXT.pdf. Holder, Y., M. Peden, E. Krug, J. Lund, J. Gururaj, and O. Kobusingye, eds. 2001. Injury Surveillance Guidelines. Geneva: WHO. Joint United Nations Programme on HIV/AIDS. 2014. Elimination of Mother to Child Transmission Five Years Strategic Plan (2015-2020). Addis Ababa, Ethiopia: Federal Ministry of Health. 330 • References Miller, Nathan P., Agbessi Amouzou, Mengistu Tafesse, Elizabeth Hazel, Hailemariam Legesse, Tedbabe Degefie, Cesar G. Victora, Robert E. Black, and Jennifer Bryce. 2014. “Integrated Community Case Management of Childhood Illness in Ethiopia: Implementation Strength and Quality of Care.” The American Journal of Tropical Medicine and Hygiene 13:751. Ministry of Women, Children, and Youth Affairs (MOWCYA). 2017. National Women Development and Change Strategy. http://www.mowcya.gov.et/web/guest/Package. MOWCYA. Negrato, Carlos Antonio, and Marilia Brito Gomes. 2013. “LowBirth Weight: Causes and Consequences.” Diabetology & Metabolic Syndrome 5(1): 49. Rutenberg, N., and J. Sullivan. 1991. “Direct and Indirect Estimates of Maternal Mortality from the Sisterhood Method.” Proceedings of the Demographic and Health Surveys World Conference 3: 16691696. Columbia, Maryland, USA: IRD/Macro International Inc. Stanton, C., N. Abderrahim, and K. Hill. 1997. DHS Maternal Mortality Indicators: An Assessment of Data Quality and Implications for Data Use. DHS Analytical Reports No. 4. Calverton, Maryland, USA: Macro International Inc. UN Women. 2016. Shelters for Women and Girls Who Are Survivors of Violence in Ethiopia. Addis Ababa, Ethiopia: UN Women. United Nations. 2006. Secretary-General’s In-depth Study on All Forms of Violence against Women. New York, USA: United Nations. World Health Organization (WHO) and UNICEF. 2013. Ending Preventable Child Deaths from Pneumonia and Diarrhoea by 2025: The Integrated Global Action Plan for Pneumonia and Diarrhoea (GAPPD). Geneva, Switzerland: WHO and UNICEF. World Health Organization (WHO). 2008. Indicators for Assessing Infant and Young Child Feeding Practices. Geneva, Switzerland: WHO. World Health Organization (WHO). 2014. CHERG-WHO Methods and Data Sources for Child Causes of Death 2000-2012. Global Health Estimates Technical Paper. WHO/HIS/HSI/GHE. World Health Organization (WHO). 2014. Injuries and Violence: The Facts 2014. http://apps.who.int/iris/bitstream/10665/149798/1/9789241508018_eng.pdf. Geneva, Switzerland: WHO. World Health Organization (WHO). 2016. Consolidated Guidelines on the Use of Antiretroviral Drugs for Treating and Preventing HIV Infection: Recommendations for a Public Health Approach. 2d ed. Geneva, Switzerland: WHO. http://apps.who.int/iris/bitstream/10665/208825/1/9789241549684_eng.pdf. Appendix A • 331 SAMPLE DESIGN Appendix A A.1 INTRODUCTION he 2016 Ethiopia Demographic and Health Survey (2016 EDHS) is the fourth in a series of Demographic and Health Surveys conducted in Ethiopia in 2000, 2005, and 2011. The main objective of the 2016 EDHS is to provide up-to-date information on fertility and childhood mortality levels; fertility preferences; awareness, approval, and use of family planning methods; maternal and child health; domestic violence; knowledge and attitudes toward HIV/AIDS and other sexually transmitted infections (STI); and prevalence of HIV among the adult population. All women age 15-49 and men age 15-59 who are the usual members of the selected households and those who spent the night before the survey in the selected households are eligible to be interviewed in the survey. All women and men who are eligible for the survey and all children under age 5 are eligible for height and weight measurements. All women and men who are eligible for the survey and all children age 6-59 months are eligible for anaemia testing. All women and men who are eligible for the survey are eligible for HIV testing. In half of the selected households, women were eligible for the interviews on domestic violence (DV) and female genital mutilation. In this subsample, one woman per each household was randomly selected for the DV module, while all women were interviewed with the female genital mutilation module. The sample for the 2016 EDHS is designed to provide estimates of population and health indicators that include fertility and mortality rates for the country as a whole, the urban and rural areas separately, and each of the 11 regions in Ethiopia. A.2 SAMPLING FRAME The sampling frame used for the 2016 EDHS is the frame of the Population and Housing Census (PHC) conducted in Ethiopia in 2007 and provided by the Central Statistical Agency (CSA). The census frame is a complete list of all census enumeration areas (EA) created for the 2007 PHC. An EA is a geographic area that covers an average of 181 households. The sampling frame contains information about the EA location, type of residence (urban or rural), and the estimated number of residential households. Except for the Somali Region, a sketch map that delineates the EA geographic boundaries is available for each EA. In Somali, a cartographic frame was used in three of the region’s nine zones, where a sketch map that delineates the EA geographic boundaries is available for each EA. In the other six zones, the satellite frame was used, where a satellite map is available for each EA. Administratively, Ethiopia is divided into 11 geographical regions. Each region is sub-divided into zones, each zone into woredas, each woreda into towns, and each town into kebeles. The sample is designed to provide estimates in 11 regions for most health and demographic indicators. Table A.1 indicates the percentage distribution of households by region and type of residence. The table indicates that about 82% of the Ethiopia’s households are concentrated in three regions: Amhara, Oromiya and SNNP, while about 4% of households are in the five smallest regions: Affar, Benishangul-Gumuz, Gambela, Harari, and Dire Dawa. The region size varies from 0.30% (Harari, the smallest) to 36.23% (Oromiya, the largest). In Ethiopia, 19.77% of the households are in urban areas. Other than Addis Ababa, which is predominantly urban, the percentage of urban areas varies greatly from 11.84% in the SNNP Region to 71.02% in Dire Dawa. T 332 • Appendix A Table A.1 Distribution of residential households Distribution of residential households in the sampling frame by region and type of residence; the percentage that each region contributes to the total number of households, and percentage of each district that is urban, Ethiopia DHS 2016 Number of residential households Percentage district contributes to the total number of households Percentage of district that is urban Region Urban Rural Total Tigray 241,947 749,342 991,289 6.43% 24.41% Affar 46,455 187,745 234,200 1.52% 19.84% Amhara 626,998 3,348,277 3,975,275 25.79% 15.77% Oromiya 884,518 4,699,858 5,584,376 36.23% 15.84% Somali 93,518 425,270 518,788 3.37% 18.03% Benishangul-Gumuz 28,676 144,363 173,039 1.12% 16.57% SNNP 366,571 2,729,671 3,096,242 20.09% 11.84% Gambela 19,811 39,074 58,885 0.38% 33.64% Harari 28,552 18,191 46,743 0.30% 61.08% Addis Ababa 655,977 655,977 4.26% 100.00% Dire Dawa 54,505 22,240 76,745 0.50% 71.02% Ethiopia 3,047,528 12,364,031 15,411,559 100.00% 19.77% Source: The 2007 Population and Housing Census (PHC) Sampling frame provided by the Central Statistical Agency (CSA). Table A.2 indicates the distribution of EAs and their average size in number of households by region and type of residence. There are a total of 84,915 EAs; among them, 17,185 are in urban areas and 67,730 in rural areas. The sampling frame excluded some special EAs with disputed boundaries. These EAs represent only 0.1% of the total population. The average EA size is 181 households; the urban EAs have a smaller size, with an average of 177 households per EA, while the rural EAs have an average of 183 households per EA. The EA size is an adequate size for the primary sampling unit (PSU) with a sample take of 28 households per EA. Table A.2 Enumeration areas and households Distribution of enumeration areas (EAs) and average number of households in a EA by region, according to residence, Ethiopia DHS 2016 Number of EAs Average EA size Region Urban Rural Total Urban Rural Total Tigray 1,484 4,098 5,582 163 183 178 Affar 245 774 1,019 190 243 230 Amhara 3,300 17,827 21,127 190 188 188 Oromiya 4,909 25,274 30,183 180 186 185 Somali 689 4,170 4,859 136 102 107 Benishangul-Gumuz 171 781 952 168 185 182 SNNP 2,058 14,310 16,368 178 191 189 Gambela 127 273 400 156 143 147 Harari 167 95 262 171 191 178 Addis Ababa 3,722 0 3,722 176 176 Dire Dawa 313 128 441 174 174 174 Ethiopia 17,185 67,730 84,915 177 183 181 Source: The 2007 Population and Housing Census (PHC) Sampling frame provided by the Central Statistical Agency (CSA). Appendix A • 333 A.3 SAMPLE DESIGN AND SELECTION The 2016 EDHS sample is stratified and was selected in two stages. Each region was stratified into urban and rural areas, which yielded 21 sampling strata. Samples of EAs were selected independently in each stratum in two stages. Implicit stratification and proportional allocation were achieved at each of the lower administrative levels by sorting the sampling frame within each sampling stratum before sample selection, according to administrative units in different levels, and by using a probability proportional to size selection at the first stage of sampling. In the first stage, 645 EAs were selected with probability proportional to the EA size and with independent selection in each sampling stratum with the sample allocation given in Table A.3. The EA size is the number of residential households in the EA as determined in the 2007 PHC. A household listing operation was implemented in the selected EAs, and the resulting lists of households served as the sampling frame for the selection of households in the second stage. Some of the selected EAs were large. To minimize the task of household listing, the selected large EAs with more than 200 households were segmented. Only one segment was selected for the survey with probability proportional to the segment size. Household listing was conducted only in the selected segment. Thus, a 2016 EDHS cluster is either an EA or a segment of an EA. In the second stage of selection, a fixed number of 28 households per cluster were selected with an equal probability systematic selection from the newly created household listing. The survey interviewer interviewed only the pre-selected households. No replacements or changes of the pre-selected households were allowed in the implementing stages to prevent bias. All women aged 15-49 who are usual members of the selected households or who spent the night before the survey in the selected households were eligible for the female survey. All men aged 15-59 who were usual members of the households or who spent the night before the survey in the households were eligible for the male survey. Table A.3 shows the allocation of selected households according to regions and urban-rural areas. Table A.4 shows the expected number of completed women and men interviews according to region and urban- rural areas. To ensure that the survey precision is comparable across regions, the sample allocation figures a power allocation between regions and between different types of residence within each region. Based on a fixed sample take of 28 households per cluster, the survey selected 645 EAs, 202 in urban areas and 443 in rural areas. The survey was conducted in 16,650 residential households, 5,232 in urban areas and 11,418 in rural areas. The sample was expected to generate an estimated 16,663 completed interviews with women age 15-49, 5,514 in urban areas and 11,149 in rural areas, and 14,195 completed interviews with men age 15-59, with 4,472 in urban areas and 9,723 in rural areas. Table A.3 Sample allocation of clusters and households Sample allocation of clusters and households by region, according to residence, Ethiopia DHS 2016 Number of clusters allocated Number of households allocated Region Urban Rural Total Urban Rural Total Tigray 15 48 63 420 1,344 1,764 Affar 9 44 53 252 1,232 1,484 Amhara 11 60 71 308 1,680 1,988 Oromiya 10 64 74 280 1,792 2,072 Somali 13 56 69 364 1,568 1,932 Benishangul-Gumuz 7 43 50 196 1,204 1,400 SNNP 8 63 71 224 1,764 1,988 Gambela 15 35 50 420 980 1,400 Harari 26 18 44 728 504 1,232 Addis Ababa 56 56 1,568 1,568 Dire Dawa 32 12 44 896 336 1,232 Ethiopia 202 443 645 5,656 12,404 18,060 334 • Appendix A Table A.4 Sample allocation of expected number of completed interviews with women and men Sample allocation of expected number of completed interviews with women age 15-49 and men 15-54 by region, according to residence, Ethiopia DHS 2016 Expected number of interviews with women age 15-49 Expected number of interviews with men age 15-59 Region Urban Rural Total Urban Rural Total Tigray 434 1,268 1,702 361 1,092 1,453 Affar 242 1,081 1,323 201 930 1,131 Amhara 313 1,560 1,873 266 1,370 1,636 Oromiya 289 1,692 1,981 251 1,522 1,773 Somali 328 1,291 1,619 261 1,062 1,323 Benishangul-Gumuz 191 1,076 1,267 164 957 1,121 SNNP 224 1,612 1,836 195 1,450 1,645 Gambela 381 812 1,193 321 709 1,030 Harari 721 457 1,178 582 381 963 Addis Ababa 1,519 1,519 1,167 1,167 Dire Dawa 872 300 1,172 703 250 953 Ethiopia 5,514 11,149 16,663 4,472 9,723 14,195 The sample allocations were derived with information obtained from the 2011 EDHS; the average number of women age 15-49 per household is 1.10 in urban areas and 1.01 in rural areas, and the average number of men age 15-59 per household is 0.99 in urban areas and 0.93 in rural areas. Tables A.5 and A.6 indicate the regional-level household response rates, as well as individual response rates for women and men. A pp en di x A • 3 35 Ta bl e A .5 S am pl e im pl em en ta ti o 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) , E th io pi a D H S 2 01 6 R es id en ce R eg io n T ot al R es ul t U rb an R ur al T ig ra y A ffa r A m ha ra O ro m iy a S om al i B en is ha ng ul - G um uz S N N P R G am be la H ar ar i A dd is A ba ba D ire D aw a S el ec te d ho u se ho ld s C om pl et ed ( C ) 92 .5 92 .5 98 .2 82 .2 95 .6 95 .9 83 .4 91 .4 95 .4 91 .4 92 .1 94 .8 94 .2 92 .5 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 ) 2. 0 1. 2 0. 3 2. 7 0. 9 0. 3 2. 0 2. 3 0. 9 2. 0 2. 5 1. 2 2. 6 1. 5 P os tp on ed ( P ) 0. 1 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 1 0. 0 0. 1 0. 0 0. 0 0. 1 0. 0 R ef us ed ( R ) 0. 8 0. 4 0. 3 0. 2 0. 0 0. 9 0. 7 1. 3 0. 2 0. 1 0. 6 1. 0 0. 4 0. 5 D w el lin g no t f ou nd ( D N F) 0. 3 0. 3 0. 0 0. 0 0. 0 0. 4 2. 1 0. 0 0. 1 0. 2 0. 2 0. 1 0. 1 0. 3 H ou se ho ld a bs en t ( H A ) 1. 1 2. 6 0. 4 6. 7 0. 7 1. 0 6. 4 1. 8 2. 3 1. 9 1. 5 0. 4 0. 6 2. 2 D w el lin g va ca nt /a dd re ss n ot a dw el lin g (D V ) 2. 3 1. 3 0. 6 1. 6 2. 0 0. 8 2. 3 2. 3 0. 8 2. 1 2. 4 2. 0 1. 3 1. 6 D w el lin g de st ro ye d (D D ) 0. 5 1. 2 0. 1 4. 9 0. 3 0. 4 2. 7 0. 7 0. 4 1. 1 0. 2 0. 3 0. 4 1. 0 O th er ( O ) 0. 4 0. 4 0. 1 1. 6 0. 6 0. 1 0. 5 0. 1 0. 1 1. 0 0. 6 0. 3 0. 2 0. 4 T ot al 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 10 0. 0 N um be r of s am pl ed h ou se ho ld s 5, 65 9 12 ,3 49 1, 76 5 1, 48 4 1, 98 9 2, 07 2 1, 87 6 1, 40 0 1, 98 8 1, 40 0 1, 23 2 1, 57 0 1, 23 2 18 ,0 08 H ou se ho ld r es po ns e ra te (H R R )1 96 .7 98 .0 99 .4 96 .6 99 .1 98 .2 94 .6 96 .2 98 .9 97 .4 96 .6 97 .7 96 .8 97 .6 E lig ib le w om en C om pl et ed ( E W C ) 93 .5 95 .1 96 .6 94 .9 98 .0 95 .7 93 .5 95 .7 96 .3 89 .6 90 .1 92 .2 94 .5 94 .6 N ot a t h om e (E W N H ) 3. 8 3. 3 1. 4 4. 1 0. 9 2. 1 4. 3 1. 9 2. 9 8. 6 7. 9 4. 2 3. 9 3. 5 P os tp on ed ( E W P ) 0. 0 0. 0 0. 0 0. 0 0. 0 0. 1 0. 0 0. 0 0. 1 0. 0 0. 0 0. 0 0. 0 0. 0 R ef us ed ( E W R ) 2. 1 0. 7 1. 2 0. 3 0. 1 1. 4 1. 2 1. 2 0. 6 1. 1 1. 5 2. 8 1. 3 1. 2 In ca pa ci ta te d (E W I) 0. 3 0. 7 0. 7 0. 5 0. 7 0. 6 0. 7 0. 8 0. 2 0. 5 0. 5 0. 5 0. 2 0. 5 O th er ( E W O ) 0. 2 0. 2 0. 1 0. 2 0. 3 0. 1 0. 3 0. 4 0. 0 0. 2 0. 0 0. 3 0. 2 0. 2 T ot al 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 10 0. 0 N um be r of w om en 5, 72 0 10 ,8 63 1, 74 1 1, 18 9 1, 75 4 1, 97 8 1, 48 8 1, 17 7 1, 92 1 1, 15 5 1, 00 5 1, 97 8 1, 19 7 16 ,5 83 E lig ib le w om en re sp on se r at e (E W R R )2 93 .5 95 .1 96 .6 94 .9 98 .0 95 .7 93 .5 95 .7 96 .3 89 .6 90 .1 92 .2 94 .5 94 .6 O ve ra ll w om en r es po ns e ra te (O R R )3 90 .4 93 .2 96 .0 91 .6 97 .1 94 .0 88 .4 92 .0 95 .1 87 .3 87 .1 90 .1 91 .4 92 .3 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 r es po ns e ca te go rie s, th e ho us eh ol d re sp on se r at e (H R R ) i s ca lc ul at ed a s: 10 0 * C — — — — — — — — — — C + H P + P + R + D N F 2 T he e lig ib le w om en r es po ns e 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 T he o ve ra ll w om en r es po ns e 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 33 6 • A pp en di x A Ta bl e A .6 S am pl e im pl em en ta ti o 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) , E th io pi a D H S 2 01 6 R es id en ce R eg io n T ot al R es ul t U rb an R ur al T ig ra y A ffa r A m ha ra O ro m iy a S om al i B en is ha ng ul - G um uz S N N P R G am be la H ar ar i A dd is A ba ba D ire D aw a S el ec te d ho u se ho ld s C om pl et ed ( C ) 92 .3 92 .8 98 .3 83 .0 95 .5 95 .9 84 .0 91 .9 95 .1 91 .6 92 .0 95 .8 94 .3 92 .7 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 ) 2. 3 1. 1 0. 3 2. 7 0. 8 0. 5 1. 7 2. 6 1. 1 2. 1 2. 4 1. 0 2. 6 1. 5 P os tp on ed ( P ) 0. 1 0. 0 0. 0 0. 0 0. 0 0. 1 0. 0 0. 1 0. 0 0. 0 0. 0 0. 0 0. 2 0. 0 R ef us ed ( R ) 0. 8 0. 4 0. 1 0. 0 0. 0 1. 0 1. 0 1. 0 0. 4 0. 0 0. 8 0. 6 0. 6 0. 5 D w el lin g no t f ou nd ( D N F) 0. 2 0. 2 0. 0 0. 0 0. 0 0. 5 1. 5 0. 0 0. 0 0. 0 0. 2 0. 0 0. 0 0. 2 H ou se ho ld a bs en t ( H A ) 1. 2 2. 6 0. 6 6. 3 0. 9 0. 7 6. 3 1. 9 2. 3 2. 3 1. 6 0. 1 0. 6 2. 2 D w el lin g va ca nt /a dd re ss n ot a dw el lin g (D V ) 2. 3 1. 2 0. 7 1. 8 1. 7 1. 0 2. 3 1. 9 0. 6 1. 7 2. 6 2. 0 1. 0 1. 5 D w el lin g de st ro ye d (D D ) 0. 5 1. 3 0. 0 4. 7 0. 5 0. 4 2. 8 0. 6 0. 4 1. 1 0. 0 0. 3 0. 6 1. 0 O th er ( O ) 0. 3 0. 4 0. 0 1. 5 0. 6 0. 0 0. 4 0. 1 0. 1 1. 1 0. 3 0. 1 0. 0 0. 4 T ot al 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 10 0. 0 N um be r of s am pl ed h ou se ho ld s 2, 82 9 6, 17 4 88 2 74 2 99 4 1, 03 6 93 8 70 0 99 4 70 0 61 6 78 5 61 6 9, 00 3 H ou se ho ld r es po ns e ra te (H R R )1 96 .5 98 .2 99 .5 96 .9 99 .2 97 .9 95 .3 96 .1 98 .4 97 .7 96 .4 98 .3 96 .5 97 .6 E lig ib le m en C om pl et ed ( E M C ) 80 .2 88 .0 90 .2 76 .1 96 .1 88 .4 81 .4 88 .8 89 .3 80 .2 72 .0 81 .1 83 .9 85 .4 N ot a t h om e (E M N H ) 14 .6 9. 6 5. 7 21 .9 2. 9 7. 2 16 .0 8. 9 8. 7 16 .6 23 .1 12 .9 12 .2 11 .2 P os tp on ed ( E M P ) 0. 0 0. 1 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 6 0. 0 0. 0 0. 0 0. 0 R ef us ed ( E M R ) 3. 6 1. 5 2. 4 1. 4 0. 2 3. 6 1. 8 2. 0 1. 1 1. 7 1. 9 4. 6 3. 3 2. 2 P ar tly c om pl et ed (E M P C ) 0. 0 0. 0 0. 0 0. 0 0. 1 0. 0 0. 0 0. 0 0. 0 0. 0 0. 2 0. 0 0. 0 0. 0 In ca pa ci ta te d (E M I) 1. 1 0. 7 1. 4 0. 2 0. 7 0. 7 0. 0 0. 4 0. 9 0. 9 2. 7 0. 9 0. 5 0. 8 O th er ( E M O ) 0. 4 0. 1 0. 3 0. 4 0. 0 0. 1 0. 8 0. 0 0. 0 0. 0 0. 2 0. 5 0. 2 0. 2 T ot al 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 10 0. 0 N um be r of m en 2, 43 3 4, 99 9 70 2 48 5 86 6 93 6 60 8 56 0 88 8 53 6 48 5 78 2 58 4 7, 43 2 E lig ib le m en r es po ns e ra te (E M R R )2 80 .2 88 .0 90 .2 76 .1 96 .1 88 .4 81 .4 88 .8 89 .3 80 .2 72 .0 81 .1 83 .9 85 .4 O ve ra ll m en r es po ns e ra te (O R R )3 77 .4 86 .3 89 .8 73 .7 95 .3 86 .5 77 .6 85 .3 87 .9 78 .4 69 .4 79 .7 81 .0 83 .4 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 r es po ns e ca te go rie s, th e ho us eh ol d re sp on se r at e (H R R ) i s ca lc ul at ed a s: 10 0 * C — — — — — — — — — — C + H P + P + R + D N F 2 T he e lig ib le m en r es po ns e 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 T he o ve ra ll m en re sp on se r at e (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 • 337 A.4 SAMPLING WEIGHTS Due to the non-proportional allocation of the sample to different regions and their urban and rural areas and the possible differences in response rates, a sampling weight must be used in all analyses using the 2016 EDHS data to ensure the actual representative of the survey results at both the national and domain levels. Since the 2016 EDHS sample is a two-stage stratified cluster sample, sampling weights are based on sampling probabilities separately for each sampling stage and each cluster. We use the following notations: P1hi: first-stage sampling probability of the ith cluster in stratum h P2hi: second-stage sampling probability within the ith cluster (households) Let ah be the number of EAs selected in stratum h, Mhi the number of households according to the sampling frame in the ith EA, and M hi the total number of households in the stratum. The probability of selecting the ith EA in the 2016 EDHS sample is calculated as: M M a hi hih  Let hib be the proportion of households in the selected cluster compared to the total number of households in EA i in stratum h if the EA is segmented, otherwise 1hib . Then the probability of selecting cluster i in the sample is: hi hi hih 1hi b M M a = P   Let hi L be the number of households listed in the household listing operation in cluster i in stratum h, let hig be the number of households selected in the cluster. The second stage’s selection probability for each household in the cluster is calculated as: hi hi hi L g P 2 The overall selection probability of each household in cluster i of stratum h is therefore the production of the two stages selection probabilities: hihihi PPP 21  The sampling 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 sampling parameters and selection probabilities was prepared to facilitate the calculation of the design weight. The design weight was adjusted for household non-response and as well as individual non-response to obtain the sampling weights for households, and for the women and men surveys respectively. The differences of the household sampling weight and the individual sampling weights are introduced by individual non-response. The final sampling weights were normalized to give the total number of unweighted cases equal to the total number of weighted cases at the national level, for 338 • Appendix A both household weight and individual weight, respectively. The normalized weights are relative weights that are valid for estimating means, proportions, and ratios, but not valid for estimating the population totals and for pooled data. Appendix B • 339 ESTIMATES OF SAMPLING ERRORS Appendix B he estimates 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 the questions by either the interviewer or the respondent, and data entry errors. Although numerous efforts were made during the implementation of the 2016 Ethiopia DHS (EDHS) to minimise this type of error, non-sampling errors are impossible to avoid and are difficult to evaluate statistically. Sampling errors, on the other hand, can be evaluated statistically. The sample of respondents selected in the 2016 EDHS is only one of many samples that could have been selected from the same population, by using the same design and the expected size. Each of those 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 (such as mean or percentage), 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% 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 2016 EDHS 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, with programs developed by ICF International. These programs use the Taylor linearisation 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 linearisation method treats any percentage or average as a ratio estimate, r = y x , where y represents the total sample value for variable y, and x represents the total number of cases in the group or subgroup under consideration. The variance of r is computed with the formula 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, T 340 • Appendix B 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 with simple formulae. Each replication considers all but one cluster in the calculation of the estimates. Pseudo-independent replications are thus created. In the 2016 EDHS, there were 643 non-empty clusters. Hence, 643 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 643 clusters, r(i) is the estimate computed from the reduced sample of 642 clusters (ith 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 with the given sample design and the standard error that would result if a simple random sample had been used. A DEFT value of 1.0 indicates that the sample design is as efficient as a simple random sample, while a value greater than 1.0 indicates that the increase in the sampling error is due to the use of a more complex, less statistically efficient design. Relative standard errors and confidence limits for the estimates are also calculated. Sampling errors for the 2016 EDHS are calculated for selected variables considered to be of primary interest. The results are presented in this appendix for the country as a whole, urban and rural areas, and each of the 11 regions. For each variable, the type of statistic (mean, proportion, or rate) and the base population are given in Table B.1. Tables B.2 through B.15 present the value of the statistic (R), its standard error (SE), the number of un-weighted (N) and weighted (WN) cases, the design effect (DEFT), the relative standard error (SE/R), and the 95% confidence limits (R±2SE), for each selected variable. The DEFT is considered undefined when the standard error of a simple random sample is zero (when the estimate is close to 0 or 1). The confidence interval (as calculated for the number of children ever born for women 40-49 years) can be interpreted as: the overall average from the national sample is 6.359 and its standard error is 0.088. Therefore, to obtain the 95% confidence limits, one adds and subtracts twice the standard error to the sample estimate, which is 6.359 ± 2×0.088. There is a high probability (95%) that the true proportion of women age 40-49 with children ever born is between 6.183 and 6.535. For the total sample, the value of the DEFT, averaged over all variables, is 1.99. This means that, due to multi-stage clustering of the sample, the average standard error is increased by a factor of 1.99 beyond that in an equivalent simple random sample. Appendix B • 341 Table B.1 Sampling errors: Total sample, Ethiopia DHS 2016 Value (R) Standard error (SE) Number of cases Design effect (DEFT) Relative Error (SE/R) Confidence limits Variable Un- weighted (N) Weighted (WN) Lower (R-2SE) Upper (R+2SE) WOMEN Urban residence 0.222 0.009 15,683 15,683 2.735 0.041 0.203 0.240 Literacy 0.420 0.010 15,683 15,683 2.658 0.025 0.399 0.441 No education 0.478 0.011 15,683 15,683 2.658 0.022 0.457 0.499 Secondary or higher education 0.172 0.008 15,683 15,683 2.630 0.046 0.156 0.188 Never married (never in union) 0.257 0.007 15,683 15,683 2.091 0.028 0.243 0.272 Currently married (in union) 0.652 0.007 15,683 15,683 1.936 0.011 0.637 0.667 Married before age 20 0.687 0.008 12,185 12,302 2.006 0.012 0.670 0.704 Had sexual intercourse before age 18 0.580 0.010 12,185 12,302 2.268 0.017 0.560 0.601 Currently pregnant 0.072 0.004 15,683 15,683 1.749 0.050 0.065 0.080 Children ever born 2.844 0.048 15,683 15,683 2.058 0.017 2.748 2.939 Children surviving 2.511 0.042 15,683 15,683 2.055 0.017 2.428 2.594 Children ever born to women age 40-49 6.359 0.088 2,279 2,306 1.522 0.014 6.183 6.535 Currently using any method 0.359 0.013 9,824 10,223 2.617 0.035 0.334 0.384 Currently using a modern method 0.353 0.013 9,824 10,223 2.613 0.036 0.327 0.378 Currently using pill 0.018 0.002 9,824 10,223 1.537 0.113 0.014 0.023 Currently using IUD 0.020 0.003 9,824 10,223 2.033 0.142 0.015 0.026 Currently using condoms 0.001 0.000 9,824 10,223 0.644 0.277 0.000 0.001 Currently using injectables 0.228 0.010 9,824 10,223 2.411 0.045 0.207 0.248 Currently using implants 0.079 0.006 9,824 10,223 2.045 0.070 0.068 0.090 Currently using female sterilisation 0.004 0.001 9,824 10,223 1.365 0.212 0.002 0.006 Using public sector source 0.838 0.012 3,203 3,884 1.849 0.014 0.814 0.862 Want no more children 0.367 0.010 9,824 10,223 1.970 0.026 0.348 0.387 Want to delay next birth at least 2 years 0.357 0.009 9,824 10,223 1.901 0.026 0.339 0.376 Ideal number of children 4.452 0.062 13,941 14,005 2.661 0.014 4.328 4.577 Mothers received antenatal care for last birth 0.624 0.015 7,193 7,590 2.637 0.024 0.594 0.653 Mothers protected against tetanus for last birth 0.490 0.014 7,193 7,590 2.424 0.029 0.462 0.519 Births with skilled attendant at delivery 0.277 0.015 10,641 11,023 3.023 0.053 0.247 0.307 Had diarrhoea in the last 2 weeks 0.118 0.006 10,006 10,417 1.876 0.054 0.105 0.130 Treated with ORS 0.295 0.019 1,090 1,227 1.400 0.065 0.257 0.334 Sought medical treatment for diarrhoea 0.444 0.024 1,090 1,227 1.617 0.054 0.396 0.492 Vaccination card seen 0.341 0.021 1,929 2,004 1.957 0.063 0.299 0.384 Received BCG vaccination 0.692 0.019 1,929 2,004 1.764 0.027 0.654 0.729 Received DPT vaccination (3 doses) 0.532 0.022 1,929 2,004 1.900 0.041 0.488 0.575 Received polio vaccination (3 doses) 0.564 0.021 1,929 2,004 1.804 0.036 0.523 0.605 Received pneumococcal vaccination (3 doses) 0.491 0.021 1,929 2,004 1.793 0.042 0.450 0.532 Received rotavirus vaccination (2 doses) 0.560 0.020 1,929 2,004 1.778 0.036 0.519 0.600 Received measles vaccination 0.543 0.021 1,929 2,004 1.838 0.039 0.501 0.585 Received all vaccinations 0.385 0.021 1,929 2,004 1.895 0.055 0.343 0.428 Height-for-age (-2SD) 0.384 0.010 9,471 10,376 1.919 0.025 0.364 0.403 Weight-for-height (-2SD) 0.099 0.005 9,444 10,356 1.560 0.048 0.090 0.109 Weight-for-age (-2SD) 0.236 0.008 9,657 10,552 1.753 0.033 0.220 0.251 Prevalence of anaemia (children 6-59 months) 0.569 0.013 8,439 9,267 2.383 0.022 0.544 0.595 Prevalence of anaemia (women 15-49) 0.236 0.008 14,489 14,923 2.420 0.036 0.220 0.253 Body Mass Index (BMI) <18.5 0.224 0.005 13,434 13,644 1.525 0.024 0.214 0.235 Body Mass Index (BMI) ≥25 0.076 0.005 13,434 13,644 2.252 0.067 0.065 0.086 Had an HIV test and received results in past 12 months 0.197 0.007 15,683 15,683 2.272 0.037 0.182 0.211 Abstinence among never-married youth (never had sex) 0.934 0.007 3,622 3,500 1.672 0.007 0.920 0.948 Ever experienced any physical violence since age 15 0.233 0.010 5,860 5,860 1.747 0.041 0.214 0.252 Ever experienced any sexual violence 0.101 0.007 5,860 5,860 1.730 0.068 0.087 0.114 Ever experienced any physical/sexual violence by husband/partner 0.263 0.011 4,720 4,469 1.693 0.041 0.241 0.285 Physical/sexual violence in the last 12 months by husband/partner 0.198 0.010 4,720 4,469 1.760 0.052 0.177 0.218 Total fertility rate (last 3 years) 4.562 0.155 43,567 43,705 2.504 0.034 4.253 4.872 Neonatal mortality (last 0-4 years) 29.466 2.986 10,644 11,041 1.735 0.101 23.494 35.437 Post-neonatal mortality (last 0-4 years) 18.620 2.283 10,671 11,045 1.675 0.123 14.054 23.187 Infant mortality (last 0-4 years) 48.086 3.385 10,661 11,061 1.581 0.070 41.316 54.857 Child mortality (last 0-4 years) 19.898 2.602 10,494 10,870 1.808 0.131 14.694 25.102 Under-5 mortality (last 0-4 years) 67.027 4.436 10,767 11,147 1.760 0.066 58.156 75.898 MEN Urban residence 0.198 0.009 11,578 11,606 2.512 0.047 0.180 0.217 Literacy 0.688 0.011 11,578 11,606 2.662 0.017 0.665 0.711 No education 0.276 0.011 11,578 11,606 2.754 0.041 0.253 0.299 Secondary or higher education 0.241 0.009 11,578 11,606 2.371 0.039 0.222 0.260 Never married (in union) 0.421 0.008 11,578 11,606 1.796 0.020 0.404 0.437 Currently married (in union) 0.555 0.008 11,578 11,606 1.801 0.015 0.538 0.572 Had first sexual intercourse before age 18 0.170 0.010 7,076 7,151 2.150 0.056 0.151 0.189 Want no more children 0.268 0.011 6,177 6,441 1.978 0.042 0.246 0.290 Want to delay birth at least 2 years 0.442 0.012 6,177 6,441 1.927 0.028 0.417 0.466 Ideal number of children 4.629 0.075 10,684 10,981 2.379 0.016 4.479 4.779 Abstinence among never married youth (never had sex) 0.855 0.010 3,947 3,889 1.821 0.012 0.835 0.875 Had HIV test and received results in past 12 months 0.190 0.008 11,578 11,606 2.306 0.044 0.173 0.207 Prevalence of anaemia (men 15-49) 0.145 0.008 10,378 10,730 2.204 0.052 0.130 0.161 Prevalence of anaemia (men 50-59) 0.193 0.017 1,028 1,038 1.395 0.088 0.159 0.227 Body Mass Index (BMI) <18.5 (men 15-49) 0.328 0.009 10,657 10,942 1.902 0.026 0.311 0.345 Body Mass Index (BMI) <18.5 (men 50-59) 0.268 0.020 1,044 1,044 1.458 0.074 0.229 0.308 Body Mass Index (BMI) ≥25 (men 15-49) 0.031 0.002 10,657 10,942 1.326 0.071 0.027 0.036 Body Mass Index (BMI) ≥25 (men 50-59) 0.071 0.013 1,044 1,044 1.668 0.185 0.045 0.097 342 • Appendix B Table B.2 Sampling errors: Urban sample, Ethiopia DHS 2016 Number of cases Confidence limits Variable Value (R) Standard error (SE) Un- weighted (N) Weighted (WN) Design effect (DEFT) Relative Error (SE/R) Lower (R-2SE) Upper (R+2SE) WOMEN Urban residence 1.000 0.000 5,348 3,476 na 0.000 1.000 1.000 Literacy 0.779 0.016 5,348 3,476 2.766 0.020 0.747 0.810 No education 0.164 0.013 5,348 3,476 2.568 0.079 0.138 0.190 Secondary or higher education 0.505 0.020 5,348 3,476 2.919 0.040 0.465 0.545 Never married (never in union) 0.395 0.016 5,348 3,476 2.374 0.040 0.363 0.427 Currently married (in union) 0.477 0.013 5,348 3,476 1.895 0.027 0.451 0.503 Married before age 20 0.470 0.018 4,102 2,671 2.311 0.038 0.434 0.506 Had sexual intercourse before age 18 0.400 0.022 4,102 2,671 2.824 0.054 0.357 0.443 Currently pregnant 0.046 0.006 5,348 3,476 2.103 0.131 0.034 0.058 Children ever born 1.489 0.078 5,348 3,476 2.739 0.052 1.333 1.644 Children surviving 1.356 0.065 5,348 3,476 2.564 0.048 1.226 1.486 Children ever born to women age 40-49 4.294 0.226 674 403 2.156 0.053 3.841 4.747 Currently using any method 0.520 0.021 2,491 1,658 2.082 0.040 0.478 0.562 Currently using a modern method 0.498 0.021 2,491 1,658 2.110 0.042 0.456 0.540 Currently using pill 0.065 0.009 2,491 1,658 1.824 0.139 0.047 0.083 Currently using IUD 0.046 0.010 2,491 1,658 2.266 0.206 0.027 0.065 Currently using condoms 0.003 0.001 2,491 1,658 0.821 0.282 0.001 0.005 Currently using injectables 0.264 0.021 2,491 1,658 2.368 0.079 0.223 0.306 Currently using implants 0.110 0.010 2,491 1,658 1.606 0.091 0.090 0.131 Currently using female sterilisation 0.004 0.002 2,491 1,658 1.509 0.472 0.000 0.008 Using public sector source 0.662 0.028 1,257 942 2.069 0.042 0.607 0.718 Want no more children 0.297 0.021 2,491 1,658 2.245 0.069 0.255 0.338 Want to delay next birth at least 2 years 0.342 0.022 2,491 1,658 2.353 0.065 0.297 0.387 Ideal number of children 3.835 0.075 5,012 3,278 2.437 0.020 3.685 3.986 Mothers received antenatal care for last birth 0.901 0.020 1,512 969 2.575 0.022 0.861 0.941 Mothers protected against tetanus for last birth 0.724 0.032 1,512 969 2.776 0.044 0.660 0.789 Births with skilled attendant at delivery 0.801 0.039 1,974 1,216 3.591 0.048 0.723 0.878 Had diarrhoea in the last 2 weeks 0.108 0.018 1,907 1,163 2.351 0.163 0.073 0.144 Treated with ORS 0.405 0.058 186 126 1.621 0.144 0.289 0.522 Sought medical treatment for diarrhoea 0.603 0.069 186 126 1.955 0.114 0.466 0.740 Vaccination card seen 0.673 0.050 409 232 1.980 0.074 0.573 0.773 Received BCG vaccination 0.888 0.040 409 232 2.365 0.045 0.809 0.967 Received DPT vaccination (3 doses) 0.795 0.056 409 232 2.623 0.071 0.682 0.908 Received polio vaccination (3 doses) 0.795 0.049 409 232 2.257 0.061 0.697 0.892 Received pneumococcal vaccination (3 doses) 0.729 0.059 409 232 2.412 0.081 0.611 0.847 Received rotavirus vaccination (2 doses) 0.791 0.063 409 232 2.786 0.080 0.664 0.918 Received measles vaccination 0.760 0.063 409 232 2.641 0.082 0.635 0.885 Received all vaccinations 0.646 0.066 409 232 2.518 0.102 0.515 0.778 Height-for-age (-2SD) 0.254 0.026 1,739 1,131 2.323 0.101 0.203 0.305 Weight-for-height (-2SD) 0.087 0.011 1,727 1,128 1.686 0.131 0.064 0.110 Weight-for-age (-2SD) 0.134 0.015 1,768 1,140 1.807 0.115 0.104 0.165 Prevalence of anaemia (children 6-59 months) 0.493 0.030 1,423 937 2.244 0.060 0.434 0.552 Prevalence of anaemia (women 15-49) 0.170 0.014 4,709 3,169 2.639 0.084 0.142 0.198 Body Mass Index (BMI) <18.5 0.148 0.009 4,667 3,100 1.761 0.061 0.130 0.166 Body Mass Index (BMI) ≥25 0.214 0.018 4,667 3,100 2.948 0.082 0.179 0.249 Had an HIV test and received results in past 12 months 0.361 0.014 5,348 3,476 2.162 0.039 0.333 0.389 Abstinence among never-married youth (never had sex) 0.891 0.014 1,677 1,087 1.881 0.016 0.862 0.919 Ever experienced any physical violence since age 15 0.209 0.019 1,784 1,266 1.936 0.089 0.172 0.247 Ever experienced any sexual violence 0.073 0.009 1,784 1,266 1.441 0.122 0.055 0.091 Ever experienced any physical/sexual violence by husband/partner 0.196 0.020 1,211 809 1.789 0.104 0.155 0.236 Physical/sexual violence in the last 12 months by husband/partner 0.119 0.017 1,211 809 1.871 0.146 0.085 0.154 Total fertility rate (last 3 years) 2.285 0.134 14,963 9,723 1.909 0.059 2.017 2.552 Neonatal mortality (last 0-9 years) 40.582 10.298 3,727 2,326 2.735 0.254 19.986 61.179 Post-neonatal mortality (last 0-9 years) 13.315 3.505 3,741 2,328 1.613 0.263 6.306 20.325 Infant mortality (last 0-9 years) 53.898 10.019 3,730 2,326 2.484 0.186 33.859 73.936 Child mortality (last 0-9 years) 13.306 3.286 3,645 2,314 1.580 0.247 6.734 19.878 Under-5 mortality (last 0-9 years) 66.487 10.222 3,753 2,344 2.318 0.154 46.043 86.930 MEN Urban residence 1.000 0.000 3,559 2,303 na 0.000 1.000 1.000 Literacy 0.925 0.008 3,559 2,303 1.829 0.009 0.909 0.942 No education 0.079 0.010 3,559 2,303 2.149 0.123 0.060 0.099 Secondary or higher education 0.644 0.022 3,559 2,303 2.731 0.034 0.600 0.688 Never married (in union) 0.535 0.013 3,559 2,303 1.596 0.025 0.508 0.562 Currently married (in union) 0.439 0.013 3,559 2,303 1.606 0.030 0.412 0.466 Had first sexual intercourse before age 18 0.171 0.019 2,194 1,436 2.326 0.109 0.134 0.208 Want no more children 0.196 0.017 1,467 1,011 1.651 0.088 0.161 0.230 Want to delay birth at least 2 years 0.384 0.024 1,467 1,011 1.894 0.063 0.336 0.432 Ideal number of children 3.768 0.104 3,297 2,198 2.184 0.028 3.560 3.975 Abstinence among never married youth (never had sex) 0.765 0.023 1,285 820 1.982 0.031 0.718 0.812 Had HIV test and received results in past 12 months 0.332 0.014 3,559 2,303 1.793 0.043 0.304 0.360 Prevalence of anaemia (men 15-49) 0.072 0.011 2,966 1,963 2.377 0.155 0.050 0.095 Prevalence of anaemia (men 50-59) 0.099 0.030 265 176 1.668 0.306 0.038 0.159 Body Mass Index (BMI) <18.5 (men 15-49) 0.258 0.017 3,137 2,082 2.173 0.065 0.225 0.292 Body Mass Index (BMI) <18.5 (men 50-59) 0.083 0.025 275 177 1.476 0.297 0.034 0.132 Body Mass Index (BMI) ≥25 (men 15-49) 0.124 0.010 3,137 2,082 1.719 0.081 0.104 0.144 Body Mass Index (BMI) ≥25 (men 50-59) 0.297 0.040 275 177 1.446 0.134 0.217 0.377 Appendix B • 343 Table B.3 Sampling errors: Rural sample, Ethiopia DHS 2016 Number of cases Confidence limits Variable Value (R) Standard error (SE) Un- weighted (N) Weighted (WN) Design effect (DEFT) Relative Error (SE/R) Lower (R-2SE) Upper (R+2SE) WOMEN Urban residence 0.000 0.000 10,335 12,207 na na 0.000 0.000 Literacy 0.318 0.011 10,335 12,207 2.500 0.036 0.295 0.341 No education 0.568 0.012 10,335 12,207 2.499 0.021 0.543 0.592 Secondary or higher education 0.077 0.006 10,335 12,207 2.283 0.078 0.065 0.089 Never married (never in union) 0.218 0.008 10,335 12,207 1.998 0.037 0.202 0.234 Currently married (in union) 0.702 0.009 10,335 12,207 1.897 0.012 0.685 0.719 Married before age 20 0.748 0.009 8,083 9,631 1.908 0.012 0.729 0.766 Had sexual intercourse before age 18 0.630 0.011 8,083 9,631 2.088 0.018 0.608 0.653 Currently pregnant 0.080 0.004 10,335 12,207 1.593 0.053 0.071 0.088 Children ever born 3.229 0.056 10,335 12,207 1.897 0.017 3.118 3.341 Children surviving 2.840 0.049 10,335 12,207 1.902 0.017 2.742 2.937 Children ever born to women age 40-49 6.797 0.095 1,605 1,903 1.474 0.014 6.607 6.986 Currently using any method 0.328 0.014 7,333 8,565 2.592 0.043 0.299 0.356 Currently using a modern method 0.324 0.014 7,333 8,565 2.584 0.044 0.296 0.353 Currently using pill 0.009 0.002 7,333 8,565 1.559 0.186 0.006 0.013 Currently using IUD 0.015 0.003 7,333 8,565 2.026 0.190 0.010 0.021 Currently using condoms 0.000 0.000 7,333 8,565 na na 0.000 0.000 Currently using injectables 0.221 0.011 7,333 8,565 2.356 0.052 0.198 0.243 Currently using implants 0.073 0.006 7,333 8,565 2.074 0.086 0.060 0.085 Currently using female sterilisation 0.004 0.001 7,333 8,565 1.315 0.236 0.002 0.006 Using public sector source 0.894 0.012 1,946 2,942 1.783 0.014 0.870 0.919 Want no more children 0.381 0.011 7,333 8,565 1.898 0.028 0.360 0.403 Want to delay next birth at least 2 years 0.360 0.010 7,333 8,565 1.796 0.028 0.340 0.381 Ideal number of children 4.641 0.078 8,929 10,728 2.536 0.017 4.485 4.796 Mothers received antenatal care for last birth 0.583 0.017 5,681 6,621 2.524 0.028 0.550 0.616 Mothers protected against tetanus for last birth 0.456 0.015 5,681 6,621 2.333 0.034 0.425 0.487 Births with skilled attendant at deliv