Ethiopia - Demographic and Health Survey - 2012

Publication date: 2012

Ethiopia 2011Demographic and Health Survey E thiopia 2011 D em ographic and H ealth S urvey Ethiopia Demographic and Health Survey 2011 Central Statistical Agency Addis Ababa, Ethiopia ICF International Calverton, Maryland, USA March 2012 The 2011 Ethiopia Demographic and Health Survey (2011 EDHS) is part of the worldwide MEASURE DHS project which is funded by the United States Agency for International Development (USAID). The survey was implemented by the Ethiopian Central Statistical Agency (CSA). The funding for the EDHS was provided by the HIV/AIDS Prevention and Control Office (HAPCO), USAID, the United Nations Population Fund (UNFPA), the United Kingdom for International Development (DFID), the United Nations Children’s Fund (UNICEF) and the Centers for Disease Control and Prevention (CDC). ICF International provided technical assistance through the MEASURE DHS project. The opinions expressed herein are those of the authors and do not necessarily reflect the views of USAID. Additional information about the 2011 EDHS may be obtained from the Central Statistical Agency, 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 MEASURE DHS project may be obtained from ICF International, 11785 Beltsville Drive, Suite 300, Calverton, MD 20705, USA; Telephone: 301-572-0200, Fax: 301-572-0999, E-mail: info@measuredhs.com, Internet: http://www.measuredhs.com. Suggested citation: Central Statistical Agency [Ethiopia] and ICF International. 2012. Ethiopia Demographic and Health Survey 2011. Addis Ababa, Ethiopia and Calverton, Maryland, USA: Central Statistical Agency and ICF International. Contents • iii CONTENTS TABLES AND FIGURES . ix FOREWORD . xv ACKNOWLEDGMENTS . xvii MILLENNIUM DEVELOPMENT GOAL INDICATORS . xix CHAPTER 1 INTRODUCTION 1.1 History, Geography, and Economy . 1 1.2 Population . 3 1.3 Population and Health Policies . 4 1.4 Objectives of the 2011 EDHS Survey . 5 1.5 Organization of the Survey . 6 1.6 Sample Design . 7 1.7. Questionnaires . 7 1.8 Listing, Pretest, Main Training, Fieldwork, and Data Processing . 8 1.9 Anthropometry, Anaemia, and HIV Testing . 10 1.10 Response Rates . 11 CHAPTER 2 HOUSING CHARACTERISTICS AND HOUSEHOLD POPULATION 2.1 Household Environment . 13 2.1.1 Drinking Water . 13 2.1.2 Household Sanitation Facilities . 15 2.1.3 Housing Characteristics . 16 2.1.4 Household Possessions . 18 2.2 Wealth Index . 19 2.3 Population by Age and Sex . 20 2.4 Household Composition . 21 2.5 Children’s Living Arrangements and Parental Survival . 22 2.6 Education of the Household Population . 25 2.6.1 School Attendance by Survivorship of Parents . 25 2.6.2 Educational Attainment . 26 2.6.3 School Attendance Ratios . 28 2.7 Child Labour . 31 CHAPTER 3 CHARACTERISTICS OF RESPONDENTS 3.1 Characteristics of Survey Respondents . 35 3.2 Educational Attainment by Background Characteristics . 37 3.3 Literacy . 39 3.4 Exposure to Mass Media. 41 3.5 Employment . 44 3.6 Occupation . 48 3.7 Type Of Women’s Employment . 50 3.8 Health Issues . 51 3.8.1 Use of Tobacco . 51 3.8.2 Alcohol Consumption . 52 3.8.3 Chewing Chat . 53 3.8.4 Knowledge and Attitudes concerning Tuberculosis . 55 iv • Contents CHAPTER 4 MARRIAGE AND SEXUAL ACTIVITY 4.1 Current Marital Status . 59 4.2 Polygyny . 60 4.3 Age at First Marriage . 62 4.4 Age at First Sexual Intercourse . 64 4.5 Recent Sexual Activity . 66 CHAPTER 5 FERTILITY LEVELS, TRENDS, AND DIFFERENTIALS 5.1 Current Fertility . 69 5.2 Fertility Differentials by Background Characteristics . 71 5.3 Fertility Trends . 72 5.4 Children Ever Born and Living . 73 5.5 Birth Intervals . 74 5.6 Postpartum Amenorrhoea, Abstinence, and Insusceptibility . 76 5.7 Menopause . 77 5.8 Age at First Birth . 78 5.9 Teenage Pregnancy and Motherhood . 79 CHAPTER 6 FERTILITY PREFERENCES 6.1 Desire for More Children . 81 6.2 Desire to Limit Childbearing by Background Characteristics . 83 6.3 Ideal Number of Children . 86 6.4 Mean Ideal Number of Children by Women’s Background Characteristics . 88 6.5 Fertility Planning Status . 89 6.6 Wanted Fertility Rates . 90 CHAPTER 7 FAMILY PLANNING 7.1 Knowledge of Contraceptive Methods . 93 7.2 Current Use of Contraceptive Methods . 95 7.2.1 Current Use of Contraceptive Methods By Age . 95 7.2.2 Trends in Contraceptive Use . 97 7.3 Current Use of Contraception by Background Characteristics . 97 7.4 Source of Modern Contraceptive Methods . 99 7.5 Informed Choice . 99 7.6 Knowledge of the Fertile Period . 100 7.7 Need and Demand for Family Planning . 101 7.8 Future Use of Contraception . 102 7.9 Exposure to Family Planning Messages . 102 7.10 Exposure to Specific Type of Family Planning Messages . 105 7.11 Contact of Nonusers with Family Planning Providers . 106 7.12 Contraceptive Discontinuation Rate . 108 CHAPTER 8 INFANT AND CHILD MORTALITY 8.1 Data Quality . 110 8.2 Levels and Trends in Infant and Child Mortality . 111 8.2.1 Early Childhood Mortality Rates . 111 8.2.2 Trends in Early Childhood Mortality . 111 8.3 Early Childhood Mortality Rates by Socioeconomic Characteristics . 112 8.4 Demographic Differentials in Infant and Child Mortality . 114 8.5 Perinatal Mortality . 115 8.6 High-Risk Fertility Behaviour . 117 Contents • v CHAPTER 9 MATERNAL HEALTH 9.1 Antenatal Care . 119 9.1.1 Coverage of Antenatal Care . 120 9.1.2 Number of ANC Visits, Timing of First Visit, and Source Where ANC Was Received . 121 9.1.3 Components of Antenatal Care . 122 9.1.4 Informed of signs of pregnancy complications during pregnancy . 124 9.2 Tetanus Toxoid Injections . 124 9.3 Place of Delivery . 126 9.4 Assistance during Delivery . 127 9.5 Reasons for Not Delivering in a Health Facility . 128 9.6 Postnatal Care . 129 9.6 Problems in Accessing Health Care . 131 CHAPTER 10 CHILD HEALTH 10.1 Child’s Size at Birth . 135 10.2 Vaccination Coverage . 138 10.2.1 Vaccinations Coverage by Background Characteristics . 140 10.3 Trends in Vaccination Coverage . 141 10.4 Acute Respiratory Infection . 142 10.5 Fever . 143 10.6 Diarrhoeal Disease . 146 10.6.1 Prevalence of Diarrhoea . 146 10.6.2 Treatment of Diarrhoea . 148 10.6.3 Feeding Practices during Diarrhoea . 150 10.7 Knowledge of ORS Packets . 152 10.8 Stool Disposal . 153 CHAPTER 11 NUTRITION OF CHILDREN AND ADULTS 11.1 Nutritional Status of Children . 156 11.1.1 Measurement of Nutritional Status among Young Children . 156 11.1.2 Data Collection. 157 11.1.3 Measures of Children’s Nutritional Status . 158 11.1.4 Trends in Children’s Nutritional Status . 161 11.2 Breastfeeding and Complementary Feeding . 162 11.2.1 Initiation of Breastfeeding . 162 11.2.2 Breastfeeding Status by Age . 164 11.2.3 Duration of Breastfeeding . 168 11.2.4 Types of Complementary Foods . 169 11.2.5 Infant and Young Child Feeding (IYCF) Practices . 171 11.3 Prevalence of Anaemia in Children . 173 11.4 Micronutrient Intake among Children . 175 11.5 Iodisation of Household Salt . 179 11.6 Nutritional Status of Women and Men . 180 11.7 Prevalence of Anaemia in Women . 184 11.8 Prevalence of Anaemia in Men . 186 11.9 Micronutrient Intake among Mothers . 186 vi • Contents CHAPTER 12 HIV/AIDS-RELATED KNOWLEDGE, ATTITUDES, AND BEHAVIOUR 12.1 HIV/AIDS Knowledge, Transmission, and Prevention Methods . 190 12.1.1 Awareness of HIV/AIDS . 190 12.1.2 Rejection of Misconceptions about HIV/AIDS . 192 12.2 Knowledge of Prevention of Mother-to-Child Transmission of HIV . 195 12.3 Attitudes towards People Living with HIV/AIDS . 196 12.4 Attitudes towards Refusing to Have Sex and Negotiating Safer Sex . 198 12.5 Adult Support for Education about Condoms for Children Age 12 14 . 200 12.6 Higher-Risk Sex . 201 12.6.1 Multiple Partners and Condom Use . 201 12.6.2 Transactional Sex . 205 12.7 Coverage of HIV Testing . 206 12.7.1 General HIV Testing . 206 12.7.2 HIV Counseling and Testing During Pregnancy . 208 12.8 Male Circumcision . 210 12.9 Self-Reporting of Sexually Transmitted Infections . 211 12.10 Prevalence of Medical Injections . 213 12.11 HIV/AIDS Knowledge and Sexual Behaviour among Youth . 215 12.11.1 HIV/AIDS-Related Knowledge among Young Adults . 215 12.11.2 Age at First Sexual Intercourse . 216 12.11.3 Abstinence and Premarital Sex . 219 12.11.4 Multiple Partnerships among Young Adults . 221 12.11.5 Age-mixing in Sexual Relationships . 222 12.11.6 Recent HIV Testing Among Youth . 223 12.12 Use of Alcohol or Chat during Sexual Intercourse . 224 12.13 Sharing of HIV Test Results Among Couples . 226 12.14 Participation in Community Conversation Programme . 227 CHAPTER 13 HIV PREVALENCE 13.1 Coverage Rates for HIV Testing . 231 13.2 HIV Prevalence . 234 13.2.1 HIV Prevalence by Age and Sex . 234 13.2.2 HIV Prevalence by Socioeconomic Characteristics . 235 13.2.3 HIV Prevalence by Demographic Characteristics . 236 13.2.4 HIV Prevalence by Sexual Risk Behaviour . 237 13.3 HIV Prevalence among Youth . 238 13.3.1 HIV Prevalence by Sexual Behaviour among Youth . 239 13.4 HIV Prevalence by Other Characteristics . 240 13.4.1 HIV Prevalence and STIs . 240 13.4.2 Prior HIV Testing and Current HIV Status . 241 13.4.3 HIV Prevalence by Male Circumcision . 241 13.5 HIV Prevalence among Cohabiting Couples . 243 Contents • vii CHAPTER 14 WOMEN’S EMPOWERMENT AND DEMOGRAPHIC AND HEALTH OUTCOMES 14.1 Employment and Form of Earnings . 246 14.2 Control Over and Relative Magnitude of Women’s and Husband’s Earnings . 247 14.2.1 Control Over Wife’s Earnings . 247 14.2.2 Control Over Husband’s Earnings . 249 14.3 Control Over Married Women’s Earnings and Relative Size of Husband’s and Wife’s Earnings . 250 14.4 Ownership of Assets . 252 14.5 Women’s Participation in Decision-Making . 253 14.6 Attitude towards Wife Beating . 256 14.7 Women’s Empowerment Indices . 259 14.8 Current Use of Contraception by Women’s Status . 260 14.9 Ideal Family Size and Unmet Need by Women’s Status . 261 14.10 Women’s Status and Reproductive Health Care . 262 14.11 Differentials in Infant and Child Mortality by Women’s Status . 263 14.12 Men’s Participation in Household Chores . 264 14.13 Law Against Domestic Violence . 265 CHAPTER 15 ADULT AND MATERNAL MORTALITY 15.1 Assessment of Data Quality . 267 15.2 Estimates of Adult Mortality . 268 15.3 Estimates of Maternal Mortality . 270 REFERENCES . 273 APPENDIX A SAMPLE IMPLEMENTATION . 275 APPENDIX B ESTIMATES OF SAMPLING ERRORS . 287 APPENDIX C DATA QUALITY TABLES . 307 APPENDIX D PERSONS INVOLVED IN THE 2011 ETHIOPIA DEMOGRAPHIC AND HEALTH SURVEY . 317 APPENDIX E QUESTIONNAIRES . 327 Tables and Figures • ix TABLES AND FIGURES CHAPTER 1 INTRODUCTION Table 1.1 Basic demographic indicators . 3 Table 1.2 Results of the household and individual interviews . 12 CHAPTER 2 HOUSING CHARACTERISTICS AND HOUSEHOLD POPULATION Table 2.1 Household drinking water . 14 Table 2.2 Household sanitation facilities . 16 Table 2.3 Household characteristics . 17 Table 2.4 Household possessions . 19 Table 2.5 Wealth quintiles . 20 Table 2.6 Household population by age, sex, and residence . 20 Table 2.7 Household composition . 22 Table 2.8 Children's living arrangements and orphanhood . 24 Table 2.9 School attendance by survivorship of parents . 26 Table 2.10.1 Educational attainment of the female household population . 27 Table 2.10.2 Educational attainment of the male household population . 28 Table 2.11 School attendance ratios . 30 Table 2.12 Child labour . 33 Figure 2.1 Population pyramid . 21 Figure 2.2 Age-specific attendance rates of the de facto population 5 to 24 years . 31 CHAPTER 3 CHARACTERISTICS OF RESPONDENTS Table 3.1 Background characteristics of respondents . 36 Table 3.2.1 Educational attainment: Women . 38 Table 3.2.2 Educational attainment: Men . 39 Table 3.3.1 Literacy: Women . 40 Table 3.3.2 Literacy: Men . 41 Table 3.4.1 Exposure to mass media: Women . 42 Table 3.4.2 Exposure to mass media: Men . 43 Table 3.5.1 Employment status: Women . 45 Table 3.5.2 Employment status: Men . 47 Table 3.6.1 Occupation: Women. 48 Table 3.6.2 Occupation: Men . 49 Table 3.7 Type of employment: Women . 50 Table 3.8 Use of tobacco: Men . 51 Table 3.9.1 Alcohol consumption: Women . 52 Table 3.9.2 Alcohol consumption: Men . 53 Table 3.10.1 Chewing chat: Women . 54 Table 3.10.2 Chewing chat: Men . 55 Table 3.11.1 Knowledge and attitude concerning tuberculosis: Women . 56 Table 3.11.2 Knowledge and attitude concerning tuberculosis: Men . 57 Figure 3.1 Women’s employment status in the past 12 months . 46 x • Tables and Figures CHAPTER 4 MARRIAGE AND SEXUAL ACTIVITY Table 4.1 Current marital status . 60 Table 4.2.1 Number of women's co-wives . 61 Table 4.2.2 Number of men's wives . 62 Table 4.3 Age at first marriage . 63 Table 4.4 Median age at first marriage by background characteristics . 64 Table 4.5 Age at first sexual intercourse . 65 Table 4.6 Median age at first sexual intercourse by background characteristics . 66 Table 4.7.1 Recent sexual activity: Women . 67 Table 4.7.2 Recent sexual activity: Men . 68 CHAPTER 5 FERTILITY LEVELS, TRENDS, AND DIFFERENTIALS Table 5.1 Current fertility . 70 Table 5.2 Fertility by background characteristics . 71 Table 5.3.1 Trends in age-specific fertility rates . 72 Table 5.3.2 Trends in age-specific and total fertility rates . 73 Table 5.4 Children ever born and living . 74 Table 5.5 Birth intervals . 75 Table 5.6 Postpartum amenorrhoea, abstinence, and insusceptibility . 76 Table 5.7 Median duration of amenorrhoea, postpartum abstinence, and postpartum insusceptibility . 77 Table 5.8 Menopause . 78 Table 5.9 Age at first birth . 78 Table 5.10 Median age at first birth . 79 Table 5.11 Teenage pregnancy and motherhood . 80 Figure 5.1 Age-specific fertility rates by urban-rural residence . 71 CHAPTER 6 FERTILITY PREFERENCES Table 6.1 Fertility preferences by number of living children . 82 Table 6.2.1 Desire to limit childbearing: Women . 84 Table 6.2.2 Desire to limit childbearing: Men . 85 Table 6.3 Ideal number of children . 87 Table 6.4 Mean ideal number of children by background characteristics . 89 Table 6.5 Fertility planning status . 90 Table 6.6 Wanted fertility rates . 91 Figure 6.1 Desire for more children among currently married women . 83 Figure 6.2 Trends in mean ideal family size among women and men . 86 CHAPTER 7 FAMILY PLANNING Table 7.1 Knowledge of contraceptive methods . 94 Table 7.2 Current use of contraception by age . 96 Table 7.3 Current use of contraception by background characteristics . 98 Table 7.4 Source of modern contraception methods . 99 Table 7.5 Informed choice . 100 Table 7.6 Knowledge of fertile period . 100 Table 7.7 Need and demand for family planning among currently married women . 101 Table 7.8 Future use of contraception . 102 Table 7.9 Exposure to family planning messages . 104 Tables and Figures • xi Table 7.10 Exposure to specific family planning messages . 106 Table 7.11 Contact of nonusers with family planning providers . 107 Table 7.12 Contraceptive discontinuation rates . 108 Figure 7.1 Trends in current use of contraceptives among currently married women . 97 CHAPTER 8 INFANT AND CHILD MORTALITY Table 8.1 Early childhood mortality rates . 111 Table 8.2 Early childhood mortality rates by socioeconomic characteristics . 113 Table 8.3 Early childhood mortality rates, by demographic characteristics . 114 Table 8.4 Perinatal mortality . 116 Table 8.5 High-risk fertility behaviour . 117 Figure 8.1 Trends in early childhood mortality . 112 Figure 8.2 Under-five mortality by socioeconomic characteristics . 114 Figure 8.3 Infant and under-five mortality rate by selected demographic characteristics . 115 CHAPTER 9 MATERNAL HEALTH Table 9.1 Antenatal care . 120 Table 9.2 Number of antenatal care visits and timing of first visit . 122 Table 9.3 Components of antenatal care . 123 Table 9.4 Informed of signs of pregnancy complications . 124 Table 9.5 Tetanus toxoid injections . 125 Table 9.6 Place of delivery . 126 Table 9.7 Assistance during delivery . 128 Table 9.8 Reasons for not delivering in a health facility . 129 Table 9.9 Timing of first postnatal checkup for the mother . 130 Table 9.10 Type of provider of first postnatal checkup for the mother. 131 Table 9.11 Problems in accessing health care . 133 CHAPTER 10 CHILD HEALTH Table 10.1 Child's weight and size at birth. 137 Table 10.2 Vaccinations by source of information . 139 Table 10.3 Vaccinations by background characteristics . 140 Table 10.4 Vaccinations in first year of life . 141 Table 10.5 Prevalence and treatment of symptoms of ARI . 143 Table 10.6 Prevalence and treatment of fever . 145 Table 10.7 Prevalence of diarrhoea . 147 Table 10.8 Diarrhoea treatment . 149 Table 10.9 Feeding practices during diarrhoea . 151 Table 10.10 Knowledge of ORS packets . 152 Table 10.11 Disposal of children's stools . 154 Figure 10.1 Percentage of children age 12-23 months with specific vaccinations . 139 Figure 10.2 Trends in vaccination coverage during the first year of life among children 12-23 months . 142 CHAPTER 11 NUTRITION OF CHILDREN AND ADULTS Table 11.1 Nutritional status of children . 159 Table 11.2 Initial breastfeeding . 163 xii • Tables and Figures Table 11.3 Breastfeeding status by age . 166 Table 11.4 Median duration of breastfeeding . 168 Table 11.5 Foods and liquids consumed by children in the day or night preceding the interview . 170 Table 11.6 Infant and young child feeding (IYCF) practices . 172 Table 11.7 Prevalence of anaemia in children . 174 Table 11.8 Micronutrient intake among children . 178 Table 11.9 Presence of iodised salt in household . 179 Table 11.10.1 Nutritional status of women . 182 Table 11.10.2 Nutritional status of men . 183 Table 11.11.1 Prevalence of anaemia in women . 185 Table 11.11.2 Prevalence of anaemia in men . 186 Table 11.12 Micronutrient intake among mothers . 188 Figure 11.1 Nutritional status of children by age . 161 Figure 11.2 Trends in nutritional status of children under age 5 . 162 Figure 11.3 Infant feeding practices by age . 165 Figure 11.4 IYCF indicators of breastfeeding status . 167 Figure 11.5 Trends in anaemia status among children 6-59 months . 175 CHAPTER 12 HIV/AIDS-RELATED KNOWLEDGE, ATTITUDES, AND BEHAVIOUR Table 12.1 Knowledge of AIDS . 190 Table 12.2 Knowledge of HIV prevention methods. 191 Table 12.3.1 Comprehensive knowledge about AIDS: Women . 193 Table 12.3.2 Comprehensive knowledge about AIDS: Men . 194 Table 12.4 Knowledge of prevention of mother-to-child transmission of HIV . 196 Table 12.5.1 Accepting attitudes toward those living with HIV/AIDS: Women . 197 Table 12.5.2 Accepting attitudes toward those living with HIV/AIDS: Men . 198 Table 12.6 Attitudes toward negotiating safer sexual relations with husband . 199 Table 12.7 Adult support of education about condom use to prevent AIDS . 200 Table 12.8.1 Multiple sexual partners: Women . 202 Table 12.8.2 Multiple sexual partners: Men . 203 Table 12.9 Point prevalence and cumulative prevalence of concurrent sexual partners . 204 Table 12.10 Payment for sexual intercourse . 205 Table 12.11.1 Coverage of prior HIV testing: Women . 207 Table 12.11.2 Coverage of prior HIV testing: Men . 208 Table 12.12 Pregnant women counselled and tested for HIV . 209 Table 12.13.1 Male circumcision . 210 Table 12.13.2 Circumstances surrounding male circumcision . 211 Table 12.14 Self-reported prevalence of sexually-transmitted infections (STIs) and STI symptoms . 212 Table 12.15 Prevalence of medical injections . 214 Table 12.16 Comprehensive knowledge about AIDS and knowledge of a source of condoms among young people . 216 Table 12.17 Age at first sexual intercourse among young people . 218 Table 12.18 Premarital sexual intercourse and condom use during premarital sexual intercourse among youth . 220 Table 12.19.1 Multiple sexual partners in the past 12 months among young people: Women . 221 Table 12.19.2 Multiple sexual partners in the past 12 months among young people: Men . 222 Table 12.20 Age-mixing in sexual relationships among women and men age 15-19 . 223 Table 12.21 Recent HIV testing among youth . 224 Table 12.22.1 Use of alcohol and/or chat at last sexual intercourse: Women . 225 Tables and Figures • xiii Table 12.22.2 Use of alcohol and/or chat at last sexual intercourse: Men . 226 Table 12.23 Sharing of HIV test results among couples . 227 Table 12.24.1 Exposure to Community Conversation programme: Women . 228 Table 12.24.2 Exposure to Community Conversation programme: Men . 229 Figure 12.1 Women and men seeking treatment for STIs . 213 Figure 12.2 Trends in age at first sexual intercourse . 219 CHAPTER 13 HIV PREVALENCE Table 13.1 Coverage of HIV testing by residence and region . 232 Table 13.2 Coverage of HIV testing by selected background characteristics . 233 Table 13.3 HIV prevalence by age . 234 Table 13.4 HIV prevalence by socioeconomic characteristics . 235 Table 13.5 HIV prevalence by demographic characteristics . 236 Table 13.6 HIV prevalence by sexual behaviour . 237 Table 13.7 HIV prevalence among young people by background characteristics . 239 Table 13.8 HIV prevalence among young people by sexual behaviour . 240 Table 13.9 HIV prevalence by other characteristics . 241 Table 13.10 Prior HIV testing by current HIV status . 241 Table 13.11 HIV prevalence by male circumcision . 242 Table 13.12 HIV prevalence among couples . 244 Figure 13.1 HIV prevalence for women and men age 15-49 by age groups . 234 CHAPTER 14 WOMEN’S EMPOWERMENT AND DEMOGRAPHIC AND HEALTH OUTCOMES Table 14.1 Employment and cash earnings of currently married women and men . 246 Table 14.2.1 Control over women's cash earnings and relative magnitude of women's cash earnings: Women . 248 Table 14.2.2 Control over men's cash earnings . 250 Table 14.3 Women's control over their own earnings and over those of their husbands . 251 Table 14.4.1 Ownership of assets: Women . 252 Table 14.4.2 Ownership of assets: Men . 253 Table 14.5 Participation in decision-making . 254 Table 14.6 Women's participation in decision-making by background characteristics . 254 Table 14.7.1 Attitude towards wife beating: Women . 257 Table 14.7.2 Attitude towards wife beating: Men . 258 Table 14.8 Indicators of women's empowerment . 260 Table 14.9 Current use of contraception by women's empowerment . 261 Table 14.10 Women's empowerment and ideal number of children, and unmet need for family planning . 262 Table 14.11 Reproductive health care by women's empowerment . 263 Table 14.12 Early childhood mortality rates by women's status . 263 Table 14.13 Men's participation in household chores . 264 Table 14.14 Knowledge of law against domestic violence . 265 Figure 14.1 Number of decisions in which currently married women participate . 255 CHAPTER 15 ADULT AND MATERNAL MORTALITY Table15.1 Adult mortality rates . 269 Table 15.2 Adult mortality probabilities . 269 xiv • Tables and Figures Table 15.3 Maternal mortality . 270 Figure 15.1 Maternal mortality ratio (MMR) with confidence intervals for the seven years preceding the 200, 2005, and 2011 Ethiopia DHS . 271 APPENDIX A SAMPLE IMPLEMENTATION Table A.1 Enumeration areas and average EA size in the sampling frame . 276 Table A.2 Distribution of households in the sampling frame . 276 Table A.3 Sample allocation of clusters and households . 277 Table A.4 Sample allocation of completed interviews with women and men . 278 Table A.5 Sample implementation . 280 Table A.6 Sample implementation: Men . 281 Table A.7 Coverage of HIV testing by social and demographic characteristics: Women . 282 Table A.8 Coverage of HIV testing by social and demographic characteristics: Men . 283 Table A.9 Coverage of HIV testing among interviewed women by sexual behavior characteristics: Women . 284 Table A.10 Coverage of HIV testing among interviewed men by sexual behavior characteristics: Men . 285 APPENDIX B ESTIMATES OF SAMPLING ERRORS Table B.1 List of selected variables for sampling errors, Ethiopia 2011 . 290 Table B.2 Sampling errors for national sample, Ethiopia 2011 . 291 Table B.3 Sampling errors for urban sample, Ethiopia 2011 . 292 Table B.4 Sampling errors for rural sample, Ethiopia 2011 . 293 Table B.5 Sampling errors for Tigray region, Ethiopia 2011 . 294 Table B.6 Sampling errors for Affar region, Ethiopia 2011 . 295 Table B.7 Sampling errors for Amhara region, Ethiopia 2011 . 296 Table B.8 Sampling errors for Oromiya region, Ethiopia 2011 . 297 Table B.9 Sampling errors for Somali region, Ethiopia 2011 . 298 Table B.10 Sampling errors for Benishangul-Gumuz region, Ethiopia 2011 . 299 Table B.11 Sampling errors for SNNP region, Ethiopia 2011 . 300 Table B.12 Sampling errors for Gambela region, Ethiopia 2011 . 301 Table B.13 Sampling errors for Harari region, Ethiopia 2011 . 302 Table B.14 Sampling errors for Addis Ababa region, Ethiopia 2011 . 303 Table B.15 Sampling errors for Dire Dawa region, Ethiopia 2011 . 304 Table B.16 Sampling errors for adult and maternal mortality rates, Ethiopia 2011 . 305 APPENDIX C DATA QUALITY TABLES Table C.1 Household age distribution . 307 Table C.2.1 Age distribution of eligible and interviewed women . 308 Table C.2.2 Age distribution of eligible and interviewed men . 309 Table C.3 Completeness of reporting . 310 Table C.4 Births by calendar years . 311 Table C.5 Reporting of age at death in days . 312 Table C.6 Reporting of age at death in months . 313 Table C.7 Nutritional status of children based on NCHS/CDC/WHO International Reference Population . 314 Table C.8 Completeness of Information on Siblings . 315 Table C.9 Sibship size and sex ratio of siblings . 316 xv • Forward FOREWORD The 2011 Ethiopia Demographic and Health Survey (EDHS) was conducted by the Central Statistical Agency (CSA) under the auspices of the Ministry of Health. The Ethiopian Health and Nutrition Research Institute (EHNRI) was responsible for the testing of HIV from the dried blood samples (DBS). This is the third Demographic and Health Survey (DHS) conducted in Ethiopia, under the worldwide MEASURE DHS project, a USAID-funded project providing support and technical assistance in the implementation of population and health surveys in countries worldwide. The three EDHS surveys have been conducted at five-year intervals since 2000, and the 2011 EDHS is the second survey presenting results on HIV and anemia prevalence. The preliminary report containing results of selected variables was released in October 2011, and this final report presents the details of the findings of the survey including results released earlier. The primary objectives of the 2011 EDHS are to provide up-to-date information for planning, policy formulation, monitoring, and evaluation of population and health programmes in the country. The survey was intentionally planned to be fielded at the beginning of the last term of the MDG reporting period to provide data for the assessment of the Millennium Development Goals (MDGs). The 2011 EDHS, in conjunction with statistical information obtained from the Welfare Monitoring Survey (WMS) and the Household Income, Consumption and Expenditure Survey (HICES), provides critical information for monitoring and evaluating the Growth and Transformation Plan (GTP) as well as various sector development policies and programmes. The survey interviewed a nationally representative population in about 18,500 households, and all women age 15-49 and all men age 15-59 in these households. In this report key indicators relating to family planning, fertility levels and determinants, fertility preferences, infant, child, adult and maternal mortality, maternal and child health, nutrition, women’s empowerment, and knowledge of HIV/AIDS are provided for the nine regional states and two city administrations. In addition, this report also provides data by urban and rural residence at the country level. Major stakeholders from various government, non-government, and UN organizations have been involved and have contributed in the technical, managerial, and operational aspects of the survey. The CSA acknowledges a number of organizations and individuals who contributed in various ways to the successful completion of the 2011 EDHS. The Agency is grateful for the commitment of the Government of Ethiopia and the generous funding support primarily by the HIV/AIDS Prevention and Control Office (HAPCO), the United States Agency for International Development (USAID), the United Nations Population Fund (UNFPA), the United Kingdom Department for International Development (DFID), the United Nations Children’s Fund (UNICEF) and the Centers for Disease Control and Prevention (CDC). ICF International provided technical assistance as well as funding to the project through the MEASURE DHS project. xvi • Forward The Agency extends a special thanks to the Ministry of Health for the overall co-ordination and undertaking of the voluntary counseling and testing (VCT) activities and to all members of institutions represented in the 2011 EDHS Steering and Technical Advisory Committees—MoFED, EHNRI, USAID, CDC, UNICEF, DFID, WHO, UNAIDS, UNFPA, CORHA—for their valuable contribution to the successful completion of the survey. Special thanks also goes to the Ethiopia Health and Nutrition Research Institute (EHNRI), which handled the complicated task of testing the dry blood samples collected in the field for determining the HIV status of the surveyed population. The Agency also wishes to acknowledge the tireless efforts of the CSA staff that made this survey a success. Finally, special thanks go to the field staff and also to the survey respondents, who were critical to the successful completion of this survey. Samia Zekaria Director General Central Statistical Agency Acknowledgements • xvii ACKNOWLEDGEMENTS The following persons contributed to the preparation of this report: Mr. Gebeyehu Abelti, Central Statistical Agency Mr. Jelaludin Ahmed, CDC Ms. Eleni Seyuom, WHO Ms. Genet Mengistu, MoFED Mr. Terefe Bogale, MoFED Ms. Wegen Tamene, EHNRI Mr. Desta Kassa, EHNRI Dr. Belete Tegbaru, EHNRI Ms. Martha Kibur, UNICEF Ms. Roman G/Yes, MOH Ms. Alemitu Seyoum, MOH Mr. Fantahun Walle, Central Statistical Agency Mr. Wondwessen Demise, Central Statistical Agency Mr. Girum Haile, Central Statistical Agency Mr. Akalework Bezu, Central Statistical Agency Mr. Assefa Negera, Central Statistical Agency Mr. Million Taye, Central Statistical Agency Mr. Ashenafi Seyoum, Central Statistical Agency Mr. Seyoum Tadesse, Central Statistical Agency Mr. Hailemariam Teklu, Central Statistical Agency Mr. Kassahun Mengistu, Central Statistical Agency Ms. Alemeshet Ayele, Central Statistical Agency Ms. Alemtsehay Beru, ICF International Ms. Zhuzhi Moore, ICF International Dr. Fred Arnold, ICF International Dr. Pav Govindasamy, ICF International Ms. Joy Fishel, ICF International Ms. Anjushree Pradhan, ICF International Ms. Velma Lopez, ICF International Millennium Development Goal Indicators • xix Millennium Development Goal Indicators, Ethiopia 2011 Value Total Female Male Goal Indicator 1. Eradicate extreme poverty and hunger 1.8 Prevalence of underweight children under five years of age1 26.8% 30.5% 28.7% 2. Achieve universal primary education 2.1 Net attendance ratio in primary education2 65.0% 64.5% 64.5% 2.3 Literacy rate of 15-24 year olds3 56.9% 75.0% 66.0% 3. Promote gender equality and empower women 3.1a Ratio of girls to boys in primary education4 1.0 3.1b Ratio of girls to boys in secondary education4 1.0 3.1c Ratio of girls to boys in tertiary education4 1.0 4. Reduce child mortality 4.1 Under-five mortality rate (per 1000 live births)5 98 per 1,000 122 per 1,000 88 per 1,000 4.2 Infant mortality rate (per 1000 live births)5 63 per 1,000 84 per 1,000 59 per 1,000 4.3 Proportion of 1 year-old children immunized against measles 55.7% 55.7% 55.7% 5. Improve maternal health 5.1 Maternal mortality ratio6 676 deaths per 100,000 5.2 Proportion of births attended by skilled health personnel7 10.0% na na 5.3 Contraceptive prevalence rate8 28.6% na na 5.4 Adolescent birth rate9 79 per 1,000 na na 5.5 a) Antenatal care coverage: at least one ANC visit 42.6% na na b) Antenatal care coverage: at least four ANC visits 19.1% na na 5.6 Unmet need for family planning 25.3% na na 6. Combat HIV/AIDS, malaria and other diseases 6.1 HIV prevalence among population aged 15-24 0.5% 0.1% 0.3% 6.2 Condom use at last high-risk sex: youth 15-24 years10 61.6% 47.2% 54.4% 6.3 Percentage of population 15-24 years with comprehensive knowledge About AIDS11 23.9% 34.2% 30.5% 6.4 Ratio of school attendance of orphans to school attendance of non-orphans aged 10-14 years 1.01 0.81 0.90 Urban Rural Total 7. Ensure environmental sustainability 7.8 Proportion of population using an improved drinking water source12 92.8% 41.6% 50.8% 7.9 Proportion of population using an improved sanitation facility13 18.2% 6.8% 8.8% na = Not applicable 1 Proportion of children age 0-59 months who are below -2 standard deviations (SD) from the median of the WHO Child Growth Standards in weight-for-age. 2 The rate is based on reported attendance, not enrollment, in primary education among primary school age children (7-14 year-olds). The rate also includes children of primary school age enrolled in secondary education. This is a proxy for MDG indicator 2.1, Net enrollment ratio. 3 Refers to respondents who attended secondary school or higher or who could read a whole sentence or part of a sentence 4 Based on reported net attendance, not gross enrollment 5 Expressed in terms of deaths per 1,000 live births. Mortality by sex refers to a 10-year reference period preceding the survey. Mortality rates for males and females combined refer to the 5-year period preceding the survey. The difference in the reference periods explains the apparent inconsistency between the sex-specific and total mortality rates. 6 Expressed in terms of maternal deaths per 100,000 live births in the 7 -year period preceding the survey 7 Among births in the five years preceding the survey 8 Percentage of currently married women age 15-49 using any method of contraception 9 Equivalent to the age-specific fertility rate for women age 15-19 for the 3-year period before the survey, expressed in terms of births per 1,000 women age 15-19 10 High-risk sex refers to sexual intercourse with a non-cohabiting, non-marital partner. Expressed as a percentage of men and women age 15-24 who had high-risk sex in the past 12 months. 11 Comprehensive knowledge about AIDS means knowing that consistent use of condoms during sexual intercourse and having just one uninfected faithful partner can reduce the chance of getting the AIDS virus, knowing that a healthy-looking person can have the AIDS virus, and rejecting the two most common local misconceptions about transmission or prevention of the AIDS virus. The two most common local misconceptions in Ethiopia are: 1) AIDS can be transmitted by mosquito bites and 2) AIDS can be transmitted by supernatural means. 12 Percentage of de-jure population whose main source of drinking water is a household connection (piped), public standpipe, borehole, protected dug well or spring, rainwater collection, or bottled water. 13 Percentage of de-jure population with access to flush toilet, ventilated improved pit latrine, traditional pit latrine with a slab, or composting toilet and does not share this facility with other households. Introduction • 1 INTRODUCTION 1 1.1 HISTORY, GEOGRAPHY, AND ECONOMY History Ethiopia is an ancient country. Paleontological studies identify Ethiopia as one of the cradles of mankind. For instance, “Dinknesh” or “Lucy,” one of the earliest and most complete hominoid skeletons ever found was discovered in Hadar through archaeological excavations in 1974, and dates back 3.5 million years. More recently, an older female skeleton, nicknamed Ardi, was discovered in 1994, and is considered to be the earliest hominid skeleton—dating a million years before the Lucy was ever found. Situated in the Horn of Africa, the country is at the crossroads between the Middle East and Africa. Thus, throughout its long history Ethiopia has been a melting pot of diverse customs and cultures. Today, it embraces a complex variety of nationalities, peoples, and linguistic groups. Its peoples altogether speak over 80 different languages, constituting 12 Semitic, 22 Cushitic, 18 Omotic, and 18 Nilo-Saharan languages (MOI, 2004). Ethiopia is one of the few African countries to have maintained its independence, even during the colonial era. Furthermore, the country is one of the founding members of the United Nations. Ethiopia takes an active role in African affairs, for example, playing a pioneering role in the formation of the Organization of African Unity (OAU). In fact, the capital city, Addis Ababa, has been a seat for the OAU since its establishment and continues to serve as the seat for the African Union (AU) today. Historically, Ethiopia was ruled by successive emperors and kings, with a feudal system of government. In 1974 the military took over the reins of rule by force and administered the country until May 1991. Currently, a federal system of government exists, and political leaders are elected every five years. The government is made up of two tiers of parliament, the House of Peoples’ Representatives and the House of the Federation. Major changes in the administrative boundaries within the country have been made three times since the mid-1970s. At present Ethiopia is administratively structured into nine regional states—Tigray, Affar, Amhara, Oromiya, Somali, Benishangul-Gumuz, Southern Nations Nationalities and Peoples (SNNP), Gambela, and Harari—and two city administrations, that is, Addis Ababa and Dire Dawa Administration Councils. Key Findings • The 2011 Ethiopia Demographic and Health Survey (EDHS) is a nationally representative survey of 16,515 women age 15-49 and 14,110 men age 15-59. • The 2011 EDHS is the third comprehensive survey conducted in Ethiopia as part of the worldwide Demographic and Health Surveys project. • The primary purpose of the EDHS is to furnish policymakers and planners with detailed information on fertility, family planning, infant, child, adult and maternal mortality, maternal and child health, nutrition and knowledge of HIV/AIDS and other sexually transmitted infections. • In all selected households, women age 15-49 and children age 6-59 months were tested for anaemia, and women age 15-49 and men age 15-59 were tested for HIV. 2 • Introduction Geography Ethiopia has great geographical diversity; its topographic features range from the highest peak at Ras Dashen, 4,550 metres above sea level, down to the Affar Depression, 110 metres below sea level (CSA, 2009). The climate varies with the topography, from as high as 47 degrees Celsius in the Affar Depression to as low as 10 degrees Celsius in the highlands. Ethiopia’s total surface area is about 1.1 million square kilometres. Djibouti, Eritrea, the Republic of the Sudan, the Republic of the Southern Sudan, Kenya, and Somalia border the country. There are three principal climates in Ethiopia: tropical rainy, dry, and warm temperate. Maximum and minimum average temperatures vary across regions of the country and seasons of the year. Generally, the mean maximum temperature is highest from March to May and the mean minimum temperature is lowest from November to December. Ethiopia’s mean annual distribution of rainfall is influenced by both the westerly and the south-easterly winds. The general distribution of annual rainfall is seasonal and also varies in amount, area, and time as it moves from the southwest to the northeast (MOI, 2004). Economy Ethiopia is an agrarian country and agriculture accounts for 43 percent of the gross domestic product or GDP (CSA, 2009). Coffee has long been one of the main export items of the country; however, other agricultural products are currently being introduced on the international market. The Ethiopian currency is the Birr and at the current exchange rate, 1 US dollar is equivalent to about 17 Birr. Between 1974 and 1991 the country operated a central command economy but has since moved toward a market-oriented economy. Currently, the country has one commercial and two specialized government owned banks and 14 privately owned commercial banks, one government-owned insurance company and eleven private insurance companies. There are also 30 micro-financing institutions established by private organizations (NBE, 2010). To help attain the Millennium Development Goals (MDGs) by 2015, Ethiopia adopted the Plan for Accelerated and Sustained Development to End Poverty (PASDEP), the second poverty reduction strategy, covering the period 2005/06 to 2009/10. In keeping with this plan, the economy has grown in real GDP at a rate of 11 percent per annum in the past five years. With an average population growth rate of 2.6 percent, the GDP growth rate translates to an 8.4 percent growth in average annual per capita income. This rapid growth is the result of diversification and commercialization of small-scale agriculture, expansion of non-agricultural production in services and industry, capacity-building and good governance, off-farm employment especially through small enterprises, and investment in infrastructure (MOFED, 2010). Introduction • 3 The Growth and Transformation Plan (GTP) has been developed for the next five years, designed to maintain rapid and broad-based economic growth and eventually to end poverty (MOFED, 2010). The primary objectives of the GTP are: • Maintain the average real GDP growth rate of 11 percent and meet the MDGs; • Expand and ensure education and health services, thereby achieving the MDGs in the social sectors; • Establish favourable conditions for sustainable state-building through the creation of a stable democratic and developmental state; • Ensure sustainability of growth by realising the above objectives within a stable macroeconomic framework. 1.2 POPULATION Despite Ethiopia’s long history, there were no estimates of its total population prior to the 1930s. The first population and housing census was conducted in 1984. The 1984 census covered about 81 percent of the population, and official estimates were made for the remaining 19 percent. A second census was conducted in 1994, and a third in 2007. Unlike the first census, the second and the third censuses covered the entire population. Table 1.1 provides a summary of the basic demographic indicators for Ethiopia from these three censuses. The population has increased steadily over the last three decades, from 42.6 million in 1984 to 53.5 million in 1994 and 73.8 million in 2007. There were slight declines in the population growth rates over these periods, from 3.1 percent per annum in 1984 to 2.9 percent in 1994 and 2.6 percent in 2007. Table 1.1 Basic demographic indicators Indicator 1984 Census1 1994 Census2 2007 Census3 Population (millions) 42.6 53.5 73.8 Growth rate (percent) 3.1 2.9 2.6 Density (population/km2) 34.0 48.6 67.1 Percent urban 11.4 13.7 16.1 Life expectancy Male 51.1 50.9 na Female 53.4 53.5 na na=Not available 1 Including Eritrea; CSA, 1991 2 CSA, 1998 3 CSA, 2010 Ethiopia is one of the least urbanized countries in the world; only 16 percent of the population lives in urban areas (CSA, 2010). The majority of the population lives in the highland areas. The main occupation of the settled rural population is farming, while the lowland areas are mostly inhabited by a pastoral people, who depend mainly on livestock production and move from place to place in search of grass and water. More than 80 percent of the country’s total population lives in the regional states of Amhara, Oromiya, and SNNP. Christianity and Islam are the main religions; about half of the population are Orthodox Christians, one-third are Muslims, about one in every five (18 percent) are Protestants, and 3 percent 4 • Introduction are followers of traditional religion. The country is home to more than 80 ethnic groups, which vary in population size from more than 26 million people to fewer than 100 (CSA, 2010). Ethiopia has made an effort to generate reliable demographic data by conducting a number of surveys. These include the 1981 Demographic Survey, the 1990 National Family and Fertility Survey (NFFS), the 1995 Fertility Survey of Urban Addis Ababa, and the 2000, 2005, and 2011 Ethiopia Demographic and Health Surveys (EDHS). The 1990 NFFS was the first nationally representative survey to yield substantial information on fertility, family planning, contraceptive use, and related topics. In addition to the topics covered by the NFFS, the 2000, 2005, and 2011 EDHS surveys collected information on maternal and child health, nutrition and breastfeeding practices, and HIV and other sexually transmitted diseases. 1.3 POPULATION AND HEALTH POLICIES National Population Policy Population policies had low priority in Ethiopia until the early 1990s. In 1993 the Transitional Government adopted a national population policy (TGE, 1993a). Since then, developments have taken place nationally and internationally that have a direct bearing on the country’s population. The primary objective of the 1993 national population policy is to harmonize the rate of population growth with socioeconomic development in order to achieve a high level of welfare. The main long-term objective is to close the gap between high population growth rates and low economic productivity and to expedite socioeconomic development through holistic, integrated programmes. Other objectives include preserving the environment, reducing rural-to-urban migration, and reducing morbidity and mortality, particularly infant and child mortality. More specifically, the population policy seeks to accomplish the following: • Reduce the total fertility rate (TFR) from 7.7 children per woman in 1990 to 4.0 children per woman in 2015; • Increase contraceptive prevalence from 4 percent in 1990 to 44 percent in 2015; • Reduce maternal, infant, and child morbidity and mortality rates, as well as promote the general welfare of the population; • Significantly increase female participation at all levels of the educational system; • Remove all legal and customary practices that prevent women from the full enjoyment of economic and social rights, including property rights and access to gainful employment; • Ensure spatially balanced population distribution patterns, with a view to maintaining environmental security and extending the scope of development activities; • Improve productivity in agriculture and introduce off-farm and non-agricultural activities for the purpose of diversifying employment; • Mount an effective countrywide population information and education programme addressing issues pertaining to small family size and its relationship with human welfare and environmental security (TGE, 1993a). Population and development has been considered as a cross cutting issue in the Growth and Transformation Plan and due emphases is given to integrate population issues in sector development plans. Introduction • 5 Health policy Ethiopia had no health policy until the early 1960s, when a health policy initiated by the World Health Organization (WHO) was adopted. In the mid-1970s, during the Derg regime, a health policy was formulated with emphasis on disease prevention and control. This policy gave priority to rural areas and advocated community involvement (TGE, 1993b). The current health policy, promulgated by the Transitional Government, takes into account broader issues such as population dynamics, food availability, acceptable living conditions, and other essentials of better health (TGE, 1993b). To realize the objectives of the health policy, the government established the Health Sector Development Programme (HSDP), which is a 20-year health development strategy implemented through a series of four consecutive 5-year investment programmes (MOH, 2010). The first phase (HSDP I) was initiated in 1996/97. The core elements of the HSDP include: democratisation and decentralisation of the health care system; development of the preventive and curative components of health care; ensuring accessibility of health care for all segments of the population; and, promotion of private sector and NGO participation in the health sector. The HSDP prioritizes maternal and newborn care, and child health, and aims to halt and reverse the spread of major communicable disease such as HIV/AIDS, TB, and malaria. The Health Extension Programme (HEP) serves as the primary vehicle for prevention, health promotion, behavioural change communication, and basic curative care. The HEP is an innovative health service delivery program that aims at universal coverage of primary health care. The programme is based on expanding physical health infrastructure and developing Health Extension Workers (HEWs) who provide basic preventive and curative health services in the rural community. The first phase (HSDP I) was initiated in 1996/97.Thus far, the country has implemented the HSDP in three cycles and is currently extending it into the forth programme, HSDP IV. Assessment of HSDP III shows remarkable achievements in the expansion and construction of health facilities, and improvement in the quality of health service provision. The assessment also shows that in the last five years the distribution of insecticide treated nets (ITN) were successful in reaching targeted areas of the country including areas that are hard to reach, placing Ethiopia as the third largest distributor of ITNs in Sub Saharan Africa (MOH, 2010). HSDP IV is designed to provide massive training of health workers to improve the provision of quality health services and the development of a community health insurance strategy for the country. In addition, HSDP IV will prioritize maternal and newborn care, and child health, and aim to halt and reverse the spread of major communicable disease such as HIV/AIDS, TB and Malaria. In line with the government’s current five-year national plan, the health sector continues to emphasize primary health care and preventive services; with focus on extending services to those who have not yet been reached and on improving the effectiveness of services, especially addressing difficulties in staffing and the flow of drugs. 1.4 OBJECTIVES OF THE 2011 EDHS SURVEY The principal objective of the 2011 Ethiopia Demographic and Health Survey (EDHS) is to provide current and reliable data on fertility and family planning behaviour, child mortality, adult and maternal mortality, children’s nutritional status, use of maternal and child health services, knowledge of HIV/AIDS, and prevalence of HIV/AIDS and anaemia. The specific objectives are these: • Collect data at the national level that will allow the calculation of key demographic rates; 6 • Introduction • Analyse the direct and indirect factors that determine fertility levels and trends; • Measure the levels of contraceptive knowledge and practice of women and men by family planning method, urban-rural residence, and region of the country; • Collect high-quality data on family health, including immunisation coverage among children, prevalence and treatment of diarrhoea and other diseases among children under age five, and maternity care indicators, including antenatal visits and assistance at delivery; • Collect data on infant and child mortality and maternal mortality; • Obtain data on child feeding practices, including breastfeeding, and collect anthropometric measures to assess the nutritional status of women and children; • Collect data on knowledge and attitudes of women and men about sexually transmitted diseases and HIV/AIDS and evaluate patterns of recent behaviour regarding condom use; • Conduct haemoglobin testing on women age 15-49 and children 6-59 months to provide information on the prevalence of anaemia among these groups; • Carry out anonymous HIV testing on women and men of reproductive age to provide information on the prevalence of HIV. This information is essential for informed policy decisions, planning, monitoring, and evaluation of programmes on health in general and reproductive health in particular at both the national and regional levels. A long-term objective of the survey is to strengthen the technical capacity of the Central Statistical Agency to plan, conduct, process, and analyse data from complex national population and health surveys. Moreover, the 2011 EDHS provides national and regional estimates on population and health that are comparable to data collected in similar surveys in other developing countries and to Ethiopia’s two previous DHS surveys, conducted in 2000 and 2005. Data collected in the 2011 EDHS add to the large and growing international database of demographic and health indicators. 1.5 ORGANIZATION OF THE SURVEY The 2011 EDHS was carried out under the aegis of the Ministry of Health (MOH) and was implemented by the Central Statistical Agency (CSA). The testing of the blood samples for HIV status was handled by the Ethiopia Health and Nutrition Research Institute (EHNRI). ICF International provided technical assistance as well as funding to the project through the MEASURE DHS project, a USAID-funded project providing support and technical assistance in the implementation of population and health surveys in countries worldwide. The resources for the conduct of the survey were provided by the government of Ethiopia and various international donor organizations and governments: the United States Agency for International Development (USAID), the HIV/AIDS Prevention and Control Office (HAPCO), the United Nations Population Fund (UNFPA), the United Nations Children’s Fund (UNICEF), the United Kingdom Department for International Development (DFID), and the United States Centers for Disease Control and Prevention (CDC). A steering committee composed of major stakeholders from the government, international organizations, and NGOs was formed. The steering committee was responsible for coordination, Introduction • 7 oversight, advice, and decision-making on all major aspects of the survey. Members of the steering committee include the MOH, CSA, EHNRI, HAPCO, the population Affairs Directorate of the Ministry of Finance and Economic Development (MOFED), the consortium of reproductive Health Associations (CORHA), USAID, UNFPA, UNICEF, the Joint United Nations Programme on HIV/AIDS (UNAIDS), CDC, and WHO. A technical committee was also formed from among the steering committee institutions to oversee all technical issues related to the survey such as questionnaire design, training, and report writing. Ethical clearance for the survey was provided by the EHNRI Review Board, the National Research Ethics Review Committee (NRERC) at the Ministry of Science and Technology, the Institutional Review Board of ICF International, and the CDC. 1.6 SAMPLE DESIGN The sample for the 2011 EDHS was designed to provide population and health indicators at the national (urban and rural) and regional levels. The sample design allowed for specific indicators, such as contraceptive use, to be calculated for each of Ethiopia’s 11 geographic/administrative regions (the nine regional states and two city administrations). The 2007 Population and Housing Census, conducted by the CSA, provided the sampling frame from which the 2011 EDHS sample was drawn. Administratively, regions in Ethiopia are divided into zones, and zones, into administrative units called weredas. Each wereda is further subdivided into the lowest administrative unit, called kebele. During the 2007 census each kebele was subdivided into census enumeration areas (EAs), which were convenient for the implementation of the census. The 2011 EDHS sample was selected using a stratified, two-stage cluster design, and EAs were the sampling units for the first stage. The sample included 624 EAs, 187 in urban areas and 437 in rural areas. Households comprised the second stage of sampling. A complete listing of households was carried out in each of the 624 selected EAs from September 2010 through January 2011. Sketch maps were drawn for each of the clusters, and all conventional households were listed. The listing excluded institutional living arrangements and collective quarters (e.g., army barracks, hospitals, police camps, and boarding schools). A representative sample of 17,817 households was selected for the 2011 EDHS. Because the sample is not self-weighting at the national level, all data in this report are weighted unless otherwise specified. In the Somali region, in 18 of the 65 selected EAs listed households were not interviewed for various reasons, such as drought and security problems, and 10 of the 65 selected EAs were not listed due to security reasons. Therefore, the data for Somali may not be totally representative of the region as a whole. However, national-level estimates are not affected, as the percentage of the population in the EAs not covered in the Somali region is proportionally very small. 1.7. QUESTIONNAIRES The 2011 EDHS used three questionnaires: the Household Questionnaire, the Woman’s Questionnaire, and the Man’s Questionnaire. These questionnaires were adapted from model survey instruments developed for the MEASURE DHS project to reflect the population and health issues relevant to Ethiopia. Issues were identified at a series of meetings with the various stakeholders. In addition to English, the questionnaires were translated into three major languages—Amharigna, Oromiffa, and Tigrigna. The Household Questionnaire was used to list all the usual members and visitors of selected households. Basic information was collected on the characteristics of each person listed, including 8 • Introduction age, sex, education, and relationship to the head of the household. For children under age 18, survival status of the parents was determined. The data on the age and sex of household members obtained in the Household Questionnaire were used to identify women and men who were eligible for the individual interview. The Household Questionnaire also collected information on characteristics of the household’s dwelling unit, such as the source of water, type of toilet facilities, materials used for the floor of the house, and ownership of various consumer durable goods. In addition, this questionnaire was used to record height and weight measurements of eligible women and men and children under age 5, as well as male and female respondents’ voluntary consent to give blood samples. The Woman’s Questionnaire was used to collect information from all women age 15-49. These women were asked questions on the following topics: • Background characteristics such as age, education and media exposure • Birth history and childhood mortality • Knowledge and use of family planning methods • Fertility preferences • Antenatal, delivery and postnatal care • Breastfeeding and infant feeding practices • Vaccinations and childhood illnesses • Marriage and sexual activity • Women’s work • Husband’s background characteristics • Awareness and behaviour regarding AIDS and other sexually transmitted infections (STIs) • Adult mortality, including maternal mortality The Man’s Questionnaire was administered to all men age 15-59 in each household in the 2011 EDHS sample. The Man’s Questionnaire collected much of the same information as the Woman’s Questionnaire but was shorter because it did not contain a detailed reproductive history or questions on maternal and child health. 1.8 LISTING, PRETEST, MAIN TRAINING, FIELDWORK, AND DATA PROCESSING Listing After the selection of the 624 clusters throughout the 11 regions and administrative areas, a listing operation was conducted in the selected clusters for about four months, starting in September 2010. For this purpose, training was conducted for 44 listing staff and 11 supervisors who had been recruited from all the regions and from the CSA head office to carry out the listing of households and preparation of the sketch map for each selected EA. A manual that described the listing and mapping Introduction • 9 procedures was prepared as a guideline, and the training involved both classroom demonstrations and field practice. The listing was performed by organizing the listing staff into teams, with two listers per team. Eleven supervisors were also assigned from the CSA branch offices to perform quality checks and handle all the administrative and financial aspects of the listing operation. Rounds of supervision were carried out by CSA central office staff to assess the quality of the field operation and to ensure proper listing. Pretest Before the start of fieldwork, the questionnaires were pretested in all three local languages to make sure that the questions were clear and could be understood by the respondents. Testing of blood sample collection was also conducted during the pretest. CSA staff and various experts from government ministries and donor organizations participated in a three-week pretest training and fieldwork conducted by staff from ICF International, from 20 September to 8 October 2010. Fifty-five participants were trained to administer paper questionnaires, take anthropometric measurements, and collect blood samples for anaemia and HIV testing. Representatives from EHNRI assisted in training participants on the finger prick for blood collection and proper handling and storage of the dried blood spots (DBS) for HIV testing. The pretest fieldwork was conducted over five days in the selected urban kebeles of Addis Ababa; and in both urban and rural kebeles in the surrounding towns of Ambo, Debre Birhan, Hawassa, and Mekele, covering 191 households. Debriefing sessions were held with the pretest field staff, and the questionnaires were modified based on lessons drawn from the pretest exercise. Main Training Recruitment of interviewers, editors, and supervisors for the main fieldwork was conducted in the nine regions and two city administrations, taking into account the languages of the specific areas. Accommodation was arranged for the trainees and trainers at a training site, Ethiopian Civil Service College in Addis Ababa. CSA recruited and trained 307 people for the main fieldwork to serve as supervisors, editors, male and female interviewers, and reserve interviewers. Also trained were field quality control staff, office editors, and office supervisors. The training of interviewers, editors and supervisors was conducted from 24 November to 23 December 2010. The training consisted of instruction on interviewing techniques and field procedures, a detailed review of the questionnaire content, instruction and practice in weighing and measuring children, mock interviews between participants in the classroom, and practice interviews with real respondents in areas outside the 2011 EDHS sample points. Field practice in anthropometry, anaemia testing, and blood sample collection was also carried out for interviewers who were assigned as team biomarker technicians. Team supervisors and editors were trained in data quality control procedures and fieldwork coordination. The Amharic questionnaires were mainly used during the training, while the Tigrigna and Oromiffa versions were simultaneously checked against the Amharic questionnaires to ensure accurate translation. Fieldwork Thirty-five interviewing teams carried out data collection for the 2011 EDHS. Each team consisted of one team supervisor, one field editor, four female interviewers, two male interviewers, one cook, and one driver. Ten staff members from CSA coordinated and supervised fieldwork activities. An ICF International staff and representatives from other organisations supporting the survey, including EHNRI, CDC, and USAID, participated in fieldwork monitoring. In addition to the field teams, a quality control team was present in each of the 11 regions. Each quality control team 10 • Introduction included a field coordinator, one female and one male staff member to monitor the quality of the interviews, and one biomarker quality control staff member. The quality control teams regularly visited and often stayed with the EDHS teams throughout the fieldwork period to closely supervise and monitor them. Data collection took place over a five-month period from 27 December 2010 to 3 June 2011. Data Processing All questionnaires for the 2011 EDHS were returned to the CSA headquarters in Addis Ababa for data processing, which consisted of office editing, coding of open-ended questions, data entry, and editing computer-identified errors. The data were processed by a team of 32 data entry operators, 6 office editors, and 4 data entry supervisors. Data entry and editing were accomplished using the CSPro software. The processing of data was initiated in January 2011 and completed in June 2011. 1.9 ANTHROPOMETRY, ANAEMIA, AND HIV TESTING The 2011 EDHS included height and weight measurement, anaemia testing, and blood sample collection for HIV testing in the laboratory. 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 measuring board. Children younger than 24 months were measured for height while lying down, and older children, while standing. Anaemia Testing Blood specimens were collected for anaemia testing from all children age 6-59 months, women age 15-49, and men age 15-59 who voluntarily consented to the testing. Blood samples were drawn from a drop of blood taken from a finger prick (or a heel prick in the case of young children with small fingers) and collected in a microcuvette. Haemoglobin analysis was carried out onsite using a battery-operated portable HemoCue analyser. Results were given verbally and in writing. Parents of children with a haemoglobin level under 7 g/dl were instructed to take the child to a health facility for follow-up care. Likewise, non- pregnant women were referred for follow-up care if their haemoglobin level was below 7 g/dl, and pregnant women and men were referred if their haemoglobin level was below 9 g/dl. All households in which anaemia testing was conducted received a brochure explaining the causes and prevention of anaemia. HIV Testing Blood specimens for laboratory testing of HIV were collected by the EDHS biomarker technicians from all women age 15-49 and men age 15-59 who consented to the test. The protocol for the blood specimen collection and analysis was based on the anonymous linked protocol developed for MEASURE DHS. This protocol allows for the merging of the HIV test results with the socio- demographic data collected in the individual questionnaires after all information that could potentially identify an individual respondent has been destroyed. Introduction • 11 Interviewers explained the procedure, the confidentiality of the data, and the fact that the test results would not be made available to the respondent. If a respondent consented to the HIV testing, five blood spots from the finger prick were collected on a filter paper card labelled with a barcode unique to the respondent. Respondents were asked whether they consented to having the laboratory store their blood sample for future unspecified testing. If the respondent did not consent to additional testing using their sample, the words “no additional testing” were written on the filter paper card. Each household, whether individuals consented to HIV testing or not, received an informational brochure on HIV/AIDS and a list of fixed sites providing voluntary counselling and testing (VCT) services within the surrounding 10 km radius from the cluster for each region. For households farther than 10 km from a fixed VCT site, mobile VCT units were set up in or near survey areas following data collection. The USAID and CDC partners provided the logistical services for the provisions of mobile VCT services. For each barcoded blood sample, a duplicate label was attached to the Biomarker Data Collection Form. A third copy of the same barcode was affixed to the Blood Sample Transmittal Form to track the blood samples from the field to the laboratory. Blood samples were dried overnight and packaged for storage the following morning. Samples were periodically collected in the field, along with the completed questionnaires, and transported to CSA in Addis Ababa to be logged in and checked; blood samples were then transported and submitted for testing to EHNRI in Addis Ababa. Upon arrival at EHNRI, each blood sample was logged into the CSPro HIV Test Tracking System (CHTTS) database, given a laboratory number, and stored at −20˚C until tested. The HIV testing protocol stipulates that testing of blood can be conducted only after the questionnaire data entry is completed, verified, and cleaned, and all unique identifiers except the anonymous barcode number are removed from the questionnaire file. The testing algorithm calls for testing all samples on the first ELISA assay test, the Vironostika® HIV Uni-Form II Plus O (Biomerieux). All positives were subjected to a second ELISA, the Murex HIV Ag/Ab Combination. If the first and second tests were discordant, a third confirmatory test, the HIV 2.2 western blot (DiaSorin), was conducted to resolve the discordance. The final result was rendered positive if the western blot confirmed the result to be positive and was rendered negative if the western blot confirmed it to be negative. When the western blot results were indeterminate, the sample result was recorded indeterminate. Following HIV testing, the HIV test results for the 2011 EDHS were entered into the CHTTS database with a barcode as the unique identifier to the result. The barcodes identifying the HIV test results were linked with the data from the individual interviews to enable analysis and publication of HIV data linked with other EDHS data. 1.10 RESPONSE RATES Table 1.2 shows household and individual response rates for the 2011 EDHS. A total of 17,817 households were selected for the sample, of which 17,018 were found to be occupied during data collection. Of these, 16,702 were successfully interviewed, yielding a household response rate of 98 percent. In the interviewed households 17,385 eligible women were identified for individual interview; complete interviews were conducted for 16,515, yielding a response rate of 95 percent. Similarly, a total of 15,908 eligible men were identified for interview; completed interviews were conducted for 14,110, yielding a response rate of 89 percent. In general, response rates were higher in rural areas than urban areas, for both women and men. 12 • Introduction Table 1.2 Results of the household and individual interviews Number of households, number of interviews, and response rates, according to residence (unweighted), Ethiopia 2011 Result Residence Total Urban Rural Household interviews Households selected 5,518 12,299 17,817 Households occupied 5,272 11,746 17,018 Households interviewed 5,112 11,590 16,702 Household response rate1 97.0 98.7 98.1 Interviews with women age 15-49 Number of eligible women 5,656 11,729 17,385 Number of eligible women interviewed 5,329 11,186 16,515 Eligible women response rate2 94.2 95.4 95.0 Interviews with men age 15-59 Number of eligible men 5,062 10,846 15,908 Number of eligible men interviewed 4,216 9,894 14,110 Eligible men response rate2 83.3 91.2 88.7 1 Households interviewed/households occupied 2 Respondents interviewed/eligible respondents Due to the non-proportional allocation of the sample to the different regions and to their urban and rural areas, sampling weights are used for analyzing the 2011 EDHS data to ensure the actual representativeness of the survey results at the national and regional level (for more information on sample weights, see Appendix A) . Whenever applicable, both weighted and unweighted numbers are used in the tables of this report. Housing Characteristics and Household Population • 13 HOUSING CHARACTERISTICS AND HOUSEHOLD POPULATION 2 his chapter summarizes demographic and socioeconomic characteristics of the population in the households sampled in the 2011 EDHS. The survey collected information from all usual residents of a selected household (the de jure population) and persons who had stayed in the selected household the night before the interview (the de facto population). Since the difference between these two populations is very small, and to maintain comparability with other DHS reports, all tables in this report refer to the de facto population unless otherwise specified. In the EDHS a household was defined as a single person or a group of related or unrelated persons who live together in the same dwelling unit(s) or in connected premises, who acknowledge one adult member as head of the household, and who have common arrangements for cooking and eating. The Household Questionnaire (see Appendix E) included a schedule collecting basic demographic and socioeconomic information (e.g., age, sex, educational attainment, and current school attendance) for all usual residents and for visitors who spent the night preceding the interview in the household. The Household Questionnaire also obtained information on housing characteristics (e.g., sources of water supply and sanitation facilities) and household possessions. The information presented in this chapter is intended to facilitate interpretation of the key demographic, socioeconomic, and health indices presented later in the report. It is also intended to assist in the assessment of the representativeness of the survey sample. 2.1 HOUSEHOLD ENVIRONMENT Physical characteristics of a household’s environment are important determinants of the health status of household members, especially children. They can also serve as indicators of the socioeconomic status of households. The 2011 EDHS asked respondents about their household environment, including access to electricity, source of drinking water, type of sanitation facility, type of flooring material, and number of rooms in the dwelling. The results are presented here in terms of households and of the de jure population. 2.1.1 Drinking Water Increasing access to improved drinking water is one of the Millennium Development Goals that Ethiopia and other nations worldwide have adopted (United Nations General Assembly, 2002). Table 2.1 presents a number of indicators that are useful in monitoring household access to improved drinking water. The source of the water is an indicator of whether it is suitable for drinking. In Table T Key Findings • More than half of households in Ethiopia (54 percent) have access to an improved source of drinking water. • Only 8 percent of households have an improved toilet facility, not shared with other households. • About one household in every four (23 percent) is electrified. • A large proportion of the Ethiopian population (47 percent) is under age 15. • More than one household in every four (26 percent) is female-headed. • Twenty-seven percent of Ethiopian children age 5-14 are engaged in child labour. 14 • Housing Characteristics and Household Population 2.1 sources that are likely to provide water suitable for drinking are identified as improved sources. These include a piped source within the dwelling, yard, or plot; a public tap/stand pipe, or borehole; a protected well; spring water and rainwater (WHO and UNICEF Joint Monitoring Program for Water Supply and Sanitation, 2010). Lack of easy access to a water source may limit the quantity of suitable drinking water that is available to a household. Even if the water is obtained from an improved source, when the water needs to be fetched from a source that is not immediately accessible to the household, it may become contaminated during transport or storage. Especially in such situations, home water treatment can be effective in improving the quality of household drinking water. Another factor in considering access to a water source is that the burden of fetching water often falls disproportionately on female members of the household. 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 by treatment of drinking water, according to residence, Ethiopia 2011 Characteristic Households Population Urban Rural Total Urban Rural Total Source of drinking water Improved source Piped into dwelling 4.2 0.0 1.0 4.9 0.0 0.9 Piped to yard/plot 44.2 0.1 10.1 41.9 0.1 7.6 Public tap/standpipe 38.6 18.8 23.3 38.6 18.9 22.5 Borehole 1.1 4.0 3.3 1.0 4.0 3.5 Protected well 4.1 7.6 6.8 3.7 7.6 6.9 Protected spring 2.0 11.1 9.0 2.4 10.8 9.3 Rainwater 0.1 0.2 0.1 0.2 0.2 0.2 Bottled water 0.3 0.0 0.1 0.1 0.0 0.0 Non-improved source 5.2 58.0 46.0 7.0 58.1 48.9 Unprotected well 0.5 4.5 3.6 0.8 4.7 4.0 Unprotected spring 2.5 32.0 25.3 3.0 32.1 26.9 Tanker truck/cart with small tank 1.4 0.5 0.7 2.0 0.4 0.7 Surface water (river/lake/pond/stream dam) 0.8 21.0 16.4 1.2 20.9 17.3 Other source 0.2 0.3 0.3 0.2 0.3 0.3 Total 100.0 100.0 100.0 100.0 100.0 100.0 Percentage using any improved source of drinking water 94.5 41.7 53.7 92.8 41.6 50.8 Time to obtain drinking water (round trip) Water on premises 50.4 1.3 12.5 49.0 1.4 10.0 Less than 30 minutes 30.1 35.9 34.6 29.1 34.8 33.8 30 minutes or longer 18.9 62.4 52.6 21.4 63.6 56.0 Don't know/missing 0.6 0.3 0.4 0.4 0.3 0.3 Total 100.0 100.0 100.0 100.0 100.0 100.0 Person who usually collects drinking water Adult woman 34.0 70.7 62.4 35.3 69.3 63.1 Adult man 8.8 7.3 7.6 6.6 5.8 5.9 Female child under 15 years old 3.8 14.9 12.4 5.3 17.6 15.4 Male child under 15 years old 1.8 4.9 4.2 2.8 5.2 4.8 Other 1.0 0.9 0.9 0.9 0.7 0.7 Water on premises 50.4 1.3 12.5 49.0 1.4 10.0 Missing 0.2 0.0 0.1 0.1 0.0 0.1 Total 100.0 100.0 100.0 100.0 100.0 100.0 Water treatment prior to drinking1 Boiled 3.8 2.4 2.7 4.0 2.2 2.6 Bleach/chlorine added2 9.2 4.9 5.8 9.3 4.9 5.7 Strained through cloth 0.6 1.4 1.2 0.5 1.5 1.3 Bio-sand, composite, ceramic pot filter 0.4 0.2 0.2 0.6 0.2 0.2 Let it stand and settle 0.0 0.2 0.1 0.0 0.2 0.2 Other 0.5 0.1 0.2 0.6 0.1 0.2 No treatment 86.9 91.1 90.2 86.3 91.1 90.2 Percentage using an appropriate treatment method3 12.3 8.2 9.1 12.9 8.3 9.1 Weighted number 3,780 12,922 16,702 13,939 63,438 77,377 Unweighted number 5,112 11,590 16,702 18,917 56,738 75,655 1 Respondents may report multiple treatment methods; therefore, the sum of treatments may exceed 100 percent. 2 Includes use of water guard, Pur, Bishan Gari, and aquatabs 3 Appropriate water treatment methods include boiling, bleaching, straining, and filtering. Housing Characteristics and Household Population • 15 As Table 2.1 shows, more than half of the households in Ethiopia (54 percent) have access to an improved source of drinking water, with a much higher proportion among urban households (95 percent) than among rural households (42 percent). The most common source of improved drinking water in urban households is piped water, used by 87 percent of urban households. In contrast, only 19 percent of rural households have access to piped water. Eleven percent of rural households have access to drinking water from a protected spring, and 8 percent have access to drinking water from a protected well. Nationally, the proportion of Ethiopian households with access to piped water has increased from 18 percent in 2000 to 24 percent in 2005 and 34 percent in 2011. In the last six years there has been a rapid increase in the percentage of households in Ethiopia that use some type of improved source of drinking water, from 35 percent in the 2005 EDHS to 54 percent in the 2011 EDHS.1 In the 2011 EDHS only 13 percent of households reported having water on their premises. Households not having water on their premises were asked how long it takes to fetch water. Thirty- five percent of all households (30 percent in urban areas and 36 percent in rural areas) take less than 30 minutes to fetch drinking water. More than half of all households (53 percent) travel 30 minutes or more to fetch their drinking water (19 percent in urban areas and 62 percent in rural areas). Women in Ethiopia, especially in rural areas, bear the burden of collecting drinking water. In six of every ten households (62 percent), adult women are responsible for water collection. In rural households adult women are ten times more likely than adult men to usually fetch the water for the household (71 percent versus 7 percent). Even in urban households women are almost four times more likely than men to collect water (34 percent versus 9 percent). Female children under age 15 are about three times more likely than male children of the same age group to fetch drinking water (12 percent versus 4 percent). In the 2011 EDHS all households also were asked whether they treat their drinking water. An overwhelming majority, nine households in every ten, do not treat their drinking water. Urban households (12 percent) are somewhat more likely than rural households (8 percent) to use an appropriate treatment method to ensure that water is safe for drinking. 2.1.2 Household Sanitation Facilities Ensuring adequate sanitation facilities is another Millennium Development Goal that Ethiopia shares with other countries. At the household level, adequate sanitation facilities include an improved toilet and disposal that separates waste from human contact. A household is classified as having an improved toilet if it is used only by members of one household (that is, it is not shared) and if the facility used by the household separates the waste from human contact (WHO and UNICEF, 2010). 1 There was an error in the 2005 Ethiopia DHS Final Report in the proportion of households with access to an improved source of drinking water. The error occurred because the codes for protected and unprotected spring water were reversed. The total percentage of households with an improved source of drinking water was actually 35 percent and not 61 percent as reported. 16 • Housing Characteristics and Household Population Table 2.2 shows that 8 percent of households in Ethiopia use improved toilet facilities that are not shared with other households, 14 percent in urban areas and 7 percent in rural areas. One in ten households (32 percent in urban areas and 3 percent in rural areas) use shared toilet facilities. The large majority of households, 82 percent, use non-improved toilet facilities (91 percent in rural areas and 54 percent in urban areas). The most common type of non-improved toilet facility is an open pit latrine or pit latrine without slabs, used by 45 percent of households in rural areas and 37 percent of households in urban areas. Overall, 38 percent of households have no toilet facility, 16 percent in urban areas and 45 percent in rural areas. Table 2.2 Household sanitation facilities Percent distribution of households and de jure population by type of toilet/latrine facilities, according to residence, Ethiopia 2011 Type of toilet/latrine facility Households Population Urban Rural Total Urban Rural Total Improved, not shared facility 14.1 6.6 8.3 18.2 6.8 8.8 Flush/pour flush to piped sewer system 1.9 0.0 0.5 2.4 0.0 0.5 Flush/pour flush to septic tank 1.2 0.1 0.4 1.6 0.1 0.4 Flush/pour flush to pit latrine 1.4 0.9 1.0 1.7 1.0 1.1 Ventilated improved pit (VIP) latrine 1.2 1.0 1.0 1.7 1.0 1.1 Pit latrine with slab 7.2 1.1 2.5 9.2 1.1 2.6 Composting toilet 1.2 3.5 3.0 1.6 3.6 3.2 Shared facility1 32.2 2.8 9.5 26.7 2.2 6.7 Flush/pour flush to piped sewer system 0.5 0.0 0.1 0.4 0.0 0.1 Flush/pour flush to septic tank 0.8 0.1 0.3 0.9 0.1 0.2 Flush/pour flush to pit latrine 1.5 0.2 0.5 1.3 0.2 0.4 Ventilated improved pit (VIP) latrine 2.0 0.3 0.7 1.7 0.2 0.5 Pit latrine with slab 24.4 1.0 6.3 20.2 0.8 4.3 Composting toilet 2.9 1.2 1.6 2.3 0.9 1.2 Non-improved facility 53.7 90.6 82.2 55.0 91.0 84.5 Flush/pour flush not to sewer/septic tank/pit latrine 0.1 0.1 0.1 0.2 0.1 0.1 Pit latrine without slab/open pit 37.1 45.4 43.5 38.3 47.7 46.0 Hanging toilet/hanging latrine 0.1 0.0 0.0 0.2 0.0 0.0 No facility/bush/field 15.9 44.8 38.3 16.1 43.0 38.2 Other 0.3 0.2 0.2 0.2 0.1 0.1 Missing 0.1 0.1 0.1 0.1 0.1 0.1 Total 100.0 100.0 100.0 100.0 100.0 100.0 Weighted number 3,780 12,922 16,702 13,939 63,438 77,377 Unweighted number 5,112 11,590 16,702 18,917 56,738 75,655 1 Facilities that would be considered improved if they were not shared by two or more households. 2.1.3 Housing Characteristics Table 2.3 presents housing characteristics of households in Ethiopia. Housing characteristics reflect the household’s socioeconomic situation. They also may influence environmental conditions— for example, in the use of biomass fuels and resulting exposure to indoor air pollution—that have a direct bearing on the health and welfare of household members. Housing Characteristics and Household Population • 17 Table 2.3 Household characteristics Percent distribution of households by housing characteristics, percentage using solid fuel for cooking, and percent distribution by frequency of smoking in the home, according to residence, Ethiopia 2011 Housing characteristic Residence Total Urban Rural Electricity Yes 85.2 4.8 23.0 No 14.8 95.2 77.0 Total 100.0 100.0 100.0 Flooring material Earth/sand 32.8 56.0 50.7 Dung 15.3 39.5 34.0 Wood/planks 0.4 0.1 0.1 Palm/bamboo 0.7 0.7 0.7 Parquet or polished wood 1.1 0.0 0.2 Vinyl or asphalt strips 23.8 1.0 6.2 Ceramic tiles 1.5 0.0 0.4 Cement 15.5 1.1 4.3 Carpet 8.4 0.9 2.6 Other 0.6 0.7 0.7 Total 100.0 100.0 100.0 Rooms used for sleeping One 67.8 71.0 70.3 Two 25.9 24.5 24.8 Three or more 6.2 4.2 4.6 Missing 0.2 0.3 0.3 Total 100.0 100.0 100.0 Place for cooking In the house 29.3 59.3 52.5 In a separate building 49.4 32.5 36.3 Outdoors 15.8 7.4 9.3 Other 0.1 0.1 0.1 No food cooked in the house 5.4 0.8 1.8 Total 100.0 100.0 100.0 Cooking fuel Electricity 2.9 0.0 0.7 LPG/natural gas/biogas 1.3 0.0 0.3 Kerosene 10.1 0.1 2.4 Charcoal 29.9 1.2 7.7 Wood 45.9 86.2 77.0 Straw/shrubs/grass 0.3 1.1 0.9 Agricultural crop 1.3 2.2 2.0 Animal dung 2.8 8.3 7.0 Other 0.1 0.1 0.1 No food cooked in household 5.4 0.8 1.8 Total 100.0 100.0 100.0 Percentage using solid fuel for cooking1 80.2 99.0 94.7 Frequency of smoking in the home Daily 6.6 7.2 7.1 Weekly 3.0 2.5 2.6 Monthly 0.7 0.6 0.6 Less than monthly 1.0 1.1 1.1 Never 88.7 88.6 88.6 Total 100.0 100.0 100.0 Weighted number 3,780 12,922 16,702 Unweighted number 5,112 11,590 16,702 LPG = Liquid petroleum gas 1 Includes charcoal, wood, straw/shrubs/grass, agricultural crops, and animal dung Only about one household in every four (23 percent) has electricity, with a very large disparity between urban and rural households (85 percent versus 5 percent). In urban areas the proportion of households with electricity rose from 76 percent in 2000 to 86 percent in 2005 but then remained virtually unchanged in 2011 at 85 percent. In rural areas the percentage increased from less than 1 percent in 2000 to 2 percent in 2005 and 5 percent in 2011. More than half (51 percent) of households have earth or sand floors, and about one-third (34 percent) have dung floors. Rural houses are more likely than urban houses to have earth, sand, or 18 • Housing Characteristics and Household Population dung floors, while urban houses are more likely to have floors made with vinyl or asphalt strips or with cement. The number of rooms used for sleeping in relation to the number of household members is an indicator of the extent of crowding, which in turn increases the risk of contracting communicable diseases. Overall, 70 percent of Ethiopian households use one room for sleeping, 25 percent use two rooms, and 5 percent use three or more rooms for sleeping. More than half (53 percent) of households cook in the housing unit where they live, while more than one-third (36 percent) use a separate building, and about one household in every ten (9 percent) cooks outdoors. Cooking and heating with solid fuels can lead to high levels of indoor smoke, which consists of a complex mix of pollutants that could increase the risk of contracting diseases. Solid fuels include charcoal, wood, straw, shrubs, grass, agricultural crops, and animal dung. The great majority (95 percent) of households primarily use solid fuel for cooking. The practice is nearly universal in with rural households, at 99 percent, and very common in urban households (80 percent) as well. Wood is the main type of cooking fuel, used by 77 percent of households (46 percent of urban households and 86 of rural households). In addition to wood, charcoal and kerosene are important types of cooking fuel in urban areas; 30 percent of urban households use charcoal and 10 percent use kerosene for cooking. The 2011 EDHS collected information on the frequency of smoking tobacco in the home. Table 2.2 shows that 7 percent of households are exposed to daily smoking and 3 percent are exposed weekly. There is little difference between rural and urban areas. 2.1.4 Household Possessions The availability of durable consumer goods is another indicator of a household’s socioeconomic status. Moreover, particular goods have specific benefits. For instance, a radio or a television can bring household members information and new ideas; a refrigerator prolongs the wholesomeness of foods; and a means of transport can increase access to many services that are beyond walking distance. Table 2.4 shows the extent of possession of selected consumer goods by urban or rural residence. Forty-one percent of households have radios, 25 percent have mobile telephones, 10 percent have televisions, 5 percent have non-mobile telephones, and 4 percent have refrigerators. In both urban and rural areas only a small percentage of households possess a means of transport. Urban households are slightly more likely than rural households to own bicycles (6 percent versus 1 percent) or a car or lorry (4 percent versus less than 1 percent). Three-fourths of all households own agricultural land (73 percent) or farm animals (76 percent). There is noticeable urban-rural variation in the proportion of households owning specific goods. Most of the electronic goods are considerably more prevalent in urban areas, while farm- oriented possessions are more common in rural areas. For example, 42 percent of urban households own televisions, compared with only 1 percent of rural households. Similarly, 65 percent of urban households own mobile telephones, compared with 13 percent of rural households. As expected, ownership of agricultural land is much more widespread among rural than urban households (88 percent versus 23 percent), as is ownership of farm animals (90 percent versus 31 percent). Housing Characteristics and Household Population • 19 Table 2.4 Household possessions Percentage of households possessing various household effects, means of transportation, agricultural land, and livestock/farm animals, by residence, Ethiopia 2011 Possession Residence Total Urban Rural Household effects Radio 63.9 33.7 40.5 Television 42.1 1.1 10.4 Mobile telephone 65.2 12.8 24.7 Non-mobile telephone 19.0 0.2 4.5 Refrigerator 14.3 0.6 3.7 Means of transportation Bicycle 5.6 1.4 2.3 Animal-drawn cart 0.7 1.1 1.0 Motorcycle/scooter 0.6 0.1 0.2 Car/truck 3.6 0.1 0.9 Ownership of agricultural land 22.5 87.8 73.1 Ownership of farm animals1 30.5 89.5 76.1 Weighted number 3,780 12,922 16,702 Unweighted number 5,112 11,590 16,702 1 Milk cows, oxen, bulls, horses, donkeys, mules, camels, goats, sheep, or chickens 2.2 WEALTH INDEX The wealth index used in this survey is a measure that has been used in many DHS and other country-level surveys to indicate inequalities in household characteristics, in the use of health and other services, and in health outcomes (Rutstein et al., 2000). It serves as an indicator of level of wealth that is consistent with expenditure and income measures (Rutstein, 1999). The index was constructed using household asset data via a principal components analysis. In its current form, which takes better account of urban-rural differences in scores and indicators of wealth, the wealth index is created in three steps. In the first step, a subset of indicators common to urban and rural areas is used to create wealth scores for households in both areas. Categorical variables to be used are transformed into separate dichotomous (0-1) indicators. These indicators and those that are continuous are then examined using a principal components analysis to produce a common factor score for each household. In the second step, separate factor scores are produced for households in urban and rural areas using area-specific indicators. The third step combines the separate area-specific factor scores to produce a nationally applicable combined wealth index by adjusting area-specific scores through a regression on the common factor scores. This three- step procedure permits greater adaptability of the wealth index in both urban and rural areas. The resulting combined wealth index has a mean of zero and a standard deviation of one. Once the index is computed, national-level wealth quintiles (from lowest to highest) are obtained by assigning the household score to each de jure household member, ranking each person in the population by his or her score, and then dividing the ranking into five equal categories, each comprising 20 percent of the population. Table 2.5 presents the wealth quintiles by residence and administrative regions of the country. In urban areas 88 percent of the population is in the highest wealth quintile, in sharp contrast to the rural areas, where only 5 percent of the population are in the highest wealth quintile. Among regions the wealth quintile distribution varies greatly. A relatively high percentage of the population in the most urbanized regions is in the highest wealth quintile—Addis Ababa (99 percent), Dire Dawa (66 percent), and Harari (60 percent). In contrast, a significant proportion of the population in the 20 • Housing Characteristics and Household Population more rural regions are in the lowest wealth quintile, as in Affar (57 percent), Somali (44 percent), and Gambela (35 percent). Table 2.5 also shows the Gini Coefficient of wealth in Ethiopia, which indicates the concentration of wealth, with 0 representing an exactly equal distribution (everyone having the same amount of wealth) and 1 representing a totally unequal distribution (one person having all the wealth). The overall Gini Coefficient for Ethiopia is 0.23. It is much higher in urban areas (0.14) than in rural areas (0.07), indicating a more unequal distribution of wealth in the urban population than in the rural population. The lowest Gini Coefficient is seen in Addis Ababa (0.02) where almost the entire population (99 percent) is in the highest wealth quintile. The highest Gini Coefficient—that is, the least equitable distribution of wealth—is observed in Affar and Gambela (both 0.29). Table 2.5 Wealth quintiles Percent distribution of the de jure population by wealth quintiles, and the Gini Coefficient, according to residence and region, Ethiopia 2011 Residence/region Wealth quintile Total Weighted number Unweighted number Gini Coefficient Lowest Second Middle Fourth Highest Residence Urban 2.3 1.0 1.1 8.0 87.6 100.0 13,939 18,917 0.14 Rural 23.9 24.2 24.1 22.6 5.1 100.0 63,438 56,738 0.07 Region Tigray 25.8 22.3 16.1 13.1 22.7 100.0 5,035 7,794 0.26 Affar 57.0 9.5 4.9 6.9 21.7 100.0 667 6,048 0.29 Amhara 22.4 22.7 21.8 17.1 16.0 100.0 19,478 9,264 0.20 Oromiya 16.0 20.9 22.4 25.3 15.4 100.0 29,800 10,325 0.19 Somali 43.9 8.0 9.7 11.6 26.8 100.0 1,810 5,150 0.20 Benishangul-Gumuz 29.7 18.7 19.0 20.2 12.3 100.0 809 5,978 0.18 SNNP 21.7 20.4 20.6 21.0 16.2 100.0 16,069 10,169 0.17 Gambela 34.9 7.5 8.0 22.7 26.9 100.0 284 5,473 0.29 Harari 2.0 6.5 10.0 21.4 60.1 100.0 213 4,865 0.26 Addis Ababa 0.3 0.2 0.1 0.4 98.9 100.0 2,919 5,710 0.02 Dire Dawa 8.0 9.7 11.0 5.7 65.7 100.0 291 4,879 0.23 Total 20.0 20.0 20.0 20.0 20.0 100.0 77,377 75,655 0.23 2.3 POPULATION BY AGE AND SEX Age and sex are important variables that are the primary basis for demographic classification in vital statistics, censuses, and surveys. They are also important variables for the study of mortality, fertility, and marriage. Table 2.6 Household population by age, sex, and residence Percent distribution of the de facto household population by five-year age groups, according to sex and residence, Ethiopia 2011 Age Urban Rural Total Male Female Total Male Female Total Male Female Total <5 11.8 10.2 10.9 17.2 15.7 16.4 16.3 14.6 15.4 5-9 13.1 10.5 11.7 18.0 17.2 17.6 17.1 15.9 16.5 10-14 13.0 13.0 13.0 15.9 13.9 14.9 15.4 13.8 14.6 15-19 11.1 14.7 13.0 8.9 10.2 9.6 9.3 11.0 10.2 20-24 11.0 12.6 11.8 7.0 7.3 7.2 7.7 8.3 8.0 25-29 9.7 11.0 10.4 6.5 7.9 7.2 7.1 8.5 7.8 30-34 7.0 6.7 6.8 4.5 5.1 4.8 4.9 5.4 5.1 35-39 6.6 5.4 6.0 4.8 5.0 4.9 5.1 5.1 5.1 40-44 4.7 3.6 4.1 3.5 3.4 3.4 3.7 3.4 3.5 45-49 3.1 2.3 2.6 2.7 2.9 2.8 2.8 2.8 2.8 50-54 2.4 3.0 2.7 2.1 3.3 2.7 2.1 3.2 2.7 55-59 1.4 1.8 1.7 1.7 3.0 2.4 1.7 2.7 2.2 60-64 1.8 1.5 1.6 2.2 1.8 2.0 2.1 1.8 1.9 65-69 1.3 1.2 1.2 1.9 1.1 1.5 1.8 1.1 1.5 70-74 0.8 0.9 0.9 1.3 1.1 1.2 1.2 1.1 1.1 75-79 0.5 0.5 0.5 0.7 0.5 0.6 0.7 0.5 0.6 80 + 0.7 1.0 0.9 1.1 0.7 0.9 1.0 0.8 0.9 Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 Weighted number 6,346 7,412 13,758 30,731 31,808 62,539 37,077 39,219 76,296 Unweighted number 8,653 9,964 18,617 27,037 28,442 55,479 35,690 38,406 74,096 Housing Characteristics and Household Population • 21 Table 2.6 shows the distribution of the household population in the 2011 EDHS by five-year age groups, according to urban or rural residence and sex. The total population counted in the survey was 76,296, with females slightly outnumbering males (39,219 compared with 37,077). The results indicate an overall sex ratio of 95 males per 100 females. The sex ratio is higher in rural areas (97 males per 100 females) than in urban areas (86 males per 100 females). The age structure of the household population in Ethiopia is typical of a society with a young population. The population pyramid in Figure 2.1 shows the sex and age distribution of the population. The pyramidal age structure reflects the large number of children under age 15. Children under age 15 account for nearly half (47 percent) of the total population, a feature of populations with high fertility levels, while only about 4 percent of Ethiopians are over age 65. This population distribution is similar to that observed in the 2000 and 2005 surveys. Figure 2.1 Population Pyramid EDHS 2011 80 + 75-79 70-74 65-69 60-64 55-59 50-54 45-49 40-44 35-39 30-34 25-29 20-24 15-19 10-14 5-9 <5 Age 0246810 0 2 4 6 8 10 Male Fem ale Percentage of total population 2.4 HOUSEHOLD COMPOSITION Table 2.7 presents information about the composition of households by sex of the household head and size of the household. These characteristics are important because they are associated with household welfare. About one-quarter (26 percent) of Ethiopian households are headed by women, a slight increase from 23 percent in 2005. Average household size is 4.6 persons, which is slightly lower than the average of 5.0 persons per household reported in 2005. Urban households have fewer members than rural households. In urban areas the average household size is 3.7 persons, compared with 4.9 persons in rural areas. Single-person households are more common in urban areas (17 percent) than in rural areas (5 percent). Also, a much lower 22 • Housing Characteristics and Household Population proportion of urban households (19 percent) have six or more members than do rural households (38 percent). The 2011 EDHS also collected information on the presence in households of foster children and orphans. Foster children are children under age 18 living in households with neither their mother nor their father present; orphans are children with one or both parents dead. Foster children and orphans are of concern because they may be neglected or exploited if no parent is present. There is little difference between rural and urban areas in the distribution of orphans. Overall, 19 percent of households have foster children, with little variation between urban and rural households. Single orphans (one parent dead) are present in 11 percent of households, whereas double orphans (both parents dead) are present in 1 percent of households. Table 2.7 Household composition Percent distribution of households by sex of head of household and by household size; mean size of household, and percentage of households with orphans and foster children under 18 years of age, according to residence, Ethiopia 2011 Characteristic Residence Total Urban Rural Household headship Male 64.2 76.8 73.9 Female 35.8 23.2 26.1 Total 100.0 100.0 100.0 Number of usual members 0 0.2 0.1 0.1 1 16.5 5.0 7.6 2 18.5 9.9 11.9 3 17.8 14.2 15.0 4 14.1 16.0 15.5 5 14.1 16.9 16.3 6 8.4 14.0 12.7 7 4.7 10.4 9.1 8 2.4 7.3 6.2 9+ 3.3 6.2 5.5 Total 100.0 100.0 100.0 Mean size of households 3.7 4.9 4.6 Percentage of households with orphans and foster children under 18 years of age Foster children1 21.2 18.9 19.4 Double orphans 1.9 1.3 1.4 Single orphans2 10.2 11.7 11.3 Foster and/or orphan children 25.7 25.6 25.6 Weighted number 3,780 12,922 16,702 Unweighted number 5,112 11,590 16,702 Note: Table is based on de jure household members, i.e., usual residents. 1 Foster children are those under age 18 living in households with neither their mother nor their father present. 2 Includes children with one dead parent and an unknown survival status of the other parent. 2.5 CHILDREN’S LIVING ARRANGEMENTS AND PARENTAL SURVIVAL Table 2.8 presents data on children’s living arrangements and orphanhood in Ethiopia. Seventy-two percent of children under age 18 live with both parents; 14 percent live with their mothers but not their fathers; 3 percent live with their fathers but not their mothers; and 11 percent live with neither of their natural parents. Housing Characteristics and Household Population • 23 The proportion of children living with both parents decreases with age. That is, younger children are more likely than older children to live with both parents. The proportion of children living with both parents varies little by the child’s sex. Rural children are substantially more likely to live with both parents than urban children (74 percent versus 58 percent). Among regions of the country, the highest proportion of children living with both parents is in Benishangul-Gumuz (75 percent), while the lowest proportion is in Addis Ababa (52 percent). The percentage of children living with both parents tends to decrease with an increase in household wealth. 24 • H ou si ng C ha ra ct er is tic s an d H ou se ho ld P op ul at io n Ta bl e 2. 8 C hi ld re n' s liv in g ar ra ng em en ts a nd o rp ha nh oo d P er ce nt d is tri bu tio n of d e ju re c hi ld re n un de r 1 8 ye ar s of a ge b y liv in g ar ra ng em en ts a nd s ur vi va l s ta tu s of p ar en ts , t he p er ce nt ag e of c hi ld re n no t l iv in g w ith a b io lo gi ca l p ar en t, an d th e pe rc en ta ge o f c hi ld re n w ith o ne o r b ot h pa re nt s de ad , a cc or di ng to b ac kg ro un d ch ar ac te ris tic s, E th io pi a 20 11 B ac kg ro un d ch ar ac te ris tic Li vi ng w ith b ot h pa re nt s Li vi ng w ith m ot he r bu t n ot w ith fa th er Li vi ng w ith fa th er bu t n ot w ith m ot he r N ot li vi ng w ith e ith er p ar en t To ta l P er ce nt ag e no t l iv in g w ith a bi ol og ic al pa re nt P er ce nt ag e w ith o ne o r bo th p ar en ts de ad 1 W ei gh te d nu m be r o f ch ild re n U nw ei gh te d nu m be r o f ch ild re n Fa th er al iv e Fa th er de ad M ot he r al iv e M ot he r de ad B ot h al iv e O nl y fa th er al iv e O nl y m ot he r al iv e B ot h de ad M is si ng in fo rm at io n on fa th er / m ot he r A ge 0- 4 82 .3 11 .1 2. 0 0. 7 0. 3 2. 8 0. 3 0. 2 0. 1 0. 2 10 0. 0 3. 4 2. 9 11 ,8 01 11 ,5 69 0 -1 86 .3 11 .0 1. 5 0. 1 0. 0 0. 7 0. 2 0. 0 0. 0 0. 2 10 0. 0 0. 9 1. 7 4, 42 3 4, 25 4 2 -4 79 .8 11 .2 2. 2 1. 0 0. 5 4. 1 0. 3 0. 3 0. 1 0. 3 10 0. 0 4. 9 3. 6 7, 37 8 7, 31 5 5- 9 73 .4 9. 0 4. 5 2. 2 0. 9 7. 7 0. 7 0. 8 0. 5 0. 4 10 0. 0 9. 7 7. 4 12 ,7 39 12 ,3 10 10 -1 4 65 .7 8. 6 7. 1 2. 5 1. 8 9. 3 1. 4 1. 8 1. 3 0. 4 10 0. 0 13 .9 13 .5 11 ,1 74 10 ,5 40 15 -1 7 54 .1 7. 3 9. 8 2. 2 2. 3 15 .1 2. 3 3. 8 1. 9 1. 2 10 0. 0 23 .1 20 .2 4, 79 8 4, 45 7 Se x M al e 72 .9 9. 1 5. 1 2. 2 1. 3 6. 2 1. 0 1. 2 0. 9 0. 3 10 0. 0 9. 2 9. 4 20 ,4 51 19 ,5 82 Fe m al e 70 .3 9. 5 5. 2 1. 5 1. 0 9. 0 0. 9 1. 4 0. 7 0. 6 10 0. 0 12 .0 9. 2 20 ,0 62 19 ,2 94 R es id en ce U rb an 58 .3 14 .9 5. 4 2. 3 0. 7 12 .5 1. 2 2. 4 1. 7 0. 7 10 0. 0 17 .8 11 .5 5, 94 8 7, 49 2 R ur al 73 .9 8. 3 5. 1 1. 8 1. 2 6. 7 0. 9 1. 1 0. 6 0. 4 10 0. 0 9. 3 8. 9 34 ,5 65 31 ,3 84 R eg io n Ti gr ay 69 .1 14 .7 5. 5 1. 2 1. 6 5. 4 0. 5 0. 8 0. 8 0. 4 10 0. 0 7. 6 9. 2 2, 61 7 4, 08 3 A ffa r 63 .3 18 .8 4. 2 2. 8 2. 9 5. 0 1. 2 1. 0 0. 7 0. 2 10 0. 0 7. 9 10 .0 36 3 3, 36 9 A m ha ra 74 .1 9. 2 3. 7 2. 3 1. 1 6. 6 0. 8 1. 1 0. 7 0. 4 10 0. 0 9. 3 7. 4 9, 63 2 4, 62 4 O ro m iy a 74 .1 6. 9 5. 7 1. 4 1. 1 7. 5 1. 0 1. 2 0. 7 0. 5 10 0. 0 10 .3 9. 6 16 ,1 24 5, 59 1 S om al i 70 .4 13 .7 4. 7 1. 6 1. 1 5. 2 1. 1 0. 8 1. 0 0. 5 10 0. 0 8. 1 8. 7 1, 08 3 3, 09 3 B en is ha ng ul -G um uz 75 .0 9. 2 3. 1 3. 1 1. 3 5. 2 0. 9 1. 1 0. 8 0. 3 10 0. 0 8. 1 7. 2 42 4 3, 14 9 S N N P 67 .8 10 .6 5. 5 2. 1 1. 3 8. 8 1. 1 1. 5 0. 9 0. 4 10 0. 0 12 .3 10 .3 8, 93 5 5, 69 6 G am be la 52 .6 15 .4 9. 0 3. 7 1. 0 11 .5 1. 7 3. 1 1. 7 0. 4 10 0. 0 17 .9 16 .5 13 2 2, 88 7 H ar ar i 70 .9 8. 2 4. 1 2. 9 1. 2 8. 7 1. 2 1. 2 1. 0 0. 6 10 0. 0 12 .1 8. 7 98 2, 24 9 A dd is A ba ba 51 .7 12 .8 6. 8 4. 1 0. 4 16 .9 1. 5 3. 1 1. 8 0. 8 10 0. 0 23 .3 13 .6 97 2 1, 84 8 D ire D aw a 65 .2 10 .4 5. 0 2. 0 0. 6 10 .9 1. 6 1. 8 1. 5 1. 0 10 0. 0 15 .8 10 .6 13 2 2, 28 7 W ea lth q ui nt ile Lo w es t 72 .0 10 .3 6. 5 1. 7 1. 3 5. 3 0. 9 1. 1 0. 6 0. 3 10 0. 0 7. 9 10 .4 8, 65 2 11 ,4 03 S ec on d 75 .5 7. 9 4. 9 1. 6 1. 3 6. 2 0. 7 1. 0 0. 7 0. 2 10 0. 0 8. 5 8. 6 8, 36 5 6, 63 5 M id dl e 75 .9 6. 9 4. 5 1. 9 1. 2 6. 5 1. 2 1. 0 0. 7 0. 4 10 0. 0 9. 3 8. 6 8, 47 0 6, 29 5 Fo ur th 71 .7 8. 6 4. 6 2. 2 1. 1 8. 3 0. 9 1. 2 0. 6 0. 6 10 0. 0 11 .1 8. 6 8, 27 7 6, 38 4 H ig he st 60 .6 13 .6 4. 9 1. 9 0. 8 12 .7 1. 0 2. 2 1. 5 0. 7 10 0. 0 17 .5 10 .5 6, 75 0 8, 15 9 To ta l < 15 73 .9 9. 6 4. 5 1. 8 1. 0 6. 6 0. 8 0. 9 0. 6 0. 3 10 0. 0 8. 9 7. 8 35 ,7 15 34 ,4 19 To ta l < 18 71 .6 9. 3 5. 1 1. 8 1. 2 7. 6 1. 0 1. 3 0. 8 0. 4 10 0. 0 10 .6 9. 3 40 ,5 13 38 ,8 76 N ot e: T ab le is b as ed o n de ju re m em be rs , i .e ., us ua l r es id en ts . 1 I nc lu de s ch ild re n w ith fa th er d ea d, m ot he r d ea d, b ot h de ad a nd o ne p ar en t d ea d bu t m is si ng in fo rm at io n on s ur vi va l s ta tu s of th e ot he r p ar en t. 24 • Housing Characteristics and Household Population Housing Characteristics and Household Population • 25 2.6 EDUCATION OF THE HOUSEHOLD POPULATION Education is a key determinant of individual opportunities, attitudes, and economic and social status. Studies have consistently shown that educational attainment has a strong effect on reproductive behaviour, fertility, infant and child mortality and morbidity, and attitudes and awareness related to family health, use of family planning, and sanitation. The 2011 EDHS reports educational attainment among household members and school attendance among youth. For many years Ethiopia’s education system did not change substantially. Recently, however, the Ethiopian government undertook a major restructuring and expansion programme within the government system, as well as opening the education sector to the free-market economy and to private investments. The current system of formal education is based on a three-tier system: eight years of primary education, followed by four years of secondary education, and four to seven years for tertiary education, depending on the area of study. Currently, several pre-university colleges and educational institutions operated by the government or the private sector offer vocational, technical, and professional training in different parts of the country. The number of public and private universities and vocational and technical schools has increased substantially over the last few years. 2.6.1 School Attendance by Survivorship of Parents The survival status of parents has an impact on their children’s school attendance. Table 2.9 shows the percentage of children age 10-14 attending school by parental survival, and the ratio of the percentage attending by parental survival, according to background characteristics. Children whose parents both are dead are less likely to attend school (69 percent) than children who have both parents alive and are living with at least one parent (76 percent), resulting in a ratio of 0.90 between the percentage of children with both parents deceased and the percentage with both parents alive and living with a parent. Male children with both parents deceased are much less likely than female children in the same situation to attend school (60 percent versus 80 percent). 26 • Housing Characteristics and Household Population Table 2.9 School attendance by survivorship of parents For de jure children 10-14 years of age, the percentage attending school by parental survival and the ratio of the percentage attending, by parental survival, according to background characteristics, Ethiopia 2011 Background characteristic Percentage attending school by survivorship of parents Ratio1 Both parents deceased Weighted number Unweighted number Both parents alive and living with at least one parent Weighted number Unweighted number Sex Male 59.9 81 81 73.6 4,513 4,273 0.81 Female 79.7 68 71 79.1 4,077 3,692 1.01 Residence Urban 93.2 50 61 94.4 1,263 1,402 0.99 Rural 56.8 100 91 73.1 7,327 6,563 0.78 Region Tigray * 8 11 78.3 542 846 0.92 Affar * 1 13 55.1 75 701 0.67 Amhara * 23 9 77.9 2,349 1,112 0.75 Oromiya * 54 20 73.4 3,198 1,117 0.88 Somali * 6 11 67.2 208 588 0.97 Benishangul-Gumuz * 1 9 81.5 90 674 0.85 SNNP (75.5) 46 27 77.6 1,882 1,202 0.97 Gambela * 1 11 93.3 22 533 0.73 Harari * 0 10 78.2 20 450 1.01 Addis Ababa * 8 17 97.5 182 342 0.97 Dire Dawa * 1 14 82.2 22 400 0.73 Wealth quintile Lowest * 22 30 62.6 1,745 2,351 1.05 Second (42.0) 29 18 71.2 1,709 1,373 0.59 Middle * 21 22 73.9 1,858 1,336 1.00 Fourth (64.3) 29 20 81.8 1,853 1,353 0.79 Highest (87.0) 49 62 94.6 1,425 1,552 0.92 Total 68.9 150 152 76.2 8,590 7,965 0.90 Note: Table is based only on children who usually live in the household. Figures in parentheses are based on 25-49 unweighted cases. An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. 1 Ratio of the percentage with both parents deceased to the percentage with both parents alive and living with a parent. 2.6.2 Educational Attainment Tables 2.10.1 and 2.10.2 show the percent distribution of the de facto female and male household population age 6 and older by highest level of education attended or completed, according to background characteristics. The majority of Ethiopians have little or no education, with females even less educated than males. Fifty-two percent of females and 38 percent of males have never attended school. While these percentages are large, they constitute a substantial decrease from the findings of the 2005 EDHS, when 67 percent of females and 52 percent of males had never attended school. About four in every ten females (39 percent) and half of all males (49 percent) have only some primary education, while 2 percent of females and 3 percent of males completed primary education and did not attend secondary school. Only 3 percent of females and 5 percent of males have attended but not completed secondary education, and an additional 3 percent of females and 5 percent of males have completed secondary or higher education. The gender gap in education is more obvious at lower levels of education, primarily because the proportion of males and females attending higher levels of education is so small. The trends in educational attainment by successive age groups indicate the long-term trend of the country’s educational achievement. There has been a marked improvement in the educational attainment of women. For example, the proportion of females with no education has declined significantly, from 98 percent among those age 65 and over to just 17 percent among females Housing Characteristics and Household Population • 27 age 10-14 at the time of the survey. Similarly, among males 89 percent of men age 65 and older had no education, compared with 13-19 percent of males age 10-24. As expected, educational attainment is much higher among the urban population than among the rural population. For example, in urban areas 28 percent of females and 15 percent of males have no education, compared with 58 percent of females and 44 percent of males in rural areas. Among regions, the proportion of females and males with no education is highest in Affar (69 and 53 percent, respectively), followed by Somali for women (68 percent) and Amhara for men (47 percent), and lowest in the capital city, Addis Ababa (23 and 10 percent). The highest percentages of females and males who have completed secondary or more than secondary education live in the urbanized regions, such as Harari, Addis Ababa, and Dire Dawa. The most substantial variation in educational attainment occurs across the wealth quintiles. Only 27 percent of females in the wealthiest households have no education, compared with 69 percent in the poorest households. Among males 14 percent of those in the wealthiest households have no education, compared with 54 percent in the poorest households. Table 2.10.1 Educational attainment of the female household population Percent distribution of the de facto female household population age six and over by highest level of schooling attended or completed and median years completed, according to background characteristics, Ethiopia 2011 Background characteristic No education Some primary Completed primary1 Some secondary Completed secondary2 More than secondary Don't know/ missing Total Weighted number Un- weighted number Median years completed Age 7-9 47.6 52.2 na na na na 0.2 100.0 3,772 3,688 0.0 10-14 17.2 81.7 0.7 0.1 0.0 0.0 0.2 100.0 5,401 4,982 1.6 15-19 18.4 60.9 8.4 9.9 0.1 2.3 0.1 100.0 4,321 4,110 4.2 20-24 39.3 34.9 4.4 11.6 0.6 9.0 0.1 100.0 3,271 3,356 2.0 25-29 60.2 25.7 2.5 4.9 1.2 5.2 0.2 100.0 3,324 3,362 0.0 30-34 67.7 22.0 2.5 2.1 2.1 3.5 0.1 100.0 2,105 2,158 0.0 35-39 70.7 21.5 1.5 1.6 1.7 2.8 0.1 100.0 2,004 2,052 0.0 40-44 77.4 15.2 1.4 1.7 1.3 2.6 0.5 100.0 1,331 1,340 0.0 45-49 85.0 11.5 1.0 0.4 0.5 1.3 0.3 100.0 1,099 1,007 0.0 50-54 89.6 7.4 1.1 0.3 0.3 0.7 0.7 100.0 1,268 1,253 0.0 55-59 94.8 4.4 0.2 0.2 0.1 0.2 0.0 100.0 1,078 976 0.0 60-64 95.1 2.8 0.3 0.4 0.1 0.2 1.2 100.0 699 762 0.0 65+ 97.8 1.4 0.0 0.0 0.1 0.1 0.6 100.0 1,340 1,342 0.0 Residence Urban 28.3 41.7 6.6 11.4 2.5 9.4 0.1 100.0 6,510 8,869 3.5 Rural 58.1 38.4 1.3 1.3 0.0 0.6 0.2 100.0 25,926 22,910 0.0 Region Tigray 47.3 42.4 3.4 4.6 0.6 1.7 0.1 100.0 2,146 3,306 0.0 Affar 69.3 25.0 1.6 2.2 0.3 1.3 0.3 100.0 265 2,397 0.0 Amhara 56.9 35.5 2.0 3.2 0.2 1.9 0.2 100.0 8,368 3,943 0.0 Oromiya 52.6 39.6 2.5 2.8 0.3 2.0 0.2 100.0 11,976 4,162 0.0 Somali 67.9 28.5 0.8 1.7 0.2 0.6 0.4 100.0 670 1,925 0.0 Benishangul- Gumuz 53.5 38.5 2.0 2.2 0.4 2.8 0.5 100.0 326 2,385 0.0 SNNP 51.4 42.7 1.4 2.5 0.1 1.6 0.3 100.0 6,920 4,353 0.0 Gambela 35.8 52.1 4.2 3.4 0.2 3.8 0.5 100.0 120 2,326 1.0 Harari 40.2 37.7 3.9 6.6 3.4 7.7 0.4 100.0 91 2,077 1.0 Addis Ababa 22.5 40.6 6.5 11.8 6.0 12.5 0.2 100.0 1,427 2,827 5.0 Dire Dawa 43.1 37.1 3.6 6.8 2.2 7.0 0.2 100.0 126 2,078 0.5 Wealth quintile Lowest 69.2 29.9 0.4 0.4 0.0 0.0 0.2 100.0 6,245 7,905 0.0 Second 63.0 35.1 0.8 0.7 0.0 0.1 0.3 100.0 6,304 4,968 0.0 Middle 57.7 39.2 1.0 1.5 0.0 0.3 0.3 100.0 6,292 4,635 0.0 Fourth 47.6 46.6 2.6 2.2 0.0 0.7 0.2 100.0 6,473 4,889 0.0 Highest 26.6 43.8 6.4 11.0 2.3 9.7 0.1 100.0 7,122 9,382 3.4 Total 52.1 39.1 2.3 3.4 0.5 2.3 0.2 100.0 31,019 31,779 0.0 Total includes 5 cases with missing information on age. na = Not applicable 1 Completed 8th grade at the primary level. 2 Completed 4th grade at the secondary level. 28 • Housing Characteristics and Household Population Table 2.10.2 Educational attainment of the male household population Percent distribution of the de facto male household population age six and over by highest level of schooling attended or completed and median years completed, according to background characteristics, Ethiopia 2011 Background characteristic No education Some primary Completed primary1 Some secondary Completed secondary2 More than secondary Don't know/ missing Total Weighted number Un- weighted number Median years completed Age 6-9 44.8 55.1 na na na na 0.1 100.0 3,877 3,716 0.0 10-14 18.1 81.2 0.5 0.2 0.0 0.0 0.1 100.0 5,712 5,437 1.6 15-19 12.6 67.1 8.0 10.3 0.1 1.8 0.1 100.0 3,449 3,164 4.4 20-24 19.3 48.1 6.5 14.8 0.8 10.5 0.1 100.0 2,837 2,709 4.7 25-29 32.0 40.0 5.3 9.4 0.9 12.3 0.1 100.0 2,616 2,578 2.9 30-34 40.6 37.8 4.8 6.0 3.4 7.3 0.1 100.0 1,824 1,948 1.5 35-39 42.2 40.5 4.3 4.4 3.8 4.7 0.1 100.0 1,906 1,751 1.4 40-44 44.9 38.6 4.1 3.6 2.1 6.4 0.2 100.0 1,358 1,382 0.9 45-49 50.5 37.3 2.9 3.2 1.5 4.3 0.3 100.0 1,029 1,039 0.0 50-54 61.4 27.7 1.6 2.3 0.9 5.5 0.5 100.0 792 805 0.0 55-59 72.8 19.6 3.1 1.3 0.9 2.2 0.1 100.0 625 532 0.0 60-64 77.1 18.2 1.3 0.9 0.2 1.5 0.7 100.0 780 775 0.0 65+ 88.8 9.3 0.3 0.6 0.3 0.4 0.3 100.0 1,756 1,638 0.0 Residence Urban 14.5 45.9 7.0 13.7 3.8 14.9 0.1 100.0 5,442 7,489 5.4 Rural 43.6 50.1 2.2 2.5 0.2 1.2 0.2 100.0 24,468 21,334 0.0 Region Tigray 37.9 50.5 2.5 4.2 0.5 4.4 0.0 100.0 1,849 2,858 1.0 Affar 53.4 35.3 3.4 3.5 1.2 3.0 0.3 100.0 257 2,290 0.0 Amhara 47.1 44.6 2.6 3.5 0.3 1.8 0.1 100.0 7,822 3,742 0.0 Oromiya 37.7 50.4 3.5 4.4 0.4 3.4 0.2 100.0 11,531 4,000 0.6 Somali 46.0 43.5 2.4 2.9 1.3 3.3 0.7 100.0 637 1,834 0.0 Benishangul- Gumuz 39.7 48.8 3.0 3.5 0.4 4.0 0.6 100.0 301 2,225 0.4 SNNP 33.3 56.0 2.4 3.9 0.6 3.5 0.2 100.0 6,038 3,810 1.2 Gambela 21.9 51.9 5.7 9.0 2.7 8.4 0.4 100.0 113 2,001 3.2 Harari 22.4 44.9 6.2 10.1 3.9 12.3 0.3 100.0 84 1,925 4.0 Addis Ababa 9.5 41.0 7.6 15.5 8.5 17.5 0.3 100.0 1,166 2,282 6.9 Dire Dawa 24.5 43.3 4.7 11.0 4.3 12.1 0.1 100.0 112 1,856 3.4 Wealth quintile Lowest 54.1 44.0 0.7 0.8 0.1 0.2 0.1 100.0 5,592 6,991 0.0 Second 47.9 48.6 1.6 1.5 0.0 0.2 0.2 100.0 5,884 4,545 0.0 Middle 43.5 51.4 2.5 1.5 0.1 0.7 0.2 100.0 6,149 4,454 0.0 Fourth 33.8 55.7 3.3 5.2 0.2 1.6 0.2 100.0 6,197 4,712 1.2 Highest 14.0 46.2 7.3 13.1 3.6 15.6 0.1 100.0 6,088 8,121 5.4 Total 38.3 49.3 3.1 4.5 0.8 3.7 0.2 100.0 29,910 28,823 0.6 Total includes 9 cases with missing information on age. 1 Completed 8th grade at the primary level. 2 Completed 4th grade at the secondary level. 2.6.3 School Attendance Ratios Table 2.11 shows data on net attendance ratios (NARs) and gross attendance ratios (GARs) for the de facto household population by school level and sex, according to residence, region, and wealth index. The NAR for primary school is the total number of students of primary school age (age 7-14) expressed as the percentage of the population of primary school age. The NAR for secondary school is the percentage of the population of secondary school age (age 15-18) that attends secondary school. By definition, the NAR cannot exceed 100 percent. The GAR for primary school is the total number of primary school students of any age, expressed as a percentage of the official primary-school-age population. The GAR for secondary school is the total number of secondary school students of any age, expressed as a percentage of the official secondary-school-age population. If there are significant numbers of overage and underage students at a given level of schooling, the GAR can exceed 100 percent. Persons are considered to be currently attending school if they attended formal academic school at any point during the school year. It is important to note that in the 2011 EDHS the NAR and GAR are based on the new organisation of education levels, in which primary school covers grades 1-8, while in the 2005 EDHS Housing Characteristics and Household Population • 29 survey the NAR and GAR were based on the previous organisation, in which primary school covered grades 1-6. Therefore, comparison of the NAR and GAR between the two surveys is not possible. As Table 2.11 shows, 65 percent of children of primary school age in Ethiopia attend primary school (64 percent of males and 65 percent of females). At the same time, only 14 percent of young people of secondary school age are attending school (14 percent of males and 13 percent of females). Attendance ratios are much lower in rural areas than in urban areas; they are lowest in Affar and Somali regions. At the primary level the GAR is higher among females (90) than males (87), and at the secondary level, higher among males (24) than females (21). Although the overall GAR at the primary level is 88, there are significant levels of over-age and/or under-age participation in the urban areas among both females (111) and males (108) as well as in Addis Ababa and Gambela (both 111). There is a strong relationship between household economic status and schooling at both the primary and secondary levels and among males and females. For example, at the primary education level the NAR increases from 52 percent in the lowest wealth quintile to 84 percent in the highest wealth quintile. Similarly, at the secondary level the NAR rises from 3 percent in the lowest wealth quintile to 37 percent in the highest wealth quintile. The Gender Parity Index (GPI) measures sex-related differences in school attendance ratios. It is the ratio of female to male attendance. A GPI of 1 indicates parity, or equality, between the school participation ratios for males and females. A GPI lower than 1 indicates a gender disparity in favour of males—that is, a higher proportion of males than females attend that level of schooling. A GPI higher than 1 indicates a gender disparity in favour of females. In Ethiopia the GPI for primary school attendance is slightly higher than 1 (1.02 for NAR and 1.04 for GAR). For secondary school attendance it is lower than 1 (0.95 for NAR and 0.85 for GAR). These data indicate that the gender gap is smaller at the primary level than at the secondary level of schooling. There are some differences in the GPI for NAR and for GAR by place of residence and by region. For both primary and secondary education, the GPI for both NAR and GAR is higher in rural areas than urban areas. The primary school and secondary school GPI for both NAR and GAR is lowest in Somali region. 30 • Housing Characteristics and Household Population Table 2.11 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 2011 Background characteristic Net attendance ratio1 Gross attendance ratio2 Male Female Total Gender Parity Index3 Male Female Total Gender Parity Index3 PRIMARY SCHOOL Residence Urban 85.8 81.5 83.6 0.95 108.4 110.6 109.5 1.02 Rural 60.3 61.9 61.1 1.03 83.1 86.0 84.5 1.04 Region Tigray 71.4 79.0 75.3 1.11 96.6 103.6 100.1 1.07 Affar 53.3 50.1 51.9 0.94 78.1 72.4 75.5 0.93 Amhara 65.2 71.9 68.4 1.10 90.2 98.9 94.4 1.10 Oromiya 60.1 60.3 60.2 1.00 82.7 83.7 83.2 1.01 Somali 63.3 50.2 57.3 0.79 86.5 68.8 78.3 0.80 Benishangul-Gumuz 70.1 69.0 69.6 0.98 98.8 94.2 96.4 0.95 SNNP 64.3 61.7 63.0 0.96 84.3 86.1 85.2 1.02 Gambela 82.2 79.6 80.9 0.97 105.1 117.3 111.2 1.12 Harari 79.1 68.5 74.1 0.87 96.4 95.9 96.2 1.00 Addis Ababa 89.6 79.7 84.2 0.89 108.7 113.6 111.3 1.05 Dire Dawa 77.5 72.6 75.2 0.94 97.0 100.6 98.7 1.04 Wealth quintile Lowest 51.3 52.7 52.0 1.03 70.2 71.8 71.0 1.02 Second 58.7 57.0 57.9 0.97 80.3 79.5 79.9 0.99 Middle 60.8 62.5 61.7 1.03 86.0 87.2 86.6 1.01 Fourth 68.2 71.9 70.0 1.05 93.5 103.2 98.2 1.10 Highest 85.7 82.2 83.9 0.96 108.4 108.7 108.5 1.00 Total 64.0 65.0 64.5 1.02 86.7 89.8 88.2 1.04 SECONDARY SCHOOL Residence Urban 43.6 36.1 39.1 0.83 75.6 54.2 62.7 0.72 Rural 6.6 5.9 6.2 0.90 11.2 9.7 10.4 0.86 Region Tigray 15.3 16.6 16.1 1.08 23.6 24.1 23.9 1.02 Affar 11.7 7.9 9.6 0.68 26.6 12.6 18.6 0.47 Amhara 11.6 12.7 12.2 1.10 22.9 18.7 20.6 0.81 Oromiya 13.3 13.3 13.3 1.00 20.4 20.6 20.5 1.01 Somali 11.4 4.8 7.9 0.42 18.3 6.7 12.1 0.37 Benishangul-Gumuz 13.5 11.2 12.4 0.83 20.1 16.0 18.0 0.80 SNNP 14.0 9.7 11.6 0.69 26.7 18.0 21.8 0.67 Gambela 17.1 10.1 13.0 0.59 25.1 15.5 19.4 0.62 Harari 29.4 19.3 23.4 0.66 52.9 29.9 39.3 0.56 Addis Ababa 42.6 30.6 34.7 0.72 69.8 44.7 53.2 0.64 Dire Dawa 32.9 26.4 28.9 0.80 62.7 35.4 45.9 0.56 Wealth quintile Lowest 2.9 2.5 2.7 0.88 4.9 3.2 4.0 0.64 Second 2.2 4.0 3.2 1.79 6.2 5.0 5.6 0.81 Middle 4.6 4.3 4.4 0.93 7.6 10.1 8.9 1.34 Fourth 13.5 12.7 13.0 0.94 24.0 17.9 20.6 0.74 Highest 40.5 34.4 36.9 0.85 67.6 53.2 59.3 0.79 Total 14.0 13.4 13.7 0.95 24.2 20.7 22.3 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 percent. 2 The GAR for primary school is the total number of primary school students, expressed as a percentage of the official primary-school-age population. The GAR for secondary school is the total number of secondary school students, expressed as a percentage of the official secondary-school-age population. If there are significant numbers of overage and underage students at a given level of schooling, the GAR can exceed 100 percent. 3 The Gender Parity Index for primary school is the ratio of the primary school NAR (GAR) for females to the NAR (GAR) for males. The Gender Parity Index for secondary school is the ratio of the secondary school NAR (GAR) for females to the NAR (GAR) for males. Figure 2.2 shows the age-specific attendance rates (ASARs) for the population age 5 and over, by sex. The ASAR indicates participation in schooling at any level, from primary to higher levels of education. Although the official minimum age for schooling in Ethiopia is age 7, some children are enrolled at younger ages. Nevertheless, only 35-39 percent of children age 7 are attending school, indicating that a large majority of children age 7 in Ethiopia have not entered the school system. However, enrolment at age 7 has improved since the 2000 EDHS, when only 15 percent of Housing Characteristics and Household Population • 31 children age 7 were attending school, and since the 2005 EDHS, when 21 percent were attending school. There are some differences in the proportion of males and females attending school. Between ages 7-9 and 16-24, the proportion of males attending school is somewhat higher than the proportion of females, while for ages 10-15 the proportion of females attending school is either higher than or similar to the proportion of males. Figure 2.2 Age-Specific Attendance Rates of the de facto Population 5 to 24 Years EDHS 2011 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 Age 0 10 20 30 40 50 60 70 80 90 100 Percentage Male Female 2.7 CHILD LABOUR Article 32 of the UN Convention on the Rights of the Child recognises the right of children to be protected from economic exploitation and to be protected from performing any work that is hazardous, interferes with their education, or is harmful to their health or physical, mental, spiritual, moral, or social development (UN General Assembly, 1989). Article 32 calls on countries to establish a minimum age for admission to employment and to appropriately regulate work hours of children. To assess the extent to which children in Ethiopia are working, the 2011 EDHS included a set of questions on the participation by each child age 5-14 in the household in different types of work. The types of work included working for persons other than members of the household, working in a household business or farm, or selling goods in the street, and doing household chores. The number of hours worked in the seven days preceding the survey was recorded for all children engaged in any type of work. For work that was done for any person not a member of the household, a question was also asked to determine whether the child was paid or not paid for the work. This information was used to calculate the percentage of children age 5-14 engaged in child labour. The definition of child labour includes (a) children age 5-11 who in the seven days preceding the survey worked for someone who is not a member of the household, with or without pay, or 32 • Housing Characteristics and Household Population engaged in any other family work or did household chores for 28 hours or more, and (b) children age 12-14 who in the seven days preceding the survey worked for someone who is not a member of the household, with or without pay, or engaged in any other family work for 14 hours or more or did household chores for 28 hours or more. This definition helps to identify the type of child work that should be eliminated in order to conform to the UN Convention on the Rights of the Child. As such, the estimate provided here is a minimum of the prevalence of child labour, since some children may be involved in hazardous labour activities for a number of hours that could be less than the numbers specified in the criteria described above. Table 2.12 shows the percentage of de jure children age 5-14 engaged in different types of work in the seven days preceding the interview, by background characteristics. Percentages do not add up to the total for child labour, as children may be involved in more than one type of work. Overall, 27 percent of children age 5-14 in Ethiopia are involved in child labour—17 percent of children age 5-11 and 55 percent of children age 12-14. Less than 1 percent of children age 5-11 and 2 percent of children age 12-14 are engaged in paid work; 3 percent and 6 percent, respectively, are engaged in unpaid work for someone who is not a member of their household; and 14 percent and 30 percent, respectively, work for a family business. Furthermore, 18 percent of children age 5-11 and 40 percent of children age 12-14 are engaged in household chores for 28 or more hours in a week. For all children age 5-14, the percentage engaged in labour is higher among males (31 percent) than females (24 percent). The proportion of children engaged in labour is substantially higher among rural children (30 percent) than urban children (13 percent). Among regions it varies from 7 percent of children in Addis Ababa to 42 percent in Tigray. Child labour decreases steadily with mother’s education and household wealth. Only 6 percent of children of mothers who have more than secondary education are engaged in child labour, compared with 29 percent of children whose mothers have no education. Similarly, this proportion decreases from 31 percent for children in the lowest wealth quintile to 15 percent for children in the highest wealth quintile. H ou si ng C ha ra ct er is tic s an d H ou se ho ld P op ul at io n • 3 3 Ta bl e 2. 12 C hi ld la bo ur P er ce nt ag e of th e de ju re c hi ld re n ag e 5- 14 w ho w er e en ga ge d in e co no m ic a ct iv ity , i n ho us eh ol d ch or es a nd in c hi ld la bo ur d ur in g th e se ve n da ys p re ce di ng th e su rv ey , b y ba ck gr ou nd c ha ra ct er is tic s, E th io pi a 20 11 B ac kg ro un d ch ar ac te ris tic s P er ce nt ag e of c hi ld re n 5- 11 in vo lv ed in : W ei gh te d nu m be r of ch ild re n ag e 5- 11 U n- w ei gh te d nu m be r of ch ild re n ag e 5- 11 P er ce nt ag e of c hi ld re n 12 -1 4 in vo lv ed in : W ei gh te d nu m be r of ch ild re n ag e 12 -1 4 U n- w ei gh te d nu m be r of ch ild re n ag e 12 -1 4 To ta l ch ild la bo ur 4 W ei gh te d nu m be r of ch ild re n ag e 5- 14 U n- w ei gh te d nu m be r of ch ild re n ag e 5- 14 E co no m ic a ct iv ity E co no m ic ac tiv ity 3 fo r a t le as t o ne ho ur p er w ee k H ou se - ho ld ch or es fo r le ss th an 28 h ou rs pe r w ee k H ou se - ho ld ch or es fo r 28 + ho ur s pe r w ee k C hi ld la bo ur 4 E co no m ic a ct iv ity E co no m ic ac tiv ity 3 fo r l es s th an 1 4 ho ur s pe r w ee k E co no m ic ac tiv ity 3 fo r 1 4 ho ur s or m or e pe r w ee k H ou se - ho ld ch or es fo r le ss th an 28 h ou rs pe r w ee k H ou se - ho ld ch or es fo r 28 + ho ur s pe r w ee k C hi ld la bo ur 4 W or ki ng o ut si de ho us eh ol d1 W or ki ng fo r f am ily bu si ne ss 2 W or ki ng o ut si de ho us eh ol d1 W or ki ng fo r f am ily bu si ne ss 2 P ai d w or k U np ai d w or k P ai d w or k U np ai d w or k C hi ld 's s ex M al e 0. 8 2. 6 17 .8 20 .4 48 .7 16 .9 20 .4 8, 63 2 8, 30 4 2. 8 4. 9 39 .3 12 .2 31 .1 52 .0 35 .4 57 .1 3, 55 0 3, 39 0 31 .1 12 ,1 81 11 ,6 94 Fe m al e 0. 4 3. 0 9. 8 12 .7 55 .5 18 .2 12 .7 8, 49 8 8, 13 4 1. 8 6. 1 20 .7 11 .2 14 .6 51 .4 44 .7 52 .0 3, 23 4 3, 02 2 23 .5 11 ,7 32 11 ,1 56 R es id en ce U rb an 0. 4 3. 9 3. 8 8. 0 53 .4 7. 6 8. 0 2, 29 6 2, 90 7 2. 0 3. 0 10 .6 6. 9 7. 6 67 .0 19 .6 24 .1 1, 12 6 1, 37 4 13 .3 3, 42 2 4, 28 1 R ur al 0. 6 2. 6 15 .3 17 .9 51 .9 19 .1 17 .9 14 ,8 33 13 ,5 31 2. 4 6. 0 34 .4 12 .7 26 .3 48 .7 43 .9 60 .8 5, 65 8 5, 03 8 29 .7 20 ,4 92 18 ,5 69 R eg io n Ti gr ay 0. 6 3. 2 34 .9 36 .6 46 .3 7. 2 36 .6 1, 04 6 1, 64 5 1. 8 7. 1 52 .8 16 .6 40 .1 65 .0 21 .9 55 .4 44 5 68 9 42 .2 1, 49 0 2, 33 4 A ffa r 0. 5 1. 6 15 .9 17 .6 33 .5 16 .9 17 .6 15 5 1, 45 5 0. 1 2. 5 25 .6 2. 1 25 .3 31 .0 39 .4 56 .8 57 52 8 28 .2 21 3 1, 98 3 A m ha ra 0. 8 4. 9 15 .7 20 .2 46 .8 16 .3 20 .2 3, 85 3 1, 85 1 2. 1 8. 4 31 .0 10 .1 27 .2 47 .7 39 .6 58 .1 1, 80 5 86 4 32 .3 5, 65 8 2, 71 5 O ro m iy a 0. 6 2. 2 6. 7 9. 4 49 .9 23 .3 9. 4 6, 82 8 2, 36 6 3. 0 4. 2 22 .1 10 .3 15 .8 45 .2 50 .0 56 .5 2, 46 8 87 1 21 .9 9, 29 7 3, 23 7 S om al i 0. 8 1. 9 11 .8 13 .9 41 .9 14 .4 13 .9 46 6 1, 33 1 2. 2 1. 5 24 .6 5. 3 22 .1 45 .7 31 .8 47 .7 16 4 47 6 22 .7 63 0 1, 80 7 B en is ha ng ul - G um uz 0. 4 2. 7 9. 1 12 .0 46 .5 9. 0 12 .0 17 0 1, 28 2 1. 3 6. 6 23 .7 11 .4 18 .9 62 .5 25 .4 39 .4 65 49 1 19 .6 23 5 1, 77 3 S N N P 0. 4 1. 9 20 .1 21 .9 64 .5 14 .2 21 .9 4, 10 3 2, 61 1 1. 9 4. 3 41 .8 16 .5 28 .8 61 .6 35 .0 55 .1 1, 52 2 97 0 30 .9 5, 62 6 3, 58 1 G am be la 0. 2 2. 1 9. 1 11 .0 53 .9 3. 6 11 .0 55 1, 27 2 1. 5 5. 6 21 .1 16 .5 9. 4 64 .3 14 .9 21 .7 20 44 1 13 .8 76 1, 71 3 H ar ar i 0. 4 1. 0 2. 2 3. 5 51 .0 13 .8 3. 5 42 95 5 1. 8 1. 4 11 .4 6. 0 8. 2 60 .7 26 .9 31 .8 16 36 8 11 .4 58 1, 32 3 A dd is A ba ba 0. 2 2. 1 0. 4 2. 6 47 .3 1. 0 2. 6 35 5 67 8 1. 5 3. 8 3. 9 5. 0 3. 8 68 .2 12 .2 15 .8 20 1 38 2 7. 4 55 5 1, 06 0 D ire D aw a 0. 8 2. 2 8. 4 11 .1 57 .8 5. 8 11 .1 57 99 2 1. 9 3. 8 14 .0 9. 4 9. 4 67 .5 12 .4 20 .7 20 33 2 13 .6 77 1, 32 4 M ot he r's ed uc at io n N o ed uc at io n 0. 6 2. 6 14 .8 17 .2 51 .4 17 .2 17 .2 11 ,2 25 10 ,7 37 2. 0 5. 5 33 .7 12 .3 25 .4 49 .6 42 .7 59 .0 4, 23 9 3, 96 9 28 .7 15 ,4 64 14 ,7 06 P rim ar y 0. 7 2. 6 10 .6 13 .5 54 .9 15 .6 13 .5 3, 08 6 2, 75 0 2. 6 4. 4 25 .8 11 .6 18 .8 59 .3 33 .8 46 .2 1, 06 3 87 1 21 .8 4, 14 9 3, 62 1 S ec on da ry 0. 0 9. 3 3. 4 12 .6 50 .9 2. 9 12 .6 24 8 35 1 0. 0 2. 7 9. 7 5. 8 5. 6 70 .2 17 .0 20 .0 94 12 0 14 .7 34 2 47 1 M or e th an se co nd ar y 0. 0 2. 0 0. 0 2. 0 50 .5 3. 0 2. 0 16 0 17 5 0. 0 10 .9 1. 2 6. 6 4. 3 77 .5 13 .5 14 .3 69 75 5. 7 22 9 25 0 M is si ng 5 0. 6 3. 6 15 .2 18 .7 52 .1 23 .8 18 .7 2, 41 0 2, 42 5 3. 4 6. 1 26 .7 10 .7 21 .9 49 .7 38 .7 52 .3 1, 32 0 1, 37 7 30 .6 3, 73 0 3, 80 2 W ea lth q ui nt ile Lo w es t 0. 6 2. 0 17 .1 19 .1 48 .4 17 .9 19 .1 3, 71 5 4, 98 7 2. 2 5. 4 36 .8 10 .7 30 .7 45 .3 45 .8 64 .6 1, 37 0 1, 79 8 31 .3 5, 08 5 6, 78 5 S ec on d 0. 9 3. 0 15 .9 18 .9 50 .1 19 .8 18 .9 3, 64 3 2, 87 9 2. 3 5. 1 36 .5 12 .8 27 .7 45 .4 46 .3 64 .4 1, 28 7 1, 02 5 30 .8 4, 93 0 3, 90 4 M id dl e 0. 6 3. 3 15 .1 18 .2 53 .6 18 .7 18 .2 3, 71 6 2, 72 1 2. 9 7. 4 31 .4 10 .9 25 .7 47 .6 46 .4 62 .3 1, 38 0 1, 01 1 30 .2 5, 09 6 3, 73 2 Fo ur th 0. 4 2. 1 13 .6 15 .6 54 .4 19 .6 15 .6 3, 44 6 2, 65 2 2. 3 5. 2 33 .2 15 .8 22 .2 53 .2 39 .4 54 .1 1, 45 2 1, 07 7 27 .0 4, 89 8 3, 72 9 H ig he st 0. 5 3. 9 4. 4 8. 6 55 .0 9. 3 8. 6 2, 60 9 3, 19 9 2. 1 4. 1 13 .5 8. 2 9. 2 67 .6 20 .6 27 .0 1, 29 5 1, 50 1 14 .7 3, 90 4 4, 70 0 To ta l 0. 6 2. 8 13 .8 16 .5 52 .1 17 .5 16 .5 17 ,1 30 16 ,4 38 2. 3 5. 5 30 .4 11 .7 23 .2 51 .7 39 .9 54 .7 6, 78 4 6, 41 2 27 .4 23 ,9 14 22 ,8 50 1 A ny w or k, p ai d or u np ai d, fo r s om eo ne w ho is n ot a m em be r o f t he h ou se ho ld 2 I nc lu de s an y w or k in a fa m ily b us in es s, o n th e fa rm , o r s el lin g go od s in th e st re et 3 E co no m ic a ct iv ity is d ef in ed a s w or ki ng , p ai d or u np ai d, fo r s om eo ne w ho is n ot a m em be r o f t he h ou se ho ld o r w or ki ng in a fa m ily b us in es s, o n th e fa rm , o r s el lin g go od s in th e st re et 4 C hi ld la bo ur in cl ud es (a ) c hi ld re n 5- 11 y ea rs w ho in th e 7 da ys p re ce di ng th e su rv ey , w or ke d fo r s om eo ne w ho is n ot a m em be r o f t he h ou se ho ld , w ith o r w ith ou t p ay , o r e ng ag ed in a ny o th er fa m ily w or k or d id h ou se ho ld c ho re s fo r 2 8 or m or e ho ur s, an d (b ) ch ild re n 12 -1 4 ye ar s w ho in th e 7 da ys p re ce di ng th e su rv ey , w or ke d fo r s om eo ne w ho is n ot a m em be r o f t he h ou se ho ld , w ith o r w ith ou t p ay , o r e ng ag ed in a ny o th er fa m ily w or k fo r 14 o r m or e ho ur s or d id h ou se ho ld c ho re s fo r 28 o r m or e ho ur s 5 I nc lu de s ch ild re n of m ot he rs w ho se e du ca tio na l s ta tu s is m is si ng , u nk no w n, o r w ho d o no t l iv e in th e ho us eh ol d. • 33Housing Characteristics and Household Population Characteristics of Respondents • 35 CHARACTERISTICS OF RESPONDENTS 3 his chapter provides a demographic and socioeconomic profile of respondents interviewed in the 2011 EDHS. Such background information is essential to interpreting the findings and understanding the results presented later in this report. Basic characteristics collected include age, level of education, marital status, religion, ethnicity, and wealth status. The EDHS also examined literacy status and exposure to mass media and collected detailed information on employment status, occupation, and earnings. In addition, this chapter includes a discussion of tobacco use, alcohol consumption and chewing chat, all of which have important health implications. 3.1 CHARACTERISTICS OF SURVEY RESPONDENTS Table 3.1 shows the percent distribution of women and men age 15-49 by their background characteristics. About six in every ten women (61 percent) and men age 15-49 (60 percent) are under age 30. In general, the proportion of women and men in each age group declines as age increases, reflecting the comparatively young age structure of the population in Ethiopia, which is a result of high fertility in the past. By religious affiliation about half of the respondents (48 percent of both women and men) are Orthodox Christians, and about three in every ten (28 percent of women and 30 percent of men) are Muslims. Protestants account for 22 percent of women and 19 percent of men. By ethnic composition about one-third of respondents (33 percent of women and 36 percent of men) belong to the Oromo ethnic group, and similar proportions (33 percent of women and 32 percent of men) are Amharas. Tigraways constitute 7 percent of women and 6 percent of men. While there are more than 80 ethnic groups in Ethiopia, most are small in number and, therefore, are not shown separately but are grouped under the category ’Other’. The majority of respondents (62 percent of women and 54 percent of men) are married or living together. The proportion not currently married varies by gender. A much lower percentage of women (27 percent) than men (44 percent) have never married. Women are more likely than men to be divorced, separated, or widowed (11 percent versus 3 percent). T Key Findings • About half of women 15-49 (51 percent) and one-third of men 15-59 (33 percent) have no formal education. These proportions have decreased since the 2005 EDHS, when 66 percent of women and 43 percent of men had no formal education. • Thirty-eight percent of women 15-49 and 65 percent of men 15-59 are literate, an increase from 29 percent and 59 percent, respectively, in 2005. • Sixty-eight percent of women and 53 percent of men age 15-49 are not exposed to any mass media. • Fifty-eight percent of women were employed in the 12 months preceding the survey. The largest group of these women (46 percent) worked in the agricultural sector. • Three in every ten working women received no pay of any kind. 36 • Characteristics of Respondents A person’s place of residence, whether rural or urban, determines access to services and information about reproductive health and other aspects of life. Over three-quarters of respondents live in rural areas—76 percent of women and 78 percent of men. More than eight respondents in every ten (83 percent of women and 84 percent of men) live in three major regions: Amhara, Oromiya, and the Southern Nations, Nationalities, and People's (SNNP) region. Respondents in Tigray (6-7 percent), Addis Ababa (5 percent), and Somali (2 percent) constitute considerably lower proportions of survey respondents. Table 3.1 Background characteristics of respondents Percent distribution of women and men age 15-49 by selected background characteristics, Ethiopia 2011 Background characteristic Women Men Weighted percent Weighted number Unweighted number Weighted percent Weighted number Unweighted number Age 15-19 24.3 4,009 3,835 23.5 3,013 2,832 20-24 17.7 2,931 3,022 18.1 2,319 2,330 25-29 19.1 3,147 3,185 17.9 2,297 2,274 30-34 12.4 2,054 2,100 11.6 1,483 1,682 35-39 11.6 1,916 1,958 12.8 1,648 1,579 40-44 7.6 1,261 1,314 8.7 1,121 1,210 45-49 7.2 1,196 1,101 7.4 952 961 Religion Orthodox 47.5 7,847 6,995 47.8 6,140 5,514 Catholic 1.1 179 177 0.9 120 125 Protestant 22.0 3,634 2,936 19.2 2,459 2,071 Muslim 27.8 4,588 6,170 29.6 3,796 4,876 Traditional 0.8 128 93 0.8 96 87 Missing 0.1 13 8 0.0 2 2 Ethnicity Affar 0.7 110 1,055 0.6 73 699 Amhara 32.5 5,364 4,232 31.7 4,064 3,264 Guragie 3.1 520 692 2.7 345 513 Nuwer 0.1 12 364 0.1 8 219 Oromo 32.5 5,362 3,853 35.9 4,607 3,280 Sidamo 3.6 602 380 3.8 487 336 Somali 1.9 316 969 1.8 225 741 Tigray 6.9 1,134 1,838 6.4 820 1,354 Welaita 3.2 528 344 2.9 368 277 Other 15.1 2,501 2,715 13.9 1,788 2,133 Missing 0.4 66 73 0.4 50 52 Marital status Never married 27.1 4,469 4,413 43.6 5,600 5,641 Married 58.1 9,594 9,478 51.5 6,610 6,427 Living together 4.2 694 726 2.0 261 348 Divorced/separated 7.4 1,222 1,317 2.5 322 383 Widowed 3.2 536 581 0.3 41 69 Residence Urban 23.9 3,947 5,329 22.5 2,882 3,915 Rural 76.1 12,568 11,186 77.5 9,952 8,953 Region Tigray 6.7 1,104 1,728 6.0 770 1,235 Affar 0.9 145 1,291 0.8 101 910 Amhara 26.8 4,433 2,087 27.1 3,481 1,739 Oromiya 36.4 6,011 2,135 38.6 4,957 1,889 Somali 2.0 329 914 1.9 245 653 Benishangul-Gumuz 1.1 174 1,259 1.1 138 1,047 SNNP 19.6 3,236 2,034 18.0 2,307 1,550 Gambela 0.4 69 1,130 0.5 59 865 Harari 0.3 49 1,101 0.3 40 898 Addis Ababa 5.4 896 1,741 5.3 682 1,237 Dire Dawa 0.4 69 1,095 0.4 53 845 Education No education 50.8 8,394 8,278 29.5 3,785 3,659 Primary 38.0 6,276 5,858 53.1 6,813 6,334 Secondary 6.8 1,117 1,395 10.1 1,296 1,565 More than secondary 4.4 728 984 7.3 940 1,310 Wealth quintile Lowest 18.1 2,986 3,711 16.7 2,141 2,563 Second 18.4 3,041 2,402 18.4 2,362 1,891 Middle 18.4 3,031 2,268 19.1 2,454 1,935 Fourth 19.5 3,215 2,505 20.9 2,683 2,203 Highest 25.7 4,242 5,629 24.9 3,194 4,276 Total 15-49 100.0 16,515 16,515 100.0 12,834 12,868 50-59 na na na na 1,276 1,242 Total 15-59 na na na na 14,110 14,110 Note: Education categories refer to the highest level of education attended, whether or not that level was completed. na = Not applicable Characteristics of Respondents • 37 Education is an important factor influencing an individual’s attitudes and opportunities. Generally, educational attainment in Ethiopia is low among both men and women, although women are much more disadvantaged than men. About half of women 15-49 (51 percent) and one-third of men 15-59 (33 percent) have no formal education. The corresponding figures in the 2005 EDHS were 66 percent for women and 43 percent for men, evidence that education has become more widespread over the past six years. A notably higher proportion of men than women have primary education (53 percent of men compared with 38 percent of women) or secondary education and higher (18 percent of men compared with 11 percent of women). 3.2 EDUCATIONAL ATTAINMENT BY BACKGROUND CHARACTERISTICS Tables 3.2.1 and 3.2.2 show the relationship between respondents’ level of education and their other background characteristics. As mentioned, men are better educated than women. The percentage of women with no education decreases steadily by age group, from 85 percent among women age 45-49 to 17 percent among women age 15-19, suggesting an improvement in women’s education over time. Six rural women in every ten (60 percent) have no education, compared with about two urban women in every ten (22 percent). The urban-rural difference is also pronounced at the secondary or higher levels. For example, only 4 percent of women in rural areas have secondary or higher education, compared with 35 percent of urban women. Women’s educational attainment also differs among regions. The highest proportions of women with no education are in the Affar and Somali regions (75 and 74 percent, respectively), and the lowest is in Addis Ababa (15 percent). Access to education increases with women’s wealth. Seven women in every ten in the lowest wealth quintile (72 percent) have no education, compared with just two women in every ten in the highest wealth quintile (21 percent). Furthermore, women in the highest wealth quintile have had substantially more opportunity to move beyond the primary level of education than other women. More than one-third of women in the highest wealth quintile (35 percent) have attended or completed secondary or higher levels of education, compared with 1-6 percent of women in the lowest four wealth quintiles. The pattern of educational attainment among men is similar to that of women. At every level of education, however, a higher percentage of men, than women, are educated. This gender disparity is more marked at higher than at lower levels of education, indicating the government’s recognition and successful intervention in recent years to address gender disparity in basic education. 38 • Characteristics of Respondents Table 3.2.1 Educational attainment: Women Percent distribution of women age 15-49 by highest level of schooling attended or completed, and median years completed, by background characteristics, Ethiopia 2011 Background characteristic Highest level of schooling Total Median years completed Weighted number of women Unweighted number of women No education Some primary Completed primary1 Some secondary Completed secondary2 More than secondary Age 15-24 26.1 50.5 7.0 10.5 0.4 5.7 100.0 3.6 6,940 6,857 15-19 17.3 61.6 8.6 9.9 0.2 2.4 100.0 4.2 4,009 3,835 20-24 38.0 35.2 4.8 11.3 0.5 10.2 100.0 2.2 2,931 3,022 25-29 60.7 26.9 2.5 4.2 0.9 4.8 100.0 0.0 3,147 3,185 30-34 67.0 22.8 1.6 2.8 1.7 4.1 100.0 0.0 2,054 2,100 35-39 67.4 23.7 2.5 1.5 2.0 2.9 100.0 0.0 1,916 1,958 40-44 78.4 15.8 1.0 1.5 1.2 2.2 100.0 0.0 1,261 1,314 45-49 85.0 11.7 1.0 0.5 0.5 1.3 100.0 0.0 1,196 1,101 Residence Urban 22.2 33.2 9.4 16.7 3.5 15.0 100.0 6.3 3,947 5,329 Rural 59.8 34.2 2.3 2.5 0.1 1.1 100.0 0.0 12,568 11,186 Region Tigray 49.4 32.3 6.0 8.4 0.8 3.2 100.0 0.0 1,104 1,728 Affar 74.6 15.6 3.0 3.9 0.5 2.4 100.0 0.0 145 1,291 Amhara 61.4 25.9 3.5 4.8 0.4 4.0 100.0 0.0 4,433 2,087 Oromiya 49.4 36.9 4.4 5.1 0.5 3.6 100.0 0.0 6,011 2,135 Somali 74.2 19.3 1.4 3.5 0.4 1.2 100.0 0.0 329 914 Benishangul-Gumuz 57.7 30.0 2.9 3.7 0.4 5.3 100.0 0.0 174 1,259 SNNP 46.6 42.2 2.8 4.9 0.4 3.1 100.0 0.4 3,236 2,034 Gambela 30.7 49.3 6.9 6.1 0.2 6.7 100.0 3.3 69 1,130 Harari 35.6 28.4 5.7 10.4 6.1 13.9 100.0 4.5 49 1,101 Addis Ababa 14.9 34.6 7.1 17.4 7.8 18.3 100.0 7.1 896 1,741 Dire Dawa 37.0 29.7 5.5 12.1 3.7 12.0 100.0 4.2 69 1,095 Wealth quintile Lowest 72.4 25.9 0.9 0.8 0.0 0.0 100.0 0.0 2,986 3,711 Second 65.5 31.3 1.7 1.3 0.0 0.2 100.0 0.0 3,041 2,402 Middle 61.7 33.6 1.8 2.4 0.1 0.4 100.0 0.0 3,031 2,268 Fourth 45.9 43.9 4.4 4.4 0.0 1.3 100.0 0.5 3,215 2,505 Highest 21.1 34.3 9.3 16.2 3.4 15.7 100.0 6.3 4,242 5,629 Total 50.8 34.0 4.0 5.9 0.9 4.4 100.0 0.0 16,515 16,515 1 Completed 8 grades at the primary level 2 Completed 4 grades at the secondary level Characteristics of Respondents • 39 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 2011 Background characteristic Highest level of schooling Total Median years completed Weighted number of women Unweighted number of women No education Some primary Completed primary1 Some secondary Completed secondary2 More than secondary Age 15-24 15.1 58.2 7.4 13.1 0.2 6.0 100.0 4.6 5,332 5,162 15-19 12.9 66.1 7.8 11.2 0.1 1.9 100.0 4.4 3,013 2,832 20-24 17.8 48.0 6.9 15.7 0.4 11.3 100.0 5.0 2,319 2,330 25-29 32.8 39.2 5.8 8.8 1.0 12.5 100.0 2.8 2,297 2,274 30-34 37.8 39.4 5.6 6.3 2.0 8.9 100.0 1.8 1,483 1,682 35-39 41.8 41.7 4.0 4.0 3.6 4.9 100.0 1.3 1,648 1,579 40-44 44.4 38.8 5.3 4.1 1.9 5.4 100.0 0.9 1,121 1,210 45-49 50.6 36.5 2.2 3.0 1.6 6.1 100.0 0.0 952 961 Residence Urban 8.2 32.0 10.1 21.5 4.6 23.6 100.0 8.0 2,882 3,915 Rural 35.7 51.6 4.7 5.2 0.3 2.6 100.0 2.0 9,952 8,953 Region Tigray 30.7 45.2 6.1 8.7 0.6 8.7 100.0 2.9 770 1,235 Affar 48.9 27.9 6.2 7.2 2.2 7.5 100.0 0.2 101 910 Amhara 45.1 39.0 4.4 7.0 0.6 3.9 100.0 0.8 3,481 1,739 Oromiya 26.1 51.5 6.7 8.1 0.5 7.0 100.0 3.1 4,957 1,889 Somali 42.4 36.1 5.5 7.7 1.7 6.7 100.0 1.0 245 653 Benishangul-Gumuz 31.6 49.2 5.3 7.1 0.2 6.6 100.0 2.7 138 1,047 SNNP 19.0 58.9 4.9 9.2 1.2 6.8 100.0 4.1 2,307 1,550 Gambela 12.8 44.7 9.4 15.7 3.3 14.1 100.0 6.1 59 865 Harari 13.0 35.4 9.5 16.5 4.3 21.4 100.0 7.2 40 898 Addis Ababa 4.1 28.7 10.0 22.2 10.1 24.9 100.0 9.1 682 1,237 Dire Dawa 16.1 31.6 8.4 14.9 6.1 23.0 100.0 7.3 53 845 Wealth quintile Lowest 50.8 44.9 1.7 2.0 0.1 0.4 100.0 0.0 2,141 2,563 Second 40.7 52.0 3.7 3.2 0.0 0.4 100.0 1.1 2,362 1,891 Middle 34.9 54.9 5.2 3.4 0.2 1.4 100.0 1.9 2,454 1,935 Fourth 23.9 55.9 6.1 10.5 0.4 3.2 100.0 3.7 2,683 2,203 Highest 7.5 32.0 10.6 20.4 4.4 25.1 100.0 8.0 3,194 4,276 Total 15-49 29.5 47.2 5.9 8.9 1.3 7.3 100.0 3.2 12,834 12,868 50-59 63.6 28.2 2.0 1.7 0.8 3.7 100.0 0.0 1,276 1,242 Total 15-59 32.6 45.5 5.5 8.2 1.2 7.0 100.0 2.8 14,110 14,110 1 Completed 8 grades at the primary level 2 Completed 4 grades at the secondary level 3.3 LITERACY The ability to read and write is an important asset, enabling individuals to have more opportunities in life. Knowing the distribution of the literate population can help managers of social programmes, including programmes in health and family planning, to decide how to reach women and men with health messages and other information. In the 2011 EDHS, literacy status was determined by the respondents’ ability to read all or part of a sentence. To test respondents’ literacy, during data collection interviewers carried a set of cards on which simple sentences were printed in five of the major languages spoken in Ethiopia. Only women and men who had never been to school and those who had not completed primary level education were asked to read the cards, in the language they were most likely able to read; those who had attained middle school or above were assumed to be literate. As Table 3.3.1 indicates, 38 percent of women are literate, an increase from 29 percent in 2005. Literacy among women varies greatly by age, increasing sharply from 13 percent among women age 45-49 to 64 percent among women age 15-19. Literacy is much higher in urban areas than rural areas. About seven urban women in every ten (69 percent) are literate compared with about three rural women in every ten (29 percent). 40 • Characteristics of Respondents 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 2011 Background characteristic Secondary school or higher No schooling or primary school Total Percentage literate1 Weighted number of women Unweighted number of women Can read a whole sentence Can read part of a sentence Cannot read at all No card with required language Blind/ visually impaired Missing Age 15-24 16.5 27.7 12.8 39.2 3.2 0.0 0.6 100.0 56.9 6,940 6,857 15-19 12.5 36.9 14.3 31.3 4.0 0.0 1.0 100.0 63.7 4,009 3,835 20-24 21.9 15.1 10.8 50.1 2.0 0.0 0.2 100.0 47.8 2,931 3,022 25-29 9.9 9.5 8.3 70.2 1.8 0.0 0.2 100.0 27.8 3,147 3,185 30-34 8.6 8.9 9.8 72.1 0.7 0.0 0.0 100.0 27.2 2,054 2,100 35-39 6.4 11.0 10.2 71.9 0.4 0.1 0.0 100.0 27.6 1,916 1,958 40-44 4.9 6.8 9.6 78.0 0.2 0.5 0.0 100.0 21.4 1,261 1,314 45-49 2.3 3.5 7.3 86.3 0.1 0.5 0.0 100.0 13.1 1,196 1,101 Residence Urban 35.2 24.7 9.2 28.9 1.2 0.0 0.9 100.0 69.0 3,947 5,329 Rural 3.6 14.0 11.1 69.0 2.0 0.1 0.1 100.0 28.8 12,568 11,186 Region Tigray 12.3 24.0 8.7 54.7 0.1 0.0 0.2 100.0 45.0 1,104 1,728 Affar 6.8 8.3 5.2 78.5 0.8 0.0 0.4 100.0 20.3 145 1,291 Amhara 9.2 18.8 8.4 62.7 0.1 0.1 0.7 100.0 36.4 4,433 2,087 Oromiya 9.2 15.7 13.0 60.7 1.1 0.1 0.2 100.0 38.0 6,011 2,135 Somali 5.1 7.3 7.4 76.3 3.9 0.0 0.0 100.0 19.8 329 914 Benishangul-Gumuz 9.4 12.3 7.7 65.5 4.7 0.0 0.4 100.0 29.4 174 1,259 SNNP 8.4 11.8 10.8 63.0 5.8 0.1 0.1 100.0 30.9 3,236 2,034 Gambela 13.0 16.1 7.2 47.5 15.7 0.2 0.3 100.0 36.3 69 1,130 Harari 30.3 16.0 7.6 45.6 0.3 0.0 0.1 100.0 54.0 49 1,101 Addis Ababa 43.5 25.9 10.3 19.3 0.6 0.0 0.3 100.0 79.7 896 1,741 Dire Dawa 27.8 13.1 10.0 45.2 3.3 0.0 0.6 100.0 50.8 69 1,095 Wealth quintile Lowest 0.8 10.2 7.0 79.7 2.0 0.2 0.1 100.0 18.0 2,986 3,711 Second 1.6 11.7 9.4 75.2 2.0 0.1 0.1 100.0 22.7 3,041 2,402 Middle 2.9 12.9 11.3 70.8 2.0 0.0 0.1 100.0 27.2 3,031 2,268 Fourth 5.7 20.1 15.7 55.6 2.2 0.1 0.5 100.0 41.5 3,215 2,505 Highest 35.4 24.5 9.8 28.5 1.2 0.0 0.6 100.0 69.7 4,242 5,629 Total 11.2 16.6 10.6 59.4 1.8 0.1 0.3 100.0 38.4 16,515 16,515 1 Refers to women who attended secondary school or higher and women who can read a whole sentence or part of a sentence. Regional differences in literacy are also marked, with literacy levels highest among women in predominantly urban Addis Ababa (80 percent) and lowest in the predominantly rural Somali and Affar regions (both 20 percent). There is also a marked difference in literacy by women’s wealth, ranging from 18 percent among women in the lowest wealth quintile to 70 percent in the highest wealth quintile. Table 3.3.2 shows that 65 percent of men 15-59 are literate, an increase from 59 percent in 2005. Men age 15-49 are much more likely than women to be literate (67 percent versus 38 percent). Similar to women, men age 15-24 (75 percent), men living in urban areas (90 percent), men residing in Addis Ababa (95 percent), and men in the highest wealth quintile (89 percent) have the highest literacy levels. Characteristics of Respondents • 41 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 2011 Background characteristic Secondary school or higher No schooling or primary school Total Percentage literate1 Weighted number of men Unweighted number of men Can read a whole sentence Can read part of a sentence Cannot read at all No card with required language Blind/ visually impaired Missing Age 15-24 19.4 38.9 16.8 22.3 2.0 0.1 0.7 100.0 75.0 5,332 5,162 15-19 13.2 44.4 17.8 21.6 2.1 0.1 0.8 100.0 75.4 3,013 2,832 20-24 27.3 31.7 15.5 23.1 1.8 0.0 0.5 100.0 74.6 2,319 2,330 25-29 22.3 25.2 14.6 35.2 1.9 0.1 0.6 100.0 62.2 2,297 2,274 30-34 17.1 24.8 17.0 39.3 1.3 0.1 0.4 100.0 58.9 1,483 1,682 35-39 12.6 27.7 19.9 39.3 0.4 0.0 0.2 100.0 60.1 1,648 1,579 40-44 11.5 30.6 19.6 37.1 1.1 0.0 0.1 100.0 61.7 1,121 1,210 45-49 10.7 28.1 19.6 40.6 0.7 0.2 0.2 100.0 58.4 952 961 Residence Urban 49.7 31.8 8.5 8.8 0.7 0.1 0.5 100.0 90.0 2,882 3,915 Rural 8.1 31.9 19.8 38.0 1.7 0.1 0.5 100.0 59.8 9,952 8,953 Region Tigray 18.1 37.6 16.1 27.6 0.4 0.2 0.0 100.0 71.8 770 1,235 Affar 16.9 21.0 14.6 46.5 0.7 0.0 0.2 100.0 52.5 101 910 Amhara 11.5 36.0 14.4 37.2 0.2 0.1 0.6 100.0 61.9 3,481 1,739 Oromiya 15.6 28.4 22.8 31.9 0.7 0.0 0.6 100.0 66.8 4,957 1,889 Somali 16.0 23.4 11.8 38.5 9.6 0.2 0.4 100.0 51.2 245 653 Benishangul-Gumuz 13.9 32.8 15.6 34.4 2.6 0.0 0.7 100.0 62.3 138 1,047 SNNP 17.2 32.5 15.1 29.8 5.0 0.1 0.3 100.0 64.8 2,307 1,550 Gambela 33.1 30.4 9.8 20.2 6.2 0.1 0.3 100.0 73.3 59 865 Harari 42.1 25.8 14.2 17.4 0.0 0.1 0.4 100.0 82.1 40 898 Addis Ababa 57.2 32.1 5.2 5.4 0.0 0.0 0.2 100.0 94.5 682 1,237 Dire Dawa 43.9 28.8 5.9 17.4 2.6 0.0 1.4 100.0 78.6 53 845 Wealth quintile Lowest 2.5 24.0 19.1 51.2 2.8 0.2 0.3 100.0 45.6 2,141 2,563 Second 3.6 30.3 18.7 45.4 1.7 0.1 0.3 100.0 52.6 2,362 1,891 Middle 5.0 35.0 21.3 36.6 1.4 0.1 0.6 100.0 61.4 2,454 1,935 Fourth 14.2 38.1 21.0 25.1 1.2 0.0 0.4 100.0 73.2 2,683 2,203 Highest 49.9 30.6 8.9 9.1 0.8 0.1 0.7 100.0 89.3 3,194 4,276 Total 15-49 17.4 31.8 17.3 31.4 1.5 0.1 0.5 100.0 66.5 12,834 12,868 50-59 6.2 21.0 22.2 49.6 0.7 0.1 0.2 100.0 49.4 1,276 1,242 Total 15-59 16.4 30.9 17.7 33.1 1.4 0.1 0.4 100.0 65.0 14,110 14,110 1 Refers to men who attended secondary school or higher and men who can read a whole sentence or part of a sentence. F 3.4 EXPOSURE TO MASS MEDIA Exposure to information on television and radio and in the print media can increase knowledge and awareness of new ideas, social changes, and opportunities and can affect an individual’s perceptions and behaviour, including those about health. The 2011 EDHS assessed exposure to the media by asking how often a respondent reads a newspaper, watches television, or listens to the radio. Tables 3.4.1 and 3.4.2 show the percentage of women and of men who are exposed to different types of media, by their age, urban or rural residence, region, level of education, and wealth quintile. 42 • Characteristics of Respondents Table 3.4.1 Exposure to mass media: Women Percentage of women age 15-49 who are exposed to specific media on a weekly basis, by background characteristics, Ethiopia 2011 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 Weighted number of women Unweighted number of women Age 15-19 9.0 17.9 25.8 2.1 61.6 4,009 3,835 20-24 6.5 20.9 25.2 2.3 62.3 2,931 3,022 25-29 3.5 15.5 22.7 1.9 69.3 3,147 3,185 30-34 3.0 14.2 19.5 1.5 72.7 2,054 2,100 35-39 1.7 12.7 18.7 0.9 73.2 1,916 1,958 40-44 1.3 12.2 19.0 0.5 74.6 1,261 1,314 45-49 0.9 9.7 14.7 0.6 79.8 1,196 1,101 Residence Urban 10.8 48.3 38.1 6.0 37.8 3,947 5,329 Rural 2.8 5.7 17.2 0.3 77.8 12,568 11,186 Region Tigray 5.5 19.3 24.7 2.5 66.1 1,104 1,728 Affar 2.1 16.8 13.4 1.0 74.7 145 1,291 Amhara 1.5 12.1 18.7 0.4 73.6 4,433 2,087 Oromiya 6.4 10.3 23.3 1.4 69.1 6,011 2,135 Somali 1.5 10.4 10.9 0.2 81.8 329 914 Benishangul-Gumuz 2.5 9.6 15.9 0.5 76.8 174 1,259 SNNP 3.4 17.8 19.3 1.1 68.7 3,236 2,034 Gambela 2.7 14.9 8.1 0.9 78.8 69 1,130 Harari 10.7 54.5 35.5 7.1 38.8 49 1,101 Addis Ababa 14.8 59.5 45.3 10.6 31.4 896 1,741 Dire Dawa 11.2 50.1 31.9 6.7 42.6 69 1,095 Education No education 0.0 5.6 13.9 0.0 82.3 8,394 8,278 Primary 6.3 18.1 25.8 1.2 61.8 6,276 5,858 Secondary 18.5 50.4 42.3 8.3 31.4 1,117 1,395 More than secondary 24.0 63.4 54.9 14.3 18.3 728 984 Wealth quintile Lowest 1.0 3.9 6.0 0.0 89.9 2,986 3,711 Second 2.0 4.5 13.0 0.2 82.0 3,041 2,402 Middle 1.9 4.8 17.9 0.0 77.7 3,031 2,268 Fourth 5.0 6.4 27.5 0.4 67.5 3,215 2,505 Highest 11.0 47.7 39.0 6.0 36.9 4,242 5,629 Total 4.7 15.9 22.2 1.7 68.2 16,515 16,515 Characteristics of Respondents • 43 Table 3.4.2 Exposure to mass media: Men Percentage of men age 15-49 who are exposed to specific media on a weekly basis, by background characteristics, Ethiopia 2011 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 Weighted number of men Unweighted number of men Age 15-19 11.5 20.1 32.0 4.0 57.7 3,013 2,832 20-24 14.2 27.4 43.6 7.5 47.2 2,319 2,330 25-29 12.6 21.8 40.6 6.2 50.8 2,297 2,274 30-34 11.7 24.3 41.8 7.0 50.8 1,483 1,682 35-39 8.9 18.8 38.2 5.2 55.6 1,648 1,579 40-44 9.8 18.2 37.2 4.7 55.2 1,121 1,210 45-49 6.9 16.5 36.8 3.6 57.4 952 961 Residence Urban 26.8 60.1 59.0 18.8 22.2 2,882 3,915 Rural 6.9 10.5 32.4 1.7 62.3 9,952 8,953 Region Tigray 12.2 33.4 38.5 5.0 42.9 770 1,235 Affar 6.0 19.1 28.4 2.1 62.7 101 910 Amhara 5.6 15.8 26.5 1.9 65.8 3,481 1,739 Oromiya 12.6 17.9 44.5 5.2 48.8 4,957 1,889 Somali 9.3 18.3 38.1 2.7 52.3 245 653 Benishangul-Gumuz 7.9 22.2 33.4 3.2 55.0 138 1,047 SNNP 6.8 15.6 30.1 2.2 62.2 2,307 1,550 Gambela 14.8 33.9 29.9 5.5 47.4 59 865 Harari 25.2 59.6 62.6 17.6 19.7 40 898 Addis Ababa 46.1 79.0 82.4 38.3 7.1 682 1,237 Dire Dawa 33.8 66.3 64.7 26.8 19.1 53 845 Education No education 1.0 5.3 22.2 0.2 74.9 3,785 3,659 Primary 9.5 19.1 38.9 3.2 52.0 6,813 6,334 Secondary 29.3 50.8 60.2 18.0 26.5 1,296 1,565 More than secondary 41.8 64.7 69.8 27.5 12.4 940 1,310 Wealth quintile Lowest 3.8 5.9 20.1 0.6 75.7 2,141 2,563 Second 3.7 8.1 26.8 1.0 68.9 2,362 1,891 Middle 6.9 9.1 32.9 1.5 62.2 2,454 1,935 Fourth 10.7 13.6 42.9 2.7 50.3 2,683 2,203 Highest 26.0 58.5 59.6 17.7 22.3 3,194 4,276 Total 15-49 11.4 21.6 38.4 5.6 53.3 12,834 12,868 50-59 6.6 14.9 32.4 3.1 61.6 1,276 1,242 Total 15-59 10.9 21.0 37.9 5.3 54.0 14,110 14,110 44 • Characteristics of Respondents The survey shows that the level of exposure to mass media is low in Ethiopia, especially exposure to the print media. Respondents are more likely to listen to the radio (22 percent of women and 38 percent of men) than to watch television or read newspapers. Men have greater access than women to each of these media. Women under age 25 are more likely than older women to be exposed to the mass media, primarily because their level of education is higher. There is also a wide gap in exposure to mass media by place of residence, education, and wealth. For example, the proportion of women who read a newspaper at least once a week is highest among urban residents (11 percent), women with some secondary education (19 percent) or more than secondary education (24 percent), and women in the wealthiest quintile (11 percent). Women in Addis Ababa are the most likely to read a newspaper on a weekly basis (15 percent). The patterns of exposure to mass media are similar among men and women. Exposure to each of the specified media sources has increased since 2005. For example, the proportion of women 15-49 who listen to the radio at least once a week has increased from 16 percent in the 2005 EDHS to 22 percent in 2011, while the proportion among men 15-59 has increased from 31 percent to 38 percent. 3.5 EMPLOYMENT The 2011 EDHS asked respondents whether they were employed at the time of the survey (that is, had worked in the past seven days) and, if not, whether they had worked any time during the 12 months preceding the survey. Table 3.5.1 and Figure 3.1 show that 38 percent of women are currently employed (worked in the past seven days). The proportion of women currently employed rises from 27 percent among women age 15-19 to a peak of 44 percent among women age 25-29 and then declines slightly for the older age groups. By marital status, women who are divorced, separated, or widowed are most likely to be currently employed (51 percent). There are notable variations in the proportion currently employed by place of residence and by region. Urban women are more likely to be currently employed than rural women (50 percent compared with 34 percent). Women in Addis Ababa and Gambela are the most likely to be currently employed (52 and 47 percent, respectively), while women in Affar and Somali regions are the least likely (19 and 22 percent, respectively). Characteristics of Respondents • 45 Table 3.5.1 Employment status: Women Percent distribution of women age 15-49 by employment status, according to background characteristics, Ethiopia 2011 Background characteristic Employed in the 12 months preceding the survey Not employed in the 12 months preceding the survey Missing/ don't know Total Weighted number of women Unweighted number of women Currently employed1 Not currently employed Age 15-19 27.1 22.3 50.5 0.1 100.0 4,009 3,835 20-24 38.9 19.0 42.2 0.0 100.0 2,931 3,022 25-29 44.0 16.1 39.8 0.1 100.0 3,147 3,185 30-34 42.1 18.6 39.3 0.0 100.0 2,054 2,100 35-39 41.4 20.5 38.1 0.0 100.0 1,916 1,958 40-44 38.9 24.2 36.9 0.0 100.0 1,261 1,314 45-49 38.2 23.9 38.0 0.0 100.0 1,196 1,101 Marital status Never married 36.8 17.7 45.4 0.1 100.0 4,469 4,413 Married or living together 35.8 20.8 43.4 0.0 100.0 10,287 10,204 Divorced/separated/widowed 50.8 22.3 26.9 0.0 100.0 1,758 1,898 Number of living children 0 36.6 19.1 44.2 0.1 100.0 5,708 5,771 1-2 39.4 19.6 40.9 0.0 100.0 3,987 4,257 3-4 40.0 18.9 41.0 0.1 100.0 3,219 3,151 5+ 35.2 23.4 41.5 0.0 100.0 3,601 3,336 Residence Urban 49.9 7.8 42.3 0.0 100.0 3,947 5,329 Rural 33.8 24.0 42.2 0.1 100.0 12,568 11,186 Region Tigray 29.9 45.2 24.8 0.0 100.0 1,104 1,728 Affar 19.0 4.4 76.7 0.0 100.0 145 1,291 Amhara 31.4 30.2 38.4 0.0 100.0 4,433 2,087 Oromiya 41.0 15.1 43.9 0.1 100.0 6,011 2,135 Somali 22.2 3.1 74.5 0.2 100.0 329 914 Benishangul-Gumuz 42.4 12.2 45.2 0.2 100.0 174 1,259 SNNP 40.7 14.5 44.8 0.0 100.0 3,236 2,034 Gambela 46.7 9.1 44.1 0.0 100.0 69 1,130 Harari 40.1 6.1 53.8 0.1 100.0 49 1,101 Addis Ababa 51.5 6.2 42.3 0.0 100.0 896 1,741 Dire Dawa 40.2 2.3 57.4 0.0 100.0 69 1,095 Education No education 34.7 22.8 42.4 0.0 100.0 8,394 8,278 Primary 37.8 19.7 42.5 0.0 100.0 6,276 5,858 Secondary 40.5 12.3 46.8 0.5 100.0 1,117 1,395 More than secondary 65.4 4.8 29.9 0.0 100.0 728 984 Wealth quintile Lowest 28.1 28.4 43.5 0.0 100.0 2,986 3,711 Second 31.8 25.8 42.4 0.0 100.0 3,041 2,402 Middle 35.7 22.7 41.4 0.2 100.0 3,031 2,268 Fourth 38.8 20.7 40.5 0.1 100.0 3,215 2,505 Highest 49.0 7.9 43.1 0.0 100.0 4,242 5,629 Total 37.6 20.1 42.2 0.1 100.0 16,515 16,515 1 "Currently employed" is defined as having done work in the past seven days. This measure includes persons who did not work in the past seven days but who are regularly employed and were absent from work due to leave, illness, vacation, or any other such reason. 46 • Characteristics of Respondents Figure 3.1 Women’s Employment Status in the Past 12 Months EDHS 2011 Currently employed 38% Not currently employed 20% Not employed in the 12 42% Not employed in the past 12 months 42% Employed in the past 12 months but not currently employed 20% The percentage of women currently employed increases as their level of education increases; the proportion of women employed rises from 35 percent among uneducated women to 65 percent among women with more than secondary education. There is also an increase in the percentage of women employed by wealth quintile; women in the highest quintile have the highest level of employment (49 percent) when compared with women in the lowest quintiles. Table 3.5.2 shows that a large majority of men, 80 percent, are currently employed. Men age 15-19 (65 percent), men who have never married (71 percent), men with no living children (73 percent), and urban men (77 percent) are less likely to be currently employed than other men. Men in Addis Ababa and SNNP (both 84 percent) have the highest level of current employment, while men in Harari have the lowest level (58 percent). Characteristics of Respondents • 47 Table 3.5.2 Employment status: Men Percent distribution of men age 15-49 by employment status, according to background characteristics, Ethiopia 2011 Background characteristic Employed in the 12 months preceding the survey Not employed in the 12 months preceding the survey Missing/ don't know Total Weighted number of men Unweighted number of men Currently employed1 Not currently employed Age 15-19 65.2 20.6 14.2 0.0 100.0 3,013 2,832 20-24 75.4 16.9 7.6 0.1 100.0 2,319 2,330 25-29 86.7 11.7 1.6 0.0 100.0 2,297 2,274 30-34 86.6 12.2 1.2 0.0 100.0 1,483 1,682 35-39 87.8 11.8 0.4 0.0 100.0 1,648 1,579 40-44 87.2 11.8 0.9 0.1 100.0 1,121 1,210 45-49 86.3 13.2 0.4 0.0 100.0 952 961 Marital status Never married 71.0 17.7 11.3 0.0 100.0 5,600 5,641 Married or living together 86.6 12.8 0.5 0.0 100.0 6,872 6,775 Divorced/separated/widowed 84.5 12.7 2.7 0.0 100.0 363 452 Number of living children 0 72.9 17.0 10.0 0.0 100.0 6,465 6,534 1-2 86.8 12.8 0.5 0.0 100.0 2,338 2,463 3-4 86.4 13.1 0.5 0.0 100.0 2,038 1,922 5+ 86.7 12.7 0.5 0.1 100.0 1,994 1,949 Residence Urban 76.6 11.4 12.1 0.0 100.0 2,882 3,915 Rural 80.7 16.0 3.3 0.0 100.0 9,952 8,953 Region Tigray 79.3 18.0 2.7 0.0 100.0 770 1,235 Affar 66.8 24.8 8.4 0.0 100.0 101 910 Amhara 76.9 17.0 6.1 0.0 100.0 3,481 1,739 Oromiya 80.3 15.5 4.1 0.0 100.0 4,957 1,889 Somali 64.2 13.8 21.8 0.2 100.0 245 653 Benishangul-Gumuz 81.6 10.9 7.6 0.0 100.0 138 1,047 SNNP 84.2 11.7 4.1 0.1 100.0 2,307 1,550 Gambela 82.8 9.7 7.5 0.0 100.0 59 865 Harari 57.7 24.2 18.0 0.1 100.0 40 898 Addis Ababa 83.9 7.9 8.2 0.0 100.0 682 1,237 Dire Dawa 78.2 10.5 11.3 0.0 100.0 53 845 Education No education 83.2 15.6 1.1 0.1 100.0 3,785 3,659 Primary 78.7 15.8 5.5 0.0 100.0 6,813 6,334 Secondary 73.9 14.0 12.1 0.0 100.0 1,296 1,565 More than secondary 81.2 7.0 11.8 0.0 100.0 940 1,310 Wealth quintile Lowest 82.9 14.2 2.8 0.1 100.0 2,141 2,563 Second 81.8 15.6 2.6 0.0 100.0 2,362 1,891 Middle 78.3 17.8 3.9 0.1 100.0 2,454 1,935 Fourth 79.9 16.1 4.0 0.0 100.0 2,683 2,203 Highest 77.1 11.7 11.2 0.0 100.0 3,194 4,276 Total 15-49 79.7 14.9 5.3 0.0 100.0 12,834 12,868 50-59 87.3 10.9 1.8 0.0 100.0 1,276 1,242 Total 15-59 80.4 14.6 5.0 0.0 100.0 14,110 14,110 1 "Currently employed" is defined as having done work in the past seven days. This measure includes persons who did not work in the past seven days but who are regularly employed and were absent from work due to leave, illness, vacation, or any other such reason. 48 • Characteristics of Respondents There is no clear pattern in the variation of men’s employment level by level of education. By wealth status, current employment among men decreases from 83 percent among the poorest men to 77 percent among the wealthiest. Current employment among women 15-49 increased from 29 percent in 2005 to 38 percent in 2011. In contrast, among men 15-59 it decreased from 86 percent to 80 percent. 3.6 OCCUPATION The 2011 EDHS asked currently employed respondents to state their occupation. Tables 3.6.1 and 3.6.2, for women and men respectively, show that 46 percent of working women 15-49 and 74 percent of working men 15-59 are in agricultural occupations, a drop from the 52 percent and 84 percent, respectively, reported in 2005. Sales and services account for 33 percent of current employment for women and 10 percent for men. Thirteen percent of employed women and 7 percent of employed men work in skilled manual labour, an increase from six years ago. Table 3.6.1 Occupation: Women Percent distribution of women age 15-49 employed in the 12 months preceding the survey by occupation, according to background characteristics, Ethiopia 2011 Background characteristic Professional/ technical/ managerial Clerical Sales and services Skilled manual Unskilled manual Agriculture Missing Total Weighted number of women Unweighted number of women Age 15-19 0.1 0.3 34.3 9.0 2.1 52.6 1.6 100.0 1,980 1,611 20-24 6.4 4.2 36.2 12.4 2.4 37.3 1.0 100.0 1,694 1,576 25-29 4.8 2.6 35.8 13.3 1.8 41.0 0.7 100.0 1,892 1,723 30-34 3.0 3.2 34.6 13.8 1.6 43.0 0.7 100.0 1,245 1,131 35-39 3.2 1.7 30.6 14.4 0.5 46.6 3.0 100.0 1,186 1,106 40-44 1.9 1.7 28.2 12.3 0.8 53.1 1.9 100.0 796 748 45-49 1.2 1.5 22.0 17.4 1.2 55.6 1.2 100.0 742 638 Marital status Never married 4.1 3.8 40.7 10.0 2.7 37.5 1.1 100.0 2,433 2,203 Married or living together 3.0 1.8 29.2 12.8 1.1 50.6 1.6 100.0 5,817 4,981 Divorced/separated/widowed 1.8 1.2 36.0 17.3 2.3 40.4 1.0 100.0 1,286 1,349 Number of living children 0 4.3 3.4 37.5 10.3 2.7 40.7 1.1 100.0 3,179 2,929 1-2 5.1 3.3 32.1 13.4 2.0 43.2 0.9 100.0 2,354 2,298 3-4 2.1 0.9 33.0 16.3 0.7 45.5 1.4 100.0 1,895 1,624 5+ 0.2 0.5 27.4 12.2 0.5 56.9 2.2 100.0 2,107 1,682 Residence Urban 9.1 8.5 52.3 14.2 5.2 9.5 1.2 100.0 2,276 2,919 Rural 1.3 0.3 27.0 12.2 0.5 57.3 1.4 100.0 7,259 5,614 Region Tigray 1.8 1.0 25.8 8.4 2.0 59.1 1.9 100.0 830 1,314 Affar 8.2 4.0 44.7 16.3 1.8 22.6 2.4 100.0 34 255 Amhara 2.3 1.2 18.5 10.3 2.1 64.3 1.4 100.0 2,731 1,293 Oromiya 3.0 1.9 33.9 13.0 1.3 45.9 1.0 100.0 3,369 1,186 Somali 1.5 2.7 68.2 19.1 2.1 2.5 3.9 100.0 83 195 Benishangul-Gumuz 3.5 3.1 26.2 19.5 0.7 45.4 1.6 100.0 95 686 SNNP 3.1 1.4 48.3 16.9 0.4 28.7 1.2 100.0 1,786 1,125 Gambela 3.0 7.7 43.3 29.2 0.4 12.2 4.2 100.0 39 513 Harari 10.5 10.3 65.1 8.7 2.2 1.9 1.2 100.0 23 501 Addis Ababa 10.1 13.6 53.6 13.0 5.1 1.8 2.8 100.0 517 1,018 Dire Dawa 8.9 5.3 67.3 11.4 1.2 3.5 2.3 100.0 29 447 Education No education 0.1 0.1 27.1 13.7 1.3 56.1 1.6 100.0 4,829 4,032 Primary 0.0 0.6 41.7 12.3 1.8 42.5 1.1 100.0 3,606 3,106 Secondary 5.2 11.4 42.8 15.7 3.6 19.6 1.9 100.0 589 710 More than secondary 51.8 23.8 16.7 2.6 1.4 3.0 0.7 100.0 511 685 Wealth quintile Lowest 0.2 0.0 21.7 11.0 1.0 65.0 1.1 100.0 1,688 1,573 Second 0.3 0.3 22.7 10.2 0.5 64.4 1.5 100.0 1,751 1,291 Middle 0.1 0.2 27.2 11.5 0.4 59.3 1.3 100.0 1,771 1,241 Fourth 0.8 0.2 35.4 14.9 1.4 45.5 1.8 100.0 1,911 1,344 Highest 11.4 8.3 50.9 14.9 4.1 9.5 1.1 100.0 2,414 3,084 Total 3.1 2.2 33.0 12.7 1.7 45.9 1.4 100.0 9,535 8,533 Characteristics of Respondents • 49 Table 3.6.2 Occupation: Men Percent distribution of men age 15-49 employed in the 12 months preceding the survey by occupation, according to background characteristics, Ethiopia 2011 Background characteristic Professional/ technical/ managerial Clerical Sales and services Skilled manual Unskilled manual Agriculture Missing Total Weighted number of men Unweighted number of men Age 15-19 0.9 0.5 9.6 3.6 2.2 76.2 6.9 100.0 2,586 2,277 20-24 4.1 1.4 12.4 6.5 2.5 70.8 2.2 100.0 2,139 2,068 25-29 8.0 1.5 11.7 9.1 1.1 67.7 0.9 100.0 2,260 2,210 30-34 5.0 2.4 10.7 10.0 2.1 68.4 1.4 100.0 1,465 1,651 35-39 3.8 1.2 8.9 9.7 0.6 75.3 0.6 100.0 1,642 1,563 40-44 3.7 1.1 10.2 8.0 1.6 74.9 0.5 100.0 1,110 1,190 45-49 5.0 1.7 7.9 4.7 0.2 79.2 1.3 100.0 948 953 Marital status Never married 4.4 1.6 12.4 6.7 2.4 67.8 4.7 100.0 4,965 4,779 Married or living together 4.1 1.1 8.8 7.3 1.0 76.8 0.8 100.0 6,832 6,694 Divorced/separated/widowed 3.7 1.5 14.5 12.9 2.6 63.3 1.4 100.0 353 439 Number of living children 0 4.8 1.6 12.0 7.3 2.2 67.9 4.2 100.0 5,815 5,650 1-2 5.9 1.8 11.8 11.0 1.6 67.0 1.0 100.0 2,327 2,435 3-4 2.8 0.6 9.7 5.9 1.4 78.9 0.7 100.0 2,027 1,903 5+ 2.3 0.7 5.1 3.8 0.1 87.3 0.7 100.0 1,981 1,924 Residence Urban 12.9 5.2 29.8 27.1 6.1 15.0 3.9 100.0 2,534 3,398 Rural 2.0 0.3 5.3 2.0 0.5 87.9 2.0 100.0 9,616 8,514 Region Tigray 5.5 0.7 9.9 9.1 2.2 71.1 1.5 100.0 749 1,204 Affar 11.4 2.9 16.6 8.3 1.5 57.9 1.4 100.0 93 850 Amhara 1.9 0.7 6.5 6.2 1.1 80.1 3.5 100.0 3,267 1,642 Oromiya 3.7 1.1 9.5 4.6 1.7 77.3 2.0 100.0 4,750 1,805 Somali 12.6 0.5 19.4 6.7 3.6 56.1 1.0 100.0 191 527 Benishangul-Gumuz 3.2 1.7 6.7 4.7 0.6 76.9 6.3 100.0 128 974 SNNP 4.6 1.5 10.5 5.0 0.4 76.6 1.3 100.0 2,211 1,501 Gambela 13.5 8.4 33.8 10.0 1.9 30.6 1.9 100.0 55 783 Harari 12.7 3.2 25.1 16.5 4.2 37.4 0.8 100.0 33 736 Addis Ababa 11.9 4.9 31.8 35.9 7.0 3.4 5.2 100.0 627 1,134 Dire Dawa 13.3 3.9 23.7 23.1 5.6 26.8 3.5 100.0 47 756 Education No education 0.4 0.0 5.1 2.9 0.5 90.4 0.6 100.0 3,741 3,581 Primary 0.8 0.4 10.7 7.1 2.2 75.9 2.8 100.0 6,440 5,848 Secondary 5.8 3.2 25.1 17.9 2.3 40.7 5.0 100.0 1,140 1,335 More than secondary 46.6 11.7 12.4 12.6 0.9 12.1 3.7 100.0 829 1,148 Wealth quintile Lowest 0.7 0.0 2.9 0.8 0.4 93.8 1.4 100.0 2,078 2,423 Second 0.5 0.1 2.5 1.7 0.2 93.6 1.4 100.0 2,301 1,828 Middle 0.7 0.1 3.6 1.3 0.4 91.4 2.5 100.0 2,358 1,848 Fourth 2.3 0.2 10.2 3.6 1.4 79.7 2.5 100.0 2,576 2,068 Highest 14.5 5.3 28.2 24.6 5.0 18.5 4.0 100.0 2,837 3,745 Total 15-49 4.2 1.3 10.4 7.2 1.6 72.7 2.4 100.0 12,150 11,912 50-59 3.8 0.8 7.4 5.2 1.0 80.7 1.0 100.0 1,253 1,215 Total 15-59 4.2 1.3 10.2 7.0 1.6 73.5 2.3 100.0 13,403 13,127 The proportion of women in sales and services decreases with age and is highest among never-married women, women with no living children, urban women, women with primary or secondary education, and women in the highest wealth quintile. The percentage of women who work in agriculture is highest among the youngest and oldest age groups, currently married women, women with five or more children, rural women, women with no education, and women in the lowest wealth quintile. The patterns among men are similar. As expected, residence, whether rural or urban, has a significant effect on type of occupation. In rural areas nearly six in every ten employed women (57 percent) and nine in every ten employed men (88 percent) are engaged in agricultural work. Women with secondary or higher education 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. Agriculture is by far the most important occupation for women in all wealth quintiles but the highest. Employment outside the agricultural sector is highest among men with more than secondary education and men in the highest wealth quintile. 50 • Characteristics of Respondents 3.7 TYPE OF WOMEN’S EMPLOYMENT Table 3.7 presents the percent distribution of employed women age 15-49 by type of earnings and employer characteristics, according to type of employment (agricultural or non-agricultural). More than half of women (56 percent) engaged in agricultural work are unpaid workers, most likely employed by family members at the peak of the agricultural season. Women are more likely to be paid in cash if they are employed in the nonagricultural sector; 68 percent of women employed in this sector are paid only in cash. Overall, three in every ten employed women (30 percent) are not paid at all, and only about four in every ten (39 percent) are paid only in cash for their work. Table 3.7 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 2011 Employment characteristic Agricultural work Nonagricultural work Total Type of earnings Cash only 6.7 67.7 39.3 Cash and in-kind 24.0 23.5 23.8 In-kind only 12.8 1.2 6.7 Not paid 56.4 7.5 30.1 Total 100.0 100.0 100.0 Type of employer Employed by family member 65.0 21.9 41.8 Employed by nonfamily member 4.8 21.5 13.7 Self-employed 30.1 56.5 44.4 Total 100.0 100.0 100.0 Continuity of employment All year 13.1 61.5 39.2 Seasonal 77.6 16.4 44.6 Occasional 9.3 22.0 16.0 Total 100.0 100.0 100.0 Weighted number of women employed during the last 12 months 4,373 5,033 9,535 Unweighted number of women employed during the last 12 months 3,143 5,227 8,533 Note: Total includes 12 cases with information missing on type of earnings, 12 cases with information missing on type of employer, and 15 cases with information missing on continuity of employment. More than four in every ten employed women work for a family member (42 percent), and another four in every ten are self-employed (44 percent). Only 14 percent of employed women work for someone outside the family. Sixty-five percent of women in the agricultural sector are working for a family member, compared with 22 percent in the nonagricultural sector. In addition, the proportion of women employed by someone outside the family is much higher among women in the nonagricultural sector than in the agricultural sector (22 percent versus 5 percent). Three-quarters of women employed in the agricultural sector are seasonal workers. In contrast, the majority of women in the nonagricultural sector (62 percent) work all year. Sixteen percent of women are also employed occasionally, with more than twice as many women in the nonagricultural sector (22 percent) employed occasionally as women in the agricultural sector (9 percent). Characteristics of Respondents • 51 3.8 HEALTH ISSUES The 2011 EDHS asked women and men about their use of cigarettes or other tobacco, consumption of alcohol, and use of chat. This information is important in helping understand how widespread the use of these substances is among the adult population in Ethiopia. Also, the 2011 EDHS collected data on women’s and men’s knowledge and attitudes concerning tuberculosis (TB). 3.8.1 Use of Tobacco Few women smoke cigarettes (35 female respondents) or use tobacco of any kind, according to the 2011 EDHS, and so data for women are not shown here. Table 3.8 shows data for men. Seven percent of men age 15-49 use tobacco products of some kind; 6 percent say that they smoke cigarettes. Men age 40-49 (11-13 percent) and men in Harari (27 percent), Somali and Dire Dawa (both 24 percent), and Affar (20 percent) are the most likely to smoke cigarettes. Table 3.8 Use of tobacco: Men Percentage of men age 15-49 who smoke cigarettes or use other tobacco products and the percent distribution of cigarette smokers, by number of cigarettes smoked in preceding 24 hours, according to background characteristics, Ethiopia 2011 Background characteristic Uses tobacco Weighted number of men Un- weighted number of men Percent distribution of men who smoke cigarettes by number of cigarettes smoked in the last 24 hours Total Weighted number of cigarette smokers Un- weighted number of cigarette smokers Cigarettes Other tobacco Does not use tobacco 0 1-2 3-5 6-9 10+ Don't know/ missing Age 15-19 1.3 0.2 98.5 3,013 2,832 8.2 17.1 39.1 6.3 23.5 5.7 100.0 40 80 20-24 2.7 0.9 96.3 2,319 2,330 9.4 17.1 21.0 22.5 23.7 6.3 100.0 63 183 25-29 6.3 1.8 92.6 2,297 2,274 9.7 28.8 33.5 6.9 20.0 1.2 100.0 146 293 30-34 8.9 2.5 89.6 1,483 1,682 2.5 9.2 33.8 15.3 37.7 1.5 100.0 132 282 35-39 9.0 2.9 89.1 1,648 1,579 4.9 12.4 33.6 20.4 28.8 0.0 100.0 148 247 40-44 12.6 4.4 85.3 1,121 1,210 5.7 12.7 34.0 10.7 36.9 0.0 100.0 142 231 45-49 11.2 5.9 84.0 952 961 3.5 13.0 41.9 14.1 27.5 0.0 100.0 106 146 Residence Urban 7.9 1.0 91.4 2,882 3,915 4.7 10.8 29.9 24.0 30.1 0.5 100.0 228 507 Rural 5.5 2.3 92.9 9,952 8,953 6.3 17.7 35.8 9.6 28.9 1.6 100.0 549 955 Region Tigray 1.5 0.1 98.4 770 1,235 * * * * * * 100.0 12 16 Affar 20.4 17.3 68.5 101 910 2.9 10.3 23.9 9.0 52.8 1.1 100.0 21 197 Amhara 2.0 1.1 97.0 3,481 1,739 (12.8) (15.9) (28.9) (27.0) (9.6) (5.7) 100.0 68 30 Oromiya 8.8 2.0 90.2 4,957 1,889 3.7 15.5 37.4 12.1 30.6 0.8 100.0 434 174 Somali 23.9 6.1 73.8 245 653 5.9 8.4 16.0 12.1 57.6 0.0 100.0 58 159 Benishangul-Gumuz 9.5 7.9 85.4 138 1,047 6.6 15.4 34.7 9.3 33.9 0.0 100.0 13 114 SNNP 3.7 2.9 93.9 2,307 1,550 10.1 29.3 42.7 9.6 6.8 1.5 100.0 85 59 Gambela 17.6 5.4 79.1 59 865 5.4 12.9 35.7 14.5 31.5 0.0 100.0 10 164 Harari 26.6 2.8 71.3 40 898 3.2 6.0 15.4 16.9 57.3 1.1 100.0 11 242 Addis Ababa 7.6 0.6 91.9 682 1,237 10.5 12.8 31.2 18.1 26.5 1.0 100.0 52 100 Dire Dawa 23.6 4.7 72.6 53 845 3.5 4.5 23.0 18.0 50.5 0.4 100.0 13 207 Education No education 6.7 4.3 90.2 3,785 3,659 6.3 15.5 32.2 14.2 30.3 1.5 100.0 253 495 Primary 5.9 1.2 93.4 6,813 6,334 4.7 17.2 35.3 10.5 30.9 1.4 100.0 405 665 Secondary 5.7 0.4 94.0 1,296 1,565 11.3 3.5 36.3 25.5 22.4 0.8 100.0 74 181 More than secondary 4.7 1.5 94.2 940 1,310 4.9 22.8 29.9 22.6 19.9 0.0 100.0 44 121 Wealth quintile Lowest 6.8 4.9 89.6 2,141 2,563 5.3 19.3 40.5 5.8 26.7 2.4 100.0 147 364 Second 5.5 2.5 92.6 2,362 1,891 3.4 15.2 33.6 17.1 30.7 0.1 100.0 130 173 Middle 4.9 1.4 94.1 2,454 1,935 14.3 18.0 34.5 9.0 20.8 3.4 100.0 119 159 Fourth 5.8 1.4 93.7 2,683 2,203 3.4 14.7 41.5 9.9 29.3 1.2 100.0 157 234 Highest 7.0 0.8 92.4 3,194 4,276 4.9 13.1 24.7 22.4 34.6 0.3 100.0 224 532 Total 15-49 6.1 2.0 92.6 12,834 12,868 5.9 15.7 34.1 13.8 29.3 1.3 100.0 777 1,462 50-59 10.8 8.0 84.5 1,276 1,242 9.0 17.1 27.9 9.2 35.3 1.6 100.0 137 192 Total 15-59 6.5 2.6 91.9 14,110 14,110 6.3 15.9 33.1 13.1 30.2 1.4 100.0 914 1,654 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. 52 • Characteristics of Respondents Among men age 15-49 who smoke cigarettes, the largest proportion (34 percent) had smoked three to five cigarettes in the previous 24 hours, while another 29 percent had smoked 10 or more cigarettes in the previous 24 hours. 3.8.2 Alcohol Consumption Tables 3.9.1 and 3.9.2 show the percentage of respondents age 15-49 who ever drank alcohol and the percent distribution by the number of days they drank alcohol in the last 30 days, according to respondents’ background characteristics. Forty-five percent of women and 53 percent of men reported drinking alcohol at some point in their lives. For both women and men this proportion increases with age, and it is higher among urban residents than rural residents. Among regions the percentage of respondents who ever drank alcohol ranges from 2 percent of women and 5 percent of men in Somali to 86 percent of women and 91 percent of men in Tigray. Alcohol consumption is highest among both women and men with more than secondary education and in the highest wealth quintile, but there is no clear association between alcohol consumption and education and wealth in general. Table 3.9.1 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, according to background characteristics, Ethiopia 2011 Background characteristic Percentage of all women who ever drank alcohol Weighted number of women Unweighted number of women Among women who ever drank alcohol, number of days they drank alcohol in the last 30 days Weighted number of women who ever drank alcohol Unweighted number of women who ever drank alcohol None 1-5 6+ Total Age 15-19 40.4 4,009 3,835 10.5 50.0 39.4 100.0 1,619 1,333 20-24 44.2 2,931 3,022 9.3 48.2 42.5 100.0 1,296 1,153 25-29 44.5 3,147 3,185 8.3 42.5 49.0 100.0 1,400 1,184 30-34 44.9 2,054 2,100 8.7 37.0 54.0 100.0 922 796 35-39 49.0 1,916 1,958 10.4 35.6 53.9 100.0 940 807 40-44 45.1 1,261 1,314 10.2 37.1 52.4 100.0 569 525 45-49 52.9 1,196 1,101 10.9 34.0 55.1 100.0 633 536 Residence Urban 49.5 3,947 5,329 16.7 55.4 27.7 100.0 1,954 2,095 Rural 43.2 12,568 11,186 7.1 37.8 55.0 100.0 5,424 4,239 Region Tigray 86.3 1,104 1,728 2.1 54.4 43.3 100.0 952 1,511 Affar 4.0 145 1,291 (6.2) (67.2) (26.6) 100.0 6 37 Amhara 78.3 4,433 2,087 4.9 30.7 64.2 100.0 3,469 1,613 Oromiya 28.7 6,011 2,135 11.6 55.3 32.9 100.0 1,722 602 Somali 2.4 329 914 * * * 100.0 8 18 Benishangul-Gumuz 42.4 174 1,259 2.4 42.9 54.7 100.0 74 554 SNNP 19.7 3,236 2,034 20.5 46.0 33.5 100.0 637 399 Gambela 41.6 69 1,130 17.8 48.9 33.3 100.0 29 361 Harari 17.2 49 1,101 47.0 45.4 7.7 100.0 8 191 Addis Ababa 51.6 896 1,741 38.3 50.7 10.6 100.0 462 906 Dire Dawa 15.0 69 1,095 10.5 71.8 17.8 100.0 10 142 Education No education 47.3 8,394 8,278 6.8 33.2 59.8 100.0 3,972 3,056 Primary 39.9 6,276 5,858 10.8 49.9 39.2 100.0 2,504 2,224 Secondary 46.3 1,117 1,395 15.7 60.2 24.0 100.0 517 586 More than secondary 52.7 728 984 23.7 65.4 10.8 100.0 384 468 Wealth quintile Lowest 45.0 2,986 3,711 7.3 39.9 52.8 100.0 1,344 1,229 Second 46.4 3,041 2,402 5.4 37.9 56.6 100.0 1,412 1,055 Middle 44.8 3,031 2,268 5.3 33.6 60.8 100.0 1,358 936 Fourth 39.3 3,215 2,505 10.0 38.6 51.2 100.0 1,264 917 Highest 47.1 4,242 5,629 16.9 55.7 27.2 100.0 2,000 2,197 Total 44.7 16,515 16,515 9.6 42.4 47.8 100.0 7,378 6,334 Characteristics of Respondents • 53 Table 3.9.2 Alcohol consumption: Men Percentage of men age 15-49 who ever drank alcohol, and among men who ever drank alcohol, percent distribution by the number of days they drank alcohol in the last 30 days, according to background characteristics, Ethiopia 2011 Background characteristic Percentage of all men who ever drank alcohol Weighted number of men Unweighted number of men Among men who ever drank alcohol, number of days they drank alcohol in the last 30 days Weighted number of men who ever drank alcohol Unweighted number of men who ever drank alcohol None 1-5 6+ Total Age 15-19 48.2 3,013 2,832 7.9 50.0 42.1 100.0 1,452 1,240 20-24 51.8 2,319 2,330 10.1 44.8 44.8 100.0 1,200 1,161 25-29 53.6 2,297 2,274 10.1 33.3 56.4 100.0 1,231 1,202 30-34 53.5 1,483 1,682 10.1 32.6 57.1 100.0 794 841 35-39 54.0 1,648 1,579 13.5 30.0 56.4 100.0 890 825 40-44 58.6 1,121 1,210 11.0 25.9 62.8 100.0 657 643 45-49 62.9 952 961 8.8 28.0 62.4 100.0 599 546 Residence Urban 60.8 2,882 3,915 15.1 45.2 39.5 100.0 1,753 2,253 Rural 50.9 9,952 8,953 8.3 34.4 57.0 100.0 5,070 4,205 Region Tigray 91.3 770 1,235 3.6 36.6 59.7 100.0 703 1,139 Affar 9.8 101 910 8.6 41.4 50.0 100.0 10 66 Amhara 84.2 3,481 1,739 4.4 28.4 66.9 100.0 2,930 1,457 Oromiya 33.9 4,957 1,889 10.1 46.2 43.4 100.0 1,682 627 Somali 4.9 245 653 (19.1) (53.3) (27.6) 100.0 12 25 Benishangul-Gumuz 59.6 138 1,047 4.8 46.6 48.4 100.0 82 635 SNNP 35.8 2,307 1,550 25.8 38.4 35.5 100.0 825 560 Gambela 58.4 59 865 9.0 44.1 46.9 100.0 35 493 Harari 26.6 40 898 25.8 48.9 25.3 100.0 11 227 Addis Ababa 75.0 682 1,237 25.2 53.5 21.2 100.0 512 935 Dire Dawa 40.6 53 845 29.4 47.6 23.0 100.0 22 294 Education No education 60.8 3,785 3,659 5.5 26.5 67.6 100.0 2,302 1,773 Primary 47.8 6,813 6,334 11.1 38.7 50.1 100.0 3,253 3,012 Secondary 53.2 1,296 1,565 15.5 51.8 32.7 100.0 690 854 More than secondary 61.5 940 1,310 15.5 54.1 29.9 100.0 578 819 Wealth quintile Lowest 53.1 2,141 2,563 6.4 32.6 60.7 100.0 1,136 1,127 Second 55.0 2,362 1,891 6.3 36.8 56.8 100.0 1,299 1,009 Middle 52.1 2,454 1,935 8.2 33.1 58.3 100.0 1,279 954 Fourth 47.5 2,683 2,203 10.4 33.4 56.3 100.0 1,275 994 Highest 57.4 3,194 4,276 16.0 45.8 37.8 100.0 1,833 2,374 Total 15-49 53.2 12,834 12,868 10.0 37.2 52.5 100.0 6,823 6,458 50-59 68.8 1,276 1,242 9.3 30.2 60.3 100.0 878 765 Total 15-59 54.6 14,110 14,110 10.0 36.4 53.4 100.0 7,700 7,223 Note: Total includes 15 cases with information missing on the number of days they drank alcohol in the last 30 days. Figures in parentheses are based on 25-49 unweighted cases. Among respondents who ever drank alcohol, the majority drank on six or more days in the preceding 30 days (48 percent of women and 53 percent of men). 3.8.3 Chewing Chat Chat is a plant native to the Horn of Africa and the Arabian Peninsula. Chat chewing in communities in these areas is a social custom that dates back thousands of years. However, chat is a strong stimulant that causes mild to moderate psychological dependence, although not as strong as that of alcohol and tobacco, and its consumption can have serious health and economic consequences. 54 • Characteristics of Respondents Tables 3.10.1 and 3.10.2 show the percentages of women and men who have ever chewed chat and, among respondents who ever chewed chat, the percent distribution by the number of days that they chewed chat in the last 30 days, according to respondents’ background characteristics. Eleven percent of women and 28 percent of men reported that they had ever chewed chat. Among both women and men, this proportion increases with age. Among women, chat consumption is higher in rural areas than in urban areas (12 percent versus 7 percent), while among men there is no marked difference by place of residence. The percentage of respondents who ever chewed chat is lowest in Tigray (1 percent of women and 4 percent of men) and highest in Harari (39 percent of women and 82 percent of men). The percentage who ever chewed chat is highest among women with no education (14 percent) and among men with more than secondary education (32 percent). Women in the highest wealth quintile are the least likely to have ever chewed chat (8 percent). Conversely, men in the highest wealth quintile are the most likely to have chewed chat (31 percent). Among respondents who have ever chewed chat, most chewed chat on six or more days in the last 30 days (43 percent of women and 57 percent of men). Table 3.10.1 Chewing chat: Women Percentage of women age 15-49 who ever chewed chat, and among women who ever chewed chat, percent distribution by the number of days they chewed chat in the last 30 days, according to background characteristics, Ethiopia 2011 Background characteristic Percentage who ever chewed chat Weighted number of women Unweighted number of women Among women who ever chewed chat, number of days they chewed chat in the last 30 days Weighted number of women who ever chewed chat Unweighted number of women who ever chewed chatNone 1-5 6+ Missing Total Age 15-19 5.6 4,009 3,835 15.1 48.5 36.4 0.1 100.0 224 176 20-24 9.3 2,931 3,022 22.3 48.6 29.1 0.0 100.0 272 269 25-29 12.3 3,147 3,185 15.0 42.3 42.0 0.7 100.0 388 382 30-34 13.0 2,054 2,100 14.2 32.9 51.9 0.9 100.0 268 266 35-39 14.0 1,916 1,958 18.8 29.2 50.8 1.1 100.0 269 292 40-44 17.4 1,261 1,314 16.8 36.9 46.3 0.0 100.0 220 201 45-49 15.0 1,196 1,101 15.1 38.8 46.0 0.0 100.0 180 174 Residence Urban 6.8 3,947 5,329 36.8 32.0 31.2 0.0 100.0 269 699 Rural 12.3 12,568 11,186 13.3 41.0 45.1 0.5 100.0 1,551 1,061 Region Tigray 0.9 1,104 1,728 * * * 0.0 100.0 10 15 Affar 6.9 145 1,291 7.0 52.3 40.7 0.0 100.0 10 74 Amhara 7.6 4,433 2,087 26.7 55.3 18.0 0.0 100.0 336 176 Oromiya 20.0 6,011 2,135 11.0 35.5 52.8 0.7 100.0 1,200 429 Somali 7.3 329 914 13.6 40.6 45.8 0.0 100.0 24 63 Benishangul-Gumuz 3.3 174 1,259 (24.9) (65.1) (7.9) 2.1 100.0 6 45 SNNP 4.2 3,236 2,034 26.8 42.6 30.6 0.0 100.0 137 81 Gambela 14.2 69 1,130 43.3 40.6 16.2 0.0 100.0 10 55 Harari 39.2 49 1,101 12.0 25.3 62.3 0.5 100.0 19 433 Addis Ababa 5.7 896 1,741 55.5 31.0 13.5 0.0 100.0 51 96 Dire Dawa 27.1 69 1,095 3.8 33.5 62.7 0.0 100.0 19 293 Education No education 13.7 8,394 8,278 11.2 38.2 50.3 0.3 100.0 1,148 919 Primary 9.0 6,276 5,858 22.1 43.0 34.0 0.9 100.0 567 590 Secondary 4.9 1,117 1,395 54.8 40.0 5.3 0.0 100.0 55 150 More than secondary 6.9 728 984 41.9 37.1 21.0 0.0 100.0 50 101 Wealth quintile Lowest 10.3 2,986 3,711 12.9 36.8 50.3 0.0 100.0 308 187 Second 12.4 3,041 2,402 14.4 33.8 51.1 0.8 100.0 377 226 Middle 12.9 3,031 2,268 10.9 37.5 50.9 0.7 100.0 392 251 Fourth 12.2 3,215 2,505 15.5 55.4 28.4 0.7 100.0 394 302 Highest 8.2 4,242 5,629 30.8 33.3 35.8 0.0 100.0 350 794 Total 11.0 16,515 16,515 16.8 39.7 43.1 0.5 100.0 1,820 1,760 Note: Figures in parentheses are based on 25-49 unweighted cases. An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. Characteristics of Respondents • 55 Table 3.10.2 Chewing chat: Men Percentage of men age 15-49 who ever chewed chat, and among men who ever chewed chat, percent distribution by the number of days they chewed chat in the last 30 days, according to background characteristics, Ethiopia 2011 Background characteristic Percentage who ever chewed chat Weighted number of men Unweighted number of men Among men who ever chewed chat, number of days they chewed chat in the last 30 days Weighted number of men who ever chewed chat Unweighted number of men who ever chewed chat None 1-5 6+ Missing Total Age 15-19 14.9 3,013 2,832 12.9 28.6 58.6 0.0 100.0 448 506 20-24 28.6 2,319 2,330 15.4 30.7 53.8 0.0 100.0 662 803 25-29 32.2 2,297 2,274 18.0 24.2 57.8 0.0 100.0 740 931 30-34 34.5 1,483 1,682 17.7 26.9 55.3 0.1 100.0 511 728 35-39 30.4 1,648 1,579 18.4 25.3 56.3 0.0 100.0 501 620 40-44 34.5 1,121 1,210 18.3 23.4 57.6 0.6 100.0 387 511 45-49 31.0 952 961 21.7 19.7 58.4 0.2 100.0 295 361 Residence Urban 28.9 2,882 3,915 31.2 30.2 38.5 0.1 100.0 833 1,782 Rural 27.2 9,952 8,953 12.9 24.8 62.2 0.1 100.0 2,711 2,678 Region Tigray 3.7 770 1,235 (40.4) (41.9) (17.7) 0.0 100.0 29 46 Affar 33.8 101 910 3.9 32.3 63.9 0.0 100.0 34 310 Amhara 12.6 3,481 1,739 21.2 54.0 24.8 0.0 100.0 440 230 Oromiya 40.6 4,957 1,889 9.3 20.3 70.3 0.1 100.0 2,014 776 Somali 54.1 245 653 7.4 18.6 73.6 0.3 100.0 132 376 Benishangul-Gumuz 18.7 138 1,047 26.5 55.1 18.0 0.4 100.0 26 200 SNNP 20.2 2,307 1,550 28.9 22.2 48.9 0.0 100.0 466 311 Gambela 32.7 59 865 27.9 30.8 41.3 0.0 100.0 19 223 Harari 81.9 40 898 8.8 11.2 79.9 0.0 100.0 33 742 Addis Ababa 45.2 682 1,237 49.2 31.1 19.6 0.2 100.0 308 559 Dire Dawa 79.1 53 845 15.1 15.5 69.2 0.3 100.0 42 687 Education No education 27.2 3,785 3,659 10.3 21.9 67.8 0.0 100.0 1,028 1,192 Primary 27.4 6,813 6,334 16.7 26.9 56.2 0.1 100.0 1,870 2,054 Secondary 26.4 1,296 1,565 27.6 26.3 46.1 0.0 100.0 342 639 More than secondary 32.3 940 1,310 32.2 34.4 33.0 0.3 100.0 304 575 Wealth quintile Lowest 23.9 2,141 2,563 12.4 23.5 63.6 0.5 100.0 511 635 Second 26.2 2,362 1,891 14.0 24.3 61.7 0.0 100.0 618 512 Middle 27.1 2,454 1,935 13.1 24.6 62.3 0.0 100.0 666 567 Fourth 28.7 2,683 2,203 12.9 24.7 62.4 0.0 100.0 770 754 Highest 30.7 3,194 4,276 27.9 30.6 41.4 0.1 100.0 979 1,992 Total 15-49 27.6 12,834 12,868 17.2 26.1 56.6 0.1 100.0 3,544 4,460 50-59 27.3 1,276 1,242 25.0 25.0 49.9 0.1 100.0 348 424 Total 15-59 27.6 14,110 14,110 17.9 26.0 56.0 0.1 100.0 3,892 4,884 Note: Figures in parentheses are based on 25-49 unweighted cases. 3.8.4 Knowledge and Attitudes Concerning Tuberculosis The 2011 EDHS collected data on women’s and men’s knowledge and attitudes concerning tuberculosis (TB). Tables 3.11.1 and 3.11.2 show the percentage of women and men who have heard of TB, and, among those who have heard of TB, the percentage who know that TB is spread through the air by coughing, the percentage who believe that TB can be cured, and the percentage who would want a family member’s TB to be kept a secret. 56 • Characteristics of Respondents Table 3.11.1 Knowledge and attitude concerning tuberculosis: Women Percentage of women age 15-49 who have heard of tubercul

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