Ethiopia DHS Final Report (2011)

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 tuberculosis (TB), and, among women 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 to keep secret that a family member has TB, by background characteristics, Ethiopia 2011 Background characteristic Percentage of all women who have heard of TB Weighted number of women Unweighted number of women Among women who have heard of TB: Weighted number of women who ever heard of TB Unweighted number of women who ever heard of TB Percentage who report that TB is spread through the air by coughing Percentage who believe that TB can be cured Percentage who would want a family member's TB kept secret Age 15-19 88.4 4,009 3,835 55.3 74.7 29.7 3,544 3,444 20-24 89.9 2,931 3,022 57.2 82.6 26.6 2,635 2,768 25-29 90.0 3,147 3,185 53.9 80.2 24.5 2,833 2,901 30-34 89.3 2,054 2,100 57.1 82.1 24.2 1,835 1,885 35-39 91.5 1,916 1,958 56.9 81.6 23.2 1,754 1,811 40-44 91.1 1,261 1,314 55.9 78.1 24.2 1,149 1,215 45-49 91.6 1,196 1,101 51.8 80.6 22.6 1,096 1,021 Residence Urban 97.4 3,947 5,329 69.3 88.5 21.5 3,846 5,192 Rural 87.5 12,568 11,186 50.8 76.5 27.3 11,000 9,853 Region Tigray 97.7 1,104 1,728 51.5 93.5 13.6 1,078 1,687 Affar 94.4 145 1,291 58.7 91.5 28.1 137 1,206 Amhara 89.4 4,433 2,087 49.6 81.0 25.7 3,964 1,849 Oromiya 86.3 6,011 2,135 56.8 80.7 17.9 5,189 1,849 Somali 84.4 329 914 48.4 89.6 28.0 278 751 Benishangul-Gumuz 84.5 174 1,259 60.0 85.3 31.2 147 1,040 SNNP 92.5 3,236 2,034 58.9 65.6 45.6 2,993 1,873 Gambela 88.5 69 1,130 47.6 83.0 42.3 61 961 Harari 96.6 49 1,101 72.1 90.4 10.4 47 1,062 Addis Ababa 98.8 896 1,741 68.6 89.4 18.0 885 1,719 Dire Dawa 96.1 69 1,095 67.4 88.2 24.3 66 1,048 Education No education 85.8 8,394 8,278 47.5 76.3 24.8 7,202 7,203 Primary 92.6 6,276 5,858 58.7 78.9 29.6 5,814 5,480 Secondary 99.1 1,117 1,395 73.0 93.5 20.4 1,107 1,382 More than secondary 99.2 728 984 83.4 96.4 13.2 723 980 Wealth quintile Lowest 84.6 2,986 3,711 47.6 72.5 25.2 2,525 3,165 Second 87.5 3,041 2,402 50.7 76.5 26.1 2,660 2,116 Middle 86.2 3,031 2,268 51.2 76.1 29.3 2,612 1,992 Fourth 90.8 3,215 2,505 53.2 78.5 28.5 2,921 2,290 Highest 97.3 4,242 5,629 67.9 88.9 21.7 4,129 5,482 Total 89.9 16,515 16,515 55.6 79.6 25.8 14,846 15,045 Characteristics of Respondents • 57 Table 3.11.2 Knowledge and attitude concerning tuberculosis: Men Percentage of men age 15-49 who have heard of tuberculosis (TB), and among men 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 to keep secret that a family member has TB, by background characteristics, Ethiopia 2011 Background characteristic Percentage who have heard of TB Weighted number of men Unweighted number of men Among men who have heard of TB: Weighted number of men who ever heard of TB Unweighted number of men who ever heard of TB Percentage who report that TB is spread through the air by coughing Percentage who believe that TB can be cured Percentage who would want a family member's TB kept secret Age 15-19 89.3 3,013 2,832 59.8 82.8 23.7 2,692 2,571 20-24 95.4 2,319 2,330 63.9 89.3 20.3 2,212 2,251 25-29 95.6 2,297 2,274 68.6 91.1 16.6 2,196 2,186 30-34 97.9 1,483 1,682 67.8 92.2 18.0 1,452 1,644 35-39 96.1 1,648 1,579 67.9 91.5 13.1 1,585 1,529 40-44 97.6 1,121 1,210 65.6 93.6 15.5 1,095 1,180 45-49 98.0 952 961 68.2 89.2 14.7 934 943 Residence Urban 98.9 2,882 3,915 74.7 93.6 12.3 2,849 3,882 Rural 93.6 9,952 8,953 62.4 87.8 20.2 9,316 8,422 Region Tigray 97.6 770 1,235 56.7 94.7 13.0 752 1,204 Affar 97.5 101 910 72.8 93.7 20.6 99 884 Amhara 93.2 3,481 1,739 54.0 88.8 19.0 3,243 1,611 Oromiya 94.7 4,957 1,889 71.6 91.2 11.8 4,694 1,786 Somali 90.8 245 653 49.6 95.1 14.9 222 588 Benishangul-Gumuz 92.6 138 1,047 68.1 89.9 27.1 128 953 SNNP 95.3 2,307 1,550 67.5 81.3 36.6 2,198 1,472 Gambela 98.1 59 865 59.6 91.9 15.6 58 843 Harari 99.1 40 898 83.8 94.7 9.1 40 890 Addis Ababa 99.6 682 1,237 79.5 93.0 7.7 680 1,233 Dire Dawa 99.6 53 845 85.3 97.5 9.2 53 840 Education No education 90.8 3,785 3,659 54.0 87.6 17.8 3,436 3,365 Primary 95.5 6,813 6,334 66.4 87.5 20.5 6,504 6,076 Secondary 99.3 1,296 1,565 75.5 95.4 15.3 1,287 1,558 More than secondary 99.8 940 1,310 85.1 98.0 9.1 938 1,305 Wealth quintile Lowest 90.4 2,141 2,563 56.7 85.5 21.4 1,936 2,351 Second 93.4 2,362 1,891 61.9 87.8 21.4 2,205 1,771 Middle 93.8 2,454 1,935 60.8 86.9 19.6 2,303 1,821 Fourth 95.6 2,683 2,203 66.7 89.1 19.9 2,565 2,121 Highest 98.8 3,194 4,276 75.2 94.2 12.0 3,157 4,240 Total 15-49 94.8 12,834 12,868 65.3 89.2 18.3 12,166 12,304 50-59 97.8 1,276 1,242 62.1 90.8 13.2 1,247 1,214 Total 15-59 95.1 14,110 14,110 65.0 89.3 17.8 13,413 13,518 58 • Characteristics of Respondents Awareness of TB is almost universal in Ethiopia; 90 percent of women and 95 percent of men age 15-49 have heard about TB. Knowledge of other aspects of TB is also widespread. Fifty-six percent of women and 65 percent of men age 15-49 who have heard of TB know that it is spread through the air by coughing, and 80 percent of women and 89 percent of men know that TB can be cured. Finally, there appears to be little stigma attached to TB in Ethiopia. Only 26 percent of women and 18 percent of men say that if a family member had TB they would want to keep it a secret. Rural women and men are less likely than urban residents to know that TB is spread through the air by coughing and to believe that TB can be cured. Among women who have heard about TB, women in Gambela are the least likely to know that TB is spread through the air by coughing (48 percent), and women in the SNNP region are the least likely to know that TB can be cured (66 percent). Among men, those in the Somali region are the least likely to know that TB is spread through the air by coughing (50 percent), and men in the SNNP region are the least likely to know that TB can be cured (81 percent). Among both women and men who have heard about TB, the percentages who know that TB is spread through the air by coughing and that it can be cured increases steadily as levels of education and wealth increase. Rural women and men who have heard of TB are more likely than those in urban areas to want to keep secret a family member’s TB infection. Women in SNNP and Gambela and men in SNNP are most likely to report that they would want to keep a family member’s TB infection a secret. This proportion decreases with respondent’s education and also tends to decrease with wealth, especially among men. Marriage and Sexual Activity • 59 MARRIAGE AND SEXUAL ACTIVITY 4 his chapter addresses the principal factors, other than contraception, that affect a woman’s risk of becoming pregnant. These factors are marriage, polygyny, and sexual activity. 4.1 CURRENT MARITAL STATUS For most women marriage marks the onset of regular exposure to the risk of pregnancy. Therefore, information on age at marriage is important for understanding fertility. Populations in which age at first marriage is low tend to have early childbearing and high fertility. Table 4.1 presents the percent distribution of women by marital status, according to age group. The term ‘married’ refers to legal or formal marriage, while the term ‘living together’ designates an informal union in which a man and a woman live together but a formal civil or religious ceremony has not taken place. In later tables that do not list ‘living together’ as a separate category, these women are included in the ‘currently married’ group. Respondents who are currently married, widowed, divorced, or separated are referred to as ‘ever married’. Twenty-seven percent of women age 15-49 have never married, 58 percent are currently married, 4 percent are living together with a man, and 11 percent are divorced, separated, or widowed. The low proportion (less than 1 percent) of women age 45-49 who have never been married indicates that marriage is nearly universal in Ethiopia. T Key Findings • The median age at first marriage among women age 25-49 is 16.5 years in 2011. For men age 25-59, the median age at first marriage is 23.1 years. • There has been a small increase in the age at first marriage among women in the last six years. In contrast, men are marrying slightly earlier now than six years ago. • The percentage never-married has increased slightly in the last six years, from 25 to 27 percent among women age 15-49 and remained unchanged among men age 15-59. • The percentage of women who were first married by exact age 15 has declined from 39 percent among women currently age 45-49 to 8 percent among women age 15-19. A similar pattern is seen among men. • Ethiopian men marry about seven years later than women. • Ethiopian women generally begin sexual intercourse at the time of their first marriage. In contrast, men initiate sexual intercourse two years before their first marriage. 60 • Marriage and Sexual Activity Table 4.1 Current marital status Percent distribution of women and men age 15-49 by current marital status, according to age, Ethiopia 2011 Age Marital status Total Percentage of respondents currently in union Weighted number of respondents Unweighted number of respondents Never married Married Living together Divorced Separated Widowed WOMEN Age 15-19 77.0 17.6 1.5 3.2 0.7 0.1 100.0 19.1 4,009 3,835 20-24 31.9 55.0 5.1 5.4 2.4 0.2 100.0 60.1 2,931 3,022 25-29 9.7 74.5 5.3 6.3 2.3 2.0 100.0 79.8 3,147 3,185 30-34 4.1 78.7 5.0 5.1 3.4 3.7 100.0 83.7 2,054 2,100 35-39 1.8 77.6 5.4 7.1 2.9 5.1 100.0 83.0 1,916 1,958 40-44 1.4 76.2 5.8 6.1 1.6 8.9 100.0 81.9 1,261 1,314 45-49 0.6 72.3 3.4 6.7 2.1 15.0 100.0 75.7 1,196 1,101 Total 15-49 27.1 58.1 4.2 5.3 2.1 3.2 100.0 62.3 16,515 16,515 MEN Age 15-19 97.6 1.9 0.3 0.2 0.1 0.0 100.0 2.1 3,013 2,832 20-24 72.5 23.5 1.7 1.8 0.5 0.0 100.0 25.2 2,319 2,330 25-29 31.5 61.1 3.3 2.9 1.2 0.0 100.0 64.5 2,297 2,274 30-34 10.1 82.7 3.2 1.9 1.7 0.4 100.0 85.9 1,483 1,682 35-39 4.3 89.6 2.4 2.5 0.6 0.6 100.0 92.0 1,648 1,579 40-44 1.8 91.3 3.4 1.8 0.6 1.1 100.0 94.7 1,121 1,210 45-49 1.4 92.2 1.5 2.2 1.4 1.3 100.0 93.7 952 961 Total 15-49 43.6 51.5 2.0 1.8 0.8 0.3 100.0 53.5 12,834 12,868 50-59 0.4 92.5 2.9 2.6 0.2 1.3 100.0 95.4 1,276 1,242 Total 15-59 39.7 55.2 2.1 1.8 0.7 0.4 100.0 57.3 14,110 14,110 The proportion age 15-49 who have never been married is notably higher among men than among women (44 percent versus 27 percent). About half the men (52 percent) are currently married, 2 percent are living together with a woman, and 3 percent are either divorced, separated, or widowed. A significant proportion of men marry when they are age 25 or older, in contrast to women, who tend to marry before the age of 25. For example, 60 percent of women age 20-24 are in union, compared with only 25 percent of men in the same age group. Like women, however, virtually all men have married by the time they reach age 50. Over the past six years the proportion of Ethiopian women who have never married has increased slightly, from 25 percent in 2005 to 27 percent in 2011, and the proportion of women currently married or living together has decreased slightly, from 65 percent in 2005 to 62 percent in 2011. There has been little change in the marital status of men over the same period. 4.2 POLYGYNY Polygyny, the practice of having more than one wife, has implications for coital frequency and, therefore, fertility. The extent of polygyny is ascertained by asking currently married women whether their husband or partner has other wives and, if so, how many. Similarly, interviewers ask currently married men how many wives or partners they have. Tables 4.2.1 and 4.2.2 show the proportion of currently married women and men, respectively, who are in polygynous unions, by background characteristics. Eleven percent of married women in Ethiopia are in polygynous unions, with 9 percent having only one co-wife and 2 percent having two or more co-wives. The percentage of women in polygynous unions tends to increase with age, from 3 percent among women age 15-19 to 17 percent among women age 40-49. The extent of polygyny has declined only slightly over the past six years, from 12 percent in the 2005 EDHS to 11 percent in the 2011 EDHS. Marriage and Sexual Activity • 61 Rural women are more likely to be in polygynous unions (12 percent) than urban women (5 percent). The regional distribution also shows substantial variation. The prevalence of polygyny is lowest in Tigray (1 percent) and highest in Somali (27 percent). Polygyny also is relatively common in Affar (22 percent), Gambela (20 percent), and Benishangul-Gumuz and SNNP (both 18 percent). There is an inverse relationship between education and polygyny. The proportion of currently married women in a polygynous union decreases from 13 percent among women with no education to less than 1 percent among women with more than secondary education. There also are substantial differences in the prevalence of polygyny among women in different wealth quintiles. Women in the lowest wealth quintile are the most likely to be in a polygynous union (16 percent), compared with just 6 percent of women in the highest wealth quintile. Table 4.2.1 Number of women's co-wives Percent distribution of currently married women age 15-49 by number of co-wives, according to background characteristics, Ethiopia 2011 Background characteristic Number of co-wives Total Weighted number of women Unweighted number of women 0 1 2+ Don’t know Age 15-19 95.9 2.9 0.3 1.0 100.0 765 784 20-24 93.5 4.9 0.5 1.2 100.0 1,762 1,788 25-29 92.3 6.5 0.8 0.5 100.0 2,511 2,480 30-34 88.7 9.0 1.7 0.6 100.0 1,720 1,722 35-39 83.4 13.0 3.0 0.6 100.0 1,591 1,600 40-44 82.0 15.0 2.4 0.6 100.0 1,033 1,047 45-49 82.8 12.7 4.4 0.1 100.0 905 783 Residence Urban 92.9 4.5 0.8 1.9 100.0 1,843 2,422 Rural 88.1 9.7 1.9 0.4 100.0 8,444 7,782 Region Tigray 98.1 0.7 0.1 1.1 100.0 620 984 Affar 77.9 19.1 2.7 0.2 100.0 104 960 Amhara 96.5 2.1 0.4 0.9 100.0 2,776 1,331 Oromiya 86.6 11.0 1.8 0.6 100.0 3,961 1,403 Somali 72.6 21.9 5.1 0.4 100.0 232 664 Benishangul-Gumuz 81.2 14.6 3.7 0.6 100.0 124 904 SNNP 81.7 14.8 3.3 0.2 100.0 2,022 1,295 Gambela 78.8 13.7 5.8 1.7 100.0 41 768 Harari 94.1 4.8 0.7 0.4 100.0 28 635 Addis Ababa 96.5 1.7 0.2 1.7 100.0 342 634 Dire Dawa 95.9 3.3 0.3 0.5 100.0 38 626 Education No education 86.8 10.7 2.0 0.5 100.0 6,735 6,569 Primary 91.8 6.0 1.3 0.8 100.0 2,862 2,739 Secondary 95.2 2.5 0.2 2.1 100.0 378 528 More than secondary 99.1 0.1 0.1 0.7 100.0 313 368 Wealth quintile Lowest 84.4 13.5 2.1 0.1 100.0 2,077 2,724 Second 89.5 8.7 1.2 0.6 100.0 2,117 1,676 Middle 89.9 7.2 2.6 0.4 100.0 2,083 1,585 Fourth 88.1 9.7 1.7 0.5 100.0 1,923 1,590 Highest 92.6 4.9 0.8 1.7 100.0 2,087 2,629 Total 88.9 8.8 1.7 0.7 100.0 10,287 10,204 62 • Marriage and Sexual Activity Data on polygynous unions among currently married men are shown in Table 4.2.2. Five percent of men age 15-49 report having two or more wives. Like women, older men, men living in rural areas, those with little or no education, and men in the lowest wealth quintile are more likely to be in polygynous unions than other men. Men in the Somali and Benishangul-Gumuz regions are the most likely to be in polygynous unions (both 14 percent), compared with less than 1 percent of men in Addis Ababa, Tigray, and Amhara regions. The level of polygyny reported by men age 15-59 has declined only slightly over the past six years, from 7 percent in the 2005 EDHS to 6 percent in the 2011 EDHS. Table 4.2.2 Number of men's wives Percent distribution of currently married men age 15-49 by number of wives, according to background characteristics, Ethiopia 2011 Background characteristic Number of wives Total Weighted number of men Unweighted number of men 1 2+ Missing Age 15-19 100.0 0.0 0.0 100.0 64 66 20-24 99.5 0.1 0.4 100.0 583 575 25-29 98.5 1.3 0.2 100.0 1,481 1,378 30-34 95.6 3.8 0.5 100.0 1,274 1,385 35-39 93.1 6.5 0.4 100.0 1,516 1,377 40-44 91.3 8.3 0.4 100.0 1,061 1,108 45-49 89.8 10.2 0.0 100.0 892 886 Residence Urban 97.8 1.8 0.3 100.0 1,235 1,580 Rural 93.9 5.8 0.3 100.0 5,637 5,195 Region Tigray 99.6 0.4 0.0 100.0 377 613 Affar 90.0 9.7 0.3 100.0 52 492 Amhara 99.3 0.3 0.4 100.0 1,867 936 Oromiya 93.0 6.6 0.3 100.0 2,738 1,040 Somali 85.6 13.8 0.6 100.0 145 391 Benishangul-Gumuz 86.6 13.3 0.2 100.0 81 614 SNNP 90.3 9.4 0.3 100.0 1,279 870 Gambela 92.6 7.4 0.0 100.0 29 488 Harari 97.6 2.2 0.2 100.0 20 460 Addis Ababa 99.8 0.0 0.2 100.0 259 442 Dire Dawa 97.5 1.5 0.9 100.0 25 429 Education No education 94.8 4.8 0.4 100.0 2,906 2,757 Primary 93.8 5.9 0.3 100.0 3,213 2,997 Secondary 96.9 3.1 0.0 100.0 385 525 More than secondary 97.6 1.5 0.9 100.0 368 496 Wealth quintile Lowest 91.2 8.7 0.0 100.0 1,344 1,631 Second 95.4 4.5 0.1 100.0 1,404 1,138 Middle 94.0 5.5 0.5 100.0 1,393 1,104 Fourth 94.5 5.2 0.3 100.0 1,339 1,152 Highest 97.8 1.6 0.6 100.0 1,391 1,750 Total 15-49 94.6 5.1 0.3 100.0 6,872 6,775 50-59 92.0 7.8 0.3 100.0 1,217 1,155 Total 15-59 94.2 5.5 0.3 100.0 8,089 7,930 4.3 AGE AT FIRST MARRIAGE In Ethiopia marriage marks the point in a woman’s life when childbearing becomes socially acceptable. Age at first marriage has a major effect on childbearing because women who marry early have on average a longer period of exposure to the risk of pregnancy and give birth to a greater number of children over their lifetimes. Interviewers obtained information on age at first marriage by asking respondents the month and year or the age at which they started living with their first partner. Table 4.3 shows the percentage of women and men who have married by specific exact ages, according to current age. For women, marriage takes place relatively early in Ethiopia. Among Marriage and Sexual Activity • 63 women age 25-49, 63 percent married by age 18, and 77 percent married by age 20. The median age at first marriage among women age 25-49 is 16.5 years, a slight increase from the 16.1 years reported in the 2005 EDHS. The proportion of women married by age 15 has declined over time, from 39 percent among women currently age 45-49 to 8 percent among women currently age 15-19. Men tend to marry at much older ages than women. Among men age 25-59, only 13 percent were married by age 18, and 27 percent, by age 20. The median age at marriage for men age 25-49 is 23.2 years, almost seven years older than for women in the same age range, at 16.5 years. The median age at marriage for men age 25-59 has decreased somewhat, from 23.8 years in 2005 to 23.1 years in 2011. Table 4.3 Age at first marriage Percentage of women and men age 15-49 who were first married by specific exact ages and median age at first marriage, according to current age, Ethiopia 2011 Current age Percentage first married by exact age: Percentage never married Weighted number of respondents Unweighted number of respondents Median age at first marriage 15 18 20 22 25 WOMEN Age 15-19 8.0 na na na na 77.0 4,009 3,835 a 20-24 16.3 41.0 58.3 na na 31.9 2,931 3,022 18.9 25-29 22.7 56.2 71.6 81.8 88.7 9.7 3,147 3,185 17.4 30-34 28.6 62.0 75.8 83.5 90.5 4.1 2,054 2,100 16.6 35-39 31.1 63.9 77.4 86.2 92.4 1.8 1,916 1,958 16.4 40-44 37.1 69.0 82.4 89.2 93.8 1.4 1,261 1,314 15.8 45-49 39.4 73.0 84.5 92.6 96.3 0.6 1,196 1,101 15.6 20-49 26.5 57.7 72.4 na na 11.1 12,506 12,680 17.1 25-49 29.6 62.8 76.7 85.4 91.4 4.7 9,575 9,658 16.5 MEN Age 15-19 0.4 na na na na 97.6 3,013 2,832 a 20-24 0.7 7.3 13.9 na na 72.5 2,319 2,330 a 25-29 2.9 12.0 22.6 37.4 58.4 31.5 2,297 2,274 23.9 30-34 4.3 13.8 26.5 42.0 63.7 10.1 1,483 1,682 23.0 35-39 3.0 14.4 31.4 45.3 64.6 4.3 1,648 1,579 22.6 40-44 3.7 14.6 27.3 43.7 63.7 1.8 1,121 1,210 22.8 45-49 3.1 13.7 29.5 44.2 64.6 1.4 952 961 22.9 20-49 2.7 12.0 23.8 na na 27.1 9,821 10,036 a 25-49 3.3 13.5 26.9 41.8 62.4 13.0 7,502 7,706 23.2 20-59 2.6 11.9 23.9 na na 24.0 11,097 11,278 a 25-59 3.1 13.1 26.5 42.2 62.8 11.2 8,778 8,948 23.1 Note: The age at first marriage is defined as the age at which the respondent began living with her/his first spouse/partner. na = Not applicable due to censoring a = Omitted because less than 50 percent of the respondents began living with their spouse or partner for the first time before reaching the beginning of the age group Table 4.4 shows the median age at first marriage for women age 20-49 and age 25-49, and for men age 25-59, by background characteristics. Data for women age 15-19 and for men age 15-24 have been omitted because of the small number of married respondents interviewed in these age groups. Women age 25-49 living in urban areas marry about two years later than rural women (18.1 years compared with 16.3 years). Median age at first marriage is highest in Addis Ababa (21.4 years) and lowest in Amhara (14.7 years). The median age at first marriage for women age 25-49 is higher among the better educated and the wealthier. Variations by background characteristics among men age 25-59 display a pattern like that among women but are not as pronounced. 64 • Marriage and Sexual Activity Table 4.4 Median age at first marriage by background characteristics Median age at first marriage among women age 20-49 and age 25-49, and median age at first marriage among men age 25-59, according to background characteristics, Ethiopia 2011 Background characteristic Women age Men age1 20-49 25-49 25-59 Residence Urban 19.3 18.1 a Rural 16.6 16.3 22.6 Region Tigray 17.1 16.6 24.4 Affar 16.8 16.5 24.6 Amhara 15.1 14.7 20.9 Oromiya 17.4 16.9 23.5 Somali 17.6 17.6 24.2 Benishangul-Gumuz 15.9 15.7 21.9 SNNP 18.3 17.9 23.7 Gambela 17.4 17.1 23.9 Harari 18.1 17.7 25.0 Addis Ababa a 21.4 a Dire Dawa 19.4 18.9 a Education No education 16.0 15.9 21.9 Primary 18.1 17.5 23.1 Secondary a 22.8 a More than secondary a 23.8 a Wealth quintile Lowest 16.4 16.3 22.7 Second 16.3 16.0 22.3 Middle 16.7 16.3 22.4 Fourth 16.9 16.4 23.2 Highest 19.1 17.9 a Total 17.1 16.5 23.1 Note: The age at first marriage is defined as the age at which the respondent began living with her/his first spouse/partner. a = Omitted because less than 50 percent of the respondents began living with their spouses/partners for the first time before reaching the beginning of the age group 1 Median age at first marriage for men age 20-59 is not shown because less than 50 percent of men in most sub-groups began living with their spouses/partners for the first time before reaching the beginning of the age group. 4.4 AGE AT FIRST SEXUAL INTERCOURSE Although age at first marriage is often used as a proxy for first exposure to sexual intercourse, the two events do not necessarily coincide. In the 2011 EDHS interviewers asked women and men how old they were when they first had sexual intercourse. Table 4.5 shows the percentage of women and men who first had sexual intercourse by specific exact ages. Among women age 25-49, 29 percent first had sexual intercourse before age 15, 62 percent before age 18, and by age 25 the majority of Ethiopian women (88 percent) had had sexual intercourse. The median age at first sexual intercourse for women age 25-49 years is 16.6 years, which is very close to the median age at first marriage of 16.5 years. This suggests that Ethiopian women generally begin sexual intercourse at the time of their first marriage. The median age at first sexual intercourse has increased over the past two decades, from 15.6 years for women currently age 45-49 to 18.8 years for women currently age 20-24. Marriage and Sexual Activity • 65 As is the case with age at first marriage, men tend to initiate sexual activity later in life than women. The median age at first sex for men age 25-49 is 21.2 years, about six years later than for women. The median ages at first intercourse among the different age cohorts suggest no significant change in age at first sexual intercourse for men over the past 20 years. The median age at first sexual intercourse for men age 25-49 years, at 21.2 years, is about two years lower than the median age at first marriage, at 23.2 years. Table 4.5 Age at first sexual intercourse Percentage of women and men age 15-49 who had first sexual intercourse by specific exact ages, percentage who never had sexual intercourse, and median age at first sexual intercourse, according to current age, Ethiopia 2011 Current age Percentage who had first sexual intercourse by exact age: Percentage who never had sexual intercourse Weighted number of respondents Unweighted number of respondents Median age at first sexual intercourse 15 18 20 22 25 WOMEN Age 15-19 na na na na 75.8 4,009 3,835 a 20-24 16.0 42.2 60.8 na na 27.4 2,931 3,022 18.8 25-29 21.8 55.5 70.7 80.7 86.8 7.2 3,147 3,185 17.4 30-34 27.5 60.5 73.8 81.1 86.6 3.3 2,054 2,100 16.7 35-39 31.4 62.9 75.5 84.1 89.2 1.0 1,916 1,958 16.4 40-44 35.7 67.5 79.8 85.6 89.7 0.9 1,261 1,314 15.9 45-49 38.9 71.8 82.2 89.0 91.9 0.2 1,196 1,101 15.6 20-49 25.9 57.1 71.6 na na 9.0 12,506 12,680 17.1 25-49 28.9 61.7 75.0 83.2 88.2 3.4 9,575 9,658 16.6 15-24 10.9 na na na na 55.4 6,940 6,857 a MEN Age 15-19 1.2 na na na na 92.2 3,013 2,832 a 20-24 1.3 14.0 27.5 na na 55.6 2,319 2,330 a 25-29 3.5 16.9 32.4 51.6 70.5 18.9 2,297 2,274 21.8 30-34 3.8 18.5 36.4 55.6 75.3 4.3 1,483 1,682 21.0 35-39 3.1 18.8 39.2 55.9 72.2 1.5 1,648 1,579 20.9 40-44 2.4 18.7 38.8 57.8 72.4 0.6 1,121 1,210 21.0 45-49 2.9 18.2 39.5 56.9 73.5 0.2 952 961 20.9 20-49 2.8 17.1 34.4 na na 18.5 9,821 10,036 a 25-49 3.3 18.1 36.5 54.9 72.5 7.1 7,502 7,706 21.2 15-24 1.2 na na na na 76.3 5,332 5,162 a 20-59 2.7 17.3 35.0 na na 16.4 11,097 11,278 a 25-59 3.1 18.2 36.9 55.6 72.6 6.1 8,778 8,948 21.1 na = Not applicable due to censoring a = Omitted because less than 50 percent of the respondents had sexual intercourse for the first time before reaching the beginning of the age group Differentials in age at first sex are shown in Table 4.6. Urban women have their first sexual experience at somewhat older ages than rural women. For example, the median age at first intercourse among urban women age 25-49 was 17.8 years, compared with 16.4 years among rural women. Among the regions median age at first intercourse for women age 25-49 is highest in Addis Ababa (19.5 years) and lowest in Amhara (15.1 years). Women’s median age at first sexual intercourse rises with levels of education and wealth. Women with more than secondary education initiate sex almost six years later than women with no education (21.8 years versus 16.0 years). Similarly, the median age at first sex is more than one year later among women in the highest wealth quintile than among women in the lowest. In contrast, among men there are no substantial variations in the median age at first sexual intercourse by various background characteristics. 66 • Marriage and Sexual Activity Table 4.6 Median age at first sexual intercourse by background characteristics Median age at first sexual intercourse among women age 20-49 and age25-49, and median age at first sexual intercourse among men age 20-59 and age 25- 59 according to background characteristics, Ethiopia 2011 Background characteristic Women age Men age1 20-49 25-49 25-59 Residence Urban 18.7 17.8 20.9 Rural 16.7 16.4 21.2 Region Tigray 16.1 15.7 22.0 Affar 17.1 16.9 20.5 Amhara 15.3 15.1 20.4 Oromiya 17.5 17.0 21.8 Somali 18.0 17.9 23.0 Benishangul-Gumuz 16.3 16.0 20.5 SNNP 18.3 17.9 21.6 Gambela 16.8 16.9 19.6 Harari 18.2 17.9 21.9 Addis Ababa a 19.5 20.8 Dire Dawa 19.5 19.3 20.9 Education No education 16.1 16.0 21.0 Primary 18.0 17.4 21.1 Secondary a 20.6 21.9 More than secondary a 21.8 21.3 Wealth quintile Lowest 16.5 16.4 21.6 Second 16.4 16.1 21.3 Middle 16.9 16.4 20.9 Fourth 17.1 16.6 21.3 Highest 18.6 17.6 20.9 Total 17.1 16.6 21.1 a = Omitted because less than 50 percent of the respondents had sexual intercourse for the first time before reaching the beginning of the age group 1 Median age at first sexual intercourse for men age 20-59 is not shown because less than 50 percent of men in most sub-groups had sexual intercourse for the first time before reaching the beginning of the age group. 4.5 RECENT SEXUAL ACTIVITY In the absence of contraception, the probability of pregnancy is entirely related to coital frequency. Therefore, information on sexual activity can be used to refine measures of exposure to pregnancy. Interviewers asked women and men how long ago their last sexual activity occurred, recording whether they had had a sexual encounter in the preceding four weeks. Tables 4.7.1 and 4.7.2 show the percent distributions of women and men by recent sexual activity. Fifty-one percent of all women age 15-49 were sexually active in the four weeks before the survey, 14 percent had been sexually active in the year before the survey but not in the four weeks prior to the interview, and 10 percent had been sexually active at some time in their lives but not for the past one or more years. One in every four women had never had sexual intercourse. The proportion of women who were sexually active during the four weeks before the survey at first increases with age, from 16 percent among those age 15-19 to 70 percent among those age 30-34, and then it decreases to 55 percent among those age 45-49. As expected, women who are currently in union are much more likely to have been sexually active in the four weeks preceding the survey (80 percent) than women who were formerly married (6 percent) or who have never been married (2 percent). Women married for 25 years or more are less likely to have been sexually active in the recent past than women married for shorter durations. Marriage and Sexual Activity • 67 Rural women were more likely to be recently sexually active (55 percent) than urban women (38 percent). Women residing in Benishangul-Gumuz (56 percent), Oromiya (55 percent), and SNNP (53 percent) were more likely than women in other regions to have been sexually active in the past four weeks, while women in Addis Ababa (32 percent) were least likely. Women with no education (65 percent) were substantially more sexually active in the recent past than women with some education (28 to 39 percent). Among wealth quintiles the richest women were the least likely to report being sexually active in the past four weeks (41 percent). Table 4.7.1 Recent sexual activity: Women Percent distribution of women age 15-49 by timing of last sexual intercourse, according to background characteristics, Ethiopia 2011 Background characteristic Timing of last sexual intercourse Never had sexual intercourse Total Weighted number of women Unweighted number of women Within the past 4 weeks Within 1 year1 One or more years2 Missing Age 15-19 15.8 5.8 2.6 0.0 75.8 100.0 4,009 3,835 20-24 51.1 14.2 7.0 0.2 27.4 100.0 2,931 3,022 25-29 67.1 16.8 8.8 0.0 7.2 100.0 3,147 3,185 30-34 70.1 16.3 10.1 0.2 3.3 100.0 2,054 2,100 35-39 65.8 17.5 15.7 0.2 1.0 100.0 1,916 1,958 40-44 64.4 16.1 18.4 0.2 0.9 100.0 1,261 1,314 45-49 55.4 14.4 30.1 0.0 0.2 100.0 1,196 1,101 Marital status Never married 2.1 2.4 3.3 0.0 92.1 100.0 4,469 4,413 Married or living together 79.9 16.7 3.1 0.1 0.2 100.0 10,287 10,204 Divorced/separated/widowed 5.9 22.7 69.3 0.1 2.0 100.0 1,758 1,898 Marital duration3 0-4 years 80.7 17.0 1.4 0.2 0.8 100.0 1,792 1,931 5-9 years 81.4 16.1 1.8 0.4 0.3 100.0 1,689 1,790 10-14 years 80.1 17.5 2.4 0.0 0.0 100.0 1,594 1,605 15-19 years 81.1 16.6 2.1 0.3 0.0 100.0 1,088 1,135 20-24 years 79.8 16.4 3.8 0.0 0.0 100.0 853 869 25+ years 73.4 18.5 8.1 0.0 0.0 100.0 963 865 Married more than once 80.3 15.6 4.0 0.1 0.0 100.0 2,308 2,009 Residence Urban 38.4 12.9 13.8 0.1 34.8 100.0 3,947 5,329 Rural 54.9 13.6 9.1 0.1 22.2 100.0 12,568 11,186 Region Tigray 44.6 16.8 14.0 0.1 24.5 100.0 1,104 1,728 Affar 45.7 22.6 15.4 0.0 16.2 100.0 145 1,291 Amhara 50.2 15.4 12.1 0.2 22.1 100.0 4,433 2,087 Oromiya 54.8 12.1 8.3 0.0 24.7 100.0 6,011 2,135 Somali 44.9 24.0 11.1 0.5 19.5 100.0 329 914 Benishangul-Gumuz 56.1 15.3 10.6 0.2 17.8 100.0 174 1,259 SNNP 53.2 10.6 7.5 0.1 28.6 100.0 3,236 2,034 Gambela 49.3 17.6 21.0 0.1 12.0 100.0 69 1,130 Harari 43.5 16.5 13.5 0.2 26.3 100.0 49 1,101 Addis Ababa 32.0 12.7 16.2 0.1 39.0 100.0 896 1,741 Dire Dawa 41.6 16.6 13.5 0.0 28.4 100.0 69 1,095 Education No education 64.5 16.7 12.5 0.2 6.2 100.0 8,394 8,278 Primary 38.7 9.7 7.1 0.1 44.4 100.0 6,276 5,858 Secondary 27.9 8.9 10.4 0.0 52.7 100.0 1,117 1,395 More than secondary 36.2 15.9 10.7 0.0 37.3 100.0 728 984 Wealth quintile Lowest 53.3 17.1 11.4 0.1 18.1 100.0 2,986 3,711 Second 57.1 13.6 9.0 0.1 20.2 100.0 3,041 2,402 Middle 56.7 13.1 8.5 0.2 21.5 100.0 3,031 2,268 Fourth 50.5 11.1 8.7 0.1 29.5 100.0 3,215 2,505 Highest 41.2 12.8 12.6 0.1 33.3 100.0 4,242 5,629 Total 51.0 13.5 10.2 0.1 25.2 100.0 16,515 16,515 1 Excludes women who had sexual intercourse within the past 4 weeks 2 Excludes women who had sexual intercourse within the past 4 weeks or within 1 year 3 Excludes women who are not currently married Among men age 15-49, 47 percent were sexually active in the four weeks preceding the survey, 12 percent had had sexual intercourse in the year before the survey but not in the four weeks prior to the survey, and 5 percent had not been sexually active for one year or more. Thirty-six percent of men said that they had never had sex. As with women, men’s recent sexual activity at first increases with age, peaks in the late thirties at 81 percent, and then declines. Men currently in union 68 • Marriage and Sexual Activity are much more likely to have been recently sexually active (84 percent) than those not in union (3 percent among those never married and 9 percent among those divorced, separated, or widowed). Like women, men in rural areas are more likely to have been sexually active in the recent past than those in urban areas (49 percent versus 39 percent). Regional variation shows patterns similar to those for women. The rate of recent sexual activity is highest among men living in SNNP (51 percent) and Benishangul-Gumuz (50 percent) and lowest in Addis Ababa (32 percent). Men’s recent sexual activity, like women’s, is inversely related to their level of education. It decreases from 65 percent among men with no education to 42 percent among men with some primary education and to 28 percent among those with some secondary education. Recent sexual activity is least common among the wealthiest men (39 percent). Table 4.7.2 Recent sexual activity: Men Percent distribution of men age 15-49 by timing of last sexual intercourse, according to background characteristics, Ethiopia 2011 Background characteristic Timing of last sexual intercourse Never had sexual intercourse Total Weighted number of men Unweighted number of men Within the past 4weeks Within 1year1 One or more years2 Missing Age 15-19 2.5 2.8 2.5 0.1 92.2 100.0 3,013 2,832 20-24 23.9 12.6 7.8 0.1 55.6 100.0 2,319 2,330 25-29 59.1 14.2 7.5 0.3 18.9 100.0 2,297 2,274 30-34 73.2 16.4 5.7 0.3 4.3 100.0 1,483 1,682 35-39 81.0 12.8 4.5 0.1 1.5 100.0 1,648 1,579 40-44 77.0 19.0 3.5 0.0 0.6 100.0 1,121 1,210 45-49 77.1 17.4 4.4 0.9 0.2 100.0 952 961 Marital status Never married 3.4 7.4 7.8 0.1 81.3 100.0 5,600 5,641 Married or living together 84.2 14.3 0.8 0.3 0.4 100.0 6,872 6,775 Divorced/separated/widowed 9.1 39.0 47.3 1.0 3.6 100.0 363 452 Marital duration3 0-4 years 83.0 14.8 0.4 0.3 1.5 100.0 1,334 1,357 5-9 years 83.4 14.5 1.4 0.3 0.3 100.0 1,282 1,245 10-14 years 84.5 13.6 1.2 0.2 0.5 100.0 978 966 15-19 years 81.9 16.8 0.9 0.4 0.0 100.0 733 683 20-24 years 80.6 19.0 0.5 0.0 0.0 100.0 405 388 25+ years 85.8 12.2 1.3 0.8 0.0 100.0 228 205 Married more than once 86.8 12.4 0.5 0.3 0.1 100.0 1,912 1,931 Residence Urban 38.7 15.4 10.3 0.2 35.4 100.0 2,882 3,915 Rural 49.1 11.0 3.7 0.2 36.0 100.0 9,952 8,953 Region Tigray 41.5 16.6 5.4 0.1 36.4 100.0 770 1,235 Affar 45.5 20.1 6.6 0.3 27.5 100.0 101 910 Amhara 45.2 11.6 4.3 0.2 38.6 100.0 3,481 1,739 Oromiya 49.3 10.7 4.3 0.1 35.5 100.0 4,957 1,889 Somali 44.0 16.9 6.4 1.0 31.7 100.0 245 653 Benishangul-Gumuz 50.4 12.4 4.7 0.1 32.4 100.0 138 1,047 SNNP 50.5 8.9 4.9 0.3 35.3 100.0 2,307 1,550 Gambela 40.9 22.2 13.1 0.0 23.8 100.0 59 865 Harari 41.8 17.2 11.2 0.2 29.5 100.0 40 898 Addis Ababa 31.6 23.6 14.6 0.0 30.3 100.0 682 1,237 Dire Dawa 40.6 18.3 12.5 0.0 28.6 100.0 53 845 Education No education 65.1 13.0 3.9 0.4 17.6 100.0 3,785 3,659 Primary 41.6 9.9 4.1 0.1 44.4 100.0 6,813 6,334 Secondary 27.7 12.9 8.8 0.0 50.5 100.0 1,296 1,565 More than secondary 37.2 21.9 13.9 0.3 26.7 100.0 940 1,310 Wealth quintile Lowest 54.1 11.4 2.7 0.4 31.5 100.0 2,141 2,563 Second 50.8 11.1 2.7 0.3 35.1 100.0 2,362 1,891 Middle 49.3 10.7 3.7 0.1 36.2 100.0 2,454 1,935 Fourth 44.5 9.6 5.3 0.1 40.5 100.0 2,683 2,203 Highest 38.8 16.0 9.9 0.2 35.1 100.0 3,194 4,276 Total 15-49 46.8 12.0 5.2 0.2 35.8 100.0 12,834 12,868 50-59 73.9 17.9 7.9 0.0 0.2 100.0 1,276 1,242 Total 15-59 49.2 12.5 5.4 0.2 32.6 100.0 14,110 14,110 1 Excludes men who had sexual intercourse within the last 4 weeks 2 Excludes women who had sexual intercourse within the past 4 weeks or within 1 year 3 Excludes men who are not currently married Fertility Levels, Trends, and Differentials • 69 FERTILITY LEVELS, TRENDS, AND DIFFERENTIALS 5 ertility is one of the three principal components of population dynamics that determine the size and structure of the population of a country. Chapter 5 looks at a number of fertility indicators, including levels, patterns, and trends in both current and cumulative fertility; the length of birth intervals; the age at which women initiate childbearing; and postpartum insusceptibility. Information on current and cumulative fertility is essential for monitoring population growth. Birth intervals are important because short intervals are strongly associated with childhood mortality. The age at which childbearing begins can also have a major impact on the health and well-being of both the mother and the child. Data on fertility were collected in several ways. First, each woman was asked the number of sons and daughters who live with her, the number who live elsewhere, and the number born alive and later died. Next, a complete history of all the woman’s births was obtained, including the name, sex, month and year of birth, age, and survival status for each of the births. For living children, a question was asked about whether the child was living in the household or away. For dead children, the age at death was recorded. Finally, information was collected on whether a woman was pregnant at the time of the survey. 5.1 CURRENT FERTILITY The level of current fertility is one of the most important topics in this report because of its direct relevance to population policies and programmes. Current fertility can be measured using the age-specific fertility rate (ASFR), the total fertility rate (TFR), the general fertility rate (GFR), and the crude birth rate (CBR). The ASFR provides the age pattern of fertility, while the TFR refers to the number of live births that a woman would have had if she were subject to the current ASFRs throughout her reproductive years (15-49 years). The GFR is expressed as the number of live births per 1,000 women of reproductive age, and the CBR is expressed as the number of live births per 1,000 persons in the population. The measures of fertility presented in this chapter refer to the three-year period preceding the survey. This time period generates a sufficient number of births to provide reliable, current estimates. F Key Findings • The total fertility rate for the three years preceding the survey is 4.8 children per women. Rural women are having about twice as many children as urban women. • Fertility declined only slightly between 2000 and 2005, from 5.5 children per woman to 5.4, and then decreased further to 4.8 children in 2011. • Childbearing begins early in Ethiopia. More than one-third (34 percent) of women age 20-49 gave birth by age 18, and more than half (54 percent), by age 20. • More than half (56 percent) of births occur within three years of a previous birth; 20 percent occur within 24 months. • Twelve percent of adolescent women, age 15-19, are already mothers or pregnant with their first child. 70 • Fertility Levels, Trends, and Differentials As Table 5.1 shows, the TFR for Ethiopia for the three-year period preceding the survey is 4.8 children per woman. This means that an Ethiopian woman who is at the beginning of her childbearing years would give birth to just under five children by the end of her reproductive period if fertility levels remained constant over the childbearing years. The TFR in rural areas exceeds the TFR in urban areas by almost three children per woman (5.5 and 2.6 children per woman, respectively). Table 5.1 Current fertility Age-specific and total fertility rates, the general fertility rate, and the crude birth rate for the three years preceding the survey, by residence, Ethiopia 2011 Age group Residence Total Urban Rural 15-19 27 99 79 20-24 123 236 207 25-29 158 262 237 30-34 101 218 192 35-39 75 171 150 40-44 21 77 68 45-49 22 29 28 TFR (15-49) 2.6 5.5 4.8 GFR 89 184 161 CBR 26.4 36.2 34.5 Notes: Age-specific fertility rates are per 1,000 women. Rates for age group 45-49 may be slightly biased due to truncation. Rates are for the period 1-36 months prior to interview. TFR: Total fertility rate, expressed per woman GFR: General fertility rate, expressed per 1,000 women age 15-44 CBR: Crude birth rate, expressed per 1,000 population The crude birth rate in Ethiopia is 34.5 births per 1,000 population. As is the case with other fertility measures, there is a substantial differential in the CBR by urban-rural residence. The CBR is 37 percent higher in rural areas (36 per 1,000 population) than in urban areas (26 per 1,000 population). The GFR in Ethiopia is 161 live births per 1,000 women of reproductive age. The rate is considerably higher in rural areas (184) than in urban areas (89). Figure 5.1 presents the age-specific fertility rates for urban and rural areas. The fertility among adolescents age 15-19 in Ethiopia is 79 births per 1,000 women. Fertility peaks at age 25-29 in both rural and urban areas. For the country as a whole, the age-specific fertility rates rise from 79 births per 1,000 women age 15-19 to 207 births among women age 20-24, reach a peak of 237 births for women age 25-29, and then fall steadily to 28 births among women age 45-49. Fertility Levels, Trends, and Differentials • 71 Figure 5.1 Age-Specific Fertility Rates by Urban-Rural Residence EDHS 2011 & & & & & & & , , , , , , , ) ) ) ) ) ) ) 15-19 20-24 25-29 30-34 35-39 40-44 45-49 Age group 0 50 100 150 200 250 300 Births per 1,000 women Urban Rural Total) , & 5.2 FERTILITY DIFFERENTIALS BY BACKGROUND CHARACTERISTICS Table 5.2 presents differentials in the total fertility rates, the percentage of women who are currently pregnant, and the mean number of children ever born (CEB) to women age 40-49, by residence, region, education, and wealth quintiles. There are substantial differentials in the TFR among the regions, ranging from 1.5 children per woman in Addis Ababa (below the replacement level of fertility) to 7.1 children per woman in Somali. Fertility levels are higher than the national average in Somali, Oromiya, Benishangul-Gumuz, Affar, and SNNP and lower than the national average in the other six regions. The level of fertility is inversely related to women’s educational attainment, decreasing sharply from 5.8 children among women with no education to 1.3 children among women who have more than secondary education. Fertility is also strongly associated with wealth Table 5.2 Fertility by background characteristics Total fertility rate for the three years preceding the survey, percentage of women age 15-49 currently pregnant, and mean number of children ever born to women age 40-49, by background characteristics, Ethiopia 2011 Background characteristic Total fertility rate Percentage of women age 15-49 currently pregnant Mean number of children ever born to women age 40-49 Residence Urban 2.6 3.8 5.0 Rural 5.5 8.4 7.3 Region Tigray 4.6 7.2 6.4 Affar 5.0 9.9 7.3 Amhara 4.2 4.7 6.9 Oromiya 5.6 8.3 7.1 Somali 7.1 12.4 7.9 Benishangul-Gumuz 5.2 10.2 6.6 SNNP 4.9 9.3 7.3 Gambela 4.0 5.7 5.6 Harari 3.8 6.7 5.5 Addis Ababa 1.5 3.6 3.3 Dire Dawa 3.4 7.2 4.8 Education No education 5.8 8.8 7.2 Primary 4.6 6.5 6.3 Secondary 1.9 3.0 2.4 More than secondary 1.3 3.4 2.8 Wealth quintile Lowest 6.0 9.8 7.2 Second 5.7 8.5 7.2 Middle 5.3 7.5 7.3 Fourth 5.0 7.3 7.3 Highest 2.8 4.5 5.3 Total 4.8 7.3 6.9 Note: Total fertility rates are for the period 1-36 months preceding the interview. 72 • Fertility Levels, Trends, and Differentials quintiles. Women in the lowest wealth quintile have a TFR of 6.0, more than twice as high as women in the highest wealth quintile, at 2.8. Table 5.2 also presents a crude assessment of trends in the various subgroups by comparing current fertility with a measure of completed fertility—the mean number of children ever born to women age 40-49. The mean number of children ever born to older women, who are nearing the end of their reproductive period, is an indicator of average completed fertility of women who began childbearing over the three decades preceding the survey. If fertility remained constant over time and the reported data on both children ever born and births during the three years preceding the survey are reasonably accurate, the TFR and the mean number of children ever born for women age 40-49 would be expected to be similar. When fertility levels have been falling, the TFR will be substantially lower than the mean number of children ever born to women age 40-49. The comparison of current fertility at the country level with completed fertility suggests that fertility has fallen by over two children per woman during the past few decades, from 6.9 children to 4.8. The table also reveals that substantial declines in fertility have taken place in both rural areas (from 7.3 to 5.5) and urban areas (from 5.0 to 2.6). The differences between the levels of current and completed fertility are highest in Amhara (2.7 children), in urban areas (2.4 children), and among women in the highest wealth quintile (2.5 children). The percentage of women currently pregnant is a useful measure of current fertility, although not all women who are pregnant are likely to be included because they may not be aware that they are pregnant or may be reluctant to disclose a pregnancy in the early stages. Seven percent of women reported that they were pregnant at the time of the survey. Rural women were much more likely to be pregnant (8 percent) than urban women (4 percent). The highest proportion of women who were pregnant is in Somali (12 percent), while the lowest proportion was in Addis Ababa (4 percent). The percentage of women currently pregnant decreases with increasing level of education, from 9 percent among women with no education to 3 percent among those with secondary or higher education. Similarly, there are more currently pregnant women in the two lowest wealth quintiles (9-10 percent) than in the highest wealth quintile (5 percent). 5.3 FERTILITY TRENDS Table 5.3.1 uses information from the retrospective birth histories obtained from the 2011 EDHS respondents to examine trends in age-specific fertility rates for successive five-year periods before the survey. To calculate these rates, births were classified according to the period of time in which the birth occurred and the mother’s age at the time of birth. Because birth histories have not been collected for women age 50 and over, the rates for older age groups become progressively more truncated for periods more distant from the survey date. For example, rates cannot be calculated for women age 45-49 for the periods 5-9 years or more prior to the survey because women in those age groups would have been 50 years or older at the time of the survey. Table 5.3.1 Trends in age-specific fertility rates Age-specific fertility rates for five-year periods preceding the survey, by mother's age at the time of the birth, Ethiopia 2011 Mother's age at birth Number of years preceding survey 0-4 5-9 10-14 15-19 15-19 87 143 169 174 20-24 227 266 296 278 25-29 248 293 298 304 30-34 206 257 288 [302] 35-39 157 205 [271] 40-44 72 [145] 45-49 [31] Note: Age-specific fertility rates are per 1,000 women. Estimates in brackets are truncated. Rates exclude the month of interview. Fertility Levels, Trends, and Differentials • 73 Table 5.3.1 shows that there was no consistent change in fertility from 15-19 years preceding the survey to 10-14 years preceding the survey. However, there has been a fertility decline in every age group in the subsequent two periods. The decline has been particularly rapid between the periods 5-9 years and 0-4 years preceding the survey. Another way to examine fertility trends is to compare current estimates with estimates from earlier surveys. Estimates of the TFR and ASFR are available from the two previous EDHS surveys (2000 and 2005). These estimates (shown in Table 5.3.2) offer an opportunity to assess fertility trends over the last decade. These data show that the TFR decreased only slightly from 5.5 children in 2000 to 5.4 children in 2005, and then decreased further to 4.8 children in 2011. Although the level of fertility decreased over time, the age pattern of fertility was similar in all four surveys, with fertility increasing from age 15-19 to age 25-29 and decreasing thereafter. 5.4 CHILDREN EVER BORN AND LIVING Table 5.4 presents the distribution of all women and currently married women by the number of children ever born, according to five-year age groups. The table also shows the mean number of children ever born and the mean number of living children. Data on the number of children ever born reflect the accumulation of births to women over their entire reproductive lifespan and therefore have limited reference to current fertility levels, particularly when a country has experienced a decline in fertility. However, the information on children ever born is useful for observing how average family size varies across age groups and also for observing the level of primary infertility. The results show that 90 percent of women age 15-19 have never given birth. This proportion declines rapidly to 14 percent for women age 25-29 and to 7 percent or lower for women age 30 and older. On average, Ethiopian women attain a parity of 7.3 children per woman by the end of their childbearing years. This number is higher than the TFR of 4.8 per woman, a difference that is attributable to the decrease in fertility. Women age 40 or older have much higher parities, with substantial proportions having 10 or more births each by the end of their childbearing years. For example, 54 percent of women age 45-49 have given birth to eight or more children. A similar pattern is observed for currently married women, except that the mean number of children ever born is higher for currently married women (4.1 children) than for all women (2.9 children). As expected, the mean number of children ever born and mean number of children surviving rise monotonically with increasing age of women. A comparison of the mean number of living children with the mean number of children ever born shows that, by the end of their childbearing years, women have lost an average of 1.7 children. Table 5.3.2 Trends in age-specific and total fertility rates Trends in age-specific and total fertility rates, Ethiopia 2011 Age group EDHS 20001 EDHS 20052 EDHS 2011 15-19 100 104 79 20-24 235 228 207 25-29 251 241 237 30-34 243 231 192 35-39 168 160 150 40-44 89 84 68 45-49 19 34 28 TFR 5.5 5.4 4.8 Note: Age-specific fertility rates are per 1,000 women; rate for 2000 EDHS is for the three years preceding the survey. 1 CSA and ORC Macro, 2001 2 CSA and ORC Macro, 2006 74 • Fertility Levels, Trends, and Differentials Table 5.4 Children ever born and living Percent distribution of all women and currently married women age 15-49 by number of children ever born, mean number of children ever born and mean number of living children, according to age group, Ethiopia 2011 Age Number of children ever born Total Weighted number of women Unweighted number of women Mean number of children ever born Mean number of living children 0 1 2 3 4 5 6 7 8 9 10+ ALL WOMEN 15-19 89.9 7.9 1.9 0.3 0.1 0.0 0.0 0.0 0.0 0.0 0.0 100.0 4,009 3,835 0.13 0.11 20-24 43.2 25.4 20.4 7.6 2.6 0.5 0.1 0.2 0.0 0.0 0.0 100.0 2,931 3,022 1.04 0.95 25-29 13.6 14.7 20.5 21.3 16.1 8.6 3.5 1.1 0.4 0.1 0.0 100.0 3,147 3,185 2.60 2.34 30-34 6.7 6.9 10.4 12.4 18.5 18.0 13.5 8.4 3.5 1.3 0.4 100.0 2,054 2,100 4.12 3.56 35-39 4.1 3.9 6.2 8.4 11.3 12.6 17.4 15.7 10.1 6.0 4.3 100.0 1,916 1,958 5.43 4.54 40-44 2.8 3.3 5.1 5.7 8.0 9.3 11.1 15.8 13.5 8.7 16.4 100.0 1,261 1,314 6.50 5.26 45-49 1.9 2.5 4.1 3.4 5.3 6.8 10.5 12.0 13.9 16.2 23.4 100.0 1,196 1,101 7.34 5.65 Total 33.7 11.0 10.7 8.7 8.2 6.6 6.0 5.2 3.7 2.7 3.5 100.0 16,515 16,515 2.88 2.42 CURRENTLY MARRIED WOMEN 15-19 53.1 36.3 9.5 0.7 0.4 0.0 0.0 0.0 0.0 0.0 0.0 100.0 765 784 0.59 0.53 20-24 15.2 35.0 31.8 12.3 4.3 0.8 0.2 0.3 0.0 0.0 0.0 100.0 1,762 1,788 1.60 1.46 25-29 4.7 12.6 22.0 24.4 19.1 10.8 4.3 1.4 0.5 0.1 0.0 100.0 2,511 2,480 3.01 2.71 30-34 2.9 4.9 9.4 11.8 20.3 20.0 15.0 9.8 3.9 1.5 0.4 100.0 1,720 1,722 4.49 3.88 35-39 2.7 2.4 5.2 7.7 10.3 13.3 18.3 17.1 11.5 6.5 5.0 100.0 1,591 1,600 5.75 4.83 40-44 1.7 2.6 3.8 5.2 7.3 8.3 10.3 16.7 14.9 9.8 19.3 100.0 1,033 1,047 6.91 5.62 45-49 1.5 1.4 2.9 2.2 4.2 5.2 9.1 11.7 15.6 18.8 27.4 100.0 905 783 7.84 6.07 Total 8.9 13.4 14.5 12.0 11.5 9.5 8.3 7.4 5.4 3.9 5.2 100.0 10,287 10,204 4.08 3.44 5.5 BIRTH INTERVALS A birth interval is defined as the length of time between two successive live births. The study of birth intervals is important in understanding the health status of young children. Research has shown that short birth intervals are closely associated with poor health of children, especially during infancy. Children born too soon after a previous birth, especially if the interval between the births is less than two years, are at increased risk for health problems and death at a young age. Longer birth intervals improve the health status of both mother and child. Table 5.5 presents the distribution of second and higher-order births in the five years preceding the survey by the number of months since the previous birth, according to background characteristics. The table also presents the median number of months since the preceding birth. The median birth interval is 34 months, implying that half of non-first births to women in Ethiopia occur less than three years after a previous birth. Twenty percent have an interval of less than two years, and 9 percent of births are less than 18 months apart. Thirty-six percent of births occur 24-35 months after the previous birth and 44 percent are at least three years apart. Fertility Levels, Trends, and Differentials • 75 Table 5.5 Birth intervals Percent distribution of non-first births in the five years preceding the survey by number of months since preceding birth, and median number of months since preceding birth, according to background characteristics, Ethiopia 2011 Background characteristic Months since preceding birth Total Weighted number of non-first births Unweighted number of non-first births Median number of months since preceding birth 7-17 18-23 24-35 36-47 48-59 60+ Age 15-19 7.0 13.4 51.1 26.9 1.1 0.5 100.0 98 109 28.5 20-29 10.2 14.0 38.0 21.3 8.7 7.7 100.0 4,401 4,229 32.0 30-39 7.5 10.6 34.4 23.9 10.7 13.0 100.0 4,052 4,001 35.1 40-49 5.4 8.4 27.9 26.7 12.6 18.9 100.0 1,048 992 38.7 Sex of preceding birth Male 8.7 11.9 35.4 23.9 9.7 10.5 100.0 4,920 4,757 33.8 Female 8.3 12.0 35.7 22.2 10.1 11.7 100.0 4,679 4,574 33.9 Survival of preceding birth Living 6.8 11.5 36.7 23.8 10.2 11.1 100.0 8,649 8,361 34.3 Dead 24.5 16.0 25.2 16.2 7.1 11.0 100.0 950 970 28.1 Birth order 2-3 9.5 12.5 34.3 21.6 9.6 12.4 100.0 3,682 3,697 33.8 4-6 7.5 11.3 36.3 23.7 10.0 11.2 100.0 3,791 3,663 34.0 7+ 8.6 12.0 36.2 24.3 10.2 8.7 100.0 2,125 1,971 33.7 Residence Urban 7.0 9.8 24.1 16.2 12.1 30.7 100.0 1,058 1,332 41.5 Rural 8.7 12.2 36.9 23.9 9.6 8.7 100.0 8,541 7,999 33.4 Region Tigray 3.7 8.4 37.6 26.4 10.5 13.4 100.0 599 962 36.1 Affar 14.5 16.0 31.9 17.7 9.5 10.5 100.0 98 915 30.2 Amhara 4.4 8.5 28.6 24.6 14.7 19.2 100.0 2,110 1,038 39.1 Oromiya 10.5 13.7 39.4 21.9 6.7 7.8 100.0 4,093 1,439 31.5 Somali 20.5 19.6 32.1 18.6 5.4 3.7 100.0 319 899 26.7 Benishangul-Gumuz 10.6 14.8 33.3 19.2 11.2 11.0 100.0 112 825 33.0 SNNP 8.2 11.9 36.5 24.2 11.5 7.8 100.0 2,070 1,352 34.0 Gambela 6.0 9.7 28.3 24.4 13.5 18.2 100.0 29 665 39.2 Harari 12.1 16.4 34.9 16.6 7.2 12.8 100.0 22 495 30.9 Addis Ababa 5.8 3.4 16.1 15.3 14.3 45.1 100.0 117 208 53.0 Dire Dawa 7.5 17.8 31.9 19.2 9.1 14.5 100.0 29 533 33.3 Education No education 8.7 12.6 36.5 23.1 9.6 9.4 100.0 7,100 7,041 33.3 Primary 8.2 9.9 33.8 23.4 10.7 13.9 100.0 2,310 2,024 35.3 Secondary 3.6 5.2 20.9 11.9 11.6 46.8 100.0 117 187 53.8 More than secondary 5.3 19.1 12.3 17.9 10.0 35.4 100.0 72 79 44.3 Wealth quintile Lowest 8.6 13.3 35.8 25.4 9.0 7.9 100.0 2,263 3,051 33.4 Second 7.9 12.5 38.5 24.1 9.6 7.5 100.0 2,179 1,750 33.2 Middle 8.8 11.4 34.0 25.1 11.3 9.3 100.0 2,028 1,553 34.5 Fourth 9.3 10.8 40.0 20.4 8.8 10.7 100.0 1,860 1,506 33.0 Highest 7.7 11.1 25.7 17.5 11.4 26.6 100.0 1,269 1,471 38.9 Total 8.5 11.9 35.5 23.0 9.9 11.1 100.0 9,599 9,331 33.9 Note: First-order births are excluded. The interval for multiple births is the number of months since the preceding pregnancy that ended in a live birth. The median birth interval increases with age, ranging from 28.5 months for births to women age 15-19 to 38.7 months for births to women age 40-49. The longer birth interval among older women may be attributed in part to a decrease in fecundity as women grow older. There are no substantial differences in the median birth interval by the child’s sex or birth order. However, the median birth interval is 6 months shorter if the previous child died than if the previous child is still alive. The median interval for births to urban women is 8 months longer than for rural women (41.5 and 33.4 months, respectively). The median birth interval ranges from 26.7 months in Somali to 53.0 months in Addis Ababa. The median number of months since the preceding birth among non- first births is longest for births to women who have gone to secondary school but do not have more than a secondary education (53.8 months). The shortest median birth interval is for births to women with no education (33.3 months). There is no substantial difference in the median birth interval by wealth quintiles, although births to women in the highest wealth quintile have the longest median birth interval (38.9 months). 76 • Fertility Levels, Trends, and Differentials 5.6 POSTPARTUM AMENORRHOEA, ABSTINENCE, AND INSUSCEPTIBILITY Postpartum amenorrhoea refers to the interval between childbirth and the return of menstruation. The length and intensity of breastfeeding influence the duration of amenorrhoea, which offers protection from conception. Postpartum abstinence refers to the period between childbirth and the time when a woman resumes sexual activity. Delaying the resumption of sexual relations can also prolong protection from conception. Women are considered to be insusceptible to pregnancy if they are not exposed to the risk of conception, either because their menstrual period has not resumed since giving birth or because they are abstaining from intercourse after childbirth. As Table 5.6 shows, the median duration of amenorrhoea among women who gave birth in the three years preceding the survey is 15.6 months. The median duration of postpartum abstinence is much shorter, at just over 2 months. Taken together, these two factors show that the median duration of postpartum insusceptibility to pregnancy is 16.6 months. During the first two months after childbirth, almost all women (99.6 percent) are insusceptible to pregnancy. Amenor- rhoea and abstinence both play important roles in insusceptibility. During the second and third months after giving birth, 88 percent of women are still insusceptible to pregnancy, but the percentage of women receiving protection from postpartum abstinence drops to 40 percent, whereas 85 percent are amenorrhoeic. By 12-13 months after childbirth, 61 percent of women are insusceptible to pregnancy and 60 percent remain amenorrhoeic, but only 4 percent are abstaining from sexual relations. A comparison of data from the 2000 and 2005 EDHS surveys indicates that there was no change in the median duration of postpartum abstinence, but the median duration of amenorrhoea and insusceptibility decreased by three months from 2000 to 2005. Between the 2005 EDHS and the 2011 EDHS, there was almost no change in the median durations of postpartum amenorrhoea, abstinence and insusceptibility. Table 5.6 Postpartum amenorrhoea, abstinence, and insusceptibility Percentage of births in the three years preceding the survey for which mothers are postpartum amenorrhoeic, abstaining, and insusceptible, by number of months since birth, and median and mean durations, Ethiopia 2011 Months since birth Percentage of births for which the mother is: Weighted number of births Unweighted number of births Amenorrhoeic Abstaining Insusceptible1 < 2 98.8 88.1 99.6 387 351 2-3 84.7 39.7 87.9 514 483 4-5 80.0 16.1 81.5 432 421 6-7 76.4 11.4 78.5 430 422 8-9 70.4 10.5 72.1 389 372 10-11 67.2 10.4 69.2 357 310 12-13 60.4 3.7 61.4 416 383 14-15 53.7 10.4 57.7 317 350 16-17 45.9 9.8 49.9 358 407 18-19 42.6 4.1 45.4 356 333 20-21 24.6 3.1 25.8 321 290 22-23 30.3 3.4 31.3 286 264 24-25 17.6 2.8 19.7 393 424 26-27 12.3 4.7 15.1 337 397 28-29 14.9 3.1 16.8 314 386 30-31 13.0 2.4 13.8 372 344 32-33 9.0 3.3 12.3 346 326 34-35 4.7 2.4 6.5 419 341 Total 46.9 13.7 49.0 6,743 6,604 Median 15.6 2.3 16.6 na na Mean 16.4 4.9 17.1 na na Note: Estimates are based on status at the time of the survey. na = Not applicable 1 Includes births for which mothers are either still amenorrhoeic or still abstaining (or both) following birth Fertility Levels, Trends, and Differentials • 77 Table 5.7 shows that the median duration of postpartum amenorrhoea is longer among women age 30-49 (16.8 months) than among women age 15-29 (14.1 months). The duration of post- partum insusceptibility is also longer among older women (17.3 months) than younger women (15.2 months). However, the median length of postpartum abstinence is about the same for younger and older women. Rural women have a much longer period of postpartum amenorrhoea than urban women (16.6 and 10.9 months, respectively) and a longer median period of postpartum insusceptibility than urban women (17.1 and 11.8 months, respectively). However, the median length of postpartum abstinence is almost the same. There are considerable regional variations in postpartum amenorrhoea and insusceptibility. The median duration of postpartum amenorrhoea ranges from 8.2 months in Somali to 19.0 months in Tigray, and the median duration of postpartum abstinence ranges from 2.0 months in Somali to 12.7 months in Gambela. The median duration of insusceptibility ranges from 8.6 months in Somali to 23.0 months in Gambela. The median durations of amenorrhoea, abstinence and insusceptibility decline as household wealth increases. This pattern is similar for women with little or no education but less obvious among women with secondary and higher education because of the small numbers of women in these two categories. 5.7 MENOPAUSE Another factor influencing the risk of pregnancy is menopause. In the context of available survey data, women are considered menopausal if they are neither pregnant nor postpartum amenorrhoeic and they have not had a menstrual period in the six months preceding the survey (Table 5.8). As expected, the proportion of women who are menopausal increases with age, ranging from 9 percent of women age 30-34 to 62 percent of women age 48-49. Less than 10 percent of both women age 30-34 and women age 35-39 and only 18-21 percent of women age 40-43 are menopausal. Table 5.7 Median duration of amenorrhoea, postpartum abstinence, and postpartum insusceptibility Median number of months of postpartum amenorrhoea, postpartum abstinence, and postpartum insusceptibility following births in the three years preceding the survey, by background characteristics, Ethiopia 2011 Background characteristic Postpartum amenorrhoea Postpartum abstinence Postpartum insusceptibility1 Mother's age 15-29 14.1 2.4 15.2 30-49 16.8 2.3 17.3 Residence Urban 10.9 2.5 11.8 Rural 16.6 2.3 17.1 Region Tigray 19.0 2.2 19.8 Affar 11.3 2.7 13.6 Amhara 18.4 2.7 19.0 Oromiya 14.4 2.2 14.9 Somali 8.2 2.0 8.6 Benishangul-Gumuz 12.5 2.3 13.7 SNNP 15.9 2.2 16.9 Gambela 16.1 12.7 23.0 Harari 8.4 2.7 8.9 Addis Ababa (3.7) (3.0) (5.1) Dire Dawa 12.9 3.5 13.3 Education No education 17.2 2.5 17.6 Primary 12.0 2.0 12.8 Secondary 3.8 2.9 5.3 More than secondary * * 8.3 Wealth quintile Lowest 18.1 2.8 18.9 Second 16.6 2.3 16.8 Middle 17.2 2.4 17.6 Fourth 12.5 2.2 14.7 Highest 10.2 2.2 10.4 Total 15.6 2.3 16.6 Note: Medians are based on the status at the time of the survey (current status). Figures in parentheses are based on 25-49 unweighted cases. An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. 1 Includes births for which mothers are either still amenorrhoeic or still abstaining (or both) following birth. 78 • Fertility Levels, Trends, and Differentials Table 5.8 Menopause Percentage of women age 30-49 who are menopausal, by age, Ethiopia 2011 Age Percentage menopausal1 Weighted number of women Unweighted number of women Age 30-34 8.6 2,054 2,100 35-39 9.4 1,916 1,958 40-41 17.6 692 776 42-43 20.8 412 394 44-45 38.7 586 579 46-47 41.7 360 319 48-49 62.0 408 347 Total 18.6 6,428 6,473 1 Percentage of all women who are not pregnant and not postpartum amenorrhoeic whose last menstrual period occurred six or more months preceding the survey A large increase is observed among women at age 44-45, 39 percent of whom are menopausal. By age 48-49, 62 percent of women are menopausal. Overall, 19 percent of women age 30-49 in Ethiopia are menopausal, an increase of three percentage points since the 2005 EDHS. 5.8 AGE AT FIRST BIRTH The age at which childbearing commences is an important determinant of the overall level of fertility as well as of the health and welfare of the mother and the child. In some societies, postponement of first births due to an increase in age at marriage has contributed to overall fertility decline. Table 5.9 shows the percentage of women in Ethiopia who have given birth by specific ages, according to age at the time of the survey. Overall, 9 percent of women age 25-49 have given birth by exact age 15, and 38 percent have given birth by exact age 18. More than half (58 percent) of women have become mothers by exact age 20. Whereas only 1 percent of women currently age 15-19 gave birth by exact age 15, the corresponding proportion for women currently age 45-49 is 12 percent. The percentage of women who gave birth by exact age 18 is almost half as high for women age 20-24 as for women age 40-49. Table 5.9 Age at first birth Percentage of women age 15-49 who gave birth by specific exact ages, percentage who have never given birth, and median age at first birth, according to current age, Ethiopia 2011 Current age Percentage who gave birth by exact age Percentage who have never given birth Weighted number of women Unweighted number of women Median age at first birth15 18 20 22 25 Age 15-19 1.0 na na na na 89.9 4,009 3,835 a 20-24 3.0 22.2 40.3 na na 43.2 2,931 3,022 a 25-29 6.1 32.8 54.5 69.3 82.6 13.6 3,147 3,185 19.6 30-34 9.5 40.0 58.7 73.3 85.4 6.7 2,054 2,100 19.0 35-39 10.2 38.2 57.4 72.4 86.0 4.1 1,916 1,958 19.2 40-44 12.6 43.0 60.4 77.4 87.2 2.8 1,261 1,314 18.7 45-49 12.3 42.9 62.6 77.4 88.0 1.9 1,196 1,101 18.8 20-49 7.8 34.3 53.7 na na 15.7 12,506 12,680 19.6 25-49 9.3 38.0 57.8 72.9 85.1 7.3 9,575 9,658 19.2 na = Not applicable due to censoring a = Omitted because less than 50 percent of women had a birth before reaching the beginning of the age group Fertility Levels, Trends, and Differentials • 79 Table 5.10 presents the median age at first birth across age cohorts for key subgroups of women. The summary measures are presented for women age 25-49 to ensure that half of the women in every group have already had a birth. The summary measure is also presented for women age 20-49 for groups of women in which at least half of women have had a birth by age 20. In Ethiopia the median age at first birth for women age 25-49 is 19.2 years. The median age at first birth for women age 25-49 in urban areas (20.5) is 1.5 months longer than the median age at first birth in rural areas (19.0 months). The median age at first birth ranges from 18.1 years in Amhara to 23.0 years in the Addis Ababa. Table 5.10 Median age at first birth Median age at first birth among women age 20-49 and 25-49 years, according to background characteristics, Ethiopia 2011 Background characteristic Women age 20-49 25-49 Residence Urban a 20.5 Rural 19.2 19.0 Region Tigray 19.3 19.0 Affar 19.2 19.0 Amhara 18.7 18.1 Oromiya 19.5 19.2 Somali a 20.2 Benishangul-Gumuz 18.7 18.5 SNNP a 19.9 Gambela 19.7 19.4 Harari a 20.3 Addis Ababa a 23.0 Dire Dawa a 21.6 Education No education 18.9 18.8 Primary a 19.6 Secondary or higher a 24.1 Wealth quintile Lowest 19.2 19.2 Second 19.1 18.9 Middle 19.3 19.0 Fourth 19.3 18.8 Highest a 20.2 Total 19.6 19.2 a = Omitted because less than 50 percent of the women had a birth before reaching the beginning of the age group The level of education for women age 25-49 is positively related to the median age at first birth, ranging from a median age of 18.8 years for women with no education to 24.1 years for women with secondary or higher education. Similarly, women in the highest wealth quintile delay the onset of their childbearing by about one year relative to women in the lowest wealth quintile. 5.9 TEENAGE PREGNANCY AND MOTHERHOOD Teenage pregnancy is a major health concern because of its association with higher morbidity and mortality for both mother and child. Childbearing during the teenage years frequently has adverse social consequences as well, particularly on educational attainment, because women who become mothers in their teens are more likely to curtail their education. 80 • Fertility Levels, Trends, and Differentials Table 5.11 Teenage pregnancy and motherhood Percentage of women age 15-19 who have had a live birth or who are pregnant with their first child, and percentage who have begun childbearing, by background characteristics, Ethiopia 2011 Background characteristic Percentage of women age 15-19 who: Percentage who have begun childbearing Weighted number of women Unweighted number of women Have had a live birth Are pregnant with first child Age 15 0.4 0.5 1.0 1,006 902 16 3.8 1.1 4.9 821 773 17 7.1 2.1 9.2 627 666 18 15.6 4.3 19.9 977 925 19 29.7 3.9 33.6 578 569 Residence Urban 3.6 0.6 4.1 1,042 1,297 Rural 12.4 2.9 15.3 2,968 2,538 Region Tigray 11.0 1.0 12.0 294 458 Affar 11.5 3.6 15.1 30 268 Amhara 10.2 1.4 11.6 1,123 528 Oromiya 12.7 3.1 15.8 1,489 531 Somali 14.8 4.4 19.2 70 193 Benishangul-Gumuz 16.9 2.4 19.3 39 286 SNNP 5.7 2.5 8.2 710 440 Gambela 17.0 3.5 20.5 18 245 Harari 12.7 1.8 14.5 11 243 Addis Ababa 1.1 1.5 2.6 210 406 Dire Dawa 6.9 0.8 7.6 15 237 Education No education 28.7 4.1 32.8 695 783 Primary 6.7 2.1 8.8 2,813 2,497 Secondary 3.9 1.3 5.2 406 429 More than secondary 0.0 0.0 0.0 95 126 Wealth quintile Lowest 16.2 4.4 20.6 686 777 Second 12.2 1.8 14.0 696 540 Middle 14.4 2.7 17.2 687 523 Fourth 6.6 2.6 9.2 889 640 Highest 4.8 0.7 5.5 1,051 1,355 Total 10.1 2.3 12.4 4,009 3,835 Table 5.11 shows that 12 percent of women age 15-19 have already started childbearing; 10 percent have had a live birth, and 2 percent are pregnant with their first child. While only 1 percent of women age 15 have started childbearing, 34 percent of women are either mothers or are pregnant with their first child by age 19. Teenagers in rural areas are much more likely to have started childbearing than their urban counterparts (15 and 4 percent, respectively), due mainly to the high prevalence of early marriage in rural Ethiopia. Among regions the percentage of women age 15-19 who have begun childbearing ranges from 3 percent in Addis Ababa to 21 percent in Gambela. There is a strong inverse relationship between early childbearing and women’s education; teenagers with less education are much more likely to have started childbearing than those who are better educated. Thirty-three percent of teenagers with no education have begun childbearing, but no teenagers with more than a secondary education in the 2011 EDHS sample have begun childbearing. Teenagers in the lowest wealth quintile are almost four times as likely to start childbearing early as women in the highest wealth quintile (21 percent and 6 percent, respectively). Fertility Preferences • 81 FERTILITY PREFERENCES 6 nformation on fertility preferences provides family planning programmes with an understanding of the potential demand for family planning in a given population. The 2011 EDHS asked women and men a series of questions to ascertain their fertility preferences, including the desire to have another child, the length of time they would like to wait before having another child, and what they would consider to be the ideal number of children. Interpretation of responses to these questions is subject to some degree of error because in most cases respondents’ reported preferences are hypothetical and thus subject to change and rationalisation. Nonetheless, these data are useful in assessing future fertility trends. In combination with data on contraceptive use, they also allow estimation of the need for family planning, both for spacing and limiting births. 6.1 DESIRE FOR MORE CHILDREN Table 6.1 and Figure 6.1 present data concerning future reproductive preferences among currently married women and men. The inclusion of women who are currently pregnant complicates the measurement of views on future childbearing. For a pregnant woman the question about desiring more children is rephrased to refer to wanting another child after the one that she is currently expecting. To take into account the way in which the preference variable is defined for pregnant women, the results are classified by number of living children, with the current pregnancy categorised as equivalent to a living child. I Key Findings • Thirty-seven percent of currently married women age 15-49 and 29 percent of men want no more children or are sterilized. • The desire to stop childbearing increased from 32 percent in 2000 to 42 percent in 2005 and then declined to 37 percent in 2011. • Women prefer a family size of 4.3 children, and men prefer 4.8 children. Women’s ideal family size has declined in the last ten years, from 5.3 children in 2000 to 4.5 children in 2005 and 4.3 children in 2011. • Overall, the total wanted fertility rate (TWFR) in Ethiopia is 3.0 children per woman, 1.8 fewer than the total fertility rate (TFR) of 4.8. This suggests that the TFR is 60 percent higher than it would be if unwanted births were avoided. 82 • Fertility Preferences Table 6.1 Fertility preferences by number of living children Percent distribution of currently married women and currently married men age 15-49 by desire for children, according to number of living children, Ethiopia 2011 Desire for children Number of living children Total 15-49 Total 15-59 0 1 2 3 4 5 6+ WOMEN1 Have another soon2 55.4 23.9 17.1 14.9 12.1 8.2 6.7 16.9 na Have another later3 34.1 61.2 53.8 44.6 37.9 27.5 13.7 38.2 na Have another, undecided when 4.0 2.4 3.0 2.1 2.2 1.7 1.7 2.3 na Undecided 1.0 2.9 3.1 3.9 3.7 4.8 4.3 3.5 na Want no more 3.4 9.1 21.4 31.9 41.4 55.8 68.6 36.5 na Sterilised4 0.0 0.0 0.5 0.4 0.7 0.5 0.7 0.5 na Declared infecund 2.1 0.4 0.9 2.1 1.5 1.5 4.0 1.9 na Missing 0.0 0.0 0.3 0.0 0.4 0.0 0.2 0.2 na Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 na Weighted number 806 1,490 1,746 1,529 1,302 1,164 2,251 10,287 na Unweighted number 878 1,658 1,772 1,462 1,287 1,137 2,010 10,204 na MEN5 Have another soon2 55.6 21.0 15.9 14.3 15.6 7.5 10.8 17.7 17.4 Have another later3 35.8 69.9 63.3 52.2 42.7 40.5 31.8 48.9 43.3 Have another, undecided when 3.2 1.6 1.5 2.7 1.8 2.5 1.7 2.0 2.0 Undecided 0.8 2.1 2.5 2.1 2.3 2.1 1.1 1.9 1.9 Want no more 3.2 5.2 15.7 27.7 36.6 46.0 53.1 28.4 32.8 Sterilised4 0.0 0.0 0.4 0.3 0.1 1.0 1.0 0.4 1.0 Declared infecund 0.5 0.3 0.7 0.4 0.7 0.4 0.5 0.5 1.6 Missing 1.0 0.1 0.0 0.2 0.2 0.1 0.0 0.2 0.2 Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 Weighted number 554 1,024 1,219 1,051 934 714 1,375 6,872 8,089 Unweighted number 567 1,117 1,180 1,019 855 688 1,349 6,775 7,930 na = Not applicable 1 The number of living children includes current pregnancy for women 2 Wants next birth within two years 3 Wants to delay next birth for two or more years 4 Includes both female and male sterilisation 5 The number of living children includes one additional child if respondent's wife is pregnant (or if any wife is pregnant, for men with more than one current wife). Although more than half of currently married women age 15-49 (57 percent) say that they want more children, 38 percent say that they want to wait for two years or more before having their next child. These women can be considered potential contraceptive users for spacing births. Seventeen percent of women say they want another child soon (within the next two years), while 2 percent want another child but are undecided about the timing of the next birth. Four percent are unsure whether they want another child. Overall, 37 percent of married women want no more children, including 1 percent who have been sterilised. Two percent of women consider themselves to be infecund. The desire for more children is related to the number of living children women already have. More than nine in every ten currently married women with no children want to have a child, with 55 percent expressing the desire to have a child soon and 34 percent wanting to delay having a child for at least two years. For women with one or more living children, the desire to stop childbearing altogether increases with the number of children. For example, 9 percent of currently married women with one child report that they want no more children compared with 69 percent of women with six or more children. Nevertheless, significant percentages of women with five children (37 percent), or six or more children (22 percent), want to have another child. Among currently married women of reproductive age, the desire to space births has not changed considerably over time. According to the 2000 EDHS, 36 percent of women age 15-49 wanted to wait at least two years before having another child compared with 35 percent of women in 2005 and 38 percent in 2011. Conversely, the proportion of women who want no more births increased from 32 percent in 2000 to 42 percent in 2005 and then declined to 37 percent in 2011. Fertility Preferences • 83 Figure 6.1 Desire for More Children Among Currently Married Women EDHS 2011 Have another soon 17% Have another later 38% Have another, undecide 2% Undecided 4% Want no more 37% Sterilised 1% Declared infecund 2% Note: Percentages add to more than 100 due to rounding. Have another/ undecided when 2% Have another later 38% Have another soon 17% Declared infecund 2% Sterilised 1% Want no more 37% Undecided 4% Overall, the percentage of men age 15-49 who want no more children or are sterilised (29 percent) is lower than among women age 15-49 (37 percent). Conversely, a higher percentage of men than women want to have another child (69 versus 57 percent). Men’s reported desire to have another child decreases as their number of living children increases, as in the case among women. 6.2 DESIRE TO LIMIT CHILDBEARING BY BACKGROUND CHARACTERISTICS Tables 6.2.1 and 6.2.2 present the percentages of currently married women and men who want no more children (or are sterilised), by number of living children. The data provide information about variations in the potential demand for family planning among women and men. Table 6.2.1 shows that overall the proportion of currently married women who desire to limit childbearing is the same in urban areas as in rural areas (37 percent). However, when the number of children is held constant, urban women are more likely than rural women to want to limit childbearing, with the largest difference among women with two living children (41 percent among urban women and 15 percent among rural women). There is significant regional variation in the desire to limit childbearing, ranging from 11 percent in the Somali region to 41 percent in the SNNP region. As women’s education increases, their reported desire to have no more children decreases. For example, 41 percent of women with no education desire to limit childbearing compared with 32 percent of women with primary education. Currently married women in the middle wealth quintile are most likely to want to limit childbearing (40 percent). 84 • Fertility Preferences Table 6.2.1 Desire to limit childbearing: Women Percentage of currently married women age 15-49 who want no more children, by number of living children, according to background characteristics, Ethiopia 2011 Background characteristic Number of living children1 Total 0 1 2 3 4 5 6+ Residence Urban 7.5 9.2 41.2 45.1 60.9 61.9 70.7 37.1 Rural 1.9 9.1 15.0 29.2 39.1 55.7 69.2 36.9 Region Tigray 0.9 2.3 11.8 17.1 26.7 42.4 59.6 26.3 Affar 2.6 6.1 15.4 13.0 16.5 21.1 24.9 15.1 Amhara 5.0 13.4 29.6 33.4 42.4 61.1 74.9 39.6 Oromiya 2.2 7.6 18.8 33.0 42.2 62.2 67.5 37.1 Somali (3.6) 3.2 8.6 7.5 5.0 11.6 18.5 10.7 Benishangul-Gumuz 10.9 10.2 22.8 29.5 49.6 50.4 64.5 34.4 SNNP 2.6 6.1 15.7 33.8 47.0 51.2 77.9 41.3 Gambela 2.9 21.8 32.9 34.3 43.5 50.8 52.5 30.0 Harari 0.0 10.9 35.0 39.2 42.0 54.0 78.2 35.9 Addis Ababa 2.7 15.2 35.3 51.2 79.0 * (81.7) 34.4 Dire Dawa 0.0 11.2 41.7 41.5 43.5 64.3 73.9 37.2 Education No education 1.3 11.1 19.2 31.8 40.9 55.0 68.2 40.6 Primary 5.5 9.0 23.2 31.0 43.9 61.4 73.8 32.2 Secondary 7.9 4.7 32.2 35.9 (77.3) * * 21.8 More than secondary 0.0 2.8 31.3 (54.8) * * * 20.5 Wealth quintile Lowest 3.6 8.3 19.2 31.0 35.4 50.9 64.2 35.9 Second 2.1 8.3 13.1 28.5 43.0 55.1 71.5 36.4 Middle 0.1 13.1 19.8 32.9 42.2 53.9 73.6 40.2 Fourth 9.2 9.2 13.0 28.7 36.4 66.8 67.0 37.9 Highest 2.8 8.0 37.4 39.4 57.5 56.6 71.4 34.6 Total 3.4 9.2 21.9 32.3 42.1 56.3 69.3 37.0 Note: Women who have been sterilised are considered to want no more children. Figures in parentheses are based on 25-49 unweighted cases. An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. 1 The number of living children includes the current pregnancy. Fertility Preferences • 85 Table 6.2.2 shows that urban, educated, and wealthy men are more likely to want to limit childbearing than men in rural areas and those with less education or wealth. Among men the desire to limit childbearing is greatest in Amhara region and least in Somali. Table 6.2.2 Desire to limit childbearing: Men Percentage of currently married men age 15-49 who want no more children, by number of living children, according to background characteristics, Ethiopia 2011 Background characteristic Number of living children1 Total 0 1 2 3 4 5 6+ Residence Urban 3.7 11.6 29.4 44.4 53.7 68.2 58.4 32.7 Rural 3.0 3.1 11.2 24.4 34.4 44.0 53.7 28.0 Region Tigray 3.4 2.6 7.8 16.5 21.0 36.4 56.2 22.4 Affar 3.5 3.9 5.4 8.4 11.7 (3.3) 14.6 8.0 Amhara 4.9 9.1 19.5 40.7 50.2 58.9 65.5 34.8 Oromiya 0.0 3.4 11.9 26.0 33.9 (41.0) 50.0 26.3 Somali (0.0) (6.4) (1.7) 6.0 1.0 0.0 6.5 4.0 Benishangul-Gumuz 9.3 4.0 20.6 19.0 39.8 46.2 45.3 26.5 SNNP (6.1) 1.6 14.8 20.1 28.2 53.6 57.8 31.4 Gambela 8.4 3.0 30.1 16.5 18.5 (30.9) 36.3 17.8 Harari (3.5) 8.1 17.1 28.0 (34.8) (47.4) 67.9 28.0 Addis Ababa 1.8 11.8 35.7 45.9 (75.0) * * 31.4 Dire Dawa (6.3) 3.1 24.4 37.7 31.9 37.8 48.5 25.5 Education No education 2.7 3.9 12.7 24.4 31.5 38.1 48.4 26.7 Primary 3.2 5.9 13.2 26.9 40.7 51.9 59.2 30.3 Secondary 3.6 3.9 42.3 48.8 (54.1) (58.4) (74.5) 36.4 More than secondary 4.4 6.7 26.1 48.9 (57.3) (90.5) (29.2) 25.7 Wealth quintile Lowest 5.3 2.5 11.9 19.9 23.0 35.4 46.4 24.1 Second 2.0 3.3 11.4 22.3 33.9 44.8 58.1 27.5 Middle 1.7 3.1 11.8 28.9 41.4 43.8 54.8 30.9 Fourth 3.9 3.0 14.2 27.4 36.6 54.7 54.6 30.4 Highest 3.6 10.4 25.4 41.2 60.6 62.8 60.8 31.4 Total 15-49 3.2 5.2 16.1 28.0 36.7 46.9 54.1 28.9 50-59 * * 40.0 61.5 64.3 49.2 65.8 61.2 Total 15-59 4.5 5.4 17.0 30.0 39.7 47.4 58.4 33.8 Note: Men who have been sterilised or who state in response to the question about desire for children that their wife has been sterilised are considered to want no more children. Figures in parentheses are based on 25-49 unweighted cases. An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. 1 The number of living children includes one additional child if respondent's wife is pregnant (or if any wife is pregnant, for men with more than one current wife). 86 • Fertility Preferences 6.3 IDEAL NUMBER OF CHILDREN This section discusses survey responses of women and men concerning their ideal number of children. Respondents who had no children were asked how many children they would like to have if they could choose the number of children to have over their entire lifetime. Those who had living children were asked the number of children they would choose if they could start their childbearing again. Responses to both questions provide an indication of future fertility, while responses to the latter question also contribute to a measure of unwanted fertility. Table 6.3 shows the distribution of respondents by ideal number of children and the mean ideal number of children. In general, a large proportion of Ethiopians, regardless of their number of living children, consider four or more children to be ideal. The mean ideal number of children is 4.3 for all women and 4.9 for currently married women. Among all women, the mean ideal number of children increases with their number of living children, from 3.3 for women with no children to 6.2 for women with six or more children. Ethiopian men, on average, prefer to have larger families than women consider ideal. Among all men, ideal family size is 4.8 children, and among married men, 5.9 children. Similarly, currently married men with six or more children want more children (8.6 children) than the number that married women want (6.2 children). There has been a steady decline in women’s ideal family size in Ethiopia in the last eleven years, from 5.3 children in 2000 to 4.5 children in 2005 and 4.3 children in 2011 (Figure 6.2). Similarly, ideal family size among men declined from 6.4 children in 2000 to 5.2 children in 2005 and 4.8 children in 2011. Fertility Preferences • 87 Table 6.3 Ideal number of children Percent distribution of women and men 15-49 by ideal number of children and mean ideal number of children for all respondents and for currently married respondents, according to the number of living children, Ethiopia 2011 Ideal number of children Number of living children Total 0 1 2 3 4 5 6+ WOMEN1 0 7.6 3.7 6.7 8.5 8.8 9.2 10.8 7.8 1 1.7 1.8 0.4 0.4 0.4 0.1 0.2 0.9 2 25.8 13.6 8.2 3.2 3.3 2.4 1.2 12.2 3 13.1 15.2 5.1 5.2 2.2 2.4 2.2 8.1 4 33.4 38.3 43.2 31.1 26.4 19.4 14.3 30.4 5 6.6 8.6 9.1 13.1 7.5 9.4 5.2 7.9 6+ 7.6 12.5 18.3 26.4 36.7 42.0 42.2 22.0 Non-numeric responses 4.2 6.4 9.0 12.2 14.7 15.1 24.0 10.6 Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 Weighted number of women 5,488 1,959 2,074 1,750 1,494 1,301 2,449 16,515 Unweighted number of women 5,532 2,191 2,120 1,702 1,486 1,281 2,203 16,515 Mean ideal number of children for:2 All women 3.3 3.9 4.2 4.6 5.1 5.6 6.2 4.3 Weighted number of women 5,258 1,834 1,886 1,537 1,275 1,105 1,862 14,757 Unweighted number of women 5,233 2,034 1,943 1,514 1,277 1,082 1,712 14,795 Currently married women 3.9 3.9 4.3 4.7 5.2 5.5 6.2 4.9 Weighted number of currently married women 760 1,390 1,591 1,342 1,115 982 1,714 8,894 Unweighted number of currently married women 816 1,532 1,618 1,299 1,110 954 1,563 8,892 MEN3 0 2.4 1.4 2.3 1.6 1.1 1.8 2.5 2.1 1 1.0 0.7 0.6 0.4 0.2 0.0 0.0 0.7 2 26.0 13.0 6.3 3.4 4.2 3.0 2.2 15.5 3 19.6 16.5 9.7 9.2 3.1 2.7 2.4 13.4 4 30.1 39.8 37.0 26.5 24.2 16.2 13.8 28.3 5 7.0 8.4 10.4 16.5 10.4 11.7 5.0 8.5 6+ 10.1 16.1 25.9 35.8 48.5 54.0 62.9 25.4 Non-numeric responses 3.8 4.1 7.9 6.5 8.2 10.6 11.2 6.0 Total men 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 Weighted number of men 6,284 1,115 1,271 1,082 970 727 1,385 12,834 Unweighted number of men 6,357 1,246 1,255 1,055 886 704 1,365 12,868 Mean ideal number of children for:2 All men 3.6 4.1 4.8 5.5 6.3 7.1 8.6 4.8 Weighted number of men 6,047 1,069 1,171 1,012 890 650 1,230 12,068 Unweighted number of men 6,047 1,183 1,166 970 793 608 1,173 11,940 Currently married men 3.8 4.2 4.8 5.6 6.3 7.1 8.6 5.9 Weighted number of currently married men 535 984 1,127 987 857 639 1,220 6,350 Unweighted number of currently married men 538 1,063 1,095 937 767 594 1,158 6,152 1 The number of living children includes current pregnancy for women. 2 Means are calculated excluding respondents who gave non-numeric responses. 3 The number of living children includes one additional child if respondent's wife is pregnant (or if any wife is pregnant, for men with more than one current wife). 88 • Fertility Preferences Figure 6.2 Trends in Mean Ideal Family Size Among All Women and Men, EDHS 2000, 2005, and 2011 5.3 6.4 4.5 5.2 4.3 4.8 Women Men 0 1 2 3 4 5 6 7 Mean ideal number of children 2000 2005 2011 6.4 MEAN IDEAL NUMBER OF CHILDREN BY WOMEN’S BACKGROUND CHARACTERISTICS There are significant variations in the mean ideal number of children by background characteristics among all women age 15-49 (Table 6.4). The older the respondent, the more children that she considers ideal; women age 15-19 respond that the ideal family size is 3.3 children, while women age 45-49 say it is 5.7. The ideal number of children among rural women is almost one child more than among urban women (4.5 versus 3.7 children). Among regions the range is from 3.3 children in Addis Ababa to 9.7 children in the Somali region. The ideal number of children declines as women’s level of education and wealth quintile increase. For example, the mean ideal number of children among women who have completed primary school is 3.8 children, compared with 5.0 children among women with no education. Similarly, women in the lowest wealth quintile consider 5.0 children to be ideal, compared with 3.7 children among women in the highest wealth quintile. These patterns are similar to those in the 2000 and 2005 EDHS. Fertility Preferences • 89 Table 6.4 Mean ideal number of children by background characteristics Mean ideal number of children for all women age 15-49 by background characteristics, Ethiopia 2011 Background characteristic Mean Weighted number of women1 Unweighted number of women1 Age 15-19 3.3 3,829 3,615 20-24 3.9 2,716 2,806 25-29 4.3 2,852 2,896 30-34 5.0 1,811 1,834 35-39 5.3 1,588 1,643 40-44 5.5 1,012 1,093 45-49 5.7 948 908 Residence Urban 3.7 3,708 4,985 Rural 4.5 11,049 9,810 Region Tigray 4.8 973 1,519 Affar 7.4 127 1,118 Amhara 4.0 3,968 1,860 Oromiya 4.3 5,342 1,893 Somali 9.7 217 619 Benishangul-Gumuz 4.9 160 1,146 SNNP 4.4 2,932 1,834 Gambela 4.4 67 1,090 Harari 4.7 47 1,070 Addis Ababa 3.3 861 1,673 Dire Dawa 4.6 62 973 Education No education 5.0 7,067 6,960 Primary 3.8 5,866 5,507 Secondary 3.4 1,102 1,365 More than secondary 3.3 721 963 Wealth quintile Lowest 5.0 2,519 3,110 Second 4.6 2,622 2,089 Middle 4.5 2,704 2,023 Fourth 4.2 2,948 2,288 Highest 3.7 3,965 5,285 Total 4.3 14,757 14,795 1 Number of women who gave a numeric response 6.5 FERTILITY PLANNING STATUS The level of unwanted fertility among women age 15-49 can be assessed through a series of survey questions asked about each of the children born to them in the preceding five years (including current pregnancy). If the birth or pregnancy was wanted then, it is considered to be planned. It is considered to be mistimed if it was wanted but at a later time, and considered to be unwanted if it was not wanted at the time of conception. In the interpretation of these results, it is important to consider that a woman may declare a birth (or pregnancy) as wanted once the child is born even if that was not her feeling during pregnancy, and this rationalisation would result in an underestimation of the true extent of unwanted births. Nevertheless, these results provide some insight into the degree to which couples are able to control their fertility. 90 • Fertility Preferences Table 6.5 shows the percent distribution of births (including current pregnancy), by fertility planning status, in the five years preceding the survey, according to birth order and mother’s age at birth. Nearly three births of every four (72 percent) were wanted at the time, 20 percent were wanted but later, and 9 percent were unwanted. The proportion of births wanted at the time of conception generally declines with both increasing birth order and mother’s age. Table 6.5 Fertility planning status Percent distribution of births to women age 15-49 in the five years preceding the survey (including current pregnancies), by planning status of the birth, according to birth order and mother's age at birth, Ethiopia 2011 Birth order and mother's age at birth Planning status of birth Total Weighted number of births Unweighted number of births Wanted then Wanted later Wanted no more Missing Birth order 1 77.5 18.6 3.5 0.3 100.0 2,462 2,516 2 73.5 23.6 2.8 0.1 100.0 2,230 2,266 3 73.2 22.2 4.6 0.0 100.0 1,844 1,858 4+ 68.1 17.7 13.9 0.2 100.0 6,542 6,291 Mother's age at birth <20 71.8 24.2 3.6 0.4 100.0 1,654 1,767 20-24 75.4 21.4 3.0 0.2 100.0 3,774 3,639 25-29 71.5 21.7 6.7 0.0 100.0 3,481 3,443 30-34 71.4 15.4 13.0 0.2 100.0 2,282 2,267 35-39 67.5 12.7 19.7 0.1 100.0 1,328 1,302 40-44 53.7 12.6 33.2 0.4 100.0 474 450 45-49 58.6 12.2 29.1 0.0 100.0 85 63 Total 71.5 19.5 8.8 0.2 100.0 13,078 12,931 Some changes in women’s fertility planning status have occurred over the past decade. The percentage of births that were wanted at the time of conception increased from 63 percent in the 2000 EDHS to 65 percent in 2005 and to 72 percent in 2011. The percentage of births that were wanted later stayed more or less the same, at 19-20 percent, while the percentage of unwanted births decreased from 17 percent in 2000 to 16 percent in 2005 and 9 percent in the 2011 EDHS. 6.6 WANTED FERTILITY RATES Table 6.6 compares wanted fertility with actual fertility for the three years preceding the survey, by selected background characteristics of women. The total wanted fertility rate (TWFR) is calculated in the same manner as the total fertility rate (TFR) but excludes unwanted births from the numerator. For this purpose unwanted births are defined as those that exceed the number considered ideal by the respondent. Women who do not report a numeric ideal family size are assumed to want all their births. The TWFR represents the level of fertility that would have prevailed in the three years preceding the survey if all unwanted births were prevented. A comparison of the TWFR with the TFR suggests the potential impact on fertility rates of avoiding unwanted births. As measured in the 2011 EDHS, the TWFR is 3.0 children per woman, 1.8 fewer than the TFR of 4.8 children per woman, suggesting that Ethiopian women have not been very successful in achieving their reproductive intentions. The total wanted fertility rate has decreased by one child since the 2005 EDHS (4.0). Fertility Preferences • 91 Urban women are relatively closer to achieving their wanted fertility than rural women. The difference between wanted and actual fertility is 0.8 children in urban areas and 2.1 children in rural areas. Among regions the gap between wanted fertility and actual fertility is highest in Somali (2.9) and lowest in Addis Ababa (0.2). The TWFR varies inversely with education and wealth, as does the TFR, declining as education and wealth increase. Also, the gap between wanted and actual fertility narrows as women’s education and wealth increase. Table 6.6 Wanted fertility rates Total wanted fertility rates and total fertility rates for the three years preceding the survey, by background characteristics, Ethiopia 2011 Background characteristic Total wanted fertility rate Total fertility rate Residence Urban 1.8 2.6 Rural 3.4 5.5 Region Tigray 3.3 4.6 Affar 3.7 5.0 Amhara 2.7 4.2 Oromiya 3.3 5.6 Somali 4.2 7.1 Benishangul-Gumuz 3.8 5.2 SNNP 3.0 4.9 Gambela 3.2 4.0 Harari 3.2 3.8 Addis Ababa 1.3 1.5 Dire Dawa 2.4 3.4 Education No education 3.7 5.8 Primary 2.8 4.6 Secondary 1.8 1.9 More than secondary 1.2 1.3 Wealth quintile Lowest 3.7 6.0 Second 3.6 5.7 Middle 3.3 5.3 Fourth 3.1 5.0 Highest 1.9 2.8 Total 3.0 4.8 Note: Rates are calculated based on births to women age 15-49 in the period 1-36 months preceding the survey. The total fertility rates are the same as those presented in Table 5.2. Family Planning • 93 FAMILY PLANNING 7 ne of targets of the Ministry of Health, with respect to improving maternal and child health, is to increase the contraceptive prevalence rate (CPR) to 66 percent by 2015. In order to achieve this target, the Ministry has given priority to the provision of safe motherhood services such as family planning in the community (MOH, 2010). This chapter presents information from the 2011 EDHS on contraceptive knowledge, attitudes, and behaviour. Information on women’s and men’s knowledge of family planning methods provides a measure of the level of awareness of contraception in the population and indicates the success of information, education, and communication programmes. In addition, knowledge of at least one family planning method and a positive attitude toward contraception are prerequisites for the use of contraception. Although the focus here is on women, some results from the male survey are also presented because men play an important role in the realisation of reproductive goals. Comparisons are made, where feasible, with findings from previous EDHS surveys to evaluate trends in Ethiopia over the last decade. 7.1 KNOWLEDGE OF CONTRACEPTIVE METHODS Knowledge of family planning is a prerequisite to obtaining access to and using a suitable contraceptive method in a timely and effective manner. Interviewers collected information regarding knowledge of contraceptive methods by describing each method and asking female and male respondents if she/he had heard of it. Using this approach, interviewers collected information about 11 modern family planning methods: female and male sterilisation, the pill, the IUD, injectables, implants, male and female condoms, lactational amenorrhea method, emergency contraception, and the standard days method. Two traditional methods were also included in the survey: periodic abstinence (or rhythm) and withdrawal. Interviewers recorded any other traditional methods that respondents mentioned spontaneously. O Key Findings • Knowledge of contraception is nearly universal in Ethiopia. • Three in every ten currently married women (29 percent) are using a method of contraception, mostly modern methods (27 percent). • By far the most popular modern method, used by 21 percent of currently married women, is injectables. • Use of modern methods among currently married women has increased from 6 percent in the 2000 EDHS to 27 percent in the 2011 EDHS—largely due to the sharp increase in the use of injectables, from 3 percent in 2000 to 21 percent in 2011. • The government sector is the major provider of contraceptive methods, catering to more than eight in every ten users of modern contraceptive methods (82 percent). • Twenty-five percent of currently married women have an unmet need for family planning services; 16 percent have a need for spacing, and 9 percent have a need for limiting. • The 12-month contraceptive discontinuation rate for all methods is 37 percent. The highest discontinuation rate is for the pill (70 percent), followed by the male condom (62 percent). 94 • Family Planning Table 7.1 shows the percentage of all respondents, currently married respondents, and sexually active unmarried respondents, age 15-49, who know any contraceptive method, by specific type. Knowledge of at least one method of contraception is nearly universal among both women and men in Ethiopia, regardless of marital status and sexual experience. Men and women are almost equally likely to have heard of a modern method (98 and 97 percent, respectively). Both women and men are more familiar with modern methods of contraceptive than with traditional methods. A higher proportion of men than women have heard of a traditional contraceptive method (64 and 50 percent, respectively). Unmarried sexually active women and men know of more methods than their married counterparts. More than nine women in every ten have heard about the pill and injectables. More than nine men in every ten know about the male condom as well as about the pill and injectables. LAM is the least known modern method. Only 3 percent of all women and of all men interviewed have heard of this method. Table 7.1 Knowledge of contraceptive methods Percentage of all respondents, currently married respondents, and sexually active unmarried respondents age 15-49 who have heard of any contraceptive method, by specific method, Ethiopia 2011 Method Women Men All women Currently married women Sexually active unmarried women1 All men Currently married men Sexually active unmarried men1 Any method 97.2 97.6 99.8 98.4 99.2 99.9 Any modern method 97.1 97.4 99.7 98.4 99.1 99.9 Female sterilisation 38.7 39.8 50.8 42.5 46.8 51.9 Male sterilisation 11.2 10.8 21.4 18.0 17.6 37.7 Pill 91.3 92.6 96.4 91.1 94.1 96.2 IUD 26.3 26.4 36.7 27.8 27.5 45.4 Injectables 94.9 96.1 98.3 91.8 95.2 97.3 Implants 67.8 69.2 81.9 59.2 63.5 69.7 Male condom 80.4 78.1 92.3 95.8 96.8 99.9 Female condom 31.9 27.3 54.9 39.8 36.4 73.4 Lactational amenorrhea (LAM) 2.9 2.6 3.5 2.8 2.5 8.3 Emergency contraception 19.0 16.0 41.0 27.4 26.2 53.6 Standard days method 11.6 10.8 14.3 19.8 20.5 30.1 Any traditional method 49.6 47.4 77.3 64.0 67.1 84.8 Rhythm 43.3 41.0 70.3 57.4 60.6 76.5 Withdrawal 26.8 24.5 47.5 42.4 42.0 69.4 Other 0.9 0.9 1.6 1.1 1.1 2.9 Mean number of methods known by respondents age 15-49 5.5 5.4 7.1 6.2 6.3 8.1 Weighted number of respondents 16,515 10,287 197 12,834 6,872 222 Unweighted number of respondents 16,515 10,204 268 12,868 6,775 366 Mean number of methods known by respondents 15-59 na na na 6.1 6.2 8.1 Weighted number of respondents na na na 14,110 8,089 224 Unweighted number of respondents na na na 14,110 7,930 373 na = Not applicable 1 Had last sexual intercourse within the 30 days preceding the survey Family Planning • 95 7.2 CURRENT USE OF CONTRACEPTIVE METHODS Current use of contraceptive methods is one of the indicators most frequently used to assess the success of family planning programmes. This section focuses on the levels, trends, and differentials in current use of family planning. 7.2.1 Current Use of Contraceptive Methods By Age Table 7.2 presents current use of contraceptive methods among all women, currently married women, and sexually active unmarried women, by age group. The contraceptive prevalence rate for all Ethiopian women age 15-49 is 20 percent. The contraceptive prevalence rate is 29 percent for currently married women, and 57 percent for sexually active unmarried women. Modern methods of contraception are more commonly used by the interviewed women. Table 7.2 shows that 29 percent of currently married women report use of a contraceptive method, with 27 percent using a modern method. The same pattern is observed among all women and unmarried sexually active women. The most common modern method used by each group of women is injectables, currently used by 14 percent of all women, 21 percent of currently married women, and 32 percent of unmarried sexually active women. Current contraceptive use is lower among young women and among older women (some of whom are no longer fecund) than among those at the intermediate age groups. For example, 5 percent of all women age 15-19 report current use of any contraceptive method. This proportion increases until it peaks at 29 percent in the 30-34 age group, after which it decreases steadily to 11 percent among women age 45-49. A similar pattern is observed among currently married women. 96 • F am ily P la nn in g Ta bl e 7. 2 C ur re nt u se o f c on tra ce pt io n by a ge P er ce nt d is tri bu tio n of a ll w om en , c ur re nt ly m ar rie d w om en , a nd s ex ua lly a ct iv e un m ar rie d w om en a ge 1 5- 49 b y co nt ra ce pt iv e m et ho d cu rr en tly u se d, a cc or di ng to a ge , E th io pi a 20 11 A ge A ny m et ho d A ny m od er n m et ho d M od er n m et ho d A ny tra di tio na l m et ho d Tr ad iti on al m et ho d N ot cu rr en tly us in g To ta l W ei gh te d nu m be r o f w om en U nw ei gh te d nu m be r o f w om en Fe m al e st er ili sa tio n P ill IU D In je ct ab le s Im pl an ts M al e co nd om O th er R hy th m W ith dr aw al O th er A LL W O M E N 15 -1 9 5. 3 5. 2 0. 0 0. 6 0. 0 4. 1 0. 4 0. 1 0. 0 0. 1 0. 1 0. 0 0. 0 94 .7 10 0. 0 4, 00 9 3, 83 5 20 -2 4 23 .3 22 .2 0. 1 1. 4 0. 1 18 .5 1. 8 0. 3 0. 0 1. 1 0. 9 0. 2 0. 0 76 .7 10 0. 0 2, 93 1 3, 02 2 25 -2 9 26 .5 25 .6 0. 2 2. 1 0. 4 18 .9 3. 5 0. 5 0. 0 0. 9 0. 7 0. 2 0. 0 73 .5 10 0. 0 3, 14 7 3, 18 5 30 -3 4 29 .3 27 .7 0. 1 2. 3 0. 2 21 .2 3. 4 0. 5 0. 0 1. 7 1. 3 0. 1 0. 2 70 .7 10 0. 0 2, 05 4 2, 10 0 35 -3 9 26 .7 25 .8 1. 0 1. 9 0. 7 18 .3 3. 7 0. 2 0. 0 1. 0 0. 8 0. 1 0. 1 73 .3 10 0. 0 1, 91 6 1, 95 8 40 -4 4 20 .3 18 .8 1. 3 2. 0 0. 4 11 .2 3. 4 0. 3 0. 2 1. 5 0. 6 0. 8 0. 0 79 .7 10 0. 0 1, 26 1 1, 31 4 45 -4 9 10 .9 10 .4 1. 0 0. 3 0. 1 7. 5 1. 5 0. 2 0. 0 0. 5 0. 3 0. 2 0. 0 89 .1 10 0. 0 1, 19 6 1, 10 1 To ta l 19 .6 18 .7 0. 4 1. 5 0. 2 14 .0 2. 3 0. 3 0. 0 0. 9 0. 7 0. 2 0. 0 80 .4 10 0. 0 16 ,5 15 16 ,5 15 C U R R EN TL Y M AR R IE D W O M EN 15 -1 9 23 .8 23 .0 0. 0 2. 5 0. 0 18 .9 1. 6 0. 0 0. 0 0. 8 0. 8 0. 0 0. 0 76 .2 10 0. 0 76 5 78 4 20 -2 4 34 .8 33 .4 0. 0 1. 9 0. 1 28 .5 2. 9 0. 0 0. 0 1. 4 1. 1 0. 3 0. 0 65 .2 10 0. 0 1, 76 2 1, 78 8 25 -2 9 29 .9 28 .9 0. 1 2. 2 0. 5 21 .7 4. 2 0. 2 0. 0 1. 1 0. 8 0. 3 0. 0 70 .1 10 0. 0 2, 51 1 2, 48 0 30 -3 4 33 .1 31 .2 0. 1 2. 7 0. 2 23 .9 3. 8 0. 5 0. 0 1. 9 1. 5 0. 2 0. 3 66 .9 10 0. 0 1, 72 0 1, 72 2 35 -3 9 29 .1 28 .0 1. 1 2. 2 0. 8 19 .7 4. 1 0. 1 0. 0 1. 1 0. 9 0. 1 0. 0 70 .9 10 0. 0 1, 59 1 1, 60 0 40 -4 4 23 .9 22 .1 1. 6 2. 3 0. 5 13 .5 3. 6 0. 4 0. 2 1. 8 0. 8 1. 0 0. 0 76 .1 10 0. 0 1, 03 3 1, 04 7 45 -4 9 13 .1 12 .5 1. 0 0. 3 0. 1 9. 2 2. 0 0. 0 0. 0 0. 6 0. 3 0. 2 0. 0 86 .9 10 0. 0 90 5 78 3 To ta l 28 .6 27 .3 0. 5 2. 1 0. 3 20 .8 3. 4 0. 2 0. 0 1. 3 0. 9 0. 3 0. 1 71 .4 10 0. 0 10 ,2 87 10 ,2 04 S EX U A LL Y A C TI VE U N M A R R IE D W O M E N 1 15 -1 9 52 .0 52 .0 0. 0 1. 0 0. 0 32 .5 6. 7 11 .9 0. 0 0. 0 0. 0 0. 0 0. 0 48 .0 10 0. 0 34 62 20 -2 4 64 .9 55 .7 3. 7 6. 7 0. 6 32 .1 0. 9 11 .0 0. 8 9. 3 9. 3 0. 0 0. 0 35 .1 10 0. 0 67 87 25 -2 9 57 .5 57 .4 0. 0 7. 3 0. 0 31 .2 1. 7 17 .0 0. 2 0. 1 0. 1 0. 0 0. 0 42 .5 10 0. 0 43 62 30 -3 4 * * * * * * * * * * * * * * 10 0. 0 18 21 35 -3 9 * * * * * * * * * * * * * * 10 0. 0 25 24 40 -4 4 * * * * * * * * * * * * * * 10 0. 0 2 5 45 -4 9 * * * * * * * * * * * * * * 10 0. 0 7 7 To ta l 56 .7 52 .3 1. 3 5. 4 0. 2 32 .0 2. 4 10 .8 0. 3 4. 4 3. 7 0. 5 0. 2 43 .3 10 0. 0 19 7 26 8 N ot e: I f m or e th an o ne m et ho d is u se d, o nl y th e m os t ef fe ct iv e m et ho d is c on si de re d in t hi s ta bu la tio n. A n as te ris k in di ca te s th at a f ig ur e is b as ed o n fe w er t ha n 25 u nw ei gh te d ca se s an d ha s be en su pp re ss ed . 1 W om en w ho h av e ha d se xu al in te rc ou rs e w ith in th e 30 d ay s pr ec ed in g th e su rv ey 96 • Family Planning Family Planning • 97 7.2.2 Trends in Contraceptive Use Figure 7.1 shows trends in contraceptive use since the 2000 Ethiopia DHS. Use of any contraceptive methods among currently married women has increased nearly six fold in the last 20 years, from 5 percent in the 1990 NFFS to 29 percent in the 2011 EDHS. The increase is especially pronounced for the use of modern methods between 2000 and 2011. The increase in modern method use is attributed primarily to the sharp increase in the use of injectables, from 3 percent in 2000 to 21 percent in 2011. Figure 7.1 Trends in Current Use of Contraceptives Among Currently Married Women, 2000-2011 8 6 3 3 2 15 14 3 10 1 29 27 2 21 1 Any method Any modern method Pill Injectables Any traditional method 0 5 10 15 20 25 30 35 P er ce nt ag e 2000 EDHS 2005 EDHS 2011 EDHS 7.3 CURRENT USE OF CONTRACEPTION BY BACKGROUND CHARACTERISTICS Table 7.3 shows a substantial variation according to background characteristics in the current use of contraceptive methods among currently married women. Currently married women in urban areas are twice as likely as their rural counterparts to use any contraceptive method (53 and 23 percent, respectively), to use any modern method (50 and 23 percent, respectively), and to use any traditional method (3 and 1 percent, respectively). Use of any contraceptive method varies notably by region, ranging from 63 percent in Addis Ababa to 4 percent in the Somali region. Use of any modern contraceptive methods is highest in Addis Ababa (56 percent) and lowest in the Somali and Affar regions (4 and 9 percent, respectively). Current contraceptive use increases with women’s education. Twenty-two percent of women with no education report current use of any method, compared with 68 percent of women with more than secondary education. Similarly, current use of any contraceptive method increases with wealth, from 13 percent of women in the lowest quintile to 52 percent of women in the highest quintile. 98 • F am ily P la nn in g Ta bl e 7. 3 C ur re nt u se o f c on tra ce pt io n by b ac kg ro un d ch ar ac te ris tic s P er ce nt d is tri bu tio n of c ur re nt ly m ar rie d w om en a ge 1 5- 49 b y co nt ra ce pt iv e m et ho d cu rre nt ly u se d, 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 A ny m et ho d A ny m od er n m et ho d M od er n m et ho d A ny tra di tio na l m et ho d Tr ad iti on al m et ho d N ot cu rr en tly us in g To ta l W ei gh te d nu m be r o f w om en U nw ei gh te d nu m be r o f w om en Fe m al e st er ili sa tio n P ill IU D In je ct ab le s Im pl an ts M al e co nd om R hy th m W ith dr aw al O th er N um be r o f l iv in g ch ild re n 0 23 .4 21 .1 0. 0 3. 0 0. 0 16 .9 0. 9 0. 3 2. 4 2. 2 0. 1 0. 0 76 .6 10 0. 0 1, 01 8 1, 10 4 1- 2 35 .3 33 .9 0. 3 2. 7 0. 4 27 .2 3. 0 0. 3 1. 3 0. 9 0. 4 0. 0 64 .7 10 0. 0 3, 19 3 3, 38 1 3- 4 29 .7 28 .4 0. 5 2. 2 0. 5 20 .8 4. 1 0. 2 1. 4 0. 8 0. 4 0. 2 70 .3 10 0. 0 2, 80 9 2, 71 8 5+ 22 .8 22 .0 0. 7 1. 2 0. 3 15 .6 4. 1 0. 0 0. 8 0. 6 0. 2 0. 0 77 .2 10 0. 0 3, 26 7 3, 00 1 R es id en ce U rb an 52 .5 49 .5 1. 5 6. 7 0. 9 35 .4 3. 8 1. 0 3. 0 2. 4 0. 6 0. 0 47 .5 10 0. 0 1, 84 3 2, 42 2 R ur al 23 .4 22 .5 0. 2 1. 1 0. 2 17 .6 3. 3 0. 0 0. 9 0. 6 0. 2 0. 1 76 .6 10 0. 0 8, 44 4 7, 78 2 R eg io n Ti gr ay 22 .2 21 .2 0. 3 2. 1 0. 0 12 .8 5. 6 0. 5 1. 0 0. 8 0. 1 0. 1 77 .8 10 0. 0 62 0 98 4 A ffa r 9. 5 9. 1 0. 0 1. 3 0. 0 7. 6 0. 2 0. 0 0. 4 0. 2 0. 2 0. 1 90 .5 10 0. 0 10 4 96 0 A m ha ra 33 .9 33 .0 0. 6 1. 5 0. 3 26 .5 4. 0 0. 0 0. 9 0. 5 0. 3 0. 1 66 .1 10 0. 0 2, 77 6 1, 33 1 O ro m iy a 26 .2 24 .9 0. 2 2. 2 0. 3 18 .8 3. 4 0. 1 1. 3 1. 1 0. 2 0. 0 73 .8 10 0. 0 3, 96 1 1, 40 3 S om al i 4. 3 3. 8 0. 0 0. 8 0. 0 2. 0 0. 5 0. 4 0. 5 0. 5 0. 0 0. 0 95 .7 10 0. 0 23 2 66 4 B en is ha ng ul -G um uz 27 .0 26 .3 0. 6 2. 7 0. 0 21 .2 1. 5 0. 3 0. 7 0. 6 0. 1 0. 0 73 .0 10 0. 0 12 4 90 4 S N N P 25 .8 24 .7 0. 5 1. 4 0. 3 19 .5 2. 9 0. 1 1. 1 0. 7 0. 4 0. 1 74 .2 10 0. 0 2, 02 2 1, 29 5 G am be la 33 .8 33 .2 0. 5 4. 4 0. 7 26 .4 0. 4 0. 8 0. 6 0. 6 0. 0 0. 0 66 .2 10 0. 0 41 76 8 H ar ar i 34 .7 31 .5 0. 3 6. 7 1. 2 19 .2 3. 0 1. 0 3. 3 2. 9 0. 3 0. 0 65 .3 10 0. 0 28 63 5 A dd is A ba ba 62 .5 56 .3 2. 3 10 .9 2. 6 35 .8 2. 8 2. 0 6. 1 5. 1 0. 9 0. 1 37 .5 10 0. 0 34 2 63 4 D ire D aw a 33 .9 31 .7 0. 2 4. 7 1. 1 15 .3 8. 0 2. 1 2. 2 2. 0 0. 1 0. 0 66 .1 10 0. 0 38 62 6 Ed uc at io n N o ed uc at io n 22 .2 21 .8 0. 4 0. 9 0. 1 16 .9 3. 4 0. 0 0. 4 0. 2 0. 1 0. 1 77 .8 10 0. 0 6, 73 5 6, 56 9 P rim ar y 35 .7 33 .7 0. 4 2. 8 0. 6 26 .5 3. 2 0. 1 2. 0 1. 4 0. 6 0. 0 64 .3 10 0. 0 2, 86 2 2, 73 9 S ec on da ry 57 .6 53 .4 0. 8 9. 1 0. 7 36 .0 5. 1 1. 8 4. 1 3. 3 0. 9 0. 0 42 .4 10 0. 0 37 8 52 8 M or e th an s ec on da ry 67 .8 57 .2 1. 3 12 .7 1. 9 34 .2 4. 4 2. 0 10 .6 8. 9 1. 6 0. 2 32 .2 10 0. 0 31 3 36 8 W ea lth q ui nt ile Lo w es t 13 .3 13 .0 0. 1 0. 4 0. 1 10 .6 1. 8 0. 0 0. 4 0. 3 0. 0 0. 1 86 .7 10 0. 0 2, 07 7 2, 72 4 S ec on d 22 .2 21 .5 0. 6 0. 6 0. 2 16 .3 3. 8 0. 0 0. 7 0. 4 0. 1 0. 1 77 .8 10 0. 0 2, 11 7 1, 67 6 M id dl e 24 .4 24 .0 0. 1 1. 4 0. 3 18 .8 3. 5 0. 0 0. 3 0. 2 0. 1 0. 0 75 .6 10 0. 0 2, 08 3 1, 58 5 Fo ur th 31 .7 30 .3 0. 8 1. 5 0. 2 23 .9 3. 8 0. 0 1. 5 1. 0 0. 4 0. 1 68 .3 10 0. 0 1, 92 3 1, 59 0 H ig he st 51 .8 48 .2 0. 8 6. 7 0. 9 34 .6 4. 2 0. 9 3. 6 2. 6 0. 9 0. 0 48 .2 10 0. 0 2, 08 7 2, 62 9 To ta l 28 .6 27 .3 0. 5 2. 1 0. 3 20 .8 3. 4 0. 2 1. 3 0. 9 0. 3 0. 1 71 .4 10 0. 0 10 ,2 87 10 ,2 04 N ot e: If m or e th an o ne m et ho d is u se d, o nl y th e m os t e ffe ct iv e m et ho d is c on si de re d in th is ta bu la tio n. 98 • Family Planning Family Planning • 99 7.4 SOURCE OF MODERN CONTRACEPTIVE METHODS Information on where women obtain their contraceptive methods is important for family planning programme managers and implementers. Interviewers asked women who reported using a modern method of contraception at the time of the survey where they had obtained the method. The results are shown in Table 7.4. Table 7.4 Source of modern contraception methods Percent distribution of users of modern contraceptive methods age 15-49 by most recent source of method, according to method, Ethiopia 2011 Source Pill Injectables Implants Male condom Total Public sector 67.2 85.6 92.3 11.7 82.0 Government hospital 4.6 1.8 3.7 1.8 2.3 Government health centre 39.4 48.0 59.4 7.9 47.3 Government health station/clinic 4.3 5.1 4.3 0.6 4.7 Government health post/HEW 18.9 30.5 22.4 1.4 27.3 Other public 0.0 0.1 2.6 0.0 0.4 Private medical sector 30.2 13.1 3.5 29.6 13.4 Private hospital 0.2 0.5 1.0 0.0 0.6 Private clinic 11.8 10.7 0.8 2.3 9.2 Pharmacy 13.9 0.4 0.0 27.3 1.8 NGO health facility 4.2 1.2 1.7 0.0 1.6 Voluntary community health workers 0.0 0.3 0.0 0.0 0.2 Other source 2.4 0.3 0.1 57.8 1.3 Drug vendor/store 1.8 0.2 0.0 5.7 0.3 Shop 0.6 0.1 0.0 51.4 0.9 Friend/relative 0.1 0.0 0.1 0.7 0.0 Other 0.0 0.2 0.0 0.9 0.1 Missing 0.2 0.8 4.0 0.0 3.2 Total 100.0 100.0 100.0 100.0 100.0 Weighted number of women 245 2,317 381 48 3,086 Unweighted number of women 301 1,962 326 107 2,794 Note: Total includes other modern methods but excludes lactational amenorrhea method (LAM) and standard days method. HEW = Health Extension Worker Table 7.4 shows that the public sector is the major source of modern contraceptive methods in Ethiopia, serving 82 percent of users. By comparison, 13 percent of current users reported that their modern method of contraceptive was obtained from the private sector. Forty-seven percent of users obtained contraceptive methods from a government health centre, and 27 percent, from a government health post or Health Extension Worker (HEW). 7.5 INFORMED CHOICE Informed choice is an important principle in the delivery of family planning services. As an aspect of informed choice, it is required that all family planning providers inform users about potential side effects of the method and what they should do if they encounter such side effects. This information assists the user in coping with side effects and thus decreases discontinuation of temporary methods. Contraceptive users should also be informed of the other methods available to them. Table 7.5 shows the percentage of current users of modern methods who reported that they were informed about side effects or problems of the method used and who reported that they were informed of other methods. These are broken down by method type, initial source, and background characteristics. Overall, 28 percent of current users of the pill, IUD, injectables, or implants were informed about potential side effects of their method, 24 percent were told what to do if they experienced side effects, and 37 percent were given information about other methods. 100 • Family Planning Table 7.5 Informed choice Among current users of selected modern methods age 15-49 who started the last episode of use within the five years preceding the survey, the percentage who were informed about possible side effects or problems of that method, the percentage who were informed about what to do if they experienced side effects, and the percentage who were informed about other methods they could use, by method and initial source, Ethiopia 2011 Method/source Among women who started last episode of modern contraceptive method within five years preceding the survey: Weighted number of women Unweighted number of women Percentage who were informed about side effects or problems of method used Percentage who were informed about what to do if side effects occur Percentage who were informed by a health or family planning worker of other methods that could be used Method Pill 35.3 28.9 48.4 223 276 IUD (65.7) (56.8) (46.0) 31 42 Injectables 23.9 19.8 34.1 2,127 1,786 Implants 44.4 44.6 48.1 365 315 Initial source of method1 Public sector 27.6 24.1 37.4 2,397 1,957 Government hospital 41.6 47.7 49.5 73 164 Government health centre 29.2 24.5 38.8 1,438 1,194 Government health station/clinic 33.4 28.0 30.8 154 120 Government health post/hew 22.2 20.3 35.4 722 477 Private medical sector 32.6 26.8 36.6 321 436 Private clinic 28.4 22.8 29.7 214 245 Pharmacy 14.8 22.2 20.6 38 62 NGO health facility 57.6 44.0 70.0 43 100 Total 28.1 24.4 37.1 2,769 2,438 Note: Table includes users of only the methods listed individually. Figures in parentheses are based on 25-49 unweighted cases. 1 Source at start of current episode of use 7.6 KNOWLEDGE OF THE FERTILE PERIOD A basic knowledge of the physiology of reproduction is especially useful for the successful practice of coitus-related method such as periodic abstinence. The successful use of such methods depends in a large part on understanding when during the ovulatory cycle a woman is most likely to conceive. All women in the survey were asked about their knowledge of women’s fertile period. Specifically, they were asked whether there are certain days between two menstrual periods when a woman is more likely to become pregnant if she has sexual intercourse. Those who answered in the affirmative were further asked if this time is just before the period begins, during the period, right after the period ends, or half way between the two periods. Results are shown in Table 7.6. Overall, only 18 percent of all women interviewed reported the correct timing of the fertile period, that is, halfway between the two menstrual periods. The percentage of women with knowledge of the correct timing of the fertile period has increased from 11 percent in the 2005 EDHS to 18 percent in 2011. To use the rhythm method effectively, correct knowledge of the fertile period is critical. Of those who use the rhythm method, 65 percent reported the correct timing of the fertile period. This proportion is only slightly higher than that reported in the 2005 EDHS (62 percent). Table 7.6 Knowledge of fertile period Percent distribution of women age 15-49 by knowledge of the fertile period during the ovulatory cycle, according to current use of the rhythm method, Ethiopia 2011 Perceived fertile period Users of rhythm method Nonusers of rhythm method All women Just before her menstrual period begins 4.3 4.2 4.2 During her menstrual period 1.3 3.6 3.6 Right after her menstrual period has ended 25.6 27.0 27.0 Halfway between two menstrual periods 65.1 17.5 17.8 Other 0.0 0.1 0.1 No specific time 0.7 20.9 20.7 Don't know 3.0 26.6 26.5 Total 100.0 100.0 100.0 Weighted number of women 107 16,408 16,515 Unweighted number of women 129 16,386 16,515 Family Planning • 101 7.7 NEED AND DEMAND FOR FAMILY PLANNING Women who say they are not using contraception and who say either that they do not want any more children or that they want to wait two or more years before having another child are considered to have an unmet need for family planning. Conversely, women using a family planning method are said to have a met need for family planning. Both unmet need and met need can be categorized as such based on whether the need is for spacing or limiting births. The combination of women with unmet need and women with met need for family planning constitutes the total demand for family planning. Table 7.7 presents estimates for unmet need, met need, and total demand for family planning among currently married Ethiopian women, by background characteristics. Twenty-five percent of currently married women have an unmet need for family planning—16 percent for spacing and 9 percent for limiting. Almost one in every three Ethiopian women (29 percent) has a met need for family planning—16 percent for spacing and 12 percent for limiting. The total demand for family planning among currently married women is 54 percent, A little more than half (53 percent) of this demand is satisfied. Of the total demand for family planning, the demand for spacing is one and a half times as great as the demand for limiting (33 and 21 percent, respectively). Table 7.7 Need and demand for family planning among currently married women Percentage of currently married women age 15-49 with unmet need for family planning, percentage with met need for family planning, the total demand for family planning, and the percentage of the demand for contraception that is satisfied, by background characteristics, Ethiopia 2011 Background characteristic Unmet need for family planning1 Met need for family planning (currently using)2 Total demand for family planning Percentage of demand satisfied Percentage of demand satisfied by modern methods Weighted number of women Un- weighted number of women For spacing For limiting Total For spacing For limiting Total For spacing For limiting Total Age 15-19 30.3 2.4 32.8 22.5 1.2 23.8 52.9 3.6 56.5 42.0 40.6 765 784 20-24 20.3 1.5 21.8 29.6 5.3 34.8 49.8 6.8 56.6 61.6 59.0 1,762 1,788 25-29 21.5 5.1 26.6 20.6 9.3 29.9 42.1 14.4 56.5 53.0 51.1 2,511 2,480 30-34 15.8 9.8 25.6 16.1 16.9 33.1 31.9 26.8 58.7 56.4 53.1 1,720 1,722 35-39 11.6 15.8 27.4 9.3 19.8 29.1 20.9 35.6 56.4 51.5 49.6 1,591 1,600 40-44 7.8 19.9 27.7 3.5 20.5 23.9 11.2 40.4 51.6 46.4 42.9 1,033 1,047 45-49 1.5 13.7 15.2 1.4 11.7 13.1 3.0 25.3 28.3 46.3 44.3 905 783 Residence Urban 8.1 6.9 15.0 31.3 21.2 52.5 39.4 28.1 67.5 77.8 73.3 1,843 2,422 Rural 18.1 9.4 27.5 13.1 10.3 23.4 31.2 19.7 50.9 46.0 44.2 8,444 7,782 Region Tigray 15.0 7.0 22.0 15.1 7.1 22.2 30.1 14.1 44.2 50.3 48.0 620 984 Affar 12.4 3.7 16.0 6.9 2.6 9.5 19.2 6.3 25.5 37.2 35.5 104 960 Amhara 12.4 9.7 22.1 19.4 14.5 33.9 31.8 24.2 56.0 60.6 58.9 2,776 1,331 Oromiya 20.7 9.2 29.9 15.2 11.0 26.2 35.9 20.2 56.1 46.7 44.4 3,961 1,403 Somali 20.9 3.1 24.0 3.3 1.0 4.3 24.2 4.1 28.3 15.3 13.5 232 664 Benishangul- Gumuz 15.3 9.2 24.5 16.3 10.7 27.0 31.6 19.9 51.5 52.5 51.1 124 904 SNNP 15.2 9.8 25.0 12.7 13.1 25.8 27.9 22.9 50.8 50.9 48.6 2,022 1,295 Gambela 12.9 5.8 18.8 21.4 12.3 33.8 34.4 18.2 52.6 64.3 63.1 41 768 Harari 14.8 9.3 24.1 20.4 14.3 34.7 35.2 23.6 58.8 59.0 53.5 28 635 Addis Ababa 5.3 5.3 10.6 39.8 22.7 62.5 45.1 28.0 73.1 85.5 77.1 342 634 Dire Dawa 16.4 5.0 21.3 21.0 12.9 33.9 37.3 17.9 55.2 61.4 57.4 38 626 Education No education 16.3 10.0 26.3 10.8 11.4 22.2 27.1 21.4 48.4 45.8 45.0 6,735 6,569 Primary 18.5 8.2 26.7 22.3 13.4 35.7 40.8 21.5 62.3 57.2 54.1 2,862 2,739 Secondary 9.7 3.0 12.7 42.0 15.6 57.6 51.7 18.5 70.2 82.0 76.1 378 528 More than secondary 5.5 1.5 7.0 51.0 16.8 67.8 56.5 18.3 74.8 90.6 76.5 313 368 Wealth quintile Lowest 19.6 10.9 30.5 7.2 6.1 13.3 26.8 17.0 43.8 30.4 29.6 2,077 2,724 Second 17.6 8.9 26.5 10.9 11.2 22.2 28.5 20.2 48.7 45.5 44.2 2,117 1,676 Middle 17.8 10.3 28.1 13.0 11.3 24.4 30.8 21.6 52.4 46.4 45.8 2,083 1,585 Fourth 18.5 8.3 26.8 18.3 13.5 31.7 36.8 21.7 58.5 54.2 51.7 1,923 1,590 Highest 8.3 6.4 14.7 32.5 19.2 51.8 40.9 25.6 66.5 77.9 72.5 2,087 2,629 Total 16.3 9.0 25.3 16.4 12.2 28.6 32.7 21.2 53.9 53.1 50.7 10,287 10,204 1 Unmet need for spacing: Includes women who are fecund and not using family planning and who say they want to wait two or more years for their next birth, or who say they are unsure whether they want another child, or who want another child but are unsure when to have the child. In addition, unmet need for spacing includes pregnant women whose current pregnancy was mistimed, or whose last pregnancy was unwanted but who now say they want more children. Unmet need for spacing also includes amenorrheic women whose last birth was mistimed, or whose last birth was unwanted but who now say they want more children. Unmet need for limiting: Includes women who are fecund and not using family planning and who say they do not want another child. In addition, unmet need for limiting includes pregnant women whose current pregnancy was unwanted but who now say they do not want more children or who are undecided whether they want another child. Unmet need for limiting also includes amenorrheic women whose last birth was unwanted but who now say they do not want more children or who are undecided whether they want another child. 2 Using for spacing is defined as women who are using some method of family planning and say they want to have another child or are undecided whether to have another. Using for limiting is defined as women who are using and who want no more children. Note that the specific methods used are not taken into account here. 102 • Family Planning The total unmet need for family planning does not vary much by women’s 5-year age groups from ages 15 to 44. However, the proportion of women with unmet need is lowest (15 percent) for those in the oldest age group. When unmet need is categorized by unmet need for spacing or limiting, an interesting age pattern is presented. Women younger than 35 years have a higher unmet need for spacing, while older women age 35 or older have a higher unmet need for limiting. Unmet need is almost twice as high among rural women as among urban women (28 percent versus 15 percent). Women with no education (16 percent) or primary education (19 percent) are much more likely to have an unmet need for spacing than those with secondary or higher education (10 and 6 percent, respectively). Unmet need is lowest among women in the wealthiest households. The share of unmet need for spacing is much higher than the one for limiting in all regions except in Addis Ababa, where they are the same. The unmet need for contraception is highest in the Oromiya region (30 percent) and lowest in Addis Ababa (11 percent). 7.8 FUTURE USE OF CONTRACEPTION Future demand for specific methods of family planning can be assessed by asking nonusers who intend to use contraception in the future which methods they prefer to use. Table 7.8 presents the results. More than half (56 percent) of currently married female nonusers intend to use family planning in the future, while 41 percent do not. The proportion of women intending to use contraception increases from 52 percent for those with no child to peak at 65 percent for those with one child and declines subsequently to 50 percent for those with four or more children. The data reflect a gradual increase in the percentage of currently married female nonusers who intend to use family planning in the future, from 46 percent in 2000 to 52 percent in 2005 and now to 56 percent in 2011. Table 7.8 Future use of contraception Percent distribution of currently married women age 15-49 who are not using a contraceptive method by intention to use in the future, according to number of living children, Ethiopia 2011 Intention to use in the future Number of living children1 Total 0 1 2 3 4+ Intends to use 51.8 65.2 62.6 60.2 50.2 55.7 Unsure 2.8 1.9 4.4 3.0 2.8 3.0 Does not intend to use 45.3 32.8 32.5 36.5 46.8 41.1 Missing 0.0 0.2 0.4 0.3 0.3 0.3 Total 100.0 100.0 100.0 100.0 100.0 100.0 Weighted number of women 568 978 1,131 1,066 3,601 7,344 Unweighted number of women 641 1,092 1,191 1,078 3,587 7,589 1 Includes current pregnancy 7.9 EXPOSURE TO FAMILY PLANNING MESSAGES The mass media and interpersonal communication can be major sources of family planning messages. Information about public exposure to messages through a particular medium allows policymakers to ensure the use of the most effective means of communication for various target groups in the population. To assess the effectiveness of the dissemination of family planning information through different media, interviewers asked respondents in the 2011 EDHS whether they had been exposed to any family planning messages in the past few months preceding the survey. Interviewers asked about family planning messages on the radio or television; in a newspaper, Family Planning • 103 magazine, pamphlet, poster, or leaflet; at a community event, and from a doctor, nurse, or other health worker. Table 7.9 presents the findings. Among women age 15-49 community events are the most common source of family planning messages, at 37 percent. Radio is the second most common at 34 percent. Another common source is television, with 18 percent of women reporting exposure to family planning messages via television. Ethiopian women do not have high exposure to written sources of family planning messages. Only 8 percent of women report seeing family planning messages in a newspaper or magazine or in a pamphlet, poster, or leaflet. In general, a higher proportion of Ethiopian men are exposed to family planning messages than women. As for women the most common sources of family planning messages for men age 15-49 are the radio or community events (51 and 44 percent, respectively). Twenty-five percent of men report exposure to family planning messages on television, while 18 percent report exposure to messages from a pamphlet, poster, or leaflet. The least common source of family planning messages for men is a newspaper or magazine, at 15 percent. Among women, there is a slight variation in exposure to printed family planning messages by their background characteristics. Women in the two lowest age categories, age 15-24, have higher levels of exposure to family planning messages in a newspaper or magazine or in pamphlets, posters, or leaflets than women in upper categories. A higher proportion of urban women than rural women are exposed to messages from each source. Especially pronounced gaps between urban and rural women are observed in their exposure to family planning messages on television (55 and 7 percent, respectively), in a newspaper or magazine (21 and 4 percent, respectively), and in a pamphlet, poster, or leaflet (23 and 3 percent, respectively). Similar urban-rural variations in exposure to printed family planning messages are observed among men. Urban women are more exposed to family planning messages at community events than rural women (40 and 36 percent, respectively), whereas rural men are more exposed than urban men (45 and 42 percent, respectively) to these messages. Regional differentials also suggest that women and men in relatively urbanized areas, namely Addis Ababa, Dire Dawa, and Harari, are more likely than other respondents to be exposed to family planning messages from all specified media sources. Exposure to family planning messages at community events is the exception to this pattern. Women in Tigray and Amhara are more likely to be exposed to family planning messages at community events (65 percent and 46 percent, respectively) than women from other regions including the more urbanized areas. There is a marked difference by women’s level of education in exposure to family planning messages from all media sources; 72 percent of women with more than secondary education are exposed to family planning messages through the television, whereas only 6 percent of women with no education are. Similar patterns are true for men. Both female and male respondents in the lowest wealth quintile are the least likely to be exposed to family planning messages through any of the specified sources when compared with respondents in higher quintiles. 10 4 • F am ily P la nn in g Ta bl e 7. 9 E xp os ur e to fa m ily p la nn in g m es sa ge s P er ce nt ag e of w om en a nd m en a ge 1 5- 49 w ho h ea rd o r sa w a fa m ily p la nn in g m es sa ge o n ra di o; o n te le vi si on ; i n a ne w sp ap er ; i n a pa m ph le t, po st er , o r le af le t; or a t a c om m un ity e ve nt in th e pa st fe w m on th s, a cc or di ng to 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 W om en M en R ad io Te le vi si on N ew sp ap er / m ag az in e P am ph le t/ po st er / le af le t C om m un ity ev en t N on e of th es e fiv e m ed ia so ur ce s W ei gh te d nu m be r o f w om en U nw ei gh te d nu m be r o f w om en R ad io Te le vi si on N ew sp ap er / m ag az in e P am ph le t/ po st er / le af le t C om m un ity ev en t N on e of th es e fiv e m ed ia so ur ce s W ei gh te d nu m be r o f m en U nw ei gh te d nu m be r o f m en A ge 15 -1 9 34 .8 18 .4 12 .7 10 .3 31 .8 42 .6 4, 00 9 3, 83 5 40 .3 21 .1 12 .6 14 .3 28 .2 39 .7 3, 01 3 2, 83 2 20 -2 4 37 .6 24 .4 11 .3 13 .3 33 .7 40 .7 2, 93 1 3, 02 2 53 .7 27 .0 17 .2 22 .2 42 .6 28 .2 2, 31 9 2, 33 0 25 -2 9 34 .5 18 .7 6. 2 6. 2 37 .7 42 .9 3, 14 7 3, 18 5 54 .1 25 .5 19 .6 21 .2 46 .4 26 .7 2, 29 7 2, 27 4 30 -3 4 32 .2 15 .7 5. 7 5. 4 40 .9 44 .3 2, 05 4 2, 10 0 55 .8 29 .6 14 .9 19 .8 51 .2 23 .4 1, 48 3 1, 68 2 35 -3 9 31 .9 15 .5 4. 7 5. 0 42 .1 42 .8 1, 91 6 1, 95 8 52 .3 25 .2 14 .4 17 .7 51 .9 25 .3 1, 64 8 1, 57 9 40 -4 4 32 .0 15 .5 3. 7 4. 8 40 .9 42 .9 1, 26 1 1, 31 4 54 .0 25 .9 13 .4 14 .8 54 .6 24 .4 1, 12 1 1, 21 0 45 -4 9 26 .2 11 .5 2. 0 3. 8 37 .1 50 .2 1, 19 6 1, 10 1 51 .2 22 .7 10 .7 13 .1 57 .7 25 .4 95 2 96 1 R es id en ce U rb an 57 .3 55 .1 21 .2 22 .7 39 .8 20 .1 3, 94 7 5, 32 9 65 .8 62 .6 29 .2 40 .0 41 .5 13 .0 2, 88 2 3, 91 5 R ur al 26 .3 6. 5 3. 8 3. 3 35 .7 50 .4 12 ,5 68 11 ,1 86 46 .1 14 .1 11 .0 11 .6 45 .0 33 .8 9, 95 2 8, 95 3 R eg io n Ti gr ay 34 .2 22 .6 11 .9 12 .4 64 .9 23 .2 1, 10 4 1, 72 8 42 .1 29 .7 19 .6 20 .3 40 .9 32 .5 77 0 1, 23 5 A ffa r 21 .8 19 .2 6. 9 6. 0 10 .7 69 .7 14 5 1, 29 1 54 .9 40 .4 21 .7 21 .5 26 .7 35 .2 10 1 91 0 A m ha ra 28 .8 14 .0 6. 9 5. 9 46 .4 40 .2 4, 43 3 2, 08 7 40 .7 18 .8 13 .5 18 .0 51 .3 32 .0 3, 48 1 1, 73 9 O ro m iy a 37 .4 14 .0 6. 6 5. 6 27 .2 48 .9 6, 01 1 2, 13 5 59 .4 22 .5 14 .0 11 .8 42 .4 27 .9 4, 95 7 1, 88 9 S om al i 21 .5 11 .2 4. 2 2. 9 31 .6 55 .6 32 9 91 4 41 .8 18 .9 11 .3 14 .5 16 .9 48 .6 24 5 65 3 B en is ha ng ul -G um uz 25 .9 13 .0 6. 3 5. 2 33 .6 52 .1 17 4 1, 25 9 53 .1 26 .8 11 .4 17 .2 40 .6 33 .4 13 8 1, 04 7 S N N P 26 .0 14 .8 5. 7 7. 7 36 .6 49 .2 3, 23 6 2, 03 4 40 .1 21 .4 11 .8 21 .3 48 .6 31 .4 2, 30 7 1, 55 0 G am be la 26 .6 27 .9 9. 6 11 .7 26 .9 52 .1 69 1, 13 0 51 .8 46 .4 27 .9 41 .6 38 .0 26 .9 59 86 5 H ar ar i 51 .1 57 .5 18 .2 19 .5 25 .4 30 .4 49 1, 10 1 75 .0 67 .6 32 .9 31 .9 45 .9 11 .3 40 89 8 A dd is A ba ba 67 .3 71 .2 25 .5 29 .7 25 .5 11 .8 89 6 1, 74 1 80 .0 74 .5 34 .6 44 .6 23 .3 6. 4 68 2 1, 23 7 D ire D aw a 50 .1 53 .8 23 .3 25 .9 40 .2 28 .5 69 1, 09 5 72 .8 64 .9 37 .0 52 .7 57 .2 9. 2 53 84 5 Ed uc at io n N o ed uc at io n 22 .0 6. 1 0. 3 0. 5 34 .6 53 .6 8, 39 4 8, 27 8 36 .7 9. 1 2. 5 3. 6 44 .9 40 .1 3, 78 5 3, 65 9 P rim ar y 38 .2 21 .1 9. 7 8. 9 36 .5 38 .4 6, 27 6 5, 85 8 51 .3 21 .9 13 .5 15 .6 42 .5 29 .4 6, 81 3 6, 33 4 S ec on da ry 66 .7 56 .7 31 .5 32 .8 46 .2 14 .6 1, 11 7 1, 39 5 70 .0 56 .8 35 .4 41 .8 45 .1 12 .3 1, 29 6 1, 56 5 M or e th an s ec on da ry 79 .4 71 .8 44 .8 48 .0 47 .7 6. 3 72 8 98 4 73 .5 68 .0 49 .9 60 .3 52 .7 6. 7 94 0 1, 31 0 W ea lth q ui nt ile Lo w es t 15 .1 3. 5 2. 2 1. 2 35 .3 56 .6 2, 98 6 3, 71 1 34 .5 9. 4 5. 3 6. 6 41 .5 43 .3 2, 14 1 2, 56 3 S ec on d 21 .5 4. 3 2. 7 2. 0 37 .5 51 .7 3, 04 1 2, 40 2 40 .9 9. 9 6. 4 7. 9 44 .6 38 .1 2, 36 2 1, 89 1 M id dl e 26 .1 6. 1 3. 1 3. 2 34 .5 51 .8 3, 03 1 2, 26 8 48 .3 12 .2 10 .3 10 .8 46 .0 32 .7 2, 45 4 1, 93 5 Fo ur th 37 .0 7. 9 6. 1 4. 3 34 .7 45 .1 3, 21 5 2, 50 5 54 .8 19 .9 17 .9 14 .9 45 .9 26 .5 2, 68 3 2, 20 3 H ig he st 58 .6 54 .7 20 .6 23 .1 40 .2 19 .8 4, 24 2 5, 62 9 66 .6 60 .8 29 .5 41 .1 43 .1 12 .7 3, 19 4 4, 27 6 To ta l 1 5- 49 33 .7 18 .1 7. 9 8. 0 36 .7 43 .1 16 ,5 15 16 ,5 15 50 .5 25 .0 15 .1 18 .0 44 .2 29 .2 12 ,8 34 12 ,8 68 50 -5 9 na na na na na na na na 45 .7 21 .1 9. 9 10 .7 53 .5 29 .3 1, 27 6 1, 24 2 To ta l 1 5- 59 na na na na na na na na 50 .1 24 .7 14 .6 17 .3 45 .1 29 .2 14 ,1 10 14 ,1 10 na = N ot a pp lic ab le 104 • Family Planning Family Planning • 105 7.10 EXPOSURE TO SPECIFIC TYPE OF FAMILY PLANNING MESSAGES Respondents in the 2011 EDHS were asked if they had heard or seen specific family planning or health messages in the past few months. Table 7.10 shows the percent distribution of women and men age 15-49 who heard or saw specific messages, by background characteristics. The most common message reported by women is ‘Birth spacing makes for a loving, caring, and healthy family’, with 44 percent women reporting having seen or heard this specific message. Thirty-two percent of women reported having heard or seen ‘It is wise to have a balanced family life’ or ‘Your family’s happiness is in your hand’. ‘Children by choice, not by chance’ was the message least seen or heard by women, at 26 percent. In general, Ethiopian men have higher exposure levels to each specific message than women. Women age 45-49 and men age 15-19 have the lowest levels of exposure to all of the specified messages, while women age 20-24 and men age 30-34 have the highest exposure levels. Urban respondents, those with higher education, and those in the richest wealth quintiles are the more likely to have been exposed to specific family planning messages than those in rural areas, respondents with little or no education, and poorer respondents, respectively. The regional differentials also show that women and men in more urbanized regions such as Addis Ababa, Dire Dawa, and Harari are more likely than respondents in more rural regions to be exposed to specific family planning messages. 106 • Family Planning Table 7.10 Exposure to specific family planning messages Percentage of all women and all men who have heard or seen specific media messages about family planning and health, in the past few months, according to background characteristics, Ethiopia 2011 Background characteristic Women Men It's wise to have a balanced family life Your family’s happiness is in your hands Birth spacing makes for a loving, caring, and healthy family Children by choice, not by chance Weighted number of women Unweighted number of women It's wise to have a balanced family life Your family’s happiness is in your hands Birth spacing makes for a loving, caring and healthy family Children by choice, not by chance Weighted number of men Unweighted number of men Age 15-19 33.6 33.6 45.9 26.4 4,009 3,835 40.0 37.9 51.1 29.6 3,013 2,832 20-24 37.5 38.2 50.8 31.3 2,931 3,022 53.9 52.8 65.2 42.9 2,319 2,330 25-29 32.3 32.9 44.8 25.9 3,147 3,185 52.9 55.3 67.8 47.5 2,297 2,274 30-34 30.8 31.7 41.8 26.1 2,054 2,100 56.0 56.7 71.3 48.6 1,483 1,682 35-39 31.6 31.3 42.2 25.7 1,916 1,958 55.4 52.3 67.0 43.7 1,648 1,579 40-44 27.2 28.6 37.3 20.4 1,261 1,314 52.7 53.7 67.9 44.3 1,121 1,210 45-49 20.9 19.6 31.9 15.6 1,196 1,101 50.6 51.6 63.8 40.0 952 961 Residence Urban 64.2 66.0 70.9 53.0 3,947 5,329 76.6 76.4 82.1 59.2 2,882 3,915 Rural 21.9 21.8 35.5 17.3 12,568 11,186 43.0 42.5 58.0 36.1 9,952 8,953 Region Tigray 36.9 35.9 46.0 32.4 1,104 1,728 48.0 47.8 61.0 52.9 770 1,235 Affar 23.3 23.0 27.6 17.9 145 1,291 46.9 52.8 45.6 36.0 101 910 Amhara 31.2 26.0 45.0 20.2 4,433 2,087 46.6 36.4 57.3 27.7 3,481 1,739 Oromiya 28.3 30.7 46.8 27.2 6,011 2,135 50.1 56.2 66.9 51.4 4,957 1,889 Somali 21.6 22.0 22.2 12.0 329 914 41.3 42.8 44.8 23.4 245 653 Benishangul- Gumuz 27.4 29.6 39.8 19.3 174 1,259 55.1 57.3 64.7 39.0 138 1,047 SNNP 24.6 29.3 28.4 18.3 3,236 2,034 47.2 46.5 62.2 31.9 2,307 1,550 Gambela 28.3 36.0 35.8 24.3 69 1,130 55.5 66.2 68.3 50.7 59 865 Harari 59.1 66.6 60.3 51.7 49 1,101 77.1 89.4 91.9 72.8 40 898 Addis Ababa 84.2 83.8 82.7 67.5 896 1,741 86.9 85.1 80.2 57.6 682 1,237 Dire Dawa 67.8 66.5 70.4 58.3 69 1,095 79.9 83.3 89.1 74.6 53 845 Education No education 18.3 17.4 30.0 13.5 8,394 8,278 36.0 32.0 50.1 25.0 3,785 3,659 Primary 36.8 38.8 51.2 29.9 6,276 5,858 49.3 49.6 63.5 40.7 6,813 6,334 Secondary 73.1 72.5 78.9 60.6 1,117 1,395 76.0 78.0 83.5 63.0 1,296 1,565 More than secondary 86.8 89.3 88.9 79.2 728 984 83.3 88.5 88.3 80.9 940 1,310 Wealth quintile Lowest 14.1 13.5 26.7 10.5 2,986 3,711 36.2 31.5 48.7 25.7 2,141 2,563 Second 19.4 19.1 31.9 14.2 3,041 2,402 38.4 36.5 54.4 31.5 2,362 1,891 Middle 21.6 20.3 37.0 16.5 3,031 2,268 41.7 41.9 59.2 37.3 2,454 1,935 Fourth 27.5 28.5 42.1 22.6 3,215 2,505 50.9 52.6 65.3 43.4 2,683 2,203 Highest 64.7 66.8 71.2 54.0 4,242 5,629 75.7 77.0 81.6 60.3 3,194 4,276 Total 15-49 32.0 32.4 44.0 25.8 16,515 16,515 50.5 50.1 63.4 41.3 12,834 12,868 50-59 na na na na na na 47.3 43.4 58.3 34.5 1,276 1,242 Total 15-59 na na na na na na 50.2 49.5 62.9 40.7 14,110 14,110 na = Not applicable 7.11 CONTACT OF NONUSERS WITH FAMILY PLANNING PROVIDERS Interviewers asked women who were not using any contraception at the time of the survey whether a family planning worker had visited and talked to them in the past 12 months. Interviewers also asked whether they had attended a health facility during the past year and, if so, whether a staff person at that facility spoke to them about family planning methods. This information, presented in Table 7.11, is important for determining whether family planning initiatives in Ethiopia are reaching nonusers of family planning. Only 15 percent of nonusers reported being visited by a health services provider at home who engaged them in a discussion of family planning. Among female nonusers 22 percent had visited a health facility in the past 12 months but did not discuss family planning with a provider, while 7 percent did discuss family planning. The majority of women who are nonusers (81 percent) neither discussed family planning with a fieldworker nor discussed family planning at a health facility. Family Planning • 107 An interesting age pattern is observed for women who were visited by a fieldworker who discussed family planning, as well as for those women who visited a health facility in the past 12 months and discussed family planning. For both groups of women, the percentage that discussed family planning is lowest in the youngest age cohort, age 15-19, but steadily increases and peaks in the 35-39 age cohort before declining in the oldest age groups. For example, only 10 percent of women age 15-19 reported being visited by a fieldworker who discussed family planning, compared with 22 percent of those age 35-39. The percentage of nonusers who were visited by a fieldworker and who discussed family planning varies notably by region. The highest percentage is in Tigray (28 percent) and the lowest percentages are observed in Somali (7 percent), Affar (8 percent), and Gambela (9 percent). Table 7.11 Contact of nonusers with family planning providers Among women age 15-49 who are not using contraception, the percentage who during the past 12 months were visited by a fieldworker who discussed family planning, the percentage who visited a health facility and discussed family planning, the percentage who visited a health facility but did not discuss family planning, and the percentage who did not discuss family planning either with a fieldworker or at a health facility, by background characteristics, Ethiopia 2011 Background characteristic Percentage of women who were visited by a fieldworker who discussed family planning Percentage of women who visited a health facility in the past 12 months and who: Percentage of women who did not discuss family planning either with a fieldworker or at a health facility Weighted number of women Unweighted number of women Discussed family planning Did not discuss family planning Age 15-19 9.6 2.6 13.1 88.6 3,795 3,611 20-24 14.0 6.6 26.0 82.2 2,247 2,380 25-29 16.8 9.3 26.7 78.2 2,312 2,398 30-34 16.7 8.0 24.9 79.7 1,451 1,576 35-39 22.3 13.0 25.9 72.7 1,404 1,485 40-44 21.1 9.0 22.3 74.7 1,005 1,095 45-49 16.5 5.4 19.6 81.0 1,066 1,009 Residence Urban 14.3 9.3 28.6 80.4 2,877 3,956 Rural 15.4 6.2 19.6 81.7 10,404 9,598 Region Tigray 28.1 20.6 23.6 64.4 925 1,450 Affar 7.8 2.3 23.3 91.2 133 1,217 Amhara 18.8 7.3 17.8 77.5 3,404 1,615 Oromiya 12.7 5.4 22.1 84.4 4,895 1,738 Somali 6.9 2.1 17.0 92.0 318 883 Benishangul-Gumuz 16.1 4.9 27.8 81.8 138 1,026 SNNP 12.8 4.5 20.9 84.6 2,679 1,702 Gambela 9.1 6.0 32.8 87.8 46 897 Harari 13.4 5.6 26.5 82.7 38 856 Addis Ababa 11.1 9.0 35.0 82.8 650 1,285 Dire Dawa 19.3 8.7 29.3 76.9 54 885 Education No education 15.8 7.0 21.1 80.8 6,789 7,050 Primary 13.9 5.7 20.3 83.2 5,132 4,734 Secondary 16.3 8.3 30.1 79.5 875 1,059 More than secondary 16.7 14.9 23.6 73.5 485 711 Wealth quintile Lowest 13.3 5.1 17.4 83.9 2,674 3,463 Second 15.4 5.8 19.2 82.0 2,530 2,065 Middle 14.7 5.5 19.3 82.6 2,482 1,899 Fourth 17.8 6.6 22.6 79.2 2,542 1,998 Highest 14.7 10.6 27.9 79.5 3,054 4,129 Total 15.2 6.9 21.5 81.4 13,281 13,554 108 • Family Planning 7.12 CONTRACEPTIVE DISCONTINUATION RATE Table 7.12 shows, among women age 15-49 who started an episode of contraceptive use within the five-year period preceding the survey, the percentage of episodes discontinued within 12 months, by specific method. The 12-month contraceptive discontinuation rate for all methods is 37 percent. Among the major methods, the highest discontinuation rate is for the pill (70 percent), followed by the male condom (62 percent). In contrast, implants have a discontinuation rate of just 5 percent. Table 7.12 Contraceptive discontinuation rates Among women age 15-49 who started an episode of contraceptive use within the five years preceding the survey, the percentage of episodes discontinued within 12 months, by specific method, Ethiopia, 2011 Method Percentage who discontinued within 12 months Pill 69.9 Injectables 34.2 Implants 4.5 Male condom 62.4 Rhythm 23.6 All methods1 37.1 Number of episodes of use 1,790 Note: Figures are based on life table calculations using information on episodes of use that began 3-62 months prior to the survey. 1 All methods are included in the discontinuation rate shown for all methods, but only selected methods are shown separately. Infant and Child Mortality • 109 INFANT AND CHILD MORTALITY 8 his chapter presents levels, trends, and differentials in perinatal, neonatal, postneonatal, infant, child, and under-five mortality in Ethiopia. The information enhances understanding of population dynamics and will assist in the planning and evaluation of health policies and programmes. Estimates of infant and child mortality rates can be used to develop population projections. Information on childhood mortality also serves the need of the health sector to identify population groups that are at high risk. One of the targets of the Millennium Development Goals (MDGs) is to reduce the under-five mortality rate by two-thirds between 1990 and 2015. Programmes to increase the proportion of births attended by skilled health personnel, to increase immunisations against the vaccine-preventable diseases, to provide early care and treatment to sick children, and to upgrade the status of women through education and enhanced participation in the labour force can all help to improve the probability of survival of young children. Results from the 2011 EDHS are timely in evaluating the impact on the achievement of this MDG goal of some major national policies, such as the National Population Policy, the National Policy on Ethiopian Women, and the National Health Policy. The data used for mortality estimation were collected in the birth history section of the Woman’s Questionnaire. The birth history section begins with questions about the respondent’s experience with childbearing (i.e., the number of sons and daughters living with the mother, the number who live elsewhere, and the number who have died). These questions are followed by a retrospective birth history, in which each respondent is asked to list each of her births, starting with the first birth. For each birth, data were obtained on sex, month and year of birth, survivorship status, and current age, or, if the child is dead, age at death. This information is used to directly estimate mortality rates. In this report age-specific mortality rates are categorised and defined as follows: • Neonatal mortality (NN): the probability of dying within the first month of life • Postneonatal mortality (PNN): the probability of dying after the first month of life but before the first birthday (the difference between infant and neonatal mortality) • Infant mortality (1q0): the probability of dying before the first birthday • Child mortality (4q1): the probability of dying between the first and the fifth birthdays T Key Findings • One in every 17 Ethiopian children dies before the first birthday, and one in every 11 children dies before the fifth birthday. • Infant mortality declined by 39 percent over the 15-year period between the 2000 EDHS and the 2011 EDHS, from 97 deaths per 1,000 live births to 59 deaths per 1,000 live births. • Under-five mortality declined by 47 percent over the same period, from 166 deaths per 1,000 live births to 88 deaths per 1,000 live births. • Childhood mortality is higher in rural areas than in urban areas. These rates were highest in Benishangul-Gumuz and lowest in Addis Ababa. • The neonatal mortality rate was 37 deaths per 1,000 live births, the post-neonatal mortality rate was 22 deaths per 1,000 live births, and the perinatal mortality rate was 46 per 1,000 pregnancies. 110 • Infant and Child Mortality • Under-five mortality (5q0): the probability of dying between birth and the fifth birthday All rates are expressed per 1,000 live births except for child mortality, which is expressed per 1,000 children surviving to 12 months of age. 8.1 DATA QUALITY Estimates of infant and child mortality that are based on retrospective birth histories are subject to possible reporting errors that may adversely affect the quality of the data. The estimates may be affected by the completeness with which births and deaths are reported and recorded, as well as the accuracy of information on current age and the age at death for children who died. A lack of accurate information on the age at death may distort the age pattern of mortality. If age at death is misreported and the net effect of this age misreporting results in transference from one age bracket to another, it will bias the estimates. For example, a net transfer of deaths from an age of under 1 month to a higher age will affect the estimates of neonatal and postneonatal mortality. To minimise errors in reporting age at death, interviewers were instructed to record age at death in days if the death took place in the month following the birth, in months if the child died before 2 years of age, and in years if the child died at age 2 years or above. Interviewers were also asked to probe for deaths reported at 1 year of age to determine a more precise age at death in terms of months. Despite the emphasis during interviewer training and fieldwork monitoring on probing for accurate age at death, Appendix Table C.6 shows that, for the five years preceding the survey, there is considerable heaping of deaths at 6 and 12 months of age. However, only the heaping at 12 months of age can potentially bias the mortality rates reported in the tables in this chapter. Age heaping at 12 months to the extent shown in Appendix Table C.6 is likely to have only a negligible effect on the estimates of infant mortality, but it is likely to lead to some overestimation of child mortality, especially for the earlier five-year periods. Another potential data quality problem is the selective omission from the birth histories of births that did not survive, which can lead to underestimation of mortality rates. When selective omission of childhood deaths occurs, it is usually most severe for deaths occurring early in infancy. One way that such omissions can be detected is by examining the proportion of infant deaths that are neonatal deaths. Generally, if there is substantial underreporting of deaths, the result is an abnormally low ratio of neonatal deaths to infant deaths. In the 2011 EDHS the proportion of infant deaths occurring in the first month of life is 65 percent in the period 0-4 years preceding the survey (Appendix Table C.6), which is within the normal range. Furthermore, it appears that early neonatal deaths among births that occurred in the first month of life have not been underreported, since 79 percent of neonatal deaths were early neonatal deaths (Appendix Table C.5). The proportion is slightly lower for deaths occurring 15-19 years before the survey, which is not surprising given the greater likelihood of recall errors for deaths occurring further in the past. Displacement of birth dates may cause a distortion of mortality trends. This can occur if an interviewer knowingly records a death as occurring in an earlier year, which would happen if an interviewer is trying to cut down on the overall workload, because a lengthy set of additional questions is asked about live births occurring during the five years preceding the interview. Appendix Table C.4 shows considerable year-of-birth transference for deceased children from 1998 to 1997, but relatively little transference for living children. This suggests that under-five mortality is likely to be underestimated to some extent for the five-year period before the survey. Infant and Child Mortality • 111 8.2 LEVELS AND TRENDS IN INFANT AND CHILD MORTALITY 8.2.1 Early Childhood Mortality Rates Table 8.1 shows neonatal, postneonatal, infant, child, and under-five mortality rates for successive five-year periods before the survey. For the five years preceding the survey, the infant mortality rate was 59 per 1,000 live births, the child mortality rate was 31 per 1,000 children surviving to age 1 year, and the under-five mortality rate was 88 per 1,000 live births. This implies that one in 17 Ethiopian children dies before the first birthday and one in 11 Ethiopian children dies before the fifth birthday. During the same five-year period, neonatal mortality was 37 deaths per 1,000 live births, and postneonatal mortality was 22 deaths per 1,000 live births. Table 8.1 Early childhood mortality rates Neonatal, postneonatal, infant, child, and under-five mortality rates for five-year periods preceding the survey, Ethiopia 2011 Years preceding the survey Neonatal mortality (NN) Postneonatal mortality (PNN)1 Infant mortality (1q0) Child mortality (4q1) Under-five mortality (5q0) 0-4 37 22 59 31 88 5-9 48 40 88 49 133 10-14 54 47 101 72 166 1 Computed as the difference between the infant and neonatal mortality rates 8.2.2 Trends in Early Childhood Mortality Mortality trends can be examined in two ways: by comparing mortality rates for the three five-year periods preceding a single survey or by comparing mortality estimates obtained from several surveys over time. It should be noted that sampling errors associated with mortality estimates are large and should be taken into account when examining trends between surveys. Results from the 2011 EDHS data show a remarkable decline in all levels of childhood mortality. Infant mortality has declined by 42 percent over the 15-year period preceding the survey from 101 deaths per 1,000 live births to 59 deaths per 1,000 live births. Furthermore, under-five mortality has declined by 47 percent over the same period from 166 deaths per 1,000 live births to 88 deaths per 1,000 live births. Even though not to the same extent, the neonatal mortality has also decreased over the 15-year period preceding the survey by 31 percent from 54 deaths per 1,000 live births to 37 deaths per 1,000 live births. Mortality trends can also be examined by comparing data from DHS surveys conducted in 2000, 2005, and 2011. Infant and under-five mortality rates obtained by these surveys evidence a continuous declining trend in mortality. Under-five mortality decreased from 166 deaths per 1,000 live births in the 2000 survey to 88 in 2011, while infant mortality decreased from 97 deaths per 1,000 live births in the 2000 survey to 59 in the 2011 survey. On the other hand, even though neonatal mortality rate decreased from 49 deaths per 1,000 live births in 2000 to 39 deaths per 1,000 live births in 2005, it has since remained stable at 37 deaths per 1,000, as reported in the 2011 EDHS (Figure 8.1). 112 • Infant and Child Mortality Figure 8.1 Trends in Early Childhood Mortality, EDHS 2000, 2005, and 2011 49 48 97 77 166 39 38 77 50 123 37 22 59 31 88 Neonatal Postneonatal Infant Child Under-5 Mortality Rate 0 20 40 60 80 100 120 140 160 180 D ea t h s P er 1 ,0 00 2000 2005 2011 8.3 EARLY CHILDHOOD MORTALITY RATES BY SOCIOECONOMIC CHARACTERISTICS Mortality differences by place of residence, region, education of the mother, and household wealth are presented in Table 8.2. To have a sufficient number of births to study mortality differentials across population subgroups, mortality rates are presented for the 10-year period preceding the survey. The table shows that infant and child survival are strongly influenced by these socioeconomic characteristics. Mortality rates in urban areas are consistently lower than in rural areas, although the difference is quite small for neonatal mortality. Infant mortality is 29 percent higher in rural areas (76 deaths per 1,000 live births) than in urban areas (59 deaths per 1,000 live births). The urban-rural difference is even more pronounced in the case of under-five mortality. Wide regional differences in infant and under-five mortality are observed, as well. Under-five mortality rates range from a low of 53 per 1,000 live births in Addis Ababa to a high of 169 per 1,000 live births in Benishangul-Gumuz. Under-five mortality is also relatively high in Affar, Gambela, and Somali (Table 8.2 and Figure 8.2). Infant and Child Mortality • 113 Table 8.2 Early childhood mortality rates by socioeconomic characteristics Neonatal, postneonatal, infant, child, and under-five mortality rates for the 10-year period preceding the survey, by background characteristics, Ethiopia 2011 Background characteristic Neonatal mortality (NN) Postneonatal mortality (PNN)1 Infant mortality (1q0) Child mortality (4q1) Under-five mortality (5q0) Residence Urban 41 19 59 25 83 Rural 43 33 76 42 114 Region Tigray 44 20 64 23 85 Affar 33 30 64 67 127 Amhara 54 23 76 34 108 Oromiya 40 32 73 42 112 Somali 34 36 71 56 122 Benishangul-Gumuz 62 39 101 76 169 SNNP 38 41 78 41 116 Gambela 39 36 76 51 123 Harari 35 29 64 32 94 Addis Ababa 21 19 40 14 53 Dire Dawa 30 30 60 39 97 Mother's education No education 46 35 81 43 121 Primary 35 23 58 32 88 Secondary 31 12 42 4 46 More than secondary 8 14 22 2 24 Wealth quintile Lowest 50 41 91 51 137 Second 48 36 84 41 121 Middle 35 25 60 38 96 Fourth 39 27 66 36 100 Highest 37 23 60 27 86 1 Computed as the difference between the infant and neonatal mortality rates As expected, mother’s education is inversely related to a child’s risk of dying. Under-five mortality among children born to mothers with no education (121 per 1,000 live births) is 2.6 times as high as that of children born to mothers with secondary education (46 per 1,000 live births) and more than five times as high as that of mothers with more than a secondary education (24 per 1,000 live births). The beneficial effect of educating mothers is evident for all childhood mortality rates. Also, childhood mortality generally decreases as wealth increases, although the differences are relatively small in the three highest wealth quintiles. 114 • Infant and Child Mortality Figure 8.2 Under-Five Mortality by Socioeconomic Characteristics, Ethiopia 2011 83 114 85 127 108 112 122 169 116 123 94 53 97 121 88 46 24 137 121 96 100 86 Urban Rural Tigray Affar Amhara Oromiya Somali Benishangul-Gumuz SNNP Gambela Harari Addis Ababa Dire Dawa No education Primary Secondary More than secondary Lowest Second Middle Fourth Highest 0 20 40 60 80 100 120 140 160 180 8.4 DEMOGRAPHIC DIFFERENTIALS IN INFANT AND CHILD MORTALITY The demographic characteristics of both mothers and children have been found to play an important role in the survival of children. Table 8.3 presents childhood mortality rates by demographic characteristics (sex of the child, mother’s age at birth, birth order, previous birth interval, and the infant’s size at birth). Table 8.3 Early childhood mortality rates, by demographic characteristics Neonatal, postneonatal, infant, child, and under-five mortality rates for the 10-year period preceding the survey, by demographic characteristics, Ethiopia 2011 Demographic characteristic Neonatal mortality (NN) Postneonatal mortality (PNN)1 Infant mortality (1q0) Child mortality (4q1) Under-five mortality (5q0) Child's sex Male 51 34 84 41 122 Female 34 29 63 38 98 Mother's age at birth <20 61 35 96 33 126 20-29 37 32 69 38 105 30-39 43 27 70 46 113 40-49 42 25 67 33 97 Birth order 1 54 24 79 30 106 2-3 36 33 70 34 102 4-6 40 30 70 45 112 7+ 46 37 82 49 128 Previous birth interval2 <2 years 58 64 122 64 179 2 years 39 26 65 45 106 3 years 30 19 49 24 72 4+ years 24 13 37 17 53 Birth size3 Small/very small 33 17 50 na na Average or larger 37 23 61 na na na = Not applicable 1 Computed as the difference between the infant and neonatal mortality rates 2 Excludes first-order births 3 Rates for the five-year period before the survey Infant and Child Mortality • 115 As noted in earlier DHS surveys, male children in general experience a higher mortality than female children. This is true for all mortality rates. Infant mortality is higher for births to mothers under age 20 than for mothers in the older age groups. Infant mortality is also higher for first births and 7th and higher-order births than for births of orders 2-6. Short birth intervals substantially reduce children’s chances of survival, especially intervals of less than two years. For example, children born less than two years after the preceding birth are 2.5 times as likely to die within the first year of life and within the first five years of life as children born three years after the preceding birth (Figure 8.3). Since most births in Ethiopia occur at home, where children often are not weighed at birth, data on birth weight is available for only a few children. However, in the Ethiopia DHS survey, mothers were asked whether their children born in the past five years were very large, larger than average, average, smaller than average, or very small at birth, since this has been found to be a good proxy for the child’s weight. The data show little variation in mortality by size of child at birth. Figure 8.3 Under-Five Mortality Rate by Selected Demographic Characteristics, Ethiopia 2011 122 98 126 105 113 97 106 102 112 128 179 106 72 53 Child's sex Male Female Mother's age at birth <20 20-29 30-39 40-49 Birth order 1 2-3 4-6 7+ Previous birth interval <2 years 2 years 3 years 4+ years 0 50 100 150 200 8.5 PERINATAL MORTALITY The 2011 EDHS asked women to report any pregnancy loss that occurred in the five years preceding the survey. For each pregnancy that did not end in a live birth, the duration of the pregnancy was recorded. Pregnancy losses occurring after seven completed months of gestation (stillbirths) plus deaths to live births within the first seven days of life (early neonatal deaths) are defined as perinatal deaths. The distinction between a stillbirth and an early neonatal death may be a fine one, often depending on observing and sometimes remembering faint signs of life after delivery. The causes of stillbirths and early neonatal deaths are closely linked, and examining just one or the other can understate the true level of mortality around the time of delivery. The perinatal mortality rate is the sum of stillbirths and early neonatal deaths divided by the sum of stillbirths and live births, expressed per 1,000 pregnancies that lasted seven or more months. 116 • Infant and Child Mortality Table 8.4 presents the number of stillbirths and early neonatal deaths and the perinatal mortality rate for the five-year period preceding the survey, by background characteristics. Since the rates are subject to a high degree of sampling variation, differences by background characteristics should be interpreted with caution. The perinatal mortality rate is 46 per 1,000 pregnancies of seven or more months of gestation. The perinatal mortality rate is higher among births to young mothers (less than 20 years of age) as well as among births that occur less than 15 months after the previous birth. Perinatal mortality generally decreases with an increase in the levels of education and of household wealth. Table 8.4 Perinatal mortality Number of stillbirths and early neonatal deaths and the perinatal mortality rate for the five-year period preceding the survey, by background characteristics, Ethiopia 2011 Background characteristic Number of stillbirths1 Number of early neonatal deaths2 Perinatal mortality rate3 Weighted number of pregnancies of 7+ months duration Unweighted number of pregnancies of 7+ months duration Mother's age at birth <20 30 66 61 1,568 1,673 20-29 96 155 37 6,712 6,485 30-39 54 111 50 3,278 3,201 40-49 (24) (15) (75) 518 460 Previous pregnancy interval in months4 First pregnancy 47 81 58 2,219 2,270 <15 19 29 71 674 756 15-26 47 70 44 2,637 2,686 27-38 33 76 34 3,235 2,928 39+ 58 91 45 3,311 3,179 Residence Urban 14 57 46 1,543 2,012 Rural 190 290 46 10,534 9,807 Region Tigray 13 26 51 766 1,223 Affar 1 2 20 122 1,135 Amhara 62 87 55 2,718 1,325 Oromiya 86 142 45 5,100 1,791 Somali 7 8 42 372 1,045 Benishangul-Gumuz 3 5 58 143 1,039 SNNP 29 70 39 2,523 1,633 Gambela 1 1 40 41 861 Harari 0 1 40 29 661 Addis Ababa (2) (5) (30) 223 404 Dire Dawa 0 1 23 39 702 Mother's education No education 150 237 46 8,377 8,265 Primary 47 97 44 3,258 2,963 Secondary (3) (13) (61) 269 392 More than secondary * * * 172 199 Wealth quintile Lowest 49 94 52 2,759 3,673 Second 49 89 51 2,708 2,142 Middle 62 53 46 2,499 1,910 Fourth 29 45 32 2,301 1,894 Highest 15 66 45 1,810 2,200 Total 204 347 46 12,076 11,819 1 Stillbirths are foetal deaths in pregnancies lasting seven or more months. Figures in parentheses are based on 250-499 unweighted cases. An asterisk indicates that a figure is based on fewer than 250 unweighted cases and has been suppressed. 2 Early neonatal deaths are deaths at age 0-6 days among live-born children 3 The sum of the number of stillbirths and early neonatal deaths divided by the number of pregnancies of seven or more months' duration, expressed per 1,000 4 Categories correspond to birth intervals of <24 months, 24-35 months, 36-47 months, and 48+ months. Infant and Child Mortality • 117 8.6 HIGH-RISK FERTILITY BEHAVIOUR Findings from scientific studies have confirmed a strong relationship between a child’s chance of dying and specific fertility behaviours. Typically, the probability of dying in early childhood is much greater for children born to mothers who are young or old, born after a short birth interval, or born to women who have had more than three births. Very young mothers may experience difficult pregnancies and deliveries because of their physical immaturity. Older women may experience age-related problems during pregnancy and delivery. In this analysis a mother is considered to be ‘too young’ if she is less than age 18 and ‘too old’ if she is more than age 34 at the time of delivery. A ‘short birth interval’ characterises a birth occurring within 24 months of a previous birth. The first column in Table 8.5 shows the percentage of children born in the five years preceding the survey that fall into different categories: 62 percent of births have high mortality risks that are avoidable; 41 percent fall into a single high-risk category, and 22 percent are in a multiple high-risk category. Only 23 percent of births are not in any high-risk category. Table 8.5 High-risk fertility behaviour Percent distribution of children born in the five years preceding the survey by category of elevated risk of mortality and the risk ratio, and percent distribution of currently married women by category of risk if they were to conceive a child at the time of the survey, Ethiopia 2011 Risk category Births in the 5 years preceding the survey Percentage of currently married women1 Percentage of births Risk ratio Not in any high-risk category 23.3 1.00 16.3a Unavoidable risk category First-order births between ages 18 and 34 years 14.4 0.98 6.8 Single high-risk category Mother's age <18 5.1 1.47 1.4 Mother's age >34 0.6 1.12 3.0 Birth interval <24 months 6.4 1.34 9.1 Birth order >3 28.5 0.94 17.5 Subtotal 40.6 1.07 31.0 Multiple high-risk category Age <18 and birth interval <24 months2 0.4 3.31 0.3 Age >34 and birth interval <24 months 0.0 * 0.2 Age >34 and birth order >3 11.7 1.13 26.8 Age >34 and birth interval <24 months and birth order >3 1.7 1.66 5.7 Birth interval <24 months and birth order >3 8.0 2.25 12.8 Subtotal 21.8 1.62 45.8 In any avoidable high-risk category 62.4 1.26 76.8 Total 100.0 na 100.0 Weighted number of births/women 11,872 na 10,287 Unweighted number of births/women 11,654 na 10,204 Note: The risk ratio is the ratio of the proportion dead among births in a specific high-risk category to the proportion dead among births not in any high-risk category. An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. na = Not applicable 1 Women are assigned to risk categories according to the status they would have at the birth of a child if they were to conceive at the time of the survey: current age less than 17 years and 3 months or older than 34 years and 2 months, latest birth less than 15 months ago, or latest birth being of order 3 or higher. 2 Includes the category age <18 and birth order >3 a Includes sterilised women 118 • Infant and Child Mortality The risk ratios displayed in the second column of Table 8.5 denote the relationship between risk factors and mortality. In general, risk ratios are higher for children in a multiple high-risk category than in a single high-risk category. The most vulnerable births are those to women age less than 18 years with a birth interval less than 24 months. These children are more than three times as likely to die as children not in any high-risk category. Fortunately, less than 1 percent of births fall into this category. The last column of Table 8.5 shows the distribution of currently married women by the risk category into which a birth would fall if conceived at the time of the survey. This column is purely hypothetical and does not take into consideration the protection provided by postpartum insusceptibility, prolonged abstinence, or family planning methods other than sterilisation. However, it provides an insight into the potential magnitude of high-risk births. Overall, 77 percent of currently married women have the potential for having a high-risk birth, with 31 percent falling into a single high-risk category and 46 percent falling into a multiple high-risk category. Maternal Health • 119 MATERNAL HEALTH 9 he Government of Ethiopia is committed to achieving Millennium Development Goal 5 (MDG5), to improve maternal health, with a target of reducing the maternal mortality ratio (MMR) by three-quarters over the period 1990 to 2015. Accordingly, the Federal Ministry of Health (FMOH) has applied multi-pronged approaches to reducing maternal and newborn morbidity and mortality. Improving access to and strengthening facility-based maternal and newborn services is one such approach, and is also a Health Sector Development Plan (HSDP) strategic objective. This chapter presents findings from several areas of importance to maternal health, including antenatal, delivery, and postnatal care. The data presented in this chapter provide an opportunity to identify critical issues affecting the health status of Ethiopian women. This information will assist policymakers, planners, and other collaborators in the health sector to formulate appropriate strategies and interventions to provide quality reproductive health services and a series of well-timed interventions to improve maternal health. 9.1 ANTENATAL CARE The quality of antenatal care (ANC) can be measured by the qualifications of the provider and the number and frequency of ANC visits. Antenatal care quality can also be monitored through the content of services received and the kinds of information given to women during their visits. These services raise awareness of the danger signs during pregnancy, delivery, and the postnatal period. They also improve the health-seeking behaviour of the client, orient the client to birth preparedness issues, and provide basic preventive and therapeutic care. The 2011 EDHS obtained information on ANC coverage from responses of women who had a birth in the five years preceding the survey. For women with two or more live births during the five-year period, the EDHS data refer to the most recent birth only. T Key Findings • Thirty-four percent of women who gave birth in the five years preceding the survey received antenatal care from a skilled provider, that is, from a doctor, nurse, or midwife, for their most recent birth. This is a marked improvement from 28 percent in 2005. • One woman in every five (19 percent) made four or more antenatal care visits during the course of her pregnancy, up from 12 percent in 2005. The median duration of pregnancy at the time of the first antenatal visit is 5.2 months. • About half of mothers (48 percent) had their last live birth protected against neonatal tetanus. • Only 10 percent of births in the past five years were delivered by a skilled provider. • More than six women in every ten (61 percent) stated that a health facility delivery was not necessary, and three in every ten (30 percent) stated that it was not customary. • Just 7 percent of women received postnatal care in the first two days after their last delivery in the two years before the survey. • The most important barrier to access to health services that women mention is taking transport to a facility (71 percent), followed by lack of money (68 percent) and distance to a health facility (66 percent). 120 • Maternal Health 9.1.1 Coverage of Antenatal Care Table 9.1 shows the percent distribution of mothers in the five years preceding the survey by source of antenatal care received during pregnancy, according to selected characteristics of the women. For women who reported receiving antenatal care from more than one provider, only the provider with the highest qualification is considered. Thirty-four percent of pregnant mothers who gave birth in the five years preceding the survey received antenatal care from a skilled provider, that is, from a doctor, nurse, or midwife, for their most recent birth—28 percent from a nurse or midwife and 5 percent from a doctor. Another 9 percent of women received ANC from a health extension worker (HEW). By comparison, in 2005 28 percent received antenatal care from a skilled provider. This improvement in the last five years is impressive, particularly since between 2000 and 2005 there was hardly any improvement in antenatal coverage. About six in every ten Ethiopian women (57 percent) did not receive any antenatal care for their last birth in the five years preceding the survey. While this percentage is still substantial, it represents a marked decrease from 2005, when 72 percent did not receive any antenatal care. Table 9.1 Antenatal care Percent distribution of women age 15-49 who had a live birth in the five years preceding the survey by antenatal care (ANC) provider during pregnancy for the most recent birth and the percentage receiving antenatal care from a skilled provider for the most recent birth, according to background characteristics, Ethiopia 2011 Background characteristic Antenatal care provider No ANC Total Percentage receiving antenatal care from a skilled provider1 Weighted number of women Un- weighted number of womenDoctor Nurse/ midwife Other health worker HEW Traditional birth attendant Voluntary community health worker (VCHW) Missing Mother's age at birth <20 4.4 29.1 0.1 9.4 0.0 0.0 0.2 56.8 100.0 33.5 954 1,028 20-34 6.1 29.4 0.1 8.3 0.2 0.0 0.3 55.7 100.0 35.5 5,630 5,484 35-49 3.2 23.8 0.0 10.2 0.0 0.2 0.2 62.4 100.0 27.0 1,324 1,252 Birth order 1 9.6 36.2 0.1 7.9 0.2 0.0 0.3 45.7 100.0 45.9 1,399 1,477 2-3 6.5 30.6 0.0 7.0 0.1 0.0 0.4 55.4 100.0 37.0 2,462 2,419 4-5 4.1 29.3 0.0 9.8 0.2 0.1 0.1 56.4 100.0 33.4 1,814 1,778 6+ 2.6 20.4 0.2 10.3 0.0 0.1 0.2 66.3 100.0 23.2 2,233 2,090 Residence Urban 21.1 54.9 0.0 0.8 0.1 0.0 0.1 23.0 100.0 76.0 1,188 1,513 Rural 2.6 23.7 0.1 10.1 0.1 0.1 0.3 63.0 100.0 26.4 6,720 6,251 Region Tigray 4.3 45.6 0.1 14.4 0.0 0.0 0.5 35.0 100.0 50.1 530 847 Affar 11.2 21.1 0.0 2.5 0.2 0.0 0.3 64.7 100.0 32.3 78 714 Amhara 2.9 30.7 0.0 7.0 0.0 0.0 0.4 59.1 100.0 33.6 1,991 965 Oromiya 5.4 25.9 0.1 7.7 0.3 0.2 0.1 60.5 100.0 31.3 3,116 1,100 Somali 7.3 14.1 0.1 3.8 0.0 0.0 0.0 74.7 100.0 21.5 198 559 Benishangul- Gumuz 4.6 30.0 0.4 4.3 1.1 0.2 0.4 59.0 100.0 35.1 92 674 SNNP 2.1 25.2 0.0 13.3 0.0 0.0 0.2 59.2 100.0 27.3 1,634 1,053 Gambela 11.2 43.3 0.0 1.4 0.0 0.7 0.2 42.3 100.0 54.5 31 608 Harari 22.6 33.0 0.3 3.6 0.0 0.0 0.0 40.5 100.0 55.9 19 440 Addis Ababa 55.1 38.6 0.0 0.7 0.0 0.0 0.2 5.4 100.0 93.6 193 348 Dire Dawa 20.7 36.5 0.0 3.7 0.0 0.0 0.4 38.7 100.0 57.2 26 456 Education No education 2.4 22.6 0.1 8.8 0.1 0.1 0.3 65.7 100.0 25.1 5,270 5,184 Primary 7.6 37.9 0.0 9.5 0.1 0.0 0.1 44.6 100.0 45.5 2,270 2,095 Secondary 31.3 54.2 0.0 3.0 1.1 0.0 0.0 10.5 100.0 85.5 226 312 More than secondary 38.4 52.4 0.0 3.0 0.0 0.0 0.0 6.2 100.0 90.9 142 173 Wealth quintile Lowest 1.0 15.9 0.0 8.1 0.0 0.0 0.4 74.4 100.0 17.0 1,739 2,279 Second 1.5 22.3 0.0 10.7 0.2 0.3 0.2 64.9 100.0 23.7 1,696 1,354 Middle 2.3 24.5 0.2 10.9 0.0 0.0 0.0 62.0 100.0 27.0 1,628 1,241 Fourth 5.1 30.2 0.0 10.9 0.4 0.0 0.5 52.8 100.0 35.4 1,493 1,229 Highest 20.0 54.9 0.0 1.8 0.0 0.0 0.0 23.2 100.0 74.9 1,351 1,661 Total 5.4 28.4 0.1 8.7 0.1 0.1 0.2 57.0 100.0 33.9 7,908 7,764 Note: If more than one source of ANC was mentioned, only the provider with the highest qualifications is considered in this tabulation. HEW = Health Extension Worker 1 Skilled provider includes doctor, nurse, or midwife Maternal Health • 121 Antenatal care from a skilled provider is more common among women age 34 and younger (34-36 percent) than among women age 35-49 (27 percent). Women are almost twice as likely to receive antenatal care from a skilled provider for first births (46 percent) than for birth orders six and higher (23 percent). The relationship is the opposite for women who received antenatal care from a HEW: 10 percent of women with birth orders six or higher received antenatal care from a HEW compared with 8 percent of women pregnant with their first child. The proportion of women who did not receive any antenatal care increases with the child’s birth order. Urban women are almost three times more likely than rural women to receive ANC from a skilled provider. Seventy-six percent of women residing in urban areas received ANC services from a skilled provider for their last birth compared with 26 percent of women in rural areas. Urban women are seven times more likely, at 21 percent, than rural women, at 3 percent, to receive antenatal care from a doctor. Similarly, a higher proportion of urban women (55 percent) received ANC from a nurse or midwife compared with rural women (24 percent). Conversely, 10 percent of rural women received antenatal care from a HEW compared with less than 1 percent of urban woman. There is a direct relationship between a woman’s education level and whether she is likely to receive ANC from a skilled provider. For example, 91 percent of women with more than secondary education received ANC from a skilled provider compared with 25 percent of women with no education. Similarly, the proportion of women who received ANC is greatest among those in the highest wealth quintile (75 percent), and decreases with each wealth quintile to a low of 17 percent among women in the lowest wealth quintile. 9.1.2 Number of ANC Visits, Timing of First Visit, and Source Where ANC Was Received Antenatal care is more beneficial in preventing adverse pregnancy outcomes when received early in the pregnancy and continued through delivery. Early detection of problems in pregnancy leads to more timely referrals for women in high-risk categories or with complications; this is particularly true in Ethiopia, where three-quarters of the population live in rural areas and where physical barriers pose a challenge to providing health care. Under normal circumstances, the World Health Organization (WHO) recommends that a woman without complications should have at least four antenatal care visits, the first of which should take place during the first trimester. Table 9.2 presents information on the number of visits and the timing of the first visit. 122 • Maternal Health Table 9.2 Number of antenatal care visits and timing of first visit Percent distribution of women age 15-49 who had a live birth in the five years preceding the survey by number of antenatal care (ANC) visits for the most recent live birth, and by the timing of the first visit, and among women with ANC, median months pregnant at first visit, according to residence, Ethiopia 2011 Number and timing of ANC visits Residence Total Urban Rural Number of ANC visits None 23.1 63.1 57.1 1 2.8 4.8 4.5 2-3 26.9 17.6 19.0 4+ 45.5 14.4 19.1 Don't know/missing 1.8 0.1 0.3 Total 100.0 100.0 100.0 Number of months pregnant at time of first ANC visit No antenatal care 23.1 63.1 57.1 <4 31.0 7.7 11.2 4-5 31.5 13.8 16.5 6-7 11.6 12.2 12.1 8+ 2.3 2.9 2.8 Don't know/missing 0.6 0.2 0.3 Total 100.0 100.0 100.0 Weighted number of women 1,188 6,720 7,908 Unweighted number of women 1,513 6,251 7,764 Median months pregnant at first visit (for those with ANC) 4.4 5.5 5.2 Weighted number of women with ANC 914 2,477 3,391 Unweighted number of women with ANC 1,203 2,295 3,498 Nineteen percent of women with a live birth in the five years before the survey made four or more ANC visits during the length of their pregnancy, a marked improvement from 12 percent reported in the 2005 EDHS. Urban women are more likely than rural women to have made four or more visits (46 percent versus 14 percent). Eleven percent of women made their first ANC visit before the fourth month of pregnancy, an almost two-fold increase from 6 percent in the 2005 EDHS. The median duration of pregnancy at the first visit is 5.2 months, while urban women made the first ANC visit earlier (4.4 months) than rural women (5.5 months). 9.1.3 Components of Antenatal Care Measuring the components of antenatal care is essential for assessing the quality of ANC services. Pregnancy complications are a primary source of maternal and child morbidity and mortality. Therefore, pregnant women should routinely receive information on the signs of complications and be tested for them at all antenatal care visits. To help assess the quality of antenatal services, respondents were asked whether they had been advised of complications or received certain screening tests during at least one of their antenatal care visits. Table 9.3 shows the percentage of women who took iron tablets or syrup, who took medicine for intestinal parasites, who were informed of the signs of pregnancy complications, and who received selected services during ANC visits for their most recent birth in the last five years. Among women with a live birth in the five years preceding the survey, 17 percent took iron tablets during their last pregnancy. There are substantial variations by women’s background characteristics. Twelve percent of women under age 20 took iron tablets or syrup compared with 18 percent among women age 25-34 and 17 percent among women age 35-49. The usage of iron tablets is much higher among urban women, at 27 percent, than among rural women, at 15 percent. Also, the use of iron tablets increases with levels of education and household wealth. The percentage of women who took iron tablets ranges from 12 percent in Oromiya region to 39 percent in Addis Ababa. Maternal Health • 123 About 6 percent of women took intestinal parasite drugs during their last pregnancy. Use of drugs to control intestinal parasites during pregnancy is least common among women under age 20, rural women, women with no education, and women in households in the lowest and middle wealth quintile. Deworming is part of the ANC in only a few regions. This explains the wide variation in the percentage of women who took intestinal parasite drugs during their last pregnancy from 3 percent in Somali, Dire Dawa, and Affar regions to 12 percent in Gambela. One in every five women who received ANC reported that they were informed of signs of pregnancy complications during their ANC visit. Women are more likely to be informed of signs of pregnancy complications while pregnant with their first birth compared with pregnancies of birth orders six or higher. A notably higher proportion of urban women (34 percent) than rural women (15 percent) reported that they were informed of signs of pregnancy complications. The proportion ranges from 16 percent of women in Amhara to 49 percent in Addis Ababa. Women with at least a secondary education and those in the highest wealth quintile were more likely to be informed of the signs of pregnancy complications than other women. Among the various ANC components, 72 percent of women had their blood pressure measured, 54 percent had a blood sample taken, and 41 percent had a urine sample taken. For all three services, women age 20-34, women having their first birth, urban residents, highly educated women, and women in the highest wealth quintiles were more likely than other women to have received each of the specified services. Table 9.3 Components of antenatal care Among women age 15-49 with a live birth in the five years preceding the survey, the percentage who took iron tablets and drugs for intestinal parasites during the pregnancy of the most recent birth, and among women receiving antenatal care (ANC) for the most recent live birth in the five years preceding the survey, the percentage receiving specific antenatal services, according to background characteristics, Ethiopia 2011 Background characteristic Among women with a live birth in the past five years, the percentage who during the pregnancy of their last birth: Weighted number of women with a live birth in the past five years Unweighted number of women with a live birth in the past five years Among women who received antenatal care for their most recent birth in the past five years, the percentage with selected services Weighted number of women with ANC for their most recent birth Unweighted number of women with ANC for their most recent birth Took iron tablets Took intestinal parasite drugs Informed of signs of pregnancy complications Blood pressure measured Urine sample taken Blood sample taken Mother's age at birth <20 12.0 4.5 954 1,028 23.4 64.2 39.0 47.6 412 470 20-34 17.8 5.5 5,630 5,484 19.7 72.8 43.0 56.0 2,484 2,555 35-49 17.2 6.1 1,324 1,252 19.0 71.4 34.2 49.4 495 473 Birth order 1 18.0 5.6 1,399 1,477 28.2 76.9 54.6 64.7 759 874 2-3 16.7 4.6 2,462 2,419 19.4 71.3 44.5 55.8 1,093 1,181 4-5 17.6 6.1 1,814 1,778 17.2 71.1 37.1 49.2 790 739 6+ 16.3 5.9 2,233 2,090 15.8 67.1 27.4 45.6 749 704 Residence Urban 27.2 8.5 1,188 1,513 33.7 83.1 74.0 79.9 914 1,203 Rural 15.2 5.0 6,720 6,251 15.0 67.3 29.2 44.5 2,477 2,295 Region Tigray 33.6 3.9 530 847 27.5 86.3 48.0 66.9 342 546 Affar 23.3 3.4 78 714 26.5 62.4 58.2 68.2 27 205 Amhara 19.0 5.6 1,991 965 16.4 61.1 37.4 49.1 813 371 Oromiya 11.8 5.1 3,116 1,100 16.6 70.2 37.1 48.4 1,232 438 Somali 19.9 2.9 198 559 31.0 68.8 56.9 62.3 50 143 Benishangul-Gumuz 23.3 8.9 92 674 26.0 65.8 37.9 51.5 38 257 SNNP 15.0 6.9 1,634 1,053 17.3 72.5 31.1 48.6 663 421 Gambela 27.5 12.4 31 608 20.1 78.5 53.1 66.3 18 267 Harari 32.9 4.1 19 440 28.5 95.8 82.1 87.3 11 259 Addis Ababa 38.7 4.3 193 348 49.1 96.6 97.8 99.5 182 327 Dire Dawa 27.8 3.3 26 456 27.4 87.7 79.0 86.2 16 264 Education No education 14.8 4.2 5,270 5,184 11.6 65.5 29.3 42.7 1,800 1,791 Primary 19.1 8.1 2,270 2,095 23.9 76.0 47.9 61.4 1,256 1,256 Secondary 31.1 6.0 226 312 50.4 83.7 81.2 86.1 202 286 More than secondary 42.8 10.8 142 173 51.5 94.1 80.3 88.2 133 165 Wealth quintile Lowest 13.2 3.4 1,739 2,279 10.6 63.8 19.3 36.6 438 579 Second 12.6 5.1 1,696 1,354 13.9 64.2 24.3 39.8 595 491 Middle 15.2 3.3 1,628 1,241 11.5 63.3 28.6 40.2 618 512 Fourth 17.9 7.5 1,493 1,229 17.7 70.1 36.5 52.2 704 595 Highest 28.7 9.2 1,351 1,661 34.2 85.0 71.0 78.9 1,037 1,321 Total 17.0 5.5 7,908 7,764 20.0 71.6 41.3 54.0 3,391 3,498 124 • Maternal Health 9.1.4 Informed of signs of pregnancy complications during pregnancy Pregnancy complications are a major health problem among women in developing countries. Table 9.4 presents the specific pregnancy complications that women were informed of during ANC visits. Among women who were informed of signs of pregnancy complications at an ANC visit for their last live birth, almost half (48 percent) were informed of abdominal pain as a sign of pregnancy complications. More than one-third (36 percent) were informed of severe headache, one-fourth (25 percent) were informed of vaginal bleeding, and about one-fifth (22 percent) were informed of vaginal gush or fluid as signs of pregnancy complications. Fourteen percent of women were informed of fever, and 7 percent were informed of blurred vision as possible signs of pregnancy complications. Table 9.4 Informed of signs of pregnancy complications Among women age 15-49 with a live birth in the five years preceding the survey who were informed of signs of pregnancy complications at an antenatal care visit for their last birth, the percentage who were informed of specific pregnancy complications, according to background characteristics, Ethiopia 2011 Background characteristic Vaginal bleeding Vaginal gush or fluid Severe headache Blurred vision Fever Abdominal pain Other Weighted number of women Unweighted number of women Age 15-19 (18.1) (11.7) (45.9) (3.8) (18.8) (51.8) (30.8) 46 44 20-34 27.4 23.8 32.4 7.0 12.7 49.1 15.0 476 635 35-49 21.6 19.9 43.5 5.7 15.9 44.8 16.5 157 168 Residence Urban 30.4 27.0 36.1 7.7 8.9 44.0 17.5 308 456 Rural 21.2 18.0 35.7 5.4 18.0 51.8 15.5 371 391 Region Tigray 45.7 27.9 16.7 8.3 4.2 51.6 16.0 94 144 Affar 27.3 24.0 49.6 14.5 32.7 45.2 9.5 7 51 Amhara 15.8 29.3 34.0 4.4 13.9 62.7 16.7 133 60 Oromiya 12.2 9.2 46.7 2.8 23.5 46.7 19.6 205 72 Somali (36.7) (16.1) (62.9) (23.6) (19.1) (34.1) (10.3) 15 42 Benishangul-Gumuz 28.3 41.4 22.3 5.1 18.1 41.3 16.7 10 65 SNNP 34.8 23.1 34.8 11.7 5.7 49.8 13.9 115 67 Gambela (21.3) (14.4) (16.4) (4.7) (16.9) (32.5) (29.9) 4 44 Harari 20.3 21.0 33.0 3.7 19.2 24.0 34.2 3 73 Addis Ababa 34.5 32.9 31.4 6.2 8.1 29.8 13.1 89 160 Dire Dawa 24.4 9.6 42.9 1.6 31.3 54.1 11.0 4 69 Education No education 19.2 22.6 35.9 6.4 15.1 57.1 14.0 209 290 Primary 24.1 19.3 36.7 5.9 17.7 47.0 13.9 300 332 Secondary 32.8 18.1 43.5 8.6 4.4 41.3 22.7 102 140 More than secondary 38.6 38.4 21.0 5.8 7.3 37.6 25.6 69 85 Wealth quintile Lowest 24.3 23.7 37.6 7.6 13.9 65.4 9.8 46 82 Second 14.9 15.6 34.5 7.7 20.0 54.2 12.5 82 76 Middle 18.4 16.5 26.7 4.0 14.1 62.3 21.4 71 70 Fourth 23.0 23.2 35.6 3.6 21.1 42.9 15.5 125 131 Highest 30.3 24.1 37.9 7.5 9.8 43.7 17.5 355 488 Total 25.4 22.1 35.9 6.5 13.9 48.3 16.4 679 847 Note: Figures in parentheses are based on 25-49 unweighted cases. 9.2 TETANUS TOXOID INJECTIONS Neonatal tetanus is a leading cause of neonatal deaths in Ethiopia and other developing countries where a high proportion of deliveries are conducted at home or in other places where hygienic conditions do not exist. Tetanus toxoid (TT) immunisation is given to pregnant women to prevent neonatal tetanus. If a woman has received no previous TT injections, she needs two doses of TT during pregnancy for full protection. However, if a woman was immunised before she became pregnant, she may require one injection or not require any TT injections during pregnancy, depending on the number of injections she has already received and the timing of the last injection. For a woman to have lifetime protection, a total of five doses are required. To assess the status of tetanus vaccination coverage, women who gave birth during the five years before the survey were asked if they had received tetanus toxoid injections during the pregnancy for their most recent birth, and if so, how many. Women who did not receive two or more tetanus Maternal Health • 125 toxoid vaccinations during this pregnancy were then asked about tetanus toxoid vaccinations they may have received prior to this pregnancy. Table 9.5 presents the results. Thirty-four percent of women with a birth in the five years preceding the survey received two or more tetanus toxoid injections during their last pregnancy, and 48 percent of mothers were protected for their last birth. In the 2011 EDHS mothers age 20-34 were more likely (35 percent) to have received two or more tetanus injections during their last pregnancy than mothers under age 20 or 35-49 (both 30 percent). Mothers in Addis Ababa were most likely to have received two or more tetanus toxoid injections (72 percent) and to have had their last birth protected against neonatal tetanus (82 percent), while mothers in Affar were least likely (22 and 27 percent, respectively). Education and wealth have a positive effect on whether women receive tetanus toxoid injections. For example, 62 percent of mothers with more than secondary education received at least two injections during their last pregnancy compared with 29 percent of mothers with no education. Also, 52 percent of mothers in the highest wealth quintile received at least two doses of tetanus toxoid injection compared with 24 percent of mothers in the lowest wealth quintile. The pattern is similar for protection against neonatal tetanus. Table 9.5 Tetanus toxoid injections Among mothers age 15-49 with a live birth in the five years preceding the survey, the percentage receiving two or more tetanus toxoid injections (TTI) during the pregnancy for the last live birth and the percentage whose last live birth was protected against neonatal tetanus, according to background characteristics, Ethiopia 2011 Background characteristic Percentage receiving two or more injections during last pregnancy Percentage whose last birth was protected against neonatal tetanus1 Weighted number of mothers Unweighted number of mothers Mother's age at birth <20 29.7 43.0 954 1,028 20-34 35.4 49.8 5,630 5,484 35-49 29.6 45.7 1,324 1,252 Birth order 1 35.5 49.5 1,399 1,477 2-3 35.3 49.2 2,462 2,419 4-5 34.1 49.7 1,814 1,778 6+ 30.8 45.4 2,233 2,090 Residence Urban 52.0 67.5 1,188 1,513 Rural 30.5 44.9 6,720 6,251 Region Tigray 31.8 68.0 530 847 Affar 22.1 26.7 78 714 Amhara 29.1 43.2 1,991 965 Oromiya 32.9 45.9 3,116 1,100 Somali 28.1 33.7 198 559 Benishangul-Gumuz 33.8 48.1 92 674 SNNP 37.7 50.8 1,634 1,053 Gambela 49.0 58.4 31 608 Harari 56.6 69.5 19 440 Addis Ababa 72.3 82.3 193 348 Dire Dawa 51.1 58.7 26 456 Education No education 28.7 40.8 5,270 5,184 Primary 41.8 60.5 2,270 2,095 Secondary 54.8 78.1 226 312 More than secondary 61.7 82.5 142 173 Wealth quintile Lowest 23.9 36.6 1,739 2,279 Second 29.6 43.2 1,696 1,354 Middle 30.8 45.7 1,628 1,241 Fourth 36.6 51.9 1,493 1,229 Highest 52.3 68.8 1,351 1,661 Total 33.8 48.3 7,908 7,764 1 Includes mothers with two injections during the pregnancy of her last birth, or two or more injections (the last within 3 years of the last live birth), or three or more injections (the last within 5 years of the last birth), or four or more injections (the last within 10 years of the last live birth), or five or more injections at any time prior to the last birth. 126 • Maternal Health 9.3 PLACE OF DELIVERY Proper medical attention and hygienic conditions during delivery can reduce the risk of complications and infections that can cause the death or serious illness of the mother and/or the newborn baby. An important component of efforts to reduce health risks to mothers and children is increasing the proportion of babies that are delivered in health facilities. Table 9.6 presents the percent distribution of all live births in the five years preceding the survey by place of delivery. Ten percent of births in Ethiopia are delivered at a health facility—9 percent in a public facility and 1 percent in a private facility. Nine women in every ten deliver at home. The percentage of deliveries in a health facility doubled from 5 percent the 2005 EDHS, while home deliveries decreased slightly from 94 percent to the current level of 90 percent. First births are much more likely than births orders six or higher to be delivered in a health facility (21 percent versus 4 percent). Delivery in a health facility is more common among births to mothers age 20-34, births to mothers who had at least four ANC visits, and births to highly educated mothers and mothers in the highest wealth quintiles. Urban births are notably more likely than rural births to be delivered in a health facility (50 percent versus 4 percent). The percentage of births delivered in health facility ranges from less than 10 percent in SNNP, Affar, Oromiya, Somalia, and Benishangul-Gumuz regions to 82 percent in Addis Ababa. Table 9.6 Place of delivery Percent distribution of live births in the five years preceding the survey by place of delivery and percentage delivered in a health facility, according to background characteristics, Ethiopia 2011 Background characteristic Health facility Home Other Missing Total Percentage delivered in a health facility Weighted number of births Unweighted number of births Public sector Private sector Mother's age at birth <20 8.9 0.7 89.1 0.8 0.4 100.0 9.6 1,538 1,647 20-34 9.2 1.5 88.9 0.4 0.0 100.0 10.7 8,663 8,425 35-49 6.1 0.3 93.3 0.1 0.2 100.0 6.4 1,672 1,582 Birth order 1 18.6 2.4 77.9 0.8 0.3 100.0 21.0 2,262 2,303 2-3 9.4 1.7 88.4 0.4 0.0 100.0 11.1 3,694 3,717 4-5 5.7 0.3 93.6 0.3 0.0 100.0 6.1 2,728 2,678 6+ 3.5 0.5 95.5 0.2 0.2 100.0 4.1 3,188 2,956 Antenatal care visits1 None 2.8 0.2 96.6 0.3 0.1 100.0 3.0 4,517 4,266 1-3 13.1 1.3 85.3 0.3 0.0 100.0 14.4 1,856 1,766 4+ 29.2 5.1 65.1 0.5 0.0 100.0 34.4 1,508 1,705 Residence Urban 43.1 6.7 49.9 0.2 0.1 100.0 49.8 1,528 1,986 Rural 3.7 0.4 95.4 0.5 0.1 100.0 4.1 10,344 9,668 Region Tigray 10.8 0.8 87.8 0.5 0.0 100.0 11.6 753 1,202 Affar 6.6 0.3 92.8 0.2 0.1 100.0 6.8 121 1,130 Amhara 9.6 0.6 89.3 0.4 0.1 100.0 10.2 2,656 1,294 Oromiya 7.0 1.0 91.5 0.4 0.1 100.0 8.0 5,014 1,761 Somali 6.5 1.1 92.4 0.0 0.0 100.0 7.6 364 1,027 Benishangul-Gumuz 7.9 1.2 81.9 8.7 0.3 100.0 9.1 140 1,020 SNNP 5.6 0.7 93.5 0.1 0.2 100.0 6.2 2,494 1,614 Gambela 23.4 4.1 71.6 0.4 0.4 100.0 27.5 40 851 Harari 27.5 4.9 67.3 0.3 0.0 100.0 32.4 29 659 Addis Ababa 62.3 20.1 17.2 0.0 0.5 100.0 82.3 222 400 Dire Dawa 34.4 5.3 60.0 0.0 0.3 100.0 39.7 39 696 Mother’s education No education 4.4 0.3 94.7 0.4 0.1 100.0 4.7 8,227 8,142 Primary 13.4 1.5 84.6 0.3 0.1 100.0 14.9 3,211 2,930 Secondary 54.3 15.3 29.4 0.8 0.2 100.0 69.6 266 386 More than secondary 58.2 17.3 23.0 1.5 0.0 100.0 75.5 168 196 Wealth quintile Lowest 2.0 0.0 97.3 0.5 0.1 100.0 2.0 2,710 3,625 Second 3.1 0.1 96.2 0.3 0.3 100.0 3.2 2,658 2,114 Middle 2.9 0.2 96.2 0.6 0.1 100.0 3.1 2,437 1,872 Fourth 6.0 0.8 92.7 0.3 0.1 100.0 6.9 2,272 1,870 Highest 38.5 6.5 54.7 0.3 0.1 100.0 45.0 1,795 2,173 Total 8.7 1.2 89.5 0.4 0.1 100.0 9.9 11,872 11,654 Note: Total includes 27 cases with missing information on ANC visits. 1 Includes only the most recent birth in the 5 years preceding the survey Maternal Health • 127 9.4 ASSISTANCE DURING DELIVERY The type of assistance a woman receives during childbirth has important health consequences for both mother and child. In addition, the proportion of births attended by skilled providers is a measure of the health system’s effectiveness, accessibility, and quality of care. Delivery assisted by skilled providers is the most important proven intervention in reducing maternal mortality and one of the MDG indicators to track national effort towards safe motherhood. Table 9.7 shows the percent distribution of births in the five years preceding the survey by type of assistance during delivery, according to women’s background characteristics. Ten percent of births were assisted by a skilled provider—4 percent by a doctor and 7 percent by a nurse or midwife. Less than 1 percent of births were assisted by a HEW, and 57 percent of births were assisted by a relative, or some other person. Twenty-eight percent of births were assisted by a traditional birth attendant, while 4 percent of births were unattended. Skilled assistance at delivery increased from 6 percent to 10 percent in the last six years. Skilled providers were most likely to attend births to mothers age 20-34 (11 percent) and first- order births (21 percent). Not surprisingly, skilled providers attended an overwhelming majority of births delivered in a health facility compared with births delivered elsewhere. Also, skilled providers attended 51 percent of births in urban areas compared with 4 percent of births in rural areas. Conversely, in rural areas the most common birth attendant was a relative or other person. Regional differences in delivery assistance are large. The proportion of births assisted by a skilled provider ranged from 6 percent in the SNNP region to 84 percent in Addis Ababa. Highly educated mothers were most likely to have their births assisted by a skilled provider (74 percent), as were mothers in the highest wealth quintile (46 percent). Less than 2 percent of births were delivered by caesarean section. C-sections were most likely to take place in a health facility, in urban areas, among highly educated mothers, and in the wealthiest quintiles. 128 • Maternal Health Table 9.7 Assistance during delivery Percent distribution of live births in the five years preceding the survey by person providing assistance during delivery, percentage of birth assisted by a skilled provider and percentage delivered by caesarean section, according to background characteristics, Ethiopia 2011 Background characteristic Person providing assistance during delivery Total Per- centage delivered by a skilled provider1 Per- centage delivered by C-section Weighted number of births Un- weighted number of births Doctor Nurse/ midwife HEW Traditional birth attendant Voluntary community health worker (VCHW) Relative/ Other No one Missing Mother's age at birth <20 2.6 7.0 1.1 30.7 0.1 54.7 3.4 0.4 100.0 9.6 1.3 1,538 1,647 20-34 4.0 6.9 0.7 28.0 0.2 56.5 3.5 0.1 100.0 10.9 1.6 8,663 8,425 35-49 1.6 4.3 0.7 28.4 0.4 58.8 5.6 0.2 100.0 5.9 1.3 1,672 1,582 Birth order 1 8.6 12.1 1.3 27.4 0.2 47.6 2.5 0.3 100.0 20.8 4.2 2,262 2,303 2-3 3.7 7.9 0.7 27.4 0.3 56.9 3.0 0.1 100.0 11.7 1.3 3,694 3,717 4-5 1.8 4.3 0.9 28.1 0.4 61.0 3.3 0.1 100.0 6.1 0.9 2,728 2,678 6+ 1.0 2.8 0.4 30.6 0.1 58.9 5.9 0.2 100.0 3.9 0.3 3,188 2,956 Place of delivery Health facility 34.6 62.2 2.2 0.6 0.1 0.4 0.0 0.0 100.0 96.7 14.9 1,181 1,571 Elsewhere 0.0 0.4 0.6 31.5 0.3 62.9 4.2 0.0 100.0 0.4 0.0 10,678 10,063 Residence Urban 19.8 30.9 0.8 21.9 0.4 25.0 1.1 0.0 100.0 50.8 8.1 1,528 1,986 Rural 1.1 2.9 0.8 29.4 0.2 61.3 4.2 0.2 100.0 4.0 0.5 10,344 9,668 Region Tigray 2.6 9.0 0.9 12.5 0.3 74.1 0.6 0.0 100.0 11.6 2.9 753 1,202 Affar 2.8 4.2 0.0 75.9 0.1 16.5 0.2 0.1 100.0 7.2 2.0 121 1,130 Amhara 2.5 7.6 0.4 28.5 0.1 59.5 1.2 0.2 100.0 10.1 1.3 2,656 1,294 Oromiya 2.2 6.0 0.8 33.7 0.1 52.3 4.9 0.1 100.0 8.1 0.5 5,014 1,761 Somali 3.5 4.7 0.0 81.2 0.0 9.9 0.5 0.0 100.0 8.4 0.7 364 1,027 Benishangul- Gumuz 1.9 7.0 1.3 27.9 0.0 39.5 22.0 0.5 100.0 8.9 1.3 140 1,020 SNNP 1.9 4.1 1.2 14.2 0.8 72.5 5.1 0.1 100.0 6.1 1.2 2,494 1,614 Gambela 8.1 18.9 0.5 12.1 0.3 53.0 6.4 0.4 100.0 27.4 8.7 40 851 Harari 16.4 16.2 0.2 63.0 0.0 1.7 2.6 0.0 100.0 32.5 7.0 29 659 Addis Ababa 60.4 23.5 0.0 5.9 0.1 8.4 1.5 0.2 100.0 83.9 21.8 222 400 Dire Dawa 17.7 22.6 0.2 49.7 0.2 7.0 2.1 0.5 100.0 40.3 6.2 39 696 Mother’s education No education 1.2 3.4 0.7 29.5 0.2 60.8 4.1 0.2 100.0 4.6 0.4 8,227 8,142 Primary 5.6 9.7 1.0 27.9 0.2 52.0 3.5 0.1 100.0 15.4 2.4 3,211 2,930 Secondary 30.6 41.5 0.1 13.8 0.0 13.3 0.5 0.0 100.0 72.4 14.6 266 386 More than secondary 29.6 44.4 3.4 11.0 1.5 8.5 1.5 0.0 100.0 74.1 13.7 168 196 Wealth quintile Lowest 0.5 1.2 0.4 27.9 0.3 65.7 3.9 0.1 100.0 1.7 0.1 2,710 3,625 Second 0.7 2.2 0.9 29.2 0.3 62.1 4.2 0.3 100.0 2.9 0.6 2,658 2,114 Middle 0.8 2.4 0.9 30.4 0.2 61.8 3.3 0.2 100.0 3.2 0.6 2,437 1,872 Fourth 1.8 5.6 1.1 32.0 0.1 55.2 4.2 0.0 100.0 7.4 0.5 2,272 1,870 Highest 17.7 27.9 0.6 20.6 0.4 29.6 3.0 0.0 100.0 45.6 7.2 1,795 2,173 Total 3.5 6.5 0.8 28.4 0.2 56.6 3.8 0.1 100.0 10.0 1.5 11,872 11,654 Note: If the respondent mentioned more than one person attending during delivery, only the most qualified person is considered in this tabulation. Total includes 14 cases with missing information on place of delivery. HEW = Health Extension Worker 1 Skilled provider includes doctor, nurse, and midwife. 9.5 REASONS FOR NOT DELIVERING IN A HEALTH FACILITY Women who did not deliver at a health facility were asked the reasons they did not deliver in a health facility. Table 9.8 shows that more than six women in ten (61 percent) stated that a health facility delivery was not necessary, and three in every ten (30 percent) stated that it was not customary. Fourteen percent of women said that the health facility was either too far or that they did not have transportation. Rural woman were more likely than urban women to report that health facility deliveries are not customary, at 31 percent versus 17 percent, or that health facilities were too far or they had no transportation, at 15 percent versus 8 percent. Maternal Health • 129 Table 9.8 Reasons for not delivering in a health facility Percent distribution of last live births in the two years preceding the survey by reason for not delivering in a health facility, according to background characteristics, Ethiopia 2011 Background characteristic Cost too much Facility not open Too far/no transportation Poor quality service No female provider Husband/ family did not allow Not necessary Not customary Other Weighted number of women Unweighted number of women Age < 20 1.7 1.8 12.4 0.3 0.1 1.8 56.3 37.6 3.7 361 359 20-34 2.0 1.0 14.7 0.4 0.3 1.1 61.7 28.7 4.9 4,736 4,380 35-49 2.6 0.3 14.2 0.9 0.4 1.6 60.8 30.1 3.8 1,883 1,759 Residence Urban 4.7 1.4 7.7 1.0 0.2 2.9 65.7 16.5 7.8 560 569 Rural 1.9 0.8 15.0 0.5 0.4 1.1 60.8 30.7 4.2 6,420 5,929 Region Tigray 0.9 0.8 9.0 1.1 0.1 0.2 77.0 16.4 2.9 457 744 Affar 13.2 3.4 41.3 0.4 1.1 5.0 45.6 41.2 1.2 72 673 Amhara 2.1 0.5 10.4 0.5 0.5 1.0 56.3 35.9 5.9 1,774 880 Oromiya 2.3 1.2 18.2 0.6 0.1 1.6 63.6 28.9 4.0 2,830 996 Somali 9.0 1.4 35.9 1.5 2.7 2.0 23.1 35.6 5.0 179 509 Benishangul-Gumuz 2.6 2.9 22.1 0.5 0.3 7.9 31.3 41.4 5.6 82 620 SNNP 1.0 0.3 9.2 0.3 0.4 0.5 64.8 26.0 4.0 1,504 984 Gambela 2.8 3.6 26.8 0.2 0.3 2.7 42.4 14.5 14.4 22 495 Harari 2.0 0.0 3.8 0.8 0.0 0.3 83.1 20.6 3.7 12 275 Addis Ababa 3.3 0.0 17.6 1.0 0.0 0.0 60.2 8.3 12.8 35 60 Dire Dawa 8.1 1.1 16.9 0.8 0.8 0.6 51.6 27.4 9.1 14 262 Education No education 2.4 0.7 15.3 0.5 0.4 1.1 58.4 31.8 4.3 5,015 4,824 Primary 1.5 1.2 12.4 0.7 0.2 1.4 67.5 24.1 5.0 1,865 1,572 Secondary 0.3 0.3 4.6 0.0 0.0 4.8 80.5 21.9 3.6 66 77 More than secondary (0.4) (0.0) (8.3) (0.0) (0.0) (0.0) (83.9) (9.6) (10.4) 35 25 Wealth quintile Lowest 2.8 0.2 17.0 0.4 0.2 0.8 55.3 34.4 4.3 1,696 2,194 Second 1.2 1.1 13.7 0.8 0.6 1.3 62.6 30.0 3.0 1,640 1,299 Middle 2.2 0.9 16.0 0.4 0.5 0.7 60.2 30.1 6.0 1,574 1,192 Fourth 2.1 1.1 13.0 0.2 0.3 1.7 63.4 28.0 3.9 1,382 1,118 Highest 2.6 1.2 9.2 1.1 0.2 2.2 69.9 17.8 6.5 689 695 Total 2.2 0.8 14.4 0.5 0.3 1.2 61.2 29.5 4.5 6,980 6,498 Note: Figures in parentheses are based on 25-49 unweighted cases. 9.6 POSTNATAL CARE A large proportion of maternal and neonatal deaths occur during the 48 hours after delivery, and these first two days following delivery are critical for monitoring complications arising from the delivery. Thus, postnatal care is important for both the mother and the child not only to treat complications arising from the delivery, but also to provide the mother with important information on how to care for herself and her child. Safe motherhood programmes have recently increased emphasis on the importance of postnatal care, recommending that all women receive a health checkup within two days of delivery. To assess the extent of postnatal care utilization, the 2011 EDHS asked respondents whether they had received a health checkup after the delivery, the timing of the first check, and the type of health provider for their last birth in the two years preceding the survey. Table 9.9 presents this information by women’s background characteristics. The level of postnatal care coverage is extremely low in Ethiopia. The great majority of women (92 percent) with a live birth in the preceding five years did not receive a postnatal checkup. Among women who received a postnatal checkup, 4 percent were examined within 4 hours of delivery, 2 percent within 4-23 hours, 1 percent within 1-2 days, and 2 percent within 3-41 days of delivery. In total, 7 percent of women received postnatal care within two days, as recommended. 130 • Maternal Health Table 9.9 Timing of first postnatal checkup for the mother Among women age 15-49 giving birth in the two years preceding the survey, the percent distribution of the mother's first postnatal check-up for the last live birth by time after delivery, and the percentage of women with a live birth in the two years preceding the survey who received a postnatal checkup in the first two days after giving birth, according to background characteristics, Ethiopia 2011 Background characteristic Time after delivery of mother's first postnatal checkup No postnatal checkup1 Total Percentage of women with a postnatal checkup in the first two days after birth Weighted number of women Unweighted number of women Less than 4 hours 4-23 hours 1-2 days 3-6 days 7-41 days Don't know/ missing Mother's age at birth <20 4.2 0.5 0.9 0.1 1.7 0.1 92.4 100.0 5.6 557 574 20-34 4.3 2.4 0.7 0.2 1.4 0.2 90.8 100.0 7.4 3,198 3,092 35-49 1.9 2.0 0.5 0.0 1.2 0.1 94.3 100.0 4.3 697 618 Birth order 1 9.5 4.1 1.3 0.3 1.4 0.3 83.1 100.0 14.9 800 809 2-3 4.0 2.2 0.7 0.2 1.0 0.3 91.5 100.0 6.9 1,449 1,390 4-5 2.5 0.9 0.4 0.2 1.4 0.0 94.6 100.0 3.8 1,008 992 6+ 1.3 1.6 0.5 0.0 1.9 0.0 94.6 100.0 3.4 1,195 1,093 Place of delivery Health facility 31.6 14.5 4.3 0.9 1.6 1.3 45.8 100.0 50.4 517 653 Elsewhere 0.3 0.5 0.2 0.1 1.4 0.0 97.5 100.0 0.9 3,936 3,631 Residence Urban 21.7 9.0 1.4 0.5 1.9 0.6 64.9 100.0 32.1 607 751 Rural 1.1 1.0 0.6 0.1 1.3 0.1 95.7 100.0 2.7 3,846 3,533 Region Tigray 8.0 4.4 0.7 0.4 2.8 0.4 83.3 100.0 13.1 273 434 Affar 2.2 1.0 2.8 0.8 3.0 1.1 89.2 100.0 6.0 40 378 Amhara 3.5 1.2 0.4 0.2 1.7 0.0 93.0 100.0 5.1 983 476 Oromiya 2.9 1.6 0.5 0.0 1.1 0.2 93.8 100.0 5.0 1,917 681 Somali 1.8 2.3 1.3 0.6 1.4 0.0 92.6 100.0 5.4 128 358 Benishangul-Gumuz 5.3 0.8 0.5 0.5 2.8 0.9 89.3 100.0 6.5 51 373 SNNP 3.2 1.4 0.8 0.2 1.1 0.0 93.2 100.0 5.5 926 600 Gambela 14.7 0.8 3.3 1.3 1.2 0.0 78.7 100.0 18.8 15 317 Harari 19.2 6.3 2.9 2.6 2.8 0.3 65.9 100.0 28.4 11 246 Addis Ababa 22.7 21.3 3.7 1.6 2.2 2.2 46.3 100.0 47.7 95 167 Dire Dawa 12.2 3.9 2.5 0.0 2.3 0.9 78.1 100.0 18.7 14 254 Education No education 1.5 1.0 0.5 0.2 1.2 0.0 95.6 100.0 3.0 2,956 2,845 Primary 5.6 2.6 0.7 0.2 2.0 0.4 88.6 100.0 8.8 1,296 1,184 Secondary 22.9 16.4 3.2 0.7 1.0 0.9 54.8 100.0 42.6 136 173 More than secondary 39.6 13.2 1.8 0.6 0.0 1.9 42.9 100.0 54.6 65 82 Wealth quintile Lowest 0.9 1.5 0.5 0.2 1.0 0.0 95.9 100.0 2.8 1,047 1,311 Second 1.0 0.6 0.3 0.0 1.7 0.0 96.4 100.0 1.9 988 782 Middle 1.0 0.0 0.2 0.1 1.6 0.0 97.2 100.0 1.2 917 704 Fourth 1.9 1.1 1.7 0.3 0.7 0.4 93.9 100.0 4.7 784 656 Highest 18.4 8.8 1.0 0.4 2.4 0.5 68.7 100.0 28.1 717 831 Total 3.9 2.1 0.7 0.2 1.4 0.2 91.5 100.0 6.7 4,453 4,284 1 Includes women who received a checkup after 41 days. Differences by women’s background characteristics are pronounced. Women under age 35, women who delivered their first live birth, urban mothers, those residing in Addis Ababa, and mothers with higher levels of education, and those in the highest wealth quintiles were most likely to have received a postnatal checkup in the first two days after childbirth. Table 9.10 shows the type of health care provider of the first postnatal checkup according to women’s background characteristics. Six percent of women received postnatal care from a doctor, nurse, or midwife. Less than 1 percent of women received care from a HEW. Differentials by background characteristics of the mother are similar to the differences for postnatal care coverage in general. Women having their first baby were more likely than women with a higher birth order to receive postnatal care from a doctor, nurse, or midwife. Thirty-two percent of women in urban areas received a postnatal checkup from a health professional compared with 2 percent of rural women. A higher proportion of women living in Addis Ababa (48 percent), women with more than secondary education (52 percent), and women in the highest wealth quintile (28 percent) received their first postnatal check-up from a doctor, nurse, or midwife compared with their counterparts. Maternal Health • 131 Table 9.10 Type of provider of first postnatal checkup for the mother Among women age 15-49 giving birth in the two years preceding the survey, the percent distribution by type of provider of the mother's first postnatal health check in the two days after the last live birth, according to background characteristics, Ethiopia 2011 Background characteristic Type of health provider of mother's first postnatal checkup No postnatal checkup in the first two days after birth1 Total Weighted number of women Unweighted number of women Doctor/ nurse/ midwife HEW Mother's age at birth <20 4.7 0.9 94.4 100.0 557 574 20-34 7.1 0.3 92.6 100.0 3,198 3,092 35-49 3.7 0.6 95.7 100.0 697 618 Birth order 1 13.9 1.0 85.1 100.0 800 809 2-3 6.6 0.3 93.1 100.0 1,449 1,390 4-5 3.7 0.1 96.2 100.0 1,008 992 6+ 3.0 0.4 96.6 100.0 1,195 1,093 Place of delivery Health facility 49.9 0.5 49.6 100.0 517 653 Elsewhere 0.5 0.4 99.1 100.0 3,936 3,631 Residence Urban 32.0 0.0 67.9 100.0 607 751 Rural 2.2 0.5 97.3 100.0 3,846 3,533 Region Tigray 12.3 0.8 86.9 100.0 273 434 Affar 5.9 0.1 94.0 100.0 40 378 Amhara 5.1 0.0 94.9 100.0 983 476 Oromiya 4.4 0.6 95.0 100.0 1,917 681 Somali 5.1 0.0 94.6 100.0 128 358 Benishangul-Gumuz 6.5 0.0 93.5 100.0 51 373 SNNP 5.0 0.5 94.5 100.0 926 600 Gambela 18.8 0.0 81.2 100.0 15 317 Harari 24.2 0.0 71.6 100.0 11 246 Addis Ababa 47.7 0.0 52.3 100.0 95 167 Dire Dawa 18.7 0.0 81.3 100.0 14 254 Education No education 2.8 0.3 97.0 100.0 2,956 2,845 Primary 8.2 0.6 91.2 100.0 1,296 1,184 Secondary 42.6 0.0 57.4 100.0 136 173 More than secondary 52.3 2.3 45.4 100.0 65 82 Wealth quintile Lowest 2.8 0.1 97.2 100.0 1,047 1,311 Second 1.3 0.7 98.1 100.0 988 782 Middle 1.1 0.1 98.8 100.0 917 704 Fourth 3.7 1.0 95.3 100.0 784 656 Highest 27.7 0.3 71.9 100.0 717 831 Total 6.3 0.4 93.3 100.0 4,453 4,284 HEW = Health Extension Worker 1 Includes women who received a checkup after 41 days. 9.6 PROBLEMS IN ACCESSING HEALTH CARE Many factors can prevent women from getting medical advice or treatment for themselves when they are sick. Information on such factors is particularly important in understanding and addressing the barriers women may face in seeking care during pregnancy and at the time of delivery. Where health services are present, there are many factors—social, cultural, and economic— that cause women not to use the services, particularly when the health concern is related to sexual or reproductive matters. The 2011 EDHS asked women whether each of the following factors would be a big problem or not a big problem in seeking health care for themselves: getting permission to go for treatment, getting money for treatment, distance to health facility, not wanting to go alone, having to take transport, concern there may not be a female provider or any health provider, concern that drugs may not be available, and workload inside and outside the house. Table 9.11 shows the results by women’s characteristics. 132 • Maternal Health Ninety-four percent of women reported that they have at least one of the specified problems when accessing health care for themselves. The most important barrier to women’s access to health services is taking transport to a facility (71 percent), followed by lack of money (68 percent), and distance to a health facility (66 percent). More than six women in every ten (61 percent) were concerned about their workload inside and outside the home. Also, about six in every ten (58 percent) were concerned that drugs may not be available at the facility or said that they did not want to go alone to a health facility. More than half of women were concerned that there may not be a health provider at the health facility (56 percent) or that there may not be a female health provider (53 percent). Twenty-nine percent expressed concern about getting permission to go for treatment. Rural women reported the most problems with access to health care. Among regions, women in Somali (98 percent) and Gambela (97 percent) were most likely to report at least one problem when accessing health care for themselves, while women in Addis Ababa were the least likely (74 percent). Women with more than secondary education (72 percent) and women in the highest wealth quintile (84 percent) were least likely to report at least one problem when accessing health care for themselves. Maternal Health • 133 Table 9.11 Problems in accessing health care Percentage of women age 15-49 who reported that they have serious problems in accessing health care for themselves when they are sick, by type of problem, according to background characteristics, Ethiopia 2011 Background characteristic Problems in accessing health care Weighted number of women Un- weighted number of women Getting permission to go for treatment Getting money for treatment Distance to health facility Not wanting to go alone Having to take transport Concern there may not be a female health provider Concern there may not be a health provider Concern there may not be drugs Work- load inside/ outside home At least one problem accessing health care Age < 20 29.7 60.5 61.7 54.0 65.9 50.2 52.4 56.0 53.2 91.8 4,009 3,835 20-34 28.7 67.2 65.7 60.0 70.9 53.8 55.7 58.3 62.3 93.6 8,132 8,307 35-49 28.7 75.4 71.2 59.2 76.1 54.9 58.0 59.7 66.3 95.4 4,374 4,373 Number of living children 0 27.5 59.6 58.5 52.6 62.7 49.2 51.3 54.4 52.0 90.4 5,708 5,771 1-2 28.0 66.4 63.9 60.0 70.2 52.0 56.4 58.7 62.0 93.0 3,987 4,257 3-4 29.3 73.9 70.5 63.8 75.9 57.2 57.2 60.8 67.8 96.4 3,219 3,151 5+ 31.7 76.6 77.1 60.7 81.0 57.4 59.6 60.8 68.8 97.0 3,601 3,336 Marital status Never married 27.8 59.6 56.9 52.2 61.6 48.3 51.2 54.4 51.4 90.1 4,469 4,413 Married or living together 30.8 69.8 71.6 60.7 76.0 55.9 57.8 60.2 65.5 95.0 10,287 10,204 Divorced/ separated/ widowed 20.4 76.1 58.3 59.8 66.5 50.1 53.2 55.2 60.7 94.9 1,758 1,898 Employed last 12 months Not employed 31.8 68.4 67.5 56.4 71.8 55.9 57.0 59.8 60.4 93.1 6,980 7,982 Employed for cash 26.2 67.0 61.9 58.2 67.7 50.9 54.2 56.9 63.3 92.8 6,015 6,054 Employed not for cash 27.6 67.4 70.8 62.3 75.5 51.8 54.7 56.6 58.9 96.2 3,508 2,469 Residence Urban 17.0 51.6 31.4 40.5 38.4 37.9 42.3 44.5 46.1 83.4 3,947 5,329 Rural 32.6 72.8 77.1 63.9 81.3 58.1 59.6 62.4 65.9 96.9 12,568 11,186 Region Tigray 5.8 46.6 52.1 48.9 52.4 31.9 47.3 51.1 37.1 85.0 1,104 1,728 Affar 38.6 61.8 75.0 62.0 77.7 74.5 76.6 77.1 67.8 90.7 145 1,291 Amhara 20.0 65.8 58.9 51.3 66.4 48.8 42.7 45.9 57.9 95.7 4,433 2,087 Oromiya 37.1 71.9 75.2 68.1 79.7 56.1 61.5 64.4 67.6 95.7 6,011 2,135 Somali 50.8 74.8 71.6 63.0 77.9 78.8 76.7 78.2 72.0 97.6 329 914 Benishangul- Gumuz 32.0 61.2 74.5 66.2 75.0 73.0 75.0 76.6 67.4 96.1 174 1,259 SNNP 36.0 76.6 74.7 60.1 77.6 61.2 65.1 66.9 68.3 95.1 3,236 2,034 Gambela 29.8 63.7 70.4 61.5 76.3 67.1 73.3 77.3 58.6 97.3 69 1,130 Harari 16.8 48.8 45.2 42.4 49.9 57.0 60.6 64.0 54.0 82.9 49 1,101 Addis Ababa 11.1 44.8 25.6 29.4 33.3 35.5 36.2 36.0 32.6 74.3 896 1,741 Dire Dawa 28.0 53.1 49.1 55.0 55.6 54.4 68.1 69.5 57.2 87.9 69 1,095 Education No education 32.7 77.3 75.7 63.0 80.8 58.3 59.3 61.3 67.0 97.2 8,394 8,278 Primary 28.2 63.0 62.8 58.4 67.2 51.5 54.4 57.7 59.2 93.2 6,276 5,858 Secondary 14.7 46.8 38.7 41.8 44.6 39.2 46.9 49.6 45.5 83.1 1,117 1,395 More than secondary 13.2 30.7 27.4 28.7 32.8 32.0 34.7 37.7 34.2 72.2 728 984 Wealth quintile Lowest 32.7 78.1 80.6 63.6 84.2 60.2 60.8 63.8 67.3 97.5 2,986 3,711 Second 33.1 76.6 79.0 65.8 83.9 60.7 60.3 62.9 63.9 97.0 3,041 2,402 Middle 35.0 73.5 78.0 63.8 82.6 58.7 62.5 64.1 68.0 96.6 3,031 2,268 Fourth 31.6 67.2 71.0 63.6 74.4 53.9 55.2 58.5 66.5 97.1 3,215 2,505 Highest 16.8 50.3 34.8 41.3 41.9 38.7 43.6 46.0 46.0 83.7 4,242 5,629 Total 28.9 67.7 66.2 58.3 71.1 53.2 55.5 58.1 61.2 93.6 16,515 16,515 Note: Total includes 12 cases with missing information on employment in the last 12 months Child Health • 135 CHILD HEALTH 10 his chapter presents findings on several areas of importance relating to child health; characteristics of the neonate (birth weight and size at birth), immunisation, and important childhood illnesses and their treatment. Information on treatment practices and contact with health services for children with three childhood illnesses (acute respiratory infection, fever, and diarrhoea), helps in the assessment of national programmes aimed at reducing mortality. The government of Ethiopia has formulated a number of strategies that provide a framework for improving child health. One of the priorities in the Health Sector Development Plan (HSDP) IV is improving child health, with a goal to reduce the under-five mortality rate to 68 per 1,000 live births and the infant mortality rate to 31 per 1,000 live births by 2015 (MOH, 2010). 10.1 CHILD’S SIZE AT BIRTH A child’s birth weight or size at birth is an important indicator of the child’s vulnerability to the risk of childhood illnesses and the child’s chances of survival. Children whose birth weight is less than 2.5 kilograms, or children reported to be “very small” or “smaller than average”, have a higher than average risk of early childhood death. The 2011 EDHS questionnaire recorded birth weight, if available from written records or mother’s recall, for all births in the five years preceding the survey. Because birth weight may not be known for many babies, and particularly for babies delivered at home and not weighed at birth, the mother’s estimate of the baby’s size at birth was also obtained. Although subjective, mothers’ estimates can be a useful proxy for the weight of the child. Table 10.1 presents information on children’s weight and size at birth. T Key Findings • One in every four children age 12-23 months (24 percent) were fully vaccinated at the time of the survey, a 19 percent increase from the level reported in the 2005 EDHS. • Seven percent of children under age five showed symptoms of acute respiratory infection (ARI) in the two weeks before the survey and for 27 percent of them advice or treatment was sought from a health care facility or provider. • Seventeen percent of children under age 5 had a fever in the two weeks before the survey, and for one-fourth of them advice or treatment was sought from a health care facility or provider. • Thirteen percent of children under age 5 had diarrhoea, and 3 percent had had diarrhoea with blood, in the two weeks before the survey. • The proportion of children with diarrhoea for whom advice or treatment was sought from a health care provider increased from 13 percent in 2000 to 22 percent in 2005 and 32 percent in 2011. 136 • Child Health Only 5 percent of children in Ethiopia are weighed at birth. This is not surprising because the majority of births do not take place in a health facility, and children are less likely to be weighed at birth in a non-institutional setting. Among children born in the five years before the survey with a reported birth weight, 11 percent weighed less than 2.5 kilograms. Low birth weight is more common among children of the youngest mothers, age less than 20 (13 percent) and older mothers, age 35-49 (17 percent), and children of birth order six and above (16 percent). The birth weight of a child also varies by place of residence. Seventeen percent of births in rural areas, compared with 9 percent in urban areas, have a reported birth weight less than 2.5 kg. As noted, a mother’s subjective assessment of the size of the baby at birth, in the absence of birth weight, may be useful. Mothers reported 21 percent of all live births in the five years preceding the survey to be very small and 9 percent as smaller than average. Children born to very young mothers (<20 years), first-order births, children of mothers with no education, and children born to mothers in the lowest wealth quintile were the most likely to be reported as very small. Nearly three children of every ten born to mothers residing in Affar (30 percent), Amhara (28 percent), Somali (26 percent), and Gambela (27 percent) were reported as very small at birth. C hi ld H ea lth • 1 37 Ta bl e 10 .1 C hi ld 's w ei gh t a nd s iz e at b irt h P er ce nt ag e of li ve b irt hs in th e fiv e ye ar s pr ec ed in g th e su rv ey w ith a re po rte d bi rth w ei gh t; am on g liv e bi rth s in th e fiv e ye ar s pr ec ed in g th e su rv ey w ith a re po rte d bi rth w ei gh t, pe rc en t d is tri bu tio n by bi rth w ei gh t; an d pe rc en t d is tri bu tio n of a ll liv e bi rth s in th e fiv e ye ar s pr ec ed in g th e su rv ey b y m ot he r's e st im at e of b ab y' s si ze a t b irt h, 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 P er ce nt ag e of al l b irt hs w ith a re po rte d bi rth w ei gh t1 P er ce nt d is tri bu tio n of b irt hs w ith a re po rte d bi rth w ei gh t1 P er ce nt d is tri bu tio n of a ll liv e bi rth s by s iz e of ch ild a t b irt h To ta l W ei gh te d nu m be r o f bi rth s U nw ei gh te d nu m be r o f bi rth s Le ss th an 2. 5 kg 2. 5 kg o r m or e To ta l W ei gh te d nu m be r o f bi rth s U nw ei gh te d nu m be r o f bi rth s V er y sm al l S m al le r th an av er ag e A ve ra ge o r la rg er D on 't kn ow / m is si ng M ot he r's a ge a t b irt h <2 0 5. 8 12 .8 87 .2 10 0. 0 89 15 8 26 .4 9. 0 64 .0 0. 6 10 0. 0 1, 54 1 1, 65 0 20 -3 4 5. 6 9. 9 90 .1 10 0. 0 49 0 88 5 19 .4 8. 6 71 .7 0. 3 10 0. 0 8, 67 5 8, 42 9 35 -4 9 2. 5 17 .1 82 .9 10 0. 0 42 75 21 .0 9. 0 69 .2 0. 7 10 0. 0 1, 65 7 1, 57 5 B irt h or de r 1 11 .1 11 .3 88 .7 10 0. 0 25 2 46 9 25 .5 8. 7 65 .0 0. 8 10 0. 0 2, 26 2 2, 30 3 2- 3 6. 6 11 .7 88 .3 10 0. 0 24 5 42 9 20 .3 8. 8 70 .7 0. 2 10 0. 0 3, 69 4 3, 71 7 4- 5 2. 9 3. 8 96 .2 10 0. 0 80 14 4 18 .2 7. 9 73 .8 0. 2 10 0. 0 2, 72 8 2, 67 8 6+ 1. 4 15 .7 84 .3 10 0. 0 44 76 19 .3 9. 2 70 .9 0. 6 10 0. 0 3, 18 8 2, 95 6 M ot he r's s m ok in g st at us S m ok es c ig ar et te s/ to ba cc o * * * 10 0. 0 0 2 18 .4 1. 2 80 .0 0. 3 10 0. 0 33 95 D oe s no t s m ok e 5. 2 10 .7 89 .3 10 0. 0 62 0 1, 11 6 20 .5 8. 7 70 .3 0. 4 10 0. 0 11 ,8 38 11 ,5 52 R es id en ce U rb an 31 .9 9. 1 90 .9 10 0. 0 48 8 92 8 17 .6 6. 5 75 .0 1. 0 10 0. 0 1, 52 8 1, 98 6 R ur al 1. 3 17 .0 83 .0 10 0. 0 13 3 19 0 21 .0 9. 0 69 .7 0. 3 10 0. 0 10 ,3 44 9, 66 8 R eg io n Ti gr ay 8. 1 10 .1 89 .9 10 0. 0 61 85 21 .1 10 .8 67 .7 0. 4 10 0. 0 75 3 1, 20 2 A ffa r (3 .7 ) (1 4. 0) (8 6. 0) 10 0. 0 5 30 30 .3 10 .2 59 .4 0. 1 10 0. 0 12 1 1, 13 0 A m ha ra (3 .2 ) (1 1. 2) (8 8. 8) 10 0. 0 86 33 27 .9 12 .3 59 .3 0. 6 10 0. 0 2, 65 6 1, 29 4 O ro m iy a 3. 6 12 .0 88 .0 10 0. 0 18 1 67 18 .7 7. 3 73 .6 0. 4 10 0. 0 5, 01 4 1, 76 1 S om al i 6. 4 14 .8 85 .2 10 0. 0 23 62 26 .2 7. 0 66 .5 0. 3 10 0. 0 36 4 1, 02 7 B en is ha ng ul -G um uz (5 .3 ) (7 .2 ) (9 2. 8) 10 0. 0 7 36 20 .6 3. 9 74 .9 0. 6 10 0. 0 14 0 1, 02 0 S N N P (3 .1 ) (5 .7 ) (9 4. 3) 10 0. 0 79 42 15 .2 7. 6 77 .0 0. 2 10 0. 0 2, 49 4 1, 61 4 G am be la 22 .1 13 .1 86 .9 10 0. 0 9 10 1 27 .4 5. 9 66 .3 0. 5 10 0. 0 40 85 1 H ar ar i 28 .1 8. 4 91 .6 10 0. 0 8 17 8 19 .4 9. 2 70 .3 1. 0 10 0. 0 29 65 9 A dd is A ba ba 66 .9 11 .4 88 .6 10 0. 0 14 8 27 8 17 .7 7. 2 74 .1 1. 0 10 0. 0 22 2 40 0 D ire D aw a 34 .8 11 .9 88 .1 10 0. 0 14 20 6 16 .1 12 .9 70 .1 0. 9 10 0. 0 39 69 6 M ot he r's e du ca tio n N o ed uc at io n 1. 3 13 .2 86 .8 10 0. 0 11 0 27 0 21 .7 9. 7 68 .1 0. 5 10 0. 0 8, 22 7 8, 14 2 P rim ar y 7. 9 8. 2 91 .8 10 0. 0 25 5 44 6 18 .6 6. 2 75 .0 0. 2 10 0. 0 3, 21 1 2, 93 0 S ec on da ry 49 .7 11 .5 88 .5 10 0. 0 13 2 24 0 14 .6 8. 6 75 .6 1. 2 10 0. 0 26 6 38 6 M or e th an s ec on da ry 73 .0 13 .3 86 .7 10 0. 0 12 3 16 2 10 .4 5. 0 82 .6 2. 0 10 0. 0 16 8 19 6 W ea lth q ui nt ile Lo w es t (0 .5 ) (2 0. 7) (7 9. 3) 10 0. 0 13 48 24 .7 9. 9 65 .0 0. 4 10 0. 0 2, 71 0 3, 62 5 S ec on d (0 .7 ) (1 1. 5) (8 8. 5) 10 0. 0 19 25 19 .9 9. 2 70 .2 0. 7 10 0. 0 2, 65 8 2, 11 4 M id dl e * * * 10 0. 0 20 22 22 .4 9. 5 67 .9 0. 1 10 0. 0 2, 43 7 1, 87 2 Fo ur th 2. 4 16 .8 83 .2 10 0. 0 54 78 17 .5 8. 1 74 .1 0. 3 10 0. 0 2, 27 2 1, 87 0 H ig he st 28 .7 10 .2 89 .8 10 0. 0 51 5 94 5 16 .4 5. 7 77 .2 0. 7 10 0. 0 1, 79 5 2, 17 3 To ta l 5. 2 10 .8 89 .2 10 0. 0 62 1 1, 11 8 20 .5 8. 7 70 .4 0. 4 10 0. 0 11 ,8 72 11 ,6 54 N ot e: T ot al in cl ud es 2 c as es w ith m is si ng in fo rm at io n on m ot he r’s s m ok in g st at us . F ig ur es in p ar en th es es a re b as ed o n 25 -4 9 un w ei gh te d ca se s. A n as te ris k in di ca te s th at a fi gu re is b as ed o n fe w er th an 2 5 un w ei gh te d ca se s an d ha s be en s up pr es se d. 1 B as ed o n ei th er a w rit te n re co rd o r t he m ot he r's re ca ll • 137 Child Health 138 • Child Health 10.2 VACCINATION COVERAGE Immunisation coverage is one of the indicators used to monitor progress towards the achievement of MDG4 and the reduction of child morbidity and mortality, as it is one of the most cost-effective public health interventions for reaching these goals. In order to reduce child morbidity and mortality, the HSDP IV has initiated several activities. The major focus areas are strengthening routine immunisation, expansion of community services and facility-based Integrated Management of Neonatal and Childhood Illnesses (IMNCI), strengthening the Health Extension Program (HEP), and implementing locally relevant and effective child health interventions. According to guidelines developed by the World Health Organization, children are considered fully vaccinated when they have received a vaccination against tuberculosis (BCG), three doses each of the DPT and polio vaccines, and a measles vaccination by the age of 12 months. The pentavalent vaccine DPT-HepB-Hib, introduced in 2007, has replaced the previous DPT vaccine. This new vaccine protects against diphtheria, pertussis (whooping cough), tetanus, hepatitis B, and Haemophilus influenzae type b. In Ethiopia, the vaccination policy calls for BCG vaccine given at birth or at first clinical contact, three doses of DPT-HepB-Hib vaccine given at approximately 4, 8, and 12 weeks of age, four doses of oral polio vaccine given approximately at 0-2, 4, 8, and 12 weeks of age, and measles vaccine given at or soon after reaching 9 months of age. The 2011 EDHS collected information on vaccination coverage in two ways: from vaccination cards shown to the interviewer and from mothers’ verbal reports. If the cards were available, the interviewer copied the vaccination dates directly onto the questionnaire. When there was no vaccination card for the child or if a vaccine had not been recorded on the card as being given, the respondent was asked to recall the vaccines given to her child. Vaccinations reported on the vaccination card represent vaccines given by routine immunization services, while vaccines based on mother’s recall usually include routine and other immunization services such as campaigns. Table 10.2 and Figure 10.1 show the percentage of children age 12-23 months who have received the various vaccinations by source of information, either vaccination card or mother’s report. This is the youngest cohort of children who have reached the age by which they should be fully vaccinated. The third row of the table shows the proportion of children 12-23 months who were immunised at any age up to the time of the survey according to either the mother’s report or the vaccination card, while the last row shows the proportion who were vaccinated by age 12 months, the age at which vaccination coverage should be complete. Overall, 24 percent of children age 12-23 months were fully vaccinated at the time of the survey. While this represents a 19 percent increase from the level reported in the 2005 EDHS, the percentage of children who are fully vaccinated remains far below the goal of 66 percent coverage set in the HSDP IV (MOH, 2010). Data from the EDHS generally show vaccination coverage to be lower than data in the service statistics from the Ministry of Health. However, comparisons of data from various sources should consider differences in the sampling frame, design, sample size, representativeness of the sample, and selection methodology, as well as differences in the source of information, phrasing of questions, and reporting of data, all of which could help to explain these differences. Child Health • 139 As for coverage for specific vaccines, 66 percent of children had received the BCG vaccine, and 56 percent had received the measles vaccine. A relatively high percentage of children received the first DPT dose (64 percent). However, only 37 percent went on to receive the third dose of DPT, reflecting a dropout rate of 43 percent. More than eight children of every ten (82 percent) received the first dose of polio, but only about four in ten (44 percent) received the third dose, reflecting a dropout rate of 46 percent. Even though DPT and polio vaccines are often routinely administered at the same time, polio coverage is higher than DPT coverage. This is primarily due to the success of the national immunisation day campaigns, during which polio vaccines are administered. Table 10.2 Vaccinations by source of information Percentage of children age 12-23 months who received specific vaccines at any time before the survey, by source of information (vaccination card or mother's report), and percentage vaccinated 12 months of age, Ethiopia 2011 Source of information BCG DPT Polio1 Measles All basic vac- cinations2 No vac- cinations Weighted number of children Unweighted number of children DPT 1 DPT 2 DPT 3 Polio 0 Polio 1 Polio 2 Polio 3 Vaccinated at any time before survey Vaccination card 25.5 28.1 25.2 21.9 10.8 27.4 24.2 20.5 22.0 16.3 0.0 554 629 Mother's report 40.8 35.5 27.2 14.6 8.9 54.9 45.9 23.8 33.8 8.0 14.5 1,376 1,298 Either source 66.3 63.5 52.4 36.5 19.7 82.3 70.0 44.3 55.7 24.3 14.5 1,930 1,927 Vaccinated by 12 months of age3 65.2 62.2 50.3 34.7 19.7 80.9 67.4 43.1 49.3 21.7 16.0 1,930 1,927 1 Polio 0 is the polio vaccination given at birth. 2 BCG, measles and three doses each of DPT and polio vaccine excluding polio vaccine given at birth. 3 For children whose information was based on the mother's report, the proportion of vaccinations given during the first year of life is assumed to be the same as for children with a written record of vaccination. Figure 10.1 Percentage of Children Age 12-23 Months with Specific Vaccinations EDHS 2011 66 64 52 37 20 82 70 44 56 24 15 BCG 1 2 3 0 1 2 3 Measles All No vaccinations 0 20 40 60 80 100 P er ce n t ag e v ac ci na te d at a ny ti m e be fo r e th e su rv ey DPT Polio Note: Based on vaccination cards and mother’s reports 1BCG, measles, and three doses each of DPT and polio vaccine (excluding polio 0) 140 • Child Health 10.2.1 Vaccination Coverage by Background Characteristics Table 10.3 presents vaccination coverage among children age 12-23 months by background characteristics. Female children are slightly more likely to be fully vaccinated (26 percent) than male children (23 percent). First births are more likely to be fully immunised (30 percent) than births of order six and higher (20 percent). Urban children are more than two times as likely as rural children to have all basic vaccinations (48 percent compared with 20 percent). Children whose mothers have secondary education are more likely to be fully immunised than those born to mothers with no education (57 and 20 percent, respectively). Similarly, 51 percent of children in the highest wealth quintile are fully immunised, compared with 17 percent of children in the lowest wealth quintile. There is a wide variation among regions in full vaccination coverage, ranging from 79 percent in Addis Ababa to 9 percent in Affar. Table 10.3 shows that mothers had vaccination cards for only 29 percent of children age 12-23 months. The actual percentage of children who have a vaccination card may be higher because in some areas the cards are kept at the health centre and not by mothers. Mothers were most likely to show vaccination cards for female children, first births, children living in urban areas, children in Addis Ababa, children of mothers with at least some secondary education, and children of mothers in the highest wealth quintile. Table 10.3 Vaccinations by background characteristics Percentage of children age 12-23 months who received specific vaccines at any time before the survey (according to a vaccination card or the mother's report), and percentage with a vaccination card, by background characteristics, Ethiopia 2011 Background characteristic BCG DPT Polio1 Measles All basic vac- cinations2 No vac- cinations Percentage with a vaccination card seen Weighted number of children Un- weighted number of children DPT 1 DPT 2 DPT 3 Polio 0 Polio 1 Polio 2 Polio 3 Sex Male 64.3 60.4 49.6 34.3 18.7 81.9 68.6 42.3 55.7 23.1 15.0 26.0 1,010 983 Female 68.5 67.0 55.4 38.8 20.9 82.8 71.6 46.5 55.7 25.7 14.1 31.6 920 944 Birth order 1 71.1 68.4 57.1 40.7 29.7 82.9 71.0 46.5 61.0 29.8 13.5 35.1 358 364 2-3 68.6 63.5 51.3 37.5 22.8 84.1 69.6 43.7 52.6 24.2 12.3 30.2 624 637 4-5 66.5 63.3 54.0 37.0 12.7 84.2 76.0 49.8 61.7 24.5 14.3 27.1 450 444 6+ 59.9 60.3 48.9 31.7 15.0 78.0 64.5 38.7 50.3 20.3 18.4 23.6 497 482 Residence Urban 81.6 79.8 73.9 60.5 53.7 89.1 82.2 65.7 79.6 48.1 6.1 54.8 274 350 Rural 63.8 60.9 48.8 32.5 14.1 81.2 68.0 40.8 51.8 20.4 15.9 24.4 1,656 1,577 Region Tigray 95.9 93.8 88.6 73.4 28.8 97.4 90.8 76.4 83.7 58.9 1.8 58.3 129 203 Affar 38.1 30.4 16.8 10.3 10.6 51.0 33.1 18.4 30.3 8.6 47.3 13.5 18 174 Amhara 67.7 68.6 53.6 38.4 18.1 86.5 76.6 47.0 62.0 26.3 9.6 31.1 446 222 Oromiya 57.4 50.4 41.0 26.8 15.5 77.0 61.5 35.8 45.9 15.6 19.4 22.9 811 290 Somali 45.7 41.4 34.9 25.3 18.9 59.8 48.4 27.9 39.5 16.6 35.4 23.7 51 150 Benishangul- Gumuz 68.7 73.3 62.2 41.7 36.4 85.5 75.8 45.7 67.2 23.6 13.0 28.9 23 170 SNNP 73.4 74.7 60.9 38.1 18.8 85.6 74.7 46.9 57.8 24.1 11.8 23.4 391 253 Gambela 72.0 72.4 48.3 27.6 35.7 87.4 73.4 41.5 51.7 15.5 7.7 23.7 8 151 Harari 72.9 76.4 66.7 51.8 30.4 92.0 81.6 59.6 64.7 34.1 8.0 37.1 5 115 Addis Ababa 97.5 94.5 92.1 89.2 87.3 97.5 92.8 81.7 93.5 78.7 2.5 79.9 43 81 Dire Dawa 87.5 90.2 86.4 75.3 43.8 96.3 89.9 79.3 79.9 58.6 3.0 52.1 7 118 Mother's education No education 60.1 56.8 45.6 31.2 14.4 78.9 64.7 40.2 49.9 20.1 18.1 24.4 1,307 1,293 Primary 75.4 75.0 62.1 42.6 23.7 87.4 77.7 49.1 63.8 28.3 8.5 34.5 522 512 Secondary 99.8 99.2 95.1 79.2 68.6 99.7 99.7 73.7 82.1 57.0 0.0 50.3 59 79 More than secondary (99.4) (81.5) (81.5) (63.9) (66.2) (99.5) (99.4) (73.0) (99.5) (57.7) (0.5) (58.0) 43 43 Wealth quintile Lowest 58.0 55.0 42.4 26.0 11.7 79.5 65.2 37.8 45.3 16.8 16.3 17.3 441 570 Second 65.8 56.5 45.2 29.4 10.5 81.3 70.3 39.9 52.0 18.2 16.3 18.8 419 338 Middle 61.8 60.1 47.1 31.0 12.9 78.5 65.6 41.5 52.0 18.2 17.6 26.5 394 312 Fourth 68.1 67.9 56.6 42.2 20.8 82.3 67.1 41.7 56.4 24.9 16.4 33.1 369 314 Highest 82.6 84.6 78.3 61.5 51.5 92.4 86.0 66.7 79.7 50.5 3.5 56.1 307 393 Total 66.3 63.5 52.4 36.5 19.7 82.3 70.0 44.3 55.7 24.3 14.5 28.7 1,930 1,927 Note: Figures in parentheses are based on 25-49 unweighted cases. 1 Polio 0 is the polio vaccination given at birth. 2 BCG, measles and three doses each of DPT and polio vaccine (excluding polio vaccine given at birth). Child Health • 141 10.3 TRENDS IN VACCINATION COVERAGE One way of measuring trends in vaccination coverage is to compare coverage among children of different ages in the 2011 EDHS. Table 10.4 shows the percentage of children who have received vaccinations during the first year of life by current age. These data provide information on trends in vaccination coverage over the past five years. There are notable changes in vaccination coverage over the past five years. The percentage of children who have received no vaccinations at all by 12 months of age has declined over the past four years from 24 percent among children age 48-59 months at the time of the survey to 16 percent among children age 12-23 months. The percentage of children fully immunised by age 12 months has increased only slightly, however, from 20 percent to 22 percent. Mothers showed vaccination cards for 29 percent of children age 12-23 months but for only 13 percent of children age 48-59 months. This may be because vaccination cards for older children have been discarded. Table 10.4 Vaccinations in first year of life Percentage of children age 12-59 months at the time of the survey who received specific vaccines by 12 months of age, and percentage with a vaccination card, by current age of child, Ethiopia 2011 Age in months BCG DPT Polio1 Measles All basic vac- cinations2 No vac- cinations Percentage with a vaccination card seen Weighted number of children Un- weighted number of children DPT 1 DPT 2 DPT 3 Polio 0 Polio 1 Polio 2 Polio 3 12-23 65.2 62.2 50.3 34.7 19.7 80.9 67.4 43.1 49.3 21.7 16.0 28.7 1,930 1,927 24-35 63.2 56.0 46.5 30.9 15.0 78.6 70.7 48.6 45.0 19.6 19.0 20.9 2,063 2,099 36-47 61.2 54.5 44.8 31.9 17.2 78.6 73.2 52.2 43.4 19.4 19.8 15.7 2,381 2,311 48-59 60.1 52.9 43.8 28.5 12.6 73.8 70.2 52.1 42.8 19.9 24.1 13.4 2,282 2,217 Total 62.8 56.6 46.5 31.8 16.0 78.7 70.9 50.1 45.7 20.2 19.1 19.2 8,657 8,554 Note: Information was obtained from the vaccination card or if there was no written record, from the mother. For children whose information was based on the mother's report, the proportion of vaccinations given during the first year of life is assumed to be the same as for children with a written record of vaccinations. 1 Polio 0 is the polio vaccination given at birth. 2 BCG, measles and three doses each of DPT and polio vaccine (excluding polio vaccine given at birth). Figure 10.2 shows trends in vaccination coverage by comparing similarly collected data in the 2011 EDHS with data from the 2000 and 2005 EDHS. Vaccination coverage in Ethiopia has increased markedly over the past ten years. The percentage of children age 12-23 months who were fully vaccinated at the time of the survey increased from 14 percent in 2000 to 20 percent in 2005 and 24 percent in 2011—a 70 percent increase over ten years and a 19 percent increase in the five years preceding the 2011 survey. The percentage who had received none of the six basic vaccinations increased from 17 percent to 24 percent between 2000 and 2005 and then decreased to 15 percent in 2011. With the exception of polio 3, the percentage of children who received all the other vaccinations has increased in the five years before the 2011 survey. 142 • Child Health Figure 10.2 Trends in Vaccination Coverage During the First Year of Life Among Children 12-23 Months, Ethiopia 2000-2011 EDHS 2000, 2005, 2011 46 21 35 27 14 17 60 32 45 35 20 24 66 37 44 56 24 15 BCG DPT 3 Polio 3 Measles All No vaccinations 0 10 20 30 40 50 60 70 80 2000 2005 2011 10.4 ACUTE RESPIRATORY INFECTION Acute respiratory infection (ARI) is among the leading causes of child morbidity and mortality in Ethiopia and throughout the world. Pneumonia is the most serious outcome of ARI in young children. Early diagnosis and treatment with antibiotics can prevent a large proportion of deaths that can result from pneumonia. The prevalence of symptoms of ARI was estimated by asking mothers whether their children under age five had been ill with a cough accompanied by short, rapid breathing in the two weeks preceding the survey. These data are subjective (i.e., based on the mother’s perception of illness) and not validated by a medical examination. Table 10.5 shows the percentage of children under age five who experienced symptoms of ARI in the two weeks preceding the survey. Seven percent of children showed symptoms of ARI in the two weeks before the survey. Symptoms of ARI were the most common among children age 6-23 months (9 percent). Children of mothers who smoke were notably more likely to have symptoms of ARI than children of non-smokers (13 percent versus 7 percent). Symptoms of ARI were also remarkably less common among children in households that use electricity or gas as cooking fuel (2 percent) than among children in households that use other cooking fuels (7 percent, the highest percentage, occurring in households using wood/straw). A lower proportion of children in urban areas, children of mothers have more than secondary education and those in the wealthiest quintile have symptoms of ARI than do children in rural areas, children of mothers with no education, and those in the lowest wealth quintiles. The proportion of children with ARI symptoms ranges from 1 percent of children in Harari to 11 percent of children in Benishangul-Gumuz. Mothers of 27 percent of children who had symptoms of ARI sought advice or treatment from a health facility or provider. Seven percent of children with ARI symptoms received antibiotics. Child Health • 143 Table 10.5 Prevalence and treatment of symptoms of ARI Among children under age five, the percentage who had symptoms of acute respiratory infection (ARI) in the two weeks preceding the survey and among children with symptoms of ARI, the percentage for whom advice or treatment was sought from a health facility or provider and the percentage who received antibiotics as treatment, according to background characteristics, Ethiopia 2011 Background characteristic Among children under age five: Percentage for whom advice or treatment was sought from a health facility or provider2 Among children under age five with symptoms of ARI: Percentage with symptoms of ARI1 Weighted number of children Unweighted number of children Percentage who received antibiotics Weighted number of children Unweighted number of children Age in months <6 7.1 1,265 1,211 25.9 3.1 90 87 6-11 9.0 1,120 1,043 32.2 5.1 101 93 12-23 8.8 1,930 1,927 36.1 12.3 171 160 24-35 6.7 2,063 2,099 26.8 8.3 139 166 36-47 7.3 2,381 2,311 20.3 5.1 173 148 48-59 4.4 2,282 2,217 19.1 3.4 100 118 Sex Male 6.9 5,676 5,515 25.4 7.8 393 386 Female 7.1 5,366 5,293 28.7 5.8 380 386 Mother's smoking status Smokes cigarettes/tobacco 12.8 28 86 * * 4 12 Does not smoke 7.0 11,012 10,716 27.1 6.8 769 760 Cooking fuel Electricity or gas 1.5 56 87 * * 1 1 Kerosene 6.1 56 180 * * 3 4 Charcoal 4.4 537 804 (80.3) (4.8) 24 26 Wood/straw3 7.3 9,612 9,318 24.9 7.3 706 715 Animal dung 5.2 758 405 (26.6) (0.0) 39 26 Residence Urban 4.8 1,436 1,865 46.9 0.7 69 100 Rural 7.3 9,606 8,943 25.0 7.4 703 672 Region Tigray 9.4 702 1,123 18.4 1.8 66 100 Affar 5.4 112 1,033 40.6 0.0 6 52 Amhara 6.4 2,478 1,203 29.4 6.0 159 80 Oromiya 7.0 4,665 1,637 23.4 9.9 328 116 Somali 8.8 339 951 18.7 2.1 30 75 Benishangul-Gumuz 10.6 127 925 42.9 7.6 13 97 SNNP 6.8 2,305 1,491 31.6 4.5 157 108 Gambela 9.2 37 782 52.5 10.9 3 83 Harari 1.3 27 616 * * 0 8 Addis Ababa 3.4 214 386 * * 7 10 Dire Dawa 6.7 37 661 (47.1) (3.2) 2 43 Mother's education No education 7.2 7,611 7,521 24.6 6.4 551 570 Primary 6.6 3,012 2,727 27.7 7.2 200 184 Secondary 7.2 252 369 * * 18 14 More than secondary 2.4 168 191 * * 4 4 Wealth quintile Lowest 7.6 2,476 3,327 15.5 3.0 188 256 Second 6.1 2,444 1,950 25.2 7.8 148 124 Middle 8.6 2,277 1,738 22.1 5.7 197 152 Fourth 8.0 2,158 1,752 33.2 11.7 173 146 Highest 4.0 1,687 2,041 61.7 6.1 67 94 Total 7.0 11,042 10,808 27.0 6.8 773 772 Note: Total includes 6 cases with missing information on mother’s smoking status. Figures in parentheses are based on 25-49 unweighted cases. An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. 1 Symptoms of ARI (cough accompanied by short, rapid breathing which was chest-related and/or by difficult breathing which was chest-related) is considered a proxy for pneumonia. 2 Excludes pharmacy, rug vendor/store, shop, and traditional healer. 3 Includes grass, shrubs, and crop residues. 10.5 FEVER Fever is a major manifestation of malaria and other acute infections in children. Malaria and fever contribute to high levels of malnutrition and mortality. While fever can occur year-round, malaria is more prevalent after the end of the rainy season. For this reason, temporal factors must be taken into account when interpreting fever as an indicator of malaria prevalence. Table 10.6 shows the percentage of children under five with fever during the two weeks preceding the survey and the percentage receiving various treatments, by selected background 144 • Child Health characteristics. Mothers reported that 17 percent of children under five had had fever in the two weeks preceding the survey. The prevalence of fever varied by age of child and was highest in children age 6-11 months and 12-23 months (25 and 22 percent, respectively). There is little variation in the prevalence of fever by sex of the child, place of residence, mother’s education, or household wealth. Prevalence of fever among children under five years varies from 11 percent in Harari to 28 percent in Gambela. The prevalence of fever is also relatively high among children living in Tigray and Benishangul-Gumuz (both 24 percent), Afar (23 percent), and Somali (21 percent). Among children with fever, nearly one-fourth sought advice or treatment for the fever at a health facility or health provider. Children age 12-35 months, male children, and children living in urban areas were more likely to have received advice or treatment than other children. Likewise, children of mothers with some secondary education and those in the wealthiest households were more likely to seek advice or treatment at a health facility or provider. Among children under five who had fever, 4 percent received antimalarial drugs and 7 percent received antibiotics to treat their fever. Child Health • 145 Table 10.6 Prevalence and treatment of fever Among children under age five, the percentage who had a fever in the two weeks preceding the survey; and among children with fever, the percentage for whom advice or treatment was sought from a health facility or provider, the percentage who took antimalarial drugs, and the percentage who received antibiotics as treatment, by background characteristics, Ethiopia 2011 Background characteristic Among children under age five: Among children under age five with fever Percentage with fever Weighted number of children Unweighted number of children Percentage for whom advice or treatment was sought from a health facility or provider1 Percentage who took antimalarial drugs Percentage who took antibiotic drugs Weighted number of children Unweighted number of children Age in months <6 17.6 1,265 1,211 22.8 1.1 3.7 222 207 6-11 24.8 1,120 1,043 23.1 2.9 7.5 278 283 12-23 21.8 1,930 1,927 27.7 3.8 7.3 421 484 24-35 18.1 2,063 2,099 26.7 5.2 5.6 373 433 36-47 14.6 2,381 2,311 21.5 3.9 6.7 348 353 48-59 10.6 2,282 2,217 21.1 3.6 10.3 243 322 Sex Male 18.3 5,676 5,515 25.3 3.4 7.4 1,038 1,086 Female 15.8 5,366 5,293 23.0 3.9 6.1 847 996 Residence Urban 15.7 1,436 1,865 37.8 2.5 4.9 226 321 Rural 17.3 9,606 8,943 22.4 3.8 7.1 1,659 1,761 Region Tigray 23.9 702 1,123 20.5 4.3 1.4 168 267 Affar 23.2 112 1,033 28.9 5.1 0.3 26 240 Amhara 16.6 2,478 1,203 18.2 0.9 4.5 412 204 Oromiya 14.9 4,665 1,637 26.6 1.4 11.2 695 244 Somali 20.9 339 951 18.5 2.8 4.2 71 195 Benishangul-Gumuz 23.7 127 925 40.0 12.9 8.0 30 214 SNNP 19.0 2,305 1,491 23.6 8.8 5.0 438 294 Gambela 27.9 37 782 46.5 19.3 4.7 10 228 Harari 11.3 27 616 46.0 1.4 3.1 3 69 Addis Ababa 12.3 214 386 (67.3) (0.0) (4.7) 26 46 Dire Dawa 13.5 37 661 50.7 1.1 8.1 5 81 Mother's education No education 16.7 7,611 7,521 21.9 2.2 6.0 1,272 1,425 Primary 18.0 3,012 2,727 27.1 7.3 8.3 543 557 Secondary 16.8 252 369 45.1 3.0 10.5 42 73 More than secondary 16.2 168 191 (43.6) (0.0) (10.9) 27 27 Wealth quintile Lowest 18.5 2,476 3,327 16.0 3.0 2.0 459 716 Second 16.4 2,444 1,950 20.9 1.4 11.5 401 356 Middle 18.0 2,277 1,738 23.1 2.8 6.2 410 344 Fourth 16.4 2,158 1,752 28.1 6.3 7.6 353 329 Highest 15.5 1,687 2,041 40.4 5.8 8.1 262 337 Total 17.1 11,042 10,808 24.2 3.6 6.8 1,885 2,082 Note: Figures in parentheses are based on 25-49 unweighted cases. 1 Excludes pharmacy, drug vendor/store, shop, and traditional healer. 146 • Child Health 10.6 DIARRHOEAL DISEASE Dehydration from diarrhoea is a major cause of death in infancy and childhood. This is unfortunate since the condition is easily treated with oral rehydration therapy (ORT). The combination of high cause-specific mortality and the existence of effective treatment make diarrhoea and its treatment a priority concern for health services. Diarrhoea with blood in the stools is indicative of cholera or other specific diseases and needs to be treated somewhat differently than diarrhoea without blood. In the 2011 EDHS mothers were asked whether any of their children under age five had diarrhoea at any time during the two-week period preceding the survey. If the child had had diarrhoea, the mother was asked about feeding practices during the diarrhoeal episode. The validity of this indicator is affected by the mother’s perception of diarrhoea as an illness and her capacity to recall the events. Moreover, the prevalence of diarrhoea varies seasonally. Thus, this variable in the 2011 EDHS should be interpreted with caution. 10.6.1 Prevalence of Diarrhoea Table 10.7 shows that 13 percent of children under age five were reported to have had diarrhoea, and 3 percent had had diarrhoea with blood in the two-week period before the survey. Diarrhoea was most common among children age 6–23 months (23-25 percent). Diarrhoea prevalence is highest among children residing in households that drink from unprotected wells (18 percent), those residing in rural areas (14 percent), and children residing in Benishangul-Gumuz and Gambela (both 23 percent). Child Health • 147 Table 10.7 Prevalence of diarrhoea Percentage of children under age five who had diarrhoea in the two weeks preceding the survey, by background characteristics, Ethiopia 2011 Background characteristic Diarrhoea in the two weeks preceding the survey Weighted number of children Unweighted number of children All diarrhoea Diarrhoea with blood Age in months <6 10.4 1.8 1,265 1,211 6-11 24.8 4.8 1,120 1,043 12-23 22.6 5.7 1,930 1,927 24-35 14.0 3.2 2,063 2,099 36-47 8.9 2.8 2,381 2,311 48-59 6.0 2.1 2,282 2,217 Sex Male 14.3 3.5 5,676 5,515 Female 12.5 3.2 5,366 5,293 Source of drinking water1 Improved source 12.4 3.1 5,150 5,469 Piped into dwelling 8.4 3.9 77 66 Piped to yard/plot 9.5 0.6 440 710 Public tap/standpipe 11.1 3.2 2,455 2,104 Borehole 16.0 5.1 369 615 Protected well 12.9 2.9 781 1,118 Protected spring 15.4 3.3 1,006 756 Rain water 11.2 4.7 22 98 Bottled water 0.0 0.0 1 2 Non-improved source 14.5 3.6 5,847 5,293 Unprotected well 18.3 5.5 490 642 Unprotected spring 14.1 3.6 3,216 2,179 Tanker truck/cart with small tank 10.9 2.1 110 219 Surface water 14.3 3.2 2,031 2,253 Other 0.7 0.0 39 42 Missing 0.0 0.0 6 4 Toilet facility2 Improved, not shared 11.4 4.0 830 916 Shared3 11.7 1.3 570 878 Non-improved 13.7 3.4 9,629 9,003 Missing 13.7 0.0 13 11 Residence Urban 11.0 2.1 1,436 1,865 Rural 13.8 3.5 9,606 8,943 Region Tigray 13.4 4.2 702 1,123 Affar 12.7 1.7 112 1,033 Amhara 13.7 4.5 2,478 1,203 Oromiya 11.3 2.6 4,665 1,637 Somali 19.5 3.7 339 951 Benishangul-Gumuz 22.7 7.8 127 925 SNNP 16.4 3.3 2,305 1,491 Gambela 22.6 6.4 37 782 Harari 11.8 3.4 27 616 Addis Ababa 9.4 1.1 214 386 Dire Dawa 7.8 1.1 37 661 Mother's education No education 13.9 3.7 7,611 7,521 Primary 12.6 2.7 3,012 2,727 Secondary 10.2 1.1 252 369 More than secondary 10.9 0.0 168 191 Wealth quintile Lowest 15.0 3.4 2,476 3,327 Second 12.3 3.7 2,444 1,950 Middle 13.1 3.6 2,277 1,738 Fourth 15.0 3.5 2,158 1,752 Highest 11.2 2.2 1,687 2,041 Total 13.4 3.3 11,042 10,808 Note: Total includes 6 cases with information missing on drinking water and 13 cases with information missing on toilet facilities. 1 See Table 2.1 for definition of categories. 2 See Table 2.2 for definition of categories. 3 Shared facility of an otherwise improved type 148 • Child Health 10.6.2 Treatment of Diarrhoea Mothers of children with diarrhoea in the two weeks preceding the survey were asked what was done to manage or treat the illness. Table 10.8 shows the percentage of children with diarrhoea in the two weeks before the survey who were taken to a health facility or provider for treatment, the percentage who received ORT, and the percentage who were given other treatments, by background characteristics. Overall, 32 percent of the children with diarrhoea were taken for advice or treatment to a health facility or provider. Children age 24-35 months were more likely than children in other age groups to be taken to a health facility or provider for treatment (39 percent). The differences in percentages of children taken for treatment were small between male and female children and by type of diarrhoea. Urban children were considerably more likely to have been taken for advice or treatment for diarrhoea than rural children (54 percent versus 29 percent). Children of highly educated mothers and those in the highest wealth quintile are more likely than other children to be taken to a health facility or provider for treatment when they have diarrhoea. For example, 22 percent of children in the lowest wealth quintile were taken to a health facility or provider for treatment of diarrhoea compared with 53 percent of children in the highest wealth quintile. During diarrhoea, oral rehydration therapy (ORT) is a simple and effective remedy for dehydration. It involves giving the child a solution prepared by mixing water with a commercially prepared packet of oral rehydration salts (ORS) or recommended home fluids (RHF), usually a home- made sugar-salt-water solution. Twenty-six percent of children with diarrhoea were treated with ORS packets and 8 percent were treated with RHF. Sixteen percent of children with diarrhoea were given increased fluids. Overall, two children in every five with diarrhoea were treated with some form of ORT or increased fluids, while 42 percent of children did not receive any form of treatment. Comparable data from the 2000 EDHS and 2005 EDHS show an increase in mothers’ health- seeking behaviour for children with diarrhoea over the past decade. The percentage of children with diarrhoea who were taken to a health provider increased steadily from 13 percent in 2000 to 22 percent in 2005 and 32 percent in 2011. Child Health • 149 Table 10.8 Diarrhoea treatment Among children under age five who had diarrhoea in the two weeks preceding the survey, the percentage for whom advice or treatment was sought from a health facility or provider, the percentage given oral rehydration therapy (ORT), the percentage given increased fluids, the percentage given ORT or increased fluids, and the percentage given other treatments, by background characteristics, Ethiopia 2011 Background characteristic Percentage of children with diarrhoea for whom advice or treatment was sought from a health facility or provider1 Oral rehydration therapy (ORT) Increased fluids ORT or increased fluids Other treatments No treatment Weighted number of children with diarrhoea Un- weighted number of children with diarrhoea Fluid from ORS packets Recom- mended home fluids (RHF) Either ORS or RHF Anti- biotic drugs Anti- motility drugs Home remedy/ other Missing Age in months <6 22.3 12.4 4.2 15.3 4.5 18.4 7.4 0.0 24.5 1.9 59.4 132 144 6-11 29.1 26.9 6.9 30.1 14.9 37.5 11.4 0.7 20.1 0.1 50.8 278 275 12-23 32.0 24.5 5.3 28.0 16.2 39.4 13.3 0.4 21.4 0.0 39.5 436 478 24-35 38.5 33.0 8.0 37.9 19.7 49.8 18.0 0.1 22.9 0.1 33.6 289 346 36-47 32.9 29.2 13.1 38.2 15.6 44.9 15.1 0.1 20.8 0.1 35.2 212 226 48-59 29.6 25.8 9.2 28.4 15.5 36.4 9.6 0.1 21.9 3.9 46.1 136 151 Sex Male 31.1 28.3 7.9 32.8 15.5 42.5 14.3 0.4 19.9 0.7 39.5 814 859 Female 32.6 23.8 6.9 28.1 15.4 36.3 12.0 0.1 23.9 0.4 45.6 670 761 Type of diarrhoea Non-bloody 32.5 24.8 8.1 29.3 15.4 38.1 12.6 0.3 20.7 0.3 45.1 982 1,085 Bloody 33.0 30.1 7.7 35.3 18.0 45.8 14.4 0.2 25.0 0.0 37.1 368 405 Missing 23.0 27.3 2.2 28.0 9.0 35.0 14.5 0.0 20.0 4.3 35.0 133 130 Residence Urban 53.5 44.6 12.9 51.4 17.6 55.4 20.3 0.2 25.3 0.0 27.4 158 228 Rural 29.2 24.1 6.9 28.2 15.2 37.8 12.4 0.3 21.3 0.6 44.0 1,326 1,392 Region Tigray 34.1 29.2 8.7 37.3 30.2 53.2 11.5 2.9 17.2 0.0 35.9 94 152 Affar 39.9 32.8 13.7 38.6 2.1 39.9 12.9 0.0 12.7 2.4 44.9 14 128 Amhara 25.4 27.6 9.4 33.1 11.1 38.3 13.1 0.0 23.1 0.0 42.3 339 172 Oromiya 35.3 23.8 4.9 26.8 19.8 40.6 13.9 0.0 22.3 1.5 40.9 529 195 Somali 19.7 30.6 8.2 33.9 6.8 36.1 8.1 0.8 15.7 0.4 54.4 66 179 Benishangul- Gumuz 50.1 28.7 17.0 38.6 8.7 43.6 24.2 1.6 26.3 0.4 29.7 29 204 SNNP 31.0 25.1 6.7 28.9 11.4 34.9 13.0 0.0 21.3 0.0 45.7 378 255 Gambela 47.7 45.3 7.1 48.7 12.9 53.6 16.9 3.0 27.8 0.0 24.0 8 177 Harari 45.0 38.6 9.5 44.2 5.8 48.1 22.5 2.7 23.4 1.1 30.2 3 73 Addis Ababa (47.2) (43.4) (32.0) (56.5) (34.1) (65.1) (8.0) (0.0) (27.8) (0.0) (27.1) 20 36 Dire Dawa (46.4) (42.8) (8.6) (45.6) (10.9) (48.6) (17.2) (1.6) (28.6) (0.0) (40.0) 3 49 Mother's education No education 28.9 23.5 6.2 27.4 12.1 34.8 11.7 0.1 21.5 0.3 46.2 1,060 1,125 Primary 34.6 29.7 9.4 35.0 23.5 49.1 15.0 0.4 21.9 1.4 34.2 380 433 Secondary 61.2 44.6 29.2 57.5 27.0 61.3 17.2 3.9 24.6 0.0 23.9 26 46 More than secondary * * * * * * * * * * * 18 16 Wealth quintile Lowest 22.4 18.0 6.1 21.8 16.5 34.8 10.5 0.3 17.6 0.7 49.6 372 539 Second 25.4 22.4 4.3 24.6 14.9 33.3 15.9 0.2 22.0 0.2 46.5 301 274 Middle 35.3 27.0 8.9 33.4 12.3 39.3 9.5 0.6 19.6 0.0 42.9 298 273 Fourth 32.8 27.7 7.2 31.4 16.7 41.2 13.8 0.1 22.1 1.6 41.0 323 304 Highest 53.0 45.3 13.5 52.4 17.3 57.5 19.3 0.2 31.8 0.0 22.1 190 230 Total 31.8 26.3 7.5 30.7 15.5 39.7 13.2 0.3 21.7 0.6 42.2 1,483 1,620 Note: ORT includes fluid prepared from oral rehydration salt (ORS) packets or recommended home fluids (RHF). Figures in parentheses are based on 25-49 unweighted cases. An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. 1 Excludes pharmacy, drug vendor/store, shop, and traditional healer 150 • Child Health 10.6.3 Feeding Practices during Diarrhoea Mothers are encouraged to continue feeding and increase the amount of liquids given to their children when they suffer from diarrhoeal illnesses. These practices help to reduce dehydration and also minimize the adverse consequences of diarrhoea on the child’s nutritional status. Mothers interviewed in the 2011 EDHS were specifically asked whether they gave the child who had had diarrhoea in the two weeks preceding the survey more or less fluid and food than usual. Table 10.9 shows that 16 percent of children with diarrhoea were given more fluids than usual, as recommended. More than one-third of children (35 percent) were given the same amount of fluids as usual. However, almost one child in every two (49 percent) were offered less fluid than usual or were given no fluids at all: 28 percent were offered somewhat less, 13 percent were offered much less, and 7 percent of children were offered no fluids at all. Likewise, almost one child in every two children (48 percent) was offered less food than usual: 25 percent were offered somewhat less, 16 percent were offered much less, and 7 percent of children were offered no food at all. Only 10 percent of children with diarrhoea were given increased liquids and continued feeding as recommended, while 25 percent of children with diarrhoea continued to feed and were given ORT or increased fluids. These findings suggest that a large proportion of mothers still engage in the dangerous practice of curtailing fluids and food intake when their children have diarrhoea. C hi ld H ea lth • 1 51 Ta bl e 10 .9 F ee di ng p ra ct ic es d ur in g di ar rh oe a P er ce nt d is tri bu tio n of c hi ld re n un de r a ge fi ve w ho h ad d ia rr ho ea in th e tw o w ee ks p re ce di ng th e su rv ey b y am ou nt o f l iq ui ds a nd fo od o ffe re d co m pa re d w ith n or m al p ra ct ic e, th e pe rc en ta ge o f c hi ld re n gi ve n in cr ea se d flu id s an d co nt in ue d fe ed in g du rin g th e di ar rh oe a ep is od e, a nd th e pe rc en ta ge o f c hi ld re n w ho c on tin ue d fe ed in g an d w er e gi ve n O R T an d/ or in cr ea se d flu id s du rin g th e ep is od e of d ia rrh oe a, 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 A m ou nt o f l iq ui ds g iv en A m ou nt o f f oo d gi ve n P er ce nt ag e gi ve n in cr ea se d flu id s an d co nt in ue d fe ed in g1 P er ce nt ag e w ho co nt in ue d fe ed in g an d w er e gi ve n O R T an d/ or in cr ea se d flu id s1 W ei gh te d nu m be r o f ch ild re n w ith di ar rh oe a U nw ei gh te d nu m be r o f ch ild re n w ith di ar rh oe a M or e S am e as us ua l S om ew ha t le ss M uc h le ss N on e D on 't kn ow / m is si ng To ta l M or e S am e as us ua l S om ew ha t le ss M uc h le ss N on e N ev er ga ve fo od D on 't kn ow / m is si ng To ta l A ge in m on th s <6 4. 5 30 .0 31 .9 13 .6 19 .8 0. 1 10 0. 0 0. 1 8. 5 10 .1 3. 8 0. 0 75 .8 1. 6 10 0. 0 0. 1 4. 2 13 2 14 4 6- 11 14 .9 32 .4 27 .9 13 .3 11 .3 0. 2 10 0. 0 3. 8 24 .9 18 .2 11 .6 9. 9 31 .6 0. 0 10 0. 0 8. 3 18 .7 27 8 27 5 12 -2 3 16 .2 37 .2 25 .7 15 .8 4. 7 0. 4 10 0. 0 5. 9 29 .9 28 .8 18 .5 6. 3 10 .2 0. 4 10 0. 0 10 .9 25 .1 43 6 47 8 24 -3 5 19 .7 33 .7 27 .6 15 .3 2. 8 0. 9 10 0. 0 9. 2 31 .9 30 .1 17 .8 10 .1 0. 2 0. 7 10 0. 0 14 .1 35 .1 28 9 34 6 36 -4 7 15 .6 32 .8 32 .5 10 .0 8. 8 0. 2 10 0. 0 7. 7 37 .8 29 .2 19 .9 5. 4 0. 0 0. 0 10 0. 0 11 .2 35 .2 21 2 22 6 48 -5 9 15 .5 47 .4 25 .5 6. 7 0. 9 4. 1 10 0. 0 5. 6 44 .2 20 .5 23 .2 2. 5 0. 0 4. 1 10 0. 0 9. 3 21 .2 13 6 15 1 Se x M al e 15 .5 34 .4 27 .9 13 .8 7. 4 1. 0 10 0. 0 6. 9 30 .3 24 .0 15 .5 5. 7 16 .5 1. 1 10 0. 0 10 .8 27 .4 81 4 85 9 Fe m al e 15 .4 36 .4 28 .1 12 .9 6. 8 0. 4 10 0. 0 4. 6 29 .4 25 .5 17 .6 7. 9 14 .7 0. 3 10 0. 0 9. 0 22 .2 67 0 76 1 Ty pe o f d ia rr ho ea N on -b lo od y 15 .4 36 .9 27 .8 12 .2 7. 3 0. 3 10 0. 0 5. 5 32 .1 23 .9 14 .9 6. 2 16 .9 0. 4 10 0. 0 11 .2 24 .9 98 2 1, 08 5 B lo od y 18 .0 33 .0 28 .2 14 .1 6. 5 0. 1 10 0. 0 7. 2 27 .1 25 .7 20 .9 6. 0 13 .1 0. 0 10 0. 0 8. 6 26 .8 36 8 40 5 M is si n g 9. 0 29 .5 28 .3 20 .1 7. 6 5. 5 10 0. 0 4. 7 21 .2 27 .7 14 .8 12 .2 14 .0 5. 5 10 0. 0 4. 7 21 .8 13 3 13 0 R es id en ce U rb an 17 .6 44 .2 15 .4 15 .0 7. 8 0. 1 10 0. 0 8. 5 38 .3 12 .6 19 .0 7. 2 14 .3 0. 1 10 0. 0 13 .1 29 .3 15 8 22 8 R ur al 15 .2 34 .2 29 .5 13 .2 7. 1 0. 8 10 0. 0 5. 6 28 .9 26 .1 16 .1 6. 6 15 .9 0. 9 10 0. 0 9. 6 24 .6 1, 32 6 1, 39 2 R eg io n Ti gr ay 30 .2 43 .2 17 .2 6. 8 2. 6 0. 0 10 0. 0 11 .1 44 .5 23 .8 9. 6 2. 7 8. 4 0. 0 10 0. 0 24 .8 43 .0 94 15 2 A ffa r 2. 1 14 .4 38 .9 36 .7 7. 2 0. 7 10 0. 0 0. 7 20 .6 30 .2 38 .4 2. 2 7. 2 0. 7 10 0. 0 0. 8 19 .9 14 12 8 A m ha ra 11 .1 46 .5 22 .6 10 .6 8. 2 1. 1 10 0. 0 7. 6 36 .2 21 .8 11 .7 4. 8 16 .3 1. 6 10 0. 0 8. 2 29 .3 33 9 17 2 O ro m i y a 19 .8 28 .1 27 .9 16 .0 7. 2 1. 0 10 0. 0 4. 0 24 .6 23 .4 20 .7 12 .9 13 .3 1. 0 10 0. 0 9. 4 19 .9 52 9 19 5 S om al i 6. 8 27 .8 30 .8 23 .2 8. 1 3. 3 10 0. 0 3. 0 14 .5 33 .3 23 .8 4. 8 19 .7 1. 0 10 0. 0 4. 1 18 .7 66 17 9 B en is ha n g ul -G um uz 8. 7 36 .3 26 .8 19 .7 8. 6 0. 0 10 0. 0 5. 1 34 .0 28 .5 18 .7 4. 0 9. 7 0. 0 10 0. 0 6. 8 27 .4 29 20 4 S N N P 11 .4 35 .2 35 .2 10 .8 7. 4 0. 0 10 0. 0 6. 3 30 .6 26 .9 13 .8 1. 2 21 .2 0. 0 10 0. 0 9. 8 24 .1 37 8 25 5 G am be la 12 .9 29 .1 31 .1 20 .9 6. 1 0. 0 10 0. 0 1. 7 20 .7 29 .3 18 .8 18 .2 11 .2 0. 0 10 0. 0 5. 6 27 .0 8 17 7 H ar ar i 5. 8 45 .1 31 .7 15 .0 1. 3 1. 1 10 0. 0 11 .5 38 .4 24 .1 15 .5 2. 3 7. 1 1. 1 10 0. 0 5. 8 34 .6 3 73 A dd is A ba ba (3 4. 1) (3 9. 1) (1 5. 7) (1 1. 0) (0 .0 ) (0 .0 ) 10 0. 0 (9 .5 ) (3 5. 4) (2 7. 9) (1 9. 3) (6 .4 ) (1 .5 ) (0 .0 ) 10 0. 0 (2 1. 5) (4 3. 3) 20 36 D ire D aw a (1 0. 9) (1 8. 1) (4 3. 8) (1 3. 7) (1 1. 4) (2 .0 ) 10 0. 0 (0 .0 ) (1 7. 1) (3 4. 6) (2 0. 3) (4 .5 ) (2 1. 5) (2 .0 ) 10 0. 0 (8 .2 ) (2 7. 4) 3 49 M ot he r's e du ca tio n N o ed uc at io n 12 .1 37 .0 29 .2 13 .9 7. 4 0. 4 10 0. 0 4. 5 29 .9 24 .5 17 .7 6. 7 16 .4 0. 4 10 0. 0 7. 1 21 .0 1, 06 0 1, 12 5 P rim ar y 23 .5 30 .7 24 .3 12 .4 7. 2 1. 9 10 0. 0 9. 0 28 .4 26 .5 12 .8 7. 5 13 .7 1. 9 10 0. 0 16 .6 33 .3 38 0 43 3 S ec on da r y 27 .0 34 .4 37 .8 0. 9 0. 0 0. 0 10 0. 0 13 .8 35 .7 18 .8 17 .7 0. 6 13 .4 0. 0 10 0. 0 18 .6 41 .6 26 46 M or e th an s ec on da r y * * * * * * 10 0. 0 * * * * * * * 10 0. 0 * * 18 16 W ea lth q ui nt ile Lo w es t 16 .5 31 .9 27 .6 12 .5 10 .6 0. 9 10 0. 0 4. 9 27 .1 25 .1 13 .4 10 .5 18 .0 1. 1 10 0. 0 10 .1 24 .0 37 2 53 9 S ec on d 14 .9 38 .4 29 .4 11 .9 5. 3 0. 2 10 0. 0 4. 2 32 .9 23 .1 18 .0 3. 7 18 .1 0. 0 10 0. 0 6. 6 17 .9 30 1 27 4 M id dl e 12 .3 33 .8 33 .4 12 .9 7. 7 0. 0 10 0. 0 5. 1 27 .1 29 .4 18 .2 4. 8 15 .3 0. 0 10 0. 0 8. 7 25 .3 29 8 27 3 Fo ur th 16 .7 36 .9 24 .3 15 .3 4. 6 2. 2 10 0. 0 7. 9 31 .3 23 .0 16 .0 7. 4 12 .1 2. 2 10 0. 0 12 .2 27 .5 32 3 30 4 H i g he st 17 .3 36 .4 24 .4 15 .1 6. 8 0. 0 10 0. 0 8. 2 32 .4 21 .6 17 .8 5. 8 14 .2 0. 0 10 0. 0 13 .3 34 .0 19 0 23 0 To ta l 15 .5 35 .3 28 .0 13 .4 7. 1 0. 8 10 0. 0 5. 9 29 .9 24 .7 16 .4 6. 7 15 .7 0. 8 10 0. 0 10 .0 25 .1 1, 48 3 1, 62 0 N ot e: It is re co m m en de d th at c hi ld re n sh ou ld b e gi ve n m or e liq ui ds to d rin k du rin g di ar rh oe a an d th at fo od s ho ul d no t b e re du ce d. F ig ur es in p ar en th es es a re b as ed o n 25 -4 9 un w ei gh te d ca se s. A n as te ris k in di ca te s th at a fi gu re is b as ed o n fe w er th an 2 5 un w ei gh te d ca se s an d ha s be en s up pr es se d. 1 C on tin ue d fe ed in g pr ac tic es in cl ud es c hi ld re n w ho w er e gi ve n m or e, s am e as u su al , o r s om ew ha t l es s fo od d ur in g th e di ar rh oe a ep is od e. • 151Child Health 152 • Child Health 10.7 KNOWLEDGE OF ORS PACKETS A simple and effective response to dehydration caused by diarrhoea is a prompt increase in the child’s fluid intake through some form of oral rehydration therapy (ORT). ORT may include the use of a solution prepared from commercially produced packets of oral rehydration salts (ORS); a homemade mixture usually prepared from sugar, salt, and water; any kind of thin, nutritious fluids such as rice water, coconut milk, or watery soup; or simply increased fluids. To ascertain how widespread knowledge of ORS is in Ethiopia, mothers were asked whether they knew about ORS packets. Table 10.10 shows that 65 percent of mothers with a live birth in the five years preceding the survey had heard about ORS packets. Mothers older than 25 years were more likely to have heard of ORS packets than younger mothers. Knowledge is more widespread in urban areas (87 percent) than in rural areas (61 percent). More than 90 percent of women in Addis Ababa, Dire Dawa, Harari, and Tigray know about ORS packets. Levels of knowledge increase with education and with household wealth. Table 10.10 Knowledge of ORS packets Percentage of women age 15-49 with a live birth in the five years preceding the survey who know about ORS packets for treatment of diarrhoea, by background characteristics, Ethiopia 2011 Background characteristic Percentage of women who know about ORS packets Weighted number of women Unweighted number of women Age 15-19 49.4 402 416 20-24 61.7 1,608 1,596 25-34 67.8 3,872 3,799 35-49 66.2 2,026 1,953 Residence Urban 86.5 1,188 1,513 Rural 61.4 6,720 6,251 Region Tigray 93.9 530 847 Affar 69.2 78 714 Amhara 60.6 1,991 965 Oromiya 60.4 3,116 1,100 Somali 74.3 198 559 Benishangul-Gumuz 60.7 92 674 SNNP 65.5 1,634 1,053 Gambela 80.6 31 608 Harari 93.2 19 440 Addis Ababa 91.7 193 348 Dire Dawa 92.1 26 456 Education No education 59.4 5,270 5,184 Primary 73.8 2,270 2,095 Secondary 93.7 226 312 More than secondary 98.2 142 173 Wealth quintile Lowest 55.1 1,739 2,279 Second 59.0 1,696 1,354 Middle 59.4 1,628 1,241 Fourth 69.4 1,493 1,229 Highest 88.4 1,351 1,661 Total 65.2 7,908 7,764 ORS = Oral rehydration salts Child Health • 153 10.8 STOOL DISPOSAL The proper disposal of children’s faeces is extremely important in preventing the spread of disease. Contact with human faeces directly, or indirectly by animal contact with the faeces, can lead to diarrhoeal diseases. Table 10.11 presents the percent distribution of mothers who have their youngest child under age 5 living with them by how the child’s stools are disposed of, according to background characteristics and type of toilet facilities in the household. Thirty-six percent of children’s stools are safely disposed, that is, 6 percent of children use a toilet or latrine, 29 percent of children’s stools are rinsed in the toilet or latrine, and 1 percent is buried. In contrast, the stools of two children in every five are left in the open, and 14 percent are thrown into the garbage. There are marked differences in the way children’s stools are disposed of according to background characteristics. A higher proportion of urban children’s stools are disposed of safely than of rural children’s stools (63 and 31 percent, respectively). Regional differentials in safe disposal also are substantial. For example, in Addis Ababa, 75 percent of children’s stools are disposed of safely compared with 24 percent in Gambela. Safe disposal of children’s stools increases with mother’s level of education and with household wealth. Comparable data from the 2005 EDHS show an increase in safe stool disposal from 21 percent to 36 percent over the five years between surveys. 154 • Child Health Table 10.11 Disposal of children's stools Percent distribution of youngest children under age 5 living with the mother, by the manner of disposal of the child's last faecal matter, and percentage of children whose stools are disposed of safely, according to background characteristics, Ethiopia 2011 Background characteristic Manner of disposal of children's stools Total Percentage of children whose stools are disposed of safely1 Weighted number of children Unweighted number of children Child used toilet or latrine Put/ rinsed into toilet or latrine Buried Put/ rinsed into drain or ditch Thrown into garbage Left in the open Other Missing Age in months <6 0.2 17.3 1.2 7.1 11.2 39.9 21.9 1.2 100.0 18.7 1,248 1,187 6-11 0.5 29.8 1.1 4.4 17.2 37.8 8.2 1.0 100.0 31.4 1,113 1,033 12-23 1.6 33.3 0.8 2.8 16.5 42.2 2.3 0.4 100.0 35.7 1,836 1,817 24-35 5.0 32.9 1.5 2.0 15.7 40.9 1.1 0.9 100.0 39.4 1,495 1,579 36-47 12.5 27.2 1.2 1.8 11.7 44.2 0.8 0.5 100.0 40.9 1,153 1,094 48-59 25.5 30.6 0.5 1.3 8.1 32.3 0.5 1.2 100.0 56.6 738 676 Toilet facility2 Improved, not shared 11.3 43.3 0.1 3.3 12.9 23.6 4.9 0.6 100.0 54.7 596 664 Shared3 4.9 58.0 0.5 5.3 10.2 17.7 2.7 0.7 100.0 63.4 419 641 Non-improved 5.4 25.7 1.2 3.2 14.4 43.2 6.0 0.9 100.0 32.3 6,560 6,073 Residence Urban 5.2 56.1 1.2 4.6 11.7 16.0 3.7 1.5 100.0 62.5 1,099 1,388 Rural 6.0 24.3 1.1 3.1 14.4 44.4 6.1 0.7 100.0 31.3 6,485 5,998 Region Tigray 3.2 29.4 2.1 2.9 12.8 47.2 2.0 0.4 100.0 34.7 515 823 Affar 1.5 8.6 23.0 7.4 26.1 32.8 0.4 0.2 100.0 33.1 73 673 Amhara 6.5 18.1 0.7 3.1 13.1 53.9 3.1 1.4 100.0 25.4 1,922 931 Oromiya 5.5 26.8 0.6 4.0 14.2 37.5 11.0 0.4 100.0 32.9 2,988 1,055 Somali 0.6 28.1 6.3 1.5 17.3 41.2 3.0 2.0 100.0 35.1 185 528 Benishangul-Gumuz 4.3 40.9 0.6 2.5 9.0 40.1 2.1 0.5 100.0 45.8 89 648 SNNP 8.0 41.1 0.6 0.9 15.2 31.5 1.7 1.0 100.0 49.7 1,563 1,010 Gambela 2.2 20.3 1.6 9.7 16.1 47.4 1.7 1.0 100.0 24.1 26 551 Harari 4.9 33.4 2.7 21.0 16.4 20.1 1.1 0.5 100.0 41.0 18 411 Addis Ababa 2.6 72.6 0.0 13.3 6.3 3.7 0.9 0.5 100.0 75.2 180 323 Dire Dawa 3.7 42.8 0.9 3.9 30.3 16.3 1.4 0.7 100.0 47.4 25 433 Mother's education No education 5.4 23.3 1.2 2.9 15.4 45.2 5.7 0.8 100.0 29.9 5,080 4,972 Primary 6.7 36.9 0.9 4.0 11.5 33.4 5.9 0.6 100.0 44.6 2,165 1,968 Secondary 7.3 55.5 0.7 4.5 11.0 9.8 7.2 4.0 100.0 63.5 209 291 More than secondary 4.2 71.0 0.2 4.0 6.5 10.2 2.4 1.5 100.0 75.5 130 155 Wealth quintile Lowest 2.7 13.2 2.0 3.4 14.0 59.1 4.9 0.6 100.0 17.9 1,670 2,183 Second 6.7 17.8 0.8 3.7 18.0 45.4 6.3 1.4 100.0 25.2 1,637 1,309 Middle 5.3 27.9 1.1 3.0 12.8 41.9 7.4 0.6 100.0 34.3 1,571 1,193 Fourth 8.2 37.2 0.7 2.4 11.9 33.8 5.5 0.4 100.0 46.1 1,442 1,174 Highest 6.9 55.8 0.6 4.1 12.7 14.1 4.5 1.2 100.0 63.3 1,264 1,527 Total 5.8 28.9 1.1 3.3 14.0 40.3 5.8 0.8 100.0 35.8 7,584 7,386 Note: Total includes 9 cases with missing information on toilet facilities. 1 Children's stools are considered to be disposed of safely if the child used a toilet or latrine, if the faecal matter was put/rinsed into a toilet or latrine or if it was buried. 2 See Table 2.2 for definition of categories. 3 Shared facility of an otherwise improved type. Nutrition of Children and Adults • 155 NUTRITION OF CHILDREN AND ADULTS 11 utritional status is the result of complex interactions between food consumption and the overall status of health and health care practices. Numerous socioeconomic and cultural factors influence patterns of feeding children and the nutritional status of women and children. The period from birth to age two is especially important for optimal growth, health, and development. Unfortunately, this period is often marked by micronutrient deficiencies that interfere with optimal growth. Additionally, childhood illnesses such as diarrhoea and acute respiratory infections (ARI) are common. For women, improving overall nutritional status throughout the life cycle is crucial to maternal health. Women who become malnourished during pregnancy and children who fail to grow and develop normally due to malnutrition at any time during their life, including during foetal development, are at increased risk of perinatal problems, increased susceptibility to infections, slowed recovery from illness, and possibly death. Improving maternal nutrition is crucial for improving children’s health. The poor nutritional status of children and women has been a serious problem in Ethiopia for many years. Therefore, the health sector has increased its efforts to enhance good nutritional practices through health education, treatment of extremely malnourished children, and provision of micronutrients to the most vulnerable group of the population, that is, mothers and children. In addition, the Health Extension Programme (HEP) has included nutrition as part of their health packages. A national nutrition strategy and programme has also been developed and implemented by the Government of Ethiopia. The Health Sector Development Plan IV (2010/11-2014/15) strives to improve the nutritional status of mothers and children through the following programmes: Enhanced Outreach Strategy (EOS) with Targeted Supplementary Food (TSF) and Transitioning of EOS into HEP, Health Facility Nutrition Services, Community Based Nutrition (CBN), and Micronutrient Interventions and Essential Nutrition Actions/Integrated Infant and Young Feeding Counselling Services. N Key Findings • There has been a marked decline in the proportion of children stunted and underweight in the last 11 years. • Breastfeeding is nearly universal in Ethiopia and half of children born in the three years before the survey are breastfed for about 25 months. • More than half (52 percent) of children less than 6 months old are exclusively breastfed. • Complementary foods are not introduced in a timely fashion for all children. At 6-9 months only about half of children receive complementary foods. • Overall, only 4 percent of children age 6-23 months are fed appropriately, based on the recommended infant and young child feeding (IYCF) practices. • Forty-four percent of children age 6-59 months are anaemic, with 21 percent mildly anaemic, 20 percent moderately anaemic, and 3 percent severely anaemic. • Overall, 17 percent of women age 15-49 are anaemic; 13 percent are mildly anaemic, 3 percent are moderately anaemic, and less than 1 percent are severely anaemic. • Twenty-seven percent of women age 15-49 are thin, that is, they fall below the cut-off of 18.5 for the body mass index (BMI), and 9 percent are moderately or severely thin. Only 6 percent of women are overweight or obese (BMI ≥25 kg/m2). 156 • Nutrition of Children and Adults The 2011 EDHS asked questions about early initiation of breastfeeding, exclusive breastfeeding during the first six months of life, continued breastfeeding until at least age 2, timely introduction of complementary foods at age 6 months (with increasing frequency of feeding solid and semi-solid foods), and diet diversity. Interviewers measured the height and weight of all children under age 5 and of women and men age 15-49. This chapter also presents findings on infant feeding practices, maternal eating patterns, household testing of salt for adequate levels of iodine, and the nutritional status of women, men, and children. 11.1 NUTRITIONAL STATUS OF CHILDREN The nutritional status of children under age five is an important outcome measure of children’s health. The anthropometric data on height and weight collected in the 2011 EDHS permit the measurement and evaluation of the nutritional status of young children. This evaluation allows identification of subgroups of the child population that are at increased risk of faltered growth, disease, impaired mental development, and death. 11.1.1 Measurement of Nutritional Status among Young Children The 2011 EDHS collected data on the nutritional status of children by measuring the height and weight of all children under age five. Data were collected to calculate three indices of anthropometric indicators—weight-for-age, height-for-age, and weight-for-height. For this report indicators of the nutritional status of children were calculated using new growth standards published by the World Health Organization (WHO) in 2006. These new growth standards were generated using data collected in the WHO Multicentre Growth Reference Study (WHO, 2006). The findings of the study, whose sample included 8,440 children in six countries (Brazil, Ghana, India, Norway, Oman, and the United States), describe how children should grow under optimal conditions. Therefore, the WHO Child Growth Standards can be used to assess children all over the world, regardless of ethnicity, social and economic influences, and feeding practices. The new child growth standards replace the previously used reference standards of the U.S. National Center for Health Statistics, accepted by the U.S. Centers for Disease Control and Prevention (NCHS/CDC/WHO). The three indices are expressed as standard deviation units from the median for the reference group. Children who fall below minus two standard deviations (−2 SD) from the median of the reference population are regarded as moderately malnourished, while those who fall below minus three standard deviations (−3 SD) from the median of the reference population are considered severely malnourished. The height-for-age index provides an indicator of linear growth retardation and cumulative growth deficits in children. Children whose height-for-age Z-score is below minus two standard deviations (−2 SD) from the median of the WHO reference population are considered short for their age (stunted), or chronically malnourished. Children who are below minus three standard deviations (−3 SD) are considered severely stunted. Stunting reflects failure to receive adequate nutrition over a long period of time and is affected by recurrent and chronic illness. Height-for-age, therefore, represents the long-term effects of malnutrition in a population and is not sensitive to recent, short- term changes in dietary intake. The weight-for-height index measures body mass in relation to body height or length; it describes current nutritional status. Children with Z-scores below minus two standard deviations Nutrition of Children and Adults • 157 (−2 SD) are considered thin (wasted) or acutely malnourished. Wasting represents the failure to receive adequate nutrition in the period immediately preceding the survey and may be the result of inadequate food intake or a recent episode of illness causing loss of weight and the onset of malnutrition. Children with a weight-for-height index below minus three standard deviations (−3 SD) are considered severely wasted. The weight-for-height index also provides data on overweight and obesity. Children more than two standard deviations (+2 SD) above the median weight-for-height are considered overweight, or obese. Weight-for-age is a composite index of height-for-age and weight-for-height. It takes into account both chronic and acute malnutrition. A child can be underweight for his/her age because he or she is stunted, wasted, or both. Weight-for-age is an overall indicator of a population’s nutritional health. Children with weight-for-age below minus two standard deviations (−2 SD) are classified as underweight. Children with weight-for-age below minus three standard deviations (−3 SD) are considered severely underweight. Importantly, the WHO Child Growth Standards reference population used for the 2011 EDHS differs from that used in past DHS surveys, and thus the measures from the 2011 EDHS are not directly comparable to previous EDHS results, which use the US Center for Health Statistics standards (NCHS/CDC/WHO). When the new WHO child growth standards are used in place of the previous reference, the following changes are observed: • The level of stunting is usually greater, but not for all age groups. • The level of wasting in infancy is substantially higher, particularly in the first six months of life. • The level of underweight is substantially higher during the first half of infancy (0-6 months) and decreases thereafter. • The level of overweight/obesity is higher. 11.1.2 Data Collection Interviewing teams obtained measurements of height and weight for all children born in the five years preceding the survey and listed in the Household Questionnaire. The survey included children who were not biological offspring of the women interviewed. Each interviewing team carried a scale and measuring board. The scales were lightweight electronic SECA scales with a digital screen. They were designed and manufactured under the authority of the United Nations Children’s Fund (UNICEF). Shorr Productions manufactured the measuring boards especially for use in survey settings. Interviewers measured children younger than 24 months lying down on the board (recumbent length) and measured the standing height of older children. In a few cases the team measured recumbent length—when the child’s age was not known and the child was less than 85 centimetres tall. The scale allowed weighing of very young children through an automatic mother-child adjustment that eliminated the mother’s weight while she was standing on the scale with her baby. 158 • Nutrition of Children and Adults A total of 11,152 children under age five were eligible to be weighed and measured. Data are presented for 10,282 (10,883 children weighted) of these children: 5 percent had missing values for height or weight and 3 percent had height or weight measures considered to be out of the range for their ages. Table 11.1 and Figure 11.1 show the percentage of children under age 5 classified as malnourished according to the three anthropometric indices of nutritional status: height-for-age, weight-for-height, and weight-for-age. 11.1.3 Measures of Children’s Nutritional Status Height-for-age Nationally, 44 percent of children under age five are stunted, and 21 percent of children are severely stunted. In general, the prevalence of stunting increases as the age of a child increases, with the highest prevalence of chronic malnutrition found in children age 24-35 months (57 percent) and lowest in children under age six months (10 percent). Male children are slightly more likely to be stunted than female children (46 percent and 43 percent, respectively). With the exception of first order births, there is an inverse relationship between the length of the preceding birth interval and the proportion of children who are stunted. The longer the interval, the less likely it is that the child will be stunted. Size at birth is an important indicator of a child’s nutritional status and the likelihood that a child will be chronically malnourished. Stunting is more common among children who were reported to have been very small at birth (52 percent) than among children who were small or average or larger in size at birth. The mother’s nutritional status, as measured by her body mass index (BMI), also has an inverse relationship with her child’s level of stunting. For example, children of thin mothers (BMI <18.5) are more likely to be stunted (47 percent) than the children of overweight/obese (BMI ≥25) mothers (26 percent). Children in rural areas are one and a half times more likely to be stunted (46 percent) than those in urban areas (32 percent). Regional variation in the prevalence of stunting in children is substantial. Stunting levels are somewhat above the national average in the Amhara (52 percent), Tigray (51 percent), Affar (50 percent), and Benishangul-Gumuz (49 percent) regions and are lowest in Addis Ababa and the Gambela region (22 and 27 percent, respectively). The mother’s level of education generally has an inverse relationship with stunting levels. For example, children of mothers with more than secondary education are the least likely to be stunted (19 percent), while children whose mothers have no education are the most likely to be stunted (47 percent). A similar inverse relationship is observed between the household wealth index and the stunting levels of children; that is, a higher proportion of children in the lowest household wealth quintile are stunted (49 percent) than of children in the highest wealth quintile (30 percent). N ut rit io n of C hi ld re n an d A du lts • 1 59 Ta bl e 11 .1 N ut rit io na l s ta tu s of c hi ld re n P er ce nt ag e of c hi ld re n un de r fiv e ye ar s cl as si fie d as m al no ur is he d ac co rd in g to th re e an th ro po m et ric in di ce s of n ut rit io na l s ta tu s: h ei gh t-f or -a ge , w ei gh t-f or -h ei gh t, an d w ei gh t-f or -a ge , 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 H ei gh t-f or -a ge 1 W ei gh t-f or -h ei gh t W ei gh t-f or -a ge 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 P er ce nt ag e be lo w −3 S D P er ce nt ag e be lo w −2 S D 2 M ea n Z- sc or e (S D ) P er ce nt ag e be lo w −3 S D P er ce nt ag e be lo w −2 S D 2 P er ce nt ag e ab ov e +2 S D M ea n Z- sc or e (S D ) P er ce nt ag e be lo w −3 S D P er ce nt ag e be lo w −2 S D 2 P er ce nt ag e ab ov e +2 S D M ea n Z- sc or e (S D ) A ge in m on th s <6 2. 7 10 .0 -0 .1 5. 4 13 .5 4. 5 -0 .4 3. 5 10 .0 3. 5 -0 .4 1, 07 8 1, 01 5 6- 8 4. 5 12 .2 -0 .4 3. 4 13 .8 2. 4 -0 .7 4. 0 13 .2 0. 2 -0 .8 58 0 55 9 9- 11 13 .9 31 .6 -1 .3 6. 3 18 .9 1. 8 -0 .9 9. 9 29 .1 0. 3 -1 .4 49 9 42 4 12 -1 7 16 .4 40 .2 -1 .5 5. 2 16 .1 1. 3 -0 .7 9. 5 28 .5 1. 3 -1 .3 1, 00 2 1, 03 0 18 -2 3 26 .0 49 .9 -2 .0 3. 6 11 .0 2. 3 -0 .6 9. 5 31 .1 1. 2 -1 .4 91 0 82 0 24 -3 5 30 .2 57 .1 -2 .2 2. 4 8. 4 1. 8 -0 .4 12 .4 33 .9 0. 5 -1 .5 2, 04 3 2, 01 5 36 -4 7 23 .7 54 .6 -2 .1 1. 0 5. 9 0. 5 -0 .4 8. 7 32 .5 0. 1 -1 .5 2, 45 0 2, 26 0 48 -5 9 22 .3 49 .1 -2 .0 1. 5 6. 6 1. 1 -0 .5 8. 7 31 .7 0. 0 -1 .5 2, 32 1 2, 15 9 Se x M al e 21 .7 46 .2 -1 .7 3. 6 11 .1 1. 5 -0 .6 8. 9 30 .5 0. 6 -1 .4 5, 58 4 5, 23 8 Fe m al e 19 .4 42 .5 -1 .6 1. 9 8. 2 1. 9 -0 .5 8. 8 26 .8 0. 8 -1 .3 5, 29 9 5, 04 4 B irt h in te rv al in m on th s3 Fi rs t b irt h4 19 .0 44 .1 -1 .7 2. 5 8. 9 2. 6 -0 .4 7. 3 27 .3 0. 5 -1 .3 1, 87 0 1, 81 9 <2 4 24 .5 49 .3 -1 .9 2. 4 9. 2 2. 0 -0 .5 9. 3 31 .5 0. 9 -1 .4 1, 61 2 1, 63 3 24 -4 7 21 .0 44 .8 -1 .7 3. 1 9. 9 1. 3 -0 .6 9. 8 30 .0 0. 8 -1 .4 4, 91 3 4, 40 2 48 + 16 .5 39 .1 -1 .5 2. 8 11 .3 1. 9 -0 .5 7. 4 25 .1 0. 6 -1 .2 1, 76 6 1, 72 9 Si ze a t b irt h3 V er y sm al l 26 .0 51 .8 -1 .9 4. 1 14 .2 1. 6 -0 .8 14 .3 39 .0 0. 6 -1 .7 2, 11 0 2, 15 4 S m al l 21 .4 45 .9 -1 .8 4. 8 12 .4 1. 5 -0 .8 10 .9 35 .5 0. 0 -1 .6 90 5 85 7 A ve ra ge o r l ar ge r 18 .7 42 .0 -1 .6 2. 2 8. 3 1. 9 -0 .4 6. 9 25 .1 0. 9 -1 .2 7, 12 5 6, 54 4 M ot he r's in te rv ie w s ta tu s In te rv ie w ed 20 .4 44 .4 -1 .7 2. 8 9. 9 1. 8 -0 .5 8. 8 28 .9 0. 7 -1 .3 10 ,1 61 9, 58 3 N ot in te rv ie w ed b ut in ho us eh ol d 21 .6 41 .1 -1 .6 3. 5 8. 7 0. 5 -0 .4 13 .8 32 .2 0. 8 -1 .3 22 4 23 8 N ot in te rv ie w ed a nd n ot in th e ho us eh ol d5 23 .5 46 .1 -1 .9 2. 3 5. 8 0. 6 -0 .3 7. 1 23 .1 0. 0 -1 .3 49 7 46 1 M ot he r's n ut rit io na l s ta tu s6 Th in (B M I< 18 .5 ) 22 .1 47 .0 -1 .8 4. 0 14 .6 1. 1 -0 .9 12 .2 38 .9 0. 4 -1 .6 2, 13 8 2, 53 8 N or m al (B M I 1 8. 5- 24 .9 ) 20 .6 44 .7 -1 .7 2. 6 8. 6 1. 8 -0 .4 8. 3 27 .1 0. 7 -1 .3 7, 57 4 6, 50 9 O ve rw ei gh t/o be se (B M I ≥ 25 ) 9. 4 26 .4 -1 .0 1. 2 6. 2 3. 9 0. 0 1. 9 11 .6 3. 2 -0 .6 45 7 56 4 R es id en ce U rb an 12 .4 31 .5 -1 .3 2. 1 5. 7 3. 3 -0 .2 4. 8 16 .3 1. 6 -0 .9 1, 34 2 1, 65 5 R ur al 21 .7 46 .2 -1 .8 2. 9 10 .2 1. 5 -0 .6 9. 4 30 .4 0. 6 -1 .4 9, 54 1 8, 62 7 R e g io n Ti gr ay 22 .4 51 .4 -2 .0 3. 0 10 .3 1. 0 -0 .6 9. 8 35 .1 0. 2 -1 .6 73 3 1, 14 0 A ffa r 29 .1 50 .2 -1 .8 6. 2 19 .5 2. 1 -0 .9 17 .2 40 .2 0. 6 -1 .7 10 5 96 2 A m ha ra 24 .2 52 .0 -2 .0 3. 1 9. 9 1. 6 -0 .6 9. 7 33 .4 0. 2 -1 .6 2, 32 5 1, 12 0 O ro m i y a 18 .1 41 .4 -1 .5 2. 8 9. 7 1. 4 -0 .5 7. 8 26 .0 0. 9 -1 .2 4, 72 3 1, 61 9 S om al i 16 .1 33 .0 -1 .1 8. 5 22 .2 1. 2 -1 .1 11 .8 33 .5 0. 9 -1 .4 27 8 79 8 B en is ha n g ul -G um uz 27 .0 48 .6 -1 .9 2. 5 9. 9 1. 2 -0 .6 12 .5 31 .9 0. 2 -1 .5 12 3 89 3 S N N P 22 .9 44 .1 -1 .7 1. 9 7. 6 2. 3 -0 .3 9. 6 28 .3 0. 8 -1 .2 2, 31 1 1, 47 7 G am be la 10 .7 27 .3 -1 .0 3. 2 12 .5 0. 7 -0 .7 7. 4 20 .7 0. 7 -1 .1 33 73 5 H ar ar i 12 .6 29 .8 -1 .1 1. 6 9. 1 1. 8 -0 .5 4. 4 21 .5 0. 6 -1 .0 23 53 7 A dd is A ba ba 5. 9 22 .0 -0 .8 1. 4 4. 6 5. 7 0. 0 1. 7 6. 4 2. 5 -0 .5 19 4 35 7 D ire D aw a 18 .3 36 .3 -1 .4 2. 0 12 .3 2. 0 -0 .7 10 .4 27 .6 0. 6 -1 .3 35 64 4 M ot he r's e du ca tio n7 N o ed uc at io n 22 .5 46 .7 -1 .8 2. 9 10 .9 1. 5 -0 .6 10 .1 31 .5 0. 6 -1 .4 7, 21 2 6, 86 4 P rim ar y 17 .0 41 .7 -1 .5 2. 8 7. 8 1. 8 -0 .4 6. 9 25 .2 0. 9 -1 .2 2, 79 7 2, 47 8 S ec on da r y 6. 9 20 .0 -0 .9 0. 4 3. 0 4. 2 0. 0 2. 0 11 .7 2. 9 -0 .5 22 9 31 5 M or e th an s ec on da r y 4. 1 18 .9 -0 .7 2. 4 4. 9 7. 4 -0 .1 0. 6 4. 2 2. 6 -0 .3 14 7 16 3 W ea lth q ui nt ile Lo w es t 25 .5 49 .2 -1 .9 3. 3 12 .1 1. 7 -0 .6 12 .0 35 .6 0. 9 -1 .5 2, 45 2 3, 16 6 S ec on d 23 .1 47 .7 -1 .8 4. 1 12 .3 1. 8 -0 .7 11 .1 33 .2 0. 3 -1 .5 2, 38 5 1, 87 8 M id dl e 21 .8 45 .6 -1 .7 2. 5 9. 4 0. 8 -0 .5 8. 7 28 .8 0. 6 -1 .4 2, 28 9 1, 70 7 Fo ur th 17 .4 45 .0 -1 .7 2. 1 7. 7 1. 5 -0 .5 5. 9 25 .8 0. 4 -1 .3 2, 16 3 1, 71 7 H i g he st 12 .0 29 .7 -1 .2 1. 6 5. 1 2. 8 -0 .2 4. 9 15 .1 1. 5 -0 .8 1, 59 3 1, 81 4 To ta l 20 .6 44 .4 -1 .7 2. 8 9. 7 1. 7 -0 .5 8. 8 28 .7 0. 7 -1 .3 10 ,8 83 10 ,2 82 N ot e: T ab le is b as ed o n ch ild re n w ho s ta ye d in th e ho us eh ol d on th e ni gh t b ef or e th e in te rv ie w . E ac h of th e in di ce s is e xp re ss ed in s ta nd ar d de vi at io n un its (S D ) f ro m th e m ed ia n of th e W H O C hi ld G ro w th S ta nd ar ds a do pt ed in 20 06 . T he in di ce s in th is ta bl e ar e N O T co m pa ra bl e to th os e ba se d on th e pr ev io us ly u se d 19 77 N C H S /C D C /W H O r ef er en ce . T ot al in cl ud es 1 8 ca se s w ith m is si ng in fo rm at io n on s iz e at b irt h. T ab le is b as ed o n ch ild re n w ith va lid d at es o f b irt h (m on th a nd y ea r) an d va lid m ea su re m en t o f b ot h he ig ht a nd w ei gh t. 1 R ec um be nt le ng th is m ea su re d fo r c hi ld re n un de r a ge 2 , o r i n th e fe w c as es w he n th e ag e of th e ch ild is u nk no w n an d th e ch ild is le ss th an 8 5 cm ; s ta nd in g he ig ht is m ea su re d fo r a ll ot he r c hi ld re n. 2 I nc lu de s ch ild re n w ho a re b el ow -3 s ta nd ar d de vi at io ns (S D ) f ro m th e W H O C hi ld G ro w th s ta nd ar ds p op ul at io n m ed ia n 3 E xc lu de s ch ild re n w ho se m ot he rs w er e no t i nt er vi ew ed 4 F irs t-b or n tw in s (tr ip le ts , e tc .) ar e co un te d as fi rs t b irt hs b ec au se th ey d o no t h av e a pr ev io us b irt h in te rv al 5 I nc lu de s ch ild re n w ho se m ot he rs a re d ec ea se d 6 E xc lu de s ch ild re n w ho se m ot he rs w er e no t w ei gh ed a nd m ea su re d. M ot he r's n ut rit io na l s ta tu s in te rm s of B M I ( B od y M as s In de x) is p re se nt ed in T ab le 1 1. 10 7 F or w om en w ho a re n ot in te rv ie w ed , i nf or m at io n is ta ke n fro m th e H ou se ho ld Q ue st io nn ai re . E xc lu de s ch ild re n w ho se m ot he rs a re n ot li st ed in th e H ou se ho ld Q ue st io nn ai re • 159Nutrition of Children and Adults 160 • Nutrition of Children and Adults Weight-for-height Overall, 10 percent of Ethiopian children are wasted, and 3 percent are severely wasted. Wasting, or acute malnutrition, is highest in children age 9-11 months (19 percent) and lowest in children age 36-47 months (6 percent). Male children are slightly more likely to be wasted (11 percent) than female children (8 percent). Ten percent of children in rural areas are wasted, compared with 6 percent in urban areas. The data show an inverse correlation between wasting and birth weight. A higher proportion of babies who are reported as very small at birth (14 percent) are acutely malnourished than babies reported as average or larger in size (8 percent). Wasting is most common in the children of thin mothers (whose BMI is less than 18.5) (15 percent), in those residing in the Somali region (22 percent), in children whose mothers have no education (11 percent), and in those in the lowest two wealth quintiles (12 percent). A small proportion of children in Ethiopia are classified as overweight or obese. Overall, 2 percent of children below age five years are overweight or obese (+2 SD). Overweight or obesity among children increases with increasing BMI of the mother, from 1 percent among children of mothers who are thin to 4 percent among children of mothers who are overweight/obese (BMI >25). There are no substantial differences between male and female children. Variation by region is minimal except for Addis Ababa, where 6 percent of children under five, the highest percentage in all regions, are overweight or obese. Overweight and obesity do not correlate with wealth quintile. However, there is a positive relationship between mothers’ education and level of overweight or obesity in children under five years of age. Weight-for-age Table 11.1 shows that 29 percent of children under age five are underweight (have low weight-for-age), and 9 percent are severely underweight. The proportion of underweight children generally increases with each age cohort. The proportion of underweight children is highest in the age groups 24-35 months (34 percent) and lowest among those under six months (10 percent). This may be explained by the fact that foods for weaning are typically introduced to children in the older age group, thus increasing their exposure to infections and susceptibility to illness. This tendency, coupled with inappropriate or inadequate feeding practices, may contribute to faltering nutritional status among children in these age groups. Also, babies reported as very small or small at birth are much more likely to be underweight later in life (39 percent and 36 percent, respectively) than those reported as average or large at birth (25 percent). Children born to mothers who are thin (BMI less than 18.5) are more than three times as likely to be underweight (39 percent) as children born to mothers who are overweight/obese (12 percent). The proportion of underweight children is eight times higher for those born to uneducated mothers than for those whose mothers have more than secondary education (32 percent versus 4 percent). Rural children are more likely to be underweight (30 percent) than urban children (16 percent). The proportion of underweight children varies by region. Addis Ababa has the lowest proportion of underweight children, at 6 percent, while Affar has the highest prevalence of underweight children, at 40 percent. The proportion of underweight children decreases as the wealth quintile of the mother increases. Children born to mothers in the lowest wealth quintile are more than twice as likely to be underweight as children born to mothers in the highest wealth quintile (36 percent compared with 15 percent). Nutrition of Children and Adults • 161 Figure 11.1 Nutritional Status of Children by Age & & &&&& &&& & && &&&&&&&& &&&&&&&&&& &&&&&&&&&&&&&&&&&&&&&&&&&&&&& & * * ********* ************************************************* ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! 0 2 4 6 8 10 12 14 16 18 20 22 24 26 28 30 32 34 36 38 40 42 44 46 48 50 52 54 56 58 Age in months 0 10 20 30 40 50 60 70 Percent Height-for-age Weight-for-height Weight-for-age! * & EDHS 2011 11.1.4 Trends in Children’s Nutritional Status Trends in the nutritional status of children for the period 2000, 2005 and 2011 are shown in Figure 11.2. For the purpose of comparison, the data for 2000 and 2005 were recalculated using the new WHO standard reference population making it comparable to the results of 2011 EDHS. Figure 11.2 shows a downward trend in the proportion of children stunted and underweight over the three EDHS surveys. Stunting prevalence decreased by 12 percent (from 58 percent to 51 percent) between 2000 and 2005 and by an additional 14 percent to 44 percent between 2005 and 2011. The decline in the proportion of stunted Ethiopian children shows improvement in chronic malnutrition over the past eleven years. A similar pattern is also observed for the proportion of children underweight which dropped by 20 percent from 2000 to 2005 and 12 percent from 2005 to 2011. The prevalence of wasting in Ethiopia has remained constant over the last 11 years. 162 • Nutrition of Children and Adults Figure 11.2 Trends in Nutritional Status of Children Under Age 5 EDHS 2011 58 12 41 51 12 33 44 10 29 Stunting Wasting Underweight Anthropometric Indicators 0 10 20 30 40 50 60 70 Percentage 2000 2005 2011 Note: For comparison purposes, the 2000 and 2005 anthropometric indicators are computed on the basis of the new WHO Standards. The values in the graph indicate percentage below -2 SD. 11.2 BREASTFEEDING AND COMPLEMENTARY FEEDING Infant feeding affects both the mother and the child. Feeding practices affect the child’s nutritional status, which in turn affects the risk of death. The duration and intensity of breastfeeding affect the mother’s period of postpartum infertility, and hence the length of the birth interval and fertility levels. 11.2.1 Initiation of Breastfeeding Early initiation of breastfeeding is important for both the mother and the child. Early suckling stimulates the release of prolactin, which helps in the production of milk, and oxytocin, which is responsible for the ejection of milk and stimulates the contraction of the uterus after childbirth. The first liquid to come from the breast, known as colostrum, is produced in the first few days after delivery and provides natural immunity to the infant. It is recommended that children be fed colostrum immediately after birth and continue to be exclusively breastfed even if the regular breast milk has not yet let down. The survey collected information on children who were ever breastfed, who were breastfed in the first hour and the first day after birth, and who were fed anything other than breast milk before breast milk was regularly given (also known as prelacteal feeding). Table 11.2 shows that 98 percent of children are breastfed for some period of time. Breastfeeding is widely practised across all subgroups of women, and variations by background characteristics are small. Nutrition of Children and Adults • 163 Table 11.2 Initial breastfeeding Among last-born children who were born in the two years preceding the survey, the percentage who were ever breastfed and the percentages who started breastfeeding within one hour and within one day of birth; and among last-born children born in the two years preceding the survey who were ever breastfed, the percentage who received a prelacteal feed, by background characteristics, Ethiopia 2011 Background characteristic Among last-born children born in the past two years: Among last-born children born in the past two years who were ever breastfed: Percentage ever breastfed Percentage who started breastfeeding within 1 hour of birth Percentage who started breastfeeding within 1 day of birth1 Weighted number of last-born children Unweighted number of last-born children Percentage who received a prelacteal feed2 Weighted number of last-born children ever breastfed Unweighted number of last- born children ever breastfed Sex Male 96.8 49.0 77.8 2,327 2,184 28.8 2,252 2,124 Female 98.2 54.3 82.9 2,126 2,100 25.2 2,089 2,052 Assistance at delivery Health professional3 95.1 52.7 80.4 508 647 20.6 483 619 Traditional birth attendant 97.0 49.0 78.0 1,266 1,546 33.6 1,229 1,507 Other 98.0 52.5 81.2 2,519 1,899 25.2 2,469 1,860 No one 99.9 51.3 82.3 159 191 25.7 159 189 Place of delivery Health facility 94.3 52.1 80.0 517 653 20.9 487 623 At home 97.9 51.5 80.3 3,916 3,583 27.8 3,833 3,505 Other (100.0) (39.9) (61.5) 20 48 (32.1) 20 48 Residence Urban 95.2 57.1 83.2 607 751 24.2 578 720 Rural 97.8 50.6 79.7 3,846 3,533 27.5 3,762 3,456 Region Tigray 97.0 44.7 82.6 273 434 25.6 265 421 Affar 97.7 59.6 77.9 40 378 30.3 39 372 Amhara 96.5 37.5 66.9 983 476 47.8 949 459 Oromiya 98.0 52.6 83.6 1,917 681 21.9 1,879 667 Somali 96.8 39.6 54.8 128 358 72.5 124 346 Benishangul-Gumuz 97.5 42.2 68.7 51 373 23.4 49 364 SNNP 97.9 66.5 91.5 926 600 10.4 907 588 Gambela 97.3 59.3 73.2 15 317 28.4 14 311 Harari 97.2 64.6 86.0 11 246 31.2 11 239 Addis Ababa 93.4 62.0 74.1 95 167 25.5 89 157 Dire Dawa 99.1 66.0 81.2 14 254 34.2 14 252 Mother's education No education 97.9 50.7 79.0 2,956 2,845 30.1 2,893 2,787 Primary 96.6 51.5 82.3 1,296 1,184 20.5 1,252 1,144 Secondary 97.6 63.4 85.8 136 173 27.7 132 168 More than secondary 97.5 65.5 83.7 65 82 17.9 63 77 Wealth quintile Lowest 97.2 48.5 72.4 1,047 1,311 37.2 1,018 1,283 Second 98.1 50.9 78.7 988 782 30.1 969 766 Middle 97.9 50.7 81.3 917 704 23.1 897 686 Fourth 98.2 51.4 87.6 784 656 19.8 769 644 Highest 95.9 57.8 84.2 717 831 21.3 687 797 Total 97.5 51.5 80.2 4,453 4,284 27.1 4,340 4,176 Note: Table is based on last-born children born in the two years preceding the survey regardless of whether the children are living or dead at the time of interview. Figures in parentheses are based on 25-49 unweighted cases. 1 Includes children who started breastfeeding within one hour of birth 2 Children given something other than breast milk during the first three days of life 3 Doctor, nurse, or midwife Fifty-two percent of infants started breastfeeding within one hour of birth, and 80 percent, within the first day. This percentage falls short of the HSDP IV target of 92 percent of children breastfed within one hour of birth. Initiation of breastfeeding in the first hour and in the first 24 hours after birth varies by background characteristics. Breastfeeding within one hour after birth was more common in urban areas (57 percent) than in rural areas (51 percent). There was also considerable variation by region. Initiation of breastfeeding within one hour was lowest in the Amhara and Somali regions (38 percent and 40 percent, respectively), and highest in the SNNP and Dire Dawa regions (67 percent and 66 percent, respectively). The likelihood that a child is breastfed in the first hour after birth increases with the mother’s educational status and wealth quintile. The proportion of children who breastfed within one hour of birth does not vary significantly by type of assistance at delivery. Overall, nearly three children in every ten (27 percent) are given prelacteal feeds within the first three days of life. The practice of giving prelacteal feeds is discouraged because it limits the infant’s frequency of suckling and exposes the baby to the risk of infection. Prelacteal feeding is 164 • Nutrition of Children and Adults slightly more common in rural areas (28 percent) than in urban areas (24 percent). It also varies by region, most commonly practiced in Somali (73 percent). In contrast, 10 percent of children residing in SNNP receive prelacteal feeds. Children whose mothers were assisted during childbirth by a traditional birth attendant are most likely to receive prelacteal feeds (34 percent), while children whose mothers were assisted by a health professional are least likely (21 percent). The practice of prelacteal feeding decreases as wealth quintile increases, with the exception of children in the highest wealth quintile. Nearly four children in every ten (37 percent) of mothers in the lowest quintile receive prelacteal feeds, compared with two children in every ten of mothers in the two highest wealth quintiles (20 percent and 21 percent, respectively). 11.2.2 Breastfeeding Status by Age UNICEF and WHO recommend that children be exclusively breastfed during the first 6 months of life and that children be given solid or semi-solid complementary food in addition to continued breastfeeding from age 6 months until 24 months or more, when the child is fully weaned. Use of bottles with nipples is not recommended at any age. Exclusive breastfeeding is recommended because breast milk is uncontaminated and contains all the nutrients necessary in the first few months of life. In addition, the mother’s antibodies in breast milk provide the infant with immunity to disease. Early supplementation is discouraged for several reasons. First, it exposes infants to pathogens and thus increases their risk of infection, especially diarrhoeal disease. Second, it decreases infants’ intake of breast milk and therefore suckling, which in turn reduces breast milk production. Third, in low- resource settings, supplementary food is often nutritionally inferior. Interviewers obtained information on complementary feeding by asking mothers about the current breastfeeding status of all children under 5 years of age and, for the youngest child born in the two-year period before the survey and living with the mother, foods and liquids given to the child the day and night before the survey. Table 11.3 shows the percent distribution of youngest children under two years living with the mother by breastfeeding status and the percentage of children under two years using a bottle with a nipple, according to age in months. The data presented in Table 11.3 and Figure 11.3 show that exclusive breastfeeding during the first six months after birth is not widely practised in Ethiopia. Currently, mothers exclusively breastfeed approximately half of children under six months (52 percent). Among sub-groups the percentage of young children who are exclusively breastfed decreases sharply from 70 percent of infants age 0-1 month to 55 percent of those age 2-3 months and, further, to 32 percent among infants 4-5 months. The HSDP IV targets an increase in the proportion of exclusively breastfed infants under age 6 months to 70 percent by 2015. Nutrition of Children and Adults • 165 Figure 11.3 Infant Feeding Practices by Age <2 2-3 4-5 6-7 8-9 10 -11 12 -13 14 -15 16 -17 18 -19 20 -21 22 -23 Age in months 0% 20% 40% 60% 80% 100% Percent Exclusively breastfed Plain water only Non-milk liquids/juice Other milk Complementary foods Not breastfeeding EDHS 2011 16 6 • N ut rit io n of C hi ld re n an d A du lts Ta bl e 11 .3 B re as tfe ed in g st at us b y ag e P er ce nt d is tri bu tio n of y ou ng es t c hi ld re n un de r t w o ye ar s w ho a re li vi ng w ith th ei r m ot he r b y br ea st fe ed in g st at us a nd th e pe rc en ta ge c ur re nt ly b re as tfe ed in g; a nd th e pe rc en ta ge o f a ll ch ild re n un de r t w o ye ar s us in g a bo ttl e w ith a n ip pl e, a cc or di ng to a ge in m on th s, E th io pi a 20 11 A ge in m on th s B re as tfe ed in g st at us P er ce nt ag e cu rr en tly br ea st fe ed in g W ei gh te d nu m be r o f yo un ge st ch ild re n un de r t w o ye ar s liv in g w ith th e m ot he r U nw ei gh te d nu m be r o f yo un ge st ch ild re n un de r t w o ye ar s liv in g w ith th e m ot he r P er ce nt ag e us in g a bo ttl e w ith a ni pp le W ei gh te d nu m be r o f al l c hi ld re n un de r t w o ye ar s U nw ei gh te d nu m be r o f a ll ch ild re n un de r t w o ye ar s N ot br ea st fe ed in g E xc lu si ve ly br ea st fe d B re as tfe ed in g an d co ns um in g pl ai n w at er o nl y B re as tfe ed in g an d co ns um in g no n m ilk li qu id s1 B re as tfe ed in g an d co ns um in g ot he r m ilk B re as tfe ed in g an d co ns um in g co m pl em en ta ry fo od s To ta l 0- 1 1. 0 70 .3 18 .0 2. 3 5. 7 2. 7 10 0. 0 99 .0 36 3 33 3 8. 8 37 3 34 3 2- 3 0. 7 55 .3 16 .8 3. 6 15 .3 8. 3 10 0. 0 99 .3 47 9 45 2 14 .3 48 1 46 1 4- 5 2. 9 31 .8 21 .2 6. 1 19 .2 18 .9 10 0. 0 97 .1 40 6 40 2 23 .1 41 1 40 7 6- 8 1. 7 16 .9 16 .7 3. 5 12 .9 48 .4 10 0. 0 98 .3 60 8 59 1 13 .9 61 0 59 7 9- 11 4. 1 3. 6 9. 2 4. 9 6. 9 71 .4 10 0. 0 95 .9 50 5 44 2 11 .5 51 0 44 6 12 -1 7 5. 2 1. 6 7. 0 2. 2 3. 8 80 .1 10 0. 0 94 .8 1, 00 0 1, 04 6 10 .2 1, 03 0 1, 08 5 18 -2 3 15 .9 1. 2 1. 3 0. 5 0. 7 80 .3 10 0. 0 84 .1 83 5 77 1 7. 8 90 0 84 2 0- 3 0. 8 61 .8 17 .3 3. 1 11 .2 5. 9 10 0. 0 99 .2 84 2 78 5 11 .9 85 4 80 4 0- 5 1. 5 52 .0 18 .6 4. 0 13 .8 10 .1 10 0. 0 98 .5 1, 24 8 1, 18 7 15 .5 1, 26 5 1, 21 1 6- 9 2. 7 14 .2 14 .6 4. 2 12 .8 51 .4 10 0. 0 97 .3 77 8 74 7 14 .3 78 0 75 4 12 -1 5 3. 6 1. 9 7. 7 2. 6 4. 6 79 .7 10 0. 0 96 .4 68 2 67 6 11 .8 69 3 69 5 12 -2 3 10 .1 1. 4 4. 4 1. 5 2. 4 80 .2 10 0. 0 89 .9 1, 83 6 1, 81 7 9. 1 1, 93 0 1, 92 7 20 -2 3 17 .8 0. 8 1. 4 0. 5 0. 5 79 .1 10 0. 0 82 .2 52 1 47 5 7. 3 56 4 52 1 N ot e: B re as tfe ed in g st at us re fe rs to a "2 4- ho ur " p er io d (y es te rd ay a nd la st n ig ht ). C hi ld re n w ho a re c la ss ifi ed a s br ea st fe ed in g an d co ns um in g pl ai n w at er o nl y co ns um ed no li qu id o r s ol id s up pl em en ts . T he c at eg or ie s of n ot b re as tfe ed in g, e xc lu si ve ly b re as tfe d, b re as tfe ed in g an d co ns um in g pl ai n w at er , n on -m ilk li qu id s, o th er m ilk , a nd c om pl em en ta ry fo od s (s ol id s an d se m i-s ol id s) a re h ie ra rc hi ca l a nd m ut ua lly e xc lu si ve , a nd th ei r pe rc en ta ge s ad d to 1 00 p er ce nt . Th us c hi ld re n w ho r ec ei ve b re as t m ilk a nd n on -m ilk li qu id s an d w ho d o no t re ce iv e ot he r m ilk a nd w ho d o no t re ce iv e co m pl em en ta ry f oo ds a re c la ss ifi ed in t he n on -m ilk li qu id ca te go ry e ve n th ou gh th ey m ay a ls o ge t p la in w at er . A ny c hi ld re n w ho g et c om pl em en ta ry fo od a re c la ss ifi ed in th at c at eg or y as lo ng a s th ey a re b re as tfe ed in g as w el l. 1 N on -m ilk li qu id s in cl ud e ju ic e, ju ic e dr in ks , c le ar b ro th o r o th er li qu id s. 166 • Nutrition of Children and Adults Nutrition of Children and Adults • 167 In addition to breast milk, 19 percent of infants under six months are given plain water only, while 14 percent receive milk in addition to breast milk, and 4 percent are given non-milk liquids and juice (Figure 11.3). Complementary feeding is uncommon in Ethiopia; only 3 percent of children age 0-1 months receive complementary food, and only 10 percent of infants under six months are given complementary foods in addition to breast milk, indicating that very young children are mostly fed breastmilk, as recommended. All children age 6-9 months, in contrast, should receive complementary foods. However, only half of children age 6-9 months (51 percent) received complementary foods the day or night preceding the survey. Sixteen percent of infants under six months are fed using a bottle with a nipple, a practice that is discouraged, as it increases the child’s risk of illness and reduces the child’s interest in breastfeeding, with consequent potential decline in milk production. The duration of breastfeeding in Ethiopia is long. The proportion of children who are currently breastfeeding is 95 percent or more for children up to age 12-17 months and then declines to 84 percent of children age 18-23 months. Figure 11.4 shows several infant and young child feeding (IYCF) indicators of breastfeeding status. As mentioned, 52 percent of children under six months and 32 percent of children 4-5 months are exclusively breastfed1, and 75 percent of children under six months are predominantly breastfed2. About half of children age 6-8 months (49 percent) consume solid, semi-solid, or soft foods. Almost seven children of every ten (66 percent) under the age of two receive age-appropriate breastfeeding3, while one child of every ten (12 percent) use a bottle with a nipple. Ninety-six percent of children continued breastfeeding at one year, and 82 percent continued breastfeeding at two years. Figure 11.4 IYCF Indicators of Breastfeeding Status EDHS 2011 52 32 96 49 82 66 75 12 Exclusive breastfeeding under 6 months Exclusive breastfeeding at 4-5 months of age Continued breastfeeding at 1 year Introduction of solid, semi-solid or soft foods Continued breastfeeding at 2 years Age-appropriate breastfeeding (0-23 months) Predominant breastfeeding (0-5 months) Bottle feeding (0-23 months) Percentage of children (6-8 months) 1 Note that the Multiple Indicator Cluster Survey (MICS) indicator makes a specific point of including in exclusive breastfeeding children who received ORS, vitamins, mineral supplements and medicines in addition to breast milk. The DHS questionnaire does not ask comparable questions on all of these items. 2 Children who are exclusively breastfed, children who breastfeed and consume plain water, and children who breastfeed and consume non-milk liquids or juice. 3 Includes children age 0-5 months who are exclusively breastfed and children age 6-23 months who receive breast milk and complementary foods. 168 • Nutrition of Children and Adults 11.2.3 Duration of Breastfeeding Table 11.4 provides information on median duration of breastfeeding among children born in the three years preceding the survey. The estimates of median and mean durations of breastfeeding are based on current status data, that is, the proportion of children last-born in the three years preceding the survey who were being breastfed at the time of the survey. The median duration and the mean duration of any breastfeeding in Ethiopia are 25 months. The median duration of exclusive breastfeeding is 2.3 months, and the mean duration of exclusive breastfeeding is 4.2 months. Predominant breastfeeding is defined as exclusive breastfeeding or breastfeeding in combination with plain water, water-based liquids, or juices. The median and mean lengths of predominant breastfeeding are 5.3 months and 6.9 months, respectively. The median duration of any breastfeeding varies little by background characteristics, with the exceptions of regional and educational differences. Among regions the median duration of breastfeeding ranges from 16.7 months in the Somali region to 32.7 months in the Amhara region. Women with secondary and higher education breastfeed for several months less than women who have little or no education. For example, the median duration of breastfeeding among women with no education is 25.4 months, whereas it is 21.5 months among those with more than secondary education. Differentials in the median months of exclusive breastfeeding and predominant breastfeeding follow a similar pattern. Table 11.4 Median duration of breastfeeding Median duration of any breastfeeding, exclusive breastfeeding, and predominant breastfeeding among children born in the three years preceding the survey, by background characteristics, Ethiopia 2011 Background characteristic Median duration (months) of breastfeeding among children born in the past three years1 Any breastfeeding Exclusive breastfeeding Predominant breastfeeding2 Sex Male 25.7 1.8 5.0 Female 24.8 2.9 5.5 Residence Urban 24.3 0.6 4.6 Rural 25.3 2.5 5.4 Region Tigray 25.6 3.1 6.7 Affar 20.7 0.6 7.1 Amhara 32.7 4.6 7.4 Oromiya 24.0 1.8 4.9 Somali 16.7 0.5 2.8 Benishangul-Gumuz 26.4 1.9 4.7 SNNP 25.4 2.2 4.3 Gambela 30.7 0.6 5.6 Harari 22.2 1.9 5.1 Addis Ababa 20.1 1.0 2.1 Dire Dawa 21.3 1.9 4.5 Mother's education No education 25.4 2.6 5.5 Primary 25.5 1.8 4.9 Secondary 23.9 2.1 4.7 More than secondary 21.5 0.6 0.6 Wealth quintile Lowest 25.0 2.6 5.3 Second 25.8 2.3 5.2 Middle 28.0 3.6 6.1 Fourth 24.8 2.3 5.2 Highest 23.8 0.6 4.0 Total 25.2 2.3 5.3 Mean for all children 25.1 4.2 6.9 Note: Median and mean durations are based on the distributions at the time of the survey of the proportion of births by months since birth. Includes children living and deceased at the time of the survey. 1 It is assumed that non-last-born children and last-born children not currently living with the mother are not currently breastfeeding. 2 Either exclusively breastfed or received breast milk and plain water, and/or non-milk liquids only. Nutrition of Children and Adults • 169 11.2.4 Types of Complementary Foods UNICEF and WHO recommend the introduction of solid food to infants around age 6 months because by that age breast milk alone is no longer adequate to maintain a child’s optimal growth. In the transition to introducing the child to the family diet, in addition to breastfeeding, children age six months and older should be fed small quantities of solid and semi-solid foods frequently throughout the day. During this transition period (age 6-23 months), the prevalence of malnutrition increases substantially in many countries because of an increase in infections and poor feeding practices. The 2011 EDHS collected data on the types of foods given on the day and night preceding the survey to the youngest child under age 2 living with the mothers. These data are presented in Table 11.5 according to breastfeeding status. Infant formula supplementation at any age is uncommon in Ethiopia. Among breastfeeding children under age two, very few (2 percent) consume infant formula. However, a much higher proportion (18 percent) receive other milk or other liquids. The introduction of other liquids, such as water, juice, and formula, takes place earlier than the recommended introduction at age six months. Among the youngest breastfeeding children (0-1 month), 6 percent consume other milk and 3 percent consume other liquids. Consumption of other milk increases gradually with age until age 6-8 months, when 24 percent of breastfeeding children consume milk. Consumption of other liquids also shows increasing trends with age through age 12-17 months, when 26 percent of breastfeeding children consume other liquids. Among children age 6-23 months, foods made from grains are consumed more often than foods from any other food group. Among breastfeeding children in this age group, 66 percent ate foods made from grains, and 20 percent ate foods from legumes or nuts during the day or night preceding the interview. Among breastfeeding children age 6-23 months, only 15 percent consumed fruits and vegetables rich in vitamin A or foods made from roots and tubers. Thirteen percent of children in this age group consumed cheese, yogurt, or other dairy products in the 24 hours preceding the survey. Meat, fish, poultry, and eggs have body-building substances essential to good health. They are important for balanced physical and mental development. The introduction of these foods in the diet is late, and few children consume them. For instance, at age 6-23 months, only 5 percent of children consume meat, fish, or poultry, and 8 percent consume eggs. Overall, almost four of every five breastfeeding children age 6-23 months (78 percent) consumed some solid or semi-soild food during the day or night preceding the survey. A comparison of dietary intake of children under two years of age by breastfeeding status shows that a higher proportion of nonbreastfeeding children are consuming solid and semi-solid foods (84 percent) than breastfeeding children (57 percent). Consumption of foods made from grains is very common (69 percent), whereas consumption of vitamin A-rich fruits and vegetables and foods made from roots and tubers is less common (24-25 percent). As expected, more nonbreastfeeding children than breastfeeding children consume milk other than breast milk (43 percent compared with 18 percent). Still; the percentage of nonbreastfeeding children consuming milk other than breast milk is low, considering that they are not benefiting from breast milk. 17 0 • N ut rit io n of C hi ld re n an d A du lts Ta bl e 11 .5 F oo ds a nd li qu id s co ns um ed b y ch ild re n in th e da y or n ig ht p re ce di ng th e in te rv ie w P er ce nt ag e of y ou ng es t c hi ld re n un de r tw o ye ar s of a ge w ho a re li vi ng w ith th e m ot he r by ty pe o f f oo ds c on su m ed in th e da y or n ig ht p re ce di ng th e in te rv ie w , a cc or di ng to b re as tfe ed in g st at us a nd a ge , E th io pi a 20 11 A ge in m on th s Li qu id s S ol id o r s em i-s ol id fo od s A ny s ol id or s em i- so lid fo od 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 In fa nt fo rm ul a O th er m ilk 1 O th er liq ui ds 2 Fo rti fie d ba by fo od s Fo od m ad e fro m gr ai ns 3 Fr ui ts a nd ve ge ta bl es ric h in vi ta m in A 4 O th er fr ui ts an d ve ge ta bl es Fo od m ad e fro m ro ot s an d tu be rs Fo od m ad e fro m le gu m es an d nu ts M ea t, fis h, po ul try Eg gs C he es e, yo gu rt, ot he r m ilk pr od uc t BR EA ST FE ED IN G C H IL D R EN 0- 1 1. 2 6. 3 3. 0 0. 0 0. 1 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 1. 0 2. 7 35 9 32 5 2- 3 3. 6 12 .9 5. 0 0. 0 4. 1 0. 0 0. 0 0. 2 0. 6 0. 0 0. 0 3. 6 8. 3 47 5 44 3 4- 5 2. 7 20 .5 13 .9 0. 6 6. 6 1. 9 0. 4 2. 2 0. 7 0. 2 2. 3 7. 0 19 .4 39 4 38 7 6- 8 1. 3 23 .7 16 .8 3. 9 34 .9 8. 5 1. 8 6. 9 7. 3 2. 8 7. 7 7. 9 49 .2 59 8 57 6 9- 11 1. 9 21 .1 21 .4 4. 4 62 .8 10 .2 2. 9 10 .6 16 .4 2. 4 9. 4 14 .0 74 .4 48 5 42 4 12 -1 7 1. 7 20 .6 26 .0 4. 7 73 .1 19 .1 3. 8 17 .6 21 .7 6. 0 8. 8 14 .9 84 .6 94 8 93 0 18 -2 3 0. 6 17 .4 23 .0 2. 7 84 .9 17 .5 4. 1 19 .6 29 .2 8. 6 7. 6 14 .4 95 .5 70 2 61 5 6- 23 1. 3 20 .5 22 .4 4. 0 65 .9 14 .8 3. 3 14 .5 19 .5 5. 3 8. 3 13 .1 77 .8 2, 73 3 2, 54 5 To ta l 1. 7 18 .3 17 .7 2. 8 46 .6 10 .4 2. 3 10 .3 13 .6 3. 7 6. 0 10 .2 56 .9 3, 96 2 3, 70 0 N O N BR EA ST FE ED IN G C H IL D R EN To ta l 3. 3 43 .3 34 .7 5. 7 69 .4 24 .6 7. 4 24 .4 17 .3 7. 4 7. 6 20 .0 84 .1 23 5 33 7 N ot e: B re as tfe ed in g st at us a nd fo od c on su m ed re fe r t o a 24 -h ou r" p er io d (y es te rd ay a nd la st n ig ht ). 1 O th er m ilk in cl ud es fr es h, ti nn ed a nd p ow de re d co w o r o th er a ni m al m ilk . 2 D oe s no t i nc lu de p la in w at er . I nc lu de s ju ic e, ju ic e dr in ks , c le ar b ro th , o r o th er n on -m ilk li qu id s. 3 I nc lu de s fo rti fie d ba by fo od . 4 I nc lu de s pu m pk in , s qu as h, c ar ro ts , s w ee t p ot at oe s th at a re y el lo w o r o ra ng e in si de , d ar k gr ee n le af y ve ge ta bl es , r ip e m an go es , r ip e pa pa ya s, a nd o th er fr ui ts a nd v eg et ab le s th at a re ri ch in v ita m in A . 170 • Nutrition of Children and Adults Nutrition of Children and Adults • 171 11.2.5 Infant and Young Child Feeding (IYCF) Practices Appropriate infant and young child feeding (IYCF) practices include timely initiation of feeding of solid and semi-solid foods from age 6 months and improving the quality of foods consumed as the child gets older, while maintaining breastfeeding (WHO, 2008). WHO has established guidelines with respect to IYCF practices for children age 6-23 months. Breastfeed children 6-23 months should receive animal-source foods and vitamin A-rich fruits and vegetables daily (PAHO/WHO, 2003). Since first foods almost universally include a grain- or tuber- based staple, it is unlikely that young children who eat two or fewer food groups will receive both an animal-source food and a vitamin A-rich fruit or vegetable. Therefore, four food groups are considered the minimum acceptable number of food groups for breastfed infants (Arimond and Ruel, 2003). Breastfed infants 6-8 months should be fed meals of complementary foods two or three times per day, with one to two snacks as desired; breastfed children 9-23 months should be fed meals three or four times per day, with one to two snacks (WHO, 2008). Nonbreastfed children 6-23 months should receive milk products at least twice a day to ensure that their calcium needs are met. In addition, they need animal-source foods and vitamin A-rich fruits and vegetables. Therefore, for nonbreastfed young children, four food groups are considered the minimum acceptable number. Nonbreastfed children should be fed meals four or five times per day, with one to two snacks as desired (WHO, 2005). Meal frequency is considered a proxy for energy intake from foods other than breast milk. Therefore, for nonbreastfed children feeding frequency indicators include both milk feeds and solid or semi-solid feeds (WHO, 2008). Table 11.6 presents summary indicators of IYCF practices. Results show that only 4 percent of youngest children 6-23 months living with their mothers are fed in accordance with IYCF practices. More than nine children of every ten (96 percent) received breast milk or milk products during the 24-hour period before the survey, and half of the children (49 percent) were fed at least the minimum number of times. Five percent of children were fed according to minimum standards with respect to food diversity (four or more food groups). Older children and children in urban areas are more likely to be fed according to the IYCF practices than younger children or rural children. In addition, feeding practices improve as the wealth quintile and the educational level of the mother increases. Among breastfed children age 6-23 months, 4 percent receive foods from at least four food groups, while 48 percent are fed the minimum number of times or more. In total, 4 percent of breastfed children are given foods from four or more groups and also are fed at least the minimum number of times per day. 17 2 • N ut rit io n of C hi ld re n an d A du lts Ta bl e 11 .6 I nf an t a nd y ou ng c hi ld fe ed in g (IY C F) p ra ct ic es P er ce nt ag e of y ou ng es t c hi ld re n ag e 6- 23 m on th s liv in g w ith th ei r m ot he r w ho a re fe d ac co rd in g to th re e IY C F fe ed in g pr ac tic es b as ed o n br ea st fe ed in g st at us , n um be r of fo od g ro up s, a nd ti m es th ey a re fe d du rin g th e da y or n ig ht p re ce di ng th e su rv ey , 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 A m on g br ea st fe d ch ild re n 6- 23 m on th s, p er ce nt ag e fe d: W ei gh te d nu m be r o f br ea st fe d ch ild re n 6- 23 m on th s U nw ei gh te d nu m be r o f br ea st fe d ch ild re n 6- 23 m on th s A m on g no n- br ea st fe d ch ild re n 6- 23 m on th s, pe rc en ta ge fe d: W ei gh te d nu m be r o f n on - br ea st fe d ch ild re n 6- 23 m on th s U nw ei gh te d nu m be r o f n on - br ea st fe d ch ild re n 6- 23 m on th s A m on g al l c hi ld re n 6- 23 m on th s, p er ce nt ag e fe d: W ei gh te d nu m be r o f al l c hi ld re n 6- 23 m on th s U nw ei gh te d nu m be r o f al l c hi ld re n 6- 23 m on th s 4+ fo od gr ou ps 1 M in im um m ea l fre qu en cy 2 B ot h 4+ fo od g ro up s an d m in im um m ea l fre qu en cy M ilk o r m ilk pr od uc ts 3 4+ fo od gr ou ps 1 M in im um m ea l fre qu en cy 4 W ith 3 IY C F pr ac tic es 5 B re as t m ilk , m ilk , o r m ilk pr od uc ts 6 4+ fo od gr ou ps 1 M in im um m ea l fre qu en cy 7 W ith 3 IY C F pr ac tic es A ge in m on th s 6- 8 1. 0 36 .5 1. 0 59 8 57 6 * * * * 10 15 99 .2 1. 0 36 .2 1. 0 60 8 59 1 9- 11 2. 1 37 .7 2. 0 48 5 42 4 * * * * 21 18 97 .5 2. 0 38 .2 1. 9 50 5 44 2 12 -1 7 6. 2 47 .4 5. 4 94 8 93 0 38 .0 5. 9 40 .9 1. 3 52 11 6 96 .7 6. 2 47 .0 5. 2 1, 00 0 1, 04 6 18 -2 3 6. 0 65 .4 5. 9 70 2 61 5 43 .4 15 .8 64 .9 8. 1 13 3 15 6 91 .0 7. 6 65 .3 6. 3 83 5 77 1 Se x M al e 3. 7 48 .3 3. 3 1, 37 9 1, 26 5 42 .4 13 .4 59 .3 7. 5 11 9 16 7 95 .4 4. 5 49 .2 3. 6 1, 49 7 1, 43 2 Fe m al e 4. 9 47 .5 4. 7 1, 35 5 1, 28 0 41 .8 8. 3 50 .7 2. 7 97 13 8 96 .1 5. 1 47 .7 4. 6 1, 45 2 1, 41 8 R es id en ce U rb an 8. 7 49 .4 7. 9 36 0 42 7 67 .3 38 .3 74 .9 19 .8 44 84 96 .4 12 .0 52 .2 9. 2 40 4 51 1 R ur al 3. 6 47 .7 3. 4 2, 37 4 2, 11 8 35 .6 4. 1 50 .4 1. 6 17 2 22 1 95 .7 3. 6 47 .9 3. 2 2, 54 5 2, 33 9 R eg io n Ti gr ay 5. 3 55 .6 4. 5 18 3 28 9 * * * * 15 24 94 .4 6. 0 56 .9 4. 2 19 8 31 3 A ffa r 5. 9 23 .7 3. 9 19 18 3 (5 7. 8) (3 .5 ) (4 7. 8) (0 .0 ) 5 46 91 .5 5. 4 28 .6 3. 1 23 22 9 A m ha ra 2. 1 34 .0 2. 1 64 6 31 6 * * * * 20 10 97 .7 2. 0 34 .0 2. 0 66 6 32 6 O ro m i y a 6. 1 56 .0 5. 8 1, 15 6 41 5 (3 3. 5) (6 .4 ) (5 4. 8) (3 .4 ) 81 28 95 .7 6. 1 55 .9 5. 7 1, 23 7 44 3 S om al i 0. 8 11 .7 0. 8 53 15 4 75 .1 9. 1 45 .4 5. 2 23 64 92 .5 3. 3 21 .9 2. 2 75 21 8 B en is ha n g ul -G um uz 5. 3 46 .0 4. 1 32 23 6 * * * * 2 14 96 .8 5. 4 46 .2 3. 9 34 25 0 S N N P 2. 5 48 .9 2. 3 56 7 37 0 (4 4. 3) (1 7. 0) (6 0. 2) (1 1. 3) 54 33 95 .2 3. 8 49 .8 3. 1 62 0 40 3 G am be la 9. 8 35 .4 7. 3 9 19 1 * * * * 0 7 97 .7 12 .0 36 .2 7. 0 9 19 8 H ar ar i 5. 9 48 .5 4. 7 7 16 0 * * * * 1 19 93 .6 7. 7 50 .9 4. 2 8 17 9 A dd is A ba ba 7. 5 50 .8 4. 6 53 92 (6 5. 9) (3 0. 2) (7 2. 8) (9 .1 ) 14 26 92 .8 12 .3 55 .4 5. 5 67 11 8 D ire D aw a 12 .0 56 .0 11 .0 8 13 9 (5 7. 8) (2 5. 4) (6 6. 2) (1 1. 9) 2 34 91 .7 14 .6 58 .0 11 .2 10 17 3 M ot he r's e du ca tio n N o ed uc at io n 2. 3 43 .8 2. 1 1, 88 1 1, 72 7 35 .8 1. 6 45 .0 0. 6 11 3 18 4 96 .4 2. 2 43 .9 2. 0 1, 99 3 1, 91 1 P rim ar y 7. 3 55 .9 6. 9 74 1 67 9 45 .0 16 .4 62 .7 7. 5 88 90 94 .2 8. 3 56 .6 7. 0 82 9 76 9 S ec on da r y 8. 2 61 .2 7. 3 69 97 * * * * 10 18 96 .5 15 .1 65 .8 10 .7 79 11 5 M or e th an s ec on da r y (3 2. 8) (6 6. 5) (3 0. 6) 43 42 * * * * 5 13 96 .1 32 .5 67 .8 28 .7 48 55 W ea lth q ui nt ile Lo w es t 1. 4 42 .2 1. 2 65 7 75 7 38 .7 1. 4 38 .4 0. 0 32 80 97 .1 1. 4 42 .0 1. 2 68 9 83 7 S ec on d 4. 7 47 .1 4. 0 61 6 48 0 (2 9. 6) (3 .6 ) (4 7. 1) (0 .0 ) 46 46 95 .1 4. 6 47 .1 3. 8 66 1 52 6 M id dl e 2. 9 50 .9 2. 9 54 7 41 5 (3 5. 6) (0 .2 ) (5 6. 1) (0 .0 ) 47 42 94 .9 2. 7 51 .3 2. 7 59 4 45 7 Fo ur th 3. 9 50 .6 3. 9 48 6 40 7 (3 7. 6) (6 .2 ) (5 4. 7) (0 .0 ) 38 43 95 .5 4. 1 50 .9 3. 6 52 4 45 0 H i g he st 10 .2 51 .0 9. 6 42 8 48 6 64 .1 37 .1 73 .0 21 .8 53 94 96 .1 13 .2 53 .4 10 .9 48 1 58 0 To ta l 4. 3 47 .9 4. 0 2, 73 3 2, 54 5 42 .1 11 .1 55 .4 5. 3 21 6 30 5 95 .8 4. 8 48 .5 4. 1 2, 94 9 2, 85 0 1 Fo od g ro up s: a . i nf an t f or m ul a, m ilk o th er th an b re as t m ilk , c he es e or y og ur t; b. fo od s m ad e fro m g ra in s, r oo ts , a nd tu be rs , i nc lu di ng p or rid ge a nd fo rti fie d ba by fo od fr om g ra in s; c . v ita m in A -ri ch fr ui ts a nd v eg et ab le s; d . o th er fr ui ts a nd v eg et ab le s; e . e gg s; f. m ea t, po ul try , f is h, s he llf is h, a nd o rg an m ea ts ; g . l eg um es a nd n ut s. 2 F or b re as tfe d ch ild re n, m in im um m ea l f re qu en cy is re ce iv in g so lid o r s em i-s ol id fo od a t l ea st tw ic e a da y fo r i nf an ts 6 -8 m on th s an d at le as t t hr ee ti m es a d ay fo r c hi ld re n 9- 23 m on th s 3 I nc lu de s tw o or m or e fe ed in gs o f c om m er ci al in fa nt fo rm ul a fre sh , t in ne d an d po w de re d an im al m ilk ; a nd y og ur t. 4 F or n on -b re as tfe d ch ild re n ag e 6- 23 m on th s, m in im um m ea l f re qu en cy is re ce iv in g so lid o r s em i-s ol id fo od o r m ilk fe ed s at le as t f ou r t im es a d ay . 5 N on -b re as tfe d ch ild re n ag e 6- 23 m on th s ar e co ns id er ed to b e fe d w ith a m in im um s ta nd ar d of th re e In fa nt a nd y ou ng c hi ld fe ed in g pr ac tic es if th ey re ce iv e ot he r m ilk o r m ilk p ro du ct s at le as t t w ic e a da y, re ce iv e th e m in im um m ea l f re qu en cy , a nd re ce iv e so lid o r se m i-s ol id fo od s fro m a t l ea st fo ur fo od g ro up s no t i nc lu di ng th e m ilk /m ilk p ro du ct g ro up . 6 B re as tfe ed in g, o r n ot b re as tfe ed in g an d re ce iv in g tw o or m or e fe ed in gs o f c om m er ci al in fa nt fo rm ul a, fr es h, ti nn ed , a nd p ow de re d an im al m ilk , a nd y og ur t. 7 C hi ld re n ar e fe d th e m in im um re co m m en de d nu m be r o f t im es p er d ay a cc or di ng to th ei r a ge a nd b re as tfe ed in g st at us a s de sc rib ed in fo ot no te s 2 an d 4. 172 • Nutrition of Children and Adults Nutrition of Children and Adults • 173 11.3 PREVALENCE OF ANAEMIA IN CHILDREN Anaemia is a condition characterised by a low level of haemoglobin in the blood. Haemoglobin is necessary for transporting oxygen to tissues and organs in the body. About half of the global burden of anaemia is due to iron deficiency. Iron deficiency, in turn, is largely due to an inadequate dietary intake of bioavailable iron, inadequate dietary iron during periods of increased iron requirements (such as pregnancy and infancy), increased blood loss due to hookworm infestation, and infections such as malaria. Nutritional anaemia includes anaemia due to deficiency in iron plus deficiencies in folate, vitamins B and B12, and certain trace elements involved with red blood cell production. Anaemia in children is associated with impaired mental and physical development and with increased morbidity and mortality. Anaemia can be a particularly serious problem for pregnant women, leading to premature delivery and low birth weight. WHO considers anaemia prevalence over 40 percent in a population to be a major public health problem, anaemia prevalence between 20 and 40 percent is considered a medium-level public health problem, and between 5 to less than 20 percent is considered a mild public health problem (WHO, 2001). A number of interventions have been put in place in Ethiopia to address the high prevalence of anaemia in children. These include distribution and promotion of the use of insecticide-treated mosquito nets (ITNs) and deworming of children age 2-5 every six months. Other programmes that seek to reduce anaemia include the Enhanced Outreach Strategy (EOS) with Targeted Supplementary Food (TSF), Health Facility Nutrition Services, Community Based Nutrition (CBN), Micronutrient Interventions, and Essential Nutrition Actions. Table 11.7 presents anaemia levels among children age 6-59 months, according to selected background characteristics. Haemoglobin was measured in 9,157 children (9,800 children weighted) that account for 93 percent of all children. Unadjusted (i.e., measured) haemoglobin values are obtained using the HemoCue instrument. Given that haemoglobin requirements differ substantially depending on altitude, an adjustment to sea-level equivalents has been made before classifying children by level of anaemia. These adjustments for altitude are reflected in Table 11.7. More than four in ten Ethiopian children (44 percent) are anaemic. One child of every five (21 percent) has mild anaemia, another 20 percent have moderate anaemia, and 3 percent have severe anaemia. Anaemia prevalence is highest among children age 9-11 months (73 percent) and decreases steadily with age from 12 to 59 months. Forty-five percent of children in rural areas have anaemia, compared with 35 percent of children in urban areas. Regional variation of anaemia in children ranges from 33 percent in Addis Ababa to 75 percent in Affar. Anaemia among children decreases with increases in mother’s education and wealth quintile. The national anaemia prevalence estimate has dropped by 19 percent in the past six years, from 54 percent in 2005 to 44 percent in 2011 (Figure 11.5). This change is due largely to the drop in the prevalence of moderate anaemia; estimates of the prevalence of mild and severe anaemia have remained stable. The prevalence of moderate anaemia decreased from 28 percent in 2005 to 20 percent in 2011. 174 • Nutrition of Children and Adults Table 11.7 Prevalence of anaemia in children Percentage of children age 6-59 months classified as having anaemia, by background characteristics, Ethiopia 2011 Background characteristic Anaemia status by haemoglobin level Weighted number of children Unweighted number of children Any anaemia (<11.0 g/dl) Mild anaemia (10.0-10.9 g/dl) Moderate anaemia (7.0-9.9 g/dl) Severe anaemia (< 7.0 g/dl) Age in months 6-8 61.3 24.2 35.7 1.5 572 528 9-11 72.7 26.3 40.7 5.7 500 411 12-17 62.6 25.3 33.7 3.6 997 1,011 18-23 52.2 22.1 27.9 2.2 901 806 24-35 45.4 22.9 18.0 4.5 2,062 2,016 36-47 35.8 19.3 15.1 1.4 2,434 2,237 48-59 30.8 18.5 11.3 1.0 2,334 2,148 Sex Male 44.3 20.9 20.7 2.7 5,032 4,692 Female 44.2 21.9 20.0 2.3 4,768 4,465 Mother's interview status Interviewed 44.6 21.7 20.5 2.5 9,073 8,461 Not interviewed but in household 38.0 16.9 16.8 4.2 217 222 Not interviewed, and not in the household1 39.4 17.2 20.5 1.8 510 474 Residence Urban 35.2 15.7 18.0 1.5 1,139 1,388 Rural 45.4 22.1 20.7 2.6 8,661 7,769 Region Tigray 37.5 17.4 17.5 2.6 661 1,027 Affar 74.7 21.6 46.1 7.0 95 877 Amhara 35.1 19.4 14.5 1.1 2,148 1,041 Oromiya 51.7 22.9 25.1 3.7 4,199 1,442 Somali 68.7 24.5 35.2 9.0 241 691 Benishangul-Gumuz 46.5 25.1 19.6 1.8 111 808 SNNP 36.9 21.3 15.1 0.5 2,111 1,352 Gambela 50.9 22.4 26.0 2.5 29 637 Harari 55.5 26.6 26.6 2.3 19 451 Addis Ababa 33.2 17.0 15.3 1.0 155 281 Dire Dawa 62.9 18.0 34.7 10.2 30 550 Mother's education2 No education 45.5 21.4 21.4 2.6 6,546 6,189 Primary 42.9 22.6 17.8 2.5 2,446 2,122 Secondary 41.4 18.6 21.1 1.6 175 250 More than secondary 30.1 15.8 14.3 0.0 122 121 Wealth quintile Lowest 47.9 20.5 24.2 3.2 2,216 2,847 Second 47.6 23.0 21.2 3.3 2,180 1,699 Middle 43.3 21.9 18.9 2.5 2,066 1,526 Fourth 43.1 21.6 19.5 2.0 1,985 1,549 Highest 35.9 18.9 16.3 0.7 1,353 1,536 Total 44.2 21.4 20.4 2.5 9,800 9,157 Note: Table is based on children who stayed in the household on the night before the interview and who were tested for anaemia. Prevalence of anaemia, based on haemoglobin levels, is adjusted for altitude using formulas from CDC, 1998. Haemoglobin in grams per decilitre (g/dl) 1 Includes children whose mothers are deceased 2 For women who are not interviewed, information is taken from the Household Questionnaire. Excludes children whose mothers are not listed in the Household Questionnaire. Nutrition of Children and Adults • 175 Figure 11.5 Trends in Anaemia Status among Children 6-59 Months EDHS 2011 54 21 28 3.9 44 21 20 2.5 Any anaemia (<11.0 g/dl) Mild anaemia (10.0-10.9 g/dl) Moderate anaemia (7.0-9.9 g/dl) Severe anaemia (<7.0 g/dl) 0 10 20 30 40 50 60 Percentage 2005 2011 11.4 MICRONUTRIENT INTAKE AMONG CHILDREN Micronutrient deficiency is a major contributor to childhood morbidity and mortality. Children can receive micronutrients from foods, food fortification, and direct supplementation. Table 11.8 summarises information collected in the 2011 EDHS on children’s intake of vitamin A and iron, receipt of deworming medications, and whether they live in households with iodized salt. Vitamin A is an essential micronutrient for the immune system that plays an important role in maintaining the epithelial tissue in the body. Severe vitamin A deficiency (VAD) can cause eye damage. VAD can also increase the severity of infections such as measles and diarrhoeal diseases in children and slow recovery from illness. Vitamin A is found in breast milk, other milks, liver, eggs, fish, butter, red palm oil, mangoes, papayas, carrots, pumpkins, and dark green leafy vegetables. The liver can store an adequate amount of the vitamin for four to six months. Periodic dosing (usually every six months) of vitamin A supplements is one method of ensuring that children at risk do not develop VAD. Table 11.8 shows that 26 percent of youngest children age 6-23 months living with their mothers consumed foods rich in vitamin A in the 24 hours preceding the interview. The proportion of children consuming vitamin A rich foods increases with age (from 16 percent at 6-8 months to 31 percent at 18-23 months). Nonbreastfeeding children are more likely than breastfeeding children to consume foods rich in vitamin A (34 percent compared with 25 percent). Urban children (38 percent) are more likely than rural children (24 percent) to consume foods rich in vitamin A. With regard to regions, children living in the Gambela region are most likely to consume foods rich in vitamin A (48 percent), while those in the Affar region are least likely (11 percent). Mother’s level of education is directly related to the consumption of foods rich in vitamin A; 20 percent of children whose mothers have no education consumed foods rich in vitamin A in the 24 hours before the survey, 176 • Nutrition of Children and Adults compared with 58 percent of children whose mothers have more than secondary education. Likewise, as household wealth increases, so does the proportion of children who receive foods rich in vitamin A, from 19 percent among children in the lowest wealth quintile to 40 percent among children in the highest wealth quintile. As noted, low iron intake can also contribute to anaemia. Also, iron is essential for cognitive development. Iron requirements are greatest at ages 6-11 months, when growth is extremely rapid. As Table 11.8 shows, 13 percent of children age 6-23 months consumed iron-rich foods in the 24 hours preceding the survey. Consumption of foods rich in iron increases with age, as children age 18-23 months are more likely to consume foods rich in iron than children age 6-8 months (16 percent and 10 percent, respectively). The consumption of iron-rich foods is more common in urban areas (22 percent) than in rural areas (12 percent). Children in Gambela are most likely to consume iron- rich foods (33 percent), while those living in Affar, SNNP, and Somali are the least likely (6 percent each). Children whose mothers have some secondary education are more likely to consume iron-rich foods (31 percent) than those whose mothers have no education (11 percent). Similarly, wealth status is directly related to the consumption of foods rich in iron, with 9 percent of children in the lowest wealth quintile consuming foods rich in iron in the 24 hours before the survey compared with 23 percent of children in the highest wealth quintile. The 2011 EDHS also collected data on vitamin A and iron supplementation for children age 6-59 months. Table 11.8 shows that more than half of children age 6-59 months (53 percent) received vitamin A supplements in the six months preceding the survey. Vitamin A supplementation does not show a clear pattern among children of different age cohorts. Children in urban areas are slightly more likely to have received vitamin A supplements in the past six months (57 percent) than those in rural areas (53 percent). At the regional level the proportion of children receiving vitamin A supplements was exceptionally low in Somali and Affar (26 percent and 35 percent, respectively), while Tigray had the highest proportion of children who were given vitamin A supplementation (83 percent). Mother’s level of education is closely associated with children receiving vitamin A supplements; 51 percent of children whose mothers have no education received vitamin A supplements in the past six months compared with 72 percent of children whose mothers have more than a secondary education. A similar pattern is observed with household wealth status. Iron supplementation coverage is generally low in Ethiopia. Only 6 percent of children age 6-59 months were given iron supplements in the seven days preceding the survey. It is, however, worth noting that Benishangul-Gumuz and Dire Dawa have relatively high coverage (20 percent and 19 percent, respectively) compared with other regions. Rural children were twice as likely as urban children to have received iron supplements in the seven days preceding the survey (6 percent compared with 3 percent). Nutrition of Children and Adults • 177 Infection with helminths or intestinal worms has an adverse impact on the physical development of children and is associated with high levels of iron deficiency anaemia and other nutritional deficiencies. Regular treatment with deworming medication is a simple, cost-effective measure to address these infections. As Table 11.8 shows, 21 percent of children age 6-59 months received deworming medication during the six months preceding the survey. The likelihood of receiving deworming medication increases with the child’s age, mother’s age at childbirth, mother’s education, and wealth status. Non-breastfed children as well as urban children are more likely to receive deworming medication than their counterparts. Benishangul-Gumuz (27 percent), Amhara and Tigray regions (26 percent, each) have the highest proportion of children who received deworming medication, while Somali is the region with the lowest proportion (6 percent). 17 8 • N ut rit io n of C hi ld re n an d A du lts Ta bl e 11 .8 M ic ro nu tri en t i nt ak e am on g ch ild re n A m on g yo un ge st c hi ld re n ag e 6- 23 m on th s w ho a re li vi ng w ith th ei r m ot he r, th e pe rc en ta ge s w ho c on su m ed v ita m in A ri ch a nd ir on -r ic h fo od s in th e da y or n ig ht p re ce di ng th e su rv ey , a nd a m on g al l c hi ld re n 6- 59 m on th s, th e pe rc en ta ge s w ho w er e gi ve n vi ta m in A s up pl em en ts in th e si x m on th s pr ec ed in g th e su rv ey , w ho w er e gi ve n iro n su pp le m en ts in th e pa st s ev en d ay s, a nd w ho w er e gi ve n de w or m in g m ed ic at io n in th e si x m on th s pr ec ed in g th e su rv ey , a nd a m on g al l ch ild re n ag e 6- 59 m on th s w ho li ve in h ou se ho ld s th at w er e te st ed fo r i od iz ed s al t, th e pe rc en ta ge w ho li ve in h ou se ho ld s w ith io di ze d sa lt, 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 A m on g yo un ge st c hi ld re n ag e 6- 23 m on th s liv in g w ith th e m ot he r: A m on g al l c hi ld re n ag e 6- 59 m on th s: A m on g ch ild re n ag e 6- 59 m on th s liv in g in ho us eh ol ds te st ed fo r i od iz ed s al t P er ce nt ag e w ho c on su m ed fo od s ric h in vi ta m in A in pa st 2 4 ho ur s1 P er ce nt ag e w ho c on su m ed fo od s ric h in iro n in p as t 24 h ou rs 2 W ei gh te d nu m be r of c hi ld re n U nw ei gh te d nu m be r o f ch ild re n P er ce nt ag e gi ve n vi ta m in A su pp le m en ts in pa st 6 m on th s P er ce nt ag e gi ve n iro n su pp le m en ts in pa st 7 d ay s P er ce nt ag e gi ve n de w or m in g m ed ic at io n in pa st 6 m on th s3 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 P er ce nt ag e liv in g in ho us eh ol ds w ith io di ze d sa lt4 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 A ge in m on th s 6- 8 16 .4 10 .3 60 8 59 1 40 .5 1. 8 3. 5 61 0 59 7 14 .4 60 0 57 0 9- 11 18 .8 11 .3 50 5 44 2 54 .7 3. 7 5. 6 51 0 44 6 15 .4 50 1 43 0 12 -1 7 30 .1 14 .2 1, 00 0 1, 04 6 51 .5 3. 3 14 .5 1, 03 0 1, 08 5 18 .1 99 6 1, 03 0 18 -2 3 31 .2 15 .7 83 5 77 1 58 .4 6. 8 17 .5 90 0 84 2 17 .9 86 5 79 2 24 -3 5 na na na na 56 .0 6. 8 24 .7 2, 06 3 2, 09 9 15 .5 1, 98 5 1, 98 4 36 -4 7 na na na na 53 .4 6. 6 23 .9 2, 38 1 2, 31 1 14 .7 2, 32 6 2, 22 7 48 -5 9 na na na na 51 .6 7. 2 26 .8 2, 28 2 2, 21 7 15 .2 2, 20 1 2, 08 5 Se x M al e 26 .3 13 .7 1, 49 7 1, 43 2 52 .2 5. 6 21 .5 5, 00 2 4, 89 4 15 .4 4, 84 6 4, 65 0 Fe m al e 25 .0 12 .9 1, 45 2 1, 41 8 53 .9 6. 5 20 .3 4, 77 5 4, 70 3 15 .9 4, 62 9 4, 46 8 B re as tfe ed in g st at us B re as tfe ed in g 25 .1 13 .2 2, 73 3 2, 54 5 55 .8 5. 2 16 .4 3, 98 7 3, 59 1 15 .1 3, 87 0 3, 40 8 N ot b re as tfe ed in g 33 .5 14 .6 21 6 30 3 51 .4 6. 6 24 .2 5, 75 1 5, 96 5 16 .1 5, 56 6 5, 67 0 M ot he r's a ge a t b irt h 15 -1 9 25 .9 14 .5 18 5 19 0 49 .7 4. 1 12 .6 33 1 34 9 19 .5 32 4 33 3 20 -2 9 28 .1 15 .6 1, 63 2 1, 54 2 51 .1 5. 4 19 .6 5, 05 5 4, 88 8 15 .1 4, 93 0 4, 66 2 30 -3 9 23 .6 10 .7 93 4 94 4 56 .2 6. 9 23 .0 3, 49 1 3, 51 0 16 .4 3, 38 1 3, 33 4 40 -4 9 15 .8 6. 1 19 9 17 4 53 .2 6. 9 23 .8 90 0 85 0 14 .3 84 0 78 9 R es id en ce U rb an 37 .9 22 .3 40 4 51 1 56 .8 3. 3 25 .0 1, 27 8 1, 67 9 23 .7 1, 24 8 1, 61 6 R ur al 23 .8 11 .9 2, 54 5 2, 33 9 52 .5 6. 4 20 .3 8, 49 9 7, 91 8 14 .4 8, 22 7 7, 50 2 R eg io n Ti gr ay 24 .6 20 .4 19 8 31 3 82 .8 11 .4 25 .7 64 0 1, 02 1 21 .9 62 4 99 5 A ffa r 11 .4 5. 5 23 22 9 35 .3 13 .3 18 .5 98 90 9 18 .9 96 88 6 A m ha ra 16 .1 10 .4 66 6 32 6 63 .8 8. 1 25 .9 2, 22 0 1, 08 3 9. 8 2, 15 2 1, 05 0 O ro m i y a 26 .8 17 .4 1, 23 7 44 3 48 .7 4. 8 19 .8 4, 08 2 1, 43 4 18 .3 3, 99 2 1, 40 3 S om al i 11 .7 6. 3 75 21 8 26 .3 1. 7 6. 0 29 4 82 9 21 .2 25 9 73 3 B en is ha n g ul -G um uz 31 .9 18 .3 34 25 0 59 .9 19 .7 26 .6 11 3 82 0 39 .0 11 0 79 6 S N N P 34 .5 6. 0 62 0 40 3 43 .9 3. 9 18 .2 2, 04 9 1, 32 6 11 .4 1, 97 1 1, 27 5 G am be la 47 .8 32 .8 9 19 8 55 .6 11 .2 23 .9 33 68 0 23 .0 27 52 5 H ar ar i 29 .6 13 .9 8 17 9 62 .6 7. 7 21 .3 24 56 2 4. 3 24 55 7 A dd is A ba ba 33 .3 16 .1 67 11 8 62 .3 5. 0 21 .1 19 1 34 6 29 .5 18 9 34 2 D ire D aw a 38 .1 23 .8 10 17 3 67 .6 19 .1 19 .3 33 58 7 5. 6 31 55 6 M ot he r's e du ca tio n N o ed uc at io n 20 .4 10 .5 1, 99 3 1, 91 1 50 .6 5. 4 19 .6 6, 79 4 6, 71 9 14 .8 6, 57 2 6, 38 7 P rim ar y 33 .6 17 .4 82 9 76 9 57 .4 7. 7 22 .8 2, 63 0 2, 38 9 15 .7 2, 56 4 2, 26 0 S ec on da r y 55 .6 30 .7 79 11 5 63 .7 4. 7 31 .0 19 8 31 8 31 .0 19 7 30 8 M or e th an s ec on da r y 57 .5 30 .4 48 55 71 .9 7. 1 34 .5 15 5 17 1 30 .1 14 3 16 3 W ea lth q ui nt ile Lo w es t 18 .5 9. 2 68 9 83 7 45 .2 5. 2 15 .4 2, 19 2 2, 91 9 13 .4 2, 09 3 2, 66 2 S ec on d 20 .4 9. 9 66 1 52 6 53 .2 8. 1 19 .7 2, 16 5 1, 73 4 12 .2 2, 12 3 1, 68 0 M id dl e 26 .4 12 .0 59 4 45 7 51 .4 5. 5 19 .9 1, 98 9 1, 51 8 15 .4 1, 92 5 1, 46 3 Fo ur th 28 .1 15 .5 52 4 45 0 59 .6 6. 5 26 .9 1, 93 5 1, 58 0 17 .7 1, 90 4 1, 54 2 H i g he st 39 .7 23 .1 48 1 58 0 58 .1 4. 3 24 .6 1, 49 5 1, 84 6 21 .6 1, 43 0 1, 77 1 To ta l 25 .7 13 .3 2, 94 9 2, 85 0 53 .1 6. 0 21 .0 9, 77 7 9, 59 7 15 .6 9, 47 5 9, 11 8 N ot e: In fo rm at io n on v ita m in A is b as ed o n bo th m ot he r's re ca ll an d th e im m un iz at io n ca rd . I nf or m at io n on ir on s up pl em en ts a nd d ew or m in g m ed ic at io n is b as ed o n th e m ot he r's re ca ll. T ot al in cl ud es 3 9 ca se s w ith m is si ng in fo rm at io n on br ea st fe ed in g st at us . na = N ot a pp lic ab le 1 I nc lu de s m ea t, or ga n m ea t, fis h, p ou ltr y, e gg s, p um pk in , s qu as h, c ar ro ts , s w ee t p ot at oe s th at a re y el lo w o r o ra ng e in si de , d ar k gr ee n le af y ve ge ta bl es , r ip e m an go es , r ip e pa pa ya s, a nd o th er fr ui ts a nd v eg et ab le s th at a re ri ch in v ita m in A 2 I nc lu de s m ea t, or ga n m ea t, fis h, a nd e gg s 3 D ew or m in g fo r i nt es tin al p ar as ite s is c om m on ly d on e fo r h el m in th s an d fo r s ch is to so m ia si s. 4 E xc lu de s ch ild re n in h ou se ho ld s in w hi ch s al t w as n ot te st ed 178 • Nutrition of Children and Adults Nutrition of Children and Adults • 179 Iodine deficiency has serious effects on body growth and mental development. The principal cause of iodine deficiency is inadequate iodine in foods. The fortification of salt with iodine is the most common method of preventing iodine deficiency. According to WHO, a country’s salt iodisation programme is considered to be on a good track (poised to attain the goal of eliminating iodine deficiency) when 90 percent of the households are using iodised salt. To assess the use of iodised salt in Ethiopia, interviewers in the 2011 EDHS asked households to provide a teaspoon of salt used for cooking. The salt was tested for iodine using the iodine rapid test kit. As Table 11.8 shows, only 16 percent of children live in households that use iodised salt. The percentage is higher in urban areas than in rural areas (24 percent compared with 14 percent). At the regional level Benishangul-Gumuz has the highest proportion of households using iodised salt (39 percent) and Harari has the lowest percentage (4 percent). In general, use of iodised salt is correlated with the mother’s education level; about 30 percent of children of mothers who are educated at the secondary or higher level live in households using iodised salt, compared with 15 percent of children whose mothers have no education. A similar pattern is observed according to household wealth quintile. 11.5 IODISATION OF HOUSEHOLD SALT Table 11.9 shows the percentage of households with salt tested for iodine content, the percentage of households without salt, and, among households with tested salt, the percentage with iodine present in the salt. Ninety-four percent of households had salt tested for iodine at the time of the interview. Of these households, 15 percent were using iodised salt. Table 11.9 Presence of iodised salt in household Among all households, the percentage with salt tested for iodine content and the percentage with no salt in the household; and among households with salt tested, the percentage with iodised salt, according to background characteristics, Ethiopia 2011 Background characteristic Among all households, the percentage: Among households with tested salt: With salt tested With no salt in the household Weighted number of households Unweighted number of households Percentage with iodised salt Weighted number of households Unweighted number of households Residence Urban 89.9 9.0 3,780 5,112 23.2 3,398 4,535 Rural 94.9 4.5 12,922 11,590 13.3 12,266 10,695 Region Tigray 95.0 4.5 1,134 1,730 22.3 1,078 1,647 Affar 93.9 5.7 143 1,267 17.8 134 1,199 Amhara 94.0 5.3 4,452 2,071 9.6 4,186 1,956 Oromiya 94.9 4.3 6,221 2,165 17.4 5,905 2,053 Somali 79.1 17.2 343 975 19.2 271 792 Benishangul-Gumuz 93.4 6.0 181 1,323 39.7 169 1,241 SNNP 93.1 6.5 3,256 2,045 12.2 3,031 1,909 Gambela 76.7 22.6 66 1,215 22.9 51 895 Harari 91.0 5.4 53 1,201 5.6 48 1,093 Addis Ababa 93.3 5.9 781 1,524 29.6 729 1,418 Dire Dawa 85.9 12.1 73 1,186 5.7 63 1,027 Wealth quintile Lowest 93.4 6.3 3,213 3,972 11.3 3,002 3,519 Second 96.2 3.4 3,222 2,534 11.7 3,100 2,397 Middle 95.3 4.1 3,091 2,364 14.7 2,945 2,226 Fourth 95.1 4.1 3,070 2,419 15.6 2,921 2,258 Highest 90.0 8.6 4,106 5,413 22.3 3,697 4,830 Total 93.8 5.5 16,702 16,702 15.4 15,664 15,230 180 • Nutrition of Children and Adults Urban households are more likely to use iodised salt (23 percent) than rural households (13 percent). At the regional level Benishangul-Gumuz and Addis Ababa have the highest proportions of households using iodised salt (40 percent and 30 percent, respectively), whereas the Dire Dawa and Harari regions have the lowest (6 percent). Households in the highest wealth quintile are twice as likely to use iodised salt as households in the lowest two wealth quintiles. 11.6 NUTRITIONAL STATUS OF WOMEN AND MEN The nutritional status of women and men was assessed by use of two anthropometric indices—height and body mass index (BMI). To derive those indices, the 2011 EDHS measured the height and weight of women age 15-49 years and men age 15-59 years. Results are presented for women in Table 11.10.1 and for men in Table 11.10.2. Short stature reflects previous poor socioeconomic conditions and inadequate nutrition during childhood and adolescence. In a woman short stature is a risk factor for poor birth outcomes and obstetric complications. For example, short stature is associated with small pelvic size, which increases the likelihood of difficulty during delivery and the risk of bearing low birth weight babies. A woman is considered to be at risk if her height is below 145 cm. BMI is used to measure thinness or obesity. BMI is defined as weight in kilograms divided by height in metres squared (kg/m2). A BMI below 18.5 indicates thinness or acute undernutrition. A BMI below 17 kg/m2 indicates severe undernutrition and is associated with increased mortality. Low pre-pregnancy BMI, like short stature, is associated with poor birth outcomes and obstetric complications. A BMI of 25.0 or above indicates overweight or obesity Table 11.10.1 shows the percentage of women with height under 145 cm, the mean BMI, and the proportion of women falling into high-risk categories, by background characteristics. Respondents for whom there was no information on height or weight and for whom a BMI could not be estimated are excluded from this analysis. The data analysis on BMI is based on 14,505 women age 15-49 years, while the height analysis is based on 16,062 women. As shown in Table 11.10.1, 3 percent of Ethiopian women are below 145 cm in height. In general, height differs little with background characteristics. Adolescent women, age 15-19 years, are most likely to be below 145 cm. Women of short stature are most likely to reside in the Amhara region, and to have no education or primary education. The mean BMI for Ethiopian women age 15-49 is 20 kg/m2. There are no major differences in mean BMI by women’s age, urban or rural residence, region, or education level. The mean BMI increases slightly with wealth, from 20 kg/m2 for women in the lowest wealth quintile to 22 kg/m2 in the highest quintile. Sixty-seven percent of Ethiopian women have a normal BMI (between 18.5 and 24.9 kg/m2), while 27 percent of women are thin or undernourished (BMI less than 18.5 kg/m2) and 6 percent are overweight or obese (BMI 25 kg/m2 or above). Adolescents (age 15-19) are more likely to be thin (36 percent) than older women. Rural women also are more likely to be thin than urban women, and those residing in the Affar region are the most likely to be thin of any region. By education, women who have attended up to primary school have the greatest likelihood of being thin. Those in the lowest wealth quintile also are more likely to be thin than women in other wealth quintiles. Nutrition of Children and Adults • 181 Overweight or obesity (BMI 25 kg/m2 or above) is not common among women in Ethiopia. Five percent are overweight (BMI 25-29 kg/m2), and just 1 percent are obese (BMI 30 kg/m2 or above). Younger women are less likely than older women to be overweight or obese. For example, 2 percent of women age 15-19 are overweight or obese compared with 9 percent of women age 40-49. Urban women are more likely to be overweight or obese (15 percent) than rural women (3 percent). One woman of every five residing in Addis Ababa and the Dire Dawa region are overweight or obese (20 percent and 19 percent, respectively), compared with 3 percent of women in Benishangul-Gumuz and Tigray. Being overweight or obese is positively correlated with educational attainment; the proportion of overweight or obese women increases steadily from 4 percent among those with no education to 17 percent among those with more than secondary schooling. Similarly, the proportion of overweight or obese women increases as wealth increases, from 2 percent in the lowest wealth quintile to 16 percent in the highest quintile. 18 2 • N ut rit io n of C hi ld re n an d A du lts Ta bl e 11 .1 0. 1 N ut rit io na l s ta tu s of w om en A m on g w om en a ge 1 5- 49 , t he p er ce nt ag e w ith h ei gh t u nd er 1 45 c m , m ea n Bo dy M as s In de x (B M I), a nd th e pe rc en ta ge w ith s pe ci fic B M I l ev el s, 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 H ei gh t B od y M as s In de x1 M ea n B od y M as s In de x (B M I) N or m al Th in O ve rw ei gh t/O be se W ei gh te d nu m be r o f w om en U nw ei gh te d nu m be r o f w om en P er ce nt ag e be lo w 1 45 c m W ei gh te d nu m be r o f w om en U nw ei gh te d nu m be r o f w om en 18 .5 -2 4. 9 (to ta l no rm al ) <1 8. 5 (to ta l th in ) 17 .0 -1 8. 4 (m ild ly th in ) <1 7 (m od er at el y an d se ve re ly th in ) ≥2 5. 0 (to ta l ov er w ei gh t o r ob es e) 25 .0 -2 9. 9 (o ve rw ei gh t) ≥3 0. 0 (o be se ) A ge 15 -1 9 5. 6 3, 89 5 3, 70 1 19 .5 61 .5 36 .1 20 .7 15 .5 2. 4 2. 2 0. 2 3, 72 4 3, 53 4 20 -2 9 2. 2 5, 92 0 6, 00 3 20 .4 73 .5 21 .3 15 .9 5. 4 5. 2 4. 6 0. 6 5, 09 9 5, 16 3 30 -3 9 3. 6 3, 84 6 3, 91 1 20 .6 68 .1 24 .1 17 .1 6. 9 7. 8 6. 2 1. 6 3, 35 9 3, 41 3 40 -4 9 2. 6 2, 40 1 2, 35 3 20 .4 62 .7 28 .5 18 .4 10 .2 8. 7 6. 7 2. 0 2, 32 3 2, 27 1 R es id en ce U rb an 2. 9 3, 74 7 5, 02 2 21 .4 65 .0 20 .1 12 .9 7. 2 14 .9 12 .1 2. 8 3, 56 9 4, 75 2 R ur al 3. 6 12 ,3 15 10 ,9 46 19 .9 68 .2 29 .1 19 .4 9. 7 2. 6 2. 3 0. 4 10 ,9 36 9, 62 9 R eg io n Ti gr ay 3. 2 1, 09 6 1, 71 6 19 .3 56 .8 40 .0 23 .7 16 .3 3. 2 2. 9 0. 3 1, 00 1 1, 56 5 A ffa r 3. 1 14 3 1, 27 7 19 .4 52 .2 43 .5 21 .7 21 .8 4. 3 3. 0 1. 3 12 5 1, 10 2 A m ha ra 4. 9 4, 30 3 2, 03 2 19 .9 66 .6 29 .8 18 .0 11 .8 3. 6 3. 1 0. 5 3, 98 5 1, 87 1 O ro m iy a 2. 7 5, 91 5 2, 09 9 20 .2 68 .4 26 .9 19 .4 7. 5 4. 7 3. 8 0. 9 5, 25 8 1, 87 2 S om al i 0. 7 30 3 84 9 20 .9 51 .4 32 .7 18 .9 13 .8 15 .9 10 .2 5. 7 25 5 71 7 B en is ha ng ul -G um uz 3. 0 17 0 1, 23 1 20 .0 69 .3 27 .8 19 .6 8. 2 2. 9 2. 3 0. 6 14 8 1, 06 3 S N N P 3. 6 3, 10 9 1, 95 5 20 .5 73 .6 20 .3 14 .3 6. 0 6. 1 5. 5 0. 5 2, 76 0 1, 73 1 G am be la 1. 8 68 1, 10 1 20 .3 62 .1 31 .0 17 .1 13 .9 6. 9 5. 6 1. 3 63 1, 00 1 H ar ar i 1. 4 46 1, 03 2 21 .4 63 .5 22 .1 15 .9 6. 2 14 .4 11 .0 3. 4 42 94 9 A dd is A ba ba 2. 7 84 5 1, 64 5 22 .2 65 .7 14 .4 9. 5 4. 9 19 .9 15 .8 4. 0 81 0 1, 58 3 D ire D aw a 1. 2 65 1, 03 1 21 .5 56 .6 24 .9 16 .9 8. 0 18 .5 13 .4 5. 1 59 92 7 Ed uc at io n N o ed uc at io n 3. 4 8, 19 3 8, 04 0 20 .1 69 .7 26 .5 18 .0 8. 5 3. 8 3. 0 0. 7 7, 19 4 7, 01 3 P rim ar y 4. 0 6, 10 7 5, 67 6 20 .1 64 .5 30 .1 19 .3 10 .8 5. 4 4. 7 0. 7 5, 62 1 5, 20 6 S ec on da ry 1. 6 1, 06 9 1, 32 5 21 .2 66 .3 20 .3 12 .8 7. 5 13 .3 10 .7 2. 7 1, 02 4 1, 27 2 M or e th an s ec on da ry 1. 1 69 3 92 7 21 .8 69 .2 14 .2 10 .5 3. 8 16 .6 13 .3 3. 2 66 5 89 0 W ea lth q ui nt ile Lo w es t 4. 1 2, 92 2 3, 63 5 19 .6 65 .8 32 .4 20 .9 11 .5 1. 8 1. 4 0. 4 2, 53 1 3, 10 6 S ec on d 4. 0 2, 98 5 2, 36 2 19 .7 66 .8 31 .0 19 .3 11 .7 2. 3 1. 9 0. 4 2, 65 8 2, 09 7 M id dl e 3. 5 2, 97 5 2, 21 6 19 .8 71 .2 26 .8 17 .6 9. 3 1. 9 1. 8 0. 2 2, 64 9 1, 96 9 Fo ur th 3. 5 3, 14 8 2, 44 9 20 .0 68 .7 28 .8 20 .4 8. 4 2. 5 2. 3 0. 2 2, 85 3 2, 19 8 H ig he st 2. 4 4, 03 1 5, 30 6 21 .5 65 .5 19 .0 12 .9 6. 1 15 .5 12 .6 3. 0 3, 81 5 5, 01 1 To ta l 3. 4 16 ,0 62 15 ,9 68 20 .2 67 .4 26 .9 17 .8 9. 1 5. 7 4. 7 1. 0 14 ,5 05 14 ,3 81 N ot e: T he B od y M as s In de x (B M I) is e xp re ss ed a s th e ra tio o f w ei gh t i n ki lo gr am s to th e sq ua re o f h ei gh t i n m et re s (k g/ m 2 ) . 1 E xc lu de s pr eg na nt w om en a nd w om en w ith a b irt h in th e pr ec ed in g 2 m on th s. 182 • Nutrition of Children and Adults Nutrition of Children and Adults • 183 Table 11.10.2 presents the nutritional status of men. The mean BMI for Ethiopian men age 15-49 is 19 kg/m2. There is little difference in the mean BMI by background characteristics. Sixty percent of Ethiopian men age 15-49 have a normal BMI (between 18.5-24.9 kg/m2), whereas 37 percent are thin or undernourished (BMI less than 18.5 kg/m2), and 2 percent are overweight or obese (BMI 25 kg/m2 or above). Young men, age 15-19, are more likely to be thin (66 percent) than their older counterparts. Rural men are slightly more likely to be thin (39 percent) than urban men (32 percent). Among regions, those residing in the Somali region are most likely to be thin (62 percent), and those living in Addis Ababa are least likely (22 percent). Men who attended only primary school are more likely than those with higher educational levels and those with no education to have a BMI of less than 18.5 kg/m2. Forty-four percent of men in the lowest wealth quintile are thin, compared with 29 percent in the highest wealth quintile. Table 11.10.2 Nutritional status of men Among men age 15-49, mean Body Mass Index (BMI), and the percentage with specific BMI levels, by background characteristics, Ethiopia 2011 Background characteristic Body Mass Index Mean Body Mass Index (BMI) Normal Thin Overweight/Obese Weighted number of men Unweighted number of men 18.5-24.9 (total normal) <18.5 (total thin) 17.0-18.4 (mildly thin) <17 (moderately and severely thin) ≥25.0 (total overweight or obese) 25.0-29.9 (overweight) ≥30.0 (obese) Age 15-19 17.8 33.8 65.9 29.1 36.7 0.4 0.3 0.1 2,864 2,681 20-29 19.5 68.1 30.7 23.8 6.9 1.3 1.2 0.1 4,440 4,376 30-39 20.0 70.5 25.3 19.3 6.0 4.2 3.8 0.3 3,033 3,106 40-49 19.9 66.5 29.0 20.1 8.9 4.5 3.7 0.8 1,979 2,070 Residence Urban 20.1 60.8 31.5 20.7 10.9 7.6 6.9 0.7 2,687 3,603 Rural 19.1 60.3 38.9 24.1 14.8 0.8 0.7 0.1 9,630 8,630 Region Tigray 18.8 49.9 47.8 27.0 20.8 2.3 2.1 0.2 757 1,216 Affar 18.5 40.8 56.8 28.4 28.4 2.4 2.4 0.0 99 885 Amhara 18.9 56.2 42.7 25.7 17.0 1.2 1.0 0.2 3,368 1,687 Oromiya 19.3 62.5 35.9 23.8 12.2 1.6 1.3 0.3 4,790 1,822 Somali 18.2 36.1 62.0 28.3 33.7 1.9 1.9 0.0 217 589 Benishangul-Gumuz 19.3 60.4 37.6 25.0 12.5 2.0 1.7 0.3 131 997 SNNP 19.7 68.1 29.5 19.1 10.4 2.4 2.4 0.1 2,171 1,460 Gambela 19.7 64.9 33.2 23.6 9.5 2.0 1.8 0.1 56 823 Harari 19.9 58.8 34.8 22.1 12.6 6.4 5.5 1.0 36 816 Addis Ababa 21.1 65.6 22.0 15.0 7.0 12.4 10.8 1.6 643 1,164 Dire Dawa 20.3 53.4 36.5 25.5 11.0 10.1 8.4 1.8 49 774 Education No education 19.3 64.1 34.6 23.9 10.7 1.3 1.2 0.1 3,668 3,526 Primary 19.0 57.2 41.6 24.3 17.3 1.2 1.0 0.1 6,547 6,032 Secondary 19.8 61.7 32.9 22.4 10.5 5.4 5.1 0.3 1,225 1,454 More than secondary 20.8 67.2 22.1 15.2 6.8 10.7 8.8 1.9 875 1,221 Wealth quintile Lowest 18.7 55.0 44.4 24.5 19.8 0.6 0.6 0.0 2,058 2,473 Second 18.9 57.7 42.1 26.1 16.0 0.2 0.1 0.1 2,293 1,829 Middle 19.1 64.4 35.1 21.5 13.6 0.5 0.4 0.1 2,399 1,872 Fourth 19.2 59.3 39.4 27.0 12.4 1.3 1.1 0.2 2,576 2,105 Highest 20.2 64.1 28.6 18.7 9.9 7.3 6.5 0.8 2,991 3,954 Total 15-49 19.3 60.4 37.3 23.3 13.9 2.3 2.0 0.3 12,316 12,233 50-59 19.9 65.0 30.5 22.3 8.2 4.5 3.9 0.6 1,230 1,184 Total 15-59 19.4 60.9 36.6 23.2 13.4 2.5 2.2 0.3 13,546 13,417 Note: The Body Mass Index (BMI) is expressed as the ratio of weight in kilograms to the square of height in metres (kg/m2). 184 • Nutrition of Children and Adults Two percent of Ethiopian men 15-49 are overweight, while less than 1 percent are obese. The proportion of overweight or obese men increases with age. Nearly 8 percent of urban men are overweight or obese, compared with less than 1 percent of rural men. Addis Ababa and Dire Dawa have relatively high proportions of overweight or obese men (12 percent and 10 percent, respectively), while the Amhara region has the lowest proportion (1 percent). The proportion of overweight or obese men increases with education and wealth. For example, 1 percent of men with no education are overweight or obese, compared with 11 percent with more than secondary school education. Similarly, 1 percent of men in the lowest wealth quintile are overweight or obese, compared with 7 percent of men in the highest quintile. 11.7 PREVALENCE OF ANAEMIA IN WOMEN Anaemia in pregnant women results in an increased risk of premature delivery and low birth weight. Table 11.11.1 presents anaemia prevalence among women age 15-49 based on haemoglobin levels, according to selected background characteristics. The raw measured values of haemoglobin were obtained using the HemoCue instrument and adjusted for altitude and smoking status. Seventeen percent of Ethiopian women age 15-49 are anaemic, with 13 percent having mild anaemia, 3 percent having moderate anaemia, and 1 percent having severe anaemia. A higher proportion of pregnant women are anaemic (22 percent) than women who are breastfeeding (19 percent) and women who are neither pregnant nor breastfeeding (15 percent). Anaemia prevalence also varies by urban and rural residence; a higher proportion of women in rural areas are anaemic (18 percent) than those in urban areas (11 percent). Also, women in the Somali, Affar, and Dire Dawa regions have a relatively high prevalence of anaemia (44 percent, 35 percent, and 29 percent, respectively). Women in Addis Ababa and the SNNP and Tigray regions are at the other end of the range, with relatively low prevalence of anaemia (9 percent, 11 percent, and 12 percent, respectively). Women with no education are twice as likely to be anaemic as women with more than secondary education (20 percent and 10 percent, respectively). Similarly, anaemia prevalence decreases as wealth status increases. The HSDP IV target is to reduce anaemia prevalence nationally to 12 percent. In comparison with the data from the 2005 EDHS, the prevalence of any anaemia has declined from 27 percent to 17 percent in 2011, a decrease of 37 percent. The prevalence of mild and moderate anaemia also has declined between the two surveys, from 17 percent to 13 percent, and from 8 percent to 3 percent, respectively. Nutrition of Children and Adults • 185 Table 11.11.1 Prevalence of anaemia in women Percentage of women age 15-49 with anaemia, by background characteristics, Ethiopia 2011 Background characteristic Not pregnant: Anaemia status by haemoglobin level Weighted number of women Unweighted Number of Women Any Mild Moderate Severe <12.0 g/dl 10.0-11.9 g/dl 7.0-9.9 g/dl <7.0 g/dl Pregnant <11.0 g/dl 10.0-10.9 g/dl 7.0-9.9 g/dl <7.0 g/dl Age 15-19 13.4 10.9 2.2 0.3 3,841 3,617 20-29 16.3 12.3 3.2 0.8 5,811 5,838 30-39 17.3 13.3 3.4 0.6 3,782 3,817 40-49 21.5 18.3 2.7 0.5 2,348 2,296 Number of children ever born 0 12.5 10.1 2.1 0.3 5,267 5,194 1 15.7 12.2 2.8 0.7 1,712 1,892 2-3 18.0 14.3 2.7 1.0 3,052 3,060 4-5 18.0 12.9 4.5 0.7 2,353 2,296 6+ 21.1 17.1 3.5 0.5 3,397 3,126 Maternity status Pregnant 22.0 12.2 8.7 1.2 1,173 1,226 Breastfeeding 18.5 14.8 3.0 0.6 4,933 4,487 Neither 15.0 12.3 2.2 0.5 9,675 9,855 Using IUD Yes (21.8) (14.9) (6.9) (0.0) 34 42 No 16.6 13.1 2.9 0.6 15,748 15,526 Smoking status Smokes cigarettes/ tobacco 15.7 13.9 1.7 0.2 117 437 Does not smoke 16.6 13.1 3.0 0.6 15,665 15,131 Residence Urban 10.9 8.8 1.9 0.2 3,621 4,780 Rural 18.3 14.4 3.3 0.7 12,161 10,788 Region Tigray 12.4 9.7 2.3 0.4 1,077 1,688 Affar 34.8 24.0 9.3 1.5 141 1,260 Amhara 16.6 13.8 2.4 0.4 4,219 1,989 Oromiya 19.2 15.2 3.3 0.7 5,834 2,068 Somali 44.0 24.8 14.7 4.5 292 813 Benishangul- Gumuz 19.1 14.3 4.2 0.6 167 1,213 SNNP 11.3 8.8 2.1 0.4 3,090 1,943 Gambela 19.4 15.7 3.5 0.2 67 1,092 Harari 19.4 14.4 4.2 0.8 43 980 Addis Ababa 9.3 7.8 1.2 0.3 788 1,525 Dire Dawa 28.8 17.4 9.9 1.5 63 997 Education No education 20.3 15.9 3.5 0.9 8,081 7,889 Primary 13.6 10.5 2.8 0.3 6,017 5,551 Secondary 9.3 8.4 0.7 0.3 1,032 1,269 More than secondary 9.7 8.4 1.2 0.2 651 859 Wealth quintile Lowest 20.1 15.0 4.0 1.1 2,894 3,596 Second 18.9 15.3 3.1 0.5 2,940 2,327 Middle 17.1 13.6 2.6 0.8 2,936 2,184 Fourth 17.4 13.4 3.6 0.4 3,123 2,402 Highest 11.3 9.3 1.7 0.2 3,890 5,059 Total 16.6 13.1 2.9 0.6 15,782 15,568 Note: Prevalence is adjusted for altitude and for smoking status if known using formulas in CDC, 1998. Figures in parentheses are based on 25-49 unweighted cases. 186 • Nutrition of Children and Adults 11. 8 PREVALENCE OF ANAEMIA IN MEN Table 11.11.2 shows the prevalence of anaemia among men. Nationally, 11 percent of men 15-49 are anaemic. Younger men, age 15-19 (18 percent) and older men, age 40-49 (14 percent) are the more likely than men age 20-39 to be anaemic. It must be noted that oldest men age 50-59 have the highest prevalence of anaemia (19 percent). Rural men are more likely to be anaemic than urban men (13 and 5 percent, respectively). Men residing in Addis Ababa have the lowest anaemia prevalence (3 percent) of any region, while men in Affar, Somali, and Dire Dawa (all 15 percent) have the highest. There are inverse relationships between the prevalence of anaemia in men and both educational level and wealth quintile. Table 11.11.2 Prevalence of anaemia in men Percentage of men age 15-49 with anaemia, by background characteristics, Ethiopia 2011 Background characteristic Any anaemia (<13.0 g/dl) Weighted number of men Unweighted number of men Age 15-19 17.8 2,818 2,637 20-29 7.4 4,352 4,254 30-39 8.9 2,985 3,028 40-49 14.4 1,927 2,015 Smoking status Smokes cigarettes/tobacco 11.3 876 1,678 Does not smoke 11.3 11,206 10,256 Residence Urban 4.8 2,555 3,413 Rural 13.1 9,527 8,521 Region Tigray 12.1 737 1,186 Affar 15.0 97 872 Amhara 13.6 3,266 1,641 Oromiya 11.8 4,742 1,803 Somali 14.9 208 568 Benishangul-Gumuz 14.1 130 993 SNNP 8.1 2,161 1,454 Gambela 10.5 56 819 Harari 8.5 34 768 Addis Ababa 2.8 603 1,085 Dire Dawa 15.1 47 745 Education No education 13.9 3,593 3,456 Primary 12.2 6,476 5,934 Secondary 4.8 1,198 1,403 More than secondary 2.3 815 1,141 Wealth quintile Lowest 16.2 2,036 2,441 Second 15.5 2,274 1,807 Middle 12.8 2,371 1,857 Fourth 9.6 2,551 2,070 Highest 4.8 2,850 3,759 Total 15-49 11.3 12,082 11,934 50-59 19.3 1,209 1,152 Total 15-59 12.0 13,291 13,086 Note: Prevalence is adjusted for altitude and smoking status, if known, using formulas from CDC, 1998. 11.9 MICRONUTRIENT INTAKE AMONG MOTHERS Adequate micronutrient intake by women has important benefits for both women and their children. A mother's nutritional status during pregnancy is important both for foetal development and for protection against maternal morbidity and mortality. Breastfeeding children benefit from micronutrient supplementation that mothers receive, especially vitamin A. Iodine deficiency is related to a number of adverse pregnancy outcomes, including abortion, foetal brain damage, congenital Nutrition of Children and Adults • 187 malformation, stillbirth, and prenatal death. Table 11.12 includes a number of measures that are useful in assessing the extent to which women are obtaining adequate intakes of vitamin A and iron. Sixteen percent of mothers who gave birth in the five years preceding the survey received postpartum vitamin A supplements. By age, the proportion of mothers that received vitamin A supplements was highest among the 30-39 age group. Vitamin A supplements are more common in urban areas than rural areas (20 percent and 15 percent, respectively). Three women of every ten residing in the Tigray region (30 percent), Addis Ababa (29 percent) and Gambela regions (28 percent) received vitamin A supplements. By comparison, less than one woman of every ten living in the Affar, Somali, SNNP, and Harari regions received vitamin A supplementation (all 9 percent). Educated women were more likely to have received vitamin A supplements during their last pregnancy—28 percent of women with more than secondary education compared with 14 percent of women with no education. Similarly, as a woman’s wealth status increases, so does her likelihood of receiving vitamin A supplements. Those in the fourth and highest wealth quintiles are twice as likely to have received a vitamin A dose postpartum as those in the lowest wealth quintile (20 percent and 10 percent, respectively). Eighty-three percent of women did not take iron tablets during their last pregnancy. Fifteen percent took them for less than 60 days, and less than 1 percent took them for 90 days or more during their last pregnancy. There are very small differences in daily iron supplements between urban and rural women and among regions. In general, the percentage of women who took iron tablets increases as educational status and wealth index increase. The proportion of women who took iron during each length of time increases with educational level and wealth quintile. Six percent of mothers received deworming medication during their last pregnancy. Urban women were more likely than rural women to have taken deworming medication (9 percent compared with 5 percent). Among regions the proportion of women who received deworming medication generally ranges between 3 and 6 percent. It is notable that 12 percent of women residing in Gambela and 9 percent in Benishangul-Gumuz received deworming medication during their last pregnancy. There is little variation in the percentage who received deworming medication by age, educational level, or wealth quintile. Iodine deficiency has adverse effects on all population groups, but women of reproductive age are often the worst affected. Table 11.12 shows the percentage of women with a child born in the five years preceding the survey who live in households using iodised salt. Nationally, 15 percent of women live in households with iodised salt. This percentage is higher in urban area (23 percent) than rural areas (14 percent). The proportion of women living in a household with iodised salt is nearly three times higher in Benishangul-Gumuz than the national average (41 percent versus 15 percent). Women who have more than secondary education are more likely to live in a household with iodised salt (30 percent) than those who are not educated (14 percent). Likewise, the proportion of women living in households using iodised salt is higher in the highest wealth quintile (22 percent) than in the second and lowest wealth quintiles (12 percent each). 18 8 • N ut rit io n of C hi ld re n an d A du lts Ta bl e 11 .1 2 M ic ro nu tri en t i nt ak e am on g m ot he rs A m on g w om en a ge 1 5- 49 w ith a c hi ld b or n in th e pa st fi ve y ea rs , t he p er ce nt ag e w ho re ce iv ed a v ita m in A d os e in th e fir st tw o m on th s af te r t he b irt h of th e la st c hi ld , t he p er ce nt d is tri bu tio n by nu m be r of d ay s th ey to ok ir on ta bl et s du rin g th e pr eg na nc y of th e la st c hi ld , a nd th e pe rc en ta ge w ho to ok d ew or m in g m ed ic at io n du rin g th e pr eg na nc y of th e la st c hi ld ; a nd a m on g w om en ag e 15 -4 9 w ith a c hi ld b or n in t he p as t fiv e ye ar s an d w ho li ve in h ou se ho ld s th at w er e te st ed f or io di ze d sa lt, t he p er ce nt ag e w ho li ve in h ou se ho ld s w ith io di ze d sa lt, b y ba ck gr ou nd 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 A m on g w om en w ith a c hi ld b or n in th e pa st fi ve y ea rs : A m on g w om en w ith a c hi ld b or n in th e pa st fi ve y ea rs w ho li ve in h ou se ho ld s th at w er e te st ed fo r i od iz ed s al t: P er ce nt ag e w ho re ce iv ed vi ta m in A do se po st pa rtu m 1 N um be r o f d ay s w om en to ok ir on ta bl et s du rin g pr eg na nc y of la st b irt h P er ce nt ag e of w om en w ho to ok de w or m in g m ed ic at io n du rin g pr eg na nc y of la st b irt h W ei gh te d nu m be r o f w om en U nw ei gh te d nu m be r o f w om en N on e <6 0 60 -8 9 90 + D on 't kn ow / m is si ng To ta l P er ce nt ag e liv in g in ho us eh ol ds w ith io di ze d sa lt2 W ei gh te d nu m be r o f w om en U nw ei gh te d nu m be r o f w om en A ge 15 -1 9 9. 4 91 .7 6. 7 0. 9 0. 0 0. 6 10 0. 0 4. 7 40 2 41 6 17 .9 39 1 39 2 20 -2 9 16 .1 82 .0 15 .5 0. 8 0. 5 1. 2 10 0. 0 5. 3 3, 99 1 3, 88 8 14 .9 3, 89 1 3, 71 3 30 -3 9 16 .9 81 .7 16 .3 0. 5 0. 3 1. 2 10 0. 0 5. 9 2, 72 8 2, 71 0 15 .4 2, 63 5 2, 57 0 40 -4 9 13 .8 84 .6 13 .0 0. 9 0. 5 1. 1 10 0. 0 5. 8 78 7 75 0 14 .2 74 3 69 8 R es id en ce U rb an 20 .4 72 .4 24 .3 1. 1 1. 0 1. 2 10 0. 0 8. 5 1, 18 8 1, 51 3 22 .9 1, 15 7 1, 45 8 R ur al 15 .0 84 .5 13 .4 0. 6 0. 3 1. 1 10 0. 0 5. 0 6, 72 0 6, 25 1 13 .8 6, 50 2 5, 91 5 R eg io n Ti gr ay 30 .2 65 .7 27 .1 3. 3 1. 3 2. 6 10 0. 0 3. 9 53 0 84 7 21 .8 51 5 82 2 A ffa r 8. 9 76 .3 22 .1 0. 7 0. 0 1. 0 10 0. 0 3. 4 78 71 4 19 .3 76 69 4 A m ha ra 10 .9 80 .6 17 .1 0. 3 0. 4 1. 7 10 0. 0 5. 6 1, 99 1 96 5 9. 5 1, 92 5 93 3 O ro m iy a 19 .5 87 .9 10 .8 0. 4 0. 3 0. 6 10 0. 0 5. 1 3, 11 6 1, 10 0 17 .5 3, 04 9 1, 07 7 S om al i 8. 9 79 .7 19 .0 0. 7 0. 2 0. 4 10 0. 0 2. 9 19 8 55 9 20 .9 17 4 49 3 B en is ha ng ul -G um uz 23 .2 76 .3 20 .4 0. 5 1. 7 1. 1 10 0. 0 8. 9 92 67 4 41 .0 90 65 5 S N N P 8. 9 84 .7 13 .7 0. 5 0. 3 0. 8 10 0. 0 6. 9 1, 63 4 1, 05 3 11 .6 1, 57 0 1, 01 2 G am be la 27 .8 72 .4 25 .9 0. 8 0. 6 0. 4 10 0. 0 12 .4 31 60 8 21 .9 26 47 6 H ar ar i 9. 1 66 .7 28 .5 2. 0 1. 7 1. 1 10 0. 0 4. 1 19 44 0 4. 4 19 43 5 A dd is A ba ba 28 .7 60 .8 29 .2 3. 9 2. 4 3. 8 10 0. 0 4. 3 19 3 34 8 27 .4 19 0 34 4 D ire D aw a 25 .3 70 .8 24 .0 2. 2 0. 3 2. 7 10 0. 0 3. 3 26 45 6 6. 6 25 43 2 Ed uc at io n N o ed uc at io n 13 .7 84 .8 13 .2 0. 5 0. 4 1. 1 10 0. 0 4. 2 5, 27 0 5, 18 4 14 .2 5, 09 4 4, 92 2 P rim ar y 19 .1 80 .7 16 .7 0. 9 0. 4 1. 3 10 0. 0 8. 1 2, 27 0 2, 09 5 15 .4 2, 20 7 1, 98 1 S ec on da ry 24 .1 68 .9 28 .1 1. 4 1. 3 0. 3 10 0. 0 6. 0 22 6 31 2 25 .9 22 4 30 4 M or e th an s ec on da ry 27 .7 57 .2 38 .4 2. 3 1. 3 0. 7 10 0. 0 10 .8 14 2 17 3 30 .0 13 5 16 6 W ea lth q ui nt ile Lo w es t 10 .1 86 .1 11 .6 0. 4 0. 3 1. 6 10 0. 0 3. 4 1, 73 9 2, 27 9 12 .1 1, 66 4 2, 07 4 S ec on d 14 .4 87 .2 11 .2 0. 3 0. 4 0. 9 10 0. 0 5. 1 1, 69 6 1, 35 4 11 .5 1, 66 3 1, 31 4 M id dl e 15 .9 84 .5 13 .2 0. 6 0. 4 1. 3 10 0. 0 3. 3 1, 62 8 1, 24 1 14 .1 1, 57 1 1, 19 7 Fo ur th 20 .1 82 .0 16 .2 0. 9 0. 1 0. 8 10 0. 0 7. 5 1, 49 3 1, 22 9 17 .8 1, 46 2 1, 19 2 H ig he st 19 .8 71 .0 25 .3 1. 5 1. 1 1. 1 10 0. 0 9. 2 1, 35 1 1, 66 1 22 .0 1, 29 9 1, 59 6 To ta l 15 .8 82 .7 15 .1 0. 7 0. 4 1. 1 10 0. 0 5. 5 7, 90 8 7, 76 4 15 .1 7, 65 9 7, 37 3 1 In th e fir st tw o m on th s af te r d el iv er y of la st li ve b irt h. 2 E xc lu de s w om en in h ou se ho ld s w he re s al t w as n ot te st ed . 188 • Nutrition of Children and Adults HIV/AIDS-Related Knowledge, Attitudes, and Behaviour • 189 HIV/AIDS-RELATED KNOWLEDGE, ATTITUDES, AND BEHAVIOUR 12 cquired immune deficiency syndrome (AIDS) is caused by the human immunodeficiency virus (HIV). HIV weakens the immune system, making the body susceptible to secondary and opportunistic infections. Without treatment, HIV infection leads to AIDS and death. The predominant mode of HIV transmission is through sexual contact. Other modes of transmission are mother-to-child transmission (in which the mother passes HIV to her child during pregnancy, delivery, or breastfeeding), use of contaminated blood supplies for transfusions, and injections using contaminated needles or syringes. AIDS is one of the most serious public health and development challenges in sub-Saharan Africa. According to the 2011 EDHS, 1.5 percent of adults age 15-49 are infected with HIV (see Chapter 13). Heterosexual contact accounts for the great majority of HIV transmission in the country. AIDS is now affecting all sectors of Ethiopian society. The future course of the AIDS epidemic in Ethiopia depends on a number of factors including HIV/AIDS-related knowledge, social stigmatisation, risk behaviour modification, access to high-quality services for sexually transmitted infections (STIs), provision and uptake of HIV counselling and testing, and access to antiretroviral therapy (ART). The principal objective of this chapter is to establish the prevalence of relevant knowledge, attitudes, and behaviours at the national level and within the geographic and socioeconomic subgroups of the population, using data from the 2011 EDHS. This chapter presents findings from the general adult population and specifically from youth. The chapter concludes with information on patterns of sexual activity among young people, as they are the main target of many HIV prevention efforts. The findings in this chapter will help HIV/AIDS control and prevention programmes to target the groups of people most in need of information and services and most vulnerable to the risk of HIV infection. Also, findings presented in this chapter can be compared with the findings from the 2000 and 2005 EDHS. A Key Findings • General knowledge of AIDS is almost universal; 97 percent of women and 99 percent of men have heard of AIDS. • Comprehensive knowledge of AIDS is uncommon. However, 19 percent of women and 32 percent of men have comprehensive knowledge of HIV/AIDS transmission and prevention methods. • Men are more likely than women to express accepting attitudes toward people with HIV. Still, only 28 percent of men and 17 percent of women always expressed accepting attitudes when reacting to four hypothetical situations involving people with HIV. • Less than 1 percent of women had two or more sexual partners in the 12 months preceding the survey. Almost half of these women reported using a condom during last sexual intercourse. • Four percent of men had two or more partners in the last 12 months. Sixteen percent of these men reported using a condom during last sex. • About one-quarter of young women and young men who are sexually active were tested for HIV in the 12 months before the survey—a dramatic increase over the levels in 2005. 190 • HIV/AIDS-Related Knowledge, Attitudes, and Behaviour 12.1 HIV/AIDS KNOWLEDGE, TRANSMISSION, AND PREVENTION METHODS 12.1.1 Awareness of HIV/AIDS Interviewers asked 2011 EDHS respondents whether they had heard of AIDS. Those who reported having heard of AIDS were then asked a number of questions such as whether and how HIV/AIDS can be avoided. Table 12.1 shows that knowledge of AIDS is almost universal; 97 percent of women and 99 percent of men age 15-49 have heard of AIDS. The level of awareness of AIDS is notably lower in Somali (82 percent of women and 93 percent of men) than in other regions. Table 12.1 Knowledge of AIDS Percentage of women and men age 15-49 who have heard of AIDS, by background characteristics, Ethiopia 2011 Background characteristic Women Men Has heard of AIDS Weighted number of women Unweighted number of women Has heard of AIDS Weighted number of men Unweighted number of men Age 15-24 96.4 6,940 6,857 98.0 5,332 5,162 15-19 96.2 4,009 3,835 97.3 3,013 2,832 20-24 96.7 2,931 3,022 98.9 2,319 2,330 25-29 96.2 3,147 3,185 99.2 2,297 2,274 30-39 97.0 3,971 4,058 99.3 3,132 3,261 40-49 96.1 2,457 2,415 99.4 2,074 2,171 Marital status Never married 97.4 4,469 4,413 98.2 5,600 5,641 Ever had sex 98.3 344 489 99.9 1,044 1,492 Never had sex 97.3 4,126 3,924 97.8 4,555 4,149 Married/living together 96.1 10,287 10,204 99.2 6,872 6,775 Divorced/separated/ widowed 96.4 1,758 1,898 99.9 363 452 Residence Urban 99.2 3,947 5,329 99.8 2,882 3,915 Rural 95.6 12,568 11,186 98.5 9,952 8,953 Region Tigray 99.7 1,104 1,728 99.8 770 1,235 Affar 96.5 145 1,291 98.7 101 910 Amhara 96.4 4,433 2,087 98.2 3,481 1,739 Oromiya 95.1 6,011 2,135 98.6 4,957 1,889 Somali 81.6 329 914 93.0 245 653 Benishangul-Gumuz 92.6 174 1,259 97.4 138 1,047 SNNP 98.8 3,236 2,034 99.8 2,307 1,550 Gambela 97.7 69 1,130 99.4 59 865 Harari 99.6 49 1,101 99.8 40 898 Addis Ababa 99.9 896 1,741 100.0 682 1,237 Dire Dawa 99.3 69 1,095 99.7 53 845 Education No education 94.5 8,394 8,278 97.2 3,785 3,659 Primary 98.1 6,276 5,858 99.3 6,813 6,334 Secondary 99.8 1,117 1,395 100.0 1,296 1,565 More than secondary 100.0 728 984 100.0 940 1,310 Wealth quintile Lowest 93.5 2,986 3,711 96.9 2,141 2,563 Second 95.9 3,041 2,402 98.2 2,362 1,891 Middle 95.0 3,031 2,268 98.7 2,454 1,935 Fourth 97.4 3,215 2,505 99.4 2,683 2,203 Highest 99.4 4,242 5,629 99.9 3,194 4,276 Total 15-49 96.5 16,515 16,515 98.8 12,834 12,868 50-59 na na na 98.8 1,276 1,242 Total 15-59 na na na 98.8 14,110 14,110 na = Not applicable In Ethiopia HIV/AIDS prevention programmes focus their messages and efforts on three important aspects of behaviour: using condoms, limiting the number of sexual partners (or staying faithful with one uninfected, mutually faithful partner), and delaying sexual debut (abstinence) among the young and the never-married. To ascertain whether programmes have effectively communicated at least two of these messages, respondents were prompted with specific questions about whether it is possible to reduce the chance of getting the virus that causes AIDS by having just one faithful sexual partner and by using a condom at every sexual encounter. HIV/AIDS-Related Knowledge, Attitudes, and Behaviour • 191 Table 12.2 shows that about seven respondents of every ten (65 percent of women and 74 percent of men) know that the chance of becoming infected with HIV is reduced by limiting sexual intercourse to one uninfected partner who has no other partners. In contrast, there is a noticeable difference between women and men in the percentages who know that using condoms consistently reduces the chance of acquiring HIV infection (56 percent for women and 82 percent for men). More than six men of every ten (64 percent) know of both ways to reduce HIV risk, compared with about four women of every ten (43 percent). Table 12.2 Knowledge of HIV prevention methods Percentage of women and men age 15-49 who, in response to prompted questions, say that people can reduce the risk of getting the AIDS virus by using condoms every time they have sexual intercourse, and by having one sex partner who is not infected and has no other partners, by background characteristics, Ethiopia 2011 Background characteristic Women Men Percentage who say HIV can be prevented by: Weighted number of women Un- weighted number of women Percentage who say HIV can be prevented by: Weighted number of men Un- weighted number of men Using condoms1 Limiting sexual intercourse to one uninfected partner2 Using condoms and limiting sexual intercourse to one uninfected partner1,2 Using condoms1 Limiting sexual intercourse to one uninfected partner2 Using condoms and limiting sexual intercourse to one uninfected partner1,2 Age 15-24 61.6 67.8 48.5 6,940 6,857 80.7 73.9 64.7 5,332 5,162 15-19 61.6 68.4 48.7 4,009 3,835 77.8 72.4 62.0 3,013 2,832 20-24 61.5 66.9 48.3 2,931 3,022 84.6 76.0 68.2 2,319 2,330 25-29 55.8 64.2 42.9 3,147 3,185 83.3 77.4 67.7 2,297 2,274 30-39 52.3 63.2 39.6 3,971 4,058 82.2 72.7 63.1 3,132 3,261 40-49 46.0 58.5 34.4 2,457 2,415 80.2 71.7 61.0 2,074 2,171 Marital status Never married 67.2 71.1 53.6 4,469 4,413 82.1 75.0 66.3 5,600 5,641 Ever had sex 81.5 73.9 64.5 344 489 92.8 82.5 77.9 1,044 1,492 Never had sex 66.1 70.9 52.7 4,126 3,924 79.6 73.3 63.6 4,555 4,149 Married/living together 51.0 62.0 38.8 10,287 10,204 81.0 72.9 62.6 6,872 6,775 Divorced/sep arated/ widowed 56.0 63.5 42.9 1,758 1,898 81.1 74.9 64.0 363 452 Residence Urban 76.6 73.0 60.6 3,947 5,329 90.0 75.4 69.5 2,882 3,915 Rural 49.4 62.0 37.8 12,568 11,186 79.0 73.5 62.7 9,952 8,953 Region Tigray 73.9 81.6 63.9 1,104 1,728 89.9 84.7 78.5 770 1,235 Affar 36.1 32.3 23.3 145 1,291 73.6 62.9 51.1 101 910 Amhara 54.3 58.9 39.4 4,433 2,087 79.0 66.4 56.1 3,481 1,739 Oromiya 52.1 64.6 41.2 6,011 2,135 82.0 79.5 69.4 4,957 1,889 Somali 20.8 36.3 15.5 329 914 51.2 59.9 36.6 245 653 Benishangul- Gumuz 53.5 53.2 38.2 174 1,259 77.9 71.9 60.3 138 1,047 SNNP 56.1 71.8 45.4 3,236 2,034 81.2 72.9 63.5 2,307 1,550 Gambela 55.1 46.3 34.3 69 1,130 85.8 72.4 67.0 59 865 Harari 58.5 53.1 38.2 49 1,101 75.0 49.3 40.2 40 898 Addis Ababa 82.4 65.4 57.0 896 1,741 94.1 70.7 68.4 682 1,237 Dire Dawa 64.6 69.5 50.1 69 1,095 86.9 82.4 72.0 53 845 Education No education 42.2 56.0 30.8 8,394 8,278 71.7 66.0 52.4 3,785 3,659 Primary 65.5 72.1 52.4 6,276 5,858 83.4 75.5 66.6 6,813 6,334 Secondary 82.4 78.1 65.2 1,117 1,395 90.8 82.3 76.3 1,296 1,565 More than secondary 90.9 78.9 73.4 728 984 94.4 82.3 78.7 940 1,310 Wealth quintile Lowest 42.3 57.1 30.9 2,986 3,711 74.4 67.5 57.2 2,141 2,563 Second 47.0 60.8 35.0 3,041 2,402 76.6 73.0 59.9 2,362 1,891 Middle 50.4 60.7 38.1 3,031 2,268 78.8 73.9 62.5 2,454 1,935 Fourth 55.1 66.8 44.0 3,215 2,505 83.7 75.1 66.5 2,683 2,203 Highest 76.5 73.7 60.9 4,242 5,629 90.0 77.8 71.6 3,194 4,276 Total 15-49 55.9 64.6 43.2 16,515 16,515 81.5 73.9 64.2 12,834 12,868 50-59 na na na na na 76.1 71.3 58.1 1,276 1,242 Total 15-59 na na na na na 81.0 73.7 63.7 14,110 14,110 na = Not applicable 1 Using condoms every time they have sexual intercourse 2 Partner who has no other partners 192 • HIV/AIDS-Related Knowledge, Attitudes, and Behaviour There are notable differences in knowledge of HIV/AIDS prevention by background characteristics. Among women, knowledge of HIV/AIDS prevention decreases with age. For example, nearly half (49 percent) of female youth, age 15-24, know that both using condoms and limiting sexual intercourse to one uninfected partner can reduce the risk of acquiring HIV, compared with about one-third (34 percent) of women age 40-49. Never-married women who have ever had sex are the most likely to know about HIV prevention methods when compared with never-married women who have never had sex or with women currently in union or previously married. Knowledge of both methods of prevention is higher among urban women than rural women (61 percent versus 38 percent). Variation by region is particularly striking. For example, more than six women of every ten residing in Tigray (64 percent) are aware of both methods of HIV/AIDS prevention compared with less than two in every ten (16 percent) in Somali. Awareness of prevention methods increases with education and wealth. Among men differentials in knowledge of HIV prevention according to background characteristics are similar to those among women but not as pronounced. For example, knowledge of HIV prevention among men decreases slightly with age, from 65 percent of men age 15-24 who are aware of both prevention methods to 61 percent of men age 40-49. Never-married men, particularly those who have ever had sex, urban men, those with secondary education or more, and men in the highest wealth quintile are the most likely to know methods of HIV prevention. Among regions knowledge of both HIV prevention methods among men ranges from 79 percent in Tigray to 37 percent in Somali. 12.1.2 Rejection of Misconceptions About HIV/AIDS As part of the effort to assess HIV and AIDS knowledge, the 2011 EDHS obtained information on common misconceptions about HIV transmission. Respondents were asked whether they think it is possible for a healthy-looking person to have HIV and whether they believe HIV is transmitted through mosquito bites, supernatural means, or sharing food with a person who has HIV. Respondents were also asked whether a person can get AIDS by sharing sharp materials, such as razors or blades, or through injection with unsterilised needles, and whether a person can reduce the chance of getting HIV by abstaining from sexual intercourse. Tables 12.3.1 and 12.3.2 present results for women and men. The majority of Ethiopian adults (63 percent of women and 78 percent of men) know that a healthy-looking person can have HIV. The most common misconception about HIV transmission is that it can be transmitted by mosquitoes. Only about half of women (52 percent) and six men of every ten (63 percent) know that HIV cannot be transmitted by mosquitoes. The second most common misconception is that HIV can be transmitted by supernatural means. About three-fourths of women and men age 15-49 (72 and 76 percent, respectively) correctly believe that HIV cannot be transmitted through supernatural means. Seventy-six percent of women and 85 percent of men know that a person cannot become infected with HIV by sharing food with a person who has HIV. About three-quarters of women and more than four men of every five report that people can reduce their chance of getting HIV by abstaining from sexual intercourse (73 and 86 percent, respectively). More than nine of every ten women and men know that people can get HIV by sharing sharp materials, such as razors or other blades, if they should cut the skin or by injection with unsterilised needles (92 and 97 percent, respectively). HIV/AIDS-Related Knowledge, Attitudes, and Behaviour • 193 Table 12.3.1 Comprehensive knowledge about AIDS: Women Percentage of women age 15-49 who say that a healthy-looking person can have the AIDS virus and who, in response to prompted questions, correctly reject local misconceptions about transmission or prevention of the AIDS virus, and the percentage with a comprehensive knowledge about AIDS, by background characteristics, Ethiopia 2011 Background characteristic Percentage of women who say that: Percentage who say that a healthy- looking person can have the AIDS virus and who reject the two most common local miscon- ceptions2 Percentage with a compre- hensive knowledge about AIDS3 Weighted number of women Unweighted number of women A healthy- looking person can have the AIDS virus The AIDS virus cannot be transmitted by mosquito bites The AIDS virus cannot be transmitted by supernatural means1 A person cannot become infected by sharing food with a person who has the AIDS virus People reduce the chance of getting the AIDS virus by abstaining from sexual intercourse People can get the AIDS virus by sharing sharp materials or by injection with unsterilised needles Age 15-24 67.0 58.5 76.8 80.3 74.5 92.4 36.9 23.9 6,940 6,857 15-19 66.5 60.0 77.6 81.6 75.1 92.7 37.3 24.0 4,009 3,835 20-24 67.6 56.3 75.7 78.5 73.8 92.0 36.3 23.6 2,931 3,022 25-29 63.0 49.1 68.8 74.1 71.1 91.7 27.8 16.9 3,147 3,185 30-39 61.6 47.7 68.9 74.1 70.8 92.5 26.2 14.9 3,971 4,058 40-49 57.0 44.8 66.6 65.9 72.7 88.9 22.7 11.5 2,457 2,415 Marital status Never married 71.0 65.4 80.9 85.4 78.0 94.9 43.7 28.8 4,469 4,413 Ever had sex 78.0 71.2 89.2 93.4 77.4 95.6 55.4 40.3 344 489 Never had sex 70.5 64.9 80.2 84.7 78.1 94.8 42.7 27.9 4,126 3,924 Married/living together 59.7 47.2 68.1 71.1 70.5 90.6 25.4 14.5 10,287 10,204 Divorced/separated/ widowed 65.8 46.6 70.5 75.6 72.4 90.9 26.4 16.2 1,758 1,898 Residence Urban 80.2 68.0 83.6 92.3 81.4 97.0 51.7 35.1 3,947 5,329 Rural 58.2 47.1 68.2 70.2 70.0 90.1 23.8 13.3 12,568 11,186 Region Tigray 76.4 37.7 76.1 74.6 86.9 97.5 27.9 22.1 1,104 1,728 Affar 42.5 38.3 39.4 63.8 41.4 80.0 11.0 4.0 145 1,291 Amhara 64.9 47.6 74.3 77.3 73.3 91.9 31.4 17.2 4,433 2,087 Oromiya 64.3 49.3 65.7 69.2 68.4 89.8 26.6 16.7 6,011 2,135 Somali 28.1 34.5 30.0 48.7 39.1 64.1 7.7 3.5 329 914 Benishangul-Gumuz 54.7 54.5 68.0 75.6 65.2 85.5 31.2 18.4 174 1,259 SNNP 54.9 66.0 80.1 82.6 77.3 94.9 34.4 21.1 3,236 2,034 Gambela 61.7 57.8 68.9 81.3 56.1 90.8 29.4 14.5 69 1,130 Harari 70.7 69.1 74.5 88.4 74.0 93.5 42.0 23.2 49 1,101 Addis Ababa 83.6 65.9 88.5 93.6 85.2 98.6 51.9 31.8 896 1,741 Dire Dawa 50.4 64.9 61.0 83.1 71.3 96.1 26.7 18.7 69 1,095 Education No education 53.8 38.8 62.0 63.1 66.6 87.4 17.0 7.7 8,394 8,278 Primary 69.0 61.2 79.1 85.8 76.8 95.6 37.3 24.2 6,276 5,858 Secondary 85.8 78.6 91.4 96.9 86.3 98.2 63.3 43.1 1,117 1,395 More than secondary 92.3 85.1 93.5 96.0 87.7 98.7 76.4 57.4 728 984 Wealth quintile Lowest 50.8 39.8 63.7 63.5 67.4 85.5 16.8 8.3 2,986 3,711 Second 55.9 44.1 68.6 68.2 70.4 91.0 20.8 10.1 3,041 2,402 Middle 59.4 48.3 66.3 69.4 68.2 89.5 24.3 14.2 3,031 2,268 Fourth 64.1 52.6 72.2 77.4 72.7 93.0 29.8 17.2 3,215 2,505 Highest 80.1 68.6 83.5 92.0 81.3 97.5 51.9 36.0 4,242 5,629 Total 15-49 63.4 52.1 71.8 75.5 72.7 91.8 30.5 18.5 16,515 16,515 1 Witchcraft, God’s curse, or other supernatural means 2 Two most common local misconceptions: (1) AIDS can be transmitted by mosquito bites and (2) AIDS can be transmitted by supernatural means. 3 Comprehensive knowledge means knowing that consistent use of condoms during sexual intercourse and having just one uninfected faithful partner can reduce the chance of getting the AIDS virus, knowing that a healthy-looking person can have the AIDS virus, and rejecting the two most common local misconceptions about HIV transmission. 194 • HIV/AIDS-Related Knowledge, Attitudes, and Behaviour Table 12.3.2 Comprehensive knowledge about AIDS: Men Percentage of men age 15-49 who say that a healthy-looking person can have the AIDS virus and who, in response to prompted questions, correctly reject local misconceptions about transmission or prevention of the AIDS virus, and the percentage with a comprehensive knowledge about AIDS, by background characteristics, Ethiopia 2011 Background characteristic Percentage of men who say that: Percentage who say that a healthy- looking person can have the AIDS virus and who reject the two most common local miscon- ceptions2 Percentage with a compre- hensive knowledge about AIDS3 Weighted number of men Un- weighted number of men A healthy- looking person can have the AIDS virus The AIDS virus cannot be transmitted by mosquito bites The AIDS virus cannot be transmitted by super- natural means1 A person cannot become infected by sharing food with a person who has the AIDS virus People reduce the chance of getting the AIDS virus by abstaining from sexual intercourse People can get the AIDS virus by sharing sharp materials or by injection with unsterilised needles Age 15-24 77.0 66.1 76.3 85.4 83.9 95.5 45.8 34.2 5,332 5,162 15-19 74.9 65.4 75.7 84.3 81.4 94.5 44.0 31.8 3,013 2,832 20-24 79.8 67.1 77.1 86.9 87.3 96.9 48.3 37.4 2,319 2,330 25-29 81.0 65.5 75.1 87.2 87.8 97.3 44.8 34.8 2,297 2,274 30-39 79.4 60.4 72.8 83.3 87.7 97.1 40.8 28.6 3,132 3,261 40-49 76.2 57.1 77.9 80.8 87.8 97.0 39.2 27.6 2,074 2,171 Marital status Never married 78.2 68.3 77.4 86.2 85.3 95.9 48.1 36.6 5,600 5,641 Ever had sex 85.5 75.2 81.9 94.3 91.5 98.0 56.3 46.3 1,044 1,492 Never had sex 76.6 66.7 76.3 84.3 83.9 95.4 46.2 34.4 4,555 4,149 Married/living together 78.4 59.6 73.7 83.1 86.7 96.9 40.1 28.6 6,872 6,775 Divorced/ separated/ widowed 74.3 52.0 79.7 84.4 88.2 98.0 32.1 21.2 363 452 Residence Urban 87.6 77.9 84.9 93.9 92.0 98.5 61.3 45.0 2,882 3,915 Rural 75.5 58.9 72.8 81.8 84.4 95.9 38.1 28.1 9,952 8,953 Region Tigray 85.9 55.5 90.8 86.5 92.1 99.5 47.4 41.0 770 1,235 Affar 78.9 55.0 52.5 78.4 83.6 95.6 32.2 19.8 101 910 Amhara 75.1 57.6 85.5 87.5 86.6 96.0 44.1 29.5 3,481 1,739 Oromiya 77.5 62.9 61.2 79.1 84.6 95.8 35.1 28.2 4,957 1,889 Somali 48.9 32.3 26.9 58.7 66.1 83.2 9.4 6.4 245 653 Benishangul- Gumuz 70.9 67.9 81.6 86.6 80.2 93.6 48.6 31.5 138 1,047 SNNP 81.8 75.0 87.2 89.3 86.7 98.7 57.1 39.9 2,307 1,550 Gambela 69.2 77.0 86.0 91.3 86.3 97.5 49.0 34.9 59 865 Harari 78.5 74.9 72.7 93.5 80.9 96.8 46.1 21.6 40 898 Addis Ababa 90.3 70.7 90.6 97.9 94.7 98.0 59.6 43.7 682 1,237 Dire Dawa 88.7 73.3 72.9 91.2 95.4 98.1 56.3 44.5 53 845 Education No education 68.1 45.0 66.5 73.6 81.7 93.3 25.2 16.5 3,785 3,659 Primary 79.5 66.1 76.5 87.1 86.1 97.4 44.7 33.0 6,813 6,334 Secondary 90.3 83.2 86.0 94.3 93.8 98.7 65.6 50.6 1,296 1,565 More than secondary 93.0 87.2 90.3 95.9 94.0 99.2 75.5 59.9 940 1,310 Wealth quintile Lowest 65.7 47.8 66.8 73.6 82.6 92.9 27.4 20.5 2,141 2,563 Second 73.5 54.9 73.2 80.3 83.7 95.7 34.6 24.7 2,362 1,891 Middle 78.0 61.2 73.6 82.7 85.1 96.0 40.6 29.3 2,454 1,935 Fourth 81.1 67.7 74.1 86.8 86.0 97.8 44.9 32.9 2,683 2,203 Highest 87.7 77.4 85.6 94.3 91.2 98.6 61.3 46.1 3,194 4,276 Total 15-49 78.2 63.2 75.5 84.5 86.2 96.5 43.3 31.9 12,834 12,868 50-59 73.2 46.7 72.8 75.3 88.5 96.4 31.1 23.3 1,276 1,242 Total 15-59 77.7 61.7 75.3 83.6 86.4 96.5 42.2 31.1 14,110 14,110 1 Witchcraft, God’s curse, or other supernatural means 2 Two most common local misconceptions: (1) AIDS can be transmitted by mosquito bites and (2) AIDS can be transmitted by supernatural means. 3 Comprehensive knowledge means knowing that consistent use of condoms during sexual intercourse and having just one uninfected faithful partner can reduce the chance of getting the AIDS virus, knowing that a healthy-looking person can have the AIDS virus, and rejecting the two most common local misconceptions about HIV transmission. Comprehensive knowledge about AIDS is defined as (1) knowing that both condom use and limiting sex partners to one uninfected partner are HIV prevention methods, (2) being aware that a healthy-looking person can have HIV, and (3) rejecting the two most common local misconceptions in Ethiopia—that HIV/AIDS can be transmitted through mosquito bites and by supernatural means. The 2011 EDHS reveals that comprehensive knowledge of AIDS is low; only two women 15-49 of every ten (19 percent) and three men of every ten (32 percent) have comprehensive knowledge about AIDS. There has been only a slight increase since 2005, when 16 percent of women and 30 percent of men HIV/AIDS-Related Knowledge, Attitudes, and Behaviour • 195 had comprehensive knowledge about AIDS. Comprehensive knowledge varies by background characteristics. Respondents age 15-24, those that have never married but have ever had sex, urban respondents, those with secondary education or more, and respondents from the wealthiest households have the highest levels of comprehensive knowledge about AIDS. Among regions, women in Affar and Somali (both 4 percent) and men living in Somali (6 percent) are the least likely to have comprehensive knowledge about AIDS. 12.2 KNOWLEDGE OF PREVENTION OF MOTHER-TO-CHILD TRANSMISSION OF HIV Increasing knowledge of ways in which HIV can be transmitted from mother to child and of the fact that the risk of transmission can be reduced by using antiretroviral drugs is critical to reducing mother-to-child transmission (MTCT) of HIV. To obtain information on these issues, the 2011 EDHS asked respondents if the virus that causes AIDS can be transmitted from a mother to a child during breastfeeding and whether a mother with HIV can reduce the risk of transmission to the baby by taking certain drugs (antiretrovirals) during pregnancy. Table 12.4 shows that more than three-quarters of respondents—77 percent of women and 76 percent of men—know that HIV can be transmitted to a baby through breastfeeding. More than four in every ten women (44 percent) and more than half of men (53 percent) know that the risk of MTCT can be reduced through the use of ARTs during pregnancy. Overall, 42 percent of women and 47 percent of men know both that HIV can be transmitted through breastfeeding and that HIV positive women can reduce the risk of MTCT by taking special drugs during pregnancy. This knowledge has increased dramatically since the 2005 EDHS, from 20 percent to 42 percent for women and from 26 percent to 47 percent for men. There are notable differences in knowledge of prevention of MTCT by background characteristic. The oldest respondents, age 40-49, are the least likely to know both facts about MTCT (34 percent of women and 42 percent of men), compared with younger respondents. Knowledge of both facts about MTCT is the highest among never-married respondents who have ever had sex (75 percent of women and 62 percent of men), compared with other marital status sub-groups. Urban women are more than twice as likely as rural women (71 and 32 percent, respectively) to report knowledge about mother-to-child transmission. Among men 67 percent of urban residents, compared with 41 percent of rural residents, have correct knowledge about both aspects of MTCT. Women and men in the Somali region are the least knowledgeable about the two aspects of MTCT (17 percent of women and 26 percent of men), while those in Addis Ababa are the most knowledgeable (81 percent of women and 71 percent of men). Knowledge of MTCT is lowest among respondents with no education (28 percent of women and 31 percent of men) and highest among those with more than secondary education (84 percent of women and 74 percent of men). This knowledge increases from 24 percent of women and 31 percent of men in the lowest wealth quintile to 71 percent of women and 68 percent of men in the highest wealth quintile. 196 • HIV/AIDS-Related Knowledge, Attitudes, and Behaviour Table 12.4 Knowledge of prevention of mother-to-child transmission of HIV Percentage of women and men age 15-49 who know that HIV can be transmitted from mother to child by breastfeeding and that the risk of mother-to-child transmission (MTCT) of HIV can be reduced by the mother taking special drugs during pregnancy, by background characteristics, Ethiopia 2011 Background characteristic Women Men Percentage who know that: Weighted number of women Unweighted number of women Percentage who know that: Weighted number of men Unweighted number of men HIV can be transmitted by breast- feeding Risk of MTCT can be reduced by mother taking special drugs during pregnancy HIV can be transmitted by breast- feeding and risk of MTCT can be reduced by mother taking special drugs during pregnancy HIV can be transmitted by breast- feeding Risk of MTCT can be reduced by mother taking special drugs during pregnancy HIV can be transmitted by breast- feeding and risk of MTCT can be reduced by mother taking special drugs during pregnancy Age 15-24 78.5 49.6 46.0 6,940 6,857 77.2 53.2 47.6 5,332 5,162 15-19 78.7 49.3 45.8 4,009 3,835 76.3 50.1 45.0 3,013 2,832 20-24 78.3 49.9 46.3 2,931 3,022 78.5 57.3 50.9 2,319 2,330 25-29 77.4 43.3 40.8 3,147 3,185 76.2 55.9 48.6 2,297 2,274 30-39 76.1 41.2 38.6 3,971 4,058 74.7 53.6 46.6 3,132 3,261 40-49 73.4 36.2 34.2 2,457 2,415 73.8 48.0 42.3 2,074 2,171 Marital status Never married 81.6 56.1 52.2 4,469 4,413 77.8 56.3 50.2 5,600 5,641 Ever had sex 86.3 81.0 75.4 344 489 81.9 70.9 62.2 1,044 1,492 Never had sex 81.2 54.0 50.3 4,126 3,924 76.8 52.9 47.4 4,555 4,149 Married/living together 75.2 39.0 36.5 10,287 10,204 74.5 50.2 44.0 6,872 6,775 Divorced/separated/ widowed 75.4 46.1 43.7 1,758 1,898 72.2 54.5 43.7 363 452 Currently pregnant Pregnant 74.6 32.3 31.0 1,205 1,277 na na na na na Not pregnant/not sure 77.2 45.3 42.3 15,310 15,238 na na na na na Residence Urban 86.3 75.4 70.9 3,947 5,329 81.6 77.2 67.3 2,882 3,915 Rural 74.1 34.6 32.3 12,568 11,186 74.2 45.9 40.7 9,952 8,953 Region Tigray 86.9 62.1 58.6 1,104 1,728 83.2 68.6 60.2 770 1,235 Affar 64.1 45.5 43.1 145 1,291 69.4 51.1 47.6 101 910 Amhara 71.0 43.8 40.4 4,433 2,087 71.7 49.0 43.0 3,481 1,739 Oromiya 79.8 42.7 40.4 6,011 2,135 77.9 54.1 48.9 4,957 1,889 Somali 47.6 18.6 17.0 329 914 56.5 30.0 25.7 245 653 Benishangul-Gumuz 67.1 36.2 32.5 174 1,259 68.3 45.4 38.2 138 1,047 SNNP 77.1 32.6 30.1 3,236 2,034 77.2 43.3 37.4 2,307 1,550 Gambela 79.5 59.9 56.2 69 1,130 81.0 70.2 62.5 59 865 Harari 82.0 60.7 57.6 49 1,101 80.3 69.9 61.1 40 898 Addis Ababa 89.1 86.4 81.2 896 1,741 78.6 85.6 71.4 682 1,237 Dire Dawa 83.5 67.8 63.8 69 1,095 81.5 72.7 63.5 53 845 Education No education 69.6 29.4 27.6 8,394 8,278 68.3 34.4 31.2 3,785 3,659 Primary 82.5 52.4 48.7 6,276 5,858 77.6 54.2 47.8 6,813 6,334 Secondary 90.7 82.4 77.4 1,117 1,395 82.8 76.7 66.4 1,296 1,565 More than secondary 93.2 89.5 84.0 728 984 84.4 85.8 74.3 940 1,310 Wealth quintile Lowest 67.5 25.3 23.9 2,986 3,711 69.8 33.3 30.8 2,141 2,563 Second 73.8 31.0 28.2 3,041 2,402 74.1 43.0 38.2 2,362 1,891 Middle 72.1 33.1 31.1 3,031 2,268 73.7 44.4 38.8 2,454 1,935 Fourth 80.6 44.1 41.6 3,215 2,505 75.4 55.8 48.7 2,683 2,203 Highest 86.7 75.6 70.8 4,242 5,629 83.4 77.7 68.1 3,194 4,276 Total 15-49 77.0 44.4 41.5 16,515 16,515 75.9 52.9 46.7 12,834 12,868 50-59 na na na na 74.6 42.5 38.3 1,276 1,242 Total 15-59 na na na na 75.8 52.0 45.9 14,110 14,110 na = Not applicable 12.3 ATTITUDES TOWARDS PEOPLE LIVING WITH HIV/AIDS Widespread stigma and discrimination towards people infected with HIV or living with AIDS can adversely affect both people’s willingness to be tested for HIV and their adherence to antiretroviral therapy. Thus, reduction of stigma and discrimination is an important indicator of the success of programmes to prevent and control HIV/AIDS. HIV/AIDS-Related Knowledge, Attitudes, and Behaviour • 197 To assess survey respondents’ attitudes towards people living with HIV/AIDS, respondents who had heard of AIDS were asked if they would be willing to care for a relative sick with AIDS in their own households, if they would be willing to buy fresh vegetables from a market vendor who had the AIDS virus, if they thought a female teacher who has the AIDS virus but is not sick should be allowed to continue teaching, and if they would want to keep a family member’s HIV positive status secret. Tables 12.5.1 and 12.5.2 show the results for women and men, respectively. Most women and men age 15-49 (82 percent of women and 93 percent of men) would be willing to care at home for a relative with AIDS. Three women 15-49 of every ten (32 percent) and about five men 15-49 in every ten (47 percent) would buy fresh vegetables from a market vendor with the AIDS virus, and six women of every ten (59 percent) and seven men of every ten (70 percent) believe that an HIV positive female teacher who is not sick should be allowed to continue teaching. More than half of respondents (59 percent of women and 66 percent of men) would not want to keep secret the fact that a family member is infected with HIV. Overall, men are more likely than women to express accepting attitudes regarding all four situations (28 percent compared with 17 percent). Accepting attitudes are generally more common among respondents in urban areas than among those in rural areas and increase with education and wealth. Women and men residing in Addis Ababa, Dire Dawa, and Harari are the most likely to express accepting attitudes on all four indicators, while those living in SNNP region are the least likely. Table 12.5.1 Accepting attitudes toward those living with HIV/AIDS: Women Among women age 15-49 who have heard of AIDS, percentage expressing specific accepting attitudes toward people with HIV/AIDS, by background characteristics, Ethiopia 2011 Background characteristic Percentage of women who: Percentage expressing accepting attitudes on all four indicators Weighted number of women who have heard of AIDS Unweighted number of women who have heard of AIDS Are willing to care for a family member with AIDS in the respondent's home Would buy fresh vegetables from shopkeeper who has the AIDS virus Say that a female teacher who has the AIDS virus but is not sick should be allowed to continue teaching Would not want to keep secret that a family member got infected with the AIDS virus Age 15-24 83.1 38.4 65.5 58.6 21.1 6,691 6,620 15-19 83.2 38.2 66.3 57.8 20.5 3,857 3,694 20-24 82.9 38.7 64.4 59.7 21.9 2,834 2,926 25-29 80.4 30.1 55.7 62.1 16.2 3,028 3,075 30-39 82.2 27.6 53.6 59.2 13.8 3,853 3,890 40-49 80.1 23.2 50.1 58.7 12.5 2,362 2,313 Marital status Never married 86.4 45.6 72.0 56.9 25.3 4,353 4,305 Ever had sex 96.7 67.2 84.8 52.9 35.5 338 486 Never had sex 85.5 43.7 71.0 57.2 24.4 4,015 3,819 Married/living together 79.8 25.3 52.3 60.5 13.3 9,886 9,756 Divorced/separated/ widowed 82.6 35.8 59.8 59.7 18.2 1,696 1,837 Residence Urban 94.7 67.0 84.5 59.1 37.8 3,915 5,285 Rural 77.7 20.6 50.0 59.5 10.4 12,019 10,613 Region Tigray 87.6 40.4 62.7 67.6 25.2 1,100 1,723 Affar 89.7 45.1 47.7 58.8 24.4 140 1,250 Amhara 87.5 31.6 56.7 56.3 16.4 4,272 2,002 Oromiya 80.6 27.6 58.1 72.7 16.6 5,716 2,032 Somali 66.6 28.9 42.7 49.1 14.4 269 724 Benishangul-Gumuz 84.7 34.0 58.6 53.6 16.5 161 1,154 SNNP 71.2 21.7 51.5 39.4 7.6 3,197 2,007 Gambela 82.7 47.3 67.1 46.6 17.6 68 1,086 Harari 86.6 59.4 72.3 65.9 37.6 49 1,096 Addis Ababa 97.0 82.1 92.5 55.2 44.9 895 1,739 Dire Dawa 88.0 60.8 80.9 62.0 37.9 68 1,085 Education No education 75.6 16.8 44.1 59.6 7.9 7,933 7,755 Primary 85.1 38.0 66.7 59.0 20.2 6,158 5,765 Secondary 98.0 71.6 90.0 59.9 42.3 1,115 1,394 More than secondary 98.9 86.3 97.3 59.6 52.7 728 984 Wealth quintile Lowest 72.7 14.6 40.5 56.6 5.5 2,792 3,412 Second 76.7 16.3 46.3 59.3 8.6 2,916 2,297 Middle 77.1 19.5 50.2 61.9 9.8 2,879 2,164 Fourth 83.1 27.7 59.4 60.7 14.8 3,131 2,433 Highest 94.0 66.1 83.8 58.7 37.4 4,216 5,592 Total 15-49 81.9 32.0 58.5 59.4 17.1 15,934 15,898 198 • HIV/AIDS-Related Knowledge, Attitudes, and Behaviour Table 12.5.2 Accepting attitudes toward those living with HIV/AIDS: Men Among men age 15-49 who have heard of AIDS, percentage expressing specific accepting attitudes toward people with HIV/AIDS, by background characteristics, Ethiopia 2011 Background characteristic Percentage of men who: Percentage expressing accepting attitudes on all four indicators Weighted number of men who have heard of AIDS Unweighted number of men who have heard of AIDS Are willing to care for a family member with AIDS in the respondent's home Would buy fresh vegetables from shopkeeper who has the AIDS virus Say that a female teacher who has the AIDS virus but is not sick should be allowed to continue teaching Would not want to keep secret that a family member got infected with the AIDS virus Age 15-24 91.6 50.4 71.3 64.8 30.1 5,225 5,061 15-19 90.1 49.1 68.7 62.7 27.6 2,933 2,757 20-24 93.5 52.1 74.7 67.5 33.4 2,292 2,304 25-29 93.5 50.2 69.7 65.7 30.8 2,280 2,255 30-39 93.6 42.9 68.9 66.2 26.1 3,111 3,231 40-49 94.1 41.9 66.9 66.2 25.0 2,061 2,144 Marital status Never married 92.2 54.7 73.1 64.8 32.9 5,496 5,543 Ever had sex 96.8 67.1 83.3 68.2 41.5 1,044 1,489 Never had sex 91.1 51.8 70.7 64.0 30.8 4,453 4,054 Married/living together 93.1 40.7 66.9 65.9 24.6 6,817 6,699 Divorced/separated/ widowed 97.3 53.6 72.6 68.7 34.2 363 449 Residence Urban 97.9 79.5 90.6 66.8 51.1 2,876 3,908 Rural 91.3 37.6 63.6 65.2 21.8 9,800 8,783 Region Tigray 95.8 56.0 67.6 51.4 24.8 768 1,232 Affar 95.4 59.3 68.5 59.0 30.3 100 898 Amhara 95.3 44.4 68.0 60.0 25.1 3,418 1,706 Oromiya 92.3 46.7 71.6 78.5 33.6 4,890 1,863 Somali 89.3 44.4 51.9 65.5 21.9 228 602 Benishangul-Gumuz 86.6 46.4 68.4 56.4 22.3 135 1,013 SNNP 88.3 34.6 62.6 53.4 16.7 2,303 1,547 Gambela 93.4 66.5 78.3 73.3 41.9 59 855 Harari 86.3 75.2 86.6 62.4 46.6 40 896 Addis Ababa 98.8 90.0 94.6 59.0 50.8 682 1,237 Dire Dawa 95.0 76.1 87.1 70.1 51.1 53 842 Education No education 89.6 27.9 53.9 64.7 14.7 3,677 3,537 Primary 92.8 46.4 70.3 64.9 27.4 6,763 6,281 Secondary 97.6 77.6 91.6 68.3 51.5 1,296 1,564 More than secondary 98.9 85.3 97.2 69.6 58.4 939 1,309 Wealth quintile Lowest 88.7 29.4 53.8 61.5 15.9 2,076 2,469 Second 92.0 35.0 59.8 62.1 19.3 2,320 1,852 Middle 91.2 36.8 65.1 66.5 20.0 2,422 1,911 Fourth 92.8 44.3 71.7 68.0 27.4 2,668 2,187 Highest 97.4 77.7 89.1 67.9 50.5 3,190 4,272 Total 15-49 92.8 47.1 69.7 65.5 28.4 12,676 12,691 50-59 92.0 34.7 54.9 63.5 18.7 1,261 1,225 Total 15-59 92.8 46.0 68.4 65.4 27.6 13,937 13,916 12.4 ATTITUDES TOWARDS REFUSING TO HAVE SEX AND NEGOTIATING SAFER SEX Knowledge about HIV transmission and ways to prevent it are of little use if a woman feels powerless to negotiate safer sex practices with her partner. The EDHS 2011 assessed the ability of women to negotiate safer sex with a spouse who has sexual intercourse with other women or who has an STI. Interviewers asked women and men two attitudinal questions: Is a wife justified in refusing to have sex with her husband when she knows he has sexual intercourse with other women, and is a woman justified in asking her husband to use a condom if he has an STI? Eight women of every ten (83 percent) and nine men of every ten (90 percent) believe that a woman may refuse to have sex with her husband if she knows he has sex with other women (Table 12.6). Among both women and men, those who never married but had ever had sex, respondents living in urban areas, those with secondary or higher education, and respondents in the HIV/AIDS-Related Knowledge, Attitudes, and Behaviour • 199 highest wealth quintile are more likely to agree that both specified behaviours are justified than are other respondents. Among age groups, women in the oldest group, age 40-49, are the least likely to believe that a woman is justified in refusing to have sex with her husband when she knows he has sex with other women or to use a condom if she knows he has an STI. Among men there is not much difference in these attitudes by age. Among regions both women and men residing in Somali are in general markedly less likely than those in other regions to believe that a woman is justified in refusing sex if she knows that the husband has sex with other women (64 and 83 percent, respectively) or in asking that they use a condom if he has an STI (31 and 61 percent, respectively). Table 12.6 Attitudes toward negotiating safer sexual relations with husband Percentage of women and men age 15-49 who believe that a woman is justified in refusing to have sexual intercourse with her husband if she knows that he has sexual intercourse with other women, and percentage who believe that a woman is justified in asking that they use a condom if she knows that her husband has a sexually transmitted infection (STI), by background characteristics, Ethiopia 2011 Background characteristic Women Men Woman is justified in: Weighted number of women Unweighted number of women Woman is justified in: Weighted number of men Unweighted number of men Refusing to have sexual intercourse with her husband if she knows he has sex with other women Asking that they use a condom if she knows that her husband has an STI Refusing to have sexual intercourse with her husband if she knows he has sex with other women Asking that they use a condom if she knows that her husband has an STI Age 15-24 84.4 73.3 6,940 6,857 87.4 87.9 5,332 5,162 15-19 84.0 73.5 4,009 3,835 85.3 86.5 3,013 2,832 20-24 85.0 73.0 2,931 3,022 90.2 89.6 2,319 2,330 25-29 81.7 68.7 3,147 3,185 90.6 90.1 2,297 2,274 30-39 83.3 66.4 3,971 4,058 91.2 89.3 3,132 3,261 40-49 77.5 58.1 2,457 2,415 92.2 86.5 2,074 2,171 Marital status Never married 85.2 77.9 4,469 4,413 87.6 88.4 5,600 5,641 Ever had sex 92.0 89.3 344 489 91.5 95.3 1,044 1,492 Never had sex 84.6 76.9 4,126 3,924 86.8 86.8 4,555 4,149 Married/living together 81.4 64.5 10,287 10,204 91.2 88.3 6,872 6,775 Divorced/separated/ widowed 83.1 68.2 1,758 1,898 91.7 90.4 363 452 Residence Urban 90.5 86.4 3,947 5,329 95.9 95.7 2,882 3,915 Rural 80.2 62.9 12,568 11,186 87.9 86.3 9,952 8,953 Region Tigray 89.1 84.6 1,104 1,728 93.2 93.1 770 1,235 Affar 63.1 49.8 145 1,291 86.5 81.1 101 910 Amhara 86.4 65.3 4,433 2,087 92.3 88.2 3,481 1,739 Oromiya 81.8 69.2 6,011 2,135 85.0 86.1 4,957 1,889 Somali 64.0 30.5 329 914 82.5 61.1 245 653 Benishangul-Gumuz 75.4 66.4 174 1,259 85.7 87.0 138 1,047 SNNP 76.9 64.1 3,236 2,034 93.9 92.9 2,307 1,550 Gambela 69.7 66.4 69 1,130 86.5 88.8 59 865 Harari 88.3 77.8 49 1,101 89.4 84.0 40 898 Addis Ababa 93.5 91.9 896 1,741 96.2 97.1 682 1,237 Dire Dawa 89.6 83.3 69 1,095 93.0 91.3 53 845 Education No education 77.3 56.4 8,394 8,278 86.0 81.2 3,785 3,659 Primary 86.5 77.1 6,276 5,858 89.8 89.7 6,813 6,334 Secondary 93.1 92.9 1,117 1,395 94.6 96.2 1,296 1,565 More than secondary 95.1 96.7 728 984 97.0 96.9 940 1,310 Wealth quintile Lowest 78.1 54.1 2,986 3,711 85.4 80.6 2,141 2,563 Second 77.6 61.4 3,041 2,402 86.8 84.7 2,362 1,891 Middle 80.2 64.3 3,031 2,268 89.4 87.4 2,454 1,935 Fourth 83.2 68.5 3,215 2,505 89.2 90.3 2,683 2,203 Highest 90.7 86.7 4,242 5,629 95.3 95.6 3,194 4,276 Total 15-49 82.6 68.5 16,515 16,515 89.7 88.4 12,834 12,868 50-59 na na na na 89.3 85.2 1,276 1,242 Total 15-59 na na na na 89.6 88.1 14,110 14,110 na = Not applicable 200 • HIV/AIDS-Related Knowledge, Attitudes, and Behaviour 12.5 ADULT SUPPORT OF EDUCATION ABOUT CONDOMS FOR CHILDREN AGE 12-14 To gauge the extent of support for programmes to increase condom knowledge among youth, all women age 18-49 and men age 18-59 were asked whether they thought that children age 12-14 should be taught about using condoms to avoid AIDS. Table 12.7 shows that 54 percent of women and 76 percent of men age 18-49 agree that children age 12-14 should be taught about using condoms to avoid AIDS. Women age 18-24 are somewhat more supportive of condom education for children than older women. Support for condom education is higher among urban than rural women (68 percent versus 49 percent), and it increases with education and wealth. There is considerable regional variability in the level of support for condom education among women, from 23 percent in the Somali region to 70 percent in Tigray. Among adult men support for condom education does not vary consistently with age or urban-rural residence. As with women Somali is the region where the lowest percentage of men (43 percent) agree that children age 12-14 should be taught about condom use to avoid AIDS. There is no clear variation by education or wealth. Table 12.7 Adult support of education about condom use to prevent AIDS Percentage of women and men age 18-49 who agree that children age 12-14 years should be taught about using a condom to avoid AIDS, by background characteristics, Ethiopia 2011 Background characteristic Women Men Percentage who agree Weighted number of women Unweighted number of women Percentage who agree Weighted number of men Unweighted number of men Age 18-24 58.5 4,486 4,516 77.4 3,462 3,436 18-19 59.7 1,555 1,494 75.0 1,144 1,106 20-24 57.9 2,931 3,022 78.6 2,319 2,330 25-29 53.6 3,147 3,185 77.8 2,297 2,274 30-39 50.2 3,971 4,058 74.9 3,132 3,261 40-49 49.7 2,457 2,415 75.5 2,074 2,171 Marital status Never married 63.8 2,324 2,405 77.3 3,746 3,931 Married/living together 50.6 10,041 9,946 76.0 6,859 6,762 Divorced/separated/ widowed 57.3 1,697 1,823 75.1 360 449 Residence Urban 68.0 3,357 4,601 76.7 2,517 3,511 Rural 49.0 10,704 9,573 76.4 8,447 7,631 Region Tigray 70.3 913 1,428 89.6 632 1,013 Affar 29.7 125 1,114 53.5 88 788 Amhara 51.3 3,723 1,749 73.7 2,874 1,428 Oromiya 53.5 5,102 1,811 77.6 4,260 1,617 Somali 22.6 285 793 43.4 211 560 Benishangul-Gumuz 56.2 150 1,085 72.4 117 883 SNNP 51.1 2,817 1,771 79.8 2,011 1,346 Gambela 64.2 58 971 82.3 54 777 Harari 51.4 43 967 67.2 36 815 Addis Ababa 67.3 784 1,520 72.2 633 1,149 Dire Dawa 55.3 60 965 73.8 48 766 Education No education 44.2 8,073 7,877 69.5 3,545 3,435 Primary 64.4 4,330 4,144 80.8 5,322 4,979 Secondary 72.8 955 1,201 78.9 1,175 1,431 More than secondary 68.0 702 952 75.0 923 1,297 Wealth quintile Lowest 42.1 2,589 3,220 70.7 1,807 2,184 Second 49.8 2,613 2,061 74.4 2,027 1,617 Middle 47.3 2,588 1,934 79.1 2,065 1,636 Fourth 55.1 2,625 2,090 80.2 2,270 1,875 Highest 67.7 3,647 4,869 76.6 2,795 3,830 Total 18-49 53.5 14,061 14,174 76.4 10,964 11,142 50-59 na na na 70.4 1,276 1,242 Total 18-59 na na na 75.8 12,240 12,384 na = Not applicable HIV/AIDS-Related Knowledge, Attitudes, and Behaviour • 201 12.6 HIGHER-RISK SEX Information on sexual behaviour is important for designing and monitoring intervention programmes to control the spread of HIV/AIDS. The 2011 EDHS included questions on the number of lifetime sexual partners and of those during the 12 months preceding the survey. For male respondents interviewers asked an additional question on whether they had paid for sex during the 12 months preceding the interview. Information on the use of condoms at the last sexual encounter with each of partner was collected for both women and men. These questions are sensitive, and it is recognized that some respondents may have been reluctant to provide information on recent sexual behaviour. 12.6.1 Multiple Partners and Condom Use Table 12.8.1 shows that a negligible proportion of women (less than 1 percent) had two or more partners in the 12 months preceding the survey. In the Gambela region a notably higher proportion of women than in other regions report that they had two or more partners in the past 12 months (1l percent compared with 1 percent or less elsewhere). Women have a mean of 1.5 lifetime sexual partners. Never-married women have the highest mean number of sexual partners, 3.5, compared with 1.4 among those currently in union and 2.1 among those previously married. Women in the Gambela region report a markedly higher mean number of lifetime sexual partners (8.1) than women in other regions (1.2 to 2 partners). Among all women who had two or more partners in the past 12 months, 47 percent reported using a condom during last sexual intercourse (data not shown). Table 12.8.2 shows that 4 percent of men had two or more partners in the past 12 months. The percentage of men with two or more sexual partners in the past 12 months increases from 1 percent among men age 15-19 to 8 percent among men age 40-49. Divorced, separated, or widowed men are somewhat more likely to have had two or more sexual partners in the past 12 months (9 percent) than men who are married or cohabiting (5 percent) or who never married (1 percent). Among regions the highest proportion of men with two or more sexual partners in the past 12 months is seen in Gambela (9 percent), followed by Affar and Benishangul-Gumuz (both 8 percent). The percentage of men with two or more partners in the past 12 months decreases with education and wealth. Among men age 15-49 with two or more partners in the past 12 months, 16 percent used a condom during last sexual intercourse. Currently married men were much less likely to have used a condom at last sex (2 percent) than men who have never married (72 percent). Men age 25-29 (47 percent), those in urban areas (54 percent), men with more than secondary education (69 percent), and those in the highest wealth quintile (55 percent) were more likely than other men to have used a condom at last sex. Men have a mean of 2.6 lifetime sexual partners. Previously married men, men residing in urban areas and in Gambela, men with secondary or higher education, and those in the highest wealth quintile have the highest mean number of lifetime sexual partners. 202 • HIV/AIDS-Related Knowledge, Attitudes, and Behaviour Table 12.8.1 Multiple sexual partners: Women Among all women age 15-49, the percentage who had sexual intercourse with two or more sexual partners in the past 12 months and the mean number of sexual partners during their lifetime for women who ever had sexual intercourse, by background characteristics, Ethiopia 2011 Background characteristic All women Among women who ever had sexual intercourse1: Percentage who had 2+ partners in the past 12 months Weighted number of women Unweighted number of women Mean number of sexual partners in lifetime Weighted number of women Unweighted number of women Age 15-24 0.4 6,940 6,857 1.5 3,090 3,236 15-19 0.3 4,009 3,835 1.4 968 1,032 20-24 0.6 2,931 3,022 1.6 2,122 2,204 25-29 0.6 3,147 3,185 1.5 2,911 2,934 30-39 0.3 3,971 4,058 1.5 3,873 3,948 40-49 0.2 2,457 2,415 1.7 2,438 2,398 Marital status Never married 0.3 4,469 4,413 3.5 351 492 Married/living together 0.3 10,287 10,204 1.4 10,252 10,163 Divorced/separated/ widowed 1.1 1,758 1,898 2.1 1,709 1,861 Residence Urban 0.7 3,947 5,329 1.9 2,558 3,508 Rural 0.3 12,568 11,186 1.4 9,753 9,008 Region Tigray 0.9 1,104 1,728 2.0 829 1,308 Affar 0.0 145 1,291 1.2 121 1,093 Amhara 0.3 4,433 2,087 1.7 3,442 1,643 Oromiya 0.2 6,011 2,135 1.3 4,522 1,606 Somali 0.6 329 914 1.2 263 737 Benishangul-Gumuz 0.5 174 1,259 1.4 142 1,031 SNNP 0.4 3,236 2,034 1.5 2,301 1,463 Gambela 11.2 69 1,130 8.1 61 995 Harari 0.1 49 1,101 1.3 36 809 Addis Ababa 0.2 896 1,741 1.6 545 1,035 Dire Dawa 0.1 69 1,095 1.5 49 796 Education No education 0.4 8,394 8,278 1.5 7,855 7,663 Primary 0.5 6,276 5,858 1.7 3,474 3,499 Secondary 0.0 1,117 1,395 1.3 528 774 More than secondary 0.1 728 984 1.3 454 580 Wealth quintile Lowest 0.1 2,986 3,711 1.4 2,442 3,138 Second 0.3 3,041 2,402 1.4 2,416 1,938 Middle 0.4 3,031 2,268 1.4 2,377 1,810 Fourth 0.2 3,215 2,505 1.5 2,259 1,875 Highest 0.7 4,242 5,629 1.9 2,817 3,755 Total 15-49 0.4 16,515 16,515 1.5 12,311 12,516 1 Means are calculated excluding respondents who gave non-numeric responses. HIV/AIDS-Related Knowledge, Attitudes, and Behaviour • 203 Table 12.8.2 Multiple sexual partners: Men Among all men age 15-49, the percentage who had sexual intercourse with two or more sexual partners in the past 12 months; among those having more than one partner in the past 12 months, the percentage reporting that a condom was used at last intercourse; and the mean number of sexual partners during their lifetime for men who ever had sexual intercourse, by background characteristics, Ethiopia 2011 Background characteristic All men Among men who had 2+ partners in the past 12 months: Among men who ever had sexual intercourse1: Percentage who had 2+ partners in the past 12 months Weighted number of men Unweighted number of men Percentage who reported using a condom during last sexual intercourse Weighted number of men Unweighted number of men Mean number of sexual partners in life time Weighted number of men Unweighted number of men Age 15-24 1.0 5,332 5,162 47.2 52 97 1.9 1,260 1,491 15-19 0.5 3,013 2,832 * 14 24 1.9 234 325 20-24 1.6 2,319 2,330 36.9 37 73 1.9 1,026 1,166 25-29 2.6 2,297 2,274 47.1 60 91 2.1 1,854 1,870 30-39 5.4 3,132 3,261 7.0 168 191 2.5 3,028 3,140 40-49 8.0 2,074 2,171 2.8 166 185 3.8 2,047 2,129 Marital status Never married 1.2 5,600 5,641 72.1 65 124 3.0 1,033 1,480 Married/living together 5.1 6,872 6,775 1.6 350 414 2.4 6,810 6,710 Divorced/separated/ widowed 8.6 363 452 (54.2) 31 26 5.3 345 440 Type of union In polygynous union 86.9 348 425 1.6 302 340 2.9 346 423 In non-polygynous union 0.7 6,502 6,328 1.8 48 73 2.4 6,443 6,265 Not currently in union 1.6 5,963 6,093 66.3 96 150 3.6 1,379 1,920 Residence Urban 3.2 2,882 3,915 53.9 93 148 4.3 1,839 2,642 Rural 3.5 9,952 8,953 5.5 353 416 2.1 6,350 5,988 Region Tigray 1.7 770 1,235 * 13 21 3.5 478 769 Affar 7.7 101 910 20.2 8 78 3.7 73 672 Amhara 1.5 3,481 1,739 (24.3) 54 25 2.6 2,121 1,061 Oromiya 4.1 4,957 1,889 10.8 201 81 2.2 3,194 1,220 Somali 6.2 245 653 (5.6) 15 39 1.9 164 441 Benishangul-Gumuz 8.4 138 1,047 3.7 12 90 2.4 93 700 SNNP 5.0 2,307 1,550 5.4 115 79 2.6 1,481 996 Gambela 8.5 59 865 30.3 5 72 5.9 45 690 Harari 1.7 40 898 * 1 15 2.4 28 624 Addis Ababa 3.2 682 1,237 (71.8) 22 42 4.6 473 852 Dire Dawa 2.7 53 845 * 1 22 3.4 38 605 Education No education 4.0 3,785 3,659 1.4 153 206 2.1 3,107 3,009 Primary 3.5 6,813 6,334 13.9 236 241 2.6 3,766 3,738 Secondary 2.4 1,296 1,565 54.0 31 65 4.0 637 940 More than secondary 2.6 940 1,310 69.4 25 52 4.0 679 943 Wealth quintile Lowest 5.7 2,141 2,563 4.6 123 184 2.1 1,456 1,845 Second 3.4 2,362 1,891 8.7 81 70 2.1 1,529 1,255 Middle 3.2 2,454 1,935 4.1 79 75 2.1 1,563 1,259 Fourth 2.9 2,683 2,203 8.1 78 97 2.4 1,589 1,392 Highest 2.7 3,194 4,276 55.3 85 138 4.0 2,051 2,879 Total 15-49 3.5 12,834 12,868 15.5 446 564 2.6 8,189 8,630 50-59 6.4 1,276 1,242 3.5 82 91 4.5 1,246 1,217 Total 15-59 3.7 14,110 14,110 13.7 528 655 2.9 9,435 9,847 Note: Total includes 22 cases with information missing on type of union. Figures in parentheses are based on 25-49 unweighted cases. An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. 1 Means are calculated excluding respondents who gave non-numeric responses. While the risk of HIV transmission increases with the mean number of lifetime partners, it is highest when the sexual partnerships are concurrent. Two sexual partnerships are considered to be concurrent if the date of the most recent sexual intercourse with the earlier partner is after the date of the first sexual intercourse with the later partner. Concurrent partnership is measured in two ways—by the point prevalence of concurrency and by the cumulative percentage of concurrency. Point prevalence refers to the percentage of respondents who had two or more sexual partners concurrently at the point six months before the survey. Cumulative prevalence measures the percentage of respondents who had two or more sexual partners concurrently at any time during the 12 months 204 • HIV/AIDS-Related Knowledge, Attitudes, and Behaviour preceding the survey. The point prevalence and the cumulative prevalence of concurrent sexual partners are presented in Table 12.9. The point prevalence and the cumulative prevalence of concurrent sexual partners among women are close to zero, while among men they are 2 and 3 percent, respectively. Among men both the point prevalence and the cumulative prevalence are highest among the oldest men, age 40-49 (7 and 8 percent, respectively), among currently married or cohabiting men (4 and 5 percent, respectively), and among those living in rural areas (both 3 percent). The percentage of multiple sexual partnerships that were concurrent in the 12 months preceding the survey is 41 percent for women and 82 percent for men 15-49. Table 12.9 Point prevalence and cumulative prevalence of concurrent sexual partners Percentage of all women and men age 15-49 who had concurrent sexual partners six months before the survey (point prevalence1), percentage of all women and all men age 15-49 who had any concurrent sexual partners during the 12 months before the survey (cumulative prevalence2), and, among women and men age 15-49 who had multiple sexual partners during the 12 months before the survey, percentage who had concurrent sexual partners, Ethiopia 2011 Background characteristic Among all respondents: Among all respondents who had multiple partners during the 12 months before the survey: Point prevalence of concurrent sexual partners1 Cumulative prevalence of concurrent sexual partners2 Weighted number of respondents Unweighted number of respondents Percentage who had concurrent sexual partners2 Weighted number of respondents Unweighted number of respondents WOMEN Age 15-24 0.0 0.1 6,940 6,857 (25.1) 28 45 15-19 0.0 0.0 4,009 3,835 * 11 24 20-24 0.0 0.2 2,931 3,022 * 17 21 25-29 0.1 0.2 3,147 3,185 * 19 21 30-39 0.0 0.2 3,971 4,058 * 10 11 40-49 0.0 0.2 2,457 2,415 * 5 2 Marital status Never married 0.0 0.1 4,469 4,413 * 13 23 Married/living together 0.0 0.2 10,287 10,204 (62.5) 29 25 Divorced/separated/ widowed 0.0 0.2 1,758 1,898 (16.1) 20 31 Residence Urban 0.0 0.2 3,947 5,329 (24.2) 29 30 Rural 0.0 0.1 12,568 11,186 (56.3) 33 49 Total 15-49 0.0 0.2 16,515 16,515 41.3 62 79 MEN Age 15-24 0.1 0.3 5,332 5,162 29.3 52 97 15-19 0.0 0.1 3,013 2,832 * 14 24 20-24 0.2 0.6 2,319 2,330 36.0 37 73 25-29 0.7 1.6 2,297 2,274 59.2 60 91 30-39 4.2 4.8 3,132 3,261 90.2 168 191 40-49 6.7 7.9 2,074 2,171 98.1 166 185 Marital status Never married 0.2 0.5 5,600 5,641 43.3 65 124 Married/living together 4.1 4.8 6,872 6,775 94.9 350 414 Divorced/separated/ widowed 0.0 1.4 363 452 (16.7) 31 26 Residence Urban 0.8 1.6 2,882 3,915 48.8 93 148 Rural 2.7 3.2 9,952 8,953 90.6 353 416 Total 15-49 2.3 2.8 12,834 12,868 81.9 446 564 50-59 5.8 6.4 1,276 1,242 99.4 82 91 Total 15-59 2.6 3.2 14,110 14,110 84.6 528 655 Note: Two sexual partners are considered to be concurrent if the date of the most recent sexual intercourse with the earlier partner is after the date of the first sexual intercourse with the later partner. Figures in parentheses are based on 25-49 unweighted cases. An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. 1 The percentage of respondents who had two (or more) sexual partners that were concurrent at the point in time six months before the survey 2 The percentage of respondents who had two (or more) sexual partners that were concurrent at any time during the 12 months preceding the survey HIV/AIDS-Related Knowledge, Attitudes, and Behaviour • 205 12.6.2 Transactional Sex Transactional sex involves the exchange of sex for money, favours, or gifts. Transactional sex is associated with a high risk of contracting HIV and other sexually transmitted infections due to compromised power relations and the tendency to have multiple partnerships. The 2011 EDHS asked male respondents if they had ever paid anyone in exchange for sex. Men who had sexual intercourse in the 12 months preceding the survey were asked if they had paid anyone for sexual intercourse during that time. Further, respondents who had engaged in paid sexual intercourse in the past 12 months were asked if they had used a condom the last time they paid for sexual intercourse. Table 12.10 shows that 5 percent of men age 15-49 have paid for sexual intercourse at some point in their lives, and 1 percent did so in the past 12 months. Men age 40-49 (13 percent), those who were previously married (20 percent), and urban men (10 percent) were more likely than other men to have ever paid for sexual intercourse. Among regions this proportion ranges from 2 percent of men in Somali and Harari to 15 percent in Gambela. The proportion of men who ever paid for sex increases with increases in men’s education and wealth. There is little variation by background characteristics in the percentage of men who paid for sex in the past 12 months. Thirty percent of men who paid for sex in the past 12 months reported condom use at last paid sexual intercourse (data not shown). Table 12.10 Payment for sexual intercourse Percentage of men age 15-49 who ever paid for sexual intercourse and percentage reporting payment for sexual intercourse in the past 12 months, by background characteristics, Ethiopia 2011 Background characteristic Percentage who ever paid for sexual intercourse Percentage who paid for sexual intercourse in the past 12 months Weighted number of men Unweighted number of men Age 15-24 1.5 1.0 5,332 5,162 15-19 0.6 0.4 3,013 2,832 20-24 2.6 1.6 2,319 2,330 25-29 4.4 1.7 2,297 2,274 30-39 8.1 1.4 3,132 3,261 40-49 12.5 0.7 2,074 2,171 Marital status Never married 2.3 1.0 5,600 5,641 Married/living together 7.1 0.8 6,872 6,775 Divorced/separated/ widowed 20.4 9.3 363 452 Residence Urban 9.5 1.9 2,882 3,915 Rural 4.2 0.9 9,952 8,953 Region Tigray 13.2 1.8 770 1,235 Affar 2.6 1.9 101 910 Amhara 6.9 1.4 3,481 1,739 Oromiya 3.0 0.8 4,957 1,889 Somali 1.5 0.9 245 653 Benishangul-Gumuz 6.3 1.2 138 1,047 SNNP 4.3 1.1 2,307 1,550 Gambela 14.9 4.4 59 865 Harari 2.0 0.3 40 898 Addis Ababa 11.3 1.4 682 1,237 Dire Dawa 7.6 0.5 53 845 Education No education 5.3 1.2 3,785 3,659 Primary 4.6 1.1 6,813 6,334 Secondary 7.0 1.0 1,296 1,565 More than secondary 9.2 1.5 940 1,310 Wealth quintile Lowest 3.7 1.2 2,141 2,563 Second 3.9 0.7 2,362 1,891 Middle 4.6 1.0 2,454 1,935 Fourth 4.9 1.3 2,683 2,203 Highest 8.7 1.4 3,194 4,276 Total 15-49 5.4 1.1 12,834 12,868 50-59 14.6 0.3 1,276 1,242 Total 15-59 6.2 1.1 14,110 14,110 206 • HIV/AIDS-Related Knowledge, Attitudes, and Behaviour 12.7 COVERAGE OF HIV TESTING 12.7.1 General HIV Testing Knowledge of HIV status helps HIV negative individuals make specific decisions to reduce risk and increase safer sex practices so that they can remain free of disease. For those who are infected with HIV, knowledge of their status allows them to take action to protect their sexual partners, to seek treatment, and to plan for the future. To assess awareness of HIV testing services and the coverage of those services, the 2011 EDHS asked respondents whether they had ever been tested for HIV. If they said that they had been, they were asked whether they had received the results of their last test. If they had never been tested, they were asked if they knew a place where they could go to be tested. Tables 12.11.1 and 12.11.2 show that 66 percent of women and 82 percent of men know where to get an HIV test. The level of this knowledge is substantially higher among urban residents (91 percent of women and 97 percent of men) than among rural residents (59 percent of women and 78 percent of men). Women and men who have never married and have ever had sex, who live in Addis Ababa, who have secondary or higher education, and who are in the highest wealth quintile are more likely to know where to get an HIV test. Results show that 36 percent of women and 38 percent of men have ever been tested for HIV and received their test results. Among age groups women age 20-24 (44 percent) and men age 25-29 (46 percent) are the most likely to have ever been tested for HIV and received their test results. Among both women and men, urban residents are more likely than rural residents to have ever had an HIV test and received results. Never-married respondents who have ever had sex are more likely to have taken the test and received results (69 percent of women and 58 percent of men) than those currently or previously in union. Among regions the percentages of men and women who have ever been tested for HIV and received results ranges from 11 percent in Somali to 65 percent in Addis Ababa for women and from 17 percent in Somali to 60 percent in Dire Dawa for men. HIV testing is more common among better educated and wealthier respondents. Overall, about six in every ten Ethiopians (61 percent of women and 59 percent of men) have never been tested for HIV. One respondent of every five (20 percent of women and 21 percent of men) were tested for HIV in the year preceding the survey and received the results. These figures are much higher than those recorded in the 2005 EDHS (2 percent for both women and men), showing an increased awareness and utilization of opportunities for HIV testing and learning one’s HIV status. HIV/AIDS-Related Knowledge, Attitudes, and Behaviour • 207 Table 12.11.1 Coverage of prior HIV testing: Women Percentage of women age 15-49 who know where to get an HIV test, percent distribution of women age 15-49 by testing status and by whether they received the results of the last test, the percentage of women ever tested, and the percentage of women age 15-49 who received their test results the last time they were tested for HIV in the past 12 months, by background characteristics, Ethiopia 2011 Background characteristic Percentage who know where to get an HIV test Percent distribution of women by testing status and by whether they received the results of the last test Total Percentage ever tested Percentage who received results from last HIV test in the past 12 months Weighted number of women Unweighted number of women Ever tested and received results Ever tested, did not receive results Never tested1 Age 15-24 69.2 37.3 3.2 59.5 100.0 40.5 21.2 6,940 6,857 15-19 67.5 32.1 3.0 64.9 100.0 35.1 18.8 4,009 3,835 20-24 71.5 44.4 3.4 52.3 100.0 47.7 24.5 2,931 3,022 25-29 68.0 39.8 2.7 57.5 100.0 42.5 23.1 3,147 3,185 30-39 65.0 35.6 3.3 61.1 100.0 38.9 19.2 3,971 4,058 40-49 59.0 26.6 2.6 70.8 100.0 29.2 13.9 2,457 2,415 Marital status Never married 73.1 36.1 3.3 60.6 100.0 39.4 21.2 4,469 4,413 Ever had sex 92.9 68.5 2.6 28.8 100.0 71.2 45.2 344 489 Never had sex 71.5 33.4 3.4 63.2 100.0 36.8 19.2 4,126 3,924 Married/living together 62.8 34.7 3.0 62.2 100.0 37.8 19.5 10,287 10,204 Divorced/separated/ widowed 70.5 40.9 2.3 56.8 100.0 43.2 19.7 1,758 1,898 Residence Urban 90.8 61.2 2.6 36.2 100.0 63.8 36.0 3,947 5,329 Rural 58.8 27.8 3.1 69.1 100.0 30.9 15.0 12,568 11,186 Region Tigray 85.3 55.5 4.9 39.6 100.0 60.4 35.3 1,104 1,728 Affar 49.2 29.4 0.7 69.9 100.0 30.1 18.7 145 1,291 Amhara 67.9 34.5 2.6 62.9 100.0 37.1 19.0 4,433 2,087 Oromiya 59.3 32.5 2.9 64.6 100.0 35.4 18.2 6,011 2,135 Somali 34.9 10.6 0.9 88.6 100.0 11.4 6.5 329 914 Benishangul-Gumuz 61.1 36.7 2.2 61.1 100.0 38.9 17.1 174 1,259 SNNP 66.1 30.5 3.9 65.5 100.0 34.5 16.1 3,236 2,034 Gambela 77.0 46.6 3.1 50.3 100.0 49.7 27.6 69 1,130 Harari 87.2 55.4 2.7 41.9 100.0 58.1 33.5 49 1,101 Addis Ababa 96.6 65.2 1.2 33.6 100.0 66.4 35.2 896 1,741 Dire Dawa 88.1 62.9 4.4 32.7 100.0 67.3 40.8 69 1,095 Education No education 52.9 24.1 2.4 73.5 100.0 26.5 12.9 8,394 8,278 Primary 75.3 41.5 3.8 54.7 100.0 45.3 23.7 6,276 5,858 Secondary 96.2 65.1 4.0 30.9 100.0 69.1 36.0 1,117 1,395 More than secondary 100.0 76.3 1.5 22.2 100.0 77.8 45.6 728 984 Wealth quintile Lowest 46.4 18.2 2.2 79.7 100.0 20.3 10.5 2,986 3,711 Second 55.1 23.4 3.5 73.1 100.0 26.9 12.2 3,041 2,402 Middle 60.0 28.3 3.5 68.2 100.0 31.8 15.2 3,031 2,268 Fourth 70.2 37.1 3.4 59.5 100.0 40.5 19.0 3,215 2,505 Highest 90.4 61.3 2.7 36.0 100.0 64.0 36.5 4,242 5,629 Total 15-49 66.4 35.8 3.0 61.2 100.0 38.8 20.0 16,515 16,515 1 Includes 'don't know/missing' 208 • HIV/AIDS-Related Knowledge, Attitudes, and Behaviour Table 12.11.2 Coverage of prior HIV testing: Men Percentage of men age 15-49 who know where to get an HIV test, percent distribution of men age 15-49 by testing status and by whether they received the results of the last test, the percentage of men ever tested, and the percentage of men age 15-49 who received their test results the last time they were tested for HIV in the past 12 months, according to background characteristics, Ethiopia 2011 Background characteristic Percentage who know where to get an HIV test Percent distribution of men by testing status and by whether they received the results of the last test Total Percentage ever tested Percentage who received results from last HIV test in the past 12 months Weighted number of men Unweighted number of men Ever tested and received results Ever tested, did not receive results Never tested1 Age 15-24 78.8 32.0 3.6 64.4 100.0 35.6 20.1 5,332 5,162 15-19 74.7 25.3 3.6 71.1 100.0 28.9 16.5 3,013 2,832 20-24 84.1 40.7 3.5 55.8 100.0 44.2 24.8 2,319 2,330 25-29 86.8 45.9 4.6 49.5 100.0 50.5 23.7 2,297 2,274 30-39 83.2 40.8 3.1 56.1 100.0 43.9 20.0 3,132 3,261 40-49 82.6 37.8 2.8 59.5 100.0 40.5 19.8 2,074 2,171 Marital status Never married 80.9 34.2 3.6 62.2 100.0 37.8 20.8 5,600 5,641 Ever had sex 95.0 57.8 3.3 38.9 100.0 61.1 34.7 1,044 1,492 Never had sex 77.7 28.7 3.7 67.6 100.0 32.4 17.6 4,555 4,149 Married/living together 82.5 39.7 3.5 56.8 100.0 43.2 20.3 6,872 6,775 Divorced/separated/ widowed 85.7 50.5 2.2 47.3 100.0 52.7 26.2 363 452 Residence Urban 96.9 56.3 2.2 41.4 100.0 58.6 30.4 2,882 3,915 Rural 77.5 32.1 3.9 64.0 100.0 36.0 17.9 9,952 8,953 Region Tigray 92.1 49.1 5.9 45.1 100.0 54.9 29.7 770 1,235 Affar 79.2 35.0 1.3 63.7 100.0 36.3 17.9 101 910 Amhara 81.4 40.6 2.9 56.5 100.0 43.5 23.4 3,481 1,739 Oromiya 76.3 31.9 2.6 65.5 100.0 34.5 18.1 4,957 1,889 Somali 54.2 17.1 1.6 81.3 100.0 18.7 7.9 245 653 Benishangul-Gumuz 77.6 39.9 2.5 57.7 100.0 42.3 23.4 138 1,047 SNNP 89.2 36.3 6.7 57.0 100.0 43.0 17.2 2,307 1,550 Gambela 91.7 51.9 4.9 43.2 100.0 56.8 29.0 59 865 Harari 81.3 42.8 1.8 55.4 100.0 44.6 24.6 40 898 Addis Ababa 98.7 58.9 0.9 40.2 100.0 59.8 29.0 682 1,237 Dire Dawa 93.5 60.1 3.5 36.4 100.0 63.6 42.0 53 845 Education No education 68.6 25.4 2.9 71.7 100.0 28.3 13.1 3,785 3,659 Primary 83.6 36.5 4.2 59.3 100.0 40.7 19.7 6,813 6,334 Secondary 99.0 59.2 3.0 37.7 100.0 62.3 35.3 1,296 1,565 More than secondary 99.5 64.7 1.5 33.8 100.0 66.2 38.2 940 1,310 Wealth quintile Lowest 65.9 22.2 3.3 74.5 100.0 25.5 11.2 2,141 2,563 Second 74.7 28.6 3.1 68.3 100.0 31.7 15.3 2,362 1,891 Middle 78.2 32.9 3.4 63.6 100.0 36.4 16.4 2,454 1,935 Fourth 86.5 38.0 5.6 56.4 100.0 43.6 23.2 2,683 2,203 Highest 96.9 57.7 2.3 40.0 100.0 60.0 32.1 3,194 4,276 Total 15-49 81.9 37.6 3.5 58.9 100.0 41.1 20.7 12,834 12,868 50-59 77.9 27.6 4.2 68.2 100.0 31.8 12.4 1,276 1,242 Total 15-59 81.5 36.7 3.6 59.8 100.0 40.2 19.9 14,110 14,110 1 Includes 'don't know/missing' 12.7.2 HIV Counselling and Testing During Pregnancy Table 12.12 presents information on HIV screening of pregnant women age 15-49 who gave birth in the two years preceding the survey. The screening process is a key tool in reducing mother-to- child transmission of HIV. Only 14 percent of women who gave birth in the two years before the survey received HIV counselling during antenatal care (ANC). One woman in every five (20 percent) were tested for HIV during antenatal care and received the test results, and 2 percent were tested but did not receive the test results. HIV/AIDS-Related Knowledge, Attitudes, and Behaviour • 209 Overall, 11 percent of women received HIV counselling, an HIV test, and the results during ANC for their most recent birth in the two years preceding the survey. Young women, age 15-24 (14 percent) and urban women (43 percent) were more likely than other women to have been counselled on HIV and received an HIV test and its results during ANC. Addis Ababa has by far the highest percentage of women receive the full screening process, at 76 percent, while Somali has the lowest, at 2 percent. The likelihood of HIV counselling and testing during ANC increases with levels of education and wealth. For example, the proportion of women who were counselled about HIV during ANC, were tested, and received results ranges from 6 percent of women with no education to 72 percent of those with more than secondary education. Table 12.12 Pregnant women counselled and tested for HIV Among all women age 15-49 who gave birth in the two years preceding the survey, the percentage who received HIV counselling and the percentage who received an HIV test during antenatal care for their most recent birth, by whether they received their test results, according to background characteristics, Ethiopia 2011 Background characteristic Percentage who received HIV counselling during antenatal care1 Percentage who were tested for HIV during antenatal care and who: Percentage who received counselling on HIV, an HIV test during ANC, and the results Weighted number of women who gave birth in the past two years2 Unweighted number of women who gave birth in the past two years2 Received results Did not receive results Age 15-24 16.0 24.3 1.3 13.8 1,366 1,333 15-19 10.8 18.2 2.5 9.6 333 336 20-24 17.6 26.3 0.9 15.2 1,034 997 25-29 13.6 20.3 1.3 11.6 1,407 1,333 30-39 12.5 17.0 1.7 9.7 1,386 1,364 40-49 7.8 12.7 1.7 6.2 293 254 Marital status Never married/ ever had sex (22.4) (29.0) (1.5) (20.9) 38 32 Married/living together 13.2 19.6 1.4 11.0 4,166 4,012 Divorced/separated/ widowed 19.5 24.6 2.7 15.6 249 240 Residence Urban 46.8 60.9 3.4 43.2 607 751 Rural 8.4 13.5 1.2 6.3 3,846 3,533 Region Tigray 29.3 43.9 2.8 27.0 273 434 Affar 13.5 19.2 0.0 10.7 40 378 Amhara 12.1 19.6 2.6 10.3 983 476 Oromiya 11.2 16.8 0.9 8.6 1,917 681 Somali 6.5 5.7 1.0 2.2 128 358 Benishangul-Gumuz 13.1 17.9 1.1 11.2 51 373 SNNP 9.4 14.1 1.3 7.8 926 600 Gambela 16.6 29.8 0.5 14.1 15 317 Harari 26.9 40.7 0.9 25.2 11 246 Addis Ababa 79.7 90.5 0.5 76.0 95 167 Dire Dawa 32.5 40.5 2.3 29.7 14 254 Education No education 7.1 11.7 1.0 5.6 2,956 2,845 Primary 20.4 29.1 2.3 16.7 1,296 1,184 Secondary 62.8 78.1 4.7 56.4 136 173 More than secondary 71.7 94.5 0.1 71.7 65 82 Wealth quintile Lowest 5.3 6.7 0.5 3.6 1,047 1,311 Second 5.5 10.3 1.3 3.4 988 782 Middle 8.1 12.8 0.6 6.2 917 704 Fourth 14.6 21.8 2.8 11.5 784 656 Highest 42.8 60.1 2.8 39.9 717 831 Total 15-49 13.6 20.0 1.5 11.3 4,453 4,284 Note: Figures in parentheses are based on 25-49 unweighted cases. 1 In this context "counselling" means that someone talked with the respondent about all three of the following topics: (1) babies getting the AIDS virus from their mother, (2) preventing transmission of the virus, and (3) getting tested for the virus. 2 Denominator for percentages includes women who did not receive antenatal care for their last birth in the past two years. 210 • HIV/AIDS-Related Knowledge, Attitudes, and Behaviour 12.8 MALE CIRCUMCISION Circumcision is widely practiced in Ethiopia and often serves as a rite of passage to adulthood. Recently, studies have shown that male circumcision, which involves the removal of the foreskin of the penis, is associated with lower susceptibility to transmission of sexually transmitted infections, including HIV (Bailey et al., 2007). The 2011 EDHS asked men if they were circumcised. Table 12.13.1 shows that 92 percent of Ethiopian men age 15-49 are circumcised. The percentage of men who are circumcised increases with age, ranging from 88 percent of men age 15-19 to 95 percent of men age 40-49. Men living in urban areas are somewhat more likely to be circumcised than men in rural areas (98 percent versus 90 percent). Circumcision is close to universal in most regions, except in Gambela and SNNP regions (76 and 79 percent, respectively). The proportion of circumcised men is highest among Orthodox Christians and Muslims (96 percent each). Table 12.13.1 Male circumcision Percentage of men age 15-49 who report having been circumcised, by background characteristics, Ethiopia 2011 Background characteristic Percentage circumcised Weighted number of men Unweighted number of men Age 15-24 89.1 5,332 5,162 15-19 87.6 3,013 2,832 20-24 91.1 2,319 2,330 25-29 93.5 2,297 2,274 30-39 93.3 3,132 3,261 40-49 94.8 2,074 2,171 Residence Urban 97.9 2,882 3,915 Rural 90.1 9,952 8,953 Region Tigray 96.2 770 1,235 Affar 99.0 101 910 Amhara 95.2 3,481 1,739 Oromiya 93.6 4,957 1,889 Somali 97.2 245 653 Benishangul-Gumuz 94.6 138 1,047 SNNP 78.5 2,307 1,550 Gambela 75.9 59 865 Harari 99.6 40 898 Addis Ababa 99.1 682 1,237 Dire Dawa 99.5 53 845 Religion Orthodox 96.3 6,133 5,510 Catholic 83.3 120 125 Protestant 78.9 2,459 2,069 Muslim 95.5 3,788 4,873 Traditional 76.6 96 87 Total 15-49 91.8 12,834 12,868 50-59 95.6 1,276 1,242 Total 15-59 92.2 14,110 14,110 Note: Total includes 15 cases with information missing on religion. Circumcised men were also asked the age at which they were circumcised, who performed the circumcision, and where the circumcision was done. As Table 12.13.2 shows, the majority of circumcised men, 61 percent, were circumcised during childhood (younger than age 5). In the majority of the cases, the circumcision was performed by a traditional practitioner or family friend (72 percent) and at the respondent’s home (73 percent). HIV/AIDS-Related Knowledge, Attitudes, and Behaviour • 211 Table 12.13.2 Circumstances surrounding male circumcision Percentage of men age 15-49 who have been circumcised, by age at circumcision, person who performed the circumcision, and place of circumcision, Ethiopia 2011 Characteristics of circumcision Total Age at circumcision During childhood (< age 5) 61.3 5-9 9.0 10+ 17.9 Don't know 11.5 Missing 0.2 Who performed the circumcision Traditional practitioner/family friend 72.0 Health worker/professional 14.0 Other 0.5 Don't know 13.3 Missing 0.1 Place where circumcision was done Health facility 10.2 Home of a health worker/professional 3.7 At home 72.7 Ritual site 2.1 Other home/place 4.0 Don't know 7.3 Total 100.0 Weighted number 13,901 Unweighted number 13,004 12.9 SELF-REPORTING OF SEXUALLY TRANSMITTED INFECTIONS Information about the incidence of sexually transmitted infections (STIs) is not only useful as a marker of unprotected sexual intercourse but also because STI infection is a co-factor in HIV transmission. The 2011 EDHS asked respondents who had ever had sex whether they had had a disease that they acquired through sexual contact in the past 12 months. They were also asked whether, in the past 12 months, they had any genital discharge and whether they had experienced a genital sore or ulcer. These symptoms have been shown to be useful in identifying STIs in men. For women, however, discharge is less easily interpreted as a symptom because women experience non- STI conditions of the reproductive tract that also produce discharge. Table 12.14 shows that 1 percent, each, of Ethiopian women and men reported having had an STI in the past 12 months. Three percent of women and 2 percent of men reported having had an abnormal genital discharge, and 1 percent each of women and men reported having had a genital sore or ulcer in the 12 months preceding the survey. These numbers may be underestimates because respondents may be embarrassed or ashamed to admit to having STIs. Given the low levels of reporting of STIs, variations across background characteristics are small. 212 • HIV/AIDS-Related Knowledge, Attitudes, and Behaviour Table 12.14 Self-reported prevalence of sexually-transmitted infections (STIs) and STI symptoms Among women and men age 15-49 who ever had sexual intercourse, the percentage reporting having an STI and/or symptoms of an STI in the past 12 months, by background characteristics, Ethiopia 2011 Background characteristic Women Men Percentage of women who reported having in the past 12 months: Weighted number of women who ever had sexual intercourse Un- weighted number of women who ever had sexual intercourse Percentage of men who reported having in the past 12 months: Weighted number of men who ever had sexual intercourse Un- weighted number of men who ever had sexual intercourseSTI Bad- smelling or abnormal genital discharge Genital sore or ulcer STI, genital discharge, sore or ulcer STI Bad- smelling or abnormal genital discharge Genital sore or ulcer STI, genital discharge, sore or ulcer Age 15-24 0.7 2.9 0.9 3.6 3,088 3,237 1.9 2.9 1.0 4.4 1,266 1,498 15-19 1.0 2.1 1.4 3.3 970 1,032 0.2 2.3 0.6 2.3 236 327 20-24 0.6 3.3 0.8 3.7 2,119 2,205 2.3 3.0 1.1 4.8 1,030 1,171 25-29 0.8 2.2 1.8 3.4 2,917 2,945 0.6 0.8 0.5 1.6 1,859 1,874 30-39 0.8 1.9 1.0 2.7 3,881 3,959 0.6 1.4 0.4 1.9 3,040 3,158 40-49 0.7 3.5 1.9 4.2 2,441 2,400 1.2 1.2 0.9 2.3 2,059 2,152 Marital status Never married/ever had sex 1.2 2.7 2.4 4.7 344 489 1.8 2.8 1.0 4.3 1,044 1,492 Married/living together 0.7 2.4 1.1 3.2 10,263 10,179 0.8 1.1 0.6 1.8 6,831 6,747 Divorced/ separated/ widowed 0.8 3.1 2.5 4.3 1,722 1,873 1.9 4.5 1.2 6.8 350 443 Male circumcision Circumcised na na na na na na 0.9 1.4 0.6 2.3 7,677 8,035 Not circumcised na na na na na na 1.7 1.8 0.7 3.0 528 626 Residence Urban 0.7 3.0 1.7 4.0 2,569 3,520 0.2 1.3 0.6 1.7 1,857 2,670 Rural 0.8 2.4 1.3 3.2 9,760 9,021 1.2 1.5 0.7 2.5 6,368 6,012 Region Tigray 0.7 3.2 1.6 4.0 833 1,316 0.5 0.9 0.5 1.3 489 786 Affar 0.5 0.8 0.5 1.4 121 1,093 1.4 4.0 1.8 4.3 73 672 Amhara 0.3 2.4 1.4 3.3 3,453 1,649 0.2 1.5 0.7 2.3 2,136 1,069 Oromiya 1.1 3.1 1.5 4.0 4,515 1,604 1.7 1.3 0.6 2.5 3,192 1,219 Somali 1.7 3.9 4.2 5.9 263 740 4.6 7.3 1.9 7.8 167 448 Benishangul- Gumuz 0.3 2.1 1.0 2.6 143 1,035 0.2 1.4 0.8 2.1 93 704 SNNP 0.6 1.5 0.6 2.2 2,308 1,466 0.5 1.6 0.6 2.2 1,488 999 Gambela 1.7 3.8 4.9 6.5 61 994 1.2 2.3 1.9 3.4 45 692 Harari 0.5 1.0 0.7 1.6 36 810 0.2 0.5 0.0 0.7 28 630 Addis Ababa 0.6 1.5 1.3 2.2 546 1,038 0.1 0.3 0.1 0.4 476 857 Dire Dawa 0.1 1.0 0.8 1.4 49 796 1.2 1.2 0.3 2.1 38 606 Education No education 0.8 2.6 1.4 3.4 7,869 7,681 0.8 1.2 0.8 2.2 3,117 3,021 Primary 0.8 2.3 1.4 3.4 3,482 3,507 1.1 1.8 0.6 2.5 3,781 3,762 Secondary 0.0 2.3 0.8 3.0 521 771 1.4 1.1 0.3 2.3 641 946 More than secondary 0.2 2.7 0.7 3.0 457 582 0.6 1.2 0.5 1.9 686 953 Wealth quintile Lowest 0.3 1.9 1.3 2.7 2,442 3,138 0.9 1.9 0.4 2.4 1,467 1,853 Second 0.9 2.6 1.1 3.2 2,425 1,946 1.2 1.1 0.9 2.4 1,530 1,261 Middle 1.3 2.7 1.4 3.7 2,374 1,812 1.1 1.4 0.9 2.4 1,566 1,263 Fourth 0.5 2.2 1.2 2.9 2,260 1,879 1.5 1.4 0.4 2.6 1,594 1,398 Highest 0.8 3.2 1.6 4.1 2,827 3,766 0.3 1.6 0.6 2.0 2,069 2,907 Total 15-49 0.7 2.5 1.3 3.4 12,328 12,541 0.9 1.5 0.6 2.3 8,225 8,682 50-59 na na na na na na 0.4 1.4 0.9 1.8 1,271 1,237 Total 15-59 na na na na na na 0.9 1.5 0.7 2.3 9,496 9,919 na = Not applicable Note: Total includes 21 men with information missing on circumcision. It is important for people experiencing symptoms of STIs to be able to recognise them and seek appropriate treatment. If respondents reported an STI or an STI symptom (i.e., discharge or sore or ulcer) in the past 12 months, they were asked questions about what they did about the illness or symptom. Figure 12.1 presents information on women and men who sought care from any source. Thirty-four percent, each, of women and men sought care for the STIs or symptoms of STIs from a clinic, hospital, or health professional. One percent of women and 6 percent of men sought advice or medicine from a shop, pharmacy, or drug vendor. Sixty-three percent of women and 56 percent of men who had STIs or STI symptoms in the 12 months preceding the survey did not seek any advice or treatment. HIV/AIDS-Related Knowledge, Attitudes, and Behaviour • 213 Figure 12.1 Women and Men Seeking Treatment for STIs EDHS 2011 34 1 1 63 34 6 2 56 Clinic/hospital private doctor/ other health Advice or medicine from shop/pharmacy/ Advice or treatment from any source No advice or treatment 0 10 20 30 40 50 60 70 P er ce nt ag e Percentage of Women Percentage of Men professional drug vendor 12.10 PREVALENCE OF MEDICAL INJECTIONS The overuse of injections in a health care setting can contribute to the transmission of blood- borne pathogens because it amplifies the effect of unsafe practices, such as reuse of injection equipment. The proportion of injections given with reused injection equipment is an important indicator in an initiative to prevent and control HIV/AIDS. Table 12.15 presents data on the prevalence of injections among respondents. Interviewers asked respondents if they had received an injection in the past 12 months and, if so, the total number of injections and the number received from a health worker. Respondents who had received one or more injections from a health worker were then asked if their most recent injection from a health worker was given using a syringe from a new, unopened package. It should be noted that self-administered medical injections (e.g., insulin for diabetes) were not included in the calculation. Women are more likely than men to report receiving medical injections (40 percent versus 24 percent). The percentage of women who received a medical injection in the past 12 months is highest among those age 20-39 (43-47 percent), most likely because of injections given to women during antenatal care or family planning visits. There is little difference among men’s age cohorts. Women and men in rural areas (36 and 20 percent, respectively) are less likely than those in urban areas (51 and 36 percent, respectively) to have had a medical injection within the past 12 months. Among regions women in Gambela and Addis Ababa are most likely to have received a medical injection (59 and 57 percent, respectively), while women in Somali are the least likely (18 percent). Similarly, the proportion of men who received a medical injection in the past 12 months is highest in Addis Ababa (54 percent) and lowest in Somali (12 percent). 21 4 • H IV /A ID S -R el at ed K no w le dg e, A tti tu de s, a nd B eh av io ur Ta bl e 12 .1 5 P re va le nc e of m ed ic al in je ct io ns P er ce nt ag e of w om en a nd m en a ge 1 5- 49 w ho r ec ei ve d at le as t o ne m ed ic al in je ct io n in th e pa st 1 2 m on th s, th e av er ag e nu m be r of m ed ic al in je ct io ns p er p er so n in th e pa st 1 2 m on th s, a nd a m on g th os e w ho r ec ei ve d a m ed ic al in je ct io n, th e pe rc en ta ge o f l as t m ed ic al in je ct io ns fo r w hi ch th e sy rin ge a nd n ee dl e w er e ta ke n fro m a n ew , u no pe ne d pa ck ag e, 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 W om en M en P er ce nt ag e w ho re ce iv ed a m ed ic al in je ct io n in th e pa st 12 m on th s A ve ra ge nu m be r o f m ed ic al in je ct io ns pe r p er so n in th e pa st 12 m on th s W ei gh te d nu m be r o f w om en U nw ei gh te d nu m be r o f w om en Fo r l as t in je ct io n, sy rin ge an d ne ed le ta ke n fro m a ne w , un op en ed pa ck ag e W ei gh te d nu m be r o f w om en re ce iv in g m ed ic al in je ct io ns in th e pa st 12 m on th s U nw ei gh te d nu m be r o f w om en re ce iv in g m ed ic al in je ct io ns in th e pa st 12 m on th s P er ce nt ag e w ho re ce iv ed a m ed ic al in je ct io n in th e pa st 12 m on th s A ve ra ge nu m be r o f m ed ic al in je ct io ns pe r p er so n in th e pa st 12 m on th s W ei gh te d nu m be r of m en U nw ei gh te d nu m be r of m en Fo r l as t in je ct io n, sy rin ge an d ne ed le ta ke n fro m a ne w , un op en ed pa ck ag e W ei gh te d nu m be r o f m en re ce iv in g m ed ic al in je ct io ns in th e pa st 12 m on th s U nw ei gh te d nu m be r o f m en re ce iv in g m ed ic al in je ct io ns in th e pa st 12 m on th s A ge 15 -2 4 38 .0 1. 3 6, 94 0 6, 85 7 98 .3 2, 63 8 2, 57 1 22 .9 0. 9 5, 33 2 5, 16 2 97 .3 1, 22 0 1, 38 6 15 -1 9 31 .5 1. 0 4, 00 9 3, 83 5 98 .1 1, 26 2 1, 22 3 21 .5 0. 8 3, 01 3 2, 83 2 96 .2 64 7 72 6 20 -2 4 47 .0 1. 7 2, 93 1 3, 02 2 98 .5 1, 37 6 1, 34 8 24 .7 1. 0 2, 31 9 2, 33 0 98 .5 57 3 66 0 25 -2 9 43 .6 1. 8 3, 14 7 3, 18 5 98 .3 1, 37 2 1, 32 0 25 .2 1. 2 2, 29 7 2, 27 4 97 .6 57 8 64 0 30 -3 9 42 .8 2. 0 3, 97 1 4, 05 8 96 .8 1, 69 9 1, 60 5 24 .5 1. 3 3, 13 2 3, 26 1 98 .1 76 6 86 2 40 -4 9 33 .4 1. 9 2, 45 7 2, 41 5 94 .8 82 0 77 0 23 .7 1. 3 2, 07 4 2, 17 1 97 .8 49 2 57 2 M ar ita l s ta tu s N ev er m ar rie d 31 .7 1. 0 4, 46 9 4, 41 3 98 .2 1, 41 8 1, 44 9 23 .7 0. 9 5, 60 0 5, 64 1 97 .2 1, 33 0 1, 58 4 E ve r h ad s e x 47 .8 1. 8 34 4 48 9 98 .3 16 4 24 5 30 .5 1. 3 1, 04 4 1, 49 2 98 .6 31 9 50 7 N ev er h ad s e x 30 .4 0. 9 4, 12 6 3, 92 4 98 .2 1, 25 4 1, 20 4 22 .2 0. 9 4, 55 5 4, 14 9 96 .8 1, 01 1 1, 07 7 M ar rie d/ liv in g to ge th er 44 .1 1. 9 10 ,2 87 10 ,2 04 97 .4 4, 54 1 4, 19 1 24 .0 1. 2 6, 87 2 6, 77 5 98 .1 1, 65 2 1, 75 6 D iv or ce d/ se pa ra te d/ w id ow ed 32 .4 1. 5 1, 75 8 1, 89 8 96 .0 57 0 62 6 20 .6 0. 9 36 3 45 2 94 .5 75 12 0 R es id en ce U rb an 51 .1 2. 3 3, 94 7 5, 32 9 98 .3 2, 01 6 2, 55 7 35 .8 1. 4 2, 88 2 3, 91 5 98 .9 1, 03 1 1, 47 9 R ur al 35 .9 1. 4 12 ,5 68 11 ,1 86 97 .1 4, 51 4 3, 70 9 20 .3 1. 0 9, 95 2 8, 95 3 97 .0 2, 02 5 1, 98 1 R eg io n Ti gr ay 40 .1 1. 2 1, 10 4 1, 72 8 97 .9 44 2 68 6 21 .5 0. 8 77 0 1, 23 5 97 .5 16 6 26 0 A ffa r 26 .2 1. 4 14 5 1, 29 1 98 .6 38 29 0 26 .1 1. 7 10 1 91 0 99 .9 26 20 9 A m ha ra 37 .5 1. 5 4, 43 3 2, 08 7 96 .3 1, 66 0 76 3 17 .8 0. 7 3, 48 1 1, 73 9 94 .6 62 1 29 8 O ro m i y a 41 .6 1. 8 6, 01 1 2, 13 5 97 .6 2, 49 8 87 1 23 .2 1. 3 4, 95 7 1, 88 9 99 .1 1, 15 2 43 4 S om al i 18 .4 0. 9 32 9 91 4 90 .8 61 16 0 12 .1 1. 1 24 5 65 3 95 .7 30 77 B en is ha n g ul -G um uz 42 .0 2. 3 17 4 1, 25 9 98 .0 73 49 4 35 .0 1. 9 13 8 1, 04 7 99 .4 48 35 4 S N N P 35 .9 1. 5 3, 23 6 2, 03 4 98 .8 1, 16 3 70 0 25 .7 1. 0 2, 30 7 1, 55 0 97 .2 59 3 38 2 G am be la 58 .5 4. 3 69 1, 13 0 99 .2 40 53 7 38 .7 2. 5 59 86 5 99 .8 23 28 4 H ar ar i 38 .4 1. 6 49 1, 10 1 98 .1 19 42 6 26 .8 1. 0 40 89 8 99 .5 11 24 4 A dd is A ba ba 57 .3 2. 2 89 6 1, 74 1 98 .4 51 3 98 2 54 .3 2. 1 68 2 1, 23 7 98 .5 37 0 68 1 D ire D aw a 33 .1 1. 3 69 1, 09 5 87 .1 23 35 7 29 .4 1. 4 53 84 5 99 .5 16 23 7 Ed uc at io n N o ed uc at io n 35 .8 1. 5 8, 39 4 8, 27 8 96 .3 3, 00 5 2, 62 7 17 .2 0. 9 3, 78 5 3, 65 9 97 .1 65 2 69 3 P rim ar y 40 .7 1. 6 6, 27 6 5, 85 8 98 .1 2, 55 2 2, 45 1 23 .5 1. 1 6, 81 3 6, 33 4 97 .1 1, 60 3 1, 68 7 S ec on da r y 51 .0 2. 2 1, 11 7 1, 39 5 99 .5 57 0 68 5 33 .8 1. 3 1, 29 6 1, 56 5 99 .0 43 8 58 1 M or e th an s ec on da ry 55 .4 2. 2 72 8 98 4 99 .0 40 3 50 3 38 .6 1. 5 94 0 1, 31 0 99 .1 36 2 49 9 W ea lth q ui nt ile Lo w es t 27 .7 1. 1 2, 98 6 3, 71 1 95 .4 82 6 90 1 13 .8 0. 7 2, 14 1 2, 56 3 96 .5 29 6 40 1 S ec on d 32 .9 1. 3 3, 04 1 2, 40 2 96 .6 1, 00 1 76 0 17 .6 0. 9 2, 36 2 1, 89 1 94 .9 41 6 38 6 M id dl e 35 .5 1. 5 3, 03 1 2, 26 8 96 .9 1, 07 7 79 0 21 .2 1. 1 2, 45 4 1, 93 5 97 .3 52 1 44 4 Fo ur th 44 .2 1. 7 3, 21 5 2, 50 5 98 .3 1, 42 2 1, 06 8 24 .4 1. 2 2, 68 3 2, 20 3 97 .4 65 4 61 3 H i g he st 52 .0 2. 4 4, 24 2 5, 62 9 98 .4 2, 20 4 2, 74 7 36 .6 1. 5 3, 19 4 4, 27 6 99 .1 1, 17 0 1, 61 6 To ta l 1 5- 49 39 .5 1. 6 16 ,5 15 16 ,5 15 97 .5 6, 53 0 6, 26 6 23 .8 1. 1 12 ,8 34 12 ,8 68 97 .6 3, 05 6 3, 46 0 50 -5 9 na na na na na na na 26 .7 1. 6 1, 27 6 1, 24 2 96 .3 34 0 32 7 To ta l 1 5- 59 na na na na na na na 24 .1 1. 1 14 ,1 10 14 ,1 10 97 .5 3, 39 6 3, 78 7 na = N ot a pp lic ab le N ot e: M ed ic al in je ct io ns a re th os e gi ve n by a d oc to r, nu rs e, p ha rm ac is t, de nt is t, or o th er h ea lth w or ke r. 214 • HIV/AIDS-Related Knowledge, Attitudes, and Behaviour HIV/AIDS-Related Knowledge, Attitudes, and Behaviour • 215 The great majority of recent medical injections received by women and men (both 98 percent) were given with a syringe taken from a newly opened package. Variation by sociodemographic characteristics is minimal, indicating that use of single-use disposable syringes is approaching universal levels. 12.11 HIV/AIDS KNOWLEDGE AND SEXUAL BEHAVIOUR AMONG YOUTH This section addresses HIV/AIDS-related knowledge and sexual behaviour among youth, age 15-24. The period between the initiation of sexual activity and marriage is often a time of sexual experimentation and may involve risky behaviours. Comprehensive knowledge among youth of HIV/AIDS transmission and prevention as well as knowledge of where to obtain condoms is analysed below. Issues such as age at first sex, age difference between partners, sex related to alcohol use, and voluntary counselling and testing for HIV also are covered in this section. 12.11.1 HIV/AIDS-Related Knowledge Among Young Adults Knowledge of how HIV is transmitted is crucial to enable people to avoid HIV infection, especially for young people, who are often at greater risk because they may have shorter relationships and thus more partners or may engage in other risky behaviours. Table 12.16 shows the level of comprehensive knowledge about AIDS among young people, measured by their responses to prompted questions. As discussed, comprehensive knowledge is defined as: (1) one’s knowledge that people can reduce their chances of getting the AIDS virus by having sex with only one uninfected, faithful partner and by using condoms consistently; (2) knowing that a healthy-looking person can have HIV; and (3) knowing that HIV cannot be transmitted by mosquito bites or by supernatural means. About one-fourth of women (24 percent) and one-third of men (34 percent) age 15-24 have comprehensive knowledge about AIDS. Never-married young adults who have ever had sex (41 percent of women and 44 percent of men) are the most likely to have comprehensive knowledge about AIDS. Urban youth (38 percent of women and 49 percent of men) are more likely than rural youth (19 percent of women and 30 percent of men) to have comprehensive AIDS knowledge. The level of knowledge increases steadily with education. For example, 7 percent of young women with no education have comprehensive knowledge about AIDS, compared with 54 percent of young women with more than secondary education. 216 • HIV/AIDS-Related Knowledge, Attitudes, and Behaviour Table 12.16 Comprehensive knowledge about AIDS and knowledge of a source of condoms among young people Percentage of young women and young men age 15-24 with comprehensive knowledge about AIDS and percentage with knowledge of a source of condoms, by background characteristics, Ethiopia 2011 Background characteristic Women Men Percentage with comprehensive knowledge of AIDS1 Percentage who know a condom source2 Weighted number of women Unweighted number of women Percentage with comprehensive knowledge of AIDS1 Percentage who know a condom source2 Weighted number of men Unweighted number of men Age 15-19 24.0 40.8 4,009 3,835 31.8 69.4 3,013 2,832 15-17 23.5 40.1 2,454 2,341 30.7 64.6 1,870 1,726 18-19 24.9 41.8 1,555 1,494 33.6 77.2 1,144 1,106 20-24 23.6 45.1 2,931 3,022 37.4 79.3 2,319 2,330 20-22 22.9 45.4 1,954 2,020 34.3 75.5 1,543 1,522 23-24 25.1 44.5 977 1,002 43.4 86.9 776 808 Marital status Never married 28.9 50.1 4,022 3,866 35.5 74.8 4,622 4,446 Ever had sex 40.5 85.7 219 285 44.0 93.4 587 804 Never had sex 28.3 48.1 3,803 3,581 34.2 72.0 4,035 3,642 Ever married 16.8 32.3 2,918 2,991 26.1 66.8 710 716 Residence Urban 37.7 75.8 1,877 2,448 49.0 95.0 1,218 1,561 Rural 18.7 30.3 5,063 4,409 29.8 67.4 4,114 3,601 Education No education 7.0 12.5 1,809 1,913 11.9 43.9 803 765 Primary 25.1 44.7 3,988 3,652 33.7 73.8 3,497 3,178 Secondary 42.3 78.2 750 786 51.7 95.7 712 751 More than secondary 53.5 92.5 393 506 57.0 98.8 320 468 Total 15-24 23.9 42.6 6,940 6,857 34.2 73.7 5,332 5,162 1 Comprehensive knowledge means knowing that consistent use of condoms during sexual intercourse and having just one uninfected faithful partner can reduce the chance of getting 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 components of comprehensive knowledge are presented in Tables 12.2, 12.3.1, and 12.3.2. 2 For this table the following responses are not considered sources for condoms: friends, family members, and home. Because of the important role that condoms play in combating the transmission of HIV, respondents were asked if they knew where condoms could be obtained. Only responses about ‘formal’ sources were counted; friends, family members, and home were not included. As shown in Table 12.16, young men are more likely than young women to know where to obtain condoms (74 percent versus 43 percent). Young women and men in urban areas are more likely than those in rural areas to know a source of condoms. Consistent with patterns for other indicators, respondents with more education are more likely than those with no or little education to know a source of condoms. 12.11.2 Age at First Sexual Intercourse Age at first sex is an important indicator of both exposure to the risk of pregnancy and exposure to STIs. Young people who initiate sex at an early age face a higher risk of becoming pregnant or contracting an STI than young people who delay initiation of sexual activity. Consistent use of condoms reduces these risks. Table 12.17 shows the proportions of women and men age 15-24 who had sex before age 15 and before age 18. Eleven percent of young women and 1 percent of young men had had sexual intercourse before age 15; 39 percent of young women and 13 percent of young men had had sex before age 18. Among young women the older age cohorts are more likely to have had sex before age 15 or age 18 than those who reached those age milestones more recently. Ever-married young women are much more likely than never-married young women to have had sexual intercourse before age 15 or 18. Twenty-six and 64 percent of ever-married young women had sexual intercourse before age 15 and 18, respectively, compared with less than 1 percent and 3 percent, respectively, of never-married women. Among young women a higher proportion of rural residents have had sex before age 15 and HIV/AIDS-Related Knowledge, Attitudes, and Behaviour • 217 before age 18 than their urban counterparts. Education has an inverse relationship with sexual debut. Young women with no schooling are considerably more likely than those who go to school to have had sex by age 15 (26 percent compared with 7 percent or less). Variation in young men’s sexual debut across background characteristics are small, except for variation associated with marital status. Like women, ever-married young men are much more likely than never-married men to have had sexual intercourse before age 18. 21 8 • H IV /A ID S -R el at ed K no w le dg e, A tti tu de s, a nd B eh av io ur Ta bl e 12 .1 7 A ge a t f irs t s ex ua l i nt er co ur se a m on g yo un g pe op le P er ce nt ag e of y ou ng w om en a nd o f yo un g m en a ge 1 5- 24 w ho h ad s ex ua l i nt er co ur se b ef or e ag e 15 a nd p er ce nt ag e of y ou ng w om en a nd o f yo un g m en a ge 1 8- 24 w ho h ad s ex ua l in te rc ou rs e be fo re a ge 1 8, 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 W om en M en W om en a ge 1 5- 24 W om en a ge 1 8- 24 M en a ge 1 5- 24 M en a ge 1 8- 24 P er ce nt ag e w ho h ad se xu al in te rc ou rs e be fo re ag e 15 W ei gh te d nu m be r o f w om en U nw ei gh te d nu m be r o f w om en P er ce nt ag e w ho h ad se xu al in te rc ou rs e be fo re ag e 18 W ei gh te d nu m be r o f w om en U nw ei gh te d nu m be r o f w om en P er ce nt ag e w ho h ad se xu al in te rc ou rs e be fo re ag e 15 W ei gh te d nu m be r o f m en U nw ei gh te d nu m be r o f m en P er ce nt ag e w ho h ad se xu al in te rc ou rs e be fo re ag e 18 W ei gh te d nu m be r of m en U nw ei gh te d nu m be r of m en A ge 15 -1 9 7. 1 4, 00 9 3, 83 5 na na na 1. 2 3, 01 3 2, 83 2 na na na 15 -1 7 5. 7 2, 45 4 2, 34 1 na na na 1. 5 1, 87 0 1, 72 6 na na na 18 -1 9 9. 4 1, 55 5 1, 49 4 32 .2 1, 55 5 1, 49 4 0. 7 1, 14 4 1, 10 6 10 .8 1, 14 4 1, 10 6 20 -2 4 16 .0 2, 93 1 3, 02 2 42 .2 2, 93 1 3, 02 2 1. 3 2, 31 9 2, 33 0 14 .0 2, 31 9 2, 33 0 2 0- 22 14 .9 1, 95 4 2, 02 0 41 .3 1, 95 4 2, 02 0 1. 0 1, 54 3 1, 52 2 13 .9 1, 54 3 1, 52 2 2 3- 24 18 .3 97 7 1, 00 2 43 .9 97 7 1, 00 2 1. 9 77 6 80 8 14 .2 77 6 80 8 M ar ita l s ta tu s N ev er m ar rie d 0. 3 4, 02 2 3, 86 6 3. 4 1, 87 7 1, 85 8 1. 0 4, 62 2 4, 44 6 8. 6 2, 76 8 2, 73 6 E ve r m ar rie d 25 .5 2, 91 8 2, 99 1 64 .1 2, 60 9 2, 65 8 3. 0 71 0 71 6 30 .4 69 4 70 0 K no w s co nd om s ou rc e1 Ye s 6. 0 2, 95 8 3, 19 1 27 .1 1, 97 3 2, 19 5 1. 4 3, 93 0 3, 84 9 13 .3 2, 72 2 2, 73 1 N o 14 .5 3, 98 2 3, 66 6 47 .8 2, 51 3 2, 32 1 0. 9 1, 40 2 1, 31 3 11 .5 74 0 70 5 R es id en ce U rb an 5. 8 1, 87 7 2, 44 8 24 .0 1, 28 7 1, 72 0 0. 9 1, 21 8 1, 56 1 12 .6 85 3 1, 15 7 R ur al 12 .8 5, 06 3 4, 40 9 44 .6 3, 19 9 2, 79 6 1. 4 4, 11 4 3, 60 1 13 .0 2, 60 9 2, 27 9 Ed uc at io n N o ed uc at io n 26 .2 1, 80 9 1, 91 3 61 .5 1, 48 8 1, 51 2 1. 1 80 3 76 5 13 .6 56 3 54 1 P rim ar y 6. 6 3, 98 8 3, 65 2 33 .5 2, 04 2 1, 93 8 1. 4 3, 49 7 3, 17 8 13 .3 2, 00 6 1, 82 3 S ec on da ry 1. 5 75 0 78 6 17 .4 58 9 59 2 0. 5 71 2 75 1 9. 4 59 0 61 7 M or e th an s ec on da ry 2. 1 39 3 50 6 9. 5 36 7 47 4 1. 6 32 0 46 8 16 .0 30 3 45 5 To ta l 10 .9 6, 94 0 6, 85 7 38 .7 4, 48 6 4, 51 6 1. 2 5, 33 2 5, 16 2 12 .9 3, 46 2 3, 43 6 na = N ot a pp lic ab le 1 Fo r t hi s ta bl e th e fo llo w in g re sp on se s ar e no t c on si de re d a so ur ce fo r c on do m s: fr ie nd s, fa m ily m em be rs ,a nd h om e. 218 • HIV/AIDS-Related Knowledge, Attitudes, and Behaviour HIV/AIDS-Related Knowledge, Attitudes, and Behaviour • 219 The percentages of young women who have had sexual intercourse before ages 15 and 18 have decreased somewhat since the 2005 EDHS, while the percentages among young men have remained almost the same (Figure 12.2). Figure 12.2 Trends in Age at First Sexual Intercourse EDHS 2011 11 2 37 10 7 1 32 11 Percentage of women 15-19 who had Percentage of men 15-19 who had Percentage of women 18-19 who had Percentage of men 18-19 who had 0 10 20 30 40 50 Percentage 2005 EDHS 2011 EDHS sexual intercourse before exact age 15 sexual intercourse before exact age 15 sexual intercourse before exact age 18 sexual intercourse before exact age 18 12.11.3 Abstinence and Premarital Sex The period between age at first sex and age at marriage is often a time of sexual experimentation. Unfortunately, in the era of HIV/AIDS, it can also be a risky time. HIV control programmes advocate consistent condom use to reduce the risk of sexual transmission of HIV. Table 12.18 presents information on premarital sexual intercourse and condom use among never-married Ethiopian youth, age 15-24. Ninety-five percent of never-married young women and 87 percent of never-married young men have never had sexual intercourse. Abstinence rates are highest among the youngest respondents (age 15-17), those that do not know a condom source, and rural and less educated young respondents. Conversely, a higher percentage of respondents age 23-24, those living in urban areas, those that know a condom source, and respondents with more than secondary education report that they had sexual intercourse in the past 12 months. Overall, 4 percent of never-married young women and 8 percent of never-married young men had sex in the past 12 months. Among those who had sex in the past year, 37 percent of women and 68 percent of men reported using a condom during their last sexual intercourse. Due to the small number of women who report having had sex in the past year and using a condom at last sex, caution should be used when interpreting these data by background characteristics. Among men condom use is higher among urban than rural respondents and increases with education. 22 0 • H IV /A ID S -R el at ed K no w le dg e, A tti tu de s, a nd B eh av io ur Ta bl e 12 .1 8 P re m ar ita l s ex ua l i nt er co ur se a nd c on do m u se d ur in g pr em ar ita l s ex ua l i nt er co ur se a m on g yo ut h A m on g ne ve r-m ar rie d w om en a nd m en a ge 1 5- 24 , t he p er ce nt ag e w ho h av e ne ve r h ad s ex ua l i nt er co ur se , t he p er ce nt ag e w ho h ad s ex ua l i nt er co ur se in th e pa st 1 2 m on th s, a nd , a m on g th os e w ho h ad p re m ar ita l se xu al in te rc ou rs e in th e pa st 1 2 m on th s, th e pe rc en ta ge w ho u se d a co nd om a t t he la st s ex ua l i nt er co ur se , 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 N ev er -m ar rie d w om en a ge 1 5- 24 N ev er -m ar rie d m en a ge 1 5- 24 P er ce nt ag e w ho h av e ne ve r h ad se xu al in te rc ou rs e P er ce nt ag e w ho h ad se xu al in te rc ou rs e in th e pa st 12 m on th s W ei gh te d nu m be r o f ne ve r m ar rie d w om en U nw ei gh te d nu m be r of n ev er m ar rie d w om en A m on g w om en w ho h ad s ex ua l in te rc ou rs e in th e pa st 1 2 m on th s: P er ce nt ag e w ho h av e ne ve r h ad se xu al in te rc ou rs e P er ce nt ag e w ho h ad se xu al in te rc ou rs e in th e pa st 12 m on th s W ei gh te d nu m be r o f ne ve r m ar rie d m en U nw ei gh te d nu m be r o f ne ve r m ar rie d m en A m on g m en w ho h ad s ex ua l in te rc ou rs e in th e pa st 1 2 m on th s: P er ce nt ag e w ho u se d a co nd om a t la st s ex ua l in te rc ou rs e W ei gh te d nu m be r o f w om en U nw ei gh te d nu m be r o f w om en P er ce nt ag e w ho u se d a co nd om a t la st s ex ua l in te rc ou rs e W ei gh te d nu m be r of m en U nw ei gh te d nu m be r of m en A ge 15 -1 9 97 .3 1. 9 3, 08 7 2, 88 7 45 .5 58 86 93 .8 3. 8 2, 94 1 2, 75 3 60 .9 11 1 18 5 15 -1 7 98 .5 1. 0 2, 14 6 2, 00 8 (6 5. 7) 21 42 96 .4 2. 5 1, 85 4 1, 71 0 44 .6 47 73 18 -1 9 94 .5 4. 0 94 1 87 9 (3 4. 1) 37 44 89 .3 5. 9 1, 08 7 1, 04 3 72 .9 64 11 2 20 -2 4 85 .4 9. 2 93 5 97 9 30 .9 86 11 4 76 .0 14 .7 1, 68 1 1, 69 3 71 .3 24 8 35 1 2 0- 22 86 .8 8. 5 71 4 72 6 37 .3 61 74 80 .2 11 .6 1, 20 6 1, 19 1 70 .3 14 0 20 3 2 3- 24 81 .2 11 .5 22 1 25 3 (1 5. 7) 26 40 65 .3 22 .7 47 4 50 2 72 .6 10 8 14 8 K no w s co nd om so ur ce 1 Ye s 90 .7 6. 3 2, 01 6 2, 11 9 39 .2 12 8 17 6 84 .1 10 .0 3, 45 5 3, 35 8 70 .0 34 5 49 4 N o 98 .4 0. 9 2, 00 6 1, 74 7 * 17 24 96 .7 1. 2 1, 16 7 1, 08 8 (1 9. 7) 14 42 R es id en ce U rb an 89 .6 6. 4 1, 36 6 1, 76 9 39 .2 87 13 7 79 .1 12 .6 1, 15 2 1, 45 3 83 .9 14 5 25 7 R ur al 97 .1 2. 2 2, 65 7 2, 09 7 33 .2 57 63 90 .0 6. 2 3, 47 0 2, 99 3 57 .4 21 4 27 9 Ed uc at io n N o ed uc at io n 97 .3 1. 2 41 4 50 4 * 5 9 93 .5 4. 2 58 4 57 5 (2 6. 8) 24 48 P rim ar y 96 .4 2. 4 2, 75 5 2, 37 4 47 .9 66 10 4 89 .9 5. 8 3, 07 4 2, 76 1 61 .4 17 9 26 2 S ec on da ry 92 .2 5. 2 56 9 59 7 (2 7. 9) 29 36 81 .7 12 .0 66 9 68 6 77 .0 80 12 1 M or e th an se co nd ar y 77 .4 15 .7 28 5 39 1 (2 6. 3) 45 51 60 .1 25 .6 29 5 42 4 87 .9 75 10 5 To ta l 94 .6 3. 6 4, 02 2 3, 86 6 36 .8 14 5 20 0 87 .3 7. 8 4, 62 2 4, 44 6 68 .1 35 9 53 6 1 F or th is ta bl e th e fo llo w in g re sp on se s ar e no t c on si de re d a so ur ce fo r c on do m s: fr ie nd s, fa m ily m em be rs ,a nd h om e. 220 • HIV/AIDS-Related Knowledge, Attitudes, and Behaviour HIV/AIDS-Related Knowledge, Attitudes, and Behaviour • 221 The proportion of never-married young men, age 15-24, who used a condom at their last sexual intercourse has increased since the 2005 EDHS from 50 percent to 68 percent. 12.11.4 Multiple Partnerships Among Young Adults Table 12.19.1 and Table 12.19.2 present information on young people, age 15-24, who had two or more sexual partners during the 12 months preceding the survey and, among those with two or more partners, those who used a condom during last sex. Table 12.19.1 shows that less than 1 percent of women age 15-24 had sexual intercourse with more than one partner in the past 12 months. Due to the small percentages, there is no variation in the prevalence of multiple partners by background characteristics. Among women age 15-24 who reported two or more sexual partners in the past 12 months, 62 percent reported using a condom at last intercourse (data not shown). Table 12.19.2 shows that 1 percent of men age 15-24 had sexual intercourse with two or more partners in the past 12 months. Again, due to the small percentages, the variation by background characteristics is not notable. Among young men who had one or more partners in the past year, 47 percent reported using a condom at last sexual intercourse. Table 12.19.1 Multiple sexual partners in the past 12 months among young people: Women Percentage of young women age 15-24 who had sexual intercourse with more than one sexual partner in the past 12 months, by background characteristics, Ethiopia 2011 Background characteristic Percentage who had 2+ partners in the past 12 months Weighted number of women Unweighted number of women Age 15-19 0.3 4,009 3,835 15-17 0.1 2,454 2,341 18-19 0.5 1,555 1,494 20-24 0.6 2,931 3,022 20-22 0.8 1,954 2,020 23-24 0.1 977 1,002 Marital status Never married 0.3 4,022 3,866 Ever married 0.6 2,918 2,991 Knows condom source1 Yes 0.7 2,958 3,191 No 0.1 3,982 3,666 Residence Urban 0.7 1,877 2,448 Rural 0.3 5,063 4,409 Education No education 0.4 1,809 1,913 Primary 0.5 3,988 3,652 Secondary 0.0 750 786 More than secondary 0.0 393 506 Total 15-24 0.4 6,940 6,857 1 For this table the following responses are not considered a source for condoms: friends, family members, and home. 222 • HIV/AIDS-Related Knowledge, Attitudes, and Behaviour Table 12.19.2 Multiple sexual partners in the past 12 months among young people: Men Among all young men age 15-24, the percentage who had sexual intercourse with more than one sexual partner in the past 12 months and, among those having more than one partner in the past 12 months, the percentage reporting that a condom was used at last intercourse, by background characteristics, Ethiopia 2011 Background characteristic Among all men age 15-24: Among men age 15-24 who had 2+ partners in the past 12 months: Percentage who had 2+ partners in the past 12 months Weighted number of men Unweighted number of men Percentage who reported using a condom at last intercourse Weighted number of men Unweighted number of men Age 15-19 0.5 3,013 2,832 * 14 24 15-17 0.3 1,870 1,726 * 6 10 18-19 0.7 1,144 1,106 * 8 14 20-24 1.6 2,319 2,330 36.9 37 73 20-22 1.2 1,543 1,522 (26.1) 18 38 23-24 2.5 776 808 (46.9) 19 35 Marital status Never married 0.8 4,622 4,446 60.6 38 73 Ever married 1.9 710 716 * 13 24 Knows condom source1 Yes 1.2 3,930 3,849 51.3 48 88 No 0.3 1,402 1,313 * 4 9 Residence Urban 2.0 1,218 1,561 (81.3) 25 47 Rural 0.7 4,114 3,601 15.8 27 50 Education No education 1.0 803 765 * 8 14 Primary 0.7 3,497 3,178 (27.1) 25 43 Secondary 1.4 712 751 (93.6) 10 27 More than secondary 2.5 320 468 * 8 13 Total 15-24 1.0 5,332 5,162 47.2 52 97 Note: Figures in parentheses are based on 25-49 unweighted cases. An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. 1 For this table the following responses are not considered a source for condoms: friends, family members, and home. 12.11.5 Age-mixing in Sexual Relationships In many societies young women have sexual relationships with men who are considerably older than they are. This practice can contribute to the spread of HIV and other STIs because older men are more likely to have been exposed to these diseases. Also, using preventive strategies, such as negotiating safer sex, is more difficult when a woman’s partner is much older. To examine age- mixing, the 2011 EDHS asked respondents who had had sex in the 12 months preceding the survey to give their partner’s age. The results are presented in Table 12.20. Overall, 21 percent of women age 15-19 who had sexual intercourse in the past 12 months had sex with a man ten or more years older than they were. Very few young men, less than 1 percent, had sex with women who were ten or more years older. Age-mixing in sexual relationships varies little by background characteristics. Young women age 15-17, those who ever married, women in urban areas, and those with primary or no education are more likely than other women to have had sex with a man ten years or more older than they are. HIV/AIDS-Related Knowledge, Attitudes, and Behaviour • 223 Table 12.20 Age-mixing in sexual relationships among women and men age 15-19 Among women and men 15-19 who had sexual intercourse in the past 12 months, percentage who had sexual intercourse with a partner who was 10 or more years older than they, by background characteristics, Ethiopia 2011 Background characteristic Women 15-19 who had sexual intercourse in the past 12 months Men 15-19 who had sexual intercourse in the past 12 months Percentage who had sexual intercourse with a man 10+ years older Weighted number of women Unweighted number of women Percentage who had sexual intercourse with a woman 10+ years older Weighted number of men Unweighted number of men Age 15-17 24.6 277 319 0.2 50 79 18-19 19.4 587 590 0.1 110 164 Marital status Never married 7.2 58 86 0.2 111 185 Ever married 22.1 806 823 0.0 48 58 Knows condom source1 Yes 18.8 240 301 0.1 138 202 No 21.9 625 608 (0.4) 22 41 Residence Urban 23.5 121 163 0.0 44 77 Rural 20.7 743 746 0.2 115 166 Education No education 21.4 356 355 * 6 15 Primary 21.9 446 494 0.1 120 176 Secondary 16.6 48 50 (0.0) 25 42 More than secondary * 14 10 * 8 10 Total 21.1 865 909 0.1 159 243 Note; Figures in parentheses are based on 25-49 unweighted cases. An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. 1 For this table the following responses are not considered a source for condoms: friends, family members, and home. 12.11.6 Recent HIV Testing Among Youth Knowledge of one’s HIV serostatus can motivate a person to protect himself/herself or to practise safer sexual behaviour to avoid transmitting the virus to others. It is particularly important to measure the coverage of HIV testing among youths, not only because of their vulnerability, but also because they in particular may encounter obstacles to counselling and testing. The 2011 EDHS asked respondents age 15-24 who had had sexual intercourse in the past 12 month whether they had been tested for HIV and received their test results in the past 12 months. Table 12.21 shows these data. Nationally, one in every four young women, age 15-24, (25 percent) and about three in every ten young men, age 15-24, (28 percent) who had had sexual intercourse in the past 12 months had been tested for HIV in the past 12 months and received the results of the test. These percentages reflect a dramatic increase since the 2005 EDHS, when 2 percent of young women and 6 percent of young men who had had sexual intercourse in the past 12 months had been tested for HIV and received results. A large difference is observed in HIV testing by marital status for both young women and young men. For instance, 58 percent of never-married women were tested for HIV in the past 12 months and received their test results, compared with 23 percent of ever-married ones. This difference is less pronounced among young men (38 percent compared with 22 percent). Urban youth, those who know a condom source, and youth with secondary or higher education are much more likely than other youth to have been tested for HIV and received the results over the past 12 months. 224 • HIV/AIDS-Related Knowledge, Attitudes, and Behaviour Table 12.21 Recent HIV testing among youth Among young women and young men age 15-24 who have had sexual intercourse in the past 12 months, the percentage who have had an HIV test in the past 12 months and received the results of the test, by background characteristics, Ethiopia 2011 Background characteristic Among women age 15-24 who have had sexual intercourse in the past 12 months: Among men age 15-24 who have had sexual intercourse in the past 12 months: Percentage who have been tested for HIV and received results in the past 12 months Weighted number of women Unweighted number of women Percentage who have been tested for HIV and received results in the past 12 months Weighted number of men Unweighted number of men Age 15-19 23.9 865 909 26.9 159 243 15-17 21.4 277 319 29.4 50 79 18-19 25.1 587 590 25.8 110 164 20-24 25.7 1,914 1,916 28.0 846 947 20-22 24.0 1,190 1,215 23.2 454 513 23-24 28.6 724 701 33.4 392 434 Marital status Never married 58.4 145 200 37.7 359 536 Ever married 23.3 2,634 2,625 22.3 647 654 Knows condom source1 Yes 45.1 968 1,109 32.5 784 950 No 14.5 1,810 1,716 11.3 221 240 Residence Urban 57.8 539 719 42.6 210 357 Rural 17.3 2,239 2,106 23.9 796 833 Education No education 10.4 1,272 1,260 20.5 218 216 Primary 32.3 1,180 1,215 20.9 566 646 Secondary 55.0 183 195 56.0 123 182 More than secondary 59.5 144 155 48.9 98 146 Total 25.2 2,778 2,825 27.8 1,006 1,190 1 For this table the following responses are not considered a source for condoms: friends, family members, and home. 12.12 USE OF ALCOHOL OR CHAT DURING SEXUAL INTERCOURSE Sexual intercourse when one or both partners are under the influence of alcohol is risky because the couple may not be fully aware of their actions, which may lead to failure to use a condom. All eligible women and men who have ever had sex were asked if they or their partner drank alcohol or chewed chat the last time they had sexual intercourse in the past 12 months. Tables 12.22.1 and Table 12.22.2 show that 1 percent of women and 4 percent of men age 15-49 drank alcohol the last time that they had sex in the past 12 months. By comparison, 5 percent of women chewed chat the last time that they had sex during the past 12 months as did 17 percent of men. Chat chewing is more common among ever-married respondents, those who live in rural areas, and respondents in Harari and Dire Dawa. For both women and men, chat use at last sexual intercourse tends to decrease with an increase in education. The relationship between chat use at last sex and wealth does not reveal a clear pattern. HIV/AIDS-Related Knowledge, Attitudes, and Behaviour • 225 Table 12.22.1 Use of alcohol and/or chat at last sexual intercourse: Women Percentage of women age 15-49 who drank alcohol or chewed chat the last time they had sexual intercourse in the past 12 months, by background characteristics, Ethiopia 2011 Background characteristic Percentage who drank alcohol at last sexual intercourse Percentage who report sexual partner drank alcohol at last sexual intercourse Percentage who chewed chat1 at last sexual intercourse Percentage who report sexual partner chewed chat1 at last sexual intercourse Weighted number of women Unweighted number of women Age 15-24 0.6 2.6 3.6 13.8 2,778 2,825 15-19 0.6 2.7 4.0 12.5 865 909 20-24 0.7 2.6 3.4 14.4 1,914 1,916 25-29 0.7 3.2 4.9 16.2 2,642 2,569 30-39 0.6 5.5 5.5 13.9 3,370 3,307 40-49 0.6 4.1 5.7 15.1 1,849 1,698 Marital status Never married 1.6 5.4 2.3 7.1 202 300 Married/living together 0.5 3.6 5.0 14.9 9,935 9,601 Divorced/separated/ widowed 2.6 9.7 4.6 13.2 503 498 Residence Urban 0.8 4.6 3.5 10.3 2,025 2,682 Rural 0.6 3.8 5.2 15.7 8,615 7,717 Region Tigray 1.0 2.4 0.3 1.1 678 1,071 Affar 0.3 0.4 4.0 16.6 99 912 Amhara 0.3 1.5 1.8 3.6 2,908 1,393 Oromiya 0.8 5.1 9.5 27.1 4,024 1,420 Somali 0.0 1.3 5.1 41.9 227 641 Benishangul-Gumuz 1.7 3.6 0.3 2.4 124 902 SNNP 0.7 6.4 2.4 8.2 2,064 1,316 Gambela 7.0 18.1 4.8 16.2 46 679 Harari 0.7 2.2 26.6 69.7 29 665 Addis Ababa 0.4 2.2 0.8 5.8 400 746 Dire Dawa 0.7 2.4 20.4 62.4 40 654 Education No education 0.6 4.2 5.3 15.5 6,815 6,439 Primary 0.8 4.1 4.9 14.5 3,034 2,906 Secondary 0.4 1.7 2.0 8.5 411 595 More than secondary 0.0 0.7 1.6 7.2 379 459 Wealth quintile Lowest 0.3 2.9 3.4 12.8 2,102 2,557 Second 0.4 4.1 6.1 16.4 2,148 1,675 Middle 0.6 3.8 6.1 15.3 2,115 1,597 Fourth 0.8 5.2 4.5 16.8 1,983 1,636 Highest 1.0 3.8 4.4 12.2 2,292 2,934 Total 0.6 3.9 4.9 14.6 10,640 10,399 1 Refers to those who chewed chat any time during the day they had sexual intercourse. 226 • HIV/AIDS-Related Knowledge, Attitudes, and Behaviour Table 12.22.2 Use of alcohol and/or chat at last sexual intercourse: Men Percentage of women age 15-49 who drank alcohol or chewed chat the last time they had sexual intercourse in the past 12 months, by background characteristics, Ethiopia 2011 Background characteristic Percentage who drank alcohol at last sexual intercourse Percentage who report sexual partner drank alcohol at last sexual intercourse Percentage who chewed chat1 at last sexual intercourse Percentage who report sexual partner chewed chat1 at last sexual intercourse Weighted number of men Unweighted number of men Age 15-24 3.1 1.3 14.7 1.8 1,006 1,190 15-19 2.6 2.4 16.5 6.3 159 243 20-24 3.2 1.1 14.3 1.0 846 947 25-29 4.0 0.5 16.0 3.4 1,684 1,652 30-39 3.3 0.3 17.3 2.8 2,876 2,872 40-49 3.8 0.1 16.9 2.9 1,976 1,999 Marital status Never married 5.4 2.8 11.0 3.0 602 924 Married/living together 3.1 0.2 17.0 2.8 6,765 6,590 Divorced/separated/ widowed 13.1 1.8 18.9 2.8 175 199 Residence Urban 3.4 0.9 12.6 1.5 1,559 2,154 Rural 3.6 0.3 17.6 3.2 5,984 5,559 Region Tigray 2.5 0.8 1.2 0.3 447 719 Affar 3.0 1.4 19.4 3.1 66 613 Amhara 2.1 0.5 2.7 0.5 1,978 993 Oromiya 4.3 0.4 30.5 5.9 2,976 1,135 Somali 0.0 0.0 38.6 2.3 149 401 Benishangul-Gumuz 2.8 0.2 2.8 0.0 87 657 SNNP 4.8 0.3 9.4 0.8 1,370 925 Gambela 8.3 4.7 16.1 2.5 37 561 Harari 3.9 1.4 74.6 13.5 24 531 Addis Ababa 3.0 0.7 9.5 1.0 376 671 Dire Dawa 2.2 1.6 67.0 14.2 31 507 Education No education 3.1 0.3 17.2 3.7 2,957 2,818 Primary 4.3 0.3 17.9 2.5 3,503 3,389 Secondary 1.8 0.9 13.4 2.2 527 755 More than secondary 2.6 1.4 7.6 1.5 555 751 Wealth quintile Lowest 3.1 0.3 13.4 3.1 1,402 1,719 Second 3.8 0.3 17.3 3.7 1,462 1,176 Middle 3.9 0.4 18.2 2.7 1,472 1,181 Fourth 3.7 0.2 19.6 2.3 1,453 1,268 Highest 3.2 0.8 14.6 2.6 1,753 2,369 Total 15-49 3.5 0.4 16.6 2.9 7,542 7,713 50-59 5.6 0.3 14.0 3.6 1,172 1,110 Total 15-59 3.8 0.4 16.2 3.0 8,714 8,823 1 Refers to those who chewed chat any time during the day they had sexual intercourse. 12.13 SHARING OF HIV TEST RESULTS AMONG COUPLES Sharing of HIV test results among couples is important. Partners can support each other in cases where one or both of them are HIV positive. When one of the partners is positive, measures can be taken to prevent the other one from being infected. When they are both HIV negative, this knowledge encourages them to practise safe sex in order to remain HIV negative. Currently married women and men age 15-49 who were ever tested for HIV and received the result of the last HIV test were asked whether they had shared these results with their partner. Table 12.23 shows that currently married men were slightly more likely than currently married women to have been tested and to have shared their HIV test results with their partners (36 percent versus 32 percent). Respondents in urban areas were much more likely (66 percent of women and 59 percent of men) to have been tested and to have shared their HIV test results with their partners than those in rural areas (24 and 31 percent, respectively). Among regions women and men residing in Addis HIV/AIDS-Related Knowledge, Attitudes, and Behaviour • 227 Ababa (81 and 70 percent, respectively) were the most likely to have been tested and to have shared their results with their partners. Sharing of HIV results among couples increases with education and wealth. Overall, 2 percent of women and 3 percent of men were tested for HIV and received their results but did not share them with their partners. Table 12.23 Sharing of HIV test results among couples Among currently married women and men age 15-49, percentage who have received the results of the last HIV test, by whether they shared the results of their last HIV test with their spouse, according to background characteristics, Ethiopia 2011 Background characteristic Women Men Ever tested, received results, and shared with partner Ever tested, received results, and did not share with partner Weighted number of women Unweighted number of women Ever tested, received results, and shared with partner Ever tested, received results, and did not share with partner Weighted number of men Unweighted number of men Age 15-24 37.5 1.4 2,527 2,572 33.1 2.1 647 641 15-19 30.1 2.5 765 784 24.9 2.0 64 66 20-24 40.7 0.9 1,762 1,788 34.0 2.1 583 575 25-29 34.5 2.0 2,511 2,480 40.0 2.8 1,481 1,378 30-39 30.6 2.8 3,311 3,322 35.8 2.9 2,790 2,762 40-49 22.7 3.0 1,938 1,830 33.1 4.1 1,953 1,994 Residence Urban 65.5 3.5 1,843 2,422 59.4 3.4 1,235 1,580 Rural 24.4 2.0 8,444 7,782 30.5 3.1 5,637 5,195 Region Tigray 49.4 6.1 620 984 44.2 10.3 377 613 Affar 26.7 1.7 104 960 34.7 3.3 52 492 Amhara 29.9 2.7 2,776 1,331 41.8 3.5 1,867 936 Oromiya 29.3 1.6 3,961 1,403 30.0 2.0 2,738 1,040 Somali 8.8 1.5 232 664 13.7 2.1 145 391 Benishangul-Gumuz 33.3 1.9 124 904 36.7 2.8 81 614 SNNP 27.2 2.0 2,022 1,295 31.2 3.2 1,279 870 Gambela 41.4 3.7 41 768 48.0 3.9 29 488 Harari 52.0 4.4 28 635 37.3 1.5 20 460 Addis Ababa 80.5 2.9 342 634 70.4 3.6 259 442 Dire Dawa 61.3 4.6 38 626 52.0 4.4 25 429 Education No education 21.4 2.0 6,735 6,569 25.3 2.7 2,906 2,757 Primary 44.8 2.6 2,862 2,739 38.6 3.6 3,213 2,997 Secondary 77.9 4.2 378 528 61.8 4.5 385 525 More than secondary 80.5 3.1 313 368 65.3 2.4 368 496 Wealth quintile Lowest 15.5 1.8 2,077 2,724 21.3 2.7 1,344 1,631 Second 19.7 2.3 2,117 1,676 26.4 2.9 1,404 1,138 Middle 24.4 1.7 2,083 1,585 31.8 2.4 1,393 1,104 Fourth 33.9 2.2 1,923 1,590 37.4 4.3 1,339 1,152 Highest 65.5 3.6 2,087 2,629 61.2 3.5 1,391 1,750 Total 15-49 31.8 2.3 10,287 10,204 35.7 3.2 6,872 6,775 50-59 na na na na 24.2 3.1 1,217 1,155 Total 15-59 na na na na 33.9 3.2 8,089 7,930 na = Not applicable 12.14 PARTICIPATION IN COMMUNITY CONVERSATION PROGRAMME The Community Conversation (CC) programme is one of the main social mobilization tools endorsed and led by the MOH and the HIV/AIDS Prevention and Control Office (HAPCO). Its methodology is based on the recognition that communities have the capacity to prevent the spread of HIV in their midst. It includes the following activities: caring for those infected with HIV, changing harmful attitudes and behaviours, and sustaining hope among those who are HIV positive. The main objective of the CC programme is to generate a response to HIV/AIDS that integrates individual and community concerns, values, and beliefs and addresses attitudes and behaviours embedded in social systems and structures. A team of two or three trained facilitators leads CC meetings. Up to 60 people can participate in a CC meeting, and they are encouraged to meet at least twice a month over a period 228 • HIV/AIDS-Related Knowledge, Attitudes, and Behaviour of ten months. By the end of the ten-month period, the team is expected to be able to develop a plan of action for the community and to follow up on its implementation. Tables 12.24.1 and 12.24.2 show the percentage of women and men age 15-49 who have heard of the Community Conversation programme and, among those, the percentage distribution by whether they have attended a CC meeting and the time since their last meeting, by background characteristics. It must be noted that there may be over-reporting of participation because respondents may have reported coffee ceremonies or other educational lectures in the community as CC meetings. Overall, 31 percent of women and 52 percent of men have heard of the Community Conversation programme. Among those who have heard of the CC programme, men are more likely than women to report having attended a CC meeting (64 percent versus 44 percent). Men also are more likely than women to report attending a CC meeting within the past three months (42 percent versus 20 percent). The percentage of respondents who have attended a CC meeting increases with age for both men and women. Previously married women and currently married men, rural men, women living in Benishangul-Gumuz, and men living in Oromiya are more likely than other respondents to have attended a CC meeting. There is no clear pattern of attendance at a CC meeting with differences in education or wealth. Table 12.24.1 Exposure to Community Conversation programme: Women Percentage of women age 15-49 who have heard of the Community Conversation programme, and, among those who have heard of the programme, the percentage distribution by whether they attended a Community Conversation meeting and time since the last meeting, by background characteristics, Ethiopia 2011 Background characteristic All women Among women who have heard of the Community Conversation programme, time since last meeting: Percentage who have heard of Community Conversation programme Weighted number of women Un- weighted number of women Never attended a Community Conversation meeting Attended within last 3 months Attended 4-11 months ago Attended one year or more ago Total Weighted number of women who have heard of programme Un- weighted number of women who have heard of programme Age 15-24 32.0 6,940 6,857 65.0 13.8 9.4 11.7 100.0 2,219 2,282 15-19 31.2 4,009 3,835 69.2 12.4 8.6 9.8 100.0 1,249 1,224 20-24 33.1 2,931 3,022 59.7 15.5 10.3 14.1 100.0 971 1,058 25-29 29.8 3,147 3,185 56.1 21.3 11.6 11.0 100.0 939 1,002 30-39 29.8 3,971 4,058 47.1 24.3 14.3 14.2 100.0 1,184 1,299 40-49 30.3 2,457 2,415 44.5 26.9 9.9 18.0 100.0 744 777 Marital status 100.0 Never married 36.7 4,469 4,413 66.2 13.9 8.6 11.3 100.0 1,639 1,769 Married/living together 28.0 10,287 10,204 52.2 21.6 12.1 13.8 100.0 2,882 2,891 Divorced/separated/ widowed 32.1 1,758 1,898 47.7 25.4 12.6 14.3 100.0 565 700 Residence Urban 47.8 3,947 5,329 56.6 18.2 11.5 13.5 100.0 1,888 2,707 Rural 25.4 12,568 11,186 56.0 20.3 10.7 12.8 100.0 3,198 2,653 Region Tigray 50.6 1,104 1,728 52.4 22.9 9.6 15.2 100.0 558 840 Affar 21.0 145 1,291 65.2 21.2 6.1 7.5 100.0 30 210 Amhara 24.9 4,433 2,087 52.3 21.0 11.4 14.9 100.0 1,106 490 Oromiya 32.7 6,011 2,135 56.9 17.5 11.7 13.7 100.0 1,966 705 Somali 20.5 329 914 51.0 22.9 12.4 12.3 100.0 67 186 Benishangul-Gumuz 22.9 174 1,259 39.6 30.6 10.8 19.0 100.0 40 288 SNNP 23.0 3,236 2,034 58.5 23.2 10.5 7.6 100.0 743 451 Gambela 31.6 69 1,130 51.6 22.4 11.4 14.6 100.0 22 272 Harari 42.3 49 1,101 56.1 14.7 8.5 20.4 100.0 21 457 Addis Ababa 55.8 896 1,741 65.0 13.8 9.4 11.8 100.0 500 984 Dire Dawa 45.8 69 1,095 50.4 18.2 17.9 13.2 100.0 32 477 Education No education 20.4 8,394 8,278 53.9 22.4 10.9 12.6 100.0 1,711 1,640 Primary 34.6 6,276 5,858 61.4 17.8 8.5 12.1 100.0 2,174 2,112 Secondary 60.3 1,117 1,395 51.3 17.8 15.2 15.3 100.0 673 891 More than secondary 72.5 728 984 48.2 19.8 16.2 15.8 100.0 528 717 Wealth quintile Lowest 20.3 2,986 3,711 59.5 19.9 7.0 13.2 100.0 607 624 Second 24.2 3,041 2,402 57.2 19.1 11.8 11.9 100.0 736 573 Middle 25.5 3,031 2,268 58.8 18.0 11.7 11.1 100.0 773 564 Fourth 29.1 3,215 2,505 53.5 22.6 10.7 13.0 100.0 935 716 Highest 48.0 4,242 5,629 55.1 18.8 11.8 14.2 100.0 2,035 2,883 Total 30.8 16,515 16,515 56.2 19.5 11.0 13.1 100.0 5,086 5,360 HIV/AIDS-Related Knowledge, Attitudes, and Behaviour • 229 Table 12.24.2 Exposure to Community Conversation programme: Men Percentage of men age 15-49 who have heard of the Community Conversation programme, and, among those who have heard of the programme, the percentage distribution by whether they attended a Community Conversation meeting and time since the last meeting, by background characteristics, Ethiopia 2011 Background characteristic All men Among men who have heard of the Community Conversation programme, time since last meeting: Percentage who have heard of Community Conversation programme Weighted number of men Unweighted number of men Never attended a Community Conversation meeting Attended within last 3 months Attended 4-11 months ago Attended one year or more ago Total Weighted number of men who have heard of programme Unweighted number of men who have heard of programme Age 15-24 44.2 5,332 5,162 52.6 26.5 9.6 11.2 100.0 2,357 2,306 15-19 38.5 3,013 2,832 63.9 18.5 8.4 9.0 100.0 1,161 1,098 20-24 51.6 2,319 2,330 41.7 34.2 10.7 13.3 100.0 1,196 1,208 25-29 55.9 2,297 2,274 32.3 44.0 9.6 13.9 100.0 1,284 1,269 30-39 58.0 3,132 3,261 26.1 49.5 11.4 12.9 100.0 1,816 1,814 40-49 58.2 2,074 2,171 24.0 56.6 9.6 9.7 100.0 1,207 1,228 Marital status Never married 46.2 5,600 5,641 52.4 25.3 10.0 12.2 100.0 2,587 2,682 Married/living together 57.1 6,872 6,775 25.5 52.7 9.8 11.9 100.0 3,922 3,713 Divorced/separated/ widowed 42.6 363 452 40.7 34.4 16.9 7.9 100,0 155 222 Residence Urban 60.0 2,882 3,915 47.5 28.2 11.0 13.2 100.0 1,729 2,530 Rural 49.6 9,952 8,953 32.3 46.3 9.7 11.4 100.0 4,934 4,087 Region Tigray 55.7 770 1,235 41.5 25.7 16.4 16.5 100.0 429 685 Affar 35.2 101 910 32.7 48.9 6.6 11.7 100.0 36 290 Amhara 36.1 3,481 1,739 41.3 39.1 8.3 10.9 100.0 1,256 611 Oromiya 64.6 4,957 1,889 28.0 54.6 7.6 9.8 100.0 3,204 1,218 Somali 32.1 245 653 41.0 26.5 13.5 18.2 100.0 79 196 Benishangul-Gumuz 36.8 138 1,047 35.9 45.2 5.7 13.0 100.0 51 385 SNNP 48.0 2,307 1,550 39.5 26.9 16.7 16.5 100.0 1,108 737 Gambela 52.2 59 865 31.2 25.3 22.8 20.6 100.0 31 420 Harari 79.3 40 898 44.0 30.2 16.3 9.5 100.0 32 717 Addis Ababa 58.6 682 1,237 70.2 9.3 8.7 11.8 100.0 400 733 Dire Dawa 75.6 53 845 50.2 23.9 10.6 15.2 100.0 40 625 Education No education 40.2 3,785 3,659 30.3 49.8 8.8 10.9 100.0 1,521 1,305 Primary 51.8 6,813 6,334 38.7 40.9 10.0 10.2 100.0 3,527 3,227 Secondary 66.6 1,296 1,565 39.6 36.1 9.9 14.4 100.0 864 1,065 More than secondary 80.0 940 1,310 33.4 34.5 13.0 19.2 100.0 752 1,020 Wealth quintile Lowest 39.7 2,141 2,563 36.5 44.6 8.3 10.1 100.0 850 844 Second 44.6 2,362 1,891 30.9 49.2 8.8 10.6 100.0 1,053 824 Middle 52.6 2,454 1,935 31.8 43.6 11.6 13.0 100.0 1,292 944 Fourth 54.0 2,683 2,203 31.1 47.7 10.2 10.9 100.0 1,448 1,161 Highest 63.3 3,194 4,276 45.5 30.8 10.5 13.3 100.0 2,021 2,844 Total 15-49 51.9 12,834 12,868 36.3 41.6 10.1 11.9 100.0 6,664 6,617 50-59 56.8 1,276 1,242 22.4 53.2 10.7 13.6 100.0 724 675 Total 15-59 52.4 14,110 14,110 34.9 42.7 10.1 12.1 100.0 7,388 7,292 HIV Prevalence • 231 HIV PREVALENCE 13 n Ethiopia much of the information on national HIV prevalence estimates is derived from sentinel surveillance at antenatal care clinics. Although surveillance data do not provide estimates of HIV prevalence for the general population, they do provide results specific to women attending antenatal clinics. The inclusion of HIV testing in the EDHS offers the opportunity to better understand the magnitude and patterns of infection within the general reproductive-age population not included in sentinel surveillance surveys, especially men age 15-59. The first such exercise was conducted as part of the 2005 EDHS. The 2011 EDHS is the second EDHS survey to anonymously link HIV testing results with demographic, socioeconomic, and behavioural characteristics of survey respondents. This chapter presents information on the HIV testing coverage rates among eligible survey respondents, the prevalence of HIV infection among those tested, and the factors associated with HIV infection in the population. Blood collection and HIV testing methodologies used in the 2011 EDHS are described in Chapter 1. 13.1 COVERAGE RATES FOR HIV TESTING Table 13.1 shows the distribution of women age 15-49 and men age 15-59 eligible for HIV testing by testing status, by residence and regions of the country. Overall, 86 percent of all EDHS respondents who were eligible for testing were interviewed and consented to HIV testing. Four percent of respondents were interviewed but refused to be tested for HIV and did not provide blood samples. Coverage rates for HIV testing were 89 percent for women and 82 percent for men. The proportion of respondents who consented to the HIV test was higher in rural areas than in urban areas for both women and men. Ninety-two percent of women in rural areas consented to HIV testing, compared with 84 percent in urban areas. Among men 86 percent in rural areas consented to testing, compared with 72 percent in urban areas. The Oromiya region has the largest proportion of respondents who consented to HIV testing, at 92 percent. I Key Findings • HIV prevalence is low in Ethiopia, with 1.5 percent of the population age 15-49 HIV positive. • Women have a higher HIV prevalence (1.9 percent) than men (1.0 percent). • For both women and men HIV prevalence increases substantially as the number of lifetime sexual partners increases. 232 • HIV Prevalence Table 13.1 Coverage of HIV testing by residence and region Percent distribution of women age 15-49 and men age 15-59 eligible for HIV testing by testing status, according to residence and region (unweighted), Ethiopia 2011 Background characteristic Testing status Total Unweighted number DBS Tested1 Refused to provide blood Absent at the time of blood collection Other/missing2 Interviewed Not interviewed Interviewed Not interviewed Interviewed Not interviewed Interviewed Not interviewed WOMEN 15-49 Residence Urban 84.1 0.0 7.8 0.8 1.6 3.8 0.8 1.1 100.0 5,656 Rural 91.8 0.1 2.4 0.5 0.7 3.1 0.5 0.9 100.0 11,729 Region Tigray 94.8 0.1 2.0 0.1 0.1 1.6 0.3 1.1 100.0 1,778 Affar 93.2 0.0 2.4 0.2 0.1 2.4 0.7 1.0 100.0 1,340 Amhara 90.6 0.1 3.7 0.4 0.8 3.0 0.7 0.6 100.0 2,177 Oromiya 93.9 0.0 2.1 0.2 0.7 2.0 0.4 0.5 100.0 2,198 Somali 81.5 0.2 9.7 1.1 0.9 5.4 0.5 0.7 100.0 987 Benishangul-Gumuz 91.5 0.0 2.3 1.0 0.6 3.1 0.5 1.0 100.0 1,326 SNNP 91.0 0.2 2.1 0.5 1.3 2.6 0.9 1.4 100.0 2,134 Gambela 88.9 0.0 1.8 1.4 0.9 6.2 0.4 0.4 100.0 1,228 Harari 83.5 0.1 7.5 1.2 2.2 3.9 0.6 1.0 100.0 1,174 Addis Ababa 81.1 0.1 9.9 0.8 1.3 3.9 0.7 2.2 100.0 1,870 Dire Dawa 84.9 0.0 5.8 0.4 2.1 5.5 0.5 0.8 100.0 1,173 Total 89.3 0.1 4.2 0.6 1.0 3.3 0.6 1.0 100.0 17,385 MEN 15-59 Residence Urban 72.0 0.1 8.0 1.7 2.4 12.3 0.9 2.6 100.0 5,062 Rural 86.4 0.1 2.8 0.6 1.4 6.9 0.7 1.2 100.0 10,846 Region Tigray 87.0 0.0 2.7 1.0 0.4 7.5 0.4 1.0 100.0 1,530 Affar 84.7 0.0 3.0 0.4 0.7 8.8 1.1 1.3 100.0 1,117 Amhara 84.9 0.3 4.3 0.4 1.3 7.4 0.6 0.9 100.0 2,159 Oromiya 90.1 0.0 2.7 0.4 1.3 4.2 0.4 0.9 100.0 2,181 Somali 69.1 0.2 9.3 2.5 1.7 12.6 2.2 2.3 100.0 868 Benishangul-Gumuz 86.1 0.0 2.4 1.1 1.6 6.8 1.0 0.9 100.0 1,249 SNNP 87.1 0.0 2.0 0.2 2.9 4.9 0.7 2.2 100.0 1,832 Gambela 82.1 0.1 2.5 0.7 1.8 11.4 0.4 1.0 100.0 1,083 Harari 71.9 0.1 9.2 1.6 2.4 11.5 1.0 2.3 100.0 1,149 Addis Ababa 69.7 0.2 7.9 1.9 1.3 13.6 0.9 4.4 100.0 1,649 Dire Dawa 73.7 0.0 6.5 1.2 3.4 13.0 0.5 1.6 100.0 1,091 Total 81.8 0.1 4.5 0.9 1.7 8.6 0.8 1.7 100.0 15,908 TOTAL (WOMEN 15-49 and MEN 15-59) Residence Urban 78.4 0.1 7.9 1.2 1.9 7.8 0.8 1.8 100.0 10,718 Rural 89.2 0.1 2.6 0.5 1.0 4.9 0.6 1.1 100.0 22,575 Region Tigray 91.2 0.0 2.3 0.5 0.2 4.3 0.4 1.0 100.0 3,308 Affar 89.3 0.0 2.7 0.3 0.4 5.3 0.9 1.1 100.0 2,457 Amhara 87.8 0.2 4.0 0.4 1.0 5.2 0.7 0.7 100.0 4,336 Oromiya 92.0 0.0 2.4 0.3 1.0 3.1 0.4 0.7 100.0 4,379 Somali 75.7 0.2 9.5 1.8 1.3 8.7 1.3 1.5 100.0 1,855 Benishangul-Gumuz 88.9 0.0 2.4 1.0 1.1 4.9 0.8 0.9 100.0 2,575 SNNP 89.2 0.1 2.0 0.4 2.1 3.7 0.8 1.7 100.0 3,966 Gambela 85.7 0.0 2.1 1.1 1.3 8.6 0.4 0.7 100.0 2,311 Harari 77.7 0.1 8.4 1.4 2.3 7.7 0.8 1.6 100.0 2,323 Addis Ababa 75.8 0.1 9.0 1.3 1.3 8.4 0.8 3.2 100.0 3,519 Dire Dawa 79.5 0.0 6.1 0.8 2.7 9.1 0.5 1.2 100.0 2,264 Total 85.7 0.1 4.3 0.8 1.3 5.9 0.7 1.3 100.0 33,293 1 Includes all Dried Blood Spot (DBS) samples tested at the lab for which there is a result, whether positive, negative, or indeterminate. Indeterminate means that the sample went through the entire testing algorithm, but the final result was inconclusive. 2 Includes 1) other results of blood collection (e.g., technical problem in the field), 2) lost specimens, 3) non-corresponding bar codes, and 4) other lab results such as blood not tested for technical reasons and not enough blood to complete the algorithm. Table 13.2 shows HIV testing coverage rates for women age 15-49 and men age 15-59 by age group, level of education, and wealth quintile. For women HIV testing coverage varied from 88 percent among women age 15-19 to 92 percent among women age 45-49. For men HIV testing coverage varied from 80 percent among men age 20-29 to 86 percent among men age 55-59. HIV Prevalence • 233 Among women and men, more education and higher wealth are associated with higher testing refusal rates. For women HIV testing coverage was lowest among women with more than a secondary education (82 percent) and women in the highest wealth quintile (84 percent). Similarly for men HIV testing coverage was lowest among men with more than a secondary education (75 percent) and men in the highest wealth quintile (73 percent). Age differentials in HIV testing coverage were not large for either women or men. Additional tables describing the relationship between participation in HIV testing and characteristics related to HIV risk are presented in Appendix A. Table 13.2 Coverage of HIV testing by selected background characteristics Percent distribution of women age 15-49 and men age 15-59 eligible for HIV testing by testing status, according to selected background characteristics (unweighted), Ethiopia 2011 Background characteristic Testing status Total Unweighted number DBS tested1 Refused to provide blood Absent at the time of blood collection Other/missing2 Interviewed Not interviewed Interviewed Not interviewed Interviewed Not interviewed Interviewed Not interviewed WOMEN 15-49 Age 15-19 88.4 0.0 3.7 0.6 1.4 4.4 0.5 0.9 100.0 4,082 20-24 88.6 0.1 3.9 0.7 1.0 3.7 0.7 1.3 100.0 3,204 25-29 89.1 0.0 5.0 0.6 0.8 2.6 0.6 1.1 100.0 3,333 30-34 88.8 0.0 5.1 0.5 1.1 2.9 0.6 0.9 100.0 2,196 35-39 90.4 0.2 3.8 0.4 0.6 3.3 0.5 0.8 100.0 2,055 40-44 90.3 0.1 3.9 0.7 0.7 2.5 0.4 1.3 100.0 1,375 45-49 91.8 0.1 3.2 0.6 0.6 2.4 0.9 0.4 100.0 1,140 Education No education 90.2 0.1 3.6 0.6 0.7 3.1 0.6 1.2 100.0 8,715 Primary 90.5 0.0 3.4 0.6 1.0 3.1 0.6 0.8 100.0 6,129 Secondary 84.0 0.0 6.5 0.7 1.9 5.1 0.7 1.1 100.0 1,498 More than secondary 81.8 0.0 10.5 0.7 1.5 4.3 0.6 0.7 100.0 1,043 Wealth quintile Lowest 91.3 0.0 2.2 0.8 0.6 3.8 0.4 1.0 100.0 3,930 Second 92.6 0.1 2.0 0.5 0.7 2.7 0.5 0.9 100.0 2,508 Middle 91.9 0.1 2.6 0.3 0.7 3.2 0.4 0.7 100.0 2,373 Fourth 91.6 0.1 2.8 0.4 0.8 2.8 0.7 0.9 100.0 2,613 Highest 84.4 0.1 7.6 0.7 1.6 3.6 0.8 1.2 100.0 5,961 Total 89.3 0.1 4.2 0.6 1.0 3.3 0.6 1.0 100.0 17,385 MEN 15-59 Age 15-19 82.8 0.1 3.6 1.0 2.1 8.4 0.8 1.1 100.0 3,172 20-24 80.2 0.2 4.0 1.1 1.9 9.9 0.7 2.0 100.0 2,683 25-29 80.0 0.0 4.9 0.8 1.8 9.9 0.6 1.9 100.0 2,602 30-34 81.6 0.1 4.7 1.1 1.5 8.3 0.8 2.0 100.0 1,898 35-39 83.0 0.0 4.9 0.5 1.3 7.7 0.6 2.0 100.0 1,758 40-44 81.2 0.1 4.4 1.1 1.3 9.2 1.0 1.6 100.0 1,375 45-49 84.2 0.0 5.6 0.8 1.1 6.6 0.8 1.0 100.0 1,048 50-54 82.0 0.1 4.9 1.1 1.7 7.6 0.7 2.0 100.0 820 55-59 85.9 0.0 4.7 0.7 0.9 5.4 0.9 1.4 100.0 552 Education No education 82.5 0.1 3.5 0.8 1.2 8.7 0.9 2.2 100.0 5,045 Primary 84.6 0.1 3.7 0.8 1.6 7.0 0.8 1.3 100.0 7,351 Secondary 75.4 0.0 6.1 1.5 2.5 12.4 0.4 1.8 100.0 1,928 More than secondary 74.7 0.1 8.8 1.3 2.2 10.7 0.6 1.7 100.0 1,582 Wealth quintile Lowest 84.6 0.1 2.8 0.7 1.1 8.0 0.9 1.7 100.0 3,184 Second 87.0 0.0 2.9 0.4 1.1 7.1 0.6 0.9 100.0 2,303 Middle 87.8 0.1 2.5 0.5 1.2 6.5 0.4 0.9 100.0 2,342 Fourth 86.5 0.1 2.9 0.5 2.3 5.7 0.7 1.3 100.0 2,602 Highest 73.2 0.1 7.7 1.7 2.1 11.8 0.9 2.5 100.0 5,477 Total 81.8 0.1 4.5 0.9 1.7 8.6 0.8 1.7 100.0 15,908 Note: Total for men includes 2 cases with missing information on education. 1 Includes all Dried Blood Spot (DBS) samples tested at the lab for which there is a result, i.e., positive, negative, or indeterminate. Indeterminate means that the sample went through the entire testing algorithm, but the final result was inconclusive. 2 Includes: 1) other results of blood collection (e.g., technical problem in the field), 2) lost specimens, 3) non corresponding bar codes, and 4) other lab results such as blood not tested for technical reasons and not enough blood to complete the algorithm. 234 • HIV Prevalence 13.2 HIV PREVALENCE 13.2.1 HIV Prevalence by Age and Sex Table 13.3 shows the percentage of adults age 15-49 in Ethiopia who are infected with HIV. Among women age 15-49 HIV prevalence is 1.9 percent, and among men age 15-49 and 15-59, HIV prevalence is 1.0 percent. For women, HIV prevalence increases with age to a peak of 3.7 percent at age 30-34. For men, HIV prevalence increases from 0.0 percent at age 15-19 to 3.0 percent at age 35- 39 and drops thereafter. Overall, HIV prevalence is higher for women than men in most age groups. Figure 13.1 illustrates the age pattern of HIV prevalence for women and men. Table 13.3 HIV prevalence by age Among women age 15-49 and men age 15-59 who were interviewed and tested, the percentage HIV positive, by age, Ethiopia 2011 Age Women Men Total Percentage HIV positive Weighted number Unweighted number Percentage HIV positive Weighted number Unweighted number Percentage HIV positive Weighted number Unweighted number 15-19 0.2 3,584 3,607 0.0 2,931 2,624 0.1 6,516 6,231 20-24 0.9 2,619 2,843 0.2 2,280 2,153 0.6 4,899 4,996 25-29 2.9 2,788 2,969 0.9 2,261 2,083 2.0 5,049 5,052 30-34 3.7 1,809 1,949 1.0 1,478 1,550 2.5 3,287 3,499 35-39 3.0 1,714 1,858 3.0 1,630 1,459 3.0 3,344 3,317 40-44 1.9 1,110 1,244 2.1 1,093 1,117 2.0 2,203 2,361 45-49 1.8 1,071 1,047 1.4 907 882 1.6 1,978 1,929 Total 15-49 1.9 14,695 15,517 1.0 12,581 11,868 1.5 27,276 27,385 50-59 na na na 0.6 1,255 1,146 na na na Total 15-59 na na na 1.0 13,836 13,014 na na na na = Not applicable Figure 13.1 HIV Prevalence for Women and Men Age 15-49 by Age Groups EDHS 2011 ) ) ) ) ) ) ) & & & & & & & 15-19 20-24 25-29 30-34 35-39 40-44 45-49 Age 0 1 2 3 4 Percent HIV+ Women Men & ) HIV Prevalence • 235 The overall adult HIV prevalence in Ethiopia has remained low. The HIV prevalence among adults age 15-49 in the 2011 EDHS is 1.5 percent (confidence interval 1.2-1.7 percent), and it was 1.4 percent (confidence interval 1.1-1.8 percent) in the 2005 EDHS. To understand the epidemic in more detail, further in depth analysis on existing data and other data sources is recommended. 13.2.2 HIV Prevalence by Socioeconomic Characteristics Table 13.4 shows the variation in HIV prevalence by various socioeconomic characteristics— employment, residence, region, educational level, and wealth quintile. Among both women and men, HIV prevalence is somewhat higher among those who are employed than those who are not employed. HIV prevalence is higher in urban areas (4.2 percent) than in rural areas (0.6 percent). Among regions HIV prevalence is highest in Gambela (6.5 percent) and in Addis Ababa (5.2 percent). A higher proportion of Ethiopians who attended secondary school (3.1 percent) are HIV positive than those with less education or with more than a secondary school education. Men and women in the highest wealth quintile have the highest HIV prevalence (3.9 percent). In general, differentials in HIV prevalence are similar for women and men. Table 13.4 HIV prevalence by socioeconomic characteristics Percentage HIV positive among women and men age 15-49 who were tested, by socioeconomic characteristics, Ethiopia 2011 Socioeconomic characteristic Women Men Total Percentage HIV positive Weighted number Unweighted number Percentage HIV positive Weighted number Unweighted number Percentage HIV positive Weighted number Unweighted number Employment (last 12 months) Not employed 1.4 6,154 7,469 0.1 678 854 1.3 6,832 8,323 Employed 2.2 8,535 8,045 1.1 11,901 11,012 1.5 20,436 19,057 Residence Urban 5.2 3,512 4,754 2.9 2,824 3,392 4.2 6,336 8,146 Rural 0.8 11,183 10,763 0.5 9,757 8,476 0.6 20,940 19,239 Region Tigray 2.2 982 1,685 1.3 755 1,188 1.8 1,738 2,873 Affar 2.0 129 1,249 1.7 99 861 1.8 228 2,110 Amhara 2.2 3,945 1,973 1.0 3,419 1,624 1.6 7,364 3,597 Oromiya 1.3 5,348 2,065 0.6 4,853 1,798 1.0 10,202 3,863 Somali 1.6 293 804 0.4 239 550 1.1 532 1,354 Benishangul-Gumuz 1.7 155 1,213 0.8 135 987 1.3 290 2,200 SNNP 1.0 2,880 1,943 0.6 2,261 1,454 0.9 5,141 3,397 Gambela 7.9 61 1,092 4.9 58 817 6.5 119 1,909 Harari 3.8 43 980 1.7 39 765 2.8 83 1,745 Addis Ababa 6.0 797 1,517 4.3 669 1,079 5.2 1,466 2,596 Dire Dawa 4.3 61 996 3.7 53 745 4.0 114 1,741 Education No education 1.3 7,473 7,858 0.8 3,711 3,431 1.1 11,184 11,289 Primary 2.2 5,620 5,547 0.9 6,714 5,902 1.5 12,335 11,449 Secondary 4.3 980 1,259 2.1 1,279 1,399 3.1 2,259 2,658 More than secondary 1.6 622 853 1.1 877 1,136 1.3 1,499 1,989 Wealth quintile Lowest 0.5 2,671 3,589 0.2 2,098 2,427 0.3 4,769 6,016 Second 0.5 2,710 2,322 0.4 2,329 1,797 0.4 5,039 4,119 Middle 0.7 2,701 2,180 0.7 2,427 1,848 0.7 5,128 4,028 Fourth 1.5 2,878 2,393 0.5 2,625 2,062 1.0 5,503 4,455 Highest 4.9 3,736 5,033 2.7 3,101 3,734 3.9 6,837 8,767 Total 15-49 1.9 14,695 15,517 1.0 12,581 11,868 1.5 27,276 27,385 50-59 na na na 0.6 1,255 1,146 na na na Total 15-59 na na na 1.0 13,836 13,014 na na na na = Not applicable Note: Total includes 14 cases with missing information on religion and 8 cases with missing information on employment. 236 • HIV Prevalence 13.2.3 HIV Prevalence by Demographic Characteristics Table 13.5 shows HIV prevalence among women and men by various characteristics—marital status, type of union, the number of times the respondent slept away from home in the 12 months before the survey, the total time away from home in the past 12 months for men, pregnancy status for women, use of antenatal care (ANC) for women, and male circumcision. HIV prevalence does not vary much with the type of union, the number of times men slept away from home in the 12 months before the survey, the total time men spent away in the past 12 months, or male circumcision. However, HIV prevalence is closely related to marital status. Widowed and divorced respondents (12.2 percent and 5.2 percent, respectively) are much more likely to be HIV positive than those who are married and those who have never been married. Both women and men show this same pattern. However, HIV prevalence is slightly higher among widowed men (14.5 percent) than among widowed women (12.0 percent). Among women who received ANC for their last birth in the three years preceding the survey, a higher proportion of women who received ANC from a non-public sector provider are HIV positive (3.1 percent) than are those who received ANC from a public sector provider (1.7 percent). Pregnant women are less likely to be HIV positive than other women. Table 13.5 HIV prevalence by demographic characteristics Percentage HIV positive among women and men age 15-49 who were tested, by demographic characteristics, Ethiopia 2011 Demographic characteristic Women Men Total Percentage HIV positive Weighted number Unweighted number Percentage HIV positive Weighted number Unweighted number Percentage HIV positive Weighted number Unweighted number Marital status Never married 0.5 3,957 4,056 0.2 5,416 5,127 0.3 9,373 9,183 Ever had sexual intercourse 3.2 306 445 1.0 992 1,314 1.5 1,298 1,759 Never had sexual intercourse 0.3 3,651 3,611 0.0 4,424 3,813 0.2 8,075 7,424 Married/living together 1.5 9,183 9,697 1.3 6,812 6,335 1.5 15,995 16,032 Divorced or separated 5.0 1,086 1,218 5.9 317 341 5.2 1,403 1,559 Widowed 12.0 470 546 14.5 36 65 12.2 506 611 Type of union In polygynous union 1.8 967 1,262 1.2 338 393 1.7 1,306 1,655 In non-polygynous union 1.5 8,166 8,383 1.3 6,453 5,923 1.4 14,619 14,306 Not currently in union 2.4 5,513 5,820 0.6 5,769 5,533 1.5 11,282 11,353 Times slept away from home in past 12 months None na na na 0.9 6,260 6,263 na na na 1-2 na na na 0.9 2,234 1,832 na na na 3-4 na na na 0.8 1,443 1,112 na na na 5+ na na na 1.4 2,581 2,605 na na na Time away in past 12 months Away for more than 1 month na na na 1.5 1,104 1,276 na na na Away for less than 1 month na na na 1.0 5,137 4,260 na na na Not away na na na 0.9 6,260 6,263 na na na Currently pregnant Pregnant 0.8 1,083 1,222 na na na na na na Not pregnant or not sure 1.9 13,612 14,295 na na na na na na ANC for last birth in the last 3 years ANC provided by the public sector 1.7 2,112 2,228 na na na na na na ANC provided by other than the public sector 3.1 162 262 na na na na na na No ANC/No birth in last 3 years 1.9 12,405 13,010 na na na na na na Male circumcision Circumcised na na na 1.0 11,563 10,914 na na na Not circumcised na na na 0.9 988 925 na na na Total 15-49 1.9 14,695 15,517 1.0 12,581 11,868 1.5 27,276 27,385 50-59 na na na 0.6 1,255 1,146 na na na Total 15-59 na na na 1.0 13,836 13,014 na na na na = Not applicable Note: Total includes 69 cases with missing information on type of union, 63 men with missing information on times slept away from home in the past 12 months, 16 women with missing information on ANC for last birth in the last 3 years, and 31 men with missing information on male circumcision. HIV Prevalence • 237 13.2.4 HIV Prevalence by Sexual Risk Behaviour Table 13.6 presents HIV prevalence rates among respondents who have ever had sexual intercourse, by sexual behaviour indicators. Among all respondents age 15-49 who have ever had sex and were tested for HIV, 2.0 percent were HIV positive (2.4 percent of women and 1.5 percent of men). In reviewing these results, one should note that responses to questions about sexual risk behaviour may be subject to reporting bias. Also, sexual behaviour in the 12 months preceding the survey may not adequately reflect lifetime sexual risk. In the general population there is no strong relationship between age at first sexual intercourse and HIV prevalence. Among men, however, those whose sexual debut was at age 16-17 were slightly more likely to be HIV positive (2.7 percent) than other men. Among women there was little difference in HIV prevalence by age at first sexual intercourse. Table 13.6 HIV prevalence by sexual behaviour Percentage HIV positive among women and men age 15-49 who have ever had sex and were tested for HIV, by sexual behaviour characteristics, Ethiopia 2011 Women Men Total Sexual behaviour characteristic Percentage HIV positive Weighted number Unweighted number Percentage HIV positive Weighted number Unweighted number Percentage HIV positive Weighted number Unweighted number Age at first sexual intercourse <16 2.4 4,936 5,036 2.1 760 889 2.3 5,696 5,925 16-17 2.1 2,191 2,397 2.7 1,084 1,115 2.3 3,276 3,512 18-19 2.3 1,736 1,825 1.5 1,736 1,749 1.9 3,472 3,574 20+ 2.6 1,614 1,941 1.1 4,216 3,959 1.5 5,831 5,900 Multiple sexual partners and partner concurrency in past 12 months 0 6.7 1,481 1,975 2.9 645 850 5.6 2,126 2,825 1 1.6 9,446 9,802 1.4 7,018 6,648 1.5 16,463 16,450 2+ 22.5 56 74 1.9 431 514 4.3 487 588 Had concurrent partners1 * 4 5 1.3 285 314 1.3 289 319 None of the partners were concurrent 24.4 52 69 3.1 146 200 8.7 198 269 Condom use at last sexual intercourse in past 12 months Used condom 17.2 175 293 5.4 524 692 8.3 698 985 Did not use condom 1.4 9,325 9,580 1.1 6,923 6,468 1.3 16,248 16,048 No sexual intercourse in last 12 months 6.9 1,490 1,984 2.8 657 861 5.6 2,147 2,845 Number of lifetime partners 1 1.3 7,996 8,857 0.1 4,261 3,871 0.9 12,257 12,728 2 5.1 2,134 2,197 2.5 1,757 1,843 3.9 3,891 4,040 3-4 4.4 711 634 2.9 1,247 1,289 3.4 1,957 1,923 5-9 8.7 102 92 3.5 516 613 4.3 619 705 10+ 23.7 29 52 6.8 289 365 8.3 317 417 Paid for sexual intercourse in past 12 months Yes na na na 4.3 119 111 na na na Used condom na na na * 33 19 na na na Did not use condom na na na 6.0 86 92 na na na No/no sexual intercourse in last 12 months na na na 1.5 7,987 7,912 na na na Total 15-49 2.4 10,992 11,860 1.5 8,105 8,023 2.0 19,097 19,883 50-59 na na na 0.6 1,250 1,143 na na na Total 15-59 na na na 1.4 9,355 9,166 na na na Note: Total includes 823 cases with inconsistent/missing information on age at first sexual intercourse, 21 cases with missing information on multiple sexual partners and partner concurrency in past 12 months, 4 cases with missing information on condom use at last sexual intercourse in past 12 months, and 70 cases with missing information on number of lifetime partners. An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. na = Not applicable 1 A respondent is considered to have had concurrent partners if he or she had overlapping sexual partnerships with two or more people during the 12 months before the survey. (Respondents with concurrent partners include polygynous men who had overlapping sexual partnerships with two or more wives). 238 • HIV Prevalence Caution should be used when interpreting HIV prevalence levels among women based on the number of sexual partners in the past 12 months because very few women report more than one partner. Among men HIV prevalence is highest for those who report no partners in the past 12 months (2.9 percent). Among men who report two or more partners in the past 12 months, HIV prevalence is higher among those with no concurrent partners (3.1 percent) than among those with concurrent partners (1.3 percent). However, these bivariate associations must be considered with caution as they may be influenced by other factors, such as respondents’ marital status. In addition, findings on sexual behaviour in the past 12 months should not be interpreted as a complete picture of an individual’s exposure to risk of HIV infection as individuals may have become infected more than 12 months before the survey. Concurrent partnerships are defined as overlapping sexual partnerships with two or more individuals during the 12 months preceding the survey. HIV prevalence increases substantially as the number of lifetime sexual partners increases, for both women and men. HIV prevalence increases from 1.3 percent for women with one lifetime partner to 5.1 percent for women with two lifetime partners and to 8.7 percent for women with 5-9 lifetime partners. Almost one-quarter of women with 10 or more lifetime partners are HIV positive. HIV prevalence ranges from 0.1 percent among men with one lifetime partner to 6.8 percent among men with 10 or more lifetime partners. Condom use at last sexual intercourse is also related to HIV prevalence. For respondents who had sex in the past 12 months, a higher proportion of those who used a condom at last sex were HIV positive (8.3 percent) than those who did not use a condom (1.3 percent). This proportion is more than three times higher among women than among men. No causal association between condom use and HIV can be assumed from these results. In these data it is not possible to know the sequence of events, e.g., whether reported condom use occurred before or after HIV infection. It is likely that those who suspect that they or their partner might be infected would also be more likely to use condoms, thus reversing the expected direction of the relationship of lower HIV prevalence among those who use condoms. Condom use at last sex has been associated with higher HIV prevalence in many other cross-sectional surveys. In addition, other factors may be influencing the relationship between condom use and HIV. For example, condom use may be higher in urban areas, among those who engage in higher risk sexual behaviours, or in other groups which are also more likely to be HIV- positive. Further analysis is required to gain a better understanding of the true relationship between condom use and HIV infection in Ethiopia. 13.3 HIV PREVALENCE AMONG YOUTH Table 13.7 shows HIV prevalence among women and men age 15-24 by background characteristics. Overall, less than 1 percent of Ethiopian youth age 15-24 tested positive for HIV. There is little variation in HIV prevalence by background characteristics, given the low overall prevalence. Regional estimates of HIV prevalence among youth are similar, with one exception: in Gambela HIV prevalence among young women is much higher, at 9 percent, than in other regions of the country. HIV Prevalence • 239 Table 13.7 HIV prevalence among young people by background characteristics Percentage HIV positive among women and men age 15-24 who were tested for HIV, by background characteristics, Ethiopia 2011 Background characteristic Women Men Total Percentage HIV positive Weighted number Unweighted number Percentage HIV positive Weighted number Unweighted number Percentage HIV positive Weighted number Unweighted number Age 15-19 0.2 3,584 3,607 0.0 2,931 2,624 0.1 6,516 6,231 15-17 0.2 2,184 2,187 0.0 1,827 1,606 0.1 4,011 3,793 18-19 0.3 1,401 1,420 0.1 1,104 1,018 0.2 2,505 2,438 20-24 0.9 2,619 2,843 0.2 2,280 2,153 0.6 4,899 4,996 20-22 0.6 1,760 1,905 0.1 1,508 1,404 0.4 3,268 3,309 23-24 1.4 859 938 0.4 772 749 0.9 1,631 1,687 Marital status Never married 0.4 3,579 3,590 0.1 4,508 4,107 0.2 8,087 7,697 Ever had sex 2.2 195 264 0.6 579 739 1.0 774 1,003 Never had sex 0.3 3,384 3,326 0.0 3,928 3,368 0.2 7,312 6,694 Married/living together 0.5 2,268 2,458 0.1 640 601 0.4 2,907 3,059 Divorced/separated/widowed 1.4 357 402 0.0 64 69 1.2 421 471 Currently pregnant Pregnant 0.4 355 405 na na na na na na Not pregnant or not sure 0.5 5,848 6,045 na na na na na na Residence Urban 0.9 1,710 2,230 0.1 1,212 1,384 0.6 2,922 3,614 Rural 0.3 4,494 4,220 0.1 4,000 3,393 0.2 8,493 7,613 Region Tigray 0.6 445 748 0.7 342 533 0.7 787 1,281 Affar 0.6 52 498 0.2 39 325 0.4 92 823 Amhara 0.4 1,692 830 0.0 1,532 728 0.2 3,225 1,558 Oromiya 0.2 2,274 873 0.1 1,952 725 0.2 4,226 1,598 Somali 1.0 107 290 0.0 92 208 0.5 199 498 Benishangul-Gumuz 1.1 64 493 0.0 57 417 0.6 121 910 SNNP 0.4 1,118 740 0.0 876 558 0.2 1,994 1,298 Gambela 9.0 32 441 0.2 24 301 5.3 55 742 Harari 1.1 18 415 0.0 16 310 0.6 34 725 Addis Ababa 1.7 376 717 0.2 262 425 1.1 639 1,142 Dire Dawa 1.2 25 405 0.7 18 247 1.0 44 652 Education No education 0.3 1,598 1,787 0.3 774 710 0.3 2,372 2,497 Primary 0.5 3,589 3,481 0.0 3,423 2,966 0.3 7,012 6,447 Secondary 1.2 677 729 0.3 704 678 0.8 1,381 1,407 More than secondary 0.7 340 453 0.0 311 423 0.3 651 876 Wealth quintile Lowest 0.1 998 1,289 0.1 779 858 0.1 1,777 2,147 Second 0.5 1,059 896 0.0 934 706 0.3 1,993 1,602 Middle 0.3 1,062 850 0.2 1,019 777 0.2 2,081 1,627 Fourth 0.2 1,267 1,034 0.0 1,131 881 0.1 2,397 1,915 Highest 1.0 1,818 2,381 0.2 1,349 1,555 0.7 3,167 3,936 Total 0.5 6,204 6,450 0.1 5,211 4,777 0.3 11,415 11,227 na = Not applicable 13.3.1 HIV Prevalence by Sexual Behaviour among Youth The 2011 EDHS collected data on behaviours that correlate with sexually transmitted infection (STI) rates. Information on sexual behaviour characteristics is important in designing, targeting, and monitoring HIV prevention interventions for the young adult population. Three behaviours that correlate with STI rates are the number of sexual partners, age at first sexual intercourse, and condom use. This section examines data on sexual behaviour related to the spread of HIV among respondents who have ever had sexual intercourse. It is important to note that responses about sexual behaviour are subject to reporting bias. 240 • HIV Prevalence Table 13.8 shows HIV prevalence among youth by sexual behaviour. Overall, 0.6 percent of respondents age 15-24 who have ever had sex and were tested for HIV in the 2011 EDHS are HIV positive. By comparison, HIV prevalence is relatively high among young respondents who report two or more sexual partners (6.7 percent) in the 12 months before the survey and among those who used a condom at last sex (2.4 percent). Table 13.8 HIV prevalence among young people by sexual behaviour Percentage HIV-positive among women and men age 15-24 who have ever had sex and were tested for HIV, by sexual behaviour, Ethiopia 2011 Sexual behaviour characteristic Women Men Total Percentage HIV positive Weighted number Unweighted number Percentage HIV positive Weighted number Unweighted number Percentage HIV positive Weighted number Unweighted number Multiple sexual partners and partner concurrency in past 12 months 0 1.5 278 386 0.2 256 281 0.9 535 667 1 0.4 2,467 2,654 0.4 940 1,015 0.4 3,407 3,669 2+ (20.5) 25 43 0.0 51 89 6.7 75 132 Had concurrent partners1 * 1 1 * 4 15 * 5 16 None of the partners were concurrent (21.5) 24 42 0.0 47 74 7.2 71 116 Condom use at last sexual intercourse in past 12 months Used condom 6.2 75 134 1.2 243 322 2.4 318 456 Did not use condom 0.4 2,417 2,562 0.1 747 782 0.3 3,164 3,344 No sexual intercourse in last 12 months 2.3 284 389 0.2 260 283 1.3 544 672 Total 0.8 2,776 3,086 0.3 1,250 1,387 0.6 4,027 4,473 Note: Total includes 10 cases with missing information on multiple sexual partners and partner concurrency in past 12 months and 1 case with missing information on condom use at last sexual intercourse in past 12 months. Figures in parentheses are based on 25-49 unweighted cases. An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. na = Not applicable 1 A respondent is considered to have had concurrent partners if he or she had overlapping sexual partnerships with two or more people during the 12 months before the survey. (Respondents with concurrent partners include polygynous men who had overlapping sexual partnerships with two or more wives). 13.4 HIV PREVALENCE BY OTHER CHARACTERISTICS 13.4.1 HIV Prevalence and STIs A strong link exists between sexually transmitted infections and the sexual transmission of HIV. Many studies have demonstrated that STIs are a co-factor for HIV transmission. Management and treatment of STIs can play an important role in the reduction of HIV transmission. The 2011 EDHS asked respondents who had ever had sex if they had contracted a disease through sexual contact in the past 12 months, or if they had any symptoms associated with STIs (an abnormal discharge from the vagina or penis or a genital sore or ulcer). Table 13.9 shows HIV prevalence among women and men age 15-49 who have ever had sex, by whether respondents reported an STI or STI symptoms in the 12 months preceding the survey. Overall, a higher percentage of respondents with STIs or STI symptoms in the past 12 months are HIV positive (4.7 percent) than of those with no STIs or STI symptoms (2.0 percent). This pattern is observed among both women and men. HIV prevalence is higher among those previously tested for HIV than among those who were never tested for HIV. Among those ever tested, respondents who received their results had a higher HIV prevalence (3.8 percent) than those who tested but did not receive results (1.6 percent) and those who never tested (0.9 percent). HIV Prevalence • 241 Table 13.9 HIV prevalence by other characteristics Percentage HIV positive among women and men age 15-49 who have ever had sex and were tested for HIV, by whether had an STI in the past 12 months and by prior testing for HIV, Ethiopia 2011 Characteristic Women Men Total Per- centage HIV positive Weighted number Un- weighted number Per- centage HIV positive Weighted number Un- weighted number Per- centage HIV positive Weighted number Un- weighted number Sexually transmitted infection in past 12 months Had STI or STI symptoms 3.9 373 365 6.2 196 199 4.7 569 564 No STI, no symptoms 2.3 10,501 11,308 1.4 7,839 7,771 2.0 18,340 19,079 Prior HIV testing Ever tested 4.7 4,340 5,105 2.4 3,749 3,862 3.6 8,089 8,967 Received results 4.8 4,037 4,777 2.6 3,465 3,577 3.8 7,503 8,354 Did not receive results 2.6 303 328 0.6 284 285 1.6 586 613 Never tested 0.9 6,637 6,742 0.8 4,356 4,161 0.9 10,994 10,903 Total 15-49 2.4 10,992 11,860 1.5 8,105 8,023 2.0 19,097 19,883 Note: Total includes 240 cases with missing information on STIs and 15 cases of women with missing information on prior HIV testing status. 13.4.2 Prior HIV Testing and Current HIV Status Table 13.10 shows the percent distribution of women and men age 15-49 by HIV testing status prior to the survey. Among respondents who are HIV positive, 72 percent were previously tested for HIV and received their result, whereas 26 percent had never been tested. Less than 3 percent were previously tested for HIV but did not receive their test result. Among respondents who are HIV negative, 36 percent were previously tested for HIV and received their result, while 60 percent had never been tested for HIV. Table 13.10 Prior HIV testing by current HIV status Percent distribution of women and men age 15-49 who tested HIV positive and who tested HIV negative by HIV testing status prior to the survey, Ethiopia 2011 HIV testing prior to the survey Women Men Total HIV positive HIV negative HIV positive HIV negative HIV positive HIV negative Previously tested Received result of last test 72.5 35.3 70.3 37.7 71.8 36.4 Did not receive result of last test 3.0 2.9 1.3 3.6 2.5 3.3 Not previously tested 24.3 61.6 28.4 58.6 25.6 60.2 Missing 0.2 0.1 0.0 0.0 0.1 0.1 Total 100.0 100.0 100.0 100.0 100.0 100.0 Weighted number 273 14,422 127 12,454 400 26,876 Unweighted number 358 15,159 171 11,697 529 26,856 13.4.3 HIV Prevalence by Male Circumcision Several recent studies in sub-Saharan Africa—including clinical trials conducted in South Africa, Kenya, and Uganda (Auvert et al., 2001; Bailey et al., 2007; Gray et al., 2007)—have documented that male circumcision provides some protection against HIV infection and other STIs. Although the research supporting circumcision’s protective effects is compelling, it is important to emphasise that circumcised men can still become infected with HIV and can infect their sexual partners. 242 • HIV Prevalence Table 13.11 presents data from the 2011 EDHS on HIV prevalence by male circumcision status. In this survey there is no marked difference between HIV prevalence among circumcised and uncircumcised men, and, due to the small number of uncircumcised men, detailed comparisons are not reliable. Male circumcision is almost universal throughout Ethiopia, except in SNNP and Gambela, where 21 and 24 percent of men are uncircumcised, respectively (see Table 12.13.1). Among the circumcised male population, the highest HIV prevalence was found among men age 35-39, Catholics, men in urban areas, men in the Gambela, Addis Ababa, and Dire Dawa regions, men with secondary education, and men in the highest wealth quintile. It must be noted that in Gambela the HIV prevalence among the uncircumcised men is almost double that of the circumcised men (7.9 percent versus 4.1 percent). Table 13.11 HIV prevalence by male circumcision Among men age 15-49 who were tested for HIV, the percentage HIV positive by whether they are circumcised, according to background characteristics, Ethiopia 2011 Background characteristic Circumcised Not circumcised Percentage HIV positive Weighted number Unweighted number Percentage HIV positive Weighted number Unweighted number Age 15-19 0.0 2,565 2,321 0.0 359 296 20-24 0.2 2,086 1,998 0.0 190 151 25-29 1.0 2,112 1,927 0.4 143 153 30-34 1.0 1,372 1,442 1.2 95 102 35-39 2.9 1,531 1,363 5.3 98 93 40-44 2.1 1,035 1,044 2.3 58 69 45-49 1.4 862 819 0.5 44 61 Religion Orthodox 1.5 5,797 4,905 0.6 218 173 Catholic 2.3 97 81 (0.3) 18 34 Protestant 0.7 1,924 1,416 1.4 499 530 Muslim 0.4 3,541 4,346 0.0 151 97 Traditional 0.0 69 58 * 20 19 Residence Urban 3.0 2,766 3,322 1.2 51 65 Rural 0.4 8,796 7,592 0.8 937 860 Region Tigray 1.1 726 1,141 (2.6) 20 34 Affar 1.7 98 852 * 1 9 Amhara 1.1 3,246 1,538 0.0 167 84 Oromiya 0.6 4,544 1,690 1.2 302 106 Somali 0.4 236 546 * 1 2 Benishangul-Gumuz 0.9 128 934 0.0 7 52 SNNP 0.7 1,785 1,130 0.6 469 319 Gambela 4.1 45 512 7.9 13 305 Harari 1.7 39 762 * 0 0 Addis Ababa 4.2 662 1,068 * 7 11 Dire Dawa 3.7 52 741 * 0 3 Education No education 0.8 3,438 3,214 0.0 265 207 Primary 0.9 6,053 5,307 1.3 638 579 Secondary 2.2 1,220 1,315 0.3 58 82 More than secondary 1.2 851 1,078 0.4 26 57 Wealth quintile Lowest 0.1 1,852 2,060 0.7 242 361 Second 0.4 2,083 1,608 0.1 240 183 Middle 0.4 2,199 1,688 2.5 223 155 Fourth 0.5 2,436 1,908 0.2 181 147 Highest 2.8 2,992 3,650 0.5 102 79 Total 15-49 1.0 11,563 10,914 0.9 988 925 50-59 0.7 1,199 1,072 0.0 56 72 Total 15-59 1.0 12,761 11,986 0.8 1,044 997 Note: Total includes 2 cases with missing information on religion. Figures in parentheses are based on 25-49 unweighted cases. An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. HIV Prevalence • 243 13.5 HIV PREVALENCE AMONG COHABITING COUPLES In the 2011 EDHS more than 6,000 cohabiting couples were interviewed and tested for HIV. Table 13.12 shows that 98.3 percent of cohabiting couples are HIV negative, while in 0.6 percent of couples both partners are HIV positive. Discordant couples, that is, one partner infected and the other not infected, constitute 1.1 percent of those tested. In 0.4 percent of couples the male partner is HIV positive and the female partner is HIV negative, and in 0.7 percent of couples the reverse is the case. Discordance is most marked in urban areas, among couples in the highest wealth quintile, and in Addis Ababa, Gambela, and Dire Dawa. A higher percentage of couples are discordant when the woman is older, when the woman or the man has a secondary education, and when the couple is in the wealthiest quintile. 244 • HIV Prevalence Table 13.12 HIV prevalence among couples Percent distribution of couples in the same household, both of whom were tested for HIV, by HIV status, according to background characteristics, Ethiopia 2011 Background characteristic Both HIV positive Man HIV positive, woman HIV negative Woman HIV positive, man HIV negative Both HIV negative Total Weighted number Unweighted number Woman's age 15-19 0.0 0.0 0.0 99.9 100.0 508 438 20-29 0.5 0.1 0.7 98.7 100.0 3,080 2,730 30-39 1.0 1.0 1.0 97.0 100.0 2,247 2,072 40-49 0.4 0.3 0.2 99.1 100.0 1,073 943 Man's age 15-19 (0.0) (0.0) (0.0) (100.0) 100.0 34 30 20-29 0.2 0.0 0.2 99.6 100.0 1,767 1,481 30-39 0.8 0.8 1.1 97.3 100.0 2,493 2,237 40-49 1.0 0.5 0.4 98.0 100.0 1,706 1,611 50-59 0.0 0.1 0.7 99.2 100.0 908 824 Age difference between partners Woman older 0.4 0.6 2.6 96.4 100.0 357 350 Same age/man older by 0-4 years 0.9 0.5 0.8 97.8 100.0 2,011 1,722 Man older by 5-9 years 0.3 0.5 0.3 98.9 100.0 2,660 2,345 Man older by 10-14 years 0.6 0.2 0.3 98.8 100.0 1,314 1,172 Man older by 15+ years 1.0 0.4 1.3 97.3 100.0 566 594 Type of union Non-polygynous 0.7 0.4 0.7 98.3 100.0 6,419 5,642 Polygynous 0.0 0.9 0.5 98.6 100.0 465 516 Multiple partners in past 12 months1 Both no 0.6 0.3 0.7 98.3 100.0 6,499 5,752 Man yes, woman no 0.0 0.9 0.0 99.1 100.0 389 410 Woman yes, man no * * * * 100.0 15 8 Both yes * * * * 100.0 0 1 Concurrent sexual partners in past 12 months2 Both no 0.6 0.4 0.7 98.3 100.0 6,572 5,835 Man yes, woman no 0.0 1.1 0.0 98.9 100.0 333 346 Woman yes, man no * * * * 100.0 3 2 Residence Urban 2.7 0.7 3.4 93.1 100.0 1,135 1,235 Rural 0.2 0.4 0.1 99.3 100.0 5,773 4,948 Region Tigray 0.6 0.3 0.7 98.4 100.0 380 608 Affar 1.0 1.4 0.4 97.2 100.0 48 422 Amhara 0.4 0.4 1.4 97.7 100.0 1,896 920 Oromiya 0.4 0.4 0.2 99.1 100.0 2,776 1,028 Somali 0.3 0.5 0.4 98.8 100.0 115 284 Benishangul-Gumuz 0.3 0.2 0.4 99.2 100.0 79 591 SNNP 0.6 0.3 0.2 98.9 100.0 1,327 874 Gambela 3.3 1.1 3.5 92.1 100.0 21 383 Harari 0.9 0.3 0.8 97.9 100.0 19 378 Addis Ababa 4.9 2.3 2.7 90.2 100.0 223 338 Dire Dawa 1.6 2.1 1.5 94.8 100.0 23 357 Woman's education No education 0.4 0.3 0.3 99.1 100.0 4,555 4,059 Primary 0.9 0.7 1.0 97.4 100.0 1,971 1,689 Secondary 1.4 1.5 4.8 92.3 100.0 229 263 More than secondary 2.5 0.1 0.6 96.8 100.0 154 172 Man's education No education 0.3 0.2 0.2 99.3 100.0 3,128 2,804 Primary 0.6 0.5 0.8 98.1 100.0 3,142 2,666 Secondary 3.6 0.9 3.3 92.2 100.0 333 386 More than secondary 0.5 1.4 1.0 97.1 100.0 304 327 Wealth quintile Lowest 0.1 0.1 0.1 99.6 100.0 1,357 1,520 Second 0.3 0.1 0.1 99.5 100.0 1,486 1,130 Middle 0.2 0.7 0.0 99.1 100.0 1,468 1,087 Fourth 0.0 0.4 0.6 98.9 100.0 1,363 1,081 Highest 2.6 0.8 2.7 93.8 100.0 1,235 1,365 Total 0.6 0.4 0.7 98.3 100.0 6,908 6,183 Note: The table is based on couples for which a valid test result (positive or negative) is available for both partners. Total includes 25 couples with missing information on type of union and 12 couples with missing information on multiple partners in past 12 months. Figures in parentheses are based on 25-49 unweighted cases. An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. 1 A respondent is considered to have had multiple sexual partners in the past 12 months if he or she had sexual intercourse with 2 or more people during this time period. (Respondents with multiple partners include polygynous men who had sexual intercourse with 2 or more wives.) 2 A respondent is considered to have had concurrent partners if he or she had overlapping sexual partnerships with two or more people during the 12 months before the survey. (Respondents with concurrent partners include polygynous men who had overlapping sexual partnerships with two or more wives). Women’s Empowerment and Demographic and Health Outcomes • 245 WOMEN’S EMPOWERMENT AND DEMOGRAPHIC AND HEALTH OUTCOMES 14 he 2011 EDHS collected data on background characteristics of women, such as age, education, and employment status. Based on this information, earlier discussions in this report showed that Ethiopian women are less educated, have a lower level of literacy, and have less exposure to mass media than men. The EDHS data also indicate that women are predominantly engaged in agricultural occupations, have few manual skills, and are less likely than men to be engaged in professional, technical, or managerial fields. Educational attainment, literacy, exposure to mass media, and employment are critical contributors to women’s empowerment and exert considerable influence not only on the development of their personality, but also on solidifying their position in the household and in society in general. The 2011 EDHS collected additional data on characteristics specific to women’s empowerment through their work. These included receipt of cash earnings, magnitude of cash earnings relative to those of a husband or other partner.1 In addition, female and male survey respondents expressed their attitudes towards specific household decisions such as who makes decisions about major household purchases and about their own health care. Further, respondents expressed their attitudes towards certain actions, such as whether a man is justified in beating his wife if she refuses to have sex with him. Married women and men who received cash earnings were asked who had control over their cash income. This chapter also discusses men’s participation in household chores and women’s knowledge about law regarding domestic violence. Finally, two separate indices of empowerment that were developed are presented in this report. They are based on (1) the number of decisions in which the woman participates and (2) the number of situations in which a woman considers wife beating justifiable. The relative ranking of women on these indices is found to predict demographic and health outcomes, including contraceptive use, ideal family size, unmet need for family planning, access to reproductive health care, and, for the woman’s children, childhood mortality. 1 For the remainder of this chapter, the term husband refers to both the current/most recent husband (for currently/formerly legally married women) and to the current/most recent partner (for women currently living together with or who formerly lived together with their partner in an informal union). T Key Findings • About six currently married women of every ten and almost all currently married men age 15-49 were employed in the 12 months preceding the survey. • Three of every ten currently married employed women are not paid, compared with about one of every ten men. • More than one-third of currently married employed women who earn cash make independent decisions about how to spend their earnings. • About half of currently married women participate in three important decisions, pertaining to the woman’s own health care, major household purchases, and visits to her family or relatives. • Contraceptive use increases with women’s empowerment. • Access to antenatal care and delivery assistance from a skilled provider increase with women’s empowerment. 246 • Women’s Empowerment and Demographic and Health Outcomes 14.1 EMPLOYMENT AND FORM OF EARNINGS Employment is one aspect of social life in which gender roles and relationships emerge. Employment can be a source of empowerment for both women and men, especially if they are in control of the income they generate. In the 2011 EDHS respondents were asked whether they were employed at the time of the survey and, if not, whether they were employed in the 12 months preceding the survey. Table 14.1 shows the distribution of employment and cash earnings of currently married women and men who were employed at any time in the 12 months preceding the survey. Nearly six in every ten currently married women (57 percent) and almost all of currently married men age 15-49 (99 percent) had been employed in the 12 months preceding the survey. The percentage of currently married women who were employed increases with age up to age 44 and then decreases slightly for the oldest age group. The employment status of men does not vary by age, except for the youngest age group, where the proportion of men employed is the lowest. Table 14.1 Employment and cash earnings of currently married women and men Percentage of currently married women and men age 15-49 who were employed at any time in the past 12 months and the percent distribution of currently married women and men employed in the past 12 months by type of earnings, according to age, Ethiopia 2011 Age Among currently married respondents: Percent distribution of currently married respondents employed in the past 12 months, by type of earnings Total Weighted number of respondents Unweighted number of respondents Percentage employed in the past 12 months Weighted number of respondents Unweighted number of respondents Cash only Cash and in-kind In-kind only Not paid Missing/ don't know WOMEN Age 15-19 45.3 765 784 22.4 19.3 13.9 44.5 0.0 100.0 347 313 20-24 54.1 1,762 1,788 38.5 22.5 9.4 29.3 0.3 100.0 953 806 25-29 56.6 2,511 2,480 40.2 25.9 5.8 27.9 0.1 100.0 1,420 1,202 30-34 57.2 1,720 1,722 37.9 27.9 8.4 25.8 0.0 100.0 984 848 35-39 58.5 1,591 1,600 34.7 28.8 7.1 29.2 0.2 100.0 930 832 40-44 62.6 1,033 1,047 33.8 27.9 9.1 29.2 0.0 100.0 647 566 45-49 59.1 905 783 27.8 26.2 6.6 39.0 0.3 100.0 535 414 Total 15-49 56.5 10,287 10,204 35.7 26.0 8.0 30.1 0.1 100.0 5,817 4,981 MEN Age 15-19 95.9 64 66 13.2 47.6 6.4 32.7 0.0 100.0 61 62 20-24 98.4 583 575 16.6 61.8 9.9 11.7 0.0 100.0 574 558 25-29 99.9 1,481 1,378 26.9 57.7 7.0 8.4 0.0 100.0 1,480 1,366 30-34 99.1 1,274 1,385 25.9 60.4 5.7 8.0 0.0 100.0 1,263 1,367 35-39 99.8 1,516 1,377 22.7 63.7 7.3 6.3 0.0 100.0 1,513 1,369 40-44 99.1 1,061 1,108 23.0 59.2 7.1 10.8 0.0 100.0 1,052 1,092 45-49 99.6 892 886 18.0 64.6 10.2 7.2 0.0 100.0 889 880 Total 15-49 99.4 6,872 6,775 23.0 60.9 7.5 8.6 0.0 100.0 6,832 6,694 50-59 98.5 1,217 1,155 18.4 62.7 9.2 9.7 0.0 100.0 1,198 1,134 Total 15-59 99.3 8,089 7,930 22.3 61.2 7.7 8.7 0.0 100.0 8,030 7,828 Women’s Empowerment and Demographic and Health Outcomes • 247 Slightly more than one-third (36 percent) of employed women age 15-49 were paid in cash only for their work, compared with 23 percent of men of the same age group. One-quarter (26 percent) of women received payment both in cash and in kind, compared with 61 percent of men. Almost one-third (30 percent) of employed women were not paid, compared with 9 percent of men. 14.2 CONTROL OVER AND RELATIVE MAGNITUDE OF WOMEN’S AND HUSBAND’S EARNINGS 14.2.1 Control Over Wife’s Earnings Along with access to employment, control over cash earnings is a dimension of gender empowerment. Currently married, employed women who earn cash for their work were asked the relative magnitude of their earnings compared with their husbands’ earnings. In addition, they were asked who is the main decision-maker with regard to the use of their earnings. This information may provide some insight into women’s empowerment within the family and the extent of their control over decision-making in the household. Women who are employed and who receive cash earnings are more likely to have control over their own earnings. Table 14.2.1 shows the percent distribution of currently married women who received cash earnings for employment in the past 12 months, according to the woman’s perception of who controls their earnings and the magnitude of their earnings relative to those of their husbands. Only 36 percent of women said that they themselves mainly decide how their cash earnings are used. Fifty-five percent indicated that the decision is made jointly with their husbands, and eight percent said that the decision is made mainly by their husbands. 24 8 • W om en ’s E m po w er m en t a nd D em og ra ph ic a nd H ea lth O ut co m es Ta bl e 14 .2 .1 C on tro l o ve r w om en 's c as h ea rn in gs a nd re la tiv e m ag ni tu de o f w om en 's c as h ea rn in gs : W om en P er ce nt d is tri bu tio n of c ur re nt ly m ar rie d w om en a ge 1 5- 49 w ho re ce iv ed c as h ea rn in gs fo r e m pl oy m en t i n th e 12 m on th s pr ec ed in g th e su rv ey b y pe rs on w ho d ec id es h ow th ei r c as h ea rn in gs a re u se d an d by w he th er w om en e ar ne d m or e or le ss th an th ei r h us ba nd s, a cc or di ng to b ac kg ro un d ch ar ac te ris tic s, E th io pi a 20 11 B ac kg ro un d ch ar ac te ris tic P er so n w ho d ec id es h ow w ife 's c as h ea rn in gs a re u se d: To ta l W ife 's c as h ea rn in gs c om pa re d w ith hu sb an d' s ca sh e ar ni ng s: To ta l W ei gh te d nu m be r o f w om en U nw ei gh te d nu m be r o f w om en M ai nl y w ife W ife a nd hu sb an d jo in tly M ai nl y hu sb an d O th er M is si ng M or e Le ss A bo ut th e sa m e H us ba nd ha s no ea rn in gs D on 't kn ow / M is si ng A ge 15 -1 9 31 .8 51 .3 14 .0 1. 1 1. 8 10 0. 0 3. 5 76 .5 16 .1 0. 1 3. 8 10 0. 0 14 5 16 4 20 -2 4 26 .7 62 .9 10 .1 0. 1 0. 2 10 0. 0 11 .0 64 .1 22 .8 1. 2 0. 9 10 0. 0 58 2 55 8 25 -2 9 36 .1 55 .1 8. 1 0. 0 0. 7 10 0. 0 8. 7 71 .3 17 .9 1. 0 1. 1 10 0. 0 94 0 87 4 30 -3 4 37 .7 55 .1 6. 8 0. 0 0. 4 10 0. 0 10 .6 67 .7 17 .7 2. 6 1. 4 10 0. 0 64 8 60 1 35 -3 9 36 .8 54 .5 7. 4 0. 0 1. 3 10 0. 0 10 .2 63 .9 22 .0 1. 1 2. 8 10 0. 0 59 1 57 7 40 -4 4 40 .1 50 .0 9. 8 0. 0 0. 0 10 0. 0 14 .2 62 .0 20 .4 2. 1 1. 3 10 0. 0 39 9 38 4 45 -4 9 44 .0 48 .8 7. 2 0. 0 0. 0 10 0. 0 10 .3 64 .3 20 .9 1. 8 2. 7 10 0. 0 28 9 25 9 N um be r o f l iv in g ch ild re n 0 33 .0 57 .7 8. 1 0. 4 0. 7 10 0. 0 10 .9 71 .0 15 .9 1. 4 0. 8 10 0. 0 36 2 40 7 1- 2 33 .6 58 .7 7. 1 0. 1 0. 5 10 0. 0 10 .7 68 .0 18 .8 1. 1 1. 3 10 0. 0 1, 14 0 1, 21 5 3- 4 36 .8 53 .4 9. 0 0. 0 0. 8 10 0. 0 8. 7 68 .6 18 .3 2. 3 2. 1 10 0. 0 99 7 89 7 5+ 38 .4 51 .8 9. 4 0. 0 0. 4 10 0. 0 10 .7 62 .8 23 .5 1. 1 1. 9 10 0. 0 1, 09 3 89 8 R es id en ce U rb an 40 .2 55 .5 3. 9 0. 0 0. 4 10 0. 0 12 .0 73 .7 10 .9 2. 1 1. 3 10 0. 0 96 7 1, 19 1 R ur al 34 .3 54 .9 10 .1 0. 1 0. 7 10 0. 0 9. 5 64 .4 23 .1 1. 3 1. 8 10 0. 0 2, 62 6 2, 22 6 R eg io n Ti gr ay 19 .9 70 .7 8. 2 0. 9 0. 2 10 0. 0 4. 0 66 .4 29 .4 0. 0 0. 2 10 0. 0 23 1 36 1 A ffa r 21 .1 71 .0 7. 2 0. 7 0. 0 10 0. 0 9. 5 60 .4 24 .7 1. 8 3. 6 10 0. 0 17 12 0 A m ha ra 32 .2 60 .0 7. 4 0. 0 0. 4 10 0. 0 8. 2 53 .5 32 .7 2. 0 3. 5 10 0. 0 74 9 32 9 O ro m i y a 33 .7 55 .4 10 .6 0. 0 0. 3 10 0. 0 11 .8 64 .5 21 .7 1. 1 0. 9 10 0. 0 1, 42 2 49 1 S om al i 56 .2 35 .1 8. 7 0. 0 0. 0 10 0. 0 16 .7 55 .1 13 .2 14 .1 0. 9 10 0. 0 47 11 8 B en is ha n g ul -G um uz 22 .5 58 .2 18 .5 0. 0 0. 8 10 0. 0 10 .5 64 .2 21 .6 1. 7 1. 9 10 0. 0 47 34 0 S N N P 45 .3 46 .8 6. 6 0. 0 1. 3 10 0. 0 10 .1 82 .0 4. 9 1. 2 1. 7 10 0. 0 86 2 55 2 G am be la 45 .2 44 .3 8. 9 0. 0 1. 7 10 0. 0 11 .4 66 .2 15 .8 4. 2 2. 4 10 0. 0 18 29 5 H ar ar i 44 .3 45 .3 9. 0 0. 0 1. 4 10 0. 0 16 .3 71 .4 9. 8 0. 0 2. 5 10 0. 0 12 26 5 A dd is A ba ba 40 .8 56 .7 2. 2 0. 0 0. 3 10 0. 0 10 .8 75 .0 11 .2 1. 2 1. 8 10 0. 0 17 2 32 7 D ire D aw a 51 .4 44 .0 4. 1 0. 0 0. 5 10 0. 0 22 .8 59 .6 13 .3 2. 1 2. 2 10 0. 0 14 21 9 Ed uc at io n N o ed uc at io n 36 .6 52 .8 10 .1 0. 0 0. 5 10 0. 0 9. 5 63 .1 23 .4 2. 0 2. 0 10 0. 0 2, 08 3 1, 84 5 P rim ar y 35 .5 55 .8 7. 5 0. 2 1. 0 10 0. 0 10 .3 71 .2 16 .3 0. 6 1. 6 10 0. 0 1, 06 1 1, 03 1 S ec on da r y 40 .5 55 .1 4. 3 0. 0 0. 0 10 0. 0 8. 2 78 .9 10 .2 2. 4 0. 3 10 0. 0 17 6 24 4 M or e th an s ec on da r y 29 .2 69 .3 1. 5 0. 0 0. 0 10 0. 0 16 .3 71 .3 12 .2 0. 0 0. 2 10 0. 0 27 3 29 7 W ea lth q ui nt ile Lo w es t 35 .6 54 .6 8. 9 0. 0 0. 8 10 0. 0 9. 3 66 .0 20 .1 1. 3 3. 4 10 0. 0 57 6 63 8 S ec on d 34 .2 53 .9 11 .1 0. 1 0. 7 10 0. 0 7. 5 62 .4 27 .1 1. 9 1. 0 10 0. 0 58 5 45 0 M id dl e 33 .5 55 .5 10 .9 0. 2 0. 0 10 0. 0 10 .1 64 .2 23 .6 1. 0 1. 1 10 0. 0 67 8 50 4 Fo ur th 36 .6 54 .1 8. 4 0. 0 0. 9 10 0. 0 9. 9 65 .7 21 .0 1. 9 1. 5 10 0. 0 67 4 54 3 H i g he st 38 .0 56 .3 5. 2 0. 1 0. 5 10 0. 0 12 .3 72 .2 12 .5 1. 4 1. 6 10 0. 0 1, 08 0 1, 28 2 To ta l 35 .9 55 .0 8. 4 0. 1 0. 6 10 0. 0 10 .2 66 .9 19 .8 1. 5 1. 7 10 0. 0 3, 59 2 3, 41 7 248 • Women’s Empowerment and Demographic and Health Outcomes Women’s Empowerment and Demographic and Health Outcomes • 249 Table 14.2.1 also shows that 10 percent of women earn more in cash than their husbands, 67 percent earn less than their husbands, and 20 percent earn about the same amount as their husbands. Only 2 percent of women say that their husbands have no cash earnings. The likelihood that a currently married woman is the main decision-maker regarding the use of her cash earnings increases with the number of children the woman has. This suggests that women who have more children are more empowered than women with fewer or no children. The table also reveals that older women and women in the highest wealth quintile are more likely than other women to decide by themselves on how their cash earnings are used. Women in urban areas (40 percent) are more likely than women in rural areas (34 percent) to make independent decisions about the use of the money they earn. In contrast, in both rural and urban areas about the same proportions of currently married women (approximately 55 percent) make joint decisions with their husbands. There are regional variations in who makes decisions about how women’s earnings are used. Among regions the percentage of women who make independent decisions on use of their earnings ranges from 56 percent in Somali to 20 percent in Tigray. Women in Tigray and Affar (both 71 percent) are most likely to decide jointly with their husbands how to spend the money they make. In Benishangul-Gumuz, husbands are the most likely (19 percent) to make decisions on the use of their wives’ earnings. The proportion of women who make these decisions jointly with their husbands increases with education. Women in urban areas are more likely than women in rural areas to earn more than their husbands. Among the regions, Dire Dawa has the highest proportion of women who earn more than their husbands. Similarly, women with more than secondary-level education and those living in households in the highest wealth quintile are more likely than other women to earn more than their husbands. Fourteen percent of women in Somali mentioned that their husbands had no earnings—the highest percentage among the regions. 14.2.2 Control Over Husband’s Earnings Currently married men who receive cash earnings were asked who decides how his cash earnings are spent. As Table 14.2.2 shows, three-fourths of currently married men age 15-49 who receive cash earnings report that they decide jointly with their wives. Twenty-two percent say they mainly make the decisions themselves. Only a small proportion of men (2 percent) say that decisions on how their earnings are used are mainly made by their wives. Differences in background characteristics have little effect on men’s reporting of who decides how a husband’s earnings are used. Sixty-eight percent of currently married women whose husbands receive cash earnings reported that they make joint decisions about how to spend their husbands’ earnings. Twenty-seven percent reported that the decision is made by the husband only. Younger women, those living in rural areas, those in the Somali region, those with no education, and those belonging to households in the lowest wealth quintile are the least likely to participate in decision-making about how their husbands’ earning are used. 250 • Women’s Empowerment and Demographic and Health Outcomes Table 14.2.2 Control over men's cash earnings Percent distributions of currently married men age 15-49 who receive cash earnings and of currently married women age 15-49 whose husbands receive cash earnings, by person who decides how husband's cash earnings are used, according to background characteristics, Ethiopia 2011 Background characteristic Men Women Person who decides how husband’s cash earnings are used: Total Weighted number of men Un- weighted number of men Person who decides how husband’s cash earnings are used: Total Weighted number of women Un- weighted number of women Mainly wife Husband and wife jointly Mainly husband Missing Mainly wife Husband and wife jointly Mainly husband Missing Age 15-19 (0.0) (71.8) (27.7) (0.5) 100.0 37 41 4.1 61.5 31.5 0.3 100.0 745 749 20-24 1.5 73.6 22.3 0.0 100.0 450 458 3.0 69.8 26.4 0.3 100.0 1,747 1,763 25-29 2.4 74.8 21.6 0.6 100.0 1,252 1,168 5.0 70.0 24.9 0.1 100.0 2,496 2,454 30-34 1.5 76.3 22.1 0.0 100.0 1,090 1,178 3.7 68.2 27.8 0.3 100.0 1,695 1,691 35-39 2.2 76.5 20.9 0.4 100.0 1,308 1,190 3.6 67.1 29.2 0.1 100.0 1,583 1,583 40-44 3.8 73.0 23.1 0.1 100.0 865 898 7.4 66.6 25.8 0.2 100.0 1,020 1,024 45-49 2.3 72.1 24.9 0.7 100.0 734 721 4.5 69.1 26.1 0.0 100.0 891 768 Number of living children 0 2.5 71.3 22.2 1.2 100.0 560 600 4.3 64.8 28.0 0.6 100.0 992 1,065 1-2 2.5 77.1 20.2 0.1 100.0 1,908 1,972 4.4 69.4 26.1 0.1 100.0 3,168 3,336 3-4 2.4 76.3 21.0 0.3 100.0 1,672 1,557 3.9 70.3 25.4 0.3 100.0 2,776 2,672 5+ 2.0 71.5 26.3 0.3 100.0 1,595 1,525 4.7 66.2 29.0 0.1 100.0 3,241 2,959 Residence Urban 3.6 77.2 19.2 0.0 100.0 1,183 1,511 7.0 73.1 19.8 0.1 100.0 1,811 2,375 Rural 2.0 74.1 23.1 0.4 100.0 4,553 4,143 3.8 67.1 28.6 0.2 100.0 8,366 7,657 Region Tigray 4.6 78.8 15.5 0.2 100.0 280 443 4.9 75.5 19.1 0.0 100.0 614 975 Affar 4.9 64.4 30.1 0.4 100.0 45 405 7.9 57.5 33.9 0.0 100.0 101 932 Amhara 0.7 84.4 13.0 0.9 100.0 1,422 699 3.0 73.0 22.9 0.3 100.0 2,744 1,316 Oromiya 3.2 72.7 23.9 0.2 100.0 2,322 876 4.8 67.7 27.4 0.1 100.0 3,935 1,394 Somali 8.2 35.7 55.6 0.0 100.0 96 254 13.0 36.6 49.4 0.4 100.0 216 630 Benishangul- Gumuz 1.2 75.5 23.2 0.2 100.0 68 525 2.7 64.6 32.5 0.2 100.0 122 890 SNNP 1.1 68.6 30.2 0.0 100.0 1,182 801 2.8 63.3 33.6 0.2 100.0 2,001 1,281 Gambela 1.9 79.7 17.3 1.0 100.0 26 432 10.6 58.1 31.2 0.1 100.0 39 735 Harari 5.5 68.1 26.4 0.0 100.0 20 455 11.4 61.0 27.0 0.3 100.0 28 634 Addis Ababa 3.3 80.5 16.2 0.0 100.0 254 435 10.0 76.4 13.1 0.5 100.0 339 629 Dire Dawa 8.7 69.7 20.7 0.8 100.0 20 329 15.8 62.3 21.7 0.2 100.0 37 616 Education No education 2.3 74.6 21.9 0.8 100.0 2,299 2,129 4.2 65.9 29.4 0.2 100.0 6,652 6,457 Primary 2.0 73.5 24.3 0.0 100.0 2,719 2,559 4.2 71.0 24.2 0.2 100.0 2,844 2,689 Secondary 1.9 79.0 19.1 0.0 100.0 355 480 8.3 73.3 17.9 0.5 100.0 371 521 More than secondary 5.6 81.4 13.1 0.0 100.0 363 486 4.4 83.5 12.0 0.1 100.0 311 365 Wealth quintile Lowest 1.8 71.2 26.1 0.2 100.0 1,017 1,207 4.8 61.8 32.8 0.0 100.0 2,062 2,665 Second 1.9 75.9 21.6 0.5 100.0 1,112 875 3.3 69.7 26.4 0.3 100.0 2,095 1,653 Middle 2.4 75.9 20.8 0.3 100.0 1,130 897 3.1 65.8 30.5 0.2 100.0 2,066 1,561 Fourth 1.8 72.3 25.2 0.6 100.0 1,140 998 3.5 71.4 24.9 0.2 100.0 1,895 1,561 Highest 3.5 77.6 18.7 0.0 100.0 1,337 1,677 7.0 72.3 20.3 0.2 100.0 2,060 2,592 Total 15-49 2.3 74.8 22.3 0.3 100.0 5,736 5,654 4.3 68.2 27.0 0.2 100.0 10,177 10,032 50-59 2.1 73.4 24.0 0.5 100.0 972 918 na na na na na na na Total 15-59 2.3 74.6 22.5 0.3 100.0 6,708 6,572 na na na na na na na Note: Figures in parentheses are based on 25-49 unweighted cases. na = Not applicable 14.3 Control Over Married Women’s Earnings and Relative Size of Husband’s and Wife’s Earnings For currently married women who earned cash in the 12 months before the survey, Table 14.3 shows who decides how the woman’s cash earnings are used, according to the relative magnitude of the woman’s and the husband’s cash earnings. Women whose cash earnings exceed their husbands’ are more likely to decide for themselves how their earnings are used (46 percent) than women who earn less than their husbands (42 percent) or who earn the same as their husbands (11 percent). In contrast, women who earn the same as their husbands are the most likely to report that decisions on the use of their earnings are mainly made jointly with their husbands (81 percent). Among women whose husbands have no cash earnings, 37 percent say that they mainly make the decisions regarding the use of their earnings, and 59 percent share the decision with their husbands. W om en ’s E m po w er m en t a nd D em og ra ph ic a nd H ea lth O ut co m es • 2 51 Ta bl e 14 .3 W om en 's c on tro l o ve r t he ir ow n ea rn in gs a nd o ve r t ho se o f t he ir hu sb an ds P er ce nt d is tri bu tio n of c ur re nt ly m ar rie d w om en a ge 1 5- 49 w ith c as h ea rn in gs in th e la st 1 2 m on th s by p er so n w ho d ec id es h ow th e w ife 's c as h ea rn in gs a re u se d an d pe rc en t d is tri bu tio n of c ur re nt ly m ar rie d w om en a ge 1 5- 49 w ho se h us ba nd s ha ve c as h ea rn in gs b y pe rs on w ho d ec id es h ow th e hu sb an d' s ca sh e ar ni ng s ar e us ed , a cc or di ng to th e re la tio n be tw ee n w ife 's a nd h us ba nd 's c as h ea rn in gs , E th io pi a 20 11 W om en 's e ar ni ng s re la tiv e to hu sb an d' s ea rn in gs P er so n w ho d ec id es h ow w ife 's c as h ea rn in gs ar e us ed : To ta l W ei gh te d nu m be r o f w om en U nw ei gh te d nu m be r o f w om en P er so n w ho d ec id es h ow h us ba nd 's c as h ea rn in gs a re u se d: To ta l W ei gh te d nu m be r o f w om en U nw ei gh te d nu m be r o f w om en M ai nl y w ife W ife a nd hu sb an d jo in tly M ai nl y hu sb an d O th er M is si ng M ai nl y w ife W ife a nd hu sb an d jo in tly M ai nl y hu sb an d O th er M is si ng M or e th an h us ba nd 46 .4 50 .9 2. 3 0. 0 0. 0 10 0. 0 36 5 38 8 13 .5 69 .3 17 .1 0. 0 0. 0 10 0. 0 36 5 38 8 Le ss th an h us ba nd 41 .7 48 .8 9. 5 0. 1 0. 0 10 0. 0 2, 40 3 2, 28 2 4. 6 65 .0 30 .5 0. 0 0. 0 10 0. 0 2, 40 3 2, 28 2 S am e as h us ba nd 10 .7 80 .9 8. 3 0. 1 0. 0 10 0. 0 71 0 61 8 3. 0 83 .7 13 .3 0. 0 0. 0 10 0. 0 71 0 61 8 H us ba nd h as n o ca sh e ar ni ng s or di d no t w or k 36 .6 58 .8 0. 1 0. 0 0. 0 10 0. 0 53 65 na na na na na na na na W om an w or ke d bu t h as n o ca sh ea rn in gs na na na na na na na na 3. 2 71 .2 24 .9 0. 3 0. 4 10 0. 0 2, 21 7 1, 55 5 W om an d id n ot w or k na na na na na na na na 4. 3 66 .1 29 .0 0. 5 0. 2 10 0. 0 4, 42 1 5, 12 5 To ta l1 35 .9 55 .0 8. 4 0. 1 0. 6 10 0. 0 3, 59 2 3, 41 7 4. 3 68 .2 27 .0 0. 3 0. 2 10 0. 0 10 ,1 77 10 ,0 32 na = N ot a pp lic ab le 1 I nc lu de s ca se s w he re a w om an d oe s no t k no w w he th er s he e ar ne d m or e or le ss th an h er h us ba nd • 251Women’s Empowerment and Demographic and Health Outcomes 252 • Women’s Empowerment and Demographic and Health Outcomes Table 14.3 also shows who decides how the husband’s cash earnings are used. Women whose cash earnings exceed their husbands’ are more likely to report that they themselves decide how their husbands’ earning are used (14 percent) than are those who earn less than their husbands (5 percent) or those who earn the same as their husbands (3 percent). Women who earn the same as their husbands are the most likely to report that decisions on the use of their husbands’ earnings are mainly made jointly with their husbands (84 percent). Thirty-one percent of women who earn less their husbands say that their husbands decide on the use of their earnings. 14.4 OWNERSHIP OF ASSETS Lack of assets makes women vulnerable to various forms of violence and affects her decision- making power in the family. Although Ethiopian laws give equal property rights to women, in fact tradition and women’s low social and economic status limits their ownership of assets. Table 14.4.1 shows that 11 percent of women own a house alone, and 45 percent, jointly. Two percent of women own houses both alone and jointly. Sole ownership of a house or land increases with age and decreases with education and wealth. Rural women are more likely to own assets than urban women. For instance, while 66 percent of rural women own a house alone or jointly, only 30 percent of urban women do. Similarly, 60 percent of rural women own land alone or jointly versus 18 percent of urban women. As Table 14.4.2 shows, men age 15-49 are more likely than women age 15-49 to own a house or land alone and jointly (26-27 percent compared with 12-13 percent, respectively). Men age 35 or older, those living in rural areas, those with no education, and those living in households in the lowest wealth quintile are more likely than other men to own a house or land jointly. Table 14.4.1 Ownership of assets: Women Percent distribution of women age 15-49 by ownership of housing and land, according to background characteristics, Ethiopia 2011 Background characteristic Percentage who own a house: Per-centage who do not own a house Total Percentage who own land: Per- centage who do not own land Total Weighted number of women Un- weighted number of women Alone Jointly Alone and jointly Alone Jointly Alone and jointly Age 15-19 2.4 12.8 0.4 84.5 100.0 3.5 10.3 0.8 85.4 100.0 4,009 3,835 20-24 6.3 38.4 1.1 53.9 100.0 6.1 32.8 1.7 59.3 100.0 2,931 3,022 25-29 12.2 54.2 1.9 31.5 100.0 9.9 45.4 1.8 42.9 100.0 3,147 3,185 30-34 12.1 61.8 2.4 23.6 100.0 11.3 52.3 1.8 34.5 100.0 2,054 2,100 35-39 17.4 63.9 1.9 16.7 100.0 15.0 55.3 1.9 27.8 100.0 1,916 1,958 40-44 20.8 63.9 1.9 13.4 100.0 20.0 55.5 2.1 22.2 100.0 1,261 1,314 45-49 27.6 59.6 2.7 9.9 100.0 25.2 53.4 2.4 19.0 100.0 1,196 1,101 Residence Urban 7.3 21.7 1.2 69.7 100.0 4.9 12.5 0.9 81.6 100.0 3,947 5,329 Rural 12.3 51.7 1.6 34.2 100.0 12.0 46.0 1.8 40.1 100.0 12,568 11,186 Region Tigray 11.4 39.6 0.8 48.1 100.0 15.5 31.7 1.1 51.6 100.0 1,104 1,728 Affar 16.8 46.4 1.6 35.1 100.0 5.6 15.2 1.2 78.0 100.0 145 1,291 Amhara 11.4 45.6 1.6 41.3 100.0 12.0 33.7 2.0 52.4 100.0 4,433 2,087 Oromiya 14.6 42.8 1.6 40.8 100.0 12.0 40.7 1.7 45.6 100.0 6,011 2,135 Somali 7.9 51.0 2.9 38.0 100.0 5.5 32.4 3.2 58.7 100.0 329 914 Benishangul- Gumuz 7.6 59.0 1.5 31.8 100.0 7.2 48.7 1.0 42.9 100.0 174 1,259 SNNP 5.9 57.2 1.0 36.0 100.0 6.3 52.9 1.2 39.6 100.0 3,236 2,034 Gambela 26.6 23.7 4.3 45.2 100.0 18.5 18.6 5.0 57.8 100.0 69 1,130 Harari 7.8 22.5 7.1 62.2 100.0 5.2 17.3 6.3 71.0 100.0 49 1,101 Addis Ababa 5.6 10.1 2.4 81.7 100.0 2.5 3.4 0.8 93.2 100.0 896 1,741 Dire Dawa 7.2 24.2 0.5 68.0 100.0 4.2 17.4 0.5 77.8 100.0 69 1,095 Education No education 16.1 60.5 1.9 21.4 100.0 15.0 52.6 2.2 30.1 100.0 8,394 8,278 Primary 6.1 31.4 1.1 61.4 100.0 6.2 27.1 0.9 65.8 100.0 6,276 5,858 Secondary 6.2 15.2 0.8 77.7 100.0 3.1 9.3 1.3 86.1 100.0 1,117 1,395 More than secondary 5.2 19.0 2.5 73.2 100.0 2.8 7.8 0.9 88.5 100.0 728 984 Wealth quintile Lowest 14.9 55.2 2.2 27.4 100.0 14.3 46.5 2.1 37.0 100.0 2,986 3,711 Second 12.7 55.0 1.8 30.3 100.0 13.0 49.3 2.2 35.5 100.0 3,041 2,402 Middle 11.9 52.8 1.3 34.0 100.0 11.1 47.6 1.7 39.4 100.0 3,031 2,268 Fourth 10.6 46.4 1.3 41.7 100.0 10.0 42.3 1.2 46.5 100.0 3,215 2,505 Highest 7.1 22.2 1.3 69.3 100.0 5.3 13.8 1.0 79.9 100.0 4,242 5,629 Total 11.1 44.6 1.5 42.7 100.0 10.3 38.0 1.6 50.0 100.0 16,515 16,515 Women’s Empowerment and Demographic and Health Outcomes • 253 Table 14.4.2 Ownership of assets: Men Percent distribution of men age 15-49 by ownership of housing and land, according to background characteristics, Ethiopia 2011 Background characteristic Percentage who own a house: Percentage who do not own a house Total Percentage who own land: Percentage who do not own land Total Weighted number of men Unweighted number of men Alone Jointly Alone and jointly Alone Jointly Alone and jointly Age 15-19 3.7 8.3 0.2 87.8 100.0 8.2 8.2 0.2 83.3 100.0 3,013 2,832 20-24 17.3 12.2 0.2 70.1 100.0 20.7 13.0 1.0 65.2 100.0 2,319 2,330 25-29 31.5 29.0 0.6 39.0 100.0 29.6 25.2 1.7 43.6 100.0 2,297 2,274 30-34 36.8 40.0 0.4 22.8 100.0 30.0 35.2 1.5 33.3 100.0 1,483 1,682 35-39 40.5 42.0 1.0 16.5 100.0 38.4 35.8 2.0 23.8 100.0 1,648 1,579 40-44 38.6 45.8 1.7 13.8 100.0 37.8 39.0 2.6 20.6 100.0 1,121 1,210 45-49 38.8 50.1 2.0 9.1 100.0 36.6 45.7 1.5 16.1 100.0 952 961 Residence Urban 14.5 18.3 0.3 66.9 100.0 12.3 9.5 0.6 77.6 100.0 2,882 3,915 Rural 28.5 29.6 0.8 41.1 100.0 29.2 28.5 1.5 40.8 100.0 9,952 8,953 Region Tigray 10.5 30.5 0.4 58.6 100.0 18.0 21.9 0.6 59.5 100.0 770 1,235 Affar 37.6 17.2 0.3 44.9 100.0 17.3 6.0 0.5 76.2 100.0 101 910 Amhara 24.6 27.3 0.5 47.6 100.0 21.8 19.4 1.0 57.7 100.0 3,481 1,739 Oromiya 29.8 23.9 0.7 45.5 100.0 31.9 24.6 0.9 42.5 100.0 4,957 1,889 Somali 41.2 14.7 1.6 42.3 100.0 34.6 15.0 3.1 47.0 100.0 245 653 Benishangul-Gumuz 16.2 39.8 1.3 42.7 100.0 12.8 33.6 1.7 51.8 100.0 138 1,047 SNNP 24.1 38.2 0.8 36.9 100.0 25.3 40.1 2.9 31.7 100.0 2,307 1,550 Gambela 45.4 3.1 0.4 51.2 100.0 38.3 4.9 1.3 55.5 100.0 59 865 Harari 35.5 12.2 0.3 51.9 100.0 24.4 14.1 0.1 61.4 100.0 40 898 Addis Ababa 9.5 15.5 0.2 74.8 100.0 4.6 3.3 0.3 91.7 100.0 682 1,237 Dire Dawa 35.2 4.7 0.6 59.4 100.0 24.9 4.3 1.1 69.7 100.0 53 845 Education No education 35.1 37.6 0.7 26.5 100.0 33.5 32.3 1.7 32.4 100.0 3,785 3,659 Primary 22.4 25.2 0.8 51.7 100.0 24.0 24.2 1.3 50.5 100.0 6,813 6,334 Secondary 16.0 15.3 0.4 68.3 100.0 15.2 13.2 0.6 71.0 100.0 1,296 1,565 More than secondary 20.5 14.9 0.1 64.5 100.0 17.0 7.7 0.6 74.8 100.0 940 1,310 Wealth quintile Lowest 27.9 36.0 0.4 35.5 100.0 26.9 33.5 1.9 37.6 100.0 2,141 2,563 Second 27.6 33.2 0.7 38.5 100.0 28.7 32.0 1.0 38.3 100.0 2,362 1,891 Middle 32.8 27.8 1.1 38.4 100.0 32.9 25.5 1.5 40.0 100.0 2,454 1,935 Fourth 25.9 26.0 0.8 47.4 100.0 27.3 26.6 1.8 44.3 100.0 2,683 2,203 Highest 15.8 17.0 0.4 66.8 100.0 14.6 9.4 0.5 75.5 100.0 3,194 4,276 Total 15-49 25.3 27.1 0.7 46.9 100.0 25.4 24.3 1.3 49.0 100.0 12,834 12,868 50-59 44.8 45.3 1.3 8.6 100.0 40.8 42.1 3.0 14.1 100.0 1,276 1,242 Total 15-59 27.1 28.7 0.7 43.4 100.0 26.8 25.9 1.5 45.9 100.0 14,110 14,110 14.5 WOMEN’S PARTICIPATION IN DECISION-MAKING Decision-making can be a complex process, and the ability of women to make decisions that affect the circumstances of their own lives an essential aspect of their empowerment. In order to assess women’s decision-making autonomy, the 2011 EDHS collected information on women’s participation in three types of household decisions: respondent’s own health care, making major household purchases, and visits to family or relatives. Table 14.5 shows the percent distribution of currently married women according to the person in the household who usually makes decisions concerning these matters. Women are considered to participate in a decision if they usually make that decision alone or jointly with their husbands. The strength of the role of women in decision-making varies with the type of decision. Thirteen percent of currently married women make their own decisions on their own health care, while one woman of every four said that her husband mainly makes such decisions. Decisions on large household purchases are most likely to be made jointly by wife and husband (60 percent), while for almost half that percentage (33 percent) the husband alone mainly makes those decisions. Only 6 percent of women make these decisions by themselves. Sixty-one percent of women said that decisions to visit family or relatives are made jointly with their husbands. 254 • Women’s Empowerment and Demographic and Health Outcomes Currently married men also were asked who makes decisions about two specific issues: their own health care and major household purchases. As Table 14.5 shows, 35 percent of currently married men mainly make decisions on their own health, and 29 percent said that they make the decisions on major household purchases. Two-thirds of men make such decisions jointly with their wives. According to men, only in rare instances are wives the chief decision-makers about their husbands’ health care (2 percent) or about major household purchases (3 percent). Table 14.5 Participation in decision-making Percent distribution of currently married women and currently married men age 15-49 by person who usually makes decisions about various issues, Ethiopia 2011 Decision Mainly wife Wife and husband jointly Mainly husband Someone else Other Missing Total Weighted number of respondents Unweighted number of respondents WOMEN Own health care 13.4 61.0 24.9 0.4 0.2 0.2 100.0 10,287 10,204 Major household purchases 5.8 60.4 32.8 0.8 0.1 0.2 100.0 10,287 10,204 Visits to her family or relatives 17.2 60.6 21.3 0.6 0.1 0.2 100.0 10,287 10,204 MEN Own health care 2.0 62.7 34.6 0.5 0.1 0.1 100.0 6,872 6,775 Major household purchases 2.7 67.2 29.2 0.7 0.1 0.1 100.0 6,872 6,775 Table 14.6 Women's participation in decision-making by background characteristics Percentage of currently married women age 15-49 who usually make specific decisions either by themselves or jointly with their husbands, by background characteristics, Ethiopia 2011 Background characteristic Specific decisions Percentage who participate in all three decisions Percentage who participate in none of the three decisions Weighted number of women Unweighted number of women Woman's own health care Making major household purchases Visits to her family or relatives Age 15-19 68.8 61.0 72.8 46.6 14.7 765 784 20-24 72.7 67.0 77.6 54.2 11.3 1,762 1,788 25-29 76.0 68.0 76.9 55.4 11.3 2,511 2,480 30-34 74.2 67.5 80.5 54.9 10.2 1,720 1,722 35-39 76.1 64.7 78.6 56.0 12.2 1,591 1,600 40-44 75.2 65.1 76.6 52.9 10.8 1,033 1,047 45-49 73.9 65.1 79.9 56.1 11.8 905 783 Employment (last 12 months) Not employed 70.8 61.9 75.0 50.8 14.6 4,468 5,218 Employed for cash 78.4 71.1 81.9 58.7 7.7 3,592 3,417 Employed not for cash 75.1 66.6 76.8 54.4 11.5 2,216 1,556 Number of living children 0 73.6 67.7 76.9 53.8 12.3 1,018 1,104 1-2 75.7 68.1 78.4 56.5 10.3 3,193 3,381 3-4 75.0 67.6 78.6 55.1 10.7 2,809 2,718 5+ 72.7 62.6 76.9 51.8 13.1 3,267 3,001 Residence Urban 86.9 79.3 87.0 70.3 4.6 1,843 2,422 Rural 71.6 63.3 75.8 50.9 13.0 8,444 7,782 Region Tigray 87.1 68.9 84.1 61.3 5.9 620 984 Affar 72.8 64.7 70.3 51.5 14.7 104 960 Amhara 79.8 67.9 80.1 58.5 9.3 2,776 1,331 Oromiya 71.9 69.4 77.3 54.8 11.8 3,961 1,403 Somali 54.6 47.4 53.1 31.1 28.0 232 664 Benishangul-Gumuz 70.9 62.3 72.9 50.1 15.6 124 904 SNNP 67.6 55.2 75.0 44.8 15.2 2,022 1,295 Gambela 71.3 61.7 69.6 45.0 12.1 41 768 Harari 81.3 75.9 84.6 65.0 5.5 28 635 Addis Ababa 90.2 87.4 91.2 77.5 1.6 342 634 Dire Dawa 80.5 77.3 78.4 64.3 9.7 38 626 Education No education 71.1 63.2 75.3 50.8 13.7 6,735 6,569 Primary 77.5 67.6 80.3 55.8 8.8 2,862 2,739 Secondary 89.5 87.6 89.3 78.0 2.6 378 528 More than secondary 97.0 90.7 96.7 88.1 0.7 313 368 Wealth quintile Lowest 68.5 57.4 71.7 47.0 17.1 2,077 2,724 Second 71.8 63.8 75.7 51.4 13.2 2,117 1,676 Middle 70.1 62.9 75.9 49.6 12.6 2,083 1,585 Fourth 76.6 67.3 78.8 54.7 10.1 1,923 1,590 Highest 85.1 79.4 87.1 69.1 4.4 2,087 2,629 Total 74.4 66.1 77.8 54.4 11.5 10,287 10,204 Note: Total includes 13 cases with missing information on employment in the last 12 months. Women’s Empowerment and Demographic and Health Outcomes • 255 Table 14.6 shows the percentage of women who participate in the three decisions (woman’s health care, making household purchases, and visits to her family or relatives), by background characteristics. Women’s participation in decision-making increases with education. Urban women and women who are in the highest wealth quintile are more likely to participate in decision-making than rural women and those in lower wealth quintiles. Similarly, women who are employed for cash are more likely than women not employed or not employed for cash to participate in decision-making. Among regions women in Addis Ababa are the most involved in decision-making, while women in Somali are the least likely to be involved. Figure 14.1 shows the number of decisions in which currently married women participate. More than half of currently married women (54 percent) participate in three decisions, 21 percent participate in two of three decisions, and 12 percent do not participate in any decisions. Almost all men participate in decision-making regarding their own health (97 percent) as well as in making major household purchases (96 percent) (data not shown). Figure 14.1 Number of Decisions in Which Currently Married Women Participate EDHS 2011 12 13 21 54 0 1 2 3 Number of decisions 0 10 20 30 40 50 P er ce n t ag e 256 • Women’s Empowerment and Demographic and Health Outcomes 14.6 ATTITUDE TOWARDS WIFE BEATING All violence against women has serious consequences for their mental and physical well- being, including their reproductive and sexual health (WHO, 1999). Wife beating is a form of physical violence that particularly degrades women. It is also a violation of women’s human rights. Worldwide, abuse by a husband is one of the most common forms of violence against women (Heise et al., 1999). Acceptance of this practice reflects women’s low status and the perception that men are superior to women. In addition to adverse physical health outcomes, this form of violence lowers a woman’s self-esteem and her image in society, leading to her disempowerment. Domestic violence is common in Ethiopia, in both urban and rural families. When a society tolerates and accepts violence against women, its eradication is more difficult. The Government of Ethiopia revised its family law in 2000 and its criminal law in 2005 to protect the rights of women and children and to promote gender equality and equity. Women who believe that a husband is justified in hitting or beating his wife may believe themselves to be of low status. Such a perception could act as a barrier to accessing health care for themselves and their children, affect their attitude towards contraceptive use, and damage their general well-being. The 2011 EDHS gathered information on attitudes towards wife beating. Women and men were asked whether a husband is justified in beating his wife in various circumstances: if the wife burns the food, argues with him, goes out without telling him, neglects the children, or refuses sexual intercourse with him. Table 14.7.1 shows that two women of every three (68 percent) agree that wife beating is justified in at least one of the specified situations. The proportion of women who believe that wife beating is justified for at least one of the specified situations has declined from 81 percent in the 2005 EDHS. This trend suggests that Ethiopian women are less likely to accept wife beating than in the past. Women’s Empowerment and Demographic and Health Outcomes • 257 Table 14.7.1 Attitude towards wife beating: Women Percentage of all women age 15-49 who agree that a husband is justified in hitting or beating his wife for specific reasons, by background characteristics, Ethiopia 2011 Background characteristic Husband is justified in hitting or beating his wife if she: Percentage who agree with at least one specified reason Weighted number of women Unweighted number of women Burns the food Argues with him Goes out without telling him Neglects the children Refuses to have sexual intercourse with him Age 15-19 41.1 39.1 35.4 45.8 31.2 64.1 4,009 3,835 20-24 43.1 44.1 40.3 51.6 34.9 65.7 2,931 3,022 25-29 48.9 48.0 47.4 52.7 41.5 70.1 3,147 3,185 30-34 49.2 46.6 44.8 53.4 41.5 69.4 2,054 2,100 35-39 52.8 48.1 49.4 54.6 42.0 71.2 1,916 1,958 40-44 52.6 47.7 45.4 55.5 43.3 73.4 1,261 1,314 45-49 56.6 53.4 50.0 57.9 49.0 74.2 1,196 1,101 Employment (last 12 months) Not employed 48.4 46.5 43.9 53.2 40.5 68.7 6,971 7,975 Employed for cash 42.3 41.3 39.9 47.1 34.2 63.1 6,015 6,054 Employed not for cash 53.7 50.2 47.3 56.8 42.2 76.9 3,508 2,469 Number of living children 0 36.4 36.3 33.1 43.1 27.8 59.3 5,708 5,771 1-2 46.3 45.1 43.3 51.2 38.6 67.7 3,987 4,257 3-4 55.6 51.6 50.7 57.9 46.5 75.2 3,219 3,151 5+ 58.2 54.3 52.2 60.6 48.5 77.6 3,601 3,336 Marital status Never married 33.2 33.3 30.1 41.4 25.0 56.6 4,469 4,413 Married or living together 53.1 50.7 49.4 56.7 44.6 73.7 10,287 10,204 Divorced/separated/widowed 49.4 45.0 40.1 49.3 38.1 67.7 1,758 1,898 Residence Urban 21.9 25.6 24.3 34.7 18.1 45.8 3,947 5,329 Rural 55.3 51.6 49.1 57.1 45.0 75.5 12,568 11,186 Region Tigray 38.5 42.8 37.5 54.2 24.6 67.1 1,104 1,728 Affar 48.5 59.1 54.7 53.2 56.1 72.6 145 1,291 Amhara 48.9 47.4 41.0 54.0 35.0 75.2 4,433 2,087 Oromiya 47.4 42.9 42.7 48.2 41.6 65.6 6,011 2,135 Somali 48.3 62.2 59.8 66.5 59.4 82.2 329 914 Benishangul-Gumuz 40.4 39.0 38.7 45.8 30.6 62.4 174 1,259 SNNP 60.0 56.2 55.9 63.3 49.7 76.5 3,236 2,034 Gambela 39.5 43.1 43.9 50.1 29.1 65.9 69 1,130 Harari 32.0 35.1 35.7 45.6 34.6 58.4 49 1,101 Addis Ababa 7.2 10.5 12.0 17.0 6.5 23.9 896 1,741 Dire Dawa 25.0 27.7 32.0 33.9 25.4 46.8 69 1,095 Education No education 59.5 55.6 53.0 60.6 48.9 78.9 8,394 8,278 Primary 41.5 40.5 38.3 47.5 32.8 64.6 6,276 5,858 Secondary 15.3 19.0 18.9 30.7 14.1 41.6 1,117 1,395 More than secondary 5.9 10.1 9.4 17.9 6.4 21.7 728 984 Wealth quintile Lowest 60.4 58.0 53.9 63.4 49.9 80.9 2,986 3,711 Second 58.9 52.4 51.1 58.8 46.4 78.0 3,041 2,402 Middle 56.3 51.4 48.8 56.1 44.0 76.0 3,031 2,268 Fourth 48.6 47.0 44.7 52.6 41.7 70.6 3,215 2,505 Highest 22.3 25.9 24.8 34.8 18.7 45.8 4,242 5,629 Total 47.3 45.4 43.2 51.8 38.6 68.4 16,515 16,515 Note: Total includes 17 cases with missing information on employment in the last 12 months. The proportion of women who believe that a husband is justified in beating his wife increases with the woman’s age. Women who are currently married or living together and women who are employed but not for cash are more likely than other women to believe that there are occasions when wife beating is justified. In addition, the more children a woman has, the more likely she is to believe that wife beating is justified. Women’s attitudes towards wife beating were also examined according to residence and region. In rural areas three women of every four (76 percent) agree with at least one specified justification for wife beating, compared with 46 percent of urban women. Among regions there is a large variation in the proportion of women who agree with at least one specified justification for wife beating, from 82 percent in the Somali region to 24 percent in Addis Ababa. 258 • Women’s Empowerment and Demographic and Health Outcomes The acceptance of wife beating inversely correlates with education and wealth. Women with no education are more than three times as likely as women with more than secondary education to agree with at least one specified justification for wife beating (79 percent and 22 percent, respectively). Similarly, 81 percent of women in the lowest wealth quintile agree with at least one specified justification for wife beating, compared with 46 percent of women in the highest wealth quintile. Table 14.7.2 shows men’s attitudes towards wife beating. Forty-five percent of men agree that wife beating is justified in at least one of the specified situations. This proportion is slightly lower than in the 2005 EDHS (52 percent). Although the declines are not large, they may indicate that wife beating is increasingly unacceptable among men. Table 14.7.2 Attitude towards wife beating: Men Percentage of all men age 15-49 who agree that a husband is justified in hitting or beating his wife for specific reasons, by background characteristics, Ethiopia 2011 Background characteristic Husband is justified in hitting or beating his wife if she: Percentage who agree with at least one specified reason Weighted number of men Unweighted number of men Burns the food Argues with him Goes out without telling him Neglects the children Refuses to have sexual intercourse with him Age 15-19 25.5 28.7 25.6 34.1 25.8 51.0 3,013 2,832 20-24 22.1 25.8 25.0 32.1 21.5 44.1 2,319 2,330 25-29 21.1 25.1 26.4 30.8 21.0 44.4 2,297 2,274 30-34 19.4 23.4 20.4 26.3 18.7 39.4 1,483 1,682 35-39 20.4 25.0 26.8 25.9 19.0 43.2 1,648 1,579 40-44 18.8 22.7 24.7 27.8 17.9 42.0 1,121 1,210 45-49 21.1 26.8 27.8 28.3 19.8 43.0 952 961 Employment (last 12 months) Not employed 12.6 17.8 15.7 28.1 14.6 40.9 680 951 Employed for cash 20.9 25.0 24.9 28.6 20.6 43.4 8,615 8,841 Employed not for cash 26.0 29.2 28.2 34.6 24.5 49.2 3,527 3,062 Number of living children 0 21.6 25.0 23.5 30.2 22.2 44.4 6,465 6,534 1-2 21.7 25.4 26.5 29.9 19.0 43.7 2,338 2,463 3-4 21.2 27.1 27.0 29.9 20.4 47.3 2,038 1,922 5+ 23.6 27.3 28.0 30.8 22.4 45.4 1,994 1,949 Marital status Never married 21.6 24.5 22.9 29.5 22.0 44.1 5,600 5,641 Married or living together 21.9 26.7 27.0 30.4 20.7 45.3 6,872 6,775 Divorced/separated/widowed 24.9 27.8 28.1 37.9 23.9 49.8 363 452 Residence Urban 5.4 9.7 10.4 14.4 7.4 24.8 2,882 3,915 Rural 26.6 30.4 29.6 34.8 25.4 50.7 9,952 8,953 Region Tigray 23.2 25.7 27.5 35.5 19.6 46.0 770 1,235 Affar 23.0 29.6 29.4 29.8 26.8 42.6 101 910 Amhara 22.6 27.2 29.5 34.3 20.5 51.3 3,481 1,739 Oromiya 19.1 23.7 19.6 24.6 21.4 39.5 4,957 1,889 Somali 18.9 34.0 31.6 38.3 35.3 57.7 245 653 Benishangul-Gumuz 23.6 25.9 30.1 37.4 19.3 48.7 138 1,047 SNNP 32.7 33.8 35.9 40.6 27.7 55.5 2,307 1,550 Gambela 16.8 18.3 19.2 26.3 12.7 39.4 59 865 Harari 12.8 20.0 18.9 24.2 16.5 36.1 40 898 Addis Ababa 2.4 4.6 4.5 6.5 2.6 11.2 682 1,237 Dire Dawa 8.9 14.8 13.5 15.2 10.2 25.2 53 845 Education No education 31.1 36.5 37.1 40.1 29.7 58.8 3,785 3,659 Primary 22.0 25.7 24.1 30.5 21.6 45.2 6,813 6,334 Secondary 8.8 10.5 11.7 16.6 8.8 26.6 1,296 1,565 More than secondary 1.6 3.9 4.8 7.0 3.4 11.5 940 1,310 Wealth quintile Lowest 33.3 37.6 36.1 41.1 31.0 57.9 2,141 2,563 Second 29.1 33.7 33.2 39.9 29.2 55.3 2,362 1,891 Middle 26.3 30.6 29.6 33.3 24.5 51.5 2,454 1,935 Fourth 20.6 23.5 22.1 28.5 19.9 42.9 2,683 2,203 Highest 6.4 10.2 11.5 14.8 7.8 24.9 3,194 4,276 Total 15-49 21.8 25.8 25.3 30.2 21.3 44.9 12,834 12,868 50-59 21.5 25.9 27.9 29.6 21.9 42.8 1,276 1,242 Total 15-59 21.8 25.8 25.5 30.1 21.4 44.7 14,110 14,110 Note: Total includes 14 cases with missing information on employment in the last 12 months. Women’s Empowerment and Demographic and Health Outcomes • 259 As in the finding for female respondents, there are only small age differentials in men’s attitudes towards wife beating. The acceptability of wife beating is slightly higher among divorced, separated, and widowed men than among men who never married or who are currently married or living together with a woman. As was observed for female respondents, men living in rural areas are more likely than men living in urban areas to accept wife beating (51 percent and 25 percent, respectively). Like women’s beliefs, men’s beliefs vary greatly among regions. Men in Somali and SNNP are the most likely to agree that wife beating is justified for at least one specified reason (58 percent and 56 percent, respectively). Among men as among women, the acceptance of wife beating inversely correlates with education and wealth. Fifty-nine percent of men with no education agree with at least one specified reason for wife beating, compared with 12 percent of men with more than secondary education. Likewise, men in the lowest wealth quintile are more than twice as likely as men in the highest quintile to agree with at least one specified reason for wife beating (58 percent and 25 percent, respectively). 14.7 WOMEN’S EMPOWERMENT INDICES Two women’s empowerment indices were created for the 2011 EDHS—namely, women’s participation in making household decisions and women’s attitudes towards wife beating. The distribution of women by these two indices is then linked to select demographic and health indicators such as contraceptive use, ideal family size, unmet need for family planning, utilization of reproductive health care, and childhood mortality. The index of women’s participation in household decisions ranges in value from 0 to 3 and corresponds with the number of decisions in which women participate alone or jointly with their husbands/partners (see Table 14.6.1 for the list of decisions). This index reflects the degree of decision-making control that women are able to exercise in areas that affect their own lives and environments. A high score on this index indicates a high level of empowerment. The index of women’s attitudes towards wife beating ranges in value from 0 to 5 and corresponds with the total number of reasons for which the respondent feels that a husband is justified in beating his wife (see Table 14.7.1 for the list of reasons). A low score on this index reflects a greater sense of self-worth and higher status of women. Table 14.8 shows how these two indices relate to each other. In general, the expectation is that women who participate more in making household decisions will be less likely to endorse wife beating. The percentage of women who do not agree with wife beating under any circumstance increases from 15 percent among women who do not participate in any decisions to 33 percent among women who participate in all three decisions. Women who agree with all five justifications for wife beating are the least likely (45 percent ) to participate in decision-making, while women who disagree with all of the reasons to justify wife beating are the most likely to participate in all decisions (68 percent). In other words, participation in making household decisions declines as the number of justifications for wife beating increases. 260 • Women’s Empowerment and Demographic and Health Outcomes Table 14.8 Indicators of women's empowerment Percentage of currently married women age 15-49 who participate in all decision-making and the percentage who disagree with all of the reasons justifying wife-beating, by value on each of the indices of women's empowerment, Ethiopia 2011 Empowerment index Percentage who participate in all decision- making Percentage who disagree with all the reasons justifying wife beating Weighted number of women Unweighted number of women Number of decisions in which women participate1 0 na 14.6 1,183 1,302 1-2 na 19.4 3,513 3,520 3 na 33.1 5,591 5,382 Number of reasons for which wife- beating is justified2 0 68.4 na 2,707 2,990 1-2 53.2 na 2,266 2,122 3-4 50.6 na 2,646 2,499 5 44.8 na 2,669 2,593 na = Not applicable 1 See Table 14.6 for the list of decisions. 2 See Table 14.7.1 for the list of reasons. 14.8 CURRENT USE OF CONTRACEPTION BY WOMEN’S STATUS A woman’s ability to control her fertility and the method of contraception she uses are likely to be affected by her self-image and sense of empowerment. A woman who feels that she is unable to control other aspects of her life may be less likely to feel she can make decisions regarding fertility. She may also feel the need to choose methods that are easier to conceal from her husband or partner. Table 14.9 shows the relationship of each of the two empowerment indices to current use of contraceptive methods among currently married women age 15-49. The two empowerment indices and contraceptive use are positively associated. For example, the proportion of currently married women who are using any method of contraception rises, from 16 percent among women who do not participate in any household decision-making to 34 percent among women who participate in all three decisions. Use of any method of contraception decreases with the increase in the number of reasons that a woman thinks wife beating is justified. Four women in every ten (41 percent) who do not feel that wife beating is justified for any reason are using a contraceptive method, compared with two in every ten women (20 percent) who believe that wife beating is justified for all five reasons. Women’s Empowerment and Demographic and Health Outcomes • 261 Table 14.9 Current use of contraception by women's empowerment Percent distribution of currently married women age 15-49 by current contraceptive method, according to selected indices of women's status, Ethiopia 2011 Empowerment index Any method Any modern method1 Modern methods Any traditional method Not currently using Total Weighted number of women Unweighted number of women Female sterilization Temporary modern female methods1 Male condom Number of decisions in which women participate2 0 16.3 16.0 0.1 15.9 0.0 0.3 83.7 100.0 1,183 1,302 1-2 24.6 23.6 0.4 23.0 0.1 1.1 75.4 100.0 3,513 3,520 3 33.7 32.1 0.6 31.3 0.3 1.6 66.3 100.0 5,591 5,382 Number of reasons for which wife-beating is justified3 0 40.8 37.9 1.1 36.2 0.5 2.9 59.2 100.0 2,707 2,990 1-2 31.2 30.0 0.3 29.6 0.1 1.2 68.8 100.0 2,266 2,122 3-4 22.8 22.3 0.2 22.1 0.0 0.5 77.2 100.0 2,646 2,499 5 19.8 19.3 0.2 19.1 0.0 0.5 80.2 100.0 2,669 2,593 Total 28.6 27.3 0.5 26.7 0.2 1.3 71.4 100.0 10,287 10,204 Note: If more than one method is used, only the most effective method is considered in this tabulation. 1 Pill, IUD, injectables, implants, female condom, diaphragm, foam/jelly, and lactational amenorrhea method 2 See Table 14.6 for the list of decisions. 3 See Table 14.7.1 for the list of reasons 14.9 IDEAL FAMILY SIZE AND UNMET NEED BY WOMEN’S STATUS As a woman becomes more empowered, she is more likely to have a say in the number (ideal family size) and spacing of children she desires. Table 14.10 depicts how a woman’s ideal family size and her unmet need for family planning vary by the two indices of women’s empowerment. There is a positive relationship between the two indices and women’s mean ideal number of children. For instance, women who participate in all three decisions desire an average of 4.7 children, compared with 5.6 children among women who do not participate in any decisions. Similarly, women who accept all five reasons for wife beating have the highest mean ideal number of children, at 5.1, compared with 3.9 children for women who do not justify wife beating for any reason. Table 14.10 further shows that the percentage of currently married women with an unmet need for family planning decreases with an increase in the number of decisions in which women participate and tends to increase with the number of reasons for which women believe wife beating is justified. For example, 29 percent of women who participate in no household decisions have an unmet need for family planning services, compared with 23 percent of women who participate in all three decisions. 262 • Women’s Empowerment and Demographic and Health Outcomes Table 14.10 Women's empowerment and ideal number of children, and unmet need for family planning Mean ideal number of children for women 15-49 and the percentage of currently married women age 15-49 with an unmet need for family planning, by indices of women's empowerment, Ethiopia 2011 Empowerment index Mean ideal number of children1 Weighted number of women Unweighted number of women Percentage of currently married women with an unmet need for family planning2 Weighted number of women Unweighted number of women For spacing For limiting Total Number of decisions in which women participate3 0 5.6 968 1,072 20.2 8.3 28.5 1,183 1,302 1-2 5.0 3,057 3,041 18.0 9.6 27.5 3,513 3,520 3 4.7 4,869 4,779 14.5 8.7 23.2 5,591 5,382 Number of reasons for which wife-beating is justified4 0 3.9 4,845 5,404 14.0 7.5 21.4 2,707 2,990 1-2 4.1 3,444 3,243 15.1 10.4 25.6 2,266 2,122 3-4 4.5 3,338 3,165 19.1 9.6 28.7 2,646 2,499 5 5.1 3,130 2,983 16.9 8.6 25.5 2,669 2,593 Total 4.3 14,757 14,795 16.3 9.0 25.3 10,287 10,204 1 Mean excludes respondents who gave non-numeric responses. 2 See Table 7.12.1 for the definition of unmet need for family planning. 3 Restricted to currently married women. See Table 14.6 for the list of decisions. 4 See Table 14.7.1 for the list of reasons. 14.10 WOMEN’S STATUS AND REPRODUCTIVE HEALTH CARE In societies where health care is widely available, women’s status may not affect their access to health services. In other societies, however, increased empowerment of women is likely to increase their ability to seek and use health services to better meet their own reproductive health needs. Table 14.11 examines whether the extent to which women receive antenatal, delivery, and postnatal care services from health workers varies by their status as measured on the two women’s empowerment indices. The proportion of women who received antenatal care from health personnel for a live birth in the five years before the survey increases with the number of decisions in which the woman participates, from 24 percent of women who do not participate in any decisions to 49 percent of those who have a say in all three decisions. Similarly, among women who do not justify wife beating for any reason, 58 percent received antenatal care from health personnel, 26 percent received assistance from health personnel at delivery, and 14 percent received postnatal care from a health care provider within the first two days after delivery. In contrast, the corresponding proportions among women who justify wife beating for all five specified reasons were only 33 percent, 5 percent, and 2 percent. Women’s Empowerment and Demographic and Health Outcomes • 263 Table 14.11 Reproductive health care by women's empowerment Percentage of women age 15-49 with a live birth in the five years preceding the survey who received antenatal care, delivery assistance, and postnatal care from health personnel for the most recent birth, by indicators of women's empowerment, Ethiopia 2011 Empowerment indicator Received antenatal care from health personnel Received delivery assistance from health personnel Received postnatal care from health personnel within the first two days after delivery1 Weighted number of women with a child born in the last five years Unweighted number of women with a child born in the last five years Number of decisions in which women participate2 0 24.1 3.7 2.4 855 973 1-2 40.1 9.0 5.4 2,543 2,544 3 48.7 16.2 8.1 3,787 3,526 Number of reasons for which wife-beating is justified3 0 58.0 25.9 14.1 1,878 2,085 1-2 44.8 13.0 6.0 1,744 1,582 3-4 36.9 8.5 5.3 2,108 1,966 5 32.9 5.0 2.4 2,177 2,131 Total 42.6 12.7 6.7 7,908 7,764 Note: “Health personnel” includes doctor, nurse, or midwife. 1 Includes both women who gave birth in a health facility and those who did not give birth in a health facility. 2 Restricted to currently married women. See Table 14.6 for the list of decisions. 3 See Table 14.7.1 for the list of reasons. 14.11 DIFFERENTIALS IN INFANT AND CHILD MORTALITY BY WOMEN’S STATUS The ability of women to access information, make decisions, and act effectively in their own interest, or in the interest of those who depend on them, are essential aspects of the empowerment of women. If women, the primary caretakers of children, are empowered, the health and survival of their infants will be enhanced. In fact, maternal empowerment fits into Mosley and Chen’s framework on child survival as an individual-level variable that affects child survival through the proximate determinants (Mosley and Chen, 1984). Table 14.12 presents childhood mortality rates by the two indices of women’s status—participation in household decision-making and attitude towards wife beating. With improvement in women’s empowerment status, the likelihood of their children surviving increases. For instance, the infant mortality rate and under-five mortality rate are 69 deaths per 1,000 live births and 101 deaths per 1,000 live births, respectively, for children whose mother participates in all three specified decisions. In contrast, for children whose mothers do not participate in any of the decisions, the infant mortality rate is 84 deaths, and under-five mortality rate is 122 deaths per 1,000 live births. Table 14.12 Early childhood mortality rates by women's status Infant, child, and under-five mortality rates for the 10-year period preceding the survey, by indices of women's status, Ethiopia 2011 Empowerment index Infant mortality (1q0) Child mortality (4q1) Under-five mortality (5q0) Number of decisions in which women participate1 0 84 42 122 1-2 78 44 119 3 69 35 101 Number of reasons for which wife-beating is justified2 0 73 32 103 1-2 63 41 101 3-4 75 38 110 5 82 45 122 1 Restricted to currently married women. See Table 14.6 for the list of decisions. 2 See Table 14.7.1 for the list of reasons. 264 • Women’s Empowerment and Demographic and Health Outcomes A similar pattern is seen with women’s attitude towards wife beating. Infant and under-five mortality rates are lower for the children of women who do not justify wife beating for any reason than for those who justify wife beating for some or all reasons. 14.12 MEN’S PARTICIPATION IN HOUSEHOLD CHORES In the 2011 EDHS currently married women were asked whether their husbands help with household chores. As Table 14.13 shows, 43 percent of currently married women reported that their husbands participate in household chores. However, only one woman of every four (24 percent) mentioned that her husband participates every day in doing household chores, while 59 percent say that their husbands rarely participate in doing household chores. The participation of husband in doing household chores increases with women’s education from 38 percent for women with no education to 70 percent for women with more than secondary education. Similarly, women in the highest wealth quintile (52 percent) are considerably more likely to report that their husbands participate in the household chores than women in the lowest quintile (38 percent). Fifty-four percent of currently married women who reside in urban areas say that their husbands participate in household chores, compared with 41 percent of women in rural areas. Table 14.13 Men's participation in household chores Percentage of currently married women age 15-49 who report that their husbands help with the household chores, and, among women whose husbands help with household chores, the frequency of that help, by background characteristics, Ethiopia 2011 Background characteristic Women whose husband participates in household chores Weighted number of women Unweighted number of women Among women whose husband participates in household chores, frequency of the chores: Every day At least once a week Rarely Total Weighted number of women Unweighted number of women Age 15-19 45.0 765 784 22.9 16.5 60.6 100.0 344 283 20-24 47.2 1,762 1,788 25.9 15.6 58.5 100.0 832 786 25-29 45.2 2,511 2,480 27.2 17.6 55.2 100.0 1,136 1,066 30-34 47.2 1,720 1,722 20.5 19.4 60.1 100.0 813 729 35-39 40.2 1,591 1,600 22.7 15.3 61.9 100.0 639 637 40-44 35.4 1,033 1,047 25.3 15.2 59.5 100.0 366 349 45-49 31.5 905 783 16.4 18.6 64.9 100.0 285 236 Residence Urban 53.6 1,843 2,422 22.9 15.7 61.4 100.0 987 1,264 Rural 40.6 8,444 7,782 24.2 17.4 58.5 100.0 3,427 2,822 Region Tigray 58.3 620 984 16.9 20.6 62.6 100.0 361 572 Affar 27.1 104 960 31.9 12.6 55.5 100.0 28 226 Amhara 41.2 2,776 1,331 22.0 17.2 60.9 100.0 1,145 542 Oromiya 38.9 3,961 1,403 20.8 17.1 62.1 100.0 1,542 537 Somali 29.1 232 664 21.1 26.3 52.6 100.0 68 185 Benishangul-Gumuz 37.6 124 904 21.3 18.9 59.7 100.0 47 328 SNNP 48.6 2,022 1,295 33.5 15.5 51.1 100.0 983 623 Gambela 42.4 41 768 24.7 19.1 56.0 100.0 17 258 Harari 32.3 28 635 32.2 18.5 49.3 100.0 9 199 Addis Ababa 58.1 342 634 23.9 13.1 63.0 100.0 198 368 Dire Dawa 42.7 38 626 30.1 18.6 50.8 100.0 16 248 Education No education 38.3 6,735 6,569 24.9 18.3 56.7 100.0 2,579 2,259 Primary 48.0 2,862 2,739 20.0 16.2 63.8 100.0 1,375 1,238 Secondary 64.5 378 528 23.2 12.7 64.1 100.0 243 325 More than secondary 69.6 313 368 36.5 11.0 52.5 100.0 218 264 Wealth quintile Lowest 38.1 2,077 2,724 23.2 17.8 59.0 100.0 791 814 Second 40.8 2,117 1,676 26.2 15.0 58.8 100.0 863 651 Middle 39.8 2,083 1,585 26.5 15.1 58.4 100.0 829 620 Fourth 44.0 1,923 1,590 19.0 22.4 58.6 100.0 846 635 Highest 52.0 2,087 2,629 24.4 15.2 60.4 100.0 1,086 1,366 Total 42.9 10,287 10,204 23.9 17.0 59.1 100.0 4,415 4,086 Women’s Empowerment and Demographic and Health Outcomes • 265 14.13 LAW AGAINST DOMESTIC VIOLENCE The Ethiopian Criminal Code of 2005 addresses human rights issues, women’s and children’s rights in particular. Using various media, concerned government institutions and development partners have been educating the community about these laws, particularly the laws that prevent gender-based violence. The 2011 EDHS collected information on knowledge of the existing law that prevents a husband from beating his wife. Table 14.14 shows that half of currently married women (49 percent) know there is a law against a husband beating his wife. There are small variations by age in the level of knowledge. Knowledge about the law is positively related to women’s education and wealth. For example, 42 percent of women with no education know that there is law against wife beating, compared with 72 percent of women with more than secondary education. Similarly, women belonging to the wealthiest households are nearly twice as likely to know about the law (62 percent) than those in the lowest wealth quintile (37 percent). Knowledge of the law varies with residence and among regions as well. Sixty-two percent of urban women and 45 percent of rural women are aware of the existence of such a law. Among the regions 27 percent in the Somali region know of the law, compared with 72 percent in the Tigray region. Table 14.14 Knowledge of law against domestic violence Percentage of women age 15-49 who know that there is a law in Ethiopia against wife beating, by background characteristics, Ethiopia 2011 Background characteristic Percentage of women who know that there is a law against wife beating Weighted number of women Unweighted number of women Age 15-19 47.3 4,009 3,835 20-24 49.7 2,931 3,022 25-29 48.2 3,147 3,185 30-34 48.4 2,054 2,100 35-39 50.2 1,916 1,958 40-44 53.0 1,261 1,314 45-49 48.8 1,196 1,101 Residence Urban 61.7 3,947 5,329 Rural 44.9 12,568 11,186 Region Tigray 72.2 1,104 1,728 Affar 30.5 145 1,291 Amhara 45.2 4,433 2,087 Oromiya 50.8 6,011 2,135 Somali 27.2 329 914 Benishangul-Gumuz 54.6 174 1,259 SNNP 42.9 3,236 2,034 Gambela 36.4 69 1,130 Harari 43.6 49 1,101 Addis Ababa 58.1 896 1,741 Dire Dawa 58.3 69 1,095 Education No education 42.0 8,394 8,278 Primary 52.5 6,276 5,858 Secondary 65.6 1,117 1,395 More than secondary 71.6 728 984 Wealth quintile Lowest 37.4 2,986 3,711 Second 43.4 3,041 2,402 Middle 47.1 3,031 2,268 Fourth 49.0 3,215 2,505 Highest 62.2 4,242 5,629 Total 48.9 16,515 16,515 Adult and Maternal Mortality • 267 ADULT AND MATERNAL MORTALITY 15 dult and maternal mortality rates are key indicators of the health status of a population. In Ethiopia they are also national development indicators. Estimation of these mortality rates requires comprehensive and accurate reporting of adult deaths and maternal deaths. The maternal mortality module included in the EDHS gathers valuable information that fills this gap. This chapter includes results based on sibling history data collected in the Sibling Survival Module (commonly referred to as the ‘Maternal Mortality Module’) of the 2011 EDHS Woman’s Questionnaire. In addition to adult mortality rates for five-year age groups, this chapter includes a summary measure (35q15) that represents the probability of dying between exact ages 15 and 50. For the measurement of trends in adult mortality probabilities, 35q15 for the 2000 and 2005 EDHS have also been calculated and are presented in Table 15.2. The term ‘maternal mortality’ used in this chapter (and in previous EDHS surveys), corresponds to the term ‘pregnancy-related mortality’ as defined in the latest International Classification of Diseases (ICD-10). The ICD-10 definition of a pregnancy-related death is ‘the death of a woman while pregnant or within 42 days of termination of pregnancy, irrespective of the cause of death.’ In keeping with this definition, the Sibling Survival Module used in the DHS surveys measures only the timing of deaths and not the cause of death. The data collected in the EDHS questionnaire are based on information about deaths during the two months following a birth, however, rather than 42 days following a birth. 15.1 ASSESSMENT OF DATA QUALITY To obtain a sibling history, the 2011 EDHS first asked each female respondent to list all children born to her biological mother, starting with the firstborn. The survey then asked the respondent whether each of these siblings was still alive. For living siblings, the questionnaire asked the current age of each sibling. For deceased siblings, the age at death and the number of years since death were recorded. When a respondent could not provide precise information on age at death or years since death, approximate but quantitative answers were accepted. For sisters who died at age 12 or older, the EDHS asked three questions to determine whether the death was maternal: ‘Was [NAME OF SISTER] pregnant when she died?’ and, if the response was negative, ‘Did she die during A Key Findings • Direct mortality estimates find that the level of adult mortality is slightly higher among men than among women (5.0 deaths and 4.1 deaths per 1,000 population, respectively). • Sixteen percent of women and 18 percent of men are likely to die between exact ages 15 and 50. These probabilities have decreased for both women and men since 2000, with most of the decreases occurring between 2005 and 2011. • Maternal deaths account for 30 percent of all deaths to women age 15-49. The maternal mortality rate for the seven-year period preceding the survey was 1.14 maternal deaths per 1,000 woman-years of exposure. • The maternal mortality ratio was 676 maternal deaths per 100,000 live births for the seven- year period preceding the survey. This ratio is not significantly different from those reported in the 2005 EDHS and the 2000 EDHS. 268 • Adult and Maternal Mortality childbirth?’ and, if negative again, ‘Did she die within two months after the end of a pregnancy or childbirth?’ Table C.8 in Appendix C shows that in the 2011 EDHS a total of 94,361 siblings were recorded in the sibling histories. The survival status was not reported for 91 siblings (0.1 percent). Among surviving siblings current age was not reported for 47 siblings (0.1 percent). For more than 99 percent of deceased siblings, both age at death (AD) and years since death (YSD) were reported. In 0.2 percent of cases both the AD and YSD were missing. The sex ratio of the enumerated siblings (the ratio of brothers to sisters times 100) is 109.4 (Table C.9), which is higher than the expected value of 102–106, a difference that suggests some underreporting of sisters. 15.2 ESTIMATES OF ADULT MORTALITY One way to assess the quality of data used to estimate maternal mortality is to evaluate the plausibility and stability of overall adult mortality estimates. If the estimated rates of overall adult mortality are implausible, rates based on a subset of deaths—maternal mortality in particular—are likely to have serious problems. Moreover, levels and trends in overall adult mortality have important implications for health and social programmes in Ethiopia in their own right, especially with regard to the potential impact of the AIDS epidemic, other infectious diseases, and noncommunicable diseases. The direct estimation of adult mortality uses the reported ages at death and years since death of the respondents’ brothers and sisters. Mortality rates are calculated by dividing the number of deaths in each age group of women and men by the total person-years of exposure to the risk of dying in that age group during a specified period prior to the survey. To have a sufficiently large number of adult deaths to generate a robust estimate, the rates are calculated for the seven-year period preceding the survey (roughly mid-2004 to mid-2011). Nevertheless, the age-specific mortality rates obtained in this manner are subject to considerable sampling variation. Table 15.1 shows age-specific mortality rates for women and men age 15-49 for the seven- year period preceding the survey. Overall, the level of adult mortality is slightly higher among men (5.0 deaths per 1,000 population) than among women (4.1 deaths per 1,000 population). Age-specific mortality rates appear to be higher for men than for women in most age groups, but none of the differences are statistically significant. The age-specific mortality rates generally show the expected increases with increasing age, for both women and men. Confidence intervals for these rates can be found in Appendix Table B.16. The confidence intervals for many of the five-year mortality rates overlap. Adult and Maternal Mortality • 269 Table15.1 Adult mortality rates Direct estimates of female and male mortality for the seven years preceding the survey by five-year age groups, Ethiopia 2011 Age Deaths Exposure years Mortality rates1 WOMEN 15-19 92 39,187 2.35 20-24 108 41,289 2.63 25-29 129 36,532 3.53 30-34 188 27,449 6.85 35-39 79 19,166 4.15 40-44 85 11,512 7.37 45-49 51 6,899 7.34 15-49 732 182,034 4.13a MEN 15-19 136 40,426 3.38 20-24 138 42,577 3.25 25-29 189 37,080 5.11 30-34 166 28,989 5.74 35-39 125 20,030 6.22 40-44 86 12,095 7.11 45-49 70 7,610 9.19 15-49 911 188,808 5.01a 1 Expressed per 1,000 population a Age-adjusted rate Table 15.2 shows a summary measure of the risk of dying between exact ages 15 and 50 (35q15). Based on the 2011 EDHS, 16 percent of women and 18 percent of men are likely to die between age 15 and age 50. Estimates of 35q15 based on the 2000 and 2005 EDHS also show that in 2000 men had a higher probability of dying between exact ages 15 and 50 than women (28 percent of men versus 22 percent of women) and in 2005 they had similar probabilities of dying between these ages (21 percent of men and 22 percent of women). However, in the eleven years between the 2000 and 2011 EDHS surveys, the probability of dying between exact ages 15 and 50 decreased for both women and men, from 22 percent to 16 percent for women and from 28 percent to 18 percent for men, showing a 29 percent decrease for women and a 34 percent decrease for men. For women, much of this decrease is seen in the most recent six years, between 2005 and 2011, whereas for men the largest decrease is observed between 2000 and 2005. Confidence intervals for the 35q15 estimates can be found in Appendix Table B.16. Table 15.2 Adult mortality probabilities The probability of dying between exact ages 15 and 50 for women and men for the seven years preceding the survey, Ethiopia 2000, 2005, and 2011 Survey Women Men 35q151 (2011 EDHS) 157 181 35q151 (2005 EDHS) 217 207 35q151 (2000 EDHS) 221 275 1 The probability of dying between exact ages 15 and 50, expressed per 1,000 person-years of exposure 270 • Adult and Maternal Mortality 15.3 ESTIMATES OF MATERNAL MORTALITY Maternal mortality in Ethiopia and other developing countries can be estimated using two procedures: the sisterhood method (Graham et al., 1989) and a direct estimation variant of the sisterhood method (Rutenberg and Sullivan, 1991). In this report the direct estimation procedure is applied. Table 15.3 presents direct estimates of maternal mortality for the seven-year period preceding the survey. The maternal mortality rate among women age 15-49 is 1.14 maternal deaths per 1,000 woman-years of exposure. This rate is 15 percent lower than that reported in the 2005 EDHS and 32 percent lower than in the 2000 EDHS. By five-year age groups, the maternal mortality rate is highest among women 30-34 (2.53), followed by those age 35-39 (1.53). Confidence intervals for the maternal mortality rates can be found in Appendix Table B.16. In the 2011 EDHS maternal deaths represent 30 percent of all deaths to women age 15-49, compared with 21 percent in the 2005 EDHS and 25 percent in the 2000 EDHS. The percentage of female deaths that are maternal varies by age and ranges from 10 percent among women 45-49 to 37 percent of all deaths among women 30-39. Table 15.3 Maternal mortality Direct estimates of maternal mortality rates for the seven years preceding the survey, by five- year age groups, Ethiopia 2011 Age Percentage of female deaths that are maternal Maternal deaths Exposure years Maternal mortality rate1 15-19 21.7 20 39,187 0.52 20-24 36.1 39 41,289 0.94 25-29 28.7 37 36,532 1.03 30-34 36.7 69 27,449 2.53 35-39 36.7 29 19,166 1.53 40-44 18.8 16 11,512 1.43 45-49 9.8 5 6,899 0.70 15-49 29.6 217 182,034 1.14a General fertility rate (GFR)2 169a Maternal mortality ratio (MMR)3 676 CI: (541, 810) Lifetime risk of maternal death4 0.036 2005 EDHS Maternal mortality ratio (MMR)3 673 CI: (548, 799) 2000 EDHS Maternal mortality ratio (MMR)3 871 CI: (703, 1,039) CI: Confidence interval 1 Expressed per 1,000 woman-years of exposure 2 Expressed per 1,000 women age 15-49 3 Expressed per 100,000 live births; calculated as the maternal mortality rate divided by the general fertility rate 4 Calculated as 1-(1-MMR)TFR where TFR represents the total fertility rate for the seven years preceding the survey a Age-adjusted rate Adult and Maternal Mortality • 271 The maternal mortality rate can be converted to a maternal mortality ratio (expressed as deaths per 100,000 live births) by dividing the maternal mortality rate by the general fertility rate (GFR) of 169 that prevailed during the same time period, and multiplying the result by 100,000. This procedure produces a maternal mortality ratio (MMR) of 676 deaths per 100,000 live births during the seven-year period preceding the survey. In other words, for every 1,000 live births in Ethiopia during the seven years preceding the 2011 EDHS, about seven women (6.76) died during pregnancy, during childbirth, or within two months of childbirth. The lifetime risk of maternal death (0.036) indicates that about 4 percent of women died during pregnancy, during childbirth, or within two months of childbirth. The estimated maternal mortality ratio is almost the same in the 2011 EDHS (676) as it was in the 2005 EDHS (673). As shown in Table 15.3 and Figure 15.1, the confidence interval surrounding the maternal mortality ratio of 676 deaths per 100,000 live births is 541-810, while the confidence interval for the 2005 ratio of 673 deaths per 100,000 live births is 548-799 deaths. Because the confidence intervals between the two estimates overlap, there is no evidence to suggest that the maternal mortality ratio changed in the six years between surveys. A similar conclusion can be drawn comparing the maternal mortality ratios measured in the 2011 EDHS with those in the 2000 EDHS. Thus, there is no evidence to suggest that the maternal mortality ratio changed decreased in Ethiopia between 2000 and 2011. It should be kept in mind that maternal mortality is difficult to measure because large sample sizes are required to calculate accurate estimates. The maternal mortality estimates presented here are subject to large sampling errors because cost and time considerations make it impossible to draw a sample large enough to keep sampling errors reasonably small. 1,039 799 810 703 548 541 871 673 676 400 600 800 1,000 1,200 Seven years preceding the 2000 EDHS (1993-2000) Seven years preceding the 2005 EDHS (1998-2005) Seven years preceding the 2011 EDHS (2004-2011) M at er na l d ea th s pe r 1 ,0 00 li ve b ir th s Figure 15.1 Maternal Mortality Ratio (MMR) with Confidence Intervals for the Seven Years Preceding the 2000, 2005, and 2011 Ethiopia DHS References • 273 REFERENCES Arimond, M., and Marie T. Ruel. 2003. Generating Indicators of Appropriate Feeding of Children 6 through 23 Months from the KPC 2000+. Report of the Food and Nutrition Technical Assistance Project (FANTA). Washington, D.C.: Academy for Educational Development. http://pdf.usaid.gov/pdf_docs/PNACW465.pdf. Auvert, B., A. Buve, E. Lagarde, M. Kahindo, J. Chege, N. 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Direct and Indirect Estimates of Maternal Mortality from the Sisterhood Method. In Proceedings of the Demographic and Health Surveys World Conference, 3: 1669-1696. Columbia, Maryland: IRD/Macro International Inc. Rutstein S. 1999. Wealth versus Expenditure: Comparison between the DHS Wealth Index and Household Expenditures in Four Departments of Guatemala. Calverton, MD: ORC Macro. Rutstein, S., K. Johnson, and D. Gwatkin. 2000. Poverty, Health Inequality, and Its Health and Demographic Effects. Paper presented at the 2000 Annual Meeting of the Population Association of America, Los Angeles, California. Transitional Government of Ethiopia (TGE). 1993a. National Population Policy of Ethiopia. Addis Ababa, Ethiopia: Transitional Government of Ethiopia. Transitional Government of Ethiopia (TGE). 1993b. Health Policy of the Transitional Government of Ethiopia. Addis Ababa, Ethiopia: Transitional Government of Ethiopia. United Nations General Assembly. 1989. Convention on the Right of the Child. New York: United Nations. http://www2.ohchr.org/english/law/crc.htm United Nations General Assembly. 2002. Road Map towards the Implementation of the United Nations Millennium Declaration: Report of the Secretary-General. A/56/326. New York: United Nations General Assembly. World Health Organization (WHO). 2001. Iron Deficiency Anemia, Assessment, Prevention, and Control. A guide for programme managers. Geneva, Switzerland. World Health Organization. World Health Organization (WHO). 2005. Guiding Principles for Feeding Nonbreastfed Children 6 to 24 Months of Age, Geneva, Switzerland. http://www.helid.desastres.net/pdf/s13445e/s13445e.pdf. World Health Organization (WHO), Multicentre Growth Reference Study Group. 2006. WHO Child Growth Standards: Length/Height-for-Age, Weight-for-Length, Weight-for-Height and Body Mass Index-for-Age: Methods and Development. Geneva, Switzerland: WHO. World Health Organization (WHO). 2008. Indicators for Assessing Infant and Young Child Feeding Practices. Part I: Definitions. Conclusions of a consensus meeting held 6-8 November 2007 in Washington, D.C., USA. http://whqlibdoc.who.int/publications/2008/9789241596664_eng.pdf. World Health Organization (WHO) and UNICEF, Joint Monitoring Program for Water Supply and Sanitation. 2010. Progress on Sanitation and Drinking Water: 2010 Update. Geneva and New York: WHO and UNICEF. Appendix A • 275 SAMPLE IMPLEMENTATION Appendix A A.1. INTRODUCTION The Ethiopia Demographic and Health Survey 2011 (2011 EDHS) is the third DHS in Ethiopia, following the 2000 and 2005 EDHS surveys. A nationally representative sample of 17,817 households was selected. All women 15-49 who were usual residents or who slept in the selected households the night before the survey were eligible for the survey. In the selected households, 17,385 eligible women were identified for individual interview. As with prior EDHS surveys, the main objective of the 2011 EDHS is to provide up-to-date information on fertility and childhood mortality levels; fertility preferences; awareness, approval and use of family planning methods; maternal and child health; and knowledge and attitudes toward HIV/AIDS and other sexually transmitted infections (STIs). A male survey was also conducted. All men 15-49 who were usual residents or who slept in the selected households the night before the survey were eligible for the male survey. In the selected households, 15,908 eligible men were identified for individual interview. 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. Anaemia testing was done for children age 6-59 months, women age 15-49, and men age 15-59, while HIV testing was done for women age 15-49 and men age 15-59 who voluntarily consented to the testing. The survey is designed to produce representative estimates for the country as a whole, for the urban and the rural areas separately, and for each of the eleven regions. A.2 SAMPLING FRAME The sampling frame used for 2011 EDHS is the Population and Housing Census (PHC) conducted in 2007 provided by the Central Statistical Agency (CSA, 2008). CSA has an electronic file consisting of 81,654 Enumeration Areas (EA) created for the 2007 census in 10 of its 11 geographic regions. An EA is a geographic area consisting of a convenient number of dwelling units which served as counting unit for the census. The frame file contains information about the location, the type of residence, and the number of residential households for each of the 81,654 EAs. Sketch maps are also available for each EA which delimitate the geographic boundaries of the EA. The 2007 PHC conducted in the Somali region used a different methodology due to difficulty of access. Therefore, the sampling frame for the Somali region is in a different file and in different format. Due to security concerns in the Somali region, in the beginning it was decided that 2011 EDHS would be conducted only in three of nine zones in the Somali region: Shinile, Jijiga, and Liben, same as in the 2000 and 2005 EDHS. However, a later decision was made to include three other zones: Afder, Gode and Warder. This was the first time that these three zones were included in a major nationwide survey such as the 2011 EDHS. The sampling frame for the 2011 EDHS consists of a total of 85,057 EAs. The sampling frame excluded some special EAs with disputed boundaries. These EAs represent only 0.1% of the total population. Ethiopia is divided into 11 geographical regions. Each region is sub-divided into zones, each zone into Waredas, each Wareda into towns, and each town into Kebeles. Table A.1 shows the 276 • Appendix A distribution of the enumeration areas and average EA size in the sampling frame, by region and by residence. Among the 85,057 EAs, 17,548 (21 percent) are in urban areas and 67,509 (79 percent) are in rural areas. The average size of EA in number of households is 169 in an urban EA and 180 in a rural EA, with an overall average of 178 households per EA. Table A.2 shows the distributions of households in the sampling frame, by region and residence. The data show that 81 percent of the Ethiopia’s households are concentrated in three regions: Amhara, Oromiya and SNNP, while 4 percent of all households are in the five smallest regions: Afar, Benishangul-Gumuz, Gambela, Harari and Dire Dawa. Table A.1 Enumeration areas and average EA size in the sampling frame Distribution of the enumeration areas (EAs) and average EA size in the sampling frame, by region and by residence, Ethiopia 2011 Region Number of EAs in the sample frame Average EA size Urban Rural Total Urban Rural Total Tigray 1,541 4,139 5,680 153 177 171 Affar 260 828 1,088 177 233 219 Amhara 3,391 18,016 21,407 183 182 182 Oromiya 5,030 25,800 30,830 172 179 178 Somali1 526 2877 3,403 141 148 147 Benishangul-Gumuz 188 786 974 140 152 150 SNNP 2,124 14,490 16,614 166 184 182 Gambela 133 347 480 145 129 134 Harari 172 98 270 163 180 169 Addis Ababa 3,865 3,865 167 0 167 Dire Dawa 318 128 446 163 169 165 Ethiopia 17,548 67,509 85,057 169 180 178 1Including six of the nine zones in the region of Somali Table A.2 Distribution of households in the sampling frame Distribution of households in the sampling frame, by region and by residence, Ethiopia 2011 Region Number of households Proportion Urban Rural Total Urban Region Tigray 235,530 734,357 969,887 0.243 0.064 Affar 45,910 192,554 238,464 0.193 0.016 Amhara 619,796 3,284,512 3,904,308 0.159 0.259 Oromiya 864,303 4,630,702 5,495,005 0.157 0.364 Somali1 74,119 425,150 499,269 0.148 0.033 Benishangul-Gumuz 26,314 119,446 145,760 0.181 0.010 SNNP 353,554 2,667,787 3,021,341 0.117 0.200 Gambela 19,275 44,879 64,154 0.300 0.004 Harari 27,975 17,651 45,626 0.613 0.003 Addis Ababa 646,216 646,216 1.000 0.043 Dire Dawa 51,991 21,643 73,634 0.706 0.005 Ethiopia 2,964,983 12,138,681 15,103,664 0.196 1.000 1Including six of the nine zones in the region of Somali A.3. SAMPLE DESIGN AND IMPLEMENTATION The sample for 2011 EDHS used a stratified sample selected in two stages from the Population and Housing Census (PHC) frame. Stratification was achieved by separating each region into urban and rural areas. The Somali region was split into two parts: the first consisting of the initial three zones, and the second part of the additional three zones that were added later. In total, 23 sampling strata have been created because Addis Ababa region is entirely urban. Appendix A • 277 The sample points were selected independently in each sampling stratum, by a two-stage selection. In the first stage, 624 EAs were selected with probability proportional to the EA size and with independent selection in each sampling stratum. Because of the time passed since the 2007 PHC, a household listing operation was carried out in all selected EAs before start of fieldwork. The household listing operation consisted of team of listers visiting each of the 624 selected EAs. The team drew a detailed sketch map of each of the EAs and recorded in the household listing forms all households in the EA, their address, and the name of the head of the household. The list of the households that resulted from listing served as the sampling frame for the selection of households in the second stage. In the second stage, a fixed number of 30 households were selected for each EA. Table A.3 shows the sample allocation of clusters and households by region, according to residence. Among the 624 selected EAs, 187 are in urban areas and 437 are in rural areas. Of all the selected 18,720 households, 5,610 are in urban areas and 13,110 are in rural areas. The regional household distribution ranges from less than 1 percent in Harari to 36 percent in Oromiya (Table A.2). Therefore, a proportional allocation provides the best precision for national level indictors, but not for regional level indicators. Regions with especially very small population such as Gambela, Harari and Dire Dawa would be allocated a very small sample size. It is estimated that a minimum number of 800 women 15-49 are necessary to have reliable estimates for most of the EDHS indicators by region. However, because of the low vaccination coverage in Affar and Somali, and the low fertility rates in Gambela, Harari, Addis Ababa and Dire Dawa, it was decided to increase the number of individual women interviews to about 1,300 per region. As a result, the final sample allocation reflected a power allocation that is between the proportional allocation and the equal size allocation. In order for the survey precision in urban areas to be comparable with that in rural areas, urban areas were slightly over sampled. The cluster and household allocation by region and residence are a function of the average number of women 15-49 per household and of the household and individual response rates (obtained from the 2005 EDHS). According to the 2005 EDHS, the average number of women 15-49 per household was 1.28 in urban areas and 1.00 in rural areas. The average number of men 15-49 per household was 1.05 in urban areas and 0.94 in rural areas. The household response rates are 97% in urban areas and 99% in rural areas, the eligible woman response rates were 94% in urban areas and 96% in rural areas, and the eligible man response rates were 84% in urban areas and 91% in rural areas. Table A.3 Sample allocation of clusters and households Sample allocation of clusters and households by region, according to residence, Ethiopia 2011 Region Allocation of clusters Allocation of households Urban Rural Total Urban Rural Total Tigray 13 47 60 390 1,410 1,800 Affar 10 38 48 300 1,140 1,440 Amhara 10 62 72 300 1,860 2,160 Oromiya 13 62 75 390 1,860 2,250 Somali 13 52 65 390 1,560 1,950 Benishangul-Gumuz 6 42 48 180 1,260 1,440 SNNP 7 65 72 210 1,950 2,160 Gambela 9 37 46 270 1,110 1,380 Harari 25 17 42 750 510 1,260 Addis Ababa 54 54 1,620 1,620 Dire Dawa 27 15 42 810 450 1,260 Ethiopia 187 437 624 5,610 13,110 18,720 278 • Appendix A Table A.4 Sample allocation of completed interviews with women and men Sample allocation of expected number of completed interviews with women and men by region, according to residence, Ethiopia 2011 Statistical Region Women interviewed Men interviewed Urban Rural Region Urban Rural Region Tigray 434 1,280 1,714 326 1,186 1,512 Affar 333 1,035 1,368 251 959 1,210 Amhara 333 1,689 2,022 251 1,564 1,815 Oromiya 434 1,689 2,123 326 1,564 1,890 Somali 434 1417 1851 326 1,312 1,638 Benishangul-Gumuz 200 1,144 1,344 150 1,060 1,210 SNNP 233 1,771 2,004 176 1,640 1,816 Gambela 299 1,008 1,307 226 934 1,160 Harari 834 463 1,297 627 429 1,056 Addis Ababa 1,800 1,800 1354 1,354 Dire Dawa 901 409 1,310 677 378 1,055 Ethiopia 6,235 11,905 18,140 4690 11,026 15,716 A.4. SELECTION PROBABILITIES AND SAMPLE WEIGHTS Due to the non-proportional allocation of the sample to the different regions and to their urban and rural areas, sampling weights are required for any analysis using 2011 EDHS data to ensure representativeness of the survey results at the national and regional level. Since the 2011 EDHS sample is a two-stage stratified cluster sample, sampling weights were calculated based on sampling probabilities separately for each sampling stage and for each cluster. We use the following notations: P1hi: first-stage sampling probability of the ith cluster in stratum h P2hi: second -stage sampling probability within the ith cluster (household selection) Let ah be the number of clusters selected in stratum h, Mhi the number of households according to the sampling frame in the ith cluster, and M hi the total number of households in the stratum. The probability of selecting the ith cluster in the 2011 EDHS sample is calculated as follows: M M a hi hih  Let hib be the proportion of households in the selected segment compared to the total number of households in the EA i in stratum h if the EA is segmented, otherwise 1=hib . Then the probability of selecting cluster i in the sample is: hi hi hih 1hi b M M a = P × Appendix A • 279 Let hiL be the number of households listed in the household listing operation in cluster i in stratum h, let hig be the number of households selected in the cluster. The second stage’s selection probability for each household in the cluster is calculated as follows: hi hi hi L gP =2 The overall selection probability of each household in cluster i of stratum h is therefore the production of the two stages selection probabilities: hihihi PPP 21 ×= The sampling weight for each household in cluster i of stratum h is the inverse of its overall selection probability: hihi PW /1= Design weights were adjusted for household non-response and as well as for individual (women and men) non-response to get the sampling weights. The differences of the household sampling weights and the individual sampling weights are introduced by individual non-response. The final sampling weights (both household and individual weights) were normalized in order to give the total number of unweighted cases equal to the total number of weighted cases at the national level. The normalized weights are relative weights which are valid for estimating means, proportions and ratios, but not valid for estimating population totals and for pooled data. The sampling weights for HIV testing were calculated in a similar way, but the normalization of the individual sampling weights was different compared to the individual survey weights. The HIV testing weights were normalized for women and men together at the national level, so that the HIV prevalence calculated for all adults (women and men) are valid. Sampling errors were calculated for selected indicators for the national sample, for the urban and rural areas separately, and for each of the eleven regions. 28 0 • A pp en di x A A .5 . SU R VE Y IM PL EM EN TA TI O N Ta bl e A. 5 S am pl e im pl em en ta tio n P er ce nt d is tri bu tio n of h ou se ho ld s an d el ig ib le w om en b y re su lts o f t he h ou se ho ld a nd in di vi du al in te rv ie w s, a nd h ou se ho ld , e lig ib le w om en a nd o ve ra ll w om en re sp on se ra te s, a cc or di ng to u rb an -r ur al re si de nc e an d re gi on (u nw ei gh te d) , E th io pi a 20 11 R es ul t R es id en ce R eg io n To ta l U rb an R ur al Ti gr ay A ffa r A m ha ra O ro m iy a S om al i B en is ha ng ul - G um uz S N N P G am be la H ar ar i Ad di s A ba ba D ire D aw a Se le ct ed h ou se ho ld s C om pl et ed (C ) 92 .6 94 .2 96 .0 90 .1 95 .7 96 .1 87 .8 93 .1 94 .7 89 .1 95 .4 94 .1 94 .2 93 .7 H ou se ho ld p re se nt b ut n o co m pe te nt re sp on de nt a t h om e (H P ) 2. 4 1. 0 1. 1 1. 8 0. 6 0. 5 1. 2 2. 1 0. 5 4. 2 1. 2 2. 0 2. 5 1. 5 P os tp on ed (P ) 0. 0 0. 0 0. 1 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 R ef us ed (R ) 0. 2 0. 1 0. 2 0. 0 0. 2 0. 0 0. 2 0. 1 0. 0 0. 3 0. 2 0. 4 0. 2 0. 2 D w el lin g no t f ou nd (D N F) 0. 3 0. 1 0. 0 0. 4 0. 1 0. 0 0. 4 0. 1 0. 1 0. 3 0. 3 0. 3 0. 1 0. 2 H ou se ho ld a bs en t ( H A ) 0. 8 1. 6 0. 7 1. 4 0. 5 0. 9 5. 6 1. 3 1. 7 2. 9 0. 2 0. 5 0. 5 1. 3 D w el lin g va ca nt /a dd re ss n ot a d w el lin g (D V ) 2. 7 1. 4 1. 7 1. 3 2. 0 1. 8 1. 9 2. 7 1. 9 1. 2 2. 0 2. 0 1. 3 1. 8 D w el lin g de st ro ye d (D D ) 0. 5 1. 2 0. 2 4. 8 0. 4 0. 5 3. 0 0. 1 1. 1 1. 3 0. 2 0. 2 0. 6 1. 0 O th er (O ) 0. 5 0. 3 0. 2 0. 2 0. 5 0. 2 0. 1 0. 4 0. 1 0. 8 0. 6 0. 6 0. 7 0. 4 To ta l 10 0. 0 10 0. 0 10 0. 0 10 0. 0 10 0. 0 10 0. 0 10 0. 0 10 0. 0 10 0. 0 10 0. 0 10 0. 0 10 0. 0 10 0. 0 10 0. 0 N um be r o f s am pl ed h ou se ho ld s 5, 51 8 12 ,2 99 1, 80 2 1, 40 6 2, 16 3 2, 25 2 1, 11 1 1, 42 1 2, 16 0 1, 36 4 1, 25 9 1, 62 0 1, 25 9 17 ,8 17 H ou se ho ld re sp on se ra te (H R R )1 97 .0 98 .7 98 .7 97 .6 99 .0 99 .5 98 .1 97 .5 99 .4 94 .9 98 .3 97 .2 97 .1 98 .1 El ig ib le w om en C om pl et ed (E W C ) 94 .2 95 .4 97 .2 96 .3 95 .9 97 .1 92 .6 94 .9 95 .3 92 .0 93 .8 93 .1 93 .4 95 .0 N ot a t h om e (E W N H ) 3. 8 3. 1 1. 7 2. 5 2. 7 1. 8 5. 2 2. 8 2. 7 6. 3 4. 1 4. 2 5. 3 3. 3 P os tp on ed (E W P ) 0. 1 0. 1 0. 1 0. 1 0. 1 0. 0 0. 1 0. 1 0. 0 0. 0 0. 0 0. 1 0. 2 0. 1 R ef us ed (E W R ) 1. 0 0. 4 0. 1 0. 1 0. 3 0. 4 0. 9 0. 8 0. 6 1. 2 1. 2 1. 2 0. 4 0. 6 P ar tly c om pl et ed (E W P C ) 0. 1 0. 1 0. 0 0. 1 0. 2 0. 0 0. 3 0. 2 0. 0 0. 2 0. 2 0. 1 0. 1 0. 1 In ca pa ci ta te d (E W I) 0. 4 0. 6 0. 7 0. 9 0. 5 0. 5 0. 6 0. 8 0. 7 0. 2 0. 6 0. 4 0. 2 0. 6 O th er (E W O ) 0. 5 0. 3 0. 3 0. 1 0. 4 0. 1 0. 3 0. 4 0. 6 0. 0 0. 2 1. 0 0. 5 0. 4 To ta l 10 0. 0 10 0. 0 10 0. 0 10 0. 0 10 0. 0 10 0. 0 10 0. 0 10 0. 0 10 0. 0 10 0. 0 10 0. 0 10 0. 0 10 0. 0 10 0. 0 N um be r o f w om en 5, 65 6 11 ,7 29 1, 77 8 1, 34 0 2, 17 7 2, 19 8 98 7 1, 32 6 2, 13 4 1, 22 8 1, 17 4 1, 87 0 1, 17 3 17 ,3 85 E lig ib le w om en re sp on se ra te (E W R R )2 94 .2 95 .4 97 .2 96 .3 95 .9 97 .1 92 .6 94 .9 95 .3 92 .0 93 .8 93 .1 93 .4 95 .0 O ve ra ll w om en re sp on se ra te (O R R )3 91 .4 94 .1 95 .9 94 .0 94 .9 96 .6 90 .8 92 .6 94 .7 87 .3 92 .2 90 .5 90 .7 93 .2 1 U si ng th e nu m be r o f h ou se ho ld s fa llin g in to s pe ci fic re sp on se c at eg or ie s, th e ho us eh ol d re sp on se ra te (H R R ) i s ca lc ul at ed a s: 10 0 * C __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ _ C + H P + P + R + D N F 2 T he e lig ib le w om en re sp on se ra te (E W R R ) i s eq ui va le nt to th e pe rc en ta ge o f i nt er vi ew s co m pl et ed (E W C ) 3 T he o ve ra ll w om en re sp on se ra te (O W R R ) i s ca lc ul at ed a s: O W R R = H R R * E W R R /1 00 280 • Appendix A A pp en di x A • 2 81 Ta bl e A. 6 S am pl e im pl em en ta tio n: M en P er ce nt d is tri bu tio n of h ou se ho ld s an d el ig ib le m en b y re su lts o f t he h ou se ho ld a nd in di vi du al in te rv ie w s, a nd h ou se ho ld , e lig ib le m en a nd o ve ra ll m en r es po ns e ra te s, a cc or di ng to u rb an -r ur al r es id en ce a nd re gi on (u nw ei gh te d) , E th io pi a 20 11 R es ul t R es id en ce R eg io n To ta l U rb an R ur al Ti gr ay A ffa r A m ha ra O ro m iy a S om al i B en is ha ng ul - G um uz S N N P G am be la H ar ar i Ad di s A ba ba D ire D aw a Se le ct ed h ou se ho ld s C om pl et ed (C ) 92 .6 94 .2 96 .0 90 .1 95 .7 96 .1 87 .8 93 .1 94 .7 89 .1 95 .4 94 .1 94 .2 93 .7 H ou se ho ld p re se nt b ut n o co m pe te nt re sp on de nt a t h om e (H P ) 2. 4 1. 0 1. 1 1. 8 0. 6 0. 5 1. 2 2. 1 0. 5 4. 2 1. 2 2. 0 2. 5 1. 5 P os tp on ed (P ) 0. 0 0. 0 0. 1 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 R ef us ed (R ) 0. 2 0. 1 0. 2 0. 0 0. 2 0. 0 0. 2 0. 1 0. 0 0. 3 0. 2 0. 4 0. 2 0. 2 D w el lin g no t f ou nd (D N F) 0. 3 0. 1 0. 0 0. 4 0. 1 0. 0 0. 4 0. 1 0. 1 0. 3 0. 3 0. 3 0. 1 0. 2 H ou se ho ld a bs en t ( H A ) 0. 8 1. 6 0. 7 1. 4 0. 5 0. 9 5. 6 1. 3 1. 7 2. 9 0. 2 0. 5 0. 5 1. 3 D w el lin g va ca nt /a dd re ss n ot a d w el lin g (D V ) 2. 7 1. 4 1. 7 1. 3 2. 0 1. 8 1. 9 2. 7 1. 9 1. 2 2. 0 2. 0 1. 3 1. 8 D w el lin g de st ro y (D D ) 0. 5 1. 2 0. 2 4. 8 0. 4 0. 5 3. 0 0. 1 1. 1 1. 3 0. 2 0. 2 0. 6 1. 0 O th er (O ) 0. 5 0. 3 0. 2 0. 2 0. 5 0. 2 0. 1 0. 4 0. 1 0. 8 0. 6 0. 6 0. 7 0. 4 To ta l 10 0. 0 10 0. 0 10 0. 0 10 0. 0 10 0. 0 10 0. 0 10 0. 0 10 0. 0 10 0. 0 10 0. 0 10 0. 0 10 0. 0 10 0. 0 10 0. 0 N um be r o f s am pl ed h ou se ho ld s 5, 51 8 12 ,2 99 1, 80 2 1, 40 6 2, 16 3 2, 25 2 1, 11 1 1, 42 1 2, 16 0 1, 36 4 1, 25 9 1, 62 0 1, 25 9 17 ,8 17 H ou se ho ld re sp on se ra te (H R R )1 97 .0 98 .7 98 .7 97 .6 99 .0 99 .5 98 .1 97 .5 99 .4 94 .9 98 .3 97 .2 97 .1 98 .1 El ig ib le m en C om pl et ed (E M C ) 83 .3 91 .2 90 .5 89 .5 91 .0 94 .5 82 .4 91 .2 92 .7 86 .8 84 .6 79 .9 84 .1 88 .7 N ot a t h om e (E M N H ) 13 .2 6. 7 7. 4 8. 7 6. 9 3. 7 13 .5 6. 6 5. 1 11 .4 12 .6 15 .6 12 .7 8. 8 P os tp on ed (E M P ) 0. 1 0. 0 0. 1 0. 0 0. 0 0. 0 0. 0 0. 0 0. 1 0. 2 0. 1 0. 0 0. 1 0. 1 R ef us ed (E M R ) 2. 0 0. 6 1. 0 0. 6 0. 6 0. 3 2. 1 0. 8 0. 3 0. 7 1. 0 3. 0 1. 6 1. 0 P ar tly c om pl et ed (E M P C ) 0. 2 0. 1 0. 1 0. 0 0. 1 0. 1 0. 6 0. 2 0. 2 0. 0 0. 3 0. 0 0. 1 0. 1 In ca pa ci ta te d (E M I) 0. 5 0. 8 0. 5 1. 2 0. 7 0. 6 1. 3 0. 7 0. 8 0. 3 0. 7 0. 7 0. 4 0. 7 O th er (E M O ) 0. 8 0. 6 0. 5 0. 0 0. 6 0. 8 0. 2 0. 4 0. 8 0. 6 0. 7 0. 8 1. 0 0. 6 To ta l 10 0. 0 10 0. 0 10 0. 0 10 0. 0 10 0. 0 10 0. 0 10 0. 0 10 0. 0 10 0. 0 10 0. 0 10 0. 0 10 0. 0 10 0. 0 10 0. 0 N um be r o f m en 5, 06 2 10 ,8 46 1, 53 0 1, 11 7 2, 15 9 2, 18 1 86 8 1, 24 9 1, 83 2 1, 08 3 1, 14 9 1, 64 9 1, 09 1 15 ,9 08 E lig ib le m en re sp on se ra te (E M R R )2 83 .3 91 .2 90 .5 89 .5 91 .0 94 .5 82 .4 91 .2 92 .7 86 .8 84 .6 79 .9 84 .1 88 .7 O ve ra ll m en re sp on se ra te (O R R )3 80 .8 90 .0 89 .3 87 .4 90 .1 94 .0 80 .8 88 .9 92 .2 82 .4 83 .1 77 .7 81 .7 87 .1 1 U si ng th e nu m be r o f h ou se ho ld s fa llin g in to s pe ci fic re sp on se c at eg or ie s, th e ho us eh ol d re sp on se ra te (H R R ) i s ca lc ul at ed a s: 10 0 * C __ __ __ __ __ __ __ __ __ __ __ __ __ __ __ _ C + H P + P + R + D N F 2 T he e lig ib le m en re sp on se ra te (E M R R ) i s eq ui va le nt to th e pe rc en ta ge o f i nt er vi ew s co m pl et ed (E M C ) 3 T he o ve ra ll m en re sp on se ra te (O M R R ) i s ca lc ul at ed a s: O M R R = H R R * E M R R /1 00 • 281Appendix A 282 • Appendix A Table A.7 Coverage of HIV testing by social and demographic characteristics: Women Percent distribution of interviewed women age 15-49 by HIV testing status, according to social and demographic characteristics (unweighted), Ethiopia 2011 Characteristic HIV test status Total Number of women DBS tested1 Refused to provide blood Absent at the time of blood collection Other/ missing2 Marital status Never married 91.9 5.6 1.8 0.7 100.0 4,413 Ever had sexual intercourse 91.0 7.2 1.2 0.6 100.0 489 Never had sexual intercourse 92.0 5.4 1.9 0.7 100.0 3,924 Married/living together 95.0 3.8 0.6 0.5 100.0 10,204 Divorced or separated 92.5 4.9 1.9 0.7 100.0 1,317 Widowed 94.0 4.5 0.3 1.2 100.0 581 Type of union In polygynous union 96.6 2.7 0.2 0.5 100.0 1,306 In non-polygynous union 94.9 3.9 0.7 0.5 100.0 8,837 Not currently in union 92.2 5.4 1.7 0.7 100.0 6,311 Ever had sexual intercourse Yes 94.6 4.1 0.8 0.6 100.0 12,541 No 92.1 5.4 1.8 0.7 100.0 3,957 Currently pregnant Pregnant 95.7 3.0 0.5 0.9 100.0 1,277 Not pregnant or not sure 93.8 4.5 1.1 0.6 100.0 15,238 Total 94.0 4.4 1.0 0.6 100.0 16,515 Total includes 61 cases with missing information on type of union and 17 cases with missing information on whether they ever had sexual intercourse. 1 Includes all Dried Blood Samples (DBS) tested at the lab and for which there is a result, i.e. positive, negative, or indeterminate. Indeterminate means that the sample went through the entire algorithm, but the final result was inconclusive. 2 Includes: 1) other results of blood collection (e.g. technical problem in the field), 2) lost specimens, 3) non corresponding bar codes, and 4) other lab results such as blood not tested for technical reason, not enough blood to complete the algorithm, etc. Appendix A • 283 Table A.8 Coverage of HIV testing by social and demographic characteristics: Men Percent distribution of interviewed men 15-49[59] by HIV testing status, according to social and demographic characteristics (unweighted), Ethiopia 2011 Characteristic HIV test status Total Number of men DBS Tested1 Refused to provide blood Absent at the time of blood collection Other/ missing2 Marital status Never married 90.9 5.6 2.6 0.9 100.0 5,653 Ever had sexual intercourse 88.1 8.5 2.5 0.9 100.0 1,501 Never had sexual intercourse 91.9 4.5 2.7 0.9 100.0 4,152 Married/living together 93.4 4.5 1.4 0.8 100.0 7,930 Divorced or separated 88.3 8.4 1.9 1.4 100.0 429 Widowed 92.9 5.1 1.0 1.0 100.0 98 Type of union In polygynous union 91.7 3.7 3.3 1.3 100.0 544 In non-polygynous union 93.5 4.5 1.2 0.7 100.0 7,359 Not currently in union 90.7 5.8 2.5 1.0 100.0 6,180 Ever had sexual intercourse Yes 92.4 5.2 1.6 0.8 100.0 9,919 No 91.9 4.5 2.7 0.9 100.0 4,178 Male circumcision Circumcised 92.2 5.2 1.8 0.9 100.0 13,004 Not circumcised 93.3 2.9 3.4 0.5 100.0 1,069 Times slept away from home in past 12 months None 91.9 5.2 2.0 0.9 100.0 7,464 1-2 94.4 3.4 1.7 0.6 100.0 2,179 3-4 92.8 4.5 1.9 0.8 100.0 1,300 5+ 91.4 5.8 1.8 1.0 100.0 3,096 Time away in past 12 months Away for more than 1 month 91.8 4.8 2.3 1.1 100.0 1,481 Away for less than 1 month 93.0 4.7 1.6 0.7 100.0 5,079 No away 91.9 5.2 2.0 0.9 100.0 7,464 Total 92.2 5.0 1.9 0.9 100.0 14,110 Total includes 27 cases with missing information on type of union, 13 cases with missing information on whether ever had sexual intercourse, 71 cases with missing information on times slept away from home in past 12 months, and 86 cases with missing information on time away in past 12 months. 1 Includes all Dried Blood Samples (DBS) tested at the lab and for which there is a result, i.e. positive, negative, or indeterminate. Indeterminate means that the sample went through the entire algorithm, but the final result was inconclusive. 2 Includes: 1) other results of blood collection (e.g. technical problem in the field), 2) lost specimens, 3) non corresponding bar codes, and 4) other lab results such as blood not tested for technical reason, not enough blood to complete the algorithm, etc. 284 • Appendix A Table A.9 Coverage of HIV testing among interviewed women by sexual behavior characteristics: Women Percent distribution of interviewed women age 15-49 who ever had sexual intercourse by HIV test status, according to sexual behavior characteristics (unweighted), Ethiopia 2011 Sexual behavior characteristic HIV test status Total Number of women DBS Tested1 Refused to provide blood Absent at the time of blood collection Other/ missing2 Age at first sexual intercourse <16 95.0 3.8 0.5 0.7 100.0 5,303 16-17 95.8 3.1 0.6 0.5 100.0 2,501 18-19 94.8 3.7 1.0 0.5 100.0 1,925 20+ 91.9 6.2 1.3 0.7 100.0 2,112 Inconsistent/missing 94.4 4.1 0.9 0.6 100.0 700 Multiple sexual partners and partner concurrency in past 12 months 0 92.7 5.1 1.3 0.9 100.0 2,131 1 95.0 3.8 0.7 0.5 100.0 10,320 2+ 93.7 5.1 0.0 1.3 100.0 79 Has concurrent partners2 100.0 0.0 0.0 0.0 100.0 5 None of the partners are concurrent 93.2 5.4 0.0 1.4 100.0 74 Condom use at last sexual intercourse in past 12 months Used condom 89.9 8.6 1.2 0.3 100.0 326 Did not use condom 95.1 3.7 0.6 0.5 100.0 10,070 No sexual intercourse in last 12 months 92.6 5.2 1.3 0.9 100.0 2,142 Number of lifetime partners 1 94.5 4.1 0.8 0.6 100.0 9,369 2 95.0 4.0 0.6 0.4 100.0 2,312 3-4 94.3 3.9 0.7 1.0 100.0 672 5-9 93.9 5.1 0.0 1.0 100.0 98 10+ 96.3 1.9 0.0 1.9 100.0 54 Prior HIV testing Ever tested 93.7 4.8 1.0 0.6 100.0 5,450 Received results 93.5 4.9 0.9 0.6 100.0 5,107 Did not received results 95.6 2.9 1.5 0.0 100.0 343 Never tested 95.3 3.5 0.6 0.6 100.0 7,077 Total 94.6 4.1 0.8 0.6 100.0 12,541 Total includes 11 cases with missing information on multiple sexual partners and partner concurrency in past 12 months, 3 cases with missing information on condom use at last sexual intercourse in past 12 months, 36 cases with missing information on number of lifetime partners, and 14 cases with missing information on prior HIV testing. 1 Includes all Dried Blood Samples (DBS) tested at the lab and for which there is a result, i.e. positive, negative, or indeterminate. Indeterminate means that the sample went through the entire algorithm, but the final result was inconclusive. 2 Includes: 1) other results of blood collection (e.g. technical problem in the field), 2) lost specimens, 3) non corresponding bar codes, and 4) other lab results such as blood not tested for technical reason, not enough blood to complete the algorithm, etc. 3 A respondent is considered to have had concurrent partners if he or she had overlapping sexual partnerships with two or more people during the 12 months before the survey. Appendix A • 285 Table A.10 Coverage of HIV testing among interviewed men by sexual behavior characteristics: Men Percent distribution of interviewed men age 15-54[59] who ever had sexual intercourse by HIV test status, according to sexual behavior characteristics (unweighted), Ethiopia 2011 Sexual behavior characteristic HIV test status Total Number of men DBS Tested1 Refused to provide blood Absent at the time of blood collection Other/ missing2 Age at first sexual intercourse <16 93.2 4.5 1.3 1.0 100.0 1,053 16-17 92.0 5.8 1.6 0.7 100.0 1,349 18-19 92.4 4.8 2.0 0.7 100.0 2,116 20+ 92.4 5.4 1.4 0.8 100.0 4,974 Inconsistent/missing 92.3 5.4 0.9 1.4 100.0 427 Multiple sexual partners and partner concurrency in past 12 months 0 88.7 7.7 2.6 1.0 100.0 1,080 1 93.0 4.9 1.3 0.8 100.0 8,168 2+ 91.5 4.4 2.7 1.4 100.0 655 Has concurrent partners2 94.7 2.7 1.9 0.7 100.0 413 None of the partners are concurrent 86.0 7.4 4.1 2.5 100.0 242 Condom use at last sexual intercourse in past 12 months Used condom 87.8 9.1 2.1 1.0 100.0 806 Did not use condom 93.4 4.5 1.4 0.8 100.0 8,015 No sexual intercourse in last 12 months 88.5 7.9 2.6 1.0 100.0 1,096 Paid for sexual intercourse in past 12 months Yes 85.6 8.6 3.6 2.2 100.0 139 Used condom 76.9 15.4 3.8 3.8 100.0 26 Did not use condom 87.6 7.1 3.5 1.8 100.0 113 No/no paid sexual intercourse/no sexual intercourse in last 12 months 92.5 5.2 1.5 0.8 100.0 9,780 Number of lifetime partners 1 93.1 4.7 1.4 0.9 100.0 4,540 2 91.4 5.4 2.1 1.0 100.0 2,337 3-4 92.3 5.4 1.6 0.7 100.0 1,637 5-9 93.2 5.4 0.6 0.8 100.0 792 10+ 92.3 5.6 1.7 0.4 100.0 533 Prior HIV testing Ever tested 92.4 5.3 1.6 0.6 100.0 4,612 Received results 92.1 5.6 1.7 0.6 100.0 4,270 Did not received results 95.9 2.0 1.5 0.6 100.0 342 Never tested 92.4 5.1 1.5 1.0 100.0 5,306 Total 92.4 5.2 1.6 0.8 100.0 9,919 Total includes 16 cases with missing information on multiple sexual partners and partner concurrency in past 12 months, 2 cases with missing information on condom use at last sexual intercourse in past 12 months, 80 cases with missing information on number of lifetime partners, and 1 case with missing information on prior HIV testing. 1 Includes all Dried Blood Samples (DBS) tested at the lab and for which there is a result, i.e. positive, negative, or indeterminate. Indeterminate means that the sample went through the entire algorithm, but the final result was inconclusive. 2 Includes: 1) other results of blood collection (e.g. technical problem in the field), 2) lost specimens, 3) non corresponding bar codes, and 4) other lab results such as blood not tested for technical reason, not enough blood to complete the algorithm, etc. 3 A respondent is considered to have had concurrent partners if he or she had overlapping sexual partnerships with two or more people during the 12 months before the survey. (Respondents with concurrent partners include polygynous men who had overlapping sexual partnerships with two or more wives). Appendix B • 287 ESTIMATES OF SAMPLING ERRORS Appendix B The estimates from a sample survey are affected by two types of errors: (1) nonsampling errors, and (2) sampling errors. Nonsampling errors are the results of mistakes made in implementing data collection and data processing, such as failure to locate and interview the correct household, misunderstanding of the questions on the part of either the interviewer or the respondent, and data entry errors. Although numerous efforts were made during the implementation of the 2011 Ethiopia Demographic and Health Survey (2011 EDHS) to minimize this type of error, nonsampling errors are impossible to avoid and difficult to evaluate statistically. Sampling errors, on the other hand, can be evaluated statistically. The sample of respondents selected in the 2011 EDHS is only one of many samples that could have been selected from the same population, using the same design and identical size. Each of these samples would yield results that differ somewhat from the results of the actual sample selected. Sampling error is a measure of the variability between all possible samples. Although the degree of variability is not known exactly, it can be estimated from the survey results. A sampling error is usually measured in terms of the standard error for a particular statistic (mean, percentage, etc.), which is the square root of the variance. The standard error can be used to calculate confidence intervals within which the true value for the population can reasonably be assumed to fall. For example, for any given statistic calculated from a sample survey, the value of that statistic will fall within a range of plus or minus two times the standard error of that statistic in 95 percent of all possible samples of identical size and design. If the sample of respondents had been selected as a simple random sample, it would have been possible to use straightforward formulas for calculating sampling errors. However, the 2011 EDHS sample is the result of a multi-stage stratified design, and, consequently, it was necessary to use more complex formulae. The computer software used to calculate sampling errors for the 2011 EDHS is a SAS program. This program used the Taylor linearization method for variance estimation for survey estimates that are means or proportions. The Jackknife repeated replication method is used for variance estimation of more complex statistics such as fertility and mortality rates. The Taylor linearization method treats any percentage or average as a ratio estimate, r = y/x, where y represents the total sample value for variable y, and x represents the total number of cases in the group or subgroup under consideration. The variance of r is computed using the formula given below, with the standard error being the square root of the variance: ( )  = =         − − −== H h h h m i hi h h h m zz m mf x rvarrSE h 1 2 1 2 2 2 1 11)()( in which hihihi rxyz −= , and hhh rxyz −= 288 • Appendix B where h represents the stratum which varies from 1 to H, mh is the total number of clusters selected in the hth stratum, yhi is the sum of the weighted values of variable y in the ith cluster in the hth stratum, xhi is the sum of the weighted number of cases in the ith cluster in the hth stratum, and fh is the sampling fraction of PSU in the hth stratum which is small and ignored The Jackknife repeated replication method derives estimates of complex rates from each of several replications of the parent sample, and calculates standard errors for these estimates using simple formulae. Each replication considers all but one cluster in the calculation of the estimates. Pseudo-independent replications are thus created. In the 2011 EDHS, there were 596 non-empty clusters. Hence, 596 replications were created. The variance of a rate r is calculated as follows: SE r var r k k r r i k i 2 1 21 1 ( ) ( ) ( ) ( )= = − − =  in which )()1( ii rkkrr −−= where r is the estimate computed from the full sample of 596 clusters, r(i) is the estimate computed from the reduced sample of 595 clusters (ith cluster excluded), and k is the total number of clusters. In addition to the standard error, the program computes the design effect (DEFT) for each estimate, which is defined as the ratio between the standard error using the given sample design and the standard error that would result if a simple random sample had been used. A DEFT value of 1.0 indicates that the sample design is as efficient as a simple random sample, while a value greater than 1.0 indicates the increase in the sampling error due to the use of a more complex and less statistically efficient design, such as multistage and cluster selection. The program also computes the relative standard error and the confidence limits for the estimates. Appendix B • 289 Sampling errors for the 2011 EDHS are calculated for selected variables considered to be of primary interest for woman’s survey and for man’s surveys, respectively. The results are presented in this appendix for the country as a whole, for urban and rural areas separately, and for each of the 11 regions. For each variable, the type of statistic (mean, proportion, or rate) and the base population are given in Table B.1. Tables B.2 to B.16 present the value of the statistic (R), its standard error (SE), the number of unweighted (N-UNWE) and weighted (N-WEIG) cases, the design effect (DEFT), the relative standard error (SE/R), and the 95 percent confidence limits (R±2SE), for each variable. The DEFT is considered undefined when the standard error considering simple random sample is zero (when the estimate is close to 0 or 1). In the case of the total fertility rate, the number of unweighted cases is not relevant, as there is no known unweighted value for woman-years of exposure to child- bearing. The confidence interval (e.g., as calculated for children ever born to women over age 40) can be interpreted as follows: the overall average from the national sample is 6.909 and its standard error is 0.112. Therefore, to obtain the 95 percent confidence limits, one adds and subtracts twice the standard error to the sample estimate, i.e., 6.909±2×0.112. There is a high probability (95 percent) that the true average number of children ever born to all women over age 40 is between 6.685 and 7.133. For the total sample, the value of the design effect (DEFT), averaged over all variables for the women survey, is 2.037 which means that, due to multistage and clustering of the sample, the average standard error is increased by a factor of 2.037 over that in an equivalent simple random sample. 290 • Appendix B Table B.1 List of selected variables for sampling errors, Ethiopia 2011 Variable Estimate Base population WOMEN Urban residence Proportion All women 15-49 Literate Proportion All women 15-49 No education Proportion All women 15-49 Secondary education or higher Proportion All women 15-49 Net attendance ratio for primary school Ratio Children 7-14 years Never married/in union Proportion All women 15-49 Currently married/in union Proportion All women 15-49 Married before age 20 Proportion Women age 20-49 Currently pregnant Proportion All women 15-49 Children ever born Mean All women 15-49 Children surviving Mean All women 15-49 Children ever born to women age 40-49 Mean Women age 40-49 Knows any contraceptive method Proportion All women 15-49 Currently using any contraceptive method Proportion Currently married women 15-49 Currently using pill Proportion Currently married women 15-49 Currently using IUD Proportion Currently married women 15-49 Currently using female sterilization Proportion Currently married women 15-49 Currently using rhythm method Proportion Currently married women 15-49 Obtained method from public sector source Proportion Currently married women 15-49 Want no more children Proportion Currently married women 15-49 Want to delay birth at least 2 years Proportion Currently married women 15-49 Ideal family size Mean All women 15-49 Mothers received tetanus injection for last birth Proportion Women with at least 1 live birth in past 5 years Mothers received medical assistance at delivery Proportion Births in last 5 years Had diarrhoea in two weeks before survey Proportion Children under 5 years Treated with oral rehydration salts (ORS) Proportion Children under 5 years with diarrhoea in past two weeks Taken to a health provider Proportion Children with diarrhoea in past two weeks Vaccination card seen Proportion Children age 12-23 months Received BCG vaccination Proportion Children age 12-23 months Received DPT vaccination (3 doses) Proportion Children age 12-23 months Received polio vaccination (3 doses) Proportion Children age 12-23 months Received measles vaccination Proportion Children age 12-23 months Received all vaccinations Proportion Children age 12-23 months Height-for-age (below -2SD) Proportion Children under 5 years who were measured Weight-for-height (below -2SD) Proportion Children under 5 years who were measured Weight-for-age (below -2SD) Proportion Children under 5 years who were measured Prevalence of anaemia (children 6-59 months) Proportion Children 6-59 months who were tested Prevalence of anaemia (women 15-49) Proportion All women 15-49 Body Mass Index (BMI) <18.5 Proportion All women 15-49 Had 2+ sex partners in past 12 months Proportion All women 15-49 Abstinence among youth (never had sex) Proportion All never married women 15-24 Sexually active in past 12 months among never-married youth Proportion All never married women 15-24 Had an injection in past 12 months Proportion All women 15-49 Had an HIV test and received results in past 12 months Proportion All women 15-49 Accepting attitudes towards people with HIV Proportion All women 15-49 who have heard of HIV/AIDS Knows about condoms Proportion All women 15-49 Knows about limiting partners Proportion All women 15-49 HIV prevalence among all women 15-49 Proportion All interviewed women with Dried Blood Sample (DBS) tested at the lab Total fertility rate (3 years) Rate Women-years of exposure to childbearing Neonatal mortality1 Rate Children exposed to the risk of mortality Post-neonatal mortality1 Rate Children exposed to the risk of mortality Infant mortality1 Rate Children exposed to the risk of mortality Child mortality1 Rate Children exposed to the risk of mortality Under five mortality1 Rate Children exposed to the risk of mortality 1 The mortality rates are calculated for 5 years and 10 years before the survey for the national sample and regional samples, respectively MEN Urban residence Proportion All men 15-59 Literate Proportion All men 15-59 No education Proportion All men 15-59 Secondary education or higher Proportion All men 15-59 Never married/in union Proportion All men 15-59 Currently married/in union Proportion All men 15-59 Want no more children Proportion Currently married men 15-59 Want to delay birth at least 2 years Proportion Currently married men 15-59 Ideal family size Mean All men 15-59 Had 2+ sex partners in past 12 months Proportion All men 15-49 Condom use at last sex Proportion Men 15-49 with 2+ sex partners in past 12 months Abstinence among youth (never had sex) Proportion All never married men 15-24 Sexually active in past 12 months among never-married youth Proportion All never married men 15-24 Had an injection in past 12 months Proportion All men 15-49 HIV test and received results past 12 months Proportion All men 15-49 Accepting attitudes towards people with HIV Proportion All men 15-49 who have heard of HIV/AIDS Knows about condoms Proportion All men 15-49 Knows about limiting partners Proportion All men 15-49 HIV prevalence among all men 15-49 Proportion All interviewed men 15-49 with Dried Blood Sample (DBS) tested at the lab HIV prevalence among all men 15-59 Proportion All interviewed men 15-59 with DBS tested at the lab MEN AND WOMEN HIV prevalence among all respondents 15-49 Proportion All interviewed women and men 15-49 with DBS tested at the lab Appendix B • 291 Table B.2 Sampling errors for national sample, Ethiopia 2011 Variable Value (R) Standard e