Uganda - Demographic and Health Survey - 2007

Publication date: 2007

Uganda Demographic and Health Survey 2006 Uganda Demographic and Health Survey 2006 Uganda Bureau of Statistics Kampala, Uganda Macro International Inc. Calverton, Maryland, USA August 2007 From the People of Japan THE REPUBLIC OF UGANDA The report presents the findings from the 2006 Uganda Demographic and Health Survey (UDHS) conducted by the Uganda Bureau of Statistics (UBOS). Macro International Inc. provided technical assistance and funding through MEASURE DHS, a USAID-funded project that assists developing countries to collect data on fertility, family planning, maternal and child health, and HIV/AIDS. Financial assistance was also provided by the UK Department for International Development (DFID), the USAID/Uganda Mission, the President’s Emergency Plan for AIDS Relief, the Government of Uganda, the Health Partnership Fund, the United Nations Children’s Fund (UNICEF), the United Nations Population Fund (UNFPA), and the Government of Japan. The opinions expressed in this report do not necessarily reflect the views of the donor organisations. Additional information about the survey may be obtained from the Uganda Bureau of Statistics (UBOS), Plot 9 Coleville Street, P.O. Box 7186, Kampala, Uganda; Telephone: (256-41) 706000; Fax: (256-41) 237553/230370; Email: ubos@ubos.org; Internet: www.ubos.org. Additional information about the DHS programme may be obtained by contacting MEASURE DHS, Macro International Inc., 11785 Beltsville Drive, Suite 300, Calverton, MD 20705, USA; Telephone: 301-572-0200; Fax: 301-572-0999; Email: reports@measuredhs.com; Internet: http://www.measuredhs.com. Recommended citation: Uganda Bureau of Statistics (UBOS) and Macro International Inc. 2007. Uganda Demographic and Health Survey 2006. Calverton, Maryland, USA: UBOS and Macro International Inc. Contents | iii CONTENTS TABLES AND FIGURES . xi PREFACE. xxi SUMMARY OF FINDINGS .xxiii MILLENNIUM DEVELOPMENT GOALS .xxix MAP OF UGANDA .xxxi CHAPTER 1 INTRODUCTION 1.1 Geography and Economy.1 1.2 Population .1 1.3 National Population and Health Programmes.2 1.4 Objectives of the Survey .3 1.5 Organization and Methodology of the Survey .4 1.5.1 The Survey Sample.4 1.5.2 Comparability of the 2006 UDHS Sample with Samples from Previous UDHS Surveys .6 1.5.3 Questionnaires .6 1.5.4 Training of Field Staff.7 1.5.5 Community Mobilization.7 1.5.6 Fieldwork .8 1.5.7 Data Processing.8 1.6 Response Rates .9 CHAPTER 2 CHARACTERISTICS OF HOUSEHOLDS AND HOUSEHOLD MEMBERS 2.1 Household Population by Age and Sex.11 2.2 Household Composition .12 2.3 Fosterhood and Orphanhood.12 2.4 Housing Characteristics .13 2.5 Household Assets .18 2.6 Wealth Quintiles.19 2.7 Birth Registration.20 2.8 Disability.21 CHAPTER 3 EDUCATION 3.1 Educational Level of Household Population .23 3.2 School Attendance Ratios.25 3.2.1 Primary School Attendance Ratios .25 3.2.2 Secondary School Attendance Ratios .27 3.2.3 Age-specific Attendance Rates .28 3.3 Age at First Primary School Attendance .29 3.4 Absenteeism among Primary School Pupils.30 3.5 Reasons for Absenteeism among Primary School Pupils .31 3.6 Absenteeism among Secondary School Students .32 3.7 Reasons for Absenteeism among Secondary School Students.33 iv | Contents CHAPTER 4 CHARACTERISTICS OF RESPONDENTS 4.1 Characteristics of Survey Respondents.35 4.2 Educational Attainment by Background Characteristics.36 4.3 Literacy .39 4.4 School Level at Which Teaching English is Appropriate .41 4.5 Access to Mass Media .41 4.6 Employment .44 4.7 Occupation.46 4.8 Earnings, Employer, and Continuity of Employment .48 4.9 Knowledge and Attitudes towards Tuberculosis .48 4.10 Use of Tobacco.50 CHAPTER 5 FERTILITY 5.1 Introduction.53 5.2 Current Fertility.53 5.3 Fertility Differentials by Background Characteristics.54 5.4 Fertility Trends .55 5.5 Children Ever Born and Living.57 5.6 Birth Intervals.58 5.7 Age at First Birth.60 5.8 Teenage Pregnancy and Motherhood.62 CHAPTER 6 FAMILY PLANNING 6.1 Knowledge of Contraceptive Methods.65 6.2 Ever Use of Contraception .66 6.3 Current Use of Contraceptive Methods .68 6.4 Differentials in Contraceptive Use by Background Characteristics.69 6.5 Trends in Contraceptive Use .71 6.6 Timing of First Use of Contraception .73 6.7 Use of Social Marketing Brands of Pills and Condoms .73 6.8 Knowledge of the Fertile Period .73 6.9 Source of Contraception .74 6.10 Cost of Contraception .75 6.11 Informed Choice.76 6.12 Contraceptive Discontinuation .77 6.13 Future Use of Contraception .78 6.14 Reasons for Not Intending to Use .79 6.15 Preferred Method for Future Use .79 6.16 Exposure to Family Planning Messages .79 6.17 Contact of Nonusers with Family Planning Providers .80 6.18 Husband’s/Partner’s Knowledge of Women’s Contraceptive Use.82 6.19 Discussion of Family Planning between Couples.83 Contents | v CHAPTER 7 OTHER PROXIMATE DETERMINANTS OF FERTILITY 7.1 Current Marital Status .85 7.2 Polygyny .87 7.3 Age at First Marriage .88 7.4 Median Age at First Marriage.89 7.5 Age at First Sexual Intercourse.90 7.6 Median Age at First Sexual Intercourse .90 7.7 Recent Sexual Activity .92 7.8 Postpartum Amenorrhoea, Abstinence, and Insusceptibility.96 7.9 Median Duration of Postpartum Insusceptibility by Background Characteristics .97 7.10 Menopause.98 CHAPTER 8 FERTILITY PREFERENCES 8.1 Desire for More Children .99 8.2 Desire to Limit Childbearing by Background Characteristics .101 8.3 Need for Family Planning Services.103 8.4 Ideal Number of Children .105 8.5 Fertility Planning .106 CHAPTER 9 INFANT AND CHILD MORTALITY 9.1 Definitions, Methodology, and Assessment of Data Quality .109 9.1.1 Reporting of Children’s Birth Dates .110 9.1.2 Reporting of Children’s Age at Death.110 9.2 Early Childhood Mortality Rates: Levels and Trends.111 9.3 Early Childhood Mortality by Socio-economic Characteristics.112 9.4 Early Childhood Mortality by Demographic Characteristics.114 9.5 Perinatal Mortality.115 9.6 High-risk Fertility Behaviour .117 CHAPTER 10 REPRODUCTIVE HEALTH 10.1 Antenatal Care .119 10.1.1 Number of Antenatal Care Visits and Timing of the First Visit.121 10.1.2 Quality of Antenatal Care .121 10.1.3 Place of Antenatal Care .123 10.1.4 Tetanus Toxoid Immunization .124 10.2 Childbirth Care .125 10.2.1 Person Accompanying Women to the Place of Delivery .126 10.2.2 Assistance During Childbirth.128 10.3 Postpartum Care .129 10.3.1 Type of Provider for the First Postpartum Checkup.131 10.3.2 Problems Encountered in Accessing Health Care .133 10.4 Female Circumcision.135 10.5 Obstetric Fistula .135 vi | Contents CHAPTER 11 CHILD HEALTH 11.1 Child’s Size at Birth .137 11.2 Vaccination Coverage .139 11.2.1 Trends in Vaccination Coverage .141 11.3 Acute Respiratory Infection .143 11.4 Fever.145 11.5 Prevalence of Diarrhoea.146 11.6 Diarrhoea Treatment.147 11.7 Feeding Practices .149 11.8 Knowledge of ORS Packets .151 11.9 Stool Disposal .151 CHAPTER 12 NUTRITION OF CHILDREN AND ADULTS 12.1 Nutritional Status of Children .153 12.2 Initiation of Breastfeeding.156 12.3 Breastfeeding Status by Age.158 12.4 Duration and Frequency of Breastfeeding .161 12.5 Types of Complementary Foods .162 12.6 Infant and Young Child Feeding (IYCF) Practices .163 12.7 Prevalence of Anaemia in Children .165 12.8 Micronutrient Intake among Children.167 12.9 Use of Iodized Salt .169 12.10 Nutritional Status of Women.170 12.11 Foods Consumed by Mothers.172 12.12 Prevalence of Anaemia in Women and Men .173 12.13 Micronutrient Intake among Mothers .176 12.14 Vitamin A Status.178 CHAPTER 13 MALARIA 13.1 Introduction.183 13.2 Mosquito Nets .183 13.2.1 Ownership of Mosquito Nets.184 13.2.2 Brands of Mosquito Nets .185 13.2.3 Source of Mosquito Nets .185 13.2.4 Use of Mosquito Nets by Children.187 13.2.5 Use of Mosquito Nets by Pregnant Women.188 13.3 Intermittent Preventive Treatment during Pregnancy .189 13.4 Fever and Treatment.191 13.4.1 Treatment of Malaria in Children.191 13.4.2 Types of Antimalarial Drugs Used.192 13.4.3 Availability of Antimalarial Drugs at Home.193 13.5 Household Insecticide Spraying.194 Contents | vii CHAPTER 14 HIV/AIDS-RELATED KNOWLEDGE, ATTITUDES, AND BEHAVIOUR 14.1 Introduction.195 14.2 Knowledge of HIV/AIDS and of Transmission and Prevention Methods .195 14.2.1 Awareness of HIV/AIDS .195 14.2.2 Knowledge of HIV Prevention .195 14.2.3 Rejection of Misconceptions about HIV/AIDS.197 14.2.4 Comprehensive Knowledge about HIV/AIDS .200 14.2.5 Knowledge of Prevention of Mother-to-Child Transmission of HIV .200 14.2.6 Knowledge of Drugs for AIDS Treatment .203 14.2.7 Exposure to Media Messages on Drug Treatments for AIDS .206 14.2.8 Expanded Knowledge about ARVs.207 14.3 Accepting Attitudes towards People Living with AIDS.209 14.4 Attitudes towards Negotiating Safer Sex.213 14.5 Perceived Norms on Abstinence and Faithfulness.214 14.6 Sexual Behaviour .214 14.6.1 Multiple Partners and Condom Use.214 14.6.2 Transactional Sex .217 14.6.3 Payment for Sexual Intercourse among Men.219 14.7 Coverage of HIV Counselling and Testing.219 14.7.1 HIV Testing during Antenatal Care.222 14.8 Prevalence of Sexually Transmitted Infections .223 14.9 Prevalence of Medical Injections .224 14.10 HIV/AIDS Knowledge and Sexual Behaviour among Young Adults.227 14.10.1 HIV/AIDS Related Knowledge among Young Adults.227 14.10.2 Knowledge of Condom Sources among Young Adults .228 14.10.3 Age at First Sexual Experience .228 14.10.4 Trends in Age at First Sex.230 14.10.5 Condom Use at First Sex .230 14.10.6 Abstinence and Premarital Sex .231 14.10.7 Higher-Risk Sex and Condom Use among Young Adults .233 14.10.8 Abstinence, Being Faithful, and Condom Use among Young Adults .235 14.10.9 Cross-generational Sexual Partners .235 14.10.10 Drunkenness during Sex among Young Adults .236 14.10.11 Voluntary HIV Counselling and Testing among Young Adults .237 CHAPTER 15 WOMEN’S EMPOWERMENT AND DEMOGRAPHIC AND HEALTH OUTCOMES 15.1 Employment and Form of Earnings .239 15.2 Women’s Control Over Their Own Earnings and Relative Magnitude of Women’s Earnings.241 15.3 Women’s Control Over Her Own and Husband’s Earnings .243 15.4 Women’s Empowerment .245 15.4.1 Women’s Participation in Household Decisionmaking.245 15.4.2 Attitudes towards Wife Beating.250 15.4.3 Attitudes towards Refusing Sex with Husband .252 15.4.4 Women’s Empowerment Indicators.257 viii | Contents 15.5 Current Use of Contraception by Women’s Empowerment Status .258 15.6 Ideal Family Size and Unmet Need by Women’s Status.259 15.7 Women’s Status and Reproductive Health Care .260 15.8 Early Childhood Mortality by Women’s Status .261 CHAPTER 16 ORPHANS AND VULNERABLE CHILDREN 16.1 Orphans and Vulnerable Children.263 16.1.1 Children’s Living Arrangements and Orphanhood .263 16.1.2 Orphaned and Vulnerable Children .264 16.2 Social and Economic Situation of Orphaned and Vulnerable Children.266 16.2.1 School Attendance .267 16.2.2 Basic Material Needs.269 16.2.3 Orphans Living with Siblings.270 16.2.4 Nutritional Status.271 16.2.5 Sex before Age 15 .272 16.3 Care and Support for OVCs .272 16.3.1 Succession Planning .273 16.3.2 Widows Dispossessed of Property .273 16.3.3 External Support for Households with OVCs.275 CHAPTER 17 ADULT AND MATERNAL MORTALITY 17.1 Data.277 17.2 Estimates of Adult Mortality.278 17.3 Estimates of Maternal Mortality .281 CHAPTER 18 VIOLENCE 18.1 Introduction.283 18.2 Measurement of Violence .283 18.2.1 The Use of Valid Measures of Violence.283 18.2.2 Ethical Considerations .285 18.2.3 Special Training for Implementing the Domestic Violence Module .285 18.2.4 Characteristics of the Sub-sample of Respondents for the Violence Module.285 18.3 Experience of Violence by Women Age 15-49 and Men Age 15-54 .286 18.3.1 Physical Violence since Age 15.286 18.3.2 Physical Violence during Pregnancy.289 18.3.3 Lifetime Sexual Violence .289 18.3.4 Physical or Sexual Violence .293 18.4 Spousal/Intimate Partner Violence.293 18.4.1 Physical, Sexual, or Emotional Violence.294 18.4.2 Frequency of Spousal Abuse.300 18.4.3 Physical Consequences of Spousal Violence .302 18.4.4 Self-report of Violence Initiated by the Respondent .303 18.5 Help Seeking .307 Contents | ix REFERENCES . 311 APPENDIX A SAMPLE IMPLEMENTATION. 313 APPENDIX B ESTIMATES OF SAMPLING ERRORS .315 APPENDIX C DATA QUALITY TABLES .331 APPENDIX D NUTRITIONAL STATUS OF CHILDREN—2006 UDHS DATA ACCORDING TO THE NCHS/CDC/WHO INTERNATIONAL REFERENCE POPULATION .337 APPENDIX E PERSONS INVOLVED IN THE 2006 UGANDA DEMOGRAPHIC AND HEALTH SURVEY .339 APPENDIX F QUESTIONNAIRES.343 Tables and Figures | xi TABLES AND FIGURES Page CHAPTER 1 INTRODUCTION Table 1.1 Basic demographic indicators.2 Table 1.2 Results of the household and individual interviews.9 Figure 1.1 Map of Uganda DHS Clusters .5 CHAPTER 2 CHARACTERISTICS OF HOUSEHOLDS AND HOUSEHOLD MEMBERS Table 2.1 Household population by age, sex, and residence.11 Table 2.2 Household composition.13 Table 2.3 Household drinking water.14 Table 2.4 Household sanitation facilities.15 Table 2.5 Household characteristics .17 Table 2.6 Household assets .18 Table 2.7 Wealth quintiles.20 Table 2.8 Birth registration of children under age five .21 Table 2.9 Disability by functional domain and age.22 Figure 2.1 Population Pyramid .12 CHAPTER 3 EDUCATION Table 3.1 Educational attainment of household population . 24 Table 3.2 School attendance ratios . 26 Table 3.3 Age at first primary school attendance. 29 Table 3.4 Absenteeism among primary school pupils . 30 Table 3.5 Reasons for absenteeism among primary school pupils. 31 Table 3.6 Absenteeism among secondary school pupils in the week of school preceding the interview . 32 Figure 3.1 Age-specific Attendance Rates of the De Facto Population Age 5-24 Years. 28 CHAPTER 4 CHARACTERISTICS OF RESPONDENTS Table 4.1 Background characteristics of respondents . 36 Table 4.2.1 Educational attainment: Women. 37 Table 4.2.2 Educational attainment: Men . 38 Table 4.3.1 Literacy: Women . 39 Table 4.3.2 Literacy: Men . 40 Table 4.4 School level at which teaching in English is appropriate. 41 Table 4.5.1 Exposure to mass media: Women. 42 Table 4.5.2 Exposure to mass media: Men . 43 Table 4.6 Employment status: Women . 44 Table 4.6.2 Employment status: Men. 45 xii | Tables and Figures Table 4.7.1 Occupation: Women. 46 Table 4.7.2 Occupation: Men . 47 Table 4.8 Type of employment. 48 Table 4.9.1 Knowledge and attitudes concerning tuberculosis: Women. 49 Table 4.9.2 Knowledge and attitude concerning tuberculosis: Men . 50 Table 4.10 Use of tobacco. 51 CHAPTER 5 FERTILITY Table 5.1 Current fertility . 53 Table 5.2 Fertility by background characteristics . 54 Table 5.3.1 Trends in age-specific fertility rates. 55 Table 5.3.2 Trends in age-specific and total fertility rates . 56 Table 5.4 Children ever born and living. 57 Table 5.5 Birth intervals. 59 Table 5.6 Age at first birth . 61 Table 5.7 Median age at first birth by background characteristics. 61 Table 5.8 Teenage pregnancy and motherhood. 62 Figure 5.1 Total Fertility Rates for the Three Years Preceding the Survey, by Residence and Education . 55 Figure 5.2 Trends in Fertility . 56 Figure 5.3 Age-specific Fertility Rates for the Three-year Period Preceding the Survey, by Residence . 57 Figure 5.4 Birth Intervals with a Duration of Less Than 24 Months, by Survival Status of Preceding Birth and Age of Mother . 60 Figure 5.5 Percentage of Women Age 15-19 Who Are Mothers or Pregnant with Their First Child, by Residence, Education, and Wealth Quintile . 63 CHAPTER 6 FAMILY PLANNING Table 6.1 Knowledge of contraceptive methods . 66 Table 6.2.1 Ever use of contraception: Women . 67 Table 6.2.2 Ever use of contraception: Men . 68 Table 6.3 Current use of contraception by age . 69 Table 6.4 Current use of contraception by background characteristics . 70 Table 6.5 Trends in contraceptive use . 71 Table 6.6 Number of children at first use of contraception . 73 Table 6.7 Use of social marketing brand pills and condoms . 73 Table 6.8 Knowledge of fertile period. 74 Table 6.9 Source of contraception. 75 Table 6.10 Cost of modern contraceptive methods. 76 Table 6.11 Informed choice . 77 Table 6.12 First-year contraceptive discontinuation rates . 78 Table 6.13 Future use of contraception . 78 Table 6.14 Reason for not intending to use contraception in the future . 79 Table 6.15 Preferred method of contraception for future use. 79 Table 6.16 Exposure to family planning messages . 80 Table 6.17 Contact of nonusers with family planning providers . 81 Table 6.18 Husband/partner’s knowledge of women’s use of contraception . 82 Table 6.19 Discussion of family planning with husband . 83 Tables and Figures | xiii Figure 6.1 Contraceptive Use among Currently Married Women. 71 Figure 6.2 Trends in Contraceptive Use among Currently Married Women . 72 Figure 6.3 Trends in Use of Specific Contraceptive Methods among Currently Married Women. 72 CHAPTER 7 OTHER PROXIMATE DETERMINANTS OF FERTILITY Table 7.1 Current marital status . 86 Table 7.2 Polygyny . 87 Table 7.3 Age at first marriage . 88 Table 7.4 Median age at first marriage. 89 Table 7.5 Age at first sexual intercourse . 90 Table 7.6 Median age at first intercourse . 93 Table 7.7.1 Recent sexual activity: Women . 94 Table 7.7.2 Recent sexual activity: Men . 96 Table 7.8 Postpartum amenorrhoea, abstinence, and insusceptibility. 96 Table 7.9 Median duration of amenorrhoea, postpartum abstinence, and postpartum insusceptibility. 97 Table 7.10 Menopause. 98 Figure 7.1 Current Marital Status of Women and Men. 86 Figure 7.2 Median Age at First Sexual Intercourse among Respondents, by Residence and Education . 91 CHAPTER 8 FERTILITY PREFERENCES Table 8.1 Fertility preferences by number of living children . 100 Table 8.2 Desire to limit childbearing . 102 Table 8.3 Need and demand for family planning among currently married women . 104 Table 8.4 Ideal number of children . 105 Table 8.5 Mean ideal number of children. 106 Table 8.6 Fertility planning status. 107 Table 8.7 Wanted fertility rates. 107 Figure 8.1 Fertility Preferences among Currently Married Women and Men Age 15-49. 100 Figure 8.2 Trends of Fertility Preferences . 101 Figure 8.3 Percentage of Currently Married Women and Men Age 15-49 Who Want No More Children, by Number of Living Children. 102 CHAPTER 9 INFANT AND CHILD MORTALITY Table 9.1 Early childhood mortality rates . 111 Table 9.2 Early childhood mortality rates by socio-economic characteristics . 113 Table 9.3 Early childhood mortality rates by demographic characteristics. 115 Table 9.4 Perinatal mortality. 116 Table 9.5 High-risk fertility behaviour . 118 Figure 9.1 Mortality Trends. 112 xiv | Tables and Figures CHAPTER 10 REPRODUCTIVE HEALTH Table 10.1 Antenatal care. 120 Table 10.2 Number of antenatal care visits and timing of first visit . 121 Table 10.3 Components of antenatal care . 122 Table 10.4 Place of antenatal care. 123 Table 10.5 Tetanus toxoid injections . 124 Table 10.6 Place of childbirth. 126 Table 10.7 Persons accompanying women to place of birth. 127 Table 10.8 Assistance during childbirth. 128 Table 10.9 Timing of first postpartum checkup . 130 Table 10.10 Type of provider of first postpartum checkup . 131 Table 10.11 Components of postpartum care . 132 Table 10.12 Problems in accessing health care . 134 Table 10.13 Female circumcision . 135 Table 10.14 Obstetric fistula. 136 Figure 10.1 Assistance by Skilled Provider during Childbirth . 129 CHAPTER 11 CHILD HEALTH Table 11.1 Child’s weight and size at birth . 138 Table 11.2 Vaccinations by source of information. 140 Table 11.3 Vaccinations by background characteristics . 141 Table 11.4 Vaccinations in first year of life. 142 Table 11.5 Prevalence and treatment of symptoms of ARI . 144 Table 11.6 Prevalence and treatment of fever. 146 Table 11.7 Prevalence of diarrhoea . 147 Table 11.8 Diarrhoea treatment . 148 Table 11.9 Feeding practices during diarrhoea . 150 Table 11.10 Knowledge of ORS packets or pre-packaged liquids. 151 Table 11.11 Disposal of children’s stools . 152 Figure 11.1 Trends in Vaccination Coverage among Children Age 12-24 Months . 142 CHAPTER 12 NUTRITION OF CHILDREN AND ADULTS Table 12.1 Nutritional status of children . 155 Table 12.2 Initial breastfeeding. 157 Table 12.3 Breastfeeding status by age . 159 Table 12.4 Median duration and frequency of breastfeeding . 161 Table 12.5 Foods and liquids consumed by children in the day and night preceding the interview . 163 Table 12.6 Infant and young child feeding (IYCF) practices . 164 Table 12.7 Prevalence of anaemia in children . 166 Table 12.8 Micronutrient intake among children . 169 Table 12.9 Presence of iodized salt in household . 170 Table 12.10 Nutritional status of women . 171 Table 12.11 Foods consumed by mothers in the day or night preceding the interview. 173 Table 12.12.1 Prevalence of anaemia in women . 174 Tables and Figures | xv Table 12.12.2 Prevalence of anaemia in men . 176 Table 12.13 Micronutrient intake among mothers . 177 Table 12.14 Prevalence of vitamin A deficiency in children . 179 Table 12.15 Prevalence of vitamin A deficiency in women . 181 Figure 12.1 Nutritional Status of Children Under Five. 156 Figure 12.2 Among Last Children Born in the Five Years Preceding the Survey Who Ever Received a Prelacteal Liquid, the Percentage Who Received Various Types of Liquids . 158 Figure 12.3 Infant Feeding Practices by Age. 160 Figure 12.4 Infant and Young Child Feeding (IYCF) Practices . 165 Figure 12.5 Trends in Anaemia Status among Children under Five Years. 167 Figure 12.6 Trends in Nutritional Status among Women Age 15-49. 172 Figure 12.7 Trends in Anaemia Status among Women Age 15-49. 175 CHAPTER 13 MALARIA Table 13.1 Ownership of mosquito nets . 184 Table 13.2 Brand of mosquito nets . 185 Table 13.3 Source of mosquito nets. 186 Table 13.4 Brand of mosquito net by source . 187 Table 13.5 Use of mosquito nets by children. 188 Table 13.6 Use of mosquito nets by women. 189 Table 13.7 Prophylactic use of antimalarial drugs and use of Intermittent Preventive Treatment (IPT) by women during pregnancy. 190 Table 13.8 Prevalence and prompt treatment of fever . 191 Table 13.9 Type and timing of antimalarial drugs. 193 Table 13.10 Availability at home of antimalarial drugs taken by children with fever . 193 Table 13.11 Household insecticide spraying . 194 CHAPTER 14 HIV/AIDS-RELATED KNOWLEDGE, ATTITUDES, AND BEHAVIOUR Table 14.1 Knowledge of AIDS. 195 Table 14.2 Knowledge of HIV prevention methods. 196 Table 14.3.1 Comprehensive knowledge about HIV/AIDS: Women . 198 Table 14.3.2 Comprehensive knowledge about HIV/AIDS: Men. 199 Table 14.4.1 Knowledge of prevention of mother-to-child transmission (PMTCT) of HIV: Women. 201 Table 14.4.2 Knowledge of prevention of mother-to-child transmission (PMTCT) of HIV: Men . 202 Table 14.5.1 Knowledge of drug treatments for AIDS: Women. 204 Table 14.5.2 Knowledge of drug treatments for AIDS: Men . 205 Table 14.6 Knowledge of sources of ARV drugs . 206 Table 14.7 Exposure of respondents to messages on drug treatments for AIDS. 207 Table 14.8 Expanded knowledge about ARVs. 208 Table 14.9.1 Accepting attitudes towards those living with HIV/AIDS: Women. 210 Table 14.9.2 Accepting attitudes towards those living with HIV/AIDS: Men . 211 Table 14.10 Accepting attitudes towards children living with HIV/AIDS . 212 Table 14.11 Attitudes towards negotiating safer sexual relations with husband. 213 xvi | Tables and Figures Table 14.12.1 Multiple sexual partners and higher-risk sexual intercourse in the past 12 months: Women. 215 Table 14.12.2 Multiple sexual partners and higher-risk sexual intercourse in the past 12 months: Men . 216 Table 14.13 Transactional sex. 218 Table 14.14 Payment for sexual intercourse and condom use at last paid sexual intercourse: Men. 219 Table 14.15.1 Coverage of prior HIV testing: Women . 220 Table 14.15.2 Coverage of prior HIV testing: Men. 221 Table 14.16 Pregnant women counselled and tested for HIV. 222 Table 14.17 Self-reported prevalence of sexually transmitted infections (STIs) and STIs symptoms . 223 Table 14.18 Prevalence of medical injections . 225 Table 14.19 Comprehensive knowledge about HIV/AIDS and of a source of condoms among young adults. 227 Table 14.20 Age at first sexual intercourse among young adults . 229 Table 14.21 Condom use at first sexual intercourse among young adults . 231 Table 14.22 Premarital sexual intercourse and condom use during premarital sexual intercourse among young adults . 232 Table 14.23.1 Higher-risk sexual intercourse among young adults and condom use at last higher-risk intercourse: Women . 233 Table 14.23.2 Higher-risk sexual intercourse among young adults and condom use at last higher-risk intercourse: Men . 234 Table 14.24 Drunkenness during sexual intercourse among young adults . 236 Table 14.25 Recent HIV tests among young adults . 237 Figure 14.1 Knowledge of Sources for PMTCT Drugs. 203 Figure 14.2 Expanded Knowledge of ARVs . 209 Figure 14.3 Perception and Beliefs about Abstinence and Faithfulness. 214 Figure 14.4 Percent Distribution of Women and Men Age 15-49 with an STI or Symptoms of STIs in the Past 12 Months Who Sought Advice or Treatment, by Source of Advice or Treatment . 224 Figure 14.5 Percent Distribution of Women and Men Age 15-49 Who Received a Medical Injection in the Past 12 Months by Type of Facility Where the Last Injection Was Received. 226 Figure 14.6 Percentage of Women and Men Age 15-49 Whose Last Injection was Given with a Syringe and Needle Taken from a New, Unopened Package, by Type of Facility . 226 Figure 14.7 Trends in Age at First Sex among Young Women and Men. 230 Figure 14.8 Abstinence, Being Faithful, and Condom Use (ABC) among Young Women and Men. 235 CHAPTER 15 WOMEN’S EMPOWERMENT AND DEMOGRAPHIC AND HEALTH OUTCOMES Table 15.1.1 Employment and cash earnings among currently married women . 240 Table 15.1.2 Employment and cash earnings among currently married men . 241 Table 15.2.1 Control over women’s cash earnings and relative magnitude of women’s earnings: Women . 242 Table 15.2.2 Control over men’s cash earnings. 244 Tables and Figures | xvii Table 15.3 Women’s control over their own earnings and over those of their husband/partner . 245 Table 15.4.1 Women’s participation in decisionmaking. 246 Table 15.4.2 Women’s participation in decisionmaking according to men. 246 Table 15.5.1 Women’s participation in decisionmaking by background characteristics . 247 Table 15.5.2 Men’s attitudes towards wives’ participation in decisionmaking. 249 Table 15.6.1 Women’s attitudes towards wife beating . 251 Table 15.6.2 Men’s attitudes towards wife beating . 252 Table 15.7.1 Women’s attitudes towards refusing sexual intercourse with husband . 253 Table 15.7.2 Men’s attitudes towards a wife refusing sexual intercourse with her husband. 255 Table 15.7.3 Men’s attitudes towards a husband’s rights when his wife refuses to have sexual intercourse. 256 Table 15.8 Indicators of women’s empowerment . 257 Table 15.9 Current use of contraception by women’s empowerment status. 258 Table 15.10 Women’s empowerment and ideal number of children and unmet need for family planning . 259 Table 15.11 Reproductive health care by women’s empowerment. 260 Table 15.12 Early childhood mortality rates by women’s status . 261 Figure 15.1 Number of Decisions in Which Currently Married Women Participate. 248 Figure 15.2 Percentage of Men and Women Who Believe That a Woman is Justified in Refusing Intercourse With Her Husband, for Specific Reasons. 254 CHAPTER 16 ORPHANS AND VULNERABLE CHILDREN Table 16.1 Children's living arrangements and orphanhood . 264 Table 16.2 Orphans and vulnerable children (OVC) . 265 Table 16.3 School attendance by survivorship of parents and OVC status . 268 Table 16.4 Possession of basic material needs by orphans and vulnerable children (OVC) . 270 Table 16.5 Orphans not living with siblings. 271 Table 16.6 Sexual intercourse before age 15 for orphans and vulnerable children (OVC) . 272 Table 16.7 Succession planning . 273 Table 16.8 Widows dispossessed of property. 274 Table 16.9 External support for orphans and vulnerable children. 275 Figure 16.1 Percentage of Children Age 0-17 Who Are Orphaned or Vulnerable. 266 Figure 16.2 Percentage of Orphaned and Vulnerable Children Currently Attending School . 269 Figure 16.3 Percentage of OVC and Non-OVC Children Under Age Five Years Who Are Underweight. 272 CHAPTER 17 ADULT AND MATERNAL MORTALITY Table 17.1 Data on siblings . 277 Table 17.2 Adult mortality . 278 Table 17.3 Trends in adult mortality . 280 Table 17.4 Maternal mortality . 281 xviii | Tables and Figures Figure 17.1 Trends in Adult Mortality Rates for Women, 1995 UDHS, 2000-01 UDHS, and 2006 UDHS. 279 Figure 17.2 Trends in Adult Mortality Rates for Men, 1995 UDHS, 2000-01 UDHS, and 2006 UDHS. 280 CHAPTER 18 VIOLENCE Table 18.1 Experience of physical violence. 287 Table 18.2 Persons committing physical violence. 288 Table 18.3 Violence during pregnancy . 289 Table 18.4 Experience of sexual violence . 290 Table 18.5 Persons committing sexual violence . 292 Table 18.6 Experience of different forms of violence . 293 Table 18.7.1 Forms of spousal violence: Women. 294 Table 18.7.2 Forms of spousal violence: Men . 296 Table 18.8.1 Spousal violence by background characteristics: Women . 298 Table 18.8.2 Spousal violence by background characteristics: Men . 299 Table 18.9 Frequency of spousal violence among women who reported violence . 301 Table 18.10 Injuries to women and men resulting from spousal violence. 303 Table 18.11.1 Violence by women against their spouse . 304 Table 18.11.2 Violence by men against their spouse. 306 Table 18.12 Help seeking to stop violence . 308 Table 18.13 Sources from which help was sought. 309 Figure 18.1 Age at First Experience of Sexual Violence . 291 Figure 18.2 Percentage of Ever-married Women Age 15-49 Who Have Experienced Various Forms of Physical and Sexual Violence by Their Husband/Partner. 295 Figure 18.3 Percentage of Ever-married Men Age 15-49 Who Have Experienced Various Forms of Physical and Sexual by Their Wife/Partner. 297 Figure 18.4 Among Ever-married Men Age 15-49 Who Reported Violence, Frequency of Spousal Violence (Emotional and Physical or Sexual). 302 APPENDIX A SAMPLE IMPLEMENTATION Table A.1 Sample implementation: Women . 313 Table A.2 Sample implementation: Men. 314 APPENDIX B ESTIMATES OF SAMPLING ERRORS Table B.1 List of selected variables for sampling errors, Uganda 2006 . 317 Table B.2 Sampling errors for national sample, Uganda 2006 . 318 Table B.3 Sampling errors for urban sample, Uganda 2006. 319 Table B.4 Sampling errors for rural sample, Uganda 2006. 320 Table B.5 Sampling errors for Central 1 region, Uganda 2006. 321 Table B.6 Sampling errors for Central 2 region, Uganda 2006 . 322 Table B.7 Sampling errors for Kampala region, Uganda 2006. 323 Table B.8 Sampling errors for East Central region, Uganda 2006. 324 Table B.9 Sampling errors for Eastern region, Uganda 2006. 325 Table B.10 Sampling errors for North region, Uganda 2006. 326 Table B.11 Sampling errors for West Nile region, Uganda 2006. 327 Tables and Figures | xix Table B.12 Sampling errors for Western region, Uganda 2006 . 328 Table B.13 Sampling errors for Southwest region, Uganda 2006 . 329 APPENDIX C DATA QUALITY TABLES Table C.1 Household age distribution . 331 Table C.2.1 Age distribution of eligible and interviewed women . 332 Table C.2.2 Age distribution of eligible and interviewed men. 332 Table C.3 Completeness of reporting . 333 Table C.4 Births by calendar years . 333 Table C.5 Reporting of age at death in days . 334 Table C.6 Reporting of age at death in months. 335 Table C.7 Data on siblings . 335 Table C.8 Sibship size and sex ratio of siblings . 335 APPENDIX D NUTRITIONAL STATUS OF CHILDREN—2006 UDHS DATA ACCORDING TO THE NCHS/CDC/WHO INTERNATIONAL REFERENCE POPULATION Table D.1 Nutritional status of children . 337 Preface | xxi The 2006 UDHS was the fourth in the series that started in 1988. The primary objective of this survey was to provide up-to-date information for policy makers, planners, researchers and program managers, to use in the planning, implementation, monitoring and evaluation of population and health programs in the country. Unlike the previous three surveys which did not cover the whole country because of insecurity in some areas, the UDHS 2006 covered all districts of the country. In addition, the content of the survey was expanded to include questions on disability and gender-related violence. The findings of the 2006 UDHS are very important in measuring the achievements of family planning and other health programs. To ensure better understanding and use of these data, the results of this survey should be widely disseminated at different planning levels. Different dissemination techniques will be used to reach different segments of society. Uganda Bureau of Statistics would like to acknowledge the efforts of a number of organizations and individuals who contributed immensely to the success of the survey. The Ministry of Health chaired the Steering and Technical Committees, which offered guidance on the implementation of the survey. In addition, the Ministry of Health and the Population Secretariat participated in the community mobilization campaign. The Institute of Statistics and Applied Economics (ISAE) of Makerere University carried out the Quality Control study and the Department of Bio-chemistry conducted laboratory testing for vitamin A deficiency. Financial assistance was provided by USAID and the President’s Emergency Plan for AIDS Relief, DFID, UNFPA, UNICEF, the Government of Japan, and the Health Partnership Fund. Macro International Inc. is greatly appreciated for having offered critically important technical support. We are grateful for the efforts of officials at national and local government levels who supported the survey. Finally, we highly appreciate all the field staff and, more importantly, the survey respondents whose participation was critical to the successful completion of this survey. John B. Male-Mukasa Executive Director Uganda Bureau of Statistics PREFACE Summary of Findings | xxiii SUMMARY OF FINDINGS The 2006 Uganda Demographic and Health Survey (UDHS) is a nationally representative survey of 8,531 women age 15-49 and 2,503 men age 15-54. The UDHS is the fourth com- prehensive survey conducted in Uganda as part of the worldwide Demographic and Health Sur- veys (DHS) project. The primary purpose of the UDHS is to furnish policymakers and planners with detailed information on fertility; family planning; infant, child, adult, and maternal mor- tality; maternal and child health; nutrition; and knowledge of HIV/AIDS and other sexually transmitted infections. In addition, in one in three households selected for the survey, women age 15-49, men age 15-54, and children under age 5 years were weighed and their height was measured. Women, men, and children age 6-59 months in this subset of households were tested for anaemia, and women and children were tested for vitamin A deficiency. The 2006 UDHS is the first DHS survey in Uganda to cover the entire country. FERTILITY Survey results indicate that the total fertility rate (TFR) for the country is 6.7 births per woman. The TFR in urban areas is much lower than in the rural areas (4.4 and 7.1 children, re- spectively). Kampala, whose TFR is 3.7, has the lowest fertility. Fertility rates in Central 1, Cen- tral 2, and Southwest regions are also lower than the national level. Removing four districts from the 2006 data that were not covered in the 2000- 2001 UDHS, the 2006 TFR is 6.5 births per woman, compared with 6.9 from the 2000-2001 UDHS. Education and wealth have a marked effect on fertility, with uneducated mothers hav- ing about three more children on average than women with at least some secondary education and women in the lowest wealth quintile having almost twice as many children as women in the highest wealth quintile. Childbearing starts early and is nearly uni- versal. Ugandan women have an average of 3.5 children by their late twenties and more than six children by their late thirties. The initiation of childbearing in Uganda has not changed much over time, although it seems that there is a slight increase in age at first birth in recent years. The median age at first birth in Uganda is 19.1 years for women age 20-24, the youngest cohort for whom a median age can be estimated. The findings further show that women in the highest wealth quintile; urban women; and women who reside in Karamoja, Kampala, and Southwest regions tend to have their first child at a later age than do other women. Women with secondary education started having children two years later than those with less education (20.6 and 18.5 years, respectively). Marriage patterns are an important determi- nant of fertility levels in a population. The age at first marriage for women appears to be increas- ing in Uganda. The median age at first marriage has increased from 17.4 years of age among women age 45-49 to 18.3 years among women age 20-24. Ugandan women tend to initiate sex- ual intercourse about one year before marriage, as evidenced by the median age at first inter- course among women age 20-49 of 16.6 years compared with the median age at first marriage of 17.8 years. Like age at first marriage, age at first sex appears to be increasing among women in Uganda. The percentages of women who had sexual intercourse by exact age 15 and exact age 18 are both lower among younger cohorts of women than older women. Men, in contrast, tend to marry several years later than women and initiate sexual activity sev- eral years before marriage. The median age at marriage among men age 20-49 is 22.7 years, while the median age at first intercourse is 18.1 years. The age at first sex for men has remained relatively constant over the years. The majority of non-first births in Uganda (75 percent) occur at least 24 months after the birth of the previous sibling. The overall median birth interval is almost 30 months (29.7). These numbers do not differ from what was reported in the 2000-2001 UDHS. Birth intervals vary slightly across regions, with the longest in Kam- pala (33.1 months) and the shortest in East Cen- xxiv | Summary of Findings tral (28.4 months). Urban women have slightly longer intervals between births compared with rural women (32.5 and 29.6 months, respec- tively). FAMILY PLANNING Overall, knowledge of family planning has remained consistently high in Uganda over the past five years, with 97 percent of all women and 98 percent of all men age 15-49 having heard of at least one method of contraception. Pills, injectables, and condoms are the most widely known modern methods among both women and men. Fifty-two percent of currently married women have ever used a family planning method at least once in their lifetime. The methods commonly ever used for family planning by married women are injectables, male condoms, pills, and the rhythm method. Twenty-four percent of currently married women age 15-49 are currently using a method of contraception, up from 19 percent in the 2000-2001 UDHS when excluding lactational amenorrhoea method (LAM). Modern methods are more widely used than traditional methods, with 18 percent of currently married women us- ing a modern method and 6 percent using a tradi- tional method. The most popular modern method is the injectable. Married women in urban areas are twice as likely to use contraception (43 per- cent) as women in rural areas (21 percent). Con- traceptive use among married women is highest in Kampala (48 percent) and lowest in the North (11 percent). Less than one percent of married women in Karamoja are currently using contra- ception, none of whom are using a modern method. Just over half (52 percent) of currently mar- ried women obtain methods of contraception from private medical sources, while 35 percent obtain their method from government facilities. Thirteen percent obtain their method from other private sources. Almost half of the users of the contraceptive pill (47 percent) and nearly all condom users (96 percent) use socially marketed brands of these contraceptives. Overall, 41 percent of currently married women have an unmet need for family planning services. The need for spacing (25 percent) is higher than the need for limiting (16 percent). If all currently married women who say they want to space or limit the number of children were to use family planning, the contraceptive preva- lence rate in Uganda would increase from 24 percent to 64 percent. Currently, only 37 percent of the demand for family planning is being met. MATERNAL HEALTH Ninety-four percent of women who had a live birth in the five years preceding the survey received antenatal care from a skilled health pro- fessional for their last birth. These results are comparable to the 2000-2001 UDHS. Only 47 percent of women make four or more antenatal care visits during their entire pregnancy, an im- provement from 42 percent in the 2000-2001 UDHS. The median duration of pregnancy for the first antenatal visit is 5.5 months, indicating that Ugandan women start antenatal care at a relatively late stage in pregnancy. Among women who received antenatal care, 35 percent reported that they were informed about how to recognize signs of problems during pregnancy. Weight and blood pressure meas- urements were taken for 77 percent and 53 per- cent of women, respectively. A urine sample was taken from only 12 percent of women, while blood samples were taken from 28 percent. Half of women received two or more tetanus toxoid injections during their last pregnancy. In the case of an additional 25 percent of women, the baby was protected against neonatal tetanus because of previous immunisations the woman had re- ceived. Four in ten births occur in a health facility. The proportion of births in a health facility has risen from 37 percent in the 2000-2001 UDHS. Overall, 42 percent of births were delivered with the assistance of a trained health professional— that is, a doctor, nurse, midwife, medical assis- tant, or clinical officer—while 23 percent were delivered by a traditional birth attendant (TBA). One-quarter of births were attended by a relative or some other person while 10 percent of births were delivered without any type of assistance at all. Summary of Findings | xxv Postpartum care is extremely low in Uganda. Three-quarters of women who had a live birth in the five years preceding the survey received no postnatal care at all, and only 23 percent of mothers received postnatal care within the criti- cal first two days after delivery. The 2006 UDHS collected data on female circumcision, or female genital cutting (FGC), and fistula. Results show that 34 percent of women have heard of FGC, while less than one percent have themselves been circumcised. The highest percentage of women who are circum- cised is found in Eastern region. The survey found that 3 percent of women report they have experienced symptoms of obstetric fistula. CHILD HEALTH Forty-six percent of children age 12-23 months have been fully vaccinated. Over nine in ten (91 percent) have received the BCG vaccina- tion, and 68 percent have been vaccinated against measles. The coverage for the first doses of DPT and polio is relatively high (90 percent for each). However, only 64 percent go on to receive the third dose of DPT, and only 59 per- cent receive their third dose of polio vaccine. There are notable improvements in vaccination coverage since the 2000-2001 UDHS. The per- centage of children age 12-23 months fully vac- cinated at the time of the survey increased from 37 percent in 2000-2001 to 44 percent in 2006. The percentage who had received none of the six basic vaccinations decreased from 13 percent in 2000-2001 to 8 percent in 2006. Nationally, 26 percent of children under age five had diarrhoea at some time in the two weeks before the survey, while 6 percent had diarrhoea with blood. Seven in ten children with diarrhoea were taken to a health provider. Diarrhoea was more prevalent in the North (36 percent) than in other regions, with a particularly high rate in IDP camps (44 percent). The prevalence of diar- rhoea decreases steadily with increasing level of mother’s education and increasing wealth quin- tile. Fifty-four percent of children with diarrhoea were treated with some kind of oral rehydration therapy (ORT): 40 percent were treated with ORS (solution prepared from ORS packets), 7 percent were given recommended home fluids (RHF), and 20 percent were given increased flu- ids. On the other hand, 17 percent of children with diarrhoea did not receive any type of treat- ment at all. Fifteen percent of children under age five showed symptoms of acute respiratory infection (ARI) in the two weeks prior to the survey. Use of a health facility for the treatment of symptoms of ARI is high, with 73 percent of children taken to a health facility or provider. MALARIA The 2006 UDHS gathered information on the use of mosquito nets, both treated and un- treated. The data show that only 34 percent of households in Uganda own a mosquito net, with 16 percent of households owning an insecticide- treated net (ITN). Only 22 percent of children under five slept under a mosquito net on the night before the interview, while a mere 10 per- cent slept under an ITN. Twenty-four percent of pregnant women slept under a mosquito net on the night preced- ing the interview, while 10 percent of pregnant women slept under an ITN. Eighteen percent of women who gave birth in the two years before the survey took at least two doses of SP/Fansidar during pregnancy, and 16 percent of pregnant women took at least two doses and received at least one of them during an antenatal care visit. Forty-one percent of children under five were reported to have had fever, a prominent symptom of both ARI and malaria, in the two weeks before the survey. Three in four children were taken to a health facility or provider for treatment. Sixty-one percent of the children who had fever took antimalarial drugs while 35 per- cent took antibiotics. Antimalarial drugs most commonly administered to children with fever are chloroquine and quinine (taken by 28 percent and 14 percent of children with fever, respec- tively). BREASTFEEDING AND NUTRITION In Uganda, almost all children are breastfed at some point. However, only six in ten children under the age of 6 months are exclusively breast- fed. The median duration of exclusive breast- feeding is 3.1 months, while the median duration xxvi | Summary of Findings of any breastfeeding is almost 20.4 months. The data also show that complementary foods are not introduced in a timely fashion for some children. At 6-9 months, around one in five children is not receiving complementary foods. The use of a bottle with a nipple is not widespread in Uganda. However, the proportion of children who are bottle-fed increases from 3 percent among chil- dren less than 2 months of age to 26 percent among children 6-8 months of age, after which it declines gradually. Ninety-six percent of women and children 6- 59 months of age live in households using ade- quately iodized salt. Over one in three children (36 percent) age 6-59 months received a vitamin A supplement in the 6 months preceding the sur- vey. Among women who gave birth in the five years preceding the survey, 33 percent received a dose of vitamin A in the 2 months after giving birth to their last child. Twenty percent of children and 19 percent of women were found to have vitamin A defi- ciency. Almost three-quarters of children (73 percent) are anaemic, compared with just under half of women (49 percent). The prevalence of anaemia among men is less pronounced. Only 28 percent of men age 15-49 are anaemic. The level of malnutrition is substantial. Nearly four in ten Ugandan children under five years of age (38 percent) are stunted (short for their age), 6 percent are wasted (thin for their height), and 16 percent are underweight. In gen- eral, rural children and children whose mothers have less than a secondary education are more likely to be stunted or underweight than other children. Regional variation in nutritional status of children is substantial. Stunting levels are highest in Southwest and North regions. Wasting is highest in Southwest and East Central regions. The percentage of underweight children is high- est in Southwest, East Central, and North re- gions. Survey results for the level of chronic en- ergy deficiency among women show that only 12 percent of women in Uganda fall below the cutoff of 18.5 for the body mass index (BMI), which utilizes both height and weight, to meas- ure thinness. Seventeen percent of women are overweight or obese. HIV/AIDS AND STIs Knowledge of AIDS is very high and wide- spread in Uganda. In terms of HIV prevention strategies, women and men are most aware that the chances of getting the AIDS virus can be reduced by limiting sex to one uninfected partner who has no other partners (89 percent of women and 95 percent of men) or by abstaining from sexual intercourse (86 percent of women and 93 percent of men). Knowledge of condoms and the role they can play in preventing transmission of the AIDS virus is not quite as high (70 percent of women and 84 percent of men). Eighty-five percent of women and 90 per- cent of men know that a healthy-looking person can have the AIDS virus. Larger proportions of respondents are also aware that the AIDS virus cannot be transmitted by supernatural means or by sharing food. However, many women and men erroneously believe that AIDS can be transmitted by mosquito bites. Seventy-three percent of women and 63 per- cent of men know that HIV can be transmitted by breastfeeding. A lower proportion of women (65 percent) and about the same proportion of men (64 percent) know that the risk of mother- to-child transmission (MTCT) can be reduced through the use of certain drugs during preg- nancy. Survey results show that 82 percent of women know of drugs for people living with AIDS. Among those, only 10 percent know ARVs by name and 12 percent know Septrin. Among men, 87 percent know of drugs for peo- ple with AIDS, and among those, 22 percent know ARVs by name, and 13 percent know Sep- trin. One in four women and 21 percent of men age 15-49 report that they have been tested for HIV at some time and received the results. Al- most four in ten women who gave birth in the two years before the survey (39 percent) report that they received information and counselling about HIV/AIDS during antenatal care for their most recent birth. However, only 18 percent re- ceived counselling, were tested, and received the results. Summary of Findings | xxvii Twenty-two percent of ever sexually active women and 13 percent of ever sexually active men reported that they had had an STI and/or STI symptoms in the 12 months prior to the sur- vey. Among young people age 15-24 who have never been married, 66 percent of young women and 54 percent of young men have never had sexual intercourse. Twenty-four percent of never-married young women had sexual inter- course in the 12 months preceding the survey, and 39 percent of those used a condom at last intercourse. Among never-married young men, 28 percent had sexual intercourse in the past 12 months, and 56 percent of those used a condom at last intercourse. ORPHANHOOD AND VULNERABILITY Almost one in seven children under age 18 is orphaned (15 percent), that is, one or both par- ents are dead. Only 3 percent of children under the age of 18 have lost both biological parents. Maternal orphans, those whose mother has died but whose father is still living, are less common than paternal orphans (3 percent vs. 9 percent). Overall, 8 percent of children under age 18 are considered vulnerable, i.e., they live in a house- hold in which at least one adult had been chroni- cally ill or died during the year before the survey or they have at least one parent living in the household or elsewhere who suffers from a chronic illness. One in five Ugandan children are orphaned or vulnerable (21 percent). Among children of secondary school-going age, children who are orphaned or vulnerable (OVC) are less likely than non-OVC to attend school (76 percent versus 83 percent). OVC are also somewhat less likely to have a pair of shoes, two sets of clothes and a blanket than non-OVC children (25 percent versus 29 percent). WOMEN’S STATUS AND GENDER VIOLENCE Data for the 2006 UDHS show that women in Uganda are generally less educated than men. Although the gender gap has narrowed in recent years, 19 percent of women age 15-49 have never been to school, compared with only 5 per- cent of men in the same age group. Only 56 per- cent of women age 15-49 are literate compared to 83 percent of men. Although female employment is high in Uganda, with 86 percent employed in the 12 months preceding the survey, a high proportion (75 percent) are employed in the agricultural sector. By comparison, 95 percent of the males were employed in the 12 months preceding the survey, with 68 percent employed in agriculture. Furthermore, a higher proportion of married women than men are not paid for their work (30 percent compared with 13 percent). While 22 percent of married women make sole decisions on their own health care, four in ten say that their husband or partner makes such decisions. Decisions on large household pur- chases are typically made by the husband or partner alone or jointly by the woman with their husband or partner. Thirty-six percent of women say that decisions to visit their own family or relatives are made mainly by their husband or partner. The 2006 UDHS included a module on vio- lence. Six in ten women and 53 percent of men have experienced physical violence since age 15. For women, their current husband or partner is the most common perpetrator of this violence. Four in ten women and 11 percent of men have ever experienced sexual violence. Survey results show that 59 percent of ever-married women have ever experienced physical or sexual vio- lence at the hands of their husband or partner. Twenty-four percent of ever-married men ex- perienced physical or sexual violence perpe- trated by their wife or partner. MORTALITY At current mortality levels, one in every 13 Ugandan children dies before reaching age one, while one in every seven does not survive to the fifth birthday. After removing districts not cov- ered in the 2000-2001 UDHS from the 2006 data, findings show that infant mortality has de- clined from 89 deaths per 1,000 live births in the 2000-2001 UDHS to 75 in the 2006 UDHS. Un- der-five mortality has declined from 158 deaths per 1,000 live births to 137. Mortality is consistently lower in urban ar- eas than in rural areas with rates of 68 and 88 deaths per 1,000 live births, respectively, for infant mortality and 114 and 153 deaths per 1,000 live births for under-five mortality. The xxviii | Summary of Findings lowest level for infant mortality is in Kampala, the most urbanized part of the country, while the highest level is in Southwest region. Survival of infants and children is strongly influenced by the gender of the child, mother’s age at birth, birth order, and birth interval. Male children experience higher mortality than female children, and the gender difference is especially pronounced for neonatal mortality. Under-five mortality is higher among children born to mothers under age 20 and over age 40. First births and births of order seven and higher also suffer higher rates of infant and under-five mor- tality than births of order two to six. Children born within two years of a preceding birth are more than twice as likely to die within the first year of life as children born three or more years after an older sibling. The 2006 UDHS measured a maternal mor- tality ratio (MMR) of 435 maternal deaths per 100,000 live births. The maternal mortality esti- mate is subject to larger sampling errors than all other indicators in the survey; the 95 percent confidence intervals indicate that the maternal mortality ratio varies from 345 to 524. There- fore, it is not possible to say conclusively that MMR has declined. Direct estimates of male and female mortal- ity obtained from the sibling history gathered in the UDHS show that the level of adult mortality is slightly higher among men than among women (9.3 and 8.2 deaths per 1,000 popula- tion). The age-specific mortality rates show ex- pected increases for both sexes with increasing age. For age groups 15-19 and 20-24, female mortality slightly exceeds male mortality; the rates are nearly the same for women and men at ages 25-29 and 30-34. Above age 35, male mor- tality exceeds female mortality by wider margins as age advances. A comparison of the 2006 UDHS data with results from the 1995 and 2000-2001 UDHS surveys suggests that there has not been much change in adult mortality lev- els over the past 10-15 years in Uganda. Millennium Development Goal Indicators | xxix MILLENNIUM DEVELOPMENT GOAL INDICATORS Value Goal Indicator Male Female Total 1. Eradicate extreme poverty and hunger � Prevalence of underweight children under five years of age1 17.3 14.4 15.9 2. Achieve universal primary education � Net enrolment ratio in primary education2 � Literacy rate of 15-24 year-olds3 82.3 69.8 81.2 57.7 81.8 60.4 3. Promote gender equality and empower women � Ratio of girls to boys in primary education � Ratio of girls to boys in secondary education � Ratio of literate women to men, 15-24 years old � Share of women in wage employment in the non- agricultural sector4 na na na na na na na na 0.95 0.81 0.83 19.9 4. Reduce child mortality � Under-five mortality rate (per 1,000 live births) � Infant mortality rate (per 1,000 live births) � Percentage of 1 year-old children immunized against measles 67.1 69.1 137 76 68.1 5. Improve maternal health � Maternal mortality ratio (per 100,000 live births) � Percentage of births attended by skilled health personnel5 na na na na 435 42.1 � Percentage of current users of contraception who are using condoms (any contraceptive method, currently married women 15-49) � Condom use at last high-risk sex (population 15-24)6 � Percentage of population aged 15-24 years with comprehensive correct knowledge of HIV/AIDS7 � Contraceptive prevalence rate (any modern method, currently married women 15-49) � Ratio of school attendance of orphans to school attendance of non-orphans aged 10-14 years � Percentage of children under five sleeping under ITN na 54.5 38.2 na 0.96 9.5 7.9 38.3 31.9 17.9 0.97 9.8 na na na na 0.96 9.7 6. Combat HIV/AIDS, malaria and other diseases � Percentage of children under five with fever who are appropriately treated Treatment:8 Prompt treatment:9 61.3 28.9 xxx | Millennium Development Goal Indicators Value Goal Indicator Urban Rural Total 7. Ensure environmental sustainability � Percentage of population using solid fuels10 � Percentage of population with sustainable access to an improved water source11 � Percentage of population with access to improved sanitation12 94.3 89.3 21.2 99.4 63.8 9.2 98.8 67.1 10.7 na = Not applicable 1 Proportion of children age 0-59 months who are below -2 standard deviations (SD) from the median of the WHO Child Growth Standards in weight-for-age 2 UHS data are based on reported attendance, not enrolment. 3 Refers to respondents who attended secondary school or higher or who can read a whole sentence 4 Wage employment includes respondents who received wages in cash or in cash and kind. 5 Among births in the past 5 years 6 High-risk refers to sexual intercourse with a partner who neither was a spouse nor who lived with the respondent; time frame is 12 months preceding the survey. 7 A person is considered to have a comprehensive knowledge about AIDS when they say that use of condoms for every sexual intercourse and having just one uninfected and faithful partner can reduce the chance of getting the AIDS virus, that a healthy-looking person can have the AIDS virus, and when they reject the two most common local misconceptions. The most common misconceptions in Uganda are that AIDS can be transmitted through mosquito bites and that a person can become infected with the AIDS virus by eating from the same plate as someone who is infected. 8 Malaria treatment is measured as the percentage of children ages 0-59 months who were ill with a fever in the two weeks preceding the interview who received an antimalarial drug. 9 The treatment is considered prompt if the child received the antimalarial the same day as the onset of fever or the following day. 10 Includes coal/lignite, charcoal, wood/straw/shrubs, agricultural crops and animal dung 11 Proportion whose main source of drinking water is a household connection (piped), public standpipe, borehole, protected dug well or spring, or rainwater collection 12 Improved sanitation technologies are: flush toilet, ventilated improved pit latrine, traditional pit latrine with a slab, or composting toilet Map of Uganda | xxxi Northern Western Central 2 Central 1 Eastern Southwest West Nile East Central Kampala Mukono Kitgum Amuru Moroto Lira Pader Bugiri Masindi Hoima Apac Kaabong Kalangala Gulu Rakai Arua Mpigi Masaka Kibaale Kotido Kiboga Soroti Kiruhura Kamuli Nebbi Mubende Nakapiripirit Kyenjojo Bushenyi Abim Kasese Mayuge Wakiso Isingiro Oyam Amuria Kumi Nakaseke MoyoYumbe Adjumani Katakwi Luwero Buliisa Nakasongola Kabale Iganga Nyadri Pallisa Kamwenge Mbarara Kabarole Mityana Ntungamo Amolatar Bu nd ibu gy o Tororo Ssembabule Dokolo Kaliro Kanungu Sironko Busia Bukedea Kisoro Kapchorwa Koboko Mbale Butaleja Bukwa K ayunga R ukungiri Jinja Ibanda Ka be ram aid o Ly an ton de N am utum ba Ma na fwa Budaka Bud uda ± UGANDA 0 50 100 15025 km TANZANIA DEM. REP. OF CONGO KENYA RWANDA SUDAN Lake Victoria Lake Albert Lake Edward Introduction � 1 INTRODUCTION 1 1.1 GEOGRAPHY AND ECONOMY The Republic of Uganda is located in East Africa and lies astride the equator. It is a landlocked country bordering Kenya in the east, Tanzania in the south, Rwanda in the southwest, the Democratic Republic of Congo in the west, and Sudan in the north. The country has an area of 241,039 square kilometres and is administratively divided into 80 districts (56 at the time of the survey). 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 making policy, setting standards, and supervising. National security is also the role of the central government. 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 heavy rains from March to May and light rains between September and December. The level of rainfall decreases towards the north, 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. Due to these combinations of climatic conditions, Uganda varies between tropical rain forest vegetation in the south and savannah woodlands and semidesert vegetation in the north. These climatic conditions determine the agricultural potential and thus the land’s population-carrying capacity, with high population densities in the Central and Western regions and declining densities towards the north. 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 the distribution is uneven over all areas. Coffee accounts for most of Uganda’s export revenues. During the period immediately following independence, from 1962 to 1970, Uganda had a flourishing economy with a gross domestic product (GDP) growth rate of 5 percent per annum, compared with a population growth rate of 2.6 percent per annum. However, 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. This seriously affected the growth of the economy and the provision of social services such as education and health care. Since 1986, however, the government has introduced and implemented several reform programmes that have steadily reversed the setbacks and aimed the country towards economic prosperity. Between 2001 and 2006, the country’s rate of growth in the GDP varied between 4.7 percent and 6.6 percent per annum (UBOS, 2006b). 1.2 POPULATION In the past, most demographic statistics in Uganda were derived from population censuses, which started in 1948. Subsequent censuses have been held in 1959, 1969, 1980, 1991, and 2002. In addition, Demographic and Health Surveys (DHS) have been conducted in 1988-1989, 1995, 2000-2001, and 2006, the subject of the present report. Additional demographic data have been obtained from other surveys devoted to specific subjects. Civil registration was made compulsory in Uganda in 1973. However, its coverage is incomplete and is therefore unsatisfactory 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 mentioned above. Since 1995, an attempt has been made to revive the civil registra- tion system in the country, but thus far, it has not reached a satisfactory level. 2 � Introduction Table 1.1 presents several demographic indices compiled from the population censuses of 1948 through 2002. The table shows that over that period, the population increased almost fivefold. The high growth rate is a result of high fertility and declining mortality levels. The annual population growth rate between 1969 and 1980 was 2.7 and decreased to 2.5 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 1948-2002 Indicator 1948 1959 1969 1980 1991 2002 Population (thousands) 4,958.5 6,536.5 9,535.1 12,632.2 16,672.7 24,227.3 Intercensal growth rate (percent) u 2.5 3.9 2.7 2.5 3.2 Density (population/kilometre2) 25 33 48 64 85 124 Percent urban u u 6.6a 6.7 9.9 12.3 Life expectancy Male u u 46.0 u 45.7 48.8 Female u u 47.0 u 50.5 52.0 Total u u 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, 2006a 1.3 NATIONAL POPULATION AND HEALTH PROGRAMMES The Government of Uganda (GOU) is aware of the challenges posed by demographic issues to the attainment of the nation’s development objectives. The country has developed several policies and programmes to help improve the health status and life of its people. To accommodate the new and emerging challenges of the quality of life of the nation, the 1995 National Population Policy has been revized and is currently under review. Among its objectives is to integrate the population and demographic factors at all planning levels, to promote positive health-seeking behaviour, and to reduce the unmet need for family planning. The policy will take into account the changing demographic, socio- economic and health environment, and other emerging issues. The National Health Sector Strategic Plan 2005/06–2009/10 (HSSP II) was developed as a consolidation and extension of the HSSP I. The overriding priority of the HSSP II is to fulfil the health sector contribution to the Poverty Eradication Action Plan (PEAP) and the Millennium Development Goals (MDG). The plan emphasizes the role of communities and households and seeks to foster a sense of individual ownership of health services. The programme targets the poor, orphans, children, women, the elderly, refugees, and internally displaced persons, among others. Reflective of the commitment of the Government of Uganda to address reproductive health issues following the 1994 International Conference on Population and Development (ICPD), the Sexual and Reproductive Health Policy Guidelines were developed. These guidelines help the GOU and reproductive health service providers to provide safe motherhood services and reduce the number of maternal-related deaths. Other components of the guidelines include family planning, adolescent sexual and reproductive health, sexually transmitted infections (STIs) including HIV/AIDS, reproductive organ cancer, and gender-based violence. Introduction � 3 To improve child health, the Ministry of Health has focused on a nationwide programme of Child Health Days Plus. This program aims to improve the health and nutrition status of children by providing vitamin A supplements, de-worming medication, and immunizations to children under 5 years of age. Other policies related to population and health include the Adolescent Sexual and Reproductive Health Policy, the Nutrition Policy, the HIV/AIDS Strategic Plan, the Gender Policy, the Poverty Eradication Action Plan, the National Malaria Control Strategic Plan, and the New Born Health Strategy, among others. To achieve the targets of these policies, the GOU, with the help of development partners, is implementing several population and reproductive health programmes in the country aimed at improving health behaviours of the population. 1.4 OBJECTIVES OF THE SURVEY The 2006 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, awareness and use of family planning methods, and breastfeeding practices. 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 2006 UDHS is a follow-up to the 1988-1989, 1995, and 2000-2001 UDHS surveys, which were also implemented by the Uganda Bureau of Statistics (UBOS). The specific objectives of the 2006 UDHS are as follows: • To collect data at the national level that will allow the calculation of demographic rates, particularly the fertility and infant mortality rates • To analyse the direct and indirect factors that determine the level 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 five and women by means of anthropometric measurements (weight and height), and to assess child feeding practices • To collect data on family health, including immunizations, prevalence and treatment of diarrhoea and other diseases among children under five, antenatal visits, assistance at delivery, and breastfeeding • 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. 4 � Introduction 1.5 ORGANIZATION AND METHODOLOGY OF THE SURVEY 1.5.1 The Survey Sample The sample of the 2006 UDHS was designed to allow separate estimates at the national level and for urban and rural areas of the country. The sample design also allowed for specific indicators, such as contraceptive use, to be calculated for each of nine sub-national regions. Portions of the northern region were oversampled in order to provide estimates for two special areas of interest: Karamoja and internally displaced persons (IDP) camps. At the time of the survey there were 56 districts. This number later increased to 80. The following shows the 80 districts divided into the regional sampling strata: Central 1: Kalangala, Masaka, Mpigi, Rakai, Lyantonde, Sembabule, and Wakiso Central 2: Kayunga, Kiboga, Luwero, Nakaseke, Mubende, Mityana, Mukono, and Nakasongola Kampala: Kampala East Central: Bugiri, Busia, Iganga, Namutumba, Jinja, Kamuli, Kaliro, and Mayuge Eastern: Kaberamaido, Kapchorwa, Bukwa, Katakwi, Amuria, Kumi, Bukedea, Mbale, Bududa, Manafwa, Pallisa, Budaka, Sironko, Soroti, Tororo, and Butaleja North: Apac, Oyam, Gulu, Amuru, Kitgum, Lira, Amolatar, Dokolo, Pader, Kotido, Abim, Kaabong, Moroto, and Nakapiripirit (Estimates for this region include both settled and IDP populations.) • Karamoja area: Kotido, Abim, Kaabong, Moroto, and Nakapiripirit • IDP: IDP camps in Apac, Oyam, Gulu, Amuru, Kitgum, Lira, Amolatar, Dokolo and Pader districts West Nile: Adjumani, Arua, Koboko, Nyadri, Nebbi, and Yumbe Western: Bundibugyo, Hoima, Kabarole, Kamwenge, Kasese, Kibaale, Kyenjojo, Masindi, and Buliisa Southwest: Bushenyi, Kabale, Kanungu, Kisoro, Mbarara, Ibanda, Isingiro, Kiruhura, Ntungamo, and Rukungiri A representative probability sample of 9,864 households was selected for the 2006 UDHS survey. The sample was selected in two stages. In the first stage, 321 clusters were selected from among a list of clusters sampled in the 2005-2006 Uganda National Household Survey (UBOS, 2006c). This matching of samples was conducted in order to allow for linking of 2006 UDHS health indicators to poverty data from the 2005-2006 UNHS. The clusters from the Uganda National Household Survey were in turn selected from the 2002 Census sample frame. For the UDHS 2006, an additional 17 clusters were selected from the 2002 Census frame in Karamoja in order to increase the sample size to allow for reporting of Karamoja- specific estimates in the UDHS. Finally, 30 IDP camps were selected from a list of camps compiled by the United Nations Office for the Coordination of Human Affairs (UN OCHA) as of July 2005, completing a total of 368 primary sampling units. Figure 1.1 shows the geographical distribution of the 368 clusters visited in the 2006 UDHS. In the second stage, households in each cluster were selected based on a complete listing of households. In the 321 clusters that were included in the UNHS sample, the lists of households used were those generated during the UNHS listing operations April-August 2005. The UNHS sampled ten households per cluster. All ten were purposively included in the UDHS sample. An additional 15 to 20 households were randomly selected in each cluster. The 17 additional clusters in Karamoja were listed, and 27 households were selected in each cluster. The selected IDP camps were divided into segments because of their large size, and one segment selected in each camp. Then a listing operation was carried out in the selected segment, and 30 households were selected in each camp from the segment of the map that was listed. Introduction � 5 Figure 1.1 Map of Uganda DHS Clusters !( !( !(!( !( !( !( !( !( !( !( !( !( !( !( !( !( !( !( !( !( !( !( !( !( !( !( !( !( !( !( !(!( !( !( !( !( !(!( !( !( !( !( !(!( !( !( !( !( !( !( !( !( !( !( !( !(!(!( !(!(!(!(!(!(!( !(!(!(!(!(!(!(!(!( !(!(!(!(!(!(!(!( !(!(!(!( !(!(!( !(!(!( !( !( !( !( !( !( !( !( !( !( !( !( !( !( !( !( !( !( !( !( !( !( !( !( !( !( !( !( !( !( !( !( !( !( !(!( !( !( !( !( !( !(!( !( !( !( !( !( !( !( !( !( !( !( !( !( !( !( !( !( !( !( !( !( !( !( !( !( !( !( !( !( !( !( !( !( !(!( !( !( !( !(!( !( !( !( !( !( !( !(!( !(!( !( !( !( !( !( !( !( !( !( !( !( !( !( !( !( !( !( !( !( !( !( !( !( !( !( !( !( !( !( !(!( !( !( !( !( !( !( !( !( !( !( !( !( !( !( !( !( !( !( !( !( !(!( !( !( !( !( !(!( !( !( !(!( !(!( !(!(!(!( !( !( !( !( !( !( !( !( !( !( !( !( !( !( !(!( !( !( !( !( !( !( !( !( !( !( !(!( !( !( !( !( !( !( !( !( !( !( !( !( !( !( !( !(!(!( !( _^ _^_^ _^ _^ _^ _^ _^ _^ _^ _^ _^ _^ _^ _^ _^ _^ _^ _^^_ _^ _^ _^_^^_ _^ _^ _^ _^ #* #* #* #* #* #*#*#* #* #* #* #* #* #* #* #* #* #* #* #* #* #* #* #* #* #* #*#* #*#* !( !( !( !( !( !( !( North Western Central 2 Central 1 Eastern Southwest West Nile East Central Kampala UGANDA DHS Clusters 0 50 100 15025 km UDHS Clusters #* IDP camps _^ Karamoja sub-region !( Other UDHS clusters ± Lake Victoria Lake Albert Lake Edward 6 � Introduction All women age 15-49 who were either permanent residents of the households in the 2006 UDHS sample or visitors present in the household on the night before the survey were eligible to be interviewed. In addition, in a sub-sample of one-third of all the households selected for the survey, all men age 15-54 were eligible to be interviewed if they were either permanent residents or visitors present in the household on the night before the survey. Indicators such as total fertility rate, childhood mortality rates, and the maternal mortality ratio require a larger sample size than other indicators. These indicators are all calculated from the data provided by female respondents only. For this reason, the number of male respondents required in the sample to obtain acceptable precision in estimates of desired indicators is lower than the number of female respondents. Biomarkers collected in the UDHS included height and weight measurements for children under 6 years, women age 15-49, and men age 15-54; anaemia testing in children age 6 to 59 months old, women age 15-49, and men age 15-54; and dried blood spot collection for vitamin A testing in children age 6 to 59 months old and women age 15 to 49 years. All of these biomarkers were measured only in those households selected for the male interview—that is, one in three households. Details of the UDHS sample design are provided in Appendix A and estimations of sampling errors are included in Appendix B. 1.5.2 Comparability of the 2006 UDHS Sample with Samples from Previous UDHS Surveys The 2006 UDHS is the first UDHS to include the entire country in the sample. In previous surveys, it was necessary to exclude groups of districts because of security problems. In the 2000-2001 UDHS, areas making up the current districts of Amuru, Bundibugyo, Gulu, Kasese, Kitgum, and Pader were excluded from the sample. According to the 2002 Census, these areas comprise around 7 percent of the population of Uganda (UBOS 2006a). The 1995 UDHS excluded Kitgum and Pader, while the 1988- 1989 UDHS excluded most of the Northern region. To show trends using comparable data, the 2006 UDHS data were run without the districts that were excluded in previous surveys. For some key indicators, the report presents two estimates from the 2006 data: one covering the entire country, and a second covering the geographic area surveyed in the 2000-2001 UDHS. Differences between these two estimates are small, seldom exceeding one or two percentage points. Because it was not possible to run every indicator twice, the report includes many comparisons between the 2000-2001 and 2006 surveys in which the 2006 data have not been adjusted. The report states explicitly when the 2006 data presented are adjusted; otherwise, the data are unadjusted. Comparisons that include unadjusted 2006 data should be interpreted with caution. 1.5.3 Questionnaires Three questionnaires were used for the 2006 UDHS, namely, the Household Questionnaire, the Women’s Questionnaire, and the Men’s Questionnaire. The contents of these questionnaires were based on the model questionnaires for the MEASURE DHS program. In consultation with technical institutions and local organizations, UBOS adapted these questionnaires to reflect population and health issues relevant in Uganda. The revized questionnaires were translated from English into six local languages, namely, Ateso/Karamojong, Luganda, Lugbara, Luo, Runyankole/Rukiga, and Runyoro/Rutoro. The questionnaires were pretested prior to their finalization in January and February of 2006. The Household Questionnaire was used to list all the usual members and visitors in the selected households. The main purpose of the Household Questionnaire was to identify women and men who were eligible for the individual interview. Some basic information was collected on the characteristics of each person listed, including age, sex, education, and relationship to the head of the household. For children under age 18, survival status of the parents was determined. The Household Questionnaire also collected Introduction � 7 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 nets. Care and support services received by orphans and other vulnerable children and disability status of household members were also collected in the Household Questionnaires. Finally, the Household Questionnaire was used to document the respondents’ decision as to whether to volunteer to give blood samples for vitamin A deficiency (VAD) testing as well as to record the height, weight, and haemoglobin measurements of women age 15-49 years, men age 15-54 years, and children age 6-59 months in those households selected for these measurements. The Women’s Questionnaire was used to collect information from all women age 15-49. These women were asked questions on the following topics: • Background characteristics (education, residential history, media exposure, etc.) • Birth history and childhood mortality • Knowledge and use of family planning methods • Fertility preferences • Antenatal and childbirth care • Breastfeeding and infant feeding practices • Vaccinations and childhood illnesses • Marriage and sexual activity • Woman’s work and husband’s background characteristics • Awareness and behavior regarding AIDS and other sexually transmitted infections (STIs) • Maternal mortality • Domestic violence. The Men’s Questionnaire was administered to all men age 15-54 living in every third household in the 2006 UDHS sample. The Men’s Questionnaire collected much of the same information found in the Women’s Questionnaire, but was shorter because it did not contain a detailed reproductive history or questions on maternal and child health or nutrition, or maternal mortality. The questionnaires used in the UDHS are presented in Appendix F. 1.5.4 Training of Field Staff UBOS recruited and trained staff to serve as supervisors, field editors, male and female interviewers, field coordinators, and health technicians. They all participated in the main interviewer training held in Entebbe April 2-28. UBOS, Macro, and invited experts from government ministries led the four-week training that included lectures, presentations, practical demonstrations, and practice interviewing in small groups, as well as two days of field practice. Participants were shown brands of contraceptives, vitamin A and iron folate supplements, and common antimalaria drugs, and they were taught how to test salt for iodine using test kits provided by UNICEF. During the training, special attention was paid to identifying brands of mosquito nets. Information sheets with photos of net material and net labels developed by the Malaria Consortium were presented and distributed to the trainees. Samples of common brands of nets were also shown. Salt samples were also tested for their iodine levels. The health technicians received training in anthropometry, hemoglobin testing, and the collection of dried blood spot (DBS) samples from a finger prick for the vitamin A deficiency (VAD) testing. 1.5.5 Community Mobilization Before and during fieldwork for the 2006 UDHS, a community mobilization programme was implemented by a multi-disciplinary team of members from the Uganda Bureau of Statistics, the Ministry of Health, and the Population Secretariat. The objective of the community mobilization was to sensitize the respondents regarding the survey, including key topics in the questionnaires and the issue of drawing 8 � Introduction blood in order to maximize participation. It was stressed that the blood sample was not for HIV-AIDS testing. Seven groups of two officials were deployed to the districts. Before their arrivals, the Ministry of Health sent an advance letter requesting all District Directors of Health Services to identify the community mobilization coordinators for the respective districts. Together with the district coordinators and reporters from local media houses, the teams went to the sub-counties in which the enumeration areas (EAs) were located. At the sub-county, local officials were engaged to conduct community mobilization in the enumeration areas. The teams sent from the national level also visited a number of enumeration areas together with the local community mobilizers. In each EA, community mobilization was done one week before the data collection teams arrived. In Kampala city, additional sensitization was done through the use of Ministry of Health film vans that moved around the enumeration areas spreading out the message and providing a number of advocacy materials. 1.5.6 Fieldwork Fifteen data collection teams consisting of three female interviewers, one male interviewer, a supervisor, a field editor, a health technician, and a driver began fieldwork on May 5, 2006. Fieldwork was completed in the first week of October 2006. Fieldwork supervision was coordinated from UBOS headquarters; four regional coordinators routinely visited teams to review their work and monitor data quality. Additionally, the UBOS headquarters and the teams maintained close contact through field visits by senior staff and Macro International staff. Regular communication was also maintained through cell phones. Teams implemented community mobilization in the sampled clusters to raise awareness of the nature and purpose of the study. Fieldwork was carried out in five 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. A regular schedule was established in order to retrieve questionnaires and blood samples from the field. Dried blood spot samples for VAD were dried overnight in light-proof boxes and then stored in portable refrigerators run on the vehicle batteries in order to prevent degradation of retinol binding protein (RBP) in the samples. Blood samples were brought in from the field and transported to the laboratory at the Biochemistry Department at Makerere University, where they were stored in a -20 C freezer until they were tested. 1.5.7 Data Processing The processing of the 2006 UDHS data began soon after the start of fieldwork. Completed questionnaires were returned periodically from the field to the UBOS data processing center, first in Entebbe and later in Kampala, where they were entered and edited by 15 data processing personnel who were specially trained for this task. The data processing personnel included a supervisor, a questionnaire administrator (who kept track of the questionnaires received from each cluster), an office editor, data entry operators, and a secondary editor. The concurrent processing of the data was an advantage since field check tables monitored various data quality parameters. As a result, the teams got specific feedback to improve performance. The data entry and editing phase of the survey was completed in mid-October 2006. Introduction � 9 1.6 RESPONSE RATES Table 1.2 shows household and individual response rates for the 2006 UDHS. A total of 9,864 households were selected for the sample, of which 9,099 were found to be occupied during data collection. Of these existing households, 8,870 were successfully interviewed, giving a household response rate of 98 percent. In these households, 9,006 women were identified as eligible for the indi- vidual interview. Interviews were com- pleted with 8,531 women, yielding a response rate of 95 percent. Of the 2,760 eligible men identified in the selected sub- sample of households, 91 percent were successfully interviewed. Response rates were higher in rural than urban areas, with the rural-urban difference in response rates most marked among eligible men. Table 1.2 Results of the household and individual interviews Number of households, number of interviews, and response rates, according to residence, Uganda 2006 Residence Result Urban Rural Total Household interviews Households selected 1,637 8,227 9,864 Households occupied 1,496 7,603 9,099 Households interviewed 1,390 7,480 8,870 Household response rate1 92.9 98.4 97.5 Interviews with women age 15-49 Number of eligible women 1,577 7,429 9,006 Number of eligible women interviewed 1,450 7,081 8,531 Eligible women response rate2 91.9 95.3 94.7 Interviews with men age 15-54 Number of eligible men 479 2,281 2,760 Number of eligible men interviewed 391 2,112 2,503 Eligible men response rate2 81.6 92.6 90.7 1 Households interviewed/households occupied 2 Respondents interviewed/eligible respondents Characteristics of Households and Household Members | 11 CHARACTERISTICS OF HOUSEHOLDS AND HOUSEHOLD MEMBERS 2 This chapter presents information on some of the socioeconomic characteristics of the household1 population and the individual survey respondents, such as age, sex, household composition, disability, and urban-rural residence. This chapter also considers the conditions of the households in which the survey population lives, including source of drinking water, availability of electricity, sanitation facilities, building materials, possession of household durable goods, and disability status of household members. 2.1 HOUSEHOLD POPULATION BY AGE AND SEX The 2006 UDHS included a Household Questionnaire, which was used to elicit information on the socioeconomic characteristics of usual residents and visitors who had spent the previous night in the selected households. Table 2.1 shows the reported distribution of the household population in five-year age groups, by sex and urban-rural residence. The data show that there are slightly more women (22,572) than men (20,949), with women constituting 52 percent of the population and men constituting 48 percent. The sex composition of the population does not show significant variation by urban-rural residence. The table further depicts Uganda as a young population, with a large proportion of the population being in the younger age groups. The population under age 15 constitutes 52 percent of the total population. The older age groups are very small in comparison, as can be seen in the population pyramid. In general, the population pyramid in Figure 2.1 reflects a broad base pattern, characteristic Table 2.1 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 2006 Urban Rural Total Age Male Female Total Male Female Total Male Female Total <5 17.4 15.0 16.1 20.0 19.3 19.6 19.7 18.7 19.2 5-9 13.0 13.5 13.3 18.5 17.3 17.9 17.8 16.8 17.3 10-14 12.1 13.3 12.7 17.0 15.7 16.3 16.4 15.4 15.9 15-19 11.2 12.5 11.9 9.7 8.9 9.3 9.9 9.3 9.6 20-24 12.5 12.9 12.7 6.1 7.4 6.8 6.9 8.2 7.6 25-29 9.1 10.2 9.7 5.5 6.5 6.0 5.9 6.9 6.5 30-34 7.9 6.2 7.0 5.0 5.2 5.1 5.3 5.3 5.3 35-39 6.2 4.7 5.4 4.5 4.4 4.4 4.7 4.4 4.6 40-44 3.6 3.0 3.3 3.1 3.3 3.2 3.1 3.2 3.2 45-49 2.0 2.3 2.1 2.7 2.7 2.7 2.6 2.6 2.6 50-54 1.5 1.7 1.6 1.8 2.6 2.2 1.8 2.5 2.1 55-59 1.1 1.3 1.2 1.5 1.7 1.6 1.4 1.6 1.5 60-64 0.9 1.1 1.0 1.3 1.8 1.6 1.2 1.7 1.5 65-69 0.6 0.9 0.7 1.2 1.0 1.1 1.1 1.0 1.0 70-74 0.4 0.5 0.4 1.0 1.0 1.0 0.9 1.0 0.9 75-79 0.2 0.5 0.4 0.6 0.6 0.6 0.5 0.6 0.6 80 + 0.2 0.5 0.3 0.7 0.7 0.7 0.6 0.7 0.6 Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 Number of respondents 2,682 2,956 5,639 18,267 19,616 37,883 20,949 22,572 43,521 1 A household was defined as a person or group of persons that usually lives and eats together. 12 | Characteristics of Households and Household Members of Uganda and half of its population being young. This type of age structure has a built-in momentum for the growth of the country’s population. When the young population eventually reaches reproductive age, the result will be a high population growth rate for some years to come. 2.2 HOUSEHOLD COMPOSITION Table 2.2 presents the headship and composition of households in Uganda. Only three in ten households are headed by women while seven in ten households are headed by men. The proportion of female-headed households is higher in urban areas than in rural areas (33 percent and 29 percent, respectively). One in every ten households has only one member. One-member households are more likely to be found in urban areas (20 percent) than in rural areas (9 percent). The proportion of households with nine or more members remained unchanged since the 2000-2001 UDHS at 10 percent. Rural areas have consistently higher percentages of larger households (five persons or more) than urban areas. In urban areas, 34 percent of the households have one or two members, compared with 19 percent in rural areas. Table 2.2 shows that the mean household size is 5.0 persons. This is slightly higher than the figure of 4.8 obtained from both the 2002 Population and Housing Census (UBOS, 2006a) and the 2000-2001 UDHS. The mean household size is larger in rural areas (5.1 persons) than in urban areas (4.1 persons). 2.3 FOSTERHOOD AND ORPHANHOOD In Uganda, a person less than 18 years old is defined as a child. Information on fosterhood and orphanhood of children is presented in Table 2.2. Three in ten households included one or more children who stayed with neither their natural father nor their natural mother. There was a higher percentage of households with foster children in rural areas than in urban areas. Households with orphans constitute one-quarter of all households in Uganda. There are more households with single orphans (18 percent) than with double orphans (6 percent). There are no major variations between rural and urban regarding households with orphans. Figure 2.1 Population Pyramid 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 0-4 0246810 0 2 4 6 8 10 UDHS 2006 Age Male Percentage Female Characteristics of Households and Household Members | 13 Table 2.2 Household composition Percent distribution of households by sex of head of household and by household size, mean size of household, and percentage of households with orphans and foster children under 18, according to residence, Uganda 2006 Residence Characteristic Urban Rural Total Household headship Male 66.9 70.7 70.1 Female 33.1 29.3 29.9 Total 100.0 100.0 100.0 Number of usual members 1 19.7 9.2 10.8 2 14.4 9.3 10.1 3 14.7 12.0 12.4 4 13.9 13.6 13.6 5 11.3 13.7 13.3 6 8.3 13.3 12.6 7 6.9 10.3 9.8 8 3.9 7.6 7.0 9+ 6.9 11.0 10.3 Total 100.0 100.0 100.0 Mean size of households 4.1 5.1 5.0 Percentage of households with orphans1 and foster children2 under 18 Foster children 26.9 30.9 30.3 Double orphans 4.8 6.1 5.9 Single orphans 15.5 17.8 17.5 No orphans 60.8 77.1 74.6 Number of households 1,389 7,481 8,870 Note: Table is based on de jure members, i.e., usual residents. 1 An orphan is a child under age 18 who has lost either one or both parents. 2 Foster children are those under age 18 living in households with neither their mother nor their father present. 2.4 HOUSING CHARACTERISTICS Increased access to safe drinking water results in improved health outcomes in the form of reduced cases of water-borne diseases like dysentery and cholera. Through the Poverty Eradication Action Plan (PEAP), which is the national planning framework, the government hopes to achieve universal access by all households to improved water sources by 2015. Information was collected in the 2006 UDHS about certain characteristics of household drinking water, including source of drinking water, time taken to collect water, persons who usually collect the water, water treatment prior to drinking, and type of sanitation facility. Table 2.3 shows that 67 percent of the households use improved water sources2. This figure is comparable to the percentage measured by the 2005-2006 UNHS (UBOS, 2006c). In urban areas, close to 9 in every 10 households have access to an improved water source. Tube wells or boreholes are still a major source of drinking water (31 percent), while protected wells and springs are the second most important source (20 percent). These two sources combined are used by just over half (51 percent) of households. Only 15 percent of households have access to piped water, mainly from a public tap. The percentage of households with access to piped water is much higher in the urban areas (60 percent) than the rural areas (7 percent). 2 Improved water sources include piped water, public tap, tube well or borehole, protected dug well, or spring and rainwater. It should be noted that the definition of improved water sources used in Uganda differs from the international definition used here in that it excludes rainwater. 14 | Characteristics of Households and Household Members Table 2.3 Household drinking water Percent distribution of households and de jure population by source of drinking water and by time to collect water, and percentage of households and population by person who usually collects drinking water and by methods of treating water, according to residence, Uganda 2006 Households Population Characteristic Urban Rural Total Urban Rural Total Source of drinking water Improved source 87.8 62.7 66.6 89.3 63.8 67.1 Piped water into dwelling/ yard/plot 20.2 0.9 3.9 20.7 0.7 3.3 Public tap/standpipe 39.3 6.3 11.4 35.8 6.0 9.8 Tube well or borehole 12.6 34.7 31.2 17.0 36.2 33.7 Protected dug well/spring 15.3 20.2 19.5 15.3 20.3 19.7 Rainwater 0.5 0.6 0.6 0.5 0.6 0.6 Non-improved source 9.7 36.1 32.0 9.7 35.2 32.0 Unprotected dug well/spring 4.6 22.3 19.6 4.8 22.3 20.1 Tanker truck/cart with small tank 1.2 0.3 0.4 0.6 0.2 0.2 Surface water 3.9 13.5 12.0 4.4 12.7 11.7 Bottled water, improved source for cooking/washing1 1.6 0.0 0.3 0.5 0.0 0.1 Bottled water, non-improved source for cooking/washing1 0.0 0.0 0.0 0.0 0.0 0.0 Other 0.9 1.2 1.1 0.4 1.0 0.9 Total 100.0 100.0 100.0 100.0 100.0 100.0 Percentage using any improved source of drinking water 89.4 62.7 66.9 89.9 63.8 67.2 Time to obtain drinking water (round trip) Water on premises 24.0 2.2 5.6 24.3 2.0 4.9 Less than 30 minutes 45.9 29.5 32.1 43.0 28.4 30.3 30 minutes or longer 29.2 67.3 61.3 32.1 68.9 64.2 Don't know/missing 0.9 1.0 1.0 0.6 0.6 0.6 Total 100.0 100.0 100.0 100.0 100.0 100.0 Persons who usually collect drinking water2 Adult male 15+ 24.6 29.0 28.3 22.0 27.3 26.6 Adult female 15+ 46.1 67.6 64.2 51.4 72.3 69.6 Male child under age 15 13.0 25.3 23.4 18.7 31.1 29.5 Female child under age 15 16.0 32.1 29.5 23.7 40.8 38.6 Not a household member 6.4 4.2 4.5 3.8 2.0 2.2 Water on premises 24.0 2.2 5.6 24.3 2.0 4.9 Water treatment prior to drinking2 Boiled 68.6 34.4 39.7 67.8 32.5 37.1 Bleach/chlorine 1.3 0.7 0.8 1.6 0.7 0.8 Strained through cloth 1.6 1.6 1.6 2.1 1.6 1.6 Ceramic, sand, or other filter 1.0 0.4 0.5 1.4 0.5 0.6 Other 3.2 1.9 2.1 3.2 2.0 2.1 No treatment 29.3 63.4 58.1 29.9 65.2 60.7 Percentage using an appropriate treatment method3 70.2 36.2 41.5 69.9 34.4 38.9 Number 1,389 7,481 8,870 5,644 38,392 44,035 1 Because the quality of bottled water is not known, households using bottled water for drinking are classified as using an improved or non-improved source according to their water source for cooking and washing. 2 Respondents may report multiple categories so the sum may exceed 100 percent. 3 Appropriate water treatment methods include boiling, bleaching, straining, filtering, and solar disinfecting. Characteristics of Households and Household Members | 15 Regarding time taken to draw water, findings show major urban-rural differences. In urban areas, 70 percent of the households take less than 30 minutes to obtain drinking water, compared with only 32 percent of rural households. The majority of rural households still take more than 30 minutes to make a round trip to and from the drinking water source. Findings show that most of the burden of fetching drinking water rests on women over age 15. Women usually collect water in almost two- thirds of households (64 percent). Girls under age 15 are the group next most likely to fetch water (30 percent of households), followed by men (28 percent of households) and boys under age 15 (23 percent of households). It should be noted that households could report more than one person who usually collects water. In urban areas, men usually collect water in a higher percentage of households than girls under age 15 (25 percent compared with 16 percent). Water from an improved source can be contaminated at collection, during transportation, and during storage. Information was collected on whether or not water is treated prior to drinking. The majority of households (58 percent) perform no treatment on their drinking water. The most commonly reported method of treatment is boiling. Four in every ten households boiled water prior to drinking. The practice is more common in urban households (69 percent) than in rural households (34 percent). Poor sanitation coupled with unsafe water sources increases the risk of water-borne diseases and illnesses due to poor hygiene. This has contributed immensely to the disease burden in Uganda. Households without proper toilet facilities are more exposed to the risk of diseases like dysentery, diarrhoea, and typhoid fever than those with improved sanitation facilities. Table 2.4 shows that about nine in ten households use non-improved toilet/latrine facilities. Households with improved toilet facilities (flush toilet, Ventilated Improved Pit (VIP) latrines, composting toilet and pit latrine with a slab) account for only 15 percent in urban and 8 percent in rural areas. Overall, 12 percent of the households in Uganda have no toilet facilities of any kind. This problem is more common in rural areas, where about 14 percent of the households have no toilet facilities, than in urban areas, where only 3 percent of the households have no facilities. Table 2.4 Household sanitation facilities Percent distribution of households and de jure population by type of toilet/latrine facilities, according to residence, Uganda 2006 Households Population Type of toilet/ latrine facility Urban Rural Total Urban Rural Total Improved, not shared facility Flush toilet 4.7 0.1 0.8 6.0 0.1 0.9 Ventilated improved pit (VIP) latrine 2.4 0.7 1.0 3.6 0.8 1.2 Pit latrine with slab 7.5 7.0 7.1 11.5 8.1 8.5 Composting toilet 0.0 0.2 0.2 0.0 0.2 0.1 Non-improved facility Any facility shared with other households 75.8 37.3 43.3 67.1 32.6 37.0 Pit latrine without slab/open pit 6.5 40.8 35.4 9.1 44.9 40.3 No facility/bush/field 2.6 13.6 11.9 2.5 13.1 11.8 Other/missing 0.6 0.4 0.4 0.3 0.2 0.2 Total 100.0 100.0 100.0 100.0 100.0 100.0 Number 1,389 7,481 8,870 5,644 38,392 44,035 16 | Characteristics of Households and Household Members Table 2.5 provides information that relates to other characteristics of dwellings, such as whether or not the household has electricity, the main construction materials used for the floor, the number of rooms used for sleeping, and information on type of power/fuel used for cooking and location of cooking. Only 9 percent of households in Uganda have access to electricity. The result is similar to what was found in the 2002 Population and Housing Census. Access to electricity is much higher in urban areas (42 percent) than in rural areas (3 percent). Indeed, findings show that electricity is still a preserve of the urban residents. The type of material used for the floor may be viewed as an indicator of the quality of housing (a wealth dimension) as well as an indicator of health risk. Some floor materials like earth, sand, and cow dung pose a health problem since they can act as breeding grounds for pests and may be a source of dust. They are also more difficult to keep clean. Overall, almost eight out of every ten households (77 percent) have floors made of earth, sand, or cow dung. In general, rural households have poorer quality floors than urban households. Eighty-six percent of rural households have earth or dung floors, compared with only 27 percent of the urban households. On the other hand, there is a larger percentage of urban households with cement, tiles, stones or brick floors (73 percent) compared with rural households (14 percent). Households with floors made from tiles or stones constitute less than 1 percent. Overall, the proportion of households with cement floors is 22 percent, which is higher than that measured in the 2002 population census. The number of rooms used for sleeping gives an indication of the extent of crowding in households. Crowding in one sleeping room increases the risks of infection by diseases. In Uganda, a room for sleeping with more than two persons is considered to be over crowded. Overall, close to half (47 percent) of the households use only one room for sleeping. There is a higher percentage of households in urban areas sleeping in one room than in rural areas (63 percent and 44 percent, respectively). Households in rural areas are more likely to use two or more rooms for sleeping than households in urban areas. Smoke from solid fuels for cooking such as charcoal, wood, and other biomass fuels is a major cause of respiratory infections. The type of fuel used for cooking, the location where food is cooked, and the type of stove used are all related to indoor air quality and the degree to which household members are exposed to risk of respiratory infections and other diseases. Eight in ten households cook in a separate building or outside. Rural households are more likely to cook in a separate building (65 percent) while urban households are more likely to cook outside (53 percent). Cooking fuel affects the air quality for household members. Clean fuel is not affordable in most cases and most households resort to using solid fuels that emit a lot of smoke. As a result, household members are likely to be exposed to air pollution. Reducing the proportion of the population relying on solid fuels is a Millennium Development Goal. In Uganda, this proportion is 99 percent. Findings in Table 2.5 show that wood fuels (wood or charcoal) serve as the fuel used for cooking in 96 percent of all households in Uganda. Use of wood fuels in rural areas is almost universal with 98 percent of the households using it, while in urban areas, 85 percent of the households use this type of fuel. Furthermore, the continued use of wood fuels contributes to deforestation and poses one of the greatest challenges to the environment. Energy-saving fire stoves have been promoted as a way of reducing firewood consumption and deforestation in general. Chimneys help to reduce the exposure of household members to the smoke from cooking fires. Results show that 94 percent of households use open fires/stoves without chimneys for cooking that waste energy and expose household members to harmful smoke. Characteristics of Households and Household Members | 17 Table 2.5 Household characteristics Percent distribution of households and de jure population by housing characteristics, according to residence, Uganda 2006 Households Population Housing characteristic Urban Rural Total Urban Rural Total Electricity Yes 41.8 2.9 9.0 40.5 2.7 7.5 No 58.0 96.9 90.8 59.5 97.0 92.2 Missing 0.2 0.2 0.2 0.1 0.2 0.2 Total 100.0 100.0 100.0 100.0 100.0 100.0 Flooring material Earth, sand 16.8 43.9 39.6 17.0 42.3 39.1 Earth and dung 10.4 41.9 37.0 10.9 43.8 39.6 Mosaic or tiles 1.8 0.0 0.3 2.4 0.1 0.4 Bricks 0.3 0.3 0.3 0.4 0.3 0.3 Cement 69.7 13.6 22.4 68.1 13.3 20.3 Stones 0.7 0.2 0.3 1.0 0.2 0.3 Other/missing 0.2 0.1 0.1 0.2 0.1 0.1 Total 100.0 100.0 100.0 100.0 100.0 100.0 Rooms used for sleeping One 62.6 44.3 47.1 46.4 32.7 34.4 Two 20.0 30.9 29.2 25.0 33.6 32.5 Three or more 15.8 24.3 22.9 27.4 33.2 32.5 Missing 1.5 0.6 0.7 1.2 0.6 0.6 Total 100.0 100.0 100.0 100.0 100.0 100.0 Place for cooking In the house 16.3 13.3 13.8 15.5 11.4 11.9 In a separate building 21.9 64.8 58.1 30.3 70.8 65.6 Outdoors 53.1 20.0 25.2 51.1 17.2 21.5 Missing 8.8 1.9 2.9 3.2 0.6 0.9 Total 100.0 100.0 100.0 100.0 100.0 100.0 Cooking fuel Electricity 0.2 0.0 0.0 0.1 0.0 0.0 LPG/natural gas/biogas 1.0 0.0 0.2 0.8 0.0 0.1 Kerosene/paraffin 5.0 0.5 1.2 1.7 0.1 0.3 Charcoal 63.6 6.9 15.7 66.0 5.2 13.0 Wood 21.5 90.6 79.8 28.1 93.9 85.5 Straw/shrubs/grass 0.1 0.3 0.3 0.2 0.4 0.3 No food cooked in household 8.7 1.7 2.8 3.0 0.4 0.8 Total 100.0 100.0 100.0 100.0 100.0 100.0 Percentage using solid fuel1 for cooking 85.1 97.8 95.8 94.3 99.4 98.8 Number of households 1,389 7,481 8,870 5,644 38,392 44,035 Type of fire/stove among households using solid fuel1 Open fire/stove with chimney 6.0 5.3 5.4 5.8 5.3 5.3 Open fire/stove without chimney 92.5 93.8 93.7 93.0 93.9 93.8 Missing 1.5 0.8 0.9 1.2 0.9 0.9 Total 100.0 100.0 100.0 100.0 100.0 100.0 Number of households/population using solid fuel 1,183 7,314 8,497 5,324 38,180 43,504 LPG = Liquid petroleum gas 1 Includes coal/lignite, charcoal, wood/straw/shrubs, agricultural crops, and animal dung 18 | Characteristics of Households and Household Members 2.5 HOUSEHOLD ASSETS The 2006 UDHS also collected information on the household’s ownership of selected assets that are in themselves believed to have a strong association with poverty levels. Some of these can be used to measure household welfare when combined with other indicators to generate a wealth index. Information was collected on household ownership of radio and television as a measure of access to mass media; telephone ownership (both mobile and non-mobile telephones) as an indicator of access to an efficient means of communication; refrigerator ownership as an indication of the capacity for hygienic storage of foods; and ownership of a means of transportation (bicycle, motorcycle, boat with or without a motor, or private car or truck) as a sign of the household’s level of access to public services and markets as well as exposure to developments in other areas. In addition, ownership of agricultural land shows the household access to means of production. Ownership of farm animals such as local cattle, exotic/cross cattle, horses/donkeys/mules, goats, sheep, pigs, or chickens indicates the level of assets households possess that could be used to meet household demands. Table 2.6 shows that 61 percent of the households in Uganda own a radio; urban households are more likely than rural households to own a radio (75 percent compared with 58 percent). Ownership of television sets has not increased since 2000-2001 UDHS with only 6 percent of households owning a television set. Sixteen percent of households own a mobile telephone while less than 1 percent own a non-mobile telephone. Regarding transport, 38 percent of households own bicycles. There are twice as many rural households with bicycles than urban households, while 7 percent of urban households own cars or trucks compared with less than 1 percent of rural households. About 3 percent of the households own a motorcycle. Goats and pigs were the most commonly owned types of livestock, each owned by 8 percent of households. Seven percent of households owned chickens, and 6 percent of households owned local cattle. As expected, rural households are more likely to own each type of livestock than urban households. Table 2.6 Household assets Percentage of households and de jure population possessing various household effects, means of trans- portation, agricultural land, and livestock/farm animals by residence, Uganda 2006 Households Population Possession Urban Rural Total Urban Rural Total Household effects Radio 74.8 58.2 60.8 77.4 60.9 63.0 Television 25.5 2.6 6.2 28.9 2.9 6.2 Mobile telephone 52.8 9.6 16.4 53.8 10.6 16.2 Non-mobile telephone 3.1 0.2 0.7 3.6 0.2 0.6 Refrigerator 13.7 1.2 3.2 16.5 1.4 3.3 Means of transport Bicycle 20.0 40.8 37.5 26.1 46.7 44.0 Animal drawn cart 0.8 0.3 0.4 1.3 0.3 0.5 Motorcycle/scooter 4.3 2.4 2.7 5.2 2.9 3.2 Car/truck 6.6 0.8 1.7 9.5 1.0 2.1 Boat with a motor 0.1 0.2 0.2 0.1 0.2 0.2 Boat without a motor 0.4 0.8 0.7 0.6 0.6 0.6 Ownership of agricultural land 40.0 82.0 75.5 47.4 85.7 80.8 Ownership of farm animals Local cattle 1.8 7.3 6.4 2.0 8.3 7.5 Exotic/cross cattle 1.0 1.6 1.5 1.2 2.0 1.9 Horses/donkeys/mules 0.0 0.2 0.1 0.0 0.2 0.2 Goats 1.8 9.3 8.2 2.3 10.0 9.0 Sheep 0.8 3.3 2.9 1.2 3.8 3.4 Pigs 1.5 8.8 7.7 1.7 9.4 8.4 Chickens 2.2 7.3 6.5 2.9 7.2 6.7 Number of households 1,389 7,481 8,870 5,644 38,392 44,035 Characteristics of Households and Household Members | 19 2.6 WEALTH QUINTILES The UDHS did not collect information on household income or consumption. However, information on household assets is used to create an index representing the wealth of the households interviewed. The wealth index is a proxy for long-term standard of living of the household. Household assets used to calculate the wealth index include consumer items such as a refrigerator, television, and car; dwelling characteristics such as floor material; type of drinking water source; toilet facilities; and other characteristics that are related to wealth status. To construct the wealth index, each household asset for which information was collected is assigned a weight or factor score generated through principal components analysis. The resulting asset scores are standardized in relation to a standard normal distribution with a mean of zero and a standard deviation of one. Each household is assigned a standardized score for each asset, where the score differs depending on whether or not the household owned that asset (or, in the case of sleeping arrangements, the number of people per room). These scores are summed by household, and individuals are ranked according to the total score of the household in which they reside. The sample is then divided into population quintiles, i.e., five groups with the same number of individuals in each. The 20 percent of the population with the lowest total asset scores become the individuals in the lowest wealth quintile, the next 20 percent become the members of the second wealth quintile, and so forth. At the national level, approximately 20 percent of the household population is in each wealth quintile. In other words, the wealth index measures the standard of living of a household relative to other households in Uganda. The wealth quintile of a household does not indicate whether or not the household lives in poverty according to Uganda’s poverty definition. Rather, it indicates that an individual living in a household in the second wealth quintile has better socio-economic status than someone in the lowest wealth quintile and worse socio-economic status than someone in the middle wealth quintile. In defining the wealth quintiles, a single asset index is developed on the basis of data from the entire country sample and used in all the tabulations presented. Separate asset indices are not prepared for rural and urban population groups on the basis of rural or urban data, respectively. Wealth quintiles are expressed in terms of quintiles of individuals in the population, rather than quintiles of individuals at risk for any one health or population indicator. Thus, for example, the quintile rates for infant mortality refer to the infant mortality rates per 1,000 live births among all people in the population quintile concerned, as distinct from quintiles of live births or newly born infants, who constitute the only members of the population at risk of mortality during infancy. The assets index has been found to be highly comparable to both poverty rates and gross domestic product per capita for India, and against expenditure data from household surveys in Nepal, Pakistan and Indonesia (Filmer and Pritchett, 1998) and Guatemala (Rutstein, 1999). Table 2.7 shows the distribution of the de jure household population into five wealth levels (quintiles) based on the wealth index by residence. These distributions indicate the degree to which wealth is evenly (or unevenly) distributed by geographic areas. The findings indicate that wealth is concentrated in urban areas. Among the population in urban areas, 73 percent is in the highest wealth quintile, compared with only 12 percent of the household population in rural areas. 20 | Characteristics of Households and Household Members Table 2.7 Wealth quintiles Percent distribution of the de jure population by wealth quintiles, according to residence and region, Uganda 2006 Wealth quintile Residence/region Lowest Second Middle Fourth Highest Total Number of population Residence Urban 2.9 4.7 4.8 14.9 72.7 100.0 5,644 Rural 22.5 22.2 22.2 20.7 12.3 100.0 38,392 Region Central 1 5.5 10.1 19.0 27.5 38.0 100.0 4,608 Central 2 4.6 14.6 19.8 29.7 31.4 100.0 4,225 Kampala 0.0 0.0 0.2 6.6 93.2 100.0 2,499 East Central 11.4 18.5 21.0 29.3 19.8 100.0 4,419 Eastern 28.7 28.2 21.0 15.2 6.9 100.0 6,441 North 58.2 24.6 6.9 5.8 4.5 100.0 7,230 West Nile 23.0 40.3 14.2 11.7 10.7 100.0 2,388 Western 12.3 20.5 30.2 27.0 10.0 100.0 6,730 Southwest 7.8 17.7 35.4 24.2 15.0 100.0 5,496 North Sub-regions IDP 69.2 22.0 5.3 2.2 1.3 100.0 3,153 Karamoja 76.0 7.3 3.4 8.8 4.5 100.0 1,602 Total 20.0 20.0 20.0 20.0 20.0 100.0 44,035 Differentials in welfare levels are manifested between regions. More than nine out of every ten persons in Kampala city are in the highest wealth quintile, indicating that they are better off compared to all other regions. In Central 1 and Central 2, more than 30 percent of the household population falls into the highest two wealth quintiles. The North region is the least well off, with 58 percent of the household population falling in the lowest wealth quintile. People living in IDP camps in the North and in Karamoja are found to be the most disadvantaged, with over 69 percent of the population in the IDP camps and 76 percent of the household population Karamoja in the lowest wealth quintile. These results further confirm other findings that poverty is more concentrated in the North than in any other region. 2.7 BIRTH REGISTRATION It is a human right for a child to know who its parents are and to have a nationality through registration. The registration system in Uganda is still undergoing revival and significant progress has been made to extend coverage to all districts. The revival process is supported by UNICEF, the Ministry of Justice and Constitutional Affairs, Plan International, and UBOS, among others. To date, registration of births is being undertaken in more than 36 districts countrywide. 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 provision of access to immunisation. Birth registration in a well established and functioning system ensures that the country has an up-to-date and reliable database for planning. This is as useful for national-level planning as it is for local government bodies that are responsible for maintaining education, health, and other social services for the community. Characteristics of Households and Household Members | 21 Table 2.8 shows that only one in every five children is registered in Uganda. There is a slightly higher proportion of children registered in urban areas than in rural areas (24 percent compared with 21 percent). There was a higher proportion of births registered in East Central (37 percent), Western (28 percent), and West Nile (27 percent) regions than in other regions. Registration of births in the IDP camps is rather high (29 percent), indicating the extent of targeting that was undertaken in the conflict areas of Gulu, Kitgum, and Pader. Birth registration is highest among births in the highest wealth quintile (26 percent), followed by births in the second wealth quintile (23 percent). Birth registration is lowest in the lowest wealth quintile (17 percent). Table 2.8 Birth registration of children under age five Percentage of de jure children under five years of age whose births are registered with the civil authorities, according to background characteristics, Uganda 2006 Percentage of children whose births are registered Background characteristic Has a birth certificate, seen Has a birth certificate, not seen Did not have a birth certificate Total registered Number of children Age <2 3.3 4.9 10.1 18.3 3,293 2-4 5.0 6.9 10.8 22.7 5,106 Sex Male 4.7 6.4 10.2 21.4 4,151 Female 4.0 5.8 10.9 20.7 4,247 Residence Urban 3.3 14.3 6.0 23.6 917 Rural 4.5 5.1 11.1 20.7 7,482 Region Central 1 1.5 4.7 3.9 10.1 811 Central 2 1.6 6.4 7.5 15.4 762 Kampala 1.8 13.4 3.5 18.7 378 East Central 9.3 10.7 17.3 37.2 890 Eastern 6.0 2.8 7.5 16.2 1,288 North 5.0 6.3 11.7 23.0 1,474 West Nile 7.7 5.5 13.9 27.1 442 Western 2.2 6.4 19.6 28.2 1,310 Southwest 3.7 4.3 4.1 12.1 1,042 North Sub-regions IDP 3.7 10.0 15.1 28.8 658 Karamoja 0.8 1.7 2.7 5.2 326 Wealth quintile Lowest 4.0 3.8 9.6 17.4 1,926 Second 5.5 3.8 13.9 23.2 1,839 Middle 4.6 4.3 9.9 18.7 1,678 Fourth 3.8 6.9 10.6 21.3 1,603 Highest 3.7 14.1 8.1 25.8 1,353 Total 4.4 6.1 10.5 21.0 8,398 2.8 DISABILITY Because of their status, persons with disabilities (PWDs) are vulnerable and suffer from social exclusion, stigma, and discrimination. The Government of Uganda has developed a National Disa- bility Policy to ensure a conducive environment for participation of PWDs and to promote effective, friendly service delivery to PWDs and their caregivers. Information was collected on each household member aged five years and over about whether he/she had difficulties with seeing, hearing, walking or climbing stairs, in remembering or concentrating, in self-care, and in communicating. 22 | Characteristics of Households and Household Members The set of six questions included in the UDHS was based on a tool that was being developed by the UN Washington Group on Disability Statistics (WG). The WG is one of several City Groups formed under the auspices of the United Nations Statistical Commission, and it is mandated to develop tools to measure disability in censuses and sample surveys. The WG’s questions focus on a person’s functional abilities rather than physical characteristics. For example, the question on vision was phrased as follows: “Does (NAME) have difficulty seeing, even if wearing glasses?” The responses were classified into one the following categories: no, no difficulty; yes, some difficulty; yes, a lot of difficulty; cannot do at all; and don’t know. Table 2.9 shows that the overall disability rate is 20 percent for persons age five years and above. The disability rate is much higher than the 3.5 percent rate from the 2002 Population and Housing Census and the 7 percent rate from the 2005-2006 Uganda National Household Survey (UBOS, 2006c)3. This is largely because of improvements and changes made in the phrasing of the disability questions. Hence, caution should be used in making comparisons. The results also show that 16 percent of the household population age five years and older were reported to have “some difficulty” in at least one of the six functional domains, while 4 percent have “a lot of difficulty” and less than 1 percent were reported as not able to perform at all at least one of the six functions asked about. The proportion of individuals defined as disabled using this set of questions increases rapidly after the age of 40. The percentage of individuals considered disabled rises from 35 percent among household members in their forties, to 50 percent among household members in their fifties and 76 percent among household members aged 60 years and over. Difficulties in seeing or walking and climbing steps were more prevalent than other types of disabilities (10 and 7 percent, respectively). Table 2.9 Disability by functional domain and age Percent distribution of de facto household population age five and over by degree of difficulty according to functional domain, and percent distribution of de facto household population age five and over by highest degree of difficulty in any functional domain, according to age, Uganda 2006 Degree of difficulty Functional area and age Can't do at all A lot of difficulty Some difficulty No difficulty Don't know/ missing Total Some difficulty, a lot of difficulty, or can't do at all Number of individuals Difficulty seeing 0.1 1.1 8.7 89.8 0.3 100.0 9.9 35,166 Difficulty hearing 0.1 0.7 4.8 94.1 0.3 100.0 5.6 35,166 Difficulty walking or climbing stairs 0.1 1.5 5.5 92.5 0.3 100.0 7.2 35,166 Difficulty remembering or 0.1 1.0 5.3 93.3 0.3 100.0 6.4 35,166 Difficulty with self-care 0.1 0.5 1.7 97.4 0.3 100.0 2.3 35,166 Difficulty communicating 0.1 0.4 1.3 97.8 0.3 100.0 1.9 35,166 Difficulty in at least one functional area 5-9 0.3 2.3 8.5 87.9 1.0 100.0 11.1 7,519 10-14 0.3 2.1 10.2 87.3 0.2 100.0 12.5 6,912 15-19 0.5 2.1 9.8 87.4 0.2 100.0 12.4 4,185 20-29 0.3 1.9 9.8 87.9 0.1 100.0 12.0 6,095 30-39 0.2 2.2 15.6 81.6 0.3 100.0 18.1 4,311 40-49 0.2 3.6 31.1 64.9 0.3 100.0 34.9 2,515 50-59 0.5 8.5 40.8 50.1 0.2 100.0 49.8 1,600 60+ 2.9 22.5 51.0 23.4 0.3 100.0 76.3 2,026 Total age 10 and over 0.5 4.1 17.5 77.7 0.2 100.0 22.1 27,647 Total age 15 and over 0.6 4.7 20.0 74.5 0.2 100.0 25.3 20,735 Total 0.5 3.7 15.6 79.9 0.4 100.0 19.8 35,166 3 Figures for disability from the 2002 Population and Housing Census and the 2005-2006 Uganda National Household Survey are for all persons, not just those age five and above. Education | 23 EDUCATION 3 3.1 EDUCATIONAL LEVEL OF HOUSEHOLD POPULATION Education affects many aspects of life, including individual demographic and health behaviour. Studies have shown that educational level is strongly associated with contraceptive use, fertility, and the general health status, morbidity, and mortality of children. In each household, for all persons age five years or older, data were collected on the highest level of education attended and the highest grade completed at that level. Table 3.1 shows the distribution of female and male household members age six years and older by the highest level of education attained and the median number of years of education completed, according to background characteristics. As shown in Table 3.1, the vast majority of Ugandans have attended school, although many do not complete primary school. Among those who never attended school, more females than males never attended. Nearly one in four females (23 percent) age six years or older in Uganda has never been to school, compared with 12 percent of males. However, the gender gap in educational attainment has narrowed over time. Males age 20 and older are less likely to have no education and more likely to have attained some secondary education than females age 20 and older. In contrast, the proportion of individuals age 6-19 with no education and with at least some secondary education is similar for males and females. This trend towards equality in educational attainment is likely related to the Government of Uganda’s Universal Primary Education (UPE) programme. It is worth noting that despite the existence of the UPE programme, about three in ten girls and boys age 6-9 years have never attended school. Other studies in Uganda, including the 2005-2006 Uganda National Household Survey (UBOS, 2006c), show that this may be attributed to hindrances like long distances to the nearest school, other educational costs to be met by parents, such as school uniforms and scholastic materials, and parents who consider their children to be too young to start school. Overall, levels of educational attainment are higher in urban areas than in rural areas. The percentage with no education is lower and the percentage with secondary education is higher in urban areas than in rural areas. Similarly, the median number of years of schooling is higher in urban areas than in rural areas. Kampala has the highest proportion of males and females who have attained more than primary education, with 52 percent of males and 47 percent of females having attended secondary school, completed secondary school, or attended school beyond the secondary level. The North region has the highest percentages of males and females with no education (17 percent and 35 percent, respectively). Slightly more than one in four females (28 percent) in the IDP camps have no education while only about one in ten males (9 percent) have no education. The percentage of males with no education in IDPs is surprisingly lower than in all other regions except Kampala. In the Karamoja sub-region, two out of three females (67 percent) and more than half of the males (53 percent) have no education. There are only very small percentages of females with more than an incomplete primary education in both the IDP camps and Karamoja. The likelihood of never having attended school increases dramatically as wealth decreases. Among females, 38 percent of those from the poorest households have never attended school while just 8 percent of females from the wealthiest households have never attended. Differences by wealth are also large among males; 21 percent of males from the poorest households have no schooling compared with 6 percent from the wealthiest households. 24 | Education The likelihood of reaching the secondary level of schooling is much greater among the wealthiest Ugandans than those from poorer households. Forty-two percent of males from the wealthiest households have attended secondary school or higher compared with 6 to 18 percent of males from the remaining wealth quintiles. A similar pattern is observed for women, with 35 percent of females from the wealthiest households and just 2 to 10 percent of those from less wealthy households having attained at least some secondary education. Table 3.1 Educational attainment of household population Percent distribution of the de facto male and female household population age six and over by highest level of schooling attended or completed and median years completed, according to background characteristics, Uganda 2006 Background characteristic No education Some primary Com- pleted primary1 Some secondary Com- pleted secondary2 More than secondary Don't know/ missing Total Number Median years completed MALE Age 6-9 28.9 71.0 0.0 0.0 0.0 0.0 0.1 100.0 3,032 0.0 10-14 3.9 93.4 1.0 1.7 0.0 0.0 0.0 100.0 3,434 2.2 15-19 3.1 60.0 9.2 26.2 0.2 1.2 0.1 100.0 2,079 5.3 20-24 4.7 38.4 15.0 31.5 2.5 7.3 0.6 100.0 1,446 6.4 25-29 7.6 41.9 13.9 22.6 3.2 9.4 1.4 100.0 1,243 6.0 30-34 7.2 48.0 13.6 19.1 1.4 9.9 0.8 100.0 1,120 5.6 35-39 8.0 45.0 15.6 18.5 2.5 9.1 1.2 100.0 994 5.7 40-44 10.9 48.2 14.5 15.2 1.7 8.5 1.0 100.0 656 5.3 45-49 12.4 45.7 19.8 11.6 1.3 8.2 1.0 100.0 542 5.1 50-54 19.9 39.4 17.7 13.8 1.4 7.1 0.7 100.0 375 5.2 55-59 18.5 43.2 18.1 12.0 0.9 5.9 1.3 100.0 300 5.1 60-64 26.8 47.6 7.9 10.8 0.4 5.0 1.5 100.0 261 3.9 65+ 37.3 46.7 3.7 5.7 0.3 4.5 1.8 100.0 653 2.1 Residence Urban 5.9 41.1 8.9 26.5 3.1 12.8 1.7 100.0 2,150 6.2 Rural 13.2 64.7 7.9 10.6 0.6 2.6 0.4 100.0 13,986 3.0 Region Central 1 11.0 59.5 7.4 15.1 1.8 4.0 1.2 100.0 1,728 3.8 Central 2 12.2 61.0 7.2 16.3 0.6 2.4 0.4 100.0 1,646 3.4 Kampala 5.1 30.7 10.2 30.3 4.1 17.6 2.0 100.0 1,001 7.4 East Central 10.2 64.9 7.4 13.4 0.6 3.1 0.4 100.0 1,527 3.1 Eastern 10.2 67.8 7.4 10.3 0.6 3.6 0.1 100.0 2,280 3.1 North 17.1 62.2 7.9 8.9 0.3 3.0 0.5 100.0 2,512 2.9 West Nile 10.0 66.0 8.0 12.4 0.6 2.9 0.1 100.0 900 3.0 Western 13.0 65.4 7.2 10.9 1.1 2.0 0.4 100.0 2,559 3.0 Southwest 15.0 62.1 10.5 8.5 0.2 3.5 0.3 100.0 1,983 2.7 North Sub-regions IDP 8.9 70.9 8.8 8.3 0.1 2.6 0.4 100.0 1,119 3.4 Karamoja 52.7 36.5 2.1 5.1 0.2 2.5 0.9 100.0 519 0.0 Wealth quintile Lowest 20.8 66.1 6.7 5.0 0.1 0.8 0.3 100.0 2,958 1.9 Second 13.0 69.4 8.6 7.1 0.1 1.5 0.2 100.0 3,160 2.7 Middle 13.9 67.2 7.6 9.3 0.4 1.3 0.4 100.0 3,242 2.7 Fourth 8.8 63.9 9.1 13.8 0.8 3.2 0.4 100.0 3,306 3.7 Highest 6.1 43.1 8.0 26.5 3.0 12.0 1.3 100.0 3,471 6.0 Total 12.3 61.6 8.0 12.7 0.9 4.0 0.5 100.0 16,136 3.3 Continued… Education | 25 Table 3.1—Continued Background characteristic No education Some primary Com- pleted primary1 Some secondary Com- pleted secondary2 More than secondary Don’t know/ missing Total Number Median years completed FEMALE Age 6-9 30.0 69.8 0.0 0.0 0.0 0.0 0.2 100.0 3,063 0.0 10-14 4.1 92.6 1.2 2.0 0.0 0.0 0.0 100.0 3,479 2.4 15-19 4.2 57.6 9.9 26.5 0.6 0.9 0.2 100.0 2,106 5.3 20-24 11.4 45.6 12.8 21.3 1.9 6.0 1.0 100.0 1,840 5.3 25-29 18.6 47.9 11.4 14.3 0.8 6.3 0.8 100.0 1,567 4.1 30-34 22.3 51.3 10.1 11.7 0.6 3.6 0.5 100.0 1,204 3.7 35-39 31.3 46.9 9.4 8.2 0.2 3.5 0.5 100.0 993 2.7 40-44 37.5 41.6 10.2 7.7 0.3 2.7 0.1 100.0 728 1.8 45-49 43.8 37.3 8.3 6.7 0.1 3.5 0.4 100.0 589 1.1 50-54 51.3 34.3 5.2 4.5 0.1 3.8 0.9 100.0 555 0.0 55-59 57.7 32.2 2.1 4.0 0.0 3.3 0.7 100.0 370 0.0 60-64 68.9 27.1 1.0 0.9 0.0 1.0 1.1 100.0 385 0.0 65+ 71.3 23.9 0.9 0.9 0.0 0.8 2.2 100.0 729 0.0 Residence Urban 11.5 43.8 8.6 24.6 2.0 8.5 0.9 100.0 2,441 5.3 Rural 24.8 61.2 5.5 6.7 0.2 1.2 0.4 100.0 15,174 1.8 Region Central 1 15.8 58.2 6.4 15.1 0.5 3.3 0.8 100.0 1,888 3.5 Central 2 19.5 59.2 7.7 11.4 0.1 1.8 0.3 100.0 1,673 2.8 Kampala 6.7 35.0 10.4 30.7 3.3 12.5 1.3 100.0 1,098 6.7 East Central 20.0 60.3 6.1 11.0 0.2 1.8 0.7 100.0 1,809 2.4 Eastern 19.5 66.0 5.7 7.0 0.2 1.4 0.1 100.0 2,536 2.1 North 34.8 57.6 3.2 2.9 0.1 0.9 0.5 100.0 2,855 0.7 West Nile 26.2 64.7 3.1 4.7 0.4 0.7 0.1 100.0 975 1.3 Western 26.2 62.0 4.7 5.6 0.0 1.2 0.4 100.0 2,555 1.6 Southwest 26.1 56.7 8.5 6.8 0.4 1.2 0.3 100.0 2,227 2.0 North Sub-regions IDP 28.0 65.4 3.9 1.6 0.0 0.5 0.6 100.0 1,142 1.1 Karamoja 66.5 29.5 1.1 1.6 0.0 0.2 1.1 100.0 683 0.0 Wealth quintile Lowest 38.0 57.5 2.5 1.5 0.0 0.1 0.4 100.0 3,397 0.2 Second 28.1 62.9 4.8 3.4 0.0 0.4 0.3 100.0 3,392 1.4 Middle 25.3 63.4 5.4 4.9 0.1 0.4 0.4 100.0 3,520 1.7 Fourth 17.4 64.3 7.6 9.1 0.1 1.1 0.6 100.0 3,526 2.8 Highest 8.0 46.8 9.2 25.2 1.7 8.5 0.6 100.0 3,779 5.4 Total 23.0 58.8 6.0 9.1 0.4 2.2 0.5 100.0 17,615 2.2 Note: Totals include 1 male and 7 females with age missing. 1 Completed 7 grades at the primary level 2 Completed 6 grades at the secondary level 3.2 SCHOOL ATTENDANCE RATIOS 3.2.1 Primary School Attendance Ratios Uganda uses a 7-6-3 formal education system, namely seven years of primary, six years of secondary (with four years of ordinary secondary and two years of advanced secondary), and three years of university/tertiary. The official age ranges for these levels are 6-12 years, 13-18 years, and 19-24 years, respectively. The Net Attendance Ratio (NAR) for the primary level is the percentage of the primary- school-age population (age 6-12) that is attending primary school. Overall, the primary school NAR is 82 percent in Uganda (see Table 3.2). In urban areas, 88 percent of children age 6-12 attend primary school compared with 81 percent in rural areas. There is virtually no difference in the primary net attendance ratio by sex; the NAR is 81 percent for females versus 82 percent for males. 26 | Education Table 3.2 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 2006 Net attendance ratio1 Gross attendance ratio2 Background characteristic Male Female Total Male Female Total Gender Parity Index3 PRIMARY SCHOOL Residence Urban 89.8 86.5 88.0 124.6 116.6 120.2 0.94 Rural 81.6 80.6 81.1 119.5 114.3 116.9 0.96 Region Central 1 82.1 83.8 83.0 115.9 111.9 113.8 0.97 Central 2 83.6 84.1 83.8 120.8 113.2 117.0 0.94 Kampala 85.8 86.6 86.2 114.8 113.0 113.8 0.98 East Central 84.8 86.0 85.4 116.2 117.5 116.8 1.01 Eastern 86.5 88.2 87.4 128.6 123.5 126.0 0.96 North 76.5 72.0 74.2 111.1 98.8 104.8 0.89 West Nile 82.7 77.2 80.1 128.6 119.8 124.3 0.93 Western 80.8 79.4 80.1 121.2 119.5 120.4 0.99 Southwest 83.2 79.8 81.5 124.5 120.6 122.6 0.97 North Sub-regions IDP 85.6 82.1 83.9 126.2 108.2 117.4 0.86 Karamoja 44.5 42.1 43.3 61.7 57.9 59.7 0.94 Wealth quintile Lowest 73.3 71.3 72.3 106.8 97.4 102.1 0.91 Second 82.5 78.2 80.4 118.2 110.6 114.5 0.94 Middle 82.3 81.9 82.1 123.8 117.6 120.7 0.95 Fourth 86.1 86.5 86.3 126.3 125.4 125.8 0.99 Highest 88.7 88.9 88.8 126.3 121.9 124.0 0.97 Total 82.3 81.2 81.8 120.0 114.6 117.3 0.95 SECONDARY SCHOOL Residence Urban 35.8 34.8 35.3 57.4 42.9 49.4 0.75 Rural 13.5 13.1 13.3 20.0 15.7 17.9 0.79 Region Central 1 25.2 32.0 28.6 30.9 38.6 34.7 1.25 Central 2 25.3 20.3 23.2 30.0 23.7 27.3 0.79 Kampala 42.2 45.2 43.9 60.6 52.8 56.2 0.87 East Central 17.1 20.6 19.0 30.4 26.1 28.0 0.86 Eastern 12.6 11.8 12.2 20.9 13.9 17.5 0.66 North 5.9 4.0 5.0 13.7 5.8 9.8 0.42 West Nile 16.6 4.9 11.1 26.7 9.3 18.5 0.35 Western 8.7 8.1 8.4 18.3 10.3 14.3 0.56 Southwest 12.3 13.7 13.0 18.0 15.6 16.8 0.87 North Sub-regions IDP 5.1 0.9 3.2 9.8 1.3 6.0 0.13 Karamoja 0.0 2.1 1.2 5.7 2.6 4.0 0.46 Wealth quintile Lowest 3.2 2.5 2.9 6.9 3.1 5.0 0.45 Second 6.3 6.4 6.4 11.5 9.6 10.5 0.84 Middle 9.2 9.3 9.2 14.8 10.6 12.8 0.72 Fourth 16.4 13.3 14.9 24.3 15.7 20.1 0.65 Highest 38.2 38.5 38.4 55.1 46.5 50.6 0.84 Total 16.2 16.4 16.3 24.7 19.9 22.3 0.81 1 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. na = Not applicable Education | 27 There is some variation in the NAR by region. Eastern leads with a primary NAR of 87 percent. The North region has the lowest NAR, with 74 percent of children age 6-12 attending primary school. The situation in the IDP camps is similar to the rest of the regions, however the Karamoja sub-region reported an exceptionally low NAR of 43 percent (45 percent for boys and 42 percent for girls). In addition, the NAR is lowest among school-age children in the poorest households (72 percent) and increases with wealth to 89 percent among children in the wealthiest households. The Gross Attendance Ratio (GAR) measures attendance irrespective of the official age at each level. The GAR for primary school is the total number of primary school students (age 5-24), expressed as a percentage of the official primary-school-age population (age 6-12). A major contributing factor to high GAR is children starting primary school later than the recommended age of 6 years. In addition, although the UPE programme, introduced in 1997, was intended for all children age 6-15, many above age 15 enrolled in primary school as a result of the initiative. This is another factor that may contribute to overage participation at the primary level and, thus, a high GAR. Overall, the primary school GAR is 117, with the highest GAR in the North (105). Considering the North sub-regions, it is notable that the GAR in the Karamoja sub-region is only 60. As was the case with the NAR, the primary GAR rises by wealth quintile (from 102 to 124) and there are no notable differences by sex. The Gender Parity Index (GPI) is a measure of the ratio of females to males attending school, regardless of age. For primary school, the GPI is 0.95, indicating that the number of female and male students is almost the same, with males slightly outnumbering females. There is not much variation in the GPI for the primary school GAR by background characteristics; however, the ratio is lower than average in the IDP camps (0.86). 3.2.2 Secondary School Attendance Ratios The concept of the NAR at the secondary level is similar to that of the primary level, being the percentage of the secondary-school-age population (13-18 years) that is attending secondary school. Overall, only 16 out of 100 children of secondary school age in Uganda attend secondary school. The secondary NARs for males and females are also both 16 percent. The Government of Uganda introduced a programme of Universal Secondary Education (USE) in 2007 to increase secondary school enrolment. The secondary school net attendance ratio is better in urban areas than in rural areas (35 percent versus 13 percent). This pattern is the same for boys and girls. At the regional level, Kampala has the highest secondary NAR with 44 percent, followed by Central 1 (29 percent) and Central 2 (23 percent). The North and Western regions lag far behind with NARs of 5 percent and 8 percent, respectively. The secondary net attendance ratio is extremely low in the IDP camps (3 percent), with 5 percent of males and less than 1 percent of secondary-school-age females attending secondary school. In the Karamoja sub-region, just 1 percent of secondary-school-age youth attends secondary school. The secondary school NAR rises with wealth from about 3 percent in the lowest wealth quintile to 38 percent in the wealthiest quintile. This finding suggests that poverty and factors related to poverty play an important role in whether children are sent to secondary school. The secondary GAR is 22 for the nation as a whole and is substantially higher in urban than in rural parts of the country (49 versus 18). There are also regional differentials, with Kampala having the highest GAR (56) and the North region having the lowest GAR (10). The IDP camps and Karamoja sub-regions have exceptionally low secondary GARs (6 and 4, respectively). Similar to the NAR, the secondary GAR increases sharply as wealth increases: the GAR is 51 among youth in the wealthiest households and 5 among youth in the poorest households. 28 | Education The GPI for the secondary school GAR is 0.81, indicating that, among students of all ages, for every five male students in secondary school, there are approximately four female students. This ratio is lower than the GPI for the primary school GAR, and it varies by background characteristics. Male students outnumber female students by more than 2 to 1 in North region, and by 3 to 1 in West Nile. On the other hand, there are more female students than male students in secondary school in Central 1 region. The GPI for the secondary school GAR is especially low in the IDP camps, indicating an extreme gender gap in favour of males. 3.2.3 Age-specific Attendance Rates Figure 3.1 presents information on school attendance among youth age 5 to 24, by age. The figure includes students who attended primary school, secondary school, or higher education during the 2006 school year. Figure 3.1 Age-specific Attendance Rates of the De Facto Population Age 5-24 Years UDHS 2006 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 Age 0 20 40 60 80 100 Percent Male Female As Figure 3.1 shows, by age 10, the vast majority of children in Uganda attend school (94 percent). Rates of attendance range from 92-94 percent among males and females age 9 to 13. Starting at age 15, attendance rates decline noticeably for all children; however, they decrease more rapidly among females than males. For instance, the attendance rate is 52 percent among males age 18, and just 34 percent among females the same age. By age 21, only 10 percent of females attend school, compared with 21 percent of their male counterparts. Figure 3.1 also shows that approximately half (48 percent) of children age 6 attend school, and attendance rates among children age 7 and 8 are around 75 percent and 86 percent, respectively. It should be noted that children age 6 at the time the household was interviewed may not yet have turned 6 at the beginning of the school year. It is therefore to be expected that not all 6-year-olds attend school. However, all children age 7 and 8 should have attended primary school during the 2006 school year. For one in four children age 7 and one in six children age 8, this was not the case. Education | 29 3.3 AGE AT FIRST PRIMARY SCHOOL ATTENDANCE There is no mechanism in place to ensure that the school system enrolls only children within the official school/grade age bracket. In Uganda, the official target entry age for P1 is six years, meaning that children registered in P1 should be age 6 and a small proportion age 7 (those who turn seven between two academic years). In addition, some children begin school at age 7 for various reasons, such as the long distances to the nearest school or because their parents consider a child who is age 6 to be too young to start schooling. For children age 5-12 who have ever attended school, the survey asked the respondent to report the age at which the child first started school. According to Table 3.3, over half (59 percent) of children started primary school on time, at the intended age for entry (age 6-7). Nearly 1 in 5 (18 percent) of children first attended primary school at an age below the target entry age for primary school, and 1 in 5 (20 percent) started school over age (at age 8 or older). The mean age of starting primary 1 was 6.6 years. Table 3.3 Age at first primary school attendance Percent distribution of de jure household members age 5 to 12 years who have ever attended primary school, by age when first attended primary 1 and mean age at school entry, according to background characteristics, Uganda 2006 Age first attended primary 1 Background characteristic Underage (<6) On time (6-7) Overage (8+) Don't know/ missing Total Mean age at entry Number of children Sex Male 17.8 58.5 20.9 2.8 100.0 6.6 4,354 Female 18.7 59.2 19.8 2.3 100.0 6.6 4,414 Residence Urban 27.7 58.7 10.5 3.1 100.0 6.2 929 Rural 17.2 58.8 21.5 2.5 100.0 6.6 7,839 Region Central 1 13.6 56.8 24.8 4.9 100.0 6.8 893 Central 2 18.2 58.9 19.0 3.9 100.0 6.5 844 Kampala 25.4 61.8 9.8 3.1 100.0 6.2 334 East Central 15.3 64.9 17.5 2.3 100.0 6.6 1,008 Eastern 14.8 64.1 18.9 2.2 100.0 6.6 1,415 North 15.4 60.8 21.9 2.0 100.0 6.7 1,507 West Nile 15.1 51.2 33.5 0.1 100.0 7.0 484 Western 18.7 59.4 20.3 1.5 100.0 6.6 1,255 Southwest 33.0 46.5 17.3 3.2 100.0 6.2 1,026 North Sub-regions IDP 18.3 59.4 20.6 1.8 100.0 6.6 774 Karamoja 15.1 44.6 37.6 2.7 100.0 7.3 204 Wealth quintile Lowest 15.8 54.7 27.6 1.9 100.0 6.8 1,698 Second 14.0 59.6 24.3 2.1 100.0 6.8 1,746 Middle 18.9 56.9 21.5 2.7 100.0 6.6 1,806 Fourth 18.5 62.4 16.5 2.6 100.0 6.5 1,928 Highest 24.6 60.2 11.7 3.5 100.0 6.2 1,590 Total 18.3 58.8 20.4 2.5 100.0 6.6 8,768 There were no gender differences in the starting age for primary 1. There were, however, differences by residence, region, and wealth. Children in urban areas are more likely than those in rural areas to start school under age (28 percent versus 17 percent), while children in rural areas are more likely than those in urban areas to start school over age (22 percent versus 11 percent). There are marked differences by region, with children in West Nile being the most likely to start primary 1 over age (34 percent) and children in Kampala being the least likely to do so (10 percent). For the sub-regions, the pattern in the IDP camps is similar to the national results, but 30 | Education Karamoja has the highest proportion in the country of children who started school over age (38 percent). In addition, children from less advantaged households are more likely than those from more advantaged households to start school over age; 28 percent of children from the poorest households started school at age 8 or older, while 12 percent of those from the wealthiest households did the same. 3.4 ABSENTEEISM AMONG PRIMARY SCHOOL PUPILS The 2006 UDHS included questions about absenteeism from school. For each child attending school, the respondent to the household questionnaire was asked to report the number of days that each child’s school was open during the previous week and the number of days the child attended. Table 3.4 shows that overall, just over 1 in 10 (13 percent) pupils were absent from school for one or more days during the school week preceding the interview. Among those students who were absent, the mean number of days missed was 2. Table 3.4 Absenteeism among primary school pupils Percent distribution of primary school pupils by absenteeism in the week of school preceding the interview, according to background characteristics, Uganda 2006 Pupil absenteeism Background characteristic Attended all school days Absent one or more days Don't know/ missing Total Number of pupils1 Mean days missed among pupils missing one or more days Sex Male 79.9 13.2 6.9 100.0 4,145 1.9 Female 81.7 11.7 6.6 100.0 3,963 2.0 Residence Urban 87.7 8.2 4.1 100.0 639 (2.0) Rural 80.2 12.9 7.0 100.0 7,468 2.0 Region Central 1 76.8 14.2 9.0 100.0 772 2.0 Central 2 80.9 13.6 5.4 100.0 1,002 2.1 Kampala 94.6 1.8 3.6 100.0 87 4.0 East Central 85.9 9.3 4.8 100.0 1,008 1.9 Eastern 78.6 13.9 7.5 100.0 1,178 2.0 North 82.3 10.4 7.3 100.0 1,473 2.2 West Nile 72.8 17.2 10.1 100.0 343 2.4 Western 83.2 10.4 6.4 100.0 1,190 1.6 Southwest 77.7 16.1 6.2 100.0 1,055 1.8 North Sub-regions IDP 84.3 11.6 4.1 100.0 1,028 2.1 Karamoja 87.6 5.9 6.5 100.0 210 * Wealth quintile Lowest 79.3 12.6 8.1 100.0 1,654 2.0 Second 79.0 12.5 8.5 100.0 1,633 2.0 Middle 79.3 14.1 6.6 100.0 1,783 1.9 Fourth 82.9 10.9 6.2 100.0 1,867 2.0 Highest 84.1 12.3 3.6 100.0 1,170 2.0 Total 80.8 12.5 6.7 100.0 8,107 2.0 Note: Figures in parentheses are based on 25-49 unweighted cases. An asterisk indicates that a figure is based on fewer than 25 cases and has been suppressed. 1 Excludes pupils whose school was closed for the entire week preceding the interview The rate of absenteeism is higher in rural areas of the country than in urban areas (13 percent versus 8 percent). At the regional level, absenteeism was lowest in Kampala at just 2 percent. In West Nile and Southwest regions, absenteeism is notably high at 17 percent and 16 percent, respectively. The average number of days missed in these regions was 2.4 (West Nile) and 1.8 (Southwest). Education | 31 Absenteeism in the Karamoja sub-region was lower than in all the other regions with the exception of Kampala. The low absenteeism in Karamoja may be related to the free lunch given to pupils by the Government as an inducement to attend school. There are no clear patterns in the rate of absenteeism across the wealth quintiles and little difference by sex. 3.5 REASONS FOR ABSENTEEISM AMONG PRIMARY SCHOOL PUPILS For those children who were absent from primary school in the week preceding the interview, respondents to the household questionnaire were asked to give one main reason why the pupil was absent. Table 3.5 shows that about one-third (36 percent) of the pupils were absent due to illness, one in ten (11 percent) were doing domestic work, and another one in ten (10 percent) were absent because they did not want to go to school. Less frequently mentioned reasons included working for a family farm/business or other employer, attending a funeral or other ceremony, problems with the school uniform, and having no stationery. Table 3.5 Reasons for absenteeism among primary school pupils Percent distribution of primary school pupils who missed school in the week preceding the interview by main reason for absenteeism, according to background characteristics, Uganda 2006 Reason pupil missed school Background characteristic Domestic work Other work1 Child did not want to go Funeral/ wedding/ ceremony/ family function Illness Lack of/ problem with school uniform No stationery Don’t know/ other Missing Total Number of pupils Sex Male 11.1 7.7 12.3 4.5 36.2 3.4 5.7 18.6 0.6 100.0 548 Female 11.5 5.8 6.1 7.5 36.6 7.5 5.3 19.1 0.6 100.0 464 Residence Urban (5.0) (9.9) (7.5) (3.4) (33.2) (14.1) (2.0) (24.7) (0.0) 100.0 53 Rural 11.6 6.7 9.6 6.0 36.6 4.8 5.7 18.5 0.6 100.0 960 Region Central 1 13.9 1.1 4.0 3.7 52.9 2.6 1.0 20.9 0.0 100.0 110 Central 2 6.2 4.2 5.1 5.2 30.6 5.6 11.1 31.4 0.8 100.0 136 Kampala * * * * * * * * * 100.0 2 East Central 5.4 0.8 3.5 11.8 34.0 9.6 2.7 30.0 2.1 100.0 94 Eastern 10.9 3.0 14.0 9.9 36.0 0.6 7.8 17.9 0.0 100.0 164 North 9.9 8.6 11.5 1.9 32.9 13.8 6.5 14.1 0.9 100.0 153 West Nile 14.2 10.0 22.8 7.7 28.7 5.0 4.0 7.7 0.0 100.0 59 Western 14.5 9.7 11.5 3.6 43.5 6.7 2.1 7.5 1.0 100.0 124 Southwest 15.1 15.2 7.6 5.2 33.1 0.5 5.6 17.7 0.0 100.0 170 North Sub-regions IDP 9.6 9.0 7.8 2.4 36.7 12.7 7.2 13.3 1.2 100.0 120 Karamoja * * * * * * * * * 100.0 12 Wealth quintile Lowest 10.7 6.3 13.7 3.9 34.0 8.7 7.7 15.0 0.0 100.0 209 Second 10.8 6.1 11.8 17.1 31.9 3.5 4.5 12.7 1.6 100.0 204 Middle 15.1 7.1 9.3 0.0 35.1 4.1 5.9 23.2 0.2 100.0 252 Fourth 7.1 4.0 3.3 6.3 45.8 1.7 6.0 24.9 1.0 100.0 203 Highest 11.5 12.3 9.0 2.3 35.2 10.2 2.6 16.7 0.0 100.0 144 Total 11.2 6.9 9.5 5.9 36.4 5.3 5.5 18.8 0.6 100.0 1,012 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 Other work includes work for family farm or business, work for an employer, and other work. It is not surprising that about one-third of pupils missed school due to illness, since the Uganda National Household Survey conducted in 2005-2006 also indicated that illness stopped most people from doing their usual activities for up to one week per month (UBOS, 2006c). 32 | Education The distribution by sex is similar to the national pattern except that larger proportions of males (12 percent) than females (6 percent) did not want to go to school and females missed school more often than males due to a problem with their school uniform (8 percent versus 3 percent). At the regional level, Central 1 and Western had the highest proportion of pupils missing school due to illness (53 percent and 44 percent, respectively). In West Nile, one-quarter (23 percent) of pupils who were absent the week before the interview missed school because they did not want to go. By wealth, there were few clear patterns among the reasons for student absenteeism with two exceptions. Pupils from the poorest households were the most likely to miss school because they did not want to go and the wealthiest pupils were more likely than others to miss school to work for a family farm/business or other employer. 3.6 ABSENTEEISM AMONG SECONDARY SCHOOL STUDENTS The national absenteeism patterns for secondary school students are similar to those for primary school pupils; one in ten students was absent from school for one or more days and missed an average of two days of school. Absenteeism by sex and by urban/rural residence is also similar to the patterns observed at the primary level. Because of low enrolment at the secondary school level, it is not possible to compare rates of secondary school absenteeism across regions. Table 3.6 Absenteeism among secondary school pupils in the week of school preceding the interview Percent distribution of secondary school pupils by absenteeism in the week of school preceding the interview, according to background characteristics, Uganda 2006 Pupil absenteeism Background characteristic Attended all school days Absent one or more days Don't know/ missing Total Number of pupils Mean days missed among pupils missing one or more days Sex Male 80.7 9.8 9.6 100.0 393 2.0 Female 78.7 10.4 10.9 100.0 255 2.0 Residence Urban 80.0 9.3 10.7 100.0 159 2.0 Rural 79.8 10.3 9.9 100.0 490 2.0 Region Central 1 87.1 4.9 8.0 100.0 74 2.6 Central 2 74.3 12.7 12.9 100.0 129 1.7 Kampala (79.4) (3.7) (16.9) 100.0 33 (1.5) East Central 77.1 11.7 11.2 100.0 104 2.8 Eastern 82.4 7.7 9.9 100.0 70 2.0 North (74.3) (9.3) (16.4) 100.0 44 (1.8) West Nile (78.0) (13.4) (8.5) 100.0 26 (2.0) Western 82.0 12.1 5.9 100.0 94 1.8 Southwest 85.5 9.7 4.9 100.0 74 1.5 North Sub-regions IDP (73.3) (10.0) (16.7) 100.0 22 (1.7) Karamoja * * * 100.0 6 * Wealth quintile Lowest (82.8) (4.9) (12.3) 100.0 30 (1.5) Second 78.0 12.6 9.4 100.0 68 1.6 Middle 82.1 7.1 10.8 100.0 94 2.2 Fourth 77.1 10.2 12.7 100.0 158 2.4 Highest 80.8 10.7 8.5 100.0 299 1.9 Total 79.9 10.0 10.1 100.0 649 2.0 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 Excludes pupils whose school was closed for the entire week preceding the interview Education | 33 3.7 REASONS FOR ABSENTEEISM AMONG SECONDARY SCHOOL STUDENTS A sizeable percentage of secondary schools in Uganda are boarding schools. As a result, for students who missed school during the week preceding the interview, many respondents did not know the reasons for the child’s absenteeism. The number of respondents who were able to report the reason was too small to allow for an analysis of the results. Characteristics of Respondents | 35 CHARACTERISTICS OF RESPONDENTS 4 This chapter provides a description of the situation of men and women of reproductive age in Uganda. The description is presented in terms of the following variables: age at the time of the survey, marital status, residence, education, literacy, and media access. In addition, this chapter will explore factors that enhance women’s empowerment, including employment, occupation, earnings, and continuity of employment. An analysis of these variables provides the socio-economic context in which demographic and reproductive health issues are examined in the subsequent chapters. 4.1 CHARACTERISTICS OF SURVEY RESPONDENTS Table 4.1 presents background characteristics of the 8,531 women age 15-49 and 2,503 men age 15-54 interviewed in the 2006 UDHS. The distribution of the respondents according to age shows a generally similar pattern for males and females. As expected of Uganda’s age structure, the proportion of respondents in each age group declines with increasing age for both sexes. Forty-three percent of women and 42 percent of men are in the 15-24 age group, 31 percent of women and 30 percent of men are age 25-34, and the remaining respondents are age 35-49 and age 35-54 for women and men, respectively. About half of the respondents (49 percent female and 50 percent male) are formally married1. Male respondents were much more likely than female respondents to have never married (39 percent for males and 24 percent for females). It is interesting to note that 14 percent of females declared themselves to be living together with a man or in consensual unions, while the corresponding percentage for males is only 6 percent. Whereas 9 percent of women are divorced or separated and 4 percent are widowed, the corresponding proportions for men are 5 percent. The distribution of male and female respondents by residence is the same. About 17 percent of respondents are found in the urban areas. Within the nine regional strata, the largest proportions of respondents are from the North and Western regions, and the smallest proportion is from West Nile. Data in Table 4.1 show that men are much more likely to have gone to school and attained higher levels of education than women. Whereas 19 percent of women have never attended school, the corresponding proportion for men is only 5 percent. Furthermore, whereas 30 percent of men have a secondary or higher education, only 21 percent of women have attained this level. Considering the wealth quintiles, the females were almost evenly distributed across quintiles except for the highest quintile, which had the highest percentage. The males did not display any systematic pattern but also had the highest percentage in the highest quintile. There is no major difference between females and males as far as religion is concerned, except for a slightly higher proportion of females belonging to the Pentecostal church (8 percent) than males (5 percent). 1 In this report, “married” refers to those in a formal or official marriage, while “living together” refers to those in informal or consensual unions. In the remainder of the report, marriage refers to both categories, i.e., formal and informal unions. 36 | Characteristics of Respondents Table 4.1 Background characteristics of respondents Percent distribution of women and men age 15-49 by selected background characteristics, Uganda 2006 Women Men Background characteristic Weighted percent Weighted Unweighted Weighted percent Weighted Unweighted Age 15-19 22.7 1,936 1,948 24.9 595 582 20-24 20.0 1,710 1,662 16.8 402 397 25-29 16.6 1,413 1,410 14.7 350 351 30-34 14.3 1,217 1,228 14.9 355 358 35-39 11.0 940 959 13.0 311 318 40-44 8.6 735 722 8.8 210 226 45-49 6.8 580 602 6.8 162 154 Marital status Never married 23.8 2,028 2,058 38.5 918 910 Married 48.7 4,152 4,186 50.1 1,195 1,208 Living together 13.9 1,185 1,176 6.2 148 138 Divorced/separated 9.4 804 757 4.6 111 115 Widowed 4.3 363 354 0.6 14 15 Residence Urban 16.9 1,442 1,450 16.9 404 381 Rural 83.1 7,089 7,081 83.1 1,982 2,005 Region Central 1 10.6 905 824 11.4 272 246 Central 2 9.0 770 759 9.8 233 230 Kampala 8.5 722 846 9.1 218 223 East Central 9.8 836 908 8.8 209 236 Eastern 13.5 1,148 917 13.6 323 276 North 15.5 1,322 1,664 14.0 333 434 West Nile 5.5 471 726 5.2 124 194 Western 14.9 1,271 931 15.5 369 269 Southwest 12.7 1,086 956 12.7 304 278 North sub-regions IDP 5.9 504 688 6.5 155 232 Karamoja 3.4 286 537 2.7 65 111 Education No education 19.3 1,650 1,768 4.9 116 133 Primary 59.3 5,062 4,922 65.0 1,551 1,528 Secondary + 21.3 1,819 1,841 30.1 719 725 Wealth quintile Lowest 18.1 1,541 1,796 15.8 378 442 Second 19.2 1,636 1,582 20.8 495 486 Middle 18.9 1,615 1,494 17.7 422 410 Fourth 19.0 1,621 1,518 21.2 506 480 Highest 24.8 2,118 2,141 24.5 584 568 Religion Catholic 42.4 3,614 3,785 42.0 1,003 1,018 Protestant 34.5 2,945 2,823 37.0 882 865 Muslim 11.2 956 970 12.0 286 287 Pentecostal 8.1 687 635 5.3 126 121 SDA 1.9 163 152 2.1 49 40 Other 1.9 163 160 1.6 39 55 Total 15-49 100.0 8,531 8,531 100.0 2,385 2,386 Men 50-54 na na na na 118 117 Total men 15-54 na na na na 2,503 2,503 Note: Education categories refer to the highest level of education attended, whether or not that level was completed. Total includes 6 women with religion missing. na = Not applicable 4.2 EDUCATIONAL ATTAINMENT BY BACKGROUND CHARACTERISTICS Tables 4.2.1 and 4.2.2 show the distribution of respondents according to the highest level of schooling attended. As mentioned before, the data show that men are better educated than women. Younger people are more likely to be educated and to reach higher levels of education than older people. For women, the percentage without formal education is 4 percent for age 15-19, 12 percent for age 20-24, and 47 percent for age 45-49. For men, the decrease in lack of formal schooling is gradual, Characteristics of Respondents | 37 from 13 percent in the 50-54 age category to 7 percent for age 25-29 to less than 1 percent for age 15-19. People in rural areas are less educated than their urban counterparts. About one in five rural women never attended school, compared with 8 percent of urban women. The corresponding figures for men are 5 percent and 3 percent for rural men and urban men, respectively. Urban women are also more likely to attend secondary school than rural women. While only 15 percent of rural women have attended secondary or higher education, 52 percent of urban women have at least some secondary education. Table 4.2.1 Educational attainment: Women Percent distribution of women age 15-49 by highest level of schooling attended or completed, and median years completed, according to background characteristics, Uganda 2006 Highest level of schooling Background characteristic No education Some primary Completed primary1 Some secondary Completed secondary2 More than secondary Total Number of women Median years completed Age 15-24 7.3 51.5 11.7 24.6 1.4 3.5 100.0 3,646 5.4 15-19 3.5 56.3 10.5 28.0 0.5 1.3 100.0 1,936 5.5 20-24 11.5 46.2 13.1 20.9 2.3 6.0 100.0 1,710 5.3 25-29 19.7 48.3 10.3 14.4 0.6 6.7 100.0 1,413 4.1 30-34 22.0 52.5 9.9 11.9 0.2 3.5 100.0 1,217 3.8 35-39 32.4 46.3 9.4 8.4 0.3 3.2 100.0 940 2.5 40-44 35.5 41.8 10.8 8.9 0.3 2.7 100.0 735 2.0 45-49 47.2 35.8 8.9 5.5 0.0 2.6 100.0 580 0.5 Residence Urban 7.5 27.3 13.5 36.8 3.1 11.7 100.0 1,442 7.1 Rural 21.7 53.0 10.1 12.6 0.3 2.3 100.0 7,089 3.9 Region Central 1 11.6 46.2 9.6 25.3 1.2 6.1 100.0 905 5.4 Central 2 11.5 47.3 15.8 22.1 0.1 3.2 100.0 770 5.5 Kampala 2.8 20.5 14.3 42.5 4.3 15.6 100.0 722 8.4 East Central 15.7 49.7 10.5 20.9 0.5 2.7 100.0 836 4.9 Eastern 15.9 55.8 11.0 14.3 0.2 2.9 100.0 1,148 4.4 North 35.5 50.1 6.5 6.3 0.0 1.7 100.0 1,322 2.2 West Nile 22.8 61.3 5.2 8.7 0.8 1.2 100.0 471 2.8 Western 25.3 54.4 8.6 9.3 0.0 2.3 100.0 1,271 3.3 Southwest 20.5 48.1 15.4 12.6 1.1 2.3 100.0 1,086 4.3 North sub-regions IDP 34.9 55.1 6.1 2.9 0.0 1.0 100.0 504 2.4 Karamoja 72.3 20.5 2.6 4.0 0.0 0.5 100.0 286 a Wealth quintile Lowest 39.7 51.9 5.0 3.0 0.0 0.5 100.0 1,541 1.4 Second 24.4 59.5 8.5 6.7 0.0 0.8 100.0 1,636 3.1 Middle 21.0 57.4 11.2 9.7 0.1 0.6 100.0 1,615 3.7 Fourth 12.7 54.3 13.3 17.1 0.2 2.4 100.0 1,621 5.0 Highest 4.4 26.9 14.1 39.3 2.9 12.3 100.0 2,118 7.4 Total 19.3 48.7 10.7 16.7 0.8 3.9 100.0 8,531 4.4 1 Completed 7 grades at the primary level 2 Completed 6 grades at the secondary level a Omitted because less than 50 percent of women in Karamoja have ever attended school 38 | Characteristics of Respondents Educational attainment among female respondents varies by region. Only 3 percent of the women in the Kampala region have no education. On the other hand, 36 percent of women in the North region have not attended school. In Western region, one in four women has not attended school, compared with 24 percent in West Nile region and 21 percent in Southwest region. Sixteen percent of women in Eastern and East Central regions never attended school, compared with 12 percent of women in Central 1 and Central 2 regions. Regional variation in education for males is smaller, with the percentages who have never attended school ranging from 2 percent in Kampala to 8 percent in the North. Considering the Northern sub-regions, 72 percent of the women from the Karamoja area have no formal education as compared with 34 percent of the men in the same sub-region. Within the IDP camps, 35 percent of the women have no education whereas only 2 percent of the males have no education. Only 1 percent of women within the IDP camps and less than one percent of women from Karamoja have attended education above the secondary level. Table 4.2.2 Educational attainment: Men Percent distribution of men age 15-49 by highest level of schooling attended or completed, and median years completed, according to background characteristics, Uganda 2006 Highest level of schooling Background characteristic No education Some primary Completed primary1 Some secondary Completed secondary2 More than secondary Total Number of men Median years completed Age 15-24 1.4 52.6 14.2 26.9 1.6 3.3 100.0 997 5.8 15-19 0.6 59.5 12.0 27.2 0.2 0.5 100.0 595 5.5 20-24 2.4 42.4 17.5 26.5 3.5 7.6 100.0 402 6.3 25-29 6.5 47.3 10.2 23.9 2.5 9.6 100.0 350 5.6 30-34 6.7 50.2 13.4 20.2 0.5 9.0 100.0 355 5.4 35-39 5.3 53.2 13.8 19.5 1.2 7.1 100.0 311 5.3 40-44 7.4 52.4 15.2 14.8 2.2 8.0 100.0 210 5.3 45-49 14.7 51.5 14.3 8.6 4.5 6.3 100.0 162 4.1 Residence Urban 3.0 29.0 10.7 34.4 5.9 17.0 100.0 404 7.8 Rural 5.2 56.0 14.1 19.7 0.9 4.0 100.0 1,982 5.2 Region Central 1 5.8 53.0 10.9 24.3 0.9 5.2 100.0 272 5.4 Central 2 4.4 54.0 10.4 27.4 1.5 2.4 100.0 233 5.2 Kampala 1.8 21.7 12.2 37.4 6.5 20.3 100.0 218 9.2 East Central 5.5 49.3 12.1 26.6 2.1 4.4 100.0 209 5.6 Eastern 3.1 56.8 13.5 19.8 0.7 6.1 100.0 323 5.5 North 7.7 53.2 15.4 17.2 1.3 5.1 100.0 333 5.3 West Nile 5.4 55.6 10.1 21.6 2.6 4.7 100.0 124 5.3 Western 4.9 56.4 11.8 21.2 1.1 4.6 100.0 369 5.0 Southwest 4.6 55.6 21.9 11.7 1.0 5.2 100.0 304 5.3 North sub-regions IDP 1.7 59.9 17.2 14.2 0.4 6.5 100.0 155 5.3 Karamoja 34.1 44.2 6.5 7.5 4.5 3.2 100.0 65 1.9 Wealth quintile Lowest 9.6 65.8 13.1 9.6 0.0 1.8 100.0 378 4.3 Second 6.5 62.8 15.5 12.2 0.3 2.8 100.0 495 4.8 Middle 3.9 60.1 13.6 20.5 0.4 1.6 100.0 422 5.0 Fourth 4.9 48.0 13.9 27.5 1.4 4.3 100.0 506 5.8 Highest 1.1 29.2 11.9 35.4 5.4 17.0 100.0 584 7.8 Total 15-49 4.9 51.5 13.6 22.2 1.7 6.2 100.0 2,385 5.5 Men 50-54 12.8 48.4 15.8 14.2 4.1 4.6 100.0 118 4.9 Total men 15-54 5.2 51.3 13.7 21.8 1.9 6.1 100.0 2,503 5.5 1 Completed 7 grades at the primary level 2 Completed 6 grades at the secondary level The last column in Tables 4.2.1 and 4.2.2 shows the median number of years of schooling. The figures confirm the previous findings: younger persons and those living in the urban areas have had more years of schooling. These columns also show that both females and males residing in Kampala region have more years of schooling than do respondents in other regions. The results also Characteristics of Respondents | 39 confirm that more men have had access to education than women have in the past. However, after many years of increasing enrolment of girls in school, the median number of years of schooling for women age 15-24 (5.4 years) is almost equal to that of men of the same age (5.8 years). 4.3 LITERACY A person’s ability to read is important in taking advantage of day-to-day opportunities. In the 2006 UDHS, level of literacy is determined by the respondent’s ability to read none, part, or all of a simple sentence. Interviewers were responsible for making this assessment, using cards on which sentences2 were printed in all the major languages spoken in Uganda. Respondents who had attended secondary school were assumed to be literate and were not asked to read a sentence. Data in Tables 4.3.1 and 4.3.2 reveal that 39 percent of Ugandan women age 15-49 cannot read at all, compared with 16 percent of men. Literacy levels decrease with increasing age among women, from 73 percent among women age 15-19 to 38 percent in the 45-49 age group. However, over 80 percent of the men in almost all age groups are literate, which shows their greater access to education over the years. Table 4.3.1 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 2006 No schooling or primary school Background characteristic Secondary school or higher Can read a whole sentence Can read part of a sentence Cannot read at all No card with required language Blind/ visually impaired Total Number of women Percent- age literate1 Age 15-19 29.8 29.6 13.3 22.4 4.6 0.2 100.0 1,936 72.7 20-24 29.2 20.7 10.4 35.1 4.5 0.0 100.0 1,710 60.3 25-29 21.7 23.3 9.2 41.2 4.3 0.1 100.0 1,413 54.3 30-34 15.6 27.9 9.3 41.6 5.6 0.0 100.0 1,217 52.8 35-39 11.9 23.9 8.0 51.5 4.7 0.0 100.0 940 43.8 40-44 11.9 27.2 5.7 51.1 4.2 0.0 100.0 735 44.7 45-49 8.1 21.9 7.5 57.7 4.6 0.2 100.0 580 37.5 Residence Urban 51.6 23.4 6.5 15.1 3.5 0.0 100.0 1,442 81.5 Rural 15.2 25.5 10.5 43.7 4.9 0.1 100.0 7,089 51.2 Region Central 1 32.5 35.6 9.9 21.1 0.9 0.0 100.0 905 78.0 Central 2 25.4 40.6 5.8 23.9 4.1 0.2 100.0 770 71.8 Kampala 62.4 22.8 5.7 6.3 2.9 0.0 100.0 722 90.8 East Central 24.1 18.4 9.7 46.8 1.0 0.0 100.0 836 52.2 Eastern 17.3 16.9 15.3 44.2 6.1 0.1 100.0 1,148 49.6 North 8.0 15.4 7.9 67.6 1.0 0.1 100.0 1,322 31.2 West Nile 10.8 15.1 15.9 46.2 11.9 0.1 100.0 471 41.8 Western 11.7 23.0 8.0 42.5 14.6 0.2 100.0 1,271 42.7 Southwest 16.0 40.0 11.6 32.2 0.2 0.0 100.0 1,086 67.6 North sub-regions IDP 3.9 14.7 9.9 71.3 0.1 0.0 100.0 504 28.5 Karamoja 4.5 5.5 1.8 84.8 3.3 0.0 100.0 286 11.8 Wealth quintile Lowest 3.4 13.1 9.8 70.2 3.5 0.0 100.0 1,541 26.3 Second 7.6 21.5 12.3 52.0 6.6 0.1 100.0 1,636 41.3 Middle 10.4 28.2 11.8 42.0 7.4 0.2 100.0 1,615 50.4 Fourth 19.6 34.9 12.2 28.7 4.5 0.1 100.0 1,621 66.7 Highest 54.5 27.1 4.7 11.5 2.0 0.1 100.0 2,118 86.3 Total 21.3 25.2 9.8 38.9 4.7 0.1 100.0 8,531 56.3 1 Refers to women who either attended secondary school or higher or can read a whole sentence or part of a sentence 2 These sentences include the following: 1) Breast milk is good for babies. 2) Most Ugandans live in villages. 3) Immunization can prevent children from getting diseases. 4) Family planning teaches people to be responsible to their family. 40 | Characteristics of Respondents For both sexes, literacy levels are higher in urban areas than in rural areas. The gap between men and women is wide in both urban and rural areas, but particularly in the rural areas where 81 percent of the men are literate, compared with 51 percent of the women. The gap between males and females in literacy is also notable across regions. In the North region, for example, the literacy level of men is 81 percent, compared with 31 percent for women. In West Nile region the literacy level for men is 85 percent while for women it is only 42 percent. Within the sub-regions in the north, the literacy level for men in Karamoja is almost four times that for women (44 and 12 percent, respectively). In the IDP camps, the literacy rate for men is three times that for females (88 and 29 percent, respectively). Table 4.3.2 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 2006 No schooling or primary school Background characteristic Secondary school or higher Can read a whole sentence Can read part of a sentence Cannot read at all No card with required language Blind/ visually impaired Missing Total Number of men Percent- age literate1 Age 15-19 27.9 42.9 15.7 12.8 0.5 0.0 0.1 100.0 595 86.5 20-24 37.6 29.6 18.6 13.6 0.6 0.0 0.0 100.0 402 85.8 25-29 36.0 32.7 12.9 16.8 1.4 0.0 0.2 100.0 350 81.6 30-34 29.7 35.6 15.0 17.6 1.4 0.0 0.7 100.0 355 80.3 35-39 27.8 41.9 12.2 16.8 1.3 0.0 0.0 100.0 311 81.9 40-44 25.0 44.2 10.9 18.9 0.6 0.3 0.0 100.0 210 80.1 45-49 19.5 42.6 12.6 24.7 0.6 0.0 0.0 100.0 162 74.6 Residence Urban 57.3 26.9 5.6 8.3 1.0 0.2 0.8 100.0 404 89.8 Rural 24.6 40.3 16.4 17.7 0.9 0.0 0.0 100.0 1,982 81.4 Region Central 1 30.4 35.8 14.7 18.3 0.9 0.0 0.0 100.0 272 80.8 Central 2 31.3 37.5 11.9 17.1 1.9 0.3 0.0 100.0 233 80.7 Kampala 64.2 24.6 5.4 3.2 1.1 0.0 1.5 100.0 218 94.2 East Central 33.1 31.4 15.9 19.6 0.0 0.0 0.0 100.0 209 80.4 Eastern 26.6 30.5 19.6 23.3 0.0 0.0 0.0 100.0 323 76.7 North 23.7 41.0 16.4 18.5 0.1 0.0 0.2 100.0 333 81.1 West Nile 28.8 37.8 18.8 8.4 6.2 0.0 0.0 100.0 124 85.4 Western 26.9 39.1 19.0 13.9 1.1 0.0 0.0 100.0 369 85.0 Southwest 17.9 58.3 7.9 15.9 0.0 0.0 0.0 100.0 304 84.1 North sub-regions IDP 21.1 50.4 16.8 11.2 0.0 0.0 0.4 100.0 155 88.4 Karamoja 15.2 22.1 7.0 55.0 0.8 0.0 0.0 100.0 65 44.2 Wealth quintile Lowest 11.5 40.3 21.8 25.5 0.9 0.0 0.0 100.0 378 73.6 Second 15.2 42.0 19.3 21.6 1.7 0.1 0.1 100.0 495 76.5 Middle 22.5 42.5 17.0 17.2 0.9 0.0 0.0 100.0 422 81.9 Fourth 33.2 39.9 11.3 15.0 0.6 0.0 0.0 100.0 506 84.4 Highest 57.8 28.4 7.1 5.6 0.5 0.0 0.6 100.0 584 93.3 Total 15-49 30.1 38.1 14.6 16.1 0.9 0.0 0.2 100.0 2,385 82.8 Men 50-54 22.9 46.9 11.8 16.7 0.6 1.1 0.0 100.0 118 81.6 Total men 15-54 29.8 38.5 14.5 16.1 0.9 0.1 0.2 100.0 2,503 82.7 1 Refers to men who either attended secondary school or higher or can read a whole sentence or part of a sentence Characteristics of Respondents | 41 4.4 SCHOOL LEVEL AT WHICH TEACHING ENGLISH IS APPROPRIATE Both women and men were asked at what level in school it is appropriate to begin teaching English. In general, women are more likely to believe it is appropriate to introduce English earlier than men. Table 4.4 shows, for example, that 31 percent of the women believe that school should be taught in English from primary one compared with one in four men. Furthermore, 23 percent of women believe that pre-primary schools should be taught in English, while only 17 percent of men believe so. By residence, women in urban areas are more likely than their counterparts in rural areas to believe that school should be taught in English beginning in pre-primary (42 percent compared with 19 percent). The same pattern applies for men. Table 4.4 School level at which teaching in English is appropriate Percent distribution of women 15-49 and men 15-54 by level of school at which they believe children should begin to be taught in English, Uganda 2006 Primary Residence Pre- primary 1 2 3 4 5 or higher Total Number WOMEN Urban 41.5 32.8 7.9 10.7 4.7 2.3 100.0 1,442 Rural 19.2 30.1 13.6 23.2 8.4 5.5 100.0 7,089 Total 15-49 23.0 30.5 12.6 21.1 7.8 5.0 100.0 8,531 MEN Urban 30.6 27.6 10.1 18.7 9.2 3.8 100.0 413 Rural 14.4 24.1 14.5 28.0 14.1 4.8 100.0 2,090 Total 15-54 17.0 24.7 13.8 26.5 13.3 4.7 100.0 2,503 4.5 ACCESS TO MASS MEDIA Information access is essential in increasing people’s knowledge and awareness of what is taking place around them, which may eventually affect their perceptions and behaviour. In the survey, exposure to the media was assessed by asking how often a respondent reads a newspaper, watches television, or listens to a radio. Most of the population is exposed to some form of media. In general, men are more likely than women to have access to mass media; this is true for all types of media. Tables 4.5.1 and 4.5.2 show that radio is the most popular medium. Around seven in ten women and nine in ten men listen to a radio broadcast at least once a week. Twenty-one percent of men read a newspaper at least once a week, compared with 15 percent of the women. Reflecting the limited television broadcast coverage in the country, the percentage of women and men who watch television is low (11 percent of women and 14 percent of men). The proportion that has access to all three media (radio, newspaper, and television) at least once a week is generally low for both men and women (6 percent for women and 9 percent for men). One in four women and one in nine men have no exposure to any mass media, which poses a challenge in the provision of information to the population, including health information. 42 | Characteristics of Respondents Table 4.5.1 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 2006 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 All three media at least once a week No media at least once a week Number of women Age 15-19 22.8 14.1 75.0 8.4 22.2 1,936 20-24 16.3 14.2 76.4 8.0 22.3 1,710 25-29 13.2 10.4 74.9 5.2 24.1 1,413 30-34 12.8 9.2 72.4 4.8 26.5 1,217 35-39 11.0 7.1 69.9 3.9 29.5 940 40-44 11.5 6.1 71.9 3.9 27.1 735 45-49 8.1 4.9 66.8 3.1 32.3 580 Residence Urban 40.1 39.1 90.1 23.9 7.2 1,442 Rural 10.1 4.9 70.1 2.4 28.7 7,089 Region Central 1 29.0 18.4 87.6 11.4 11.4 905 Central 2 20.3 12.5 85.5 6.5 13.0 770 Kampala 51.2 57.0 94.4 35.1 2.6 722 East Central 12.6 8.9 75.2 3.7 22.3 836 Eastern 12.3 4.9 66.2 1.8 31.7 1,148 North 3.8 1.2 50.0 0.5 49.4 1,322 West Nile 6.4 1.1 64.9 0.6 34.2 471 Western 5.0 3.2 73.0 1.9 26.6 1,271 Southwest 10.6 4.2 78.8 2.2 19.7 1,086 North sub-regions IDP 2.2 0.4 46.2 0.1 53.2 504 Karamoja 2.5 0.9 23.2 0.3 75.8 286 Education No education 0.4 2.0 56.6 0.0 43.0 1,650 Primary 8.3 5.5 73.0 1.6 25.8 5,062 Secondary + 47.6 33.1 90.2 23.9 6.7 1,819 Wealth quintile Lowest 2.9 0.5 39.1 0.0 59.9 1,541 Second 5.1 1.0 66.5 0.3 32.1 1,636 Middle 5.8 2.1 75.2 0.3 23.9 1,615 Fourth 12.0 4.9 85.2 2.1 13.4 1,621 Highest 41.5 36.6 93.7 22.2 4.0 2,118 Total 15.2 10.7 73.5 6.0 25.1 8,531 Tables 4.5.1 and 4.5.2 also show the variation in media exposure by background characteristics of respondents. The results for women indicate that the proportion who are exposed to any media at least once a week generally declines gradually with age. Urban women are more likely to have access to mass media than rural residents. Only 10 percent of the women in rural areas read a newspaper at least once a week while the percentage for urban women is 40. In terms of watching television at least once a week, 5 percent of rural women watch as compared with 39 percent of women in urban areas. For those women listening to the radio, 70 percent of rural women listen to the radio compared with 90 percent of their urban counterparts. The findings for men also show a gap in media access between urban and rural areas. For example, 52 percent of men in urban areas read a newspaper at least once a week, compared with only 15 percent of those in rural areas. Characteristics of Respondents | 43 Table 4.5.2 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 2006 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 All three media at least once a week No media at least once a week Number of men Age 15-19 18.9 13.0 85.2 7.1 13.5 595 20-24 24.0 19.0 85.8 10.0 11.5 402 25-29 22.0 15.9 89.2 9.3 10.1 350 30-34 21.9 15.5 88.1 11.0 10.8 355 35-39 20.8 11.9 89.8 8.1 9.3 311 40-44 20.3 13.1 87.9 9.1 11.6 210 45-49 16.5 8.3 89.6 5.5 10.0 162 Residence Urban 52.1 43.6 91.7 29.7 6.4 404 Rural 14.5 8.4 86.6 4.4 12.3 1,982 Region Central 1 26.1 22.8 97.2 14.9 2.0 272 Central 2 23.8 17.7 94.5 7.9 4.9 233 Kampala 63.4 54.3 93.3 40.4 4.1 218 East Central 9.3 13.4 86.1 4.4 13.1 209 Eastern 13.2 5.1 72.2 1.2 25.4 323 North 14.3 4.1 81.3 3.4 16.9 333 West Nile 19.2 2.4 88.4 1.0 11.6 124 Western 12.1 7.0 88.5 4.6 10.3 369 Southwest 18.1 11.4 91.2 5.7 8.5 304 North sub-regions IDP 10.3 2.6 90.5 1.3 8.2 155 Karamoja 19.4 2.7 27.6 1.4 66.1 65 Education No education 2.1 2.4 72.6 0.0 27.4 116 Primary 10.7 8.0 85.6 3.1 13.4 1,551 Secondary + 45.8 29.9 93.7 22.1 4.3 719 Wealth quintile Lowest 5.5 2.8 72.6 0.2 25.9 378 Second 9.5 2.5 83.6 1.0 15.6 495 Middle 11.8 3.8 90.3 1.8 8.7 422 Fourth 17.4 10.0 90.7 3.8 7.2 506 Highest 50.1 43.3 95.4 29.8 3.7 584 Total 15-49 20.9 14.4 87.4 8.7 11.3 2,385 Men 50-54 14.8 5.5 87.3 4.1 11.8 118 Total men 15-54 20.6 13.9 87.4 8.5 11.3 2,503 The proportions of both women and men who are exposed to all three media are highest in Kampala. For example, 35 percent of women in Kampala are exposed to all three sources of media at least once a week, compared with less than 1 percent of women in North and West Nile regions. The data further reveal that exposure to media is positively associated with educational attainment. For example, 93 percent of women with secondary education or higher are exposed to at least one form of media each week, compared with 57 percent of women with no education. A similar pattern exists for men. The data also show that media exposure is limited among women in the North sub-regions. Overall, half of all women in the IDP camps and three-quarters of all women in Karamoja are not exposed to any media on a weekly basis. Radio has the widest coverage. Almost no women watch television in the Karamoja sub-region or in the IDP camps. Furthermore, only 2 to 3 percent of the women in both the Karamoja and IDP sub-regions read newspapers at least once a week. The proportions are somewhat higher among the men, particularly in the IDP camps. 44 | Characteristics of Respondents 4.6 EMPLOYMENT 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. Tables 4.6.1 and 4.6.2 show that 81 percent of women and 94 percent of men are classified as currently employed. The proportion currently employed increases with age and number of living children among women. The data for men show less variation in employment status by age and number of children. Women who were divorced, separated, or widowed are the most likely to be employed (91 percent), followed by those who were married (87 percent). Never-married women and men are the least likely to be employed (61 percent and 86 percent, respectively). Current employment for married men is almost universal (99 percent). Table 4.6.1 Employment status: Women Percent distribution of women age 15-49 by employment status, according to background characteristics, Uganda 2006 Employed in the 12 months preceding the survey Background characteristic Currently employed1 Not currently employed Not employed in the 12 months preceding the survey Missing/ don't know Total Number of women Age 15-19 61.9 5.9 32.1 0.1 100.0 1,936 20-24 78.6 5.9 15.4 0.2 100.0 1,710 25-29 87.6 4.8 7.6 0.0 100.0 1,413 30-34 89.1 5.0 5.9 0.0 100.0 1,217 35-39 90.8 5.1 4.1 0.0 100.0 940 40-44 91.5 4.5 4.0 0.0 100.0 735 45-49 91.8 4.2 4.0 0.0 100.0 580 Marital status Never married 61.0 5.6 33.3 0.1 100.0 2,028 Married or living together 86.6 5.2 8.1 0.1 100.0 5,337 Divorced/separated/widowed 91.2 4.9 3.9 0.0 100.0 1,167 Number of living children 0 62.6 6.2 31.1 0.1 100.0 2,177 1-2 82.4 5.3 12.2 0.1 100.0 2,135 3-4 89.1 4.6 6.3 0.1 100.0 1,804 5+ 90.8 4.8 4.3 0.0 100.0 2,414 Residence Urban 62.2 5.6 32.3 0.0 100.0 1,442 Rural 85.0 5.2 9.7 0.1 100.0 7,089 Region Central 1 64.6 10.0 25.3 0.0 100.0 905 Central 2 76.5 4.5 19.1 0.0 100.0 770 Kampala 57.3 5.1 37.7 0.0 100.0 722 East Central 78.3 5.6 15.8 0.2 100.0 836 Eastern 93.7 3.6 2.6 0.1 100.0 1,148 North 92.3 2.8 4.7 0.2 100.0 1,322 West Nile 74.0 13.6 12.4 0.0 100.0 471 Western 91.3 2.7 6.0 0.0 100.0 1,271 Southwest 80.7 5.8 13.5 0.0 100.0 1,086 North sub-regions IDP 94.9 1.9 3.1 0.1 100.0 504 Karamoja 88.3 5.0 6.2 0.6 100.0 286 Education No education 91.2 4.5 4.2 0.1 100.0 1,650 Primary 84.3 5.3 10.3 0.0 100.0 5,062 Secondary + 63.2 5.8 30.9 0.1 100.0 1,819 Wealth quintile Lowest 92.9 3.6 3.4 0.1 100.0 1,541 Second 89.2 5.1 5.5 0.2 100.0 1,636 Middle 85.5 5.5 8.9 0.0 100.0 1,615 Fourth 80.6 6.1 13.4 0.0 100.0 1,621 Highest 63.6 5.7 30.7 0.0 100.0 2,118 Total 81.2 5.2 13.5 0.1 100.0 8,531 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. Characteristics of Respondents | 45 Table 4.6.2 Employment status: Men Percent distribution of men age 15-49 by employment status, according to background characteristics, Uganda 2006 Employed in the 12 months preceding the survey Background characteristic Currently employed1 Not currently employed Not employed in the 12 months preceding the survey Total Number of men Age 15-19 83.3 3.3 13.3 100.0 595 20-24 93.7 0.8 5.6 100.0 402 25-29 98.4 0.5 1.1 100.0 350 30-34 98.4 0.8 0.8 100.0 355 35-39 98.8 0.6 0.7 100.0 311 40-44 99.4 0.3 0.3 100.0 210 45-49 98.2 0.0 1.8 100.0 162 Marital status Never married 86.0 2.5 11.5 100.0 918 Married or living together 99.2 0.4 0.4 100.0 1,343 Divorced/separated/widowed 96.1 0.8 3.0 100.0 124 Number of living children 0 87.1 2.4 10.5 100.0 980 1-2 98.9 0.3 0.8 100.0 452 3-4 98.5 0.5 1.0 100.0 363 5+ 98.8 0.6 0.6 100.0 591 Residence Urban 86.6 1.4 12.0 100.0 404 Rural 95.5 1.2 3.3 100.0 1,982 Region Central 1 93.8 1.8 4.4 100.0 272 Central 2 97.2 0.7 2.1 100.0 233 Kampala 86.7 1.0 12.3 100.0 218 East Central 87.2 1.7 11.1 100.0 209 Eastern 98.7 1.0 0.2 100.0 323 North 93.9 2.7 3.4 100.0 333 West Nile 95.9 0.5 3.6 100.0 124 Western 94.0 0.0 6.0 100.0 369 Southwest 95.6 1.6 2.8 100.0 304 North sub-regions IDP 95.7 1.7 2.6 100.0 155 Karamoja 89.0 5.3 5.7 100.0 65 Education No education 98.9 1.1 0.0 100.0 116 Primary 96.0 1.0 3.0 100.0 1,551 Secondary + 88.7 1.8 9.4 100.0 719 Wealth quintile Lowest 95.9 1.5 2.7 100.0 378 Second 96.2 0.9 2.9 100.0 495 Middle 94.4 1.5 4.0 100.0 422 Fourth 95.3 0.8 3.9 100.0 506 Highest 89.3 1.7 9.1 100.0 584 Total 15-49 94.0 1.3 4.8 100.0 2,385 Men 50-54 98.2 1.8 0.0 100.0 118 Total men 15-54 94.2 1.3 4.6 100.0 2,503 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. 46 | Characteristics of Respondents The current employment level for women is higher in rural areas than in urban areas, while for men the difference is less pronounced. Women in the Eastern region are the most likely to be employed (94 percent) whereas women in Kampala are least likely to be employed (57 percent). For men, employment levels are 94 percent or more with the exception of Kampala and East Central regions, which had levels of 87 percent. It is worth noting that for both women and men, current employment levels are inversely associated with educational attainment. 4.7 OCCUPATION Respondents who were currently employed were asked to state their occupation, and the results are presented in Tables 4.7.1 and 4.7.2. Among women who are currently employed, 75 percent are engaged in agriculture and 25 percent are involved in non-agricultural activities. The percentages for men are 68 percent and 32 percent, respectively. The strong involvement of the population in agriculture reflects the predominance of the agricultural sector in the Ugandan economy. Table 4.7.1 Occupation: Women Percent distribution of women age 15-49 employed in the 12 months preceding the survey by occupation, according to background characteristics, Uganda 2006 Background characteristic Profes- sional/ technical/ managerial Clerical Sales and services Skilled manual Unskilled manual Domestic service Agricul- ture Missing Total Number of women Age 15-19 0.3 0.1 6.3 3.8 0.5 4.7 84.1 0.2 100.0 1,313 20-24 3.6 0.7 16.6 4.5 0.4 1.9 71.9 0.4 100.0 1,444 25-29 5.8 0.5 16.6 5.6 0.8 0.8 69.6 0.4 100.0 1,306 30-34 3.8 0.6 14.8 6.4 0.8 0.6 72.9 0.2 100.0 1,145 35-39 3.2 0.6 14.2 4.4 0.6 0.6 75.8 0.6 100.0 901 40-44 2.7 0.1 11.4 6.8 1.2 0.4 77.3 0.0 100.0 705 45-49 3.3 0.2 10.6 5.5 0.4 0.1 79.7 0.1 100.0 557 Marital status Never married 4.1 0.7 11.3 4.3 0.5 6.1 72.6 0.4 100.0 1,351 Married or living together 3.3 0.4 11.4 4.9 0.5 0.1 79.1 0.3 100.0 4,899 Divorced/separated/widowed 2.4 0.4 23.4 7.3 1.3 2.4 62.7 0.1 100.0 1,121 Number of living children 0 3.7 0.7 10.1 4.7 0.6 4.9 74.9 0.4 100.0 1,498 1-2 4.7 0.9 17.5 5.4 0.8 1.5 69.0 0.2 100.0 1,874 3-4 3.3 0.2 15.6 5.7 0.7 0.6 73.6 0.3 100.0 1,691 5+ 1.8 0.0 10.1 4.9 0.6 0.3 82.3 0.2 100.0 2,309 Residence Urban 10.0 2.4 48.8 9.0 1.7 8.0 19.2 1.0 100.0 977 Rural 2.3 0.1 7.8 4.6 0.5 0.6 84.0 0.2 100.0 6,395 Region Central 1 6.4 0.0 25.3 9.9 0.4 2.9 55.1 0.0 100.0 676 Central 2 3.2 0.2 18.3 8.0 0.7 1.8 67.6 0.2 100.0 623 Kampala 12.2 4.0 57.2 8.4 1.3 13.0 2.8 1.1 100.0 450 East Central 4.2 0.3 10.7 3.0 0.0 0.3 81.1 0.3 100.0 702 Eastern 1.8 0.2 4.0 3.0 0.0 0.2 90.1 0.6 100.0 1,117 North 1.4 0.1 4.2 5.5 2.1 0.1 86.4 0.2 100.0 1,258 West Nile 1.3 0.3 19.8 13.7 0.3 0.0 64.5 0.1 100.0 413 Western 2.1 0.2 7.7 1.6 0.6 0.8 87.0 0.0 100.0 1,194 Southwest 2.7 0.3 9.3 2.7 0.1 1.2 83.6 0.1 100.0 939 North sub-regions IDP 0.8 0.0 2.7 3.6 1.8 0.0 90.7 0.5 100.0 488 Karamoja 2.3 0.0 5.2 5.5 3.3 0.2 83.3 0.2 100.0 267 Education No education 0.5 0.0 6.1 3.7 0.9 0.4 88.2 0.3 100.0 1,579 Primary 0.3 0.1 12.0 5.3 0.7 1.8 79.9 0.2 100.0 4,537 Secondary + 17.6 2.3 26.8 6.5 0.4 2.4 43.2 0.7 100.0 1,255 Wealth quintile Lowest 0.0 0.0 2.3 3.5 1.1 0.0 92.8 0.2 100.0 1,487 Second 0.7 0.0 4.7 4.7 0.2 0.3 89.3 0.2 100.0 1,542 Middle 1.0 0.0 7.8 4.1 0.1 0.4 86.5 0.0 100.0 1,470 Fourth 3.0 0.1 13.4 6.2 0.6 0.6 76.0 0.1 100.0 1,405 Highest 11.9 2.0 38.5 7.3 1.3 6.7 31.5 0.8 100.0 1,467 Total 3.3 0.4 13.2 5.1 0.7 1.6 75.4 0.3 100.0 7,371 Characteristics of Respondents | 47 Table 4.7.2 Occupation: Men Percent distribution of men age 15-49 employed in the 12 months preceding the survey by occupation, according to background characteristics, Uganda 2006 Background characteristic Profes- sional/ technical/ managerial Clerical Sales and services Skilled manual Unskilled manual Domestic service Agricul- ture Missing Total Number of men Age 15-19 0.2 0.0 6.3 5.9 5.8 0.2 80.9 0.6 100.0 516 20-24 2.8 0.0 10.3 15.4 7.8 0.5 62.8 0.4 100.0 379 25-29 4.8 0.5 15.1 16.6 5.7 0.0 56.3 0.9 100.0 346 30-34 9.1 0.5 10.4 13.3 2.3 0.0 63.8 0.7 100.0 352 35-39 5.2 0.5 15.2 11.9 1.9 0.0 65.2 0.3 100.0 309 40-44 10.9 0.2 12.2 7.1 3.1 0.0 65.8 0.6 100.0 209 45-49 6.2 0.7 0.8 10.8 1.9 0.0 79.5 0.0 100.0 160 Marital status Never married 2.8 0.2 9.4 9.7 6.3 0.3 70.7 0.6 100.0 812 Married or living together 6.1 0.4 11.2 12.6 3.0 0.1 66.2 0.5 100.0 1,338 Divorced/separated/widowed 4.2 0.0 6.3 12.4 8.7 0.0 67.0 1.4 100.0 121 Number of living children 0 2.7 0.2 8.7 9.3 6.7 0.3 71.5 0.6 100.0 876 1-2 5.8 0.0 13.1 16.5 4.5 0.2 59.7 0.2 100.0 449 3-4 6.4 0.6 9.2 14.4 3.0 0.0 65.8 0.6 100.0 359 5+ 6.2 0.5 11.3 9.4 2.2 0.0 69.8 0.6 100.0 587 Residence Urban 13.3 1.1 26.1 35.8 9.8 0.7 12.1 1.0 100.0 355 Rural 3.2 0.1 7.4 7.0 3.5 0.0 78.2 0.5 100.0 1,916 Region Central 1 3.2 0.4 13.2 15.2 12.1 0.0 54.9 1.0 100.0 260 Central 2 0.8 0.0 9.8 15.7 6.4 0.0 66.8 0.5 100.0 228 Kampala 14.8 2.1 30.2 36.7 10.7 1.3 3.0 1.2 100.0 191 East Central 5.4 0.4 14.7 9.9 4.5 0.4 64.1 0.7 100.0 186 Eastern 3.8 0.0 6.9 3.9 0.4 0.0 85.0 0.0 100.0 323 North 2.5 0.0 4.0 6.2 4.3 0.0 82.7 0.3 100.0 322 West Nile 4.0 0.9 7.5 5.4 2.1 0.0 80.1 0.0 100.0 120 Western 7.3 0.0 6.2 10.2 1.2 0.0 74.9 0.3 100.0 347 Southwest 3.6 0.0 9.0 8.1 2.1 0.0 76.2 1.0 100.0 295 North sub-regions IDP 2.7 0.0 2.2 6.2 5.3 0.0 83.2 0.4 100.0 151 Karamoja 7.5 0.0 2.4 3.2 3.0 0.0 82.9 1.0 100.0 62 Education No education 0.0 0.0 5.6 4.0 7.0 0.0 83.1 0.2 100.0 116 Primary 0.6 0.1 9.0 10.3 4.0 0.1 75.6 0.2 100.0 1,504 Secondary + 15.4 0.8 14.2 15.7 5.2 0.2 47.3 1.3 100.0 651 Wealth quintile Lowest 1.1 0.0 2.4 2.9 2.9 0.0 90.5 0.1 100.0 368 Second 0.5 0.0 3.0 6.0 2.5 0.0 88.0 0.0 100.0 481 Middle 1.9 0.3 10.0 6.0 2.6 0.0 78.7 0.6 100.0 405 Fourth 6.3 0.0 11.7 9.9 3.8 0.0 67.3 0.9 100.0 486 Highest 12.1 1.1 21.2 28.3 9.6 0.6 26.1 1.0 100.0 531 Total 15-49 4.8 0.3 10.3 11.5 4.5 0.1 67.8 0.5 100.0 2,271 Men 50-54 5.3 1.1 4.8 3.1 0.7 0.0 84.0 1.0 100.0 118 Total men 15-54 4.8 0.3 10.0 11.1 4.3 0.1 68.6 0.6 100.0 2,389 Most women and men who are engaged in non-agricultural activities work in sales and services occupations or skilled manual labour. The professional, technical, and managerial occupations, which require more skill and have higher income-earning potential, employ only 3 percent of working women and 5 percent of working men. Both women and men who work are most likely to work in agriculture unless they live in urban areas or belong to the highest wealth quintile. 48 | Characteristics of Respondents 4.8 EARNINGS, EMPLOYER, AND CONTINUITY OF EMPLOYMENT Table 4.8 shows the distribution of women by their employment status. The data indicate that 21 percent of employed women receive payment in cash only, 31 percent are paid both in cash and in kind, 16 percent receive only payment in kind, and 32 percent receive no payment for their work. The table further shows that women who work in agriculture are much more likely to receive no payment than those who work in non-agricultural jobs (41 percent and 4 percent, respectively). The data on type of employer indicate that about 60 percent of working women are self- employed, while 29 percent are employed by a family member, and 11 percent are employed by a non-family member. The table further presents the distribution of women by the continuity of their employment. Forty-eight percent of working women work all year, 42 percent work seasonally, and 10 percent work occasionally. The percentage of women who work all year is higher among women who work in non-agricultural occupations than among those working in agriculture (75 percent and 39 percent, respectively), while seasonal employment is high among agricultural workers (52 percent). Table 4.8 Type of employment 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 non- agricultural), Uganda 2006 Employment characteristic Agricultural work Non-agricultural work Total Type of earnings Cash only 5.1 69.4 20.9 Cash and in-kind 32.9 25.3 31.0 In-kind only 21.1 1.1 16.2 Not paid 40.8 4.0 31.8 Total 100.0 100.0 100.0 Type of employer Family member 36.1 7.1 28.9 Non-family member 4.7 31.8 11.4 Self-employed 59.2 61.0 59.6 Total 100.0 100.0 100.0 Continuity of employment All year 39.1 75.0 47.9 Seasonal 51.8 13.6 42.4 Occasional 8.9 11.2 9.5 Total 100.0 100.0 100.0 Number of women employed during the past 12 months 5,558 1,793 7,371 Note: Total includes 20 women with missing information on type of employment who are not shown separately. Totals may not add to 100.0 because of a small fraction of missing information. 4.9 KNOWLEDGE AND ATTITUDES TOWARDS TUBERCULOSIS Tables 4.9.1 and 4.9.2 show several indicators relating to respondents’ knowledge and attitudes concerning tuberculosis (TB) including the percentages who have heard of the disease, who know that TB is spread through the air by coughing, who believe that TB can be cured, and who would want to keep it a secret that a family member has TB. Characteristics of Respondents | 49 Table 4.9.1 Knowledge and attitudes concerning tuberculosis: Women Percentage of women age 15-49 who have heard of tuberculosis (TB), and among women who have heard of TB, the percentage who know that TB is spread through the air by coughing, the percentage who believe that TB can be cured, and the percentage who would want to keep secret that a family member has TB, by background characteristics, Uganda 2006 Among respondents who have heard of TB, the percentage who: Among all respondents Background characteristic Percentage who have heard of TB Number Report that TB is spread through the air by coughing Believe that TB can be cured Would want a family member's TB kept secret Number of women Age 15-19 96.3 1,936 55.9 54.3 36.4 1,865 20-24 98.0 1,710 54.8 60.4 27.5 1,676 25-29 98.3 1,413 52.6 64.6 25.3 1,389 30-34 98.6 1,217 52.1 63.9 22.8 1,200 35-39 98.7 940 52.6 67.7 24.6 927 40-44 98.4 735 51.9 64.9 21.1 723 45-49 98.0 580 50.7 66.3 21.5 569 Residence Urban 98.9 1,442 62.0 67.5 23.3 1,426 Rural 97.6 7,089 51.8 60.7 27.9 6,923 Region Central 1 98.2 905 52.2 56.2 32.7 888 Central 2 98.6 770 43.3 49.8 32.1 759 Kampala 99.5 722 59.0 60.6 21.6 718 East Central 98.

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