Uganda DHS Final Report (2011)

Publication date: 2012

Uganda U ganda 2011 D em ographic and H ealth Survey Demographic and Health Survey 2011 THE REPUBLIC OF UGANDA Uganda Demographic and Health Survey 2011 Uganda Bureau of Statistics Kampala, Uganda MEASURE DHS ICF International Calverton, Maryland, USA August 2012 The 2011 Uganda Demographic and Health Survey (2011 UDHS) was implemented by the Uganda Bureau of Statistics from May through December 2011. The funding for the 2011 UDHS was provided by the government of Uganda, USAID, UNFPA, UNICEF, WHO, Irish Aid, and the UK government. ICF International provided technical assistance 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 opinions expressed herein are those of the authors and do not necessarily reflect the views of the U.S. Agency for International Development. Additional information about the 2011 UDHS may be obtained from the Uganda Bureau of Statistics (UBOS), Plot 9 Collville Street, P.O Box 7186, Kampala, Uganda; Telephone: (256-41) 706000; Fax: (256-41) 237553/230370; Email: ubos@ubos.org; Internet: http://www.ubos.org. 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: reports@measuredhs.com; Internet: http://www.measuredhs.com. Recommended citation: Uganda Bureau of Statistics (UBOS) and ICF International Inc. 2012. Uganda Demographic and Health Survey 2011. Kampala, Uganda: UBOS and Calverton, Maryland: ICF International Inc. Contents • iii CONTENTS TABLES AND FIGURES . xix PREFACE . xvii MILLENNIUM DEVELOPMENT GOALS . xix MAP OF UGANDA . xx CHAPTER 1 INTRODUCTION 1.1 History, Geography, and Economy . 1 1.2 Population . 2 1.3 Population and Health Policies . 3 1.4 Objectives of the 2011 UDHS Survey . 4 1.5 Organization of the Survey . 5 1.6 Sample Design . 5 1.7 Questionnaires . 7 1.8 Anthropometry, Anaemia, and Vitamin A Testing . 8 1.9 Listing, Pretest, Main Training, Fieldwork, and Data Processing . 9 1.10 Response Rates . 10 CHAPTER 2 HOUSING CHARACTERISTICS AND HOUSEHOLD POPULATION 2.1 Household Environment . 11 2.1.1 Drinking Water . 11 2.1.2 Household Sanitation Facilities . 13 2.1.3 Housing Characteristics . 13 2.1.4 Household Possessions . 15 2.1.5 Hand Washing . 15 2.2 Wealth Index . 16 2.3 Population by Age and Sex . 17 2.4 Household Composition . 19 2.5 Birth Registration . 19 2.6 Children’s Living Arrangements and Parental Survival . 20 2.7 Education Level of the Household Population . 21 2.7.1 School Attendance by Survivorship of Parents . 21 2.7.2 Educational Attainment . 22 2.7.3 School Attendance Ratios . 24 2.8 Disability . 27 CHAPTER 3 CHARACTERISTICS OF RESPONDENTS 3.1 Characteristics of Survey Respondents . 29 3.2 Educational Attainment by Background Characteristics. 30 3.3 Literacy . 33 3.4 Access to Mass Media . 35 3.5 Employment . 36 3.5.1 Employment Status . 36 3.5.2 Occupation . 40 3.5.3 Type of Women’s Employment . 42 iv • Contents 3.6 Health Insurance . 42 3.7 Use of Tobacco . 44 CHAPTER 4 MARRIAGE AND SEXUAL ACTIVITY 4.1 Current Marital Status . 47 4.2 Polygyny . 48 4.3 Age at First Marriage . 50 4.4 Age at First Sexual Intercourse . 52 4.5 Recent Sexual Activity . 54 CHAPTER 5 FERTILITY 5.1 Introduction . 57 5.2 Current Fertility . 57 5.3 Fertility Differentials by Background Characteristics . 58 5.4 Fertility Trends . 60 5.5 Children Ever Born and Living . 61 5.6 Birth Intervals . 62 5.7 Postpartum Amenorrhoea, Abstinence, and Insusceptibility . 64 5.8 Menopause . 65 5.9 Age at First Birth . 65 5.10 Teenage Pregnancy and Motherhood . 67 CHAPTER 6 FERTILITY PREFERENCES 6.1 Desire for More Children . 69 6.2 Desire to Limit Childbearing by Background Characteristics . 70 6.3 Ideal Family Size . 71 6.4 Fertility Planning . 73 6.5 Wanted Fertility Rates. 74 CHAPTER 7 FERTILITY PREFERENCES 7.1 Knowledge of Contraceptive Methods . 78 7.2 Current Use of Contraception . 79 7.3 Current Use of Contraceptive by Background Characteristics . 81 7.4 Trends in Current Use of Family Planning . 83 7.5 Timing of Female Sterilization . 84 7.6 Source of Contraception . 84 7.7 Use of Social Marketing Brands of Pills and Condoms . 85 7.8 Informed Choice . 86 7.9 Contraceptive Discontinuation Rates . 87 7.10 Reasons for Discontinuation of Contraceptive Use . 87 7.11 Knowledge of the Fertile Period . 88 7.12 Need and Demand for Family Planning Services . 89 7.13 Future Use of Contraception . 92 7.14 Exposure to Family Planning Messages . 93 7.15 Contact of Nonusers with Family Planning Providers . 94 7.16 Family Planning Counseling . 95 CHAPTER 8 INFANT AND CHILD MORTALITY 8.1 Data Quality . 98 8.2 Early Childhood Mortality Rates: Levels and Trends . 98 8.3 Early Childhood Mortality Rates by Socioeconomic Characteristics . 100 Contents • v 8.4 Early Childhood Mortality by Demographic Characteristics . 101 8.5 Perinatal Mortality . 102 8.6 High-risk Fertility Behaviour . 103 CHAPTER 9 REPRODUCTIVE HEALTH 9.1 Antenatal Care . 105 9.1.1 Number and Timing of Antenatal Visits . 107 9.2 Components of Antenatal Care . 107 9.3 Tetanus Toxoid Vaccination . 109 9.4 Place of Delivery . 110 9.5 Assistance during Delivery . 112 9.6 Postnatal Care . 113 9.6.1 Duration of Health Facility Stay and Timing of First Postnatal Checkup 113 9.6.2 Provider of First Postnatal Checkup for Mother . 115 9.7 Newborn Care . 116 9.8 Problems Accessing Health Care . 118 9.9 FEMALE CIRCUMCISION . 119 9.10 Obstetric Fistula . 121 CHAPTER 10 CHILD HEALTH 10.1 Child’s Size at Birth . 123 10.2 Vaccination Coverage . 125 10.3 Trends in Vaccination Coverage . 127 10.4 Acute Respiratory Infection . 129 10.5 Fever . 130 10.6 Diarrhoeal Disease . 132 10.6.1 Prevalence of Diarrhoea . 132 10.6.2 Treatment of Diarrhoea . 133 10.6.3 Feeding Practices during Diarrhoea . 134 10.7 Knowledge of ORS Packets . 137 10.8 Stool Disposal . 137 CHAPTER 11 NUTRITION OF CHILDREN AND ADULTS 11.1 Nutritional Status of Children . 140 11.1.1 Measurement of Nutritional Status among Young Children . 140 11.1.2 Data Collection . 141 11.1.3 Measures of Children’s Nutritional Status . 141 11.1.4 Trends in Children’s Nutritional Status . 144 11.2 Breastfeeding and Complementary Feeding . 145 11.2.1 Initiation of Breastfeeding . 145 11.2.2 Breastfeeding Status by Age . 147 11.2.3 Duration of Breastfeeding . 149 11.2.4 Types of Complementary Foods . 150 11.2.5 Infant and Young Child Feeding (IYCF) Practices . 151 11.3 Prevalence of Anaemia in Children . 154 11.4 Micronutrient Intake among Children . 156 11.5 Iodisation of Household Salt . 159 vi • Contents 11.6 Nutritional Status of Women and Men . 159 11.7 Prevalence of Anaemia in Women . 162 11.8 Micronutrient Intake among Mothers . 164 CHAPTER 12 MALARIA 12.1 Introduction . 167 12.2 Ownership of Mosquito Nets . 168 12.3 Indoor Residual Spraying . 169 12.4 Access to Insecticide-treated Nets . 170 12.5 Use of Mosquito Nets. 172 12.5.1 Overall Use of Mosquito Nets . 172 12.5.2 Use of Mosquito Nets by Children under Age 5 . 174 12.5.3 Use of Mosquito Nets by Pregnant Women . 175 12.6 Preventive Malaria Treatment during Pregnancy . 177 12.7 Fever among Children under Age 5 . 178 12.7.1 Prevalence and Treatment of Fever among Children . 178 12.7.2 Type and Timing of Antimalarial Drugs . 180 12.8 Anaemia Prevalence among Children Age 6-59 Months . 181 CHAPTER 13 HIV AND AIDS-RELATED KNOWLEDGE, ATTITUDES, AND BEHAVIOR 13.1 Introduction . 183 13.2 HIV/AIDS Knowledge, Transmission, and Prevention Methods . 184 13.2.1 Awareness of HIV/AIDS . 184 13.2.2 Knowledge of HIV Prevention . 185 13.2.3 Rejection of Misconceptions about HIV/AIDS . 186 13.2.4 Knowledge of Prevention of Mother-to-Child Transmission of HIV . 189 13.3 Accepting Attitudes towards People Living with Aids . 191 13.4 Attitudes towards Refusing to Have Sex and Negotiating Safer Sex . 193 13.5 Adult Support of Education about Condoms for Children Age 12-14 . 195 13.6 High-risk Sex . 195 13.6.1 Multiple Partners and Condom Use . 196 13.6.2 Transactional Sex . 200 13.7 Coverage of HIV Counseling and Testing . 200 13.7.1 HIV Testing During Antenatal Care . 203 13.8 Male Circumcision . 205 13.9 Self-reporting of Sexually Transmitted Infections . 205 13.10 Treatment of Sexually Transmitted Infections . 207 13.11 Prevalence of Medical Injections . 207 13.12 HIV/AIDS Knowledge and Sexual Behaviour among Young Adults . 209 13.12.1 HIV/AIDS-related Knowledge among Young Adults . 209 13.12.2 Age at First Sexual Intercourse . 210 13.12.3 Abstinence and Premarital Sex . 212 13.12.4 Multiple Partnerships among Young Adults . 213 13.12.5 Age-mixing in Sexual Relationships . 214 13.12.6 Recent HIV Testing among Youth . 215 Contents • vii CHAPTER 14 WOMEN’S EMPOWERMENT AND DEMOGRAPHIC AND HEALTH OUTCOMES 14.1 Employment and Form of Earnings . 217 14.2 Women’s Control over Their Own Earnings and Relative Magnitude of Women’s and Their Husband’s Earnings . 218 14.3 Women’s Control over Husbands’ Earnings . 220 14.4 Women’s Empowerment . 222 14.4.1 Ownership of Assets . 222 14.4.2 Women’s Participation in Household Decision Making . 224 14.4.3 Attitudes towards Wife Beating . 228 14.4.4 Women’s Empowerment Indicators . 231 14.5 Current Use of Contraception by Women’s Empowerment Status . 232 14.6 Ideal Family Size and Unmet Need by Women’s Status . 233 14.7 Women’s Status and Reproductive Health Care . 234 CHAPTER 15 ADULT AND MATERNAL MORTALITY 15.1 Assessment of Data Quality . 235 15.2 Estimates of Adult Mortality . 236 15.3 Estimates of Maternal Mortality . 237 CHAPTER 16 DOMESTIC VIOLENCE 16.1 Measurement of Violence . 239 16.1.1 Use of Valid Measures of Violence . 239 16.1.2 Ethical Considerations in the 2011 UDHS . 241 16.1.3 Subsample for the Violence Module . 241 16.2 Experience of Physical Violence . 241 16.3 Perpetrators of Physical Violence . 245 16.4 Experience of Sexual Violence . 245 16.5 Perpetrators of Sexual Violence . 248 16.6 Age at First Experience of Non-Spousal Sexual Violence . 248 16.7 Experience of Different Forms of Violence . 249 16.8 Violence during Pregnancy . 250 16.9 Marital Control by Spouse . 252 16.10 Forms of Spousal Violence . 255 16.11 Spousal Violence by Background Characteristics . 258 16.12 Violence by Spousal Characteristics and Women’s Empowerment Indicators . 261 16.13 Frequency of Spousal Violence . 263 16.14 Onset of Spousal Violence . 265 16.15 Physical Consequences of Spousal Violence . 265 16.16 Violence by Women/Men against Their Spouse . 266 16.17 Violence Against the Spouse by Spousal Characteristics and Women’s Empowerment Indicators . 269 16.18 Help-seeking Behaviour by Women Who Experience Violence . 270 viii • Contents REFERENCES . 275 APPENDIX A SAMPLE DESIGN AND IMPLEMENTATION . 279 APPENDIX B ESTIMATES OF SAMPLING ERRORS . 287 APPENDIX C DATA QUALITY TABLES . 305 APPENDIX D PERSONS INVOLVED IN THE 2011 UGANDA DEMOGRAPHIC AND HEALTH SURVEY . 311 APPENDIX E QUESTIONNAIRES . 317 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 . 10 Figure 1.1 Map of Uganda DHS clusters . 6 CHAPTER 2 HOUSING CHARACTERISTICS AND HOUSEHOLD POPULATION Table 2.1 Household drinking water . 12 Table 2.2 Household sanitation facilities . 13 Table 2.3 Household characteristics . 14 Table 2.4 Household possessions . 15 Table 2.5 Hand washing . 16 Table 2.6 Wealth quintiles . 17 Table 2.7 Household population by age, sex, and residence . 18 Table 2.8 Household composition . 19 Table 2.9 Birth registration of children under age 5 . 20 Table 2.10 Children's living arrangements and orphanhood . 21 Table 2.11 School attendance by survivorship of parents . 22 Table 2.12.1 Educational attainment of the female household population . 23 Table 2.12.2 Educational attainment of the male household population . 24 Table 2.13 School attendance ratios . 26 Table 2.14 Disability by functional area and age . 28 Figure 2.1 Population pyramid . 18 Figure 2.2 Age-specific attendance rates of the de facto population age 5-24. 27 CHAPTER 3 CHARACTERISTICS OF RESPONDENTS Table 3.1 Background characteristics of respondents . 30 Table 3.2.1 Educational attainment: Women . 31 Table 3.2.2 Educational attainment: Men . 32 Table 3.3.1 Literacy: Women . 33 Table 3.3.2 Literacy: Men . 34 Table 3.4.1 Exposure to mass media: Women . 35 Table 3.4.2 Exposure to mass media: Men . 36 Table 3.5.1 Employment status: Women . 37 Table 3.5.2 Employment status: Men . 39 Table 3.6.1 Occupation: Women . 40 Table 3.6.2 Occupation: Men . 41 Table 3.7 Type of employment: Women . 42 Table 3.8.1 Health insurance coverage: Women . 43 Table 3.8.2 Health insurance coverage: Men . 44 Table 3.9.1 Use of tobacco: Women . 45 Table 3.9.2 Use of tobacco: Men . 46 Figure 3.1 Women's employment status in the past 12 months . 38 x • Tables and Figures CHAPTER 4 MARRIAGE AND SEXUAL ACTIVITY Table 4.1.1 Current marital status . 48 Table 4.1.2 Current marital status and type of marriage . 48 Table 4.2.1 Number of women's co-wives . 49 Table 4.2.2 Number of men's wives . 50 Table 4.3 Age at first marriage . 51 Table 4.4 Median age at first marriage by background characteristics . 52 Table 4.5 Age at first sexual intercourse . 53 Table 4.6 Median age at first sexual intercourse by background characteristics . 54 Table 4.7.1 Recent sexual activity: Women . 55 Table 4.7.2 Recent sexual activity: Men . 56 CHAPTER 5 FERTILITY Table 5.1 Current fertility . 57 Table 5.2 Fertility by background characteristics . 59 Table 5.3.1 Trends in age-specific fertility rates . 60 Table 5.3.2 Trends in age-specific and total fertility rates, Uganda 2000-01, 2006, 2011 . 60 Table 5.4 Children ever born and living . 62 Table 5.5 Birth intervals . 63 Table 5.6 Postpartum amenorrhoea, abstinence and insusceptibility . 64 Table 5.7 Median duration of amenorrhoea, postpartum abstinence, and postpartum insusceptibility . 65 Table 5.8 Menopause . 65 Table 5.9 Age at first birth . 66 Table 5.10 Median age at first birth . 66 Table 5.11 Teenage pregnancy and motherhood . 67 Figure 5.1 TFR in eastern and southern Africa, DHS surveys . 58 Figure 5.2 Trends in fertility . 61 CHAPTER 6 FERTILITY PREFERENCES Table 6.1 Fertility preferences by number of living children . 70 Table 6.2 Desire to limit childbearing: Women . 71 Table 6.3 Ideal number of children by number of living children . 72 Table 6.4 Mean ideal number of children . 73 Table 6.5 Fertility planning status . 74 Table 6.6 Wanted fertility rates . 75 CHAPTER 7 FAMILY PLANNING Table 7.1 Knowledge of contraceptive methods . 78 Table 7.2 Current use of contraception by age . 80 Table 7.3 Current use of contraception by background characteristics . 82 Table 7.4 Trends in the current use of contraception . 83 Table 7.5 Source of modern contraception methods . 85 Table 7.6 Use of social marketing brand pills and condoms . 85 Table 7.7 Informed choice . 86 Table 7.8 12-month contraceptive discontinuation rates . 87 Table 7.9 Reasons for discontinuation . 88 Table 7.10 Knowledge of fertile period . 88 Table 7.11 Need and demand for family planning among currently married women . 91 Table 7.12 Future use of contraception . 92 Tables and Figures • xi Table 7.13 Exposure to family planning messages . 93 Table 7.14 Contact of nonusers with family planning providers . 94 Table 7.15 Family planning counseling . 95 Figure 7.1 Trends in contraceptive use among currently married women . 84 Figure 7.2 Trends in unmet need for family planning, Uganda 2000-2011 . 92 CHAPTER 8 INFANT AND CHILD MORTALITY Table 8.1 Early childhood mortality rates . 99 Table 8.2 Early childhood mortality rates by socioeconomic characteristics . 100 Table 8.3 Early childhood mortality rates by demographic characteristics . 101 Table 8.4 Perinatal mortality . 102 Table 8.5 High-risk fertility behaviour . 103 Figure 8.1 Trends in childhood mortality . 99 CHAPTER 9 REPRODUCTIVE HEALTH Table 9.1 Antenatal care . 106 Table 9.2 Number of antenatal care visits and timing of first visit . 107 Table 9.3 Components of antenatal care . 108 Table 9.4 Doses of drugs for intestinal worms . 109 Table 9.5 Tetanus toxoid injections . 110 Table 9.6 Place of delivery . 111 Table 9.7 Assistance during delivery . 113 Table 9.8 Timing of first postnatal checkup . 115 Table 9.9 Type of provider of first postnatal checkup for the mother . 116 Table 9.10 Timing of first postnatal checkup for the newborn . 117 Table 9.11 Type of provider of first postnatal checkup for the newborn . 118 Table 9.12 Problems accessing health care . 119 Table 9.13 Female circumcision . 120 Table 9.14 Obstetric fistula . 121 Figure 9.1 Mother’s duration of stay in the health facility after giving birth . 114 CHAPTER 10 CHILD HEALTH Table 10.1 Child's weight and size at birth . 124 Table 10.2 Vaccinations by source of information . 126 Table 10.3 Vaccinations by background characteristics . 127 Table 10.4 Vaccinations in first year of life . 128 Table 10.5 Prevalence and treatment of symptoms of ARI . 129 Table 10.6 Prevalence and treatment of fever . 131 Table 10.7 Prevalence of diarrhoea . 132 Table 10.8 Diarrhoea treatment . 134 Table 10.9 Feeding practices during diarrhoea . 136 Table 10.10 Knowledge of ORS packets . 137 Table 10.11 Disposal of children's stools . 138 Figure 10.1 Trends in vaccination coverage during the first year of life among children 12-23 months . 128 xii • Tables and Figures CHAPTER 11 NUTRITION OF CHILDREN AND WOMEN Table 11.1 Nutritional status of children . 143 Table 11.2 Initial breastfeeding . 146 Table 11.3 Breastfeeding status by age . 148 Table 11.4 Median duration of breastfeeding . 150 Table 11.5 Foods and liquids consumed by children in the day or night preceding the interview . 151 Table 11.6 Infant and young child feeding (IYCF) practices . 153 Table 11.7 Prevalence of anaemia in children . 155 Table 11.8 Micronutrient intake among children . 158 Table 11.9 Presence of iodized salt in household . 159 Table 11.10.1 Nutritional status of women . 160 Table 11.10.2 Nutritional status of men . 162 Table 11.11 Prevalence of anaemia in women . 163 Table 11.12 Micronutrient intake among mothers . 165 Figure 11.1 Nutritional status of children by age . 144 Figure 11.2 Trends in nutritional status of children under 5 years . 145 Figure 11.3 Infant feeding practices by age . 147 Figure 11.4 IYCF indicators on breastfeeding status . 149 Figure 11.5 IYCF indicators on minimum acceptable diet . 154 Figure 11.6 Trends in anaemia status among children under 5 years . 156 Figure 11.7 Trends in nutritional status among women 15-49 years . 161 Figure 11.8 Trends in anaemia status among women age 15-49 years . 164 CHAPTER 12 MALARIA Table 12.1 Household possession of mosquito nets . 169 Table 12.2 Indoor residual spraying against mosquitoes . 170 Table 12.3 Access to an insecticide-treated net (ITN) . 171 Table 12.4 Use of mosquito nets by persons in the household . 173 Figure 12.2 Ownership of, access to, and use of ITNs . 174 Table 12.5 Use of mosquito nets by children . 175 Table 12.6 Use of mosquito nets by pregnant women . 176 Table 12.7 Prophylactic use of antimalarial drugs and use of intermittent preventive treatment (IPTp) by women during pregnancy . 178 Table 12.8 Prevalence, diagnosis, and prompt treatment of children with fever . 179 Table 12.9 Type and timing of antimalarial drugs used . 181 Table 12.10 Haemoglobin <8.0 g/dl in children . 182 Figure 12.1 Percentage of the de facto household population with access to an insecticide-treated net . 172 CHAPTER 13 HIV AND AIDS-RELATED KNOWLEDGE, ATTITUDES, AND BEHAVIOR Table 13.1 Knowledge of AIDS . 184 Table 13.2 Knowledge of HIV prevention methods . 185 Table 13.3.1 Comprehensive knowledge about AIDS: Women . 187 Table 13.3.2 Comprehensive knowledge about AIDS: Men . 188 Table 13.4 Knowledge of prevention of mother to child transmission of HIV . 190 Table 13.5.1 Accepting attitudes toward those living with HIV/AIDS: Women . 191 Table 13.5.2 Accepting attitudes toward those living with HIV/AIDS: Men . 192 Table 13.6 Attitudes toward negotiating safer sexual relations with husband . 194 Table 13.7 Adult support of education about condom use to prevent AIDS . 195 Table 13.8.1 Multiple sexual partners: Women. 196 Tables and Figures • xiii Table 13.8.2 Multiple sexual partners: Men . 197 Table 13.9 Point prevalence and cumulative prevalence of concurrent sexual partners . 199 Table 13.10 Payment for sexual intercourse and condom use at last paid sexual intercourse . 200 Table 13.11.1 Coverage of prior HIV testing: Women . 201 Table 13.11.2 Coverage of prior HIV testing: Men . 202 Table 13.12 Pregnant women counseled and tested for HIV . 204 Table 13.13 Male circumcision . 205 Table 13.14 Self-reported prevalence of sexually-transmitted infections (STIs) and STI symptoms . 206 Table 13.15 Prevalence of medical injections . 208 Table 13.16 Comprehensive knowledge about AIDS and of a source of condoms among young people . 209 Table 13.17 Age at first sexual intercourse among young people . 211 Table 13.18 Premarital sexual intercourse and condom use during premarital sexual intercourse among young people . 212 Table 13.19 Multiple sexual partners in the past 12 months among young people . 213 Table 13.20 Age-mixing in sexual relationships among women age 15 19 . 214 Table 13.21 Recent HIV tests among young people . 215 Figure 13.2 Trends in age at first sexual intercourse . 212 Figure 13.1 Women and men seeking advice or treatment for STIs . 207 CHAPTER 14 WOMEN’S EMPOWERMENT AND DEMOGRAPHIC AND HEALTH OUTCOMES Table 14.1 Employment and cash earnings of currently married women and men . 218 Table 14.2.1 Control over women's cash earnings and relative magnitude of women's cash earnings: Women . 219 Table 14.2.2 Control over men's cash earnings . 221 Table 14.3 Women's control over their own earnings and over those of their husbands . 222 Table 14.4.1 Ownership of assets: Women . 223 Table 14.4.2 Ownership of assets; Men . 224 Table 14.5 Participation in decision making . 225 Table 14.6.1 Women's participation in decision making by background characteristics . 226 Table 14.6.2 Men's participation in decision making by background characteristics . 228 Table 14.7.1 Attitude toward wife beating: Women . 229 Table 14.7.2 Attitude toward wife beating: Men . 231 Table 14.8 Indicators of women's empowerment . 232 Table 14.9 Current use of contraception by women's empowerment . 233 Table 14.10 Women's empowerment and ideal number of children and unmet need for family planning . 233 Table 14.11 Reproductive health care by women's empowerment . 234 Figure 14.1 Number of decisions in which currently married women participate . 227 CHAPTER 15 ADULT AND MATERNAL MORTALITY Table 15.1 Adult mortality rates . 236 Table 15.2 Adult mortality probabilities . 237 Table 15.3 Maternal mortality . 237 Figure 15.1 Maternal mortality ratio (MMR) for the seven years preceding the 2000-01, 2006, and 2011 Uganda DHS with confidence intervals . 238 xiv • Tables and Figures CHAPTER 16 DOMESTIC VIOLENCE Table 16.1.1 Experience of physical violence: women . 243 Table 16.1.2 Experience of physical violence: men . 244 Table 16.2.2 Persons committing physical violence: men . 245 Table 16.2.1 Persons committing physical violence: women . 245 Table 16.3.1 Experience of sexual violence: women . 246 Table 16.3.2 Experience of sexual violence: men . 247 Table 16.4.1 Persons committing sexual violence: women . 248 Table 16.4.2 Persons committing sexual violence: men . 248 Table 16.5.1 Age at first experience of non-spousal sexual violence: women . 249 Table 16.5.2 Age at first experience of non-spousal sexual violence: men . 249 Table 16.6.1 Experience of different forms of violence: women . 250 Table 16.6.2 Experience of different forms of violence: men . 250 Table 16.7 Experience of violence during pregnancy . 251 Table 16.8.1 Marital control exercised by husbands . 253 Table 16.8.2 Marital control exercised by wives . 254 Table 16.9.1 Forms of spousal violence: women . 256 Table 16.9.2 Forms of spousal violence: men . 258 Table 16.10.1 Spousal violence by background characteristics: women . 259 Table 16.10.2 Spousal violence by background characteristics: men . 260 Table 16.11.1 Spousal violence by husband's characteristics and empowerment indicators: women . 261 Table 16.11.2 Spousal violence by wife's characteristics and empowerment indicators: men . 262 Table 16.12.1 Frequency of physical or sexual violence: women . 263 Table 16.12.2 Frequency of physical or sexual violence: men . 264 Table 16.13.1 Experience of spousal violence by duration of marriage: women . 265 Table 16.13.2 Experience of spousal violence by duration of marriage: men . 265 Table 16.14.1 Injuries to women due to spousal violence: women . 266 Table 16.14.2 Injuries to men due to spousal violence: men . 266 Table 16.15.1 Violence by women against their spouse by background characteristics . 267 Table 16.15.2 Men's violence against their spouse by background characteristics . 268 Table 16.16.1 Violence by women against their spouse by spouse's characteristics and empowerment indicators . 269 Table 16.16.2 Men's violence against their spouse by wife's characteristics and empowerment indicators . 270 Table 16.17.1 Help seeking to stop violence: women . 271 Table 16.17.2 Help seeking to stop violence: men . 272 Table 16.18.1 Sources for help to stop the violence: women . 273 Table 16.18.2 Sources for help to stop the violence: men . 273 Figure 16.1 Percentage of ever-married women age 15-49 who have experienced specific types of spousal physical and sexual violence by the current or most recent husband/partner . 257 Tables and Figures • xv APPENDIX A SAMPLE DESIGN AND IMPLEMENTATION Table A.1 Enumeration areas and households . 280 Table A.2 Population . 280 Table A.3 Sample allocation of clusters and households . 281 Table A.4 Sample allocation of completed interviews with women and men . 281 Table A.5 Sample implementation . 282 Table A.6 Sample implementation: Men . 283 APPENDIX B ESTIMATES OF SAMPLING ERRORS Table B.1 List of selected variables for sampling errors, 2011 Uganda. 289 Table B.2 Sampling errors for national sample, Uganda 2011 . 290 Table B.3 Sampling errors for urban sample, Uganda 2011 . 291 Table B.4 Sampling errors for rural sample, Uganda 2011 . 292 Table B.5 Sampling errors for Kampala region, Uganda 2011 . 293 Table B.6 Sampling errors for Central 1 region, Uganda 2011 . 294 Table B.7 Sampling errors for Central 2 region, Uganda 2011 . 295 Table B.8 Sampling errors for East Central region, Uganda 2011 . 296 Table B.9 Sampling errors for Eastern region, Uganda 2011 . 297 Table B.10 Sampling errors for Karamoja region, Uganda 2011 . 298 Table B.11 Sampling errors for North region, Uganda 2011 . 299 Table B.12 Sampling errors for North region, Uganda 2011 . 300 Table B.13 Sampling errors for Western region, Uganda 2011 . 301 Table B.14 Sampling errors for Southwest region, Uganda 2011 . 302 Table B.15 Sampling errors for adult and maternal mortality rates for the seven-year period preceding the survey, Uganda 2011 . 303 APPENDIX C DATA QUALITY TABLES Table C.1 Household age distribution . 305 Table C.2.1 Age distribution of eligible and interviewed women . 306 Table C.2.2 Age distribution of eligible and interviewed men . 306 Table C.3 Completeness of reporting . 307 Table C.4 Births by calendar years . 307 Table C.5 Reporting of age at death in days . 308 Table C.6 Reporting of age at death in months . 308 Table C.7 Nutritional status of children . 309 Table C.8 Completeness of information on siblings . 310 Table C.9 Sibship size and sex ratio of siblings . 310 Preface • xvii he 2011 Uganda Demographic and Health Survey (2011 UDHS) was designed as a follow-up to the 1988/89, 1995, 2000-01, and 2006 Uganda DHS surveys. The main objective of the 2011 UDHS was to obtain current statistical data on the Ugandan population’s demographic characteristics, family planning efforts, maternal mortality, and infant and child mortality. Another objective was to collect information on health care services and activities, antenatal, delivery, and postnatal care, children’s immunisations, and management of childhood diseases. In addition, the survey was designed to evaluate the nutritional status of mothers and children, to measure the prevalence of anaemia among women and children, to assess the level of knowledge about HIV and AIDS among men and women, and to determine the extent of interpersonal violence. The findings of the 2011 UDHS are critical to measurement of the achievements of family planning and other health programmes. To better understand and utilise these findings, the results will be widely disseminated at different planning levels using diverse dissemination techniques to reach the various segments of society. The Uganda Bureau of Statistics would like to acknowledge the efforts of a number of organisations and individuals who contributed immensely to the success of the survey. The Ministry of Health (MOH) chaired the Technical Working Committee, which offered guidance on the implementation of the survey. The Makerere University School of Public Health (MakSPH) and the Makerere University Department of Biochemistry and Sports Science under the College of Natural Sciences conducted the Quality Control and the laboratory testing for vitamin A deficiency respectively. ICF International is greatly appreciated for providing important technical support. Financial assistance was provided by the government of Uganda, USAID/Uganda, the United Nations Population Fund (UNFPA), the United Nations Children’s Fund (UNICEF), the World Health Organisation (WHO), the UK Government and Irish Aid-the Government of Ireland. We are grateful for the efforts of officials at national and local government levels who supported the survey. Finally, we highly appreciate all the hard work of field staff and, most important, the contributions of survey respondents whose participation was critical to the successful completion of this survey. John B. Male-Mukasa Executive Director Uganda Bureau of Statistics PREFACE T Millennium Development Goal Indicators • xix MILLENNIUM DEVELOPMENT GOAL INDICATORS Millennium Development Goal Indicators Uganda 2011 Indicator Sex Total Female Male 1. Eradicate extreme poverty and hunger 1.8 Prevalence of underweight children under five years of age 12.7 14.9 13.8 2. Achieve universal primary education 2.1 Net attendance ratio in primary education1 81.0 81.1 81.0 2.3 Literacy rate of 15-24 year olds2 75.2a 77.1 76.1 b 3. Promote gender equality and empower women 3.1a Ratio of girls to boys in primary education3 na na 1.0 3.1b Ratio of girls to boys in secondary education3 na na 1.1 3.1c Ratio of girls to boys in tertiary education3 na na 0.7 4. Reduce child mortality 4.1 Under five mortality rate4 98 114 90 4.2 Infant mortality rate4 59 70 54 4.3 Proportion of 1 year-old children immunized against measles 76.6 74.8 75.8 5. Improve maternal health 5.1 Maternal mortality ratio5 na na 438 5.2 Percentage of births attended by skilled health personnel6 na na 58.0 5.3 Contraceptive prevalence rate7 30.0 na na 5.4 Adolescent birth rate8 134.5 na na 5.5a Antenatal care coverage: at least 1 visit by a skilled health professional 94.9 na na 5.5b Antenatal care coverage: four or more visits by any provider 47.6 na na 5.6 Unmet need for family planning 34.3 na na 6. Combat HIV/AIDS, malaria and other diseases 6.2 Condom use at last high-risk sex9 51.0 a 61.1 56.1 b 6.3 Percentage of the population age 15-24 years with comprehensive correct knowledge of HIV/AIDS10 38.1 a 39.5 38.8 b 6.4 Ratio of school attendance of orphans to school attendance of non-orphans aged 10-14 years 0.92 0.83 0.87 6.7 Percentage of children under 5 sleeping under insecticide treated bednets 44.0 41.6 42.8 6.8 Percentage of children under 5 with fever who are treated with appropriate antimalarial drugs11 66.7 62.1 64.5 Residence Total Urban Rural 7. Ensure environmental sustainability 7.8 Percentage of population using an improved drinking water source12 89.6 66.6 70.0 7.9 Percentage of population with access to improved sanitation13 26.3 17.4 18.7 na = Not applicable 1 The rate is based on reported attendance, not enrollment, in primary education among primary school age children (6-12 year-olds). The rate also includes children of primary school age enrolled in secondary education. This is proxy for MDG indicator 2.1, Net enrollment ratio. 2 Refers to respondents who attended secondary school or higher or who could read a whole sentence or part of a sentence 3 Based on reported net attendance, not gross enrollment, among 6-12 year-olds for primary, 13-18 year-olds for secondary and 19-24 year- olds for tertiary education 4 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. 5 Expressed in terms of maternal deaths per 100,000 live births in the 7-year period preceding the survey 6 Among births in the five years preceding the survey 7 Percentage of currently married women age 15-49 using any method of contraception 8 Equivalent to the age-specific fertility rate for women age 15-19 for the 3-year preceding the survey, expressed in terms of births per 1,000 women age 15-19 9 Higher-risk sex refers to sexual intercourse with a non-marital, non-cohabitating partner. Expressed as a percentage of men and women age 15-24 who had higher-risk sex in the past 12 months. 10 Comprehensive knowledge means knowing that consistent use of a condom during sexual intercourse and having just one uninfected faithful partner can reduce the chance of getting the AIDS virus, knowing 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. 11 Measured as the percentage of children age 0-59 months who were ill with a fever in the two weeks preceding the interview and received any anti-malarial drug 12 Percentage of de-jure population whose main source of drinking water is a household connection (piped), private and public tap, boreholes, protected /dug well or spring, rain and bottled water 13 Percentage of de-jure population whose household has a flush toilet, ventilated improved pit latrine, pit latrine with a slab, composting toilet, or Ecosan and does not share this facility with other households a Restricted to men in sub-sample of households selected for the male interview b The total is calculated as the simple arithmetic mean of the percentages in the columns for male and females xx • Map of Uganda Introduction • 1 INTRODUCTION 1 1.1 HISTORY, GEOGRAPHY, AND ECONOMY History ganda’s first elections were held on 1 March 1961 and the country obtained independence from Britain in 1962. Uganda became a republic in 1963 and maintained its British Commonwealth membership. There was conflict between supporters of a centralized state and supporters of a loose federation and a strong role of the tribally-based local kingdoms. In February 1966, the Prime Minister Milton Obote suspended the constitution, removed the president and the vice president, and abolished traditional kingdoms. In 1963, a new constitution proclaimed Uganda a republic and gave President Obote greater power. In 1971, a military coup led by armed forces commander Idi Amin Dada overthrew President Obote's government. Amin became the President, dissolved the parliament, and amended the constitution to give himself absolute power. During Amin’s rule, there was economic decline, social disintegration, and open human rights and ethnic violations. The Ugandan army attacked Tanzania because of a border dispute involving Ugandan exiles who had a camp close to the Ugandan border of Mutukula. In 1978, the Tanzanian armed forces fought against Amin's troops that invaded the Tanzanian territory. In return, the Tanzanian army, helped by Ugandans in exile, started a war against Amin's troops and in April 1979 captured Kampala and forced Amin and his remaining forces to flee to Libya. After Amin's removal, there was a succession of leaders before the return of President Milton Obote in 1980. The security forces of Uganda had one of the world's worst human rights records under President Obote. He ruled until July 1985, when an army brigade took over and proclaimed a military government. Obote fled to exile in Zambia. The new government was headed by the former defense force commander General Tito Okello. The Okello government carried out a brutal counterinsurgency in an attempt to destroy the support for the National Resistance Army (NRA) led by Yoweri Kaguta Museveni. Despite negotiations between the Okello government and the NRA and an agreement to a cease- fire in late 1985, the NRA continued the resistance and seized Kampala and the country in late January 1986, forcing Okello's forces to flee to Sudan. The NRA organized a government and proclaimed U Key Findings  The 2011 Uganda Demographic and Health Survey (UDHS) is a nationally representative survey of 10,086 households with 9,247 women age 15-49 and 2,573 men age 15-54.  The 2011 UDHS is the fifth comprehensive survey conducted in Uganda as part of the worldwide Demographic and Health Surveys project.  The primary purpose of the UDHS is to furnish policymakers and planners with detailed information on fertility and 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 for vitamin A deficiency. 2 • Introduction Museveni as president. The new government ended human rights abuses of earlier governments in Uganda, instituted broad economic reforms, and started political liberalization and freedom of the press. The armed resistance against the government has continued since 1986 in northern areas of the country, such as Acholiland. Some of the rebel groups include the Uganda People's Democratic Army, the Holy Spirit Movement, and the Lord's Resistance Army, headed by Joseph Kony, which carried out widespread abduction of children to serve as soldiers or sex slaves. Peace has however started returning to the Northern region and people originally living in internally displaced peoples camps have started settling in their villages. Geography The republic of Uganda is located in East Africa and lies astride the equator. It is a landlocked country that borders Kenya to the east, Tanzania to the south, Rwanda to the southwest, the Democratic Republic of Congo to the west, and South Sudan to the north. The country has an area of 241,039 square kilometres and is administratively divided into 112 districts. Uganda has a decentralized system of governance and several functions have been ceded to the local governments. However, the central government retains the role of formulating policy, setting and supervising standards, and providing national security. Uganda has a favourable climate because of its relatively high altitude. The Central, Eastern, and Western regions of the country have two rainy seasons per year, with relatively heavy rains from March through May and light rains from September through December. The level of rainfall decreases as one travels northward, turning into just one rainy season a year. The soil fertility varies accordingly, being generally fertile in the Central and Western regions and becoming less fertile as one moves to the east and the north. Because climate varies, Uganda’s topography ranges from tropical rain forest vegetation in the south to savannah woodlands and semi-arid vegetation in the north. Climate determines the agricultural potential and thus the land’s capacity to sustain human population; population densities are high in the Central and Western regions and decline towards the north. Economy The economy is predominantly agricultural, with the majority of the population dependent on subsistence farming and light agro-based industries. The country is self-sufficient in food, although its distribution is uneven over all areas. Coffee remains the main foreign exchange earner for the country. During the period immediately following independence, from 1962 to 1970, Uganda had a flourishing economy with a 5 percent growth Gross Domestic Product (GDP) per annum; this contrasted with a population growth rate of 2.6 percent per annum. In the 1970s through the early 1980s, Uganda faced a period of civil and military unrest, resulting in the destruction of the economic and social infrastructure. The growth of the economy and the provision of social services such as education and health care were seriously affected. Since 1986, however, the government has introduced and implemented several reform programmes that have steadily reversed prior setbacks and aimed the country towards economic prosperity. Between 2006 and 2011, the country’s growth in GDP varied between 5.6 percent and 7.1 percent a year (UBOS, 2006a). 1.2 POPULATION In the past, most demographic statistics in Uganda were derived from population censuses, which began in 1948. Subsequent censuses have been held in 1959, 1969, 1980, 1991, and 2002. In addition, Demographic and Health Surveys have been conducted in 1988-1989, 1995, 2000-2001, 2006, and most recently in 2011, the subject of the present report. Additional demographic data have been obtained from other surveys devoted to specific subjects. Introduction • 3 Civil registration was made compulsory in Uganda in 1973. However, its coverage is incomplete, and it is therefore not viable as a source of demographic statistics. Efforts to streamline the system were made between 1974 and 1978, but the achievements from this effort were later frustrated by the economic and civil instability. Table 1.1 presents several demographic indices compiled from the population censuses of 1969 through 2002. Over that period, the population has increased as a result of high fertility and declining mortality. The annual population growth rate between 1969 and 1980 was 2.7 percent, which decreased to 2.5 percent between 1980 and 1991. Instability in Uganda during the early 1980s may have contributed to this decline. The annual population growth rate increased to 3.2 percent between the 1991 census and the 2002 census. The level of urbanization is still low but has been increasing over time. In 2002, a little more than 12 percent of the population lived in urban areas (UBOS, 2006a). Table 1.1 Basic demographic indicators Selected demographic indicators, Uganda 1969-2002 Indicator 1969 1980 1991 2002 Population (thousands) 9,535.1 12,632.2 16,672.7 24,227.3 Intercensal growth rate (percent) 3.9 2.7 2.5 3.2 Density (population/kilometre2) 48 64 85 124 Percent urban 6.6a 6.7 9.9 12.3 Life expectancy Male 46.0 u 45.7 48.8 Female 47.0 u 50.5 52.0 Total 46.5 u 48.1 50.4 u = Unknown (not available) a The 1969 data are based on a different definition of urban Source: UBOS, 2006b 1.3 POPULATION AND HEALTH POLICIES National Population Policy Uganda’s first explicit National Population Policy was promulgated by the government in 1995. That policy elaborated clear strategies with an overall goal of contributing to the improvement of the quality of life of the people of Uganda. Since its foundation, a number of lessons have been learnt. Some important targets were achieved, but others were not. There have also been some major challenges and opportunities at local, regional, and international levels, which need to be taken into account as the country moves forward. It is against this backdrop that the government began to revise the National Population Policy to accommodate new and emerging challenges. The revised policy is a clarion call to plan for and invest in the increasing population, so that the country’s human capital develops to its full potential. Only then can Ugandans hope to benefit from an increasing population as a demographic ‘bonus’ instead of a demographic ‘burden’ (POPSEC, 2008). A National Population Action Plan was also developed and rolled out at the subnational level. Health Policy The first Health Sector Strategic Plan (HSSP I) for Uganda covered the period 2000/01 to 2004/05. The plan helped to guide the government of Uganda in its health sector investments, which were led by the Ministry of Health, health development partners (HDPs), and other stakeholders over this period. Continuous monitoring through quarterly and mid-term reviews helped to assess key achievements and challenges during the implementation of HSSP I and formed the basis for the development of HSSP II for the period 2005/06 to 2009/10. HSSP II was completed in June 2010. 4 • Introduction The government of Uganda, with the stewardship of the Ministry of Health (MOH), developed the second National Health Policy (NHP II) to cover a ten-year period from 2010/11 to 2019/20. The third Health Sector Strategic Plan (HSSP III) was developed to operationalize the NHP II and the health sector component of the National Development Plan (NDP) 2010/11-2014/15, which is the overall development plan for Uganda. The HSSP III provides an overall framework for the health sector. Its major aim is to contribute towards the overall development goal of the government of Uganda by accelerating economic growth to reduce poverty. 1.4 OBJECTIVES OF THE 2011 UDHS SURVEY The 2011 Uganda Demographic and Health Survey (UDHS) was designed to provide information on demographic, health, and family planning status and trends in the country. Specifically, the UDHS collected information on fertility levels, marriage, sexual activity, fertility preferences, breastfeeding practices, and awareness and use of family planning methods. In addition, data were collected on the nutritional status of mothers and young children; infant, child, adult, and maternal mortality; maternal and child health; awareness and behaviour regarding HIV/AIDS and other sexually transmitted infections; and levels of anaemia and vitamin A deficiency. The 2011 UDHS is a follow-up to the 1988-1989, 1995, 2000-2001, and 2006 UDHS surveys, which were implemented by the Statistics Department of Ministry of Finance and Planning, and later by the Uganda Bureau of Statistics (UBOS). The specific objectives of the 2011 UDHS were as follows:  To provide data at the national and subnational level that would allow the calculation of demographic rates, particularly fertility and infant mortality rates  To analyse the direct and indirect factors that determine the level of and trends in fertility and mortality  To measure the level of contraceptive knowledge and practice of women and men by method, by urban-rural residence, and by region  To collect data on knowledge and attitudes of women and men about sexually transmitted infections and HIV/AIDS, and to evaluate patterns of recent behaviour regarding condom use  To assess the nutritional status of children under age 5 and women by means of anthropometric measurements (weight and height), and to assess child feeding practices  To collect data on family health, including antenatal visits, assistance at delivery, breastfeeding, immunizations, and prevalence and treatment of diarrhoea and other diseases among children under age 5  To measure vitamin A deficiency in women and children, and to measure anaemia in women, men, and children  To measure key education indicators, including school attendance ratios and primary school grade repetition and dropout rates  To collect information on the extent of disability  To collect information on the extent of gender-based violence Introduction • 5 This information is essential for informed policy-making and planning, monitoring, and evaluation of health programmes in general and reproductive health programmes in particular, at both the national and regional levels. A long-term objective of the survey was to strengthen the technical capacity of the National Statistics Office to plan, conduct, process, and analyse data from complex national population and health surveys. The 2011 UDHS provides national and regional estimates on population and health that are comparable to data collected in Uganda’s four previous DHS surveys and similar surveys in other developing countries. Data collected in the 2011 UDHS add to the large and growing international database of demographic and health indicators. 1.5 ORGANIZATION OF THE SURVEY The Uganda Bureau of Statistics (UBOS) was the major implementer of the survey. Other agencies and organizations that facilitated the successful implementation of the survey through their technical support include the Ministry of Health, Makerere University School of Public Health, and the Biochemistry Department of Makerere University. A multi-sect oral Technical Working Committee was also constituted to provide technical backstopping. The same team was also responsible for questionnaire design, training, and report writing. Financial assistance was provided by the government of Uganda, USAID/Uganda, the United Nations Population Fund (UNFPA), the United Nations Children’s Fund (UNICEF), the World Health Organization (WHO), the UK Government and Irish Aid-the Government of Ireland. In addition, ICF International provided limited technical assistance in data processing and report production through the MEASURE DHS project, a USAID-funded program supporting the implementation of population and health surveys in countries worldwide. The UDHS Technical Working Committee, composed of members drawn from the Ministry of Health, the Population Secretariat, and various development partners, oversaw technical issues related to the survey, such as questionnaire design, training, and report writing. 1.6 SAMPLE DESIGN The sample for the 2011 UDHS was designed to provide population and health indicator estimates for the country as a whole and for urban and rural areas separately. Estimates were also reported for the 10 regions of Uganda shown in Figure 1.1. 6 • Introduction Figure 1.1 Map of Uganda DHS clusters Introduction • 7 A representative sample of 10,086 households was selected for the 2011 UDHS. The sample was selected in two stages. In the first stage, 404 enumeration areas (EAs) were selected from among a list of clusters sampled for the 2009/10 Uganda National Household Survey (2010 UNHS). This matching of samples was done to allow linking of the 2011 UDHS health indicators to poverty data from the 2010 UNHS. The clusters in the UNHS were selected from the 2002 Population Census sample frame. In the second stage of sampling, households in each cluster were selected from a complete listing of households, which was updated prior to the survey. Households were purposively selected from those listed. All households in the 2010 UNHS that were in the 404 EAs were included in the UDHS sample. All women age 15-49 who were either permanent residents of the households or visitors who slept in the households the night before the survey were eligible to be interviewed. In addition, in a subsample of one-third of households selected for the survey, all men age 15-54 were eligible to be interviewed if they were either permanent residents or visitors who slept in the household on the night before the survey. Details about the sample design are presented in Appendix A. An additional sample was selected for administration of the Maternal Mortality Module. 1.7 QUESTIONNAIRES Four types of questionnaires were used in the 2011 UDHS: the Household Questionnaire, the Woman’s Questionnaire, the Maternal Mortality Questionnaire, and the Man’s Questionnaire. These questionnaires were adapted from model survey instruments developed by ICF for the MEASURE DHS project and by UNICEF for the Multiple Indicator Cluster Survey (MICS) project. The intent was to reflect the population and health issues relevant to Uganda. Questionnaires were discussed at a series of meetings with various stakeholders, ranging from government ministries and agencies to nongovernmental organizations (NGOs) and development partners. The questionnaires were translated into seven major languages: Ateso, Ngakarimojong, Luganda, Lugbara, Luo, Runyankole-Rukiga, and Runyoro-Rutoro. The Household Questionnaire was used to list all the usual members and visitors who spent the previous night in the selected households. Basic information was collected on the characteristics of each person listed, including his or her age, sex, education, relationship to the head of the household, and disability status. For children under age 18, survival status of the parents was determined. Data on the age and sex of household members were used to identify women and men eligible for an individual interview. In addition, the Household Questionnaire collected information on characteristics of the household’s dwelling unit, such as the source of water, type of toilet facilities, materials used for the floor of the house, ownership of various durable goods, and ownership and use of mosquito bednets. The Woman’s Questionnaire was used to collect information from all eligible women age 15-49. The eligible women were asked questions on the following topics:  Background characteristics (age, education, media exposure, etc.)  Birth history and childhood mortality  Knowledge and use of family planning methods  Fertility preferences  Antenatal, delivery, and postnatal care  Breastfeeding and infant feeding practices  Vaccinations and childhood illnesses  Marriage and sexual activity  Woman’s work and husband’s background characteristics  Awareness and behaviour regarding AIDS and other sexually transmitted infections (STIs) 8 • Introduction  Adult mortality, including maternal mortality  Knowledge of tuberculosis and other health issues  Gender-based violence The Maternal Mortality Questionnaire was administered to all eligible women age 15-49 in 35 additional households in 394 out of 404 EAs. It collected data on maternal mortality using the Sibling Survival Module (commonly referred to as the ‘Maternal Mortality Module’). The Man’s Questionnaire was administered to all eligible men age 15-54 years in every third household in the 2011 UDHS sample. The Man’s Questionnaire collected information similar to that in 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 ANTHROPOMETRY, ANAEMIA, AND VITAMIN A TESTING The 2011 UDHS included height and weight measurements, testing for anaemia, and blood sample collection on filter paper cards for vitamin A testing in the laboratory. The protocol for anaemia testing and for the blood specimen collection for vitamin A testing was similar to that used in the 2006 UDHS. Height and Weight Measurement Height and weight measurements were carried out on eligible women age 15-49 and children under age 5 in all selected households, and eligible men age 15-54 in one-third of the households. Weight measurements were obtained using lightweight, SECA mother-infant scales with a digital screen that were 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 were measured while standing. Anaemia Testing Blood specimens were collected to test for anaemia in all children age 6-59 months, women age 15-49 years, and men age 15-54 years 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 on site using a battery-operated portable HemoCue analyzer. Results were given verbally and in writing. Parents of children with a haemoglobin level under 7 grams per decilitre (g/dl) were instructed to take the child to a health facility for follow-up care. Likewise, non-pregnant women, pregnant women, and men were referred for follow-up care if their haemoglobin level was below 7 g/dl, 9 g/dl, and 9 g/dl, respectively. All households in which testing was conducted were given a brochure explaining the causes and prevention of anaemia. Resulting data were adjusted for altitude prior to being tabulated. Vitamin A Testing Blood specimens were collected by the health technicians to test for vitamin A in all women age 15-49 who consented and all children age 6-59 months whose parent or responsible adult consented. The protocol for the blood specimen collection and analysis was based on the anonymous linked protocol developed for the MEASURE DHS project. This protocol allows the merging of the vitamin A test results with the socio-demographic data collected from the individual questionnaires (after removal of all identifying information). Introduction • 9 The health technicians explained the procedure, the confidentiality of the data, and the fact that the vitamin A test results would not be made available to the respondent. If a respondent consented to the vitamin A testing, a maximum of three blood drops from the finger prick were collected on a filter paper card to which a barcode label unique to the respondent was affixed. Respondents were asked whether they consented to having the laboratory store their blood sample for future unspecified testing. If the respondent did not consent to additional testing using their sample, the words ‘no additional testing’ were written on the filter paper card. Each dried blood spot sample was given a unique barcode label in triplicate. The first copy was affixed to the filter paper card. The second copy was attached to the biomarker data collection page of the Household Questionnaire. The third copy of the barcode label was attached to the blood sample transmittal form to track the blood samples as they moved from the field to the laboratory. Blood samples were dried overnight and packaged for storage the following morning. Samples were periodically collected from the field and transported to the laboratory at the biochemistry department of Makerere University in Kampala to be logged in, checked, and stored. The vitamin A test results are shown in a separate report. 1.9 LISTING, PRETEST, MAIN TRAINING, FIELDWORK, AND DATA PROCESSING Listing A household listing operation was conducted in the 404 selected clusters and 10 regions for about three months, starting in April 2011. For this purpose, 18 listing staff were recruited from the UBOS head office to carry out the household listing and prepare the sketch map for each selected EA. A manual of instructions that described the listing and mapping procedures was prepared as a guideline, and the training involved both classroom demonstrations and field practice. Instructions were given on the use of global positioning system (GPS) units to obtain location coordinates for the selected clusters. The listing was performed by organizing the listing staff into six teams, with two listers per team. Six supervisors were also assigned from the UBOS offices to perform quality checks and handle all administrative and technical aspects of the listing operation. Rounds of supervision were also carried out 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 seven local languages to make sure that the questions were clear and could be understood by the respondents. Thirty field workers, comprising of women and men were hired to conduct the pretest. They were trained from August 30, 2010, to September 14, 2010, on how to administer the UDHS survey questionnaires. Seven days of fieldwork and one day of interviewer debriefing and examination followed. Pretest fieldwork was conducted in two clusters each (one urban and one rural) in seven districts. The majority of pretest participants attended the 2011 UDHS training and served as field editors and team leaders in the survey. A second pretest was undertaken to test the management and implementation of the computer- assisted field data editing (CAFE) program and, more specifically, to develop data editing guidelines for the 2011 UDHS. The 2011 UDHS marked the first time tablet computers were used to collect data from the field. The data file transfer process was tested using the internet file streaming system (IFSS) developed by the DHS programme, through which data from the field could be transferred to the UBOS main office via the internet. Main Training UBOS recruited and trained 146 field workers to serve as team supervisors, field editors, male and female interviewers, and reserve interviewers for the main survey. The training, which was conducted from 2 May 2011 to 1 June 2011, consisted of instruction regarding interviewing techniques and field procedures, a detailed review of questionnaires, tests, and instruction and practice in weighing and 10 • Introduction measuring children. The training also included mock interviews and role plays among participants in the classroom and in the neighbouring villages. Team supervisors and editors were further trained in data quality control procedures and fieldwork coordination. The training mainly used the English questionnaires, while the translated versions were simultaneously checked against the English questionnaires to ensure accurate translation. Fieldwork Sixteen data collection teams were formed, each comprised of a team supervisor, a field editor, three female interviewers, one male interviewer, one health technician, and a driver. UBOS staff coordinated and supervised fieldwork activities. USAID/Uganda technical staff also participated in the fieldwork monitoring. A data validation team was formed for each of the 10 regions. Each data validation team included a field supervisor and three interviewers. An independent quality control team that was looking at survey protocol issues also visited the data collection teams. Data collection took place over a six-month period, from end of June 2011 to early December 2011. Fieldwork was carried out in six separate field trips. Between trips, all teams met in Kampala to discuss problems with fieldwork logistics or data collection and to receive feedback and training reinforcement from UBOS staff. Data Processing As mentioned above, questionnaire data were entered in the field by the field editors on each team and the files were periodically sent to the UBOS office by internet. All the paper questionnaires were also returned to UBOS headquarters in Kampala for data processing, which consisted of office editing, coding of open-ended questions, a second data entry, and finally, editing computer-identified errors. The data were processed by a team of eight data entry operators, two office editors, and one data entry supervisor. Data entry and editing were accomplished using CSPro software. The processing of data was initiated in August 2011 and completed in January 2012. 1.10 RESPONSE RATES Table 1.2 shows household and individual response rates for the 2011 UDHS. A total of 10,086 households were selected for the sample, of which 9,480 were found to be occupied during data collection. Of these, 9,033 households were successfully interviewed, giving a household response rate of 95 percent. Of the 9,247 eligible women identified in the selected households, interviews were completed with 8,674 women, yielding a response rate of 94 percent for women. Of the 2,573 eligible men identified in the selected subsample of households for men, 2,295 were successfully interviewed, yielding a response rate of 89 percent for men. Response rates were higher in rural than in urban areas, with the rural-urban difference being more pronounced among men (92 and 82 percent, respectively) than among women (95 and 91 percent, respectively). Table 1.2 Results of the household and individual interviews Number of households, number of interviews, and response rates, according to residence (unweighted), Uganda 2011 Result Residence Total Urban Rural Household interviews Households selected 2,977 7,109 10,086 Households occupied 2,794 6,686 9,480 Households interviewed 2,551 6,482 9,033 Household response rate1 91.3 96.9 95.3 Interviews with women age 15-49 Number of eligible women 2,805 6,442 9,247 Number of eligible women interviewed 2,562 6,112 8,674 Eligible women response rate2 91.3 94.9 93.8 Interviews with men age 15-54 Number of eligible men 772 1,801 2,573 Number of eligible men interviewed 631 1,664 2,295 Eligible men response rate2 81.7 92.4 89.2 1 Households interviewed/households occupied 2 Respondents interviewed/eligible respondents Housing Characteristics and Household Population • 11 HOUSING CHARACTERISTICS AND HOUSEHOLD POPULATION 2 his chapter summarizes demographic and socioeconomic characteristics of the households selected in the 2011 UDHS. Information was collected from both 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). This chapter provides information on the conditions of the households in which the survey population lives, including the source of drinking water, availability of electricity, sanitation facilities, building materials, and possession of household durable goods. Also addressed are specific findings on birth registration of children under age 5, household living arrangements, orphanhood status, school attendance, educational attainment, and disability status. The background information presented in this chapter is intended to facilitate the interpretation of the demographic, socioeconomic, and health indices presented in later chapters. 2.1 HOUSEHOLD ENVIRONMENT The characteristics of a household determine the socioeconomic and health status of its members. The household is where all decisions about health, education, and general welfare are made and acted upon. The 2011 UDHS asked respondents about their household environment, including the source of drinking water, type of sanitation facility, access to electricity, type of material used for roofing, flooring, and walls, and number of rooms used for sleeping in the dwelling. 2.1.1 Drinking Water Increasing access to improved drinking water is one of the targets of the National Development Plan. Access to improved drinking water is also one of the Millennium Development Goals that Uganda has adopted. Unimproved water sources increase the prevalence of waterborne disease and the burden of service delivery through increased demand for health care. Table 2.1 presents indicators useful in monitoring household access to improved drinking water. Improved water sources include piped water into the dwelling, yard, or plot; a public tap/stand pipe or borehole; a protected well or protected spring water, and rainwater. Lack of easy access to an improved water source may limit the quantity of suitable drinking water that is available to a household as well as increase the risk of illness. Access to improved sources of drinking water has increased from 67 percent in T Key Findings  More than half of the population of Uganda is age 15 or younger.  Seventy percent of households use an improved source of drinking water.  Fifty-eight percent of the population take more than 30 minutes roundtrip to fetch water.  Only 16 percent of households have an improved sanitation facility.  About one in every seven households (15 percent) has electricity.  Three out of every ten children under age 5 have their birth registered.  Twelve percent of children under age 18 are orphans.  About three in ten households are headed by a woman. 12 • Housing Characteristics and Household Population 2006 to 70 percent of households in 2011. Nine in ten households in urban areas use improved water sources compared with only two in three households in rural areas. Access to improved water sources in rural areas increased from 63 percent to 67 percent during the same period. The most common source of improved drinking water in urban areas is piped water, used by 67 percent of households. In contrast, only 10 percent of rural households have access to piped water. A large proportion of rural households (44 percent) get their drinking water from a borehole. Ten percent of rural households get their drinking water from a protected spring or well. If water needs to be fetched from a source that is not immediately accessible to the household, it may get contaminated during transportation or storage even if the water is obtained from an improved source. Another factor that influences access to a water source is the burden of fetching water, which often falls disproportionately on female members of the household. Table 2.1 shows that, on average, 6 percent of the households have water on their premises. Urban households are more likely than rural households to have a water source in their house or yard (28 percent and 2 percent, respectively). Households that did not have water on their premises were asked how long it took to fetch water round trip. Thirty-three percent of all households (43 percent in urban areas and 31 percent in rural areas) take less than 30 minutes to fetch drinking water. More than half of all households (54 percent) travel 30 minutes or more to fetch their drinking water: 17 percent in urban areas and 62 percent in rural areas travel this length of time. The 2011 UDHS asked all households whether they treat their water to ensure that it is safe for drinking. Forty-four percent of households boil their drinking water. Urban households (71 percent) are more likely than rural households (38 percent) to boil the water. Six in ten households (59 percent) in rural areas do not treat their drinking water. Table 2.1 Household drinking water Percent distribution of households and de jure population by source of drinking water, time to obtain drinking water, and treatment of drinking water, according to residence, Uganda 2011 Characteristic Households Population Urban Rural Total Urban Rural Total Source of drinking water Improved source 90.6 65.6 70.3 89.6 66.6 70.0 Piped into dwelling/yard/plot 27.9 1.5 6.4 28.4 1.3 5.3 Public tap/standpipe 38.9 8.2 13.9 34.9 7.8 11.7 Borehole 11.8 43.9 37.9 16.1 45.9 41.6 Protected well/spring 6.9 10.2 9.6 7.6 10.2 9.8 Rain water 0.5 1.4 1.3 0.4 1.3 1.2 Bottled water 4.6 0.4 1.2 2.1 0.1 0.4 Non-improved source 8.9 33.6 29.0 10.1 32.8 29.5 Unprotected well/spring 5.6 18.2 15.8 7.0 17.6 16.1 Tanker truck/vendor 2.2 0.9 1.1 1.6 0.6 0.8 Surface water 1.0 14.6 12.0 1.4 14.5 12.6 Other source 0.6 0.8 0.7 0.3 0.6 0.5 Total 100.0 100.0 100.0 100.0 100.0 100.0 Percentage using any improved source of drinking water 90.6 65.6 70.3 89.6 66.6 70.0 Time to obtain drinking water (round trip) Water on premises 40.1 6.2 12.5 37.4 5.4 10.0 Less than 30 minutes 42.8 31.1 33.3 41.5 29.7 31.4 30 minutes or longer 16.6 62.0 53.5 20.7 64.3 57.9 Don't know/missing 0.5 0.7 0.7 0.4 0.6 0.6 Total 100.0 100.0 100.0 100.0 100.0 100.0 Water treatment prior to drinking1 Boiled 70.6 37.7 43.9 68.8 34.8 39.8 Added water guard 3.3 2.7 2.8 3.6 2.6 2.8 Bleach/chlorine added 0.1 0.2 0.2 0.1 0.2 0.2 Strained through cloth 0.8 1.4 1.3 1.0 1.6 1.5 Ceramic, sand, or other filter 0.5 0.5 0.5 0.5 0.5 0.5 Solar disinfection 0.0 0.2 0.2 0.1 0.2 0.1 Let it stand and settle 0.3 0.6 0.5 0.4 0.5 0.5 Other 0.5 0.4 0.4 0.5 0.4 0.4 No treatment 26.7 58.9 52.8 27.8 61.6 56.6 Percentage using an appropriate treatment method2 72.8 40.8 46.8 71.6 38.0 43.0 Number 1,691 7,342 9,033 6,468 37,782 44,250 1 Respondents may report multiple treatment methods, so the sum of treatment may exceed 100 percent. 2 Appropriate water treatment methods include boiling, adding waterguard, bleaching, straining, filtering, and solar disinfecting. Housing Characteristics and Household Population • 13 2.1.2 Household Sanitation Facilities Ensuring adequate sanitation facilities is good public health practice. At the household level, the availability of hygienic sanitation facilities reduces the risk of exposure to illnesses and further lightens the burden on the public health delivery system. Appropriate sanitation facilities include an improved toilet and method of waste disposal that separates waste from human contact. A household is classified as having an improved toilet if the toilet is used only by household members (that is, the toilet is not shared) and if the toilet separates the waste from human contact (WHO and UNICEF, 2010). Flush/pour toilets that flush to a piped sewer system, and ventilated improved pit (VIP) latrines, pit latrines with a slab, and composting toilets (which separate solid waste from water) are also classified as improved toilets. Table 2.2 shows that 16 percent of households in Uganda use improved toilet facilities that are not shared with other households (21 percent in urban areas and 15 percent in rural areas). Overall, 19 percent of households have improved facilities but shared toilet facilities− 52 percent in urban areas and 11 percent in rural areas. Two in three households use non-improved toilet facilities (73 percent in rural areas and 28 percent in urban areas). The most common type of toilet in urban areas is a pit latrine with a slab (34 percent), while in rural areas the most common type of toilet is a pit latrine without a slab (62 percent). Ten percent of the households, mainly in rural areas, have no toilet facilities. This proportion has declined over time, from 17 percent in 2000-01 to 12 percent in 2006 and to 10 percent in 2011 (UBOS and ORC Macro, 2001; UBOS and Macro International, Inc., 2007). Table 2.2 Household sanitation facilities Percent distribution of households and de jure population by type of toilet/latrine facilities, according to residence, Uganda 2011 Type of toilet/latrine facility Households Population Urban Rural Total Urban Rural Total Improved, not shared facility 20.9 15.3 16.4 26.3 17.4 18.7 Flush/pour flush to piped sewer system 8.6 0.2 1.8 9.4 0.1 1.5 Ventilated improved pit (VIP) latrine 3.7 2.0 2.3 4.8 2.1 2.5 Pit latrine with slab 8.4 12.8 12.0 12.1 14.8 14.4 Composting toilet/Ecosan 0.1 0.3 0.3 0.1 0.4 0.3 Shared facility1 51.6 11.3 18.8 43.6 8.0 13.2 Flush/pour flush to piped sewer system 2.7 0.1 0.6 2.0 0.1 0.3 Ventilated improved pit (VIP) latrine 14.9 2.2 4.6 12.3 1.5 3.1 Pit latrine with slab 33.8 8.9 13.5 29.1 6.4 9.7 Composting toilet/Ecosan 0.2 0.1 0.1 0.2 0.1 0.1 Non-improved facility 27.5 73.4 64.8 30.1 74.7 68.1 Pit latrine without slab/open pit 25.2 61.7 54.9 28.0 63.6 58.4 No facility/bush/field 1.8 11.5 9.7 1.8 10.9 9.6 Other 0.5 0.2 0.3 0.2 0.1 0.2 Total 100.0 100.0 100.0 100.0 100.0 100.0 Number 1,691 7,342 9,033 6,468 37,782 44,250 1 Facilities that would be considered improved if they were not shared by two or more households 2.1.3 Housing Characteristics Housing characteristics reflect the household’s socioeconomic status in society. The availability or lack of adequate housing facilities determines the magnitude of exposure to risks associated with air pollution and ill health. Table 2.3 shows that only 15 percent of the households in Uganda have electricity, and there is a very large disparity between urban and rural households (55 percent versus 5 percent). The proportion of households with access to electricity has increased since 2006. In urban areas, the proportion of households with electricity rose from 42 percent in 2006 to 55 percent in 2011. In rural areas, the percentage increased from less than 3 percent in 2006 to 5 percent in 2011. The quality of housing for most Ugandans is still inadequate. More than two thirds (69 percent) of households have either earth, sand, or dung floors. Rural houses (81 percent) are more likely than urban 14 • Housing Characteristics and Household Population houses (19 percent) to have this type of floor. Urban houses are more likely to have floors made of cement than rural houses (76 percent versus 18 percent, respectively). 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, 46 percent of the households use one room for sleeping, 29 percent use two rooms, and 25 percent use three or more rooms for sleeping. Urban households are more likely to use one room for sleeping than rural households, implying that overcrowding is more rampant in urban than rural households. More than half of the households in Uganda (58 percent) cook in a building separate from the house, while about one-third (28 percent) cook outdoors. In urban areas, one in five households (22 percent) cooks indoors. Cooking and heating with solid fuels can lead to high levels of indoor smoke, which consists of a complex mix of pollutants that can increase the risk of contracting respiratory infections. Uganda is predominantly agriculture based, and the use of solid fuels is widespread. Solid fuels include charcoal, wood, straw, shrubs, grass, agricultural crops, and animal dung. The use of solid fuel in Uganda is almost universal, with 96 percent of households using solid fuel for cooking. The practice is nearly universal in rural households at 98 percent and very common in urban households (85 percent). Wood is the main type of fuel used for cooking in rural areas (85 percent), while charcoal is the most used cooking fuel in urban areas (68 percent). The 2011 UDHS collected information on the frequency of smoking tobacco in the home. Smoking increases the risk of non- communicable diseases, not only for smokers but also for passive smokers. Table 2.3 shows that 16 percent of households are exposed to daily smoking, and 3 percent are exposed weekly. Rural households (17 percent) are almost twice as likely to be exposed to daily smoking as urban households (10 percent). 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, Uganda 2011 Housing characteristic Residence Total Urban Rural Electricity Yes 55.4 5.3 14.6 No 44.6 94.7 85.4 Total 100.0 100.0 100.0 Flooring material Earth/sand 13.0 47.5 41.0 Earth and dung 5.5 33.1 27.9 Parquet or polished wood 0.1 0.1 0.1 Mosaic or tiles 3.2 0.1 0.7 Bricks 0.4 0.3 0.3 Cement 76.1 17.9 28.8 Stones 1.2 0.6 0.7 Other 0.4 0.4 0.4 Total 100.0 100.0 100.0 Rooms used for sleeping One 62.3 42.0 45.8 Two 21.9 30.2 28.7 Three or more 15.1 27.2 24.9 Missing 0.7 0.6 0.6 Total 100.0 100.0 100.0 Place for cooking In the house 22.3 8.8 11.3 In a separate building 22.3 66.6 58.3 Outdoors 48.8 23.0 27.8 No food cooked in household 6.4 1.5 2.4 Other 0.2 0.1 0.1 Total 100.0 100.0 100.0 Percentage using a separate room as a kitchen within the house 9.5 2.5 3.8 Cooking fuel Electricity 1.3 0.1 0.3 LPG/natural gas/biogas 3.3 0.0 0.6 Kerosene 4.3 0.3 1.1 Charcoal 67.8 12.4 22.8 Wood 16.9 85.3 72.5 Straw/shrubs/grass 0.0 0.2 0.2 No food cooked in household 6.4 1.5 2.4 Total 100.0 100.0 100.0 Percentage using solid fuel for cooking1 84.7 98.0 95.5 Frequency of smoking in the home Daily 9.7 17.1 15.7 Weekly 2.4 3.6 3.4 Monthly 0.9 1.4 1.3 Less than monthly 2.0 3.5 3.2 Never 85.0 74.4 76.4 Total 100.0 100.0 100.0 Number 1,691 7,342 9,033 LPG = Liquid petroleum gas 1 Includes coal/lignite, charcoal, wood/straw/shrubs/grass, agricultural crops, and animal dung Housing Characteristics and Household Population • 15 2.1.4 Household Possessions The availability of durable consumer goods is an indicator of a household’s welfare status. Moreover, particular goods have specific benefits. For instance, a radio, a mobile phone, or a television can be a source of information and new ideas for household members; 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 that two-thirds of Ugandan households have radios, 59 percent have mobile telephones, 12 percent have televisions, and 5 percent have refrigerators. There is a significant increase in the level of penetration of the mobile phone industry into rural areas. Between 2006 and 2011, the percentage of rural households owning mobile phones increased more than fivefold, from 10 percent to 53 percent. In urban areas, the percentage of households with mobile phones increased from 53 percent to 87 percent, representing a growth of 64 percent over the same period. Televisions and refrigerators continue to be available mainly in urban households. More than one-third of the households possess a bicycle as a means of transport, with rural households being more likely to possess bicycles (41 percent) than urban households (20 percent). Ownership of motorcycles and cars increased between 2006 and 2011. Eight percent of the households own a motorcycle in 2011 compared with 3 percent in 2006. The proportion of households owning cars/trucks has increased slightly, from 2 percent to 3 percent, during the same period. In 2011, 72 percent of households owned farming land and 62 percent owned farm animals. Urban households are less likely than rural households to own land and farm animals. For example, 36 percent of urban households own farm animals compared with 68 percent of rural households. 2.1.5 Hand Washing Observance and promotion of basic hygiene is fundamental good public health. Hand washing with a detergent ensures that the transmission of germs is restricted, especially among children who are more prone than adults to diarrhoea and other childhood illnesses. Respondents were asked if they had a place for washing hands after using the toilet. Table 2.6 shows that three in ten households (29 percent) had such a place where washing of hands was observed. More than one in four households (27 percent) have both water and soap. Another 27 percent have only water available. Hand washing with water and soap is practiced most in households in Kampala, Central 1, and Western regions. On the other hand, Karamoja and West Nile regions are on the other extreme end with more than 80 percent of households not having any of the hand washing facilities (water/soap/detergents). Table 2.4 Household possessions Percentage of households possessing various household effects, means of transportation, agricultural land and livestock/farm animals by residence, Uganda 2011 Possession Residence Total Urban Rural Household effects Radio 71.8 64.6 66.0 Television 45.0 4.9 12.4 Mobile telephone 86.8 53.1 59.4 Non-mobile telephone 4.8 0.7 1.5 Refrigerator 19.7 1.7 5.1 Means of transport Bicycle 19.5 41.1 37.1 Animal drawn cart 0.3 0.8 0.7 Motorcycle/scooter 11.4 7.1 7.9 Car/truck 10.1 1.6 3.2 Boat with a motor 0.1 0.4 0.4 Boat without a motor 0.2 1.0 0.9 Ownership of agricultural land 44.2 78.8 72.3 Ownership of farm animals1 35.7 67.7 61.7 Local cattle 14.5 23.2 21.6 Exotic/cross cattle 3.9 3.7 3.7 Horses/donkeys/mules 0.1 0.4 0.4 Goats 17.6 39.8 35.7 Sheep 2.2 8.6 7.4 Pigs 7.1 20.1 17.7 Chickens 23.7 51.2 46.0 Number 1,691 7,342 9,033 1 Cattle, cows, bulls, horses, donkeys, mules, goats, sheep, pigs, or chicken 16 • Housing Characteristics and Household Population Table 2.5 Hand washing Percentage of households in which the place most often used for washing hands was observed, and among households in which the place for hand washing was observed, percent distribution by availability of water, soap, and other cleansing agents, Uganda 2011 Background characteristic Percentage of households where place for washing hands was observed Number of households Among households where place for hand washing was observed Number of households with place for hand washing observed Soap and water1 Water and cleansing agent2 other than soap only Water only Soap but no water3 Cleansing agent other than soap only2 No water, no soap, no other cleansing agent Total Residence Urban 34.9 1,691 37.7 0.0 30.0 2.1 0.0 30.2 100.0 589 Rural 27.6 7,342 23.9 0.5 25.9 3.0 0.7 45.8 100.0 2,026 Region Kampala 39.0 797 41.7 0.0 30.2 1.2 0.0 26.9 100.0 311 Central 1 50.1 1,140 45.2 0.0 17.6 3.9 1.2 32.0 100.0 571 Central 2 45.1 1,038 26.5 0.7 18.1 3.9 1.5 49.4 100.0 468 East Central 30.6 904 11.9 0.0 42.9 1.8 0.0 43.3 100.0 277 Eastern 25.2 1,226 9.3 0.9 29.9 3.2 0.0 56.8 100.0 309 Karamoja 12.5 306 1.6 0.0 10.1 0.2 0.0 88.2 100.0 38 North 7.2 757 10.3 7.7 19.0 2.3 0.0 60.7 100.0 55 West Nile 16.4 508 4.5 1.0 9.9 0.7 0.0 84.0 100.0 84 Western 22.1 1,228 31.8 0.0 51.1 3.4 0.0 13.7 100.0 272 Southwest 20.5 1,128 15.6 0.0 22.2 1.8 0.0 60.4 100.0 232 Wealth quintile Lowest 17.0 1,719 11.9 0.8 17.2 0.4 0.8 68.9 100.0 292 Second 23.7 1,767 12.4 0.8 26.3 3.9 1.0 55.6 100.0 418 Middle 28.5 1,672 15.0 0.3 31.5 2.5 0.4 50.3 100.0 476 Fourth 32.4 1,723 26.8 0.4 28.0 2.7 1.0 40.8 100.0 559 Highest 40.4 2,152 45.7 0.2 27.1 3.4 0.0 23.5 100.0 870 Total 29.0 9,033 27.0 0.4 26.9 2.8 0.5 42.3 100.0 2,615 1 Soap includes soap or detergent in bar, liquid, powder, or paste form. This column includes households with soap and water only as well as those that had soap and water and another cleansing agent. 2 Cleansing agents other than soap include locally available materials such as ash, mud, or sand. 3 Includes households with soap only as well as those with soap and another cleansing agent 2.2 WEALTH INDEX Household income or expenditure is usually regarded as the gold standard for measuring welfare and overall standard of living. However, studies have shown that the wealth index is a good proxy for measuring wealth of households. It serves as an indicator of level of wealth that is consistent with expenditure and income measures (Rutstein, 1999). The wealth index was constructed using household asset data via 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 2.6 shows that in urban areas three-quarters of the population is in the highest wealth quintile, in sharp contrast to the rural areas, where only one in nine persons are in the highest wealth quintile. The wealth quintile distribution varies greatly across regions. Over 90 percent of the population in Kampala is in the highest wealth quintile, while in other regions the proportion is 35 percent or lower. In Housing Characteristics and Household Population • 17 Karamoja, eight in ten households are in the lowest quintile. In North, West Nile, and Eastern regions, 33 percent or more of the households are in the lowest quintile. This finding is consistent with the results of Uganda National Household survey, which showed that poverty is more concentrated in the northern region (UBOS, 2010). Table 2.6 further shows the Gini Coefficient of wealth in Uganda, with 0 representing 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 Uganda is 0.4. The coefficient is higher in rural areas (0.3) than in urban areas (0.2), indicating a more unequal distribution of wealth in the rural than in the urban population. The lowest Gini Coefficient is in Kampala (0.1), where over 90 percent of the population is in the highest wealth quintile. Table 2.6 Wealth quintiles Percent distribution of the de jure population by wealth quintiles, and the Gini Coefficient, according to residence and region, Uganda 2011 Residence/region Wealth quintile Total Number of persons Gini Coefficient Lowest Second Middle Fourth Highest Residence Urban 1.9 3.1 4.5 15.5 74.9 100.0 6,468 0.19 Rural 23.1 22.9 22.7 20.8 10.6 100.0 37,782 0.32 Region Kampala 0.0 0.1 1.2 7.6 91.0 100.0 2,770 0.12 Central 1 6.0 9.8 18.6 30.9 34.8 100.0 4,823 0.30 Central 2 8.4 12.8 19.7 29.4 29.7 100.0 4,656 0.34 East Central 12.1 21.0 21.2 29.8 15.9 100.0 4,697 0.31 Eastern 32.8 25.2 20.7 15.0 6.3 100.0 6,790 0.35 Karamoja 79.2 6.2 6.7 5.2 2.7 100.0 1,628 0.56 North 40.7 34.6 12.4 7.0 5.3 100.0 4,117 0.34 West Nile 41.2 31.2 14.3 8.0 5.2 100.0 2,810 0.31 Western 14.1 21.4 28.1 21.8 14.7 100.0 6,402 0.35 Southwest 6.3 23.3 32.5 24.5 13.4 100.0 5,555 0.28 Total 20.0 20.0 20.0 20.0 20.0 100.0 44,250 0.39 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 2.7 shows the distribution of the household population in the 2011 UDHS by five-year age groups, urban-rural residence, and sex. The total population in the survey is 43,508, with females slightly outnumbering males (22,285 compared with 21,223). There is no variation in sex composition across rural- urban residence. The overall sex ratio is 95 (or 95 males per 100 females). The sex ratio is higher in rural than in urban areas (96 compared with 92 males per 100 females). The broad base of the population pyramid in Figure 2.1 shows the large number of children under age 15, which characterizes a population with high fertility. Children under age 15 account for more than half (52 percent) of the total population. 18 • Housing Characteristics and Household Population Table 2.7 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, Uganda 2011 Age Urban Rural Total Male Female Total Male Female Total Male Female Total <5 17.1 16.1 16.6 19.9 19.0 19.4 19.5 18.5 19.0 5-9 14.6 12.4 13.4 18.7 17.7 18.2 18.1 16.9 17.5 10-14 10.7 11.2 11.0 16.8 15.1 15.9 15.9 14.6 15.2 15-19 9.8 12.0 11.0 10.5 9.4 10.0 10.4 9.8 10.1 20-24 11.2 13.1 12.2 5.3 6.7 6.1 6.2 7.7 7.0 25-29 11.1 11.5 11.3 5.7 6.8 6.2 6.5 7.5 7.0 30-34 6.8 7.1 7.0 4.7 4.8 4.8 5.0 5.1 5.1 35-39 7.1 5.3 6.2 4.3 4.6 4.5 4.7 4.7 4.7 40-44 3.4 3.1 3.3 3.4 3.4 3.4 3.4 3.4 3.4 45-49 2.7 2.1 2.4 2.7 2.9 2.8 2.7 2.8 2.7 50-54 2.1 2.2 2.2 2.2 2.5 2.4 2.2 2.5 2.3 55-59 1.3 1.3 1.3 1.5 1.8 1.6 1.5 1.7 1.6 60-64 0.9 0.9 0.9 1.2 1.5 1.4 1.2 1.4 1.3 65-69 0.4 0.5 0.5 1.0 1.2 1.1 0.9 1.1 1.0 70-74 0.4 0.4 0.4 0.8 0.9 0.9 0.7 0.8 0.8 75-79 0.2 0.2 0.2 0.6 0.6 0.6 0.5 0.6 0.5 80 + 0.3 0.5 0.4 0.7 1.0 0.8 0.6 0.9 0.8 Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 Number 3,058 3,325 6,383 18,166 18,960 37,125 21,223 22,285 43,508 Figure 2.1 Population pyramid UDHS 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 Female Percentage Housing Characteristics and Household Population • 19 2.4 HOUSEHOLD COMPOSITION Table 2.8 shows that three in ten households are headed by women, the same proportion as in the 2006 UDHS. This is consistent between rural and urban residence. The average household size is 4.9 persons, which is slightly less than the average of 5.0 persons per household reported in 2006. The average household size is smaller in urban areas than in rural areas (3.8 compared with 5.1 persons). The average household size in urban areas declined from 4.1 in 2006 to 3.8 in 2011, while it remained the same in rural areas over the same time period. Single-person households are more common in urban areas (19 percent) than in rural areas (10 percent). In fact, more than half of the urban households have three or fewer household members. On the other hand, 56 percent of rural households have five or more members. All persons below age 18 are defined as children. The 2011 UDHS collected information on the presence of foster children and orphans in households. 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. Close to one third of households have foster children; rural households are more likely to have foster children than urban households (30 percent and 24 percent, respectively). Eighteen percent of households have orphans. There are more households with a single orphan (14 percent) than double orphans (4 percent). There is little difference between rural and urban areas in the distribution of orphans. 2.5 BIRTH REGISTRATION Registration of births ought to be universally practised. It is a human right for a child to know who its parents are and to acquire a nationality through registration. The registration system in Uganda aims to ensure that all children are registered. A collaborative effort involving UNICEF, the Ministry of Justice and Constitutional Affairs, Plan International, and UBOS, among others, is spearheading the exercise in over 54 districts in Uganda. Apart from being the first legal acknowledgment of a child’s existence, the registration of births is fundamental to the realisation of a number of rights and practical needs, including but not limited to provision of access to health care and immunisation, education, and other social services. Table 2.9 shows that three in ten children are registered in Uganda. This represents an increase of 9 percentage points from the 2006 UDHS (21 percent). Children age 2-4 are more likely to be registered than children below age 2 (32 percent and 26 percent, respectively). Similarly, children in urban areas are more likely to be registered than children in rural areas (38 percent compared with 29 percent). Registration coverage is highest in Kampala (45 percent), Central 1 (42 percent), and Western (36 percent) regions. On the other hand, Karamoja and Southwest regions have the lowest coverage. The highest Table 2.8 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 age 18, according to residence, Uganda 2011 Characteristic Residence Total Urban Rural Household headship Male 69.0 70.8 70.5 Female 31.0 29.2 29.5 Total 100.0 100.0 100.0 Number of usual members 0 0.1 0.1 0.1 1 19.0 9.7 11.5 2 16.1 8.4 9.8 3 17.7 12.3 13.3 4 13.6 13.7 13.7 5 11.7 13.5 13.2 6 7.9 13.1 12.1 7 5.1 9.9 9.0 8 3.5 7.6 6.8 9+ 5.2 11.7 10.5 Total 100.0 100.0 100.0 Mean size of households 3.8 5.1 4.9 Percentage of households with orphans and foster children under 18 years of age Foster children1 23.8 29.7 28.6 Double orphans 2.9 3.8 3.6 Single orphans2 10.3 14.8 14.0 Foster and/or orphan children 26.2 34.4 32.9 Number of households 1,691 7,342 9,033 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. 20 • Housing Characteristics and Household Population proportion of registered births is found in the highest wealth quintile (44 percent) whereas the lowest percentage is found in the second lowest quintile (26 percent). Table 2.9 Birth registration of children under age 5 Percentage of de jure children under age 5 whose births are registered with the civil authorities, according to background characteristics, Uganda 2011 Background characteristic Children whose births are registered Number of children Percentage who had a birth certificate Percentage who did not have birth certificate Percentage registered Age <2 15.3 11.0 26.3 3,301 2-4 19.2 13.0 32.2 5,060 Sex Male 17.3 12.6 29.9 4,182 Female 18.0 11.9 29.9 4,179 Residence Urban 25.5 12.5 38.0 1,068 Rural 16.5 12.2 28.7 7,293 Region Kampala 27.5 17.0 44.5 440 Central 1 22.6 19.8 42.3 866 Central 2 25.5 7.7 33.3 873 East Central 21.9 4.6 26.4 924 Eastern 16.2 16.6 32.8 1,390 Karamoja 7.9 3.2 11.1 314 North 18.7 13.1 31.8 749 West Nile 9.3 8.6 17.8 530 Western 16.1 19.3 35.5 1,230 Southwest 9.3 4.1 13.5 1,047 Wealth quintile Lowest 14.1 13.1 27.2 1,864 Second 14.9 10.8 25.7 1,790 Middle 15.8 11.1 26.9 1,726 Fourth 19.6 8.2 27.8 1,513 Highest 25.7 18.3 44.0 1,467 Total 17.7 12.2 29.9 8,361 2.6 CHILDREN’S LIVING ARRANGEMENTS AND PARENTAL SURVIVAL Table 2.10 presents data on children’s living arrangements and orphanhood in Uganda. Fifty- five percent of children under age 18 live with both parents; 20 percent live with their mothers but not their father (whether alive or dead); 5 percent live with their fathers but not with mother (whether alive or dead); and 19 percent live with neither of their natural parents. The proportion of children living with both parents decreases with age. Although 72 percent of children under age 2 live with both parents, by age 10-14 only 46 percent of children live with their father and mother. The proportion of children living with both parents varies little by the child’s sex. Rural children are more likely to live with both parents than urban children (56 percent versus 49 percent). Regions with the highest proportion of children living with both parents are Eastern (63 percent), North (62 percent) and Southwest (61 percent), while the region with the lowest is Karamoja (49 percent). In general, the percentage of children living with both parents tends to decrease with an increase in household wealth. Housing Characteristics and Household Population • 21 Table 2.10 Children's living arrangements and orphanhood Percent distribution of de jure children under age 18 by living arrangements and survival status of parents, the percentage of children not living with a biological parent, and the percentage of children with one or both parents dead, according to background characteristics, Uganda 2011 Background characteristic Living with both parents Living with mother but not with father Living with father but not with mother Not living with either parent Total Percent- age not living with a biolo- gical parent Percent- age with one or both parents dead1 Number of children Father alive Father dead Mother alive Mother dead Both alive Only father alive Only mother alive Both dead Missing informa- tion on father/ mother Age 0-4 68.0 18.4 2.2 1.7 0.1 7.8 0.4 0.6 0.3 0.4 100.0 9.1 3.7 8,361 <2 72.2 21.7 1.9 0.7 0.0 2.8 0.1 0.1 0.2 0.3 100.0 3.2 2.4 3,301 2-4 65.2 16.3 2.4 2.4 0.2 11.0 0.7 1.0 0.4 0.4 100.0 13.0 4.6 5,060 5-9 55.7 15.2 4.1 4.8 0.7 13.3 1.6 2.6 1.4 0.7 100.0 18.9 10.4 7,688 10-14 45.5 13.9 6.4 6.6 1.6 15.6 2.3 4.2 3.2 0.7 100.0 25.3 17.9 6,659 15-17 39.7 13.2 8.6 6.0 1.9 17.9 2.5 4.8 4.4 0.9 100.0 29.7 22.4 2,875 Sex Male 56.2 15.4 4.4 5.1 0.9 11.6 1.5 2.4 1.9 0.6 100.0 17.4 11.2 12,947 Female 54.2 16.1 4.9 3.6 0.8 13.7 1.6 2.9 1.7 0.6 100.0 19.8 11.9 12,636 Residence Urban 48.9 18.9 3.3 5.1 0.6 15.1 1.8 3.7 1.9 0.5 100.0 22.5 11.5 3,058 Rural 56.1 15.3 4.8 4.3 0.9 12.3 1.5 2.5 1.8 0.6 100.0 18.1 11.5 22,525 Region Kampala 50.5 19.0 3.5 5.2 0.9 13.7 1.7 3.5 1.3 0.7 100.0 20.2 11.0 1,106 Central 1 49.5 15.9 3.7 6.8 1.5 16.5 1.6 2.6 1.3 0.6 100.0 21.9 10.8 2,722 Central 2 52.6 14.2 3.3 5.6 0.4 17.0 1.6 3.0 1.9 0.4 100.0 23.5 10.3 2,696 East Central 52.6 17.9 3.2 4.7 0.7 15.3 1.5 2.1 1.5 0.6 100.0 20.4 9.1 2,890 Eastern 62.5 12.4 3.8 4.4 1.1 10.5 1.1 2.4 1.2 0.6 100.0 15.2 9.8 4,086 Karamoja 48.9 23.6 6.8 1.2 1.6 7.5 2.6 2.7 4.9 0.1 100.0 17.7 18.7 999 North 61.5 9.0 6.9 3.1 1.1 8.8 1.2 3.8 4.0 0.6 100.0 17.8 17.1 2,476 West Nile 55.3 13.6 4.0 6.2 0.6 14.0 0.9 4.0 0.8 0.4 100.0 19.8 10.5 1,607 Western 49.5 21.4 6.0 4.8 0.5 11.0 2.4 2.1 1.6 0.8 100.0 17.0 12.5 3,822 Southwest 61.3 14.8 5.3 1.3 0.6 11.3 1.2 1.6 1.8 0.8 100.0 15.8 10.6 3,179 Wealth quintile Lowest 56.3 16.0 7.8 3.1 1.0 8.9 1.2 2.4 2.6 0.9 100.0 15.0 15.0 5,449 Second 58.4 14.3 4.9 3.9 0.5 11.3 2.1 2.3 1.7 0.5 100.0 17.4 11.6 5,291 Middle 56.5 15.3 4.5 4.4 0.8 12.0 1.5 2.7 1.6 0.7 100.0 17.8 11.1 5,287 Fourth 53.4 15.6 3.0 5.5 1.4 15.4 1.3 2.6 1.5 0.4 100.0 20.8 9.8 5,197 Highest 50.8 17.6 2.3 5.3 0.7 16.3 1.4 3.3 1.8 0.5 100.0 22.8 9.6 4,359 Total <15 57.2 16.0 4.1 4.2 0.7 11.9 1.4 2.3 1.5 0.6 100.0 17.2 10.1 22,707 Total <18 55.2 15.7 4.6 4.4 0.9 12.6 1.5 2.6 1.8 0.6 100.0 18.6 11.5 25,583 Note: Table is based on de jure members, i.e., usual residents. 1 Includes children with father dead, mother dead, both dead and one parent dead but missing information on survival status of the other parent. 2.7 EDUCATION LEVEL OF THE HOUSEHOLD POPULATION Education is a key determinant of an individual’s stock of human capital. Studies have consistently shown that educational attainment strongly affects reproductive behaviour, fertility, infant and child morbidity and mortality, and attitudes and awareness related to family health, use of family planning, and sanitation. The 2011 UDHS collected information on educational attainment of all persons age 3 and older in the selected households. 2.7.1 School Attendance by Survivorship of Parents The survival status of parents has an impact on their children’s school attendance. Table 2.11 shows the percentage of children age 10-14 attending school, by parental survival status (deceased or alive), and the ratio of the percentage attending with both parents deceased to the percentage attending with both parents alive, according to background characteristics. Data show that double orphaned children are less likely to attend school (84 percent) than children who have both parents alive and live with at least one parent (96 percent), resulting in a school attendance ratio of 0.87 between the percentage of children with both parents deceased and the percentage of children with both parents alive and living with a parent. 22 • Housing Characteristics and Household Population Male children with both parents deceased are much less likely than female children in the same situation to attend school (80 percent versus 88 percent). Table 2.11 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, Uganda 2011 Background characteristic Percentage attending school by survivorship of parents Ratio1 Both parents deceased Number Both parents alive and living with at least one parent Number Sex Male 80.0 117 96.0 2,290 0.83 Female 87.7 97 95.1 2,101 0.92 Residence Urban (83.8) 22 97.9 419 (0.86) Rural 83.4 192 95.4 3,972 0.87 Region Kampala * 5 97.6 123 0.68 Central 1 * 18 98.2 456 0.86 Central 2 (91.0) 28 97.5 447 0.93 East Central * 18 97.5 511 0.96 Eastern * 21 97.3 742 0.86 Karamoja 49.4 25 60.3 166 0.82 North (93.4) 33 96.9 417 0.96 West Nile * 9 92.1 279 0.78 Western (100.0) 29 96.7 693 1.03 Southwest * 29 97.3 558 0.79 Wealth quintile Lowest 73.1 61 87.4 889 0.84 Second (81.6) 52 95.6 915 0.85 Middle (91.0) 31 97.6 930 0.93 Fourth (90.9) 32 98.9 1,016 0.92 Highest (90.2) 38 98.8 643 0.91 Total 83.5 214 95.6 4,392 0.87 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 attending with both parents deceased to the percentage attending with both parents alive and living with at least one parent 2.7.2 Educational Attainment Tables 2.12.1 and 2.12.2 show the percent distribution of the de facto female and male household population age 6 and older by the highest level of education attended or completed, according to background characteristics. The majority of Ugandans have either no formal education or only some primary education. One in five females (20 percent) and 13 percent of males age 6 and older have never had any formal education. Fifty-eight percent of females and 59 percent of males have attained some primary education only, and 7 percent each of females and males have completed primary education, but not continued. A slightly higher percentage of both females (12 percent) and males (14 percent) have attended but did not complete secondary education. Only 4 percent of females and 6 percent of males have completed secondary or higher education. The trends in educational attainment by successive age groups indicate that, despite free universal primary education, 33 percent of girls and 34 percent of boys age 6-9 have never attended school. Studies have attributed the poor school attendance to long distances to and from schools, costs of education beyond tuition, and the fact that children below age 8 are still considered too young to start school by some sections of society in Uganda (UBOS, 2010). The proportion of females and males with no education increases with increasing age. For example, 12 percent of women age 25-29 have never attended school compared with 59 percent of women age 60-64. Housing Characteristics and Household Population • 23 As expected, educational attainment is much higher among the urban population than among the rural population. For example, in urban areas only 8 percent of females and 7 percent of males have no education, compared with 22 percent of females and 14 percent of males in rural areas. At the regional level, Karamoja has the highest proportion of females and males with no education in Uganda. The highest percentage of females and males who have completed secondary or higher education live in Kampala, Central 1 and Central 2 regions and, among men, North region. The most substantial variation in educational attainment occurs across the wealth quintiles. Only 7 to 8 percent of females and males in the wealthiest households have no education, compared with 34 percent of females and 20 percent of males in the poorest households. Table 2.12.1 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, Uganda 2011 Background characteristic No education Some primary Completed primary1 Some secondary Completed secondary2 More than secondary Don't know/ missing Total Number Median years completed Age 6-9 32.6 67.4 0.0 0.0 0.0 0.0 0.0 100.0 3,069 0.0 10-14 4.3 92.8 0.9 2.0 0.0 0.0 0.0 100.0 3,243 2.5 15-19 3.3 56.8 9.0 29.0 0.5 1.4 0.1 100.0 2,191 5.4 20-24 5.6 40.8 13.5 28.7 3.7 7.6 0.1 100.0 1,711 6.2 25-29 11.6 43.9 12.2 21.5 1.2 9.5 0.1 100.0 1,663 5.5 30-34 17.6 48.9 10.6 14.1 1.0 7.7 0.0 100.0 1,145 4.1 35-39 21.8 50.8 9.6 11.1 0.9 5.7 0.0 100.0 1,056 3.4 40-44 27.3 45.7 11.3 12.2 0.7 2.7 0.1 100.0 753 3.2 45-49 30.7 46.1 13.0 5.5 0.4 4.2 0.1 100.0 620 2.6 50-54 42.1 36.8 8.9 7.4 1.9 2.6 0.4 100.0 553 1.4 55-59 47.9 36.6 6.9 5.4 0.4 2.1 0.8 100.0 381 0.0 60-64 59.4 29.2 2.0 5.5 0.0 3.1 0.8 100.0 319 0.0 65+ 72.0 23.3 0.8 1.8 0.1 0.9 1.1 100.0 749 0.0 Residence Urban 8.2 40.9 8.3 27.0 3.2 12.2 0.1 100.0 2,719 6.1 Rural 22.0 60.9 6.2 8.9 0.3 1.5 0.1 100.0 14,739 2.3 Region Kampala 5.3 33.0 9.3 30.0 4.4 17.9 0.1 100.0 1,202 7.1 Central 1 16.0 53.6 9.1 15.4 1.7 4.0 0.1 100.0 1,908 3.8 Central 2 16.8 54.8 8.8 16.4 0.7 2.1 0.3 100.0 1,829 3.5 East Central 17.6 60.0 6.4 13.4 0.5 2.1 0.1 100.0 1,843 3.0 Eastern 14.8 68.4 6.0 8.8 0.4 1.5 0.1 100.0 2,620 2.6 Karamoja 58.1 36.3 1.4 3.1 0.3 0.8 0.0 100.0 677 0.0 North 22.7 66.3 4.6 4.9 0.3 1.1 0.2 100.0 1,583 2.2 West Nile 24.8 64.1 4.6 4.8 0.1 1.2 0.4 100.0 1,047 1.6 Western 21.4 59.8 5.1 11.1 0.2 2.4 0.0 100.0 2,476 2.6 Southwest 23.8 58.2 7.0 8.7 0.3 2.1 0.0 100.0 2,273 2.1 Wealth quintile Lowest 34.0 60.4 3.2 2.2 0.1 0.1 0.2 100.0 3,462 0.7 Second 24.4 64.1 5.4 5.6 0.1 0.3 0.0 100.0 3,309 1.9 Middle 18.8 65.0 7.1 8.0 0.3 0.7 0.0 100.0 3,440 2.5 Fourth 15.7 59.5 7.9 14.9 0.3 1.4 0.3 100.0 3,511 3.4 Highest 7.7 41.5 8.8 26.5 2.9 12.5 0.1 100.0 3,736 6.1 Total 19.9 57.8 6.5 11.7 0.8 3.2 0.1 100.0 17,458 2.7 1 Completed 7th grade at the primary level 2 Completed 6th grade at the secondary level 24 • Housing Characteristics and Household Population Table 2.12.2 Educational attainment of the male household population Percent distribution of the de facto male household population age six and over by highest level of schooling attended or completed and median years completed, according to background characteristics, Uganda 2011 Background characteristic No education Some primary Completed primary1 Some secondary Completed secondary2 More than secondary Don't know/ missing Total Number Median years completed Age 6-9 33.6 66.4 0.0 0.0 0.0 0.0 0.0 100.0 3,049 0.0 10-14 3.6 94.4 0.6 1.4 0.0 0.0 0.1 100.0 3,373 2.2 15-19 2.8 65.1 5.8 24.7 0.6 1.0 0.1 100.0 2,203 5.0 20-24 4.7 36.1 11.6 32.7 4.9 9.2 0.7 100.0 1,315 6.7 25-29 4.3 33.9 15.8 28.2 4.8 12.4 0.5 100.0 1,370 6.7 30-34 7.7 36.9 15.0 24.8 2.9 11.4 1.2 100.0 1,069 6.3 35-39 9.0 42.6 12.6 21.6 3.7 9.0 1.3 100.0 994 5.8 40-44 11.4 40.1 15.7 20.4 2.2 8.9 1.4 100.0 724 5.8 45-49 13.2 40.0 14.5 17.0 2.5 12.2 0.6 100.0 576 5.6 50-54 14.7 42.7 16.5 15.1 1.1 9.0 1.0 100.0 459 5.2 55-59 12.3 42.4 17.5 15.6 1.0 10.7 0.4 100.0 309 5.5 60-64 17.9 42.2 16.0 12.3 1.9 8.1 1.6 100.0 252 4.9 65+ 37.2 46.1 3.9 6.4 0.6 4.7 0.9 100.0 594 1.8 Residence Urban 6.6 37.3 6.8 26.6 6.1 15.8 0.7 100.0 2,442 6.7 Rural 13.5 63.0 7.4 12.1 0.8 2.9 0.4 100.0 13,851 3.1 Region Kampala 4.1 28.1 6.2 30.5 8.4 21.7 1.0 100.0 1,045 9.0 Central 1 15.5 53.9 7.3 16.6 1.5 4.3 1.0 100.0 1,852 3.5 Central 2 12.8 56.1 8.2 16.0 2.2 3.3 1.4 100.0 1,725 3.7 East Central 12.3 61.3 5.9 16.0 1.1 2.9 0.6 100.0 1,708 3.3 Eastern 8.7 68.0 6.7 12.8 0.5 3.2 0.1 100.0 2,451 3.4 Karamoja 45.3 37.2 5.8 8.2 1.2 2.4 0.0 100.0 522 0.0 North 9.3 64.9 9.8 9.9 0.7 5.3 0.2 100.0 1,535 3.7 West Nile 9.9 65.1 8.5 11.3 1.1 3.9 0.3 100.0 1,022 3.3 Western 11.7 63.3 7.0 13.7 0.7 3.3 0.3 100.0 2,419 3.3 Southwest 14.5 63.1 7.5 9.6 1.4 4.0 0.0 100.0 2,013 2.6 Wealth quintile Lowest 20.3 67.3 5.4 5.8 0.0 1.0 0.2 100.0 3,032 2.0 Second 13.1 66.8 8.3 9.3 0.6 1.7 0.2 100.0 3,246 2.9 Middle 12.3 64.5 8.3 12.2 0.5 1.9 0.3 100.0 3,245 3.2 Fourth 10.8 59.5 7.4 17.1 1.2 3.4 0.6 100.0 3,449 3.8 Highest 6.6 38.4 7.1 25.9 5.4 15.7 1.0 100.0 3,321 6.5 Total 12.5 59.1 7.3 14.2 1.6 4.8 0.5 100.0 16,293 3.4 1 Completed 7th grade at the primary level 2 Completed 6th grade at the secondary level 2.7.3 School Attendance Ratios Uganda’s educational system is a three-tier system that consists of seven years of primary education, followed by six years of secondary education (four years of ordinary secondary and two years of advanced secondary), and at least three years of university/tertiary education. The official age ranges for these levels are 6-12 years for primary education, 13-18 years for secondary education, and age 19-24 for university/tertiary education. The official age range for pre-primary education is 3-5 years. Table 2.13 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 pre-primary school is the percentage of the pre-primary-school-age population (3-5 years) that attends pre-primary school; the NAR for primary school is the percentage of the primary-school-age population (6-12 years) that attends primary school; and the NAR for secondary school is the percentage of the population of secondary school age (13-18 years) that attends secondary school. The GAR for pre-primary school is the total number of pre-primary school students of any age, expressed as a percentage of the official pre-primary-school-age population (3-5 years); 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 (6-12 years); and 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 (13-18 years). 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. Housing Characteristics and Household Population • 25 Table 2.13 shows that 23 and 24 percent, each, of male and female children of pre-primary school age in Uganda attend pre-primary school. Further, 81 percent each of male and female children of primary school age in Uganda attend primary school. At the same time, only 17 percent of secondary-school age population attend secondary school (16 percent of males and 18 percent of females). At the pre-primary school level, the NAR is substantially lower in rural areas (20 percent) than in urban areas (53 percent). West Nile region has the lowest NAR at the pre-primary school level (5 percent) and Kampala has the highest NAR for pre-primary school (62 percent). The NAR at the pre-primary education level increases from just 7 percent in the lowest wealth quintile to 53 percent in the highest wealth quintile. The pre-primary education GAR is almost the same among males and females (41 and 42 percent, respectively). Similar to the NAR, the GAR for pre-primary education level is higher in urban than rural areas (75 percent versus 37 percent). It is lowest in West Nile (7 percent) and highest in Kampala (82 percent), and it increases from 15 percent in the lowest wealth quintile to 75 percent in the highest wealth quintile. The Gender Parity Index (GPI) measures sex-related differences in school attendance ratios regardless of age. 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 of less 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 that is higher than 1 indicates a gender disparity in favour of females. The GPI for pre- primary school level is 1.02, indicating that there is no gender gap. At the primary level, the GAR is higher among males (124 percent) than among females (119 percent). The same pattern is observed at the secondary level (25 and 22 percent, respectively). The overall GAR of 121 percent shows that there are many overage students attending primary schools, and this applies to pupils in both rural and urban areas. 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 73 percent in the lowest wealth quintile to 87 percent in the highest wealth quintile. Similarly, at the secondary level the NAR rises from 4 percent in the lowest wealth quintile to 33 percent in the highest wealth quintile. The GPI for primary school level is 0.96, indicating that there is almost no gender gap. At the secondary level, the gender difference is slightly larger (0.89). The disparity in attendance between females and males at primary education is minimal in all regions except in West Nile (0.85) and Karamoja (0.88). However, at secondary school level, the variation widens in the North (0.57), West Nile (0.59), and Kampala (0.57) regions. 26 • Housing Characteristics and Household Population Table 2.13 School attendance ratios Net attendance ratios (NAR) and gross attendance ratios (GAR) for the de facto household population, by sex and level of schooling; and the Gender Parity Index (GPI), according to background characteristics, Uganda 2011 Background characteristic Net attendance ratio1 Gross attendance ratio2 Male Female Total Gender Parity Index3 Male Female Total Gender Parity Index3 PRE-PRIMARY SCHOOL Residence Urban 50.0 55.7 52.8 1.11 72.2 77.0 74.6 1.07 Rural 18.9 20.2 19.5 1.07 37.1 37.0 37.1 1.00 Region Kampala 61.1 62.3 61.7 1.02 79.5 83.4 81.5 1.05 Central 1 31.9 39.6 35.8 1.24 50.4 53.7 52.1 1.07 Central 2 34.3 35.2 34.8 1.03 66.1 69.6 67.8 1.05 East Central 14.7 21.2 17.9 1.44 31.2 34.7 33.0 1.11 Eastern 11.1 14.8 13.0 1.33 23.1 22.3 22.7 0.97 Karamoja 4.4 7.4 6.0 1.66 10.8 15.9 13.5 1.47 North 11.8 10.4 11.2 0.88 18.6 17.9 18.3 0.96 West-Nile 5.4 4.2 4.8 0.79 6.6 6.8 6.7 1.03 Western 24.7 27.8 26.1 1.13 46.4 54.9 50.2 1.18 Southwest 33.0 27.0 30.0 0.82 70.6 56.5 63.4 0.80 Wealth quintile Lowest 5.9 7.6 6.7 1.28 12.5 17.1 14.8 1.37 Second 15.2 15.3 15.3 1.01 32.2 32.6 32.4 1.01 Middle 23.1 20.1 21.6 0.87 44.4 37.4 40.9 0.84 Fourth 26.0 30.4 28.2 1.17 55.2 52.9 54.1 0.96 Highest 50.1 56.3 53.2 1.12 72.0 78.6 75.3 1.09 Total 22.5 24.4 23.4 1.08 41.1 41.7 41.4 1.02 PRIMARY SCHOOL Residence Urban 85.3 84.6 85.0 0.99 114.4 118.1 116.2 1.03 Rural 80.6 80.6 80.6 1.00 125.2 118.7 122.0 0.95 Region Kampala 86.6 83.3 84.9 0.96 107.1 103.3 105.1 0.96 Central 1 85.5 89.2 87.3 1.04 121.7 121.5 121.6 1.00 Central 2 79.0 80.2 79.6 1.01 118.9 116.7 117.8 0.98 East Central 84.0 85.0 84.5 1.01 127.8 123.8 125.9 0.97 Eastern 86.3 89.3 87.7 1.03 136.3 128.6 132.5 0.94 Karamoja 53.9 49.3 51.4 0.91 76.9 67.8 71.9 0.88 North 80.1 77.9 79.0 0.97 131.8 125.5 128.8 0.95 West Nile 81.2 76.7 78.9 0.95 132.8 112.9 122.9 0.85 Western 80.5 78.9 79.7 0.98 124.7 122.4 123.6 0.98 Southwest 78.1 79.2 78.6 1.01 119.8 118.1 118.9 0.99 Wealth quintile Lowest 75.0 71.4 73.2 0.95 114.6 101.0 107.8 0.88 Second 79.6 79.3 79.5 1.00 128.0 118.3 123.3 0.92 Middle 82.6 84.9 83.7 1.03 129.7 125.1 127.4 0.96 Fourth 82.8 85.5 84.1 1.03 129.3 129.1 129.2 1.00 Highest 87.1 85.9 86.5 0.99 117.6 122.4 120.0 1.04 Total 81.1 81.0 81.0 1.00 124.1 118.6 121.4 0.96 SECONDARY SCHOOL Residence Urban 39.7 31.0 34.7 0.78 54.9 36.0 44.0 0.66 Rural 12.6 15.5 14.0 1.23 20.5 19.2 19.9 0.93 Region Kampala 48.6 34.4 39.8 0.71 64.5 36.7 47.4 0.57 Central 1 16.6 30.5 23.7 1.84 26.4 34.6 30.6 1.31 Central 2 19.6 25.2 22.4 1.29 28.1 28.3 28.2 1.01 East Central 19.4 20.7 20.0 1.07 30.6 26.6 28.7 0.87 Eastern 13.4 14.2 13.8 1.06 24.7 17.8 21.4 0.72 Karamoja 7.2 7.5 7.4 1.05 8.1 7.7 7.9 0.95 North 5.8 3.7 4.8 0.64 10.9 6.2 8.6 0.57 West Nile 11.5 7.6 9.7 0.66 20.9 12.3 16.9 0.59 Western 15.7 15.2 15.5 0.96 23.2 18.3 20.8 0.79 Southwest 13.1 16.8 14.9 1.28 19.2 23.6 21.3 1.23 Wealth quintile Lowest 4.7 3.9 4.3 0.81 7.8 4.5 6.2 0.58 Second 8.7 10.6 9.6 1.23 15.8 13.4 14.7 0.85 Middle 11.8 11.5 11.6 0.97 20.2 15.6 18.0 0.78 Fourth 20.0 25.9 23.0 1.30 31.6 31.3 31.5 0.99 Highest 35.1 31.5 33.1 0.90 48.2 37.0 41.8 0.77 Total 15.8 18.0 16.9 1.14 24.6 21.9 23.3 0.89 -1 The NAR for pre-primary school is the percentage of the pre-primary-school-age (3-5 years) population that is attending primary school. The NAR for primary school is the percentage of the primary-school-age (6-12 years) population that is attending primary school. The NAR for secondary school is the percentage of the secondary-school-age (13-18 years) population that is attending secondary school. By definition the NAR cannot exceed 100 percent. 2 The GAR for primary school is the total number of primary school students, expressed as a percentage of the official primary- school-age population. The GAR for secondary school is the total number of secondary school students, expressed as a percentage of the official secondary-school-age population. If there are significant numbers of overage and underage students at a given level of schooling, the GAR can exceed 100 percent. 3 The Gender Parity Index for primary school is the ratio of the primary school NAR (GAR) for females to the NAR (GAR) for males. The Gender Parity Index for secondary school is the ratio of the secondary school NAR (GAR) for females to the NAR (GAR) for males. Housing Characteristics and Household Population • 27 Figure 2.2 shows the age-specific attendance rates (ASARs) for the population age 5-24 at primary, secondary, or tertiary/university level in the 2011 school year. In Uganda, the minimum age for schooling is age 6. However, some children start school at age 5. Over 80 percent of boys and girls age 8- 15 attend school. There are some differences in the proportion of males and females attending school. The difference is obvious at age 16 and older, when the proportion of adolescent males attending school is higher than that of adolescent females. Figure 2.2 Age-specific attendance rates of the de facto population age 5-24 UDHS 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 2.8 DISABILITY Persons with disabilities are considered vulnerable in Uganda. They are disadvantaged in work places and in other public places. The government of Uganda has developed a National Disability Policy to promote effective service delivery to persons with disabilities. Recently, the Expanding Social Protection Programme (ESP) was developed primarily to incorporate a national social protection system, including direct income support for the poorest and most vulnerable people, a population that includes those with disabilities. In the 2011 UDHS, information was collected on each household member age 5 and older about whether he or she had difficulties with seeing, hearing, communicating, walking or climbing stairs, remembering or concentrating, or performing self-care. Table 2.14 shows that 19 percent of persons age 5 and over have some form of disability. The prevalence of disability increases with age, from 12 percent among children age 5-9 to 67 percent among those age 60 and above. The prevalence of disability is about 12 to 13 percent among persons age 5-29, and starts to rise after age 30. The prevalence increases significantly, from 19 percent among persons age 30-39, to 31 percent at age 40-49, and to 49 percent at age 50-59. Difficulties in seeing and walking or climbing stairs are the most common types of disabilities reported during the survey. 28 • Housing Characteristics and Household Population Table 2.14 Disability by functional area and age Percent distribution of de facto household population age five and over by the degree of difficulty according to the functional area, and percent distribution by the highest degree of difficulty in at least one functional area by age, Uganda 2011 Functional area and age Degree of difficulty Some difficulty, a lot of difficulty, or can't do at all Number of individuals Can't do at all A lot of difficulty Some difficulty No difficulty Don't know/ missing Total Functional area Difficulty seeing 0.1 1.6 7.7 90.5 0.1 100.0 9.4 35,226 Difficulty hearing 0.1 0.8 4.5 94.5 0.1 100.0 5.4 35,226 Difficulty walking or climbing stairs 0.1 1.7 5.4 92.6 0.1 100.0 7.2 35,226 Difficulty remembering or concentrating 0.1 1.3 4.8 93.6 0.1 100.0 6.2 35,226 Difficulty with self-care 0.3 0.4 1.6 97.6 0.1 100.0 2.3 35,226 Difficulty communicating 0.1 0.3 1.0 98.4 0.1 100.0 1.5 35,226 Difficulty in at least one functional area 5-9 1.0 1.8 8.7 88.3 0.2 100.0 11.5 7,602 10-14 0.4 2.4 9.5 87.6 0.1 100.0 12.3 6,616 15-19 0.4 2.2 9.7 87.6 0.1 100.0 12.3 4,394 20-29 0.3 2.1 10.4 87.1 0.1 100.0 12.8 6,059 30-39 0.1 3.2 15.2 81.4 0.0 100.0 18.5 4,265 40-49 0.5 6.0 24.9 68.6 0.0 100.0 31.4 2,672 50-59 0.6 11.6 36.6 51.2 0.0 100.0 48.8 1,703 60+ 3.4 24.8 38.6 33.0 0.2 100.0 66.8 1,914 Total age 10 and over 0.6 4.9 15.8 78.7 0.1 100.0 21.3 27,624 Total age 15 and over 0.6 5.7 17.8 75.9 0.1 100.0 24.1 21,007 Total 0.7 4.2 14.3 80.8 0.1 100.0 19.2 35,226 Characteristics of Respondents • 29 CHARACTERISTICS OF RESPONDENTS 3 he purpose of this chapter is to create a demographic and socioeconomic profile of individual female and male respondents. This information helps to interpret findings presented later in the report and indicates the representativeness of the survey. The chapter begins by describing basic background characteristics, including age, marital status, religion, ethnicity, and wealth. It then provides more detailed information on education, media exposure, employment, health insurance, and tobacco use. 3.1 CHARACTERISTICS OF SURVEY RESPONDENTS The basic characteristics of the 8,674 women and 2,191 men age 15-49 interviewed in the 2011 UDHS are presented in Table 3.1. Relatively high proportions of both female and male respondents are in the younger age groups, with more than half of the respondents (61 percent of women and 57 percent of men) under age 30. In general, the proportion of women and men in each group declines as age increases, reflecting the comparatively young age structure of the population in Uganda, which results from previous high fertility levels. The majority of women and men are Catholic (41 percent and 44 percent), 30 percent of women and 32 percent of men are Protestant, and 13 percent of women and 12 percent of men are Muslim. In addition, 13 percent of women and 9 percent of men are Pentecostal, and 2 percent of each sex are Seventh-day Adventists (SDA). In general the percentages for various religions are consistent across males and females. More than one-fifth of women (24 percent) and more than one-third of men (38 percent) have never married. The majority of women (36 percent) and men (41 percent) are currently married, and 27 percent of women and 15 percent of men live together. Nine percent of women and 5 percent of men are divorced or separated. Four percent of women and very few men are widowed. Eight in ten respondents reside in rural areas. Across the ten regions, the Eastern and Western regions have the largest populations, while Karamoja has the smallest population for both men and women. T Key Findings  Thirteen percent of women and 4 percent of men age 15-49 have no education. However, the percentage of women and men with at least some secondary education has increased by 30 percent and 18 percent, respectively, in the past five years.  Twenty-one percent of women and 11 percent of men age 15-49 are not exposed to any source of mass media.  Less than 1 percent of women and 2 percent of men are covered by health insurance.  Sixty-nine percent of women were employed in the 12 months preceding the survey, with the majority (57 percent) employed in the agricultural sector.  Twenty-six percent of working women are not paid for their work, and 79 percent of women in nonagricultural work are paid by cash only. 30 • Characteristics of Respondents Table 3.1 Background characteristics of respondents Percent distribution of women and men age 15-49 by selected background characteristics, Uganda 2011 Background characteristic Women Men Weighted percent Weighted number Unweighted number Weighted percent Weighted number Unweighted number Age 15-19 23.6 2,048 2,026 25.5 554 562 20-24 18.8 1,629 1,666 14.6 318 340 25-29 18.1 1,569 1,618 16.6 361 365 30-34 12.5 1,086 1,101 14.9 323 310 35-39 11.8 1,026 992 12.3 268 284 40-44 8.4 729 709 8.8 191 179 45-49 6.8 587 562 7.2 157 151 Religion Catholic 40.6 3,524 3,731 43.8 952 994 Protestant 30.0 2,601 2,463 32.0 695 678 Muslim 13.0 1,124 1,173 12.4 269 287 Pentecostal 13.3 1,154 1,079 8.5 185 169 SDA 1.9 168 149 1.8 39 34 Marital status Never married 24.4 2,118 2,208 38.4 834 872 Married 35.6 3,087 3,071 41.4 899 878 Living together 26.9 2,331 2,281 15.1 329 326 Divorced/separated 9.3 805 790 4.7 103 107 Widowed 3.8 328 319 0.3 8 8 Residence Urban 19.8 1,717 2,562 20.2 439 614 Rural 80.2 6,957 6,112 79.8 1,734 1,577 Region Kampala 9.7 839 1,039 10.2 221 238 Central 1 11.0 956 767 9.6 209 178 Central 2 10.4 902 830 10.8 236 221 East Central 10.0 869 875 10.8 236 244 Eastern 14.6 1,267 943 13.3 289 234 Karamoja 3.3 289 659 2.5 55 116 North 8.5 735 823 9.2 199 222 West Nile 5.8 500 910 6.1 133 236 Western 14.1 1,221 919 14.8 322 280 Southwest 12.7 1,097 909 12.6 273 222 Education No education 12.9 1,120 1,332 4.1 90 112 Primary 59.4 5,152 4,820 60.2 1,309 1,250 Secondary+ 27.7 2,402 2,522 35.6 774 829 Wealth quintile Lowest 17.5 1,519 1,755 15.9 345 382 Second 18.2 1,579 1,433 19.5 423 400 Middle 18.5 1,608 1,404 18.5 402 361 Fourth 19.9 1,726 1,542 22.3 486 459 Highest 25.8 2,242 2,540 23.8 517 589 Total 15-49 100.0 8,674 8,674 100.0 2,173 2,191 50-54 na na na na 122 104 Total 15-54 na na na na 2,295 2,295 Note: Education categories refer to the highest level of education attended, whether or not that level was completed. na = Not applicable SDA = Seventh-day Adventist 3.2 EDUCATIONAL ATTAINMENT BY BACKGROUND CHARACTERISTICS Education affects many aspects of life, including individual demographics and health behaviours. Studies have shown that educational level is strongly associated with contraceptive use, fertility, general health status, morbidity, and mortality of children. Tables 3.2.1 and 3.2.2 show the distribution of respondents by educational attainment, according to background characteristics. Table 3.2.1 shows that 13 percent of women age 15-49 have never been to school, 48 percent have only some primary education, 11 percent have completed only primary school, and 21 percent have some secondary education. One percent of women stopped after completing secondary Characteristics of Respondents • 31 school, and 5 percent have higher than secondary education. Older women and those who reside in rural areas are most likely to have no education. The advantage of urban residents over rural residents in education is pronounced for those who have completed secondary school. For example, women in urban areas are much more likely than those in rural areas to have completed secondary or more than secondary education (20 percent and 3 percent, respectively). Table 3.2.1 Educational attainment: Women Percent distribution of women age 15-49 by highest level of schooling attended or completed, and median grade completed, according to background characteristics, Uganda 2011 Background characteristic Highest level of schooling Total Median years completed Number of women No education Some primary Completed primary1 Some secondary Completed secondary2 More than secondary Age 15-24 3.8 48.7 11.7 29.7 1.7 4.4 100.0 5.9 3,677 15-19 2.9 54.1 10.7 30.2 0.6 1.5 100.0 5.6 2,048 20-24 4.9 41.8 12.9 29.2 3.2 8.0 100.0 6.2 1,629 25-29 11.2 45.4 12.2 21.5 1.4 8.4 100.0 5.5 1,569 30-34 16.9 49.6 10.5 15.1 1.3 6.4 100.0 4.0 1,086 35-39 22.6 51.4 9.0 11.6 0.5 4.9 100.0 3.3 1,026 40-44 27.3 46.6 10.3 12.4 0.5 2.8 100.0 3.2 729 45-49 32.3 45.2 13.1 5.7 0.1 3.5 100.0 2.5 587 Residence Urban 3.5 26.5 11.1 38.7 4.1 16.1 100.0 8.0 1,717 Rural 15.2 53.4 11.3 16.9 0.6 2.5 100.0 4.6 6,957 Region Kampala 1.4 22.5 12.0 39.0 4.6 20.6 100.0 8.7 839 Central 1 9.2 39.3 15.0 28.2 2.4 5.9 100.0 6.1 956 Central 2 8.9 41.7 15.5 28.7 1.3 3.9 100.0 6.0 902 East Central 9.0 50.3 10.7 25.1 0.9 4.0 100.0 5.4 869 Eastern 9.1 60.6 10.6 16.5 0.6 2.6 100.0 4.6 1,267 Karamoja 57.9 29.8 2.5 7.4 0.7 1.7 100.0 0.0 289 North 15.7 64.4 8.3 9.2 0.5 1.9 100.0 4.0 735 West Nile 19.3 61.7 8.1 8.5 0.3 2.1 100.0 3.6 500 Western 16.0 48.8 9.7 20.8 0.7 4.0 100.0 5.0 1,221 Southwest 15.7 51.3 13.0 15.4 0.6 3.9 100.0 4.4 1,097 Wealth quintile Lowest 29.5 59.9 6.0 4.4 0.1 0.1 100.0 2.5 1,519 Second 17.3 61.8 9.6 10.5 0.2 0.5 100.0 4.0 1,579 Middle 11.4 57.7 13.5 15.6 0.9 0.9 100.0 4.8 1,608 Fourth 9.1 46.5 13.8 27.7 0.6 2.4 100.0 5.6 1,726 Highest 2.7 24.7 12.6 39.1 3.7 17.2 100.0 8.1 2,242 Total 12.9 48.1 11.3 21.2 1.3 5.2 100.0 5.2 8,674 1 Completed grade 7 at the primary level 2 Completed grade 6 at the secondary level Women in the Kampala, Central 1, Central 2, East Central, Western, and Southwest regions are more likely than those in the other regions to have more than a secondary level education (4 percent or higher), while more than half of the women in the Karamoja region have no education at all. The respondent’s educational attainment relates directly to her or his economic status. An examination of education by wealth quintile indicates that 30 percent of women from the poorest households have never attended school, compared with 3 percent of those from the wealthiest households. Women in the highest wealth quintile are most likely to have a secondary education or higher. For example, 21 percent of women in the highest wealth quintile have completed secondary school or have more than a secondary education compared with less than 1 percent of women in the lowest wealth quintile. At the national level, women have completed a median of 5.2 years of school. The median for urban women is 8.0 years, which compares with 4.6 years for rural women. The median number of years of schooling completed is highest among women in Kampala (8.7) and lowest among women in the Karamoja region (0.0). There is a large difference in median number of years completed by wealth quintile (8.1 in the highest quintile versus 2.5 in the lowest quintile). 32 • Characteristics of Respondents Table 3.2.2 Educational attainment: Men Percent distribution of men age 15-49 by highest level of schooling attended or completed, and median grade completed, according to background characteristics, Uganda 2011 Background characteristic Highest level of schooling Total Median years completed Number of men No education Some primary Completed primary1 Some secondary Completed secondary2 More than secondary Age 15-24 1.5 53.8 7.7 29.5 2.5 4.9 100.0 5.7 872 15-19 1.0 62.4 5.8 27.8 1.1 1.8 100.0 5.2 554 20-24 2.4 39.0 11.0 32.4 5.0 10.3 100.0 6.8 318 25-29 3.0 41.9 13.9 25.0 3.5 12.7 100.0 6.3 361 30-34 4.5 46.9 11.2 23.4 2.3 11.7 100.0 5.9 323 35-39 8.3 50.6 9.2 19.5 1.9 10.5 100.0 5.4 268 40-44 8.5 47.0 13.4 21.5 1.2 8.3 100.0 5.5 191 45-49 7.9 47.4 20.8 14.7 1.9 7.3 100.0 5.3 157 Residence Urban 1.0 23.8 9.1 35.2 7.9 23.1 100.0 9.1 439 Rural 4.9 55.8 11.3 22.2 1.0 4.6 100.0 5.3 1,734 Region Kampala 0.4 21.9 10.2 37.1 6.5 24.0 100.0 9.3 221 Central 1 6.0 50.8 12.5 23.2 1.5 6.1 100.0 5.5 209 Central 2 4.4 44.9 11.1 29.6 5.2 4.8 100.0 6.1 236 East Central 3.7 51.8 5.9 31.7 2.2 4.7 100.0 5.7 236 Eastern 4.6 58.6 9.7 20.4 0.7 5.9 100.0 5.2 289 Karamoja 29.5 20.7 20.1 26.6 1.2 1.8 100.0 6.0 55 North 0.0 55.8 14.6 19.2 0.5 10.0 100.0 5.8 199 West Nile 3.7 45.7 11.5 30.6 1.9 6.6 100.0 6.0 133 Western 4.2 54.7 11.0 20.8 0.5 8.8 100.0 5.1 322 Southwest 3.4 59.1 10.6 16.5 3.5 6.9 100.0 5.2 273 Wealth quintile Lowest 11.2 58.8 11.9 16.1 0.0 1.9 100.0 4.6 345 Second 4.8 63.5 12.8 15.8 0.7 2.4 100.0 5.0 423 Middle 4.2 58.5 12.2 19.7 1.6 3.8 100.0 5.1 402 Fourth 1.7 49.0 8.6 32.9 1.7 6.1 100.0 6.0 486 Highest 1.1 24.6 9.8 34.4 6.7 23.3 100.0 8.8 517 Total 15-49 4.1 49.3 10.9 24.8 2.4 8.4 100.0 5.8 2,173 50-54 11.7 43.7 16.2 18.7 1.0 8.7 100.0 5.3 122 Total 15-54 4.5 49.0 11.2 24.5 2.3 8.4 100.0 5.7 2,295 1 Completed 7 grade at the primary level 2 Completed 6 grade at the secondary level A similar educational attainment pattern is found among men (Table 3.2.2). Men are more educated than women in all categories. At the national level, 4 percent of men age 15-49 have no education, but almost half (49 percent) have some primary education only. Twenty-five percent of men have only some secondary schooling, and 11 percent have a secondary education or higher. Men age 40-44 are more likely to have no education (9 percent) than men age 15-24 (2 percent). Men in urban areas have higher levels of educational attainment than their rural counterparts. One percent of urban men have no formal education compared with 5 percent of rural men. Three in ten men (31 percent) in urban areas have completed secondary or have more than a secondary education, compared with only (6 percent) in rural areas. Overall, men age 15-49 have completed a median of 5.8 years of schooling. It is also worth noting that the percentage of women and men attending or who have completed primary education is higher in rural than urban areas, while for secondary higher and education, the reverse is true. The likelihood of attending school and reaching higher levels of education increases dramatically as wealth increases. Differences by wealth are large among men; 11 percent of men from the poorest households have no schooling compared with 1 percent from the wealthiest households. At the other end of the spectrum, 64 percent of men from the wealthiest households have attended secondary school or higher compared with 18 to 41 percent for men in the lower quintiles. Looking at trends over time, the percentage of women who attended secondary education or higher education has increased by 30 percent, from 21 percent in 2006 to 28 percent in 2011. A smaller increase (18 percent) was seen among men, from 30 percent in 2006 to 36 percent in 2011. Characteristics of Respondents • 33 3.3 LITERACY The ability to read and write empowers women and men. Literacy statistics are important for policymakers and program managers to assess the ability of the population to absorb information on health and nutrition from printed materials. In the 2011 UDHS, literacy was determined by the respondent’s ability to read all or part of a simple sentence. During data collection, interviewers carried a set of cards on which simple sentences were printed in all the major languages spoken in Uganda. Only women and men who had never been to school and women and men who had only a primary education were asked to read the cards in the language they were most familiar with. Those with a secondary education or higher were assumed to be literate. Table 3.3.1 indicates that two-thirds of women age 15-49 in Uganda (64 percent) are literate, which represents an increase from the 2006 figure of 56 percent. The level of literacy is much higher among women age 15-19 than among women in other age groups. This suggests that younger women have had more opportunity to learn than older women. Literacy varies by place of residence; 86 percent of urban women are literate compared with 59 percent of rural women. 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, Uganda 2011 Background characteristic Secondary school or higher No schooling or primary school Total Percent- age literate1 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 Age 15-24 35.9 24.2 15.2 23.7 1.1 0.0 100.0 75.2 3,677 15-19 32.3 28.7 17.4 20.8 0.8 0.0 100.0 78.4 2,048 20-24 40.4 18.5 12.3 27.3 1.5 0.0 100.0 71.2 1,629 25-29 31.3 20.5 11.5 35.1 1.6 0.0 100.0 63.2 1,569 30-34 22.9 18.2 14.7 41.8 2.4 0.0 100.0 55.8 1,086 35-39 17.0 20.2 13.4 47.0 1.9 0.4 100.0 50.6 1,026 40-44 15.8 27.3 11.0 43.4 2.3 0.1 100.0 54.1 729 45-49 9.4 28.5 11.9 47.4 2.2 0.7 100.0 49.7 587 Residence Urban 58.9 17.7 9.4 12.9 1.2 0.0 100.0 86.0 1,717 Rural 20.0 24.1 14.7 39.3 1.8 0.1 100.0 58.8 6,957 Region Kampala 64.2 16.0 10.5 7.8 1.5 0.0 100.0 90.6 839 Central 1 36.5 27.0 16.2 20.0 0.1 0.2 100.0 79.6 956 Central 2 34.0 25.1 15.5 23.5 1.9 0.0 100.0 74.5 902 East Central 29.9 16.0 11.8 41.3 1.0 0.1 100.0 57.7 869 Eastern 19.7 17.2 12.1 48.3 2.5 0.1 100.0 49.0 1,267 Karamoja 9.8 5.5 7.4 72.9 4.3 0.0 100.0 22.8 289 North 11.6 18.8 18.4 50.9 0.0 0.2 100.0 48.8 735 West Nile 10.9 17.0 17.3 54.0 0.7 0.2 100.0 45.1 500 Western 25.5 28.9 8.9 33.0 3.4 0.2 100.0 63.3 1,221 Southwest 20.0 37.7 17.7 23.3 1.2 0.0 100.0 75.5 1,097 Wealth quintile Lowest 4.7 14.9 12.5 64.5 3.4 0.0 100.0 32.0 1,519 Second 11.2 22.4 16.0 48.0 2.1 0.3 100.0 49.6 1,579 Middle 17.4 30.6 17.3 33.2 1.2 0.3 100.0 65.3 1,608 Fourth 30.6 27.3 13.9 26.8 1.3 0.0 100.0 71.8 1,726 Highest 60.0 19.6 10.0 9.7 0.7 0.0 100.0 89.6 2,242 Total 27.7 22.8 13.7 34.0 1.7 0.1 100.0 64.2 8,674 1 Refers to women who attended secondary school or higher and women who can read a whole sentence or part of a sentence 34 • Characteristics of Respondents Regional differences in literacy are marked, with literacy levels highest among women in predominantly urban Kampala (91 percent) and lowest in the Karamoja region (23 percent). There is a significant difference in literacy by household wealth, with the literacy rate ranging from 32 percent among women in the lowest wealth quintile to 90 percent among women in the highest quintile. This reinforces the positive association between economic status and literacy. Men are more likely to be literate than women (Table 3.3.2). Seventy-eight percent of Ugandan men age 15-49 are literate, a decline from 83 percent in 2006. The pattern of male literacy is similar to the pattern among women. However, there are marked differences between men and women across age groups. Seventy-nine percent of men age 45-49 are literate compared with 50 percent of women in the same age group. The gap in urban-rural literacy among men is smaller than that among women, suggesting that men in rural areas have better access to learning than women. Men in Kampala, North, Central 2, and West Nile regions are more likely to be literate than those in other regions. Men in the highest wealth quintile have the highest literacy level (90 percent). 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, Uganda 2011 Background characteristic Secondary school or higher No schooling or primary school Total Percent- age literate1 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 36.9 22.1 18.1 21.2 1.7 0.0 0.1 100.0 77.1 872 15-19 30.8 26.9 20.6 20.1 1.6 0.0 0.0 100.0 78.3 554 20-24 47.6 13.7 13.6 23.0 1.8 0.0 0.2 100.0 74.9 318 25-29 41.1 19.5 19.0 18.8 1.5 0.0 0.2 100.0 79.6 361 30-34 37.4 23.2 15.2 23.5 0.7 0.0 0.0 100.0 75.8 323 35-39 31.9 32.2 13.7 20.7 1.5 0.0 0.0 100.0 77.8 268 40-44 31.1 30.8 14.9 20.5 2.7 0.0 0.0 100.0 76.8 191 45-49 23.8 37.7 17.9 17.6 3.0 0.0 0.0 100.0 79.4 157 Residence Urban 66.2 12.9 12.0 7.7 1.1 0.0 0.1 100.0 91.1 439 Rural 27.9 28.0 18.2 24.0 1.8 0.0 0.0 100.0 74.1 1,734 Region Kampala 67.6 10.6 13.5 6.5 1.9 0.0 0.0 100.0 91.6 221 Central 1 30.7 23.7 19.3 25.3 1.0 0.0 0.0 100.0 73.8 209 Central 2 39.7 13.5 30.8 14.4 1.6 0.0 0.0 100.0 84.0 236 East Central 38.6 16.6 16.9 27.5 0.4 0.0 0.0 100.0 72.1 236 Eastern 27.0 25.1 15.1 30.1 2.7 0.0 0.0 100.0 67.2 289 Karamoja 29.7 18.5 14.7 35.4 1.8 0.0 0.0 100.0 62.8 55 North 29.6 50.0 5.2 14.7 0.5 0.0 0.0 100.0 84.8 199 West Nile 39.1 13.9 29.5 15.7 1.3 0.0 0.5 100.0 82.5 133 Western 30.1 28.7 15.8 21.6 3.6 0.0 0.2 100.0 74.6 322 Southwest 26.9 38.4 12.4 21.5 0.8 0.0 0.0 100.0 77.7 273 Wealth quintile Lowest 18.1 25.0 21.5 32.8 2.5 0.0 0.0 100.0 64.6 345 Second 18.9 33.0 19.5 26.9 1.6 0.0 0.2 100.0 71.4 423 Middle 25.1 29.8 17.5 26.6 1.1 0.0 0.0 100.0 72.3 402 Fourth 40.7 24.3 17.8 15.3 1.9 0.0 0.0 100.0 82.8 486 Highest 64.4 15.2 10.6 8.2 1.4 0.0 0.1 100.0 90.2 517 Total 15-49 35.6 25.0 17.0 20.7 1.7 0.0 0.1 100.0 77.5 2,173 50-54 28.5 29.2 19.3 20.5 0.0 2.5 0.0 100.0 77.0 122 Total 15-54 35.2 25.2 17.1 20.7 1.6 0.1 0.1 100.0 77.5 2,295 1 Refers to men who attended secondary school or higher and men who can read a whole sentence or part of a sentence Characteristics of Respondents • 35 3.4 ACCESS TO MASS MEDIA Exposure to information on television and radio and in print can increase an individual’s knowledge and awareness of new ideas, social changes, and opportunities, which in turn can affect the individual’s perceptions and behaviour, including those related to health. In the 2011 UDHS, exposure to media was assessed by asking respondents how often they listened to a radio, watched television, or read newspapers or magazines. Media exposure in Uganda is higher among men than women; 14 percent of men and 6 percent of women are exposed to all three media at least once a week (Table 3.4.1 and Table 3.4.2). Seventy-four percent of women and 86 percent of men listen to the radio at least once a week, and 20 percent of women and 30 percent of men watch television at least once a week. 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, Uganda 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 Number of women Age 15-19 23.3 24.0 75.2 7.6 18.3 2,048 20-24 16.8 23.6 77.1 9.2 18.6 1,629 25-29 12.3 21.2 74.1 6.0 20.3 1,569 30-34 13.1 16.8 72.1 5.2 22.4 1,086 35-39 10.1 14.6 69.4 3.8 27.0 1,026 40-44 10.9 12.9 74.6 4.1 22.4 729 45-49 10.4 12.9 73.9 5.8 24.9 587 Residence Urban 36.9 59.7 78.0 23.0 8.4 1,717 Rural 10.0 9.8 73.2 2.3 24.2 6,957 Region Kampala 41.1 77.4 73.5 29.6 6.2 839 Central 1 21.6 27.6 79.0 9.0 14.8 956 Central 2 26.8 20.0 79.7 8.3 15.3 902 East Central 11.0 14.4 77.2 4.1 20.1 869 Eastern 8.7 6.6 58.0 1.6 38.5 1,267 Karamoja 4.8 3.7 28.3 0.6 69.3 289 North 6.2 5.4 82.2 1.8 16.3 735 West Nile 9.5 8.2 77.9 1.6 20.4 500 Western 9.5 16.9 80.4 3.2 17.4 1,221 Southwest 10.0 10.0 80.0 2.7 18.0 1,097 Education No education 0.1 6.6 60.0 0.1 39.0 1,120 Primary 8.5 12.5 73.5 2.0 23.0 5,152 Secondary+ 37.1 41.2 82.1 18.9 8.6 2,402 Wealth quintile Lowest 2.8 3.2 49.4 0.1 48.8 1,519 Second 5.6 4.6 72.5 0.5 25.7 1,579 Middle 8.6 5.6 79.6 0.8 18.3 1,608 Fourth 15.0 12.8 83.8 2.8 13.7 1,726 Highest 35.8 57.0 80.7 21.7 6.6 2,242 Total 15.3 19.7 74.1 6.4 21.0 8,674 Women and men under age 30 are more likely to be exposed to the mass media than older women and men, presumably in part because of their higher level of education. There is a wide gap in exposure to mass media by place of residence. For example, the proportion of newspaper readers is notably higher among urban women (37 percent) and men (60 percent) than among their rural counterparts (10 percent and 16 percent, respectively). Not surprisingly, media exposure is closely related to the respondent’s educational level as well as economic status. Although 19 percent of women and 30 percent of men with secondary and higher levels of education access all three media at least once a week, less than 1 percent of women and men with no education access all three media sources. Likewise, 22 percent of women and 44 36 • Characteristics of Respondents percent of men from the highest wealth quintile access all three media at least once a week compared with less than 1 percent of women and men from the lowest quintile. Women and men in Kampala are more likely to be exposed to all three media on a weekly basis than those in other regions. Forty-one percent of women and 58 percent of men in Kampala read a newspaper on a weekly basis. The patterns of exposure to mass media are similar among men and women. 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, Uganda 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 Number of men Age 15-19 21.3 32.3 83.7 10.5 12.3 554 20-24 29.3 37.4 85.6 19.0 11.3 318 25-29 29.5 36.4 90.7 19.5 6.9 361 30-34 28.3 28.5 85.4 16.4 10.4 323 35-39 21.9 25.4 82.4 13.7 14.4 268 40-44 20.3 16.9 86.7 7.5 12.5 191 45-49 22.5 16.1 84.0 10.6 15.0 157 Residence Urban 60.3 77.3 87.7 49.2 4.3 439 Rural 16.0 17.7 85.0 5.4 13.2 1,734 Region Kampala 57.7 88.7 86.1 49.2 3.3 221 Central 1 23.1 31.0 92.3 12.9 5.5 209 Central 2 29.6 34.3 88.5 18.1 8.6 236 East Central 19.7 34.4 88.1 11.8 9.4 236 Eastern 19.6 13.9 74.4 4.7 22.7 289 Karamoja 14.7 16.1 73.7 5.1 23.6 55 North 7.7 7.5 81.6 2.2 17.1 199 West Nile 25.6 8.0 76.9 5.2 18.9 133 Western 25.9 29.2 88.1 14.4 10.2 322 Southwest 19.3 20.4 93.5 10.8 6.1 273 Education No education 2.2 10.5 69.9 0.0 27.9 90 Primary 12.1 22.5 83.7 5.7 14.0 1,309 Secondary + 49.3 44.3 90.4 30.4 5.2 774 Wealth quintile Lowest 8.7 10.9 62.9 0.6 30.7 345 Second 12.7 12.7 87.6 2.1 11.2 423 Middle 13.8 13.4 87.9 4.6 11.5 402 Fourth 22.5 27.9 92.6 10.4 6.1 486 Highest 56.8 70.8 90.5 44.4 3.7 517 Total 15-49 25.0 29.8 85.5 14.3 11.4 2,173 50-54 17.3 21.2 87.6 8.6 11.8 122 Total 15-54 24.6 29.3 85.6 14.0 11.5 2,295 3.5 EMPLOYMENT 3.5.1 Employment Status The 2011 UDHS asked respondents a number of questions regarding their employment status, including whether they worked in the seven days preceding the survey and, if not, whether they had worked in the 12 months before the survey. The results for women and men are presented in Tables 3.5.1 and 3.5.2. At the time of the survey, 69 percent of the women were currently employed, 4 percent were not employed but had worked sometime during the preceding 12 months, and 26 percent were not employed (Table 3.5.1 and Figure 3.1). Characteristics of Respondents • 37 Table 3.5.1 Employment status: Women Percent distribution of women age 15-49 by employment status, according to background characteristics, Uganda 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 Number of women Currently employed1 Not currently employed Age 15-19 47.3 4.1 48.5 0.0 100.0 2,048 20-24 64.6 5.3 30.0 0.1 100.0 1,629 25-29 75.1 4.9 19.9 0.1 100.0 1,569 30-34 78.8 4.0 17.1 0.1 100.0 1,086 35-39 84.1 3.2 12.7 0.0 100.0 1,026 40-44 82.7 4.0 13.1 0.2 100.0 729 45-49 82.6 2.6 14.7 0.0 100.0 587 Marital status Never married 47.5 4.2 48.2 0.0 100.0 2,118 Married or living together 75.0 4.3 20.7 0.0 100.0 5,418 Divorced/separated/widowed 82.8 4.1 13.0 0.0 100.0 1,134 Number of living children 0 49.1 4.0 46.8 0.0 100.0 2,279 1-2 70.9 5.0 24.0 0.2 100.0 2,099 3-4 76.1 5.0 18.9 0.0 100.0 1,832 5+ 81.4 3.3 15.2 0.1 100.0 2,464 Residence Urban 64.3 3.9 31.7 0.1 100.0 1,717 Rural 70.5 4.3 25.2 0.1 100.0 6,957 Region Kampala 63.2 3.1 33.7 0.0 100.0 839 Central 1 56.2 5.1 38.7 0.0 100.0 956 Central 2 71.4 3.4 25.2 0.0 100.0 902 East Central 72.3 4.8 22.5 0.5 100.0 869 Eastern 63.5 3.1 33.5 0.0 100.0 1,267 Karamoja 85.3 6.8 8.0 0.0 100.0 289 North 53.0 10.3 36.6 0.0 100.0 735 West Nile 71.1 4.2 24.7 0.0 100.0 500 Western 79.5 1.4 19.0 0.1 100.0 1,221 Southwest 82.2 4.4 13.4 0.0 100.0 1,097 Education No education 77.8 4.0 18.2 0.0 100.0 1,120 Primary 70.8 4.4 24.7 0.1 100.0 5,152 Secondary + 62.0 4.0 33.9 0.0 100.0 2,402 Wealth quintile Lowest 73.9 4.1 22.0 0.0 100.0 1,519 Second 71.3 5.7 23.0 0.0 100.0 1,579 Middle 71.3 4.2 24.4 0.1 100.0 1,608 Fourth 68.0 4.4 27.4 0.1 100.0 1,726 Highest 64.2 3.2 32.6 0.0 100.0 2,242 Total 69.3 4.2 26.4 0.1 100.0 8,674 1 Currently employed is defined as having done work in the past seven days. Includes persons who did not work in the past seven days but who are regularly employed and were absent from work for leave, illness, vacation, or any other such reason. 38 • Characteristics of Respondents Figure 3.1 Women's employment status in the past 12 months Uganda 2011 DHS Currently employed 70% Not currently employed 4% Did not work in last 1 26% Currently employed 69% Not currently employed, but worked in last 12 months 4% Did not work in last 12 months 26% The proportion of women currently employed increases with age. Current employment is lowest among women age 15-19 (47 percent) and highest among those age 35-49 (83 percent, or higher). Women who are divorced, separated, or widowed are more likely to be currently employed than other women (83 percent versus 75 percent or lower). Women who have five or more children are more likely to be employed (81 percent) than those with no children (49 percent). The proportion of women currently employed varies by place of residence and region. Rural women are more likely to be currently employed than urban women (71 percent versus 64 percent). Women in Karamoja, Southwest, and Western regions are more likely to be employed (85 percent, 82 percent, and 80 percent, respectively) than women in other regions. The proportion of women currently employed decreases with level of education. For example, 78 percent of women with no education are employed, compared with 62 percent of women with a secondary or higher level of education. Women living in the poorest households are much more likely to be employed (74 percent) than women in the wealthiest households (64 percent). The proportion of currently employed men (91 percent) is higher than that of women (Table 3.5.2). The percentage of currently employed men increases with age, from 75 percent among men age 15- 19 to 99 percent among men age 30-34, and then declines to 97 percent among men age 45-49. Men who have never married (79 percent), men with no living children (81 percent), and urban men (87 percent) are less likely to be employed than other men. Characteristics of Respondents • 39 Table 3.5.2 Employment status: Men Percent distribution of men age 15-49 by employment status, according to background characteristics, Uganda 2011 Background characteristic Employed in the 12 months preceding the survey Not employed in the 12 months preceding the survey Total Number of men Currently employed1 Not currently employed Age 15-19 75.1 7.4 17.5 100.0 554 20-24 89.1 4.4 6.5 100.0 318 25-29 97.4 0.9 1.7 100.0 361 30-34 99.0 0.6 0.4 100.0 323 35-39 97.9 0.8 1.4 100.0 268 40-44 96.1 2.0 1.9 100.0 191 45-49 96.7 1.7 1.6 100.0 157 Marital status Never married 79.2 6.3 14.5 100.0 834 Married or living together 97.7 1.3 1.0 100.0 1,228 Divorced/separated/widowed 98.1 0.0 1.9 100.0 111 Number of living children 0 80.8 5.8 13.4 100.0 902 1-2 96.6 1.9 1.5 100.0 386 3-4 98.9 0.9 0.2 100.0 339 5+ 97.5 1.1 1.4 100.0 546 Residence Urban 86.8 3.5 9.7 100.0 439 Rural 91.6 3.1 5.3 100.0 1,734 Region Kampala 82.7 4.4 12.9 100.0 221 Central 1 96.7 0.2 3.0 100.0 209 Central 2 96.0 1.6 2.3 100.0 236 East Central 84.4 8.3 7.3 100.0 236 Eastern 91.1 1.1 7.8 100.0 289 Karamoja 88.7 4.1 7.2 100.0 55 North 90.0 8.0 2.0 100.0 199 West Nile 90.0 5.6 4.4 100.0 133 Western 89.8 0.0 10.2 100.0 322 Southwest 94.7 2.4 3.0 100.0 273 Education No education 93.9 2.1 4.0 100.0 90 Primary 91.3 3.4 5.3 100.0 1,309 Secondary + 89.1 2.9 8.1 100.0 774 Wealth quintile Lowest 95.1 2.3 2.5 100.0 345 Second 91.2 4.3 4.5 100.0 423 Middle 93.1 1.6 5.3 100.0 402 Fourth 90.3 2.7 7.0 100.0 486 Highest 85.6 4.5 10.0 100.0 517 Total 15-49 90.6 3.2 6.2 100.0 2,173 50-54 94.2 0.8 4.9 100.0 122 Total 15-54 90.8 3.0 6.1 100.0 2,295 1 Currently employed is defined as having done work in the past seven days. Includes persons who did not work in the past seven days but who are regularly employed and were absent from work for leave, illness, vacation, or any other such reason. There is no clear pattern in the variation of men’s employment by level of education. By wealth status, current employment among men decreases from 95 percent in the poorest households to 86 percent in the wealthiest households. Current employment among women age 15-49 has decreased from 81 percent in 2006 to 69 percent in 2011, and employment among men has decreased from 94 percent in 2006 to 91 percent in 2011. 40 • Characteristics of Respondents 3.5.2 Occupation Respondents who were currently employed or who had worked in the 12 months preceding the survey were asked to specify their occupation. The results are presented in Table 3.6.1 and Table 3.6.2. 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, Uganda 2011 Background characteristic Professional/ managerial/ technical/ assistant professional Clerical Sales and services Skilled agriculture, forestry, and fishery workers Craft and related trade workers Plant and machine operators and assemblers Elementary occupations Total Number of women Age 15-19 0.8 0.2 13.2 60.2 5.7 0.0 19.9 100.0 1,054 20-24 6.1 0.5 18.8 52.2 7.3 0.0 15.2 100.0 1,138 25-29 9.1 0.4 19.9 52.1 6.0 0.2 12.4 100.0 1,255 30-34 6.3 0.4 16.5 56.3 7.9 0.0 12.5 100.0 899 35-39 4.7 0.4 15.9 61.1 4.7 0.0 13.2 100.0 896 40-44 4.7 0.0 15.3 63.5 6.7 0.0 9.7 100.0 632 45-49 3.2 0.1 13.9 63.4 7.6 0.0 11.9 100.0 500 Marital status Never married 7.4 0.7 16.1 49.4 6.1 0.0 20.3 100.0 1,096 Married or living together 5.4 0.3 15.0 61.3 6.5 0.0 11.4 100.0 4,293 Divorced/separated/widowed 2.4 0.2 24.2 48.8 6.6 0.0 17.8 100.0 986 Number of living children 0 6.4 0.7 16.2 50.4 7.2 0.0 19.1 100.0 1,211 1-2 8.6 0.4 21.2 48.6 6.7 0.0 14.5 100.0 1,592 3-4 5.7 0.2 18.7 56.1 6.3 0.1 12.9 100.0 1,485 5+ 1.8 0.1 11.9 68.9 6.0 0.0 11.3 100.0 2,087 Residence Urban 13.8 1.4 40.7 13.6 7.8 0.0 22.7 100.0 1,173 Rural 3.4 0.1 11.2 67.2 6.1 0.0 12.0 100.0 5,202 Region Kampala 14.2 2.0 45.5 2.4 7.6 0.0 28.4 100.0 557 Central 1 8.0 0.0 28.2 39.0 5.6 0.0 19.1 100.0 586 Central 2 6.1 0.2 21.8 54.0 5.9 0.0 12.0 100.0 674 East Central 5.0 0.4 15.1 64.1 4.0 0.0 11.4 100.0 669 Eastern 3.8 0.1 8.3 71.3 3.3 0.2 13.0 100.0 843 Karamoja 1.8 0.0 2.6 50.6 13.6 0.2 31.2 100.0 266 North 1.4 0.0 11.5 52.5 15.9 0.0 18.7 100.0 466 West Nile 1.9 0.1 24.4 41.1 17.9 0.0 14.6 100.0 376 Western 4.8 0.3 10.9 71.7 4.5 0.0 7.8 100.0 988 Southwest 3.9 0.0 6.8 81.8 2.1 0.0 5.3 100.0 951 Education No education 0.0 0.0 5.7 74.6 7.0 0.0 12.6 100.0 916 Primary 0.1 0.0 14.3 64.2 6.5 0.1 14.9 100.0 3,873 Secondary + 21.1 1.3 28.7 30.7 6.0 0.0 12.3 100.0 1,586 Wealth quintile Lowest 0.1 0.0 6.2 70.5 7.0 0.0 16.2 100.0 1,185 Second 1.2 0.0 8.0 71.8 8.9 0.0 10.1 100.0 1,216 Middle 1.8 0.0 9.6 72.5 5.5 0.1 10.3 100.0 1,213 Fourth 4.3 0.0 17.5 60.3 5.7 0.0 12.2 100.0 1,250 Highest 16.2 1.3 36.7 20.7 5.4 0.0 19.6 100.0 1,511 Total 5.3 0.3 16.6 57.3 6.4 0.0 13.9 100.0 6,375 In Uganda, the agricultural sector remains the main employer, with 57 percent of women and 55 percent of men age 15-49 engaged in work in agriculture, forestry and fishery. These figures are lower than those in the 2006 UDHS, when 75 percent of women and 68 percent of men were employed in agricultural occupations. The survey indicates that 17 percent of women work in sales and services, an increase from 13 percent in 2006. Five percent of women work in professional, technical, and managerial fields. Among men, 11 percent work in sales and services, and 5 percent have professional, technical, and managerial positions, similar to the 2006 UDHS findings. Fourteen percent of women and 15 percent of men work in elementary occupations (i.e., cleaners and helpers). Characteristics of Respondents • 41 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, Uganda 2011 Background characteristic Professional/ managerial/ technical/ assistant professional Clerical Sales and services Skilled agriculture forestry and fishery workers Craft and related trade workers Plant and machine operators, and assemblers Elementary occupations Total Number of men Age 15-19 1.2 0.2 6.4 66.9 7.1 0.7 17.6 100.0 457 20-24 3.1 0.5 15.9 45.3 12.8 4.9 17.5 100.0 298 25-29 6.0 0.2 13.1 43.6 7.7 10.5 18.9 100.0 355 30-34 9.1 0.7 10.1 52.8 9.1 7.2 11.1 100.0 322 35-39 7.3 0.9 8.3 57.1 7.2 5.8 13.3 100.0 265 40-44 5.7 0.0 12.5 62.9 5.8 1.1 12.0 100.0 187 45-49 6.2 0.0 11.3 60.9 5.6 1.6 14.3 100.0 154 Marital status Never married 3.5 0.4 9.5 55.9 9.6 2.4 18.7 100.0 713 Married or living together 6.2 0.4 11.6 55.8 7.1 5.8 13.2 100.0 1,216 Divorced/separated/widowed 4.4 0.0 9.0 46.9 10.9 9.6 19.2 100.0 109 Number of living children 0 4.1 0.4 10.0 55.7 9.2 2.1 18.6 100.0 782 1-2 9.0 0.5 12.3 44.9 9.0 9.4 15.0 100.0 380 3-4 7.0 0.2 11.4 49.1 9.6 8.8 13.9 100.0 338 5+ 2.9 0.4 10.2 66.2 5.2 3.0 12.1 100.0 539 Residence Urban 14.8 1.9 22.7 10.1 17.3 12.0 21.2 100.0 396 Rural 2.8 0.0 7.8 66.3 6.0 3.1 14.1 100.0 1,642 Region Kampala 16.0 1.2 26.7 2.3 18.0 11.6 24.2 100.0 193 Central 1 5.9 0.0 10.8 53.1 6.9 7.4 16.0 100.0 203 Central 2 3.5 1.0 11.8 54.3 9.3 4.6 15.4 100.0 230 East Central 3.1 0.0 9.7 54.3 10.5 3.7 18.7 100.0 218 Eastern 2.7 0.0 8.7 72.7 5.1 3.7 7.2 100.0 266 Karamoja 2.9 1.5 19.3 34.3 11.3 0.0 30.7 100.0 51 North 5.0 0.0 6.0 73.2 3.4 0.7 11.6 100.0 195 West Nile 5.1 0.0 7.4 74.6 7.5 1.2 4.1 100.0 127 Western 5.9 0.8 4.7 66.8 4.3 6.1 11.4 100.0 289 Southwest 2.0 0.0 11.1 49.2 9.6 4.3 24.0 100.0 265 Education No education 2.3 0.0 9.8 66.5 3.8 0.4 17.3 100.0 86 Primary 1.0 0.0 8.7 63.2 6.8 3.8 16.6 100.0 1,240 Secondary + 12.8 1.1 14.4 40.3 11.1 7.2 13.2 100.0 712 Wealth quintile Lowest 0.8 0.0 5.7 77.6 4.4 0.6 10.9 100.0 336 Second 1.7 0.0 6.0 71.7 6.4 1.2 13.0 100.0 404 Middle 1.6 0.0 8.4 65.3 6.1 3.1 15.5 100.0 381 Fourth 2.7 0.3 13.0 53.6 5.3 6.5 18.6 100.0 452 Highest 16.5 1.3 18.2 18.6 16.9 10.8 17.7 100.0 466 Total 15-49 5.2 0.4 10.7 55.4 8.2 4.8 15.4 100.0 2,038 50-54 5.1 0.0 4.9 64.0 12.5 1.8 11.6 100.0 116 Total 15-54 5.1 0.4 10.4 55.8 8.4 4.6 15.2 100.0 2,154 As expected, place of residence has a significant effect on type of occupation. In rural areas, two of three employed men and women (66 percent and 67 percent, respectively) are engaged in agricultural work. Employment outside the agricultural sector is highest among women and men with more than secondary education and those in the highest wealth quintile. Women in the Southwest, Western, and Eastern regions are more likely than other women to be involved in agriculture, forestry, or fisheries (71 percent or higher). Seventy-two percent or more of men in Eastern, North, and West Nile regions work in agricultural fields. However, since 2006, employment in agriculture has declined and shifted to other occupations, especially sales and services. The lowest proportion of women and men engaged in the agricultural sector live in Kampala region. There is a positive relationship between women’s education and their involvement in sales and services. For example, 29 percent of women with secondary or higher education are involved in this sector, compared with 6 to 14 percent of women with less education. A similar pattern is found among men. Seventy-one percent of employed women in the lowest wealth quintile work in agriculture compared with 42 • Characteristics of Respondents 21 percent of women in the highest wealth quintile. Agricultural work is also less common among men with some secondary or higher education and men in the highest wealth quintile. The proportion of respondents in elementary occupations, such as cleaners and helpers, decreases with age and is highest among the never-married, respondents with no living children, urban respondents, and those with no education or primary education. 3.5.3 Type of Women’s Employment Table 3.7 presents the percent distribution of employed women age 15-49 by type of earnings, employer characteristics, and continuity of employment, according to type of employment (agricultural or nonagricultural). About half (49 percent) of women who were employed in the 12 months preceding the survey received cash payment only; with 35 percent in the agricultural sector versus 79 percent in the nonagricultural sector. Women working in agriculture are more likely not to be paid than those working in nonagricultural work (36 percent compared with 4 percent). Five percent of women employed in the agricultural sector are paid in-kind only. Two in three women, in both agriculture and nonagricultural sectors, are self-employed. Women who work in agriculture are more likely to be employed by a family member (22 percent), whereas those who work in a nonagricultural sector are more likely to be employed by a nonfamily member (28 percent). 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), Uganda 2011 Employment characteristic Agricultural work Nonagricultural work Total Type of earnings Cash only 35.1 78.9 49.1 Cash and in-kind 23.6 14.5 20.7 In-kind only 5.4 2.2 4.4 Not paid 35.8 4.4 25.8 Total 100.0 100.0 100.0 Type of employer Employed by family member 22.0 7.7 17.4 Employed by nonfamily member 11.4 27.5 16.5 Self-employed 66.6 64.7 66.0 Total 100.0 100.0 100.0 Continuity of employment All year 54.1 72.2 59.9 Seasonal 36.5 13.1 29.1 Occasional 9.4 14.6 11.1 Total 100.0 100.0 100.0 Number of women employed during the last 12 months 4,339 2,034 6,375 Note: Total includes women with missing information on type of employment who are not shown separately. Six in ten employed women work all year, 54 percent of those who work in the agricultural sector and 72 percent of those in the non-agricultural sector. Three in ten women are employed seasonally. Women in the agricultural sector are three times more likely to work seasonally than those who work in the nonagricultural sector (37 percent and 13 percent, respectively). 3.6 HEALTH INSURANCE Over the last two decades, interest has grown in the potential of social health insurance (SHI) as a health financing mechanism for low- and middle-income countries. Like many other African countries, Uganda is currently trying to find an efficient, equitable, and sustainable health financing mechanism that Characteristics of Respondents • 43 will raise a substantial amount of funds for the health sector. A National Health Insurance scheme (NHIS) has been introduced in a phased manner, with the objective of obtaining additional funding for the health sector and promoting financial risk protection. The scheme is expected to bring additional resources for the health sector and improve equity in access to health services. In the 2011 UDHS, respondents were asked whether they have any type of health insurance. The health insurance may be obtained through a mutual health organization or community-based program, or privately purchased from a commercial provider. Tables 3.8.1 and 3.8.2 show that only 1 percent of women and less than 2 percent of men are covered by health insurance. Urban women, women who live in Kampala, those with secondary or higher education, and those from the wealthiest households are the most likely to be covered by some type of health insurance. Men show the same pattern as women. Table 3.8.1 Health insurance coverage: Women Percentage of women age 15-49 with specific types of health insurance coverage, according to background characteristics, Uganda 2011 Background characteristic Mutual health organization/ community- based insurance Privately purchased commercial insurance Other None Number of women Age 15-19 0.3 0.5 0.0 99.2 2,048 20-24 0.4 0.9 0.0 98.7 1,629 25-29 0.2 1.3 0.2 98.4 1,569 30-34 0.1 1.3 0.0 98.6 1,086 35-39 0.1 0.7 0.1 99.1 1,026 40-44 0.4 1.0 0.1 98.4 729 45-49 0.3 0.5 0.0 99.2 587 Residence Urban 0.3 3.4 0.2 96.0 1,717 Rural 0.2 0.3 0.0 99.5 6,957 Region Kampala 0.1 4.6 0.2 95.1 839 Central 1 0.2 0.7 0.2 98.9 956 Central 2 0.0 0.6 0.0 99.4 902 East Central 0.2 0.6 0.0 99.1 869 Eastern 0.1 0.2 0.1 99.6 1,267 Karamoja 0.0 0.3 0.0 99.7 289 North 0.2 0.1 0.0 99.8 735 West Nile 0.0 0.1 0.0 99.9 500 Western 0.1 0.7 0.0 99.2 1,221 Southwest 1.3 0.8 0.0 98.0 1,097 Education No education 0.3 0.1 0.1 99.5 1,120 Primary 0.2 0.2 0.0 99.6 5,152 Secondary + 0.4 2.8 0.1 96.6 2,402 Wealth quintile Lowest 0.1 0.0 0.1 99.8 1,519 Second 0.2 0.2 0.0 99.7 1,579 Middle 0.2 0.2 0.0 99.6 1,608 Fourth 0.1 0.3 0.1 99.5 1,726 Highest 0.5 3.0 0.1 96.4 2,242 Total 0.3 0.9 0.1 98.8 8,674 44 • Characteristics of Respondents Table 3.8.2 Health insurance coverage: Men Percentage of men age 15-49 with specific types of health insurance coverage, according to background characteristics, Uganda 2011 Background characteristic Mutual health organization/ community based insurance Privately purchased commercial insurance Other None Number of men Age 15-19 0.0 0.4 0.0 99.6 554 20-24 0.3 2.0 0.0 97.7 318 25-29 0.8 1.9 0.0 97.3 361 30-34 0.9 3.1 0.0 96.0 323 35-39 0.1 0.7 0.0 99.3 268 40-44 0.0 0.1 0.0 99.9 191 45-49 0.6 1.5 0.3 97.6 157 Residence Urban 0.3 5.2 0.1 94.4 439 Rural 0.4 0.4 0.0 99.2 1,734 Region Kampala 0.2 7.3 0.0 92.4 221 Central 1 0.0 0.6 0.2 99.2 209 Central 2 0.4 0.4 0.0 99.2 236 East Central 0.0 0.6 0.0 99.4 236 Eastern 0.9 0.5 0.0 98.6 289 Karamoja 0.0 0.8 0.0 99.2 55 North 0.0 1.0 0.0 99.0 199 West Nile 0.2 0.0 0.0 99.8 133 Western 0.0 1.3 0.0 98.7 322 Southwest 1.3 0.9 0.0 97.8 273 Education No education 0.0 1.6 0.0 98.4 90 Primary 0.5 0.2 0.0 99.3 1,309 Secondary + 0.2 3.4 0.1 96.4 774 Wealth quintile Lowest 0.8 0.3 0.0 98.9 345 Second 0.0 0.2 0.0 99.8 423 Middle 0.7 0.2 0.0 99.1 402 Fourth 0.2 0.9 0.0 98.9 486 Highest 0.3 4.4 0.1 95.2 517 Total 15-49 0.4 1.4 0.0 98.2 2,173 50-54 0.0 1.2 0.0 98.8 122 Total 15-54 0.4 1.4 0.0 98.3 2,295 3.7 USE OF TOBACCO Smoking and using other forms of tobacco can cause a wide variety of diseases and lead to death. Smoking is a risk factor for cardiovascular disease, lung cancer, and other forms of cancer, and contributes to the severity of pneumonia, emphysema, and chronic bronchitis. Further, secondhand smoke may adversely affect health and aggravate illnesses. In the 2011 UDHS, women and men age 15-49 were asked whether they currently smoke cigarettes and, if so, how many cigarettes they had smoked in the past 24 hours. Those who were not currently smoking cigarettes were asked whether they used any other forms of tobacco, such as a pipe, chewing tobacco, or snuff. Results are shown in Tables 3.9.1 and 3.9.2 for women and men, respectively. Characteristics of Respondents • 45 Table 3.9.1 Use of tobacco: Women Percentage of women age 15-49 who smoke cigarettes or a pipe or use other tobacco products, according to background characteristics and maternity status, Uganda 2011 Background characteristic Uses tobacco Does not use tobacco Number of women Cigarettes Pipe Other tobacco Age 15-19 0.0 0.0 0.5 99.5 2,048 20-24 0.4 0.1 1.1 98.5 1,629 25-29 0.7 0.2 2.1 96.8 1,569 30-34 0.5 0.3 2.2 97.0 1,086 35-39 1.1 1.1 2.4 95.5 1,026 40-44 1.0 1.2 2.8 95.4 729 45-49 2.4 0.7 5.1 92.8 587 Maternity status Pregnant 0.2 0.0 1.9 97.7 1,011 Breastfeeding (not pregnant) 0.6 0.2 2.3 96.9 2,500 Neither 0.7 0.5 1.6 97.3 5,163 Residence Urban 0.3 0.6 0.2 98.8 1,717 Rural 0.7 0.3 2.2 96.8 6,957 Region Kampala 0.2 0.9 0.2 98.8 839 Central 1 0.5 1.3 0.8 97.5 956 Central 2 0.2 0.5 0.2 99.2 902 East Central 0.3 0.0 0.0 99.1 869 Eastern 0.0 0.0 0.0 100.0 1,267 Karamoja 0.3 0.0 35.4 64.4 289 North 0.0 0.0 0.0 100.0 735 West Nile 1.6 0.3 2.6 95.7 500 Western 1.8 0.2 0.9 97.4 1,221 Southwest 1.2 0.4 1.9 96.7 1,097 Education No education 2.1 0.5 9.0 89.1 1,120 Primary 0.5 0.5 1.1 97.9 5,152 Secondary + 0.1 0.1 0.1 99.5 2,402 Wealth quintile Lowest 1.4 0.0 7.7 91.4 1,519 Second 0.9 0.4 0.7 98.1 1,579 Middle 0.6 0.6 0.8 98.0 1,608 Fourth 0.5 0.3 0.8 98.4 1,726 Highest 0.1 0.5 0.2 99.0 2,242 Total 0.6 0.4 1.8 97.2 8,674 46 • Characteristics of Respondents Table 3.9.2 Use of tobacco: Men Percentage of men age 15-49 who smoke cigarettes or a pipe 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, Uganda 2011 Background characteristic Uses tobacco Does not use tobacco Number of men Cigarettes Pipe Other tobacco Age 15-19 1.2 0.4 0.2 98.3 554 20-24 6.5 0.0 3.0 92.4 318 25-29 12.0 0.9 4.7 84.7 361 30-34 19.2 1.3 5.0 77.6 323 35-39 20.9 1.1 8.6 75.7 268 40-44 18.2 1.4 6.1 78.1 191 45-49 28.3 0.0 11.7 67.2 157 Residence Urban 7.9 0.0 0.7 91.8 439 Rural 13.4 0.9 5.4 83.6 1,734 Region Kampala 8.2 0.0 0.0 91.7 221 Central 1 12.6 2.0 3.8 84.9 209 Central 2 9.4 1.6 2.0 87.4 236 East Central 6.1 1.3 0.4 92.7 236 Eastern 11.2 0.1 1.4 88.4 289 Karamoja 5.1 1.6 42.2 53.8 55 North 18.9 0.0 12.1 80.0 199 West Nile 31.1 0.0 16.3 66.3 133 Western 14.3 0.0 1.7 85.0 322 Southwest 9.8 1.1 1.7 88.6 273 Education No education 12.4 2.0 12.5 75.8 90 Primary 15.6 0.8 5.5 81.6 1,309 Secondary + 6.7 0.3 1.8 92.6 774 Wealth quintile Lowest 24.6 0.3 15.4 68.4 345 Second 17.1 0.9 5.7 80.6 423 Middle 11.1 1.2 2.5 87.3 402 Fourth 8.0 0.8 1.7 90.0 486 Highest 5.2 0.3 0.1 94.4 517 Total 15-49 12.3 0.7 4.4 85.3 2,173 50-54 25.1 4.0 9.1 66.1 122 Total 15-54 13.0 0.9 4.7 84.3 2,295 Tables 3.9.1 and 3.9.2 show that tobacco use is more common among Ugandan men than women (15 percent compared with 3 percent). Twelve percent of men age 15-49 smoke cigarettes, while 1 percent smoke pipes, and 4 percent consume other forms of tobacco. Use of tobacco is most common among older men, men living in rural areas, and those with no education. The highest tobacco use is found among men in the lowest wealth quintile (32 percent). Cigarette smoking among men is most prevalent in West Nile region (31 percent), while Karamoja has the highest proportion of men who use other types of tobacco (42 percent). Karamoja also accounts for a large proportion of the women who use tobacco. Among women age 15-49 who smoke cigarettes, 18 percent smoked 3 to 5 cigarettes, and 18 percent smoked 10 or more cigarettes in the previous 24 hours (data not shown). Among men who smoked cigarettes, 28 percent smoked 1 to 2 cigarettes, 32 percent smoked 3 to 5 cigarettes, and 20 percent smoked 10 or more cigarettes in the 24 hours prior to the survey (data not shown). Marriage and Sexual Activity • 47 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 in Uganda, marriage marks the onset of regular exposure to the risk of pregnancy. Therefore, information on age at first marriage is important for understanding fertility. Populations in which age at first marriage is low tend to have early childbearing and high fertility. Table 4.1.1 presents the percent distribution of women and men by current 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 respondents are included in the ‘currently married’ group. Respondents who are currently married, widowed, divorced, or separated are referred to as ‘ever married’. Table 4.1.1 shows that the proportion of women currently in union (married or cohabiting) is 63 percent, the same as in the 2006 UDHS, and a reduction from 67 percent in the 2000-2001 UDHS. Notable, however, is the decrease in the proportion of married women, from 49 percent in 2006 to 36 percent in 2011, and the increase in the proportion of those living together, from 14 percent to 27 percent during the same period. One in four women (24 percent) has never been married, while about 13 percent are divorced, widowed, or separated. The proportion of women who have never married declines sharply with age, and by age 30, almost all women have married. The proportion of women in a formal union increases with age and peaks at age 35-39. The decline after age 40 is the result of widowhood, divorce, and separation. As expected, older women are more likely to be widowed or divorced than younger women. Men age 15-49 are more likely to have never been married (38 percent) than women (24 percent). The proportion of men age 15-49 who are married has declined since the previous survey, from 50 percent in 2006 to 41 percent in 2011. This decline is noticeable among men under 25. Among the ever-married, men are less likely than women to be widowed or separated. This is partly due to remarriage and polygyny. T Key Findings  The median age at marriage for men age 25-49 is 22.3 years, four years older than the median age for women in the same age range, at 17.9 years.  The percentage of women who were first married by age 15 has declined from 19 percent among women currently age 45-49 to 3 percent among women age 15-19.  For Ugandan women, the median age at first sex is about one year less than the median age at first marriage. In contrast, men typically initiate sexual intercourse four years before their first marriage.  Overall, 25 percent of married women in Uganda are in a polygynous union. The percentage of women who are in a polygynous union has declined steadily over the past decade from 32 percent in the 2000-01 to 25 percent in 2011. 48 • Marriage and Sexual Activity Table 4.1.1 Current marital status Percent distribution of women and men age 15-49 by current marital status, according to age, Uganda 2011 Age Marital status Percentage of respondents currently in union Number of respondents Never married Married Living together Divorced Separated Widowed Total WOMEN 15-19 77.3 8.6 11.4 0.1 2.6 0.1 100.0 20.0 2,048 20-24 23.9 31.8 35.5 0.5 7.2 1.0 100.0 67.3 1,629 25-29 5.6 44.6 37.9 0.6 9.9 1.3 100.0 82.5 1,569 30-34 2.3 48.2 32.9 0.9 12.1 3.6 100.0 81.1 1,086 35-39 1.5 51.3 28.6 0.4 11.9 6.3 100.0 79.9 1,026 40-44 0.8 50.8 25.0 1.7 10.6 10.9 100.0 75.8 729 45-49 2.2 46.2 15.8 1.8 15.5 18.5 100.0 62.0 587 Total 24.4 35.6 26.9 0.7 8.6 3.8 100.0 62.5 8,674 MEN 15-19 96.9 0.6 1.2 0.0 1.2 0.0 100.0 1.9 554 20-24 63.4 16.1 15.7 0.4 4.4 0.0 100.0 31.9 318 25-29 19.9 50.6 24.1 1.1 4.0 0.3 100.0 74.6 361 30-34 6.0 61.3 25.9 1.7 4.8 0.4 100.0 87.2 323 35-39 0.9 72.5 17.9 1.0 5.9 1.9 100.0 90.4 268 40-44 0.6 76.2 17.7 1.7 3.9 0.0 100.0 93.8 191 45-49 0.6 78.4 12.7 4.6 3.7 0.0 100.0 91.1 157 Total 15-49 38.4 41.4 15.1 1.1 3.7 0.3 100.0 56.5 2,173 50-54 0.0 75.5 14.4 1.9 7.5 0.7 100.0 89.9 122 Total 15-54 36.3 43.2 15.1 1.1 3.9 0.4 100.0 58.3 2,295 Table 4.1.2 shows the current marital status and type of marriage among women and men age 15-49. One in four women (25 percent) and about one in three men (32 percent) have had a customary marriage, 27 percent of women and 15 percent of men are cohabiting, and 9 percent of women and 8 percent of men 15-49 have had a religious marriage. Just 1 percent, each, of women and men have had a civil marriage. Table 4.1.2 Current marital status and type of marriage Percent distribution of women and men age 15-49 by current marital status and type of marriage, according to age, Uganda 2011 Age Marital status an type of marriage Percentage of respondents currently in union Number of respondents Marriage Living together Never married/ previously married Total Civil marriage Customary marriage Religious marriage WOMEN 15-19 0.2 7.7 0.7 11.4 80.0 100.0 20.0 2,048 20-24 0.9 27.0 4.0 35.5 32.6 100.0 67.3 1,629 25-29 1.3 33.3 10.0 37.9 17.3 100.0 82.5 1,569 30-34 1.7 32.4 14.1 32.9 18.9 100.0 81.1 1,086 35-39 1.4 34.9 15.0 28.6 20.0 100.0 79.9 1,026 40-44 1.4 30.3 19.2 25.0 24.0 100.0 75.8 729 45-49 1.6 26.6 18.1 15.8 38.0 100.0 62.0 587 Total 1.1 25.4 9.1 26.9 37.5 100.0 62.5 8,674 MEN 15-19 0.0 0.4 0.2 1.2 98.1 100.0 1.9 554 20-24 1.0 12.9 2.2 15.7 68.1 100.0 31.9 318 25-29 2.1 42.3 6.2 24.1 25.4 100.0 74.6 361 30-34 0.4 52.1 8.8 25.9 12.8 100.0 87.2 323 35-39 1.7 57.4 13.5 17.9 9.6 100.0 90.4 268 40-44 1.3 53.5 21.4 17.7 6.2 100.0 93.8 191 45-49 1.8 50.4 26.2 12.7 8.9 100.0 91.1 157 Total 15-49 1.0 32.2 8.2 15.1 43.5 100.0 56.5 2,173 50-54 0.9 54.2 20.4 14.4 10.1 100.0 89.9 122 Total 15-54 1.0 33.4 8.8 15.1 41.7 100.0 58.3 2,295 4.2 POLYGYNY Marital unions are predominantly of two types: monogamous and polygynous. The distinction has social significance and probable fertility implications, although the association between union type and fertility is complex and not well understood. Polygyny, the practice of having more than one wife, has Marriage and Sexual Activity • 49 implications for the frequency of sexual intercourse and thus an effect on 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. Overall, 25 percent of married women in Uganda are in a polygynous union. In the 2011 UDHS, 5 percent of women are in a polygynous union with two or more co-wives, compared with 7 percent in 2006. The extent of polygyny reported by women has declined steadily over the last decade from 32 percent in the 2000-01 UDHS to 28 percent in the 2006 UDHS and to 25 percent in 2011. The prevalence of polygynous unions generally increases with age; young women are more likely to be in a monogamous marriage than older women. Eighty-two percent of married women age 15-19 are in a monogamous union as compared with 69 percent of women age 45-49. Rural women are more likely to be in polygynous unions (26 percent) than urban women (20 percent). The regional distribution also shows substantial variation. The prevalence of polygyny is lowest in Central 1 (17 percent) and highest in Karamoja (51 percent). Polygyny also is relatively common in East Central (39 percent), West Nile (31 percent), and Central 2 (27 percent) regions. There is an inverse relationship between education and polygyny. The proportion of currently married women in a polygynous union decreases from 33 percent among women with no education to 20 percent among women with more than secondary education. The relationship between wealth quintile of the household and polygyny is not clear. Data on polygynous unions among currently married men are shown in Table 4.2.2. Seventeen percent of men age 15-54 report having two or more wives. Like women, older men, men living in rural areas, and those with little or no education are more likely to be in polygynous unions than other men. Polygyny is higher among men in Karamoja (27 percent), North (26 percent) and East Central (23 percent) regions. The level of polygyny reported by men age 15-54 has remained constant over the past five years at 17 percent. 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, Uganda 2011 Background characteristic Number of co-wives Total Number of women 0 1 2+ Don't know Missing Age 15-19 82.4 11.1 2.6 3.9 0.0 100.0 409 20-24 80.2 14.3 1.5 4.0 0.0 100.0 1,097 25-29 72.6 19.7 3.7 4.0 0.0 100.0 1,295 30-34 67.4 22.5 6.9 3.0 0.2 100.0 880 35-39 64.7 23.9 8.6 2.8 0.1 100.0 820 40-44 65.1 21.1 10.1 3.7 0.0 100.0 553 45-49 68.7 20.0 9.1 2.2 0.0 100.0 364 Residence Urban 73.5 15.5 4.7 6.3 0.0 100.0 892 Rural 71.5 19.9 5.6 3.0 0.1 100.0 4,526 Region Kampala 73.3 14.9 2.7 9.1 0.0 100.0 397 Central 1 75.9 14.6 2.7 6.8 0.0 100.0 559 Central 2 64.4 20.3 6.4 9.0 0.0 100.0 565 East Central 58.3 27.6 11.1 3.0 0.0 100.0 580 Eastern 80.0 14.4 3.8 1.8 0.0 100.0 859 Karamoja 48.4 33.5 17.8 0.3 0.0 100.0 215 North 74.7 22.4 2.7 0.2 0.0 100.0 487 West Nile 67.7 24.3 7.0 0.4 0.5 100.0 330 Western 74.2 17.4 6.3 2.0 0.2 100.0 743 Southwest 79.5 16.2 2.3 2.1 0.0 100.0 681 Education No education 65.4 23.3 9.3 1.9 0.1 100.0 877 Primary 71.8 19.3 5.1 3.7 0.1 100.0 3,313 Secondary + 76.4 15.9 3.6 4.1 0.0 100.0 1,227 Wealth quintile Lowest 71.1 20.9 5.9 2.2 0.0 100.0 1,063 Second 75.5 17.9 4.3 2.3 0.1 100.0 1,101 Middle 73.3 18.9 5.0 2.8 0.1 100.0 1,042 Fourth 67.5 20.8 7.7 4.0 0.0 100.0 997 Highest 71.4 17.8 4.7 6.0 0.1 100.0 1,215 Total 71.8 19.2 5.4 3.5 0.1 100.0 5,418 50 • Marriage and Sexual Activity Table 4.2.2 Number of men's wives Percent distribution of currently married men age 15-49 by number of wives, according to background characteristics, Uganda 2011 Background characteristic Number of wives Total Number of men 1 2+ Age 15-19 * * 100.0 10 20-24 94.7 5.3 100.0 101 25-29 90.7 9.3 100.0 270 30-34 83.0 17.0 100.0 282 35-39 85.4 14.6 100.0 242 40-44 76.8 23.2 100.0 179 45-49 73.5 26.5 100.0 143 Residence Urban 90.5 9.5 100.0 215 Rural 82.9 17.1 100.0 1,014 Region Kampala 94.9 5.1 100.0 96 Central 1 84.9 15.1 100.0 120 Central 2 85.3 14.7 100.0 127 East Central 77.3 22.7 100.0 122 Eastern 85.9 14.1 100.0 199 Karamoja 73.1 26.9 100.0 40 North 73.9 26.1 100.0 117 West Nile 83.6 16.4 100.0 77 Western 86.0 14.0 100.0 183 Southwest 88.9 11.1 100.0 147 Education No education 67.0 33.0 100.0 73 Primary 83.6 16.4 100.0 754 Secondary + 88.7 11.3 100.0 402 Wealth quintile Lowest 80.5 19.5 100.0 243 Second 86.1 13.9 100.0 257 Middle 80.6 19.4 100.0 233 Fourth 83.5 16.5 100.0 247 Highest 90.3 9.7 100.0 248 Total 15-49 84.3 15.7 100.0 1,228 50-54 71.0 29.0 100.0 109 Total 15-54 83.2 16.8 100.0 1,338 Note: An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. 4.3 AGE AT FIRST MARRIAGE Marriage is the leading social and demographic indicator of exposure of women to the risk of pregnancy, especially in the case of low levels of contraceptive use. Early marriages in the Ugandan context, where use of family planning is limited, lead to early childbearing and a longer period of exposure of women to reproductive risks, which lead to high cumulative fertility levels. Table 4.3 shows the percentage of women and men who have married by specific exact ages, according to current age. Although the minimum legal age for a woman to get married is 18 years in Uganda, marriage among young girls is a common practice. Among women age 20-49, 15 percent were married by age 15, and 49 percent were married by age 18. The median age at first marriage among women age 25-49 is 17.9 years and has been fairly stable for the past 30 years. However, the trend has shifted toward fewer women marrying at very young ages. The proportion of women married by age 15 has declined over time, from 19 percent among women currently age 45-49 to 3 percent among women currently age 15-19. Men tend to marry at much older ages than women. Among men age 25-49, only 9 percent were married by age 18, and 25 percent by age 20. The median age at marriage for men age 25-49 is 22.3 years, four years older than the median age for women in the same age range, at 17.9 years. The median age at marriage for men age 25-49 has remained the same in the last five years. Marriage and Sexual Activity • 51 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, Uganda 2011 Current age Percentage first married by exact age: Percentage never married Number of respondents Median age at first marriage 15 18 20 22 25 WOMEN 15-19 3.2 na na na na 77.3 2,048 a 20-24 9.9 39.7 61.2 na na 23.9 1,629 18.9 25-29 14.0 48.0 66.8 79.7 90.7 5.6 1,569 18.2 30-34 18.1 52.4 71.8 83.0 91.6 2.3 1,086 17.8 35-39 16.5 52.9 73.4 84.0 91.4 1.5 1,026 17.7 40-44 21.9 55.6 73.1 84.2 93.2 0.8 729 17.6 45-49 19.3 51.3 70.4 79.5 87.9 2.2 587 17.9 20-49 15.4 48.6 68.3 na na 8.1 6,626 18.1 25-49 17.2 51.5 70.6 82.0 91.1 2.9 4,997 17.9 MEN 15-19 0.0 na na na na 96.9 554 a 20-24 0.8 5.5 16.6 na na 63.4 318 a 25-29 0.6 8.0 24.0 47.6 67.6 19.9 361 22.4 30-34 0.3 12.7 27.3 48.7 68.2 6.0 323 22.2 35-39 0.4 6.9 25.4 46.7 67.3 0.9 268 22.4 40-44 0.0 5.2 23.5 48.5 74.7 0.6 191 22.1 45-49 1.0 7.6 26.7 44.0 61.7 0.6 157 23.0 20-49 0.5 7.9 23.6 na na 18.4 1,619 a 25-49 0.4 8.5 25.4 47.4 68.0 7.4 1,301 22.3 Note: The age at first marriage is defined as the age at which the respondent began living with her/his first spouse/partner. na = Not applicable due to censoring a = Omitted because less than 50 percent of the women or men began living with their spouse or partner for the first time before reaching the beginning of the age group Table 4.4 shows the median age at first marriage for women age 20-49 and age 25-49, and for men age 25-54 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 in these age groups. Women age 25-49 living in urban areas marry about two years later than rural women (20 years compared with 17.6 years). The median age at first marriage is highest in Kampala (20.7 years) and lowest in North region at 16.7 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 25-54 display a pattern like that among women but are not as pronounced. 52 • 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 25-54, according to background characteristics, Uganda 2011 Background characteristic Women age Men age 20-49 25-49 25-54 Residence Urban a 20.0 a Rural 17.8 17.6 21.9 Region Kampala a 20.7 a Central 1 18.2 17.7 23.0 Central 2 17.8 17.6 22.9 East Central 17.3 17.0 22.5 Eastern 17.6 17.5 21.7 Karamoja 18.4 18.6 20.8 North 16.9 16.7 21.4 West Nile 18.1 17.9 22.3 Western 18.1 17.9 21.9 Southwest 18.9 18.6 22.8 Education No education 16.9 16.9 22.3 Primary 17.4 17.4 21.6 Secondary + a 20.8 24.5 Wealth quintile Lowest 17.5 17.5 21.6 Second 17.5 17.4 21.3 Middle 17.8 17.5 22.2 Fourth 17.8 17.5 21.9 Highest a 19.7 a Total 18.1 17.9 22.5 Note: The age at first marriage is defined as the age at which the respondent began living with her/his first spouse/partner a = Omitted because less than 50 percent of the respondents began living with their spouse/partners for the first time before reaching the beginning of the age group 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 UDHS interviewers asked women and men how old they were when they first had sexual intercourse. Table 4.5 shows the percentages of women and men who first had sexual intercourse by specific exact ages. Among women age 25-49, 23 percent first had sexual intercourse before age 15, 64 percent before age 18, and by age 25 the majority of Ugandan women (90 percent) had had sexual intercourse. The median age at first sexual intercourse for women age 25-49 is 16.8 years compared with the median age at first marriage of 17.9 years. This suggests that Ugandan women generally begin sexual intercourse about a year earlier than their first marriage. The median age at first sexual intercourse has increased over the past two decades, from 16.8 years for women currently age 45-49 to 17.5 years for women currently age 20-24. 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 years is 18.6 years, about two 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 30 years. The median age at first sexual intercourse for men age 25-49 years, at 18.6 years, is about four years lower than the median age at first marriage, at 22.3 years. Marriage and Sexual Activity • 53 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, Uganda 2011 Current age Percentage who had first sexual intercourse by exact age: Percentage who never had intercourse Number of respondents Median age at first intercourse 15 18 20 22 25 WOMEN 15-19 12.2 na na na na 54.9 2,048 a 20-24 16.1 57.9 77.1 na na 8.2 1,629 17.5 25-29 19.6 61.7 77.9 86.6 91.1 0.8 1,569 17.0 30-34 23.7 64.2 81.0 88.4 90.8 0.8 1,086 16.8 35-39 22.7 65.4 80.8 86.9 89.5 0.2 1,026 16.7 40-44 27.2 63.2 79.5 84.7 88.2 0.0 729 16.7 45-49 27.5 64.1 81.7 86.1 89.9 0.0 587 16.8 20-49 21.4 62.1 79.2 na na 2.4 6,626 17.0 25-49 23.1 63.5 79.8 86.7 90.1 0.4 4,997 16.8 15-24 13.9 na na na na 34.2 3,677 a MEN 15-19 17.9 na na na na 59.9 554 a 20-24 12.8 42.9 69.5 na na 14.5 318 18.4 25-29 8.8 37.6 65.2 79.5 89.7 3.3 361 18.8 30-34 7.7 39.4 70.6 84.4 91.4 1.1 323 18.5 35-39 8.8 40.2 67.7 81.3 89.8 0.3 268 18.5 40-44 6.2 35.3 66.6 84.1 89.7 0.0 191 18.6 45-49 6.6 39.5 69.8 83.9 90.4 0.0 157 18.5 20-49 8.8 39.3 68.2 na na 3.9 1,619 18.5 25-49 7.9 38.5 67.8 82.3 90.2 1.3 1,301 18.6 15-24 16.0 na na na na 43.3 872 a 20-54 8.7 39.6 67.9 na na 3.6 1,741 18.5 25-54 7.8 38.8 67.5 82.4 90.2 1.2 1,423 18.6 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 Table 4.6 shows the median age at first sexual intercourse for women and men by current age and background characteristics. Urban women have their first sexual experience at somewhat older ages than rural women. Examination by region reveals that women of the Eastern and East Central regions engage in sexual relations earliest (16.3 and 16.2 years respectively), while their counterparts in the Southwest region initiate sex about two years later, at age 18.7 years. Women with at least some secondary education start sexual relations almost two years later than less educated women. The relationship between the level of household wealth and the initiation of sexual intercourse is not strong. For men age 25-54, the differences in the median age at first sexual intercourse by background characteristics are minimal. The largest differences are observed by region. Men in the West Nile region and the Southwest region start sexual intercourse later than men in other regions (19.3 and 20.0 years, respectively). 54 • Marriage and Sexual Activity Table 4.6 Median age at first sexual intercourse by background characteristics Median age at first sexual intercourse among women age 20-49 and age 25-49, and median age at first sexual intercourse among men age 20-54 and 25-54, according to background characteristics, Uganda 2011 Background characteristic Women age Men age 20-49 25-49 20-54 25-54 Residence Urban 17.6 17.4 18.4 18.6 Rural 16.8 16.7 18.6 18.5 Region Kampala 17.8 17.6 18.4 18.4 Central 1 16.5 16.3 18.2 18.4 Central 2 16.6 16.5 18.4 18.4 East Central 16.2 15.9 18.4 18.5 Eastern 16.3 16.2 18.4 18.4 Karamoja 17.8 17.9 18.9 19.0 North 16.7 16.6 18.0 18.1 West Nile 17.8 17.6 19.3 19.3 Western 16.9 16.8 18.4 18.3 Southwest 18.7 18.4 a 20.0 Education No education 16.4 16.3 17.9 18.0 Primary 16.6 16.5 18.5 18.5 Secondary + 18.2 18.2 18.8 18.9 Wealth quintile Lowest 16.6 16.6 18.4 18.4 Second 16.9 16.8 18.4 18.4 Middle 16.9 16.6 18.6 18.6 Fourth 16.7 16.5 18.6 18.6 Highest 17.6 17.4 18.6 18.7 Total 17.0 16.8 18.5 18.6 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 4.5 RECENT SEXUAL ACTIVITY In societies with low use of contraception, the probability of a woman becoming pregnant is closely related to the exposure to and frequency of sexual intercourse. 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, 22 percent had been sexually active in the year before the survey but not in the four weeks prior to the interview, and 13 percent had been sexually active at some time in their lives but not for the past one or more years. Fifteen percent of the women had never had sexual intercourse. The highest level of recent sexual activity is observed among women age 25-34 (65 to 67 percent). The proportion of women who are sexually active gradually declines after age 34. The proportion sexually active in the four weeks preceding the survey among women in marital union declines slightly with the number of years in union, from 78 percent among women married for less than five years to 72 percent for women married 25 years or more. Women who were married in the past or who have never been married are less likely to have had sex in the recent past. As expected, women who are currently in union are much more likely to have been sexually active in the four weeks preceding the survey (76 percent) than women who were formerly married (14 percent) or who have never been married (8 percent). Marriage and Sexual Activity • 55 Rural women were more likely to be recently sexually active (52 percent) than urban women (48 percent). Women residing in the North region (56 percent), Western (55 percent), and Central 1 (53 percent) were more likely than women in other regions to have been sexually active in the past four weeks, while women in West Nile (42 percent) were least likely. Women with no education (59 percent) were substantially more sexually active in the recent past than women with some education (46 to 52 percent). Among wealth quintiles the richest women were the least likely to report being sexually active in the past four weeks (49 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, Uganda 2011 Background characteristic Timing of last sexual intercourse Never had sexual intercourse Total Number of women Within the past 4 weeks Within 1 year1 One or more years Missing Age 15-19 18.7 17.8 8.5 0.0 54.9 100.0 2,048 20-24 57.6 25.2 8.9 0.1 8.2 100.0 1,629 25-29 67.2 23.6 8.1 0.2 0.8 100.0 1,569 30-34 65.2 21.9 11.8 0.2 0.8 100.0 1,086 35-39 61.7 22.8 15.1 0.2 0.2 100.0 1,026 40-44 61.6 18.8 19.4 0.2 0.0 100.0 729 45-49 44.6 18.5 36.2 0.8 0.0 100.0 587 Marital status Never married 7.9 18.3 13.4 0.0 60.5 100.0 2,118 Married or living together 75.8 20.5 3.5 0.1 0.0 100.0 5,418 Divorced/separated/widowed 13.6 32.2 53.7 0.5 0.0 100.0 1,134 Marital duration2 Married only once 75.5 20.7 3.6 0.1 0.0 100.0 4,402 0-4 years 77.6 20.8 1.5 0.1 0.0 100.0 1,171 5-9 years 76.2 21.2 2.6 0.0 0.0 100.0 916 10-14 years 75.0 22.2 2.7 0.1 0.0 100.0 818 15-19 years 74.5 19.8 5.7 0.0 0.0 100.0 634 20-24 years 74.2 18.5 6.9 0.5 0.0 100.0 426 25+ years 72.4 20.2 6.9 0.5 0.0 100.0 437 Married more than once 76.8 19.7 3.3 0.2 0.0 100.0 1,018 Residence Urban 47.6 22.7 14.2 0.5 15.1 100.0 1,717 Rural 51.9 21.2 12.1 0.1 14.7 100.0 6,957 Region Kampala 45.4 22.6 16.8 0.1 15.1 100.0 839 Central 1 53.4 20.4 12.0 0.1 14.1 100.0 956 Central 2 51.8 24.3 9.8 0.7 13.5 100.0 902 East Central 51.0 25.9 10.1 0.5 12.5 100.0 869 Eastern 49.6 24.6 12.3 0.0 13.5 100.0 1,267 Karamoja 46.6 20.1 20.8 0.1 12.4 100.0 289 North 56.4 17.6 11.3 0.1 14.5 100.0 735 West Nile 41.6 26.1 15.8 0.1 16.3 100.0 500 Western 55.4 19.5 12.7 0.2 12.2 100.0 1,221 Southwest 51.5 15.4 10.8 0.0 22.2 100.0 1,097 Education No education 58.5 20.0 18.6 0.1 2.9 100.0 1,120 Primary 51.6 21.2 12.0 0.2 14.9 100.0 5,152 Secondary+ 46.3 22.9 10.7 0.2 19.9 100.0 2,402 Wealth quintile Lowest 47.5 25.3 16.6 0.1 10.5 100.0 1,519 Second 54.8 19.9 12.6 0.1 12.5 100.0 1,579 Middle 54.9 21.5 9.1 0.1 14.5 100.0 1,608 Fourth 49.6 20.5 11.0 0.3 18.6 100.0 1,726 Highest 49.1 20.9 13.2 0.3 16.5 100.0 2,242 Total 51.0 21.5 12.5 0.2 14.8 100.0 8,674 Total includes 5 women whose marital status is missing. 1 Excludes women who had sexual intercourse within the last 4 weeks 2 Excludes women who are not currently married Overall, men are as likely as women to have had recent sexual intercourse (Table 4.7.2). Fifty-two percent of men age 15-49 had sexual intercourse in the four weeks before the survey, 21 percent had sexual intercourse in the past year but not in the previous four weeks, 10 percent had sex one or more years ago, and 18 percent have never had sexual intercourse. As with women, men’s recent sexual activity at first increases with age, peaks in the late thirties at 81 percent, and then declines. 56 • Marriage and Sexual Activity As in the case with women, men who are currently married or living with a woman are most likely to have had recent sexual intercourse: 82 percent compared with 11 percent of never-married men. Important variations in sexual activity are observed at the regional level. The proportion of men who had sex in the past four weeks ranges from 41 percent in the West Nile region and 43 percent in Kampala to 58 percent in Karamoja region. Men’s recent sexual activity, like women’s, is inversely related to their level of education. It decreases from 78 percent among men with no education to 52 percent among men with some primary education and to 47 percent among those with secondary education or higher education. Recent sexual activity is least common among the wealthiest men (45 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, Uganda 2011 Background characteristic Timing of last sexual intercourse Never had sexual intercourse Total Number of men Within the past 4 weeks Within 1 year1 One or more years Missing Age 15-19 7.5 15.9 16.7 0.0 59.9 100.0 554 20-24 34.4 34.6 16.5 0.0 14.5 100.0 318 25-29 68.2 22.9 5.5 0.0 3.3 100.0 361 30-34 74.4 20.2 4.4 0.0 1.1 100.0 323 35-39 81.0 14.4 4.2 0.0 0.3 100.0 268 40-44 80.1 16.5 3.4 0.0 0.0 100.0 191 45-49 72.4 20.5 6.5 0.6 0.0 100.0 157 Marital status Never married 10.9 22.2 19.5 0.0 47.3 100.0 834 Married or living together 81.6 17.6 0.8 0.0 0.0 100.0 1,228 Divorced/separated/widowed 26.0 42.8 30.3 0.9 0.0 100.0 111 Marital duration2 Married only once 81.3 18.0 0.7 0.0 0.0 100.0 938 0-4 years 75.3 24.3 0.4 0.0 0.0 100.0 254 5-9 years 78.0 21.1 0.9 0.0 0.0 100.0 207 10-14 years 86.3 13.5 0.2 0.0 0.0 100.0 194 15-19 years 88.1 10.9 1.0 0.0 0.0 100.0 135 20-24 years 85.2 13.2 1.6 0.0 0.0 100.0 98 25+ years 80.2 19.0 0.8 0.0 0.0 100.0 50 Married more than once 82.6 16.1 1.3 0.0 0.0 100.0 291 Residence Urban 47.0 26.9 11.9 0.0 14.1 100.0 439 Rural 52.8 19.1 8.9 0.1 19.2 100.0 1,734 Region Kampala 42.7 27.2 13.7 0.0 16.4 100.0 221 Central 1 53.6 20.5 9.3 0.0 16.5 100.0 209 Central 2 54.3 21.6 8.8 0.0 15.4 100.0 236 East Central 47.9 26.0 8.4 0.0 17.7 100.0 236 Eastern 52.2 23.3 6.3 0.0 18.2 100.0 289 Karamoja 57.8 25.2 4.4 0.0 12.6 100.0 55 North 55.3 17.6 12.1 0.0 15.0 100.0 199 West Nile 41.0 28.3 11.1 0.0 19.6 100.0 133 Western 55.6 15.9 10.2 0.3 18.0 100.0 322 Southwest 54.2 10.4 8.9 0.0 26.4 100.0 273 Education No education 77.9 11.1 5.6 0.0 5.4 100.0 90 Primary 52.4 19.4 8.3 0.1 19.8 100.0 1,309 Secondary + 47.4 23.8 12.0 0.0 16.8 100.0 774 Wealth quintile Lowest 55.7 22.8 5.1 0.3 16.1 100.0 345 Second 55.9 17.0 8.8 0.0 18.3 100.0 423 Middle 56.2 16.0 9.2 0.0 18.6 100.0 402 Fourth 48.0 21.3 11.6 0.0 19.1 100.0 486 Highest 45.3 25.2 11.3 0.0 18.2 100.0 517 Total 15-49 51.6 20.6 9.5 0.0 18.2 100.0 2,173 50-54 67.8 22.1 9.2 0.9 0.0 100.0 122 Total 15-54 52.5 20.7 9.5 0.1 17.2 100.0 2,295 1 Excludes men who had sexual intercourse within the last 4 weeks 2 Excludes men who are not currently married Fertility Levels, Trends, and Differentials • 57 FERTILITY LEVELS, TRENDS, AND DIFFERENTIALS 5 5.1 INTRODUCTION he chapter discusses current, cumulative, and past fertility in terms of levels, patterns, and trends observed in the 2011 UDHS and past DHS surveys. To generate data on fertility, all women who were interviewed were asked to report the total number of sons and daughters to whom they had ever given birth in their lifetime. To ensure all information was reported, women were asked separately about children still living at home, those living elsewhere, and those who had died. A complete birth history was obtained, including information on sex, date of birth, and survival status of each child. For living children, the mother was asked whether the child was living with her or away. For dead children, the age of the child at death was recorded. 5.2 CURRENT FERTILITY The current level of fertility is one of the most important statistics in the report because it represents the prevailing situation and is relevant to population policies and programmes. Table 5.1 presents age-specific fertility rates (ASFRs), the total fertility rate (TFR), the general fertility rate (GFR), and the crude birth rate (CBR) for the three-year period preceding the survey. The ASFRs provide the age pattern of fertility, while the TFR (the most commonly used measure) refers to the number of live births that a woman would have had if she were subject to the current ASFRs throughout the reproductive ages (15-49 years). More generalized indicators of fertility include the general fertility rate (GFR), expressed as the annual number of live births per 1,000 women age 15-44, and the crude birth rate (CBR), expressed as the annual number of live births per 1,000 population. T 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, Uganda 2011 Age group Residence Total Urban Rural 15-19 91 146 134 20-24 205 350 313 25-29 194 318 291 30-34 171 248 232 35-39 87 187 172 40-44 16 82 74 45-49 (2) 26 23 TFR (15-49) 3.8 6.8 6.2 GFR 148 234 217 CBR 40.3 42.4 42.1 Notes: Figures in parentheses are based on 125-249 unweighted person-years of exposure. 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 Key Findings  The total fertility rate in Uganda for the three years preceding the survey is 6.2 children per woman. Rural women have almost twice as many children as urban women.  Fertility declined only slightly between 2000-01 and 2006, from 6.9 children per woman to 6.7 children, and decreased further to 6.2 children in 2011.  Childbearing begins early in Uganda. More than one-third (39 percent) of women age 20-49 gave birth by age 18, and more than half (63 percent) by age 20.  About two thirds (66 percent) of births occur within three years of a previous birth; 25 percent occur within 24 months.  Twenty four percent of women age 15-19 are already mothers or pregnant with their first child. 58 • Fertility Levels, Trends, and Differentials Table 5.1 shows that a Ugandan woman would bear an average of 6.2 children in her lifetime if her fertility were to remain constant at current levels. This represents a decrease of 0.5 children in the 5 years since the 2006 UDHS, when the TFR was 6.7 births per woman. Fertility is significantly higher among rural than urban women (6.8 and 3.8, respectively). However, because of the small proportion of the population living in urban areas (less than 20 percent), the low urban fertility has only minimal impact on fertility for the country as a whole. The table also shows a GFR of 217 live births per 1,000 women and a crude birth rate of 42 live births per 1,000 population. This is a decrease from 230 and 45, respectively, since the 2006 UDHS. Figure 5.1 shows that Uganda and Zambia have the highest TFRs in eastern and southern Africa with 6.2 live births per woman. Figure 5.1 TFR in eastern and southern Africa, DHS surveys 6.9 6.7 6.2 6.1 5.5 6 5.7 5.9 6.2 5.7 5.4 5.4 4.8 5.2 5.5 5.2 4.8 4.9 4.6 4.2 3.6 3.5 3.3 Uganda* 2000-01 2006 2011 Rwanda 2005 2007-08 Malawi 2004 2010 Zambia 2001-02 2007 Tanzania 2004-05 2010 Ethiopia 2005 2011 Mozambique 1997 2003 Madagascar 2003-04 2008-09 Kenya 2003 2008-09 Namibia 2000 2006-07 Lesotho 2004 2009 Total Fertility RateTotal Fertility Rate * In the 2000-2001 UDHS, areas making up the districts of Amuru, Nwoya, Bundibugyo, Ntoroko, Gulu, Kasese, Kitgum, Lamwo, Agago, and Pader were excluded from the sample. These areas contained about 5 percent of the national population of Uganda. Thus, the trends need to be viewed in that light. 5.3 FERTILITY DIFFERENTIALS BY BACKGROUND CHARACTERISTICS As observed in earlier surveys, fertility varies by the respondent’s characteristics, such as residence and education. In this report, fertility differentials are measured using the TFR, the percentage of women age 15-49 who are currently pregnant, and the mean number of children ever born to women age 40-49. The mean number of births to women age 40-49 is an indicator of cumulative fertility; reflecting the fertility performance of older women approaching the end of their reproductive span. If fertility remains stable over time, the TFR and the number of children ever born tend to be very similar. The percentage of women pregnant provides a useful additional measure of current fertility, though it may not capture pregnancies in early stages because early pregnancies are often undetected. Fertility Levels, Trends, and Differentials • 59 Table 5.2 shows substantial variations across background characteristics. By region, the TFR in Kampala, which is mostly urban, is almost half the national level (3.3 and 6.2, respectively). Since the 2006 UDHS, the TFRs in the Eastern, East Central, and West Nile regions have remained above the national level (7.5, 6.9, and 6.8, respectively). The difference between the TFR and completed fertility is an indicator of the magnitude and direction of fertility. Table 5.2 shows that the difference between the mean number of children ever born to women age 40-49 and TFR is one child, 0.4 higher than that in the 2006 UDHS (0.6), reflecting a larger decline in fertility in the last five years than in the previous five years. Women’s education and their household wealth status show a strong negative relationship with their fertility level. Women with no education have on average 6.9 children compared with 4.8 children for women with more than secondary education. Similarly, the TFR decreases from 7.9 children among women in the lowest wealth quintile to 4.0 children among women in the highest wealth quintile. 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 years, by background characteristics, Uganda 2011 Background characteristic Total fertility rate Percentage women age 15-49 currently pregnant Mean number of children ever born to women age 40-49 Residence Urban 3.8 8.2 5.5 Rural 6.8 12.5 7.5 Region Kampala 3.3 8.3 5.0 Central 1 5.6 9.9 7.2 Central 2 6.3 9.6 7.1 East Central 6.9 13.7 7.9 Eastern 7.5 12.5 7.5 Karamoja 6.4 18.7 7.5 North 6.3 12.4 7.3 West Nile 6.8 10.4 7.4 Western 6.4 13.2 7.4 Southwest 6.2 11.3 7.2 Education No education 6.9 11.9 7.7 Primary 6.8 12.3 7.4 Secondary+ 4.8 10.1 5.5 Wealth quintile Lowest 7.9 15.2 7.8 Second 7.1 14.6 7.6 Middle 6.9 12.4 7.8 Fourth 6.1 9.2 7.3 Highest 4.0 8.5 5.7 Total 6.2 11.7 7.2 Note: Total fertility rates are for the period 1 to 36 months prior to interview. 60 • Fertility Levels, Trends, and Differentials 5.4 FERTILITY TRENDS One way to examine trends in fertility is to use retrospective data from the birth histories collected in the 2011 UDHS. Table 5.3.1 shows age-specific fertility rates for successive five-year periods preceding the 2011 UDHS. Because women age 50 and older were not interviewed in the survey, the rates are successively truncated as the number of years before the survey increases. Fertility rates are lower in every age group during the period zero to four years before the survey than they are in the period five to nine years before the survey, suggesting a recent decline in fertility. In the 2011 UDHS, as in the 2006 UDHS, the largest decline is in age group 15-19. 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, Uganda 2011 Mother's age at birth Number of years preceding survey 0-4 5-9 10-14 15-19 15-19 146 173 207 211 20-24 304 319 334 349 25-29 298 318 329 342 30-34 243 284 283 [295] 35-39 182 212 [236] 40-44 82 [130] 45-49 [26] Note: Age-specific fertility rates are per 1,000 women. Estimates in brackets are truncated. Rates exclude the month of interview. Another way to examine fertility trends is to compare current estimates with earlier surveys. Table 5.3.2 and Figure 5.2 show the ASFRs for the 2000-01, 2006, and 2011 surveys. In the 2000-2001 UDHS, areas making up the districts of Amuru, Nwoya, Bundibugyo, Ntoroko, Gulu, Kasese, Kitgum, Lamwo, Agago, and Pader were excluded from the sample. These areas contained about 5 percent of the national population of Uganda. Thus, the trends need to be viewed in that light. The largest differences are observed in the age group 15-19. The ASFR for this age group has declined steadily from 178 in the 2000-01 UDHS to 134 in the 2011 UDHS, indicating a trend towards later age at marriage, first intercourse, and first birth. ASFRs in other age groups have changed more gradually. Table 5.3.2 Trends in age-specific and total fertility rates, Uganda 2000-01, 2006, 2011 Age-specific and total fertility rates (TFR) for the three-year period preceding several surveys Mother’s age at birth 2000-2001 UDHS1 2006 UDHS 2011 UDHS 15-19 178 152 134 20-24 332 309 313 25-29 298 305 291 30-34 259 258 232 35-39 187 190 172 40-44 76 94 74 45-49 40 26 23 TFR 6.9 6.7 6.2 Note: Age-specific fertility rates are per 1,000 women. 1 In the 2000-2001 UDHS, areas making up the districts of Amuru, Nwoya, Bundibugyo, Ntoroko, Gulu, Kasese, Kitgum, Lamwo, Agago, and Pader were excluded from the sample. These areas contained about 5 percent of the national population of Uganda. Thus, the trends need to be viewed in that light. Fertility Levels, Trends, and Differentials • 61 Figure 5.2 Trends in fertility , , , , , , , ) ) ) ) ) ) ) ' ' ' ' ' ' ' 15-19 20-24 25-29 30-34 35-39 40-44 45-49 Mother's age at birth 0 50 100 150 200 250 300 350 R at e (p er 1 ,0 00 w om en ) 2000-01 2006 2011' ) , Note: In the 2000-2001 UDHS, areas making up the districts of Amuru, Nwoya, Bundibugyo, Ntoroko, Gulu, Kasese, Kitgum, Lamwo, Agago, and Pader were excluded from the sample. These areas contained about 5 percent of the national population of Uganda. Thus, the trends need to be viewed in that light. 5.5 CHILDREN EVER BORN AND LIVING Table 5.4 gives the percent distribution of women by the number of children ever born for all women and women currently married, by five-year age groups. The table also presents the mean number of children ever born. In Uganda childbearing starts early and is nearly universal. Eight in ten women age 15-19 have never given birth compared with only one in four women age 20-24. In the subsequent age groups the percentage of women who have never given birth drops to 5 percent or lower. The mean number of children ever born among women age 15-19 has remained at 0.2 live births per woman since the 2006 UDHS. By her late twenties, a woman in Uganda has given birth to more than three children and by her late thirties to more than six children. These findings are similar to those of the 2006 UDHS. Currently married women have had more births than all women in all age groups. The largest difference is still in the youngest age groups (15-19) because a large number of unmarried young women are not exposed to the risk of pregnancy. Currently married women age 15-19 have an average of almost one child compared with 0.2 children for all women. Differences at older ages reflect the impact of marital dissolution through divorce and widowhood. The last column in Table 5.4 shows the mean number of children who survive. The difference between the mean number of children ever born and living children is an indicator of the level of mortality in the population. 62 • Fertility Levels, Trends, and Differentials Because voluntary childlessness is rare in Uganda, it is assumed that most married women with no births are unable to physiologically bear children. The percentage of women who are childless at the end of the reproductive period is an indirect measure of primary infertility (the proportion of women who are unable to bear children at all). Table 5.4 shows that primary infertility is low and has remained the same at about 3 percent since the 2006 UDHS. 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, Uganda 2011 Age Number of children ever born Total Number of women Mean number of children ever born Mean number of living children 0 1 2 3 4 5 6 7 8 9 10+ ALL WOMEN 15-19 81.9 13.3 4.0 0.7 0.0 0.0 0.0 0.0 0.0 0.0 0.0 100.0 2,048 0.24 0.22 20-24 23.9 24.9 27.6 16.1 6.3 1.1 0.0 0.2 0.0 0.0 0.0 100.0 1,629 1.60 1.47 25-29 4.8 9.4 18.3 20.1 22.9 14.6 7.4 2.0 0.5 0.1 0.0 100.0 1,569 3.34 3.04 30-34 2.9 3.3 7.0 9.8 16.0 18.2 17.2 16.1 6.6 2.2 0.6 100.0 1,086 4.97 4.37 35-39 1.6 1.7 4.2 5.8 9.8 12.0 16.0 17.6 14.2 8.8 8.4 100.0 1,026 6.27 5.37 40-44 1.2 1.8 2.8 4.8 6.1 7.6 13.7 14.1 16.1 13.9 18.0 100.0 729 7.13 6.00 45-49 3.4 2.0 3.4 4.4 4.9 8.7 10.9 9.6 13.3 12.5 26.9 100.0 587 7.36 5.96 Total 25.6 10.4 11.3 9.4 9.3 7.8 7.3 6.3 4.9 3.4 4.4 100.0 8,674 3.42 2.97 CURRENTLY MARRIED WOMEN 15-19 38.0 40.2 18.9 2.9 0.0 0.0 0.0 0.0 0.0 0.0 0.0 100.0 409 0.87 0.80 20-24 8.7 26.0 33.0 21.8 8.6 1.5 0.0 0.2 0.0 0.0 0.0 100.0 1,097 2.01 1.84 25-29 1.5 7.4 17.5 20.6 24.7 16.6 8.6 2.3 0.6 0.2 0.0 100.0 1,295 3.60 3.27 30-34 1.0 2.7 5.8 8.7 14.9 18.6 18.8 18.6 7.7 2.4 0.8 100.0 880 5.27 4.64 35-39 1.1 1.2 3.3 5.3 8.6 10.9 16.3 19.5 14.6 10.0 9.1 100.0 820 6.50 5.59 40-44 0.7 1.2 1.7 4.5 5.3 7.9 11.5 14.6 15.9 15.1 21.4 100.0 553 7.47 6.33 45-49 2.8 1.3 2.8 2.6 4.0 7.6 7.6 9.3 13.0 14.4 34.6 100.0 364 7.98 6.53 Total 5.6 10.9 14.1 12.4 12.2 10.3 9.3 8.7 6.1 4.5 6.0 100.0 5,418 4.47 3.90 5.6 BIRTH INTERVALS Birth interval is the length of time between two live births. The recommended interval before the any two births is at least two years, to reduce morbidity and mortality risks for the mother and baby. Research has shown that short birth intervals are closely associated with poor health of children, especially during infancy. Longer birth intervals, on the other hand, contribute to improved health status of both mother and child. They allow the mother to recover physically and emotionally before she becomes pregnant again and must face the demands of another pregnancy and birth, with the added stressors of breastfeeding and child care. The study of birth intervals uses two measures, namely median birth interval and proportion of non-first births that occur both before and after an interval of 24 months after the previous birth. 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 last birth. The findings in Table 5.5 indicate that a quarter of non-first births (25 percent) occur within 24 months of the previous birth, 41 percent occur between 24 and 35 months, 18 percent between 36 and 47 months, and 16 percent after 48 months (four or more years). The overall median birth interval is 30.2 months. These findings show a very slight change in the birth intervals over time. The proportion of births with an interval of 48 months or longer from a preceding birth has increased from 13 percent in 2000-01 to 16 percent in 2011, while the proportion of births within an interval of less than 24 months has decreased from 28 percent in 2000-01 to 25 percent in both 2006 and 2011. Fertility Levels, Trends, and Differentials • 63 Similar to the findings of the 2006 UDHS, younger women are more likely than older women to have shorter birth intervals (less than 24 months). The median birth interval increases with age from 25.9 months among women age 15-19 to 34 months among women age 40.and over. The median birth interval does not vary by the sex of the preceding birth or the birth order. However, median birth intervals do vary by the survival of the preceding birth. The median interval for births following a child that died is 24.5 months compared with 30.6 months for births following a surviving birth. Births in rural areas have a median birth interval of 29.8 months compared with 35.1 months for births in urban areas. There are variations in birth intervals across regions. Kampala has the longest median birth interval (37.5 months) compared with other regions. East Central, Eastern, and Karamoja regions have the shortest median interval (28 months or less). There is no clear pattern in the variation by education and wealth. 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, Uganda 2011 Background characteristic Months since preceding birth Total Number of non- first births Median number of months since preceding birth 7-17 18-23 24-35 36-47 48-59 60+ Age 15-19 15.5 23.5 38.3 15.3 5.7 1.8 100.0 107 25.9 20-29 10.0 17.8 43.8 17.6 5.8 5.1 100.0 3,348 28.8 30-39 8.1 14.5 37.9 18.1 9.2 12.2 100.0 2,547 32.0 40-49 5.8 14.8 34.1 19.9 7.8 17.6 100.0 635 34.0 Sex of preceding birth Male 9.2 16.7 40.6 17.8 6.9 8.7 100.0 3,294 30.1 Female 8.7 16.0 40.4 18.0 7.6 9.3 100.0 3,343 30.4 Survival of preceding birth Living 6.8 16.0 42.2 18.4 7.5 9.1 100.0 5,990 30.6 Dead 28.3 19.7 24.4 14.2 5.2 8.1 100.0 648 24.5 Birth order 2-3 9.3 17.0 39.1 18.5 6.9 9.2 100.0 2,508 30.1 4-6 8.5 15.4 42.6 17.5 6.9 9.2 100.0 2,533 30.3 7+ 9.0 16.9 39.3 17.9 8.4 8.4 100.0 1,596 30.1 Residence Urban 8.2 14.1 29.6 17.7 12.2 18.1 100.0 804 35.1 Rural 9.0 16.7 42.0 18.0 6.6 7.7 100.0 5,833 29.8 Region Kampala 6.1 16.8 24.5 18.8 10.3 23.6 100.0 318 37.5 Central 1 7.9 14.0 41.1 17.4 6.6 13.0 100.0 653 30.6 Central 2 11.2 16.8 35.5 17.8 7.4 11.4 100.0 690 31.3 East Central 12.7 17.5 42.0 15.8 4.8 7.1 100.0 792 28.1 Eastern 9.4 18.9 41.9 16.8 6.8 6.1 100.0 1,110 28.4 Karamoja 14.8 20.9 40.8 14.9 5.8 2.8 100.0 273 27.5 North 5.7 11.7 46.7 21.3 8.1 6.6 100.0 611 32.4 West-Nile 6.5 11.8 45.7 20.8 7.2 8.0 100.0 393 31.8 Western 8.1 16.9 37.1 17.9 10.5 9.6 100.0 992 30.8 Southwest 7.2 16.6 44.1 19.0 5.6 7.5 100.0 807 30.3 Education No education 10.3 12.9 41.0 20.6 6.9 8.3 100.0 1,095 31.2 Primary 8.4 18.0 42.0 16.8 7.0 7.7 100.0 4,326 29.5 Secondary+ 9.5 13.4 34.7 19.7 8.6 14.0 100.0 1,217 32.5 Wealth quintile Lowest 9.9 17.2 42.9 18.2 6.4 5.4 100.0 1,564 29.7 Second 8.4 16.4 44.7 17.1 6.6 6.9 100.0 1,440 29.8 Middle 9.5 18.4 41.7 17.0 6.8 6.6 100.0 1,335 29.1 Fourth 8.7 14.4 40.2 18.4 7.7 10.6 100.0 1,198 30.8 Highest 7.9 14.8 30.4 19.2 9.7 18.0 100.0 1,099 34.4 Total 8.9 16.4 40.5 17.9 7.3 9.0 100.0 6,637 30.2 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. 64 • Fertility Levels, Trends, and Differentials 5.7 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. Table 5.6 shows that the median duration of amenorrhoea among women who gave birth in the three years preceding the survey is 9.4 months and the median duration of postpartum abstinence is 2.4 months. The two factors, postpartum amenorrhoea and abstinence, taken together indicate that the median duration of postpartum insusceptibility to pregnancy is 11 months. Table 5.6 further shows that during the first two months after childbirth, almost all women (99 percent) are insusceptible to pregnancy. The percentage of births in which the mother is amenorrheic, abstaining, and insusceptible is negatively associated with the number of months after a woman gives birth. During the second and third months after giving birth; there is a substantial drop− from 80 percent to 42 percent− in the percentage of women who are protected by postpartum abstinence. Within 12 to 13 months of childbirth, 44 percent of women are insusceptible to pregnancy, 35 percent are amenorrhoeic, and only 13 percent are abstaining from sexual relations. Table 5.7 shows that the median duration of postpartum amenorrhoea is longer among women age 30-49 (10.6 months) than among women 15-29 (8.9 months). The duration of postpartum insusceptibility is also longer among women age 30-49 (12.9 months) than among younger women (10.5 months). However, the median length of postpartum abstinence is the same for younger and older women (2.4). Rural women have a much longer period of postpartum amenorrhoea than urban women (10 and 6.1 months, respectively) and longer median period of postpartum insusceptibility (11.7 and 7 months, respectively). The median length of postpartum abstinence for both rural and urban women is the same (2.4 months). There are considerable regional variations in postpartum amenorrhoea and insusceptibility. The median duration of postpartum amenorrhoea ranges from 4.4 months in Kampala to 14.8 months in West Nile, while postpartum abstinence ranges from 1.3 months in Southwest to 5.5 months in Karamoja. Postpartum insusceptibility ranges from 4.6 months in Kampala to 16.2 months in West Nile. 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, Uganda 2011 Months since birth Percentage of births for which the mother is: Number of births Amenorrhoeic Abstaining Insusceptible1 < 2 98.3 79.6 98.9 241 2-3 82.8 42.1 85.8 293 4-5 67.7 27.7 72.1 282 6-7 65.5 17.2 69.9 298 8-9 48.5 19.7 56.0 263 10-11 49.4 15.0 54.8 295 12-13 35.0 13.4 44.2 252 14-15 27.9 14.0 33.4 264 16-17 16.5 6.9 20.5 250 18-19 14.1 8.1 20.0 232 20-21 9.6 5.1 13.2 261 22-23 6.1 4.8 9.3 295 24-25 4.2 1.8 5.2 275 26-27 3.0 3.8 5.5 275 28-29 1.5 3.1 4.7 252 30-31 0.9 3.0 3.8 250 32-33 2.5 1.1 3.5 282 34-35 0.0 1.3 1.3 262 Total 30.1 14.8 33.9 4,821 Median 9.4 2.4 11.0 na Mean 10.9 5.7 12.3 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 • 65 The median duration of amenorrhoea and insusceptibility generally declines as the woman’s education and household wealth increase. For example, postpartum amenorrhoea lasts 12.7 months among women from the lowest quintile compared with 5.6 months among women from the highest wealth quintile. 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, Uganda 2011 Background characteristic Postpartum amenorrhoea Postpartum abstinence Postpartum insusceptibility1 Mother's current age 15-29 8.9 2.4 10.5 30-49 10.6 2.4 12.9 Residence Urban 6.1 2.4 7.0 Rural 10.0 2.4 11.7 Region Kampala 4.4 2.4 4.6 Central 1 6.4 2.0 7.2 Central 2 9.2 2.4 9.5 East Central 9.4 2.4 10.8 Eastern 9.8 3.4 11.2 Karamoja 12.8 5.5 14.7 North 12.6 2.5 13.2 West Nile 14.8 4.0 16.2 Western 8.7 1.7 9.9 Southwest 11.3 1.3 12.5 Education No education 13.3 2.9 14.3 Primary 10.0 2.3 11.4 Secondary+ 6.5 2.7 8.5 Wealth quintile Lowest 12.7 4.1 14.1 Second 9.8 2.3 10.4 Middle 8.8 2.0 9.7 Fourth 9.2 2.3 11.4 Highest 5.6 2.3 7.0 Total 9.4 2.4 11.0 Note: Medians are based on the status at the time of the survey (current status) 1 Includes births for which mothers are either still amenorrhoeic or still abstaining (or both) following birth 5.8 MENOPAUSE Another factor influencing the risk of pregnancy is menopause. Women are considered menopausal if they are neither pregnant nor postpartum amenorrhoeic, and if they have not had a menstrual period in the six months preceding the survey. Table 5.8 indicates that overall, 9 percent of women age 30-49 in Uganda are menopausal. The proportion of women who are menopausal increases with age, ranging from 3 percent of women age 30-34 to 40 percent of women age 48-49. 5.9 AGE AT FIRST BIRTH The age at which childbearing starts has important consequences for the overall level of fertility as well as the health and welfare of the mother and the child. Today, teenage pregnancy and motherhood are a major health and social concern. In some societies, the postponement of age at marriage and age at first birth has contributed to overall fertility decline. However, in many societies, it is common for women to have children before getting married. Table 5.8 Menopause Percentage of women age 30-49 who are menopausal, by age, Uganda 2011 Age Percentage menopausal1 Number of women 30-34 2.6 1,086 35-39 4.0 1,026 40-41 9.3 356 42-43 10.2 265 44-45 15.1 245 46-47 19.5 187 48-49 39.7 263 Total 9.0 3,428 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 66 • Fertility Levels, Trends, and Differentials Table 5.9 shows that the median age at first birth among women age 20-49 is 18.9 years, similar to the median age reported in the 2006 UDHS. Women age 15-19 are left out in the presentation because less than 50 percent had given birth before age 15. The last column in Table 5.9 shows that the initiation of child bearing in Uganda has not changed much over time. The median age at first birth for women age 20-24 is 19.3 years compared with 18.9 years or younger for older women. Table 5.9 Age at first birth Percentage of women age 15-49 who gave birth by exact ages, percentage who have never given birth, and median age at first birth, according to current age, Uganda 2011 Current age Percentage who gave birth by exact age Percentage who have never given birth Number of women Median age at first birth15 18 20 22 25 15-19 1.7 na na na na 81.9 2,048 a 20-24 6.6 33.0 57.3 na na 23.9 1,629 19.3 25-29 8.3 39.3 63.1 78.4 91.8 4.8 1,569 18.9 30-34 10.0 43.7 68.9 81.3 91.7 2.9 1,086 18.5 35-39 9.8 42.1 65.3 82.3 91.8 1.6 1,026 18.7 40-44 13.0 42.8 65.2 82.9 93.4 1.2 729 18.6 45-49 11.0 38.2 59.9 76.1 87.0 3.4 587 18.9 20-49 9.2 39.2 62.9 na na 8.2 6,626 18.9 25-49 10.0 41.2 64.8 80.2 91.4 3.0 4,997 18.7 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 As shown in Table 5.10, urban women, women in Kampala and Southwest, women with secondary or higher education, and women in the highest wealth quintile have their first child at age 20, a later age than other women. There is a clear positive relationship between a woman’s education and the initiation of child bearing. Women with at least secondary education on average start giving birth at age 20.8 years, 2.7 years later than women with no education. Table 5.10 Median age at first birth Median age at first birth among women age 20-49 (25-49) years, according to background characteristics, Uganda 2011 Background characteristic Women age Women age 20-49 25-49 Residence Urban a 19.6 Rural 18.7 18.6 Region Kampala a 20.2 Central 1 18.5 18.1 Central 2 18.3 18.2 East Central 18.1 17.9 Eastern 18.6 18.7 Karamoja 19.2 19.4 North 17.9 17.8 West-Nile 19.5 19.4 Western 18.8 18.8 Southwest a 20.0 Education No education 18.1 18.1 Primary 18.3 18.3 Secondary+ a 20.8 Wealth quintile Lowest 18.4 18.5 Second 18.5 18.5 Middle 18.8 18.6 Fourth 18.5 18.3 Highest a 19.6 Total 18.9 18.7 a = Omitted because less than 50 percent of the women had a birth before reaching the beginning of the age group Fertility Levels, Trends, and Differentials • 67 5.10 TEENAGE PREGNANCY AND MOTHERHOOD Teenage pregnancy and motherhood has remained a major health and social concern in Uganda because of its association with higher morbidity and mortality for both the mother and child. In addition to the physiological risks, there is a negative effect on the socioeconomic status of the mother, and hence the child, because current school policy is to have pregnant girls terminate their education. Table 5.11 shows that 24 percent of teenagers have begun childbearing: 18 percent of them have had a live birth and 6 percent are carrying their first child. The findings show that the proportion of teenagers who have started childbearing has declined over time, from 43 percent in the 1995 UDHS, to 31 percent in the UDHS 2000-01, to 25 percent in the 2006 UDHS, and finally, to 24 percent in 2011. As expected, the percentage of women who have started their reproductive life increases with age because of longer exposure, from 2 percent of women age 15 to 58 percent of women age 19. Rural teenagers start parenthood earlier than their urban counterparts (24 percent versus 21 percent, respectively). Teenage pregnancy also varies greatly with a woman’s education. Sixteen percent of girls with secondary education have begun their reproductive life compared with 45 percent of those with no education. The percentage of teenagers who have begun childbearing varies by region and wealth index of the household. Region wise, East Central, Eastern, and Karamoja regions have the highest percentages compared with other regions (around 30 percent), while Southwest region has the lowest (15 percent). The percentage of teenagers who have begun childbearing in the poorest households is 34 percent compared with only 16 percent in the wealthiest households. 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, Uganda 2011 Background characteristic Percentage of women age 15-19 who: Percentage who have begun childbearing Number of women Have had a live birth Are pregnant with first child Age 15 0.7 0.9 1.6 480 16 5.0 3.5 8.5 414 17 13.1 7.7 20.8 367 18 28.3 9.1 37.4 417 19 48.7 8.8 57.6 370 Residence Urban 16.6 4.8 21.4 395 Rural 18.4 6.0 24.4 1,652 Region Kampala 15.3 6.3 21.6 190 Central 1 17.1 2.0 19.1 230 Central 2 17.5 5.1 22.6 199 East Central 23.6 7.0 30.6 202 Eastern 24.5 5.8 30.3 318 Karamoja 11.5 18.2 29.7 65 North 17.5 8.2 25.6 181 West Nile 19.7 6.6 26.4 127 Western 17.3 5.3 22.6 288 Southwest 11.1 3.4 14.6 249 Education No education 29.9 14.6 44.5 60 Primary 20.9 6.0 26.9 1,327 Secondary+ 11.4 4.4 15.8 661 Wealth quintile Lowest 24.0 10.4 34.4 316 Second 24.9 7.9 32.8 346 Middle 20.0 4.3 24.3 368 Fourth 14.1 5.0 19.1 481 Highest 12.5 3.3 15.8 537 Total 18.1 5.8 23.8 2,048 Fertility Preferences • 69 FERTILITY PREFERENCES 6 he 2011 Uganda DHS included questions to ascertain fertility preferences. Women and men were asked about their desire to have another child, the length of time they would like to wait before having another child, and how many they would consider to be the ideal number of children. These fertility preferences were then used to assess future fertility patterns and potential demand for contraception. The information also was used to construct measures of unwanted or mistimed births. 6.1 DESIRE FOR MORE CHILDREN Information about the desire for more children helps predict future reproductive behaviour in Uganda. The provision of adequate and accessible family planning services depends on the availability of such information. In the 2011 UDHS, currently married women and men were asked about their desire to have another child and, if they had such preferences, they were asked how soon they wanted the child. The same question was phrased differently in the case of pregnant women or men whose spouses or partners were pregnant at the time of the interview; the question then focused on desire for subsequent children after completion of the current pregnancy. Sterilized women and men were considered to want no more children, so they were not asked questions about their desire for more children. Table 6.1 shows that 14 percent of women and 19 percent of men age 15-49 want to have another child soon (within two years), while 38 percent of women and 46 percent of men want another child in two or more years. Forty percent of women and 29 percent of men do not want any more children, and 3 percent of women and less than 1 percent of men have already been sterilized. Overall, 3 percent of currently married women and 2 percent of currently married men are undecided about having more children. Fertility preferences have not changed substantially since the 2006 UDHS survey. Fertility preferences relate closely to the number of living children among both women and men. The desire to limit childbearing increases with the number of living children, from 3 percent among married women and men with no children to 72 percent among women and 52 percent among men with six or more children. On the other hand, almost four-fifths of respondents (79 percent of women and 78 percent of men) with no living children want to have a child soon; in comparison, only 3 percent of women and 10 percent of men with six or more children want to have another soon. T Key Findings  About two-fifths (43 percent) of currently married women age 15-49 and one-third (30 percent) of currently married men age 15-49 either want no more children or have been sterilized.  The desire to limit the number of children in a family has increased somewhat among married men and women over the past decade. The ‘ideal’ number of children—5 for women and 6 for men— has not changed over the past 10 years among women and men age 15-49.  The percentage of planned births has decreased from 60 percent in the 2000-01 UDHS to 56 percent in the 2011 UDHS. 70 • 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, Uganda 2011 Desire for children Number of living children Total 15-49 Total 15-54 0 1 2 3 4 5 6+ WOMEN1 Have another soon2 78.9 25.7 17.2 16.7 8.6 8.9 3.4 14.3 na Have another later3 9.4 67.7 63.7 49.3 37.6 27.6 11.9 37.8 na Have another, undecided when 1.3 0.9 1.0 0.7 1.0 0.7 0.5 0.8 na Undecided 0.8 1.5 1.7 3.9 3.3 3.3 2.8 2.7 na Want no more 3.1 3.0 14.3 25.9 46.5 53.3 72.4 39.5 na Sterilized4 0.0 0.0 0.7 2.2 1.6 4.1 6.6 3.0 na Declared infecund 6.4 0.9 1.3 1.1 1.4 2.1 2.3 1.8 na Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 na Number of women 192 660 871 790 738 665 1,502 5,418 na MEN5 Have another soon2 (77.5) 31.0 26.8 21.3 15.8 13.9 9.6 19.3 18.1 Have another later3 (14.3) 67.7 63.3 54.7 50.9 37.7 32.4 46.1 43.1 Have another, undecided when (0.0) 0.9 0.5 0.1 3.2 1.2 1.9 1.4 1.3 Undecided (0.0) 0.4 1.3 4.0 4.2 2.3 2.4 2.4 2.7 Want no more (2.6) 0.0 6.6 17.3 24.9 45.0 52.0 29.4 32.8 Sterilized4 (0.0) 0.0 0.0 0.0 0.0 0.0 1.1 0.4 0.6 Declared infecund (4.4) 0.0 1.4 0.3 1.0 0.0 0.2 0.6 0.9 Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 Number of men 39 118 194 155 172 133 418 1,228 1,338 na =Not applicable Figures in parentheses are based on 25-49 unweighted cases. 1 The number of living children includes the current pregnancy. 2 Wants next birth within two years 3 Wants to delay next birth for two or more years 4 Includes both female and male sterilization 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). 6.2 DESIRE TO LIMIT CHILDBEARING BY BACKGROUND CHARACTERISTICS Table 6.2 shows the percentage of currently married women who want no more children (or who are sterilized), by number of living children and background characteristics. Currently married rural women are more likely to want to limit childbearing than their counterparts in urban areas (44 percent versus 37 percent). However, among women with one or more living children, urban women are more likely than rural women to want to limit childbearing. Among regions, married women in Southwest (50 percent) are the most likely to want to limit childbearing, and women in Karamoja are the least likely (27 percent). Overall, the desire to limit childbearing decreases with increasing education. About half of women (53 percent) with no education want to limit the size of their families compared with about one-third (32 percent) of those with secondary or higher education. However, among women with 4, 5, and 6 living children, there is a clear pattern of those with more education being more likely to want no more children. There is no clear pattern in the variation of this indicator by women’s wealth. For all background characteristics, the desire to limit childbearing among currently married women increases with an increase in the number of living children. Fertility Preferences • 71 Table 6.2 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, Uganda 2011 Background characteristic Number of living children1 Total 0 1 2 3 4 5 6+ Residence Urban 1.0 3.9 19.9 39.6 58.6 70.1 83.0 36.6 Rural 3.7 2.7 13.4 25.6 46.3 55.5 78.6 43.6 Region Kampala (0.0) 4.6 24.9 43.6 62.5 (74.1) (81.2) 34.6 Central 1 * 0.5 9.4 42.2 49.8 41.4 73.8 40.6 Central 2 * 8.7 14.7 22.1 41.4 64.1 74.2 41.6 East Central * 3.6 6.6 27.2 40.2 55.8 80.5 45.7 Eastern * 3.4 16.6 26.2 47.2 56.4 85.5 46.2 Karamoja * 1.7 12.5 21.2 33.9 35.8 43.1 27.3 North * 2.9 6.8 20.4 56.8 57.3 82.2 45.0 West Nile * 1.8 12.9 24.4 36.8 62.7 74.8 37.9 Western * (2.1) 12.3 20.7 46.1 51.6 79.1 39.8 Southwest * 0.0 23.1 27.3 58.9 73.1 84.1 50.0 Education No education (0.0) 7.6 14.8 27.2 39.6 51.7 77.7 53.2 Primary 0.9 2.9 13.6 28.2 44.5 57.4 79.1 43.4 Secondary + 8.4 2.5 17.4 28.3 63.7 65.1 82.3 32.4 Wealth quintile Lowest 0.0 2.9 14.3 19.1 47.0 51.6 75.9 40.8 Second 0.0 4.0 15.8 23.5 52.9 57.5 78.1 43.5 Middle 2.9 2.3 9.9 25.4 31.9 57.1 83.2 43.8 Fourth 0.0 2.6 17.2 34.7 44.1 51.5 78.2 46.7 Highest 7.7 3.0 16.6 36.4 60.7 69.5 79.1 38.3 Total 3.1 3.0 15.0 28.1 48.1 57.3 79.0 42.5 Note: Women who have been sterilized are considered to want no more children. Figures in parentheses are based on 25-49 unweighted cases. An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. 1 The number of living children includes any current pregnancy. 6.3 IDEAL FAMILY SIZE In the preceding section of this chapter, the discussion concentrated on the respondents’ current childbearing preferences. These preferences are influenced by the number of children a respondent already has. The 2011 UDHS asked women and men about the total number of children they would like to have in their lifetime. For respondents who already had living children, the question was posed hypothetically: ‘If you could go back to the time when you did not have any children and could choose exactly the number of children to have in your whole life, how many would that be?’ Even though this question is based on a hypothetical situation, it provides two measures. First, for women and men who have not yet started a family, the findings point to the respondent’s ideal future fertility. Second, for older and high-parity women, the excess of past fertility reflects the difference between the desired and unwanted fertility. This information helps family planners understand the potential demand for fertility control in Uganda. Table 6.3 shows that almost all women (97 percent) and men (99 percent) were able to provide a numeric response to the question when asked to assess the ideal family size. Both women and men age 15- 49 in Uganda prefer a relatively big family (4.8 children for women and 5.7 children for men). The ideal family size is even higher among currently married respondents age 15-49 when compared with all respondents: 5.1 children for currently married women and 6.6 children for currently married men. The majority of women and men (81 percent of women and 83 percent of men) want four or more children. By contrast, only 2 percent of women and men do not want children or want just one child. Table 6.3 shows that the mean ideal number of children increases with the number of living children among both women and men, from 3.9 children for all women and 4.5 children for all men with no children to 6.1 and 8.5 children among respondents with six or more children. 72 • Fertility Preferences Despite the overall high ideal family size in Uganda, the survey results also reflect evidence of unwanted fertility. For example, 41 percent of women with 6 or more living children say their ideal family size is 5 or fewer. Similarly, one-third of women with 5 children say they ideally would prefer fewer. The mean ideal number of children among women and men has remained almost unchanged since the 2000-01 UDHS that reported an ideal family size of 4.8 for women and 5.6 for men. This finding could also explain why the total fertility rate in Uganda has remained high over the past decade. Table 6.3 Ideal number of children by number of living children Percent distribution of women and men 15-49 by ideal number of children, and mean ideal number of children for all respondents and for currently married respondents, according to the number of living children, Uganda 2011 Ideal number of children Number of living children Total 0 1 2 3 4 5 6+ WOMEN1 0 2.4 0.1 0.4 0.7 0.4 0.1 1.0 1.0 1 1.1 1.0 0.2 0.5 0.6 0.3 0.4 0.7 2 14.2 11.9 6.3 4.7 4.8 3.3 2.8 7.5 3 12.7 15.0 7.3 6.6 3.1 3.8 2.4 7.6 4 44.8 46.4 55.0 42.3 33.5 26.9 22.5 38.6 5 10.2 10.4 11.1 15.3 11.6 11.3 11.6 11.4 6+ 12.9 14.8 18.0 28.5 43.2 50.2 53.7 30.5 Non-numeric responses 1.6 0.4 1.8 1.4 2.6 4.1 5.7 2.7 Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 Number of women 2,083 1,015 1,121 972 914 792 1,777 8,674 Mean ideal number children for:2 All women 3.9 4.1 4.4 4.8 5.2 5.7 6.1 4.8 Number of women 2,050 1,011 1,100 958 890 760 1,676 8,444 Currently married women 4.3 4.2 4.4 4.8 5.1 5.7 6.0 5.1 Number of currently married women 188 658 854 781 721 642 1,419 5,263 MEN3 0 2.1 1.3 0.0 0.0 0.1 1.0 1.3 1.3 1 0.7 0.6 0.4 0.0 0.0 0.6 0.0 0.4 2 7.9 3.7 3.4 3.4 0.9 2.2 1.3 4.5 3 14.1 17.3 10.4 9.7 2.3 3.8 2.6 9.7 4 37.0 45.5 38.5 39.3 19.9 14.4 15.2 30.8 5 16.0 17.6 17.2 17.0 16.2 17.0 8.3 14.9 6+ 21.5 14.1 29.1 29.7 59.8 59.2 67.5 37.1 Non-numeric responses 0.5 0.0 1.0 0.8 0.8 1.7 3.7 1.3 Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 Number of men 871 155 231 172 178 143 424 2,173 Mean ideal number children for:2 All men 4.5 4.5 5.2 5.1 6.2 6.2 8.7 5.7 Number of men 866 155 228 171 177 140 408 2,145 Currently married men (4.1) 4.6 5.2 5.2 6.2 6.1 8.7 6.5 Number of currently married men 39 118 192 154 171 130 402 1,205 Mean ideal number children for men 15-54:2 All men 4.5 4.5 5.2 5.1 6.3 6.2 8.5 5.7 Number of men 867 158 231 177 188 151 489 2,261 Currently married men (4.1) 4.6 5.2 5.2 6.3 6.1 8.6 6.6 Number of currently married men 39 119 193 160 181 140 476 1,309 Note: Figures in parentheses are based on 25-49 unweighted cases. 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). Table 6.4 shows the mean ideal number of children for all women age 15-49, by background characteristics. This increases with the age of the woman, ranging from 4.1 children among women age 15-19 to 6.2 among those age 45-49. The ideal number of children for women is slightly lower among urban women than among rural women (4.1 children versus 5.0 children). Fertility Preferences • 73 There are differences in the mean ideal number of children by region, with the highest number being in Karamoja (7.2 children) and the lowest number in Kampala (4.0 children). The mean ideal number of children is inversely related to education and wealth. It ranges from 6.2 children among women with no education to 4.0 children among women with secondary or higher education. Similarly, women in the lowest wealth quintile want 5.5 children compared with 4.2 children in the highest wealth quintile. Table 6.4 Mean ideal number of children Mean ideal number of children for all women age 15- 49, by background characteristics, Uganda 2011 Background characteristic Mean Number of women1 Age 15-19 4.1 2,023 20-24 4.3 1,610 25-29 4.7 1,545 30-34 5.1 1,057 35-39 5.6 985 40-44 6.0 688 45-49 6.2 536 Residence Urban 4.1 1,689 Rural 5.0 6,755 Region Kampala 4.0 828 Central 1 4.8 906 Central 2 5.0 871 East Central 4.9 851 Eastern 5.0 1,252 Karamoja 7.2 280 North 4.6 728 West Nile 5.1 480 Western 4.9 1,195 Southwest 4.5 1,054 Education No education 6.2 1,055 Primary 4.9 5,013 Secondary + 4.0 2,376 Wealth quintile Lowest 5.5 1,473 Second 4.9 1,530 Middle 4.9 1,568 Fourth 4.9 1,667 Highest 4.2 2,205 Total 4.8 8,444 1 Number of women who gave a numeric response 6.4 FERTILITY PLANNING The analysis of the level of fertility planning in a society provides some insight into the degree to which couples are able to control their fertility. To measure the level of unwanted fertility, women in the UDHS were asked, for all children born in the preceding five years, whether the pregnancy was wanted at the time, wanted at a later time, or not wanted at all. For women who were pregnant at the time of the interview, this question was also asked with reference to the current pregnancy. The procedure required the respondents to recall accurately their wishes at one or more points in the last five years. Care has to be exercised in interpreting these results because an unwanted conception may have become a cherished child, leading to the rationalization of responses to these questions. The rationalization of the responses may result in an underestimate of the true extent of unwanted births. 74 • Fertility Preferences Table 6.5 shows that in the five years preceding the survey, 56 percent of births were planned (wanted then), 32 percent were mistimed (wanted later), and 12 percent were unwanted. Generally, the proportion of planned births decreases and the proportion of unwanted births increases with an increase in the birth order. Sixty-four percent of first-order births were wanted when they occurred compared with 48 percent of fourth and higher-order births. On the other hand, only 2 percent of first-order births were unwanted compared with 21 percent of fourth and higher-order births. The proportion of mistimed births does not vary much by birth order. The proportion of planned births and mistimed births tends to decrease with a woman’s age, while the proportion of unwanted births increases with an increase in women’s age. For example, the percentage of unwanted births increases from 2 percent among mothers below age 20 to 50 percent among mothers age 40-44. 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, Uganda 2011 Birth order and mother's age at birth Planning status of birth Total Number of births Wanted then Wanted later Wanted no more Missing Birth order 1 64.1 34.1 1.5 0.2 100.0 1,609 2 66.3 31.8 1.7 0.1 100.0 1,524 3 62.4 35.0 2.6 0.0 100.0 1,303 4+ 48.4 30.0 21.4 0.1 100.0 4,650 Mother's age at birth <20 58.1 40.0 1.7 0.2 100.0 1,512 20-24 63.7 33.9 2.3 0.1 100.0 2,678 25-29 58.8 33.6 7.5 0.1 100.0 2,208 30-34 48.9 29.4 21.4 0.3 100.0 1,440 35-39 44.3 18.5 37.2 0.0 100.0 918 40-44 36.8 12.5 50.3 0.4 100.0 285 45-49 (20.5) (5.0) (74.5) (0.0) 100.0 45 Total 56.2 31.8 11.9 0.1 100.0 9,086 Note: Figures in parentheses are based on 25-49 unweighted cases. The percentage of planned births has decreased from 60 percent in the 2000-01 UDHS to 56 percent in the 2011 UDHS. On the other hand, the percentage of mistimed births has increased from 25 percent to 32 percent over the same period. 6.5 WANTED FERTILITY RATES The wanted fertility rate measures the potential demographic impact of avoiding unwanted births. It is calculated in the same manner as the total fertility rate but excludes unwanted births from the numerator. A birth is considered wanted if the number of living children at the time of conception is less than the ideal number of children reported by the respondent. The gap between wanted and actual fertility shows how successful women are in achieving their reproductive intentions. This measure also may be an underestimate because women may not want to report an ideal family size that is lower than their actual family size. The total wanted fertility rates in Table 6.6 represent the levels of fertility that would have prevailed in the three years preceding the survey if all unwanted births had been avoided. Overall, women have 1.7 children more than their ideal number (6.2 children compared with 4.5 children). This implies that the total fertility rate (TFR) is higher by almost two children than it would be if unwanted births were avoided. Fertility Preferences • 75 The gap between wanted and observed fertility rates is wider among women who live in rural areas (2.0 children) than among women who live in urban areas (0.6 children). The gap is widest among women residing in East Central region (2.5 children) and narrowest among women living in Kampala (0.4 children). The difference between wanted and observed total fertility rates varies from 1.0 child among women with secondary or higher education to 1.9 children among women with no education or only primary school. There is an inverse relationship between the wanted fertility rate and wealth quintile. The gap between wanted and actual fertility rates ranges from 0.7 children among women in the highest wealth quintile to 2.3 children among women in the lowest wealth quintile. The comparison between the findings of the 2000-01 and 2011 UDHS surveys reveals that the gap between wanted and actual fertility rates has increased slightly, from 1.6 to 1.7 children. Table 6.6 Wanted fertility rates Total wanted fertility rates and total fertility rates for the three years preceding the survey, by background characteristics, Uganda 2011 Background characteristic Total wanted fertility rates Total fertility rate Residence Urban 3.2 3.8 Rural 4.8 6.8 Region Kampala 2.9 3.3 Central 1 4.2 5.6 Central 2 4.6 6.3 East Central 4.4 6.9 Eastern 5.3 7.5 Karamoja 5.8 6.4 North 4.3 6.3 West Nile 5.1 6.8 Western 4.7 6.4 Southwest 4.4 6.2 Education No education 5.0 6.9 Primary 4.9 6.8 Secondary + 3.8 4.8 Wealth quintile Lowest 5.6 7.9 Second 4.9 7.1 Middle 5.0 6.9 Fourth 4.4 6.1 Highest 3.3 4.0 Total 4.5 6.2 Note: Rates are calculated based on births to women age 15-49 in the period 1 to 36 months preceding the survey. The total fertility rates are the same as those presented in Table 5.2. Family Planning • 77 FAMILY PLANNING 7 he government of Uganda is committed to improving family planning use and access in the country as highlighted in various government plans and policies. The five-year National Development Plan (2010/11-2014/15) acknowledges that limited access to family planning services hinders overall development of the society and of women in particular. One of the goals outlined in the plan is to reduce unmet need for family planning by ensuring access to family planning services, especially in rural areas (NPA, 2010). Furthermore, the 2008 National Population Policy urges special emphasis on family planning and reproductive commodity security, including use of contraceptives (MoFPED, 2008). In addition, some of the strategies in the Health Sector Strategic and Investment Plan (2010/11-2014/15) are geared toward improvement of overall sexual and reproductive health and rights of the population. Goals include provision of integrated family planning services in all health facilities at all levels, procurement and distribution of contraceptives to men and women of reproductive age, and design of programmes to engage men in family planning services and use. Budget constraints, however, serve as a major impediment to these interventions (MOH, 2010b). This chapter presents information on knowledge of various contraceptive methods and discusses past and current prevalence. For users of periodic abstinence (the rhythm method), knowledge of the ovulatory cycle is examined; for those relying on sterilization, the timing of the procedure is assessed. Also discussed are the source of modern contraceptive methods, informed choice, discontinuation rates and reasons for discontinuation, unmet need for family planning, nonuse of contraception, and intent to use contraceptive methods in the future. In addition, information is provided on exposure to family planning T Key Findings  Awareness of at least one method of contraception in Uganda is nearly universal.  Three in ten currently married women are using a method of contraception, with most women using a modern method (26 percent).  Injectables remain the most commonly used method of contraception among currently married women (14 percent).  The use of modern methods of family planning has consistently increased over the past decade, growing from 14 percent of currently married women in 2000-01 (excluding LAM) to 26 percent in 2011.  The government sector remains the major provider of contraceptive methods for nearly half of the users of modern contraceptive methods (47 percent).  Forty-three percent of family planning users in Uganda discontinue use of a method within 12 months of starting its use. Fear of side effects is the main reason for discontinuation (16 percent). The pill has the highest discontinuation rate (54 percent).  Only one-third of the users of the rhythm/moon beads method know when the fertile period occurs.  About one-third (34 percent) of currently married women have an unmet need for family planning services, with 21 percent in need of spacing and 14 percent in need of limiting. 78 • Family Planning messages through the media and contact with family planning providers. These topics are of practical use in formulating efficient and effective family planning strategies and policies. Although the focus is on women, some results from the male survey are presented, because men play an important role in the realization of reproduction goals. Comparisons, where possible, are made with findings from the previous surveys to show trends over the last decade. 7.1 KNOWLEDGE OF CONTRACEPTIVE METHODS Knowledge of contraceptive methods is an important precursor to their use. The ability to recognize a family planning method when it is described is a simple test of a respondent’s knowledge but does not necessarily indicate the extent of her or his knowledge. The 2011 UDHS collected information on knowledge of contraception by asking respondents whether or not they had heard about 10 modern methods (female and male sterilization, the pill, intrauterine devices [IUDs], injectables, implants, male and female condoms, lactational amenorrhoea [LAM], and emergency contraception) and two traditional methods (rhythm/moon beads and withdrawal). Respondents were also asked whether they knew about other methods in addition to those listed. Table 7.1 shows that knowledge of at least one contraceptive method is nearly universal in Uganda among both women and men. Modern methods are more widely known than traditional methods; almost all women and men know of a modern method (98 and 100 percent, respectively) compared with 74 percent of all women and 83 percent of all men who know of a traditional method. Among both women and men, the male condom (97 and 99 percent, respectively), injectables (94 and 91 percent), and the pill (93 and 92 percent) are the most well-known modern methods, while LAM (13 and 11 percent) is the least known modern 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, Uganda 2011 Method Women Men All women Currently married women Sexually active unmarried women1 All men Currently married men Sexually active unmarried men1 Any method 98.2 98.7 99.5 99.7 99.9 99.9 Any modern method 98.1 98.6 99.5 99.7 99.8 99.9 Female sterilization 79.2 83.7 85.2 80.2 86.2 81.1 Male sterilization 53.0 57.5 51.0 62.2 68.2 59.2 Pill 92.6 95.2 93.8 92.0 95.1 95.9 IUD 70.2 75.4 75.6 65.5 73.0 74.0 Injectables 94.1 96.9 96.4 91.3 95.3 96.0 Implants 77.4 84.5 78.3 62.2 73.5 63.8 Male condom 96.6 97.1 98.9 99.2 99.3 99.9 Female condom 70.5 72.8 75.3 81.4 85.0 89.5 Lactational amenorrhoea (LAM) 13.0 14.6 10.5 11.4 13.5 13.9 Emergency contraception 30.7 32.1 39.3 37.1 40.4 51.7 Any traditional method 73.7 80.4 85.8 82.6 90.5 90.9 Rhythm/moon beads 53.3 58.0 58.3 68.7 76.8 75.5 Withdrawal 62.8 70.3 75.2 72.7 81.6 84.1 Folk method 9.5 11.6 8.6 3.5 4.1 5.2 Mean number of methods known by respondents 15-49 8.0 8.5 8.5 8.3 8.9 8.9 Number of respondents 8,674 5,418 320 2,173 1,228 120 Mean number of methods known by respondents 15-54 na na na 8.3 8.9 9.0 Number of respondents 0 0 0 2,295 1,338 125 na = Not applicable 1 Had sexual intercourse within 30 days preceding the survey Because knowledge of at least one method of contraception is nearly universal, there are few differences in knowledge by background characteristics. The knowledge of any contraceptive method is slightly lower among respondents in Karamoja where 79 percent of all women and 96 percent of all men Family Planning • 79 have heard of a contraceptive method (data not shown). The high level of knowledge could be attributed to the successful dissemination of family planning messages through the mass media. 7.2 CURRENT USE OF CONTRACEPTION This section presents information on the prevalence of current contraceptive use among women age 15-49 at the time of the survey. Level of current use is the most widely employed and valuable measure of the success of family planning programs. The contraceptive prevalence rate (CPR) is usually defined as the percentage of currently married women who are currently using a method of contraception. Table 7.2 shows the percent distribution by age of all women, currently married women, and sexually active unmarried women who use specific family planning methods. Twenty-four percent of all women, 30 percent of currently married women, and 52 percent of sexually active unmarried women are using some method of contraception. Users of the modern methods of contraception make up the large majority of all users. Among currently married women, 26 percent are using a modern method and only 4 percent are using a traditional method. The same pattern is observed among all women and unmarried sexually active women. The most commonly used modern method among all women and currently married women is injectables (used by 11 percent of all women and 14 percent of currently married women), while the most commonly used methods among unmarried sexually active women are the male condom (19 percent) and injectables (18 percent). Current contraceptive use varies by age. Use is lowest among young women below age 25 (because they are in the early stages of family building) and among older women age 45 and above (some of whom are no longer fecund) than among those at the intermediate age groups. For example, 14 percent of currently married women age 15-19 report current use of any contraceptive method. This proportion increases until it peaks at 38 percent among those age 35-44, after which it decreases to 21 percent among women age 45-49. A similar pattern is observed among all women. 80 • 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 Pe rc en t 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 rre nt ly u se d, a cc or di ng to a ge , U ga nd a 20 11 Ag e An y m et ho d An y m od er n m et ho d M od er n m et ho d A ny tr ad i- tio na l m et ho d Tr ad iti on al m et ho d N ot cu rre nt ly us in g To ta l N um be r o f w om en Fe m al e st er ili- za tio n M al e st er ili- za tio n P ill IU D In je ct - ab le s Im pl an ts M al e co nd om LA M R hy th m / m oo n be ad s W ith - dr aw al Fo lk AL L W O M EN 15 -1 9 6. 8 6. 0 0. 0 0. 0 0. 3 0. 0 2. 6 0. 2 2. 9 0. 0 0. 8 0. 2 0. 6 0. 0 93 .2 10 0. 0 2, 04 8 20 -2 4 22 .1 19 .8 0. 0 0. 0 2. 8 0. 3 11 .3 1. 0 4. 3 0. 1 2. 3 0. 6 1. 6 0. 1 77 .9 10 0. 0 1, 62 9 25 -2 9 31 .6 27 .6 0. 3 0. 2 2. 3 0. 7 16 .9 3. 5 3. 4 0. 2 3. 9 1. 7 1. 9 0. 3 68 .4 10 0. 0 1, 56 9 30 -3 4 33 .5 30 .0 2. 0 0. 0 4. 2 0. 4 16 .8 3. 3 3. 1 0. 2 3. 5 1. 3 1. 4 0. 8 66 .5 10 0. 0 1, 08 6 35 -3 9 34 .5 30 .3 6. 0 0. 0 2. 8 0. 8 13 .5 3. 8 3. 2 0. 3 4. 1 1. 3 1. 9 0. 9 65 .5 10 0. 0 1, 02 6 40 -4 4 32 .0 26 .5 7. 8 0. 0 3. 3 0. 2 11 .3 1. 3 2. 6 0. 0 5. 4 2. 5 2. 3 0. 6 68 .0 10 0. 0 72 9 45 -4 9 17 .5 14 .1 7. 4 0. 2 0. 4 0. 0 3. 7 0. 6 1. 7 0. 0 3. 4 0. 8 2. 0 0. 7 82 .5 10 0. 0 58 7 To ta l 23 .6 20 .7 2. 2 0. 1 2. 1 0. 4 10 .7 1. 9 3. 2 0. 1 2. 9 1. 1 1. 5 0. 4 76 .4 10 0. 0 8, 67 4 C U R R E N TL Y M A R R IE D W O M EN 15 -1 9 13 .9 13 .1 0. 0 0. 0 0. 5 0. 0 8. 0 0. 7 3. 8 0. 1 0. 8 0. 0 0. 8 0. 0 86 .1 10 0. 0 40 9 20 -2 4 22 .9 20 .4 0. 0 0. 0 2. 9 0. 5 13 .4 1. 1 2. 5 0. 1 2. 5 0. 6 1. 9 0. 0 77 .1 10 0. 0 1, 09 7 25 -2 9 32 .0 27 .8 0. 3 0. 2 2. 6 0. 8 17 .1 3. 6 2. 8 0. 3 4. 2 1. 7 2. 1 0. 4 68 .0 10 0. 0 1, 29 5 30 -3 4 35 .4 31 .2 2. 0 0. 0 4. 7 0. 5 17 .7 3. 6 2. 5 0. 3 4. 2 1. 4 1. 8 1. 0 64 .6 10 0. 0 88 0 35 -3 9 37 .8 33 .4 6. 9 0. 0 2. 9 0. 9 14 .3 4. 7 3. 3 0. 3 4. 4 1. 6 2. 1 0. 7 62 .2 10 0. 0 82 0 40 -4 4 37 .5 30 .6 9. 4 0. 0 4. 1 0. 3 12 .6 1. 7 2. 6 0. 0 6. 9 3. 1 3. 1 0. 7 62 .5 10 0. 0 55 3 45 -4 9 20 .5 15 .2 7. 3 0. 4 0. 5 0. 0 4. 8 0. 9 1. 2 0. 0 5. 3 1. 2 3. 2 0. 9 79 .5 10 0. 0 36 4 To ta l 30 .0 26 .0 2. 9 0. 1 2. 9 0. 5 14 .1 2. 7 2. 7 0. 2 4. 0 1. 4 2. 1 0. 5 70 .0 10 0. 0 5, 41 8 SE XU AL LY A C TI VE U N M A R R IE D W O M EN 1 15 -1 9 45 .1 35 .3 0. 0 0. 0 1. 3 0. 0 9. 6 0. 0 24 .3 0. 0 9. 9 0. 0 9. 9 0. 0 54 .9 10 0. 0 80 20 -2 4 54 .3 47 .9 0. 0 0. 0 7. 1 0. 0 15 .9 1. 5 23 .3 0. 0 6. 5 2. 0 4. 1 0. 4 45 .7 10 0. 0 81 25 + 53 .9 47 .0 1. 2 0. 0 3. 7 0. 2 23 .7 3. 9 14 .2 0. 0 6. 9 3. 3 1. 4 2. 2 46 .1 10 0. 0 16 0 To ta l 51 .8 44 .3 0. 6 0. 0 4. 0 0. 1 18 .2 2. 4 19 .0 0. 0 7. 5 2. 2 4. 2 1. 2 48 .2 10 0. 0 32 0 N ot e: If m or e th an o ne m et ho d is u se d, o nl y th e m os t e ffe ct iv e m et ho d is c on si de re d in th is ta bu la tio n. LA M = L ac ta tio na l a m en or rh oe a m et ho d 1 W om en w ho h av e ha d se xu al in te rc ou rs e w ith in 3 0 da ys p re ce di ng th e su rv ey 80 • Family Planning Family Planning • 81 7.3 CURRENT USE OF CONTRACEPTIVE BY BACKGROUND CHARACTERISTICS Analysing current use of contraception by background characteristics helps to identify subgroups of the population that may need to be targeted for family planning services. Table 7.3.1 presents the percent distribution of currently married women by their use of family planning methods, according to background characteristics. The table allows a comparison of levels of current contraceptive use across major population groups. There are variations in current use of contraception among subgroups. There is a direct association between use of family planning methods and the number of children that women have. The majority of women do not begin to use contraception until they have had at least one child. Only five percent of married women with no living children use contraception; the percentage increases to 27 percent among women with one or two children and to 34 percent among women with three or more children. There is a wide gap in the use of any methods between urban and rural areas (46 percent versus 27 percent). Distribution by region shows that the percentage of currently married women using a contraceptive method is highest in Kampala (48 percent) and lowest in Karamoja (8 percent). The use of contraception increases with education. Forty-four percent of currently married women with secondary or more education are using a contraceptive method compared with 18 percent of those with no education. Contraceptive use also increases as household wealth increases, from 15 percent of women in the lowest wealth quintile to 46 percent among those in the highest wealth quintile. As mentioned above, by far the most commonly used method among currently married women is injectables, used by 14 percent of women. Use of injectables follows the same pattern as use of any contraceptive method: it increases with number of living children, education, and wealth. Injectable use is higher in urban than in rural areas (20 percent versus 13 percent) and is highest in Kampala (19 percent) and lowest in Karamoja (3 percent). The rhythm, or moon beads, method is used by 1 of currently married women. Female sterilization, the pill, implants, and male condoms are used by 3 percent each. 82 • F am ily P la nn in g T ab le 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 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 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, U ga nd a 20 11 Ba ck gr ou nd ch ar ac te ris tic An y m et ho d An y m od er n m et ho d M od er n m et ho d A ny tr ad i- tio na l m et ho d Tr ad iti on al m et ho d N ot cu rre nt ly us in g To ta l N um be r of w om en Fe m al e st er ili- za tio n M al e st er ili- za tio n P ill IU D In je ct - ab le s Im pl an ts M al e co nd om LA M R hy th m / m oo n be ad s W ith - dr aw al Fo lk N um be r o f l iv in g ch ild re n 0 5. 1 4. 2 0. 0 0. 0 1. 8 0. 0 1. 3 0. 0 1. 2 0. 0 0. 8 0. 2 0. 6 0. 0 94 .9 10 0. 0 34 1 1- 2 27 .1 23 .7 0. 3 0. 1 3. 1 0. 5 13 .8 1. 3 4. 3 0. 2 3. 4 1. 3 1. 9 0. 2 72 .9 10 0. 0 1, 53 2 3- 4 33 .5 29 .1 1. 8 0. 1 3. 0 1. 1 16 .4 3. 6 2. 8 0. 1 4. 4 1. 8 2. 4 0. 2 66 .5 10 0. 0 1, 47 5 5+ 33 .8 29 .2 6. 0 0. 1 2. 9 0. 2 14 .6 3. 4 1. 7 0. 2 4. 6 1. 4 2. 2 1. 0 66 .2 10 0. 0 2, 06 9 R es id en ce U rb an 45 .8 39 .2 2. 5 0. 2 7. 9 1. 6 19 .9 1. 8 4. 7 0. 6 6. 6 2. 8 3. 3 0. 6 54 .2 10 0. 0 89 2 R ur al 26 .9 23 .4 3. 0 0. 1 1. 9 0. 3 12 .9 2. 8 2. 3 0. 1 3. 5 1. 1 1. 9 0. 5 73 .1 10 0. 0 4, 52 6 R eg io n Ka m pa la 48 .2 40 .2 2. 0 0. 5 10 .3 1. 8 19 .3 1. 6 4. 7 0. 0 8. 0 3. 6 3. 8 0. 6 51 .8 10 0. 0 39 7 C en tra l 1 37 .3 30 .7 2. 2 0. 2 4. 6 0. 8 15 .0 2. 2 5. 4 0. 2 6. 6 2. 6 3. 6 0. 4 62 .7 10 0. 0 55 9 C en tra l 2 33 .7 30 .7 4. 9 0. 3 3. 0 0. 5 14 .3 3. 4 3. 3 1. 1 2. 9 0. 4 2. 5 0. 0 66 .3 10 0. 0 56 5 Ea st C en tra l 32 .0 27 .7 3. 9 0. 0 2. 5 0. 2 16 .3 0. 6 4. 2 0. 0 4. 3 1. 1 1. 5 1. 7 68 .0 10 0. 0 58 0 Ea st er n 26 .1 23 .2 4. 1 0. 0 0. 8 0. 0 15 .3 1. 8 1. 2 0. 0 3. 0 1. 2 1. 2 0. 5 73 .9 10 0. 0 85 9 Ka ra m oj a 7. 8 7. 4 0. 2 0. 0 1. 9 0. 0 2. 8 1. 6 0. 9 0. 0 0. 4 0. 0 0. 4 0. 0 92 .2 10 0. 0 21 5 N or th 23 .9 23 .4 2. 7 0. 0 1. 2 0. 9 12 .7 5. 0 0. 8 0. 1 0. 5 0. 4 0. 1 0. 0 76 .1 10 0. 0 48 7 W es t N ile 14 .6 13 .6 1. 0 0. 0 1. 3 0. 7 4. 8 3. 7 2. 1 0. 0 0. 9 0. 5 0. 3 0. 1 85 .4 10 0. 0 33 0 W es te rn 32 .7 26 .8 2. 1 0. 0 1. 5 0. 5 15 .5 4. 2 2. 8 0. 2 5. 9 2. 8 2. 2 0. 9 67 .3 10 0. 0 74 3 So ut hw es t 29 .6 25 .1 2. 7 0. 0 4. 0 0. 5 14 .0 2. 5 1. 6 0. 0 4. 4 0. 5 3. 7 0. 2 70 .4 10 0. 0 68 1 Ed uc at io n N o ed uc at io n 17 .9 15 .5 3. 1 0. 0 1. 7 0. 1 6. 3 2. 3 1. 7 0. 2 2. 5 1. 3 0. 9 0. 3 82 .1 10 0. 0 87 7 Pr im ar y 28 .0 24 .5 3. 2 0. 1 1. 9 0. 4 13 .9 2. 9 2. 0 0. 1 3. 5 0. 8 2. 1 0. 6 72 .0 10 0. 0 3, 31 3 Se co nd ar y + 44 .2 37 .7 1. 9 0. 1 6. 5 1. 3 19 .9 2. 3 5. 3 0. 4 6. 5 3. 1 3. 0 0. 3 55 .8 10 0. 0 1, 22 7 W ea lth q ui nt ile Lo w es t 14 .7 12 .7 0. 9 0. 0 0. 4 0. 2 8. 2 2. 0 1. 0 0. 0 2. 0 0. 6 1. 2 0. 1 85 .3 10 0. 0 1, 06 3 Se co nd 23 .2 21 .2 2. 6 0. 0 1. 3 0. 0 12 .6 2. 8 2. 0 0. 0 2. 0 0. 8 1. 1 0. 1 76 .8 10 0. 0 1, 10 1 M id dl e 29 .3 24 .7 2. 8 0. 1 2. 0 0. 4 13 .5 3. 1 2. 5 0. 2 4. 6 1. 1 2. 6 0. 9 70 .7 10 0. 0 1, 04 2 Fo ur th 35 .0 31 .0 4. 9 0. 1 2. 7 0. 4 17 .6 2. 7 2. 5 0. 1 4. 0 1. 3 1. 7 0. 9 65 .0 10 0. 0 99 7 H ig he st 46 .2 39 .1 3. 4 0. 1 7. 5 1. 5 18 .1 2. 7 5. 1 0. 6 7. 0 2. 9 3. 6 0. 5 53 .8 10 0. 0 1, 21 5 To ta l 30 .0 26 .0 2. 9 0. 1 2. 9 0. 5 14 .1 2. 7 2. 7 0. 2 4. 0 1. 4 2. 1 0. 5 70 .0 10 0. 0 5, 41 8 N ot e: If m or e th an o ne m et ho d is u se d, o nl y th e m os t e ffe ct iv e m et ho d is c on si de re d in th is ta bu la tio n. LA M = L ac ta tio na l a m en or rh ea m et ho d 82 • Family Planning Family Planning • 83 7.4 TRENDS IN CURRENT USE OF FAMILY PLANNING Table 7.4 and Figure 7.1 show trends in contraceptive use since the 2000-01 Uganda DHS. Use of contraceptive methods by currently married women has increased over the last decade, from 19 percent in 2000-01 to 30 percent in 2011. One of the targets of the Ministry of Health in the Health Sector Strategic and Investment Plan is an increase in the contraceptive prevalence rate from 24 percent in 2006 to 35 percent in 2015. The results in the 2011 UDHS show that the government is on track to achieve this indicator (MoH, 2010b). Table 7.4 Trends in the current use of contraception Percent distribution of currently married women age 15-49 by contraceptive method currently used, Uganda 2000-2011 Method 2000-01 UDHS 2006 UDHS 2011 UDHS Any method1 18.6 23.7 29.9 Any modern method1 14.0 17.9 25.9 Female sterilization 2.0 2.4 2.9 Male sterilization 0.0 0.1 0.1 Pill 3.2 2.9 2.9 IUD 0.2 0.2 0.5 Injectables 6.4 10.2 14.1 Implants 0.3 0.3 2.7 Male condom 1.9 1.7 2.7 Any traditional method 4.6 5.8 4.0 Rhythm/moon beads 2.5 2.8 1.4 Withdrawal 1.1 2.1 2.1 Folk/other method 1.0 0.9 0.5 Not currently using 81.4 76.3 70.0 Total 100.0 100.0 100.0 Number of women 4,881 5,337 5,418 1Excludes LAM in order to increase comparability across surveys. Note: In the 2000-01 UDHS, areas making up the districts of Amuru, Nwoya, Bundibugyo, Ntoroko, Gulu, Kasese, Kitgum, Lamwo, Agago, and Pader were excluded from the sample. These areas contained about 5 percent of the national population of Uganda. Thus, the trends need to be viewed in that light. The increase is especially pronounced for the use of modern methods, which has increased from 14 percent to 26 percent during the same period. The use of traditional methods has remained constant at 4 to 6 percent over the last decade 84 • Family Planning Figure 7.1 Trends in contraceptive use among currently married women 19 14 2 3 6 2 5 3 1 1 24 18 2 3 10 2 6 3 2 1 30 26 3 3 14 3 4 1 2 1 Any method Any modern Female sterilization Pill Injectables Male condom Any traditional Rhythm/moon beads Withdrawal Folk/other method Percentage of currently married women 2000-01 UDHS 2006 UDHS 2011 UDHS Note: In the 2000-2001 UDHS, areas making up the districts of Amuru, Nwoya, Bundibugyo, Ntoroko, Gulu, Kasese, Kitgum, Lamwo, Agago, and Pader were excluded from the sample. These areas contained about 5 percent of the national population of Uganda. Thus, the trends need to be viewed in that light. 7.5 TIMING OF FEMALE STERILIZATION Given the effectiveness of female sterilization as a means of preventing pregnancies among women in high-risk groups, the family planning programmes should emphasize dissemination of information about this method. Trends in the use of sterilization as a family planning method are of interest, especially trends in women’s age at the time of the operation. Results show that the vast majority (86 percent) of women were age 39 or younger at the time of sterilization (data not shown). Six percent were under 25, 19 percent were age 25-29, 30 percent were 30-34, and 31 percent were 35-39 at the time of the sterilization. Only 14 percent were 40 or older. The median age at sterilization is 33.4 years. 7.6 SOURCE OF CONTRACEPTION Table 7.5 documents the main sources of contraception for users of modern methods. This information is important to those who plan, manage, and implement programmes. In the 2011 UDHS, all current users of modern contraceptive methods were asked the most recent source of their methods. The public sector is a major source of modern contraceptive methods in Uganda, providing contraception to 47 percent of current users. Within the public sector, 14 percent of users obtain their contraception from government hospitals and 29 percent from government health centers. Forty-five percent of users obtain their methods from the private medical sector, mainly from private hospitals or clinics (40 percent). Female sterilizations are performed mostly in government hospitals and health centers (53 and 24 percent, respectively). Pill users are almost evenly split between those who rely on public sector sources and those who use private medical sources. Most of the women using implants also obtain them from public sector sources (85 percent). Injectables are mostly obtained from private facilities (60 percent), mainly private hospitals or clinics (57 percent). Four in ten male condom users obtain their condoms from various sources outside of the public and private sectors, primarily shops (33 percent). Family Planning • 85 Table 7.5 Source of modern contraception methods Percent distribution of users of modern contraceptive methods age 15-49 by most recent source of method, according to method, Uganda 2011 Source Female sterili- zation Pill IUD Inject- ables Implants Male condom Total Public sector 79.1 45.7 (38.9) 39.0 85.1 28.6 46.6 Government hospital 52.5 12.1 (7.0) 7.4 22.7 7.5 14.2 Government health center 24.2 27.7 (21.9) 29.1 57.0 14.1 28.6 Family planning clinic 1.8 4.4 (5.4) 2.3 2.8 0.6 2.3 Outreach 0.0 0.0 (4.6) 0.1 2.6 3.2 0.9 Fieldworker/VHT 0.0 1.5 (0.0) 0.0 0.0 1.9 0.5 Other public sector 0.6 0.0 (0.0) 0.0 0.0 1.2 0.3 Private medical sector 19.0 51.5 (50.4) 60.1 14.4 28.6 45.4 Private hospital/clinic 17.7 42.5 (46.3) 57.1 8.6 16.2 40.2 Pharmacy 0.0 9.0 (0.0) 1.1 0.0 10.0 3.1 Private doctor 0.0 0.0 (0.0) 0.7 0.0 0.6 0.5 Outreach 0.5 0.0 (4.1)) 0.0 2.4 0.2 0.4 Fieldworker/VHT 0.0 0.0 (0.0) 0.1 0.0 0.6 0.2 Other private medical 0.7 0.0 (0.0) 1.0 3.4 1.0 1.1 Other source 0.0 2.7 (7.2) 0.8 0.0 39.7 7.0 Shop 0.0 1.2 (0.0) 0.4 0.0 32.8 5.5 Church 0.0 0.0 (0.0) 0.2 0.0 0.0 0.1 Friends relatives 0.0 1.5 (7.2) 0.2 0.0 7.0 1.5 Other 0.8 0.1 (0.0) 0.1 0.1 3.1 0.6 Don't know 1.1 0.0 (0.0) 0.0 0.0 0.0 0.2 Missing 0.0 0.0 (3.4) 0.1 0.5 0.0 0.2 Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 Number of women 188 186 31 929 164 280 1,783 Note: Total includes other modern methods but excludes lactational amenorrhoea method (LAM). Figures in parentheses are based on 25-49 unweighted cases. VHT = Village Health Team 7.7 USE OF SOCIAL MARKETING BRANDS OF PILLS AND CONDOMS Women who said they were currently using pills or condoms as a method of contraception were asked which brands of pills and condoms they used. Interviewers presented a brochure with photographs of different brands of pills and condoms to assist the respondents in identification of the brand. At the time of the 2011 UDHS, Pilplan and Microgynon were the socially marketed brands of contraceptive pills, and Engabu, Lifeguard, Trust, and Protector were the socially marketed brands of condoms. Table 7.6 shows that one in four pill users (25 percent) use Pilplan, and about four in ten (38 percent) use Microgynon. More than half of condom users (54 percent) use Engabu, Lifeguard, or Trust, and about three in ten (29 percent) use Protector. There is no clear pattern in the use of socially marketed brands of pills and condoms by residence. Table 7.6 Use of social marketing brand pills and condoms Percentage of pill and condom users age 15-49 using a social marketing brand, by residence, Uganda 2011 Residence Among pill users Among condom users Percentage using Pilplan Percentage using Microgynon Number of women using the pill Percentage using Engabu/ Lifeguard/ Trust Percentage using Protector Number of women using condoms Urban 27.4 37.1 82 56.8 22.7 96 Rural 23.1 38.9 101 51.9 33.1 138 Total 25.0 38.1 182 54.0 28.8 234 Note: Table excludes pill and condom users who do not know the brand name. Condom use is based on women's reports 86 • Family Planning 7.8 INFORMED CHOICE Informed choice is an important aspect in determining the quality of family planning services. Current users of modern methods of contraception were asked whether they were informed of side effects or problems they might have with a method, what to do if they experienced side effects, and alternative methods they could use. This information assists users in coping with side effects and decreases unnecessary discontinuation of a method. Moreover, such data serve as a measure of the quality of family planning service provision. Table 7.7 presents results by method type and source. Fifty-six percent of current users of modern contraceptives were informed about potential side effects or problems with the method they use, 53 percent were told what to do if they experienced side effects, and 59 percent were given information about other methods by a health worker or family planning worker. Users of implants. IUS, and those who obtained their methods from public sector sources were most likely to be informed about potential side effects or problems associated with the method, what to do if side effects were experienced, and what other methods could be used. Table 7.7 Informed choice Among current users of 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, Uganda 2011 Method/source Among women who started last episode of modern contraceptive method within five years preceding the survey: Percentage who were informed about side effects or problems of method used Percentage who were informed what to do if side effects were experienced Percentage who were informed by a health or family planning worker of other methods that could be used Number of women Method Female sterilization 46.5 38.8 49.3 100 Pill 55.1 49.4 68.8 173 IUD (71.5) (73.8) (93.9) 30 Injectables 51.9 49.5 53.7 860 Implants 80.5 81.9 79.1 163 Initial source of method1 Public sector 66.1 63.3 66.9 702 Government hospital 71.0 65.4 68.3 206 Government health center 64.7 63.1 66.7 452 Family planning clinic (58.0) (53.5) (63.6) 38 Other public sector * * * 6 Private medical sector 44.3 42.2 50.7 607 Private hospital/clinic 43.4 40.4 50.1 560 Pharmacy (48.5) (56.7) (51.6) 21 Other private medical sector * * * 26 Total 55.9 53.2 59.4 1,325 Note: Table includes users of only the methods listed individually. Total includes two cases with missing information on the initial source. 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 Source at start of current episode of use Family Planning • 87 7.9 CONTRACEPTIVE DISCONTINUATION RATES Couples can only realize their reproductive goals when they use contraceptive methods consistently and correctly. Discontinuation of a method is a major concern for managers of family planning programmes. In the 2011 UDHS ‘Calendar’ section of the Woman’s Questionnaire, all segments of contraceptive use since 2006 were recorded. During analysis, the month of interview and the two months prior to the survey are excluded to avoid any bias that may be introduced by unrecognized pregnancies. One-year contraceptive discontinuation rates based on the calendar data are presented in Table 7.8. Forty-three percent of family planning users in Uganda discontinued using the method within 12 months of starting its use. Discontinuation rates are highest for pill users (54 percent) and lowest for users of implants (12 percent). About one in six (16 percent) episodes of discontinuation occurred because of fear of side effects or health concerns, 8 percent because a woman wanted to become pregnant, and 6 percent because a method failed. Table 7.8 12-month 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 reason for discontinuation and specific method, Uganda, 2011 Method Reason for discontinuation Switched to another method4 Number of episodes of use5 Method failure Desire to become pregnant Other fertility- related reasons1 Side effects/ health concerns Wanted more effective method Other method- related reasons2 Other reasons Any reason3 Pill 9.4 6.2 4.4 21.7 2.1 5.9 4.4 54.0 12.5 325 Injectables 3.5 8.9 2.5 23.3 1.1 2.1 5.0 46.5 4.3 840 Implants 0.8 2.0 0.0 8.0 0.0 1.3 0.0 12.0 1.9 19 Male condom 3.9 4.8 17.4 0.7 0.9 4.7 8.4 40.9 4.2 176 Rhythm/moon beads 9.8 7.1 2.2 0.4 1.9 0.3 2.3 23.9 1.9 32 Withdrawal 22.0 10.8 1.5 0.0 4.1 0.9 4.5 43.7 6.0 101 All methods 6.3 7.5 4.3 15.8 1.4 2.6 4.7 42.6 5.2 1,544 Note: Figures are based on life table calculations using information on episodes of use that began 3 to 62 months preceding the survey. Male and female sterilization, IUD, female condom, and LAM are included under ‘All methods’ and are not shown separately. 1 Includes infrequent sex/husband away, difficult to get pregnant/menopausal, and marital dissolution/separation 2 Includes lack of access/too far, costs too much, and inconvenient to use 3 Reasons for discontinuation are mutually exclusive and add to the total given in this column 4 The episodes of use included in this column are a subset of the discontinued episodes included in the discontinuation rate. A woman is considered to have switched to another method if she used a different method in the month following discontinuation or if she gave ‘wanted a more effective method’ as the reason for discontinuation and started another method within two months of discontinuation. 5 Number of episodes of use includes both episodes of use that were discontinued during the period of observation and episodes of use that were not discontinued during the period of observation. 7.10 REASONS FOR DISCONTINUATION OF CONTRACEPTIVE USE Another perspective on discontinuation of modern contraceptive use is provided in Table 7.9, which shows the percent distribution of discontinuations of contraceptive methods in the five years preceding the survey by reasons for discontinuation, according to method. The most common reason for discontinuing a method is health concerns or side effects (32 percent), followed by desire to become pregnant (25 percent) and pregnancy (14 percent). This pattern of reasons is largely the same as those observed for the one-year discontinuation rates. The patterns are also similar for individual methods except for the male condom, for which the main reason for discontinuation was the husband’s absence (34 percent), and the rhythm/moon beads and withdrawal, for which the main reason was that the respondent wanted to become pregnant (42 and 30 percent, respectively). 88 • Family Planning Table 7.9 Reasons for discontinuation Percent distribution of discontinuations of contraceptive methods in the five years preceding the survey by main reason stated for discontinuation, according to specific method, Uganda 2011 Reason Pill Injection Implants Male condom Rhythm/ moon beads With- drawal Other All methods Became pregnant while using 14.5 7.3 6.4 13.6 32.5 41.0 56.0 13.9 Wanted to become pregnant 20.5 25.5 34.5 17.4 42.1 30.3 25.7 24.9 Husband disapproved 3.2 3.3 0.4 10.2 4.3 7.5 1.7 4.2 Wanted a more effective method 3.5 1.8 0.0 3.8 9.0 12.3 3.6 3.4 Health concerns/side effects 33.8 45.1 50.1 1.7 0.5 0.0 1.3 32.4 Lack of access/too far 2.6 1.3 2.2 4.3 0.0 0.0 0.0 1.7 Cost too much 0.9 1.5 0.0 0.7 0.0 0.0 0.0 1.1 Inconvenient to use 9.1 1.5 0.0 7.8 2.9 2.4 1.2 3.6 Up to God/fatalistic 0.4 0.1 0.0 0.7 0.0 0.0 0.0 0.4 Difficult to get pregnant/menopausal 0.1 0.4 0.8 0.0 1.0 0.0 1.3 0.3 Infrequent sex/husband away 6.7 4.8 0.6 33.7 2.8 3.1 2.1 7.9 Marital dissolution/separation 1.4 2.4 1.4 1.0 2.7 1.4 1.9 2.0 Other 3.4 4.6 3.2 3.6 2.3 2.0 5.3 4.0 Don't know 0.0 0.3 0.4 1.5 0.0 0.0 0.0 0.3 Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 Number of discontinuations 461 1,538 57 299 93 197 74 2,760 All methods column include other methods that are too small to be listed in separate columns. 7.11 KNOWLEDGE OF THE FERTILE PERIOD Basic understanding of the physiology of human reproduction is especially useful for the successful practice of coitus-related methods of contraception such as the rhythm method. The successful use of such methods depends in 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 a woman’s fertile period. Specifically, they were asked whether there are certain days between two menstrual periods when a woman is most 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 in Table 7.10 show that overall, only 14 percent of all women interviewed reported the correct timing of the fertile period, that is, halfway between the two menstrual periods. This percentage has declined slightly from 16 percent in the 2006 UDHS. Almost half of women (45 percent) believe that the fertile period is right after the woman’s period ends. An additional 17 percent report no specific time, and an equal proportion report that they don’t know. To use the rhythm method effectively, correct knowledge of the fertile period is very crucial. Of those who use the rhythm/moon beads method, only one-third (33 percent) reported the correct timing of the fertile period, similar to the percentage reported in the 2006 UDHS (31 percent). Most of the rhythm/moon beads method users (48 percent) believe the fertile period is right after the woman’s period ends. Table 7.10 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/moon beads method, Uganda 2011 Perceived fertile period Users of rhythm/ moon beads method Nonusers of rhythm/ moon beads method All women Just before her menstrual period begins 14.6 6.8 6.9 During her menstrual period 0.0 1.2 1.2 Right after her menstrual period has ended 47.8 45.0 45.0 Halfway between two menstrual periods 32.9 13.2 13.5 Other 1.9 0.3 0.4 No specific time 1.0 16.7 16.6 Don't know 1.9 16.7 16.5 Total 100.0 100.0 100.0 Number of women 92 8,582 8,674 Family Planning • 89 These data show that there is a continued need to educate Ugandan women about the physiology of reproduction, the fertile period, and effective use of contraception. 7.12 NEED AND DEMAND FOR FAMILY PLANNING SERVICES This section provides information on the extent of need and potential demand for family planning services in Uganda. Unmet need for family planning refers to fecund women who are not using contraception, but who wish to postpone the next birth (spacing) or who wish to stop childbearing altogether (limiting). Specifically, women are considered to have unmet need for spacing if they are:  At risk of becoming pregnant, not using contraception, and either do not want to become pregnant within the next two years, or are unsure if or when they want to become pregnant  Pregnant with a mistimed pregnancy  Postpartum amenorrhoeic for up to two years following a mistimed birth and not using contraception Women are considered to have unmet need for limiting if they are:  At risk of becoming pregnant, not using contraception, and do not want (more) children  Pregnant with an unwanted pregnancy  Postpartum amenorrhoeic for up to two years following an unwanted birth and not using contraception Women who are classified as infecund have no unmet need because they are not at risk of becoming pregnant. Women using contraception are considered to have a met need. Women using contraception who say they want no (more) children are considered to have a met need for limiting, and women who are using contraception and say they want to delay having a child, or are unsure if or when they want another child, are considered to have a met need for spacing. Total unmet need, demand, and demand satisfied are defined as follows:  Total unmet need is the sum of unmet need for spacing plus unmet need for limiting  Demand for family planning is the sum of total unmet need plus total contraceptive use  Proportion of demand satisfied is total contraceptive use divided by the sum of total unmet need plus total contraceptive use The definition of unmet need for family planning has been revised to make levels of unmet need comparable over time and across surveys. Therefore, all of the unmet need trend estimates in Figure 7.2 have been recalculated using the revised definition of unmet need and may differ slightly from numbers published in the final reports for each survey. Table 7.11 shows need and demand for family planning among currently married women, by background characteristics. Thirty-four percent of currently married women have an unmet need for family planning, with 21 percent having an unmet need for spacing and 14 percent having an unmet need for limiting. 90 • Family Planning Thirty percent of women have a met need for family planning. If all currently married women who say they want to space or limit their children were to use a family planning method, the contraceptive prevalence rate would increase to 64 percent. Currently, only 47 percent of the family planning needs of married women are being met. Unmet need for family planning does not vary much with age, although it is somewhat lower among the youngest women age 15-19 (31 percent) and those in the oldest age group 45-49 (24 percent). Unmet need is higher in rural than in urban areas (37 and 23 percent, respectively). Regional variations show that unmet need is highest in West Nile and North regions (43 percent, each), followed by East Central region (42 percent), and is lowest in Kampala and Karamoja regions (17 and 21 percent, respectively). Unmet need is lowest among women with secondary or higher education (24 percent) and those in the wealthiest quintile (23 percent). Total demand for family planning increases with age, from 45 percent of women age 15-19 to a peak of 73 percent among those age 35-39, after which it decreases to 45 percent among the oldest women age 45-49. Demand is somewhat higher in urban areas (69 percent) than in rural areas (64 percent). There are only slight variations among regions, with the exception of Karamoja which has the lowest demand for family planning (28 percent). Demand increases with women’s education, from 52 percent among women with no education to 69 percent among those with secondary or higher education. Similarly, demand increases with wealth, from 57 percent of women in the lowest wealth quintile to 69 percent of women in the highest two quintiles. Fa m ily P la nn in g • 9 1 Ta bl e 7. 11 N ee d an d de m an d fo r f am ily p la nn in g am on g cu rr en tly m ar rie d w om en Pe rc en ta ge o f c ur re nt ly m ar rie d w om en a ge 1 5- 49 w ith u nm et n ee d fo r f am ily p la nn in g, p er ce nt ag e w ith m et n ee d fo r f am ily p la nn in g, to ta l d em an d fo r f am ily p la nn in g, a nd th e pe rc en ta ge o f th e de m an d fo r c on tra ce pt io n th at is s at is fie d, b y ba ck gr ou nd c ha ra ct er is tic s, U ga nd a 20 11 Ba ck gr ou nd ch ar ac te ris tic U nm et n ee d fo r fa m ily p la nn in g1 M et n ee d fo r f am ily p la nn in g (c ur re nt ly u si ng )2 To ta l d em an d fo r fa m ily p la nn in g Pe rc en ta ge of d em an d sa tis fie d Pe rc en ta ge of d em an d sa tis fie d by m od er n m et ho ds N um be r o f w om en Fo r sp ac in g Fo r lim iti ng To ta l Fo r sp ac in g Fo r lim iti ng To ta l Fo r sp ac in g Fo r lim iti ng To ta l A ge 15 -1 9 30 .7 0. 6 31 .3 13 .0 0. 9 13 .9 43 .8 1. 5 45 .3 30 .8 28 .9 40 9 20 -2 4 32 .5 2. 9 35 .4 20 .2 2. 7 22 .9 52 .7 5. 5 58 .3 39 .2 34 .9 1, 09 7 25 -2 9 28 .2 7. 6 35 .7 23 .3 8. 8 32 .0 51 .5 16 .3 67 .8 47 .3 41 .0 1, 29 5 30 -3 4 17 .7 18 .9 36 .6 15 .2 20 .2 35 .4 32 .8 39 .1 72 .0 49 .2 43 .4 88 0 35 -3 9 12 .1 23 .4 35 .5 8. 0 29 .7 37 .8 20 .2 53 .1 73 .3 51 .6 45 .5 82 0 40 -4 4 4. 0 27 .9 31 .9 3. 4 34 .1 37 .5 7. 4 62 .0 69 .4 54 .0 44 .1 55 3 45 -4 9 0. 2 23 .8 24 .0 0. 6 19 .9 20 .5 0. 8 43 .7 44 .5 46 .0 34 .0 36 4 R es id en ce U rb an 15 .8 6. 9 22 .7 25 .3 20 .5 45 .8 41 .1 27 .4 68 .5 66 .9 57 .2 89 2 R ur al 21 .7 14 .8 36 .5 12 .6 14 .3 26 .9 34 .4 29 .1 63 .5 42 .4 36 .9 4, 52 6 R eg io n Ka m pa la 12 .0 4. 7 16 .6 27 .4 20 .7 48 .2 39 .4 25 .4 64 .8 74 .3 62 .0 39 7 C en tra l 1 15 .4 11 .0 26 .5 18 .8 18 .6 37 .3 34 .2 29 .6 63 .8 58 .5 48 .1 55 9 C en tra l 2 22 .3 13 .1 35 .4 17 .1 16 .6 33 .7 39 .4 29 .7 69 .1 48 .8 44 .5 56 5 Ea st C en tra l 24 .6 17 .2 41 .9 13 .9 18 .1 32 .0 38 .5 35 .3 73 .8 43 .3 37 .5 58 0 Ea st er n 22 .4 15 .9 38 .3 10 .1 16 .0 26 .1 32 .5 31 .9 64 .5 40 .5 35 .9 85 9 Ka ra m oj a 11 .3 9. 2 20 .5 6. 3 1. 5 7. 8 17 .6 10 .7 28 .3 27 .6 26 .1 21 5 N or th 27 .5 15 .0 42 .5 12 .2 11 .8 23 .9 39 .7 26 .7 66 .4 36 .0 35 .2 48 7 W es t N ile 28 .0 15 .0 42 .9 8. 7 5. 8 14 .6 36 .7 20 .8 57 .5 25 .3 23 .7 33 0 W es te rn 18 .3 12 .1 30 .4 20 .2 12 .5 32 .7 38 .5 24 .6 63 .1 51 .8 42 .5 74 3 So ut hw es t 21 .0 15 .8 36 .9 9. 8 19 .7 29 .6 30 .9 35 .6 66 .4 44 .5 37 .8 68 1 Ed uc at io n N o ed uc at io n 12 .9 21 .3 34 .1 6. 9 11 .1 17 .9 19 .7 32 .3 52 .1 34 .5 29 .7 87 7 P rim ar y 23 .8 14 .2 38 .0 12 .4 15 .6 28 .0 36 .1 29 .8 65 .9 42 .4 37 .2 3, 31 3 Se co nd ar y + 18 .3 6. 1 24 .4 26 .7 17 .5 44 .2 45 .0 23 .6 68 .6 64 .4 55 .0 1, 22 7 W ea lth q ui nt ile Lo w es t 26 .0 16 .3 42 .3 7. 9 6. 8 14 .7 33 .9 23 .0 57 .0 25 .8 22 .3 1, 06 3 Se co nd 22 .8 16 .4 39 .2 11 .9 11 .3 23 .2 34 .7 27 .7 62 .4 37 .2 34 .0 1, 10 1 M id dl e 20 .7 13 .5 34 .2 13 .9 15 .4 29 .3 34 .6 28 .9 63 .5 46 .1 38 .9 1, 04 2 Fo ur th 20 .3 13 .9 34 .3 13 .7 21 .3 35 .0 34 .0 35 .3 69 .3 50 .6 44 .8 99 7 H ig he st 14 .8 8. 1 22 .9 24 .7 21 .4 46 .2 39 .5 29 .5 69 .0 66 .9 56 .7 1, 21 5 To ta l 20 .8 13 .5 34 .3 14 .7 15 .3 30 .0 35 .5 28 .8 64 .3 46 .7 40 .5 5, 41 8 N ot e: N um be rs in th is ta bl e co rre sp on d to th e re vi se d de fin iti on o f u nm et n ee d de sc rib ed in B ra dl ey e t a l., 2 01 2. 1 T ot al d em an d is th e su m o f u nm et n ee d an d m et n ee d. 2 P er ce nt ag e of d em an d sa tis fie d is m et n ee d di vi de d by to ta l d em an d. Family Planning • 91 92 • Family Planning The government’s target in the Health Sector Strategic and Investment Plan is to reduce the unmet need for family planning in Uganda to 20 percent by 2015. Figure 7.2 shows that unmet need first increased from the 2000-01 to the 2006 UDHS surveys; then it decreased to 34 percent in the 2011 survey. Figure 7.2 Trends in unmet need for family planning, Uganda 2000-2011 Uganda DHS 2011 35 38 34 2000-2001 2006 2011 Percentage 2000-01 Note: Estimates for all years are according to the revised definition of unmet need 7.13 FUTURE USE OF CONTRACEPTION Future demand for specific methods of family planning can be assessed. Nonusers who intend to use contraception in the future are asked which methods they prefer to use. This is an important indicator of how demand for family planning may change in the future. In the survey, women who were not currently using a method of contraception were asked about their intention to use family planning in the future. Results are presented in Table 7.12. Almost two-thirds (64 percent) of currently married nonusers intend to use family planning in the future, while 31 percent do not. The proportion of women intending to use contraception increases from 54 percent for those with no child to a peak at 69 percent for those with three children, after which it declines to 63 percent among those with four or more children. The data reflect no significant change from the 2006 UDHS. Table 7.12 Future use of contraception Percent distribution of currently married women age 15-49 who are not using a contraceptive method by intention to use in the future, according to number of living children, Uganda 2011 Intention Number of living children1 Total 0 1 2 3 4+ Intends to use 54.1 64.7 65.3 68.8 62.9 63.9 Unsure 7.9 3.7 4.6 4.4 4.8 4.7 Does not intend to use 37.3 31.5 29.7 26.4 32.3 31.2 Missing 0.8 0.1 0.4 0.4 0.1 0.2 Total 100.0 100.0 100.0 100.0 100.0 100.0 Number of women 175 489 627 541 1,959 3,791 1 Includes current pregnancy Family Planning • 93 7.14 EXPOSURE TO FAMILY PLANNING MESSAGES The mass media play an important role in communicating messages about family planning. Data on the level of exposure to radio, television, and printed materials are important for programme managers and planners to effectively target population subgroups for information, education, and communication campaigns. To assess the effectiveness of the dissemination of family planning information through various media, interviewers asked respondents in the 2011 UDHS if they had been exposed to family planning messages on the radio or television, in video or films, and in print (newspapers and magazines) in the few months preceding the survey. The results are shown in Table 7.13. Radio is the most popular source for family planning messages in Uganda, with 70 percent of women and 74 percent of men age 15-49 having heard a family planning message on a radio in the past few months. Among women, fifteen percent each report having seen a family planning message on television or in a newspaper or magazine, while among men these proportions are 17 percent and 25 percent, respectively. The second most popular source of messages is the print media (newspapers and magazines), with 15 percent of women and 25 percent of men having seen a family planning message in one or the other. Four percent of women and 9 percent of men had seen a family planning message in a video or film. Table 7.13 Exposure to family planning messages Percentage of women and men age 15-49 who heard or saw a family planning message on radio, on television, in a newspaper or magazine, or in a video or film in the past few months, according to background characteristics, Uganda 2011 Background characteristic Women Men Radio Tele- vision News- paper/ magazine Video/ film None of these four media sources Number of women Radio Tele- vision News- paper/ magazine Video/ film None of these four media sources Number of men Age 15-19 61.1 14.9 18.4 5.1 34.2 2,048 66.5 12.8 21.0 9.2 29.3 554 20-24 74.7 19.1 18.1 5.6 22.1 1,629 74.3 19.5 28.5 12.0 21.2 318 25-29 72.0 16.4 13.8 4.2 24.5 1,569 76.5 21.2 29.5 11.1 19.6 361 30-34 72.1 16.9 13.8 3.5 24.2 1,086 80.3 20.3 27.7 9.8 16.4 323 35-39 70.4 10.7 12.2 3.3 27.1 1,026 73.9 15.5 23.6 8.1 21.9 268 40-44 71.1 10.9 12.2 2.2 27.0 729 77.3 11.9 16.5 4.4 20.8 191 45-49 68.6 11.9 12.2 3.1 30.4 587 79.6 14.1 29.4 4.5 17.6 157 Residence Urban 73.4 47.7 33.6 9.8 17.1 1,717 74.0 43.1 48.6 12.9 18.0 439 Rural 68.5 7.1 10.7 2.9 29.7 6,957 74.2 9.9 19.1 8.2 23.1 1,734 Region Kampala 69.7 66.6 37.9 9.6 15.1 839 70.5 51.6 45.1 8.3 19.4 221 Central 1 75.1 23.4 20.2 5.0 20.9 956 70.3 20.4 28.2 10.7 24.5 209 Central 2 75.6 18.3 22.3 4.2 22.2 902 87.9 26.5 42.0 22.3 9.7 236 East Central 67.5 11.5 13.8 6.7 31.2 869 68.6 15.9 24.1 10.9 25.9 236 Eastern 66.0 4.9 7.9 2.2 32.6 1,267 66.2 6.4 15.9 4.8 29.8 289 Karamoja 30.3 1.1 5.3 1.6 69.0 289 38.7 1.0 8.7 7.7 60.3 55 North 69.4 1.9 3.6 2.5 30.1 735 71.6 2.7 12.3 3.5 26.9 199 West Nile 53.6 1.6 17.9 1.9 39.7 500 71.5 14.5 6.9 2.7 27.2 133 Western 74.2 8.8 13.0 5.0 23.8 1,221 78.7 13.2 28.0 9.5 18.6 322 Southwest 77.1 6.7 9.3 2.1 22.0 1,097 86.4 6.9 20.0 7.3 12.0 273 Education No education 54.2 2.8 2.2 0.9 45.0 1,120 45.0 8.9 4.8 5.5 50.6 90 Primary 68.6 8.6 7.9 2.2 29.1 5,152 72.0 10.8 14.1 7.1 25.6 1,309 Secondary + 78.4 35.0 37.1 10.2 14.8 2,402 81.1 27.5 45.9 13.0 12.8 774 Wealth quintile Lowest 52.8 1.2 4.3 1.1 45.2 1,519 59.1 5.6 9.9 5.1 37.7 345 Second 65.8 2.6 6.3 1.3 33.1 1,579 74.6 6.3 13.2 4.6 23.1 423 Middle 72.7 3.6 7.3 2.2 26.2 1,608 74.3 7.9 17.8 8.3 23.7 402 Fourth 75.8 8.6 14.1 3.9 22.4 1,726 82.2 14.3 25.9 11.4 15.4 486 Highest 76.1 46.8 35.7 10.2 15.3 2,242 76.2 41.4 49.6 14.1 15.9 517 Total 15-49 69.5 15.2 15.3 4.2 27.2 8,674 74.2 16.6 25.0 9.1 22.1 2,173 50-54 na na na na na na 86.9 16.5 26.1 9.3 12.8 122 Total 15-54 na na na na na na 74.8 16.6 25.1 9.1 21.6 2,295 na = Not applicable 94 • Family Planning Overall, 27 percent of women and 22 percent of men have not been exposed to any family planning messages in any of the four specified media sources. As expected, women and men in urban areas are more likely to be exposed to family planning messages in the media than are their rural counterparts. Regional variations show that respondents in Karamoja are the least likely to be exposed to family planning messages from any sources, with 69 percent of women and 60 percent of men reporting having not seen or heard any family planning messages. By contrast, women in Kampala and men in Central 2 have the lowest proportions of respondents (15 percent and 10 percent) who have not been exposed to any of the four media sources. The likelihood of exposure to media messages on family planning from any of the four media sources rises as the respondent’s level of education and wealth increase. 7.15 CONTACT OF NONUSERS WITH FAMILY PLANNING PROVIDERS To gain insight into the level of contact between nonusers and family planning providers, interviewers in the 2011 UDHS asked women who were not using contraception whether a fieldworker or health worker had visited them during the 12 months preceding the survey and discussed family planning. In addition, women were asked whether they had visited a health facility in the 12 months preceding the survey for any reason and whether anyone at the facility had discussed family planning with them during the visit. This information is important to determine whether family planning initiatives in Uganda are reaching nonusers of family planning. Table 7.14 shows that only 9 percent of female nonusers had been visited by fieldworkers to discuss family planning during the 12 months preceding the survey. Among women who were not using contraception, only 18 percent had visited a health facility and discussed family planning at the facility in the past 12 months, while 44 percent had visited a health facility but did not discuss family planning. Table 7.14 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, Uganda 2011 Background characteristic Percentage of women who were visited by fieldworker who discussed family planning Percentage of women who visited a health facility in the past 12 months and who: Percentage of women who did not discuss family planning either with fieldworker or at a health facility Number of women Discussed family planning Did not discuss family planning Age 15-19 6.9 7.2 33.6 87.2 1,908 20-24 9.4 23.4 48.5 70.8 1,269 25-29 11.3 24.0 51.2 70.1 1,074 30-34 9.9 25.5 48.1 70.8 722 35-39 6.7 20.1 50.5 75.2 673 40-44 6.2 21.8 43.6 73.7 496 45-49 10.2 10.9 47.5 82.4 484 Residence Urban 8.7 16.3 44.8 78.5 1,150 Rural 8.6 18.0 44.3 76.6 5,475 Region Kampala 7.4 13.2 44.6 82.4 570 Central 1 5.9 11.7 48.1 83.7 676 Central 2 6.6 18.7 48.9 77.0 644 East Central 8.8 17.0 42.9 78.0 639 Eastern 6.9 19.7 47.1 76.0 1,004 Karamoja 14.4 24.1 46.6 68.5 269 North 8.9 23.3 34.5 71.6 599 West Nile 13.0 19.2 36.5 73.8 441 Western 10.0 19.2 45.4 74.1 907 Southwest 8.9 14.4 44.9 78.9 877 Education No education 7.4 16.1 47.5 79.7 934 Primary 8.6 18.0 44.2 76.4 4,023 Secondary + 9.2 17.8 43.1 76.5 1,668 Wealth quintile Lowest 9.6 21.3 46.2 72.8 1,333 Second 8.1 18.4 44.1 76.8 1,291 Middle 8.7 17.7 46.5 77.1 1,244 Fourth 8.1 17.0 41.5 77.2 1,265 Highest 8.4 14.4 43.6 80.2 1,492 Total 8.6 17.7 44.4 76.9 6,625 Family Planning • 95 Seventy-seven percent of female nonusers did not discuss family planning with a fieldworker or at a health facility in the 12 months preceding the survey. There are no substantial differences in the contact of nonusers with family planning providers by background characteristics, with the exception of regional variations. Nonusers in Karamoja (14 percent) and West Nile (13 percent) regions are more likely to be contacted about family planning by a fieldworker than those from other regions, increases of 4 and 3 percent, respectively, over percentages reported in the 2006 UDHS survey. This improvement is probably due to the strong Village Health Team programme in these regions. 7.16 FAMILY PLANNING COUNSELING The 2011 UDHS included questions on family planning counseling for women during the post- miscarriage, post-abortion, or post-stillbirth period. It also contained questions on family planning counseling for women who gave birth in a health facility in the five years preceding the survey thus allowing determination of the percentage who received counseling before their discharge. The results are shown in Table 7.15. Only 28 percent of women who had a miscarriage, abortion, or stillbirth in the five years preceding the survey were counselled on family planning after the pregnancy ended. Among women who had a live birth in a health facility in the five years preceding the survey, only 16 percent were counseled on family planning during their postpartum checkup before discharge. These results indicate many missed opportunities to provide family planning counseling and services to women who may need them to limit or space their births. The proportion of women who had a miscarriage, abortion, or a stillbirth in the five years preceding the survey and who were counseled on family planning after their pregnancy ended is lowest among women age 40-49, those in urban areas, and women in the East Central region. There are no clear variations by women’s education or wealth. Table 7.15 Family planning counseling Among women age 15-49 who had a miscarriage, abortion, or stillbirth in the five years preceding the survey, the percentage who received family planning counseling when the pregnancy ended, and among women who gave birth in a health facility in the five years preceding the survey, the percentage who received counseling before discharge, by background characteristics, Uganda 2011 Background characteristic Among women with a miscarriage, stillbirth, or abortion that ended in the five years preceding the survey, percentage who received counseling Number of women Among women who gave birth in a health facility in the five years preceding the survey, percentage who received counseling before discharge Number of women Age 15-19 34.6 67 11.9 370 20-24 27.4 180 15.2 1,197 25-29 29.8 193 15.7 1,337 30-34 35.0 115 17.0 875 35-39 26.5 131 16.4 719 40-44 19.5 104 18.5 358 45-49 23.7 57 23.1 112 Residence Urban 22.2 146 28.6 805 Rural 29.5 700 13.6 4,163 Region Kampala 21.5 63 33.7 358 Central 1 31.4 102 13.8 504 Central 2 19.9 118 14.7 507 East Central 15.8 113 10.3 532 Eastern 35.3 108 17.1 794 Karamoja 50.2 27 17.9 186 North 24.7 61 18.8 445 West Nile 27.3 45 19.6 299 Western 26.3 114 13.2 739 Southwest 44.7 96 11.1 604 Education No education 23.7 127 10.7 713 Primary 27.4 534 14.0 3,079 Secondary + 33.8 186 24.5 1,177 Wealth quintile Lowest 27.5 142 11.8 1,055 Second 29.7 151 12.6 1,026 Middle 23.8 172 13.3 963 Fourth 31.1 167 15.9 897 Highest 28.9 214 26.4 1,027 Total 28.2 846 16.0 4,968 96 • Family Planning The proportion of women who had a live birth in a health facility in the five years preceding the survey and were counseled on family planning before their discharge is lowest among the youngest women (age 15-19), rural women, those in East Central and Southwest regions, women with no education, and those in the lowest wealth quintile. Infant and Child Mortality • 97 INFANT AND CHILD MORTALITY 8 his chapter presents levels, trends, and differentials in perinatal, neonatal, postneonatal, infant, child, and under-5 mortality in Uganda. 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-5 mortality rate by two-thirds between 1990 and 2015. Results from the 2011 UDHS can be used to monitor the impact of major interventions, strategies, and policies at the national level. Policies that affect the under 5 mortality rate are the National Health Policy (NHP II 2010/19) and the Health Sector Strategic and Investment Plan (HSSIP 2010/11-2014/15). The data used to estimate mortality 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 who live 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 are 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 arithmetic difference between neonatal and infant 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  Under-5 mortality (5q0): the probability of dying between birth and the fifth birthday T Key Findings  One in every 19 Ugandan children dies before the first birthday, and one in every 11 children dies before the fifth birthday.  Infant mortality declined from 88 deaths to 54 deaths per 1,000 live births between the 2000-01 UDHS and the 2011 UDHS.  Under-5 mortality from 152 deaths per 1,000 live births to 90 deaths per 1,000 live births between the two survey periods.  Childhood mortality is higher in rural areas than in urban areas. The mortality rates were lowest in Kampala.  The neonatal and postneonatal mortality rates were 27 deaths per 1,000 live births, each. The perinatal mortality rate was 40 deaths per 1,000 pregnancies. 98 • Infant and Child Mortality 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 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 less than 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 age 2, and in years if the child died at age 2 or older. Interviewers were also asked to probe for deaths reported at age 1 year 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 age 12 months, which is likely to lead to some underestimation of infant mortality. 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 UDHS, the proportion of infant deaths occurring in the first month of life is 53 percent for the period zero to four years preceding the survey (Appendix Table C.6), which is within the normal range. Appendix Table C.5 shows death heaping at 7 and 14 days, which indicates rounding of age at death to one and two weeks, respectively. The age heaping at seven days leads to lower estimates of early neonatal mortality and perinatal mortality. However, it appears that early neonatal deaths among births that occurred in the first month of life have not been seriously underreported, since 76 percent of neonatal deaths were early neonatal deaths for the period zero to four years before the survey. Displacement of birth dates may distort mortality trends. This can occur if an interviewer knowingly records a death as occurring in an earlier year, which could happen if an interviewer were trying to cut down on the overall workload, because a lengthy set of additional questions must be 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 2006 to 2005, but relatively little transference for living children. This suggests that under-5 mortality is likely to be underestimated to some extent for the five-year period before the survey. 8.2 EARLY CHILDHOOD MORTALITY RATES: LEVELS AND TRENDS 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 54 per 1,000 live births. This implies that one in every 19 babies born in Uganda does not live to the first birthday. Those who survive to the first birthday, 38 out of 1,000 would die before reaching their fifth birthday. This shows that one in 11 children dies before their fifth birthday. The under-five mortality rate was 90 per 1,000 live births. The first month of life is associated with the highest risk to survival. As childhood mortality declines, postneonatal mortality usually declines faster than the neonatal mortality Infant and Child Mortality • 99 because neonatal mortality is frequently caused by biological factors that are not easily addressed by primary health care interventions. The neonatal and postneonatal mortality rates were 27 deaths per 1,000 live births, each. Results from the 2011 UDHS data show a remarkable decline in all levels of childhood mortality over the 15-year period preceding the survey. Infant mortality declined by 39 percent, from 89 deaths per 1,000 live births to 54 deaths per 1,000 live births. Furthermore, under-5 mortality declined by 37 percent over the same period, from 143 deaths per 1,000 live births to 90 deaths per 1,000 live births. As childhood mortality declines, postneonatal mortality usually declines faster than neonatal mortality because neonatal mortality is frequently caused by biological factors that are not easily addressed by primary care interventions. This is corroborated in the data: the neonatal and postneonatal mortality declined over the 15-year period preceding the survey by 21 percent and 50 percent, respectively. Mortality trends can also be examined by comparing data from UDHS surveys conducted in 2000-01, 2006, and 2011. Figure 8.1 shows improvement in all components of early childhood mortality rates. Under-5 mortality declined from 152 deaths per 1,000 live births in the 2000-01 UDHS to 90 in the 2011 UDHS, infant mortality declined from 88 deaths to 54 deaths per 1,000 live births, and postneonatal mortality declined from 55 deaths to 27 deaths per 1,000 live births during the same period. The change in neonatal mortality rate is not as pronounced; it declined from 33 deaths per 1,000 live births in 2000-01 to 29 deaths per 1,000 live births in 2006, and it declined only slightly to 27 deaths per 1,000 deaths in 2011. Figure 8.1 Trends in childhood mortality 33 55 88 69 152 29 46 76 67 137 27 27 54 38 90 Neonatal Postneonatal Infant Child Under-five 0 20 40 60 80 100 120 140 160 180 Deaths per 1,000 2000-01 2006 2011 Note: In the 2000-2001 UDHS, areas making up the districts of Amuru, Nwoya, Bundibugyo, Ntoroko, Gulu, Kasese, Kitgum, Lamwo, Agago, and Pader were excluded from the sample. These areas contained about 5 percent of the national population of Uganda. Thus, the trends need to be viewed in that light. Data refer to the 5 years before the survey. Table 8.1 Early childhood mortality rates Neonatal, postneonatal, infant, child, and under-5 mortality rates for five-year periods preceding the survey, Uganda 2011 Years preceding the survey Neonatal mortality (NN) Post- neonatal mortality (PNN)1 Infant mortality (1q0) Child mortality (4q1) Under-5 mortality (5q0) 0-4 27 27 54 38 90 5-9 34 43 77 52 125 10-14 34 54 89 60 143 1 Computed as the difference between the infant and neonatal mortality rates 100 • Infant and Child Mortality 8.3 EARLY CHILDHOOD MORTALITY RATES BY SOCIOECONOMIC CHARACTERISTICS Table 8.2 shows differentials in childhood mortality by socioeconomic characteristics of the mother for the 10-year period preceding the survey. All childhood mortality rates, except neonatal mortality, are lower in urban than in rural areas. For example, the infant and under-5 mortality rates in rural areas are 66 and 111 deaths per 1,000 live births compared with 54 and 77 deaths per 1,000 live births, respectively, in urban areas. There are substantial regional variations in early childhood mortality rates. With the exception of neonatal mortality, Kampala, an entirely urban region with a higher socioeconomic status than the other regions, has the lowest childhood mortality rates when compared with other regions. The infant mortality rate ranges from a low of 47 deaths per 1,000 live births in Kampala to 87 and 88 deaths per 1,000 live births in Karamoja and West Nile, respectively. Similarly, the under-5 mortality is lowest in Kampala (65 deaths per 1,000 live births) and highest in Karamoja (153 deaths per 1,000 live births). As expected, the mother’s level of education is associated with the child’s probability for survival. Generally, children born to mothers with secondary or higher education have much lower childhood mortality rates when compared with children of uneducated mothers. For example, child mortality among children born to mothers with no education (59 deaths per 1,000 live births) is more than double that of children born to mothers with secondary or higher education (23 deaths per 1,000 live births). Similarly, the under-5 mortality among children born to uneducated mothers is 133 deaths per 1,000 live births compared with 79 deaths per 1,000 live births among children born to mothers with secondary or higher education. The only exception is neonatal mortality, where there is no clear pattern by mother’s education. With the exception of neonatal mortality, all other childhood mortality rates are highest among children in the lowest or second lowest wealth quintile and lowest among those in the wealthiest quintile. For example, under-5 mortality ranges from 72 deaths per 1,000 live births among the richest children to 125 deaths per 1,000 live births among children in the second lowest quintile. Table 8.2 Early childhood mortality rates by socioeconomic characteristics Neonatal, postneonatal, infant, child, and under-5 mortality rates for the 10-year period preceding the survey, by background characteristics, Uganda 2011 Background characteristic Neonatal mortality (NN) Post- neonatal mortality (PNN)1 Infant mortality (1q0) Child mortality (4q1) Under-5 mortality (5q0) Residence Urban 31 23 54 25 77 Rural 30 36 66 47 111 Region Kampala 27 20 47 19 65 Central 1 44 31 75 37 109 Central 2 31 23 54 35 87 East Central 23 38 61 48 106 Eastern 24 23 47 41 87 Karamoja 29 59 87 72 153 North 31 35 66 42 105 West Nile 38 50 88 41 125 Western 30 38 68 52 116 Southwest 33 42 76 57 128 Mother's education No education 32 46 78 59 133 Primary 29 34 63 45 105 Secondary+ 33 24 57 23 79 Wealth quintile Lowest 26 50 76 52 123 Second 31 38 69 60 125 Middle 30 34 64 38 100 Fourth 33 30 63 44 104 Highest 34 14 48 25 72 1 Computed as the difference between the infant and neonatal mortality rates Infant and Child Mortality • 101 8.4 EARLY CHILDHOOD MORTALITY BY DEMOGRAPHIC CHARACTERISTICS The demographic charac- teristics of both mothers and children play an important role in the survival probability 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 child’s size at birth). Table 8.3 shows that childhood mortality rates are consistently higher among male children than among their female counterparts. For example, the infant and under-5 mortality rates for males are 70 deaths and 114 deaths per 1,000 live births, respectively, compared with 59 deaths and 98 deaths per 1,000 live births, respectively, for females. Although there is no clear pattern in the variation of childhood mortality rates by mother’s age at birth, these rates are lowest among children whose mother’s age at birth was 20-29. Childhood mortality rates are highest among children of first and seventh or higher birth order. For example, under-5 mortality is 120 deaths and 134 deaths per 1,000 live births for children of the first and seventh or higher birth order compared with 90 to 98 deaths per 1,000 live births for other children. Short birth intervals (those less than two years) substantially reduce children’s chances of survival. For example, the infant mortality rate is 95 deaths per 1,000 live births for children born less than two years following a preceding birth compared with 46 to 49 deaths per 1,000 live births for children born after longer intervals. Children’s weight at birth is an important determinant of their survival. Because many births in Uganda occur at home and, as a result, children often are not weighed at birth, data on birth weight are available for only a few children. However, in the 2011 UDHS mothers were asked whether their child was very large, larger than average, average, smaller than average, or very small at birth, and the answer was used as a proxy for a child’s weight. Babies who were reported as smaller than average or very small at birth had higher mortality rates than those who were reported as average or larger at birth. The data show that 66 in 1,000 children who were reported as small or very small at birth died before reaching their first birthday compared with 50 deaths per 1,000 children who were reported as average or large. This differential is most pronounced for neonatal mortality (38 deaths per 1,000 live births for children born small or very small compared with 23 deaths per 1,000 live births for those born average or larger). Table 8.3 Early childhood mortality rates by demographic characteristics Neonatal, postneonatal, infant, child, and under-5 mortality rates for the 10-year period preceding the survey, by demographic characteristics, Uganda 2011 Demographic characteristic Neonatal mortality (NN) Post- neonatal mortality (PNN)1 Infant mortality (1q0) Child mortality (4q1) Under-5 mortality (5q0) Child's sex Male 34 36 70 48 114 Female 27 33 59 41 98 Mother's age at birth <20 43 34 77 44 117 20-29 27 30 57 42 96 30-39 27 44 71 50 118 40-49 49 21 70 63 129 Birth order 1 46 33 78 45 120 2-3 25 28 54 38 90 4-6 24 35 59 42 98 7+ 36 44 80 59 134 Previous birth interval2 <2 years 36 59 95 54 144 2 years 22 27 49 41 88 3 years 23 23 46 42 86 4+ years 28 18 46 34 78 Birth size3 Small/very small 38 28 66 na na Average or larger 23 27 50 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 102 • Infant and Child Mortality 8.5 PERINATAL MORTALITY In the 2011 UDHS women were asked 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. Perinatal deaths refer to 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). Underreporting remains a problem, especially with regard to early deaths and stillbirths. 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 the number of stillbirths and early neonatal deaths divided by the number of pregnancies of seven or more months’ duration. The perinatal mortality is an important indicator in providing the infor- mation needed to improve the health status of pregnant women, new mothers, and newborns. Table 8.4 shows that out of the 8,240 reported pregnancies of at least seven months’ gestation in the five years preceding the survey, 165 were stillbirths and 164 were early neonatal deaths, yielding an overall perinatal mortality rate of 40 per 1,000 pregnancies. The perinatal mortality rate is highest among births to young mothers less than age 20 (61 deaths per 1,000 pregnancies) and old mothers age 40-49 (86 deaths per 1,000 pregnancies) compared with women age 20-29 and 30-39 (33 to 34 deaths per 1,000 pregnancies, respectively). Table 8.4 further shows that first births and births that occur within 15 months of a previous birth have the highest perinatal mortality at 60 and 62 pregnancy losses or early deaths per 1,000 pregnancies, respectively. The safest pregnancy interval is between 27 and 38 months, which has a perinatal mortality rate of 24 pregnancy losses or early deaths per 1,000 pregnancies, which is less than half the risk for first pregnancies or pregnancies with a birth interval of less than 15 months. Table 8.4 Perinatal mortality Number of stillbirths and early neonatal deaths, and the perinatal mortality rate for the 5- year period preceding the survey, by background characteristics, Uganda 2011 Background characteristic Number of stillbirths1 Number of early neonatal deaths2 Perinatal mortality rate3 Number of pregnancies of 7+ months duration Mother's age at birth <20 46 40 61 1,396 20-29 68 76 33 4,427 30-39 35 38 34 2,115 40-49 16 10 86 302 Previous pregnancy interval in months4 First pregnancy 46 35 60 1,361 <15 21 15 62 583 15-26 48 49 38 2,550 27-38 24 26 24 2,131 39+ 25 38 39 1,615 Residence Urban 17 23 35 1,164 Rural 147 141 41 7,076 Region Kampala 7 9 33 496 Central 1 20 19 47 817 Central 2 19 19 44 861 East Central 13 14 28 936 Eastern 21 23 32 1,380 Karamoja 6 10 48 328 North 6 9 22 711 West Nile 6 13 39 490 Western 37 29 54 1,214 Southwest 29 19 48 1,007 Mother's education No education 17 17 29 1,178 Primary 123 101 42 5,284 Secondary+ 25 46 40 1,779 Wealth quintile Lowest 29 24 29 1,841 Second 43 44 49 1,769 Middle 28 28 34 1,643 Fourth 35 36 49 1,460 Highest 30 32 41 1,527 Total 165 164 40 8,240 1 Stillbirths are fetal deaths in pregnancies lasting seven or more months. 2 Early neonatal deaths are deaths at age 0-6 days among live-born children. 3 The sum of the number of stillbirths and early neonatal deaths divided by the number of pregnancies of seven or more months' duration, expressed per 1000. 4 Categories correspond to birth intervals of <24 months, 24-35 months, 36-47 months, and 48+ months Infant and Child Mortality • 103 The perinatal mortality rate is higher in rural than in urban areas (41 versus 35 stillbirths or early deaths per 1,000 pregnancies, respectively). It is highest in the Western region (54 stillbirths or early deaths per 1,000 pregnancies) and lowest in the North region (22 stillbirths or early deaths per 1,000 pregnancies). Unlike data from the 2006 UDHS, the 2011 data show that perinatal mortality is lowest among mothers with no education. Women in the lowest wealth quintile have the lowest perinatal mortality rate of 29 pregnancy losses or early deaths per 1,000 pregnancies, while those in the second and fourth quintiles have the highest perinatal mortality of 49 pregnancy losses or early deaths per 1,000 pregnancies. 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 preg- nancy 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: 66 percent of births have high mortality risks that are avoidable; 42 percent fall into a single high-risk category, and 24 percent are in a multiple high-risk category. Only 22 percent of births are not in any high-risk category. 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 older than age 34 with a birth interval less than 24 months and of the third order or above. These children are about three times (2.75) as likely to die as children not in any high-risk category. Fortunately, only 3 percent of births fall into this 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, Uganda 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 22.0 1.00 16.6a Unavoidable risk category First order births between ages 18 and 34 years 12.5 1.30 4.7 Single high-risk category Mother's age <18 5.9 1.86 0.5 Mother's age >34 0.3 * 1.7 Birth interval <24 months 7.5 1.22 9.6 Birth order >3 27.9 1.18 20.0 Subtotal 41.7 1.28 31.8 Multiple high-risk category Age <18 and birth interval <24 months2 0.7 2.14 0.3 Age >34 and birth interval <24 months 0.0 * 0.1 Age >34 and birth order >3 10.6 1.50 24.3 Age >34 and birth interval <24 months and birth order >3 2.7 2.75 5.4 Birth interval <24 months and birth order >3 9.9 2.09 16.8 Subtotal 23.8 1.90 46.9 In any avoidable high-risk category 65.5 1.51 78.7 Total 100.0 na 100.0 Number of births/women 8,077 na 5,418 Note: Risk ratio is the ratio of the proportion dead among births in a specific high-risk category to the proportion dead among births not in any high-risk category. An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. na = Not applicable 1 Women are assigned to risk categories according to the status they would have at the birth of a child if they were to conceive at the time of the survey: current age less than 17 years and 3 months or older than 34 years and 2 months, latest birth less than 15 months ago, or latest birth being of order 3 or higher. 2 Includes the category age <18 and birth order >3 a Includes sterilized women 104 • Infant and Child Mortality 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 insight into the potential magnitude of high-risk births. Overall, 79 percent of currently married women have the potential for having a high-risk birth, with 32 percent falling into a single high-risk category and 47 percent falling into a multiple high-risk category. Maternal Health • 105 REPRODUCTIVE HEALTH 9 9.1 ANTENATAL CARE major objective of antenatal care is to identify and treat problems such as anaemia and infection. A well-designed and well-implemented antenatal care (ANC) programme therefore facilitates detection and treatment of such problems during pregnancy; it also provides an opportunity to disseminate health messages to women and their families. ANC from a trained provider is vital in monitoring the pregnancy and reducing the morbidity risk for the mother and child during pregnancy and delivery. In the 2011 UDHS, women who had given birth in the five years preceding the survey were asked about the type of ANC provider, number of ANC visits, number of months pregnant at the time of the first and last visits, and services and information provided during ANC. For women with two or more live births during the five-year period, data on antenatal care refer to the most recent birth only. 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. Women were asked to report on all persons they saw for antenatal care for their last birth. However, if a woman saw more than one provider, only the provider with the highest qualifications was considered in the tabulation of results. Ninety-five percent of mothers received antenatal care from a skilled provider (a doctor, nurse/midwife, or clinical officer/medical assistant) for their most recent birth in the five years preceding the survey. Less than one percent of mothers received antenatal care from a traditional birth attendant. Four percent of women received no antenatal care for births in the five years before the survey. A Key Findings  Ninety-five percent of mothers receive antenatal care from a skilled provider. This proportion has not changed since the 2006 UDHS.  Forty-eight percent of women make four or more antenatal care visits during their pregnancy, and this percentage has remained almost the same since 2006. The median duration of pregnancy for the first antenatal visit is 5.1 months.  More than half (51 percent) of the mothers were informed of possible complications during pregnancy, an increase from 35 percent in the 2006 UDHS.  Eighty-four percent of last-born children during the five-year period before the survey were fully protected against neonatal tetanus.  Fifty-eight percent of births in the past five years were assisted by a skilled provider, an increase from 42 percent in 2006.  The percentage of births taking place in a health facility has increased noticeably in the past five years from 41 percent in the 2006 UDHS to 57 percent in the 2011 UDHS.  One-third of women receive postnatal care in the first two days after delivery.  For births in the two years preceding the survey, only 2 percent received a postnatal checkup within one hour, while 13 percent received a postnatal checkup within six days.  Fifty-six percent of Ugandan women have heard of female circumcision while less than 2 percent of women have been circumcised.  Two percent of Ugandan women have ever experienced obstetric fistula. 106 • Maternal Health Women age 20-34 are more likely to receive antenatal care from a skilled provider than older mothers age 35-49. There is almost no variation by birth order in antenatal care received from a skilled provider. 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, Uganda 2011 Background characteristic Antenatal care provider No ANC Total Percentage receiving antenatal care from a skilled provider1 Number of women Doctor Nurse/ midwife Medical assistant/ clinical officer Traditional birth attendant Other Missing Mother's age at birth <20 11.5 80.5 0.9 0.9 0.8 0.0 5.3 100.0 93.0 703 20-34 12.2 82.2 1.7 0.4 0.2 0.1 3.2 100.0 96.1 3,412 35-49 12.8 77.1 1.6 0.9 0.2 0.1 7.2 100.0 91.5 853 Birth order 1 13.5 80.5 1.7 0.4 0.1 0.0 3.8 100.0 95.7 759 2-3 13.9 81.0 1.3 0.4 0.5 0.1 2.8 100.0 96.2 1,489 4-5 13.0 80.9 1.3 0.4 0.3 0.0 4.1 100.0 95.2 1,134 6+ 9.5 81.6 1.9 0.9 0.2 0.1 5.8 100.0 93.0 1,587 Residence Urban 22.4 74.4 0.6 0.1 0.1 0.0 2.4 100.0 97.4 805 Rural 10.3 82.4 1.7 0.7 0.3 0.1 4.6 100.0 94.4 4,163 Region Kampala 27.1 70.1 0.8 0.1 0.0 0.0 1.9 100.0 98.0 358 Central 1 20.0 66.5 1.3 1.8 0.9 0.0 9.6 100.0 87.8 504 Central 2 19.3 73.9 0.9 1.2 0.6 0.0 4.1 100.0 94.1 507 East Central 9.2 80.9 1.1 0.5 0.6 0.5 7.2 100.0 91.2 532 Eastern 7.3 85.1 1.8 0.0 0.2 0.0 5.5 100.0 94.3 794 Karamoja 1.9 93.5 1.2 0.5 0.4 0.0 2.5 100.0 96.6 186 North 8.7 89.3 0.7 0.1 0.0 0.0 1.2 100.0 98.7 445 West Nile 5.1 91.7 0.8 0.0 0.5 0.2 1.7 100.0 97.6 299 Western 11.6 79.6 4.6 0.4 0.0 0.0 3.7 100.0 95.9 739 Southwest 10.2 87.3 0.2 1.0 0.0 0.0 1.4 100.0 97.6 604 Education No education 8.4 82.8 1.1 1.3 0.6 0.0 5.8 100.0 92.3 713 Primary 10.5 82.4 1.9 0.5 0.3 0.1 4.3 100.0 94.8 3,079 Secondary + 19.2 76.5 0.9 0.2 0.2 0.0 3.1 100.0 96.6 1,177 Wealth quintile Lowest 6.3 86.0 1.6 0.3 0.1 0.0 5.7 100.0 93.9 1,055 Second 7.5 85.3 1.7 0.8 0.6 0.0 4.1 100.0 94.5 1,026 Middle 10.5 81.5 2.3 0.6 0.4 0.2 4.5 100.0 94.3 963 Fourth 13.2 80.0 1.2 0.9 0.4 0.1 4.0 100.0 94.5 897 Highest 23.8 72.3 1.0 0.2 0.0 0.0 2.7 100.0 97.1 1,027 Total 12.2 81.1 1.6 0.6 0.3 0.1 4.2 100.0 94.9 4,968 Note: If more than one source of ANC was mentioned, only the provider with the highest qualifications is considered in this tabulation. 1 Skilled provider includes doctor, nurse/midwife, and medical assistant/clinical officer There are only very minor differences in the use of antenatal care services between urban and rural women. Ninety-seven percent of urban mothers received antenatal care from a skilled provider compared with 94 percent of rural mothers. Almost all mothers living in the North region received antenatal care from a skilled provider compared with 88 percent of mothers in the Central 1 region. Over 90 percent of the women in the remaining regions received antenatal care from a skilled provider. The use of antenatal care services from a skilled provider increases with mother’s education. Ninety-two percent of women with no education received antenatal care from a skilled provider, compared with 95 percent of women with primary education and 97 percent of women with secondary and higher education. Similarly, women in the highest wealth quintile were more likely to receive care from a skilled provider (97 percent) compared with 94 percent of the women in the lowest wealth quintile. The proportion of women receiving antenatal care from a skilled provider has not changed in the past five years. Ninety-four percent of women received antenatal care from a skilled provider in 2006. However, the proportion of women who received care from a doctor increased from 9 percent in 2006 to 12 percent in 2011. Maternal Health • 107 9.1.1 Number and Timing of Antenatal Visits Regular antenatal care is helpful in identifying and preventing adverse pregnancy outcomes when it is sought early in the pregnancy and is continued through delivery. In line with the WHO guidelines, the Ministry of Health (MOH) recommends that a woman have at least four ANC visits, the first of which should be made in the first trimester. It is possible during these visits to detect health problems associated with a pregnancy. In the event of any complications, more frequent visits are advised, and admission to a health facility may be necessary. Table 9.2 presents information on the number of antenatal visits and the timing of the first antenatal visit for the most recent birth in the five years preceding the survey. The findings show that 48 percent of pregnant women make four or more antenatal care visits during their entire pregnancy. Urban women (57 percent) are more likely to have had four or more antenatal visits than rural women (46 percent). Only 21 percent of women made their first antenatal care visit before the fourth month of pregnancy. The median duration of pregnancy at the first antenatal care visit was 5.1 months (5.0 months in urban areas and 5.2 months in rural areas). Over the past 5 years, the results show almost no change in the percentage of women with four or more antenatal visits during their pregnancy (from 47 percent in 2006 to 48 percent in 2011). Overall, antenatal attendance by gestational age has improved only slightly. The median gestational age at first visit has decreased from 5.5 months in the 2006 UDHS to 5.1 months in the 2011 survey. 9.2 COMPONENTS OF ANTENATAL CARE Focused antenatal care hinges on the principle that every pregnancy is at risk of complications. Ensuring that pregnant women receive information and undergo screening for complications should be a routine part of all antenatal care visits. Therefore, apart from receiving basic care, every pregnant woman should be monitored for complications as outlined in the Sexual and Reproductive Health Policy Guidelines for Uganda (MOH, 2011). To assess ANC services, mothers in the 2011 UDHS were asked a number of questions about the care they received during pregnancy for their most recent live birth in the five years preceding the survey. Table 9.3 presents information on the content of ANC services during their most recent pregnancy for women with a live birth in the five years preceding the survey. Three-quarters of the mothers took iron tablets during pregnancy, while half of the women took drugs for parasites. Slightly more than half of the mothers were informed during their antenatal visits of the danger signs of pregnancy-related complications. Seventy-nine percent of the mothers were weighed during these visits. Blood pressure measurements were part of antenatal care for 59 percent of mothers. Urine and blood samples also were taken from 22 percent and 81 percent of women, respectively. 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, Uganda 2011 Number and timing of ANC visits Residence Total Urban Rural Number of ANC visits None 2.4 4.6 4.3 1 2.4 4.3 4.0 2-3 35.7 43.7 42.4 4+ 57.0 45.8 47.6 Don't know/missing 2.4 1.6 1.7 Total 100.0 100.0 100.0 Number of months pregnant at time of first ANC visit No antenatal care 2.4 4.6 4.3 <4 23.6 20.2 20.8 4-5 45.2 43.7 43.9 6-7 27.4 27.7 27.7 8+ 1.1 3.5 3.1 Don't know/missing 0.2 0.3 0.3 Total 100.0 100.0 100.0 Number of women 805 4,163 4,968 Median months pregnant at first visit (for those with ANC) 5.0 5.2 5.1 Number of women with ANC 785 3,971 4,756 108 • Maternal Health 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 or syrup and drugs for intestinal parasites during the pregnancy of the most recent birth, and among women receiving antenatal care (ANC) for the most recent live birth in the five years preceding the survey, the percentage receiving specific antenatal services, according to background characteristics, Uganda 2011 Background characteristic Among women with a live birth in the past five years, the percentage who during the pregnancy of their last birth: 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 Number of women with ANC for their most recent birth Took iron tablets or syrup Took intestinal parasite drugs Informed of signs of pregnancy complications Weighed Blood pressure measured Urine sample taken Blood sample taken Mother's age at birth <20 74.4 51.7 703 51.0 77.5 55.3 23.8 82.8 666 20-34 76.5 50.9 3,412 50.2 78.4 59.2 22.5 81.1 3,300 35-49 69.8 44.5 853 52.4 82.3 62.0 20.1 76.0 790 Birth order 1 78.0 51.1 759 56.4 77.5 64.6 32.3 86.4 730 2-3 78.6 52.8 1,489 51.0 80.5 59.0 22.6 85.9 1,445 4-5 74.6 50.8 1,134 49.6 78.3 58.4 21.8 78.3 1,087 6+ 70.7 45.9 1,587 48.3 78.5 57.1 17.4 74.0 1,494 Residence Urban 83.1 53.7 805 61.6 87.1 81.7 42.7 91.6 785 Rural 73.5 49.2 4,163 48.5 77.3 54.7 18.2 78.3 3,971 Region Kampala 83.9 51.5 358 68.4 92.5 91.5 56.0 95.2 352 Central 1 69.8 43.9 504 40.7 73.2 59.7 25.6 75.2 455 Central 2 77.5 51.2 507 33.9 76.6 59.0 22.3 78.3 486 East Central 69.6 37.6 532 32.2 74.4 48.6 13.0 73.0 491 Eastern 76.8 57.5 794 45.1 72.2 48.9 20.6 83.6 750 Karamoja 90.8 43.1 186 76.4 96.8 88.7 9.5 85.4 182 North 81.3 51.2 445 62.6 88.7 63.8 20.7 89.7 440 West Nile 86.4 61.9 299 60.9 91.9 75.0 11.9 68.3 294 Western 73.3 51.7 739 61.1 80.6 53.5 22.7 80.9 712 Southwest 61.7 46.7 604 49.7 68.0 47.7 19.3 77.3 595 Education No education 70.4 43.7 713 48.6 79.6 55.0 15.4 69.0 671 Primary 73.5 49.7 3,079 48.7 75.8 54.5 18.2 79.8 2,945 Secondary + 82.0 54.2 1,177 57.1 86.4 73.6 36.9 89.0 1,141 Wealth quintile Lowest 75.4 48.4 1,055 53.0 80.7 57.2 16.0 76.1 995 Second 72.5 48.3 1,026 48.9 74.9 48.5 16.3 76.7 984 Middle 71.0 47.1 963 45.9 73.9 51.0 17.6 78.3 919 Fourth 74.6 51.3 897 46.2 78.1 58.6 21.5 81.0 859 Highest 81.4 54.5 1,027 58.3 86.4 79.6 39.3 90.2 1,000 Total 75.1 49.9 4,968 50.7 78.9 59.1 22.3 80.5 4,756 The quality of antenatal care relates to a mother’s education, wealth, and place of residence, as well as birth order of her infant. For example, 57 percent of women with at least some secondary education were informed of signs of pregnancy complications, compared with 49 percent of women with little or no education. Results by wealth quintile generally show a U-shaped relationship. For example, more women in the lowest wealth quintile (53 percent) and highest wealth quintile (58 percent) were provided information about signs of pregnancy complications than women in the second, third, or fourth wealth quintiles. More urban women than rural women were provided with each of the components of antenatal care asked about in the survey. The overall quality of antenatal care has improved in the past five years. The percentage of women who were informed of complications during pregnancy increased from 35 to 51 percent, the percentage that had their blood pressure measured increased from 53 percent to 59 percent, and the percentage that had urine samples taken increased from 12 to 22 percent during the same period. Table 9.4 shows the percent distribution by the number of doses/times that drugs for intestinal parasites were taken among women with a live birth in the five years preceding the survey who reported that they took such drugs. Overall, 48 percent of women took one dose of drugs for intestinal worms, 24 percent took two doses, 14 percent took three doses, and 11 percent took four or more doses. There are no major variations by background characteristics. Maternal Health • 109 Table 9.4 Doses of drugs for intestinal worms Among women age 15-49 with a live birth in the five years preceding the survey who took intestinal parasite drugs during the pregnancy of the most recent birth, the percent distribution by the number of doses/times the intestinal parasite drugs were taken, according to background characteristics, Uganda 2011 Background characteristic Number of times/doses drugs for intestinal worms were taken Total Number of women 1 2 3 4+ Don't know Mother's age at birth <20 39.3 24.1 18.2 13.6 4.7 100.0 363 20-34 48.1 25.4 13.5 10.4 2.5 100.0 1,736 35-49 53.4 19.3 10.0 12.9 4.4 100.0 380 Birth order 1 41.7 24.2 18.2 11.1 4.7 100.0 388 2-3 45.4 27.1 14.1 10.6 2.7 100.0 787 4-5 51.9 21.9 13.8 10.5 1.9 100.0 576 6+ 49.8 23.2 10.7 12.6 3.7 100.0 729 Residence Urban 46.9 23.1 14.0 11.8 4.2 100.0 432 Rural 47.8 24.5 13.6 11.2 2.9 100.0 2,047 Region Kampala 52.3 22.3 13.7 7.3 4.4 100.0 184 Central 1 50.4 21.3 13.7 9.3 5.3 100.0 221 Central 2 47.7 27.5 11.4 9.4 4.0 100.0 260 East Central 40.3 25.3 19.6 10.5 4.2 100.0 200 Eastern 58.2 23.5 13.6 3.5 1.2 100.0 456 Karamoja 58.8 23.5 9.4 7.0 1.2 100.0 80 North 34.8 25.9 17.6 21.4 0.4 100.0 228 West Nile 35.8 24.7 13.5 21.3 4.7 100.0 185 Western 36.7 27.7 13.9 16.9 4.7 100.0 382 Southwest 60.4 19.7 9.4 9.0 1.6 100.0 282 Education No education 47.2 25.0 10.5 14.9 2.4 100.0 311 Primary 47.8 24.0 13.6 11.5 3.2 100.0 1,530 Secondary + 47.5 24.6 15.5 9.0 3.4 100.0 638 Wealth quintile Lowest 51.9 23.3 11.8 10.7 2.3 100.0 510 Second 43.3 26.0 14.0 14.4 2.3 100.0 496 Middle 46.9 23.2 15.4 10.2 4.2 100.0 454 Fourth 51.0 23.3 12.3 10.8 2.6 100.0 460 Highest 45.5 25.3 14.7 10.3 4.2 100.0 560 Total 47.7 24.3 13.7 11.3 3.1 100.0 2,480 9.3 TETANUS TOXOID VACCINATION Tetanus toxoid (TT) injections are given to women during pregnancy to prevent deaths from neonatal tetanus. Neonatal tetanus can result when sterile procedures are not followed in cutting the umbilical cord after delivery. In the 2011 UDHS, information was collected on the number of doses of TT vaccine the mother received during the pregnancy of her most recent birth during the five-year period prior to the survey. In addition, questions were included to ascertain whether mothers received tetanus injections prior to the last birth as a means of determining whether the last birth was fully protected from neonatal tetanus. Table 9.5 shows the percentage of women with a live birth in the five years preceding the survey who reported receiving TT injections during the pregnancy for the last live birth. Also shown is whether the last birth was fully protected against neonatal tetanus. An infant is considered to be fully protected if any of the following criteria are met: (1) the mother had two TT injections during the pregnancy; (2) the mother had two TT injections, the last of which was within 3 years of the last birth (3) the mother had at least 3 TT injections, the last of which was within 5 years of the last birth; (4) the mother had at least 4 TT injections, the last of which was within 10 years of the last birth; or (5) the mother had at least five TT injections prior to the pregnancy. 110 • Maternal Health 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, Uganda 2011 Background characteristic Percentage receiving two or more injections during last pregnancy Percentage whose last birth was protected against neonatal tetanus1 Number of mothers Mother's age at birth <20 54.9 80.2 703 20-34 56.9 85.0 3,412 35-49 50.4 84.6 853 Birth order 1 59.8 82.2 759 2-3 59.2 84.8 1,489 4-5 55.0 86.5 1,134 6+ 50.3 83.1 1,587 Residence Urban 61.3 86.4 805 Rural 54.4 83.8 4,163 Region Kampala 62.3 84.6 358 Central 1 57.8 80.3 504 Central 2 61.5 84.2 507 East Central 62.7 82.5 532 Eastern 44.7 84.8 794 Karamoja 67.7 93.1 186 North 59.8 84.3 445 West Nile 44.3 87.1 299 Western 53.9 83.6 739 Southwest 52.8 84.8 604 Education No education 52.6 79.8 713 Primary 53.2 83.7 3,079 Secondary + 63.1 88.5 1,177 Wealth quintile Lowest 50.8 83.8 1,055 Second 53.0 80.9 1,026 Middle 51.9 83.6 963 Fourth 56.9 84.2 897 Highest 64.9 88.7 1,027 Total 55.5 84.3 4,968 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 According to the 2011 UDHS results, 56 percent of the mothers received two or more tetanus toxoid injections during their pregnancy, and 84 percent of last-born children during the five-year period before the survey were fully protected against neonatal tetanus, an increase from 76 percent during the 2006 UDHS. There were regional variations in the percentage of last-born children who were fully protected against neonatal tetanus, with Karamoja region having the highest percentage (93 percent) and Central 1 having the lowest (80 percent). There is little variation in tetanus toxoid coverage by age at birth, birth order, or place of residence. However, there are differences by education. For example, 80 percent of births to women with no education in Uganda are protected against tetanus, compared with 89 percent of those births to women with secondary or higher education. Women living in wealthier households are more likely to have their births protected against tetanus than women living in less wealthy households. 9.4 PLACE OF DELIVERY An important component of efforts to reduce the health risks of mothers and children is increasing the proportion of babies delivered under the supervision of health professionals. Proper medical attention and hygienic conditions during delivery can reduce the risk of complications and infections that may cause Maternal Health • 111 death or serious illness to either the mother or the baby (or both). Data on delivery care were obtained for all births that occurred in the five years preceding the survey. Table 9.6 presents the percent distribution of live births in the five years preceding the survey by place of delivery, according to background characteristics. Fifty-seven percent of births take place in a health facility: 44 percent are delivered in a public-sector health facility and 13 percent in a private sector facility. Forty-two percent of deliveries in the last five years took place at home. Delivery in a health facility is common among young mothers less than age 20 (66 percent) and mothers of first-order births (73 percent). Children of women in urban areas are more likely to be delivered in an institutional setting than children born to rural women (90 percent versus 52 percent). 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, Uganda 2011 Background characteristic Health facility Home Other Missing Total Percentage delivered in a health facility Number of births Public sector Private sector Mother's age at birth <20 53.2 12.6 33.5 0.6 0.1 100.0 65.8 1,351 20-34 43.1 13.4 42.3 1.1 0.1 100.0 56.5 5,632 35-49 37.1 14.0 48.0 0.8 0.1 100.0 51.1 1,092 Birth order 1 56.5 16.6 26.2 0.6 0.1 100.0 73.1 1,423 2-3 46.7 14.4 38.0 0.8 0.1 100.0 61.1 2,523 4-5 40.5 11.8 46.3 1.4 0.1 100.0 52.3 1,816 6+ 36.1 11.5 51.2 1.0 0.2 100.0 47.6 2,313 Antenatal care visits1 None 22.2 10.0 64.9 1.7 1.2 100.0 32.2 212 1-3 41.0 12.1 45.9 1.0 0.0 100.0 53.1 2,305 4+ 51.8 16.6 30.6 1.0 0.0 100.0 68.5 2,366 Don't know/missing 63.3 22.0 14.7 0.0 0.0 100.0 85.3 86 Residence Urban 63.5 26.1 9.8 0.6 0.0 100.0 89.5 1,147 Rural 40.8 11.3 46.8 1.0 0.1 100.0 52.0 6,928 Region Kampala 56.4 36.5 6.7 0.4 0.0 100.0 92.9 489 Central 1 38.1 23.6 37.6 0.8 0.0 100.0 61.7 797 Central 2 49.4 19.7 30.2 0.6 0.0 100.0 69.1 842 East Central 42.8 24.3 32.3 0.2 0.4 100.0 67.1 923 Eastern 49.5 1.7 48.0 0.7 0.0 100.0 51.2 1,358 Karamoja 25.0 2.1 71.3 1.6 0.0 100.0 27.1 322 North 45.7 6.2 47.4 0.7 0.0 100.0 51.9 704 West Nile 55.7 3.0 40.1 0.9 0.4 100.0 58.7 484 Western 41.9 14.0 43.1 0.7 0.3 100.0 55.9 1,177 Southwest 33.4 7.0 56.6 3.0 0.0 100.0 40.3 978 Mother's education No education 26.7 9.5 62.4 1.2 0.3 100.0 36.1 1,161 Primary 43.3 10.7 44.9 1.0 0.1 100.0 54.0 5,161 Secondary + 57.5 23.9 17.9 0.7 0.0 100.0 81.4 1,754 Wealth quintile Lowest 37.2 5.0 56.7 1.0 0.0 100.0 42.2 1,812 Second 39.1 9.8 49.8 1.1 0.2 100.0 48.9 1,727 Middle 43.6 10.8 44.6 0.9 0.1 100.0 54.4 1,616 Fourth 42.7 15.7 40.6 0.8 0.3 100.0 58.4 1,425 Highest 59.7 28.0 11.3 0.9 0.0 100.0 87.7 1,496 Total 44.0 13.4 41.6 1.0 0.1 100.0 57.4 8,076 1 Includes only the most recent birth in the five years preceding the survey Delivery in a health facility varies widely by region, being lowest in the Karamoja region (27 percent) and highest in Kampala (93) and Central 2 (69 percent) region. There is a strong association between health facility delivery, mother’s education, and wealth quintile. The proportion of deliveries in a health facility is more than twice as high among births to mothers with secondary or higher education (81 percent) as among births to mothers with no education (36 percent). A similar pattern is observed among women by wealth quintile: delivery at a health facility is less likely among births in the lowest wealth quintile (42 percent) than in the highest wealth quintile (88 percent). The percentage of births taking place in a health facility has increased noticeably in the past five years (from 41 percent in the 2006 UDHS to 57 percent in the 2011 UDHS). 112 • Maternal Health 9.5 ASSISTANCE DURING DELIVERY Obstetric care from a health professional during delivery is recognized as critical for the reduction of maternal and neonatal mortality. Children delivered at home are usually more likely to be delivered without assistance from a trained provider, whereas children delivered at a health facility are more likely to be delivered by a trained health professional. Table 9.7 shows delivery assistance by type of provider, according to background characteristics. Fifty-eight percent of births take place with the assistance of a skilled provider, which may be a doctor, nurse or midwife, medical assistant or clinical officer. During the survey, there are cases where the respondent mentioned more than one person attending during delivery. The analysis has considered only the most qualified person. Doctors assist in the delivery of 7 percent of births, nurses/midwives assist in 50 percent, and traditional birth attendants (TBAs) assist in 18 percent of the births. Fifteen percent of the births are only attended by a relative, a friend, or some other person, while 7 percent of births take place without any type of assistance. Births to mothers less than age 20 and first-order births (67 percent and 74 percent, respectively) are more likely to be assisted by a skilled provider. Almost nine in ten births in urban areas are assisted by a skilled provider compared with 53 percent of births in rural areas. Births in Karamoja region (31 percent) are less likely to be attended by a skilled provider than births in other areas. The results further show that 19 percent of the women in the Southwest region deliver without any person providing assistance. There is a strong relationship between mother’s education and delivery by a skilled provider. The percentage of births to highly educated women (those with at least some secondary education) attended by a skilled provider was 81 percent, which compares favorably with 38 percent of births to women with no education. Similarly, assistance during delivery by a skilled provider varies by women’s economic status: births to women in the highest wealth quintile are much more likely to be assisted by a skilled provider (88 percent) than births to women in the lowest wealth quintile (44 percent). Table 9.7 also shows that 5 percent of births are delivered by caesarean section. Delivery by C- section is highest among births to highly educated mothers (11 percent), births to mothers in the highest wealth quintile (13 percent), urban births (14 percent), births in Kampala (18 percent), and first births (9 percent). The percentage of births assisted at delivery by a skilled provider has increased in the last five years (from 42 percent in the 2006 UDHS to 58 percent in the 2011 UDHS), while the percentage of births assisted by relatives and others has declined from 25 percent to 15 percent. The percentage of births attended by a TBA dropped from 23 percent in the 2006 UDHS to 18 percent in the 2011 UDHS. Also noteworthy is the fact that delivery assistance by a skilled provider in rural areas has increased in the last five years, from 37 percent in the 2006 UDHS to 53 percent in the 2011 UDHS Maternal Health • 113 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, Uganda 2011 Background characteristic Person providing assistance during delivery Total Percentage delivered by a skilled provider1 Percentage delivered by C-section Number of births Doctor Nurse/ midwife Medical assistant/ clinical officer Nursing aide Traditional birth attendant Relative/ friend/ other No one Don't know/ missing Mother's age at birth <20 9.2 57.5 0.4 1.1 16.7 13.0 2.0 0.1 100.0 67.1 6.5 1,351 20-34 6.9 49.6 0.7 1.2 18.7 15.8 7.1 0.2 100.0 57.1 5.1 5,632 35-49 6.1 44.7 0.5 1.8 18.5 15.3 13.1 0.1 100.0 51.3 4.6 1,092 Birth order 1 12.7 60.6 0.5 0.6 14.1 10.3 1.2 0.1 100.0 73.7 9.3 1,423 2-3 8.2 53.0 0.8 1.4 19.4 13.4 3.8 0.1 100.0 62.0 6.1 2,523 4-5 5.9 47.1 0.3 1.5 19.4 17.4 8.4 0.1 100.0 53.2 4.2 1,816 6+ 3.6 43.3 0.7 1.3 18.9 18.7 13.1 0.3 100.0 47.6 2.6 2,313 Place of delivery Health facility 12.4 84.3 0.9 1.4 0.4 0.4 0.2 0.0 100.0 97.6 9.2 4,633 Elsewhere 0.2 4.4 0.1 1.1 42.5 35.3 16.3 0.1 100.0 4.7 0.0 3,433 Residence Urban 20.5 68.1 0.5 1.2 4.8 4.0 0.9 0.0 100.0 89.1 13.7 1,147 Rural 5.0 47.3 0.6 1.3 20.5 17.1 8.1 0.2 100.0 52.8 3.9 6,928 Region Kampala 29.5 63.2 0.2 0.8 3.7 1.8 0.7 0.0 100.0 93.0 17.8 489 Central 1 14.0 45.9 2.0 2.4 25.9 7.4 2.3 0.0 100.0 62.0 7.8 797 Central 2 4.9 63.4 1.6 0.6 14.0 11.3 4.2 0.0 100.0 69.9 5.8 842 East Central 3.6 63.1 0.5 3.2 9.5 11.4 8.3 0.4 100.0 67.1 4.1 923 Eastern 3.1 48.7 0.2 0.8 17.4 22.2 7.7 0.0 100.0 51.9 2.5 1,358 Karamoja 1.9 28.8 0.0 0.1 18.4 47.3 3.4 0.0 100.0 30.8 1.1 322 North 4.6 48.5 0.3 1.3 37.0 6.3 2.0 0.0 100.0 53.4 2.5 704 West Nile 4.1 53.7 0.7 2.2 13.8 16.7 8.4 0.5 100.0 58.5 4.6 484 Western 6.6 48.8 0.4 1.0 20.3 15.7 6.8 0.4 100.0 55.8 5.5 1,177 Southwest 7.1 34.3 0.1 0.3 19.1 20.3 18.9 0.0 100.0 41.5 4.9 978 Mother's education No education 3.4 34.0 0.3 0.6 22.3 27.7 11.5 0.3 100.0 37.7 2.6 1,161 Primary 5.2 49.0 0.6 1.3 20.3 15.8 7.6 0.1 100.0 54.8 4.0 5,161 Secondary + 15.5 64.6 0.8 1.5 9.7 5.3 2.5 0.0 100.0 80.8 10.9 1,754 Wealth quintile Lowest 3.6 39.7 0.2 0.6 23.2 24.7 7.9 0.1 100.0 43.5 2.2 1,812 Second 3.3 45.2 0.3 1.4 22.0 18.2 9.3 0.2 100.0 48.9 3.2 1,727 Middle 4.9 48.4 1.1 1.6 17.8 15.9 10.3 0.1 100.0 54.4 3.9 1,616 Fourth 6.0 53.1 0.4 1.4 21.6 11.5 5.7 0.3 100.0 59.6 5.7 1,425 Highest 19.5 68.0 0.9 1.4 5.6 3.3 1.3 0.0 100.0 88.4 12.6 1,496 Total 7.2 50.2 0.6 1.3 18.3 15.3 7.0 0.1 100.0 58.0 5.3 8,076 Note: If the respondent mentioned more than one person attending during delivery, only the most qualified person is considered in this tabulation. 1 Skilled provider includes doctor, nurse/midwife, or medical assistant/clinical officer. 9.6 POSTNATAL CARE During the postpartum period, women may develop serious, life-threatening complications. Evidence has shown that a large proportion of deaths occur during this period, with postpartum hemorrhage and infections being important causes. A postnatal care visit is an ideal time to educate a new mother on how to care for herself and her newborn. 9.6.1 Duration of Health Facility Stay and Timing of First Postnatal Checkup Figure 9.1 shows the length of stay in a health facility following the last live birth among women with a birth in the five years preceding the survey who delivered in a health facility. The vast majority of women who had a vaginal birth stayed in the health facility either for less than one day (47 percent) or for one to two days (45 percent). By comparison, the majority of women who had a delivery by Caesarean section (68 percent) stayed in the health facility for three or more days. 114 • Maternal Health Figure 9.1 Mother’s duration of stay in the health facility after giving birth 17 5 16 6 14 3 45 17 8 68 Vaginal birth Caesarean section 0 10 20 30 40 50 60 70 Percentage < 6 hours 6-11 hours 12-23 hours 1-2 days 3+ days Uganda 2011 DHS Table 9.8 shows that in the two years preceding the survey, 33 percent of women received postnatal care for their last birth within the critical first two days following delivery (21 percent of women received postnatal care within four hours of delivery, 8 percent received care within 4-23 hours, and 4 percent were seen one to two days following delivery). More than two in every three women (64 percent) did not receive any postnatal checkup. There are differences in postnatal care by mother’s age, birth order, place of residence, wealth quintile, and education; these are similar to the differences discussed for delivery care. The percentage of women with a postnatal visit in the two days after birth has increased over the last five years, from 26 percent in 2006 to 33 percent in 2011. The percentage of mothers who did not receive any postpartum checkup declined from 74 percent in 2006 to 64 percent in 2011. Maternal Health • 115 Table 9.8 Timing of first postnatal checkup Among women age 15-49 giving birth in the two years preceding the survey, the percent distribution of the mother's first postnatal checkup 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, Uganda 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 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 20.1 8.7 3.6 0.8 2.8 1.0 62.9 100.0 32.4 480 20-34 22.0 8.3 3.3 0.9 1.2 0.6 63.7 100.0 33.7 2,160 35-49 17.7 8.3 4.5 1.0 0.2 1.2 67.1 100.0 30.5 453 Birth order 1 25.7 9.7 2.6 1.1 3.1 1.0 56.9 100.0 38.0 528 2-3 24.4 10.0 3.9 1.1 1.5 0.7 58.4 100.0 38.3 975 4-5 19.0 6.9 3.6 0.8 0.7 0.8 68.2 100.0 29.5 691 6+ 16.4 6.9 3.7 0.7 0.4 0.7 71.2 100.0 27.0 898 Place of delivery Health facility 31.8 12.8 4.2 0.8 1.3 1.2 47.8 100.0 48.9 1,831 Elsewhere 5.5 2.0 2.5 1.0 1.3 0.1 87.6 100.0 10.0 1,258 Residence Urban 35.8 14.9 5.1 0.7 1.9 1.4 40.1 100.0 55.9 450 Rural 18.6 7.3 3.3 0.9 1.2 0.6 68.1 100.0 29.1 2,642 Region Kampala 40.5 15.5 5.2 0.8 2.5 2.2 33.3 100.0 61.2 187 Central 1 29.0 7.7 2.7 0.8 1.0 0.6 58.2 100.0 39.4 322 Central 2 27.9 10.1 1.2 0.7 2.0 0.6 57.5 100.0 39.3 340 East Central 18.8 3.5 2.3 0.4 2.2 1.3 71.4 100.0 24.5 345 Eastern 22.8 10.1 2.6 0.0 0.5 0.3 63.7 100.0 35.5 529 Karamoja 12.8 10.3 3.6 0.6 0.6 1.8 70.3 100.0 26.8 107 North 10.3 6.5 11.0 2.8 3.3 0.5 65.7 100.0 27.8 276 West Nile 29.1 8.8 2.6 1.5 1.3 1.2 55.6 100.0 40.5 187 Western 16.9 8.5 3.5 1.8 0.1 0.1 69.2 100.0 28.8 423 Southwest 9.4 6.4 3.0 0.3 0.6 0.8 79.5 100.0 18.8 375 Education No education 13.3 3.7 3.4 0.9 0.0 0.7 77.9 100.0 20.5 399 Primary 17.5 7.8 3.7 0.8 1.3 0.8 68.1 100.0 29.0 1,975 Secondary + 35.3 12.4 3.2 1.2 1.9 0.6 45.2 100.0 51.0 718 Wealth quintile Lowest 12.8 9.1 3.2 0.5 0.8 0.6 72.9 100.0 25.1 694 Second 18.8 5.9 3.5 1.2 1.3 0.9 68.4 100.0 28.2 679 Middle 14.9 8.5 2.3 1.3 0.7 0.7 71.6 100.0 25.7 602 Fourth 20.5 8.4 4.6 0.9 1.6 0.1 64.0 100.0 33.5 561 Highest 41.7 10.4 4.2 0.6 2.1 1.4 39.5 100.0 56.3 556 Total 21.1 8.4 3.5 0.9 1.3 0.8 64.1 100.0 33.0 3,092 1 Includes women who received a checkup after 41 days 9.6.2 Provider of First Postnatal Checkup for Mother The skill level of the provider who performs the first postnatal checkup also has important implications for maternal and neonatal health. Table 9.9 shows that 30 percent of women received postnatal care from a doctor, nurse, or midwife. Only 2 percent of women received postnatal care from a TBA. Mothers of births of order 1 to 3, those who delivered in a health facility, those with secondary and higher education, those from the wealthiest households, and those in urban areas were more likely to have received postnatal care from a skilled provider than other mothers. Postnatal care from a doctor, nurse, or midwife was highest in Kampala (57 percent), followed by Central 2 (38 percent) and Central 1 (34 percent) regions. The Southwest region had the lowest percentage of postnatal checkup (18 percent). 116 • Maternal Health Table 9.9 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, Uganda 2011 Background characteristic Type of health provider of mother's first postnatal checkup No postnatal checkup in the first two days after birth Total Number of women Doctor/nurse/ midwife Medical assistant/ clinical officer Nursing aide/VHT Traditional birth attendant Mother's age at birth <20 30.3 0.0 0.1 2.0 67.6 100.0 480 20-34 30.1 0.5 0.4 2.8 66.2 100.0 2,160 35-49 28.7 0.4 0.5 0.9 69.5 100.0 453 Birth order 1 34.5 0.1 0.2 3.1 62.0 100.0 528 2-3 35.2 0.7 0.6 1.9 61.5 100.0 975 4-5 26.3 0.0 0.2 3.0 70.4 100.0 691 6+ 24.2 0.5 0.4 2.0 73.0 100.0 898 Place of delivery Health facility 47.9 0.6 0.3 0.1 51.0 100.0 1,831 Elsewhere 3.7 0.2 0.5 5.7 90.0 100.0 1,258 Residence Urban 53.9 0.8 0.5 0.8 44.1 100.0 450 Rural 25.8 0.4 0.4 2.6 70.8 100.0 2,642 Region Kampala 57.1 1.8 0.8 1.5 38.8 100.0 187 Central 1 33.8 0.7 0.0 5.3 60.2 100.0 322 Central 2 37.6 0.8 0.0 0.8 60.7 100.0 340 East Central 22.7 0.0 0.8 1.1 75.3 100.0 345 Eastern 31.6 0.0 0.7 3.2 64.5 100.0 529 Karamoja 26.8 0.0 0.0 0.0 73.2 100.0 107 North 22.6 0.0 1.2 3.9 72.2 100.0 276 West Nile 33.0 1.2 0.3 5.9 59.5 100.0 187 Western 27.1 0.5 0.0 1.2 71.2 100.0 423 Southwest 17.9 0.1 0.0 0.8 81.2 100.0 375 Education No education 18.5 0.2 0.0 1.7 79.5 100.0 399 Primary 25.5 0.3 0.4 2.8 70.9 100.0 1,975 Secondary+ 48.3 0.8 0.5 1.6 48.8 100.0 718 Wealth quintile Lowest 22.0 0.1 0.2 2.8 74.9 100.0 694 Second 24.7 0.4 0.6 2.4 71.8 100.0 679 Middle 23.1 0.3 0.1 2.4 74.1 100.0 602 Fourth 30.2 0.1 0.4 2.8 66.5 100.0 561 Highest 53.1 1.4 0.6 1.4 43.6 100.0 556 Total 29.9 0.4 0.4 2.4 66.9 100.0 3,092 VHT = Village Health Team 9.7 NEWBORN CARE Newborn care is essential to reduce neonatal problems and death and to identify, manage, and prevent complications soon after delivery. According to the Sexual and Reproductive Health Policy Guidelines for Uganda (MOH, 2011), a newborn is expected to receive a postnatal checkup within the first 24 hours of life. The policy guidelines further indicate that within the first 6 hours of birth, care should be provided on an hourly basis. After the mother is discharged from the health facility, she is expected to return for a checkup within seven days of delivery. The next follow-up visit is recommended within six weeks of delivery, that is, when mothers bring their infants for immunisation. Mothers who deliver outside a health facility are expected to seek postnatal care immediately after giving birth, that is, within the first six hours after birth. Thereafter, the mother is expected to return to the health facility within the first seven days and then within six weeks. Table 9.10 shows the percent distribution of last births in the two years preceding the survey by timing of the first postnatal checkup after birth, along with the percentage of births with a postnatal checkup in the first two days after birth, according to background characteristics. Eleven percent of newborns were taken for their first postnatal checkup within the critical first two days after birth. Only 2 percent of the births had a postnatal checkup within the first hour after birth, while 9 percent of births had a postnatal visit within 24 hours after birth. The vast majority of newborns (86 percent) did not receive a postnatal checkup. Maternal Health • 117 Table 9.10 Timing of first postnatal checkup for the newborn Percent distribution of last births in the two years preceding the survey by time after birth of first postnatal checkup, and the percentage of births with a postnatal checkup in the first two days after birth, according to background characteristics, Uganda 2011 Background characteristic Time after birth of newborn's first postnatal checkup No postnatal checkup1 Total Percentage of births with a postnatal checkup in the first two days after birth Number of births Less than 1 hour 1-3 hours 4-23 hours 1-2 days 3-6 days Don't know/ missing Mother's age at birth <20 1.9 4.5 2.4 1.9 2.3 0.0 86.9 100.0 10.8 480 20-34 2.3 4.5 2.3 1.9 2.4 0.2 86.2 100.0 11.1 2,160 35-49 1.3 3.4 2.1 2.7 3.3 0.4 86.9 100.0 9.5 453 Birth order 1 3.1 5.6 2.7 2.3 2.8 0.0 83.4 100.0 13.8 528 2-3 3.2 4.8 2.5 1.9 2.3 0.1 85.2 100.0 12.4 975 4-5 1.1 3.9 2.3 1.8 3.2 0.5 87.1 100.0 9.2 691 6+ 1.1 3.5 1.9 2.2 2.1 0.2 89.1 100.0 8.6 898 Place of delivery Health facility 3.3 6.7 3.1 1.4 1.1 0.3 84.1 100.0 14.5 1,831 Elsewhere 0.3 1.0 1.2 2.9 4.7 0.1 89.8 100.0 5.4 1,258 Residence Urban 5.1 10.2 3.4 2.2 1.9 0.3 76.9 100.0 20.9 450 Rural 1.6 3.4 2.1 2.0 2.6 0.2 88.1 100.0 9.1 2,642 Region Kampala 8.3 13.8 4.1 2.8 2.0 0.0 68.9 100.0 29.1 187 Central 1 4.9 3.7 1.5 0.5 0.8 0.0 88.5 100.0 10.6 322 Central 2 1.0 5.3 1.4 0.0 1.5 0.0 90.8 100.0 7.7 340 East Central 1.6 4.7 1.0 1.0 1.2 0.4 90.1 100.0 8.3 345 Eastern 1.3 5.6 3.8 3.1 3.6 0.3 82.3 100.0 13.8 529 Karamoja 0.0 5.5 2.3 10.8 16.0 0.0 65.4 100.0 18.6 107 North 1.7 2.4 5.2 3.8 2.5 0.0 84.5 100.0 13.0 276 West Nile 1.2 4.7 1.7 3.4 6.5 1.2 81.2 100.0 11.1 187 Western 2.0 2.9 2.4 1.5 1.3 0.4 89.5 100.0 8.7 423 Southwest 0.6 0.1 0.1 0.4 0.3 0.0 98.5 100.0 1.2 375 Mother's education No education 1.7 2.7 1.3 2.2 4.3 0.5 87.2 100.0 7.9 399 Primary 1.3 3.3 2.2 2.1 2.5 0.2 88.4 100.0 8.9 1,975 Secondary + 4.4 8.3 3.2 1.8 1.6 0.2 80.5 100.0 17.7 718 Wealth quintile Lowest 1.4 3.9 1.7 3.9 4.3 0.4 84.4 100.0 10.8 694 Second 1.1 2.1 2.4 2.4 2.8 0.4 88.9 100.0 7.9 679 Middle 1.4 2.8 2.5 0.6 1.9 0.0 90.7 100.0 7.4 602 Fourth 2.0 3.8 1.8 1.2 1.2 0.2 89.7 100.0 8.8 561 Highest 5.1 10.0 3.3 1.7 1.8 0.0 78.1 100.0 20.0 556 Total 2.1 4.4 2.3 2.0 2.5 0.2 86.4 100.0 10.8 3,092 1 Includes newborns who received a checkup after the first week The proportion of postnatal checkups within the first two days of birth is higher among births to mothers with secondary or higher education (18 percent) compared with 8 percent of mothers with no education. Newborns delivered outside of a health facility were less likely to receive a postnatal checkup within the first two days after birth (5 percent) than newborns delivered in a health facility (15 percent). Similarly, postnatal checkups were less likely among births of order six and over, rural births, and births in the Southwest region than among births in the other categories. Table 9.11 presents the percent distribution of last births in the two years preceding the survey by type of provider of newborn care during the first two days after delivery, according to background characteristics. The findings show that one in every ten newborns received postnatal care in the two days following birth from a doctor, nurse, or midwife. The distribution of newborns who received care from a skilled provider by background characteristics is similar to the pattern described for providers of mothers’ postnatal checkups. 118 • Maternal Health Table 9.11 Type of provider of first postnatal checkup for the newborn Percent distribution of last births in the two years preceding the survey by type of provider of the newborn's first postnatal health check during the two days after the last live birth, according to background characteristics, Uganda 2011 Background characteristic Type of health provider of newborn's first postnatal checkup No postnatal checkup in the first two days after birth Total Number of births Doctor/ nurse/ midwife Medical assistant/ clinical officer Nursing aide/ VHT Traditional birth attendant Mother's age at birth <20 9.6 0.0 0.0 1.2 89.2 100.0 480 20-34 10.3 0.3 0.0 0.5 88.9 100.0 2,160 35-49 9.0 0.0 0.1 0.4 90.5 100.0 453 Birth order 1 12.7 0.0 0.0 1.1 86.2 100.0 528 2-3 11.5 0.5 0.0 0.4 87.6 100.0 975 4-5 8.7 0.1 0.1 0.3 90.8 100.0 691 6+ 7.7 0.0 0.0 0.9 91.4 100.0 898 Place of delivery Health facility 14.2 0.1 0.0 0.1 85.5 100.0 1,831 Elsewhere 3.8 0.3 0.1 1.3 94.6 100.0 1,258 Residence Urban 20.0 0.6 0.1 0.2 79.1 100.0 450 Rural 8.3 0.1 0.0 0.7 90.9 100.0 2,642 Region Kampala 27.8 1.3 0.0 0.0 70.9 100.0 187 Central 1 9.3 0.0 0.1 1.2 89.4 100.0 322 Central 2 7.7 0.0 0.0 0.0 92.3 100.0 340 East Central 8.3 0.0 0.0 0.0 91.7 100.0 345 Eastern 12.9 0.3 0.0 0.5 86.2 100.0 529 Karamoja 16.3 0.8 0.1 1.3 81.4 100.0 107 North 10.9 0.0 0.2 1.9 87.0 100.0 276 West Nile 9.2 0.2 0.0 1.6 88.9 100.0 187 Western 8.4 0.0 0.0 0.3 91.3 100.0 423 Southwest 0.8 0.1 0.0 0.3 98.8 100.0 375 Mother's education No education 7.1 0.2 0.0 0.6 92.1 100.0 399 Primary 8.0 0.1 0.1 0.7 91.1 100.0 1,975 Secondary + 16.9 0.3 0.0 0.5 82.3 100.0 718 Wealth quintile Lowest 9.6 0.1 0.1 0.9 89.2 100.0 694 Second 7.3 0.1 0.0 0.6 92.1 100.0 679 Middle 6.6 0.0 0.0 0.8 92.6 100.0 602 Fourth 8.1 0.3 0.0 0.5 91.2 100.0 561 Highest 19.2 0.5 0.1 0.2 80.0 100.0 556 Total 10.0 0.2 0.0 0.6 89.2 100.0 3,092 9.8 PROBLEMS 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. In the 2011 UDHS, women were asked whether or not each of the following factors would be a significant problem for them in seeking medical care: getting permission to go for treatment, getting money for treatment, distance to a health facility, and not wanting to go alone. The majority of women (65 percent) reported that at least one of these problems would pose a barrier to seeking health care for themselves when they are sick (Table 9.12). Almost half of women said that getting money for treatment was a problem in accessing health care, while almost as many (41 percent) said that distance to a facility was a problem. Twenty-two percent of women stated that not wanting to go alone is a problem in accessing health care. Only 6 percent of women perceived getting permission to go for treatment as a problem. Maternal Health • 119 Table 9.12 Problems 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, Uganda 2011 Background characteristic Problems in accessing health care Number of women Getting permission to go for treatment Getting money for treatment Distance to health facility Not wanting to go alone At least one problem accessing health care Age 15-19 7.3 42.8 36.0 22.6 60.0 2,048 20-34 5.2 47.3 39.7 21.8 63.7 4,284 35-49 4.7 56.8 49.0 23.5 71.5 2,342 Number of living children 0 7.0 40.9 33.4 21.1 56.7 2,279 1-2 4.5 43.5 38.4 20.7 61.8 2,099 3-4 5.3 51.9 41.6 22.5 66.2 1,832 5+ 5.3 58.3 51.0 25.1 74.2 2,464 Marital status Never married 6.8 41.7 32.4 20.3 57.0 2,118 Married or living together 5.4 48.4 43.7 22.8 66.0 5,418 Divorced/separated/widowed 3.8 64.4 47.3 24.8 75.0 1,134 Employed last 12 months Not employed 7.2 45.3 34.0 18.7 58.8 2,299 Employed for cash 5.0 47.9 41.0 22.8 64.7 4,446 Employed not for cash 4.8 55.2 50.9 26.1 72.6 1,928 Residence Urban 3.8 32.2 13.3 9.3 39.9 1,717 Rural 6.0 52.9 48.3 25.7 71.1 6,957 Region Kampala 2.4 27.9 9.9 6.4 34.5 839 Central 1 5.1 33.8 36.5 15.2 53.2 956 Central 2 5.2 43.7 41.4 17.6 61.9 902 East Central 5.0 40.9 36.3 22.1 57.5 869 Eastern 5.9 49.3 41.7 19.7 66.1 1,267 Karamoja 5.3 86.3 41.9 18.0 87.0 289 North 4.7 77.4 52.4 19.0 87.6 735 West Nile 6.2 59.6 46.2 29.9 76.4 500 Western 8.4 53.5 49.0 29.5 71.8 1,221 Southwest 5.9 48.5 55.0 40.6 71.5 1,097 Education No education 6.9 67.5 56.1 26.8 81.4 1,120 Primary 6.0 52.7 45.3 25.3 70.0 5,152 Secondary + 4.0 31.8 26.0 14.3 46.4 2,402 Wealth quintile Lowest 6.4 71.1 55.4 26.8 85.3 1,519 Second 7.0 61.8 57.2 29.6 78.8 1,579 Middle 5.0 54.6 47.1 29.0 72.5 1,608 Fourth 6.4 40.3 40.5 21.6 61.2 1,726 Highest 3.6 27.0 17.2 10.4 38.7 2,242 Total 5.5 48.8 41.4 22.4 64.9 8,674 Note: Total includes 5 women with missing information on marital status and 1 woman missing information on employment status Women with five or more children, those who are divorced, widowed, or separated, those employed but not for cash, and those living in rural areas, Karamoja, North, and West Nile regions were more likely than their counterparts to cite having at least one of these problems in seeking health care for themselves, as were women with no education and women from the poorest households. 9.9 FEMALE CIRCUMCISION Female genital cutting (FGC)—also called female circumcision and female genital mutilation— involves cutting some part of the clitoris or labia, usually as part of a traditional ceremony or rite of passage into adolescence. In Uganda, this practice is mostly practiced by members of two ethnic groups, the Sabiny group that live in the Eastern region, and the Pokot group that live in the Karamoja region. Female circumcision in these groups is carried out as a ritual to initiate young girls into womanhood. It involves cutting the genital area of young girls, usually age 10 and older, which is occasionally followed by a more severe form of female circumcision. 120 • Maternal Health During the early nineties, the REACH (Reproductive and Community Health) programme was introduced in Kapchorwa and Kween Districts located in the Eastern region to curb the practice. The programme aims to sensitize community leaders and point out the many harmful effects of genital cutting. In December 2010, a law against female circumcision was enacted by the parliament of Uganda. Women interviewed during the 2011 UDHS were asked whether they had ever heard of female circumcision. Those who had heard were asked if they were circumcised. Information was also solicited on their opinions as to whether the practice should be continued or stopped. Table 9.13 presents the findings. Table 9.13 Female circumcision Percentage of women age 15-49 who have heard of female circumcision and percentage who are circumcised, and among women who have heard of female circumcision, percent distribution according to their attitude toward continuation of the practice, according to background characteristics, Uganda 2011 Background characteristic Percentage of women who have heard of female circumcision Percentage of women circumcised Number of women Attitude about female circumcision Total Number of women who heard of circumcision Continue Be stopped Depends/ Don't know Age 15-19 47.9 1.0 2,048 12.8 80.6 6.6 100.0 980 20-24 60.0 0.8 1,629 9.4 83.2 7.4 100.0 978 25-29 57.1 1.9 1,569 7.4 84.8 7.8 100.0 896 30-34 59.9 2.1 1,086 8.9 80.6 10.5 100.0 650 35-39 54.4 1.3 1,026 7.1 82.6 10.3 100.0 559 40-44 56.7 1.7 729 5.5 81.9 12.6 100.0 414 45-49 58.1 1.9 587 4.3 86.1 9.5 100.0 341 Residence Urban 68.2 1.4 1,717 4.6 90.0 5.5 100.0 1,172 Rural 52.4 1.4 6,957 10.0 80.3 9.7 100.0 3,645 Region Kampala 74.2 1.8 839 3.8 90.5 5.7 100.0 622 Central 1 52.6 1.5 956 8.8 86.6 4.5 100.0 503 Central 2 61.1 1.4 902 5.3 86.3 8.4 100.0 551 East Central 67.8 0.6 869 6.3 83.3 10.3 100.0 589 Eastern 75.4 2.3 1,267 8.2 78.9 12.9 100.0 955 Karamoja 67.8 4.8 289 10.9 80.1 9.0 100.0 196 North 55.5 0.5 735 16.9 73.1 10.0 100.0 408 West-Nile 21.6 0.2 500 13.3 78.5 8.2 100.0 108 Western 37.6 1.1 1,221 9.5 85.3 5.3 100.0 459 Southwest 38.8 1.4 1,097 13.5 77.7 8.8 100.0 426 Education No education 43.9 1.5 1,120 11.1 76.5 12.4 100.0 491 Primary 50.1 1.4 5,152 10.0 79.9 10.0 100.0 2,582 Secondary + 72.6 1.5 2,402 6.0 88.4 5.7 100.0 1,743 Wealth quintile Lowest 49.8 2.2 1,519 13.1 74.5 12.4 100.0 757 Second 49.0 1.2 1,579 10.6 77.9 11.5 100.0 774 Middle 48.7 1.2 1,608 10.6 81.9 7.5 100.0 783 Fourth 53.9 1.0 1,726 7.4 83.1 9.4 100.0 930 Highest 70.2 1.5 2,242 5.4 89.0 5.6 100.0 1,573 Total 55.5 1.4 8,674 8.7 82.6 8.7 100.0 4,817 The results show that 56 percent of Ugandan women have heard of female circumcision, an increase from 34 percent during the 2006 UDHS. Knowledge of female circumcision varies by residence and region, with higher proportions among urban women (68 percent) than among rural counterparts (52 percent). Knowledge of female circumcision was highest among women in the Eastern region (75 percent) followed by Kampala (74 percent). The West Nile region had the lowest percentage (22 percent). Prevalence of female circumcision in Uganda is low, with less than 2 percent of the women circumcised. The Karamoja region recorded the highest percentage of female circumcision (5 percent) followed by the Eastern region (2 percent). Greater support for discontinuation of circumcision among younger women suggests that the practice is likely to continue declining in the future. Overall, 9 percent of the female respondents declared that they wanted the practice to continue, while 83 percent declared that they wanted the practice to stop. Maternal Health • 121 Nine percent of the women were undecided. Variations by age show that young women under age 20 were more likely to be in favour of female circumcision (13 percent) compared with women in older age groups. Regional differentials show that women in the North (17 percent) followed by those residing in the Southwest and West Nile regions (14 and 13 percent, respectively) were in favour of female circumcision, compared with 4 percent of those residing in Kampala. There is an inverse relationship between support for continuation of the practice of female circumcision and education and household wealth. Less educated women and women with the least wealth were more likely to declare that female circumcision should be continued compared with women who have more education and wealth. 9.10 OBSTETRIC FISTULA Obstetric fistula (fistula is a Latin word for ‘hole’) is predominantly caused by neglect of obstructed labour. If the obstruction is unrelieved, the baby usually dies. The prolonged impact of a baby’s head against the mother’s internal tissue results in a serious medical condition in which a hole (fistula) develops between either the rectum and vagina or the bladder and vagina. Loss of the baby, persistent incontinence, and foul smelling odor may follow, along with many other possible complications such as infertility and chronic infection. As a result, the woman may be isolated from family, society, and employment. Though a simple surgical repair can mend most cases of obstetric fistula, most women go untreated, afraid to admit to the condition or too poor to afford the repair. Obstetric fistula is particularly prevalent in Sub-Saharan Africa, and Uganda has been reported to have the third-highest rate of fistula in the world.1 The 2006 UDHS collected data on this condition to assess its prevalence. All women in the survey were asked the following question: ‘Sometimes a woman can have a problem of constant leakage of urine or stool from her vagina during day and night. This problem usually occurs after a difficult child birth, but may also occur after sexual assault or after pelvic surgery. Have you ever experienced constant leakage of urine or stool from your vagina during day and night?’ Table 9.14 presents data on women who responded affirmatively to this question, according to selected background characteristics. The data show that 2 percent of Ugandan women have experienced fistula. In the 2006 UDHS, the prevalence was 3 percent. Differences by background characteristics are small. Among those who have ever experienced fistula, 62 percent sought treatment, 12 percent felt that it was an embarrassment and hence did not seek treatment, 9 percent did not know where to go for treatment, 7 percent did not know that a fistula could be fixed, and 3 percent said treatment is too expensive (data not shown). 1 See Uganda village project website: http://www.ugandavillageproject.org/what-we-do/healthy- villages/obstetric-fistula/ Table 9.14 Obstetric fistula Percentage of women age 15-49 who have experienced obstetric fistula, according to background characteristics, Uganda 2011 Background characteristic Percentage of women who have experienced obstetric fistula Number of women Age 15-19 1.0 2,048 20-24 1.8 1,629 25-29 1.8 1,569 30-34 3.1 1,086 35-39 2.5 1,026 40-44 2.8 729 45-49 2.6 587 Residence Urban 1.1 1,717 Rural 2.2 6,957 Region Kampala 1.0 839 Central 1 1.8 956 Central 2 2.1 902 East Central 1.8 869 Eastern 1.5 1,267 Karamoja 0.6 289 North 2.3 735 West Nile 2.0 500 Western 4.0 1,221 Southwest 1.4 1,097 Education No education 1.8 1,120 Primary 2.3 5,152 Secondary + 1.3 2,402 Wealth quintile Lowest 2.1 1,519 Second 2.6 1,579 Middle 2.6 1,608 Fourth 1.7 1,726 Highest 1.3 2,242 Total 2.0 8,674 Child Health • 123 CHILD HEALTH 10 his chapter presents findings relevant to child health and survival, including characteristics of the neonate (birth weight and size), the vaccination status of young children, and treatment practices— particularly contact with health services—among children suffering from three childhood illnesses: acute respiratory infection (ARI), fever, and diarrhoea. Because appropriate sanitary practices can help prevent and reduce the severity of diarrhoeal disease, information is also provided on how children’s faecal matter is disposed of. These results from the 2011 UDHS are expected to assist policymakers and program managers as they formulate appropriate strategies and interventions to improve the health of children in Uganda. In particular, the results can be used to assess the Health Sector Strategic Plan (HSSP) III. One of the four priority intervention areas of the plan is improving child health, with the goal being to ensure that Uganda achieves Millennium Development Goal 4 (MOH, 2010c). 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 UDHS 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  Half of children age 12-23 months (52 percent) were fully vaccinated at the time of the survey, an increase from the level of 46 percent reported in the 2006 UDHS.  Fifteen percent of children under age 5 showed symptoms of acute respiratory infection (ARI) in the two weeks before the survey; for 79 percent of them, advice or treatment was sought from a health care facility or provider.  Forty percent of children under age 5 had a fever in the two weeks before the survey; for 80 percent, advice or treatment was requested from a health care facility or provider.  Twenty-three percent of children under age 5 had diarrhoea, including 4 percent with bloody diarrhoea, in the two weeks before the survey; 72 percent of them were taken for advice or treatment. 124 • Child Health Table 10.1 Child's weight and size at birth Percentage of live births in the five years preceding the survey that have a reported birth weight; among live births in the five years preceding the survey that have a reported birth weight, percent distribution by birth weight; and percent distribution of all live births in the five years preceding the survey by mother's estimate of baby's size at birth, according to background characteristics, Uganda 2011 Background characteristic Percentage of all births that have a reported birth weight1 Percent distribution of births with a reported birth weight1 Percent distribution of all live births by size of child at birth Less than 2.5 kg 2.5 kg or more Total Number of births Very small Smaller than average Average or larger Don't know/ missing Total Number of births Mother's age at birth <20 57.9 13.5 86.5 100.0 782 6.3 20.2 71.6 2.0 100.0 1,351 20-34 50.1 9.7 90.3 100.0 2,823 5.0 14.8 77.5 2.7 100.0 5,632 35-49 43.3 7.9 92.1 100.0 474 6.4 12.3 78.5 2.8 100.0 1,092 Birth order 1 64.4 13.0 87.0 100.0 917 6.4 19.5 72.5 1.6 100.0 1,423 2-3 55.3 10.4 89.6 100.0 1,396 4.7 15.2 76.9 3.2 100.0 2,523 4-5 45.1 9.5 90.5 100.0 819 5.4 14.8 77.7 2.1 100.0 1,816 6+ 40.9 8.0 92.0 100.0 947 5.4 13.4 78.2 3.0 100.0 2,313 Mother's smoking status Smokes cigarettes/ tobacco (35.0) (12.9) (87.1) 100.0 23 5.2 7.3 85.9 1.6 100.0 66 Does not smoke 50.6 10.2 89.8 100.0 4,049 5.4 15.4 76.6 2.6 100.0 8,000 Residence Urban 86.4 11.3 88.7 100.0 991 5.3 14.6 78.6 1.5 100.0 1,147 Rural 44.5 9.9 90.1 100.0 3,087 5.4 15.5 76.4 2.8 100.0 6,928 Region Kampala 90.8 10.5 89.5 100.0 444 3.9 13.6 80.8 1.7 100.0 489 Central 1 49.9 14.4 85.6 100.0 399 5.4 16.5 76.6 1.4 100.0 797 Central 2 57.1 12.5 87.5 100.0 481 4.0 18.4 71.0 6.6 100.0 842 East Central 49.0 11.9 88.1 100.0 452 8.4 19.6 69.9 2.0 100.0 923 Eastern 50.4 6.8 93.2 100.0 685 4.0 14.7 79.1 2.2 100.0 1,358 Karamoja 25.1 9.8 90.2 100.0 81 9.9 20.4 69.5 0.2 100.0 322 North 53.1 11.4 88.6 100.0 374 5.1 11.5 74.3 9.1 100.0 704 West Nile 58.3 10.6 89.4 100.0 282 8.3 20.2 68.0 3.5 100.0 484 Western 48.3 8.3 91.7 100.0 568 5.0 12.9 81.6 0.6 100.0 1,177 Southwest 31.9 7.9 92.1 100.0 312 4.0 10.9 85.1 0.0 100.0 978 Mother's education No education 29.0 9.9 90.1 100.0 337 7.4 14.6 74.5 3.4 100.0 1,161 Primary 46.7 10.2 89.8 100.0 2,412 5.3 15.6 76.3 2.8 100.0 5,161 Secondary+ 75.8 10.4 89.6 100.0 1,329 4.2 14.9 79.2 1.6 100.0 1,754 Wealth quintile Lowest 39.5 10.5 89.5 100.0 716 7.5 16.5 71.9 4.2 100.0 1,812 Second 41.0 8.5 91.5 100.0 709 4.7 15.9 76.6 2.7 100.0 1,727 Middle 44.2 9.3 90.7 100.0 714 4.9 14.2 78.9 2.1 100.0 1,616 Fourth 51.8 10.9 89.1 100.0 739 4.1 15.0 78.0 2.9 100.0 1,425 Highest 80.2 11.2 88.8 100.0 1,200 5.3 14.9 78.9 0.9 100.0 1,496 Total 50.5 10.2 89.8 100.0 4,078 5.4 15.3 76.7 2.6 100.0 8,076 Figures in parentheses are based on 25-49 unweighted cases. 1 Based on either a written record or the mother's recall Half of the children (51 percent) in Uganda are weighed at birth, a practice that has steadily increased in the past few years since the 2006 UDHS when only 35 percent of newborns were reported to have been weighed. This is not surprising because a substantial percentage of births in Uganda take place in a health facility (see Chapter 9). Among children born in the five years before the survey with a reported birth weight, 10 percent had a low birth weight (less than 2.5 kg). In Uganda, low birth weight of children tends to decrease as a woman’s age at birth increases. For example, younger mothers, those less than age 20, are more likely than women age 35-49 to have infants with low birth weight (14 percent and 8 percent, respectively). By birth order, first births are more likely to result in low birth weight relative to subsequent births. The likelihood of low birth weight decreases as birth order increases. The birth weight of a child also varies somewhat by mother’s region of residence. Low birth weight ranges from a low of 7 percent in the Eastern region to a high of 14 percent in the Central 1 region. There is no clear relationship between low birth weight and urban or rural residence, mother’s education, or wealth quintile. 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 5 percent of all live births in the five years preceding the survey Child Health • 125 to be very small and 15 percent as smaller than average. Children born to very young mothers (<20 years) and first-order births are the most likely to be reported as very small or smaller than average. In addition, children of mothers with less than secondary education and children born to mothers in the lowest wealth quintile are slightly more likely to be reported as very small or smaller than average at birth. Among the regions, nearly three in ten children born to mothers residing in Karamoja (30 percent), West Nile (29 percent), and East Central (28 percent) were reported as either very small or smaller than average at birth. 10.2 VACCINATION COVERAGE Immunization of children against the eight vaccine-preventable diseases (tuberculosis, diphtheria, whooping cough (pertussis), tetanus, hepatitis B, Haemophilus influenzae, polio, and measles) is crucial to reducing infant and child mortality. Differences in vaccination coverage among subgroups of the population are useful for programme planning and targeting resources to areas most in need. Additionally, information on immunization coverage is important for the monitoring and evaluation of the Expanded Programme on Immunization (EPI). 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 diphtheria, pertussis, and tetanus (DPT) and polio vaccines, and a measles vaccination by the age of 12 months. The pentavalent vaccine DPT-HepB-Hib that protects against diphtheria, pertussis (whooping cough), tetanus, hepatitis B, and Haemophilus influenzae type b has replaced the DPT vaccine. In Uganda, 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 age 4, 8, and 12 weeks, four doses of oral polio vaccine given approximately at age 0-2, 4, 8, and 12 weeks, and measles vaccine given at or soon after reaching age 9 months. Information on vaccination coverage was obtained in two ways – from child health cards and from mothers’ verbal reports. All mothers were asked to show the interviewer the child health cards in which immunization dates were recorded for all children born since January 2006. If a card was available, the interviewer recorded onto the questionnaire the dates of each vaccination received by the child. If a child never received a health card, if the mother was unable to show the card to the interviewer, or if a particular vaccination was not recorded on the child’s health card, the vaccination information for the child was based on the mother’s report. Questions were asked for each vaccine type. Mothers were asked to recall whether the child had received BCG, polio, pentavalent (DPT-HepB-Hib), and measles vaccinations. If the mother indicated that the child had received the polio or DPT/pentavalent vaccines, she was asked about the number of doses that the child received. The mother was then asked whether the child had received other vaccinations that were not recorded on the card, and they too were noted on the questionnaire. The results presented here are based on both health card information and, for children without a card, information provided by the mother. Table 10.2 presents information on vaccination coverage for children age 12-23 months. Coverage levels include data from both health cards and verbal reports of mothers. Overall, only 52 percent of children age 12-23 months are fully vaccinated: almost all (94 percent) had received the BCG vaccine, 72 percent had received DPT 1-3 vaccinations, 63 percent had received polio 1-3, and 76 percent had received the measles vaccine at any time before the survey. Four percent of children age 12-23 months have not received any vaccinations. The coverage of the first DPT and polio vaccine is very high (93 percent for each). However, coverage for all three vaccination dosages of DPT and polio declines with subsequent doses; only 72 percent of children received all three DPT vaccines and 63 percent of children received all three of the recommended polio vaccinations. These figures reflect dropout rates (the proportion of children who received the first dose of a vaccine but who did not get the third dose) of 23 percent for DPT and 33 percent for polio. 126 • Child Health Table 10.2 also shows vaccination coverage for children who have reached age 12 months. The coverage rates for each vaccination by the time the child reaches 12 months is a measure of the children receiving vaccines on time. Overall, only 4 in 10 children are fully vaccinated by 12 months, while 6 in 10 are not. 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 by age 12 months, Uganda 2011 Source of information BCG DPT Polio1 Measles All basic vaccina- tions2 No vaccina- tions 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 58.2 58.0 55.2 49.8 41.8 58.2 54.8 49.1 47.1 42.4 0.0 876 Mother's report 35.5 35.1 30.3 21.7 25.4 35.0 28.5 13.8 28.7 9.2 3.7 604 Either source 93.7 93.1 85.4 71.5 67.1 93.3 83.4 62.9 75.8 51.6 3.7 1,480 Vaccinated by 12 months of age3 92.1 91.4 83.6 67.9 66.1 90.9 81.1 59.5 58.4 40.3 5.6 1,480 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 is 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. Table 10.3 presents information on vaccine coverage among children age 12-23 months from vaccination cards and mother’s report, by background characteristics. There is no notable difference in vaccination coverage between male and female children. Vaccination coverage decreases as birth order increases; first births are more likely to be fully immunised (58 percent) than births of order six and higher (43 percent). Children living in urban areas are more likely than those living in rural area to be fully- vaccinated (61 percent and 50 percent, respectively). Among the regions, the proportion of children that received all of their basic vaccinations varies. Children residing in Kampala are the most likely to have received all of their vaccinations (63 percent), while children living in the East Central region (39 percent) are the least likely to be fully immunized when compared with children living in other regions. Vaccination coverage increases as the educational attainment of a child’s mother also increases. For example, 45 percent of children whose mothers have no education are fully immunized compared with 62 percent among children of mothers with secondary or higher education. Similarly, children in households in the middle wealth quintile are slightly less likely to have been fully immunized compared with children in households in the other wealth quintiles. Table 10.3 also shows that an immunization card/book was seen for 59 percent of children age 12- 23 months. A higher proportion of first-order births (62 percent), children living in rural areas (60 percent), children living in the Southwest region (74 percent), and children of mothers with at least some education (60 percent) had a vaccination card seen compared with their counterparts. Children of households in the highest wealth quintile were less likely to have a vaccination card seen compared with children in the other quintiles. Child Health • 127 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, Uganda 2011 Background characteristic BCG DPT Polio1 Measles All basic vaccina- tions2 No vaccina- tions Percent- age with a vaccina- tion card seen Number of children DPT 1 DPT 2 DPT 3 Polio 0 Polio 1 Polio 2 Polio 3 Sex Male 94.1 94.3 87.9 72.0 67.8 94.2 84.4 63.9 74.8 51.6 3.0 59.6 679 Female 93.3 92.0 83.3 71.0 66.6 92.5 82.5 62.1 76.6 51.7 4.4 58.9 800 Birth order 1 94.9 93.7 85.5 74.2 69.0 94.8 85.0 68.2 80.5 57.9 3.8 62.1 278 2-3 95.2 95.0 90.2 77.0 69.8 95.1 86.5 67.4 78.9 57.6 2.2 59.4 460 4-5 94.2 94.0 84.5 72.1 68.7 92.8 84.2 60.1 77.7 48.7 3.1 60.7 318 6+ 90.9 89.9 80.9 63.1 61.8 90.7 78.3 56.7 67.9 43.3 5.8 55.9 425 Residence Urban 96.3 94.6 87.7 75.4 83.3 92.1 83.3 69.2 80.8 60.8 3.4 55.3 204 Rural 93.3 92.8 85.1 70.8 64.5 93.5 83.4 61.9 75.0 50.2 3.8 59.8 1,275 Region Kampala 94.6 91.8 85.9 73.5 76.3 91.6 82.1 71.6 82.0 63.4 5.4 54.1 86 Central 1 85.2 84.4 79.8 66.4 55.3 87.3 78.2 51.1 75.0 43.9 10.1 44.0 153 Central 2 94.5 89.3 80.1 61.7 67.3 91.9 78.6 54.0 70.7 43.0 3.3 52.9 169 East Central 95.5 94.1 79.6 52.8 67.0 93.3 81.2 54.3 71.4 39.2 1.3 53.1 169 Eastern 97.5 95.4 89.3 74.2 81.2 97.3 87.5 62.3 76.8 52.4 0.6 54.0 260 Karamoja 99.8 98.7 93.6 89.5 93.1 97.7 88.7 65.4 90.6 62.2 0.2 62.6 58 North 94.0 95.3 89.1 73.4 77.5 93.4 80.3 59.5 72.0 49.0 2.4 68.4 140 West Nile 98.5 97.6 90.0 82.0 91.9 97.4 90.2 64.3 77.7 52.1 0.0 67.4 78 Western 95.4 98.2 86.9 77.6 55.2 95.1 83.9 72.2 81.7 59.7 1.8 66.9 196 Southwest 85.9 88.9 86.1 79.2 36.7 88.9 86.2 78.1 71.4 61.6 11.1 74.2 171 Mother's education No education 92.5 93.1 81.4 69.7 63.8 91.5 79.4 55.1 72.6 45.0 5.2 54.7 191 Primary 93.8 93.1 84.9 68.9 64.1 93.8 83.0 61.9 73.7 49.2 3.1 59.7 937 Secondary+ 94.0 93.0 89.2 79.2 77.1 92.8 86.4 69.8 83.1 61.7 4.6 60.4 351 Wealth quintile Lowest 95.6 94.3 87.7 73.8 71.3 95.3 86.1 60.8 75.1 50.6 2.3 61.4 328 Second 94.6 95.4 88.2 71.6 64.3 93.9 83.7 65.5 72.1 51.4 3.0 64.6 321 Middle 92.4 91.0 80.8 66.0 57.7 94.4 79.6 61.5 74.1 48.7 3.1 61.1 271 Fourth 90.6 90.3 83.6 70.6 64.8 89.3 83.1 62.3 76.4 52.6 6.8 57.1 276 Highest 94.7 93.7 86.0 74.7 76.8 92.9 83.7 64.3 81.6 54.9 3.9 50.7 283 Total 93.7 93.1 85.4 71.5 67.1 93.3 83.4 62.9 75.8 51.6 3.7 59.2 1,480 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) 10.3 TRENDS IN VACCINATION COVERAGE Trends in vaccination coverage can be seen by comparing coverage among children of different age groups in the 2011 UDHS. 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. The percentage of children who have received no vaccinations at all by age 12 months has remained constant over the past four years. At the time of the survey, 6 percent of children age 48-59 months had not received any vaccinations compared with 6 percent of children age 12-23 months. Among children who had received all basic vaccinations by age 12 months, there is a slight increase, from 38 percent of children age 48-59 months to 40 percent of children age 12-23 months within the same period. This shows some improvement in vaccination coverage in recent years. Not surprisingly, vaccination cards were shown for 59 percent of children age 12-23 months but for only 43 percent of children age 48-59 months. This may be because vaccination cards for older children have been discarded or lost. 128 • Child Health 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 age 12 months, and percentage with a vaccination card, by current age of child, Uganda 2011 Age in months BCG DPT Polio1 Measles All basic vaccina- tions2 No vaccina- tions Percen- tage with a vaccina- tion card seen Number of children DPT 1 DPT 2 DPT 3 Polio 0 Polio 1 Polio 2 Polio 3 12-23 92.1 91.4 83.6 67.9 66.1 90.9 81.1 59.5 58.4 40.3 5.6 59.2 1,480 24-35 92.7 90.4 81.3 64.3 66.9 90.6 81.0 55.2 58.5 37.0 6.7 46.6 1,515 36-47 91.1 90.4 82.1 66.7 64.4 90.4 79.2 54.8 60.6 37.1 6.9 44.7 1,473 48-59 93.0 90.5 81.6 65.0 63.7 91.6 82.3 54.0 63.9 38.2 6.0 43.0 1,438 12-59 92.3 90.8 82.3 66.1 65.3 90.9 81.1 56.0 60.5 38.2 6.2 48.4 5,906 Note: Information was obtained from the vaccination card or, if there was no written record, from the mother. For children whose information is 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) Trends in immunization coverage can also be identified by comparing data collected from the UDHS throughout the years. Figure 10.1 shows trends in vaccination coverage seen by comparing the results of the 2000-01, 2006, and 2011 UDHS surveys. It should be noted that the 2006 and 2011 UDHS surveys collected data from the entire country, but the 2000-01 survey excluded several districts for security reasons. Therefore, the trends presented here should be interpreted in that light. Figure 10.1 shows that vaccination coverage in Uganda has improved over the past ten years. The percentage of children age 12-23 months fully vaccinated by 12 months of age has increased from 29 percent in 2000-01 to 36 percent in 2006 and 40 percent in 2011. There has also been a steady decrease in the proportion of children who received none of the basic, recommended vaccinations, from 17 percent in 2000-2001 to 9 percent in 2006 and to 6 percent in 2011. The percentage of children who received each specific vaccination has also increased in the past ten years. Figure 10.1 Trends in vaccination coverage during the first year of life among children 12-23 months 29 17 75 73 60 42 32 79 68 50 42 36 9 89 87 77 59 45 88 78 55 52 40 6 92 91 84 68 66 91 81 60 58 All None BCG DPT 1 DPT 2 DPT 3 Polio 0 Polio 1 Polio 2 Polio 3 Measles Percentage of children who received specific vaccines 2000-01 2006 2011 Note: In the 2000-2001 UDHS, areas making up the current districts of Amuru, Bundibugyo, Gulu, Kasese, Kitgum, and Pader, comprising around 7 percent of the national population of Uganda, were excluded from the sample. Thus, the trends need to be viewed in that light. Child Health • 129 10.4 ACUTE RESPIRATORY INFECTION Acute respiratory infection (ARI) is among the leading causes of child morbidity and mortality in Uganda and throughout the world. Pneumonia is the most serious illness of ARI in young children. Early diagnosis and treatment of pneumonia with antibiotics can prevent a large proportion of deaths. In the 2011 UDHS, ARI prevalence was estimated by asking mothers whether any of their children under age 5 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 5 who experienced symptoms of ARI in the two weeks preceding the survey. Fifteen percent of children showed symptoms of ARI in the two weeks before the survey. The percentage of children with reported ARI symptoms peaks at age 6-11 months (21 percent) and declines thereafter. There are no significant differences in the prevalence of ARI between female and male children. Slightly more children of mothers who do not smoke experience ARI symptoms (15 percent) when compared with children of mothers who smoke (13 percent). Furthermore, children living in households that use wood/straw for cooking are more likely to exhibit symptoms of ARI than children living in households using charcoal (16 percent compared with 11 percent). Table 10.5 Prevalence and treatment of symptoms of ARI Among children under age 5, the percentage who had symptoms of acute respiratory infection (ARI) in the 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, Uganda 2011 Background characteristic Among children under age 5: Among children under age 5 with symptoms of ARI: Percentage for whom advice or treatment was sought from a health facility or provider2 Percentage who received antibiotics Number of children Percentage with symptoms of ARI1 Number of children Age in months <6 13.9 802 68.4 57.1 112 6-11 20.7 827 78.3 56.2 171 12-23 18.3 1,480 83.0 49.6 271 24-35 14.1 1,515 78.8 45.6 213 36-47 12.5 1,473 81.3 42.2 184 48-59 11.7 1,438 75.9 36.6 168 Sex Male 15.4 3,757 74.9 45.6 578 Female 14.3 3,778 82.8 49.4 540 Mother's smoking status Smokes cigarettes/ tobacco 13.3 62 * * 8 Does not smoke 14.9 7,463 78.7 47.0 1,109 Cooking fuel Charcoal 11.4 1,515 82.6 65.9 172 Wood/straw3 15.8 5,979 78.0 44.1 946 Residence Urban 13.0 1,089 80.8 60.0 141 Rural 15.2 6,447 78.4 45.6 977 Region Kampala 13.9 467 87.2 65.5 65 Central 1 9.4 743 78.7 53.9 70 Central 2 11.9 794 78.9 51.8 94 East Central 15.1 852 78.3 33.3 129 Eastern 16.7 1,284 80.0 37.4 214 Karamoja 20.0 281 86.0 29.8 56 North 22.1 669 80.5 43.6 148 West Nile 14.0 446 81.3 53.5 62 Western 16.8 1,096 76.0 68.6 184 Southwest 10.6 903 66.8 39.4 96 Mother's education No education 15.0 1,081 69.6 42.1 162 Primary 15.8 4,792 79.9 43.5 755 Secondary+ 12.1 1,662 81.6 66.5 201 Wealth quintile Lowest 20.1 1,673 77.8 40.3 336 Second 16.5 1,594 78.9 42.7 263 Middle 12.6 1,510 78.1 55.0 190 Fourth 12.1 1,331 77.2 45.2 161 Highest 11.9 1,428 82.3 62.6 170 Total 14.8 7,535 78.7 47.4 1,118 An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. 1 Symptoms of ARI (cough accompanied by short, rapid breathing, which was chest-related, and/or by difficult breathing, which was chest-related) is considered a proxy for pneumonia 2 Excludes pharmacy, shop, and traditional practitioner 3 Includes grass, shrubs, crop residues 130 • Child Health A slightly lower proportion of children in rural areas have symptoms of ARI than do children in urban areas. The proportion of children with ARI symptoms ranges from 9 percent of children living in the Central 1 region to 22 percent of children in the North region. ARI prevalence tends to decrease with a woman’s increase in educational attainment. Children of mothers with only primary education are slightly more likely to experience ARI symptoms (16 percent) than children of mothers with secondary or higher education (12 percent). ARI symptoms are less common in children in higher wealth quintiles compared with those in the lower quintiles. For example, children in the lowest wealth quintile are 1.7 times more likely to have experienced ARI symptoms in the past two weeks compared with those in the highest wealth quintile (20 percent and 12 percent, respectively). Almost eight in ten children under age 5 with symptoms of ARI (79 percent) were taken to a health facility or provider for advice or treatment. This represents a slight increase over 73 percent in 2006. Health-treatment-seeking behaviour for children with ARI symptoms is more common among children age 12-23 months, female children, and those living in households that cook with charcoal. Urban children are also more likely than rural children to have been taken to a health facility or provider for treatment, as are those children residing in Kampala. Children of women with no education are least likely to be taken to a health facility or provider when they have ARI symptoms compared with children of mothers with secondary education or higher (70 percent and 82 percent, respectively). Overall, almost half (47 percent) of children with ARI symptoms received antibiotics. The likelihood of receiving antibiotics increases with the mother’s education but decreases among older children. Urban children are more likely than those living in rural areas to have received an antibiotic for their ARI symptoms (60 percent and 46 percent, respectively). 10.5 FEVER Fever is a symptom of malaria, but it may also be due to other illnesses, including pneumonia, common colds, and influenza. Because malaria is a major cause of death in infancy and childhood in many developing countries, the presumptive treatment of fever with antimalarial medication has been advocated in many countries where malaria is endemic. Although fever can occur year-round, malaria is more prevalent after the end of the rainy season (June-July and November-December), which coincided with the UDHS fieldwork (June-December). The temporal factors must be taken into account when interpreting fever as an indicator of malaria prevalence. The prevention and treatment of malaria is discussed in detail in Chapter 12. Table 10.6 shows the percentage of children under 5 with fever during the two weeks preceding the survey, the percentage for whom advice or treatment was sought from a health facility or provider, and the percentage receiving various treatments, by selected background characteristics. Overall, two-fifths of children under age 5 were reported to have had fever in the two weeks preceding the survey. The prevalence of fever varies by the age of the child. The prevalence of fever increases as the children’s age increases until it peaks among children 12-23 months (48 percent). Thereafter, the proportion of children reporting fever decreases. There is no difference in the prevalence of fever by sex of the child. However, there is notable difference in the prevalence of fever between children in urban and rural areas. Three in ten urban children under age 5 were reported to have had fever in the two weeks preceding the survey compared with more than four in ten (42 percent) rural children. Regional variations are also present; prevalence of fever ranges from a low of 13 percent in the Southwest region to a high of 69 percent in the East Central region. Child Health • 131 Children of mothers with only primary education (43 percent) have the highest prevalence of fever when compared with their counterparts. The proportion of children with fever decreases with increasing wealth quintile of the household, from a high of 50 percent among children living in households in the lowest wealth quintile to a low of 30 percent among children living in households in the highest wealth quintile. Four-fifths of children with fever were taken to a health facility or provider for treatment. Children under 6 months were less likely to be taken to a health facility or provider for treatment compared with the other children. Likewise, children living in the East Central region were less likely to be treated in a health facility or by a provider when compared with children living in other regions. Urban children are more likely than rural children to have been taken to a health facility or provider for advice or treatment. A higher proportion of children whose mothers have secondary education or higher, and children of households in the highest wealth quintile were taken for treatment or advice compared with their counterparts. Children with fever were more likely to have received an antimalarial drug than an antibiotic: 65 percent of children with fever received antimalarial drugs, and 32 percent received antibiotic drugs. Use of antimalarial and antibiotic drugs among children varies by background characteristics. The differences are similar to those observed for children for whom advice or treatment was sought from a health facility or provider. Table 10.6 Prevalence and treatment of fever Among children under age 5, 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, percentage who took antimalarial drugs, and percentage who received antibiotics as treatment, by background characteristics, Uganda 2011 Background characteristic Among children under age 5: Among children under age 5 with fever Percentage for whom advice or treatment was sought from a health facility or provider1 Percentage who took antimalarial drugs Percentage who took antibiotic drugs Number of children Percentage with fever Number of children Age in months <6 26.3 802 75.0 31.9 46.9 211 6-11 46.6 827 81.2 60.7 38.0 385 12-23 48.4 1,480 82.1 68.7 30.6 716 24-35 43.0 1,515 80.9 67.7 33.0 651 36-47 37.7 1,473 81.1 66.8 29.3 555 48-59 36.4 1,438 76.6 68.2 27.0 524 Sex Male 39.3 3,757 78.2 62.1 31.4 1,478 Female 41.4 3,778 81.9 66.7 33.2 1,564 Residence Urban 30.3 1,089 87.2 63.4 43.8 330 Rural 42.1 6,447 79.2 64.6 30.9 2,712 Region Kampala 24.0 467 88.2 60.2 50.3 112 Central 1 42.4 743 85.0 63.4 33.5 315 Central 2 42.4 794 82.4 59.4 34.3 337 East Central 69.3 852 67.1 46.0 30.1 590 Eastern 55.6 1,284 79.8 75.9 27.5 714 Karamoja 40.9 281 88.4 75.5 28.5 115 North 38.5 669 87.8 79.7 26.5 258 West Nile 37.6 446 82.7 70.6 30.0 168 Western 29.1 1,096 87.9 66.4 49.2 319 Southwest 12.7 903 69.7 50.7 21.0 115 Mother's education No education 39.7 1,081 74.6 56.3 29.1 430 Primary 43.1 4,792 80.0 66.1 30.8 2,064 Secondary+ 33.0 1,662 84.7 64.9 40.4 549 Wealth quintile Lowest 49.8 1,673 78.8 64.5 28.0 832 Second 42.6 1,594 79.1 66.6 27.5 679 Middle 36.8 1,510 82.3 62.2 33.9 556 Fourth 40.7 1,331 77.6 61.9 34.4 542 Highest 30.3 1,428 84.5 67.4 43.8 432 Total 40.4 7,535 80.1 64.5 32.3 3,042 1 Excludes pharmacy, shop, and traditional practitioner 132 • Child Health 10.6 DIARRHOEAL DISEASE Dehydration caused by severe diarrhoea is a major cause of morbidity and mortality among young children, although the condition can be easily treated with oral rehydration therapy (ORT). Exposure to diarrhoea-causing agents is frequently related to the use of contaminated water and to unhygienic practices in food preparation and disposal of excreta. In the 2011 UDHS, mothers were asked whether any of their children under age 5 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 mother was also asked whether there was blood in the child’s stools. Diarrhoea with blood in the stools needs to be treated differently from diarrhoea, which is not accompanied by blood in the stools. Prevalence of diarrhoea is affected by the mother’s perception of diarrhoea as an illness and her capacity to recall the events. In interpreting the findings of the 2011 UDHS, it should be borne in mind that prevalence of diarrhoea varies seasonally and peaks at the end of the rainy season, which occurs during the period of survey data collection. 10.6.1 Prevalence of Diarrhoea Table 10.7 shows the percentage of children under age 5 with diarrhoea in the two weeks preceding the survey, according to selected background characteristics. Overall, nearly one- quarter (23 percent) of all children under five had diarrhoea, while 4 percent had diarrhoea with blood. The occurrence of diarrhoea varies by age of the child. Young children age 6-23 months are more prone to diarrhoea than children in the other age groups; those age 6-11 months have the highest prevalence of diarrhoea among the age cohorts. There is little variation in the prevalence of diarrhoea by child’s sex or source of drinking water. However, diarrhoea is more common among children who live in households with a non-improved toilet facility or a shared toilet facility compared with children who live in households with improved, not shared facilities (24 percent and 19 percent, respectively). Rural children are only slightly more likely than urban children to get sick with diarrhoea (24 percent versus 22 percent). Among the regions, prevalence of diarrhoea varies. Children living in the East Central and Eastern regions are more susceptible to episodes of diarrhoea (32 and 33 percent) compared with children living in the other regions. Children living in the Southwest region have the lowest prevalence of diarrhoea (14 percent) when compared with children living in the other regions. The prevalence of diarrhoea decreases steadily with increasing wealth quintile and is lowest among children whose mothers have at least a secondary 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, Uganda 2011 Background characteristic Diarrhoea in the two weeks preceding the survey Number of children All diarrhoea Diarrhoea with blood Age in months <6 19.2 2.7 802 6-11 43.0 6.0 827 12-23 37.6 6.5 1,480 24-35 22.2 4.6 1,515 36-47 14.6 3.0 1,473 48-59 10.3 2.3 1,438 Sex Male 24.1 4.8 3,757 Female 22.8 3.6 3,778 Source of drinking water1 Improved 23.8 4.3 5,347 Not improved 22.6 3.9 2,188 Toilet facility2 Improved, not shared 18.7 4.0 1,173 Shared3 23.9 3.1 1,112 Non-improved 24.4 4.4 5,246 Residence Urban 21.8 2.9 1,089 Rural 23.7 4.4 6,447 Region Kampala 24.1 1.8 467 Central 1 22.3 3.8 743 Central 2 20.9 3.3 794 East Central 31.9 6.8 852 Eastern 32.5 6.3 1,284 Karamoja 20.3 6.3 281 North 23.8 4.6 669 West Nile 18.7 2.5 446 Western 18.8 3.4 1,096 Southwest 14.0 1.8 903 Mother's education No education 21.4 5.1 1,081 Primary 25.2 4.6 4,792 Secondary+ 19.6 2.3 1,662 Wealth quintile Lowest 28.8 7.1 1,673 Second 25.2 4.1 1,594 Middle 21.8 3.5 1,510 Fourth 20.6 3.5 1,331 Highest 19.5 2.3 1,428 Total 23.4 4.2 7,535 1 See Table 2.1 for definition of categories 2 See Table 2.2 for definition of categories 3 Facilities that would be considered improved if they were not shared by two or more households Child Health • 133 education. The prevalence of diarrhoea with blood follows a pattern similar to that observed for diarrhoea in general. 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, 72 percent of the children with diarrhoea were taken for advice or treatment to a health facility or provider. Children age 12-23 months were more likely than children in other age groups to be taken to a health facility or provider for treatment (77 percent). The differences in percentages of children taken for treatment were small between male and female children. Treatment-seeking behaviour is more prevalent for children with bloody diarrhoea. Children suffering from diarrhoea in rural areas (73 percent) and in the Karamoja region (93 percent) and North regions (88 percent) are more likely than their counterparts to have been taken for treatment or advice. Advice or treatment for children with diarrhoea is less often sought for children whose mothers have secondary education or higher and for children from households in the highest wealth quintile. Oral rehydration therapy (ORT) is a simple and effective remedy for the dehydration often caused by diarrhoea. 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. Some form of ORT, either fluid from ORS sachets or recommended home fluids (RHF), was used to treat the diarrhoea in about half of the children (48 percent). Forty-four percent of these children suffering from diarrhoea in the two weeks preceding the survey were given fluid from ORS packets, and 12 percent were given fluid from RHF. Almost one-fifth (18 percent) of the children with diarrhoea were given increased amounts of other fluids. Overall, slightly more than half (55 percent) of children were given either ORT or increased fluids. The other treatments given to children with diarrhoea were antibiotics (32 percent) and anti-motility drugs (6 percent), while a few children received zinc supplements (2 percent) or intravenous solutions (1 percent). Home remedies were used to treat more than one-third (36 percent) of children. Fourteen percent of children with diarrhoea did not receive any treatment. 134 • Child Health Table 10.8 Diarrhoea treatment Among children under age 5 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 who were given other treatments, by background characteristics, Uganda 2011 Background characteristic Percentage of children with diarrhoea for whom advice or treatment was sought from a health facility or provider1 In- creased fluids ORT or increased fluids No treatment Number of children with diarrhoe a Oral rehydration therapy (ORT) Other treatments Fluid from ORS packets Recom- mended home fluids (RHF) Either ORS or RHF Antibiotic drugs Anti- motility drugs Zinc supple- ments Intra- venus solution Home remedy/ other Age in months <6 55.1 25.0 6.7 27.6 10.4 31.8 26.5 2.6 2.8 0.1 26.9 33.1 154 6-11 73.2 41.0 11.9 46.6 15.0 54.2 29.1 8.0 2.3 0.7 34.2 12.5 356 12-23 76.7 52.8 11.9 56.3 18.8 62.4 30.2 6.3 2.2 1.2 39.9 12.3 556 24-35 74.7 45.8 13.6 51.8 22.6 59.2 35.1 5.4 1.9 0.7 33.1 11.5 337 36-47 71.4 41.7 9.7 46.0 19.7 55.3 33.6 4.7 1.2 0.0 36.9 12.3 215 48-59 67.9 31.8 11.8 37.4 20.0 46.2 38.8 1.2 0.2 2.5 44.4 12.3 148 Sex Male 71.2 40.5 11.3 46.0 18.6 53.5 31.8 5.6 2.1 1.1 35.1 14.1 904 Female 73.6 46.8 11.7 50.5 17.8 57.1 31.7 5.5 1.7 0.6 37.6 13.9 862 Type of diarrhoea Non-bloody 71.7 43.2 11.2 47.5 18.9 55.2 31.4 5.7 1.7 0.8 36.2 14.1 1,430 Bloody 77.2 45.5 13.2 51.2 16.4 56.2 32.1 4.8 3.0 1.5 38.3 12.8 315 Residence Urban 70.2 46.2 18.4 54.4 21.7 63.9 32.8 5.0 3.3 0.5 29.8 14.5 237 Rural 72.7 43.1 10.4 47.2 17.7 53.9 31.6 5.6 1.7 1.0 37.3 13.9 1,528 Region Kampala 68.7 46.3 19.4 53.8 21.9 62.4 36.0 5.1 2.7 0.5 26.6 13.9 112 Central 1 73.2 37.4 25.2 50.9 25.7 60.4 18.5 3.1 1.7 0.0 49.5 12.4 166 Central 2 66.0 50.6 9.9 54.1 23.9 62.9 18.8 9.8 3.2 1.1 24.6 16.9 166 East Central 73.2 56.2 10.0 60.8 4.2 61.8 32.1 0.5 0.0 0.9 51.2 10.4 272 Eastern 75.9 37.9 15.0 42.4 21.7 49.5 51.9 3.7 1.0 2.0 27.2 14.5 418 Karamoja 93.0 77.3 1.1 77.4 16.6 82.1 22.6 2.7 1.0 1.6 30.9 6.0 57 North 87.5 46.3 2.5 46.5 33.5 61.4 32.9 16.3 4.0 0.0 35.6 8.2 159 West Nile 76.0 43.4 6.7 49.3 18.2 57.6 29.2 9.5 5.3 0.0 27.3 9.5 83 Western 64.4 37.9 3.3 38.5 5.4 41.0 17.9 7.9 3.6 1.0 44.8 15.7 206 Southwest 51.7 22.0 12.6 27.3 19.3 38.9 21.4 1.3 0.0 0.0 36.4 29.5 126 Mother's education No education 74.4 47.5 11.0 52.4 12.2 55.5 27.3 2.9 0.8 0.4 35.4 12.6 232 Primary 73.0 41.6 11.0 45.8 18.8 54.0 31.1 6.2 1.8 1.0 38.1 14.2 1,208 Secondary+ 68.5 47.9 13.5 53.9 20.7 59.8 37.0 4.7 3.3 0.9 30.2 14.1 326 Wealth quintile Lowest 73.7 42.9 8.4 45.5 18.9 53.3 32.2 5.5 2.2 1.2 35.1 13.9 481 Second 72.5 40.4 8.1 44.1 16.4 51.5 34.4 7.4 2.1 0.7 37.2 13.5 402 Middle 74.4 40.9 12.8 45.2 18.3 52.5 30.3 3.8 1.5 0.8 36.8 14.2 329 Fourth 72.7 50.7 11.7 57.0 16.7 62.0 28.7 3.8 2.1 0.8 39.8 12.6 274 Highest 67.1 45.4 20.0 53.4 21.3 60.7 31.8 6.6 1.7 0.9 33.2 15.9 279 Total 72.4 43.5 11.5 48.2 18.3 55.3 31.7 5.5 1.9 0.9 36.3 14.0 1,766 Note: ORT includes fluid prepared from oral rehydration salt (ORS) packets and recommended home fluids (RHF). 1 Excludes pharmacy, shop, and traditional practitioner 10.6.3 Feeding Practices during Diarrhoea When a child has diarrhoea, mothers are encouraged to continue feeding their child the same amount of food as they would if the child did not have diarrhoea. They are also encouraged to increase the child’s fluid intake. These practices help to reduce dehydration and minimise the adverse consequences of diarrhoea on the child’s nutritional status. In the 2011 UDHS, mothers were asked whether they gave their child with diarrhoea less, the same amount, or more fluids and food than usual. Table 10.9 shows the percent distribution of children under age 5 who had diarrhoea in the two weeks preceding the survey by feeding practices during the episode of diarrhoea. Table 10.9 shows that 18 percent of children with diarrhoea were given more fluids than usual, as recommended, while 37 percent of children who had diarrhoea were given the same amount of liquid as usual. One in five children was either given somewhat less to drink (22 percent) or much less to drink than usual (18 percent). Five percent of children who had diarrhoea were given no liquids. Regarding the amount of food offered to children who had diarrhoea, only 6 percent were given more food to eat than Child Health • 135 usual, and one-third (34 percent) were given the same amount of food as usual. One-quarter of children with diarrheoa were given somewhat less than the usual amount of food to eat while sick, and one-fifth (19 percent) were given much less than usual to eat. Six percent of children with diarrhoea did not receive food during their illness. Overall, 13 percent of children had increased fluid intake and continued feeding. About one-third (36 percent) of children suffering from diarrhoea were given ORT and/or increased fluids, and continued feeding. When feeding and treatment practices are observed by background characteristics, variations among certain groups become apparent. Among children suffering from diarrhoea, those under age 6 months are less likely than those in other age groups to be continually fed and given ORT and/or increased fluids during the episode. Female children, children in urban areas, children residing in Karamoja region, children of mothers with at least some secondary education, and children from the fourth wealth quintile are more likely than other children to receive ORT and/or increased fluids with continued feeding. The percentage of children with diarrhoea who were given increased fluids and continued feeding has slightly declined in the last five years, from 17 percent as measured in the 2006 UDHS to 13 percent as reported in the current survey. Similarly, the practice of giving ORT and/or increased fluids along with continued feeding has declined over the same period, from 51 percent to 36 percent. 13 6 • C hi ld H ea lth 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 t he p er ce nt ag e of 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 i nc re as ed f lu id s du rin g th e ep is od e of d ia rr ho ea , by b ac kg ro un d ch ar ac te ris tic s, U ga nd 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 N um be r of ch ild re n w ith di ar rh oe a M or e S am e as us ua l S om e- w 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 e- w 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 10 .4 46 .5 15 .9 18 .0 9. 2 0. 0 10 0. 0 1. 7 15 .0 5. 6 8. 5 1. 8 66 .2 1. 1 10 0. 0 2. 7 9. 1 15 4 6- 11 15 .0 44 .5 18 .8 17 .3 4. 3 0. 0 10 0. 0 5. 2 34 .2 19 .0 18 .1 7. 6 15 .7 0. 1 10 0. 0 9. 7 30 .4 35 6 12 -2 3 18 .8 34 .0 24 .3 19 .1 3. 6 0. 1 10 0. 0 5. 3 32 .5 29 .9 24 .5 5. 8 1. 8 0. 1 10 0. 0 13 .4 42 .0 55 6 24 -3 5 22 .6 32 .7 20 .6 17 .8 5. 1 1. 1 10 0. 0 8. 9 39 .3 26 .9 18 .8 4. 7 0. 8 0. 7 10 0. 0 17 .1 42 .6 33 7 36 -4 7 19 .7 36 .1 22 .0 15 .6 4. 0 2. 6 10 0. 0 8. 4 38 .0 25 .4 17 .5 7. 3 0. 7 2. 6 10 0. 0 17 .2 42 .7 21 5 48 -5 9 20 .0 34 .3 24 .1 15 .3 5. 2 1. 1 10 0. 0 5. 6 38 .7 33 .0 15 .6 6. 1 0. 0 1. 1 10 0. 0 16 .0 34 .0 14 8 Se x M al e 18 .6 37 .3 21 .4 17 .8 4. 1 0. 8 10 0. 0 5. 7 34 .5 23 .3 20 .2 5. 1 10 .4 0. 8 10 0. 0 13 .2 34 .6 90 4 Fe m al e 17 .8 37 .2 21 .6 17 .5 5. 4 0. 5 10 0. 0 6. 5 33 .0 26 .2 18 .0 6. 6 9. 1 0. 6 10 0. 0 13 .0 38 .2 86 2 Ty pe o f d ia rr ho ea N on -b lo od y 18 .9 38 .0 21 .3 15 .7 5. 2 0. 8 10 0. 0 5. 3 35 .1 24 .8 17 .8 5. 8 10 .3 0. 8 10 0. 0 13 .5 36 .5 1, 43 0 B lo od y 16 .4 34 .1 21 .5 25 .1 2. 6 0. 3 10 0. 0 9. 0 27 .9 24 .2 25 .1 6. 3 7. 2 0. 3 10 0. 0 12 .2 36 .2 31 5 R es id en ce U rb an 21 .7 37 .5 21 .2 16 .5 1. 7 1. 4 10 0. 0 8. 5 34 .1 21 .8 15 .2 7. 6 11 .4 1. 4 10 0. 0 16 .3 43 .3 23 7 R ur al 17 .7 37 .2 21 .5 17 .8 5. 2 0. 6 10 0. 0 5. 7 33 .8 25 .2 19 .7 5. 6 9. 5 0. 6 10 0. 0 12 .6 35 .2 1, 52 8 R eg io n K am pa la 21 .9 35 .6 19 .7 22 .1 0. 7 0. 0 10 0. 0 6. 6 35 .5 21 .7 14 .4 11 .5 10 .3 0. 0 10 0. 0 13 .2 38 .2 11 2 C en tra l 1 25 .7 41 .3 18 .8 13 .4 0. 0 0. 7 10 0. 0 13 .4 28 .6 27 .3 16 .1 4. 1 9. 7 0. 7 10 0. 0 19 .6 44 .1 16 6 C en tra l 2 23 .9 36 .8 26 .0 12 .4 0. 0 0. 9 10 0. 0 11 .1 23 .3 29 .8 18 .4 7. 1 10 .2 0. 0 10 0. 0 17 .5 40 .5 16 6 E as t C en tra l 4. 2 40 .1 26 .8 26 .4 2. 6 0. 0 10 0. 0 1. 2 27 .1 28 .9 28 .6 6. 1 8. 1 0. 0 10 0. 0 3. 4 36 .0 27 2 E as te rn 21 .7 33 .7 14 .5 21 .2 7. 8 1. 1 10 0. 0 4. 4 39 .3 17 .8 25 .4 7. 3 4. 8 1. 1 10 0. 0 15 .3 30 .6 41 8 Ka ra m o j a 16 .6 40 .6 19 .2 21 .9 1. 8 0. 0 10 0. 0 12 .8 43 .5 19 .4 12 .4 5. 0 6. 9 0. 0 10 0. 0 13 .9 63 .5 57 N or th 33 .5 35 .1 7. 4 8. 6 15 .4 0. 0 10 0. 0 3. 8 48 .1 19 .2 11 .1 6. 5 11 .4 0. 0 10 0. 0 24 .3 43 .5 15 9 W es t N ile 18 .2 31 .1 17 .5 25 .0 6. 5 1. 6 10 0. 0 0. 9 27 .1 21 .3 25 .4 6. 9 16 .1 2. 3 10 0. 0 5. 3 27 .1 83 W es te rn 5. 4 42 .7 37 .3 11 .6 1. 4 1. 6 10 0. 0 2. 5 39 .5 31 .5 8. 4 2. 1 14 .3 1. 6 10 0. 0 5. 1 32 .4 20 6 S ou th w es t 19 .3 35 .9 27 .5 10 .1 7. 1 0. 0 10 0. 0 14 .5 21 .9 31 .7 13 .5 0. 8 16 .1 1. 4 10 0. 0 15 .8 29 .9 12 6 M ot he r's e du ca tio n N o ed uc at io n 12 .2 42 .8 19 .3 17 .9 7. 8 0. 0 10 0. 0 6. 8 34 .1 23 .3 16 .6 8. 0 11 .2 0. 0 10 0. 0 10 .1 36 .1 23 2 P rim ar y 18 .8 35 .8 22 .0 17 .4 5. 1 0. 9 10 0. 0 6. 1 33 .3 24 .9 20 .5 5. 4 8. 7 1. 0 10 0. 0 13 .3 35 .6 1, 20 8 S ec on da r y + 20 .7 38 .6 21 .0 18 .6 1. 0 0. 2 10 0. 0 5. 4 35 .4 25 .0 15 .8 5. 7 12 .4 0. 3 10 0. 0 14 .6 39 .2 32 6 W ea lth q ui nt ile Lo w es t 18 .9 40 .7 15 .5 17 .1 7. 1 0. 7 10 0. 0 3. 7 39 .7 21 .6 19 .1 6. 2 9. 3 0. 4 10 0. 0 12 .6 36 .0 48 1 S ec on d 16 .4 32 .3 22 .9 20 .5 7. 1 0. 8 10 0. 0 3. 7 29 .9 29 .9 23 .2 4. 7 7. 3 1. 3 10 0. 0 13 .0 33 .0 40 2 M id dl e 18 .3 36 .3 22 .8 18 .8 3. 2 0. 5 10 0. 0 8. 2 32 .2 22 .6 18 .4 7. 7 10 .3 0. 5 10 0. 0 11 .8 32 .7 32 9 Fo ur th 16 .7 38 .5 28 .8 13 .3 2. 7 0. 0 10 0. 0 7. 7 30 .1 29 .1 17 .4 3. 3 12 .1 0. 2 10 0. 0 12 .2 42 .2 27 4 H i g he st 21 .3 38 .2 20 .9 17 .5 1. 0 1. 2 10 0. 0 9. 4 34 .7 20 .8 15 .8 7. 0 11 .1 1. 2 10 0. 0 16 .5 40 .2 27 9 To ta l 18 .3 37 .2 21 .5 17 .6 4. 7 0. 7 10 0. 0 6. 1 33 .8 24 .7 19 .1 5. 8 9. 7 0. 7 10 0. 0 13 .1 36 .3 1, 76 6 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. 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. 136 • Child Health Child Health • 137 10.7 KNOWLEDGE OF ORS PACKETS To ascertain respondents’ knowledge of ORS in Uganda, women were asked whether they had heard of a special product called an ORS packet that can be used to treat diarrhoea. Table 10.10 shows that 9 in 10 mothers with a live birth in the five years preceding the survey had heard about ORS packets. ORS knowledge is slightly higher among urban women (93 percent) than among rural women (89 percent). Knowledge of ORS also varies by region; it ranges from a low of 77 percent among mothers in the Southwest region to a high of 99 percent in Karamoja region. Knowledge of ORS packets increases as a woman’s educational attainment also increases: 87 percent of mothers with no education know about ORS packets while 93 percent of mothers with secondary or higher education know about ORS packets. There is a U-shaped relationship between knowledge of ORS packets and wealth. 10.8 STOOL DISPOSAL The proper disposal of children’s faeces is important in preventing the spread of disease. If faeces are not properly disposed of, disease may be spread by direct contact or through animal contact. The safe disposal of children’s faeces is of particular importance because children’s faeces are more likely to be the cause of faecal contamination in the household environment than other causes, as they are often not disposed of properly and may be mistakenly considered less harmful than adult faeces. Children’s stools are considered to be safely disposed of if the child uses a toilet or latrine, the child’s stool is put in or rinsed into a toilet or latrine, or the stool is buried. Table 10.11 presents the percent distribution of the youngest child under age 5 living with their mother by how the child’s stools are disposed of, according to background characteristics. Eighty-two percent of children’s stools are safely disposed, that is, 15 percent of children use a toilet or latrine, 63 percent of children’s stools are rinsed in the toilet or latrine, and 5 percent are buried. There are marked differences in the way children’s stools are disposed of, depending on background characteristics. A higher proportion of urban children’s stools are disposed of safely than are rural children’s stools (88 and 81 percent, respectively). In addition, children living in homes with improved, non-shared toilet facilities are more likely than those living in homes with shared or non- improved toilet facilities to safely dispose of faecal matter. Regional differentials in safe disposal also are substantial. For example, in Kampala, 89 percent of children’s stools are disposed of safely compared with 41 percent in Karamoja. Safe disposal of children’s stools increases with mother’s level of education and with household wealth quintile. Comparable data from the 2006 UDHS show an increase in safe stool disposal, from 77 percent to 82 percent, over the five years between surveys. 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, Uganda 2011 Background characteristic Percentage of women who know about ORS packets Number of women Age 15-19 86.5 370 20-24 86.8 1,197 25-34 90.8 2,213 35-49 91.5 1,189 Residence Urban 93.3 805 Rural 89.0 4,163 Region Kampala 92.6 358 Central 1 90.4 504 Central 2 94.4 507 East Central 95.0 532 Eastern 85.7 794 Karamoja 98.5 186 North 98.0 445 West Nile 92.5 299 Western 87.3 739 Southwest 76.6 604 Education No education 87.2 713 Primary 89.1 3,079 Secondary+ 92.8 1,177 Wealth quintile Lowest 91.8 1,055 Second 87.9 1,026 Middle 84.4 963 Fourth 89.7 897 Highest 94.2 1,027 Total 89.7 4,968 ORS = Oral rehydration salts 138 • 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, Uganda 2011 Background characteristic Manner of disposal of children's stools Total Percentage of children whose stools are disposed of safely1 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 Don’t know/ Missing Age in months <6 3.6 44.2 1.3 19.7 13.2 2.8 14.7 0.5 100.0 49.1 784 6-11 4.6 69.5 4.8 5.4 6.8 1.9 6.9 0.0 100.0 78.9 812 12-23 5.4 79.2 6.1 1.7 2.7 1.4 3.5 0.0 100.0 90.7 1,324 24-35 13.8 72.0 6.2 1.1 1.2 3.2 2.1 0.4 100.0 92.0 885 36-47 47.2 42.4 2.5 0.3 2.3 2.4 2.8 0.0 100.0 92.1 517 48-59 63.6 24.7 4.1 0.5 0.5 3.3 3.2 0.1 100.0 92.4 309 Toilet facility2 Improved, not shared 22.7 66.6 0.8 2.6 3.1 0.9 2.9 0.3 100.0 90.2 735 Shared3 13.9 71.4 1.1 7.0 2.7 0.5 3.2 0.2 100.0 86.4 679 Non-improved 13.6 59.6 6.1 5.2 5.5 3.0 6.7 0.1 100.0 79.3 3,215 Residence Urban 19.0 67.5 1.0 7.6 2.4 0.3 2.1 0.1 100.0 87.5 690 Rural 14.4 61.6 5.1 4.6 5.1 2.7 6.2 0.2 100.0 81.2 3,941 Region Kampala 19.0 69.9 0.0 7.5 2.2 0.0 1.5 0.0 100.0 88.9 299 Central 1 14.3 72.2 1.2 1.4 5.3 3.0 2.7 0.0 100.0 87.6 454 Central 2 17.8 69.5 0.3 2.8 4.6 0.0 5.0 0.0 100.0 87.6 473 East Central 14.7 65.3 1.1 6.3 7.0 1.2 3.5 0.9 100.0 81.0 502 Eastern 9.0 66.1 9.7 4.1 4.3 1.9 4.9 0.0 100.0 84.8 761 Karamoja 7.7 18.4 14.5 6.9 20.5 24.0 8.0 0.0 100.0 40.6 172 North 13.3 49.7 12.0 5.3 2.4 1.2 16.2 0.0 100.0 74.9 430 West Nile 12.3 66.6 5.8 3.7 1.4 0.9 8.6 0.8 100.0 84.7 280 Western 17.8 61.5 2.0 7.0 6.6 2.9 2.0 0.2 100.0 81.3 685 Southwest 21.9 59.7 3.0 6.3 0.7 0.8 7.6 0.0 100.0 84.7 575 Mother's education No education 15.3 52.0 7.3 4.4 6.2 6.9 7.7 0.1 100.0 74.6 675 Primary 13.5 63.5 5.0 5.3 4.2 2.0 6.2 0.3 100.0 82.0 2,877 Secondary+ 19.4 66.3 1.4 4.9 5.1 0.2 2.7 0.0 100.0 87.1 1,078 Wealth quintile Lowest 7.8 47.0 13.3 6.0 9.0 6.7 10.1 0.1 100.0 68.1 1,008 Second 15.0 63.0 4.4 4.7 3.2 2.3 7.4 0.0 100.0 82.4 981 Middle 13.8 67.8 2.1 5.1 4.7 1.6 4.5 0.5 100.0 83.7 908 Fourth 17.4 68.7 1.4 4.7 4.3 0.4 2.9 0.3 100.0 87.4 838 Highest 22.8 68.0 0.2 4.7 2.0 0.0 2.3 0.0 100.0 91.0 895 Total 15.1 62.5 4.5 5.1 4.7 2.3 5.6 0.2 100.0 82.1 4,631 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 Facilities that would be considered improved if they were not shared by two or more households Nutrition of Children and Adults • 139 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 women and their nutritional status. From birth to age 2 is a period especially important for optimal growth, health, and development. Unfortunately, this period is often marked by micronutrient deficiencies that interfere with optimal growth. In addition, 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, slow recovery from illness, and possibly death. Improving maternal nutrition is crucial for improving children’s health. The 2011 UDHS 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. N Key Findings  There has been a decline over the past five years in the proportion of children that are stunted and underweight.  Breastfeeding is nearly universal in Uganda; about half of all children born in the three years before the survey are breastfed for about 19 months.  More than six in ten children (63 percent) younger than 6 months are exclusively breastfed.  Complementary foods are not introduced in a timely fashion for all children. At 6-9 months, fewer than seven in ten children (68 percent) receive complementary foods.  Overall, only 6 percent of children age 6-23 months are fed appropriately, based on the recommended infant and young child feeding (IYCF) practices.  Forty-nine percent of children age 6-59 months are anaemic, 22 percent are mildly anaemic, 26 percent are moderately anaemic, and 2 percent are severely anaemic.  Overall, 23 percent of women age 15-49 are anaemic; 18 percent are mildly anaemic, 5 percent are moderately anaemic, and less than 1 percent are severely anaemic.  The prevalence of anaemia among both children and women has decreased over the past five years.  Twelve 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). Another 9 percent are mildly thin, and 3 percent are moderately or severely thin. About one in five women (19 percent) are overweight or obese (BMI ≥25 kg/m2).  Thirty-eight percent of children age 6-59 months, and 36 percent of women age 15-49 have vitamin A deficiency. 140 • Nutrition of Children and Adults 11.1 NUTRITIONAL STATUS OF CHILDREN The nutritional status of children under age 5 is an important outcome measure of children’s health. The anthropometric data on height and weight collected in the 2011 UDHS 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 UDHS collected data on the nutritional status of children by measuring the height and weight of all children under age 5. Data were collected to calculate three indices of anthropometric indicators—height-for-age, weight-for-height, and weight-for-age. 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, based on a sample of 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) in 1977. 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 (−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. Nutrition of Children and Adults • 141 Children with weight-for-age below minus three standard deviations (−3 SD) are considered severely underweight. The WHO Child Growth Standards reference population used for the 2006 and 2011 UDHS differs from that used in past UDHS surveys. 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. The team measured recumbent length whenever 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. A total of 2,573 children under age 5 were eligible to be weighed and measured. Of these children, 8 percent had missing values for height or weight and 2 percent had height or weight measures considered to be out of range for their ages. Thus, data are presented for 2,336 children (2,350 children weighted). 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, 33 percent of children under age 5 are stunted, and 14 percent of children are severely stunted. In general, the prevalence of stunting increases as the age of the child increases, with the highest prevalence of chronic malnutrition found in children age 24-35 months (43 percent) and lowest in children 6-8 months (12 percent). Male children are more likely to be stunted than female children (37 and 30 percent, respectively). 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 (43 percent) than among children who were average or larger in size at birth. 142 • Nutrition of Children and Adults The mother’s nutritional status, as measured by her body mass index (BMI), does not have a clear relationship with her child’s level of stunting. As expected, children of overweight or obese mothers are the least likely to be stunted (25 percent); however, interestingly, children of thin mothers (31 percent) are less likely to be stunted than those of normal weight mothers (36 percent). Children in rural areas are almost twice as likely to be stunted as those in urban areas (36 percent versus 19 percent). Regional variation in the prevalence of stunting in children is substantial. Stunting level is lowest among children in Kampala (14 percent) and highest among children in Karamoja (45 percent). The mother’s level of education generally has an inverse relationship with stunting levels. For example, children of mothers with secondary or higher education are the least likely to be stunted (25 percent), while children whose mothers have no education are the most likely to be stunted (42 percent). The relationship between household wealth index and the stunting levels of children does not follow a clear pattern. However, children in the wealthiest households are the least likely to be stunted (21 percent) when compared with children in other quintiles. Weight-for-height Overall, 5 percent of Ugandan children are wasted, and 2 percent are severely wasted. Wasting, or acute malnutrition, is highest in children age 0-8 months (14 percent) and lowest in children age 24-59 months (2 percent). There is no major variation by gender, birth interval, or urban-rural residence. The data show an inverse correlation between wasting and birth weight. A higher proportion of babies who are reported to be very small at birth (12 percent) are acutely malnourished than are babies reported to be average or larger in size (4 percent). Wasting is most common among children of thin mothers (13 percent), among those residing in Karamoja (7 percent), among children whose mothers have no education (7 percent), and among those in the second and middle wealth quintiles (6 percent). A small proportion of children in Uganda are classified as overweight or obese. Overall, 3 percent of children below age 5 are overweight or obese (+2 SD). Variation by background characteristics is minimal. Weight-for-age Table 11.1 shows that 14 percent of children under age 5 are underweight (have low weight-for- age), and 3 percent are severely underweight. The proportion of underweight children is lowest among children 36-59 months old and highest among those 6-8 months old (19 percent). Male children are slightly more likely to be underweight than female children (15 percent versus 13 percent). The percentage of children who are underweight decreases as the length of the birth interval increases. Babies reported to be very small at birth (33 percent) are three times as likely as those reported to be average or larger at birth (11 percent) to be underweight. Children born to mothers who are thin (BMI less than 18.5) (23 percent) are more than three times as likely as children born to mothers who are overweight/obese (7 percent) to be underweight. Nutrition of Children and Adults • 143 Table 11.1 Nutritional status of children Percentage of children under 5 classified as malnourished according to three anthropometric indices of nutritional status: height-for-age, weight-for-height, and weight-for-age, by background characteristics, Uganda 2011 Background characteristic Height-for-age1 Weight-for-height Weight-for-age Number of children Percent- age below -3 SD Percent- age below -2 SD2 Mean Z- score (SD) Percent- age below - 3 SD Percent- age below -2 SD2 Percent- age above +2 SD Mean Z- score (SD) Percent- age below -3 SD Percent- age below -2 SD2 Percent- age above +2 SD Mean Z- score (SD) Age in months <6 4.6 16.1 -0.3 4.4 13.5 6.6 -0.2 3.2 13.3 2.0 -0.5 228 6-8 2.3 12.4 -0.4 6.0 13.6 3.4 -0.6 7.0 19.1 0.1 -0.8 131 9-11 5.8 21.1 -1.0 0.0 5.9 4.3 -0.2 0.0 12.6 0.5 -0.7 120 12-17 13.5 32.0 -1.4 1.4 5.7 2.7 -0.3 3.4 16.1 0.4 -0.9 245 18-23 19.1 42.2 -1.7 1.2 4.9 2.7 -0.1 5.9 17.0 1.7 -0.9 269 24-35 18.7 42.7 -1.8 0.4 2.3 4.8 0.2 2.9 14.6 0.6 -0.8 444 36-47 16.7 37.8 -1.7 0.5 1.8 2.9 0.2 3.9 11.5 0.2 -0.9 477 48-59 12.7 33.1 -1.5 1.4 2.3 1.7 -0.0 2.0 11.2 0.2 -0.9 436 Sex Male 15.6 37.0 -1.5 1.0 4.9 3.9 -0.0 3.0 14.9 0.7 -0.8 1,163 Female 11.9 29.9 -1.3 1.9 4.6 3.0 -0.0 3.8 12.7 0.7 -0.8 1,188 Birth interval in months3 First birth4 11.9 34.3 -1.5 1.2 4.4 2.8 0.0 2.6 13.0 0.8 -0.8 331 <24 18.1 37.4 -1.6 1.1 4.1 3.3 -0.1 3.6 16.2 0.2 -0.9 419 24-47 13.8 33.3 -1.4 1.9 5.6 3.5 -0.0 3.4 13.7 0.9 -0.8 1,025 48+ 8.6 24.9 -1.1 1.8 4.6 6.2 -0.0 4.1 10.0 0.3 -0.7 278 Size at birth3 Very small 23.7 43.0 -1.8 5.1 11.8 2.2 -0.6 11.0 32.5 0.0 -1.5 100 Small 14.9 42.3 -1.7 1.7 7.2 3.4 -0.3 4.5 22.1 0.6 -1.2 338 Average or larger 12.7 30.4 -1.3 1.4 3.9 3.8 0.1 2.6 10.6 0.7 -0.7 1,560 Missing 17.0 39.7 -1.5 1.7 9.3 7.3 -0.0 5.2 13.6 0.0 -0.9 53 Mother's interview status Interviewed 13.7 33.2 -1.4 1.6 5.0 3.7 -0.0 3.4 13.6 0.6 -0.8 2,053 Not interviewed but in household 13.3 31.4 -1.3 1.1 4.3 0.5 -0.1 2.0 18.1 1.6 -0.8 100 Not interviewed and not in the household5 14.7 36.6 -1.5 0.2 2.3 1.9 0.1 4.5 13.2 0.4 -0.8 197 Mother's nutritional status6 Thin -BMI<18.5 13.2 30.8 -1.4 1.7 12.9 2.0 -0.6 6.0 22.6 0.0 -1.2 202 Normal -BMI 18.5- 24.9 14.7 35.8 -1.5 1.6 4.3 3.7 -0.0 3.3 14.4 0.6 -0.9 1,541 Overweight/ obese - BMI ≥ 25 10.3 25.2 -1.1 1.3 3.2 4.7 0.3 2.2 7.1 1.4 -0.4 347 Residence Urban 5.6 18.6 -0.8 2.3 4.2 4.1 0.0 1.1 6.6 2.6 -0.4 307 Rural 15.0 35.6 -1.5 1.4 4.8 3.3 -0.0 3.8 14.9 0.4 -0.9 2,043 Region Kampala 3.1 13.5 -0.7 1.6 4.4 3.5 0.1 2.0 5.7 3.7 -0.3 132 Central 1 14.2 32.5 -1.5 0.4 5.8 4.3 0.0 2.5 12.9 0.9 -0.8 243 Central 2 14.8 36.1 -1.3 2.1 5.3 4.8 0.1 1.4 11.4 1.2 -0.7 219 East Central 12.9 33.5 -1.4 1.7 5.0 2.1 -0.1 3.3 16.7 0.7 -0.8 269 Eastern 7.9 25.3 -1.1 0.6 4.8 2.5 -0.2 1.3 10.0 0.0 -0.8 446 Karamoja 23.5 45.0 -1.8 2.6 7.1 0.1 -0.7 13.4 31.9 0.0 -1.5 82 North 9.9 24.7 -1.3 0.7 3.4 4.1 0.1 3.2 12.3 0.7 -0.7 191 West Nile 18.6 37.8 -1.7 2.4 6.2 2.2 -0.1 5.2 17.9 0.0 -1.1 149 Western 18.9 43.9 -1.8 1.4 2.7 3.2 0.0 4.6 15.5 0.2 -1.0 325 Southwest 18.6 41.7 -1.6 2.8 4.9 5.8 0.3 5.1 14.9 0.6 -0.8 294 Mother's education No education 19.1 41.8 -1.7 2.7 6.9 3.1 -0.1 6.1 20.3 0.0 -1.1 275 Primary 14.5 34.3 -1.4 1.5 4.7 3.7 -0.0 3.2 13.6 0.6 -0.9 1,406 Secondary + 8.0 24.7 -1.1 1.2 4.7 3.5 0.0 2.3 11.1 1.3 -0.6 457 Wealth quintile Lowest 18.9 37.3 -1.6 1.3 4.1 2.5 -0.2 5.8 18.1 0.6 -1.0 505 Second 12.5 30.9 -1.4 2.0 6.2 3.4 -0.1 3.2 14.3 0.3 -0.8 509 Middle 18.4 45.0 -1.8 1.0 5.7 3.2 -0.0 4.4 17.3 0.2 -1.1 487 Fourth 11.7 30.5 -1.3 2.0 4.5 5.1 0.1 2.0 9.5 0.2 -0.7 445 Highest 5.5 20.8 -0.9 1.0 2.8 3.1 0.1 1.3 8.4 2.1 -0.4 405 Total 13.7 33.4 -1.4 1.5 4.7 3.4 -0.0 3.4 13.8 0.7 -0.8 2,350 Note: Table is based on children who stayed in the household on the night before the interview. Each of the indices is expressed in standard deviation units - SD from the median of the WHO Child Growth Standards adopted in 2006. The indices in this table are NOT comparable to those based on the previously used 1977 NCHS/CDC/WHO reference. Table is based on children with valid dates of birth -month and year- and valid measurement of both height and weight. 1 Recumbent length is measured for children under age 2, or in the few cases when the age of the child is unknown and the child is less than 85 cm; standing height is measured for all other children. 2 Includes children who are below -3 standard deviations from the WHO Child Growth standards population median 3 Excludes children whose mothers were not interviewed 4 First-born twins -triplets, etc. are counted as first births because they do not have a previous birth interval 5 Includes children whose mothers are deceased 6 Excludes children whose mothers were not weighed and measured. Mother's nutritional status in terms of BMI (Body Mass Index) is presented in Table 11.10.1 7 For women who are not interviewed, information is taken from the Household Questionnaire. Excludes children whose mothers are not listed in the Household Questionnaire 144 • Nutrition of Children and Adults 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 0 10 20 30 40 50 Height-for-age Weight-for-height Weight-for-age# & , Note: Stunting reflects chronic malnutrition; wasting reflects acute malnutrition; underweight reflects chronic or acute malnutrition or a combination of both. Plotted values are smoothed by a 5-month moving average. Rural children are substantially more likely to be underweight (15 percent) than urban children (7 percent). The proportion of underweight children varies by region. Kampala has the lowest proportion of underweight children, at 6 percent, while Karamoja has the highest prevalence of underweight children, at 32 percent. The proportion of underweight children decreases as mother’s education and household wealth increase. The proportion of underweight children is about two times higher for those born to uneducated mothers than for those whose mothers have secondary or higher education (20 percent versus 11 percent). 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 (18 percent compared with 8 percent). 11.1.4 Trends in Children’s Nutritional Status Trends in the nutritional status of children for the period 2006 through 2011 are shown in Figure 11.2. Figure 11.2 shows a downward trend in the proportion of children stunted and underweight over the last two UDHS surveys, but the proportion of children who are wasted has remained unchanged. Stunting prevalence decreased from 38 percent to 33 percent, a 15 percent decrease. The decline in the proportion of stunted Ugandan children shows overall improvement in chronic malnutrition over the past five years. A similar pattern is observed for the proportion of children that are underweight, which dropped from 16 percent in 2006 to 14 percent in 2011. Nutrition of Children and Adults • 145 Figure 11.2 Trends in nutritional status of children under 5 years 38 6 16 33 5 14 Stunting Wasting Underweight 2006 2006 20062011 2011 2011 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 appeared. 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. 146 • Nutrition of Children and Adults 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, Uganda 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 Number of last- born children Percentage who received a prelacteal feed2 Number of last- born children ever breastfed Sex Male 98.3 51.2 88.8 1,537 42.3 1,511 Female 98.3 53.8 88.6 1,555 39.9 1,528 Assistance at delivery Health professional3 98.5 54.9 89.6 1,882 39.5 1,853 Traditional birth attendant 97.5 52.8 89.2 573 41.3 559 Other 98.6 45.0 85.9 425 44.5 419 No one 98.2 45.7 86.6 210 49.1 206 Place of delivery Health facility 98.4 55.0 89.6 1,831 39.1 1,801 At home 98.1 49.3 87.6 1,225 44.2 1,202 Other (100.0) (38.8) (87.8) 34 (44.0) 34 Residence Urban 97.7 59.6 89.6 450 44.4 440 Rural 98.4 51.3 88.6 2,642 40.6 2,600 Region Kampala 98.3 57.5 89.8 187 41.2 184 Central 1 97.2 46.7 86.2 322 48.7 313 Central 2 97.9 63.4 91.4 340 42.9 333 East Central 98.7 63.9 92.1 345 54.8 340 Eastern 98.5 44.6 89.8 529 26.3 521 Karamoja 99.9 70.4 94.1 107 19.2 107 North 98.9 38.4 80.8 276 38.4 273 West Nile 98.8 27.1 86.8 187 36.5 185 Western 98.3 61.2 89.0 423 48.0 416 Southwest 97.7 54.0 88.0 375 44.2 367 Mother's education No education 98.0 52.5 88.9 399 39.5 391 Primary 98.6 51.4 88.6 1,975 40.4 1,947 Secondary + 97.7 55.5 88.9 718 44.0 702 Wealth quintile Lowest 99.1 50.9 90.5 694 32.6 688 Second 97.8 45.3 87.6 679 38.8 664 Middle 97.9 53.9 89.1 602 46.1 590 Fourth 98.4 54.9 86.8 561 43.2 552 Highest 98.2 59.4 89.3 556 47.1 546 Total 98.3 52.5 88.7 3,092 41.1 3,039 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/midwife, or medical assistant/clinical officer Fifty-three percent of infants started breastfeeding within one hour of birth, and 89 percent within the first day. Initiation of breastfeeding in the first hour after birth varies somewhat by background characteristics. It was more common among female babies (54 percent), babies assisted at delivery by a health professional or born at a health facility (55 percent, each), and those in urban areas (60 percent). By region, initiation of breastfeeding within one hour was lowest in West Nile (27 percent) and highest in Karamoja (70 percent). The likelihood that a child is breastfed in the first hour after birth is slightly higher among children of mothers with secondary or higher education (56 percent) and also higher among children of those in the highest wealth quintile (59 percent). The proportion of children who are breastfed within one day of birth does not vary significantly by background characteristics, except that it is particularly low in North region (81 percent). Overall, more than four in ten children born in the last two years (41 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 more common in children whose delivery was not assisted by anyone (49 percent), children not born in a health facility (44 percent), urban children (44 percent), and children in East Central region (55 percent). Nutrition of Children and Adults • 147 The practice of prelacteal feeding increases with mother’s education and tends to increase with wealth. Thirty-three percent of children in the lowest quintile receive prelacteal feeds compared with 47 percent of those in the highest wealth quintile. 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 age 5 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 age 2 and living with the mother by breastfeeding status and the percentage of children under age 2 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 Uganda. Currently, mothers exclusively breastfeed approximately six in ten children younger than age 6 months (63 percent). Among sub-groups the percentage of young children who are exclusively breastfed decreases sharply from 82 percent of infants age 0-1 month to 69 percent of those age 2-3 months and, further, to 41 percent among infants 4-5 months. 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 Percentage Not Breastfed Exclusively breastfed Plain water only Non-milk liquids Other milk Complementary foods 148 • Nutrition of Children and Adults Table 11.3 Breastfeeding status by age Percent distribution of youngest children under age 2 and living with their mother, by breastfeeding status; the percentage currently breastfeeding; and the percentage of all children under age 2 using a bottle with a nipple, according to age in months, Uganda 2011 Age in months Not breast- feeding Breastfeeding status Total Percentage currently breast- feeding Number of youngest child under two years living with their mother Percentage using a bottle with a nipple Number of all children under two years Exclu- sively breastfed Breast- feeding and consu- ming plain water only Breast- feeding and consu- ming non- milk liquids1 Breast- feeding and consu- ming other milk Breast- feeding and consu- ming comple- mentary foods 0-1 3.9 81.9 4.7 1.8 2.0 5.8 100.0 96.1 238 3.7 242 2-3 0.7 68.5 3.7 4.0 11.7 11.4 100.0 99.3 279 12.1 285 4-5 3.1 41.0 7.8 5.8 17.8 24.4 100.0 96.9 267 28.9 275 6-8 4.0 12.1 5.6 5.7 9.2 63.4 100.0 96.0 408 29.2 417 9-11 6.4 1.7 2.5 1.2 1.9 86.1 100.0 93.6 405 29.5 411 12-17 16.3 2.1 1.9 0.9 0.6 78.1 100.0 83.7 681 25.0 723 18-23 46.9 0.9 0.5 1.0 1.2 49.6 100.0 53.1 643 19.4 756 0-3 2.1 74.7 4.2 3.0 7.2 8.8 100.0 97.9 517 8.3 527 0-5 2.5 63.2 5.4 4.0 10.8 14.1 100.0 97.5 784 15.3 802 6-9 4.6 9.9 5.7 4.7 7.3 67.7 100.0 95.4 536 30.2 548 12-15 13.1 2.1 1.8 0.8 0.9 81.4 100.0 86.9 465 28.5 485 12-23 31.2 1.5 1.3 0.9 0.9 64.3 100.0 68.8 1,324 22.2 1,480 20-23 54.2 1.0 0.8 1.0 1.0 42.0 100.0 45.8 438 17.8 535 Note: Breastfeeding status refers to a ‘24-hour’ period (yesterday and last night). Children who are classified as breastfeeding and consuming plain water only consumed no liquid or solid supplements. The categories of not breastfeeding, exclusively breastfed, breastfeeding and consuming plain water, non-milk liquids, other milk, and complementary foods (solids and semi-solids) are hierarchical and mutually exclusive, and their percentages add to 100 percent. Thus children who receive breast milk and non-milk liquids and who do not receive other milk and who do not receive complementary foods are classified in the non-milk liquid category even though they may also get plain water. Any children who get complementary food are classified in that category as long as they are breastfeeding as well. 1 Non-milk liquids include juice, juice drinks, clear broth, or other liquids In addition to breast milk, 14 percent of infants under age 6 months are given complementary foods, 11 percent are given other milk, 5 percent are given plain water only, and 4 percent are given non- milk liquids and juice (Figure 11.3 and Table 11.3). Complementary feeding increases from 6 percent of children age 0-1 months to 24 percent among those 4-5 months. Fifteen percent of infants under age 6 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 Uganda is long. The proportion of children who are currently breastfeeding is 94 percent or more for children up to age 9-11 months and then declines to 84 percent of children age 12-17 months and 53 percent for those 18-23 months. Figure 11.4 shows several infant and young child feeding (IYCF) indicators of breastfeeding status. As mentioned above, 63 percent of children under age 6 months and 41 percent of children 4-5 months are exclusively breastfed, and 73 percent of children under age 6 months are predominantly breastfed1. Close to seven in ten children age 6-8 months (67 percent) consume solid, semi-solid, or soft foods. A similar proportion (67 percent) of children under the age of two receive age-appropriate breastfeeding2, while about one in five children (22 percent) use a bottle with a nipple. Eighty-seven percent of children continued breastfeeding at one year, and 46 percent continued breastfeeding at two years. 1 Children who are exclusively breastfed, children who breastfeed and consume plain water, and children who are breastfeed and consume non-milk liquids or juice. 2 Includes children age 0-5 months who are exclusively breastfed and children age 6-23 months who receive breast milk and complementary foods. Nutrition of Children and Adults • 149 Figure 11.4 IYCF indicators on breastfeeding status 63 41 87 67 46 67 73 22 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 of age (6-8 months) 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 Uganda are 19 months. The median duration of exclusive breastfeeding is 3.4 months, and the mean duration of exclusive breastfeeding is 4.6 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 4.4 months and 5.7 months, respectively. The median duration of any breastfeeding varies somewhat by background characteristics. It is longer among rural children (19.7 months) and among children in Karamoja (23.0 months). Women with secondary and higher education breastfeed for about three months less than women who have no education (18.1 months versus 21.4 months). Similarly, children in the highest wealth quintile have a lower median duration of any breastfeeding (17.2 months) than those in the lowest quintile (20.5 months). The variation in the median duration of exclusive and predominant breastfeeding by background characteristics is not as pronounced. 150 • Nutrition of Children and Adults Table 11.4 Median duration of breastfeeding Median duration of any breastfeeding, exclusive breastfeeding, and predominant breastfeeding among children born in the three years preceding the survey, by background characteristics, Uganda 2011 Background characteristic Median duration (months) of breastfeeding among children born in the past three years1 Any breast- feeding Exclusive breast- feeding Predominant breast- feeding2 Sex Male 19.8 3.6 4.6 Female 19.0 3.1 4.2 Residence Urban 16.3 3.2 4.3 Rural 19.7 3.4 4.4 Region Kampala 13.6 1.7 3.2 Central 1 18.2 3.4 4.6 Central 2 18.8 4.8 5.2 East Central 18.6 3.0 4.3 Eastern 19.5 3.1 3.9 Karamoja 23.0 4.4 4.7 North 21.4 3.8 5.5 West Nile 21.5 3.3 4.8 Western 16.5 4.4 5.4 Southwest 21.1 2.1 2.3 Mother's education No education 21.4 3.6 4.1 Primary 19.4 3.4 4.5 Secondary + 18.1 3.3 4.4 Wealth quintile Lowest 20.5 3.5 4.6 Second 20.7 3.7 5.0 Middle 18.9 3.5 4.4 Fourth 18.8 3.6 4.3 Highest 17.2 2.6 3.6 Total 19.4 3.4 4.4 Mean for all children 19.0 4.6 5.7 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 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 the family diet, in addition to breastfeeding, children age 6 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 UDHS 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 their mothers. These data are presented in Table 11.5 according to breastfeeding status. Infant formula supplementation at any age is uncommon in Uganda. Among breastfeeding children under age 2, less than 1 percent consume infant formula. However, a much higher proportion receive other milk (22 percent). The introduction of other liquids, such as water, juice, and formula, takes place earlier than the recommended introduction at age 6 months. Among the youngest breastfeeding children (0-1 month), 3 percent, each, consume other milk and other liquids. Consumption of other milk increases gradually with age until age 9-11 months, when about three in ten (29 percent) breastfeeding Nutrition of Children and Adults • 151 children consume milk. Consumption of other liquids also shows increasing trends with age through age 9- 17 months, when 51 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, 58 percent ate foods made from grains, 42 percent ate foods made from roots and tubers, and 41 percent ate fruits and vegatables rich in vitamin A during the day or night preceding the interview. Meat, fish, poultry, and eggs have body- building substances essential to good health. They are important for balanced physical and mental development. Overall, 27 percent of children age 6-23 months consume meat, fish, or poultry, and 8 percent consume eggs. Only 3 percent of children in this age group consumed cheese, yogurt, or other dairy products in the 24 hours preceding the survey. Overall, almost nine in ten breastfeeding children age 6-23 months (87 percent) consumed some solid or semi-soild food during the day or night preceding the survey. A comparison of dietary intake of children under age 2 by breastfeeding status shows that a higher proportion of nonbreastfeeding children (93 percent) than breastfeeding children (87 percent) are consuming solid and semi-solid foods. The consumption of all groups of liquids and solid or semi-solid foods is more common among the nonbreastfeeding children than among those who are still breastfeeding. Table 11.5 Foods and liquids consumed by children in the day or night preceding the interview Percentage of youngest children under age 2 who are living with the mother by type of foods consumed in the day or night preceding the interview, according to breastfeeding status and age, Uganda 2011 Age in months Liquids Solid or semi-solid foods Any solid or semi- solid food Number of children Infant formula Other milk1 Other liquids2 Food made from grains3 Fruits and vege- tables rich in vitamin A4 Other fruits and vege- tables Food made from roots and tubers Food made from legumes and nuts Meat, fish, poultry Eggs Cheese, yogurt, other milk product BREASTFEEDING CHILDREN 0-1 0.0 3.4 2.9 6.0 3.2 1.2 3.6 0.0 0.4 0.0 0.0 6.0 229 2-3 1.1 11.8 7.2 10.0 4.4 0.5 3.9 0.0 0.5 0.0 0.1 11.4 277 4-5 0.1 24.7 17.0 18.6 8.0 2.9 5.6 1.8 5.1 0.7 0.9 25.2 259 6-8 0.3 27.0 37.7 45.9 27.2 8.6 25.6 3.1 18.5 6.7 1.9 66.1 391 9-11 0.5 29.2 51.0 61.5 39.7 12.0 46.2 3.2 28.8 8.2 3.1 92.1 378 12-17 0.5 23.9 51.1 60.1 48.3 21.0 46.7 6.8 32.0 8.6 3.2 93.4 570 18-23 0.0 20.6 47.6 62.4 46.8 18.5 48.8 9.3 28.5 7.5 2.1 93.3 341 6-23 0.3 25.1 47.2 57.6 41.1 15.6 42.1 5.6 27.4 7.8 2.6 86.7 1,681 Total 0.4 21.5 35.4 43.2 29.9 11.2 30.3 4.1 19.5 5.5 1.9 64.1 2,446 NONBREASTFEEDING CHILDREN 0-11 0.0 48.8 29.4 48.6 27.1 9.0 29.9 1.2 12.1 12.4 4.7 68.4 62 12-23 0.1 39.3 57.2 71.5 47.4 25.7 50.3 5.6 37.4 14.5 4.4 96.8 412 Total 1.0 40.5 53.6 68.5 44.7 23.5 47.6 5.0 34.1 14.3 4.4 93.1 474 Note: Breastfeeding status and food consumed refer to a 24-hour period (yesterday and last night). 1 Other milk includes fresh, tinned, and powdered cow or other animal milk 2 Doesn't include plain water 3 Includes fortified baby food 4 Includes pumpkin, red or yellow yams or squash, carrots, red sweet potatoes, dark green leafy vegetables such as spinach, amaranths, cassava and bean leaves, mangoes, papayas, and other locally grown fruits and vegetables that are rich in vitamin A 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. Breastfed children age 6-23 months should receive animal-source foods and vitamin A-rich fruits and 152 • Nutrition of Children and Adults 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 age 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 age 9-23 months should be fed meals three or four times per day, with one to two snacks (WHO, 2008). Nonbreastfed children age 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. Close to nine in ten (86 percent) children age 6-23 months received breast milk or milk products during the 24-hour period before the survey, and more than four in ten (45 percent) were fed at least the minimum number of times. Only one in eight (13 percent) of all children age 6-23 months were fed according to minimum standards with respect to food diversity (four or more food groups). Overall, only 6 percent of youngest children age 6-23 months living with their mothers are fed in accordance with 3 IYCF practices. Older children, children in urban areas, and those residing in Kampala 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 increase. N ut rit io n of C hi ld re n an d A du lts • 1 53 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 o f f oo d gr ou ps , 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, U ga nd a 20 11 Ba ck gr ou nd ch ar ac te ris tic Am 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: N um be r o f br ea st fe d ch ild re n 6- 23 m on th s Am on g no nb re as tfe d ch ild re n 6- 23 m on th s, p er ce nt ag e fe d: N um be r of 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, pe rc en ta ge fe d: N um 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 Bo th 4 + fo od gr ou ps a nd m in im um m ea l fre qu en cy M ilk o r m ilk pr od uc ts 3 4+ fo od gr ou ps 1 M in im um m ea l fre qu en cy 4 W ith 3 IY C F pr ac tic es 5 Br ea st 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 6. 1 55 .7 4. 5 39 1 42 .8 0. 0 42 .8 0. 0 16 97 .7 5. 8 55 .2 4. 3 40 8 9- 11 9. 8 35 .2 3. 6 37 8 61 .0 12 .9 65 .2 5. 8 26 97 .5 10 .0 37 .2 3. 7 40 5 12 -1 7 13 .4 42 .8 7. 4 57 0 42 .6 28 .0 49 .6 7. 7 11 1 90 .6 15 .8 43 .9 7. 4 68 1 18 -2 3 11 .5 41 .1 6. 6 34 1 29 .4 21 .1 47 .4 5. 8 30 1 66 .9 16 .0 44 .0 6. 3 64 3 Se x M al e 11 .0 43 .3 5. 9 84 1 36 .3 18 .6 48 .9 6. 4 20 8 87 .4 12 .5 44 .4 6. 0 1, 04 9 Fe m al e 10 .0 44 .2 5. 5 84 0 33 .8 24 .0 48 .7 5. 8 24 7 85 .0 13 .2 45 .2 5. 5 1, 08 7 R es id en ce U rb an 17 .2 42 .8 8. 1 19 8 56 .1 30 .7 65 .0 14 .5 86 86 .7 21 .3 49 .5 10 .1 28 5 R ur al 9. 6 43 .9 5. 4 1, 48 3 30 .0 19 .4 45 .0 4. 1 36 8 86 .1 11 .6 44 .1 5. 1 1, 85 1 R eg io n Ka m pa la 18 .5 46 .9 12 .5 77 63 .0 35 .8 71 .9 20 .5 49 85 .6 25 .2 56 .6 15 .6 12 6 C en tra l 1 20 .5 38 .8 3. 0 13 9 42 .3 29 .7 63 .8 7. 2 73 80 .2 23 .6 47 .4 4. 4 21 2 C en tra l 2 17 .7 39 .6 9. 3 18 4 54 .4 26 .8 54 .0 3. 7 47 90 .8 19 .5 42 .5 8. 2 23 1 Ea st C en tra l 2. 8 30 .7 0. 6 18 1 24 .9 9. 2 30 .8 2. 0 56 82 .2 4. 3 30 .8 0. 9 23 7 Ea st er n 11 .3 53 .2 9. 8 30 8 14 .2 20 .3 36 .7 2. 0 74 83 .3 13 .0 50 .0 8. 3 38 2 Ka ra m o j a 3. 3 26 .8 1. 9 75 60 .9 5. 6 66 .5 5. 6 7 96 .9 3. 5 30 .0 2. 2 82 N or th 7. 2 28 .5 2. 4 18 0 17 .8 11 .3 21 .2 4. 9 22 91 .0 7. 6 27 .7 2. 7 20 2 W es t N ile 7. 1 50 .5 5. 1 11 8 17 .6 5. 8 27 .9 0. 0 15 90 .5 7. 0 47 .9 4. 5 13 3 W es te rn 12 .3 56 .3 6. 6 20 9 29 .3 23 .9 53 .0 4. 0 73 81 .6 15 .3 55 .5 5. 9 28 2 So ut hw es t 5. 7 49 .7 3. 8 21 1 39 .5 12 .4 47 .1 9. 5 39 90 .6 6. 7 49 .3 4. 7 25 0 M ot he r's e du ca tio n N o ed uc at io n 6. 1 31 .8 2. 1 23 9 26 .0 8. 1 37 .1 3. 2 39 89 .7 6. 4 32 .5 2. 3 27 8 P rim ar y 9. 9 44 .9 6. 2 1, 09 3 28 .0 19 .3 39 .2 3. 6 28 4 85 .1 11 .8 43 .7 5. 7 1, 37 8 Se co nd ar y + 15 .4 48 .4 6. 5 34 9 52 .6 30 .1 72 .7 12 .2 13 2 87 .0 19 .5 55 .0 8. 1 48 1 W ea lth q ui nt ile Lo w es t 4. 3 36 .3 2. 8 42 3 18 .4 9. 3 27 .8 0. 5 76 87 .5 5. 1 35 .0 2. 4 49 9 Se co nd 6. 2 44 .3 4. 2 38 3 24 .2 17 .0 38 .8 3. 6 86 86 .1 8. 2 43 .3 4. 1 46 9 M id dl e 12 .6 48 .3 8. 4 32 9 35 .3 28 .7 50 .8 5. 5 87 86 .5 16 .0 48 .8 7. 8 41 5 Fo ur th 15 .6 44 .7 5. 5 29 5 27 .7 20 .6 46 .3 3. 0 89 83 .2 16 .8 45 .0 4. 9 38 4 H i g he st 18 .7 48 .5 9. 5 25 2 58 .9 28 .2 70 .2 14 .4 11 7 87 .0 21 .7 55 .4 11 .1 36 9 To ta l 10 .5 43 .8 5. 7 1, 68 1 35 .0 21 .5 48 .8 6. 1 45 5 86 .2 12 .8 44 .8 5. 8 2, 13 6 1 Fo od g ro up s: a . i nf an t f or m ul a, m ilk o th er th an b re as t m ilk , c he es e or y og ur t o r ot he r m ilk p ro du ct s; b . f oo ds m ad e fro m g ra in s, r oo ts , a nd tu be rs , i nc lu di ng p or rid ge a nd fo rti fie d ba by fo od fr om g ra in s; c . vi ta m in A -r ic h fru its a nd v eg et ab le s; d . o th er fr ui ts a nd v eg et ab le s; e . e gg s; f. m ea t, po ul try , f is h, a nd s he llf is h (a nd o rg an m ea ts ); g. le gu m es a nd n ut s. 2 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, fr es h, ti nn ed , a nd p ow de re d an im al m ilk , a nd y og ur t 4 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 s em i-s ol id fo od s fro m a t l ea st fo ur fo od g ro up s no t i nc lu di ng th e m ilk /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 Nutrition of Children and Adults • 153 154 • Nutrition of Children and Adults Among breastfed children age 6-23 months, 11 percent receive foods from at least four food groups, while 44 percent are fed the minimum number of times or more. In total, 6 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. Among nonbreastfed children in the same age group, 35 percent receive milk or milk products, 22 percent receive foods from at least four food groups, and 49 percent are fed the minimum number of times or more. Similar to breastfed children, 6 percent of nonbreastfed children are fed in accordance with IYCF practices (Figure 11.5). Figure 11.5 IYCF indicators on minimum acceptable diet 11 44 6 22 49 6 13 45 6 IYCF 5: Minimum dietary diversity IYCF 6: Minimum meal frequency IYCF 7: Minimum acceptable diet Breastfed Nonbreastfed All children 6-23 months 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), and 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 to be a medium-level public health problem, and between 5 and less than 20 percent to be a mild public health problem (WHO, 2001a). Table 11.7 presents anaemia levels among children age 6-59 months, according to selected background characteristics. Haemoglobin was measured in 2,121 children (2,142 children, weighted) that account for 92 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, Nutrition of Children and Adults • 155 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. About half of Ugandan children 6-59 months (49 percent) are anaemic. More than one of every five (22 percent) has mild anaemia, more than one in four (26 percent) has moderate anaemia, and 2 percent have severe anaemia. Anaemia prevalence is highest among children age 9-11 months (69 percent) and decreases steadily with age from 12 to 59 months. Fifty-one percent of children in rural areas have anaemia, compared with 38 percent of children in urban areas. Regional variation of anaemia in children ranges from 25 percent in Southwest to 70 percent in Karamoja. Anaemia among children generally decreases with increases in mother’s education and wealth quintile. Table 11.7 Prevalence of anaemia in children Percentage of children age 6-59 months classified as having anaemia, by background characteristics, Uganda 2011 Background characteristic Anaemia status by haemoglobin level Any anaemia (<11.0 g/dl) Mild anaemia (10.0- 10.9 g/dl) Moderate anaemia (7.0-9.9 g/dl) Severe anaemia (< 7.0 g/dl) Number of children Age in months 6-8 67.0 22.3 41.3 3.4 124 9-11 68.5 24.6 41.6 2.3 120 12-17 65.2 32.1 29.6 3.5 250 18-23 54.6 20.4 32.3 2.0 265 24-35 49.4 21.6 26.7 1.2 444 36-47 40.5 21.3 19.0 0.1 480 48-59 36.8 19.3 16.5 1.0 459 Sex Male 50.2 22.1 27.0 1.0 1,064 Female 48.4 22.5 24.0 1.9 1,078 Mother's interview status Interviewed 50.3 22.1 26.6 1.6 1,796 Not interviewed but in household 58.8 32.2 26.6 0.0 106 Not interviewed and not in the household1 37.8 19.9 17.1 0.8 240 Residence Urban 38.0 19.3 18.3 0.4 265 Rural 50.9 22.7 26.5 1.6 1,877 Region Kampala 39.8 17.0 22.3 0.5 122 Central 1 56.8 27.0 29.1 0.7 209 Central 2 54.2 22.2 30.8 1.1 199 East Central 67.5 21.7 43.4 2.4 257 Eastern 54.6 22.3 28.9 3.4 419 Karamoja 69.5 34.7 34.6 0.2 79 North 34.0 21.1 12.6 0.4 178 West Nile 64.4 26.9 36.3 1.2 141 Western 38.6 22.3 14.9 1.4 285 Southwest 24.6 16.2 8.4 0.0 253 Mother's education1 No education 49.9 24.7 25.0 0.2 253 Primary 52.0 21.4 28.7 1.9 1,238 Secondary + 47.2 24.7 21.1 1.4 395 Wealth quintile Lowest 59.0 23.6 33.1 2.4 477 Second 51.7 21.4 28.3 2.1 453 Middle 51.0 25.6 24.4 1.0 460 Fourth 42.8 19.2 22.5 1.1 394 Highest 38.2 21.0 16.6 0.5 357 Total 49.3 22.3 25.5 1.5 2,142 Note: Table is based on children who stayed in the household on the night before the interview and who were tested for anaemia. Prevalence of anaemia, based on haemoglobin levels, is adjusted for altitude using formulas in CDC, 1998. Haemoglobin in grams per decilitre (g/dl). 1 Includes children whose mothers are deceased 2 For women who are not interviewed, information is taken from the Household Questionnaire. Excludes children whose mothers are not listed in the Household Questionnaire. 156 • Nutrition of Children and Adults The national anaemia prevalence estimate decreased substantially from 73 percent in 2006 to 49 percent in 2011 (Figure 11.6). This change is due largely to the drop in the prevalence of moderate anaemia. Figure 11.6 Trends in anaemia status among children under 5 years 73 22 43 7 49 22 26 2 Any Anemia Mild Moderate Severe Any anaemia Mild Moderate Severe 2006 2006 20062011 2011 2011 2006 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 UDHS 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) with vitamin A supplements is one method of ensuring that children at risk do not develop VAD. Table 11.8 shows that 61 percent of the 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 43 percent at 6-8 months to 67 percent at 18-23 months). Nonbreastfeeding children are more likely than breastfeeding children to consume foods rich in vitamin A (69 percent compared with 59 percent). Male children are slightly more likely to consume foods rich in vitamin A than female children (63 percent versus 60 percent). There are no major variations in children’s consumption of foods rich in vitamin A in the past 24 hours and mother’s age at birth or urban-rural residence. With regard to regions, children living in the Eastern region are most likely to consume foods rich in vitamin A (74 percent), while those in the Southwest region are least likely (50 Nutrition of Children and Adults • 157 percent). Mother’s level of education and wealth do not have a clear relationship with consumption of foods rich in vitamin A by young children age 6-23 months. As noted, low iron intake can also contribute to anaemia. Also, iron is essential for cognitive development. Iron requirements are greatest at age 6-11 months, when growth is extremely rapid. As Table 11.8 shows, about one-third (34 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 from 23 percent at age 6-8 months to 37-38 percent among children 12-23 months. Nonbreastfeeding children are more likely than breastfeeding children to consume iron-rich foods (42 percent versus 32 percent). Further, consumption of iron-rich foods is more common in urban areas (45 percent) than in rural areas (32 percent). Children in Southwest and Karamoja are the least likely to consume iron-rich foods (10 percent, each), while those living in Kampala are the most likely (49 percent). Children whose mothers have some secondary education are more likely to consume iron-rich foods (37 percent) than those whose mothers have no education (26 percent). Similarly, wealth status is directly related to the consumption of foods rich in iron, with 28 percent of children in the lowest wealth quintile consuming foods rich in iron in the 24 hours before the survey compared with 42 percent of children in the highest wealth quintile. The 2011 UDHS also collected data on vitamin A and iron supplementation for children age 6-59 months. Table 11.8 shows that almost six in ten children age 6-59 months (57 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, genders, mother’s age at birth, urban-rural residence, or wealth. Vitamin A supplementation is higher among breastfeeding than nonbreastfeeding children (63 percent versus 55 percent). At the regional level, the proportion of children receiving vitamin A supplements is lowest in Central 1 (36 percent) and highest in Karamoja (74 percent). Mother’s level of education is closely associated with children receiving vitamin A supplements; 54 percent of children whose mothers have no education received vitamin A supplements in the past six months compared with 63 percent of children whose mothers have more than a secondary education. Iron supplementation coverage is generally low in Uganda. Only 7 percent of children age 6-59 months were given iron supplements in the seven days preceding the survey. It does not vary much by background characteristics, except for regional variations. Kampala and Southwest have the lowest coverage (4 percent each) compared with Karamoja, North, and West Nile regions that have the highest coverage (12 percent each). 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, half 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, from 19 percent for children 6-8 months to 58 percent among those 18-23 months, after which it starts to decrease. It is lower among breastfeeding children (42 percent), children whose mother’s age at childbirth was 15-19 (40 percent), and among rural children (49 percent). Karamoja (65 percent) has the highest proportion of children who received deworming medication, while East Central and Southwest (43 percent each) have the lowest proportion. The proportion of children 6-59 months receiving deworming medication increases with mother’s education and household wealth. 158 • Nutrition of Children and Adults Table 11.8 Micronutrient intake among children Among youngest children age 6-23 months who are living with their mother, the percentages who consumed vitamin A-rich and iron-rich foods in the day or night preceding the survey, and among all children 6-59 months, the percentages who were given vitamin A supplements in the six months preceding the survey, who were given iron supplements in the past seven days, and who were given deworming medication in the six months preceding the survey, and among all children age 6-59 months who live in households that were tested for iodized salt, the percentage who live in households with iodised salt, by background characteristics, Uganda 2011 Background characteristic Among youngest children age 6-23 months living with the mother: Among all children age 6-59 months: Among all children age 6- 59 months living in households tested for iodised salt: Percentage who consumed foods rich in vitamin A in past 24 hours1 Percentage who consumed foods rich in iron in past 24 hours2 Number of children Percentage given vitamin A supple- ments in past 6 months Percentage given iron supple- ments in past 7 days Percentage given deworming medication in past 6 months3 Number of children Percentage living in households with iodised salt4 Number of children Age in months 6-8 43.4 23.2 408 53.2 6.6 18.7 417 98.6 401 9-11 59.8 33.2 405 66.2 8.8 33.5 411 98.5 395 12-17 67.0 37.7 681 68.6 7.7 51.5 723 99.4 695 18-23 67.3 36.6 643 59.4 6.6 57.8 756 98.9 724 24-35 na na na 56.8 7.6 56.2 1,515 99.3 1,440 36-47 na na na 52.4 6.4 52.0 1,473 99.1 1,424 48-59 na na na 52.4 6.9 51.4 1,438 98.7 1,359 Sex Male 62.6 34.5 1,049 57.1 7.1 50.4 3,344 99.1 3,205 Female 59.9 32.9 1,087 56.5 7.1 50.1 3,389 99.0 3,232 Breastfeeding status Breastfeeding 59.1 31.5 1,681 63.1 7.8 41.9 1,821 99.1 1,738 Not breastfeeding 69.0 41.8 455 54.5 6.8 53.3 4,897 99.0 4,684 Mother's age at birth 15-19 59.4 30.3 194 58.2 8.2 39.6 332 99.6 310 20-29 59.6 34.7 1,178 58.1 7.3 50.5 3,662 99.1 3,524 30-39 65.3 33.3 647 55.4 6.5 51.3 2,192 98.8 2,092 40-49 57.8 31.7 117 53.2 6.9 50.5 546 98.9 511 Residence Urban 61.7 45.2 285 57.7 7.0 59.8 947 99.2 905 Rural 61.2 31.9 1,851 56.7 7.1 48.6 5,786 99.0 5,532 Region Kampala 60.5 49.0 126 50.7 3.6 59.2 415 99.0 401 Central 1 68.0 43.8 212 36.2 5.9 46.8 649 99.6 617 Central 2 53.7 36.7 231 44.1 5.9 49.6 703 97.5 674 East Central 54.9 33.4 237 70.8 5.4 42.6 767 98.8 735 Eastern 73.9 45.0 382 71.0 9.9 56.5 1,162 100.0 1,105 Karamoja 68.1 9.8 82 73.7 12.3 64.5 260 99.8 229 North 58.6 25.9 202 59.4 11.6 48.2 606 100.0 592 West Nile 71.6 44.5 133 53.7 11.7 46.7 399 98.4 370 Western 56.3 30.8 282 60.0 4.7 52.7 978 98.4 947 Southwest 49.5 9.6 250 44.1 3.9 42.6 794 98.6 768 Mother's education No education 61.5 26.4 278 53.8 8.1 43.3 982 98.8 902 Primary 61.9 34.0 1,378 55.4 6.5 47.6 4,297 99.0 4,125 Secondary + 59.2 37.2 481 63.0 8.0 62.5 1,455 99.1 1,411 Wealth quintile Lowest 63.7 27.5 499 62.1 8.6 47.8 1,514 99.3 1,410 Second 63.3 33.4 469 58.3 7.8 48.7 1,423 99.2 1,372 Middle 58.1 32.3 415 50.8 5.9 43.9 1,350 98.8 1,288 Fourth 59.5 35.4 384 55.5 5.8 51.8 1,174 98.5 1,132 Highest 60.6 42.3 369 56.4 7.0 60.1 1,272 99.2 1,235 Total 61.2 33.7 2,136 56.8 7.1 50.2 6,733 99.0 6,437 Note: Information on vitamin A is based on both mother's recall and the immunization card (where available). Information on iron supplements and deworming medication is based on the mother's recall. Total includes 15 children with missing information on breastfeeding status. na = Not applicable 1 Includes meat (and organ meat), fish, poultry, eggs, pumpkin, red or yellow yams or squash, carrots, red sweet potatoes, dark green leafy vegetables such as spinach, amaranths, cassava, and bean leaves, mangoes, papayas, and other locally grown fruits and vegetables that are rich in vitamin A 2 Includes meat (including organ meat) 3 Deworming for intestinal parasites is commonly done for helminthes and for schistosomiasis. 4 Excludes children in households in which salt was not tested. 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 Uganda, interviewers in Nutrition of Children and Adults • 159 the 2011 UDHS 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, almost all children (99 percent) live in households that use iodised salt. There is no major variation by background characteristics. 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-two percent of households had salt tested for iodine at the time of the interview. Of these households, 99 percent were using iodised salt. Because the presence of iodised salt in the households is almost universal, there is no major variation by background characteristics. Table 11.9 Presence of iodized 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 iodized salt, according to background characteristics, Uganda 2011 Background characteristic Among all households, the percentage: Among households with tested salt: With salt tested With no salt in the household Number of households Percentage with iodized salt Number of households Residence Urban 88.0 12.0 1,691 98.7 1,489 Rural 92.3 7.7 7,342 99.1 6,775 Region Kampala 89.0 11.0 797 98.3 709 Central 1 91.5 8.5 1,140 99.6 1,043 Central 2 89.9 10.1 1,038 98.8 934 East Central 91.4 8.6 904 98.5 826 Eastern 91.2 8.8 1,226 100.0 1,118 Karamoja 81.3 18.7 306 99.8 249 North 95.5 4.5 757 100.0 723 West Nile 89.0 11.0 508 98.6 453 Western 94.3 5.7 1,228 98.5 1,159 Southwest 93.0 7.0 1,128 98.4 1,049 Wealth quintile Lowest 89.6 10.4 1,719 99.3 1,541 Second 91.9 8.1 1,767 98.7 1,624 Middle 92.0 8.0 1,672 98.8 1,538 Fourth 91.6 8.4 1,723 99.2 1,579 Highest 92.1 7.9 2,152 99.1 1,981 Total 91.5 8.5 9,033 99.0 8,263 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 UDHS measured the height and weight of women age 15-49 and men age 15-59. 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 160 • Nutrition of Children and Adults 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 less than 145 cm, mean BMI, and the proportions of women falling into normal and 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 2,355 women age 15-49 years (2,316 weighted women), while the height analysis is based on 2,707 women (2,667 weighted women). As shown in Table 11.10.1, just 2 percent of Ugandan women are below 145 cm in height. In general, height differs little with background characteristics. The mean BMI for Ugandan women age 15-49 is 22.3 kg/m2. There are no major differences in mean BMI by women’s background characteristics. Table 11.10.1 Nutritional status of women Among women age 15-49, the percentage with height under 145 cm, the mean Body Mass Index (BMI), and the percentage with specific BMI levels, by background characteristics, Uganda 2011 Background characteristic Height Body Mass Index1 Mean Body Mass Index (BMI) Normal Thin Overweight/obese Number of women 18.5-24.9 (total normal) <18.5 (total thin) 17.0-18.4 (mildly thin) <17 (modera- tely and severely thin) ≥25.0 (total over- weight or obese 25.0-29.9 (over- weight) ≥30.0 (obese) Percent- age below 145 cm Number of women Age 15-19 1.9 645 21.5 74.2 14.3 10.4 3.9 11.5 10.5 1.0 583 20-29 1.8 967 22.2 73.8 10.1 8.1 2.0 16.1 13.4 2.7 785 30-39 1.5 670 22.8 65.4 10.3 8.5 1.8 24.4 16.8 7.5 575 40-49 0.8 385 22.8 59.3 13.4 11.0 2.4 27.3 20.2 7.1 374 Residence Urban 0.5 551 23.9 57.5 7.6 5.8 1.8 34.9 25.5 9.5 503 Rural 1.9 2,116 21.8 72.8 12.9 10.2 2.7 14.3 11.6 2.7 1,813 Region Kampala 0.8 263 24.4 51.9 7.7 5.3 2.4 40.4 27.4 13.0 241 Central 1 1.9 272 23.0 69.4 7.3 6.8 0.5 23.3 17.0 6.3 242 Central 2 1.5 267 22.6 71.4 8.2 7.1 1.1 20.4 16.8 3.6 233 East Central 0.0 272 21.9 72.3 11.9 8.3 3.6 15.7 14.4 1.4 224 Eastern 2.0 397 20.8 70.8 20.0 13.9 6.1 9.2 7.3 1.9 340 Karamoja 0.0 82 19.8 66.1 32.8 25.9 7.0 1.0 1.0 0.0 63 North 0.0 220 20.8 76.5 16.3 13.9 2.4 7.2 7.0 0.2 190 West Nile 0.5 163 20.5 74.6 20.9 18.0 2.8 4.5 4.0 0.6 139 Western 3.1 386 22.8 69.4 7.8 7.3 0.4 22.9 17.3 5.6 333 Southwest 3.3 345 23.1 72.2 4.8 3.1 1.7 23.0 18.9 4.1 311 Education No education 1.9 327 21.8 62.8 19.7 17.0 2.7 17.4 12.4 5.1 274 Primary 1.8 1,591 22.0 71.5 12.7 10.0 2.8 15.8 12.4 3.4 1,381 Secondary + 1.0 750 23.1 67.9 6.3 4.5 1.9 25.8 20.2 5.5 661 Wealth quintile Lowest 2.3 461 20.3 71.7 22.8 17.9 4.8 5.6 4.3 1.3 379 Second 1.9 476 21.3 72.9 18.3 14.6 3.7 8.8 7.2 1.6 389 Middle 2.2 484 22.0 78.1 9.0 6.9 2.1 13.0 10.3 2.7 422 Fourth 1.6 560 22.7 69.1 7.9 6.1 1.8 23.0 18.9 4.1 504 Highest 0.5 686 23.9 60.4 5.9 4.7 1.2 33.7 25.1 8.7 622 Total 1.6 2,667 22.3 69.5 11.7 9.2 2.5 18.8 14.6 4.2 2,316 Note: The Body Mass Index (BMI) is expressed as the ratio of weight in kilograms to the square of height in meters (kg/m2). 1 Excludes pregnant women and women with a birth in the preceding 2 months Seven in ten Ugandan women have a normal BMI (between 18.5 and 24.9 kg/m2). Overall, 12 percent of women are thin or undernourished (BMI less than 18.5 kg/m2): 9 percent mildly thin (BMI Nutrition of Children and Adults • 161 between 17.0-18.4 kg/m2) and 3 percent moderately and severely thin (BMI less than 17.0 kg/m2). Adolescents age 15-19 are somewhat more likely to be thin (14 percent) than older women. Rural women are more likely to be thin than urban women (13 percent versus 8 percent). Women residing in Karamoja are the most likely to be thin (33 percent), while women in Southwest are the least likely (5 percent). The percentage of women who are thin is inversely associated with education and wealth; uneducated women (20 percent) and those in the lowest wealth quintile (23 percent) are more likely to be thin than women with secondary or higher education or those in the highest wealth quintile (6 percent, each). Overweight or obesity (BMI 25 kg/m2 or above) is common among women in Uganda. Overall, 19 percent are overweight or obese (BMI 25 kg/m2 or above), 15 percent are overweight and 4 percent are obese. The percentage of women who are overweight or obese increases with age, from 12 percent among women age 15-19 to 27 percent among those age 40-49. It is substantially higher among urban than rural women (35 and 14 percent, respectively). By region, women in Kampala are the most likely to be overweight or obese (40 percent), while women in Karamoja are the least likely (1 percent). The percentage of women who are overweight or obese increases substantially with education and wealth. Figure 11.7 shows that the percentage of thin women has remained constant at 12 percent between the 2006 and 2011 UDHS surveys, while the percentage of overweight or obese women has increased from 17 to 19 percent. Figure 11.7 Trends in nutritional status among women 15-49 years 12 17 12 19 Undernutrition Overnutrition 2006 2011 2006 2011 Table 11.10.2 presents the nutritional status of men. The mean BMI for Ugandan men age 15-49 is 20.6 kg/m2. There is little difference in the mean BMI by background characteristics. Seventy-eight percent of Ugandan men age 15-49 have a normal BMI (between 18.5 and 24.9 kg/m2). Eighteen percent are thin or undernourished (BMI less than 18.5 kg/m2); 13 percent are mildly thin (BMI between 17.0 and 18.4 kg/m2), and 5 percent moderately or severely thin (BMI less than 17.0 kg/m2). 162 • Nutrition of Children and Adults Young men age 15-19 are much more likely to be thin (33 percent) than their older counterparts (10-17 percent). Rural men are more likely to be thin (19 percent) than urban men (12 percent). Among regions, those residing in West Nile are most likely to be thin (34 percent), and those living in Central 2 are least likely (10 percent). There is no clear pattern in the relationship between education and the percentage of men who have a BMI of less than 18.5 kg/m2. The percentage of men who are thin decreases with wealth, declining from 25 percent of men in the lowest wealth quintile to 14 percent of those 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, Uganda 2011 Background characteristic Body Mass Index Mean Body Mass Index - BMI Normal Thin Overweight/obese Number of men 18.5-24.9 (total normal) <18.5 (total thin) 17.0-18.4 (mildly thin) <17 (modera- tely and severely thin) ≥25.0 (total over- weight or obese) 25.0-29.9 (over- weight) ≥30.0 (obese) Age 15-19 19.4 66.6 32.9 21.0 11.9 0.5 0.5 0.0 544 20-29 21.0 86.0 10.0 7.7 2.3 4.0 3.8 0.2 667 30-39 21.0 79.8 13.4 10.2 3.1 6.8 5.9 0.8 584 40-49 20.8 76.0 16.9 12.0 4.9 7.1 5.3 1.8 342 Residence Urban 21.5 76.1 12.4 8.5 3.9 11.5 9.8 1.7 426 Rural 20.3 78.2 19.2 13.5 5.7 2.6 2.3 0.3 1,711 Region Kampala 21.3 71.2 17.1 9.6 7.6 11.7 10.1 1.5 211 Central 1 20.7 85.2 12.4 8.6 3.8 2.4 2.1 0.2 208 Central 2 21.2 83.7 9.9 7.7 2.2 6.4 5.0 1.4 233 East Central 20.6 79.1 17.8 13.7 4.1 3.1 3.1 0.0 229 Eastern 20.1 78.6 20.3 13.5 6.8 1.0 0.9 0.1 286 Karamoja 19.4 65.0 33.1 21.9 11.2 1.9 1.9 0.0 53 North 20.0 76.6 20.6 17.3 3.3 2.8 2.8 0.0 199 West Nile 19.6 65.2 34.0 22.4 11.7 0.7 0.7 0.0 131 Western 20.7 81.7 14.0 11.4 2.6 4.3 2.8 1.5 317 Southwest 20.9 75.0 18.6 10.8 7.7 6.4 6.4 0.0 270 Education No education 20.7 82.9 14.8 11.7 3.1 2.3 2.3 0.0 87 Primary 20.3 76.3 20.9 15.0 5.8 2.8 2.6 0.3 1,292 Secondary + 21.0 79.7 13.1 8.3 4.8 7.2 6.1 1.2 758 Wealth quintile Lowest 19.7 75.1 24.5 19.3 5.2 0.3 0.3 0.0 341 Second 20.2 80.0 18.5 14.3 4.1 1.5 1.3 0.2 416 Middle 20.4 77.2 19.8 13.5 6.3 3.0 3.0 0.0 398 Fourth 20.9 80.9 14.6 7.9 6.7 4.5 3.6 0.8 480 Highest 21.4 75.2 14.3 9.9 4.4 10.5 9.0 1.5 501 Total 15-49 20.6 77.8 17.9 12.5 5.4 4.4 3.8 0.6 2,137 50-54 20.9 81.0 11.6 10.0 1.6 7.4 6.9 0.5 119 Total 15-54 20.6 77.9 17.5 12.4 5.2 4.5 4.0 0.6 2,256 Note: The Body Mass Index (BMI) is expressed as the ratio of weight in kilograms to the square of height in meters (kg/m2). Only 4 percent of men are overweight (BMI 25 kg/m2 or above), while less than 1 percent are obese. The proportion of overweight or obese men is highest among urban men and those living in Kampala (12 percent each), men with secondary or higher education (7 percent), and men in the highest wealth quintile (11 percent). 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 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. Nutrition of Children and Adults • 163 Twenty-three percent of Ugandan women age 15-49 are anaemic, with 18 percent having mild anaemia, 5 percent having moderate anaemia, and less than 1 percent having severe anaemia. Prevalence of anaemia is higher among older women age 40-49 (27 percent), those with six or more children (28 percent), pregnant women (31 percent), and women who smoke (31 percent). Anaemia prevalence also varies by urban and rural residence; a higher proportion of women in rural areas are anaemic (24 percent) than those in urban areas (20 percent). Also, women in Karamoja have the highest prevalence of anaemia (43 percent, while women in Southwest have the lowest prevalence (11 percent). Prevalence of anaemia generally decreases as education and wealth status increases. Table 11.11 Prevalence of anaemia in women Percentage of women age 15-49 with anaemia, by background characteristics, Uganda 2011 Background characteristic Not pregnant Anaemia status by haemoglobin level Any Mild Moderate Severe Number of women <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 7.0-9.9g/dl <7.0g/dl Age 15-19 18.9 14.9 2.9 1.1 632 20-29 23.3 18.2 4.6 0.5 948 30-39 24.5 19.0 5.4 0.1 650 40-49 26.8 18.9 7.1 0.8 381 Number of children ever born 0 18.8 14.5 2.8 1.4 688 1 24.6 18.5 5.8 0.4 242 2-3 20.5 16.6 3.4 0.5 536 4-5 23.6 18.2 5.5 0.0 468 6+ 28.4 21.2 6.9 0.3 677 Maternity status Pregnant 30.6 19.5 11.1 0.0 290 Breastfeeding 25.9 21.4 4.3 0.2 762 Neither 20.3 15.5 3.8 1.0 1,559 Smoking status Smokes cigarettes/tobacco 30.8 21.9 7.4 1.5 72 Does not smoke 22.8 17.6 4.7 0.6 2,538 Residence Urban 19.9 13.9 5.8 0.2 521 Rural 23.8 18.6 4.5 0.7 2,090 Region Kampala 19.6 14.1 5.3 0.3 246 Central 1 23.5 17.8 5.5 0.1 269 Central 2 30.9 23.3 6.1 1.6 259 East Central 29.9 23.1 6.4 0.4 272 Eastern 27.9 23.8 3.7 0.4 389 Karamoja 43.3 35.2 8.1 0.0 81 North 13.1 10.3 2.7 0.0 219 West Nile 32.3 26.4 5.5 0.5 163 Western 17.3 10.8 4.7 1.9 381 Southwest 11.4 8.5 2.9 0.0 333 Education No education 27.4 21.9 5.5 0.0 318 Primary 23.0 17.4 4.7 0.8 1,566 Secondary + 21.3 16.4 4.5 0.4 727 Wealth quintile Lowest 28.6 21.9 6.5 0.2 454 Second 26.4 22.1 4.3 0.0 467 Middle 19.0 14.4 4.4 0.2 478 Fourth 22.2 16.9 4.6 0.7 558 Highest 20.5 14.7 4.3 1.5 653 Total 23.0 17.7 4.8 0.6 2,610 Note: Prevalence is adjusted for altitude and for smoking status, if known, using formulas in CDC, 1998. In comparison with the data from the 2006 UDHS, the prevalence of any anaemia has declined substantially from 49 percent to 23 percent. The prevalence of mild and moderate anaemia also has declined between the two surveys, from 35 percent to 18 percent, and from 13 percent to 5 percent, respectively (Figure 11.8). 164 • Nutrition of Children and Adults Figure 11.8 Trends in anaemia status among women age 15-49 years 49 35 13 1 23 18 5 1 Any Anemia Mild Moderate Severe Any anaemia Mild Moderate Severe <1 <1 2006 2011 2006 2011 2006 2011 2006 2011 11.8 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 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. More than four in ten mothers (42 percent) who gave birth in the five years preceding the survey received postpartum vitamin A supplements. The proportion of mothers that received vitamin A supplements does not vary much by age. Vitamin A supplements are more common in urban areas than rural areas (51 and 40 percent, respectively). More than six in ten women (63 percent) residing in Karamoja received vitamin A supplements, compared with about one in four women (23 percent) in Central 1. Educated women were more likely to have received vitamin A supplements during their last pregnancy—48 percent of women with secondary or higher education compared with 38 percent of women with no education. The likelihood of women receiving vitamin A supplements is highest among those in the lowest and highest wealth quintiles (47 and 48 percent, respectively). About one in four women (24 percent) did not take any iron tablets during their last pregnancy. Sixty-one percent of women took them for fewer than 60 days, and 4 percent took them for 90 days or more during their last pregnancy. The percentage of women who took iron tablets for 90 or more days decreases somewhat with age and is higher among urban women (9 percent) and those residing in Kampala (10 percent). In general, the percentage of women who took iron tablets for 90 or more days increases as educational status and wealth index increase. Nutrition of Children and Adults • 165 Half of mothers received deworming medication during their last pregnancy. Urban women were more likely than rural women to have taken deworming medication (54 percent compared with 49 percent). Among regions the proportion of women who received deworming medication ranges from 38 percent in East Central to 62 percent in West Nile. The percentage of women who received deworming medication generally increases with increasing education and wealth. Iodine deficiency has adverse effects on all population groups, but women of reproductive age are often most 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, 99 percent of women live in households with iodised salt. This percentage does not vary much by background characteristics. Table 11.12 Micronutrient intake among mothers Among women age 15-49 with a child born in the past five years, the percentage who received a vitamin A dose in the first two months after the birth of the last child, the percent distribution by number of days they took iron tablets or syrup during the pregnancy of the last child, and the percentage who took deworming medication during the pregnancy of the last child; and among women age 15-49 with a child born in the past five years and who live in households that were tested for iodised salt, the percentage who live in households with iodized salt, by background characteristics, Uganda 2011 Background characteristic Per- centage who received vitamin A dose post- partum1 Among women with a child born in the past five years: Among women with a child born in the past five years, who live in households that were tested for iodised salt: Number of days women took iron tablets or syrup during pregnancy of last birth Percentage of women who took deworming medication during pregnancy of last birth Number of women None <60 60-89 90+ Don't know/ missing Total Per- centage living in households with iodised salt2 Number of women Age 15-19 40.6 23.9 60.1 3.6 5.4 7.1 100.0 50.3 370 99.6 347 20-29 43.6 22.2 63.5 2.9 4.2 7.2 100.0 51.2 2,535 99.1 2,438 30-39 40.6 26.9 58.1 2.5 3.8 8.7 100.0 50.2 1,594 98.9 1,518 40-49 38.6 27.8 56.7 2.5 1.6 11.4 100.0 41.8 470 99.0 445 Residence Urban 50.5 16.7 60.1 3.4 9.2 10.6 100.0 53.7 805 99.0 770 Rural 40.3 25.9 61.0 2.7 2.9 7.6 100.0 49.2 4,163 99.0 3,977 Region Kampala 52.4 15.8 58.4 4.0 10.1 11.6 100.0 51.5 358 98.9 347 Central 1 23.4 29.8 56.7 2.0 1.7 9.9 100.0 43.9 504 99.7 476 Central 2 36.8 22.3 52.9 2.5 4.9 17.4 100.0 51.2 507 98.1 487 East Central 41.0 29.3 62.4 1.0 1.1 6.2 100.0 37.6 532 98.5 512 Eastern 48.2 22.8 68.2 2.6 1.9 4.6 100.0 57.5 794 100.0 753 Karamoja 62.9 9.2 76.7 4.0 2.0 8.1 100.0 43.1 186 99.5 163 North 58.6 18.4 66.9 6.7 6.7 1.3 100.0 51.2 445 100.0 435 West Nile 55.6 12.9 68.7 3.8 7.5 7.1 100.0 61.9 299 98.7 276 Western 36.4 25.8 62.2 1.4 4.0 6.5 100.0 51.7 739 98.4 716 Southwest 29.3 37.4 46.6 2.8 3.0 10.1 100.0 46.7 604 98.5 583 Education No education 38.3 28.1 59.8 2.3 1.8 8.0 100.0 43.7 713 99.0 650 Primary 40.4 26.1 61.1 2.4 3.2 7.2 100.0 49.7 3,079 99.0 2,957 Secondary + 48.1 17.7 60.8 4.2 7.1 10.3 100.0 54.2 1,177 99.2 1,141 Wealth quintile Lowest 47.3 24.2 63.2 3.6 3.2 5.7 100.0 48.4 1,055 99.4 983 Second 40.3 26.2 61.6 2.2 3.0 7.0 100.0 48.3 1,026 99.1 982 Middle 36.6 28.7 58.8 2.1 3.8 6.5 100.0 47.1 963 98.9 918 Fourth 36.5 24.6 62.4 2.0 1.8 9.2 100.0 51.3 897 98.6 864 Highest 47.9 18.3 58.3 3.9 7.5 12.0 100.0 54.5 1,027 99.1 1,001 Total 41.9 24.4 60.9 2.8 3.9 8.1 100.0 49.9 4,968 99.0 4,748 1 In the first two months after delivery 2 Excludes women in households where salt was not tested Malaria • 167 MALARIA 12 12.1 INTRODUCTION alaria remains the leading cause of morbidity and mortality in Uganda. The illness contributes, more than any other, to the high burden of disease in the country. This undermines investment in social and economic development (NPA, 2010). In Africa, Uganda ranks third in the number of deaths attributable to malaria and has some of the highest recorded malaria transmission rates. Whereas the 2009 Uganda Malaria Indicator Survey, which used rapid diagnostic blood testing (RDT), showed that 52 percent of children under age 5 had malaria (UBOS and ICF Macro, 2010), recent findings from the 2009-2010 Uganda National Household Survey (UNHS) revealed that slightly more than half of the population that fell sick 30 days prior to the survey reported malaria or fever as the major illness responsible (UBOS 2010). The 2011 UDHS collected data on measures to prevent malaria, including indoor residual spraying, the possession and use of mosquito nets among the Ugandan population, especially women and children, and the use of prophylactic antimalarial drugs among pregnant women age 15-49. M Key Findings  Six in ten households (60 percent) own at least one insecticide-treated net, while 28 percent of households have at least one net for every two people that slept in the household the preceding night.  Forty-five percent of Ugandans have access to an insecticide-treated net; in other words, almost five in ten people could sleep under one if every net in a household were used by two people.  Use of insecticide-treated nets has increased dramatically in Uganda during the past five years: 35 percent of the household population, 43 percent of children under age 5, and 47 percent of pregnant women slept under one the night before the survey.  One-quarter of women received intermittent preventive treatment (IPTp) for malaria during pregnancy; that is, they received at least two doses of SP/Fansidar, with at least one dose during an antenatal care visit.  Five percent of Ugandan children have severe anaemia (haemoglobin level less than 8.0 grams per decilitre). 168 • Malaria 12.2 OWNERSHIP OF MOSQUITO NETS Nets and window screens have long been considered useful protection against mosquitoes and other insects (Lindsay and Gibson, 1988). Nets reduce the human-vector contact by acting as a physical barrier and thus reducing the number of bites from infected vectors (Bradley et al., 1986). However, nets and screens are often not well fitted or are torn, thus allowing mosquitoes to enter or feed on the part of the body adjacent to the netting fabric during the night (Lines et al., 1987). The problem of ill-used nets and screens provided a motive for impregnating nets with a fast-acting insecticide that will repel or kill mosquitoes before or shortly after feeding (Lines et al., 1987; Hossain and Curtis, 1989). Treatment of nets has been made possible by the availability of synthetic pyrethroids, the only insecticides currently used for this purpose. This class of insecticides was developed to mimic the insecticidal compounds of the naturally occurring pyrethrum, an insecticide from the flowers of the chrysanthemum. Currently, insecticide-treated mosquito nets (ITNs) are regarded as a promising malaria control tool, and when used by all or most members of the community can reduce malaria transmission. ITNs have been shown to reduce malaria transmission by as much as 90 percent under trial conditions (Lengeler 2004). They also reduce malaria morbidity and mortality. Long-lasting insecticidal nets (LLINs) are a subset of ITNs. An LLIN is a factory-treated mosquito net made with netting material that has insecticide incorporated within or bound around the fibers. The net must retain its effective biological activity, without re-treatment for repeated washes, for three years of use under field conditions (WHO/Global Malaria Program 2007). The current generation of LLINs lasts three to five years, after which the net should be replaced. Insecticide-treated nets (ITNs) are a principal tool in efforts to reduce malaria transmission in Uganda. All households interviewed in the 2011 UDHS were asked whether they owned a mosquito net and, if so, how many of each type of net they owned. Respondents were also asked to show the mosquito nets they owned to the interviewer so he or she might identify and record the brand name. Brand name and treatment history were used to classify nets as treated or untreated during analysis. Table 12.1 provides information on the percentage of households owning at least one mosquito net (any net, an ITN, or an LLIN), the average number of nets per household, and the percentage of households with at least one net for every two people who slept in the household the previous night. Overall, 74 percent of Ugandan households own at least one mosquito net of any type, 60 percent own at least one insecticide-treated net (ITN), and 59 percent have at least one LLIN. The vast majority of ITNS in Uganda are LLINs. Furthermore, the findings show that, overall, the average number of nets owned per household is 1.6 nets of any type and 1.3 ITNs. There is no difference between the percentages of urban and rural households that own at least one ITN (59 and 60 percent, respectively). Among the regions, however, ITN ownership varies. Households in the East Central region are the least likely to own an ITN (38 percent), while those in the West Nile region are the most likely (82 percent). ITN ownership also tends to increase as wealth quintile increases. For example, over half (56 percent) of households in the lowest wealth quintile own at least one ITN compared with six in ten (63 percent) households in the highest quintile. Mosquito net ownership has dramatically increased within Uganda in the past five years. In the 2006 UDHS, 34 percent of households reported possession of a treated or untreated mosquito net, while only 16 percent reported ITN ownership. In the 2009 UMIS, the proportion of households with at least one ITN had climbed to 47 percent. The current survey shows more than a fourfold increase in ITN ownership among households since 2006 (from 16 to 60 percent). Although mosquito net ownership is an important indicator of the success of a vector control program, it is also important to determine if a household has a sufficient number of nets for those sleeping within the home. By assuming that each net is shared by two people in the household, universal net Malaria • 169 coverage within the population can be measured. Table 12.1 also shows the percentage of households with at least one mosquito net for every two persons staying in the household the night before the interview. Table 12.1 Household possession of mosquito nets Percentage of households with at least one mosquito net (treated or untreated), insecticide-treated net (ITN), and long-lasting insecticidal net (LLIN); average number of nets, ITNs, and LLINs per household; and percentage of households with at least one net, ITN, and LLIN per two persons who stayed in the household last night, by background characteristics, Uganda 2011 Background characteristic Percentage of households with at least one mosquito net Average number of nets per household Number of households Percentage of households with at least one net for every two persons who stayed in the household last night1 Number of households with at least one person who stayed in the household last night Any mosquito net Insecticide- treated mosquito net (ITN)2 Long- lasting insecticidal net (LLIN) Any mosquito net Insecticide- treated mosquito net (ITN)2 Long- lasting insecticidal net (LLIN) Any mosquito net Insecticide- treated mosquito net (ITN)2 Long- lasting insecticidal net (LLIN) Residence Urban 80.9 58.7 56.9 1.9 1.3 1.2 1,691 59.7 38.5 36.8 1,686 Rural 72.4 60.1 59.5 1.6 1.3 1.3 7,342 33.2 25.2 24.8 7,313 Region Kampala 82.0 57.5 55.5 1.9 1.2 1.2 797 64.4 41.1 38.9 795 Central 1 74.0 59.4 58.5 1.6 1.3 1.2 1,140 45.8 32.9 32.2 1,134 Central 2 71.6 59.8 59.0 1.6 1.3 1.3 1,038 41.0 33.2 33.0 1,036 East Central 61.0 38.0 36.3 1.2 0.8 0.7 904 25.6 14.1 13.3 899 Eastern 73.4 56.2 55.4 1.7 1.2 1.1 1,226 32.3 20.5 19.9 1,224 Karamoja 68.4 57.5 57.5 1.3 1.0 1.0 306 27.2 20.5 20.5 305 North 75.0 67.1 66.7 1.6 1.4 1.4 757 30.5 25.1 24.9 755 West Nile 88.1 82.1 82.1 2.1 1.9 1.9 508 42.7 37.7 37.5 504 Western 77.8 69.4 69.2 1.8 1.6 1.6 1,228 37.1 28.6 28.2 1,220 Southwest 71.8 58.6 57.6 1.5 1.2 1.2 1,128 33.0 24.9 24.2 1,128 Wealth quintile Lowest 67.2 55.5 55.1 1.2 1.0 1.0 1,719 23.4 17.8 17.7 1,715 Second 69.8 57.7 57.5 1.4 1.2 1.2 1,767 29.7 22.8 22.6 1,761 Middle 70.8 60.6 59.7 1.5 1.3 1.3 1,672 29.9 23.6 23.4 1,661 Fourth 75.5 61.9 61.0 1.8 1.4 1.4 1,723 39.9 28.7 28.0 1,719 Highest 84.2 62.7 61.1 2.1 1.5 1.4 2,152 61.9 41.9 40.3 2,144 Total 74.0 59.8 59.0 1.6 1.3 1.3 9,033 38.2 27.7 27.1 8,999 1 De facto household members 2 An insecticide-treated net (ITN) is (1) a factory-treated net that does not require any further treatment (LLIN) or (2) a net that has been soaked with insecticide within the past 12 months About three in ten Ugandan households (28 percent) have reached universal ITN coverage; that is, these households have at least one ITN for every two people who slept in the household the previous night. Households in urban areas are more likely to own at least one ITN for every two persons who stayed in the household the night before the survey when compared with those in rural areas (39 percent and 25 percent, respectively). Two-fifths (41 percent) of those residing in Kampala have at least one ITN for every two people, while 14 percent of households in East Central region have at least one ITN for every two people who stayed in the household the preceding night. By wealth quintile, households in the highest quintile are twice as likely to have reached universal ITN coverage when compared with those in the lowest quintile (42 percent versus 18 percent). 12.3 INDOOR RESIDUAL SPRAYING Indoor residual spraying (IRS) is considered one effective method of malaria prevention through vector control. Specially trained staff of a government or non-government malaria control programme visit a household dwelling and spray insecticide on the interior walls. The insecticide kills mosquitoes for several months, especially in endemic areas. Uganda is committed to increasing use of this intervention, although its cost remains a challenge. The 2011 UDHS collected information on whether the interior walls of the household’s dwelling had been sprayed in the 12 months preceding the survey and, if so, who sprayed the dwelling. The percentage of households with IRS in the past 12 months is presented in Table 12.2. Seven percent of the households in Uganda have been sprayed by IRS in the 12 months preceding the survey. Rural households are almost twice as likely to have been sprayed by IRS as those in urban areas (8 percent and 4 percent, respectively). Regional variations further show that two-thirds (66 percent) 170 • Malaria of households in the North region had IRS in the preceding 12 months. This is due to the intensive IRS interventions carried out in ten districts in the malaria-endemic North region every 6 months that have been spearheaded by governmental as well as nongovernmental organisations (NGOs). Households in the lowest wealth quintile are much more likely to have been sprayed by IRS (14 percent) compared with their counterparts in the higher three quintiles (less than 5 percent). The majority of IRS activities in Uganda are conducted by the government, as 80 percent of all households reported that their dwelling was sprayed by government workers (data not shown). Table 12.2 also shows which households are covered by vector control. They are considered to be covered if they own at least one ITN and/or they have been sprayed by IRS at any time in the past 12 months. Overall, 62 percent of households in Uganda are covered by vector control; that is, they reported either ownership of at least one ITN and/or IRS of their dwelling places in the 12 months preceding the survey. There is little difference between vector control coverage among the urban and rural populations or among wealth quintiles. The percentage of households that owned at least one ITN and/or were sprayed by IRS in the past 12 months ranges from a low of 39 percent in the East Central region to a high of 85 percent in the North region. 12.4 ACCESS TO INSECTICIDE- TREATED NETS Use of ITNs is one of the most effective measures for preventing malaria. The government of Uganda, with support from several NGO partners, has distributed millions of mosquito nets across the country. In addition, increasing knowledge among the populace of the importance of using mosquito nets has led to increased demand. The 2011 UDHS data show the proportion of the population that could sleep under an ITN, if each ITN in the household were used by up to two people. This population is referred to as having access to an ITN. Coupled with data on actual mosquito net usage, ITN access data can provide useful information on the magnitude of the behavioural gap in ITN ownership and use, or, in other words, the population with access to an ITN but not using it. If the difference between these indicators is substantial, the programme may need to focus on behaviour change and identify the main drivers or barriers to ITN use to design an appropriate intervention. This analysis helps ITN programmes determine whether they need to achieve higher ITN coverage, promote ITN use, or both. Table 12.3 shows the percent distribution of the de facto household population by the number of ITNs that the household owns, according to the number of persons who stayed in the household the night before the survey. Table 12.2 Indoor residual spraying against mosquitoes Percentage of households in which someone has come into the dwelling to spray the interior walls against mosquitoes (IRS) in the past 12 months, and the percentage of households with at least one ITN and/or IRS in the past 12 months, by background characteristics, Uganda 2011 Background characteristic Percentage of households with IRS1 in the past 12 months Percentage of households with at least one ITN2 and/or IRS in the past 12 months Number of households Residence Urban 4.4 60.2 1,691 Rural 7.8 62.1 7,342 Region Kampala 5.2 59.7 797 Central 1 2.4 59.5 1,140 Central 2 1.8 60.3 1,038 East Central 1.2 38.6 904 Eastern 2.6 56.7 1,226 Karamoja 0.4 57.6 306 North 66.1 84.8 757 West Nile 1.4 82.3 508 Western 0.3 69.5 1,228 Southwest 0.6 58.6 1,128 Wealth quintile Lowest 13.6 60.4 1,719 Second 10.5 59.7 1,767 Middle 4.5 61.4 1,672 Fourth 3.4 62.5 1,723 Highest 4.5 64.1 2,152 Total 7.2 61.7 9,033 1 Indoor residual spraying (IRS) is limited to spraying conducted by a government, private, or nongovernmental organization. 2 An insecticide-treated net (ITN) is (1) a factory-treated net that does not require any further treatment (LLIN) or (2) a net that has been soaked with insecticide within the past 12 months, Malaria • 171 A sizable proportion of the Ugandan population either does not have or has limited access to ITNs. One-third of the population (36 percent) slept in homes without any ITN the night before the survey and therefore was not able to use an ITN. About two in ten individuals stayed in households that own one ITN (18 percent) or two ITNs (21 percent), and 15 percent of the population slept in a home with three ITNs. Few individuals slept in homes with more than four ITNs. Table 12.3 Access to an insecticide-treated net (ITN) Percent distribution of the de facto household population by number of ITNs the household owns, according to number of persons who stayed in the household the night before the survey, Uganda 2011 Number of ITNs Number of persons who stayed in the household the night before the survey Total 1 2 3 4 5 6 7 8+ 0 59.9 49.0 44.5 38.6 34.4 34.6 30.8 31.7 35.7 1 30.2 31.0 25.7 23.4 19.6 15.9 18.8 11.7 18.1 2 7.8 16.6 20.2 24.4 25.6 22.7 22.4 18.8 21.2 3 1.6 3.0 8.4 10.0 14.3 17.2 16.3 19.8 15.0 4 0.4 0.4 0.8 2.7 3.7 4.3 6.2 10.3 5.7 5 0.1 0.1 0.3 0.7 1.5 2.7 3.2 4.1 2.5 6 0.0 0.0 0.1 0.1 0.6 2.2 1.9 2.0 1.3 7+ 0.0 0.0 0.0 0.1 0.2 0.4 0.4 1.5 0.6 Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 Number 1,086 1,847 3,614 4,829 6,058 6,363 5,577 14,134 43,508 Percent with access to an ITN1 40.1 51.0 46.9 49.7 48.7 47.3 43.9 39.4 44.7 1 Percentage of the de facto household population who could sleep under an ITN if each ITN in the household were used by up to two people As a nation, 45 percent of the population has access to an ITN. As expected, the proportion of persons with access to an ITN is indirectly proportional to the number of nets within a household. ITN access tends to gradually decrease as household size increases. For example, 51 percent of households where two persons slept the night before the survey had access to an ITN, whereas 39 percent of households where more than eight people slept had access to an ITN. Figure 12.1 shows the percentage of the population with access to an ITN in the household, by background characteristics. Those living in urban areas are more likely than those living in rural areas to have access to an ITN (52 percent and 44 percent, respectively). Residents of the West Nile region are the most likely to have access to an ITN when compared to individuals living in other regions, while the East Central residents are the least likely. ITN access steadily increases as household wealth increases, making those in the highest wealth quintile the most likely to have access to an ITN. 172 • Malaria Figure 12.1 Percentage of the de facto household population with access to an insecticide-treated net Uganda 2011 DHS 45 52 44 52 49 49 25 38 37 46 60 53 43 37 42 43 47 54 Total RESIDENCE Urban Rural REGION Kampala Central 1 Central 2 East Central Eastern Karamoja North West Nile Western Southwest WEALTH QUINTILE Lowest Second Middle Fourth Highest 0 10 20 30 40 50 60 Percent 12.5 USE OF MOSQUITO NETS 12.5.1 Overall Use of Mosquito Nets Mosquito net coverage of the entire population is necessary to achieve a large reduction in the malaria burden. Although vulnerable groups, such as children under age 5 and pregnant women, should still be prioritized, the equitable and communal benefits of wide-scale ITN use by older children and adults should be promoted and evaluated by national malaria control programs (Killeen, 2007). The 2011 UDHS asked about use of mosquito nets by household members during the night before the survey. Table 12.4 presents the percentages of the de facto household population that slept under a mosquito net of any type, under an ITN, or under an LLIN the night before the survey. Overall, 45 percent of the Ugandans reported that they had slept under any net, 35 percent under an ITN, and 35 percent under a LLIN the night before the survey (first three columns of Table 12.4). Children under age 5 (42 percent) and adults age 35-49 (41 percent) report the highest use of ITNs. Women are slightly more likely than men to have slept under an ITN the night before the survey (37 percent and 33 percent, respectively). Urban residents, those in the West Nile region, and those in the highest wealth quintile are more likely than their counterparts to report having slept under an ITN the night before the survey. Among households with at least one ITN (final two columns), net utilization is high. Half (55 percent) of those in households that own at least one ITN slept under the ITN the previous night. Net usage among the population that owns at least one ITN is greater than that of the general population, indicating that ITN ownership increases the likelihood of net usage. Variations of ITN use among those households that own at least one ITN, however, are similar to those within the general population, except those in Kampala households with at least one ITN reported the highest ITN utilization of all regions (70 percent). Malaria • 173 Table 12.4 Use of mosquito nets by persons in the household Percentage of the de facto household population who slept the night before the survey under a mosquito net (treated or untreated), under an insecticide-treated net (ITN), under a long-lasting insecticidal net (LLIN), and under an ITN or in a dwelling in which the interior walls have been sprayed against mosquitoes (IRS) in the past 12 months; and among the de facto household population in households with at least one ITN, the percentage who slept under an ITN the night before the survey, by background characteristics, Uganda 2011 Background characteristic Household population Household population in households with at least one ITN1 Percentage who slept under any net last night Percentage who slept under an ITN1 last night Percentage who slept under an LLIN last night Percentage who slept under an ITN1 last night or in a dwelling sprayed with IRS2 in the past 12 months Number Percentage who slept under an ITN1 last night Number Age (in years) <5 53.0 42.8 42.2 46.5 8,295 62.9 5,641 5-14 35.8 29.0 28.5 34.6 14,198 44.7 9,212 15-34 46.1 35.3 34.6 39.6 12,662 55.4 8,074 35-49 53.6 41.7 40.9 46.0 4,725 64.5 3,057 50+ 42.7 31.5 31.2 37.0 3,619 56.9 2,004 Sex Male 42.2 32.8 32.2 37.8 21,223 51.6 13,489 Female 46.9 37.2 36.6 41.7 22,285 57.1 14,504 Residence Urban 59.4 42.2 40.9 45.1 6,383 65.2 4,133 Rural 42.0 33.8 33.3 38.9 37,125 52.6 23,859 Region Kampala 64.5 43.8 41.9 47.5 2,735 69.8 1,714 Central 1 45.8 35.0 34.5 36.0 4,806 52.0 3,232 Central 2 44.9 37.0 36.5 37.5 4,588 57.6 2,945 East Central 33.2 19.4 18.6 20.8 4,656 47.8 1,890 Eastern 49.8 35.1 34.2 36.8 6,676 58.2 4,030 Karamoja 39.8 35.1 35.1 35.4 1,556 59.9 913 North 42.3 36.3 36.0 77.3 4,014 52.5 2,773 West Nile 50.7 46.4 46.3 47.0 2,677 54.2 2,292 Western 45.1 40.5 40.3 40.7 6,313 54.0 4,740 Southwest 36.2 29.5 29.0 30.1 5,488 46.8 3,463 Wealth quintile Lowest 40.1 32.9 32.6 42.8 8,663 55.3 5,159 Second 41.9 33.4 33.1 39.7 8,629 53.7 5,362 Middle 39.6 32.8 32.4 36.0 8,692 50.8 5,611 Fourth 42.3 33.6 32.9 35.4 8,764 50.2 5,873 Highest 59.0 42.3 41.2 45.0 8,758 61.9 5,988 Total 44.6 35.0 34.5 39.8 43,508 54.5 27,992 1 An insecticide-treated net (ITN) is (1) a factory-treated net that does not require any further treatment (LLIN), or (2) a net that has been soaked with insecticide within the past 12 months 2 Indoor residual spraying (IRS) is limited to spraying conducted by a government, private, or nongovernmental organization. Figure 12.2 presents ownership of, access to, and use of ITNs in Uganda. As shown in column 1, half of households own at least one ITN. Among the population, however, only 45 percent of individuals have access to an ITN. Thirty-five percent of people in Uganda slept under an ITN the night before the survey. When comparing column one and column two, the graph shows that Ugandan households do not have a sufficient number of nets to be used by the number of people sleeping in the household; ITN coverage for individuals is lower than it appears at the household level. When column 2 and column 3 are compared, net access is higher than net usage. This implies that among those with an opportunity to sleep under an ITN, not everyone is taking advantage of the ITN. In other words, there are individuals in the population that could sleep under a net, but they are not. 174 • Malaria Figure 12.2 Ownership of, access to, and use of ITNs Uganda 2011 DHS 60 45 35 Percent of households with at least one ITN Percent of the household population with access to Percent of the household population who slept an ITN within their household under an ITN 12.5.2 Use of Mosquito Nets by Children under Age 5 Those living in areas of high malaria transmission naturally acquire immunity to the disease over time (Doolan et al., 2009). Acquired immunity is not the same as sterile immunity—that is, acquired immunity does not prevent P. falciparum infection but rather protects against severe disease and death. Age is an important factor in determining levels of acquired immunity to malaria. For about six months following birth, antibodies acquired from the mother during pregnancy protect children born in areas of endemic malaria. This immunity is gradually lost, and children start to develop their own immunity to malaria. The pace at which immunity develops depends on their exposure to malaria infection, and in high malaria-endemic areas, children are thought to have attained a high level of immunity by their fifth birthday. Such children may experience episodes of malaria illness but usually do not suffer from severe, life-threatening malaria. Immunity in areas of low malaria transmission is acquired more slowly. Malaria affects all age groups of the population. Table 12.5 shows the percentage of children under age 5 who slept under various categories of mosquito nets the night before the survey. The survey findings show that half (53 percent) of children under age 5 slept under a mosquito net of any type, 43 percent slept under an ITN, and 42 percent of children slept under an LLIN the night before the survey (first three columns). Children under age 2 are more likely than older children to have slept under an ITN last night, while ITN utilization is slightly higher among female children (44 percent) than male children (42 percent). Sleeping under an ITN is more common for urban children compared with those living in rural areas (49 percent and 42 percent, respectively). A higher proportion of children living in the West Nile (57 percent) region and those from the highest wealth quintile (49 percent) slept under an ITN last night relative to children living in other parts of Uganda or from other quintiles. Additionally, among children under age 5 in households with at least one ITN (final two columns in table), six in ten (63 percent) slept under an ITN the night before the survey. Differences by background characteristic among this group are similar to those observed for children under age 5 who slept under a net in all households. Malaria • 175 Table 12.5 Use of mosquito nets by children Percentage of children under age 5 who, the night before the survey, slept under a mosquito net (treated or untreated), under an insecticide-treated net (ITN), under a long-lasting insecticidal net (LLIN), and under an ITN or in a dwelling in which the interior walls have been sprayed against mosquitoes (IRS) in the past 12 months; and among children under age 5 in households with at least one ITN, the percentage who slept under an ITN the night before the survey, by background characteristics, Uganda 2011 Background characteristic Children under age 5 in all households Children under age 5 in households with at least one ITN1 Percentage who slept under any net last night Percentage who slept under an ITN1 last night Percentage who slept under an LLIN last night Percentage who slept under an ITN1 last night or in a dwelling sprayed with IRS2 in the past 12 months Number of children Percentage who slept under an ITN1 last night Number of children Age (in months) <12 57.4 46.7 45.6 49.9 1,681 67.3 1,165 12-23 59.7 48.7 48.1 51.9 1,606 68.5 1,141 24-35 49.3 40.3 39.7 44.2 1,705 61.0 1,127 36-47 50.0 39.6 39.4 43.5 1,645 59.4 1,096 48-59 48.9 38.7 38.6 43.3 1,657 57.8 1,111 Sex Male 52.3 41.6 40.9 45.0 4,163 62.2 2,783 Female 53.7 44.0 43.5 48.1 4,132 63.6 2,858 Residence Urban 66.7 48.9 47.8 51.3 1,060 70.5 736 Rural 51.0 41.9 41.4 45.8 7,235 61.7 4,905 Region Kampala 74.1 52.1 50.6 55.4 431 74.8 301 Central 1 54.0 41.6 40.7 43.0 873 57.7 629 Central 2 52.5 43.9 43.1 44.4 874 64.2 597 East Central 38.7 23.9 23.5 25.1 943 59.0 382 Eastern 58.9 42.5 41.4 44.2 1,379 68.8 851 Karamoja 54.4 49.9 49.9 50.5 304 79.0 192 North 54.8 49.3 49.1 81.3 740 67.4 542 West Nile 60.1 57.1 57.1 57.5 521 63.6 468 Western 55.3 49.9 49.8 50.0 1,203 61.7 974 Southwest 40.8 34.0 33.7 34.5 1,027 49.5 705 Wealth quintile Lowest 52.8 44.8 44.3 52.3 1,849 69.8 1,185 Second 50.7 40.7 40.6 45.2 1,760 61.8 1,160 Middle 46.3 39.0 38.6 41.3 1,693 55.7 1,185 Fourth 48.8 41.3 40.6 43.0 1,520 59.2 1,059 Highest 67.9 48.6 47.4 50.5 1,472 68.0 1,052 Total 53.0 42.8 42.2 46.5 8,295 62.9 5,641 Note: Table is based on children who stayed in the household the night before the interview. 1 An insecticide-treated net (ITN) is (1) a factory-treated net that does not require any further treatment (LLIN) or (2) a net that has been soaked with insecticide within the past 12 months. 2 Indoor residual spraying (IRS) is limited to spraying conducted by a government, private or non-governmental organization. ITN usage has substantially increased within the past five years in Uganda. As measured in the 2006 UDHS, only one in ten children under age 5 slept under an ITN the night before the survey. It increased to 33 percent in the 2009 UMIS. The 2011 UDHS shows that more than four in ten children slept under an ITN the night before the survey. This represents a more than fourfold increase in ITN utilization among children since 2006. These substantial increases have undoubtedly been driven by the free distribution of nets by the government and other key players that contribute to the development of the health sector. 12.5.3 Use of Mosquito Nets by Pregnant Women In malaria-endemic areas, adults usually have acquired some degree of immunity to severe, life- threatening malaria. However, pregnancy depresses the immune system so that pregnant women, especially those in their first pregnancy, have a higher risk of malaria. Moreover, malaria among pregnant women may be asymptomatic. Malaria during pregnancy is a major contributor to low birth weight, maternal anaemia, infant mortality, spontaneous abortion, and stillbirth. Pregnant women can reduce the risk of the adverse effects of malaria by sleeping under insecticide-treated mosquito nets. Table 12.6 shows that almost three in five pregnant women in Uganda (59 percent) slept under a mosquito net of any type, 47 percent slept under an ITN, and 46 percent slept under an LLIN the night before the survey. Pregnant women living in urban areas (55 percent), as well as those residing in the West 176 • Malaria Nile region (72 percent) were more likely than pregnant women living in other areas to have slept under an ITN the night before the survey. Relative to their counterparts, a higher proportion of pregnant women with no education (58 percent) and those in the second wealth quintile (49 percent) slept under an ITN the previous night. Not surprisingly, ITN utilization is 1.5 times higher for pregnant women in households that own at least one ITN compared with ITN utilization among pregnant women in the general population: seven in ten (71 percent) pregnant women age 15-49 in households that own at least one ITN report having slept under an ITN the night before the survey. Table 12.6 Use of mosquito nets by pregnant women Percentages of pregnant women age 15-49 who, the night before the survey, slept under a mosquito net (treated or untreated), under an insecticide-treated net (ITN), under a long-lasting insecticidal net (LLIN), and under an ITN or in a dwelling in which the interior walls have been sprayed against mosquitoes (IRS) in the past 12 months; and among pregnant women age 15-49 in households with at least one ITN, the percentage who slept under an ITN the night before the survey, by background characteristics, Uganda 2011 Background characteristic Among pregnant women age 15-49 in all households Among pregnant women age 15-49 in households with at least one ITN1 Percentage who slept under any net last night Percentage who slept under an ITN1 last night Percentage who slept under an LLIN last night Percentage who slept under an ITN1 last night or in a dwelling sprayed with IRS2 in the past 12 months Number of women Percentage who slept under an ITN1 last night Number of women Residence Urban 71.1 55.4 53.3 57.1 135 85.0 88 Rural 57.0 45.6 45.1 48.7 874 68.6 581 Region Kampala 74.9 59.5 55.9 61.7 65 87.8 44 Central 1 63.2 41.9 41.6 42.7 95 62.3 63 Central 2 51.2 43.1 43.1 43.1 87 67.4 56 East Central 43.4 25.6 24.4 26.4 119 59.3 51 Eastern 65.8 50.5 49.6 50.5 159 77.9 103 Karamoja 64.5 52.4 52.4 52.4 54 76.0 37 North 54.1 45.5 45.5 74.4 92 68.5 61 West Nile 75.6 72.1 71.8 72.1 51 81.3 45 Western 61.4 55.2 55.2 55.2 161 71.1 125 Southwest 49.7 40.0 38.9 40.0 127 61.6 82 Education No education 63.8 58.4 58.4 59.4 133 84.9 91 Primary 56.3 43.8 43.1 47.5 639 68.4 409 Secondary + 63.1 48.6 47.6 50.6 238 68.8 168 Wealth quintile Lowest 56.3 47.6 47.0 52.8 231 75.5 146 Second 58.5 49.1 49.1 54.9 232 74.4 153 Middle 53.1 43.0 41.7 43.6 199 69.6 123 Fourth 57.6 47.4 47.3 48.2 161 62.8 121 Highest 69.8 46.8 45.4 48.0 186 69.7 125 Total 58.9 46.9 46.2 49.8 1,009 70.8 669 Note: Table is based on women who stayed in the household the night before the interview. 1 An insecticide-treated net (ITN) is (1) a factory-treated net that does not require any further treatment (LLIN), or (2) a net that has been soaked with insecticide within the past 12 months. 2 Indoor residual spraying (IRS) is limited to spraying conducted by a government, private or nongovernmental organization. ITN use among pregnant women also dramatically increased over the past five years. Compared with results of the 2006 UDHS, which measured ITN use among pregnant women at 10 percent, the percentage of pregnant women that slept under an ITN has increased to 44 percent in 2009 and to 47 percent in 2011. This represents more than a 350 percent increase since 2006. Malaria • 177 12.6 PREVENTIVE MALARIA TREATMENT DURING PREGNANCY Intermittent preventive treatment during pregnancy (IPTp), an important component of the malaria control programme, is intended to reduce malaria during pregnancy. IPTp comprises at least two doses of an effective antimalarial drug, such as sulfadoxine-pyrimethamine (SP), given during pregnancy as part of a routine antenatal clinic visit. IPTp prevents development of malaria and eliminates malaria parasites from the placenta. The Ministry of Health aims to prevent malaria by increasing the percentage of antenatal care (ANC) clients who receive at least two doses of IPTp and by promoting the use of ITNs among pregnant women in both the public and private sectors as indicated in the 2005/06-2009/10 Uganda Malaria Control Strategic Plan or UMCSP (MOH, 2005). In the 2011 UDHS, women who had a live birth in the two years preceding the survey were asked several questions regarding the time they were pregnant with their most recent birth. They were asked if anyone told them during their pregnancy that pregnant women need to take medicine to keep them from getting malaria. They were also asked if they had taken any drugs to prevent getting malaria during that pregnancy and, if yes, which drug. If the respondent did not know the name of the drug she took, interviewers were instructed to show her some examples of common antimalarials. If respondents had taken SP or Fansidar, they were further asked how many times they took it and whether they had received it during a prenatal care visit. IPTp data are presented in Table 12.7. Table 12.7 shows that, overall, six in ten (62 percent) women in Uganda reported that they took antimalarial drugs (any type) for malaria prevention during pregnancy in the two years preceding the survey. Almost half of women (48 percent) took at least one dose of SP/Fansidar, and 45 percent took at least one dose of SP/Fansidar at an ANC visit. Almost three in ten (27 percent) women reported taking two or more doses of SP/Fansidar during their last pregnancy, as recommended. Almost all of the women who took at least two doses of SP/Fansidar received at least one dose during an antenatal care (ANC) visit, or received IPTp. IPTp usage is higher among women living in urban areas (29 percent) compared with those living in rural areas (24 percent). The proportion of pregnant women that received IPTp varies by region. For example, pregnant women living in the Eastern region are 2.7 times more likely to have received IPTp compared with those in the East Central region (33 percent and 12 percent, respectively). A woman’s likelihood of having received IPTp increases as her education attainment increases. Those with at least some secondary education are 1.5 times more likely to have received IPTp than those with no education. By wealth quintile, a greater proportion of women in the highest quintile received IPTp during their last pregnancy when compared with women in other quintiles. There has been a 51 percent increase in the proportion of Ugandan women receiving IPTp in the past five years. The 2006 UDHS showed that only 16 percent of pregnant women received IPTp, whereas the current survey reports that one-quarter of Ugandan women received IPTp for their last pregnancy. 178 • Malaria Table 12.7 Prophylactic use of antimalarial drugs and use of intermittent preventive treatment (IPTp) by women during pregnancy Percentage of women age 15-49 with a live birth in the two years preceding the survey who, during the pregnancy preceding the last birth, took any antimalarial drug for prevention, who took one dose of SP/Fansidar, and who received intermittent preventive treatment (IPTp)1, by background characteristics, Uganda 2011 Background characteristic Percentage who took any antimalarial drug SP/Fansidar Intermittent preventive treatment1 Number of women with a live birth in the two years preceding the survey Percentage who took any SP/Fansidar Percentage who received any SP/Fansidar during an ANC visit Percentage who took 2+ doses of SP/Fansidar Percentage who took 2+ doses of SP/Fansidar and received at least one during an ANC visit Residence Urban 65.1 55.1 53.0 30.2 29.4 450 Rural 61.7 47.3 43.5 26.1 23.7 2,642 Region Kampala 64.1 55.2 52.3 30.1 28.5 187 Central 1 59.9 40.7 37.2 22.5 20.7 322 Central 2 58.3 42.5 38.5 25.9 23.2 340 East Central 43.5 26.2 21.2 15.6 12.1 345 Eastern 76.1 65.8 60.2 35.5 32.5 529 Karamoja 61.0 56.0 55.4 28.6 28.2 107 North 68.8 51.0 48.9 25.9 24.3 276 West Nile 57.1 40.2 38.3 21.9 20.5 187 Western 65.2 51.3 47.5 31.8 29.0 423 Southwest 58.8 49.5 48.1 23.5 22.8 375 Education No education 55.6 44.5 40.6 21.4 19.9 399 Primary 61.1 47.1 43.6 26.2 23.6 1,975 Secondary + 68.9 54.2 50.9 30.9 29.4 718 Wealth quintile Lowest 63.9 53.1 49.1 28.4 26.2 694 Second 57.9 43.8 40.6 24.2 21.7 679 Middle 61.8 43.3 39.2 25.1 22.5 602 Fourth 58.7 45.8 43.1 23.1 21.1 561 Highest 69.1 56.2 52.6 32.9 31.3 556 Total 62.2 48.4 44.9 26.7 24.5 3,092 1 IPTp: Intermittent preventive treatment during pregnancy is preventive treatment with two or more doses of SP/Fansidar. 12.7 FEVER AMONG CHILDREN UNDER AGE 5 Fever is a major manifestation of malaria in young children, although it also accompanies other illnesses. Most malarial fevers and convulsions occur at home. Prompt and effective malaria treatment is important to prevent the disease from becoming severe and complicated. The 2011 UDHS asked mothers whether their children under age 5 had had a fever in the two weeks preceding the survey and if so, whether any treatment was sought. Questions were also asked about blood testing, the types of drugs given to the child, and how soon the drugs had been taken. 12.7.1 Prevalence and Treatment of Fever among Children Table 12.8 shows the percentage of children under age 5 who had fever in the two weeks preceding the survey and, among those children under age 5, the percentage for whom advice or treatment was sought from a health facility, provider, or pharmacy, the percentage of such children who had a drop of blood taken from a finger or heel-prick (presumably for a malaria test), the percentage who took antimalarial drugs, and the percentage taking drugs on the same or next day. Malaria • 179 Nationally, four in ten Ugandan children under age 5 had fever in the two weeks preceding the survey. Rural children suffered from fever more often than urban children (42 percent and 30 percent, respectively). By region, children living in the East Central (69 percent) region were the most likely to have been reported as suffering from fever compared with children of other regions. The prevalence of fever was highest among children age 12-23 months (48 percent), female children (41 percent), children whose mothers have only primary education (43 percent), and children from the lowest wealth quintile (50 percent). Table 12.8 Prevalence, diagnosis, and prompt treatment of children with fever Percentage of children under age 5 with fever in the two weeks preceding the survey; and among children under age 5 with fever, the percentage for whom advice or treatment was sought from a health facility, provider, or pharmacy, the percentage who had blood taken from a finger or heel, the percentage who took artemisinin-based combination therapy (ACT), the percentage who took ACT the same or next day following the onset of fever, by background characteristics, Uganda 2011 Background characteristic Among children under age 5: Among children under age 5 with fever: Percentage for whom advice or treatment was sought from a health facility, provider, or pharmacy1 Percentage who had blood taken from a finger or heel for testing Percentage who took antimalarial drugs Percentage who took antimalarial drugs same or next day Number of children Percentage with fever in the two weeks preceding the survey Number of children Age (in months) <12 36.6 1,630 80.3 24.7 50.5 32.4 596 12-23 48.4 1,480 83.0 29.4 68.7 44.2 716 24-35 43.0 1,515 82.2 28.8 67.7 44.8 651 36-47 37.7 1,473 82.8 22.9 66.8 45.6 555 48-59 36.4 1,438 79.4 22.2 68.2 45.6 524 Sex Male 39.3 3,757 79.7 25.3 62.1 41.7 1,478 Female 41.4 3,778 83.4 26.5 66.7 43.3 1,564 Residence Urban 30.3 1,089 90.5 52.6 63.4 43.8 330 Rural 42.1 6,447 80.6 22.7 64.6 42.3 2,712 Region Kampala 24.0 467 92.9 56.6 60.2 43.1 112 Central 1 42.4 743 86.9 25.1 63.4 38.6 315 Central 2 42.4 794 83.7 29.9 59.4 44.8 337 East Central 69.3 852 71.1 17.7 46.0 26.7 590 Eastern 55.6 1,284 80.2 22.8 75.9 52.9 714 Karamoja 40.9 281 88.4 40.1 75.5 61.2 115 North 38.5 669 87.8 28.2 79.7 49.9 258 West Nile 37.6 446 84.7 22.5 70.6 57.0 168 Western 29.1 1,096 88.3 28.9 66.4 37.7 319 Southwest 12.7 903 69.7 25.5 50.7 19.3 115 Mother's education No education 39.7 1,081 75.1 21.6 56.3 36.6 430 Primary 43.1 4,792 81.4 24.3 66.1 43.0 2,064 Secondary + 33.0 1,662 87.8 35.4 64.9 45.3 549 Wealth quintile Lowest 49.8 1,673 79.2 25.3 64.5 43.0 832 Second 42.6 1,594 79.3 18.2 66.6 45.5 679 Middle 36.8 1,510 84.3 22.5 62.2 37.4 556 Fourth 40.7 1,331 80.3 23.8 61.9 39.7 542 Highest 30.3 1,428 88.2 46.3 67.4 46.9 432 Total 40.4 7,535 81.6 25.9 64.5 42.5 3,042 1 Excludes market, shop, and traditional practitioner Among children with fever, treatment or advice was sought from a health facility, provider, or pharmacy for four in five children (82 percent), whereas one-quarter of children with fever had blood taken from a finger or heel for testing (26 percent). There is little variation by age of children in the proportion of children for whom advice or treatment for fever was sought. Female children are slightly more likely than male children to have been taken for treatment or advice (83 percent and 80 percent, respectively). Treatment-seeking behaviour is more prevalent for urban children with fever (91 percent) relative to rural children (81 percent). Likewise, children living in Kampala (93 percent) are more likely than others to be taken for treatment or advice. Treatment-seeking behaviour increases with both education and wealth. Similar patterns are presented for children with fever who had blood taken from their finger or heel for testing. 180 • Malaria More than three in five (65 percent) children suffering from fever took an antimalarial drug, and 43 percent took it within the recommended timeframe, the same or next day. Children less than age 1 are the least likely to have taken an antimalarial. Female children are only slightly more likely than male children to have taken an antimalarial drug, and there is no meaningful difference observed by urban-rural residence. By region, on the other hand, the highest percentage of children taking an antimalarial reside in the North region (80 percent), while the lowest percentage of children taking an antimalarial drug live in the East Central region (46 percent). Children whose mothers have at least some primary education are more likely than children of women with no education to have taken an antimalarial. Nearly seven in ten children with fever who were in the second and the highest wealth quintiles (67 percent) took an antimalarial drug. 12.7.2 Type and Timing of Antimalarial Drugs In Uganda, a range of antimalarial drugs are marketed. The 2011 UDHS collected information on the type of antimalarial drugs taken and the timing (same or next day); this was assessed for children under age 5 with reported fever in the two weeks prior to the survey who also took antimalarial drugs. Table 12.9 depicts the type and timing of antimalarial drugs used among children under 5 with fever in the two weeks preceding the survey and the percentage of children who took specific antimalarial drugs the same or next day after developing fever, by the various background characteristics. Among children with fever that took an antimalarial drug, almost seven in ten (69 percent) took Coartem or ACT, the recommended malaria treatment. One-quarter (24 percent) of these children took quinine, 6 percent took chloroquine, and 4 percent took SP/Fansidar. By age, older children age 36-47 months with fever that received an antimalarial are more likely to have taken ACT compared with other children. Male children (70 percent) and urban children (70 percent) are slightly more likely to have taken an ACT compared with female children (67 percent) and those living in rural areas (68 percent). Adherence to the recommended malaria treatment, ACT, is particularly low for children living in the Southwest (59 percent) region, where use of chloroquine and quinine are high relative to other regions. ACT use is lowest for children whose mothers have no education (66 percent), and highest for children from households in the highest wealth quintile (72 percent). Table 12.9 also shows the percentage of children who took a specific drug the same or next day among those children with fever that took an antimalarial drug. Of children who took an antimalarial drug, the majority were treated within the recommended time frame. For example, more than four in ten children (46 percent) taking an antimalarial took ACT the same or next day, which represents two-thirds of those who took ACT (46 percent out of 69 percent). Malaria • 181 Table 12.9 Type and timing of antimalarial drugs used Among children under age 5 with fever in the two weeks preceding the survey who took any antimalarial medication, the percentage who took specific antimalarial drugs and the percentage who took each type of drug the same or next day after developing fever, by background characteristics, Uganda 2011 Background characteristic Percentage of children who took drug: Percentage of children who took drug the same or next day: Number of children with fever who took anti- malarial drug SP/ Fansidar Chloro- quine Chloro- quine with Fansidar Coartem/ ACT Quinine Other anti- malarial SP/ Fansidar Chloro- quine Chloro- quine with Fansidar Coartem/ ACT Quinine Other anti- malarial Age (in months) <12 3.2 6.1 0.8 60.9 31.9 1.8 2.1 3.7 0.8 38.9 20.9 0.0 301 12-23 5.5 4.7 0.5 71.0 24.9 1.4 3.3 2.0 0.2 46.1 14.5 0.0 491 24-35 2.5 7.2 0.9 69.1 22.1 4.3 1.7 4.0 0.3 48.5 12.8 0.3 441 36-47 2.6 5.4 2.4 72.1 21.2 2.8 1.3 3.7 1.1 50.8 14.0 0.0 371 48-59 4.5 5.2 2.0 67.6 22.3 2.8 3.0 2.9 1.0 46.1 15.3 0.0 357 Sex Male 4.1 5.0 1.6 70.0 22.3 2.8 2.5 2.7 1.0 49.0 13.6 0.1 918 Female 3.4 6.2 0.9 67.4 25.8 2.4 2.2 3.6 0.3 44.1 16.5 0.1 1,043 Residence Urban 2.2 4.9 1.1 70.0 24.6 4.0 1.6 2.5 0.9 50.6 15.6 0.2 209 Rural 3.9 5.8 1.3 68.4 24.1 2.5 2.4 3.3 0.6 45.9 15.1 0.1 1,752 Region Kampala 1.7 4.9 1.6 79.0 12.8 3.5 1.0 4.0 1.0 57.3 7.6 0.8 68 Central 1 3.7 6.4 2.1 74.2 18.0 2.3 1.5 2.4 1.4 49.8 7.4 0.0 200 Central 2 2.0 6.6 0.7 65.6 25.5 3.2 2.0 4.9 0.0 48.9 20.4 0.5 200 East Central 7.6 12.5 3.5 63.3 17.5 4.0 5.3 5.7 1.8 38.7 10.7 0.0 272 Eastern 3.7 4.6 0.8 59.8 35.6 2.8 2.7 3.1 0.2 40.7 24.9 0.0 542 Karamoja 2.4 7.9 0.9 81.3 15.0 0.5 0.8 7.7 0.9 66.3 9.1 0.0 87 North 1.0 0.6 1.0 82.3 15.8 2.8 0.0 0.6 1.0 52.3 8.8 0.0 205 West Nile 3.7 1.9 0.9 76.2 21.6 0.0 2.2 1.9 0.0 62.6 15.6 0.0 118 Western 3.5 2.2 0.0 72.0 22.6 2.9 2.7 0.0 0.0 45.7 8.9 0.0 212 Southwest 6.1 13.8 0.0 59.1 31.9 0.0 0.0 4.3 0.0 20.8 15.1 0.0 58 Mother’s education No education 2.8 5.2 1.3 73.6 21.8 1.9 1.9 4.2 0.3 47.7 13.9 0.0 242 Primary 4.2 6.3 1.3 66.3 25.3 2.5 2.7 3.4 0.7 44.2 15.6 0.0 1,363 Secondary + 2.3 3.7 1.2 74.0 21.2 3.5 1.3 1.5 0.5 53.9 14.4 0.4 356 Wealth quintile Lowest 3.4 5.9 1.2 66.0 27.5 2.1 1.9 4.6 0.4 44.3 18.6 0.0 537 Second 3.6 4.9 0.7 69.5 25.8 1.5 2.9 2.6 0.4 47.7 15.8 0.0 452 Middle 2.8 8.6 2.3 68.0 22.6 2.2 1.5 3.0 1.5 42.6 12.4 0.0 346 Fourth 6.2 4.6 1.2 69.1 21.7 3.5 4.1 2.8 0.3 45.6 13.7 0.0 335 Highest 2.7 4.2 1.0 72.4 20.0 4.8 1.2 2.1 0.6 53.6 12.9 0.5 291 Total 3.7 5.7 1.2 68.6 24.2 2.6 2.3 3.2 0.6 46.4 15.2 0.1 1,962 ACT = Artemisinin-based combination therapy 12.8 ANAEMIA PREVALENCE AMONG CHILDREN AGE 6-59 MONTHS Anaemia—a low level of functional haemoglobin in the blood—decreases the amount of oxygen reaching the tissues and organs of the body, reducing their capacity to function. It is associated with impaired cognitive and motor development in children. Although there are many causes of anaemia, inadequate intake of iron folate, vitamin B12, or other nutrients usually account for the majority of cases in many populations. Severe malaria also accounts for a large proportion of anaemia in children under 5 in malaria endemic areas. Other causes of anaemia include thalassemia, sickle cell disease, and intestinal worm infestation. Promotion of the use of insecticide-treated bed nets and deworming medication every six months for children under age 5 reduces anaemia prevalence among children. 182 • Malaria As mentioned earlier, malaria is the leading cause of sickness and death among children under age 5 in Uganda. In areas of constant, high malaria transmission, partial immunity develops within the first two years of life. Many people, including children, may have malaria parasites in their blood without showing any outward signs of infection. Such asymptomatic infection not only contributes to further transmission of malaria but also takes a toll on the health of individuals by contributing to anaemia. Anaemia is a major cause of morbidity and mortality associated with malaria, making prevention and treatment of malaria among children and pregnant women very important. Table 12.10 shows the percentage of children age 6-59 months classified as having severe anaemia (haemoglobin concentration of less than 8.0 grams per decilitre) by background characteristics. A haemoglobin level below 8.0 grams per decilitre is often associated with malaria infection in malaria-endemic regions. Five percent of Ugandan children 6-59 months old are severely anaemic. Young children, those 6-8 months (13 percent), are much more likely to be severely anaemic than older children. Severe anaemia threatens slightly fewer children in urban areas than in rural areas (2 percent and 5 percent, respectively). By region, the prevalence of severe anaemia varies greatly, ranging from a low of less than 1 percent in the Southwest region to a high of 9 percent among children living in the East Central region. Children of households in the highest wealth quintile have the lowest prevalence of severe anaemia. There is little variation in the proportion of children with severe anaemia by sex or mother’s education level. The results show improvement in severe anaemia in young children. The proportion of children age 6-59 months with severe anaemia declined from 10 percent in 2009 to 5 percent in 2011 (UBOS and ICF Macro, 2010). Table 12.10 Haemoglobin <8.0 g/dl in children Percentage of children age 6-59 months with haemoglobin lower than 8.0 g/dl, by background characteristics, Uganda 2011 Background characteristic Hemoglobin <8.0 g/dl Number of children Age (in months) 6-8 12.5 124 9-11 6.7 120 12-17 5.0 250 18-23 7.4 265 24-35 5.6 444 36-47 0.7 480 48-59 3.5 459 Sex Male 3.8 1,064 Female 5.5 1,078 Mother's interview status Interviewed 4.8 1,796 Not interviewed but in household 5.0 106 Not interviewed, and not in the household1 3.5 240 Residence Urban 1.5 265 Rural 5.1 1,877 Region Kampala 1.4 122 Central 1 6.2 209 Central 2 3.3 199 East Central 8.9 257 Eastern 7.9 419 Karamoja 6.4 79 North 0.4 178 West Nile 5.2 141 Western 3.0 285 Southwest 0.4 253 Mother's education2 No education 3.2 253 Primary 5.5 1,238 Secondary + 3.5 395 Wealth quintile Lowest 6.7 477 Second 5.7 453 Middle 4.8 460 Fourth 4.3 394 Highest 0.8 357 Total 4.7 2,142 Note: Table is based on children who stayed in the household the night before the interview. Prevalence of anemia is based on hemoglobin levels and is adjusted for altitude using CDC formulas (CDC, 1998). Hemoglobin is measured in grams per deciliter (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. HIV/AIDS-Related Knowledge, Attitudes, and Behaviour • 183 HIV/AIDS-RELATED KNOWLEDGE, ATTITUDES, AND BEHAVIOUR 13 13.1 INTRODUCTION 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. All sectors of Ugandan society are affected. The future course of the AIDS epidemic in Uganda depends on a number of factors including HIV/AIDS-related knowledge, degree of social stigmatisation, risky behaviour, access to high-quality services for sexually transmitted infections (STIs), provision and uptake of HIV counseling and testing, and access to antiretroviral therapy (ART). The key 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 UDHS. This chapter presents findings from the survey of the general adult population and, specifically, from young people. 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 control and prevention programmes to target the groups of people most in A Key Findings  Nearly all Ugandans have heard of HIV, but only 4 in 10 (38 percent of women and 43 percent of men) have a comprehensive knowledge of HIV/AIDS prevention and transmission; that is, they know that both condom use and limiting sexual intercourse to one uninfected partner can prevent HIV, they are aware that a healthy-looking person can have HIV, and they reject the two most common local misconceptions about HIV: that HIV can be transmitted by mosquitoes and by sharing food.  Among those who had more than one sexual partner in the past 12 months, nearly one-third (31 percent) of women and one-fifth (19 percent) of men report using a condom during their last sexual intercourse.  HIV testing has increased dramatically in the past five years. The current survey shows that 7 in 10 women (71 percent) and 1 in 2 men (52 percent) age 15-49 have been tested for HIV and received their results. Testing has increased from 25 percent of women and 21 percent of men in the 2006 UDHS.  Sixty-four percent of never-married young women and 51 percent of never-married young men have never had sexual intercourse. Overall, one-quarter of never-married young women (24 percent) and 3 in 10 never-married young men report sexual intercourse in the past 12 months. 184 • HIV/AIDS-Related Knowledge, Attitudes, and Behaviour need of information and services and most vulnerable to the risk of HIV infection. The findings presented in this chapter may be compared with the findings from the 2006 UDHS. 13.2 HIV/AIDS KNOWLEDGE, TRANSMISSION, AND PREVENTION METHODS 13.2.1 Awareness of HIV/AIDS The 2011 UDHS respondents were asked whether they had heard of AIDS. Those who reported having heard of AIDS were then asked a number of questions about whether and how infection can be avoided. The past five DHS and AIS surveys in Uganda have shown that general awareness of HIV and AIDS among the population is universal. It is not surprising, therefore, that almost everyone interviewed in the 2011 UDHS had heard of AIDS. Table 13.1 shows that in Uganda today knowledge of AIDS is universal among all sub-groups of men and women. Table 13.1 Knowledge of AIDS Percentage of women and men age 15-49 who have heard of AIDS, by background characteristics, Uganda 2011 Background characteristic Women Men Has heard of AIDS Number of women Has heard of AIDS Number of men Age 15-24 99.6 3,677 99.4 872 15-19 99.3 2,048 99.1 554 20-24 99.9 1,629 99.9 318 25-29 99.6 1,569 99.8 361 30-39 99.8 2,112 100.0 592 40-49 99.9 1,316 100.0 348 Marital status Never married 99.1 2,123 99.3 834 Ever had sex 99.9 837 100.0 438 Never had sex 98.6 1,286 98.5 397 Married/Living together 99.9 5,418 100.0 1,228 Divorced/Separated/Widowed 99.6 1,134 100.0 111 Residence Urban 99.7 1,717 99.9 439 Rural 99.7 6,957 99.7 1,734 Region Kampala 99.7 839 100.0 221 Central 1 99.7 956 100.0 209 Central 2 100.0 902 100.0 236 East Central 99.4 869 100.0 236 Eastern 99.5 1,267 100.0 289 Karamoja 99.9 289 99.1 55 North 99.9 735 100.0 199 West Nile 99.9 500 99.4 133 Western 99.2 1,221 98.5 322 Southwest 99.9 1,097 100.0 273 Education No education 99.7 1,120 99.6 90 Primary 99.6 5,152 99.6 1,309 Secondary + 99.8 2,402 100.0 774 Wealth quintile Lowest 99.7 1,519 98.4 345 Second 99.7 1,579 100.0 423 Middle 99.4 1,608 100.0 402 Fourth 99.8 1,726 99.9 486 Highest 99.8 2,242 100.0 517 Total 15-49 99.7 8,674 99.7 2,173 50-54 na na 100.0 122 Total 15-54 na na 99.7 2,295 na = Not applicable HIV/AIDS-Related Knowledge, Attitudes, and Behaviour • 185 13.2.2 Knowledge of HIV Prevention Among Ugandan adults, HIV is mainly transmitted through sexual contact between an infected partner and an uninfected partner. Consequently the HIV prevention programme has mainly sought to reduce further sexual transmission through three programmatically important ways: promotion of sexual abstinence, mutually faithful monogamy among uninfected individuals, and condom use among the sexually active. In the 2011 UDHS, men and women 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. As can be shown in Table 13.2, eight in 10 respondents (79 percent of women and 84 percent of men) agreed that condom use can reduce the risk of getting AIDS. Nine in ten respondents (89 percent of women and 91 percent of men) know that the risk of getting HIV can be reduced by limiting sexual intercourse to one uninfected partner. Three-quarters (74 percent) of women and four-fifths (79 percent) of men recognize that both using condoms and limiting sexual intercourse to one uninfected partner are methods to reduce the risk of getting HIV. Table 13.2 Knowledge of HIV prevention methods Percentage of women and men age 15-49 who, in response to prompted questions, say that people can reduce the risk of getting 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, Uganda 2011 Background characteristic Women Men Percentage who say that HIV can be prevented by: Number of women Percentage who say that HIV can be prevented by: 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 79.0 87.3 73.6 3,677 83.9 90.9 79.1 872 15-19 75.7 85.1 69.5 2,048 82.4 89.8 77.2 554 20-24 83.1 90.1 78.8 1,629 86.7 93.0 82.4 318 25-29 79.2 89.6 75.1 1,569 87.1 92.6 83.0 361 30-39 80.7 89.6 75.5 2,112 82.6 91.6 78.3 592 40-49 75.5 90.5 72.0 1,316 83.1 89.5 76.9 348 Marital status Never married 76.3 85.8 70.4 2,123 83.9 91.0 79.0 834 Ever had sex 85.0 89.7 79.5 837 88.5 94.1 85.0 438 Never had sex 70.7 83.2 64.4 1,286 78.8 87.5 72.3 397 Married/living together 79.8 89.9 75.4 5,418 84.0 90.6 78.9 1,228 Divorced/separated/widowed 79.8 88.9 74.9 1,134 84.2 99.1 84.2 111 Residence Urban 86.4 91.7 82.1 1,717 87.2 93.5 83.5 439 Rural 77.1 88.0 72.1 6,957 83.1 90.6 78.1 1,734 Region Kampala 88.7 90.3 83.0 839 85.2 94.6 84.0 221 Central 1 87.6 91.9 81.3 956 88.4 98.5 87.5 209 Central 2 84.4 91.7 80.0 902 92.9 98.4 91.9 236 East Central 88.2 91.8 83.9 869 86.5 91.1 81.8 236 Eastern 70.3 81.1 66.4 1,267 79.4 70.4 60.9 289 Karamoja 38.3 85.1 37.3 289 53.1 80.9 52.9 55 North 87.7 94.8 85.5 735 92.3 98.2 91.1 199 West Nile 65.5 86.2 59.9 500 55.6 91.9 50.6 133 Western 78.8 87.0 72.5 1,221 88.6 95.1 85.7 322 Southwest 73.0 89.0 67.5 1,097 82.7 90.7 77.8 273 Education No education 65.0 84.2 59.9 1,120 71.3 84.4 62.8 90 Primary 78.4 88.1 73.4 5,152 83.9 90.6 78.9 1,309 Secondary + 86.6 92.3 82.2 2,402 85.5 93.0 81.6 774 Wealth quintile Lowest 66.7 83.4 62.1 1,519 76.3 76.5 63.2 345 Second 75.2 88.0 71.0 1,579 81.1 90.1 76.4 423 Middle 80.0 89.2 74.1 1,608 84.4 94.4 81.2 402 Fourth 83.2 90.3 78.9 1,726 87.5 94.8 84.5 486 Highest 85.7 91.4 80.7 2,242 87.7 96.0 85.5 517 Total 15-49 78.9 88.8 74.1 8,674 83.9 91.2 79.2 2,173 50-54 na na na na 82.5 90.0 74.8 122 Total 15-54 na na na na 83.9 91.1 78.9 2,295 na = Not applicable 1 Using condoms every time they have sexual intercourse 2 Partner who has no other partners 186 • HIV/AIDS-Related Knowledge, Attitudes, and Behaviour There are notable differences in knowledge of prevention. Those in the youngest (15-19) and oldest (40-49) age cohorts generally have lower levels of knowledge than those in other age categories. Never-married respondents who have not had sex are also less likely to know about HIV prevention methods than those that have married or ever had sex. Knowledge of HIV prevention methods is higher among urban residents than among those living in rural areas. Variation in knowledge levels by region is particularly striking. For example, 86 percent women of residing in the North region recognize that both using condoms and limiting sexual intercourse to one uninfected partner are ways to reduce the risk of getting HIV, compared with slightly more than one-third (37 percent) of women living in the Karamoja region. Men and women with higher levels of education are more likely than those with lower levels of education to be aware of HIV prevention methods. For example, 82 percent of women with secondary or higher education know that both using condoms and limiting sexual intercourse to one uninfected partner are methods to reduce the risk of getting HIV compared with 60 percent of women with no education. Knowledge of HIV prevention also increases as wealth of the respondents increases. 13.2.3 Rejection of Misconceptions about HIV/AIDS In addition to knowing effective ways to avoid contracting HIV, it is useful to be able to identify incorrect beliefs about AIDS. Common misconceptions about AIDS include the idea that all HIV-infected people always appear ill and the belief that the virus can be transmitted through mosquito or other insect bites, by sharing food with someone who is infected, or by witchcraft or other supernatural means. Tables 13.3.1 and 13.3.2 show the proportions of women and men who know that a healthy- looking person can have HIV and who reject common misconceptions about HIV transmission. Eighty- seven percent of women and 92 percent of men know that a healthy-looking person can have the AIDS virus. Fewer respondents understand that the AIDS virus cannot be transmitted by mosquito bites (60 percent of women and 62 percent of men). Knowledge that people cannot get the AIDS virus by sharing food with a person who has AIDS is slightly more prevalent, as 78 percent of women and 83 percent of men said a person cannot become infected by sharing food with a person who has AIDS. Respondents were also asked if they thought that people could get the AIDS virus by witchcraft or other supernatural means. Nearly 9 in 10 respondents (87 percent of women and 91 percent of men) knew that the AIDS virus cannot be transmitted by supernatural means. HIV/AIDS-Related Knowledge, Attitudes, and Behaviour • 187 Table 13.3.1 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, Uganda 2011 Background characteristic Percentage of respondents 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- ceptions1 Percentage with a compre- hensive knowledge about AIDS2 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 means A person cannot become infected by sharing food with a person who has the AIDS virus Age 15-24 84.5 62.4 87.8 77.6 47.5 38.1 3,677 15-19 81.5 63.0 85.6 77.7 46.8 35.6 2,048 20-24 88.2 61.6 90.6 77.6 48.5 41.1 1,629 25-29 88.1 59.2 89.3 78.3 47.8 38.6 1,569 30-39 89.9 59.5 86.5 77.5 48.2 38.5 2,112 40-49 86.6 54.3 84.0 76.9 43.4 34.5 1,316 Marital status Never married 83.1 66.7 86.6 80.2 51.7 39.8 2,123 Ever had sex 88.4 69.1 88.9 82.1 54.8 45.0 837 Never had sex 79.6 65.2 85.1 79.0 49.6 36.4 1,286 Married/Living together 87.6 57.6 87.5 76.8 45.3 36.7 5,418 Divorced/Separated/Widowed 89.8 58.3 86.5 76.5 47.2 38.8 1,134 Residence Urban 93.5 69.4 91.6 82.3 59.4 50.5 1,717 Rural 85.1 57.6 86.1 76.5 44.1 34.6 6,957 Region Kampala 95.5 74.1 91.3 83.3 64.6 55.4 839 Central 1 96.1 63.6 92.3 78.2 53.8 44.8 956 Central 2 94.2 55.6 87.5 72.4 45.4 39.2 902 East Central 92.3 53.4 86.8 71.0 41.0 35.5 869 Eastern 76.3 53.9 83.9 78.2 38.2 27.1 1,267 Karamoja 58.7 52.9 74.3 66.9 31.4 20.3 289 North 84.4 62.9 92.3 85.5 51.8 46.6 735 West Nile 81.3 43.7 76.2 75.0 29.8 19.1 500 Western 81.8 61.9 87.6 79.4 46.9 37.4 1,221 Southwest 90.6 66.3 87.8 78.4 53.5 38.4 1,097 Education No education 76.5 46.8 78.2 68.5 31.6 22.8 1,120 Primary 86.0 54.6 86.1 74.7 41.2 32.6 5,152 Secondary + 93.3 77.5 93.6 88.0 67.0 55.7 2,402 Wealth quintile Lowest 76.3 50.6 80.6 74.2 35.3 26.1 1,519 Second 83.1 53.0 84.5 73.3 38.7 30.0 1,579 Middle 87.3 57.3 88.2 76.9 44.8 35.0 1,608 Fourth 89.6 60.0 87.7 75.9 46.4 38.4 1,726 Highest 94.0 72.7 92.4 84.8 63.2 52.5 2,242 Total 15-49 86.8 59.9 87.2 77.6 47.1 37.7 8,674 1 Two most common local misconceptions: AIDS can be transmitted by mosquito bites and a person can become infected by sharing food with a person who has AIDS 2 Comprehensive knowledge means knowing that consistent use of condoms during sexual intercourse and having just one uninfected faithful partner can reduce the chance of getting the AIDS virus, knowing that a healthy-looking person can have the AIDS virus, and rejecting the two most common local misconceptions about AIDS transmission or prevention. 188 • HIV/AIDS-Related Knowledge, Attitudes, and Behaviour Table 13.3.2 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, Uganda 2011 Background characteristic Percentage of respondents 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- ceptions1 Percentage with a compre- hensive knowledge about AIDS2 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 supernatural means A person cannot become infected by sharing food with a person who has the AIDS virus Age 15-24 88.4 62.7 90.3 82.8 49.5 39.5 872 15-19 86.9 59.1 89.3 82.1 45.1 34.8 554 20-24 90.9 69.1 92.0 83.8 57.2 47.7 318 25-29 92.8 58.6 91.6 81.2 52.0 42.8 361 30-39 94.4 63.5 91.4 84.9 56.4 45.3 592 40-49 94.2 63.3 92.1 84.1 56.3 46.0 348 Marital status Never married 88.6 64.4 90.3 83.7 51.2 40.6 834 Ever had sex 90.3 66.5 91.7 84.2 53.4 45.2 438 Never had sex 86.8 62.0 88.6 83.2 48.7 35.6 397 Married/Living together 93.7 61.6 92.1 83.4 54.5 44.3 1,228 Divorced/Separated/Widowed 92.0 55.1 86.6 78.6 47.5 40.1 111 Residence Urban 96.1 76.6 94.6 85.2 67.9 57.8 439 Rural 90.6 58.8 90.2 82.8 49.1 38.8 1,734 Region Kampala 96.3 78.5 96.5 84.2 69.4 59.5 221 Central 1 98.1 43.4 88.6 71.8 36.3 34.5 209 Central 2 97.1 61.8 92.6 76.2 53.2 49.5 236 East Central 91.3 54.2 93.0 80.2 44.9 35.8 236 Eastern 83.5 55.2 87.8 85.0 42.7 27.3 289 Karamoja 83.1 64.9 71.6 78.1 58.9 43.9 55 North 97.5 71.7 96.5 94.8 67.9 61.3 199 West Nile 90.7 81.4 81.9 88.6 68.5 29.5 133 Western 89.4 67.1 94.4 86.6 57.1 51.1 322 Southwest 88.0 56.7 90.0 84.4 44.9 34.1 273 Education No education 85.9 40.3 73.6 56.3 25.3 19.3 90 Primary 90.4 53.9 90.6 79.5 44.0 35.2 1,309 Secondary + 94.5 79.2 94.1 92.7 71.1 58.0 774 Wealth quintile Lowest 85.2 59.1 85.6 80.9 48.3 34.8 345 Second 92.3 59.6 89.1 81.3 49.6 37.5 423 Middle 90.5 57.0 91.5 83.1 47.6 35.1 402 Fourth 91.9 61.6 93.5 84.4 52.1 44.9 486 Highest 96.2 71.7 93.9 85.5 63.6 55.9 517 Total 15-49 91.7 62.4 91.1 83.3 52.9 42.7 2,173 50-54 97.0 48.4 89.4 76.0 40.7 32.5 122 Total 15-54 92.0 61.6 91.0 82.9 52.2 42.1 2,295 1 Two most common local misconceptions: AIDS can be transmitted by mosquito bites and a person can become infected by sharing food with a person who has AIDS 2 Comprehensive knowledge means knowing that consistent use of condoms during sexual intercourse and having just one uninfected faithful partner can reduce the chance of getting the AIDS virus, knowing that a healthy-looking person can have the AIDS virus, and rejecting the two most common local misconceptions about AIDS transmission or prevention. Two composite measures of HIV/AIDS knowledge are included in Tables 13.3.1 and 13.3.2. The first measure indicates that approximately half of respondents (47 percent of women and 53 percent of men) know that the two most common misconceptions about HIV/AIDS (i.e., HIV can be transmitted by mosquitoes or by sharing food with a person who has AIDS) are incorrect and also are aware that a healthy-looking person can have HIV. The second measure shows that about 4 in 10 Ugandans (38 percent of women and 43 percent of men) have what can be considered comprehensive knowledge of HIV/AIDS prevention and transmission; that is, they know that both condom use and limiting sexual intercourse to HIV/AIDS-Related Knowledge, Attitudes, and Behaviour • 189 one uninfected partner can prevent HIV, they are aware that a healthy-looking person can have HIV. They reject the two most common local misconceptions (that HIV can be transmitted through mosquitoes and that a person can become infected with HIV by sharing food with a person who has AIDS). In Uganda, comprehensive knowledge about AIDS is generally lowest among the youngest age cohort, those age 15-19; however, among women, comprehensive knowledge about AIDS is also low among the oldest age cohort, those age 40-49. By marital status, respondents that have never married, but who have had sex, are more likely than their counterparts to have comprehensive knowledge about AIDS. Among both men and women, urban residents are 1.5 times more likely than those living in rural areas to have comprehensive knowledge about AIDS. Comprehensive knowledge varies widely by region in Uganda. Among women, those living in Karamoja (20 percent) and West Nile (19 percent) have the lowest levels of comprehensive knowledge in the country. Among men, the lowest proportion is in Eastern region(27 percent). Of note is the increase in comprehensive knowledge about AIDS among respondents in the North region. There has been tremendous improvement in respondents’ knowledge levels since the 2006 UDHS. The current survey shows that 47 percent of women and 61 percent of men residing in the North region have comprehensive knowledge about AIDS. In the 2006 UDHS, only 20 percent of women and 39 percent of men living in the North region were considered to have a comprehensive knowledge of HIV. Within the past five years, comprehensive knowledge of AIDS has more than doubled among women in the North region, while among men living in the North region, it has increased by 56 percent. 13.2.4 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 reducing the risk of transmission using antiretroviral drugs are critical to reducing mother-to-child transmission (MTCT) of HIV. In Uganda, about 21 percent of HIV transmission is currently believed to be caused by MTCT (UAC, 2007) and, as such, the country has implemented strategies for prevention of mother-to- child transmission (PMTCT). To assess MTCT and PMTCT knowledge, the 2011 UDHS asked respondents if the virus that causes AIDS can be transmitted from a mother to a child during pregnancy, delivery, and breastfeeding. Respondents were also asked whether a mother with HIV can reduce the risk of transmission to the baby by taking certain drugs (antiretrovirals) during pregnancy. Table 13.4 shows that Ugandan women are slightly more knowledgeable than Ugandan men about MTCT and PMTCT. Eighty-six percent of women know that HIV can be transmitted to a baby through breastfeeding, compared with 79 percent of men, while 78 percent of women and 73 percent of men are aware that the risk of MTCT can be reduced by taking special drugs during pregnancy. Overall, 7 in 10 women (71 percent) and 6 in 10 men (61 percent) are aware 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. MTCT and PMTCT knowledge has increased considerably in the past five years. The 2006 UDHS showed that 52 percent of women and 43 percent of men knew that HIV can be transmitted through breastfeeding and that HIV positive women could reduce the risk of MTCT by taking special drugs during pregnancy. 190 • HIV/AIDS-Related Knowledge, Attitudes, and Behaviour Table 13.4 Knowledge of prevention of mother to child transmission of HIV Percentage of women and men age 15-49 who know that HIV can be transmitted from mother to child by breastfeeding and that the risk of mother to child transmission (MTCT) of HIV can be reduced by mother taking special drugs during pregnancy, by background characteristics, Uganda 2011 Background characteristic Women 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 Number of women 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 Number of men Age 15-24 84.4 74.1 67.2 3,677 77.7 67.8 56.8 872 15-19 80.0 67.7 59.6 2,048 77.4 64.7 54.7 554 20-24 90.0 82.2 76.7 1,629 78.3 73.3 60.5 318 25-29 87.9 82.4 76.0 1,569 83.4 79.8 70.3 361 30-39 88.1 81.5 75.0 2,112 77.9 74.5 60.3 592 40-49 83.6 77.6 69.5 1,316 80.1 73.6 62.6 348 Marital status Never married 81.4 70.3 62.8 2,123 77.9 68.0 58.0 834 Ever had sex 86.7 77.7 70.6 837 78.4 73.0 61.4 438 Never had sex 77.9 65.6 57.8 1,286 77.2 62.5 54.1 397 Married/Living together 87.0 79.8 73.1 5,418 80.3 75.3 63.1 1,228 Divorced/Separated/Widowed 88.5 83.3 76.6 1,134 74.9 76.1 58.5 111 Currently pregnant Pregnant 86.4 77.9 71.6 1,011 na na na na Not pregnant or not sure 85.8 78.0 71.0 7,663 na na na na Residence Urban 91.2 85.2 79.6 1,717 79.2 78.1 64.2 439 Rural 84.5 76.2 68.9 6,957 79.1 71.1 60.1 1,734 Region Kampala 92.3 89.5 83.9 839 79.0 79.4 64.9 221 Central 1 86.8 84.5 76.2 956 70.4 69.9 53.3 209 Central 2 87.6 83.5 76.2 902 76.5 79.8 64.1 236 East Central 79.5 76.3 65.5 869 70.2 72.2 54.4 236 Eastern 86.5 77.1 70.0 1,267 76.9 65.8 55.6 289 Karamoja 63.2 47.5 38.8 289 87.4 48.5 45.7 55 North 91.8 88.2 82.7 735 87.2 72.8 63.7 199 West Nile 82.0 52.5 46.5 500 91.6 79.1 76.4 133 Western 84.4 73.3 66.5 1,221 82.9 75.9 67.8 322 Southwest 88.1 79.0 75.0 1,097 79.9 67.7 57.5 273 Education No education 77.6 65.4 58.1 1,120 71.1 64.0 51.5 90 Primary 85.0 76.3 69.0 5,152 78.8 68.8 58.5 1,309 Secondary + 91.5 87.3 81.5 2,402 80.4 79.9 66.1 774 Wealth quintile Lowest 80.4 65.9 59.5 1,519 82.0 67.8 61.4 345 Second 83.8 73.6 66.2 1,579 78.6 68.8 56.8 423 Middle 84.3 78.4 70.3 1,608 77.0 70.3 58.8 402 Fourth 86.8 80.1 72.8 1,726 79.5 75.1 62.4 486 Highest 91.3 87.2 81.5 2,242 78.9 78.2 64.2 517 Total 15-49 85.8 77.9 71.0 8,674 79.1 72.5 60.9 2,173 50-54 na na na na 72.3 70.2 50.8 122 Total 15-54 na na na na 78.7 72.4 60.4 2,295 na = Not applicable There are notable differences in knowledge of prevention of MTCT by background characteristics. Respondents age 15-24 are the least likely to know both facts about MTCT (60 percent of women and 55 percent of men), compared with older respondents. Knowledge of both facts about MTCT is the highest among previously married women (77 percent) and currently married men (63 percent) compared with other marital status sub-groups. Urban residents are more likely to report knowledge about mother-to-child transmission than those living in rural areas. Women and men living in the Karamoja region are the least knowledgeable about the two aspects of MTCT, while women residing in Kampala (84 percent) and men residing in the West Nile region (76 percent) are the most knowledgeable. Knowledge levels of MTCT tend to increase with educational attainment and wealth quintile status. HIV/AIDS-Related Knowledge, Attitudes, and Behaviour • 191 13.3 ACCEPTING ATTITUDES TOWARDS PEOPLE LIVING WITH 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 against people living with AIDS is an important indicator of the success of programmes aimed at preventing and controlling infection. The HIV/AIDS programmes in Uganda strive to fight such attitudes and to encourage positive living and utilization of HIV testing, care, treatment, and support services by fighting secrecy and denial. To assess the level of stigma, the UDHS survey 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 status secret. Tables 13.5.1 and 13.5.2 show the results for women and men, respectively. Table 13.5.1 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, Uganda 2011 Background characteristic Percentage of women who: Percentage expressing acceptance attitudes on all four indicators 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 86.7 70.3 72.0 37.2 20.0 3,660 15-19 84.3 67.9 69.0 37.4 19.2 2,032 20-24 89.7 73.4 75.8 36.9 21.0 1,628 25-29 91.2 72.9 75.0 39.2 23.8 1,563 30-39 91.8 73.1 74.2 43.8 24.6 2,108 40-49 92.3 71.5 70.8 41.6 23.3 1,314 Marital status Never married 86.7 71.4 72.3 37.3 21.8 2,104 Ever had sex 91.4 77.8 77.2 36.9 22.8 836 Never had sex 83.6 67.2 69.0 37.6 21.1 1,268 Married/Living together 89.9 71.1 72.3 40.4 21.8 5,412 Divorced/Separated/Widowed 93.8 74.7 76.9 41.9 25.9 1,130 Residence Urban 94.4 82.9 84.2 36.7 26.2 1,713 Rural 88.5 68.9 70.1 40.6 21.4 6,933 Region Kampala 94.9 86.0 86.5 32.1 23.3 837 Central 1 95.8 74.7 74.9 33.6 18.8 953 Central 2 92.0 68.8 68.9 33.8 18.0 902 East Central 89.5 61.5 63.6 32.8 15.9 863 Eastern 85.8 69.3 68.9 39.8 20.2 1,261 Karamoja 52.4 44.6 46.1 60.2 13.7 289 North 93.8 84.7 86.9 66.4 51.7 735 West Nile 83.7 60.9 60.3 58.0 26.1 499 Western 93.4 75.8 76.0 37.2 23.0 1,212 Southwest 88.3 69.8 75.9 33.0 15.9 1,096 Education No education 81.9 59.7 59.7 43.8 17.0 1,116 Primary 88.5 67.5 69.0 39.9 20.7 5,131 Secondary + 95.6 86.2 87.4 37.7 28.2 2,398 Wealth quintile Lowest 81.6 63.1 63.1 50.5 25.3 1,515 Second 87.3 66.2 67.0 40.4 19.6 1,573 Middle 90.1 68.9 71.5 40.1 20.8 1,598 Fourth 90.7 71.7 72.4 35.2 19.5 1,722 Highest 95.5 83.2 85.1 35.6 25.5 2,237 Total 15-49 89.6 71.6 72.9 39.8 22.3 8,645 192 • HIV/AIDS-Related Knowledge, Attitudes, and Behaviour Table 13.5.2 Accepting attitudes toward those living with HIV/AIDS: Men Among men age 15-49 who have heard of HIV/AIDS, percentage expressing specific accepting attitudes toward people with HIV/AIDS, by background characteristics, Uganda 2011 Background characteristic Percentage of men who: Percentage expressing acceptance attitudes on all four indicators 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 shop- keeper 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 87.9 76.9 71.3 47.5 27.4 867 15-19 84.8 73.9 69.6 46.2 23.8 549 20-24 93.3 82.2 74.2 49.7 33.7 318 25-29 91.0 79.1 73.3 59.5 37.5 361 30-39 94.1 82.7 77.1 59.1 41.3 592 40-49 94.1 80.7 74.7 57.0 35.3 348 Marital status Never married 87.5 78.0 71.9 48.8 28.3 828 Ever had sex 91.7 82.3 76.2 50.1 31.8 438 Never had sex 82.7 73.3 67.1 47.3 24.5 390 Married/Living together 93.7 81.8 75.5 58.3 38.7 1,228 Divorced/Separated/Widowed 90.0 64.9 68.7 49.5 27.2 111 Residence Urban 93.5 84.0 78.8 55.8 36.1 439 Rural 90.5 78.3 72.5 53.8 33.7 1,729 Region Kampala 94.0 83.5 79.9 58.2 36.7 221 Central 1 90.6 74.4 67.8 52.3 32.0 209 Central 2 97.6 74.9 67.2 59.5 37.0 236 East Central 93.7 79.3 74.2 31.9 22.1 236 Eastern 89.3 70.3 64.3 49.3 25.1 289 Karamoja 62.9 58.7 44.1 68.5 24.2 55 North 99.3 93.8 89.7 71.9 60.2 199 West Nile 89.6 90.5 92.7 33.5 23.3 132 Western 87.4 81.2 74.9 60.0 36.4 317 Southwest 87.8 80.4 72.5 59.6 37.0 273 Education No education 74.3 54.8 42.6 64.0 24.0 90 Primary 89.4 75.2 68.4 51.0 28.4 1,303 Secondary + 95.9 89.5 86.4 58.4 45.1 774 Wealth quintile Lowest 88.3 74.5 68.6 53.3 30.2 339 Second 89.3 74.5 69.8 54.0 31.8 423 Middle 89.6 78.4 70.9 56.1 33.8 402 Fourth 91.5 82.1 76.5 50.3 34.8 485 Highest 95.2 85.1 80.0 57.0 38.4 517 Total 15-49 91.1 79.5 73.8 54.2 34.2 2,167 50-54 95.3 81.6 77.6 57.0 37.2 122 Total 15-54 91.3 79.6 74.0 54.3 34.3 2,289 HIV/AIDS-Related Knowledge, Attitudes, and Behaviour • 193 The majority of women and men, nine in ten, reported that they are willing to care for a family member with AIDS at home. Lower proportions of women (72 percent) and men (80 percent), however, said that they would buy fresh vegetables from an HIV-positive vendor. Approximately three-quarters of Ugandans (73 percent of women and 74 percent of men) feel that a female teacher who has the AIDS virus but is not sick should be allowed to continue teaching in the school. Four in 10 women (40 percent) and more than 5 in 10 men (54 percent) reported that if a member of their family got infected with the AIDS virus, they would not want it to remain a secret. Overall, less than one-quarter of women (22 percent) and one-third of men (34 percent) of men expressed positive attitudes on all four indicator situations (i.e., they would care for a family member with AIDS in their own home, would buy fresh food from a shopkeeper with HIV, would support an HIV-positive female teacher to continue teaching, and would not want to keep the HIV-positive status of a family member a secret). Variations in stigma levels by background characteristics are evident in Tables 13.5.1 and 13.5.2. Accepting attitudes were generally more common among the older age cohorts compared with those younger than 25 years. Urban residents are somewhat more likely than rural respondents to express accepting attitudes on all four issues examined. There are notable regional variations in accepting attitudes towards people living with HIV/AIDS. For example, the proportion of women who express accepting attitudes on all four indicators of stigma ranges from a low of 14 percent of women residing in the Karamoja region to a high of 52 percent of women living in the North region. Among men, the proportion expressing accepting attitudes ranges from a low of 22 percent in the East Central region to a high of 60 percent in the North region. In general, the proportion with accepting attitudes on all four indicators increases with increasing education level and, among men, with increasing wealth quintile. For example, men with at least a secondary education are almost twice as likely as men with no education to have accepting attitudes in all four situations (45 percent compared with 24 percent). 13.4 ATTITUDES TOWARDS REFUSING TO HAVE SEX AND NEGOTIATING SAFER SEX Knowledge about HIV transmission and ways to prevent it are of little use if people feel powerless to negotiate safer sex practices with their partners. In an effort to assess the ability of women to negotiate safer sex with their husbands, women and men were asked whether they thought that a wife is justified in refusing to have sexual intercourse with her husband if she knows he has sex with women other than his wives or asking that he use a condom if she knows he has a sexually transmitted infection (STI). The results are presented in Table 13.6. 194 • HIV/AIDS-Related Knowledge, Attitudes, and Behaviour Table 13.6 Attitudes toward negotiating safer sexual relations with husband Percentage of women and men age 15-49 who believe that a woman is justified in refusing to have sexual intercourse with her husband if she knows that he has sexual intercourse with other women, and percentage who believe that a woman is justified in asking that they use a condom if she knows that her husband has a sexually transmitted infection (STI), by background characteristics, Uganda 2011 Background characteristic Women Men Woman is justified in: Number of women Woman is justified in: 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 73.4 83.3 3,677 74.9 93.5 872 15-19 73.1 82.1 2,048 76.7 92.8 554 20-24 73.8 84.9 1,629 71.8 94.9 318 25-29 76.7 86.7 1,569 71.4 95.3 361 30-39 72.9 85.0 2,112 74.4 93.7 592 40-49 73.1 83.7 1,316 76.4 95.2 348 Marital status Never married 75.6 82.5 2,123 75.8 93.5 834 Ever had sex 79.3 88.9 837 74.7 95.1 438 Never had sex 73.1 78.4 1,286 77.0 91.7 397 Married/living together 73.1 84.8 5,418 73.7 94.6 1,228 Divorced/separated/Widowed 74.3 85.7 1,134 72.2 94.2 111 Residence Urban 78.0 86.4 1,717 74.4 95.0 439 Rural 72.8 83.9 6,957 74.4 93.9 1,734 Region Kampala 79.6 86.4 839 77.1 94.0 221 Central 1 74.5 81.5 956 83.6 94.4 209 Central 2 78.2 75.4 902 70.4 93.8 236 East Central 75.5 85.7 869 77.6 96.7 236 Eastern 73.8 87.8 1,267 79.9 93.2 289 Karamoja 46.0 35.6 289 70.3 59.2 55 North 76.6 93.8 735 61.3 97.9 199 West Nile 74.9 79.2 500 87.4 90.6 133 Western 68.0 88.9 1,221 73.1 96.0 322 Southwest 75.5 91.7 1,097 65.9 96.9 273 Education No education 65.0 72.6 1,120 73.3 84.9 90 Primary 74.2 85.3 5,152 74.1 93.4 1,309 Secondary + 77.2 87.9 2,402 75.2 96.4 774 Wealth quintile Lowest 69.3 77.2 1,519 70.6 86.9 345 Second 72.3 83.8 1,579 77.0 95.8 423 Middle 74.1 86.5 1,608 74.5 94.8 402 Fourth 75.2 86.5 1,726 71.6 96.0 486 Highest 76.7 86.5 2,242 77.5 95.4 517 Total 15-49 73.8 84.4 8,674 74.4 94.1 2,173 50-54 na na na 78.8 93.9 122 Total 15-54 na na na 74.7 94.1 2,295 na = Not applicable Three-quarters of Ugandans (74 percent of women and men each) believe that a woman is justified in refusing to have sex with her husband if she knows he has sex with other women (Table 13.6). Eighty-four percent of women and 94 percent of men reported that a woman is justified in asking to use a condom if she knows that her husband has an STI. Women age 25-29; those who have never married but have had sex; urban residents; those with at least some secondary education; and women from a higher wealth quintile tend to believe that a woman is justified in negotiating safer sexual intercourse with her husband compared with women in other subgroups. Among the regions, however, a much lower proportion of women living in the Karamoja region support negotiation of safer sexual relations compared with women living in the rest of Uganda. HIV/AIDS-Related Knowledge, Attitudes, and Behaviour • 195 Men living in the North region are the least supportive of a woman refusing to have sex with her husband when she knows he has sex with other women compared with men living in other regions. Men from the Karamoja region are much less likely to agree to a women’s negotiation of condom use relative to men living in other places. Like women, men with secondary education or higher tend to believe that a woman in justified in negotiating safer sexual intercourse with her husband. Men in the lowest wealth quintile are the least likely to agree to that a woman is justified in negotiating safer sex. 13.5 ADULT SUPPORT OF EDUCATION ABOUT CONDOMS FOR CHILDREN AGE 12-14 Condom use is one of the main strategies for combating the spread of HIV. However, educating young people about condoms is controversial, as some say it promotes early sexual experimentation. To gauge attitudes toward condom education, UDHS respondents were asked whether they thought that children age 12-14 should be taught about using a condom to avoid getting AIDS. Because the focus is on adults’ opinions, results are tabulated for respondents age 18-49. Table 13.7 shows that more than 6 in 10 adults agree that children age 12-14 should be taught about using condoms to avoid AIDS (64 percent of women and 66 percent of men age 18-49). Women age 20-29 are somewhat more supportive than older women of condom education for children, while men age 25-29 are the most likely to agree that children age 12-14 should be taught about condoms as an HIV prevention method. Support for condom education is higher among urban women than rural women (67 percent versus 63 percent) whereas for men it is the reverse (62 percent of urban men versus 67 percent of rural men, respectively). There is considerable regional variability in the level of support for condom education among women, from a low of 24 percent of women in the Karamoja region to a high of 72 percent of women living in the Western region. Among men, support for condom education is highest in West Nile (76 percent) and lowest in Karamoja (31 percent). Both women and men with no education are less likely to support condom education compared with those with at least some education. There is no clear pattern observed by wealth quintile. 13.6 HIGH-RISK SEX Information on sexual behaviour is important in designing and monitoring intervention programmes to control the spread of the epidemic. The 2011 UDHS included questions on respondents’ sexual partners during their lifetimes and over the 12 months preceding the survey. Men were also asked whether they paid for sex during the 12 months preceding the interview. In addition, information was Table 13.7 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, Uganda 2011 Background characteristic Women Men Percentage who agree Number of women Percentage who agree Number of men Age 18-24 64.0 2,416 64.6 497 18-19 62.7 787 61.7 179 20-24 64.7 1,629 66.3 318 25-29 65.3 1,569 70.8 361 30-39 63.0 2,112 62.5 592 40-49 61.5 1,316 67.2 348 Marital status Never married 60.4 978 63.8 461 Married or living together 63.1 5,315 66.7 1,228 Divorced/separated/ widowed 68.1 1,121 61.7 109 Residence Urban 66.6 1,483 62.4 382 Rural 62.8 5,930 66.6 1,417 Region Kampala 63.8 732 63.4 183 Central 1 60.8 828 69.7 175 Central 2 65.8 770 65.9 205 East Central 69.6 744 66.3 176 Eastern 70.3 1,086 72.2 243 Karamoja 23.9 249 30.8 51 North 58.6 609 65.2 157 West Nile 56.6 421 76.1 114 Western 71.6 1,021 63.4 267 Southwest 59.4 953 62.4 228 Education No education 55.2 1,087 60.0 86 Primary 64.8 4,290 66.7 1,028 Secondary + 65.3 2,036 64.9 685 Wealth quintile Lowest 58.9 1,330 62.6 299 Second 61.6 1,367 72.3 347 Middle 67.2 1,368 62.3 334 Fourth 65.6 1,411 67.6 395 Highest 63.9 1,938 63.3 424 Total 18-49 63.5 7,413 65.7 1,798 50-54 na na 61.9 122 Total 18-54 na na 65.4 1,920 na = Not applicable 196 • HIV/AIDS-Related Knowledge, Attitudes, and Behaviour collected on women’s and men’s use of condoms during their most recent sexual intercourse with each type of partner. These questions are sensitive, and it is recognized that some respondents may have been reluctant to provide information on recent sexual behaviour. 13.6.1 Multiple Partners and Condom Use Tables 13.8.1 and 13.8.2 show the percentages of women and men, respectively, who had two or more partners in the 12 months preceding the survey. The tables also show the percentages of men and women with two or more partners who used a condom during their last sexual intercourse. Finally, the tables provide information on the mean number of lifetime sexual partners among those who have ever had sexual intercourse. Table 13.8.1 Multiple sexual partners: Women Among all women age 15-49, the percentage who had sexual intercourse with more than one sexual partner in the past 12 months; among those having more than one partner in the past 12 months and the mean number of sexual partners during their lifetime for women who ever had sexual intercourse, by background characteristics, Uganda 2011 Background characteristic All women Among women who ever had sexual intercourse1: Percentage who had 2+ partners in the past 12 months Number of women Mean number of sexual partners in lifetime Number of women Age 15-24 2.1 3,677 1.8 2,415 15-19 1.5 2,048 1.6 923 20-24 2.7 1,629 1.9 1,492 25-29 1.7 1,569 2.1 1,546 30-39 1.0 2,112 2.2 2,093 40-49 1.1 1,316 2.5 1,306 Marital status Never married 1.5 2,120 1.8 834 Married or living together 1.3 5,421 2.0 5,400 Divorced/separated/widowed 3.3 1,134 2.9 1,125 Residence Urban 2.4 1,717 2.5 1,444 Rural 1.4 6,957 2.0 5,915 Region Kampala 1.7 839 2.5 703 Central 1 3.4 956 2.4 814 Central 2 1.9 902 2.4 772 East Central 2.6 869 2.3 756 Eastern 1.9 1,267 2.1 1,094 Karamoja 0.2 289 1.4 253 North 0.2 735 1.7 628 West Nile 0.9 500 1.8 417 Western 1.3 1,221 2.2 1,068 Southwest 0.5 1,097 1.4 853 Education No education 1.0 1,120 1.9 1,087 Primary 1.6 5,152 2.1 4,365 Secondary + 1.9 2,402 2.2 1,908 Wealth quintile Lowest 0.8 1,519 1.9 1,359 Second 0.9 1,579 1.9 1,377 Middle 1.6 1,608 2.0 1,374 Fourth 2.8 1,726 2.2 1,397 Highest 1.8 2,242 2.4 1,852 Total 15-49 1.6 8,674 2.1 7,359 1 Means are calculated excluding respondents who gave non-numeric responses HIV/AIDS-Related Knowledge, Attitudes, and Behaviour • 197 Table 13.8.2 Multiple sexual partners: Men Among all men age 15-49, the percentage who had sexual intercourse with more than one sexual partner in the past 12 months; among those having more than one partner in the past 12 months, 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, Uganda 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 Number of men Percentage who reported using a condom during last sexual intercourse Number of men Mean number of sexual partners in lifetime Number of men Age 15-24 8.9 872 47.3 78 3.5 489 15-19 5.4 554 (55.7) 30 2.8 222 20-24 15.0 318 42.1 48 4.2 267 25-29 23.3 361 18.2 84 5.6 346 30-39 24.1 592 10.0 142 7.7 573 40-49 29.0 348 10.3 101 9.0 339 Marital status Never married 7.5 834 70.4 63 4.1 437 Married or living together 25.7 1,228 6.3 316 6.9 1,204 Divorced/separated/widowed 23.7 111 * 26 10.0 106 Type of union In polygynous union 86.4 193 6.1 167 9.2 189 In non-polygynous union 14.4 1,035 6.5 149 6.4 1,014 Not currently in union 9.4 945 64.0 89 5.2 543 Residence Urban 20.0 439 36.0 88 7.2 370 Rural 18.3 1,734 14.2 317 6.1 1,377 Region Kampala 16.9 221 (43.9) 37 6.5 180 Central 1 27.0 209 (18.9) 56 8.6 167 Central 2 18.0 236 (24.6) 42 6.6 196 East Central 25.7 236 24.5 61 5.7 190 Eastern 10.7 289 (8.1) 31 6.6 234 Karamoja 26.4 55 (3.5) 15 3.8 48 North 19.9 199 (4.3) 40 7.3 169 West Nile 14.5 133 (15.1) 19 4.5 105 Western 19.4 322 15.1 63 7.4 263 Southwest 15.1 273 (17.6) 41 4.0 195 Education No education 37.6 90 (6.9) 34 5.9 78 Primary 18.1 1,309 17.2 237 6.6 1,035 Secondary + 17.3 774 25.1 134 6.1 635 Wealth quintile Lowest 17.7 345 8.1 61 4.7 285 Second 18.2 423 7.0 77 6.4 345 Middle 19.3 402 14.3 78 6.8 323 Fourth 20.3 486 25.2 99 6.6 382 Highest 17.5 517 33.6 91 6.9 413 Total 15-49 18.6 2,173 19.0 405 6.4 1,747 50-54 32.3 122 (11.3) 39 14.1 118 Total 15-54 19.4 2,295 18.3 444 6.8 1,865 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 A much smaller proportion of women report having had two or more partners in the 12 months preceding the survey compared with men (2 percent and 19 percent). Data for women are not discussed by background characteristics due to the small number of women with more than one sexual partner. Among men, the proportion of men reporting more than one sexual partner in the past 12 months increases steadily with age. For example, 5 percent of men age 15-19 report having had more than one partner, yet almost 3 in 10 men age 40-49 (29 percent) report that they had two or more sexual partners within the past year. Those who had ever been married and those with no education were more likely than their counterparts to have had more than one sexual partner in the past 12 months. As would be expected, the proportion of men with multiple sexual partners in the past 12 months was particularly high among those in polygynous 198 • HIV/AIDS-Related Knowledge, Attitudes, and Behaviour unions (86 percent). By residence, urban men are only slightly more likely than rural men to report multiple sexual partners in the last year. More than one-quarter of men living in Central 1 (27 percent), East Central (26 percent), and Karamoja (26 percent) regions had more than one sexual partner within the past 12 months. The likelihood of having more than one sexual partner does not have a uniform pattern with wealth. Among women who had more than one sexual partner in the past 12 months, nearly one-third (31 percent) report using a condom during their last sexual intercourse (data not presented). Almost one-fifth (19 percent) of men with multiple sexual partners in the last year report that they used a condom during their last sexual intercourse. Among those with more than one sexual partner in the past 12 months, never-married men were 11 times more likely to report condom use during their most recent sexual intercourse than those who were married (70 percent and 6 percent, respectively). Urban men with two or more sexual partners in the 12 months before the survey were also more likely than rural men to report using a condom during their last sexual intercourse (36 percent and 14 percent, respectively). Condom use among men during last sexual intercourse and generally increased with education level and wealth. On average, men report having had 6.4 sexual partners over their lifetimes, whereas women report 2.1 partners. Among men, the mean number of lifetime sexual partners increased with age, with men age 40-49 reporting an average of 9 lifetime partners. Men in a polygynous union and those who were divorced, separated, or widowed had the highest average numbers of lifetime sexual partners (9 and 10 partners, respectively). Similarly, older women and those that are divorced, separated, or widowed reported slightly more lifetime sexual partners relative to other women. Urban residents also reported a slightly higher average of lifetime sexual partners compared with rural residents. Mean reported number of lifetime sex partners among men varied from 4 in the Karamoja region to 9 in the Central 1 region. Among women, mean number of lifetime sex partners varied from 1 in the Karamoja and Southwest regions to 3 in Kampala. There is little variation in the mean number of lifetime partners by educational attainment or wealth in women or men. Point prevalence and cumulative prevalence of concurrent sexual partners are new concepts that were incorporated for the first time in the 2011 UDHS. The point prevalence of concurrent sexual partners is defined as the percentage of respondents who had two (or more) sexual partners concurrently at the point in time six months before the survey. The cumulative prevalence of concurrent sexual partners is defined as the percentage of respondents who had two (or more) sexual partners concurrently at any time during the 12 months preceding the survey. Table 13.9 shows the point prevalence and cumulative prevalence of concurrent sexual partners among all respondents during the 12 months before the survey. It also shows the percentage of respondents who had concurrent sexual partners among those who had multiple sexual partners during the 12 months before the survey. The point prevalence of concurrent sexual partners among women 15-49 is less than 1 percent compared with 10 percent among men in the same age range, and cumulative prevalence of concurrent sexual partners is 1 percent among women compared with 15 percent of men. Among respondents who had multiple partners during the 12 months before the survey, 59 percent of women and 82 percent of men age 15-49 had concurrent partners. There are no major variations in the point or cumulative prevalence of concurrent sexual partners among women, by background characteristics. Among men, the point and cumulative prevalence of concurrent sexual partners increase with age, are highest among men who are married or cohabiting, men in polygynous unions, and men in rural areas. The variation in the percentage of men with multiple partners in the past 12 months who had concurrent sexual partners during the specified period by background characteristics follows the same pattern as the point and cumulative prevalence. HIV/AIDS-Related Knowledge, Attitudes, and Behaviour • 199 Table 13.9 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), and percentage of all women and all men 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, Uganda 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 Number of respondents Percentage who had concurrent sexual partners2 Number of respondents WOMEN Age 15-24 0.6 1.1 3,677 54.3 75 15-19 0.1 0.5 2,048 (30.1) 31 20-24 1.2 1.9 1,629 (71.1) 45 25-29 0.4 1.3 1,569 (78.6) 27 30-39 0.1 0.4 2,112 * 22 40-49 0.3 0.9 1,316 * 14 Marital status Never married 0.2 0.5 2,120 (33.3) 32 Married or living together 0.4 0.9 5,421 72.0 69 Divorced/separated/widowed 0.7 1.9 1,134 (55.9) 38 Residence Urban 0.6 1.5 1,717 61.1 41 Rural 0.3 0.8 6,957 57.8 97 Total 15-49 0.4 0.9 8,674 58.8 139 MEN Age 15-24 1.5 4.8 872 54.2 78 15-19 0.4 1.9 554 (35.1) 30 20-24 3.5 9.9 318 66.1 48 25-29 11.4 20.6 361 88.4 84 30-39 13.2 20.7 592 86.2 142 40-49 22.6 27.2 348 93.8 101 Marital status Never married 1.2 3.6 834 48.5 63 Married or living together 15.8 23.3 1,228 90.7 316 Divorced/separated/widowed 6.1 15.0 111 (63.5) 26 Type of union In polygynous union 71.6 80.8 193 93.5 167 In non-polygynous union 5.3 12.6 1,035 87.6 149 Not currently in union 1.8 5.0 945 52.9 89 Residence Urban 7.5 14.6 439 72.8 88 Rural 10.2 15.6 1,734 85.1 317 Total 15-49 9.7 15.4 2,173 82.4 405 50-54 26.7 32.3 122 (100.0) 39 Total 15-54 10.6 16.3 2,295 84.0 444 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 anytime during the 12 months preceding the survey 200 • HIV/AIDS-Related Knowledge, Attitudes, and Behaviour 13.6.2 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 UDHS asked men if they had ever paid anyone for sexual intercourse and if they had done so in the 12 months preceding the survey. 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 13.10 shows that 6 percent of men age 15-49 report having paid for sexual intercourse at some point in their lives, while 2 percent did so in the past 12 months. Men age 30-39 (9 percent), those who were previously married (19 percent), and urban men (7 percent) were more likely than other men to have ever paid for sexual intercourse. Among regions, this proportion ranges from less than 1 percent of men living in the West Nile region to 10 percent of men living in the East Central region. Similar patterns by background characteristics in the percentage of men who paid for sex in the past 12 months are observed. More than four in ten men (44 percent) age 15-49 who paid for sex in the past 12 months reported condom use at last paid sexual intercourse (data not shown). 13.7 COVERAGE OF HIV COUNSELING AND TESTING People’s knowledge of their HIV status is considered a key motivating factor for behaviour change and a critical linkage to care, treatment, and support services for infected individuals. 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. The HIV/AIDS programme has been engaged in increasing coverage of HIV counseling and testing services based on a multiple programme approach. In the 2011 UDHS, respondents were asked if they knew a place where they could go to be tested and further if they had ever undergone an HIV test and received the results of the test. Table 13.10 Payment for sexual intercourse and condom use at last paid sexual intercourse Percentage of men age 15-49 who ever paid for sexual intercourse and percentage reporting payment for sexual intercourse in the past 12 months, and among them, the percentage reporting that a condom was used the last time they paid for sexual intercourse, by background characteristics, Uganda 2011 Background characteristic Among all men: Percentage who ever paid for sexual intercourse Percentage who paid for sexual intercourse in the past 12 months Number of men Age 15-24 4.2 2.0 872 15-19 2.1 1.3 554 20-24 7.9 3.3 318 25-29 8.2 3.5 361 30-39 8.5 3.0 592 40-49 5.7 0.5 348 Marital status Never married 3.9 2.2 834 Married or living together 6.7 2.1 1,228 Divorced/separated/widowed 19.4 5.3 111 Residence Urban 7.4 3.3 439 Rural 6.0 2.1 1,734 Region Kampala 7.5 4.6 221 Central 1 7.4 5.0 209 Central 2 5.5 1.5 236 East Central 10.1 4.2 236 Eastern 7.2 2.9 289 Karamoja 1.9 1.9 55 North 1.6 0.1 199 West Nile 0.7 0.1 133 Western 7.0 0.6 322 Southwest 7.0 1.6 273 Education No education 2.5 0.3 90 Primary 7.4 2.6 1,309 Secondary + 4.8 2.0 774 Wealth quintile Lowest 2.4 0.9 345 Second 7.1 2.6 423 Middle 8.7 2.4 402 Fourth 5.9 1.6 486 Highest 6.6 3.5 517 Total 15-49 6.3 2.3 2,173 50-54 7.1 2.3 122 Total 15-54 6.3 2.3 2,295 HIV/AIDS-Related Knowledge, Attitudes, and Behaviour • 201 Tables 13.11.1 and 13.11.2 show that almost all Ugandans know where to get an HIV test (95 percent of women and 93 percent of men). Those living in urban areas (97 percent for both women and men) are slightly more likely than rural residents (94 percent of women and 92 percent of men) to know where to get an HIV test. Those who had ever had sex are more likely than those who had never married and never had sex to know where to get an HIV test. The proportion of both women and men who know where to get an HIV test increases as educational attainment and wealth quintile increase. In general, differences by region are not large. Table 13.11.1 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 were tested in the past 12 months and received the results of the last test, according to background characteristics, Uganda 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 have been tested for HIV in the past 12 months and received the results of the last test Number of women Ever tested and received results Ever tested, did not receive results Never tested1 Age 15-24 91.8 61.5 3.7 34.8 100.0 65.2 40.2 3,677 15-19 88.2 45.5 3.4 51.1 100.0 48.9 30.7 2,048 20-24 96.5 81.6 4.1 14.3 100.0 85.7 52.0 1,629 25-29 97.2 85.5 4.4 10.1 100.0 89.9 50.7 1,569 30-39 97.0 78.9 4.8 16.3 100.0 83.7 41.6 2,112 40-49 95.6 69.9 2.7 27.4 100.0 72.6 35.3 1,316 Marital status Never married 88.5 46.0 2.8 51.2 100.0 48.8 30.0 2,123 Ever had sex 95.1 70.2 3.3 26.5 100.0 73.5 45.9 837 Never had sex 84.3 30.3 2.5 67.2 100.0 32.8 19.6 1,286 Married/living together 96.6 79.8 4.5 15.7 100.0 84.3 45.7 5,418 Divorced/separated/wido wed 96.9 78.2 3.6 18.2 100.0 81.8 44.5 1,134 Residence Urban 97.3 79.1 2.5 18.5 100.0 81.5 46.1 1,717 Rural 94.0 69.4 4.3 26.2 100.0 73.8 40.6 6,957 Region Kampala 96.1 78.0 2.3 19.7 100.0 80.3 43.2 839 Central 1 96.1 73.1 2.8 24.1 100.0 75.9 43.3 956 Central 2 95.8 71.3 4.0 24.8 100.0 75.2 39.6 902 East Central 93.0 62.6 7.5 29.9 100.0 70.1 40.6 869 Eastern 94.0 70.5 4.4 25.0 100.0 75.0 41.4 1,267 Karamoja 84.2 62.2 5.8 32.0 100.0 68.0 36.8 289 North 97.5 81.4 3.5 15.1 100.0 84.9 49.6 735 West Nile 94.8 66.6 4.3 29.1 100.0 70.9 42.3 500 Western 94.1 72.0 4.1 23.9 100.0 76.1 40.9 1,221 Southwest 94.6 69.8 2.4 27.8 100.0 72.2 38.8 1,097 Education No education 88.8 65.0 5.5 29.5 100.0 70.5 32.9 1,120 Primary 94.0 69.6 4.1 26.3 100.0 73.7 40.3 5,152 Secondary + 98.6 78.2 2.8 19.0 100.0 81.0 48.8 2,402 Wealth quintile Lowest 91.2 70.7 4.4 24.9 100.0 75.1 41.0 1,519 Second 93.7 68.3 5.0 26.7 100.0 73.3 40.7 1,579 Middle 95.0 68.8 4.4 26.8 100.0 73.2 39.7 1,608 Fourth 94.0 68.5 3.5 28.0 100.0 72.0 41.0 1,726 Highest 97.8 78.0 3.0 19.0 100.0 81.0 44.8 2,242 Total 15-49 94.6 71.3 4.0 24.7 100.0 75.3 41.7 8,674 1 Includes 'don't know/missing' 202 • HIV/AIDS-Related Knowledge, Attitudes, and Behaviour Table 13.11.2 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 were tested in the past 12 months and received the results of the last test, according to background characteristics, Uganda 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 have been tested for HIV in the past 12 months and received the results of the last test Number of men Ever tested and received results Ever tested, did not receive results Never tested1 Age 15-24 88.3 35.4 4.0 60.5 100.0 39.5 24.1 872 15-19 84.9 25.1 3.1 71.8 100.0 28.2 17.4 554 20-24 94.4 53.4 5.7 40.9 100.0 59.1 35.8 318 25-29 95.2 65.6 3.5 30.8 100.0 69.2 39.4 361 30-39 96.5 64.0 2.7 33.3 100.0 66.7 34.8 592 40-49 98.1 60.0 3.7 36.4 100.0 63.6 31.0 348 Marital status Never married 88.0 35.5 3.3 61.3 100.0 38.7 24.3 834 Ever had sex 94.8 48.5 3.6 47.9 100.0 52.1 33.3 438 Never had sex 80.5 21.0 3.0 76.0 100.0 24.0 14.3 397 Married/Living together 96.8 63.7 3.5 32.8 100.0 67.2 34.9 1,228 Divorced/Separated/Wid owed 93.4 50.1 5.8 44.1 100.0 55.9 32.0 111 Residence Urban 96.9 66.1 2.0 31.9 100.0 68.1 38.9 439 Rural 92.3 48.6 4.0 47.4 100.0 52.6 28.6 1,734 Region Kampala 96.6 68.8 0.7 30.5 100.0 69.5 43.3 221 Central 1 92.2 55.6 2.2 42.2 100.0 57.8 30.9 209 Central 2 89.5 47.4 3.3 49.2 100.0 50.8 20.8 236 East Central 93.2 37.9 4.9 57.1 100.0 42.9 20.7 236 Eastern 92.2 50.3 5.5 44.2 100.0 55.8 32.4 289 Karamoja 73.7 51.2 0.0 48.8 100.0 51.2 33.6 55 North 99.2 67.7 6.4 25.9 100.0 74.1 44.7 199 West Nile 97.0 56.0 1.4 42.6 100.0 57.4 36.5 133 Western 94.6 50.5 4.8 44.7 100.0 55.3 30.9 322 Southwest 91.9 43.3 2.1 54.6 100.0 45.4 21.8 273 Education No education 84.1 31.9 7.3 60.8 100.0 39.2 25.0 90 Primary 90.7 45.0 3.8 51.3 100.0 48.7 25.2 1,309 Secondary + 98.7 66.7 2.8 30.5 100.0 69.5 40.6 774 Wealth quintile Lowest 90.3 48.6 4.2 47.1 100.0 52.9 32.1 345 Second 91.9 47.0 5.7 47.2 100.0 52.8 25.7 423 Middle 92.3 45.8 4.1 50.1 100.0 49.9 27.6 402 Fourth 94.5 52.0 2.5 45.5 100.0 54.5 30.9 486 Highest 95.9 63.8 1.9 34.3 100.0 65.7 36.0 517 Total 15-49 93.3 52.2 3.6 44.3 100.0 55.7 30.7 2,173 50-54 95.1 51.5 6.0 42.5 100.0 57.5 25.8 122 Total 15-54 93.4 52.1 3.7 44.2 100.0 55.8 30.4 2,295 1 Includes 'don't know/missing' Tables 13.11.1 and 13.11.2 also show the coverage of HIV testing services. . Overall, 7 in 10 women (71 percent) and half of men (52 percent) had ever been tested and had received the result of the last test. A larger proportion of men (44 percent) than women (25 percent) had never been tested, implying that they are less likely to know their HIV status. Among women the likelihood of having ever had an HIV test and receiving the result was highest in the 25-29 age group (86 percent); similarly, the highest rate of ever being tested for HIV and receiving the result among men was among those age 25-29 (66 percent). Among both women and men, urban residents are more likely than rural residents to have ever had an HIV test and received results. Married respondents are more likely to have taken the test and received results (80 percent of women and 64 percent of men) than those never married. Among regions the percentages of men and women who have ever been tested for HIV and received results range from a low of 62 percent of HIV/AIDS-Related Knowledge, Attitudes, and Behaviour • 203 women living in Karamoja region to a high of 81 percent of women residing in the North. For men, the proportion that has ever been tested and received their results also varies by region, from a low of 38 percent in the East Central region to 69 percent of men living in Kampala. As education and wealth status increase, the likelihood of having been tested for HIV and received the test result also increases. Four in 10 women (42 percent) and 3 in 10 men (31 percent) were tested for HIV in the year preceding the survey and had been told the result of the last test they took. HIV testing has increased dramatically in the past five years. The current survey shows that 7 in 10 women (71 percent) and 1 in 2 men (52 percent) age 15-49 have ever been tested for HIV and received their results. This shows a sizeable increase from 25 percent of women and 21 percent of men in the 2006 UDHS who reported being tested for HIV and receiving the result. 13.7.1 HIV Testing During Antenatal Care Table 13.12 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. Sixty-eight percent of women who gave birth in the two years before the survey received HIV counseling during antenatal care (ANC). Almost 3 in 5 women (59 percent) were tested for HIV during antenatal care and received the test results and post-test counseling, while 15 percent received results but did not receive post-test counseling. Four percent of women were tested for HIV during an ANC visit but did not receive the test results. Overall, 60 percent of women received HIV counseling, an HIV test, and the results during ANC for their most recent birth in the two years preceding the survey. By age, a higher proportion of women in the 20-24 age cohort were counseled, tested, and received their HIV result during ANC than women in other age groups. Women were more likely to have been counseled and tested and to have received the result of the test if they lived in urban areas (76 percent) or in Kampala (82 percent). The likelihood of HIV counseling and testing during ANC increases with levels of education and wealth. For example, the proportion of women who were counseled about HIV during ANC, were tested, and received results ranges from 48 percent of women with no education to 71 percent of those with at least some secondary education. Likewise, those in the lowest wealth quintile (54 percent) are the least likely to have been counseled, tested, and received their results while women in the highest quintile (74 percent) were the most likely. 204 • HIV/AIDS-Related Knowledge, Attitudes, and Behaviour Table 13.12 Pregnant women counseled 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 pretest counseling, the percentage who received an HIV test during antenatal care for their most recent birth by whether they received their results and post-test counseling, and percentage who received an HIV test at the time of delivery for their most recent birth by whether they received their test results, according to background characteristics, Uganda 2011 Background characteristic Percentage who received counseling on HIV during antenatal care1 Percentage who were tested for HIV during antenatal care and who: Percentage who received counseling on HIV and an HIV test during ANC, and the results Percentage who had an HIV test during ANC or labor and who:2 Number of women who gave birth in the past two years3 Received results and: Did not receive results Received post-test counseling Did not receive post-test counseling Received results Did not receive results Age 15-24 67.4 60.4 15.5 4.5 61.1 77.6 4.9 1,190 15-19 60.7 57.7 14.0 7.7 54.2 73.3 8.3 319 20-24 69.8 61.4 16.1 3.3 63.7 79.2 3.7 871 25-29 67.9 62.0 14.5 4.3 61.7 77.6 4.5 851 30-39 69.0 55.2 15.8 3.8 59.3 72.6 4.0 886 40-49 63.6 50.9 16.5 1.8 55.0 70.2 1.8 166 Marital status Never married 66.3 62.8 13.6 3.6 61.5 79.9 3.6 142 Ever had sex 67.9 64.4 14.0 3.7 63.0 81.8 3.7 138 Never had sex * * * * * * * 3 Married/Living together 67.3 58.1 15.8 4.3 59.7 75.2 4.6 2,643 Divorced/Separated/Widowed 72.5 63.5 12.5 2.4 66.3 78.9 2.8 308 Residence Urban 79.4 73.7 12.7 4.4 75.6 87.9 4.4 450 Rural 65.8 56.3 15.8 4.1 57.9 73.7 4.4 2,642 Region Kampala 86.1 76.0 10.5 4.0 81.5 87.0 4.1 187 Central 1 62.6 51.6 12.8 3.4 52.3 66.5 3.9 322 Central 2 63.9 54.1 19.7 4.6 59.4 76.6 4.6 340 East Central 57.3 42.0 11.6 9.4 44.7 59.0 9.6 345 Eastern 57.2 55.7 20.2 2.2 51.2 77.2 2.9 529 Karamoja 64.8 63.5 7.4 5.1 54.7 72.8 5.2 107 North 79.5 76.7 10.3 2.0 76.1 87.5 2.0 276 West Nile 73.4 63.4 9.3 4.7 64.4 72.9 4.7 187 Western 70.6 64.4 12.3 4.9 63.0 77.3 5.2 423 Southwest 77.4 57.5 25.3 2.2 70.8 82.9 2.6 375 Education No education 56.0 48.4 14.0 3.9 48.1 63.3 4.2 399 Primary 67.3 56.5 16.6 5.1 59.3 74.9 5.3 1,975 Secondary + 75.8 71.0 12.8 1.6 70.6 85.2 2.0 718 Wealth quintile Lowest 61.1 57.2 13.0 2.7 53.5 71.4 2.9 694 Second 63.6 54.8 16.5 3.6 57.5 72.5 4.2 679 Middle 68.2 55.1 17.4 5.9 57.9 73.9 6.0 602 Fourth 69.6 57.5 17.5 4.7 61.5 77.3 4.7 561 Highest 78.9 71.1 12.7 4.1 74.3 85.7 4.4 556 Total 15-49 67.8 58.8 15.4 4.1 60.4 75.8 4.4 3,092 Note: An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. 1 In this context, "pretest counseling" means that someone talked with the respondent about all three of the following topics: 1) babies getting the AIDS virus from their mother, 2) preventing the virus, and 3) getting tested for the virus. 2 Women are asked whether they received an HIV test during labor only if they were not tested for HIV during ANC. 3 Denominator for percentages includes women who did not receive antenatal care for their last birth in the past two years. HIV/AIDS-Related Knowledge, Attitudes, and Behaviour • 205 13.8 MALE CIRCUMCISION 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 UDHS asked men if they were circumcised. Table 13.13 shows that 27 percent of Ugandan men age 15-49 are circumcised. Men living in urban areas are 1.7 times more likely to be circumcised than men in rural areas (40 percent versus 23 percent). Male circumcision varies by region in Uganda. It is most prevalent among men living in the East Central region (42 percent) and in Kampala (41 percent), but it is least practiced among men living in the North region (4 percent). The proportion of circumcised men is highest among Muslims (94 percent) and men from the Basoga ethnicity (49 percent) compared with men from other religions and ethnic backgrounds. 13.9 SELF-REPORTING OF SEXUALLY TRANSMITTED INFECTIONS Information about the prevalence 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 UDHS asked respondents who had ever had sex whether they had suffered from 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 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 13.14 shows the self-reported prevalence of STIs and STI symptoms among both men and women. Women were somewhat more likely than men to report having had an STI or having experienced STI symptoms. Among women, in the 12 months preceding the survey, 15 percent reported that they had an STI; 15 percent had a bad-smelling, abnormal discharge; and 17 percent had a genital sore or ulcer. Among men, 8 percent reported that they had an STI; 5 percent had a bad-smelling, abnormal discharge; and 8 percent had a genital sore or ulcer. Taken together, over 1 in 4 women (27 percent) and 14 percent of men had either had an STI or symptoms of an STI during the 12 months preceding the survey. Table 13.13 Male circumcision Percentage of men age 15-49 who report having been circumcised, by background characteristics, Uganda 2011 Background characteristic Percentage circumcised Number of men Age 15-24 28.2 872 15-19 27.3 554 20-24 29.8 318 25-29 27.7 361 30-39 25.6 592 40-49 24.4 348 Residence Urban 40.2 439 Rural 23.4 1,734 Region Kampala 40.7 221 Central 1 22.5 209 Central 2 26.4 236 East Central 42.4 236 Eastern 36.6 289 Karamoja 18.7 55 North 4.2 199 West Nile 28.9 133 Western 29.5 322 Southwest 9.2 273 Religion Catholic 14.9 952 Protestant 19.9 695 Muslim 93.5 269 Pentecostal 21.9 185 SDA (22.2) 39 Ethnicity Baganda 30.3 356 Banyankole 17.9 218 Basoga 49.4 195 Bakiga 10.6 161 Itesa 7.8 152 Other 28.5 1,090 Total 15-49 26.8 2,173 50-54 27.2 122 Total 15-54 26.8 2,295 Note: Figures in parentheses are based on 25-49 unweighted cases. 206 • HIV/AIDS-Related Knowledge, Attitudes, and Behaviour Table 13.14 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, Uganda 2011 Background characteristic Women Men Percentage of women who reported having in the past 12 months: Number of women who ever had sexual intercourse Percentage of men who reported having in the past 12 months: Number of men who ever had sexual intercourseSTI Bad smelling/ abnormal genital discharge Genital sore/ulcer STI/ genital discharge/ sore or ulcer STI Bad smelling/ abnormal genital discharge Genital sore/ulcer STI/ genital discharge/ sore or ulcer Age 15-24 13.4 13.8 15.8 24.3 2,415 5.3 5.6 8.4 14.3 492 15-19 9.5 11.6 12.4 19.7 923 2.1 6.3 8.6 14.5 220 20-24 15.8 15.2 17.8 27.1 1,492 8.0 5.1 8.2 14.1 272 25-29 17.2 15.9 16.8 27.7 1,555 10.0 5.0 6.1 13.3 349 30-39 16.7 17.4 18.8 29.4 2,099 10.7 6.0 8.7 15.8 587 40-49 12.9 13.8 15.4 24.4 1,313 7.2 2.9 6.2 11.1 348 Marital status Never married 10.4 13.7 13.9 22.5 837 2.9 4.9 5.7 10.1 438 Married/living together 15.9 15.4 17.3 27.2 5,413 9.9 5.0 8.1 14.8 1,228 Divorced/separated/ widowed 14.4 16.0 16.6 25.9 1,133 12.4 6.9 9.0 19.3 111 Male circumcision Circumcised na na na na na 7.2 3.6 7.3 12.0 499 Not circumcised na na na na na 8.8 5.6 7.7 14.7 1,276 Residence Urban 18.4 17.6 17.7 28.9 1,454 6.5 3.2 4.9 10.0 377 Rural 14.2 14.7 16.6 25.9 5,929 8.9 5.6 8.3 15.0 1,400 Region Kampala 19.9 19.8 19.2 31.1 712 6.4 2.9 4.8 9.2 185 Central 1 17.7 20.6 19.4 32.7 821 11.8 8.6 5.5 16.2 174 Central 2 18.1 19.4 21.1 34.0 779 10.5 3.4 9.3 15.5 199 East Central 18.8 19.5 27.2 37.1 755 8.4 10.3 16.7 28.0 194 Eastern 10.8 10.9 12.0 21.2 1,095 9.6 8.3 10.4 17.6 236 Karamoja 1.1 0.5 0.2 1.1 253 2.5 2.1 2.1 2.5 48 North 4.0 4.8 7.2 10.0 628 2.2 1.7 4.4 5.4 169 West Nile 4.5 5.1 7.5 11.1 417 1.8 0.7 1.8 1.8 107 Western 22.2 21.4 24.4 35.0 1,070 12.6 3.9 5.2 14.1 264 Southwest 16.4 13.8 12.1 23.6 853 8.2 4.2 8.6 13.3 201 Education No education 12.8 13.9 15.8 23.0 1,087 8.7 7.8 7.0 16.2 85 Primary 15.4 15.7 17.7 27.6 4,374 9.3 6.1 8.5 16.0 1,048 Secondary + 15.5 15.0 15.1 25.9 1,922 6.8 3.1 6.2 10.4 644 Wealth quintile Lowest 8.3 9.5 12.7 18.2 1,358 9.5 4.7 6.4 13.3 289 Second 12.1 13.1 15.2 23.9 1,380 6.4 3.8 8.3 13.2 346 Middle 18.3 19.0 19.1 30.4 1,374 9.8 8.5 10.4 17.6 326 Fourth 18.3 17.4 19.6 30.8 1,403 8.6 6.1 8.4 15.6 393 Highest 17.4 16.7 17.1 28.2 1,867 8.0 2.7 5.0 10.6 423 Total 15-49 15.1 15.3 16.8 26.5 7,383 8.4 5.1 7.6 14.0 1,777 50-54 na na na na na 5.9 2.0 3.9 7.1 121 Total 15-54 na na na na na 8.2 4.9 7.4 13.5 1,897 na = Not applicable Among both women and men, the prevalence of STIs and STI symptoms was higher among the 30-39 age cohort (29 percent of women and 16 percent of men) and also among those living in the East Central region (37 percent of women and 28 percent of men). By wealth, for both men and women, those in the middle and fourth quintiles were slightly more likely than others to have reported STI infections or STI symptoms. There were variations among women in the prevalence of STIs or their symptoms by marital status, residence, and education. Women in urban areas were a little more likely than women in rural areas to have had an STI or STI symptoms. Women with no education (23 percent) and those that have never married (23 percent) had the lowest prevalence of STIs or STI symptoms. The prevalence of STIs by background characteristic differed for men. Among men, those living in rural areas were more likely to have an STI or STI symptoms compared with urban men. Formerly married men were more likely than married or non-married sexually active men to report an STI or STI symptom. Men with at least some secondary education have the lowest prevalence of STIs or STI symptoms. HIV/AIDS-Related Knowledge, Attitudes, and Behaviour • 207 13.10 TREATMENT OF SEXUALLY TRANSMITTED INFECTIONS 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 13.1 presents information on women and men who sought care from any source. Close to seven in ten women and men (69 percent of women and 67 percent of men) sought care for the STIs or symptoms of STIs from a clinic, hospital, or health professional. One percent of women and 4 percent of men sought advice or medicine from a shop, pharmacy, or drug vendor, while 5 percent of women and 4 percent of men sought treatment from another source. Twenty-six percent of women and 27 percent of men who had STIs or STI symptoms in the 12 months preceding the survey did not seek any advice or treatment. Among women, this is a reduction from the 32 percent of women that did not seek treatment as reported in the 2006 UDHS, but for men, it is an increase from 17 percent of men with an STI or STI symptom that did not seek advice treatment. Figure 13.1 Women and men seeking advice or treatment for STIs 69 1 5 26 67 4 4 27 Clinic/hospital/ private doctor/ other health Advice or medicine from shop/pharmacy Advice or treatment from any other source No advice or treatment Percentage of women Percentage of men professional 13.11 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. To measure the potential risk of transmission of HIV associated with medical injections, respondents in the 2011 UDHS were asked if they had received an injection in the past 12 months, and if so, the number of injections. Those who had received injections were further asked if the syringe and needle were taken from a new, previously unopened pack. It should be noted that self-administered medical injections (e.g., insulin injections for diabetes) were not included in the calculations. Table 13.15 shows that women are more likely than men to report receiving medical injections in the last 12 months (43 percent versus 26 percent). The percentage of women who received a medical injection in the past 12 months is highest among those age 25-29 (51 percent), most likely because of injections given to women during antenatal care or family planning visits. Younger women age 15-19 and older women age 40-49 have a lower proportion of medical injections. Conversely, older men, those age 40-49, are the most likely to have received a medical injection. There is little variation by residence in the proportion receiving injections for both women and men. For both men and women, a higher proportion of 208 • HIV/AIDS-Related Knowledge, Attitudes, and Behaviour those that are currently married report having received a medical injection in the last 12 months compared with others. Among the regions, women in East Central and Eastern regions are most likely to have received a medical injection (49 percent), while men living in the Central 1 region (34 percent) and the Eastern region (33 percent) are the most likely to have received a medical injection in the past 12 months. Injection prevalence for both women and men increases with education, but there is no strong pattern in reporting of medical injections by wealth status. Table 13.15 Prevalence of medical injections Percentage of women and men age 15-49 who received at least one medical injection in the last 12 months, the average number of medical injections per person in the last 12 months, and among those who received a medical injection, the percentage of last medical injections for which the syringe and needle were taken from a new, unopened package, by background characteristics, Uganda 2011 Background characteristic Women Men Percentage who received a medical injection in the last 12 months Average number of medical injections per person in the last 12 months Number of women For last injection, syringe and needle taken from a new, unopened package Number of women receiving medical injections in the last 12 months Percentage who received a medical injection in the last 12 months Average number of medical injections per person in the last 12 months Number of men For last injection, syringe and needle taken from a new, unopened package Number of men receiving medical injections in the last 12 months Age 15-24 41.0 1.5 3,677 96.9 1,506 22.7 1.1 872 95.3 198 15-19 35.5 1.4 2,048 96.2 727 21.1 1.0 554 96.1 117 20-24 47.8 1.7 1,629 97.5 779 25.5 1.3 318 94.2 81 25-29 50.8 1.9 1,569 97.3 798 25.2 1.5 361 94.9 91 30-39 43.4 2.1 2,112 97.1 916 28.4 1.5 592 95.3 168 40-49 37.1 2.1 1,316 95.7 488 33.1 2.3 348 89.3 115 Marital status Never married 32.2 1.2 2,123 97.1 683 21.4 1.0 834 95.4 178 Ever had sex 38.6 1.4 837 98.3 323 20.4 1.1 438 97.1 89 Never had sex 28.0 1.1 1,286 96.1 360 22.5 0.9 397 93.8 89 Married/Living together 47.4 2.0 5,418 96.9 2,567 30.6 1.8 1,228 93.1 376 Divorced/Separated/ Widowed 40.4 1.7 1,134 96.4 458 16.5 0.8 111 * 18 Residence Urban 44.1 1.8 1,717 97.6 757 25.7 1.3 439 97.5 113 Rural 42.4 1.8 6,957 96.7 2,952 26.5 1.5 1,734 93.2 459 Region Kampala 42.2 1.7 839 97.8 354 24.6 1.2 221 99.9 54 Central 1 43.9 1.5 956 95.7 419 33.5 2.2 209 95.3 70 Central 2 47.3 1.7 902 95.9 426 29.6 1.8 236 98.1 70 East Central 49.1 2.4 869 98.5 427 29.1 1.3 236 88.3 68 Eastern 48.7 2.7 1,267 95.8 616 33.3 1.7 289 95.7 96 Karamoja 47.4 1.5 289 98.4 137 25.3 0.9 55 (72.2) 14 North 41.6 1.7 735 98.6 306 30.1 1.5 199 93.3 60 West Nile 34.1 1.3 500 98.7 170 17.8 1.1 133 (96.6) 24 Western 40.1 1.7 1,221 97.1 490 21.5 1.0 322 96.4 69 Southwest 33.1 1.2 1,097 95.2 363 17.1 1.5 273 (87.0) 47 Education No education 36.9 2.0 1,120 96.9 413 25.4 3.8 90 (85.8) 23 Primary 42.7 1.8 5,152 97.2 2,202 25.2 1.4 1,309 95.2 330 Secondary + 45.5 1.8 2,402 96.3 1,094 28.3 1.3 774 93.1 219 Wealth quintile Lowest 41.9 2.0 1,519 97.0 637 26.2 1.3 345 89.1 90 Second 40.7 1.9 1,579 97.9 643 25.8 1.9 423 90.4 109 Middle 42.3 1.6 1,608 95.9 680 24.3 1.3 402 95.6 98 Fourth 45.0 1.7 1,726 96.4 777 26.0 1.3 486 95.2 126 Highest 43.4 1.8 2,242 97.2 972 28.7 1.4 517 97.6 149 Total 15-49 42.8 1.8 8,674 96.9 3,708 26.3 1.5 2,173 94.0 572 50-54 na na na na na 38.9 2.8 122 (96.7) 47 Total 15-54 na na na na na 27.0 1.5 2,295 94.2 620 Note: Medical injections are those given by a doctor, nurse, pharmacist, dentist, or other health worker. Figures in parentheses are based on 25-49 unweighted cases. An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. na = Not applicable HIV/AIDS-Related Knowledge, Attitudes, and Behaviour • 209 On average, women reported having 1.8 medical injections per person in the past 12 months. Men reported an average of 1.5 injections per person in the past year. The vast majority of respondents reported that the syringe and needle used for their last injection was taken from a new, unopened package (97 percent of women and 94 percent of men). More than 9 in 10 women and men in almost all subgroups who had had a medical injection reported that the syringe used for the last injection came from an unopened package. 13.12 HIV/AIDS KNOWLEDGE AND SEXUAL BEHAVIOUR AMONG YOUNG ADULTS This section addresses HIV/AIDS-related knowledge and behaviour among young adults 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. Special attention is paid to this group because it accounts for half of all new HIV infections worldwide (Ross et al., 2006). 13.12.1 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. Young respondents were asked the same set of questions on facts and beliefs about HIV transmission as other respondents. Table 13.16 shows the level of comprehensive knowledge of HIV/AIDS among young people and the percentage of young people who know a source for condoms. As discussed earlier in the chapter, comprehensive knowledge of HIV/AIDS is defined as knowing that both condom use and limiting sexual intercourse to one uninfected partner are HIV prevention methods, knowing that a healthy-looking person can have HIV, and rejecting the two most common local misconceptions about HIV transmission. Table 13.16 Comprehensive knowledge about AIDS and 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, Uganda 2011 Background characteristic Women 15-24 Men 15-24 Percentage with compre- hensive knowledge of AIDS1 Percentage who know a condom source2 Number of women Percentage with compre- hensive knowledge of AIDS1 Percentage who know a condom source2 Number of men Age 15-19 35.6 69.4 2,048 34.8 86.5 554 15-17 34.1 64.7 1,261 35.8 84.0 375 18-19 38.1 77.0 787 32.8 91.7 179 20-24 41.1 82.3 1,629 47.7 96.2 318 20-22 40.3 82.1 1,035 44.2 94.9 195 23-24 42.5 82.8 594 53.3 98.2 123 Marital status Never married 38.7 71.0 1,972 39.1 89.2 738 Ever had sex 43.0 83.9 713 43.0 97.7 359 Never had sex 36.3 63.7 1,260 35.3 81.1 380 Ever married 37.3 80.0 1,704 42.1 94.5 134 Residence Urban 48.4 89.3 812 56.7 94.4 189 Rural 35.2 71.1 2,865 34.8 88.8 683 Education No education 20.8 44.1 140 * * 13 Primary 30.0 67.2 2,218 31.8 86.0 537 Secondary + 53.5 91.8 1,318 53.4 97.5 322 Total 15-24 38.1 75.1 3,677 39.5 90.0 872 An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. 1 Comprehensive knowledge means knowing that consistent use of condoms during sexual intercourse and having just one uninfected faithful partner can reduce the chance of getting 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 13.2, 13.3.1, and 13.3.2 2 For this table, the following responses are not considered sources for condoms: friends, family members and home 210 • HIV/AIDS-Related Knowledge, Attitudes, and Behaviour Overall, approximately 4 in 10 Ugandans age 15-24 (38 percent of women and 40 percent of men) have comprehensive knowledge about AIDS. Comprehensive knowledge increases with age. For example, 34 percent of women age 15-17 have comprehensive knowledge about AIDS compared with 43 percent of those age 23-24. A similar pattern is observed for young men. Never-married young adults who have ever had sex are slightly more likely than their counterparts to have comprehensive knowledge about AIDS (43 percent of women and men). Comprehensive knowledge about AIDS is more prevalent among urban youth (48 percent of women and 57 percent of men) than rural youth (35 percent of women and men). The level of knowledge increases steadily with education. For example, one-fifth of young women (21 percent) with no education have comprehensive knowledge about AIDS, compared with more than half of women (54 percent) with at least some secondary education. 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 13.16, knowledge of a source for condoms is relatively common. Young men are more likely than young women to know where to obtain condoms (90 percent versus 75 percent). Variation by background characteristics is similar to the differences observed in comprehensive knowledge about AIDS. Older, urban, non-married but sexually active, and more educated youth are more likely than their counterparts to know a source of condoms. 13.12.2 Age at First Sexual Intercourse Because HIV transmission in Uganda occurs predominantly through sexual intercourse between an infected and a non-infected person, age at first intercourse marks the time at which most individuals first risk exposure to the virus. Age at first sex is also 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 13.17 shows the percentages of young women and men who had sexual intercourse before reaching age 15 and age 18, by background characteristics. About 14 percent of young women and 16 percent of young men in the age group 15-24 had their first sex early in life, i.e., before the age of 15. Nearly 6 in 10 young women (58 percent) and half of young men (47 percent) had had sex before age 18. HIV/AIDS-Related Knowledge, Attitudes, and Behaviour • 211 Table 13.17 Age at first sexual intercourse among young people Percentage of young women and young men age 15-24 who had sexual intercourse before age 15 and percentage of young women and young men age 18-24 who had sexual intercourse before age 18, by background characteristics, Uganda 2011 Background characteristic Women age 15-24 Women age 18-24 Men age 15-24 Men age 18-24 Percentage who had sexual intercourse before age 15 Number of women Percentage who had sexual intercourse before age 18 Number of women Percentage who had sexual intercourse before age 15 Number of men Percentage who had sexual intercourse before age 18 Number of men Age 15-19 12.2 2,048 na na 17.9 554 na na 15-17 11.5 1,261 na na 19.8 375 na na 18-19 13.3 787 57.0 787 13.8 179 52.9 179 20-24 16.1 1,629 57.9 1,629 12.8 318 42.9 318 20-22 15.3 1,035 58.6 1,035 12.3 195 46.8 195 23-24 17.5 594 56.8 594 13.7 123 36.7 123 Marital status Never married 8.0 1,971 33.6 829 15.4 738 44.4 365 Ever married 20.7 1,705 70.2 1,586 19.2 134 52.4 132 Knows condom source1 Yes 14.9 2,763 59.4 1,948 17.3 785 47.8 470 No 10.9 914 50.2 468 5.0 87 (23.5) 27 Residence Urban 15.5 812 52.5 577 17.9 189 54.0 132 Rural 13.5 2,865 59.2 1,839 15.5 683 43.8 365 Education No education 18.3 140 65.8 108 * 13 * 9 Primary 16.9 2,218 65.0 1,356 16.2 537 48.4 255 Secondary + 8.5 1,318 46.1 952 16.2 322 44.1 233 Total 13.9 3,677 57.6 2,416 16.0 872 46.5 497 Note: Figures in parentheses are based on 25-49 unweighted cases. An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. na = Not applicable 1 For this table, the following responses are not considered a source for condoms: friends, family members, and home. Among young women, the older age cohorts are more likely to have had sex before age 15 than are those who have reached those age milestones more recently. As expected, ever-married young women are much more likely than never-married young women to have had sexual intercourse before age 15 or 18. Twenty-one and 70 percent of ever-married young women had sexual intercourse before age 15 and 18, respectively, compared with 8 percent and 34 percent, respectively, of never-married women. Education has an inverse relationship with sexual debut among female youth. Young women with no schooling are twice as likely as those who go to secondary school to have had sex by age 15 (18 percent compared with 9 percent). Variation in young men’s sexual debut across background characteristics are small, except for variation observed with knowledge of condom source and marital status. Young men who know a condom source are almost 3.5 times more likely to have an early sexual debut than those who do not know a source of condoms (17 percent compared with 5 percent). Like women, ever-married young men are much more likely than never-married men to have had sexual intercourse before age 15 or 18. Figure 13.2 presents trends in age at first sexual intercourse among young people. The percentage of young people age 15-19 who have had sex by age 15 has remained stable for women (12 percent) but has slightly increased among men since 2006 (from 14 percent to 18 percent among young men). Similar trends are presented for those who had sexual intercourse before the age of 18. Fifty-eight percent of women age 18-19 reported that they had sexual intercourse before age 18 in the 2006 UDHS; this figure had remained the same (at 57 percent) in the 2011 UDHS. Among young men age 18-19, however, an increase is observed (from 44 percent in 2006 to 53 percent in 2011). 212 • HIV/AIDS-Related Knowledge, Attitudes, and Behaviour Figure 13.2 Trends in age at first sexual intercourse 12 14 58 44 12 18 57 53 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 sexual 2006 UDHS 2011 UDHS sexual intercourse before exact age 15 sexual intercourse before exact age 15 sexual intercourse before exact age 18 intercourse before exact age 18 13.12.3 Abstinence and Premarital Sex HIV control programmes in Uganda advocate delayed sexual debut as well as consistent condom use to reduce the risk of sexual transmission of HIV. Table 13.18 presents information on premarital sexual intercourse and condom use among never-married Ugandan youth age 15-24. Table 13.18 Premarital sexual intercourse and condom use during premarital sexual intercourse among young people Among never-married women and men age 15-24, the percentage who have never had sexual intercourse, the percentage who had sexual intercourse in the past 12 months, and, among those who had premarital sexual intercourse in the past 12 months, the percentage who used a condom at the last sexual intercourse, by background characteristics, Uganda 2011 Background characteristic Never-married women age 15-24 Never-married men age 15-24 Percentage who have never had sexual intercourse Percentage who had sexual intercourse in the past 12 months Number of never married women Among women who had sexual intercourse in the past 12 months: Percentage who have never had sexual intercourse Percentage who had sexual intercourse in the past 12 months Number of never married men Among men who had sexual intercourse in the past 12 months: Percentage who used a condom at last sexual intercourse Number of women Percentage who used a condom at last sexual intercourse Number of men Age 15-19 71.1 19.4 1,582 53.6 308 62.1 21.3 537 54.9 114 15-17 77.9 14.2 1,142 55.0 162 70.5 14.4 373 45.5 54 18-19 53.3 33.0 440 52.1 145 43.1 37.2 163 63.1 61 20-24 34.5 44.7 389 53.5 174 22.9 51.9 202 71.3 105 20-22 37.9 43.6 283 50.3 123 29.9 47.3 145 68.2 68 23-24 25.5 47.7 107 61.1 51 5.3 63.6 57 (77.1) 36 Knows condom source1 Yes 57.3 30.3 1,400 55.8 425 46.8 33.0 658 63.2 218 No 79.9 10.0 571 37.4 57 89.7 1.9 80 * 2 Residence Urban 49.8 35.2 496 54.7 174 33.9 44.9 162 73.1 73 Rural 68.6 20.8 1,475 52.9 307 56.3 25.4 576 57.6 146 Education No education 70.2 14.9 44 * 6 56.2 * 8 * 3 Primary 71.2 17.3 1,070 52.2 185 57.2 26.7 447 49.5 119 Secondary + 54.3 33.8 858 55.3 290 42.2 34.3 284 78.6 97 Total 15-24 63.8 24.4 1,971 53.6 482 51.4 29.7 738 62.7 219 Note: Figures in parentheses are based on 25-49 unweighted cases. An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. 1 For this table, the following responses are not considered a source for condoms: friends, family members and home. HIV/AIDS-Related Knowledge, Attitudes, and Behaviour • 213 Sixty-four percent of never-married young women and 51 percent of never-married young men have never had sexual intercourse. The percentage of never-married young people who have never had sex declines rapidly with age; 78 percent of young women and 71 percent of young men age 15-17 report that they have not yet had sexual intercourse compared with 26 percent of women age 23-24 and 5 percent of men age 23-24. Abstinence rates are highest among those that do not know a condom source and rural respondents and respondents with less than secondary education. Overall, one-quarter of never-married young women (24 percent) and 3 in 10 never-married young men report that they had sexual intercourse in the past 12 months. Among those who had sex in the past year, 54 percent of women and 63 percent of men reported using a condom during their last sexual intercourse. Differentials by background characteristics in the percentages of never-married young people using condoms during their most recent sexual intercourse in the past 12 months are not large, with the exception of knowledge of condom source. Not surprisingly, reported condom use at last sexual encounter is more common among those who know a condom source. Condom use at last sexual intercourse is also more common among never-married young women and young men in urban areas (55 percent and 73 percent, respectively) than among those in rural areas (53 percent and 58 percent, respectively). The proportion of never-married youth who report having used a condom at their last sexual intercourse has increased since the 2006 UDHS, from 56 percent of men age 15-24 to 63 percent of men age 15-24 as measured in the 2011 UDHS. Similarly, reported condom use among female youth has also increased in the past five years, from 39 percent of women age 15-24 as measured in the 2006 UDHS to 54 percent of women age 15-24. 13.12.4 Multiple Partnerships Among Young Adults Table 13.19 presents 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 13.19 Multiple sexual partners in the past 12 months among young people Among all young women and men age 15-24, the percentage who had sexual intercourse with more than one sexual partner in the past 12 months, by background characteristics, Uganda 2011 Background characteristic Percentage who had 2+ partners in the past 12 months Number of women Percentage who had 2+ partners in the past 12 months Number of men Age 15-19 1.5 2,048 5.4 554 15-17 1.1 1,261 3.5 375 18-19 2.1 787 9.2 179 20-24 2.7 1,629 15.0 318 20-22 3.1 1,035 16.5 195 23-24 2.1 594 12.7 123 Marital status Never married 1.5 1,971 6.2 738 Ever married 2.7 1,705 23.6 134 Knows condom source1 Yes 2.4 2,763 9.5 785 No 1.1 914 3.9 87 Residence Urban 3.2 812 18.0 189 Rural 1.7 2,865 6.4 683 Education No education 1.7 140 * 13 Primary 1.9 2,218 8.2 537 Secondary + 2.3 1,318 9.2 322 Total 15-24 2.1 3,677 8.9 872 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 214 • HIV/AIDS-Related Knowledge, Attitudes, and Behaviour Data show that 2 percent of women age 15-24 had sexual intercourse with more than one partner in the past 12 months. There is minimal 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, more than one-quarter (27 percent) reported using a condom at last intercourse (data not shown). A total of 9 percent of men age 15-24 had sexual intercourse with two or more partners in the past 12 months. Young men in their twenties, those who have ever married, and those in urban areas are more likely to have had more than one partner in the previous 12 months. Among young men who had one or more sex partners in the past year, almost half (47 percent) reported using a condom at last sexual intercourse (data not shown). 13.12.5 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 UDHS 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 13.20. Table 13.20 Age-mixing in sexual relationships among women age 15-19 Among women age 15-19 who had sexual intercourse in the past 12 months, percentage who had sexual intercourse with a partner who was 10 or more years older than themselves, by background characteristics, Uganda 2011 Background characteristic Women age 15-19 who had sexual intercourse in the past 12 months Percentage who had sexual intercourse with a man 10+ years older Number of women Age 15-17 8.9 280 18-19 15.7 468 Marital status Never married 4.3 308 Ever married 19.4 441 Knows condom source1 Yes 14.0 587 No 10.2 161 Residence Urban 13.7 142 Rural 13.0 606 Education No education (24.2) 31 Primary 13.4 502 Secondary + 11.1 216 Total 13.2 748 Note: Figures in parentheses are based on 25-49 unweighted cases. 1 For this table, the following responses are not considered a source for condoms: friends, family members, and home Overall, 13 percent of women age 15-19 who had had sexual intercourse in the past 12 months had sex with a man 10 or more years older than they were. Young women age 18-19, those who have ever been married, and women who know a source of condoms are more likely than other women to have had sex with a man 10 or more years older than they are. HIV/AIDS-Related Knowledge, Attitudes, and Behaviour • 215 13.12.6 Recent HIV Testing among Youth Knowledge of one’s HIV serostatus can motivate a person to protect himself or 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 counseling and testing. The 2011 UDHS asked respondents age 15-24 who had had sexual intercourse in the past 12 months whether they had been tested for HIV and received their test results. Table 13.21 shows these data. Table 13.21 Recent HIV tests among young people Among young women and young men age 15-24 who have had sexual intercourse in the past 12 months, the percentage who were tested for HIV in the past 12 months and received the results of the last test, by background characteristics, Uganda 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 in the past 12 months and received the results of the last test Number of women Percentage who have been tested for HIV in the past 12 months and received the results of the last test Number of men Age 15-19 49.1 748 25.9 130 15-17 41.6 280 21.9 55 18-19 53.6 468 28.9 74 20-24 54.8 1,349 36.2 220 20-22 56.1 834 36.7 118 23-24 52.7 515 35.6 101 Marital status Never married 49.4 482 32.5 219 Ever married 53.8 1,615 32.2 130 Knows condom source1 Yes 56.1 1,726 32.7 340 No 37.5 371 * 9 Residence Urban 56.2 473 36.8 98 Rural 51.8 1,624 30.7 251 Education No education 36.6 92 * 8 Primary 48.6 1,269 25.5 206 Secondary + 62.0 735 42.9 135 Total 52.8 2,097 32.4 349 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 Nationally, more than 5 in 10 young women (53 percent) and about 3 in 10 young men (32 percent) who had had sexual intercourse in the last year had been tested for HIV in the past 12 months and received the results of the test. Older youth, urban residents, 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. Among young women, the percentage who were recently tested for HIV and received the results is higher among those who ever married (54 percent) than those who never married (49 percent) and among young women who know of a condom source (56 percent) than those who don’t know of a source (38 percent). Recent HIV testing among youth has dramatically increased in Uganda in recent years. In the 2006 UDHS, 17 percent of young women and 13 percent of young men who had had sexual intercourse in the past 12 months had been tested for HIV and received results. This represents a three-fold increase among women that have been tested and received their test results and more than a doubling of the percentage of young men who have been tested and received results. Women’s Empowerment and Demographic and Health Outcomes • 217 WOMEN’S EMPOWERMENT AND DEMOGRAPHIC AND HEALTH OUTCOMES 14 his chapter presents new data on the status of women in Uganda. Topics address gender differences in employment, access to and control over cash earnings, asset ownership, participation in household decision making, and the relative earnings of husbands and wives. The chapter also explores how demographic and health indicators vary by women’s empowerment, as measured by the number of decisions in which the woman participates and her ability to negotiate safer sexual relations with her husband. The 2011 UDHS survey analyzes and reports on these relationships and offers comparisons with data from the 2006 UDHS. Three separate indices of empowerment were developed based on (1) the number of household decisions in which the respondent participates: (2) her opinion of the circumstances under which a woman is justified in refusing to have sexual intercourse with her husband/partner, and (3) her opinion of whether specific actions justify wife beating. The relationship of these indices with selected demographic and health outcomes is analyzed. The ranking of women on the indices is associated with outcomes that include contraceptive use, need for family planning, and access to reproductive health care. 14.1 EMPLOYMENT AND FORM OF EARNINGS Employment, particularly employment for cash, and control over how earnings are used are important indicators of empowerment. Currently married respondents were asked whether they were employed at the time of the survey and, if not, whether they were employed in the 12 months that preceded the survey. Table 14.1 shows the percentage of currently married women and men age 15-49 who were employed at any time in the 12 months before the survey and the percent distribution of employed women and men by type of earnings they received (cash only, cash and in-kind, in-kind only). Overall, 79 percent of currently married women and 99 percent of currently married men age 15-49 were employed at some time in the year prior to the survey. The percentage of currently employed married women increases with age and peaks at 87 percent among those age 35-39. All married men younger than age 25 are employed, and this percentage decreases only slightly at older ages. The traditional role of men as breadwinners and the differences in employable skills between women and men may explain the gender differential in the rate of employment. There has T Key Findings  More than half of currently married employed women (53 percent) who earn cash mainly make independent decisions about how to spend their earnings.  About four in ten women own a house and/or land, mostly jointly with their husband.  Only 38 percent of currently married women participate in all three decisions pertaining to their own health care, major household purchases, and visits to their family or relatives.  Close to six in ten women (58 percent) believe that wife beating is justified for at least one of the specified reasons, a decline from seven in ten women in the 2006 UDHS.  Contraceptive use increases with women’s empowerment. 218 • Women’s Empowerment and Demographic and Health Outcomes been a general decline in the level of employment from 2006 to 2011, with women affected more than men. Employment among currently married women declined by more than 10 percent from the 2006 level (92 percent in 2006 and 79 percent in 2011) compared with men where the decline was less than 1 percent (100 percent in 2006 and 99 percent in 2011). Employed women and men differ in the type of earnings they receive for their work, with married men being more likely to be paid for their work than women. A quarter of the women were not paid for the work they performed (25 percent) compared with only a tenth of the men (12 percent). Overall participation in the cash only economy has increased over the last five years, more than doubling among women and almost doubling among men. In 2006 less than 20 percent of women were paid in cash only, compared with 49 percent in 2011; the increase for men was from 34 percent in 2006 to 62 percent in 2011. There is an inverse relationship between age and payment in only cash for men, with payment decreasing as age increases. At older ages the gap between the sexes in cash earnings narrows. 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, Uganda 2011 Age Among currently married respondents: Percent distribution of currently married respondents employed in the past 12 months, by type of earnings Total Number of respondents Percentage employed Number of respondents Cash only Cash and in-kind In-kind only Not paid WOMEN 15-19 66.6 409 42.7 16.6 5.8 34.9 100.0 272 20-24 71.5 1,097 47.7 17.3 3.8 31.2 100.0 785 25-29 78.5 1,295 53.1 20.6 3.9 22.3 100.0 1,017 30-34 81.7 880 49.9 21.3 6.3 22.6 100.0 719 35-39 87.1 820 47.1 27.0 3.3 22.7 100.0 715 40-44 86.8 553 50.6 21.7 3.9 23.7 100.0 480 45-49 83.8 364 49.4 20.7 6.1 23.8 100.0 305 Total 79.2 5,418 49.4 21.1 4.5 25.1 100.0 4,293 MEN 15-19 * 10 * * * * 100.0 10 20-24 100.0 101 60.2 24.9 1.9 13.0 100.0 101 25-29 98.8 270 66.6 22.8 1.4 9.1 100.0 267 30-34 99.9 282 64.0 21.1 2.5 12.4 100.0 282 35-39 99.0 242 62.4 27.1 1.2 9.3 100.0 240 40-44 98.0 179 53.9 27.9 4.4 13.8 100.0 176 45-49 98.2 143 58.0 22.8 3.7 15.6 100.0 140 Total 15-49 99.0 1,228 61.8 24.1 2.3 11.8 100.0 1,216 50-54 95.0 109 57.1 30.2 1.6 11.1 100.0 104 Total 15-54 98.7 1,338 61.5 24.5 2.3 11.7 100.0 1,320 An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. 14.2 WOMEN’S CONTROL OVER THEIR OWN EARNINGS AND RELATIVE MAGNITUDE OF WOMEN’S AND THEIR HUSBAND’S EARNINGS Control over cash earnings is another dimension of empowerment. Currently married and employed women were asked about the relative magnitude of their earnings compared with their husband’s or partner’s earnings. In addition, they were asked who decides how the cash earnings are used. This information provides insight into women’s empowerment within the family, their autonomy, and the extent of their control over resources. It is expected that employment and earnings are more likely to empower women if women themselves control their own earnings and if they perceive them as significant relative to those of their husbands or partners. Table 14.2.1 shows the percent distribution of currently married women age 15-49 who received cash earnings for employment in the 12 months preceding the survey. The distribution is by the person who decides how the cash earnings are to be used and by the relative magnitude of their earnings compared with those of their husbands, according to background characteristics. Women do not have total control Women’s Empowerment and Demographic and Health Outcomes • 219 over their earnings. Slightly more than half (53 percent) of the currently married women who earn cash said that they are the main decision makers for how their cash earnings are used—a 2 percentage point decline compared with 2006 data; three in ten (31 percent) indicated that the decisions are made jointly, and 14 percent said that the decisions are mainly made by their husband. Older women are more likely to have control over their cash earnings than younger women. Urban women exercise more influence over how their cash earnings are used than rural women (67 percent and 49 percent, respectively). Women with no children are least likely to be the main decision maker with regard to spending their cash earnings. Joint decisions on cash earnings are more frequent among rural married women than among their counterparts in urban areas (33 percent compared with 22 percent). The percentage of women with primary control over their earnings ranged from 35 percent in the Southwest to 78 percent in Kampala. It is expected that women would gain more control over their cash earnings with more education; the survey results revealed that among women with no education 49 percent control their cash earnings compared with 58 percent of women with more than secondary education. Differences by wealth quintiles are pronounced between the lowest (52 percent) and the highest (62 percent) quintiles. Less than 10 percent of women in the highest wealth quintile say their husband is the main decision maker on use of her cash earnings. Table 14.2.1 Control over women's cash earnings and relative magnitude of women's cash earnings: Women Percent distribution of currently married women age 15-49 who received cash earnings for employment in the 12 months preceding the survey by person who decides how wife's cash earnings are used and by whether she earned more or less than her husband, according to background characteristics, Uganda 2011 Background characteristic Person who decides how the wife's cash earnings are used: Total Wife's cash earnings compared with husband's cash earnings: Total Number of women Mainly wife Wife and husband jointly Mainly husband Other Missing More Less About the same Husband has no earnings Don't know/ Missing Age 15-19 44.1 30.5 20.5 0.3 4.6 100.0 7.8 81.0 4.4 1.0 5.8 100.0 161 20-24 52.0 28.7 18.0 0.2 1.1 100.0 4.8 83.8 7.3 0.7 3.4 100.0 510 25-29 50.9 30.5 15.5 0.6 2.5 100.0 10.5 76.0 7.1 0.7 5.7 100.0 750 30-34 55.5 29.9 12.4 0.3 1.8 100.0 7.8 79.2 8.6 0.3 4.1 100.0 512 35-39 51.2 33.1 13.3 0.0 2.4 100.0 10.0 73.0 10.1 1.7 5.2 100.0 529 40-44 56.2 33.1 10.0 0.0 0.7 100.0 13.3 69.8 10.3 3.4 3.2 100.0 347 45-49 58.7 30.9 10.2 0.0 0.2 100.0 14.4 66.1 14.3 1.6 3.7 100.0 214 Number of living children 0 47.5 32.9 17.0 0.4 2.2 100.0 7.8 78.5 7.4 2.3 4.1 100.0 147 1-2 54.5 29.6 12.5 0.4 3.0 100.0 8.0 78.4 7.5 0.4 5.7 100.0 828 3-4 54.0 27.6 16.1 0.2 2.1 100.0 8.7 76.8 7.6 1.5 5.4 100.0 857 5+ 51.2 33.9 13.9 0.1 0.9 100.0 11.2 73.9 10.4 1.4 3.1 100.0 1,192 Residence Urban 66.7 21.7 5.4 0.5 5.7 100.0 7.9 75.4 5.0 1.1 10.4 100.0 585 Rural 49.4 33.1 16.4 0.2 1.0 100.0 9.8 76.3 9.5 1.2 3.1 100.0 2,438 Region Kampala 77.5 17.8 4.8 0.0 0.0 100.0 4.8 86.1 3.6 1.2 4.3 100.0 252 Central 1 57.5 24.1 18.4 0.0 0.0 100.0 6.6 81.8 7.5 1.4 2.6 100.0 314 Central 2 68.7 18.3 12.5 0.5 0.0 100.0 8.2 81.4 7.6 0.8 2.0 100.0 429 East Central 60.9 19.8 18.9 0.5 0.0 100.0 11.9 78.1 4.9 1.4 3.8 100.0 272 Eastern 44.4 31.9 23.7 0.0 0.0 100.0 12.3 73.0 11.2 0.6 2.9 100.0 269 Karamoja 68.6 22.7 7.4 0.9 0.4 100.0 13.3 44.2 15.9 8.1 18.5 100.0 105 North 36.7 47.0 13.9 0.6 1.8 100.0 15.1 72.6 9.9 0.5 1.9 100.0 267 West Nile 66.8 24.1 7.9 0.0 1.2 100.0 10.2 79.9 5.1 0.8 4.0 100.0 200 Western 37.5 40.2 14.0 0.2 8.1 100.0 7.8 69.8 13.0 0.8 8.7 100.0 607 Southwest 35.0 49.8 15.3 0.0 0.0 100.0 9.9 80.1 6.9 1.3 1.8 100.0 309 Education No education 48.7 32.5 18.2 0.1 0.4 100.0 9.4 68.3 15.2 2.7 4.4 100.0 466 Primary 51.4 30.7 16.5 0.2 1.2 100.0 9.9 77.7 8.2 0.9 3.4 100.0 1,773 Secondary + 58.2 30.4 6.8 0.4 4.2 100.0 8.5 77.5 5.9 0.9 7.2 100.0 785 Wealth quintile Lowest 51.8 31.7 16.0 0.1 0.4 100.0 10.5 70.2 12.5 1.5 5.3 100.0 462 Second 47.1 34.3 17.0 0.3 1.3 100.0 12.3 70.6 11.6 2.5 2.9 100.0 597 Middle 47.9 32.2 18.5 0.3 1.0 100.0 10.1 78.8 7.4 0.5 3.1 100.0 578 Fourth 51.6 33.1 14.5 0.1 0.6 100.0 8.4 79.8 8.9 0.9 2.0 100.0 611 Highest 62.0 25.1 7.8 0.3 4.8 100.0 6.9 79.1 4.8 0.8 8.3 100.0 776 Total 52.7 30.9 14.3 0.2 1.9 100.0 9.4 76.2 8.7 1.2 4.5 100.0 3,023 220 • Women’s Empowerment and Demographic and Health Outcomes Regarding the magnitude of a woman’s cash earnings relative to those of her husband or partner, about three in four employed women (76 percent) reported that their cash earnings were less than those of their husbands/partners; only 1 percent reported that their husbands did not have any earnings. The North region had the highest percentage of women (15 percent) who perceived their cash earnings to be more than the earnings of their husbands or partners, followed by Karamoja region, with 13 percent of the women believing their earnings were more than those of their partners. The data also reveal that education does not bring about gender equality in cash earnings. Regardless of education, , only 8-9 percent of women perceived their cash earnings to exceed those of their husbands. Gender disparities in cash earnings widen as wealth increases and appear biased against women. Only 7 percent of the women in the highest wealth quintile perceived their cash earnings to be more than their husbands or partners and only 5 percent in the same quintile perceived their cash earnings to be the same as that of their husbands or partners. Compared with the results of the 2006 UDHS, a similar proportion of women continue to perceive that they earn less than men. 14.3 WOMEN’S CONTROL OVER HUSBANDS’ EARNINGS Table 14.2.2 shows the percent distribution of currently married men age 15-49 who receive cash earnings and of currently married women age 15-49 whose husbands receive cash earnings by the person who decides how men’s earnings are used, according to background characteristics. Women’s and men’s reports on who decides how the husband’s cash earnings will be used are not the same. Fifty-four percent of women whose husbands have cash earnings report that their husband mainly decides on how his cash earnings are used. This differs from the 39 percent reported by the men themselves. There is no clear pattern by age for women; however, older men are less likely to report that they themselves mainly decide on how their cash earnings are used. The pattern of reporting for women and men differs by residence. A higher percentage of urban men (45 percent) compared with rural men (38 percent) report that they are the main decision makers on how their cash earnings are used. Men and women from the North region reported the highest prevalence of joint decision making on how the husband’s cash earnings were used (83 percent of married men and 55 percent of married women). The percentage of men who reported that they are the main decision maker decreased with the level of education. Conversely, joint decision making increased with education among men. Six in ten married men (59 percent) with at least some secondary education reported that the use of their cash earnings was jointly decided upon compared with 51 percent of men with no education. There is little difference by education for women with respect to joint decision making about their husbands’ cash earnings. Men in the lowest wealth quintile are more likely (64 percent) to jointly decide with their wives how their cash earnings will be used compared with men in the highest quintile (52 percent). The difference in reporting on joint decision making by women does not vary much by wealth quintile. Women’s Empowerment and Demographic and Health Outcomes • 221 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, Uganda 2011 Background characteristic Men Women Mainly wife Husband and wife jointly Mainly husband Other Total Number of men Mainly wife Husband and wife jointly Mainly husband Other Missing Total Number of women Age 15-19 0.0 37.9 45.0 17.1 100.0 8 8.6 39.1 51.5 0.8 0.0 100.0 396 20-24 6.2 48.1 45.7 0.0 100.0 86 6.8 39.6 53.3 0.0 0.3 100.0 1,091 25-29 4.8 52.5 42.8 0.0 100.0 238 7.4 37.1 55.0 0.4 0.1 100.0 1,286 30-34 8.2 55.1 36.6 0.0 100.0 240 6.6 35.0 58.0 0.1 0.3 100.0 873 35-39 3.4 56.3 40.3 0.0 100.0 215 7.7 38.0 54.1 0.1 0.1 100.0 809 40-44 1.3 64.1 34.6 0.0 100.0 144 10.4 36.9 52.1 0.4 0.2 100.0 536 45-49 4.9 58.5 36.6 0.0 100.0 113 10.3 36.2 53.4 0.0 0.0 100.0 356 Number of living children 0 10.5 40.9 46.2 2.4 100.0 61 8.8 41.3 49.5 0.5 0.0 100.0 328 1-2 4.5 53.7 41.8 0.0 100.0 267 7.6 39.9 52.0 0.2 0.3 100.0 1,526 3-4 5.5 53.5 41.0 0.0 100.0 278 7.9 36.4 55.4 0.1 0.2 100.0 1,456 5+ 4.0 60.3 35.8 0.0 100.0 439 7.8 35.8 56.1 0.2 0.1 100.0 2,037 Residence Urban 5.2 49.5 45.3 0.0 100.0 205 6.6 37.6 55.7 0.1 0.1 100.0 883 Rural 4.8 57.2 37.8 0.2 100.0 840 8.0 37.4 54.1 0.2 0.2 100.0 4,464 Region Kampala 1.8 40.7 57.5 0.0 100.0 90 6.1 35.2 58.7 0.0 0.0 100.0 394 Central 1 4.4 44.7 50.8 0.0 100.0 103 8.2 31.6 59.6 0.3 0.3 100.0 554 Central 2 9.6 50.3 40.2 0.0 100.0 119 7.6 29.1 63.1 0.0 0.3 100.0 561 East Central 1.1 61.6 37.3 0.0 100.0 110 6.0 27.3 66.3 0.2 0.2 100.0 571 Eastern 8.2 49.3 41.5 1.0 100.0 148 10.5 34.0 54.9 0.7 0.0 100.0 849 Karamoja 2.9 44.2 52.8 0.0 100.0 24 23.9 38.4 37.5 0.2 0.0 100.0 199 North 0.0 82.8 17.2 0.0 100.0 106 4.8 55.4 39.1 0.5 0.2 100.0 485 West Nile 34.9 38.0 26.6 0.0 100.0 27 9.1 30.4 60.1 0.0 0.4 100.0 321 Western 3.0 65.8 31.2 0.0 100.0 183 4.9 41.0 53.8 0.2 0.2 100.0 738 Southwest 3.3 51.5 45.2 0.0 100.0 136 6.8 50.0 43.2 0.0 0.0 100.0 674 Education No education 4.8 51.1 44.1 0.0 100.0 57 9.5 38.8 51.6 0.1 0.0 100.0 852 Primary 4.5 54.0 41.2 0.2 100.0 616 7.8 36.0 55.7 0.3 0.2 100.0 3,277 Secondary + 5.5 59.1 35.4 0.0 100.0 372 6.7 40.4 52.8 0.0 0.2 100.0 1,218 Wealth quintile Lowest 6.4 64.4 28.4 0.8 100.0 170 11.1 37.8 51.0 0.0 0.0 100.0 1,038 Second 3.7 62.5 33.9 0.0 100.0 202 8.3 40.5 50.5 0.3 0.4 100.0 1,079 Middle 3.8 53.0 43.2 0.0 100.0 211 5.9 37.8 55.7 0.5 0.1 100.0 1,036 Fourth 7.8 49.8 42.4 0.0 100.0 225 7.4 34.3 58.0 0.3 0.1 100.0 988 Highest 3.0 51.6 45.4 0.0 100.0 236 6.5 36.8 56.5 0.0 0.2 100.0 1,206 Total 15-49 4.9 55.7 39.3 0.1 100.0 1,045 7.8 37.5 54.4 0.2 0.2 100.0 5,347 50-54 0.0 62.0 38.0 0.0 100.0 91 na na na na na na na Total 15-54 4.5 56.2 39.2 0.1 100.0 1,136 na na na na na na na na = Not applicable Table 14.3 shows, for currently married women who earned cash in the last 12 months, the person who decided how their cash earnings would be used. It also shows, for currently married women whose husbands earned cash in the past 12 months, the person who decided how their husband’s cash earnings would be used. Overall slightly more than 50 percent of those who earn the money are the main decision makers, irrespective of the relative magnitude of their cash earnings compared with those of their partners. Joint decisions about the use of the wife’s and the husband’s earnings are most likely when wives and husbands receive the same amount of cash earnings (69 percent and 72 percent, respectively). Gender equality in control over cash earnings is likely to bring about better resource utilization that will lead to better household welfare. 222 • Women’s Empowerment and Demographic and Health Outcomes Table 14.3 Women's control over their own earnings and over those of their husbands Percent distribution of currently married women age 15-49 with cash earnings in the last 12 months by person who decides how the wife's cash earnings are used and percent distribution of currently married women age 15-49 whose husbands have cash earnings by person who decides how the husband's cash earnings are used, according to the relation between wife's and husband's cash earnings, Uganda 2011 Women's earnings relative to husband's earnings Person who decides how the wife's cash earnings are used: Total Number of women Person who decides how husband's cash earnings are used: Total Number of women Mainly wife Wife and husband jointly Mainly husband Other Missing Mainly wife Wife and husband jointly Mainly husband Other Missing More than husband 63.9 25.6 9.9 0.6 0.0 100.0 285 16.6 33.2 50.0 0.2 0.0 100.0 285 Less than husband 55.1 28.6 16.2 0.1 0.0 100.0 2,303 7.4 34.5 58.0 0.2 0.0 100.0 2,303 Same as husband 22.1 69.4 8.3 0.1 0.0 100.0 262 4.2 71.8 24.0 0.0 0.0 100.0 262 Husband has no cash earnings or did not work 75.9 16.9 3.9 0.0 3.2 100.0 36 na na na na na na na Woman worked but has no cash earnings na na na na na na na 8.2 41.4 50.1 0.3 0.1 100.0 1,254 Woman did not work na na na na na na na 5.7 32.6 60.9 0.4 0.4 100.0 1,105 Don't know/ Missing 41.7 10.8 5.3 1.5 40.6 100.0 137 16.0 35.0 47.2 0.0 1.8 100.0 137 Total1 52.7 30.9 14.3 0.2 1.9 100.0 3,023 7.8 37.5 54.4 0.2 0.2 100.0 5,347 na = Not applicable 1 Includes cases where a woman does not know whether she earned more or less than her husband 14.4 WOMEN’S EMPOWERMENT Amid persistent gender inequality, the government of Uganda is committed to improvement of gender development as evidenced by the 2007 Uganda Gender Policy (Ministry of Gender, Labour, and Social Development, 2007) and the National Development Plan 2010/11-2014/15 (Republic of Uganda, 2010). The goal of the policy is to achieve gender equality and women's empowerment as an integral part of Uganda's socioeconomic development. The National Development Plan observes that discrimination against women in Uganda results from traditional rules and practices that explicitly exclude women or give preference to men, which serves as a key constraint on women’s empowerment and economic progress. The plan has strategies to address gender-related constraints to development and suggests how to mainstream gender-neutral policies, plans, and programmes. In addition to educational attainment, employment status, and control over cash earnings, information was obtained in the survey on some direct measures of women’s autonomy and status. Specifically, questions were asked on ownership of assets, participation in household decision making, acceptance of wife beating, and conditions that justified denial of sex to one’s husband. The answers provided insight into women’s control over their environment and their attitudes toward gender roles, both of which are relevant to understanding women’s demographic and health behaviour. 14.4.1 Ownership of Assets Ownership and control of assets by women and men influence their individual participation in development processes at all levels. Lack of assets makes women vulnerable to various forms of violence and lessens their decision-making power in the household. Tradition and low economic status limit women’s ownership of productive assets such as land and housing. Ownership of assets confers additional economic value, status, and bargaining power. Table 14.4.1 shows the percent distribution of women age 15-49 by ownership of a house and land, according to background characteristics. Owning a house is more common among women than owning land. Overall, 44 percent of women own a house and 39 percent own land. The majority who do own assets own them jointly; 29 percent of women own a house jointly and 25 percent own land jointly. There are variations in level of ownership of a house and land by age, residence, region, education, and wealth. Ownership of houses and land increases with age. Ninety percent of young women age 15-19 do not own land or a house. Individual ownership of a house or land is more common in the rural than in the urban areas. Seventy-eight percent of urban women versus 51 percent of rural women do not own a house. More urban women (72 percent) than rural women (59 percent) do not own land. Women’s Empowerment and Demographic and Health Outcomes • 223 Thirty percent of women in Karamoja region own a house alone and 12 percent own land alone; these percentages are among the highest of the regions. The highest percentages of women who own neither a house nor land are in Kampala, at 83 percent and 75 percent, respectively. The chances of owning either a house or land decrease with increasing education. The percentage of women with secondary education without a house (72 percent) is more than double that of those with no education (32 percent). Seventy-six percent of women in the highest quintile have no house compared with 36 percent in the lowest quintile. Furthermore, 70 percent of women in the highest quintile have no land compared with 50 percent of women in the lowest quintile. The results of the survey reveal that tradition is likely to play a bigger part in asset ownership than the socioeconomic status of the women. These results could be explained with the fact that respondents who live in urban areas are more educated and wealthier than their rural counterparts, and are probably also more likely to rent a place to live and to not own any land in the urbanized areas where they live when compared with those in rural areas. 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, Uganda 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 Number of women Alone Jointly Alone and jointly Alone Jointly Alone and jointly Age 15-19 1.4 7.6 0.6 90.4 100.0 2.6 7.1 1.0 89.3 100.0 2,048 20-24 4.2 26.8 4.6 64.3 100.0 6.7 21.4 2.8 69.0 100.0 1,629 25-29 6.1 36.2 6.4 51.1 100.0 8.9 31.1 4.1 55.8 100.0 1,569 30-34 11.0 37.8 8.8 42.4 100.0 11.0 31.1 7.1 50.7 100.0 1,086 35-39 15.7 45.1 7.7 31.6 100.0 15.9 38.2 5.3 40.6 100.0 1,026 40-44 19.0 36.8 9.5 34.5 100.0 18.0 30.4 8.1 43.3 100.0 729 45-49 28.0 37.4 8.3 26.2 100.0 24.7 35.1 6.0 34.3 100.0 587 Residence Urban 6.7 13.5 2.1 77.6 100.0 9.9 14.8 2.8 72.4 100.0 1,717 Rural 9.5 32.9 6.4 51.1 100.0 9.9 27.1 4.4 58.5 100.0 6,957 Region Kampala 6.4 9.7 0.8 83.0 100.0 10.0 12.6 2.7 74.8 100.0 839 Central 1 8.3 15.3 3.8 72.6 100.0 12.2 12.7 3.3 71.6 100.0 956 Central 2 11.1 17.8 3.3 67.7 100.0 11.5 14.9 3.0 70.7 100.0 902 East Central 6.9 35.5 3.0 54.0 100.0 9.4 26.2 1.8 62.0 100.0 869 Eastern 7.9 35.5 6.8 49.7 100.0 7.1 26.6 3.2 63.1 100.0 1,267 Karamoja 29.5 27.2 6.8 36.5 100.0 11.7 21.8 8.2 58.3 100.0 289 North 9.2 51.6 6.2 32.9 100.0 8.0 48.2 4.8 39.0 100.0 735 West Nile 7.3 37.7 2.9 52.0 100.0 7.4 29.9 6.0 56.6 100.0 500 Western 9.8 28.5 5.3 56.2 100.0 11.6 25.1 5.7 57.5 100.0 1,221 Southwest 6.6 34.6 13.6 45.2 100.0 10.5 30.8 5.3 53.4 100.0 1,097 Education No education 18.9 42.2 7.4 31.5 100.0 13.6 35.0 5.2 46.1 100.0 1,120 Primary 8.0 31.7 5.9 54.4 100.0 9.2 25.8 4.2 60.8 100.0 5,152 Secondary + 6.3 17.4 4.0 72.2 100.0 9.9 17.3 3.4 69.3 100.0 2,402 Wealth quintile Lowest 16.5 41.7 6.0 35.7 100.0 11.5 34.0 4.3 50.2 100.0 1,519 Second 9.5 38.7 7.0 44.7 100.0 9.5 31.4 4.5 54.5 100.0 1,579 Middle 8.3 32.4 6.7 52.5 100.0 9.6 26.6 3.6 60.1 100.0 1,608 Fourth 6.1 25.4 5.4 63.0 100.0 9.1 19.5 4.0 67.3 100.0 1,726 Highest 6.0 14.2 3.5 76.3 100.0 10.1 16.1 4.0 69.7 100.0 2,242 Total 8.9 29.1 5.5 56.4 100.0 9.9 24.6 4.1 61.3 100.0 8,674 na = Not applicable The pattern of ownership of land by men is the same as for women with the exception that more men than women own a house and land. Overall, 37 percent of men age 15-49 did not own a house compared with 56 percent of women, and 42 percent of men did not own land compared with 61 percent of women. By age 40, 12 percent or less of men do not own a house or land, while comparable ownership for women of the same age is less than 43 percent. It is easier for men in the rural areas to own a house and land than for their counterparts in the urban areas. Owning a house is most difficult in Kampala where 76 percent of the men do not own a house compared with only 17 percent of men in the Eastern region who do not own a house. The pattern of owning land is the same as of a house by region; 69 percent of men in 224 • Women’s Empowerment and Demographic and Health Outcomes Kampala do not own land compared with 29 percent in the Eastern region. Education and wealth do not improve land and house ownership status for men any more than they do for women. 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, Uganda 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 Number of men Alone Jointly Alone and jointly Alone Jointly Alone and jointly Age 15-19 19.3 5.2 0.8 74.7 100.0 10.9 6.5 0.9 81.7 100.0 554 20-24 39.3 9.1 0.9 50.7 100.0 23.6 11.0 1.7 63.3 100.0 318 25-29 53.7 14.7 4.5 27.0 100.0 48.6 15.2 7.6 28.6 100.0 361 30-34 52.8 20.3 4.9 22.0 100.0 52.6 18.5 4.4 24.5 100.0 323 35-39 60.5 20.3 8.0 11.2 100.0 58.3 21.7 7.1 12.8 100.0 268 40-44 59.8 24.7 9.2 6.3 100.0 60.7 17.4 10.4 11.6 100.0 191 45-49 60.5 20.0 10.9 8.6 100.0 71.3 16.5 5.1 7.1 100.0 157 Residence Urban 24.0 11.9 0.8 63.3 100.0 27.9 13.4 3.3 55.4 100.0 439 Rural 49.8 14.8 5.3 30.1 100.0 42.8 14.1 4.8 38.1 100.0 1,734 Region Kampala 18.3 5.7 0.5 75.5 100.0 22.2 7.2 1.7 68.9 100.0 221 Central 1 40.9 11.9 0.0 47.2 100.0 48.5 6.8 0.0 44.7 100.0 209 Central 2 42.6 12.2 0.0 45.1 100.0 34.2 11.5 2.0 52.3 100.0 236 East Central 38.4 21.4 8.9 31.4 100.0 33.7 13.9 10.2 42.2 100.0 236 Eastern 54.5 21.9 6.5 17.1 100.0 47.5 18.6 5.0 29.0 100.0 289 Karamoja 29.0 30.4 20.2 20.4 100.0 49.9 13.0 6.2 30.9 100.0 55 North 62.4 14.1 1.6 21.9 100.0 35.7 31.6 1.2 31.6 100.0 199 West Nile 41.0 21.1 10.6 27.3 100.0 39.7 17.6 6.1 35.6 100.0 133 Western 53.3 6.2 5.8 34.7 100.0 46.5 8.2 6.3 39.0 100.0 322 Southwest 46.7 13.4 3.0 36.9 100.0 42.6 14.6 6.6 36.3 100.0 273 Education No education 55.5 19.4 8.8 16.3 100.0 59.9 11.9 8.0 20.2 100.0 90 Primary 48.6 14.0 4.4 33.0 100.0 41.2 14.3 4.4 40.1 100.0 1,309 Secondary + 36.4 14.0 4.0 45.6 100.0 35.2 13.7 4.4 46.7 100.0 774 Wealth quintile Lowest 49.5 23.7 9.4 17.4 100.0 40.2 19.9 6.7 33.2 100.0 345 Second 58.7 17.0 4.5 19.9 100.0 45.3 18.9 3.7 32.1 100.0 423 Middle 54.7 10.8 3.1 31.4 100.0 49.7 9.6 4.6 36.1 100.0 402 Fourth 42.6 9.3 5.4 42.8 100.0 38.3 10.3 5.8 45.2 100.0 486 Highest 23.7 13.0 1.2 62.1 100.0 28.8 12.8 2.5 55.9 100.0 517 Total 15-49 44.6 14.2 4.4 36.8 100.0 39.8 14.0 4.5 41.6 100.0 2,173 50-54 61.9 20.0 7.8 10.3 100.0 61.1 19.2 10.2 8.9 100.0 122 Total 15-54 45.5 14.5 4.6 35.4 100.0 40.9 14.2 4.8 39.9 100.0 2,295 na = Not Applicable 14.4.2 Women’s Participation in Household Decision Making One of the objectives of the current Uganda Gender Policy is to strengthen women's presence and capacities in decision making to enhance their participation in administrative and political processes. Decision making at the household and personal level is equally important for the empowerment of women and serves as an important factor in national development. To assess decision-making autonomy, information was sought on participation in three different types of household decisions: those about personal health care, major household purchases, and visits to her family relatives. Women are considered participants in decision making if they make decisions alone or jointly with their husband or someone else. Table 14.5 shows the percent distribution of currently married women by the person who usually makes decisions, as reported by women and men. Husbands are the most important decision makers on women’s health care, major household purchases, and visits to family or relatives. About two in five (39-42 percent) currently married women report that decisions on their own health care, major household purchases, and visits to their family or relatives are made primarily by their husband. On the other hand, 23 percent of the married women reported that they make solo decisions on their own health care and visits to family or relatives, and 16 percent reported making solo decisions on major household purchases. (Men disagreed, however, reporting Women’s Empowerment and Demographic and Health Outcomes • 225 that only 7 percent of women make decisions on major household purchases.) Independence in decision making on women’s own health has not changed much since 2006. At that time, only about two in ten married women (22 percent) independently decided on their own health care; the percentage remains almost the same (23 percent) five years later. Men are increasingly accepting their wives’ opinions in making decisions on major household purchases. Joint decision making on major household purchases as reported by men has almost doubled since 2006 (47 percent in 2011 compared with 27 percent in 2006). 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, Uganda 2011 Decision Mainly wife Wife and husband jointly Mainly husband Someone else Other Missing Total Number WOMEN Own health care 23.3 36.9 39.1 0.5 0.2 0.1 100.0 5,418 Major household purchases 16.2 41.2 42.0 0.3 0.3 0.1 100.0 5,418 Visits to her family or relatives 22.9 36.6 39.9 0.2 0.2 0.1 100.0 5,418 MEN Own health care 12.8 42.7 43.4 0.0 1.1 0.1 100.0 1,228 Major household purchases 6.8 47.1 45.4 0.0 0.3 0.3 100.0 1,228 Table 14.6.1 shows how women’s participation in decisionmaking varies by background characteristics. Thirty-eight percent of married women reported participating in all decisions, while 21 percent reported participating in none. Participation in decisionmaking increases with age, doubling from 23 percent of women age 15-19 to 48 percent of women age 45-49. Women are more likely to participate in decisionmaking if employed, and especially if employed for cash. Women from the North and Karamoja regions are more likely to participate in all three decisions compared with women from other regions. Only 5 percent of women from the North region and 7 percent of women from the Karamoja region were not able to take part in any of the decisions. Women from the Eastern region are the least empowered, with one in three (34 percent) not participating in any of the three decisions. The relationship between education and empowerment is mixed. Nearly one in two women (47 percent) with no education participated in all three decisions compared with 34 percent of women with primary and 39 percent of women with secondary and higher education. A similar relationship is seen between decision making and wealth quintile, with women in the poorest households more likely than women in wealthier households to make decisions. Women in the poorest households are most likely to participate in all types of decisions; this finding is similar to that of the 2006 UDHS. 226 • Women’s Empowerment and Demographic and Health Outcomes Table 14.6.1 Women's participation in decision making by background characteristics Percentage of currently married women age 15-49 who usually make specific decisions either by themselves or jointly with their husband, by background characteristics, Uganda 2011 Background characteristic Specific decisions Percentage who participate in all three decisions Percentage who participate in none of the three decisions Number of women Woman's own health care Making major household purchases Visits to her family or relatives Age 15-19 45.3 43.2 42.8 23.4 31.6 409 20-24 51.1 48.1 48.1 26.3 28.3 1,097 25-29 57.5 57.1 59.8 36.1 21.1 1,295 30-34 61.3 56.1 63.1 38.5 20.0 880 35-39 71.1 67.5 67.3 47.4 12.7 820 40-44 69.4 67.5 70.4 50.2 14.4 553 45-49 72.5 66.9 69.4 48.3 12.8 364 Employment (last 12 months) Not employed 48.8 43.7 50.5 27.6 31.6 1,124 Employed for cash 64.8 62.5 64.2 41.9 16.2 3,023 Employed not for cash 59.3 57.2 56.5 36.0 21.7 1,269 Number of living children 0 50.3 51.5 46.5 28.0 28.8 341 1-2 55.4 52.0 54.1 31.4 24.5 1,532 3-4 60.1 56.9 59.2 37.0 20.7 1,475 5+ 65.4 62.7 65.9 44.0 16.5 2,069 Residence Urban 63.6 61.6 66.2 41.7 17.0 892 Rural 59.5 56.5 58.2 36.7 21.4 4,526 Region Kampala 61.3 62.3 69.1 41.8 17.4 397 Central 1 48.0 42.7 55.6 26.2 27.9 559 Central 2 53.2 50.4 63.1 32.2 21.5 565 East Central 56.9 43.8 49.2 26.7 25.4 580 Eastern 50.6 45.9 42.7 26.3 33.8 859 Karamoja 81.6 78.4 80.7 69.2 7.3 215 North 85.5 79.4 77.0 61.9 4.5 487 West Nile 71.6 66.8 67.1 44.6 10.8 330 Western 54.0 59.5 60.3 36.8 22.8 743 Southwest 66.3 68.9 60.6 42.1 13.6 681 Education No education 63.8 65.6 66.8 47.4 17.6 877 Primary 57.9 54.0 56.1 34.4 22.7 3,313 Secondary + 63.6 60.4 63.7 39.0 17.4 1,227 Wealth quintile Lowest 64.8 63.6 64.3 45.5 18.3 1,063 Second 61.7 57.8 56.4 37.4 20.0 1,101 Middle 58.7 54.9 56.7 34.7 22.5 1,042 Fourth 55.5 52.2 57.5 31.7 22.5 997 Highest 59.8 57.8 62.3 37.8 20.4 1,215 Total 60.2 57.4 59.5 37.5 20.7 5,418 Women’s Empowerment and Demographic and Health Outcomes • 227 Figure 14.1 shows the relative percentages of currently married women, according to the number of decisions in which they participate, either alone or jointly with their husbands/partners. It is important to note that women are most likely to participate in all three decisions (38 percent) and least likely to participate in one decision (19 percent). Figure 14.1 Number of decisions in which currently married women participate 21 19 23 38 0 1 2 3 Number of decisions Table 14.6.2 shows decision-making power among men age 15-49, according to decisions about their own health care and about major household purchases, by background characteristics. More than 80 percent of men make decisions about their own health care and major household purchases; only 5 percent do not make any decisions on either of the two issues. Making decisions about one’s own health care and major household purchases increases with age. By age 15-49 the vast majority of men make decisions on major household purchases (96 percent) and their own health care (90 percent). Employed men are more than twice as likely as unemployed men to participate in both decisions. There is little difference in decision making by urban or rural residence. Less than half (49 percent) of men from the West Nile region participate in making decisions on both issues, and in contrast, the highest proportion of men who say that they make decisions on both issues are from the Southwest region. Forty-one percent of men from the West Nile region do not participate in either decision. Education and wealth do not strongly influence men’s decision-making behaviour. 228 • Women’s Empowerment and Demographic and Health Outcomes Table 14.6.2 Men's participation in decision making by background characteristics Percentage of currently married men age 15-49 who usually make specific decisions either alone or jointly with their wife, by background characteristics, Uganda 2011 Background characteristic Specific decision Both decisions Neither of the two decisions Number of men Man's own health care Making major household purchases Age 15-19 69.0 69.0 69.0 31.0 10 20-24 87.8 91.3 84.3 5.2 101 25-29 86.9 90.6 83.0 5.5 270 30-34 83.5 93.0 82.4 5.9 282 35-39 87.5 93.1 83.5 2.9 242 40-44 84.3 93.9 82.8 4.6 179 45-49 89.9 95.5 88.4 3.0 143 Employment (last 12 months) Not employed 68.2 69.8 39.3 1.3 12 Employed for cash 86.7 94.2 84.4 3.4 1,045 Employed not for cash 83.7 83.9 81.4 13.8 172 Number of living children 0 85.3 82.0 76.6 9.3 70 1-2 85.4 92.7 83.3 5.2 312 3-4 87.6 92.8 85.3 4.9 316 5+ 85.8 93.8 83.6 4.1 530 Residence Urban 88.3 91.9 84.5 4.3 215 Rural 85.7 92.7 83.4 5.0 1,014 Region Kampala 89.8 91.8 84.0 2.3 96 Central 1 95.7 97.8 94.6 1.1 120 Central 2 90.5 92.4 89.8 6.8 127 East Central 93.5 97.2 90.7 0.0 122 Eastern 84.3 95.0 82.6 3.2 199 Karamoja 94.5 87.5 85.1 3.1 40 North 81.1 93.4 76.1 1.6 117 West Nile 52.3 56.6 49.4 40.5 77 Western 79.7 94.2 77.6 3.7 183 Southwest 95.9 99.2 95.1 0.0 147 Education No education 85.4 91.6 82.3 5.3 73 Primary 85.6 93.3 83.7 4.8 754 Secondary + 87.3 91.3 83.5 4.9 402 Wealth quintile Lowest 85.1 89.0 81.5 7.4 243 Second 82.0 91.3 79.2 5.9 257 Middle 86.1 95.6 84.6 3.0 233 Fourth 87.2 92.6 85.7 5.9 247 Highest 90.4 94.6 86.9 2.0 248 Total 15-49 86.1 92.6 83.6 4.9 1,228 50-54 88.1 92.9 83.8 2.8 109 Total 15-54 86.3 92.6 83.6 4.7 1,338 14.4.3 Attitudes towards Wife Beating Gender-based violence (GBV) refers to violence that occurs as a result of the normative role expectations associated with each gender, along with the unequal power relationships between the two genders within the context of a specific society (Bloom, 2008). GBV is a result of an unequal balance of power between women and men; it cuts across cultures, ethnic groups, socioeconomic statuses, and religions. It is the most common type of violence that women experience worldwide, and it has serious consequences for women’s mental and physical well-being, including their reproductive and sexual health (WHO, 1999). Gender-based violence was declared to be a violation of human rights by the United Nations General Assembly in 1993 in its declaration on the elimination of violence against women (United Nations, 1993). GBV continues to occur despite various efforts to stop it. It remains a complex problem that requires examination from many different perspectives. Women’s Empowerment and Demographic and Health Outcomes • 229 The UDHS gathered information on women’s attitudes towards wife beating by asking women and men whether a husband is justified in beating his wife in five situations: if she burns the food, if she argues with him, if she goes out without telling him, if she neglects the children, and if she refuses to have sexual intercourse with him. Women who believe that a husband is justified in hitting or beating his wife for any of the specified reasons may believe themselves to be lower in status than men. High proportions of women who justify wife beating indicate that women generally accept the right of a man to control his wife’s behaviour through violence. Such a perception could act as a barrier to prevent women from accessing health care for themselves and their children. Table 14.7.1 shows the percentage of all women age 15-49 who agree that a husband is justified in hitting or beating his wife for specified reasons, by background characteristics. Table 14.7.1 Attitude toward wife beating: Women Percentage of all women age 15-49 who agree that a husband is justified in hitting or beating his wife for specific reasons, by background characteristics, Uganda 2011 Background characteristic Husband is justified in hitting or beating his wife if she: Percentage who agree with at least one specified reason 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 21.2 31.0 39.6 47.2 22.1 61.8 2,048 20-24 17.2 28.6 38.9 47.0 21.6 60.4 1,629 25-29 14.6 26.7 35.1 43.0 19.6 55.5 1,569 30-34 12.4 24.2 34.6 43.0 19.6 53.4 1,086 35-39 17.0 30.2 40.3 45.9 24.2 60.2 1,026 40-44 18.8 29.4 37.3 42.1 22.8 55.8 729 45-49 15.7 28.4 37.0 43.2 26.8 56.4 587 Employment (last 12 months) Not employed 20.6 31.0 36.6 44.6 23.5 58.8 2,293 Employed for cash 15.3 26.2 38.9 44.6 20.0 58.2 4,446 Employed not for cash 17.1 31.0 36.6 46.7 24.4 58.2 1,928 Number of living children 0 18.9 27.6 36.8 44.9 20.5 58.1 2,279 1-2 15.4 27.3 35.8 43.8 21.3 56.6 2,099 3-4 15.7 26.4 36.4 42.9 19.9 56.9 1,832 5+ 17.8 31.9 41.2 47.7 25.1 60.9 2,464 Marital status Never married 19.2 26.6 35.2 44.1 19.3 57.3 2,118 Married or living together 16.9 30.2 39.3 45.9 23.0 59.1 5,418 Divorced/separated/widowed 14.1 24.1 35.1 42.9 21.5 56.3 1,134 Residence Urban 9.4 17.6 28.1 36.2 10.9 46.1 1,717 Rural 19.0 31.2 40.1 47.2 24.6 61.3 6,957 Region Kampala 6.0 10.4 22.7 31.0 8.6 38.6 839 Central 1 13.4 28.9 51.3 51.2 21.9 66.8 956 Central 2 15.1 25.3 49.1 47.2 18.1 64.3 902 East Central 30.0 40.8 55.2 63.1 28.0 74.1 869 Eastern 26.3 41.0 43.4 53.9 32.5 70.0 1,267 Karamoja 4.4 14.0 20.8 38.3 17.1 43.9 289 North 11.9 32.4 18.8 29.2 18.2 42.1 735 West Nile 33.7 45.9 40.0 52.9 25.3 66.0 500 Western 13.4 22.5 29.7 37.4 15.8 53.2 1,221 Southwest 13.0 20.4 32.8 41.2 26.8 51.7 1,097 Education No education 17.2 30.7 35.0 43.8 25.1 56.3 1,120 Primary 20.2 32.4 40.7 47.6 25.3 62.2 5,152 Secondary + 10.5 19.0 32.6 40.0 13.1 50.7 2,402 Wealth quintile Lowest 18.6 34.1 34.2 44.0 24.9 57.6 1,519 Second 22.0 35.1 38.6 48.4 26.4 61.1 1,579 Middle 18.6 30.3 42.1 48.4 25.2 63.1 1,608 Fourth 19.9 30.9 44.4 51.3 24.3 66.8 1,726 Highest 9.3 17.0 31.3 36.0 12.3 46.7 2,242 Total 17.1 28.5 37.7 45.0 21.9 58.3 8,674 230 • Women’s Empowerment and Demographic and Health Outcomes About six in ten women (58 percent) believe that wife beating is justified for at least one of the specified reasons. This percentage shows significant improvement from the 2006 UDHS results where seven of ten women agreed that at least one reason was sufficient justification for wife beating. It is gratifying to observe that the percentages of women who justify wife beating for each of the specified reasons have decreased since the 2006 UDHS. The most widely accepted reasons for wife beating are neglecting the children (45 percent compared with 56 percent in 2006) and going out without informing the husband (38 percent compared with 52 percent in 2006). About three in ten women in 2011 compared with four in ten in 2006 think that arguing with a spouse justifies wife beating. The percentage of women who think that denying a husband sex justifies wife beating has declined from 31 percent in 2006 to 22 percent in 2011, while that of women who think burning food deserves beating has fallen from 23 percent to 17 percent over the same period. Acceptance of wife beating varies by women’s age and is highest among the youngest age group (62 percent) and lowest among women age 30-34 (53 percent). Rural women are much more accepting of wife beating (61 percent) than urban women (46 percent). Nearly three of four women residing in East Central region are accepting of wife beating for any reason, in contrast with women living in Kampala who are least likely to accept wife beating (39 percent). Acceptance of wife beating is most prevalent among women with a primary education and among women living in households in the second, middle, and fourth wealth quintiles. Differences by other background characteristics are not as marked. Men were also asked their opinions on the justification of wife beating under certain circumstances. Table 14.7.2 shows that the proportion of men age 15-49 who agree with at least one of the reasons justifying wife beating is lower than that observed among women (44 percent versus 58 percent). The pattern of acceptance by background characteristics has remained the same since 2006, although the levels of acceptance have declined. The results are similar to those among women. Young men; those who are employed, but not for cash; divorced, separated, or widowed men; and men with no children are most likely to agree with at least one reason justifying wife beating. A high percentage of rural men (47 percent) compared with urban men (29 percent) believe that wife beating is justified for at least one of the specified reasons. By region, men in Kampala (23 percent) followed by those of West Nile (25 percent), are least likely to accept wife beating. Men from the North region (59 percent) are most likely to agree with at least one reason for hitting or beating a wife. The primary driver of GBV is the power imbalance between women and men. GBV violates basic human rights and is deeply entrenched in some cultural practices and intimate relationships. Earlier presentation of data in this chapter has highlighted imbalances between women and men; therefore, the perceptions of wife beating, which is one form of gender-based violence, are not surprising. Since GBV is not a private issue but one that involves society as a whole, prevention calls for a holistic approach. Women’s Empowerment and Demographic and Health Outcomes • 231 Table 14.7.2 Attitude toward wife beating: Men Percentage of all men age 15-49 who agree that a husband is justified in hitting or beating his wife for specific reasons, by background characteristics, Uganda 2011 Background characteristic Husband is justified in hitting or beating his wife if she: Percentage who agree with at least one specified reason 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 15.6 29.1 34.1 39.2 15.9 52.2 554 20-24 8.6 18.0 21.0 25.9 10.4 38.0 318 25-29 6.6 19.7 22.9 27.7 8.2 40.6 361 30-34 6.8 19.1 23.8 29.6 8.6 41.7 323 35-39 3.7 18.4 22.7 28.7 9.8 38.8 268 40-44 8.0 23.9 25.1 26.9 11.7 44.1 191 45-49 9.7 21.3 27.1 31.0 14.1 43.9 157 Employment (last 12 months) Not employed 13.4 18.9 28.9 35.3 14.3 41.1 135 Employed for cash 8.4 21.7 25.4 31.2 11.0 43.7 1,657 Employed not for cash 11.1 24.7 28.0 28.1 12.4 44.5 382 Number of living children 0 12.8 23.4 28.8 34.0 13.7 46.0 902 1-2 8.2 19.7 22.2 25.2 9.0 38.3 386 3-4 8.2 22.3 25.3 31.2 11.2 43.1 339 5+ 4.6 21.5 24.9 29.9 9.8 44.0 546 Marital status Never married 12.7 24.0 28.7 33.4 13.7 45.4 834 Married or living together 6.4 21.0 24.0 28.3 9.5 42.0 1,228 Divorced/separated/widowed 14.0 19.6 29.7 41.3 16.6 49.0 111 Residence Urban 3.2 10.7 16.0 22.3 3.8 28.9 439 Rural 10.8 25.0 28.6 33.1 13.4 47.4 1,734 Region Kampala 2.6 7.3 13.0 18.1 2.8 23.2 221 Central 1 19.3 20.6 31.5 40.2 19.7 55.8 209 Central 2 7.9 15.4 23.5 26.2 9.5 37.0 236 East Central 15.6 25.5 38.1 41.7 16.2 50.8 236 Eastern 14.2 27.9 34.0 38.2 9.8 56.1 289 Karamoja 10.0 33.4 8.4 28.0 1.7 42.7 55 North 3.2 46.9 29.7 33.8 20.7 59.3 199 West Nile 7.5 15.9 15.6 19.5 7.3 25.1 133 Western 3.5 15.2 21.0 23.7 8.1 33.8 322 Southwest 9.1 22.4 27.9 34.0 12.8 46.6 273 Education No education 9.7 14.6 25.5 32.3 8.7 39.6 90 Primary 11.6 26.0 31.6 34.8 14.4 49.4 1,309 Secondary + 5.1 16.3 16.9 24.2 6.8 34.5 774 Wealth quintile Lowest 13.5 31.0 25.5 31.8 16.9 49.2 345 Second 8.3 26.8 29.2 34.0 12.8 49.2 423 Middle 11.3 24.2 30.0 35.3 12.2 47.0 402 Fourth 9.0 17.5 26.1 28.7 10.7 40.2 486 Highest 5.7 15.0 20.7 26.5 6.9 36.1 517 Total 15-49 9.2 22.1 26.1 30.9 11.5 43.7 2,173 50-54 4.8 12.4 15.4 18.7 7.3 26.6 122 Total 15-54 9.0 21.6 25.5 30.3 11.2 42.8 2,295 14.4.4 Women’s Empowerment Indicators Two sets of empowerment indicators, namely women’s participation in making household decisions and women’s attitude towards wife beating can be summarized in two indices. The first index shows the number of decisions in which women participate alone or jointly with their husband or partner (see Table 14.6.1 for the detailed list). This index ranges in value from 0 to 3 and relates positively to women’s empowerment. It reflects the degree of decision-making control that women are able to exercise in areas that affect their own lives and environments. The second index, which ranges 232 • Women’s Empowerment and Demographic and Health Outcomes in value from 0 to 5, presents the total number of reasons for which the respondent feels that the husband is justified in beating his wife (see Table 14.7.1 for list of reasons). A lower score on this indicator is interpreted as reflecting a greater sense of entitlement and self-esteem and a higher status of women. Table 14.8 shows how these indices relate to each other. There is a clear relationship between the two indices. The percentage of women who disagree with all reasons justifying wife beating increases as the number of household decisions in which the women participate increases, from 35 percent among women who participate in none of the household decisions to 52 percent among women who participate in all three household decisions. The percentage of women who participate in all three household decisions decreases as the number of reasons for which wife beating is justified increases, from 48 percent among women who agree with none of the reasons justifying wife beating to 28 percent among women who agree with all five reasons justifying wife beating. The data reflect improvements in women’s empowerment since 2006. The percentage of women who disagree with all reasons justifying wife beating has increased from 33 to 52 percent for women who took part in all decisions. The percentage of women who participate in all decisions has declined from 30 percent to 28 percent for women who agree with all five reasons for wife beating. 14.5 CURRENT USE OF CONTRACEPTION BY WOMEN’S EMPOWERMENT 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. The 2011 UDHS supports this assertion whereby the most common method used by married women is injectables which are easy to conceal from partners. Table 14.9 shows the relationship of each of the empowerment indicators with current use of contraceptive methods by currently married women. As expected, contraceptive use is positively associated with participation in household decisions. Use of any contraceptive method is lower among women who do not participate in any household decision (25 percent) than among women who participate in at least one household decision. Thirty-one percent of women who participate in at least one household decision are currently using a method of family planning. Contraceptive use is negatively associated with the acceptance of wife beating. Use of any contraceptive method and use of any modern method is lower among women who agree with all the five reasons justifying wife beating (25 percent and 21 percent, respectively) than among women who agree with none of the reasons (31 percent and 27 percent, respectively). Table 14.8 Indicators of women's empowerment Percentage of currently married women age 15-49 who participate in all decision making and percentage who disagree with all of the reasons justifying wife-beating, by value on each of the indicators of women's empowerment, Uganda 2011 Empowerment indicator Percentage who participate in all decision making Percentage who disagree with all the reasons justifying wife- beating Number of women Number of decisions in which women participate1 0 na 34.8 1,120 1-2 na 34.0 2,265 3 na 51.9 2,033 Number of reasons for which wife-beating is justified2 0 47.6 na 2,214 1-2 31.8 na 1,640 3-4 29.5 na 1,171 5 28.4 na 393 na = Not applicable 1 See Table 14.6.1 for the list of decisions. 2 See Table 14.7.1 for the list of reasons. Women’s Empowerment and Demographic and Health Outcomes • 233 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 indicators of women's status, Uganda 2011 Empowerment indicator Any method Modern methods Any traditional method Not currently using Total Number of women Any modern method Female sterili- zation Male sterili- zation Temporary modern female methods1 Male condom Number of decisions in which women participate2 0 25.2 22.0 1.4 0.2 17.0 3.4 3.2 74.8 100.0 1,120 1-2 31.4 27.0 2.7 0.0 21.6 2.7 4.3 68.6 100.0 2,265 3 31.2 27.1 3.9 0.1 20.8 2.3 4.0 68.8 100.0 2,033 Number of reasons for which wife-beating is justified3 0 31.4 26.8 2.5 0.1 21.4 2.8 4.6 68.6 100.0 2,214 1-2 32.3 28.7 3.6 0.1 21.8 3.2 3.6 67.7 100.0 1,640 3-4 25.9 22.4 2.0 0.1 18.0 2.2 3.5 74.1 100.0 1,171 5 25.1 21.4 4.6 0.0 15.0 1.7 3.8 74.9 100.0 393 Total 30.0 26.0 2.9 0.1 20.3 2.7 4.0 70.0 100.0 5,418 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 14.6.1 for the list of decisions. 3 See Table 14.7.1 for the list of reasons. 14.6 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. She has more control over her ability to access and use contraceptives to space and limit her family size. Women who have a desire to limit their births but who are not using family planning are defined as having an unmet need for family planning. Table 14.10 shows the mean ideal number of children for women age 15-49 and the percentage of currently married women age 15-49 with an unmet need of family planning by the two indicators of women’s empowerment. 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 indicators of women's empowerment, Uganda 2011 Empowerment indicator Mean ideal number of children1 Number of women Percentage of currently married women with an unmet need for family planning2 Number of currently married women For spacing For limiting Total Number of decisions in which women participate1 0 5.2 1,094 24.2 12.6 36.8 1,120 1-2 5.0 2,221 21.7 11.3 32.9 2,265 3 5.3 1,948 17.9 16.5 34.4 2,033 Number of reasons for which wife- beating is justified2 0 4.7 3,516 17.9 14.6 32.5 2,214 1-2 4.8 2,613 23.1 11.3 34.4 1,640 3-4 5.1 1,762 22.2 14.3 36.5 1,171 5 5.3 553 23.1 13.9 37.0 393 Total 4.8 8,444 20.8 13.5 34.3 5,418 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 14.6.1 for the list of decisions. 4 See Table 14.7.1 for the list of reasons. 234 • Women’s Empowerment and Demographic and Health Outcomes The relationship between fertility and empowerment indicators continue to be mixed, similar to the 2006 UDHS. It is surprising that women who participate in all decisions desire the most children, but consistently women who participated in one to two decisions had the lowest desire for children and the lowest unmet need for family planning. There is a clear negative relationship between the index derived from the attitudes towards wife beating and ideal family size and unmet need. Women who accept all the reasons for wife beating have the highest mean ideal number of children at 5.3 compared with 4.7 children for women who do not justify wife beating for any reason. Table 14.10 shows that unmet need for family planning increases with the number of reasons for which women believe wife beating is justified, from 33 percent among women who don’t believe wife beating is justified for any reason at all to 37 percent among women who believe that wife beating is justified for three to five reasons. 14.7 WOMEN’S STATUS AND REPRODUCTIVE HEALTH CARE Table 14.11 presents the percentage of women age 15-49 with live births 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. The data show that there is not much variation in use of reproductive health care among women who participate in all decisions versus those who do not take part in any decisions. Women who agree with all of the reasons justifying wife beating were less likely to seek reproductive care services than women who do not justify wife beating at all. This difference was especially marked with regard to postnatal care from health personnel within the first two days following delivery. Generally, postnatal care is much lower (23 percent) among women who justified wife beating for any reason at all when compared with women who did not justify wife beating for any reason (39 percent). 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, Uganda 2011 Empowerment indicator Percentage receiving antenatal care from a skilled provider1 Percentage receiving delivery care from a skilled provider1 Percentage of women with a postnatal checkup in the first two days after birth2 Number of women with a child born in the last five years Number of decisions in which women participate1 0 94.4 58.9 32.9 889 1-2 94.8 63.1 34.1 1,775 3 96.2 59.8 33.2 1,524 Number of reasons for which wife-beating is justified2 0 96.0 64.3 38.9 2,013 1-2 95.4 61.9 33.4 1,539 3-4 92.8 59.7 29.2 1,090 5 91.8 54.6 23.4 326 Total 94.9 61.9 34.1 4,968 1 'Skilled provider' includes doctor, nurse/midwife, medical assistant/clinical officer, nurse aide, or Village Health Team (VHT) 2 Includes women who received a postnatal checkup from a doctor, nurse/midwife, medical assistant/clinical officer, nurse aide, or Village Health Team (VHT) or traditional birth attendant (TBA) in the first two days after the birth. Includes women who gave birth in a health facility and those who did not give birth in a health facility. 3 Restricted to currently married women. See Table 14.6.1 for the list of decisions. 4 See Table 14.7.1 for the list of reasons. Adult and Maternal Mortality • 235 ADULT AND MATERNAL MORTALITY 15 dult and maternal mortality rates are key indicators of the health status of a population. Estimation of these mortality rates requires comprehensive and accurate reporting of adult deaths and maternal deaths. The UDHS 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 UDHS Woman’s Questionnaire and the 2011 UDHS Maternal Mortality 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, summary measures for the 2000-01 and 2006 UDHS have also been calculated and are presented in Table 15.2. The term ‘maternal mortality’ used in this chapter (and in previous UDHS 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 deaths. The data collected in the UDHS questionnaire are based on information about deaths during the two months following a birth, however, rather than the 42 days following a birth. 15.1 ASSESSMENT OF DATA QUALITY To obtain a sibling history, the 2011 UDHS interviewer first asked each female respondent to list all children born to her biological mother, starting with the firstborn. The interviewer then asked the respondent whether each of these siblings was still alive. For living siblings, the current age of each sibling was recorded. 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 UDHS A Key Findings • Adult mortality is slightly higher among men than among women (6.5 deaths and 5.3 deaths per 1,000 population, respectively). • Twenty percent of women and 25 percent of men are likely to die between ages 15 and 50. These probabilities have decreased for both women and men since 2000-01, with most of the decreases occurring between 2006 and 2011. • Maternal deaths account for 18 percent of all deaths to women age 15-49. The maternal mortality rate for the seven-year period preceding the survey was 0.93 maternal deaths per 1,000 woman-years of exposure. • The maternal mortality ratio was 438 maternal deaths per 100,000 live births for the seven-year period preceding the survey. This ratio is not significantly different from that reported in the 2006 UDHS, but it is lower than the ratio reported in the 2000-01 UDHS. 236 • Adult and Maternal Mortality 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 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 UDHS a total of 136,846 siblings were recorded in the sibling histories. The survival status was not reported for 200 siblings (0.1 percent). Among surviving siblings, the current age was not reported for 362 siblings (0.3 percent). For 98 percent of deceased siblings, both age at death and years since death were reported. In 1.1 percent of cases, both the age at death and years since death were missing. The sex ratio of the enumerated siblings (the ratio of brothers to sisters times 100) is 101.1 (Table C.9), which is a reasonable value and indicates that there has not been any 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 Uganda 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 (6.5 deaths per 1,000 population) than among women (5.3 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 for women and men generally show the expected increases with increasing age. 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. Table 15.1 Adult mortality rates Direct estimates of female and male mortality rates for the seven years preceding the survey by five-year age groups, Uganda 2011 Age Deaths Exposure years Mortality rates1 WOMEN 15-19 133 54,586 2.43 20-24 199 57,177 3.49 25-29 225 48,985 4.59 30-34 259 38,962 6.64 35-39 232 28,172 8.24 40-44 159 18,269 8.70 45-49 122 11,308 10.78 15-49 1,329 257,460 5.33a MEN 15-19 119 52,562 2.27 20-24 174 55,086 3.16 25-29 247 48,814 5.07 30-34 294 38,476 7.63 35-39 315 29,069 10.84 40-44 259 17,796 14.53 45-49 146 10,086 14.46 15-49 1,554 251,888 6.49a 1 Expressed per 1,000 population a Age-adjusted rate Adult and Maternal Mortality • 237 Table 15.2 shows a summary measure of the risk of dying between exact ages 15 and 50 (35q15). Based on the 2011 UDHS, 20 percent of women and 25 percent of men are likely to die between age 15 and age 50. Estimates of 35q15 based on the 2000-01 and 2006 UDHS also show that men had a higher probability of dying between exact ages 15 and 50 (37 and 35 percent, respectively) than women (30 percent in both years). In the decade from the 2000-01 to the 2011 UDHS surveys, the probability of dying between exact ages 15 and 50 decreased for both women and men. It decreased, from 30 percent to 20 percent for women and from 37 percent to 25 percent for men, showing a 34 percent decrease for women and a 31 percent decrease for men. For both women and men, much of this decrease is seen in the most recent five years, between 2006 and 2011. Confidence intervals for the 35q15 estimates can be found in Appendix Table B.16. 15.3 ESTIMATES OF MATERNAL MORTALITY Maternal mortality in Uganda 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 0.93 maternal deaths per 1,000 woman-years of exposure. By five-year age groups, the maternal mortality rate is highest among women 35-39 (1.38), followed by those age 30-34 (1.30). Confidence intervals for the maternal mortality rates can be found in Appendix Table B.16. In the 2011 UDHS maternal deaths represent 18 percent of all deaths to women age 15-49. The percentage of female deaths that are maternal varies by age and ranges from 10 percent among women 45 to 49 to 23 percent of all deaths among women 20-29. Table 15.2 Adult mortality probabilities The probability of dying between the ages of 15 and 50 for women and men for the seven years preceding the survey, Uganda 2000-01, 2006, and 2011 Survey Female 35q151 Male 35q151 2011 UDHS 201 252 2006 UDHS 295 352 2000-01 UDHS 303 366 1 The probability of dying between exact ages 15 and 50, expressed per 1,000 person-years of exposure Table 15.3 Maternal mortality Direct estimates of maternal mortality rates for the seven years preceding the survey, by five-year age groups, Uganda 2011 Age Percentage of female deaths that are maternal Maternal deaths Exposure years Maternal mortality rate1 15-19 17.6 23 54,586 0.43 20-24 22.6 45 57,177 0.79 25-29 22.7 51 48,985 1.04 30-34 19.6 51 38,962 1.30 35-39 16.7 39 28,172 1.38 40-44 12.2 19 18,269 1.06 45-49 10.3 13 11,308 1.11 15-49 18.1 241 257,460 0.93a General fertility rate (GFR)2 212a Maternal mortality ratio (MMR)3 438 CI: (368, 507) Lifetime risk of maternal death4 0.029 2006 UDHS Maternal mortality ratio (MMR)3 418 CI: (314, 521) 2000-01 UDHS Maternal mortality ratio (MMR)3 524 CI: (412, 636) 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 238 • Adult and Maternal Mortality 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 212 that prevailed during the same time period, and multiplying the result by 100,000. This procedure produces a maternal mortality ratio (MMR) of 438 deaths per 100,000 live births during the seven-year period preceding the survey. In other words, for every 1,000 live births in Uganda during the seven years preceding the 2011 UDHS, about four women (4.38) died during pregnancy, during childbirth, or within two months of childbirth. The lifetime risk of maternal death (0.029) indicates that about 3 percent of women died during pregnancy, during childbirth, or within two months of childbirth. In the reports for the 2000-01 and 2006 UDHS surveys, the maternal mortality ratios were shown for the 10-year period preceding the survey. To look at trends over time, these ratios were recalculated for the seven-year period preceding the surveys (Table 15.3). The estimated maternal mortality ratio for the seven-year period decreased from 524 deaths per 1000,000 live births in 2000-01 to 418 deaths in 2006, and it increased to 438 deaths per 1000,000 live births in 2011. As shown in Table 15.3 and Figure 15.1, the confidence interval surrounding the maternal mortality ratio of 438 deaths per 100,000 live births in 2011 is 368-507, while the confidence interval for the 2006 ratio of 418 deaths per 100,000 live births is 314-521 deaths. Because the confidence intervals between the two estimates overlap widely, there is no evidence to suggest that the maternal mortality ratio has changed substantially in the five years between the two surveys. On the other hand, the confidence interval for the 2000-01 maternal mortality ratio of 524 deaths per 100,000 live births is 412-636, and it does not overlap widely with the 2011 estimate, implying that there has been some decrease in maternal mortality ratio over the last decade. 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. Figure 15.1 Maternal Mortality Ratio (MMR) for the Seven Years Preceding the 2000-01, 2006, and 2011 Uganda DHS with Confidence Intervals 636 521 507 412 314 368 524 418 438 100 200 300 400 500 600 700 Seven years preceding the 2000-01 UDHS (1994-2000) Seven years preceding the 2006 UDHS (mid-1999 - mid-2006) Seven years preceding the 2011 UDHS (mid-2004 - mid-2011) Domestic Violence • 239 DOMESTIC VIOLENCE 16 ender-based violence is defined as any act that results in, or is likely to result in, physical, sexual, or psychological harm or suffering among women, including threats of such acts and coercion or arbitrary deprivations of liberty, whether occurring in public or in private life (United Nations, 1993; United Nations, 1995). Domestic violence has negative health consequences for victims, especially with respect to the reproductive health of women and the physical, emotional, and mental health of their children. Acts of domestic violence can also happen to men. The 2001 UDHS included a domestic violence module for both women and men, in recognition of the seriousness of the problem of domestic violence in Uganda. 16.1 MEASUREMENT OF VIOLENCE Collecting valid, reliable, and ethical data on domestic violence poses particular challenges. What constitutes violence or abuse varies across cultures and among individuals. A culture of silence usually surrounds domestic violence and can affect reporting. The sensitivity of the topic is another issue. Assuring the safety of respondents and interviewers when asking about domestic violence in a familial setting, protecting women who disclose violence, and reducing the risk of double-victimisation of respondents as they relive their experiences, are all specific ethical concerns. The responses to these challenges by the 2011 UDHS are described in the sections that follow. 16.1.1 Use of Valid Measures of Violence In the 2011 UDHS, information was obtained from the ever-married respondents on violence committed by their current and former spouses and by others. Information was collected from never- married respondents on violence by anyone. Since international research shows that intimate partner violence is one of the most common forms of violence especially against women, information on spousal violence was measured in more detail than violence by other perpetrators. This was done by using a shortened, modified version of the Conflict Tactics Scale (Strauss, 1990). Specifically, violence by the current spouse/partner for currently married respondents and by the most recent spouse/partner for G Key Findings  Fifty-six percent of women and 55 percent of men age 15-49 have experienced physical violence at least once since age 15, and 27 and 22 percent, respectively, have experienced physical violence within the 12 months prior to the survey.  Twenty-eight percent of women and 9 percent of men age 15-49 report having experienced sexual violence at least once in their lifetime.  Overall, six in ten ever-married women and four in ten men age 15-49 report having experienced emotional, physical, or sexual violence from a spouse.  Among ever-married women and men who have ever experienced spousal violence (physical or sexual), 37 and 26 percent, respectively, reported experiencing physical injuries.  About four in ten women and men have sought assistance from any source for the violence they have experienced. 240 • Domestic Violence formerly married respondents was measured by asking all ever-married women and men the following set of questions. (Does/did) your (last) (spouse/partner) ever: (a) Push you, shake you, or throw something at you? (b) Slap you? (c) Twist your arm or pull your hair? (d) Punch you with his/her fist or with something that could hurt you? (e) Kick you, drag you, or beat you up? (f) Try to choke you or burn you on purpose? (g) Threaten or attack you with a knife, gun, or any other weapon? (h) Physically force you to have sexual intercourse with him/her even when you did not want to? (i) Force you to perform any sexual acts you did not want to? For every question that a respondent answered ‘yes,’ she or he was asked about the frequency of the act in the 12 months preceding the survey. A ‘yes’ answer to one or more of items (a) to (g) above constitutes evidence of physical violence, and a ‘yes’ answer to item (h) or (i) constitutes evidence of sexual violence. Similarly, emotional violence among ever-married respondents was measured by the following questions. (Does/did) your (last) (spouse/partner) ever: (a) Say or do something to humiliate you in front of others? (b) Threaten to hurt or harm you or someone close to you? (c) Insult you or make you feel bad about yourself? This approach of asking about specific acts to measure different forms of violence has the advantage of not being affected by different understandings of what constitutes a summary term such as ‘violence.’ By including a wide range of acts, this approach has the additional advantage of giving the respondent multiple opportunities to disclose any experience of violence. In addition to these questions that were asked only of ever-married respondents, all women and men were asked about physical violence from persons other than the current or most recent spouse/partner. Respondents who answered yes to this question were asked who committed violence against them and the frequency of such violence during the 12 months preceding the survey. Respondents who reported experiencing different forms of violence were asked for the perpetrators of the violence. Although this approach to questioning is generally considered to be optimal, the possibility of underreporting of violence, particularly sexual violence, cannot be entirely ruled out in any survey, and this survey is no exception. Domestic Violence • 241 16.1.2 Ethical Considerations in the 2011 UDHS In recognition of the challenges in collecting data on violence, the interviewers in the 2011 UDHS were given special training. The training focused on how to ask sensitive questions, ensure privacy, and build rapport between interviewer and respondent. Rapport with the interviewer, confidentiality, and privacy are all keys to building respondents’ confidence so that they can safely share their experiences with the interviewer. Placing questions about violence at the end of the questionnaire also provides time for the interviewer to develop a certain degree of intimacy that should further encourage respondents to share their experiences of violence, if any. In addition, the following protections were built into the survey or the questionnaire in keeping with the World Health Organization’s ethical and safety recommendations for research on domestic violence (WHO, 2001): 1. To maintain confidentiality, only one woman or man per household was administered the questions on violence. In the one-third of the households selected for the male survey, one man per household was randomly selected to receive the questions on domestic violence. In the remaining two-thirds of the households, one woman per household was selected for the questions on violence. The random selection of one woman or man was done through a simple selection procedure based on the Kish Grid, which was built into the Household Questionnaire (Kish, 1965). 2. As a means of obtaining additional consent, beyond the initial consent at the start of the interview, the respondent was informed that the questions could be sensitive and was reassured regarding the confidentiality of her/his responses. 3. The violence module was implemented only if privacy could be obtained. The interviewers were instructed to skip the module, thank the respondent, and end the interview if they could not maintain privacy during the implementation of this module. 4. A brochure that included information on domestic violence and contact information for service centers across the country was provided to all eligible respondents after the interview was completed, irrespective of whether they were selected for the module or not. This was done to safeguard against identifying the respondent selected for the module and to provide information to all respondents so that they could access the services and be informed about what to do in the event of domestic violence. 16.1.3 Subsample for the Violence Module The domestic violence module was implemented only in the subsample of households selected for the men’s survey. Further, in keeping with ethical requirements, as mentioned above, only one woman or man per household was selected for the module. These restrictions resulted in a total of 2,056 women age 15-49 (1,705 ever-married women) and 1,730 men age 15-54 (1,211 ever-married men) who completed the domestic violence module. Fifteen eligible women and 14 eligible men were not interviewed because either they declined or complete privacy could not be obtained. Specially constructed weights were used to adjust for the selection of only one woman or man per household and to ensure that the domestic violence subsample was nationally representative. 16.2 EXPERIENCE OF PHYSICAL VIOLENCE Tables 16.1.1 and 16.1.2 show the percentages of women and men, respectively, that have ever experienced physical violence since age 15 and the percentages that have experienced violence during the 12 months preceding the survey, by background characteristics. Fifty-six percent of women and 55 percent of men age 15-49 have experienced physical violence since age 15, and 27 percent and 22 percent, respectively, experienced physical violence in the 12 months prior to the survey. Overall, 7 percent of women and 3 percent of men reported that they had experienced physical violence often in the past 12 242 • Domestic Violence months, and 20 percent, each, said they had experienced physical violence sometimes during the past 12 months. The experience of physical violence varies by background characteristics. The percentage of women who have experienced physical violence since age 15 does not vary much by age, employment status, or education. This percentage is highest among women who belong to the Pentecostal religion (61 percent), among the Itesa ethnic group (70 percent), among rural women (58 percent), women in the Eastern region (66 percent), and women with five or more children (60 percent). Ever-married women are more likely than those who never married to have experienced physical violence, implying that in Uganda violence perpetrated by spouses is more prevalent than violence perpetrated by other individuals. Sixty- five percent of women who are divorced, separated, or widowed and 56 percent of currently married women have experienced physical violence since age 15, as compared with 51 percent of never-married women. The percentage of women who have experienced physical violence since age 15 ranges from 47 percent of women in the highest wealth quintile to 63 percent of those in the lowest quintile. The percentage of men who have ever experienced physical violence since age 15 is lowest among men age 40-49 (51 percent) and Pentecostal men (52 percent), when compared with younger men or those of other religions (54-58 percent). Men of Banyankole ethnicity (67 percent), those living in Karamoja (72 percent), previously married men (75 percent), men with 3-4 children (64 percent), and those who are unemployed (58 percent) are more likely to have experienced physical violence since age 15 than other men. This percentage increases with education, from 47 of uneducated men to 58 percent of those with secondary or higher education. There is no clear relationship between experience of physical violence by men since age 15 and wealth. The percentage of women who have experienced physical violence in the past 12 months (often or sometimes) also varies by background characteristics. It decreases steadily by age, from 35 percent among women 15-19 to 18 percent among those 45-49. This percentage is higher among Catholic women (31 percent), those of Itesa ethnicity (32 percent), rural women (29 percent), women in the North region (42 percent), and those with no children (30 percent). These women differ from those experiencing physical violence since age 15. Previously married women are the least likely to have experienced physical violence in the past year (16 percent) compared with those who are never-married or currently married (29 percent, each). Recent physical violence is substantially higher among unemployed women (34 percent) than those who are employed, for cash or otherwise (24 percent). The percentage of women who experienced physical violence in the past 12 months decreases with education and wealth. Somewhat similar patterns are observed among men, except that men with no education are least likely to have experienced violence in the 12 months before the survey. There is also no pattern between violence in the previous 12 months and wealth among men. Domestic Violence • 243 Table 16.1.1 Experience of physical violence: women Percentage of women age 15-49 who have ever experienced physical violence since age 15 and percentage who have experienced violence during the 12 months preceding the survey, by background characteristics, Uganda 2011 Background characteristic Percentage who have ever experienced physical violence since age 151 Percentage who have experienced physical violence in the past 12 months Number of women Often Sometimes Often or sometimes2 Age 15-19 54.3 4.2 30.5 34.7 464 20-24 58.1 11.3 18.8 30.1 412 25-29 55.2 8.6 18.7 27.3 384 30-39 55.4 7.1 15.2 22.2 482 40-49 58.5 5.1 12.6 17.7 315 Religion Catholic 55.7 10.1 21.3 31.4 827 Protestant 56.0 4.2 20.7 24.8 591 Muslim 54.4 5.9 17.2 23.0 279 Pentecostal 60.5 7.6 16.3 23.9 306 SDA/Other (48.3) (1.6) (14.5) (16.1) 53 Ethnicity Baganda 47.3 2.9 16.0 18.9 368 Banyankole 58.9 5.5 23.7 29.2 207 Basoga 55.9 4.0 14.5 18.5 153 Bakiga 54.3 9.3 21.1 30.4 149 Itesa 69.8 11.1 20.8 31.9 162 Other 56.9 8.8 20.5 29.3 1,017 Residence Urban 49.3 4.9 14.3 19.2 398 Rural 57.8 7.8 20.9 28.7 1,658 Region Kampala 49.5 7.1 10.3 17.4 185 Central 1 50.0 5.9 19.1 25.0 231 Central 2 54.0 3.1 17.5 20.6 221 East Central 61.9 6.1 22.1 28.2 185 Eastern 66.4 6.6 21.3 27.9 314 Karamoja 47.3 11.3 23.0 34.3 63 North 60.6 14.2 27.7 41.9 178 West Nile 56.4 4.1 16.6 20.7 127 Western 50.2 8.4 17.8 26.2 288 Southwest 57.1 8.2 22.0 30.2 263 Marital status Never married 51.3 2.2 26.9 29.2 468 Married or living together 56.0 9.2 19.3 28.5 1,307 Divorced/separated/widowed 65.1 6.6 9.1 15.7 281 Number of living children 0 52.7 2.7 27.2 29.9 517 1-2 56.3 10.9 17.9 28.8 509 3-4 54.7 7.1 17.2 24.3 442 5+ 60.2 8.3 16.3 24.5 588 Employment Employed for cash 55.7 7.3 16.7 24.1 1,025 Employed not for cash 58.3 4.9 18.9 23.8 447 Not employed 55.2 8.9 25.2 34.2 584 Education No education 58.2 11.0 21.9 32.8 283 Primary 56.4 6.9 20.1 26.9 1,187 Secondary + 54.7 6.3 17.7 24.0 586 Wealth quintile Lowest 63.3 12.0 24.3 36.2 360 Second 58.6 8.1 25.2 33.3 360 Middle 60.9 9.8 18.6 28.4 389 Fourth 54.6 4.2 16.9 21.2 436 Highest 47.0 4.0 15.5 19.5 511 Total 15-49 56.1 7.3 19.6 26.9 2,056 Figures in parentheses are based on 25-49 unweighted cases. 1 Includes violence in the past 12 months. For women who were married before age 15 and who reported physical violence by a husband, the violence could have occurred before age 15. 2 Includes women who report physical violence in the past 12 months but for whom frequency is not known 244 • Domestic Violence Table 16.1.2 Experience of physical violence: men Percentage of men age 15-49 who have ever experienced physical violence since age 15 and percentage who have experienced violence during the 12 months preceding the survey, by background characteristics, Uganda 2011 Background characteristic Percentage who have ever experienced physical violence since age 151 Percentage who have experienced physical violence in the past 12 months Often Sometimes Often or sometimes2 Number of men Age 15-19 54.0 4.0 30.3 34.2 432 20-24 57.3 3.1 17.7 20.8 238 25-29 58.0 1.6 18.4 20.0 262 30-39 57.1 2.4 15.9 18.3 450 40-49 50.8 1.2 12.6 13.8 273 Religion Catholic 55.3 2.0 22.3 24.3 739 Protestant 56.1 2.1 16.6 18.7 525 Muslim 57.7 4.2 18.5 22.7 202 Pentecostal 51.9 3.9 19.4 23.3 130 SDA/Other (51.5) (5.9) (21.5) (27.4) 59 Ethnicity Baganda 56.1 3.3 18.8 22.1 273 Banyankole 66.6 3.0 25.7 28.7 170 Basoga 64.5 3.4 17.3 20.7 151 Bakiga 51.1 4.3 10.1 14.4 116 Itesa 51.0 1.4 19.5 20.9 113 Other 52.5 2.0 20.7 22.7 831 Residence Urban 57.7 3.0 18.0 21.0 335 Rural 54.9 2.5 20.2 22.7 1,320 Region Kampala 55.0 1.9 21.4 23.3 170 Central 1 66.0 4.2 24.7 28.9 169 Central 2 55.9 3.1 20.3 23.4 174 East Central 65.2 2.5 19.7 22.2 181 Eastern 54.0 3.8 18.9 22.7 216 Karamoja 71.9 0.0 35.8 35.8 44 North 56.9 0.0 18.1 18.1 142 West Nile 37.7 1.7 13.8 15.5 102 Western 42.7 4.1 16.3 20.4 247 Southwest 59.3 1.2 19.8 21.0 208 Marital status Never married 53.6 3.5 25.5 29.1 645 Married or living together 55.1 1.4 16.3 17.7 928 Divorced/separated/widowed 74.7 8.5 13.1 21.6 81 Number of living children 0 53.6 3.5 25.0 28.5 687 1-2 58.0 4.1 19.0 23.1 288 3-4 63.7 2.1 15.3 17.5 251 5+ 51.8 0.4 14.5 14.9 428 Employment Employed for cash 56.1 2.6 17.3 19.9 1,276 Employed not for cash 51.7 3.3 26.7 30.0 278 Not employed 57.9 0.8 31.7 32.5 99 Education No education 47.3 1.4 10.7 12.1 72 Primary 54.5 2.6 20.8 23.4 974 Secondary + 57.9 2.6 19.2 21.8 608 Wealth quintile Lowest 51.4 0.0 20.8 20.8 256 Second 57.9 3.0 20.6 23.6 327 Middle 57.7 3.2 19.4 22.6 307 Fourth 52.2 3.9 15.2 19.1 372 Highest 57.2 2.2 22.9 25.1 392 Total 15-49 55.4 2.6 19.8 22.4 1,654 50-54 62.5 3.3 14.1 17.4 76 Total 15-54 55.7 2.6 19.5 22.1 1,730 Figures in parentheses are based on 25-49 unweighted cases. 1 Includes violence in the past 12 months. For men who were married before age 15 and who reported physical violence by a wife, the violence could have occurred before age 15. 2 Includes men who report physical violence in the past 12 months but for whom frequency is not known. Domestic Violence • 245 16.3 PERPETRATORS OF PHYSICAL VIOLENCE Tables 16.2.1 and 16.2.2 show perpetrators of physical violence, according to women’s and men’s marital status, respectively, among those who have experienced physical violence since age 15. Among ever-married women, the most commonly reported perpetrator of physical violence is the current husband or partner (60 percent), followed by former husband/partner (20 percent), indicating a high level of spousal violence. Among ever-married men, the most common perpetrator are others (48 percent), followed by current wife or partner (31 percent). Table 16.2.1 Persons committing physical violence: women Among women age 15-49 who have experienced physical violence since age 15, percentage who report specific persons who committed the violence, according to the respondent's current marital status, Uganda 2011 Person Marital status Total Ever married Never married Current husband/partner 60.0 na 47.5 Former husband/partner 18.9 na 15.0 Current boyfriend 2.0 8.6 3.4 Former boyfriend 2.3 0.6 2.0 Father/step-father 12.7 20.8 14.4 Mother/step-mother 12.7 23.9 15.0 Sister/brother 5.9 8.6 6.5 Daughter/son 0.2 0.0 0.1 Other relative 6.9 8.0 7.2 Mother-in-law 0.1 na 0.1 Father-in-law 0.1 na 0.1 Other in-law 1.5 na 1.2 Teacher 10.1 56.6 19.8 Employer/someone at work 0.1 3.6 0.9 Police/soldier 0.1 0.5 0.1 Other 8.5 9.2 8.6 Number of women 914 240 1,154 Note: Women can report more than one person who committed the violence na = Not applicable Among never-married women who have experienced physical violence since age 15, the most common perpetrators of violence are teachers (57 percent), followed by fathers or step-fathers (21 percent) and mothers or step-mothers (24 percent). Among never-married men, the most commonly reported perpetrators of physical violence since age 15 are others (45 percent), followed by teachers (34 percent) and father or step-father (18 percent). 16.4 EXPERIENCE OF SEXUAL VIOLENCE Tables 16.3.1 and 16.3.2 show the percentage of women and men, respectively, who have experienced sexual violence ever and in the past 12 months, according to background characteristics. Table 16.3.1 shows that 28 percent of women age 15-49 have ever experienced sexual violence and 16 percent have experienced sexual violence in the past 12 months. There are notable variations in the experience of sexual violence by age. Younger women (age 15-19) are less likely to report sexual violence ever and in the past 12 months than older women (19 and 9 percent, respectively). Muslim women, those of Basoga and Itesa ethnicity, and rural women are more likely than other women to have experienced sexual violence ever and in the past year. The percentage of women who have ever experienced sexual violence ranges from 17 percent of women in Karamoja to 35 percent of women in Central 2 region. Recent sexual violence among women ranges from 7 percent of women in Kampala to 22 percent of those in East Central region. Experience of sexual violence ever and in the past 12 months is lowest among never-married women (13 and 3 percent, respectively), women with no living children (16 and 5 percent, respectively), those with secondary or higher education (22 and 11 percent, respectively), and women in the highest wealth quintile (21 and 10 percent, respectively). Table 16.2.2 Persons committing physical violence: men Among men age 15-49 who have experienced physical violence since age 15, percentage who report specific persons who committed the violence, according to the respondent's current marital status, Uganda 2011 Person Marital status Total Ever married Never married Current wife/partner 31.1 na 19.4 Former wife/partner 5.4 na 3.4 Current girlfriend 0.2 0.4 0.3 Former girlfriend 1.9 1.1 1.6 Father/step-father 8.4 17.9 12.0 Mother/step-mother 5.4 8.0 6.4 Sister/brother 10.3 9.3 9.9 Daughter/son 0.2 0.7 0.4 Other relative 5.5 9.6 7.0 Other in-law 0.6 na 0.5 Teacher 12.9 34.3 21.0 Employer/someone at work 2.9 1.3 2.3 Police/soldier 6.5 3.6 5.4 Other 48.2 44.8 46.9 Number of men 572 345 917 Note: Men can report more than one person who committed the violence na = Not applicable 246 • Domestic Violence Table 16.3.1 Experience of sexual violence: women Percentage of women age 15-49 who have ever experienced sexual violence and percentage who have experienced sexual violence in the 12 months preceding the survey, by background characteristics, Uganda 2011 Background characteristic Percentage who have experienced sexual violence: Number of women Ever1 Past 12 months Age 15-19 18.9 8.8 464 20-24 26.7 17.3 412 25-29 31.0 21.9 384 30-39 30.5 18.9 482 40-49 34.3 14.8 315 Religion Catholic 28.6 17.2 827 Protestant 26.1 13.9 591 Muslim 30.2 21.4 279 Pentecostal 26.6 13.3 306 SDA/Other (28.3) (16.7) 36 Ethnicity Baganda 27.6 12.7 368 Banyankole 26.2 13.7 207 Basoga 31.1 18.7 153 Bakiga 22.0 15.4 149 Itesa 30.2 23.2 162 Other 28.2 16.7 1,017 Residence Urban 24.4 12.9 398 Rural 28.6 17.1 1,658 Region Kampala 18.9 7.2 185 Central 1 32.7 16.2 231 Central 2 34.7 20.9 221 East Central 34.0 21.8 185 Eastern 32.9 19.8 314 Karamoja 17.2 10.9 63 North 24.6 20.6 178 West Nile 23.5 13.7 127 Western 24.4 15.5 288 Southwest 24.1 11.1 263 Marital status Never married 13.4 3.2 468 Married or living together 29.9 22.2 1,307 Divorced/separated/widowed 42.1 10.5 281 Employment Employed for cash 30.9 19.3 1,025 Employed not for cash 28.5 14.1 447 Not employed 21.9 12.5 584 Number of living children 0 16.4 5.4 517 1-2 27.3 18.9 509 3-4 34.8 21.9 442 5+ 33.0 19.2 588 Education No education 28.3 16.9 283 Primary 30.6 18.8 1,187 Secondary + 21.9 10.8 586 Wealth quintile Lowest 32.8 21.5 360 Second 27.1 17.8 360 Middle 30.8 19.0 389 Fourth 29.1 16.1 436 Highest 21.4 9.5 511 Total 15-49 27.8 16.2 2,056 Figures in parentheses are based on 25-49 unweighted cases. 1 Includes violence in the past 12 months Domestic Violence • 247 Table 16.3.2 shows that 9 percent of men age 15-49 have ever experienced sexual violence and 4 percent have experienced sexual violence in the past 12 months. The variation by background characteristics generally follows the same pattern as for women. Table 16.3.2 Experience of sexual violence: men Percentage of men age 15-49 who have ever experienced sexual violence and percentage who have experienced sexual violence in the 12 months preceding the survey, by background characteristics, Uganda 2011 Background characteristic Percentage who have experienced sexual violence: Number of men Ever1 Past 12 months Age 15-19 5.9 1.5 432 20-24 10.7 6.6 238 25-29 7.5 3.6 262 30-39 10.7 4.8 450 40-49 10.4 3.2 273 Religion Catholic 7.2 2.6 739 Protestant 8.1 4.6 525 Muslim 14.7 4.8 202 Pentecostal 11.5 3.6 130 SDA/Other (10.8) (6.3) 59 Ethnicity Baganda 8.3 4.4 273 Banyankole 8.5 3.5 170 Basoga 12.9 4.3 151 Bakiga 8.7 5.3 116 Itesa 14.9 8.6 113 Other 7.6 2.6 831 Residence Urban 7.7 3.1 335 Rural 9.1 3.9 1,320 Region Kampala 3.9 1.4 170 Central 1 13.6 5.4 169 Central 2 10.9 5.8 174 East Central 11.7 4.1 181 Eastern 14.2 6.5 216 Karamoja 8.8 0.0 44 North 2.5 0.5 142 West Nile 2.0 0.9 102 Western 9.8 4.1 247 Southwest 5.9 3.4 208 Marital status Never married 5.5 1.5 645 Married or living together 10.2 4.8 928 Divorced/separated/widowed 19.9 8.3 81 Employment Employed for cash 9.5 4.1 1,276 Employed not for cash 7.7 2.6 278 Not employed 3.7 2.4 99 Number of living children 0 5.9 2.5 687 1-2 13.6 7.0 288 3-4 10.7 6.0 251 5+ 9.3 2.2 428 Education No education 14.0 3.7 72 Primary 9.2 3.8 974 Secondary + 7.7 3.6 608 Wealth quintile Lowest 8.8 4.0 256 Second 8.0 2.6 327 Middle 11.2 5.0 307 Fourth 8.7 3.5 372 Highest 8.1 3.7 392 Total 15-49 8.9 3.7 1,654 50-54 12.3 5.3 76 Total 15-54 9.0 3.8 1,730 Figures in parentheses are based on 25-49 unweighted cases. 1 Includes violence in the past 12 months 248 • Domestic Violence 16.5 PERPETRATORS OF SEXUAL VIOLENCE Tables 16.4.1 and 16.4.2 show perpetrators of sexual violence, according to women’s and men’s marital status, respectively, among those who have ever experienced sexual violence. Among ever-married women and men, the most commonly reported perpetrators of sexual vio- lence are current spouses/partners (55 and 38 percent, respectively), followed by former spouses/partners (18 and 17 percent, respectively). Among never-married respondents who have ever experienced sexual violence, the most common perpetrators of violence are strangers (reported by 29 percent of women and 36 percent of men), followed by friends or acquaintances (reported by 18 percent of women and 23 percent of men), and other relatives (reported by 15 percent of women and 23 percent of men). Table 16.4.1 Persons committing sexual violence: women Among women age 15-49 who have experienced sexual violence, percentage who report specific persons who committed the violence according to the respondent's current marital status, Uganda 2011 Person Marital status Total Ever married Never married Current husband/partner 55.4 na 49.3 Former husband/partner 17.7 na 15.7 Current/former boyfriend 1.0 (9.6) 2.0 Father/step father 0.0 (1.0) 0.1 Brother/step brother 0.3 (1.5) 0.4 Other relative 3.4 (15.0) 4.7 In-law 1.5 na 1.9 Own friend/acquaintance 4.1 (18.1) 5.6 Family friend 1.0 (13.2) 2.4 Teacher 1.0 (2.0) 1.1 Police/soldier 0.7 (0.0) 0.6 Stranger 12.3 (29.3) 14.1 Other 1.6 (5.1) 2.0 Number of women 509 63 572 na = Not applicable Figures in parentheses are based on 25-49 unweighted cases. 16.6 AGE AT FIRST EXPERIENCE OF NON-SPOUSAL SEXUAL VIOLENCE Tables 16.5.1 and 16.5.2 show the percent distribution of respondents age 15-49 that experienced non-spousal sexual violence by specific exact ages, according to current age and current marital status. Overall, 89 percent of women and 94 percent of men have not experienced non-spousal sexual violence. Among women and men, 1 percent or less experienced non-spousal sexual violence by exact age of 10 or 12. Six percent of women and 2 percent of men experienced non-spousal sexual violence by age 15, 9 percent of women and 3 percent of men by age 18, and 10 percent of women and 5 percent of men experienced non-spousal sexual violence by age 22. Among women 40-49, the percentage that experienced non-spousal sexual violence by exact age 15, 18, and 22 is highest when compared with younger women. Further, a higher percentage of never- married women experienced non-spousal sexual violence by exact age 15, 18, and 22 than ever-married women. Among men, similar patterns are observed, but they are much less pronounced. Table 16.4.2 Persons committing sexual violence: men Among men age 15-49 who have experienced sexual violence, percentage who report specific persons who committed the violence according to the respondent's current marital status, Uganda 2011 Person Marital status Total Ever married Never married Current wife/partner 38.2 na 28.9 Former wife/partner 17.1 na 12.9 Current/former girlfriend 6.8 (1.3) 5.4 Other relative 2.4 (23.0) 7.4 In-law 4.3 na 4.9 Own friend/acquaintance 12.9 (22.5) 15.2 Family friend 7.4 (0.0) 5.6 Employer/someone at work 0.2 (0.0) 0.2 Police/soldier 0.6 (0.0) 0.4 Stranger 6.4 (35.7) 13.5 Other 3.4 (10.8) 5.2 Number of men 111 36 147 na = Not applicable Figures in parentheses are based on 25-49 unweighted cases. Domestic Violence • 249 Table 16.5.1 Age at first experience of non-spousal sexual violence: women Percent distribution of women age 15-49 who experienced non-spousal sexual violence by specific exact ages, according to current age and current marital status, Uganda 2011 Background characteristic Percentage who first experienced non-spousal sexual violence by exact age: Percentage who have not experienced non-spousal sexual violence Number of women 10 12 15 18 22 Age 15-19 0.8 1.1 8.9 na na 86.2 464 20-24 0.4 0.9 5.9 8.3 na 87.6 412 25-29 0.4 1.0 3.2 6.6 7.4 91.4 384 30-39 0.8 0.8 4.1 6.3 7.5 90.9 482 40-49 0.1 1.3 7.9 9.9 11.5 86.1 315 Marital status Never married 0.9 1.5 8.4 12.3 13.4 86.6 468 Ever married 0.4 0.9 5.2 7.9 9.5 89.1 1,588 Total 0.5 1.0 5.9 8.9 10.4 88.5 2,056 na = Not applicable Table 16.5.2 Age at first experience of non-spousal sexual violence: men Percent distribution of men age 15-49 who experienced non-spousal sexual violence by specific exact ages, according to current age and current marital status, Uganda 2011 Background characteristic Percentage who first experienced non-spousal sexual violence by exact age: Percentage who have not experienced non-spousal sexual violence Number of men 10 12 15 18 22 Age 15-19 1.2 1.7 3.6 na na 94.2 432 20-24 0.3 0.3 1.4 3.2 na 92.3 238 25-29 0.4 0.7 1.1 1.3 2.7 95.8 262 30-39 0.0 0.3 0.5 1.1 3.0 94.6 450 40-49 0.7 1.0 1.6 4.4 6.9 91.1 273 Marital status Never married 1.0 1.3 2.9 4.3 5.3 94.5 645 Ever married 0.3 0.6 1.0 2.5 4.6 93.4 1,009 Total 15-49 0.5 0.9 1.7 3.2 4.9 93.8 1,654 na = Not applicable 16.7 EXPERIENCE OF DIFFERENT FORMS OF VIOLENCE Tables 16.6.1 and 16.6.2 present information on the experience of various forms of violence among respondents age 15-49. Table 16.6.1 shows that 62 percent of women age 15-49 reported that they have experienced either physical or sexual violence. Thirty-four percent have experienced physical violence only, 6 percent have experienced sexual violence only, and 22 percent have experienced both physical and sexual violence. The percentage of women who have ever experienced physical or sexual violence increases only slightly with age. Overall, 59 percent of men age 15-49 reported that they have experienced either physical or sexual violence; 50 percent have experienced physical violence only, 3 percent have experienced sexual violence only, and 6 percent have experienced both physical and sexual violence. There is no clear pattern in the relationship of various forms of violence by age (Table 16.6.2). 250 • Domestic Violence Table 16.6.1 Experience of different forms of violence: women Percentage of women age 15-49 who have ever experienced different forms of violence by current age, Uganda 2011 Age Physical violence only Sexual violence only Physical and sexual violence Physical or sexual violence Number of women 15-19 38.7 3.3 15.6 57.6 464 15-17 39.3 2.4 13.9 55.6 277 18-19 37.8 4.6 18.2 60.7 187 20-24 37.6 6.2 20.5 64.2 412 25-29 33.4 9.2 21.8 64.5 384 30-39 31.1 6.2 24.3 61.6 482 40-49 30.3 6.1 28.1 64.6 315 Total 34.4 6.1 21.7 62.2 2,056 Table 16.6.2 Experience of different forms of violence: men Percentage of men age 15-49 who have ever experienced different forms of violence by current age, Uganda 2011 Age Physical violence only Sexual violence only Physical and sexual violence Physical or sexual violence Number of men 15-19 50.0 1.9 4.0 55.9 432 15-17 47.0 2.3 4.7 53.9 301 18-19 57.0 0.8 2.6 60.4 130 20-24 51.4 4.7 6.0 62.0 238 25-29 53.3 2.8 4.7 60.8 262 30-39 48.5 2.1 8.5 59.2 450 40-49 45.6 5.2 5.2 56.0 273 Total 15-49 49.6 3.0 5.8 58.5 1,654 50-54 55.0 4.8 7.5 67.3 76 Total 15-54 49.8 3.1 5.9 58.8 1,730 16.8 VIOLENCE DURING PREGNANCY Respondents who had ever been pregnant were asked specifically whether they had ever experienced physical violence while pregnant and, if so, who the perpetrators of the violence were. Table 16.7 shows that 16 percent of women experienced physical violence during pregnancy. This percentage increases with age from 9 percent among women age 15-19 to 24 percent among those age 40-49. Physical violence during pregnancy is higher among Pentecostal women (24 percent), those of Itesa ethnic background (27 percent), women in rural areas (17 percent), and those residing in Eastern region (25 percent). Women who are divorced, separated, or widowed are more likely to report experiencing violence during pregnancy (25 percent) than women who are currently married (15 percent) or never married (3 percent). Women with no living children (5 percent) or with one to four children (11-14 percent) are substantially less likely to report violence during pregnancy than women with five or more children (24 percent). The experience of violence during pregnancy declines with education, from 21 percent among women with no education to 10 percent among women with secondary or higher education. Similarly, women in the lowest wealth quintile are more likely than those in the highest wealth quintile to have experienced violence during pregnancy (24 percent versus 10 percent). Domestic Violence • 251 Table 16.7 Experience of violence during pregnancy Among women age 15-49 who have ever been pregnant, percentage who have ever experienced physical violence during pregnancy, by background characteristics, Uganda 2011 Background characteristic Percentage who experienced violence during pregnancy Number of women who have ever been pregnant Age 15-19 8.5 129 20-24 14.2 338 25-29 14.9 369 30-39 16.3 475 40-49 23.8 306 Religion Catholic 14.8 649 Protestant 16.3 448 Muslim 13.1 233 Pentecostal 23.6 241 SDA/Other (17.1) 45 Ethnicity Baganda 5.3 261 Banyankole 17.0 157 Basoga 14.0 136 Bakiga 12.6 113 Itesa 26.9 127 Other 19.0 822 Residence Urban 12.5 289 Rural 17.2 1,327 Region Kampala 19.0 124 Central 1 7.7 179 Central 2 15.7 177 East Central 11.6 158 Eastern 24.8 252 Karamoja 17.1 48 North 18.7 149 West Nile 23.3 101 Western 12.0 237 Southwest 15.8 191 Marital status Never married 2.6 80 Married or living together 15.4 1,266 Divorced/separated/widowed 24.7 270 Number of living children 0 5.4 77 1-2 11.2 509 3-4 14.1 442 5+ 23.9 588 Education No education 21.1 268 Primary 17.7 971 Secondary + 9.6 377 Wealth quintile Lowest 24.1 310 Second 17.5 310 Middle 15.4 312 Fourth 15.4 332 Highest 10.3 352 Total 15-49 16.3 1,616 Note: Figures in parentheses are based on 25-49 unweighted cases. 252 • Domestic Violence 16.9 MARITAL CONTROL BY SPOUSE Close control and monitoring of their wives’/husbands’ behavior by their spouse is known to be an important warning sign and correlate of violence in a relationship. A series of questions were included in the 2011 UDHS to elicit the degree of marital control exercised by husbands or wives over their spouses. Controlling behaviors most often manifest themselves in terms of extreme possessiveness, jealousy, and attempts to isolate the spouse from their family and friends. To determine the degree of marital control, ever-married women and men were asked whether their current or former spouse exhibited each of the following controlling behaviors: (1) is jealous or gets angry if she/he talks to other men/women, (2) frequently accuses her/him of being unfaithful, (3) does not permit meetings with female/male friends, (4) tries to limit contact with her/his family, and (5) insists on knowing where she/he is at all times. In addition, men were asked if their wife does not trust them with money. Because the concentration of such behaviors is more significant than the display of any single behavior, the proportion of respondents whose spouses display at least three of the specified behaviors is highlighted. Tables 16.8.1 and 16.8.2 present the percentage of ever-married women and men, respectively, whose spouses display each of the listed behaviors, by selected background characteristics. The main controlling behaviors women experienced from their husbands were jealousy or anger if they talked to other men (59 percent) and husbands insisting on knowing where they are at all times (56 percent). The next most common behaviors were husbands frequently accusing them of being unfaithful (34 percent) and not permitting them to meet female friends (29 percent). Thirty-nine percent of ever-married women say that their husbands display three or more of these controlling behaviors. Women 25-29 (44 percent), Muslim women (44 percent), those of Itesa ethnicity (49 percent), women living in Eastern region (51 percent), and those who have been previously married (51 percent) are more likely than other women to report that their husbands display three or more of these controlling behaviors. Having a husband who displays at least three controlling behaviors is least likely among women with no living children (31 percent) and those employed not for cash (31 percent). This percentage increases somewhat with woman’s education, but there is no clear relationship with wealth. Domestic Violence • 253 Table 16.8.1 Marital control exercised by husbands Percentage of ever-married women age 15-49 whose husbands/partners have ever demonstrated specific types of controlling behaviours, by background characteristics, Uganda 2011 Background characteristic Percentage of women whose husband/partner: Number of women Is jealous or angry if she talks to other men Frequently accuses her of being unfaithful Does not permit her to meet her female friends Tries to limit her contact with her family Insists on knowing where she is at all times Displays 3 or more of the specific behaviours Displays none of the specific behaviours Age 15-19 50.1 27.3 24.8 22.7 42.5 27.4 27.9 122 20-24 59.4 36.6 31.4 24.4 57.5 41.6 22.7 314 25-29 59.8 36.1 32.0 19.7 64.7 43.7 21.6 365 30-39 60.0 34.4 27.7 19.6 56.8 40.5 27.5 477 40-49 58.7 31.5 24.5 17.3 46.6 33.0 28.0 310 Religion Catholic 57.4 36.9 29.6 23.8 56.3 40.5 24.0 638 Protestant 60.3 29.7 25.4 15.8 53.7 34.7 25.0 442 Muslim 62.3 34.1 36.3 22.6 57.0 44.3 28.7 223 Pentecostal 59.9 36.6 24.4 18.3 56.5 37.5 24.7 242 SDA/Other (38.8) (24.9) (28.3) (17.2) (53.6) (41.9) (34.4) 43 Ethnicity Baganda 55.7 34.8 31.3 16.7 50.3 37.6 26.0 246 Banyankole 50.7 27.2 26.0 18.3 54.0 31.4 34.4 155 Basoga 74.1 35.6 35.0 19.1 61.5 44.8 19.3 132 Bakiga 45.0 28.7 19.4 19.4 38.1 27.5 50.0 113 Itesa 70.7 46.0 25.1 20.4 61.7 49.3 14.3 122 Other 58.9 34.0 29.0 22.2 58.1 40.0 22.7 820 Residence Urban 58.3 32.4 31.2 17.6 54.4 38.4 24.9 271 Rural 58.9 34.5 28.0 20.9 55.9 39.1 25.4 1,317 Region Kampala 54.0 38.1 33.3 14.5 48.9 37.0 24.9 116 Central 1 57.2 37.2 24.4 20.0 56.0 37.0 23.5 176 Central 2 65.2 41.6 38.4 23.9 55.2 48.3 22.7 171 East Central 64.4 31.0 32.1 19.7 59.3 41.1 26.1 152 Eastern 74.3 44.8 30.0 31.4 60.2 51.3 11.7 253 Karamoja 35.2 19.5 11.0 4.4 29.9 15.1 49.1 51 North 48.5 23.2 34.7 18.3 72.9 35.5 20.4 142 West Nile 55.7 25.9 35.8 20.8 60.8 37.7 26.9 104 Western 66.5 36.3 20.7 16.3 52.5 37.4 21.3 226 Southwest 39.5 24.6 21.5 17.4 45.9 27.5 47.9 195 Marital status Married or living together 56.4 31.9 26.2 18.5 54.8 36.4 26.4 1,307 Divorced/separated/widowed 70.0 44.3 39.7 29.2 59.7 51.3 20.2 281 Number of living children 0 51.8 22.2 29.2 22.2 44.3 30.5 24.9 111 1-2 58.6 35.3 28.4 20.7 57.3 38.5 24.7 458 3-4 60.8 38.1 34.1 24.2 61.8 46.0 22.1 434 5+ 58.8 32.5 24.4 16.9 51.9 35.8 28.3 585 Employment Employed for cash 63.0 36.1 29.9 20.3 59.3 41.2 21.3 905 Employed not for cash 51.4 24.8 22.5 19.5 47.1 30.5 36.0 338 Not employed 54.9 38.2 31.0 21.4 54.4 41.7 25.3 344 Education No education 55.4 32.2 23.0 15.4 49.1 34.6 31.7 268 Primary 61.7 34.1 29.8 22.0 56.7 39.8 23.4 965 Secondary + 53.5 35.7 29.5 19.6 57.6 40.0 25.8 355 Wealth quintile Lowest 61.2 37.8 26.9 20.1 53.5 38.8 25.2 309 Second 59.8 35.8 28.6 19.3 60.3 39.1 22.7 303 Middle 56.3 34.1 24.8 23.2 56.1 38.4 27.0 310 Fourth 60.8 33.6 31.1 22.2 55.5 43.4 25.7 317 Highest 56.2 29.8 31.0 17.4 53.3 35.6 26.0 348 Total 58.8 34.1 28.6 20.4 55.6 39.0 25.3 1,588 Note: Husband/partner refers to the current husband/partner for currently married women and the most recent husband/partner for divorced, separated, or widowed women. Figures in parentheses are based on 25-49 unweighted cases. 254 • Domestic Violence Table 16.8.2 shows that similar to women, the main controlling behaviors men age 15-49 experi- enced from their wives were jealousy or anger if they talked to other women (57 percent) and wives insisting on knowing where they are at all times (47 percent). Thirty-five percent of men reported that their wives frequently accuse them of being unfaithful, 21 percent report that the wives do not trust them with money, and 16 percent say that their wives do not permit them to meet male friends. Table 16.8.2 Marital control exercised by wives Percentage of ever-married men age 15-49 whose wives/partners have ever demonstrated specific types of controlling behaviors, by background characteristics, Uganda 2011 Background characteristic Percentage of men whose wife/partner: Number of men Is jealous or angry if he talks to other women Frequently accuses him of being unfaithful Does not permit him to meet his male friends Tries to limit his contact with his family Insists on knowing where he is at all times Does not trust him with any money Displays 3 or more of the specific behaviors Displays none of the specific behaviors Age 15-19 * * * * * * * * 13 20-24 63.9 42.5 20.5 6.0 39.5 22.5 37.4 19.1 88 25-29 66.3 37.6 18.9 8.9 50.5 19.5 33.5 21.0 209 30-39 54.2 36.1 17.4 5.5 51.3 22.5 33.6 26.8 429 40-49 52.8 31.4 9.4 5.0 39.3 18.7 22.5 25.5 270 Religion Catholic 57.4 35.4 14.7 4.7 44.1 18.7 28.9 24.1 452 Protestant 55.5 34.4 17.2 7.5 51.5 23.0 32.6 24.8 318 Muslim 69.8 50.6 19.4 4.9 53.8 23.8 40.7 16.4 114 Pentecostal 47.6 23.2 15.3 5.0 45.0 18.2 26.6 33.5 89 SDA/Other (59.2) (24.8) (13.5) (17.0) (29.3) (27.1) (24.5) (24.5) 37 Ethnicity Baganda 68.7 50.6 14.4 7.0 61.8 33.5 49.0 14.5 165 Banyankole 54.1 34.8 15.8 8.0 41.3 15.1 26.0 28.0 93 Basoga 75.6 51.6 20.5 2.5 53.3 23.3 38.9 11.5 88 Bakiga 40.4 14.1 14.9 8.1 46.0 16.6 18.4 33.4 85 Itesa 66.6 31.2 3.1 2.6 45.6 14.8 24.7 17.2 76 Other 52.6 31.7 18.0 6.2 42.7 19.1 27.8 28.6 502 Residence Urban 68.5 37.9 20.8 6.2 58.3 24.7 39.7 17.9 182 Rural 55.0 34.8 15.0 6.0 44.7 20.1 29.1 25.7 827 Region Kampala 69.8 35.4 18.9 8.6 58.8 21.0 38.7 19.5 87 Central 1 71.7 60.2 18.7 12.1 64.6 31.1 51.0 9.9 106 Central 2 61.1 50.3 20.0 7.5 63.2 43.7 50.4 15.8 110 East Central 70.9 50.8 16.5 4.5 46.5 22.9 35.4 14.4 104 Eastern 59.6 32.9 10.1 5.9 44.5 15.7 27.8 21.1 156 Karamoja 34.6 18.0 1.0 1.0 13.3 1.0 2.2 56.1 34 North 50.0 20.0 4.4 1.8 41.1 11.4 13.6 30.9 82 West Nile 54.3 34.7 18.5 3.2 24.8 13.2 23.8 36.8 66 Western 47.4 22.4 25.6 5.4 52.6 23.3 28.1 25.9 148 Southwest 43.1 20.8 14.6 5.8 31.2 9.1 18.0 39.2 117 Marital status Married or living together 56.5 34.0 13.8 4.9 46.0 19.7 29.2 25.4 928 Divorced/separated/widowed 68.0 50.6 42.3 18.7 59.5 34.4 52.3 12.5 81 Number of living children 0 64.9 39.6 27.1 9.8 55.0 26.3 44.6 17.9 62 1-2 60.1 33.4 18.9 7.7 51.9 23.2 33.5 21.2 272 3-4 58.7 36.6 17.7 5.3 50.6 21.6 33.2 24.8 248 5+ 53.9 35.2 11.7 4.9 40.9 18.2 26.2 27.0 428 Employment Employed for cash 57.1 36.1 16.5 6.1 48.2 21.3 32.0 24.0 863 Employed not for cash 58.4 32.3 14.8 6.8 38.9 20.7 28.1 27.4 130 Not employed * * * * * * * * 16 Education No education 45.1 29.3 10.9 13.8 34.3 23.8 23.7 38.7 67 Primary 57.5 36.7 16.4 5.8 47.1 21.3 30.9 23.7 609 Secondary + 59.8 34.1 16.4 5.0 49.8 19.5 32.8 22.5 333 Wealth quintile Lowest 46.8 27.8 11.0 6.7 36.8 17.4 21.7 31.8 189 Second 56.4 34.0 13.0 6.4 43.1 20.8 27.1 25.8 225 Middle 61.0 39.2 17.3 6.4 46.5 22.1 35.7 25.7 187 Fourth 56.4 37.7 21.6 4.6 50.7 20.3 33.7 21.3 218 Highest 66.7 37.8 17.1 6.4 58.6 24.0 37.4 17.3 190 Total 15-49 57.4 35.3 16.0 6.0 47.1 20.9 31.0 24.3 1,009 50-54 56.5 47.9 13.0 6.5 48.7 18.5 39.3 30.8 76 Total 15-54 57.3 36.2 15.8 6.1 47.2 20.7 31.6 24.8 1,085 Note: Wife/partner refers to the current wife/partner for currently married men and the most recent wife/partner for divorced, separated, or widowed men. An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. Figures in parentheses are based on 25-49 unweighted cases. Domestic Violence • 255 Three in ten ever-married men (31 percent) say that their wives display three or more of these controlling behaviors. This percentage decreases with age. It is higher among Muslim men, those of Baganda ethnicity, urban men, men living in Central 1 and Central 2 regions, and those who have been previously married. The percentage of men whose wives display at least three controlling behaviours decreases with an increase in the number of living children, and surprisingly, increase with education and wealth. 16.10 FORMS OF SPOUSAL VIOLENCE Different types of violence are not mutually exclusive, and women may report multiple forms of violence. Research suggests that physical violence in intimate relationships is often accompanied by psychological abuse and, in one-third to more than one-half of cases, by sexual abuse (Krug et al., 2002). Tables 16.9.1 and 16.9.2 show the percentage of ever-married women and men age 15-49, respectively, who have experienced various forms of violence by their spouse, over the course of the marriage and in the 12 months preceding the survey. Note that respondents who are currently married reported on violence by their current spouse, and respondents who are widowed, divorced, or separated reported on violence by their most recent spouse. Table 16.9.1 shows that 43 percent of ever-married women report ever experiencing physical violence committed by their current or most recent husband or partner, 27 percent report sexual violence, and 43 percent report emotional violence. More than half of ever-married women (51 percent) have experienced physical and/or sexual violence, and six in ten have experienced at least one of the three forms of spousal violence. The most common form of spousal violence ever experienced by ever-married women, is being slapped (37 percent) (Figure 16.1). Twenty-four percent of ever-married women report having been pushed, shaken, or had something thrown at them, 26 percent have been physically forced to have sexual intercourse by their husbands when they did not want to, and 35 percent report that their husbands have insulted them or made them feel bad about themselves. Twenty-five percent of ever-married women report experiencing spousal physical violence in the past 12 months, with 16 percent having experienced violence sometimes and 9 percent having experienced it often. Twenty-one percent report having experienced spousal sexual violence in the past 12 months, 12 percent sometimes, 9 percent often. Additionally, 33 percent of women report spousal emotional violence in the past 12 months, 20 percent sometimes, 12 percent often. Overall, 45 percent of ever-married women have experienced at least one of the three forms of violence by their current or most recent husband or partner in the past year. Fifty-six percent of ever-married women reported having ever experienced physical and/or sexual violence by any husband or partner. 256 • Domestic Violence Table 16.9.1 Forms of spousal violence: women Percentage of ever-married women age 15-49 who have experienced various forms of violence ever or in the 12 months preceding the survey, committed by their husband/partner, Uganda 2011 Type of violence Ever In the past 12 months1 Often Sometimes Often or sometimes SPOUSAL VIOLENCE COMMITTED BY CURRENT OR MOST RECENT HUSBAND/PART Physical violence Any physical violence 42.7 8.6 16.4 24.9 Pushed her, shook her, or threw something at her 23.8 5.2 9.7 15.0 Slapped her 36.5 4.4 16.2 20.6 Twisted her arm or pulled her hair 13.0 1.9 5.6 7.4 Punched her with his fist or with something that could hurt her 18.0 3.3 7.0 10.2 Kicked her, dragged her, or beat her up 17.9 3.1 6.6 9.7 Tried to choke her or burn her on purpose 7.3 1.0 2.4 3.4 Threatened her or attacked her with a knife, gun, or other weapon 7.7 1.6 2.4 4.0 Sexual violence Any sexual violence 27.3 8.7 12.2 20.9 Physically forced her to have sexual intercourse with him when she did not want to 25.7 8.1 11.5 19.5 Physically forced her to perform any other sexual acts she did not want to 10.5 2.6 5.3 7.9 Forced her with threats or in any other way to perform sexual acts she did not want to 5.9 1.6 2.6 4.1 Emotional violence Any emotional violence 42.9 12.3 20.3 32.6 Said or did something to humiliate her in front of others 22.0 5.8 10.1 15.8 Threatened to hurt or harm her or someone she cared about 23.3 5.7 10.0 15.7 Insulted her or made her feel bad about herself 35.2 10.1 16.6 26.7 Any form of physical and/or sexual violence 50.5 14.0 20.6 34.6 Any form of emotional and/or physical and/or sexual violence 59.7 19.6 24.9 44.5 SPOUSAL VIOLENCE COMMITTED BY ANY HUSBAND/PARTNER Physical violence 48.3 na na 24.2 Sexual violence 30.8 na na 19.9 Physical and/or sexual violence 55.6 na na 33.3 Number of ever married women 1,588 1,588 1,588 1,588 1 For widows, estimates of spousal violence by the current or most recent spouse in the past 12 months are not known; hence widows are excluded from the estimate of spousal violence by the current or most recent spouse in the past 12 months. However, widows are included in the estimate of spousal violence committed by any husband/partner in the past 12 months. na = Not applicable Domestic Violence • 257 Figure 16.1 Percentage of ever-married women age 15-49 who have experienced specific types of spousal physical and sexual violence by the current or most recent husband/partner 24 37 13 18 18 7 8 26 11 6 15 21 7 10 10 3 4 20 8 4 Pushed her, shook her, or threw something at her Slapped her Twisted her arm or pulled her hair Punched her with his fist or with something Kicked her, dragged her, or beat her up Tried to choke her or burn her on purpose Threatened her or attacked her with a Physically forced her to have sexual intercourse Physically forced her to perform any other sexual Forced her with threats or in any other way to Ever In the past 12 months that could hurt her gun, or other weapon with hm when she did not want to acts she did not want to perform sexual acts she did not want to Table 16.9.2 shows that among ever-married men, 21 percent report ever experiencing physical violence by their current or most recent wife or partner, 7 percent report sexual violence, and 33 percent report emotional violence. About one in four ever-married men (24 percent) have ever experienced physical and/or sexual violence, and more than four in ten (42 percent) have experienced at least one of the three forms of spousal violence. Fifteen percent of ever-married men reported having been pushed, shaken, or had something thrown at them, and 9 percent reported having been slapped. Five percent have been physically forced to have sexual intercourse by their current or most recent wives or partners when they did not want to, and 25 percent report that their current or most recent spouse or partner insulted them or made them feel bad about themselves. Over the past 12 months, 12 percent of ever-married men reported experiencing spousal physical violence in the past 12 months, with 11 percent having experienced violence sometimes and 2 percent having experienced it often. Five percent reported having experienced spousal sexual violence in the past 12 months, 4 percent sometimes, 1 percent often. Finally, 26 percent of men reported emotional violence in the past 12 months, 21 percent sometimes, 5 percent often. Overall, one-third of ever-married men (33 percent) have experienced at least one of the three forms of spousal violence by their current or most recent wife or partner in the past year. About three in ten ever-married men (31 percent) report having ever experienced physical and/or sexual violence by any wife or partner. 258 • Domestic Violence Table 16.9.2 Forms of spousal violence: men Percentage of ever-married men age 15-49 who have experienced various forms of violence ever or in the 12 months preceding the survey, committed by their wife/partner, Uganda 2011 Type of violence Ever In the past 12 months1 Often Sometimes Often or sometimes SPOUSAL VIOLENCE COMMITTED BY CURRENT OR MOST RECENT WIFE/PARTNER Physical violence Any physical violence 20.7 1.5 10.7 12.2 Pushed him, shook him, or threw something at him 15.4 0.9 8.6 9.5 Slapped him 8.6 0.7 3.9 4.6 Twisted his arm or pulled his hair 5.7 0.3 3.8 4.1 Punched him with her fist or with something that could hurt him 6.2 0.4 3.2 3.6 Kicked him, dragged him, or beat him up 3.2 0.2 1.4 1.6 Tried to choke him or burn him on purpose 3.1 0.2 1.6 1.8 Threatened him or attacked him with a knife, gun, or other weapon 4.0 0.1 1.8 2.0 Sexual violence Any sexual violence 7.1 1.0 4.4 5.4 Physically forced him to have sexual intercourse with her when he did not want to 5.0 0.4 3.2 3.7 Physically forced him to perform any other sexual acts he did not want to 3.0 0.7 1.7 2.4 Forced him with threats or in any other way to perform sexual acts he did not want to 1.1 0.3 0.4 0.7 Emotional violence Any emotional violence 33.3 5.0 21.3 26.3 Said or did something to humiliate him in front of others 18.3 1.9 10.9 12.8 Threatened to hurt or harm him or someone he cared about 12.7 1.4 7.3 8.7 Insulted him or made him feel bad about himself 24.8 3.9 15.9 19.9 Any form of physical and/or sexual violence 24.3 2.1 13.6 15.8 Any form of emotional and/or physical and/or sexual violence 42.3 6.0 26.8 32.7 Spousal violence committed by any wife/partner Physical violence 26.8 na na 12.7 Sexual violence 8.7 na na 5.4 Physical and/or sexual violence 30.6 na na 16.2 Number of ever married men 1,009 1,009 1,009 1,009 1 For widowers, estimates of spousal violence by the current or most recent spouse in the past 12 months are not known; hence widowers are excluded from the estimate of spousal violence by the current or most recent spouse in the past 12 months. However, widowers are included in the estimate of spousal violence committed by any wife/partner in the past 12 months. na = Not applicable 16.11 SPOUSAL VIOLENCE BY BACKGROUND CHARACTERISTICS Tables 16.10.1 and 16.10.2 show the percentages of ever-married women and men age 15-49, respectively, who have experienced spousal emotional, physical, or sexual violence by selected background characteristics. Six in ten ever-married women have experienced at least one form of spousal violence (emotional, physical, or sexual), and about one in seven (15 percent) have experienced all three forms of spousal violence. The percentage of women who have ever experienced at least one form of spousal violence tends to increase with age and with an increase in the number of living children. It is higher among Pentecostal women (65 percent) and those of Itesa ethnicity (74 percent), among rural women (61 percent), among women in Eastern region (71 percent), and women who are divorced, separated, or widowed (64 percent). Women with secondary or higher education and those in the wealthiest quintile are the least likely to have ever experienced at least one form of spousal violence. Domestic Violence • 259 Table 16.10.1 Spousal violence by background characteristics: women Percentage of ever-married women age 15-49 who have ever experienced emotional, physical, or sexual violence committed by their husband/partner, by background characteristics, Uganda 2011 Background characteristic Emotional violence Physical violence Sexual violence Physical and sexual Physical and sexual and emotional Physical or sexual Physical or sexual or emotional Number of ever- married women Age 15-19 28.1 26.6 22.9 13.3 8.8 36.1 45.8 122 20-24 36.0 43.7 25.5 18.8 13.6 50.3 56.7 314 25-29 45.0 43.1 28.8 17.9 15.2 54.0 63.0 365 30-39 44.2 43.3 28.2 20.5 15.8 51.0 60.5 477 40-49 51.2 46.8 27.5 23.0 19.3 51.2 62.9 310 Religion Catholic 40.9 45.8 26.2 20.4 15.6 51.5 60.7 638 Protestant 40.4 38.1 25.9 17.4 13.7 46.6 55.3 442 Muslim 42.8 35.4 33.2 19.5 14.9 49.1 60.2 223 Pentecostal 52.3 50.7 28.3 21.0 17.5 58.0 65.3 242 SDA/Other (46.0) (36.7) (21.8) (20.0) (20.0) (38.5) (54.1) 43 Ethnicity Baganda 35.9 21.9 23.0 10.8 8.7 34.1 49.3 246 Banyankole 46.8 43.9 24.5 21.7 18.8 46.8 58.9 155 Basoga 51.6 34.3 30.2 16.6 13.3 47.9 66.0 132 Bakiga 37.5 39.0 24.4 20.2 15.6 43.1 51.4 113 Itesa 49.0 63.6 36.3 28.3 20.5 71.6 74.3 122 Other 42.7 47.5 27.7 20.8 16.2 54.3 60.8 820 Residence Urban 34.9 33.0 25.3 14.3 11.1 44.0 52.8 271 Rural 44.5 44.7 27.7 20.6 16.3 51.8 61.1 1,317 Region Kampala 35.8 35.1 21.6 11.8 7.6 44.9 53.0 116 Central 1 40.8 28.4 23.9 16.4 13.7 35.9 52.4 176 Central 2 42.3 31.5 32.7 14.3 12.5 50.0 58.7 171 East Central 51.7 40.6 33.5 22.0 17.6 52.1 68.5 152 Eastern 48.0 58.0 36.4 30.2 22.1 64.2 71.3 253 Karamoja 35.3 38.0 15.0 14.2 11.8 38.7 45.0 51 North 50.2 56.4 26.4 22.3 18.8 60.6 65.0 142 West Nile 43.2 49.8 26.8 21.4 15.3 55.2 60.8 104 Western 31.6 44.2 23.0 17.0 11.9 50.2 54.6 226 Southwest 45.6 37.5 21.3 17.2 16.0 41.6 54.3 195 Marital status Married or living together 41.6 41.0 26.5 18.2 14.2 49.4 58.8 1,307 Divorced/separated/widowed 48.9 50.5 30.8 25.7 21.0 55.5 63.5 281 Number of living children 0 29.8 17.5 19.9 9.7 7.2 27.6 43.8 111 1-2 33.5 40.2 23.9 15.6 11.3 48.5 54.5 458 3-4 45.6 43.9 30.2 21.5 17.2 52.7 61.3 434 5+ 50.7 48.6 29.1 23.0 18.7 54.6 65.5 585 Employment Employed for cash 44.3 42.8 28.1 19.4 14.9 51.5 61.2 905 Employed not for cash 41.9 42.4 26.6 22.8 17.5 46.2 57.0 338 Not employed 40.1 42.8 25.9 16.8 14.4 51.9 58.3 344 Education No education 44.9 47.1 23.2 20.3 17.3 50.0 55.3 268 Primary 47.0 45.6 30.3 21.7 17.4 54.2 63.7 965 Secondary + 30.2 31.6 22.1 13.0 8.3 40.7 52.1 355 Wealth quintile Lowest 48.7 56.5 31.0 27.3 21.0 60.2 64.3 309 Second 43.2 47.3 27.4 20.8 16.2 53.9 61.0 303 Middle 45.6 47.8 28.1 20.8 17.4 55.0 65.1 310 Fourth 46.3 37.4 29.1 17.9 14.7 48.6 61.4 317 Highest 31.9 26.8 21.5 11.9 8.5 36.4 48.0 348 Total 15-49 42.9 42.7 27.3 19.5 15.4 50.5 59.7 1,588 Note: Husband/partner refers to the current husband/partner for currently married women and the most recent husband/partner for divorced, separated, or widowed women. Figures in parentheses are based on 25-49 unweighted cases. Table 16.10.2 shows that 42 percent of ever-married men have experienced at least one form of spousal violence (emotional, physical, or sexual), and just 3 percent have ever experienced all three forms of spousal violence. As with women, the percentage of men who have ever experienced at least one form of spousal violence increases with age. This percentage is higher among Catholic men (46 percent), Bakiga men (49 percent), men in rural areas (43 percent), those residing in Karamoja (56 percent), previously 260 • Domestic Violence married men (59 percent), and those with three or four living children. Men with secondary or higher education (39 percent) and those in the fourth highest wealth quintile (34 percent) are the least likely to have ever experienced at least one form of spousal violence. Table 16.10.2 Spousal violence by background characteristics: men Percentage of ever-married men age 15-49 who have ever experienced emotional, physical, or sexual violence committed by their wife/partner, by background characteristics, Uganda 2011 Background characteristic Emotional violence Physical violence Sexual violence Physical and sexual Physical and sexual and emotional Physical or sexual Physical or sexual or emotional Number of ever- married men Age 15-19 * * * * * * * 13 20-24 30.0 15.5 15.4 8.5 5.4 22.4 40.6 88 25-29 28.6 20.9 5.1 2.3 1.9 23.8 41.0 209 30-39 35.7 22.4 7.6 4.4 4.0 25.6 42.5 429 40-49 34.3 19.8 4.1 0.8 0.8 23.0 43.4 270 Religion Catholic 39.5 22.9 5.6 3.1 2.3 25.4 46.4 452 Protestant 24.0 19.2 8.3 3.2 2.6 24.3 37.7 318 Muslim 38.8 19.0 9.5 7.0 7.0 21.5 42.8 114 Pentecostal 28.5 16.3 6.9 3.1 3.1 20.1 36.9 89 SDA/Other (30.3) (22.0) (7.8) (0.0) (0.0) (29.9) (43.5) 37 Ethnicity Baganda 41.4 19.9 7.1 5.4 4.2 21.7 47.6 165 Banyankole 25.9 16.8 8.0 4.3 3.4 20.5 31.4 93 Basoga 23.7 14.7 7.2 4.8 3.8 17.1 31.3 88 Bakiga 30.2 19.8 14.3 3.2 1.0 30.9 48.9 85 Itesa 38.7 25.3 5.7 3.5 3.5 27.5 45.6 76 Other 33.3 22.2 5.8 2.5 2.5 25.5 42.9 502 Residence Urban 29.3 20.6 6.1 3.1 3.1 23.6 39.1 182 Rural 34.1 20.7 7.3 3.5 2.9 24.4 43.0 827 Region Kampala 28.8 21.9 2.8 1.0 1.0 23.6 42.1 87 Central 1 45.9 24.2 11.5 8.2 6.4 27.4 52.6 106 Central 2 40.0 26.6 7.3 4.9 4.9 29.0 49.6 110 East Central 23.7 12.8 6.9 3.3 2.5 16.4 31.4 104 Eastern 33.2 22.8 8.6 3.8 3.8 27.5 43.6 156 Karamoja 52.4 33.3 0.0 0.0 0.0 33.3 55.7 34 North 37.8 20.3 1.0 1.0 1.0 20.3 43.4 82 West Nile 33.4 20.5 2.3 1.2 1.2 21.6 44.2 66 Western 24.9 17.3 11.7 3.3 2.7 25.7 34.7 148 Southwest 29.2 16.3 7.5 3.5 1.9 20.3 38.1 117 Marital status Married or living together 31.6 19.2 6.4 2.9 2.3 22.6 40.9 928 Divorced/separated/widowed 52.2 38.0 15.1 9.9 9.9 43.3 58.7 81 Number of living children 0 22.9 11.4 13.5 4.4 4.4 20.5 31.1 62 1-2 29.4 20.0 8.7 4.7 3.1 24.0 40.3 272 3-4 39.9 23.9 7.5 4.4 4.4 26.9 48.5 248 5+ 33.3 20.6 4.9 2.0 1.8 23.5 41.6 428 Employment Employed for cash 34.0 18.8 7.3 3.4 2.8 22.7 41.9 863 Employed not for cash 31.7 28.2 6.2 4.0 4.0 30.4 43.0 130 Not employed * * * * * * * 16 Education No education 27.8 17.3 10.7 5.3 4.1 22.7 37.0 67 Primary 35.3 22.3 7.2 3.4 3.1 26.2 44.6 609 Secondary + 30.6 18.4 6.1 3.3 2.5 21.2 39.2 333 Wealth quintile Lowest 32.9 19.9 5.3 3.4 2.9 21.9 41.0 189 Second 37.7 25.8 9.0 4.1 3.6 30.7 48.9 225 Middle 36.1 19.6 8.0 3.5 3.0 24.1 44.0 187 Fourth 27.9 15.6 4.9 0.9 0.9 19.6 34.4 218 Highest 31.8 22.3 8.2 5.8 4.3 24.7 43.1 190 Total 15-49 33.3 20.7 7.1 3.5 2.9 24.3 42.3 1,009 50-54 40.3 20.1 6.1 0.8 0.8 25.5 47.4 76 Total 15-54 33.7 20.6 7.0 3.3 2.8 24.4 42.7 1,085 Note: Wife/partner refers to the current wife/partner for currently married men and the most recent wife/partner for divorced, separated, or widowed men. An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. Figures in parentheses are based on 25-49 unweighted cases. Domestic Violence • 261 16.12 VIOLENCE BY SPOUSAL CHARACTERISTICS AND WOMEN’S EMPOWERMENT INDICATORS Tables 16.11.1 and 16.11.2 present information on ever-married women and men age 15-49, respectively, who have experienced emotional, physical, or sexual violence committed by their spouse according to spousal characteristics and empowerment indicators. Table 16.11.1 shows that among ever-married women, spousal violence is highest among those whose husband has no or only primary education (60 and 66 percent, respectively), whose husband gets drunk very often (82 percent), who are better educated than the husband (64 percent), and who are one to four years younger than the husband (62 percent). Table 16.11.1 Spousal violence by husband's characteristics and empowerment indicators: women Percentage of ever-married women age15-49 who have ever experienced emotional, physical or sexual violence committed by their husband/partner, by husband's characteristics and empowerment indicators, Uganda 2011 Background characteristic Emotional violence Physical violence Sexual violence Physical and sexual Physical and sexual and emotional Physical or sexual Physical or sexual or emotional Number of ever- married women Husband's/partner's education No education 53.0 48.5 23.8 18.3 18.2 54.0 60.2 125 Primary 48.6 50.2 31.4 24.9 19.5 56.7 65.5 824 Secondary 34.0 33.9 23.3 13.1 10.1 44.1 52.4 447 More than secondary 32.6 26.4 20.1 10.2 7.0 36.3 52.9 141 Husband's/partner's alcohol consumption Does not drink 35.6 33.5 25.1 15.2 11.0 43.5 52.8 850 Drinks/never gets drunk 30.5 22.8 7.3 2.3 1.2 27.8 46.2 75 Gets drunk sometimes 41.8 48.1 23.5 17.5 13.6 54.1 61.5 384 Gets drunk very often 70.7 69.3 44.9 40.8 35.3 73.5 82.4 275 Spousal education difference Husband better educated 42.6 42.6 27.2 19.5 15.7 50.3 59.0 939 Wife better educated 46.4 42.2 29.9 19.7 14.3 52.4 64.0 308 Both equally educated 39.9 46.0 24.9 17.5 14.5 53.4 60.6 197 Neither educated 47.3 49.5 26.4 25.0 22.6 50.9 55.6 76 DK/missing 34.5 29.5 24.9 19.7 10.4 34.6 51.4 68 Spousal age difference1 Wife older 38.7 36.3 30.3 17.8 14.4 48.8 57.2 78 Wife is same age 27.8 51.2 19.4 14.0 8.4 56.6 59.1 61 Wife's 1-4 years younger 46.8 44.5 26.9 20.0 15.4 51.5 62.1 429 Wife's 5-9 years younger 41.1 40.9 28.2 18.7 14.1 50.4 59.4 433 Wife's 10+ years younger 38.1 35.6 23.7 15.5 13.0 43.8 53.5 300 Number of marital control behaviours displayed by husband/partner2 0 20.1 20.6 11.3 6.3 3.7 25.6 34.4 402 1-2 38.4 37.1 21.4 15.0 10.0 43.5 54.1 566 3-4 58.9 60.8 40.5 28.6 23.8 72.8 80.9 496 5-6 73.6 68.0 53.0 47.3 44.2 73.7 82.3 123 Number of decisions in which women participate1,3 0 40.8 45.0 30.4 19.3 15.6 56.1 63.9 262 1-2 44.8 42.0 26.0 18.8 14.7 49.1 59.8 603 3 37.8 37.4 24.9 16.7 12.6 45.7 54.5 442 Number of reasons for which wife-beating is justified4 0 35.2 38.8 25.0 17.5 12.6 46.3 54.1 647 1-2 47.8 43.5 29.1 20.7 18.0 51.9 61.9 487 3-4 48.9 49.3 25.0 19.9 15.2 54.4 65.0 355 5 48.0 40.8 41.6 25.5 21.3 56.8 66.2 98 Woman's father beat her mother Yes 50.0 53.7 33.2 26.5 21.6 60.4 68.9 720 No 35.7 32.4 22.4 13.0 9.3 41.8 51.3 685 DK/Missing 41.9 38.2 22.1 16.5 13.7 43.8 54.5 183 Total 15-49 42.9 42.7 27.3 19.5 15.4 50.5 59.7 1,588 Note: Husband/partner refers to the current husband/partner for currently married women and the most recent husband/partner for divorced, separated, or widowed women. Total includes women with missing information on husband’s/partner’s education, husband’s/partner’s alcohol consumption, and spousal age difference that are not shown separately. 1 Includes only women who are currently married or living together. 2 According to the wife's report. See Table 16.8.1 for a list of the behaviours. 3 According to the wife's report. See Table 14.5 for a list of decisions. 4 According to the wife's report. See Table 14.7.1 for a list of reasons. 262 • Domestic Violence Spousal violence increases linearly with the number of controlling behaviours displayed by the husband. Among women whose husbands exhibit three or more types of controlling behaviors, more than eight in ten (81-82 percent) have experienced one or more forms of violence. In contrast, among women whose husbands display none of the six controlling behaviors, about one-third (34 percent) have experienced any form of spousal violence. Women’s experience of violence decreases as the number of decisions they participate in increases. On the other hand, this experience increases as the number of reasons given by women for which wife-beating is justified increases. Finally, women whose father did not beat their mother are much less likely to experience any type of violence by their husband than women whose father beat their mother (51 percent versus 69 percent). Table 16.11.2 shows similar patterns in spousal violence against ever-married men. Spousal violence against men is higher for those whose wife gets drunk sometimes, and it increases steadily as the number of controlling behaviors displayed by the wife increases. Only 27 percent of ever-married men whose wife displays none of the six controlling behaviors have experienced one or more forms of violence compared with 79 percent of men whose wife exhibits five or six controlling behaviors. Men’s experience of violence is slightly higher among those who participate in one to two decisions compared with those who participate in none. The percentage of men who experience any form of violence increases as the number of reasons given by men for which wife-beating is justified increases. As with women, men whose father did not beat their mother are much less likely to experience any type of violence by their spouse than men whose fathers beat their mother (34 percent versus 46 percent). Table 16.11.2 Spousal violence by wife's characteristics and empowerment indicators: men Percentage of ever-married men age 15-49 who have ever experienced emotional, physical, or sexual violence committed by their wife/partner, by wife's characteristics and empowerment indicators, Uganda 2011 Background characteristic Emotional violence Physical violence Sexual violence Physical and sexual Physical and sexual and emotional Physical or sexual Physical or sexual or emotional Number of ever- married men Wife's/partner's alcohol consumption Does not drink 29.0 16.3 7.3 3.5 2.9 20.1 37.2 777 Drinks/never gets drunk 38.8 24.4 7.1 2.4 1.4 29.0 50.2 88 Gets drunk sometimes 50.9 38.1 5.6 4.4 4.4 39.3 63.1 127 Gets drunk very often * * * * * * * 18 Number of marital control behaviors displayed by wife/partner2 0 19.4 9.2 3.6 0.8 0.0 12.1 26.9 245 1-2 31.8 20.8 4.7 2.1 1.9 23.4 41.4 451 3-4 40.6 24.9 10.4 5.6 4.5 29.7 50.2 253 5-6 70.2 49.4 24.7 16.1 16.1 58.1 78.6 60 Number of decisions in which men participate1,3 0 18.3 20.8 6.6 0.0 0.0 27.3 36.4 47 1-2 32.3 19.1 6.4 3.1 2.4 22.4 41.1 881 Number of reasons for which wife-beating is justified4 0 29.7 16.7 3.9 1.6 1.5 19.0 36.9 587 1-2 33.3 24.9 10.4 4.7 3.7 30.6 46.4 277 3-4 47.0 29.7 14.2 8.6 7.2 35.4 55.5 123 5 * * * * * * * 21 Man's father beat his mother Yes 36.8 23.1 7.3 4.0 3.5 26.4 46.0 551 No 24.8 16.8 5.9 2.2 1.9 20.5 33.5 357 DK/Missing 43.8 21.2 10.4 5.3 3.5 26.2 53.2 101 Total 15-49 33.3 20.7 7.1 3.5 2.9 24.3 42.3 1,009 50-54 40.3 20.1 6.1 0.8 0.8 25.5 47.4 76 Total 15-54 33.7 20.6 7.0 3.3 2.8 24.4 42.7 1,085 Note: Wife/partner refers to the current wife/partner for currently married men and the most recent wife/partner for divorced, separated, or widowed men. An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. 1 Includes only men who are currently married or living together. 2 According to the husband's report. See Table 16.8.2 for a list of the behaviours. 3 According to the husband's report. See Table 14.5 for a list of decisions. 4 According to the husband's report. See Table 14.7.2 for a list of reasons. Domestic Violence • 263 16.13 FREQUENCY OF SPOUSAL VIOLENCE Tables 16.12.1 and 16.12.2 show the percentage of ever-married women and men, respectively, who have experienced physical or sexual violence by any spouse/partner in the past 12 months, by background characteristics. Overall, 35 percent of ever- married women experienced physical or sexual violence by any husband or partner in the past 12 months. The percentage of ever-married women who have experienced physical or sexual violence in the past 12 months by any spouse or partner is higher among women 20-24 (42 percent), Catholic women (38 percent), women of Itesa ethnicity (49 percent), rural women (37 percent), and women living in the North region (51 percent). Currently married women are much more likely to experience physical or sexual violence by any husband or partner in the past 12 months than those previously married (37 percent versus 25 percent). This percentage is lowest among women who have no living children (22 percent), those who are employed but not for cash (28 percent), women with secondary or higher education (27 percent) and those in the highest wealth quintile (23 percent). Among ever-married men, 16 percent have experienced physical or sexual violence in the past 12 months by any wife or partner. This proportion decreases with age, from 21 percent of men age 20-24 to 13 percent of those age 40-49. The percentage of ever-married men who have experienced physical or sexual violence in the past 12 months by any wife or partner is higher among Itesa men (21 percent), men living in Karamoja (33 percent), and those who were previously married (19 percent). On the other hand, physical or sexual violence by any spouse or partner in the past 12 months is lowest among ever-married men with five or more children (14 percent) and among those employed for cash (15 percent). There is no clear pattern in the relationship of physical or sexual violence by a spouse or partner in the past 12 months among ever-married men and education or wealth. Table 16.12.1 Frequency of physical or sexual violence: women Percentage of ever-married women who have experienced physical or sexual violence by any husband/partner in the past 12 months, by background characteristics, Uganda 2011 Background characteristic Percentage of women who have experienced physical or sexual violence in the past 12 months from any husband/ partner Number of ever- married women Age 15-19 31.1 122 20-24 41.8 311 25-29 37.6 363 30-39 31.4 450 40-49 31.2 264 Religion Catholic 38.3 610 Protestant 32.9 420 Muslim 34.6 208 Pentecostal 32.3 229 SDA/Other (25.0) 43 Ethnicity Baganda 20.3 235 Banyankole 34.5 145 Basoga 28.2 124 Bakiga 30.3 105 Itesa 49.1 118 Other 39.1 783 Residence Urban 27.1 261 Rural 36.7 1,248 Region Kampala 26.6 113 Central 1 22.9 161 Central 2 35.7 163 East Central 36.4 148 Eastern 40.0 235 Karamoja 28.4 50 North 51.4 134 West Nile 30.3 102 Western 41.2 218 Southwest 27.8 185 Marital status Married or living together 36.5 1,307 Divorced/separated/widowed 25.2 203 Number of living children 0 22.3 109 1-2 37.7 449 3-4 34.3 418 5+ 35.9 534 Employment Employed for cash 36.0 855 Employed not for cash 28.2 325 Not employed 39.0 330 Education No education 37.2 246 Primary 37.4 915 Secondary + 27.3 349 Wealth quintile Lowest 44.8 287 Second 43.0 282 Middle 39.1 292 Fourth 28.4 310 Highest 22.7 339 Total 15-49 35.0 1,510 Note: Any husband/partner includes all current, most recent, and former husbands/partners. Table excludes widows who were not asked about spousal violence in the past 12 months. Figures in parentheses are based on 25-49 unweighted cases. 264 • Domestic Violence Table 16.12.2 Frequency of physical or sexual violence: men Percentage of ever-married men who have experienced physical or sexual violence by any wife/partner in the past 12 months, by background characteristics, Uganda 2011 Background characteristic Percentage of men who have experienced physical or sexual violence in the past 12 months from any wife/partner Number of ever- married men Age 15-19 * 13 20-24 20.6 88 25-29 17.9 208 30-39 17.0 423 40-49 13.1 270 Religion Catholic 16.3 448 Protestant 16.8 315 Muslim 13.9 114 Pentecostal 15.7 89 SDA/Other (21.7) 37 Ethnicity Baganda 16.3 164 Banyankole 14.8 92 Basoga 12.3 88 Bakiga 15.2 83 Itesa 20.5 76 Other 16.9 499 Residence Urban 17.7 181 Rural 16.1 822 Region Kampala 17.9 86 Central 1 16.1 106 Central 2 23.9 109 East Central 10.2 103 Eastern 22.2 156 Karamoja 32.5 34 North 6.3 81 West Nile 15.4 66 Western 15.8 148 Southwest 9.5 114 Marital status Married or living together 16.1 928 Divorced/separated/widowed 19.1 74 Number of living children 0 18.2 60 1-2 20.4 269 3-4 15.9 247 5+ 13.8 427 Employment Employed for cash 15.0 859 Employed not for cash 20.6 128 Not employed * 16 Education No education 13.8 67 Primary 16.8 604 Secondary + 16.0 331 Wealth quintile Lowest 15.4 189 Second 19.1 223 Middle 16.4 184 Fourth 12.8 218 Highest 18.1 188 Total 15-49 16.4 1,002 50-54 17.6 75 Total 15-54 16.4 1,078 Note: Any wife/partner includes all current, most recent and former wives/partners Table excludes widowers who were not asked about spousal violence in the past 12 months. An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. Figures in parentheses are based on 25-49 unweighted cases. Domestic Violence • 265 16.14 ONSET OF SPOUSAL VIOLENCE To obtain information on the onset of marital violence, the 2011 UDHS asked ever-married women and men how long after marriage the onset of spousal violence occurred, if ever. Tables 16.13.1 and 16.3.2 show the data for ever-married women and men, respectively. The data show that about half of ever-married women (51 percent) have never experienced spousal physical or sexual violence by their current or most recent husband, 19 percent experienced violence in the first two years of marriage, 35 percent experienced it in the first five years, and 43 percent experienced it within the first ten years of marriage. These data clearly suggest that, for a considerable percentage of women who have experienced spousal physical or sexual violence, the violence began relatively early in their marriage. Table 16.13.1 Experience of spousal violence by duration of marriage: women Among currently married women age 15-49 who have been married only once, percentage who first experienced physical or sexual violence committed by their current husband/partner by specific exact marital duration lengths, according to marital duration, Uganda 2011 Duration of marriage Percentage with first experience of spousal physical or sexual violence by exact marital duration Percentage who have not experienced sexual or physical violence Number of currently married women Before marriage 2 years 5 years 10 years <2 3.1 33.9 na na 64.9 152 2-4 2.6 29.0 na na 52.0 133 5-9 0.4 16.9 40.1 na 49.5 238 10+ 1.2 12.9 30.4 42.1 47.4 529 Total 15-49 1.5 18.9 35.3 43.3 51.0 1,052 Among ever-married men, eight in ten have not experienced spousal physical or sexual violence by their current or most recent wife, 6 percent experienced violence in the first two years of marriage, 15 percent experienced it in the first five years, and 18 percent experienced it within the first ten years of marriage. Table 16.13.2 Experience of spousal violence by duration of marriage: men Among currently married men age 15-49 who have been married only once, percentage who first experienced physical or sexual violence committed by their current wife/partner by specific exact marital duration lengths according to marital duration, Uganda 2011 Duration of marriage Percentage with first experience of spousal physical or sexual violence by exact marital duration Percentage who have not experienced sexual or physical violence Number of currently married men Before marriage 2 years 5 years 10 years <2 0.3 14.5 na na 85.5 60 2-4 0.0 10.3 na na 78.9 116 5-9 0.0 2.9 17.8 na 79.6 130 10+ 0.0 4.2 10.5 15.7 79.5 264 Total 15-49 0.0 6.2 14.8 17.7 80.0 570 16.15 PHYSICAL CONSEQUENCES OF SPOUSAL VIOLENCE In the 2011 UDHS, ever-married women and men were asked whether they had sustained some form of injury as a result of physical or sexual violence inflicted by their spouse. About one-third of women (32 percent) who reported ever having experienced spousal physical or sexual violence suffered cuts, bruises, or aches; 19 percent had eye injuries, sprains, dislocations, or burns; and 14 percent had deep wounds, broken bones, broken teeth, or other serious injuries (Table 16.14.1). Overall, 37 percent of women who had ever experienced spousal physical or sexual violence suffered one or more of these 266 • Domestic Violence injuries. The prevalence of all forms of injury is similar among women who had experienced violence in the past 12 months. Table 16.14.2 shows that among ever-married men who reported ever having experienced spousal physical or sexual violence, about one in four (24 percent) suffered cuts, bruises, or aches; 8 percent had eye injuries, sprains, dislocations, or burns; and 9 percent had deep wounds, broken bones, broken teeth, or other serious injuries. Twenty-six percent of men who had ever experienced spousal physical or sexual violence suffered one or more of these injuries. Similar percentages of men who had experienced violence in the past 12 months suffered each of the above injuries. Table 16.14.1 Injuries to women due to spousal violence: women Percentage of ever-married women age 15-49 who have experienced specific types of spousal violence by types of injuries resulting from the violence, according to the type of violence and whether they experienced the violence ever and in the 12 months preceding the survey, Uganda 2011 Type of violence Cuts, bruises, or aches Eye injuries, sprains, dislocations, or burns Deep wounds, broken bones, broken teeth, or any other serious injury Any of these injuries Number of ever-married women Experienced physical violence1 Ever2 36.2 21.5 15.7 41.4 678 In the past 12 months3 40.2 22.6 16.0 45.4 376 Experienced sexual violence Ever2 37.3 23.4 15.7 43.5 433 In the past 12 months3 36.3 21.1 14.0 41.8 316 Experienced physical or sexual violence1 Ever2 31.9 18.6 13.6 36.7 801 In the past 12 months3 33.4 19.0 12.7 38.1 522 Note: Husband/partner refers to the current husband/partner for currently married women and the most recent husband/partner for divorced, separated, or widowed women. 1 Excludes women who experienced physical violence only during pregnancy 2 Includes in the past 12 months 3 Excludes widows Table 16.14.2 Injuries to men due to spousal violence: men Percentage of ever-married men age 15-49 who have experienced specific types of spousal violence by types of injuries resulting from the violence, according to the type of violence and whether they experienced the violence ever and in the 12 months preceding the survey, Uganda 2011 Type of violence Cuts, bruises, or aches Eye injuries, sprains, dislocations, or burns Deep wounds, broken bones, broken teeth, or any other serious injury Any of these injuries Number of ever- married men Experienced physical violence Ever1 26.2 9.5 9.8 28.2 209 In the past 12 months2 30.6 10.7 10.2 32.4 122 Experienced sexual violence Ever1 25.2 9.8 12.6 29.1 71 In the past 12 months2 17.0 4.9 6.0 19.0 54 Experienced physical or sexual violence1 Ever1 24.2 8.1 8.8 26.4 245 In the past 12 months2 25.8 8.3 8.6 27.9 158 Note: Wife/partner refers to the current wife/partner for currently married men and the most recent wife/partner for divorced, separated, or widowed men. 1 Includes in the past 12 months 2 Excludes widowers 16.16 VIOLENCE BY WOMEN/MEN AGAINST THEIR SPOUSE In cases of domestic violence, either person (husband or wife) can be the perpetrator of violence. In the 2011 UDHS, ever-married women, and men were asked about instances when they were the instigator of spousal violence. Specifically, all eligible ever-married respondents were asked whether they Domestic Violence • 267 had ever tried to initiate physical violence against their spouse when they were not already hitting or beating the respondent. Tables 16.15.1 and 16.15.2 show the percentage of ever-married women and men age 15-49, respectively, who reported initiating physical violence against their spouses ever and in the 12 months prior to the survey, by background characteristics. Table 16.15.1 Violence by women against their spouse by background characteristics Percentage of ever-married women who have committed physical violence against their current or most recent husband/partner when he was not already beating or physically hurting her, ever and in the past 12 months according to women's own experience of spousal violence and their background characteristics, Uganda 2011 Background characteristic Percentage who have committed physical violence against their husband/partner Number of ever-married women2 Ever1 Number of ever-married women In the past 12 months2 Woman's experience of spousal physical violence Ever1 11.7 678 4.6 645 In the past 12 months 9.5 376 6.7 376 Never 2.7 909 1.7 864 Age 15-19 7.3 122 6.8 122 20-24 6.2 314 4.3 311 25-29 6.0 365 2.6 363 30-39 6.0 477 2.2 450 40-49 8.1 310 1.4 264 Religion Catholic 6.8 638 4.4 610 Protestant 5.6 442 2.3 420 Muslim 5.7 223 2.7 208 Pentecostal 7.9 242 1.0 229 SDA/Other (10.2) 43 (1.1) 43 Ethnicity Baganda 5.2 246 2.3 235 Banyankole 4.0 155 0.9 145 Basoga 4.6 132 0.7 124 Bakiga 9.8 113 2.8 105 Itesa 14.7 122 4.0 118 Other 6.1 820 3.8 783 Residence Urban 8.2 271 3.4 261 Rural 6.2 1,317 2.9 1,248 Region Kampala 6.5 116 3.7 113 Central 1 4.6 176 2.6 161 Central 2 5.6 171 2.1 163 East Central 6.8 152 3.1 148 Eastern 9.8 253 5.0 235 Karamoja 8.6 51 5.7 50 North 6.1 142 2.1 134 West Nile 6.9 104 4.4 102 Western 7.0 226 2.6 218 Southwest 4.0 195 0.5 185 Marital status Married or living together 6.3 1,307 3.2 1,307 Divorced/separated/widowed 7.8 281 1.6 203 Employment Employed for cash 6.6 905 3.1 855 Employed not for cash 6.7 338 3.3 325 Not employed 6.4 344 2.3 330 Number of living children 0 9.6 111 7.6 109 1-2 4.3 458 2.2 449 3-4 8.5 434 3.2 418 5+ 6.3 585 2.4 534 Education No education 5.2 268 2.1 246 Primary 7.9 965 3.6 915 Secondary + 3.9 355 1.9 349 Wealth quintile Lowest 7.7 309 3.0 287 Second 5.9 303 3.5 282 Middle 7.6 310 5.1 292 Fourth 6.9 317 1.5 310 Highest 4.9 348 2.0 339 Total 15-49 6.6 1,588 3.0 1,510 Note: Husband/partner refers to the current husband/partner for currently married women and the most recent husband/partner for divorced, separated, or widowed women. Figures in parentheses are based on 25-49 unweighted cases. 1 Includes in the past 12 months 2 Excludes widows 268 • Domestic Violence Overall, 7 percent of ever-married women reported that they had initiated physical violence against their husbands, and 3 percent had done so in the past 12 months. Women who have been physically abused by their husband ever and in the past 12 months (12 and 10 percent, respectively) are more likely to have initiated spousal physical abuse than women who have never been abused (3 percent). Women’s use of violence against their husbands does not vary much by age, religion, urban-rural residence, or employment. It is higher among women of Itesa ethnicity (15 percent), among those in Eastern region (10 percent), previously married women (8 percent), and women with no living children (10 percent). On the other hand, women with secondary or higher education (4 percent) and those in the highest wealth quintile (5 percent) are less likely than other women to have ever initiated spousal violence. The percentage of ever-married women who reported that they had initiated physical violence against their husbands in the past 12 months does not vary notably by background characteristics. Table 16.15.2 shows that 41 percent of ever-married men age 15-49 reported having initiated physical violence against their wives, and 16 percent had done so in the past 12 months. Men who have been physically abused by their spouse ever and in the past 12 months are more than twice as likely (72 percent, each) as those who have never been abused (33 percent) to initiate physical violence against their wives. Men age 20-24 are less likely, when compared with older men age 25-49, to have ever initiated violence against their spouse (23 percent versus 43-44 percent). This percentage is higher among Catholic men (48 percent), Itesa men (54 percent), rural men (43 percent), those living in Karamoja and North regions (55 and 54 percent, respectively), currently married men (42 percent), and those employed but not for cash (45 percent). Men with no living children, those with no education, and those in the highest wealth quintile are the least likely to initiate physical violence against their wife or partner. Table 16.15.2 Men's violence against their spouse by background characteristics Percentage of ever-married men age 15-49 who have committed physical violence against their current or most recent wife/partner when she was not already beating or physically hurting him, ever and in the past 12 months, according to men's own experience of spousal violence and background characteristics, Uganda 2011 Background Characteristic Percentage who have committed physical violence against their wife/partner Ever1 Number of ever- married men In the past 12 months2 Number of ever- married men2 Man's experience of spousal physical violence Ever1 71.6 209 33.4 207 In the past 12 months 71.5 122 49.6 122 Never 33.1 801 11.8 795 Age 15-19 * 13 * 13 20-24 23.3 88 12.1 88 25-29 44.1 209 23.3 208 30-39 42.7 429 17.0 423 40-49 43.4 270 11.5 270 Religion Catholic 47.8 452 18.3 448 Protestant 35.7 318 16.3 315 Muslim 33.7 114 11.9 114 Pentecostal 33.7 89 11.3 89 SDA/Other (45.1) 37 (16.4) 37 Ethnicity Baganda 31.6 165 14.9 164 Banyankole 44.3 93 12.9 92 Basoga 32.7 88 8.5 88 Bakiga 41.2 85 14.5 83 Itesa 54.4 76 19.2 76 Other 43.0 502 18.6 499 Residence Urban 31.7 182 10.4 181 Rural 43.1 827 17.6 822 Region Kampala 36.8 87 14.7 86 Central 1 40.5 106 22.7 106 Central 2 22.9 110 11.2 109 East Central 33.7 104 7.5 103 Eastern 46.6 156 19.6 156 Karamoja 54.8 34 41.2 34 North 54.4 82 22.0 81 West Nile 46.7 66 16.4 66 Western 38.4 148 11.2 148 Southwest 47.5 117 14.6 114 Marital status Married or living together 41.5 928 17.0 928 Divorced/separated/widowed 35.7 81 7.7 74 Employment Employed for cash 39.8 863 14.4 859 Employed not for cash 45.2 130 24.2 128 Not employed * 16 * 16 Number of living children 0 16.3 62 12.7 60 1-2 34.9 272 17.8 269 3-4 51.8 248 18.3 247 5+ 42.3 428 14.6 427 Education No education 29.0 67 14.9 67 Primary 45.2 609 17.7 604 Secondary + 35.8 333 14.0 331 Wealth quintile Lowest 47.6 189 20.8 189 Second 43.8 225 18.7 223 Middle 48.7 187 22.0 184 Fourth 34.1 218 9.8 218 Highest 31.6 190 10.6 188 Total 15-49 41.0 1,009 16.3 1,002 50-54 25.7 76 11.7 75 Total 15-54 40.0 1,085 16.0 1,078 Note: Wife/partner refers to the current wife/partner for currently married men and the most recent wife/partner for divorced, separated, or widowed men. An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. Figures in parentheses are based on 25-49 unweighted cases. 1 Includes in the past 12 months 2 Excludes widows Domestic Violence • 269 The percentage of ever-married men who reported that they had initiated physical violence against their wives in the past 12 months varies in a similar manner by background characteristics. 16.17 VIOLENCE AGAINST THE SPOUSE BY SPOUSAL CHARACTERISTICS AND WOMEN’S EMPOWERMENT INDICATORS Tables 16.16.1 and 16.16.2 present information on ever-married women and men age 15-49, respectively, who have committed physical violence against their spouse, ever and in the past 12 months, according to spousal characteristics and empowerment indicators. Table 16.16.1 shows that among ever-married women, violence against the spouse is highest among those whose husbands get drunk very often (13 percent) and when the wife is equally or better educated than the husband (9 and 10 percent, respectively). Women’s violence against their spouse increases with the number of controlling behaviors displayed by the husband, and with the number of reasons given by women for which wife-beating is justified. Women’s violence against her spouse decreases as the number of decisions they participate in increases. As expected, women whose father beat their mother are more likely to commit physical spousal violence than women whose fathers did not beat their mothers (9 percent versus 4 percent). Similar patterns are observed in variations of women’s physical violence against their spouse in the past 12 months by background characteristics. Table 16.16.2 shows similar patterns in violence against spouses among the ever-married men. Violence against the spouse is higher among men whose wife gets drunk sometimes, and it increases steadily as the number of controlling behaviors displayed by the wife increases. Thirty percent of ever-married men whose wife displays none of the six controlling behaviors have initiated physical violence against their spouse compared with 50 Table 16.16.1 Violence by women against their spouse by spouse's characteristics and empowerment indicators Percentage of ever-married women who have committed physical violence against their current or most recent husband/partner when he was not already beating or physically hurting her, ever and in the past 12 months, by their husband's/partner's characteristics and empowerment indicators, Uganda 2011 Background characteristic Percentage who have committed physical violence against their husband/partner Number of ever-married women2 Ever1 Number of ever- married women In the past 12 months2 Husband's/partner's education No education 7.0 125 3.7 117 Primary 7.5 824 3.4 788 Secondary 5.0 447 1.9 424 More than secondary 4.8 141 2.6 138 Husband's/partner's alcohol consumption Does not drink 5.4 850 2.1 821 Drinks/never gets drunk 5.8 75 2.1 72 Gets drunk sometimes 4.8 384 2.8 364 Gets drunk very often 12.7 275 6.2 249 Spousal education difference Husband better educated 5.1 939 2.7 884 Wife better educated 9.8 308 3.6 296 Both equally educated 8.9 197 3.1 197 Neither educated 5.9 76 3.6 73 DK/missing 6.2 68 2.6 60 Spousal age difference3 Wife older 6.0 78 0.0 78 Wife is same age 4.0 61 4.0 61 Wife's 1-4 years younger 6.4 429 3.3 429 Wife's 5-9 years younger 6.7 433 2.7 433 Wife's 10+ years younger 6.3 300 4.5 300 Number of marital control behaviours displayed by husband/partner4 0 3.3 402 1.8 385 1-2 5.8 566 3.8 538 3-4 9.6 496 2.7 469 5-6 8.3 123 4.3 118 Number of decisions in which women participate3,5 0 9.2 262 5.4 262 1-2 6.0 603 2.7 603 3 5.0 442 2.5 442 Number of reasons for which wife-beating is justified6 0 6.2 647 2.5 618 1-2 4.7 487 2.5 462 3-4 9.2 355 3.5 339 5 8.2 98 6.1 91 Woman's father beat her mother Yes 8.7 720 4.3 686 No 3.8 685 1.7 645 DK/Missing 8.1 183 2.4 179 Total 15-49 6.6 1,588 3.0 1,510 Note: Husband/partner refers to the current husband/partner for currently married women and the most recent husband/partner for divorced, separated, or widowed women. Total includes women with missing information on husband’s/partner’s education, husband’s/partner’s alcohol consumption, and spousal age difference that are not shown separately. 1 Includes in the past 12 months 2 Excludes widows 3 Includes only women who are currently married or living together 4 According to the wife's report. See Table 16.8.1 for a list of the behaviours. 5 According to the wife's report. See Table 14.5 for a list of decisions. 6 According to the wife's report. See Table 14.7.1 for a list of reasons. 270 • Domestic Violence percent of men whose wife exhibits five or six controlling behaviors. Men’s violence against their spouse is somewhat higher among those who participate in one or two decisions compared with those who participate in none (42 percent versus 36 percent). The percentage of men who initiate physical violence against their spouse is lowest among men who agree with none of the reasons that justify wife-beating. Similar to women, men whose father did not beat their mother are much less likely to commit physical violence against their spouse than men whose fathers beat their mother (28 percent versus 48 percent). Table 16.16.2 Men's violence against their spouse by wife's characteristics and empowerment indicators Percentage of ever-married men age 15-49 who have committed physical violence against their current or most recent wife/partner when she was not already beating or physically hurting him, ever and in the past 12 months, according wife's characteristics and empowerment indicators, Uganda 2011 Background Characteristic Percentage who have committed physical violence against their wife/partner Ever1 Number of ever- married men In the past 12 months2 Number of ever- married men2 Wife's/partner's alcohol consumption Does not drink 38.7 777 14.1 771 Drinks/never gets drunk 43.4 88 14.9 88 Gets drunk sometimes 49.2 127 26.6 127 Gets drunk very often * 18 8 17 Number of marital control behaviors displayed by wife/partner3 0 29.6 245 9.4 244 1-2 45.2 451 17.4 446 3-4 42.6 253 16.8 253 5-6 49.6 60 33.7 60 Number of decisions in which men participate24 0 36.1 47 17.1 47 1-2 41.8 881 17.0 881 Number of reasons for which wife- beating is justified5 0 35.6 587 12.0 583 1-2 47.1 277 20.7 276 3-4 45.3 123 22.4 122 5 * 21 * 21 Man's father beat his mother Yes 48.4 551 20.6 547 No 27.9 357 10.4 354 DK/Missing 47.6 101 13.2 101 Total 15-49 41.0 1,009 16.3 1,002 50-54 25.7 76 11.7 75 Total 15-54 40.0 1,085 16.0 1,078 Note: Wife/partner refers to the current wife/partner for currently married men and the most recent wife/partner for divorced, separated, or widowed men. An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. 1 Includes in the past 12 months 2 Excludes widowers 3 According to the husband's report. See Table 16.8.2 for a list of the behaviours. 4 According to the husband's report. See Table 14.5 for list of decisions. 5 According to the husband's report. See Table 14.7.2 for list of reasons. 16.18 HELP-SEEKING BEHAVIOUR BY WOMEN WHO EXPERIENCE VIOLENCE This final section of this chapter describes help-seeking behavior by women and men age 15-49 who have ever experienced physical or sexual violence. Tables 16.17.1 and 16.17.2 show the percent distribution of women and men, respectively, who have ever experienced physical or sexual violence committed by anyone, according to whether they ever sought help to stop the violence and, among those who did not seek help, whether or not they told anyone about the violence. Domestic Violence • 271 Table 16.17.1 Help seeking to stop violence: women Percent distribution of women age 15-49 who have ever experienced physical or sexual violence by their help-seeking behaviour by type of violence and background characteristics, Uganda 2011 Background characteristic Sought help to stop violence Never sought help but told someone Never sought help, never told anyone Missing/ don't know Total Number of women who have ever experienced any physical or sexual violence Type of violence experienced Physical only 38.7 12.0 47.3 2.1 100.0 708 Sexual only 22.3 9.9 65.0 2.9 100.0 125 Physical and sexual 52.6 15.1 32.2 0.1 100.0 446 Age 15-19 33.0 12.4 53.4 1.2 100.0 267 20-24 33.4 13.6 52.0 0.9 100.0 264 25-29 43.7 17.1 38.4 0.9 100.0 247 30-39 48.1 10.7 37.8 3.3 100.0 297 40-49 53.4 10.5 35.5 0.6 100.0 203 Religion Catholic 37.0 13.8 46.7 2.4 100.0 511 Protestant 42.8 11.2 45.2 0.8 100.0 368 Muslim 43.6 11.2 44.7 0.5 100.0 174 Pentecostal 51.3 15.2 32.4 1.1 100.0 202 SDA/Other (40.9) (10.3) (45.2) (3.5) 100.0 26 Ethnicity Baganda 33.4 8.7 56.8 1.1 100.0 214 Banyankole 44.2 13.2 42.7 0.0 100.0 129 Basoga 39.3 22.1 38.6 0.0 100.0 94 Bakiga 44.8 13.6 40.6 1.1 100.0 86 Itesa 50.2 15.5 33.2 1.1 100.0 121 Other 42.7 12.3 42.7 2.3 100.0 636 Residence Urban 40.5 9.9 48.4 1.2 100.0 224 Rural 42.2 13.5 42.8 1.5 100.0 1,056 Region Kampala 38.6 5.9 53.3 2.2 100.0 103 Central 1 37.1 16.5 45.4 0.9 100.0 136 Central 2 33.9 10.5 55.6 0.0 100.0 146 East Central 41.8 25.9 32.3 0.0 100.0 122 Eastern 46.3 12.6 39.5 1.7 100.0 223 Karamoja 22.2 18.2 58.6 1.0 100.0 31 North 57.1 13.2 29.7 0.0 100.0 116 West Nile 50.6 12.5 32.6 4.3 100.0 78 Western 36.4 8.8 50.0 4.8 100.0 163 Southwest 43.7 10.0 46.4 0.0 100.0 161 Marital status Never married 29.3 9.3 59.8 1.6 100.0 258 Married or living together 41.1 13.9 43.6 1.4 100.0 818 Divorced/separated/widowed 61.3 13.1 24.1 1.4 100.0 204 Number of living children 0 31.5 11.6 55.5 1.4 100.0 292 1-2 37.4 15.4 46.0 1.2 100.0 320 3-4 43.9 14.2 41.0 0.9 100.0 279 5+ 52.0 10.8 35.0 2.2 100.0 388 Employment Employed for cash 41.1 11.9 44.7 2.3 100.0 646 Employed not for cash 50.4 15.9 33.7 0.0 100.0 277 Not employed 36.8 12.2 49.8 1.1 100.0 356 Education No education 49.0 11.8 38.3 0.8 100.0 176 Primary 43.2 14.2 40.7 1.9 100.0 754 Secondary + 35.5 10.6 53.1 0.8 100.0 349 Wealth quintile Lowest 53.2 15.1 29.9 1.8 100.0 242 Second 41.1 14.4 42.8 1.8 100.0 232 Middle 42.4 11.7 45.7 0.2 100.0 261 Fourth 40.0 13.5 43.4 3.1 100.0 270 Highest 34.1 10.1 55.2 0.5 100.0 275 Total 15-49 41.9 12.9 43.7 1.5 100.0 1,280 Note: Figures in parentheses are based on 25-49 unweighted cases. Overall, more than four in ten women (42 percent) who have experienced any type of physical or sexual violence from anyone sought help from any source to stop the violence. A similar proportion (44 percent) have never sought help and never told anyone, and 13 percent never sought help but told someone. Women who have experienced both physical and sexual violence (53 percent), older women 45-49 (53 percent), Pentecostal women (51 percent), those of Itesa ethnicity (50 percent), and women in the North region (57 percent) are more likely than other women to seek help to stop the violence. A much higher proportion of divorced, separated, or widowed women (61 percent) than never-married (29 percent) 272 • Domestic Violence and currently married women (41 percent) have ever sought help. Help seeking increases with the number of living children, from 32 percent of women with no living children to 52 percent of those with five or more children. It is interesting to note that unemployed women, as well as highly educated women and those in the wealthiest quintile are less likely than other women to seek help from any source to stop the violence. Table 16.17.2 Help seeking to stop violence: men Percent distribution of men age 15-49 who have ever experienced physical or sexual violence by their help-seeking behavior by type of violence and background characteristics, Uganda 2011 Background characteristic Sought help to stop violence Never sought help but told someone Never sought help, never told anyone Missing/ don't know Total Number of men who have ever experienced any physical or sexual violence Type of violence experienced Physical only 41.0 24.8 32.6 1.6 100.0 820 Sexual only (16.4) (22.5) (59.6) (1.5) 100.0 50 Physical and sexual 45.2 19.1 34.6 1.1 100.0 97 Age 15-19 * * * * 100.0 241 20-24 38.1 28.4 32.1 1.3 100.0 148 25-29 40.2 29.5 28.4 2.0 100.0 159 30-39 40.3 23.0 34.5 2.2 100.0 266 40-49 53.3 20.0 25.2 1.5 100.0 153 Religion Catholic 40.6 23.7 34.5 1.3 100.0 427 Protestant 38.7 26.7 33.8 0.8 100.0 305 Muslim 40.0 20.9 34.5 4.6 100.0 125 Pentecostal 45.0 25.4 29.5 0.0 100.0 77 SDA/Other (37.4) (15.1) (44.2) (3.3) 100.0 33 Ethnicity Baganda 36.0 26.2 37.3 0.5 100.0 155 Banyankole 43.9 28.8 27.3 0.0 100.0 118 Basoga 30.7 21.7 47.6 0.0 100.0 105 Bakiga 42.8 27.0 30.2 0.0 100.0 62 Itesa 46.0 25.4 28.6 0.0 100.0 68 Other 41.6 22.2 33.2 3.0 100.0 458 Residence Urban 37.0 23.7 38.4 0.9 100.0 197 Rural 41.0 24.2 33.1 1.7 100.0 770 Region Kampala 39.3 28.2 32.5 0.0 100.0 94 Central 1 38.2 23.8 38.0 0.0 100.0 114 Central 2 44.7 22.5 32.8 0.0 100.0 105 East Central 37.5 17.7 44.2 0.7 100.0 126 Eastern 45.1 19.6 31.8 3.5 100.0 132 Karamoja 20.0 22.2 57.2 0.6 100.0 32 North 67.0 28.0 4.7 0.2 100.0 81 West Nile 42.4 15.4 20.0 22.2 100.0 39 Western 22.1 19.9 57.7 0.2 100.0 117 Southwest 40.2 38.3 21.5 0.0 100.0 127 Marital status Never married 32.7 24.4 42.3 0.7 100.0 361 Married or living together 44.5 23.5 30.0 2.0 100.0 544 Divorced/separated/widowed 45.3 27.9 24.1 2.7 100.0 62 Number of living children 0 33.2 25.3 40.7 0.8 100.0 386 1-2 45.6 23.9 28.4 2.1 100.0 176 3-4 40.0 24.0 34.6 1.5 100.0 164 5+ 47.5 22.5 27.8 2.2 100.0 241 Employment Employed for cash 41.4 23.4 34.2 1.0 100.0 755 Employed not for cash 37.0 30.6 28.9 3.5 100.0 151 Not employed (33.0) (16.8) (47.7) (2.5) 100.0 60 Education No education 39.3 25.4 30.9 4.4 100.0 39 Primary 40.1 25.3 33.4 1.3 100.0 561 Secondary + 40.4 22.2 35.7 1.6 100.0 368 Wealth quintile Lowest 43.5 23.4 30.9 2.2 100.0 139 Second 48.0 24.7 24.0 3.4 100.0 195 Middle 38.6 29.4 31.6 0.5 100.0 188 Fourth 33.4 22.0 43.3 1.3 100.0 214 Highest 39.1 21.7 38.5 0.6 100.0 231 Total 15-49 40.2 24.1 34.2 1.5 100.0 967 50-54 46.6 19.3 30.0 4.1 100.0 51 Total 15-54 40.5 23.9 34.0 1.7 100.0 1,018 Note: An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. Figures in parentheses are based on 25-49 unweighted cases. Domestic Violence • 273 Among ever-married men who have experienced any type of physical or sexual violence from anyone, four in ten sought from any source help to stop the violence. Twenty-four percent never sought help but told someone, and 34 percent have never sought help and never told anyone. The observed patterns in help seeking among men who have ever experienced any type of physical or sexual violence by background characteristics are similar to those among women. Tables 16.18.1 and 16.8.2 show the percentage of abused women and men, respectively, who reported seeking help, by sources from which help was sought. The most common sources of help are the respondent’s own family (reported by 23 percent of women and 16 percent of men), others (reported by 8 percent of women and 11 percent of men), and the police (reported by 6 percent of women and 8 percent of men). A relatively high percentage of women (12 percent) seek help from their husband’s or partner’s family. Table 16.18.1 Sources for help to stop the violence: women Percentage of women age 15-49 who have experienced physical or sexual violence and sought help by sources from which they sought help, according to the type of violence that women reported, Uganda 2011 Person Type of violence experienced Experienced physical or sexual violence Physical only Sexual only Physical and sexual Own family 19.8 19.6 28.9 23.0 Husband/partner's family 9.8 4.7 18.6 12.3 Husband/partner 0.7 0.0 0.8 0.7 Boyfriend 0.7 0.0 0.0 0.4 Friend 4.1 3.2 4.8 4.2 Neighbor 2.7 2.8 3.5 3.0 Religious leader 0.4 1.4 0.3 0.5 Doctor/medical personnel 1.3 2.0 1.7 1.5 Police 5.3 4.0 6.6 5.6 Lawyer 0.1 0.0 0.0 0.0 Social work organization 0.8 2.0 1.2 1.0 Other 7.0 0.5 12.8 8.4 Number of women 708 125 446 1,280 Note: Women can report more than one source from which they sought help Table 16.18.2 Sources for help to stop the violence: men Percentage of men age 15-49 who have experienced physical or sexual violence and sought help by sources from which they sought help, according to the type of violence that men reported, Uganda 2011 Person Type of violence experienced Total Physical only Sexual only Physical and sexual Own family 15.1 (14.7) 21.7 15.7 Wife/partner's family 3.2 (0.0) 6.2 3.3 Wife/partner 0.2 (0.0) 0.3 0.2 Friend 4.9 (1.7) 11.5 5.4 Neighbor 0.9 (0.0) 1.0 0.9 Religious leader 0.2 (0.0) 1.2 0.3 Doctor/medical personnel 5.6 (0.0) 5.0 5.2 Police 9.1 (0.0) 3.9 8.1 Lawyer 1.5 (0.0) 0.0 1.3 Social work organization 0.2 (0.0) 1.3 0.3 Other 11.7 (0.0) 8.1 10.7 Number of men 820 50 97 967 Note: Men can report more than one source from which they sought help. 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