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

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